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Titolo: RENAMEDBYADMWHILEHIDDENTOALLOWDUPLICATEACCELERATORS
Autore: Stefano Carrano - ARSIAL

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Pilot project 2. Climate
monitoring & suburban
areas development

Projet Interreg IIIB Medocc n° 2005-05-2.1-I-137

August 2007

Content
Foreword ............................................................................................................................1
Methodological approach .................................................................................................5
Introduction to climate and meteorology science ..........................................................6
Guidelines to the realisation...........................................................................................11
Weather station ............................................................................................................11
Network .........................................................................................................................21
Climate monitoring and the link ‘Country-Town’ ..........................................................26
Climate change perspectives......................................................................................31
Climate monitoring science for decision makers......................................................34
Instances of climate monitoring for productive services .........................................41
Conclusions..................................................................................................................45
Pilot project frame: Terracina state of art......................................................................47
Geographical situation ................................................................................................47
Tourism fluxes..............................................................................................................51
Meteorological data......................................................................................................58
Services involved .........................................................................................................61
Proposed action...............................................................................................................64
Future perspectives .....................................................................................................66
Costs and benefits...........................................................................................................72
On global scale.............................................................................................................72
Proposed action costs & benefits...............................................................................75
Future perspectives indication ...................................................................................77
Meteorological symbols and measurement units.........................................................81
Bibliography.....................................................................................................................82
Acknowledgements .........................................................................................................87

Foreword

The

European

Commission

“Environment

Climate”

on

its

official

website

(http://ec.europa.eu/environment/climat/home_en.htm) comments in an alarming way on the
climate change issue:
“The warming of the climate system is unequivocal, as is now evident from observations of
increases in global average air and ocean temperatures, widespread melting of snow and
ice, and rising global mean sea level. The Earth's average surface temperature has risen by
0.76° C since 1850. Most of the warming that has occurred over the last 50 years is very
likely to have been caused by human activities. In its Fourth Assessment Report (AR4),
published on 2 February 2007, the Intergovernmental Panel on Climate Change1 (IPCC)
projects that, without further action to reduce greenhouse gas emissions, the global average
surface temperature is likely to rise by a further 1.8-4.0°C this century. Even the lower end of
this range would take the temperature increase since pre-industrial times above 2°C, the
threshold beyond which irreversible and possibly catastrophic changes become far more
likely.

Projected global warming this century is likely to trigger serious consequences for humanity
and other life forms, including a rise in sea levels of between 18 and 59 cm which will
endanger coastal areas and small islands, and a greater frequency and severity of extreme
weather events.”

Coming to Mediterranean Basin scenario, scientists (Rambal and Hoff 1998) evidenced as in
the last 20-30 years there was a growth higher than the average yearly global temperature
increase, with a higher frequency of heath waves. A recent analysis of historical records
concerning Italian thermic and rainfall data showed a significant increase of yearly average
temperature (0.4 °C in the North, 0.7 °C in the South) with an evident decrease of yearly
rains, specially concerning Southern Italy (Brunetti et al., 2000).

1

Recognizing the problem of potential global climate change, the World Meteorological Organization (WMO)
and the United Nations Environment Programme (UNEP) established the Intergovernmental Panel on
Climate Change (IPCC) in 1988. It is open to all members of the UN and WMO). IPCC website:
http://www.ipcc.ch/index.html (see also page 7).
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Climate scenarios for Mediterranean Basin toward 2030-2050 forecast higher temperatures
and an intensity modification of drought and rain episodes: in certain areas there would be a
strengthening of these phenomena, in others a weakening. Moreover a growth of sea level is
forecasted, due essentially to the earth poles ice melting.
Evaluations actually disposable concerning vulnerability of Italian territory to the climatic
change effects do not consider the speed with whom the changes could take places during
the next 50-100 years. If these changes will happen, as IPCC judge, with a very faster speed
than in the last 10.000 years of life of the Earth, there will be a further vulnerability factor that
actually is impossible to plan.
According to a CNR2 study (Duce P., 2005), as concerning the Italian coasts, the last century
tendency of sea level increase was comparable to the global average, that is equal to 1-2
mm/year. For the next 30-40 years the sea level increase, due to the temperature growth,
should be included between 50 and 290 mm. Sea level increase will have effects on coast
areas: lowlands and coastal marshes invasion, speed up of coastal erosion, saltiness
increase for estuaries and deltas due to migrations of underground salt front, increase of salt
water in the underground waters of coast areas. Lowlands will be more subjected to flooding
for meteorological events with very high sea waves, rivers flow to sea will be more difficult
with greater probability of overflow and flooding for intense atmospheric precipitation.
The impact on coast areas would be heavier if in the meantime atmospheric precipitation
would decrease: rivers flow rate would be reduced and the underground waters too, as
consequently. If the number and capacity of artificial basins will be incremented to build new
fresh water reserves, there will be more decrease of solid transport in the rivers, necessary
for beaches consolidation and the impact on the coast will be higher.
As concerning the inland territories, modifications have been forecasted for an increase of
rain on Northern Italy with consequently flooding risks and hydro-geological disasters. On
Central and especially on Southern Italy and in the Islands, due to a decrease of rain and an
increase of temperature, it seems that desertification processes will take place with high
probability.
Floods and heavier and longer summer droughts will give effects on soil productivity and
erosion, on slopes stability, on rivers capacity and on their solid transport, on underground
water table.
As concerning forest ecosystem, these are strictly linked to climate both for their distribution
as for their efficiency and productivity. An increase of yearly average temperature of only 2-4

2

CNR – Consiglio Nazionale delle Ricerche, the National Research Council of Italy. CNR English website:
http://www.cnr.it/sitocnr/Englishversion/Englishversion.html
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°C would upset the territorial distribution of forests, with a transfer of the different
phytoclimate families toward higher latitudes and higher placement on sea level.
The vegetal species could adapt to climate change trough migration in a rhythm that could
vary from 4 to 200 km every century. Knowing that the modification of 1 degree (°C) of mean
temperature imply 150 km of displacement for the optimal conditions of an ecosystem and
that is not the temperature, but the water stress and the consequently phenomena (forest
fires) that are the most probably causes for evolutional modifications, it is to be presumed
that vegetation and landscape will change in an evident manner, bringing to a chaotic
situation (decrease of forests resistance to diseases, vegetation reduction, birds migration
routes disorganisation, massive mortality of certain species, etc…).
The specific vegetal composition of the woods will change bringing along probable reduction
of typical continental species. Fire risks will grow in summer for Mediterranean species, in
winter for alpine species and there would be an increment of avalanche risk.
This picture on coast, soil and vegetation effects highlights how serious could be the
consequences on agriculture production, on hydraulic works and on human dwelling, on
water resources, on energy production, etc….
Since this, from now onward, it is evident that the implications of global warming have to be
considered in every human activity that concerns forecast and planning.
According to the International Geosphere-Biosphere Programme (IGBP), an international
network of environmental scientists3, the adaptation to the global climate change impacts, as
outlined in the IPCC’s Working Group 2 Report, “Climate Change 2007: Impacts, Adaptation
and Vulnerability”, will require new evaluation tools to help choose the best way forward. This
quest for adaptation strategies opens a new chapter in global environmental change research
that requires not only continued development of sophisticated climate models (and
understanding the processes behind them) but also a new integration of those models with
predictive descriptions of human behaviour.
Always according to IGBP sources, there is a need to continue discovering how the Earth
system works in order to evaluate the numerous ways that humans can adapt to climate
change. The additional challenge is to model unpredictable human behaviour and merge this
into deterministic Earth system models.

3

The International Geosphere-Biosphere Programme (IGBP) is a research programme that studies the
phenomenon of Global Change and is hosted by the Royal Swedish Academy of Sciences. IGBP website:
http://www.igbp.net/ (see also page 7).
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Human adaptation to a changing climate can take many forms, and can have both positive
and negative environmental impacts. Small-scale measures could include increased use of
air conditioning, architectural changes for more efficient heating and cooling, better
forecasting and warning systems for extreme events, and increased water usage. Largerscale issues could vary from switching to renewable energy sources to attempts at
“geoengineering”. The large-scale movement of people away from areas adversely affected
by climate change and by other environmental and socioeconomic stresses is also a form of
adaptation. Each of these options has environmental consequences that must be carefully
evaluated before they are implemented. The larger the adaptation scheme, the greater care
needs to be taken in considering its application.
Therefore, as could be easily gathered from these premises, one of the basic needs in
forecasting climate change on territorial level is the availability of historical data on small
scale to establish a network as possible reliable of geographic connections and weather
events. In this frame it is of prominent importance to gather meteorological data on climate in
all those situations where there is a border effect, like sea coast-hinterland, plain-mountain,
town-countryside. Because the climate change is more effective in these conditions and
could bring to more determinate consequences.
This work is meant to be helpful for local authorities and planners in order to consider their
work in a broader context, updated to global change issue and to dispose of some
meaningful suggestions for the adoption of common instruments useful to the record and
survey of their own territory climate and to enhance adaptation and mitigation of the future
climate effects.

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Methodological approach
This pilot project study will be divided in different sections, each one supplying information
and data and exemplifying procedures to be carried out to perform each action necessary to
apply climate monitoring principles to planning and governance issues of a specific territory.
A relevant part of the work is committed to illustrate what is happening in this field all over the
word, with the selection of examples and successful cases of productive instances related in
particular to tourism sector. This latter, in fact, is becoming one of the most important
industries in many instances of the relationship town-countryside. In planning future
perspectives there is a relevant place for the exploitation of this sector, with the forethought of
taking into account possible involvements of local climate changes, adaptations and
mitigations of its consequences.
At the end, the analysis of costs & benefits will complete the framework of the study stressing
particularly on the monitoring costs side. Forecasted global benefits are, in fact, too many
and too complex to be computable in this frame.

Introduction on CM science
Weather station (WS)

Guidelines for the realisation

Network
Climate change perspectives

CM into the link country-town

CM science for decision makers
Instances of CM for productive services

PP frame: Terracina state-of-art

Geographic situation

T. fluxes historical data

Tourism fluxes

Traffic fluxes

Meteorological data
Services involved

Proposed action

WS network evaluation
CM historical databases
T. business, Agro-food, SMEs

Cross data analysis

Provisional program elaboration

Future perspectives
On global scale

Cost & benefits

Proposed action
Future perspectives indication

Climate Monitoring (CM) & suburban areas development methodological approach

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Introduction to climate and meteorology science
Meteorology is the study of climate, scientifically defined as weather conditions averaged
over a period of time and is a branch of the atmospheric sciences (Wikipedia, 2007). Climate
is defined as the average atmospheric conditions taken over a long (usually months,
seasons, years or decades) period of time.
Meteorology (from Greek: µİIJȑȦȡȠ, meteron, "high in the sky"; and ȜȩȖȠȢ, logos,
"knowledge") is the interdisciplinary scientific study of the atmosphere that focuses on
weather processes and forecasting. Meteorological phenomena are observable weather
events and are explained by the science of meteorology. Those events are bound by the
variables that exist in Earth's atmosphere. They are temperature, pressure, water vapour,
and the gradients and interactions of each variable, and how they change in time.
In particular meteorology studies short term weather systems lasting up to a few weeks, while
climatology studies the frequency and trends of those systems. This latter studies the
periodicity of weather events over years to millennia, as well as changes in long-term
average weather patterns, in relation to atmospheric conditions. Climatologists, those who
practice climatology, study both the nature of climates - local, regional or global - and the
natural or human-induced factors that cause climates to change. Climatology considers the
past and can help predict future climate change.
Phenomena of climatological interest include the atmospheric boundary layer, circulation
patterns, heat transfer (radiative, convective and latent), interactions between the
atmosphere and the oceans and land surface (particularly vegetation, land use and
topography), and the chemical and physical composition of the atmosphere.
Outline of climatology history
One of the first climate researchers include Edmund Halley, who published a map of the
trade winds in 1686, after a voyage to the southern hemisphere. Benjamin Franklin in the
18th century, in order to the mail sending overseas from the United States to Europe, was the
first to map the course of the Gulf Stream. Francis Galton invented the term anticyclone.
Helmut Landsberg led to statistical analysis being used in climatology, which led to its
evolution into a physical science
The arrival of the electrical telegraph in 1837 afforded, for the first time, a practical method for
quickly gathering information on surface weather conditions from over a wide area. This data
could be used to produce maps of the state of the atmosphere for a region near the Earth's
surface and to study how these states evolved through time. To make frequent weather
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forecasts based on these data required a reliable network of observations, but it was not until
1849 that the Smithsonian Institute began to establish an observation network across the
United States under the leadership of Joseph Henry. Similar observation networks were
established in Europe at this time. In 1854, the United Kingdom government established the
new office of Meteorological Statist to the Board of Trade, with the role of gathering weather
observations at sea. This could be considered the first national meteorological service in the
world. The first daily weather forecasts made were published in The Times newspaper in
1860. The following year a system was introduced of hoisting storm warning cones at
principal ports when a gale was expected.
Over the next 50 years many countries established national meteorological services starting
from the Finnish Meteorological Central Office (1881), that was formed from part of Magnetic
Observatory of Helsinki University.
On September 1873 at an International Meteorological Conference in Vienna, Austria, was
founded the IMO, International Meteorological Organization. This was succeeded by the
WMO, World Meteorological Organization, that in 1950 became the specialized agency of
the United Nations for meteorology (weather and climate), operational hydrology and related
geophysical sciences. It has its headquarters in Geneva, Switzerland. In summary among
WMO aims are:
x

worldwide cooperation in the establishment of networks of stations for making
meteorological observations;

x

exchange of meteorological and related information, standardization of meteorological
and related observations

x

application of meteorology to aviation, shipping, water problems, agriculture and other
human activities;

The WMO helped the establishment of the Intergovernmental Panel on Climate Change
(IPCC). It is also directly responsible for the creation of the Global Atmosphere Watch
(GAW).
On 1986 the International Council of Scientific Unions, a coordinating body of national
science organizations, launched IGBP, International Geosphere-Biosphere Programme. This
is a research programme that studies the phenomenon of global change, looks at the total
Earth system, the changes that are occurring, and the manner in which changes are
influenced by human actions.
Climate dynamics knowledge
Understanding the kinematics of how exactly the rotation of the Earth affects airflow was
partial at first. Only late in the 19th century was understood the full extent of the large scale
interaction of pressure gradient force and deflecting force that in the end causes air masses
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to move along isobars. Early in the 20th century this deflecting force was named the “Coriolis
effect” after Gaspard-Gustave Coriolis, who had published in 1835 on the energy yield of
machines with rotating parts, such as waterwheels. In 1856, William Ferrel proposed the
existence of a circulation cell in the mid-latitudes with air being deflected by the coriolis force
to create the prevailing westerly winds.
Numerical weather prediction
In 1904 the Norwegian scientist Vilhelm Bjerknes first postulated that prognostication of the
weather is possible from calculations based upon natural laws.
Early in the 20th century, advances in the understanding of atmospheric physics led to the
foundation of modern numerical weather prediction. In 1922, Lewis Fry Richardson published
`Weather prediction by numerical process` which described how small terms in the fluid
dynamics equations governing atmospheric flow could be neglected to allow numerical
solutions to be found. However, the sheer number of calculations required was too large to
be completed before the advent of computers.
At this time a group of meteorologists in Norway (V. Bjerknes, C. Rossby, T. Bergeron and J.
Bjerknes) developed the model that explains the generation, intensification and ultimate
decay (the life cycle) of mid-latitude cyclones, introducing the idea of fronts, that is, sharply
defined boundaries between air masses. They explained the large scale atmospheric flow in
terms of fluid dynamics and the mechanism by which rain forms too.
Starting in the 1950s, numerical experiments with computers became feasible. The first
weather forecasts derived this way used single-vertical-level models, and could successfully
predict the large-scale pattern of atmospheric lows and highs.
In the 1960s, the chaotic nature of the atmosphere was first observed and understood by
Edward Lorenz, founding the field of chaos theory. These advances have led to the current
use of ensemble forecasting in most major forecasting centres, to take into account
uncertainty arising due to the chaotic nature of the atmosphere.
Equipment of Meteorology
Meteorology is a science short on "lab" equipment and long or wide on field-mode weather
observation equipment. In the atmosphere, there are many things or qualities of the
atmosphere that can be measured. Rain, which can be observed, or seen anywhere and
anytime was one of the first ones to be measured historically. Also, two other accurately
measured qualities were wind and humidity. Neither of these can be seen, but can be felt.
The devices to measure these three sprang up in the mid-1400's and where respectively the
rain gauge, the anemometer, and the hygrometer. These basic instruments developed in time
to the modern automatic weather stations and remote controlled devices.
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In 1960 the launch of TIROS-1, the first successful weather satellite marked the beginning of
the age where weather information is available globally. Weather satellites along with more
general-purpose Earth-observing satellites circling the earth at various altitudes have become
an indispensable tool for studying a wide range of phenomena from forest fires to El Niño.
In recent years, climate models have been developed that feature a resolution comparable to
older weather prediction models. These climate models are used to investigate long-term
climate shifts, such as what effects might be caused by human emission of greenhouse
gases.
Weather forecasting
Although meteorologists now rely heavily on computer models (numerical weather
prediction), it is still relatively common to use techniques and conceptual models that were
developed before computers were powerful enough to make predictions accurately or
efficiently (generally speaking, prior to around 1980). They are:
• Persistence method. This assumes that conditions will not change. Often summarised as
"Tomorrow equals today". This method works best over short periods of time in stagnant
weather regimes.
• Extrapolation method. This assumes that the systems in the atmosphere propagate at
similar speeds than seen in the past at some distance into the future. This method works best
over short periods of time, and works best if you take diurnal changes in the pressure and
precipitation patterns into account.
• Numerical weather prediction or NWP. This uses computers to take into account a large
number of variables and creates a computer model of the atmosphere. This is most
successful when used with the methods below, and when model biases and relative skill are
taken into account.
• Consensus/ensemble methods of forecasting. Statistically, it is difficult to beat the mean
solution, and the consensus and ensemble methods of forecasting take advantage of the
situation by only favouring models that have the greatest support with their ensemble means
or other pieces of global model guidance..
• Trends method. This involves determining the change in fronts and high and low pressure
centres in the model runs over various lengths of time. If the trend is seen over a long
enough time frame (24 hours or so), it is more meaningful.
• Climatology/Analog method. This involves using historical weather data collected over long
periods of time (years) to predict conditions on a given date. A variation on this theme is the
use of teleconnections, which rely upon the date and the expected position of other positive
or negative pressure anomalies to give someone an impression of what the overall pattern
would look like with this anomaly in place, and is of more significant help than a model trend
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since it verifies roughly 75 percent of the time, when used properly and with a stable anomaly
centre. Another variation is the use of standard deviations from climatology in various
meteorological fields.
As can be easily seen from the above description, the most trustworthy methods rely firmly
on historical data collections. These are obtained thanks to local meteorological station
networks on long period of time, and more close are the rings of the network, the more
reliable will result the forecasting, both for weather predictions and for climate change
purposes.

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Guidelines to the realisation
Weather station

Weather station installation requires first of all the application of the fundamental norms of
WMO, published into the guidelines established by this Organisation on 1983. The following
directions are taken from the WMO “Guide to Meteorological Instruments and Methods of
Observation” (WMO, 2006).
The requirements for observational data may be met by using in situ measurements or by
remote sensing systems, according to the ability of the various sensing systems to measure
the elements needed. The surface-based subsystem comprises a wide variety of types of
station according to the particular application.
The representativeness of an observation is the degree to which it describes well the value of
the variable needed for a specific purpose. Therefore it is not a fixed quality of any
observation, but results from joint appraisal of instrumentation, measurement interval and
exposure against the requirements of some particular application. For instance, synoptic4
observations should typically be representative of an area up to 100 km around the station,
but for small-scale or local applications the considered area may have dimensions of 10 km
or less. Good exposure, which is representative on scales from a few metres to 100
kilometres, is difficult to achieve. Errors of unrepresentative exposure may be much larger
than those expected from the instrument system in isolation. A station in a hilly or coastal
location is likely to be unrepresentative on the large scale.
Users of meteorological observations often need to know the actual exposure, type and
condition of the equipment and its operation; and perhaps the circumstances of the
observations.
Site selection
The following considerations apply to the selection of site and instrument exposure
requirements for a typical synoptic or climatological station in a regional or national network.
(a) Outdoor instruments should be installed on a level piece of ground, approximately 10
metres by seven metres (the enclosure), covered with short grass or a surface
representative of the locality, and surrounded by open fencing or palings to exclude
unauthorized persons. Within the enclosure, a bare patch of ground about two metres by
two metres is reserved for observations of the state of the ground and of soil temperature
4

= Observations that give a broad view of a subject at a particular time.
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at depths of equal or less than 20 centimetres; soil temperatures at depths larger greater
than 20 cm can be measured outside this bare patch of ground).
(b) There should be no steeply sloping ground in the vicinity and the site should not be in a
hollow.
(c) The site should be well away from trees, buildings, walls or other obstructions.
(d) The sunshine recorder, rain gauge, and anemometer must have exposures to satisfy
their requirements, preferably on the same site as the other instruments.
(e) It should be noted that the enclosure may not be the best place from which to estimate
the wind speed and direction, another observing point, more exposed to the wind, may be
desirable.
(f) Very open sites which are satisfactory for most instruments are unsuitable for rain
gauges. For such sites, the rainfall catch is reduced in other than light winds and some
degree of shelter is needed;
(g) If in the surroundings of the instrument enclosure, maybe at some distance, objects like
trees or buildings obstruct the horizon significantly, then for observations of sunshine or
radiation alternative viewpoints should be selected.
(h) The position used for observing cloud and visibility should be as open as possible and
command the widest possible view of the sky and the surrounding country.
(i) At coastal stations, it is desirable that the station should command a view of the open
sea, but it should not be too near the edge of a cliff because the wind eddies created by
the cliff will affect the measurements of wind and the amount of precipitation.
(j) Night observations of cloud and visibility are best made from a site unaffected by
extraneous lighting.
It is obvious that some of the above considerations are somewhat contradictory and require
compromise solutions, specially when the placement of the site is in an urban place.
The position of a station referred to in the World Geodetic System 1984, Earth Geodetic
Model 1996 (WGS 84-EGM96), must be accurately known and recorded. The coordinates of
a station are:
(a) The latitude in degrees with a resolution of 1 in 1 000;
(b) The longitude in degrees with a resolution of 1 in 1 000;
(c) The height of the station above mean sea-level (MSL), 3 i.e. the elevation of the station,
to the nearest metre.
These coordinates refer to the plot on which the observations are taken and may not be the
same as those of the town, village or airfield after which the station is named. The elevation
of the station is defined as the height above mean sea-level of the ground on which the rain
gauge stands or, if there is no rain gauge, the ground beneath the thermometer screen.
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The characteristics of an observing site will generally change over time, e.g. through growth
of trees or erection of buildings on adjacent plots. Sites should be chosen to minimize these
effects, if possible.

Ideal layout of an observing station in the northern hemisphere showing
minimum distances between installations. (WMO, 2006)

Maintenance
All synoptic land stations and principal climatological stations should be inspected not less
than once every two years. Agricultural meteorological and special stations should be
inspected at intervals sufficiently short to ensure the maintenance of a high standard of
observations and the correct functioning of instruments.
Observing sites and instruments should be maintained regularly so that the quality of
observations does not deteriorate significantly between station inspections. Routine
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(preventive) maintenance schedules include regular “housekeeping” at observing sites (e.g.
grass cutting and cleaning of exposed instrument surfaces) and manufacturers’
recommended checks on automatic instruments. Routine quality control checks carried out at
the station or at a central point should be designed to detect equipment faults at the earliest
possible stage. Depending on the nature of the fault and the type of station, the equipment
should be replaced or repaired according to agreed priorities and time-scales.
Automatic weather stations (AWS)
An automatic weather station (AWS) is defined as a meteorological station at which
observations are made and transmitted automatically.
At an AWS, the instrument measurements are read out or received by a central data
acquisition unit. The collected data from the autonomous measuring devices can be
processed locally at the AWS or elsewhere, e.g. at the central processor of the network.
Automatic weather stations are used for increasing the number and reliability of surface
observations. They do this by:
(a) Increasing the density of an existing network by providing data from new sites and from
sites which are difficult to access and are inhospitable.
(b) Supplying, for manned stations, data outside the normal working hours.
(c) Increasing the reliability of the measurements by using sophisticated technology and
modern, digital measurement techniques.
(d) Ensuring homogeneity of networks by standardizing the measuring techniques.
(e) Satisfying new observational needs and requirements.
(f) Reducing human errors.
(g) Lowering operational costs by reducing the number of observers.
(h) Measuring and reporting with high frequency or continuously.
It is possible to classify AWSs into a number of functional groups:


Real-time AWS: A station providing data to users of meteorological observations in real
time, typically at programmed times, but also in emergency conditions or upon external
request. Typical real-time use of an AWS is the provision of synoptic data and the
monitoring of critical warning states such as storms, river, or tide levels.



Off-line AWS: A station recording data on site on internal or external data storage devices
eventually combined with a display of actual data. The intervention of an observer is
required to send stored data to the remote data user.

Since the cost of AWSs can be very high, the station facilities can also be used to satisfy
common and specific needs and requirements of several applications, such as synoptic,
aeronautical and agricultural meteorology, hydrology, and climatology. They may also be

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used for special purposes, such as nuclear power safety, air and water quality, and road
meteorology. Some AWSs are, therefore, multipurpose automatic weather stations.
An AWS may consist of an Integrated Automated Weather Observing (and data-acquisition)
System (AWOS) or a set of autonomous measuring devices connected to a data collection
and transmission unit. The layout of an AWS is typically:
(a) On a standard observing area, larger than 25 m ´ 25 m, a series of automated sensors
sited at the recommended positions and interconnected to one or more data collection units
using interfaces, or for AWOS, a set of sensors installed in close combination, but not
affecting each other, directly connected to a central processing system by means of shielded
cables, fibre optics, or radio links.
(b) A Central Processing System (CPS) for sensor data acquisition and conversion into
computer-readable format, proper processing of data by means of a microprocessor-based
system in accordance with specified algorithms, the temporary storage of processed data,
and their transmission to remote users of meteorological information.
(c) Peripheral equipment such as a stabilized power supply providing power to the various
parts of the station, a real-time clock, and built-in test equipment for automatic monitoring of
the status of vital parts of the station. For specific applications, local terminals for manual
entry and editing of data, display devices and printers, or recorders are added to the station.
Sensors
Because measurements at most AWSs are controlled from large distances, these sensors
must be robust, fairly maintenance-free and should have no intrinsic bias or uncertainty in the
way in which they sample the variables to be measured. In general, all sensors with an
electrical output are suitable candidates. There are a large number of sensors of varying
performance and quality (and price) that are suitable for use with automatic data-acquisition
systems. There are frequent new developments, some enhancing the performance of existing
sensors while others are often based on new physical principles. Depending on their output
characteristics, sensors can be classified as analogue, digital and ‘intelligent’ sensors.


Analogue sensors: commonly sensor output is in the form of voltage, current, charge,
resistance, or capacitance. Signal conditioning converts these basic signals into voltage
signals.



Digital sensors: sensors with digital signal outputs with information contained in a bit or
group of bits, and sensors with pulse or frequency output.



‘Intelligent’ sensors/transducers : sensors including a microprocessor performing basic
data acquisition and processing functions and providing an output in serial digital or
parallel form.

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Central processing unit
The core of an AWS is its central processing system (CPU). Its hardware configuration
depends on the complexity and magnitude of the functions it has to perform and on whether
no unique hardware solution exists. In general, the main functions of the CPU are data
acquisition, data processing, data storage, and data transmission. In the majority of existing
AWSs, all these functions are carried out by one microprocessor-based system installed in a
weather-proof enclosure as close as possible to the sensors, or at some local indoor place. If
the unit is located near the sensors, on-site processing reduces the amount of data which
must be transmitted and enables those data to be presented in a form suitable for direct
connection to communication channels.
Data acquisition, processing and transmission
In general, the data acquisition hardware is composed of:
(a) Signal conditioning hardware for preventing unwanted external sources of interference
from influencing the raw sensor signals, for protecting the CPU electronics, and for
adapting signals to make them suitable for further data processing;
(b) Data acquisition electronics with analogue and digital input channels and ports, scanning,
and data conversion equipment to enter the signals into the CPU memory.
The data processing hardware is the heart of the Central Processing System (CPS) and its
main functions are the master control of the input/output of data to, and from, the CPS and
the proper processing of all incoming data by means of relevant software. Its operation is
governed by a microprocessor. Microprocessors do not change the principles of
meteorological measurements and observing practices but they do allow the instrument
designer to perform technical functions in a new way to make measurements easier, faster
and more reliable, and to assign to the instrument higher capabilities, especially in data
handling. The unit can be equipped with different types of memory as random access
memories (RAM) for data and program storage, non-volatile programmable read-only
memories (PROM) for program storage (programs are entered by means of a PROM
programmer), and non volatile electrical erasable ROMs (EEPROMS) mostly used for the
storage of constants which can be modified directly by software. In most stations, the RAM
memory is equipped with a battery backup to avoid loss of data after power failures.
The data transmission part of the CPS forms the link with the ‘outside world’ which may be
the local observer or the maintenance personnel, the central network processing system, or
even directly the users of meteorological information. The equipment is interfaced to the CPS
by using commonly available serial and parallel input/output ports. The most suitable means
of data transmission depends mainly on the site in question and the readily available
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transmission equipment. No single solution can be regarded as universally superior and
sometimes the transmission chain requires the use of several means.
Urban observations
There is a growing need for meteorological observations conducted in urban areas. Urban
populations continue to expand and Meteorological Services are increasingly required to
supply meteorological data in support of detailed forecasts for citizens, building and urban
design, energy conservation, transport and communications, air quality and health, storm
water and wind engineering, insurance and emergency measures. At the same time
Meteorological Services have difficulty in taking urban observations that are not severely
compromised. This is because most developed sites make it impossible to conform to the
standard guidelines for site selection and instrument exposure due to obstruction of airflow
and radiation exchange by buildings and trees, unnatural surface cover and waste heat and
water vapour from human activities.
The need for flexibility runs slightly counter to the general notion of standardization that is
promoted as WMO observing practice. In urban areas it is sometimes necessary to accept
exposure over non-standard surfaces at non-standard heights, to split observations between
two or more locations, or to be closer than usual to buildings or waste heat exhausts.
The units of measurement, and the instruments used in urban areas are the same as those
for other environments. Therefore only those aspects that are unique to urban areas, or are
made difficult to handle because of the nature of cities, such as the choice of site, the
exposure of the instruments.
The clarity of the reason for establishing an urban station is essential to its success. Two of
the most usual reasons are, the wish to represent the meteorological environment at a place
for general climatological purposes; and the wish to provide data in support of the needs of a
particular user. In both cases the spatial and temporal scales of interest must be defined and,
as outlined below, the siting of the station and the exposure of the instruments in each case
may have to be very different.
There is no more important input to the success of an urban station than an appreciation of
the concept of scale. There are three scales of interest:
(a) Microscale – every surface and object has its own microclimate on it and in its immediate
vicinity. Surface and air temperatures may vary by several degrees in very short
distances, even millimetres, and airflow can be greatly perturbed by even small objects.
Typical scales of urban microclimates relate to the dimensions of individual buildings,
trees, roads, streets, courtyards, gardens, etc. Typical scales extend from less than one
metre to hundreds of metres. The climate station recommendations are designed to
standardize all sites, as far as practical. Hence the use of a standard height of
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measurement, a single surface cover, minimum distances to obstacles and little horizon
obstruction. The aim is to achieve climate observations that are free of extraneous
microclimate signals and hence they characterize local climates. With even more
stringent standards at first order stations they may be able to represent conditions at
synoptic space and time scales. The data may be used to assess climate trends at even
larger scales. Unless the objectives are very specialized, urban stations should also avoid
microclimate influences, but this is hard to achieve;
(b) Local scale – this is the scale that standard climate stations are designed to monitor. It
includes landscape features such as topography but excludes microscale effects. In
urban areas this translates to mean the climate of neighbourhoods with similar types of
urban development (surface cover, size and spacing of buildings, activity). The signal is
the integration of a characteristic mix of microclimatic effects arising from the source area
in the vicinity of the site. The source area is the portion of the surface upstream that
contributes the main properties of the flux or meteorological concentration being
measured (Schmid, 2002). Typical scales are one to several kilometres ;
(c) Mesoscale – a city influences weather and climate at the scale of the whole city, typically
tens of kilometres in extent. A single station is not able to represent this scale.

Schematic of climatic scales and vertical layers found in urban areas: Planetary

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Boundary Layer PBL, Urban Boundary Layer UBL, Urban Canopy Layer UCL (WMO, 2006)

An essential difference between the climate of urban areas and that of rural locations is that
in cities the vertical exchanges of momentum, heat and moisture does not occur at a (nearly)
plane surface, but in a layer of significant thickness called the Urban Canopy Layer (UCL).
The height of the UCL is approximately equivalent to that of the mean height of the main
roughness elements (buildings and trees). The microclimatic effects of individual surfaces
and obstacles persist for a short distance away from their source but are then mixed and
muted by the action of turbulences. The distance before the effect is obliterated depends on
the magnitude of the effect, the wind speed and the stability (i.e. stable, neutral or unstable).
This blending occurs both in the horizontal and the vertical. As noted, horizontal effects may
persist up to a few hundred metres. In the vertical, the effects of individual features are
discernable in the Roughness Sub-Layer (RSL), that extends from ground level to the
blending height, where the blending action is complete.
It follows from the preceding discussion that if the objective of an instrumented urban site is
to monitor the local scale climate near the surface, there are two viable approaches:
(a) Locate the site in the UCL at a location surrounded by average or ‘typical’ conditions for
the urban terrain, and place the sensors at heights similar to those used at non-urban sites.
This assumes that the mixing induced by flow around obstacles is sufficient to blend
properties to form a UCL average at the local scale;
(b) Mount the sensors on a tall tower above the RSL and obtain blended values that can be
extrapolated down into the UCL.
In general, approach (a) works best for air temperature and humidity, and approach (b) for
wind speed and direction and precipitation. For radiation, the only significant requirement is
for an unobstructed horizon. Urban stations, therefore, often consist of instruments deployed
both below and above roof-level; this requires that site assessment and description include
the scales relevant to both contexts.
Urban climate zone classification
Characterization of the sites of urban climate stations needs to take account of the most
important basic features of the urban structure (dimensions of the buildings and the spaces
between them, the street widths and street spacing), the urban cover (built-up, paved,
vegetated, bare soil, water), the urban fabric (construction and natural materials) and the
urban metabolism (heat, water and pollutants due to human activity). No universally accepted
scheme of urban classification for climatic purposes exists. A good approach is the Urban
Climate Zones (UCZ) scheme below illustrated.

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Simplified classification of distinct urban forms arranged in approximate
decreasing order of their ability to impact local climate (WMO, 2006)

Key points for urban stations
When establishing an urban station, the rigid guidelines for climate stations are often
inappropriate. It is necessary to apply guiding principles rather than rules, and to retain a
flexible approach. This often means different solutions for individual atmospheric properties
and may mean that not all observations at a ‘site’ are made at the same place.
Because the environment of urban stations changes frequently as development proceeds,
frequently updated metadata are as important as the meteorological data gathered. Without
good station descriptions it is impossible to link measurements to the surrounding terrain.
An essential first step in selecting urban station sites is to evaluate the physical nature of the
urban terrain, using a climate zone classification. This will reveal areas of homogeneity.
Several urban terrain types comprise an urban area. In order to build a picture of the climate
of a settlement, multiple stations are required. Sites should be selected that are likely to
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sample air drawn across relatively homogenous urban terrain and so are representative of a
single climate zone. Care is necessary to ensure that microclimatic effects do not interfere
with the objective of measuring the local-scale climate.
(a) Air temperature and humidity measurements made within the UCL can be locally
representative if the site is carefully selected. If these variables are observed above roof
-level, including above the RSL, there is no established link between them and those
within the UCL;
(b) Wind and turbulent flux measurements should be made above the RSL but within the
internal boundary layer of the selected urban climate zone. Such measurements must
establish that the surface ‘footprint’ contributing to the observations is representative of
the climate zone. For wind, it is possible to link the flow at this level and that experienced
within the canopy;
(c) Precipitation observations can be conducted either near ground at an unobstructed site,
or above the RSL, corrected according to parallel wind measurements;
(d) With the exception of incoming solar radiation, roof top sites are to be avoided, unless
instruments are exposed on a tall mast;
(e) Net and upwelling radiation fluxes must be made at heights sufficient to sample
adequately the range of surface types and orientations typical of the terrain zone.

Network
An AWS usually forms part of a network of meteorological stations each transmitting its
processed data to a central network processing system by various data transmission means.
As the tasks to be executed by this central system are strongly related and often
complementary to the tasks of the AWSs, the functional and technical requirements of both
the central system and the AWSs, should be very well coordinated.
When planning the installation and operation of a network of AWSs it is of the utmost
importance to consider the various problems associated with maintenance and calibration
facilities, with their organization, and with the training and education of technical staff.
Network density considerations are beyond the scope of this work as they depend on the
particular applications. However, the optimum siting and exposure of stations have an
important influence on the performance of the stations and have to be studied before
installing stations.
The network might use landline or radio communications (especially for very remote sites) or
a combination of both.
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The advantage of using a telecommunications service provider is that all care for
maintenance of the network service and probably the communications interfaces lies with the
provider who should respond promptly to the AWS system manager's fault reports. Note the
need to be able to determine on which side of the communications interface (AWS or
telecommunications circuits) the fault lies, which may be problematical. AWS networks have
often used dial-up circuits in the public switched telephone network with costs related to
distance and connect time, depending on the tariffs of the local communications provider.
The other option is to have a 'private network' network based on dedicated leased lines of
defined quality. There will be no switching delay in establishing the circuits, higher
transmission speeds are available, and there will be a high certainty that the circuit will be
maintained. The leasing costs will depend on the line distances, but not on the volume of
data. Costs are higher than for dial-up connections when the volume of data is fairly low.
ARSIAL SIARL weather station network utilise Global System for Mobile communications
(GSM).
An AWS usually forms part of a network of meteorological stations and transmits its
processed data or messages to a central network processing system by various data
telecommunication means. The specification of the functional and, consequently, the
technical requirements of a central system is a complex and often underestimated task. It
requires good cooperation between AWS designers, specialists in telecommunication,
software specialists, and data users. The main functions of a central network system are data
acquisition including decoding of messages from the AWS network, remote control and
housekeeping of AWSs, network monitoring and data quality control, further processing of
data to satisfy users’ requirements, entry to the network database, display of data, and data
transfer to internal or external users.
The cost of servicing a network of automatic stations on land and, in particular, at sea can
greatly exceed the cost of their purchase. It is, therefore, of central importance that AWSs are
designed to have the greatest possible reliability and maintainability. Special protection
against environmental factors is often justified, even at high initial costs.
As an AWS is based on the application of technology that differs considerably from the
equipment at conventional stations and networks, a profound revision of existing training
programmes and of the necessary technical staff is obvious. Any new training programme
should be organized according to a plan that is geared to meeting the needs of users. It
should especially cover the maintenance and calibration outlined above and should be
adapted to the system.
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Requesting existing personnel to take on new functions, even if they have many years of
experience with conventional stations, is not always possible and may create serious
problems if it has no basic knowledge of electrical sensors, digital and microprocessor
techniques, and use of computers.
ARSIAL SIARL Network
ARSIAL SIARL (Latium Region Integrated Service for Agriculture Meteorology) Network was
created for agro-meteorological service, in accordance with the Regional Law n. 40/1966. It
gathers 83 AWSs, diffused on the regional territory: 26 in Rome, 21 in Viterbo, 9 in Latina, 15
in Rieti, 11 in Frosinone provinces. Moreover, there are two manual stations in Tarquinia and
Canino municipalities that record data starting from 1980.
All the stations are equipped with sensors responding to the site peculiar exigencies (from 3
to 12 sensors) and are powered thanks to a photovoltaic solar cell. The power supply is
integrated by a battery that ensures 5 days emergency service. Weather stations were
installed in the respect of WMO guidelines and UCEA (Central Italian National Office of
Agronomic Ecology) prescriptions. The stations were manufactured by tree companies: SIAP,
CAMPBELL and SILIMET.
All the stations are equipped with datalogger for data acquisition and processing that could
work at extreme conditions (from -20 to + 70 °C temperature and 0-100% humidity) and

Dislocation of ARSIAL SIARL AWSs in the Latium Region
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GSM modem for the transmission of data to the control centre. The data are transmitted
during the night thanks to automatic calls and are published on ARSIAL website
(http://www.arsial.it/portalearsial/agrometeo/index.asp) at 10 a.m. of the next day.

Internet download menu of the real time ARSIAL urban AWS in Rome

All the stations could be remote programmed from the control centre and it is possible to
modify software settings, as the acquisition period or processing timetable.
On the roof of ARSIAL headquarters in Rome is placed a real time urban AWS that acquires
data downloadable in real time in Internet
(http://www.arsial.it/portalearsial/agrometeo/D5.asp ).

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Main sensors of an ARSIAL SIARL standard field weather station are:


wind speed and direction sensor: cup, propeller sensor and vane (banner);



air temperature and humidity: electric transducers;



soil temperature: platinum thermoelectric
transducer;



atmospheric

pressure:

piezoelectric

transducer;



rain & snow: electric rain gauge;



solar radiation: thermo battery transducer;



solar quantum: silicium photovoltaic receptor;

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Climate monitoring and the link “Country-Town”
Climate monitoring practical involvement is particular important into the boarder perspective
of the link country-town. Urban ecosystems influence in a peculiar way local climate with
relevance for inhabitants and traffic fluxes. It is well known the urban climate (Salmond J.,
2005) has its peculiarities: like higher temperatures (Heath Island effect) and less humidity,
barrier effect for light winds, less mitigation of extremes events. Heat islands can occur yearround during the day or night. Urban-rural temperature differences are often largest during
calm, clear evenings. This is because rural areas cool off faster at night than cities, which
retain much of the heat stored in roads, buildings, and other structures. As a result, the
largest urban-rural temperature difference, or maximum heat island effect (1 to 6°C), is often
three to five hours after sunset (EPA 2007). Another important problem of town climate is due
to the greenhouse emissions. These are generally produced in urban environment and could
be reduced and mitigated thanks to the filter effect of wood areas, green belts, tree shelter
belts, etc…

Heat island effect in the country-town profile (EPA, 2007)

Tourism as key role in the link country-town. The importance of planning. The need of
investigations on climate effects on human beings.
But what differs towns from country is basically the human density of its inhabitants. Towns
are places characterised not only by road, buildings and other artificial structures, but by
stable great agglomerations of human subjects too. And what are the effects of climate on
human beings?
Another important climatic effect to be considered among the whole involved in the link
country-town, is the evolution of the periodical (week-end and holydays)

migratory

phenomena of citizens to and from the urban centres, usually recognised under the name
“tourism”. As was highlighted at the 1st International Conference on Climate Change and
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Tourism (Djerba, Tunisia, 9-11 April 2003), whatever the environmental outcome, tourism
cannot be seen in isolation. Major changes in the pattern of demand will lead to wider
impacts on many areas of economic and social policy - such as, for example, in employment
and labour demand and in regional policy issues such as housing, transport and social
infrastructure. Knock-on effects could influence other sectors, such as agriculture supplying
tourism demand, handicraft industries, local small business networks and so on. (WTO,
2003). Conclusions of the conference stressed out that: “… there is an opportunity to pursue
the interests of the sector through further studies undertaken by the World Tourism
Organization, in collaboration with key United Nations agencies, such as the World
Meteorological Organization (WMO),… the Intergovernmental Panel on Climate Change
(IPCC), ….. it was suggested that further studies should be encouraged by the tourism
industry on national, regional and/or local levels as appropriate … The studies should involve
all the main stakeholders in the industry, as well as the scientific community....
In order to focus closely on the implications for the tourism industry - its investment decisions,
marketing programmes, physical infrastructure development and so on - local studies
ultimately will be needed in order to form the basis for planning suitable responses, whether
these fall into the category of mitigation, adaptation or retreat.
The importance of the planning perspective in this context has been stressed by many
important organisms. In the United Kingdom the TCPA (Town & Country Planning
Association) took a strong position on the problem of planning and climate change from
January 2003 (TCPA, 2003):
“Climate change is potentially the most catastrophic challenge of our time. Doing nothing is
not an option. We must act now to prevent the worst. This means effecting a real change in
the way we plan our communities. The planning system has a crucial role to play to prevent
further damage through the provision of sustainable energy, energy efficiency, food security,
high quality housing, green spaces and integrated transport, as well as helping us adapt to
the inevitable impacts of climate chaos.
Planners already make a significant contribution through policy- and decision-making. Often
this relates to adaptation measures – such as flood prevention – but increasingly planners
are taking steps to reduce dangerous greenhouse gas emissions that will cause further
climate change.
As well as setting targets on renewable energy and carbon emissions, Government has
identified climate change as a priority in a number of planning policy statements, and
considers the UK Sustainable Development Strategy to be material to the planning process.
However, there are growing calls for a single comprehensive statement on climate change,
which communicates the vital importance of this issue to decision-makers. Such a statement

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would embed climate change in decision-making and would have a significant impact on the
planning system, the actions of developers, architects, local authorities and individuals.”
But planning has to be supported mainly by central authorities and governments and they will
support their decisions mainly on the base of data obtained through scientific investigation on
environmental and geomorphologic effects. But effects on human beings must not be
neglected too.
One of the more fecund scientific contributions in this way was due to the scientific
investigation of climate and human behaviour.
Climate change most apparent effects on human health
With the realization that global climate change is on the march, another calamity needs to be
added: increase in temperature and in UV-radiation. Hence the strong relationships between
weather and climate and health that are emerging as an important and completely new
scientific issue. A rough list of the main climate change weather parameters and their
importance for the comfort and safety of human health run as follows:
1) Temperature: This may appear simple but is vital as in the future it will be more often
subjected to sudden changes of up to 10-15 degrees in the course of short time period.
Human body requires time to adjust to such abrupt changes.
2) Intensity of Radiation: Sometimes even though the temperature may be bearable, the
radiation type and intensity due to the hole in the ozone layer at certain period may be
harmful because of the fragility of the skin, the eye and other body parts. Intense UV-B
radiation, most particularly, is to be avoided or may lead to skin cancer and eye cataract.
3) Reflected radiation: Often tourists on the beach, or in particular urban places consider
themselves protected under large umbrellas or building shadow. Such may not be the case
as equally intense radiation, capable of roasting the skin and likely to cause severe eye
damage, is reflected by the sand or large white or glass surfaces.
4) Wind: Although slow winds are always welcome in the warm climates, it becomes a
nuisance for outdoor activities above a certain speed. This may be especially the case when
such winds are often loaded with moisture, another source of discomfort.
5) Humidity: High humidity is never welcome in warm climates. Already elevated
temperatures combined with high relative humidity values may produce an uncomfortable
atmosphere. More and more scientists are considering apparent temperature as an important
factor for the health of populations. For example, a temperature of 30 degrees Celsius
combined with a relative humidity of 80% is equivalent to an apparent temperature of 38
degrees. Exposure to such temperatures may lead to dehydration and even fatality for frail or
aged people.
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Biometeorology science
In recent years scientists developed different methods for assessing climate effects in human
behaviour. Biometeorology, for instances, is a science developed mainly in Germany, where
capital studies were conducted on heat balance modelling, on the effects of climate on
human health, on urban bioclimatology, on human biometeorological assessment (Hoppe P.
1993, Jenritzky G. 1992, Mayer H. 1993, Matzarakis A. 1995,)
In biometeorology thermal indices that are derived from the energy balance of the human
body are considered very useful. The problem is that input environmental data required for
these schemes are rather specialized and usually not available. Standard climate data are air
temperature, air humidity and wind speed. However, the most important environmental
parameters for deriving modern thermal indices are the short and long wave radiation (and
the derived mean radiant temperature). These can be determined using special techniques.
Matzarakis (Matzarakis A., 2002) developed the RayMan model, for urban climate studies. It
has been shown as an helpful tool for the assessment of tourism and climate related
questions. Cause and effect relations between the atmospheric environment and human
health or human comfort can be analyzed by a humanbiometeorological classification:
• thermal complex,
• air pollution complex,
• actinic complex
• and biotropy.
The thermal complex represents the meteorological factors air temperature, air humidity and
wind velocity, and also contains the short and long wave radiation that thermophysiologically
affects humans in indoor and outdoor climate. This complex is relevant to human health
because of a close relationship between the thermoregulatory mechanism and the circulatory
system. The air pollution complex includes solid, liquid and gaseous natural and
anthropogenic compounds that cause adverse health effects in humans, indoors as well as
outdoors. The relevance of air quality conditions to human health depends on the emission
sources and the transmission conditions (dispersion, dilution, possible chemical reactions,
wash out and rain out of air pollutants). These factors are determined by atmospheric layers
(grade of turbulence), wind, precipitation, and possibly air humidity and solar radiation. The
actinic complex comprises the visible and ultraviolet range of the solar radiation that shows –
apart from mere thermal effects – direct biological effects. Biotropy deals with the biological
effects of the weather.
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Atmospheric environment and human (WMO, 1999)

Results of human biometerological analysis of different spaces are of interest because of
their possible application in:
• urban and landscape planning (regarding investigation of impacts of big constructional
projects),
• tourism (for the selection of holiday or the duration of holidays),
• giving advice concerning the location of residential areas,
• climate change and relation to human biometeorology,
• climate and health (for the analysis of thermal stress situations).
Classic examples of application in a Mediterranean climate, were carried on for the
evaluation of a thermal urban structure environment, like an airport, not only in summer, but
also throughout the whole year. On the other hand structures in urban areas are very
complex and the variability of the meteorological parameters is very high, due for instances
to climate manipulation owing to the influence of natural components as trees, parks, woods,
etc.
For the evaluation of the thermal component of urban and regional climate precise and high
resolution radiation data of the whole surrounding are necessary. These data can be either
measured or calculated using a radiation model.
Tourism Climatic Index (TCI)
Mieczkowski on 1985 described a method of computing tourism climatic indices to integrate
all the climatic elements relevant to the tourism experience. He noted that human response to
climatic elements is as much psychological and physiological. The TCI is a composite
indicator that captures the climatic elements most relevant for the ‘average’ tourist, assuming
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that the tourist is engaged in light physical activities, such as beach recreation, sight-seeing,
shopping and relaxing. It has been widely used in studies examining the impacts of climatic
factors including climate change on tourism. The TCI includes seven climate variables:
monthly means for maximum daily temperature; mean daily temperature; minimum daily
relative humidity; mean daily relative humidity, total precipitation, total hours of sunshine, and
average wind speed. These seven climate variables are combined into five indices that
comprise the TCI (Mieczkowski, 1985).

Climate change perspectives
Its obvious that climate change will involve all human activities, starting from basic needs as
food production and agriculture (only this latter originates the rough 20% of greenhouse gas
emissions and will be strongly affected by its consequences, in terms of crops growing ability,
at last) . But as stressed before in this study, in the perspective of the link country-town, we
are considering one of the most recurrent phenomena that is tourism. Effects of climate
change and tourism could be considered on two-way, as to say the effects of climate change
on tourism and those on climate originated by tourism.

Interactive effect of climate change and tourism (Moreno A., 2006)

For the first part of the problem, many scientist stressed that the most important direct
effects of climate on human behaviour occurs on tourism sector.
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Tourism is one of the biggest of all industries, powering economies of several nations. Has
been estimated that the average sum visitors spend yearly on travel, hotels, meals and other
items in foreign countries represents roughly 10% of all international trade and 5% of total
global economic output (Boodhoo, 2001).
Climate change effects are significant for both the tourism industry and the holiday makers
themselves, but they are also of importance to the planning and design of tourism buildings,
recreation facilities and a variety of other issues. At word level alarm for climate change
effects on tourism sector was arouse first of all by Small Island States stakeholders. Small
Island States and low-lying areas, especially in the tropics, with their warm climates and the
sun and sea are preferred destinations for tourists. While tourism account for about 6% of the
total economy of Thailand and France, 7% in Malaysia, its represents as much as 50% in
Bali, 60% in the Bahamas, 80% in Seychelles and 90% in the Maldives. These states are the
most endangered in perspective for the upheaval of the sea level.
Concerning Europe, obviously all along the coasts infrastructures are at risk and low-lying
areas and large deltas are threatened even more. But the problem of the assessment of the
climatic change into the tourist’s offer occurs for the hinterland too, on the mountains for the
winter sport seasons and on lowland areas for peculiar tourist offers. The problem of the
sustainable development of tourism was particularly stressed in many European countries. In
France, for instance, this problem was debated at governmental level

(Ministére de

l’Economie, de Finances e de l’Emploi, 2007). In this case the solutions advanced concern a
diversification of the tourist offer (trekking and others activities instead o ski) in a caution logic
but the problem of re-conversion of mid-mountain ski resorts is still left over. What is the
future of winter sports into the different types of French resorts?
Many opportunities could be offered by the local typical resources. Many tourist activities in
fact are linked to the local typical resources that could be adjoined to the edge of
fundamental tourist practices motivated by other reasons (sun appeal , snow appeal, etc….)
but that could represent the core of other tourism practices (the wine tourism, for instance).
But the climate change can endanger these patrimonial local elements too and is urgent the
request for institutional or technological innovations. In this way for instance, the climate
change could bring to replace the grape varieties of a well-known wine territory and this will
drive to re-define the attribution criteria of wine PDO, Protected Designation of Origin. For the
French government is still open the problem of the future disappearance or rarefying of
certain local typical patrimonies that are an important source for the tourism sector, as for the
truffle. French government is thus considering if it is possible to face a re-equilibration of the
tourist fluxes against a modification of climate change. But it considers too that at present
there are too few studies on the possible relation and the potential impacts of this change on
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the tourism. It considers again that certain knowledges are still essential to operate fast on
the sustainable development of tourism, like : a) a sharper knowledge on tourist climatic
exigencies, b) an inventory and a geographic referenced study of the territory threats and
opportunities inserted in a word context and framed by regional climatic scenarios.
It is important too to develop research themes on the adaptation strategies for littoral- and
mountain-tourism.
A good example of managing the problem is offered by the Portuguese CLITOP in-progress
study (Casimiro E., 2005). The aim is to address climate and/or climate change impacts on
tourism, to investigate how climatic changes in Portugal influence outdoor air and water
thermal comfort and it’s implication to tourism demand and population (and tourist) health, in
four popular tourist coastal destinations. Ambient air thermal comfort levels are calculated
using biometeorological models, while coastal water thermal comfort levels are assessed
based on observed and modelled sea surface temperatures. The impact of thermal extremes
on human health are assessed using standard epidemiological methods.
Potential changes in energy demands that are required to maintain comfortable indoor
thermal levels in tourist related facilities and equipments, such as hotels, swimming pools,
and tour buses, in these destinations are assessed too. Climate data used in the impact
studies are based on observed data and climate change scenarios 50 years into the future.
Among the expected results there is the identification and discussion of adaptation measures
to reduce vulnerability to resulting climate change impacts.
One the other end it is important to investigate on the effects of tourism on climate. While
concern about tourism's polluting effects covers all aspects of a tourist's activity, there is a
consensus that the primary issue relates to travellers' consumption of transport services,
notably road and air transport. In the former case, there is clear evidence from major tourism
destinations such as France, that the use of road transport by travellers contributes
significantly to greenhouse gas (GHG) emissions. The 1st International Conference on
Climate Change and Tourism clearly announced that the tourism industry shares some of the
responsibility for road transport pollution and thus also shares a responsibility to minimise
harmful emissions by encouraging sustainable, carbon-neutral road transport solutions. As
for air transport, the effects are surely far heavier, but there is still a lot of misinformation on
this argument.
In the wider area of the sustainability of tourism, serious concerns were also raised about
tourism's high per capita consumption of water, energy efficiency and the effects that tourism
has on flora and fauna. One of the mainly problems due to climate change is the possible
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reduction of water resources. Recent studies on this scenario (Schmude J. 2004) explore the
importance of water as a resource for tourism. Here two different aspects have to be
considered. On the one hand, water is a factor concerning the attractiveness of a tourist
destination, because it can be used for a variety of sports and leisure activities. Furthermore,
areas covered with water or shorelines function as background scenery for tourism. Hence,
the availability of water affects tourist demand. On the other hand, water is used for running
tourist services. The focus of attention is on the water demands of the tourist superstructure
(e.g. in accommodation facilities) and also of the tourist infrastructure in the frame of future
changes. This could help to calculate a basic water supply index for tourist demand that could
be very helpful for planners and decision making actors.
Need for decision support tools
As we can now understand, the action of planning the development of the link country-town,
at the light of climate global change, involves primarily the tourist business sector, interested
by an extra wide complex of factors that taking into account the preliminary exigencies of
economic development and ecological sustainability has to cope with the more different
problems as we have seen, for instances: economic analysis, people exposure to radiation,
water demand, environmental forecasting,… Not to mention all the territorial and
geographical variables linked with the traditional planner profession.
The quantity and quality of elements to be valued is so high that the potential risk of mistake
increases at exponential level with the rise of variables.
Is therefore urgent the need of developing tools to aid the planning process .

Climate monitoring: science for decision makers
A considerable amount of new environmental data is being generated as the result of the
deployment of regional observing networks from both space-based (satellites) as well as
ground-, air- and sea- based sensors. While much new information is being generated and
used to answer research questions, there is a significant gap in its “uptake” and use to inform
decision making processes by the business community. There are many reasons for this.
Among the major barriers are lack of awareness of the availability and relevance of the
information, lack of knowledge of the reliability of the information, lack of business “access
portals” to the information and the lack of “know-how” as to how to use the information in
business operation and planning decisions.

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A strong remind and alarm concerning the need of decision making science for climate
change problems was originally launched on 2001, with the Third Assessment Report of the
Intergovernmental Panel on Climate Change (IPCC) stressing out the three concepts of
“Impacts, Adaptation, and Vulnerability” (McCarthy J.J., 2001). This appeal has been
answered by many institutions white quite good solicitude but in different ways.
Quoting Kevin Noone, IGBP’s executive director (Noone K., 2007): “The science need to
support decision making about adaptation requires a sophisticated understanding about how
the Earth system works, but goes well beyond just that. We need new tools to help us
develop robust “what if” scenarios for different potential adaptation schemes, and their
consequences”. Noone describes theis new tools as new types of models that couple
together active, predictive descriptions of human behaviour and choice with the kinds of
models used to predict future climate.
But this process has to be supported mainly by central authorities and governments. Looking
out at the positions of the latters it stands out that the most important issue of the future
strategies at European Policy level is the question: “How to cope with climate change due to
greenhouse emissions?” The future impact problem has been thoroughly deepened into the
EU environment climate website (ECCP, 2007):

“…Therefore, in addition to avoiding and

reversing climate change through reducing in emissions of greenhouse gases, there is an
urgent need to ensure that we are able to adequately adapt to climate changes predicted for
the European regions.”
One of the solution pointed out is the ‘Adaptation policy’: “… Adaptation to climate change is
a complex area. It involves considering climate change impacts on a range of sectors,
organizations and people. Making decisions about adaptation policy involve risk assessments
and assessments of costs and benefits. The main goal of such policies is to ensure that
decisions we make today do not compromise the resilience of the European Union in the
future.
The impacts of climatic changes will hit locally and regionally in different ways. The majority
of adaptation actions will therefore need to be decided and to be undertaken at the local,
regional and national level.
The European Commission is therefore exploring its role and the scope for a policy strategy
to adapt to the impacts of unavoidable climate change and how best to assist local, regional
and national efforts….”

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Vulnerability, Adaptation and Mitigation to climate change
At decisional level the problem of how to cope with climate change had a first answer with
the definition of a strategy. This was firstly set by the IPCC (IPCC, 2007) with the publication
of the Reports of Working Groups II (Impacts, Adaptation and Vulnerability) and III (Mitigation
of Climate Change).
The best definition of this strategy has been described by the Netherlands Organisation for
Scientific Research (NWO, 2004) in the Brochure of its “Vulnerability, Adaptation and
Mitigation" (VAM) Programme. The emphasis here is that the themes are more oriented
towards social and behavioural sciences than in the earlier programmes. VAM focuses on
research into the social and behavioural aspects of climate change, particularly within and in
cooperation between public administration, geography, environmental economics, sociocultural sciences, environmental law, psychology and other disciplines. The programme is not
intended for biological and ecological research. The VAM themes are:
1) Vulnerability; can be seen as the extent to which health, economy and nature and
biodiversity will be affected as a result of a certain climatic change.
2) Adaptation; means adapting to a changed or changing climate, and covers local, national
and global aspects. Adaptation is intended to reduce the vulnerability of systems.
3) Mitigation; this term can be explained in various ways. Sometimes it is seen as the
avoidance of climate change, whatever strategy may be followed. This may include a
reduction in the emission of greenhouse gases. Another choice would be to clearly separate
mitigation from reduction. Mitigation is then limited to the neutralisation of greenhouse
emissions which have already been produced, such as storing CO2 underground or
absorbing it by planting forests.
4) Adaptation-plus-mitigation; adaptation and mitigation are not alternatives for each other.
They form two complementary, parallel tracks in climate policy. Mitigation is the only
fundamental solution for the climate problem, but adaptation is necessary in order to
withstand the inevitable consequences of climate change.
While "adaptation" sounds reasonably specific, it is a very comprehensive term which is
difficult to conceptualise and analyse. One important question is how adaptation to climate
change can be fitted into mainstream development policy and projects. As for mitigation it is
important to realise that the core of international climate policy is formed by the details and
policy of mitigation, although the acceptance of transfers for the purpose of adaptation can be
functional in this. Therefore the development of adaptation and mitigation scenarios in the
event of rapid and extreme manifestations of climate changes, and the related costs and
acceptance issues, can represent an interesting scientific challenge.

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The utilisation of vulnerability strategy to implement research studies on the impact of climate
on tourism is at the core of the ECLAT-COAST project “The influence of climate & weather on
tourist demand in Europe’s coastal zones: analysis and exploration” (Moreno A., 2006). One
of the focus of this project is the hypothesis that vulnerability to climate change of
Mediterranean tourist destinations is generally higher than that of northern European
destinations as a result of higher sensitivity, greater exposure and less room for adaptation.
Current or newly developed tourism climatic indices can be reliable indicators of coastal
destinations´

sensitivity

to

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in

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visitation

as

a

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of

climate

change/variability. In this study the operationalization of vulnerability is given by the equation
between sensitivity & exposure (utilising TCI as index) and adaptive capacity (utilising Gross
Domestic product – GDP as index)

Definition of climate change vulnerability (Moreno A., 2006)

Climate research and policy
One of the latest examples of utilisation of these concepts strategies in the frame of the
European Union 6th Framework Programme is offered by the ADAM project (ADaptation And
Mitigation strategies) worked out by the CICERO Center for International Climate and
Environmental Research of Norway. One of the outputs of the project is a study (Hein l.,
2007) that investigates the impacts of climate change on tourism in Spain. The analysis
demonstrates how the suitability of the Spanish climate for tourism will change, and how this
will affect tourism flows to Spain. The suitability of the climate for tourists is expressed
through the TCI aggregated index. The impacts on tourist flows are modelled using a simple
non-linear equation, calibrated on the basis of the current monthly tourism flows in Europe.
The model shows that, climate change as forecasted with the Hadley model under the IPCC
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SRES A1 scenario5 would lead to a reduction of total annual tourist flow to Spain of 20% in
2080 compared to 2004. The effect would be entirely due to the much higher temperatures
forecasted for the summer, which would make summer temperatures unpleasant for many
tourists. In spring and autumn, there would be an increase in tourist flows.
But still more interesting work has been done in the frame of CICERO research centre
activities (http://www.cicero.uio.no) . For instance, is to be noticed the Project “Key actors
and

the climate regime 2007”. The purpose here is to consolidate and further develop

collaboration research to benefit Norwegian policymakers. Policy-oriented research is carried
out to understand the further development of the climate regime, as well as for effective use
of interdisciplinary approaches, applying insights from political science, economics,
environmental studies, and sinology and discuss the consequences for the negotiating
positions of key actors. This is one of the few existent examples of public research worked
out with the purpose of enabling political decision.
Still, in Europe there were good assumptions. On 2003, the éCLAT Network was established
at an European Science Founded Workshop held in Milan (Viner D., Amelung B., 2003). The
initial participants include researchers from the international research community, industry
and a number of stakeholder organisations. The aims and objectives of éCLAT were: “The
promotion of an international network of researchers, stakeholders and industry that will set
the research agenda and establish the research framework for the studies of climate change
and tourism; to raise awareness (within the industry and amongst other stakeholders) of the
impacts that climate change will have on tourism destinations; to investigate the contribution
of tourism to climate change; to investigate the nature of the interactions that exist between
climate change, tourism and the environment; to help facilitate and promote the exchange of
ideas, research proposals and data within the éCLAT community.” The network is now
carrying on many researches all over the word linked with the forecasting of future scenarios
(www.e-clat.org).
On the other side of the word
While in Europe the central problem was still on the debate on how to cope with climate
change and of finding the methods of resolving it primary at philosophical, research and
political level, apparently in the USA more practical approaches are going to be carried out.
The United States Global Change Research Program issued a report on December 2000
5

SRES refers to the IPCC Special Report on Emission Scenarios (2000). The SRES scenario families and
illustrative cases, which did not include additional climate initiatives, are summarized as follows: approximate
CO2 equivalent concentrations corresponding to the computed radiative forcing due to anthropogenic
greenhouse gases and aerosols in 2100 for the SRES B1, A1T, B2, A1B, A2 and A1FI illustrative marker
scenarios are about 600, 700, 800, 850, 1250 and 1550 ppm respectively. Scenarios B1, A1B, and A2 have
been the focus of model inter-comparison studies.
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from an ad hoc Working Group on Climate Modelling, (USGCRP, 2000) that in the 7th chapter
stressed the importance to set out an Institute for Climate Science Product-driven services:
“7.1) An "Institute" for Product-driven Climate Science.
We, ultimately, envision the evolution of a Climate Service that integrates all aspects of
Modeling, Data, and Computational Systems. However, the planning and development of this
service is difficult and necessary and subject to reconciliation with current Agency missions.
Therefore, we propose an evolutionary process that starts, soon, to align the major
components of a climate service while a more structured service is planned and developed.”
A specific work of investigation was carried out in the USA to define the requirements of the
national industry for Climate, Weather and ocean information (Altalo M. et al., 2000). The
purpose of this work was to provide the National Oceanic and Atmospheric Administration
(NOAA) with an in-depth overview of the data needs of the industry and assess the
importance of its particular products to society. This aided the Agency in assessing its own
strategic goals and setting priorities for many of its programs in light of the needs of the
industries or constituencies that use NOAA’s services. Particularly developed was the section
of the study dedicated to the environmental information needs of the energy sector.
This search for a product-driven climate services has been developed in two ways:
qualitatively an typologically. As to say deepening the quality of weather forecast products,
and widening the typology of offer product, applying the results to different productive
sectors.
In the quality perspective of the USA, many local weather forecasting agencies worked out
products-driven services moistly directed to farmers.
In agriculture the conjunction of climate monitoring with Expert Systems brought to computer
modelling for irrigation scheduling and the first examples are dated more than 20 years ago.
Nowadays there are many commercial products in this sector utilised mostly for irrigation
management or greenhouses frost protection.
In Australia too this approach has been carried out advertising and emphasizing productdriven climate services as the Managing Climate Variability Program (Managing Climate
Variability Program, 2007). Top of all, in this case there is programmatic statement: “Farmers
and natural resources managers need information to make decisions that will reduce their
exposure to risk from climate. While three month climate forecasts are widely available, most
farmers and resource managers need lead times of 12 months or more. Our top priority through our research and field trials - is to provide more accurate climate forecasts with

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longer lead times for farmers and natural resources managers.”

Actually this is not a

typological difference of the service supplied but a quality and duration difference (that
nevertheless could be of fundamental importance).
Managing Climate Variability
But in the same time Australia is investing heavily on programs to improve Natural Resource
Management (NRM) and has also invested substantially on advancing climate science.
On 2005, as a first step on establishing a more tight collaboration between climate science
and productive sector was launched the Managing Climate Variability (MCV) collaborative
programme among the Grains, Rural Industries and Sugar Research and Development
Corporations; the Australian Government Natural Heritage Trust and Department of
Agriculture, Fisheries and Forestry; Dairy Australia; Meat & Livestock Australia; and Land &
Water Australia (MCV, 2006). This was the consequence of having drawn attention to the fact
that, while most degradation of natural resources in Australia is strongly influenced by climate
variability, there was a gap between natural resource managers and information from climate
science. The principal investigators of the programme said that: “In discussion with NRM
decision makers and climate scientists, we have found that, generally, they have limited
knowledge of what climate science has to offer, and the applied climate science community
only vaguely understands the context of NRM decision making. This project will develop and
evaluate frameworks that enable NRM decision makers to integrate the advances in climate
science into their planning and decision making” (Hayman P., Hertzler G., Howden M., 2006).
The programme contributes to improved use of seasonal climate forecasts by industries and
resource managers. Programme objectives are: 1) Work with three sets of NRM decision
makers (farmers, catchment’s authorities and conservation estate managers) to detail a
range of specific climatically risky decisions. 2) Develop and apply a framework for thinking
about uncertainty, based on the development of several ideas to ‘proof-of-concept’ level,
leveraging the considerable conceptual development and application of approaches such as
Bayesian6 revision or Real Options7 in the financial and economic domains, which enables
NRM decision makers to better manage climate risk for three case studies. 3) Evaluate the
framework(s) and produce a manual on applying the framework(s) to any climate-sensitive
NRM decision. Particularly interesting is the programmatic methodology: “Previous
experience in participatory research with farmers in large …. farming systems projects
indicates that proceeding from a general area of concern or problematic issue to a clearly
Bayes' theorem (also known as Bayes' rule or Bayes' law) is a result in probability theory, which relates the
conditional and marginal probability distributions of random variables. In some interpretations of probability,
Bayes' theorem tells how to update or revise beliefs in light of new evidence a posteriori.
7
In corporate finance, real options analysis applies put option and call option valuation techniques to capital
budgeting decisions. A real option is the right, but not the obligation, to undertake some business decision,
typically the option to make a capital investment.
6

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defined decision that can be analysed and solved is not a trivial task. However, with patience,
it is often the most valuable part of the engagement between managers and professional
agricultural scientists and economists. The process of constructing, populating and testing a
map of the decision problem through processes such as influence diagrams generates many
valuable insights. This also presents an opportunity for dialogue between different sources of
knowledge and presents information in formal but accessible ways. The framework will be a
series of worked examples and spreadsheets whereby decision makers can follow a number
of steps. We aim to work on at least one specific example with each group of decision
makers; this will give a real world example for the abstract concepts that can be evaluated.”
It has to be stressed in the above citation the particular urgency of a collaborative approach
among the different actors.

Instances of climate monitoring for productive services
The emerging ability of scientists to predict future climatic events has been developed as
powerful tool to assist planning and management for all economic and social activities. At the
beginning, climate prediction was considered very useful to the agricultural community but
gradually it is becoming well established for other sectors such as energy, health and
tourism.
The basic need to predict weather change for agriculture is recently developing the offer of
new services that can bring some help in decisional choice for sector stakeholders.
For instance the Department of Agriculture of West Australia offers now a web service tool to
help farmers in decision support. (DAWA, 2007).

This is called “Climate decision support

tools” and consists on a set of computer software programs which promise to take some of
the guesswork out of risky farming decisions. These decision support tools provide
information about plant available water, potential yields, seasonal rainfall, flowering time,
temperature events and climate analyses to help farmers make more informed strategic and
tactical decisions. In particular these tools consist of:
1) a Potential Yield Calculator, widely referred to as PYCAL, that was developed in the
1990s to calculate potential yields and water use efficiencies for wheat and other crops.
These were used to provide benchmarks for assessing production efficiency in high yield
cropping packages.

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2) A Flowering Calculator, that was developed in the mid 1990s to estimate flowering time
and incidence of suitable temperatures for pod set (critical temperatures), frost and damaging
high temperature events for any date of sowing.
3) A Climate Calculator that was developed in the early 2000s to display and analyse climate
information. It can be used to analyse historical climate information and the probability of
climate risks in relation to strategic and tactical farm management decisions.
The Pileus tourist forecast model
But the most wide famous tool used for decision making support is represented by the
Michigan State University (USA) that realised Pileus Project as “Climate science for decision
Makers” (Michigan State University Board of Trustees, 2005). The overarching purpose of
the Pileus Project is to provide useful climate information to assist decision-makers. The
current focus is on two leading industries in the Great Lakes region: Agriculture and Tourism.
The goals of the project were to:
• Provide a better understanding of historical climate trends, variability, and their past impacts
on people and industry.
• Evaluate how future climate trends and variability may impact people and industry, using
newly developed, climate-related models.
• Create an economic framework, which explicitly incorporates climate into the decisionmaking process.
The project involved stakeholders and researchers that build on each other’s experiences,
pooling expertise, and expanding knowledge about climate impacts on industry. The project
developed different tools for several utilisation. One was the forecasting of tourism demand.
It could be interesting to know how this tool was developed.
The researchers used a common methodology known as multiple regression analysis. The
term “multiple regression” was first used by Pearson in 1908.

The general purpose of

multiple regression is to learn more about the relationship between several independent (or
predictor) variables and a dependent (or criterion) variable. In the social sciences, including
tourism research, multiple regression procedures are very widely used. In general, multiple
regression allows researchers to ask (and hopefully answer) the general question, "what is
the best predictor of …”. As the uncertainties of travel (including tastes, policies, traveller
demographics, changing climate, and diversity of destinations) increase, projections can
become less reliable. By using this tool, tourism service providers can gain a better
understanding of the demand that exists for their products and/or services, given the
existence of certain conditions or scenarios. To develop the tool were taken into account the
factors that are typically believed to have the greatest influence on tourists' behaviours.
These where: 1) weather conditions, 2) economic environment, 3) the prices of products and
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services offered to tourists, 4) the amount of leisure time that pleasure travellers have
available to them. (Leisure time is the residual that is left after necessary obligations are met
to work, sleep, eat, and maintain personal hygiene; it is discretionary time to be used as one
chooses.)
First, a search was conducted to determine whether the four factors described above were
available in quantifiable data sets. A wide variety of historical weather variables, as well as
measures of consumer confidence in the U.S. economy, were located. Data sets containing
historical gasoline prices and auto ownership costs were also available. However, no good
indicator of people’s leisure time was found. The Michigan Department of Transportation
provided an extensive data set containing daily counts of vehicles from counters located on
roadways across the state. Then a mathematical equation was elaborated to represent the
tourism traffic models.
The regression analysis revealed that the best measure of tourism traffic on selected
Michigan roadways on a daily basis was: “traffic (the dependent variable) is determined to be
a function of the amount of daily precipitation, the daily recorded high temperature, the
monthly Midwestern region Consumer Confidence Index (CCI)—as defined by The
Conference Board, whether the day is a holiday, whether the day falls on a weekend, and in
which year the day occurs (the independent variables).”
Conceptually, this equation is expressed as: Traffic = f(precipitation, maximum temperature,
CCI, holiday, weekends, year).
Variables that were tested in the model but were found to be statistically insignificant or
collinear (which occurs when two variables are highly correlated and both convey essentially
the same information), and were thusly disregarded, included:

monthly state wide

unemployment rates, monthly Great Lakes water levels, daily historical heat index values,
annual auto ownership costs, and surprisingly—gasoline prices.

It remains to be seen

whether the recent, dramatic rise in gasoline prices will make this variable statistically
significant in versions of the model containing more recent data.
Upon further examination, the researchers decided that the model would provide more
accurate output if it was split into four seasonal models to account for climatic and other
changes across the years. The seasons were defined as:
Spring = March, April, May;
Summer = June, July, August;
Fall = September, October, November; and
Winter = December, January, February.
The two weather variables that were used in the model include:
Temp = The daily recorded high temperature; and
Precip = The daily recorded precipitation total, including all types.
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The economic variable included in the model is the monthly Midwest region Consumer
Confidence Index, as reported by The Conference Board. Since past research has proven
that the vast majority of tourists in Michigan originate from this region, this variable was
deemed to be a better measure than the national Consumer Confidence Index for this
application. This variable was defined as:
CCI = Monthly Midwest region Consumer Confidence Index.
Several dummy variables were also developed to allow for the consideration of whether
individual days occurred during holiday periods known to impact tourism traffic.

Those

variables include:
Wk1 = A Friday or Sunday of a non holiday-associated weekend;
Wk2 = A Saturday of a non holiday-associated weekend;
Hdy1 = A single-day holiday that falls on Tuesday, Wednesday, or Thursday
(i.e., July 4thon a Wednesday);
Hdy2 = The day prior to, or the last day of, a holiday-weekend period
(i.e., A Friday or Monday of a Labour Day weekend); and
Hdy3 = A day that falls in the middle of a holiday-weekend period
(i.e., A Saturday or Sunday of a Labour Day weekend).
And finally, a year variable was added.
Year = The year (i.e., 1998).
Hence, the output of the equations was defined as:
Traffic = The projected number of tourist-containing, motorized vehicles passing by the
MDOT traffic counter on a selected roadway during a selected day.
Regression analyses were run for a variety of traffic stations across the state on roads known
to be major tourist routes. The research team identified ten locations where the results were
sufficient to be able to develop reliable, statistically significant seasonal tourism traffic
models.
All these data were used to develop a tool that can be freely accessed trough the web.
But the most provoking tool furnished by the Michigan state University was the decision
making service linking Climate Variability and Tart Cherry Production. This was due to the
fact that Michigan produces approximately 75% of the tart cherries grown in the United States
and tart cherries are responsible for € 32 million per year (out of € 160 million per year for all
fruit specialty crops) in the state. Two-thirds of the tart cherries grown in Michigan are grown
in five counties that border Lake Michigan and so are influenced climatically by a very large
body of water. Tart cherries are extremely vulnerable to temperature extremes. The impact
of climate on the tart cherry industry is not well understood and has not been investigated in

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an industry-wide context. Collectively, these factors allowed an unique opportunity to link
expertise in tart cherry production, economics, and climate science.

Conclusions
Now could be concluded that the act of transferring basic scientific knowledge (climate
monitoring and weather forecasting) into practical application frame, flows through different
steps, going from basic research to applied research. Those include important
communication processes, as discussion and collaboration with all possible stakeholders
“partners” and customers, before attaining the decision making and feedback stages, that are
the ultimate purposes of a tool generating socioeconomic benefits.

Weather monitoring for utilitarian purposes: the chain framework (from: Williamson R. et al. 2002)

All the instances gathered in this study highlighted a fundamental underneath exigency: in
the frame of the relationship country-town the simple climate monitoring has to be supported
with other functional data in order to be analysed and elaborated by utilitarian services to
allow the building of instruments helpful for a wise and long-term planning. In this context
there is an essential need for:
1) recording not only climatic daily or hourly events but also the main fluxes of factors that
constitute the relationship country-town (these, according to the circumstances could be:
traffic, tourist fluxes, users access to determinate services, customers sales, insects or

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birds migration records, summer fires, arsons, vandal acts, etc…..). In fact the disposal of
valid historical daily series of data is vital to support “pilot” model development.
2) Preservation of records. Long term records of different items data are useful only when
they cover periods for a minimum of the last five years, preferably ten. These historical
series are irreplaceable in order to be analysed and compared to meteorological and
climatic data. These actions are fundamental for the realisation of models that can be
utilised to build decision-making tools. Is therefore vital to keep records, to store them in a
way easy to find and recover, and to ensure them wide accessibility in the long term too.
3) Promotion and support centres for data analyse and elaboration in order to realise
models and decision making tools. Those could be public or privates entities, they could
be reconverted from research institutes already existent or newly set, but it is important
they operate at least in a strictly jointly context with governance enabled authorities.

Terracina’s view from the hinterland mountains. Intensive agriculture area (glasshouses)
and urban area are directly linked without transitional areas

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Pilot project frame: Terracina state of art
Coming now to the case study involvement, the basic purpose of this chapter will be to
ascertain the global picture of Terracina environmental and socio-economical situation,
gathering the available records and historical series of all the critical features. Once collected
the elements of this scenario will be utilised in the next step for a cross analysis to promote
wise and sustainable country-town development planning methods.
Geographical situation
It must be considered that Terracina is a very small town (approx. 37 000 inhabitants in
winter, autumn and spring) placed into a huge plain that was interested by a massive land
reform thanks to a government action starting from 1931. The town of Terracina lies at the
end of this plain, closed by the mountains and the sea. The Historical urban centre is up to an
hill about 60 m. altitude, the modern down town lies at 22 m on the sea level. Municipality
range of altitude goes from 0 up to 863 m on sea level. To the North and East side the town
is closed by rocky hills and mountains that elevates themselves till 600-700 m on the sea
level, thus protecting the urban centre from the cold winds. To West the town is open to the
great Pontine Plain, to South to the sea.

Terracina municipality boundaries (blue lines) and altimetry (brown lines: intervals
between the lines = 50 m, intervals between the large brown lines = 100 m)

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