Diapositiva 1

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WORLD METEOROLOGICAL ORGANIZATION
FOOD AND AGRICULTUREORGANIZATION
COST ACTION OF THE EUROPEANSCIENCE FOUNDATION
WORKSHOP ON CLIMATIC ANALYSIS AND MAPPING FOR
AGRICULTURE (14-17 June 2005, Bologna, Italy)
Simulation of micrometeorological fields during a
frost event in the Po Plane M. Nardino, G.
Antolini, F. Rossi, T. Georgiadis, G. Leoncini,
R. Pielke
CONSIGLIO NAZIONALE DELLE RICERCHE
ISTITUTO DI
BIOMETEOROLOGIA
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A RADIATIVE FROST

• THE PROBLEMA strong spring frost episode was
  recorded in the Emilia Romagna region during the
  17 March 2003 night. The event was a typical
  radiative late frost frequent in this region.
• WHAT is a RADIATIVE FROST?
• Clear sky nights
• heat cumulated during the day is rapidly
  transferred to the atmosphere causing a strong
  decrease of the surface temperature leading to an
  inversion layer
• the air temperature increases with the height
• the inversion layer height depends on the local
  atmospheric conditions.

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THE ATMOSPHERIC CONDITIONS
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GOALS

• To simulate this frost event with an atmospheric
  diagnostic model (MODAMBO_2D) to obtain a
  regional map of the principal micrometeorological
  fields.
• To give an input for the frost risk mapping of
  the Emilia Romagna region.
• To have the local micrometeorology starting from
  the results of a fluido_dynamic model (RAMS-
  Regional Atmospheric Model System).
• To forecast the frost events (RAMSMODAMBO) in
  order to give a early warning to farmers.
• To use the diagnostic model for other
  agrometeorological applications (i.e. fire risk
  index, ecophysiology modeling, crop
  production,.).

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MODAMBO_2D
THE MODEL INPUT_1 geometrical characteristics of
the domain.1) topography map2) land use
map Surface surface roughness albedo
length INPUT_2 meteorological conditions.the
model needs1) air temperature 2) relative
humidity3) wind speed4) wind direction obtained
from the meteo stations of the regional
hydrometeorological service (ARPA-SIM).
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MODAMBO_2D
THE MODEL OUTPUT_1For each grid point1) air
temperature (C)2) relative humidity ()3)
cloud fraction (tenths)4) Global Radiation (W
m-2)5) Net Radiation (W m-2)6) Soil Heat Flux
(W m-2)7) Sensible heat flux (W m-2)8) Latent
heat flux (W m-2)9) friction velocity (m/s)10)
U wind speed component (m/s)11) V wind speed
component (m/s)12) mixing height (m)
THE MODEL OUTPUT_2Some files that can be
utilized by MODAMBO_3D, able to compute the
vertical profiles of the principal
micrometeorological fields.
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MODAMBO_2D
THE MODEL THEORY 2D terrain following model ?
For each grid cell the slope and the azimuth is
computed
N3 (i1,j1)
Cell (i,j)
N2 (i1,j)
N1 (i,j)
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MODAMBO_2D
THE MODEL GEOMETRIC INTERPOLATION For each
meteorological station and for each grid cell we
compute
The geometric interpolation is utilized to
calculate the values for each grid point of air
temperature, relative humidity and cloud fraction.
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MODAMBO_2D

• THE MODEL
• WIND INTERPOLATIONThe model takes into account
  the effects of
• Surface roughness

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MODAMBO_2D
THE MODEL WIND INTERPOLATIONThe model takes into
account the effects of 2) Topography
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MODAMBO_2D

• THE MODEL
• MICROMETEOROLOGY PARAMETERIZATIONSThrough the
  measurements of air temperature, wind speed and
  relative humidity for each grid cell are
  computed
• global radiation
• cloud fraction
• net radiation
• soil heat flux
• friction velocity
• Monin-Obukhov length
• sensible heat flux
• latent heat flux
• mixing height
• .

By using parameterizations verified through
micrometeorological experimental campaigns.
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INPUT MAPS
Topography Resolution 900 m
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INPUT MAPS
Land use
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INPUT DATA
0000 GMT 16 meteo stations
0400 GMT 23 meteo stations
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GOODNESS of INTERPOLATION
No data
16 meteorological stations
No data
149 meteorological stations
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0000 (GMT)
0400 (GMT)
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No data
Air Temperature (C)
0000 (GMT)
No data
0400 (GMT)
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Relative Humidity ()
0000 (GMT)
0400 (GMT)
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No data
Sensible Heat Flux (W m-2)
0000 (GMT)
No data
0400 (GMT)
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No data
Latent Heat Flux (W m-2)
0000 (GMT)
No data
0400 (GMT)
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RAMS simulation Resolution 2.5 km
Air Temperature (C) 0400
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Sensible Heat Flux (W m-2) 0400
RAMS simulation Resolution 2.5 km
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REMARKS

• MODAMBO (Environmental Diagnostic Model) is a
  mass consistent model developed at IBIMET Bologna
  Institute
• RAMS (Regional Atmospheric Modeling System) is a
  fluido-dynamic prognostic model.
• RAMS, as used in its standard mode (land use and
  soil characteristics data downloaded from USGS
  site) was not able to simulate the frost event as
  well as MODAMBO model, that has been developed ad
  hoc for this kind of applications.
• MODAMBO proved to be able to offer good
  simulation of frost events, but it obviously does
  not take into account the meteorological
  conditions (synoptic, but also mesoscale) out of
  its domain.

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REMARKS
Moreover, RAMS is not a so easy and portable
instrument while MODAMBO can be installed in a
simple PC and can run on real time with standard
meteorological stations data. It can be hence a
very useful instrument for the regional
agrometeorological services. The next step is to
feed RAMS with the Emilia Romagna land use and
soil characteristics for forecast purposes and
then feed MODAMBO with the output of RAMS to
obtain a more realizable local characterization
of micrometeorological features of extreme events.