Regional climatic model (RegCM) and Georgia

Report
Regional Climatic Model
(RegCM) and Georgia
Bagrat Kikvadze
[email protected]
PhD Student of Geography
Ivane Javakhishvili Tbilisi State University, Georgia
Introduction
There is a general agreement that intensification of global warming will increase the frequency and
intensity of extreme weather and climate events . Over the last decades significant changes were observed in
Georgia: rise of average temperature, changes in desertification and redistribution of precipitation, reduction in
glaciers, sea level rise, variations in river sedimentation rates. Moreover, against the background of climate
changes extreme climate phenomena have become more frequent: droughts, strong winds, torrential rains,
floods as well as extreme temperatures and other phenomena which significantly affect agriculture, economy,
health of the population and even the security of the country. Thus, predicting extreme events is profoundly
importantfortheregionalstability.
July 2012 in Telavi during 3 hours - 72 mm precipitation, more than one
month climatological norm. In May 2012 in Tbilisi 90 mm precipitation in
lessthanoneday.
The work in using RegCM-outputs for the predictions of extreme weather and climate events over the Georgia
has already been started. Within the framework of guidelines for the preparation of the second national
communication to the United Nations Framework Convention on Climate Change (on the web at:
http://www.global-issues-rtd.info/programmes/2177.html) various future climate scenarios for socio-economic
development of Georgia were constructed. The RegCM - PRECIS (Providing Regional Climates for Impacts
Studies) was used with model domain and boundary conditions defined by the scientists from the Hadley
Centre, UK using two different global models (HadAM3P and ECHAM 4). Together with othefuture
forecasts (1961-1990), as well as two future runs (2020-2050 and 2070-2100) for IPCC A1, A2 and r South
Caucasus countries several runs were carried out for the baseline period used to correct B1, B2 (IPCC, 2007)
climate scenarios. Based on these simulations, future changes in average values of major climatic parameters
were estimated over the territory of Georgia. In addition to this, under the scope of the project “Study and
Modelling of Extreme climate Events in Georgia by Regional Climate Model (RegCM)” (funded by Shota
Rustaveli National Science Foundation) Dr..Elizbarashvili has visited North Carolina State University
(NCSU). Within 3 months (January to April, 2012) the project team was able to transfer the RegCM model
from the Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy to Dr. Meskhidze’s
machine at High Performance Computing (HPC) system at NCSU. The research team was able to
successfully compile and run the code. The team created spatial distribution maps for various types of extreme
indices including five temperature-based indices and five precipitation based indices, using model outputs, for
the Georgia and Caucasus region. The aim of our study was to make simulation of RegCM and
analyze model-predicted distribution of extreme precipitation indices over Georgia Territory.
Climatic peculiarities in Georgia are largely conditioned by the
Greater Caucasus mountain range to the north and the Black Sea to
the west. The Greater Caucasus range serves as a barrier against
cold air from the north. Warm, moist air from the Black Sea moves
easily into the coastal lowlands from the west. Climatic zones are
determined by distance from the Black Sea and by altitude. The
Lesser Caucasus range runs parallel to the Turkish and Armenian
borders. The Likhi Range stretching from the north to the south
connecting the Greater Caucasus and the Lesser Caucasus
mountains divides the country into two distinct climatic zones humid subtropical west and continental east.
The Black Sea
Georgia
The Black Sea
Number of days with precipitation above 30 mm
Climate and Agro-Climatic Atlas of Georgia, 2011
Number of days with precipitation above 10 mm
Climate and Agro-Climatic Atlas of Georgia, 2011
Number of days with precipitation ≥ 0.1 mm
Climate and Agro-Climatic Atlas of Georgia, 2011
Model and Method
• We have applied the Abdus Salam International Center for Theoretical Physics
Regional Climate Model Version4.1 - RegCM4.1.
• For the model simulation the Lambert Conformal projection was chosen. We
defined central latitude and central longitude of model domain clat=42.00, clon
=43.5 degrees as well as 34 number of points in the N/S direction and 48 number
of points in the E/W direction and 18 vertical levels.
• The domain used in current simulations includes Georgia, Part of Armenia,
Azerbaijan, Turkey and Russia.
• The model simulation has been carried out for 1982 - 1996 time period with the
minimal horizontal resolution of 20 km.
• The run was conducted using reanalysis data (ERA40). ERA-40 is the European
Centre for Medium-Range Weather Forecasts (ECMWF) re-analysis of the global
atmosphere and surface conditions for 45-years, over the period from September
1957 through August 2002 available at 2.5° x 2.5° (latitude-longitude) and 23
pressure levels. For a sea surface temperature (SST) the optimum interpolation of
sea surface temperature (OISST) was used, which is available weekly on a 1.0° x
1.0° grid. All these data were downloaded from web page:
http://users.ictp.it/~pubregcm/RegCM4/globedat.htm
Extreme Precipitation Indices
• To investigate the characteristics of precipitation extremes over the Georgian
territory, we consider frequency, intensity, and duration properties. Table
presents indices used in this study. All these indices are calculated as annual
values for the years examined in this study.
•
•
Abbreviation and definition of the indices
•
Variable
Abbreviation
(unit)
Precipitation PN80 (days)
Definition of extreme indices
Number of days with precipitation above 80 mm
intensity
PX1D (mm)
Greatest 1-day total precipitation
MDRY (days) Maximum duration of consecutive dry days,
precipitation ≤ 0.1mm
MWET (days) Maximum duration of consecutive wet days,
precipitation ≥ 0.1mm
Computer codes were used (written in MATLAB language) for calculation of
the 4 indices. Codes were developed during Elizbarashvili’s visit at NCSU.
Spatial distribution maps were created for various types of extreme indices
including four precipitation based indices, using model outputs, for the Georgia
and Caucasus region.
Results
Model-predicted distribution of number of PN80 (days), PX1D (mm) PX1D (mm)
MDRY (days) MWET (days) for 1982-1996 time period. Star indicates Georgian
capital, thin black line depicts country borders, while thick black line shows the
coastline.
PN80 (days)
Model-predicted distribution of
number of days with precipitation
above 80 mm intensity for 1982-1996
time period.
The highest values of PN80
concentrated over the Caucasus
Mountains and near the Black Sea
coast. Due to the lack of
measurement stations it is hard to
verify such high values of PN80
over the mountains. However, local
meteorological observations suggest
that with yearly precipitation of
2,500 mm, Batumi is a place with
highest precipitation throughout the
Georgia.
Model-predicted distribution of greatest
1-day total precipitation
for 1982-1996 time period
Model-predicted distribution of
number of MWET days for
1982-1996 time period.
As expected, the highest values for
the maximum duration of consecutive
dry days are found in the eastern part
of Georgia, increasing towards
Azerbaijan, while the lowest values
are found over the Caucasus
Mountains. The spatial distribution
map of MDRY days is also in a good
agreement with physical geography
of the country.
Model-predicted distribution of
number of MDRY days for
1982-1996 time period.
Conclusions and Future Work
• Although some values are very high and needs corrections, the model
captures well the influences of the Caucasus Mountains and the Black Sea on
distribution of extreme precipitation events over the Georgian territory.
• In the future by using RegCM4 it is possible to investigate the effects of
extreme climate and weather events on Georgian Agricultural sector, with
particular emphasis on viticulture.
References
• Filippo Giorgi, Nellie Elguindi, Stefano Cozzini and Graziano Giuliani. Regional
Climatic Model RegCM User’s Guide Version 4.3. Trieste, Italy p.62, 2011
• .
• Elizbarashvili M., Meskhidze N., Gantt B., Mikava D. Model Simulation Study of
Temperature and Precipitation Extremes in Georgia, International Multidisciplinary
Scientific GeoConference SGEM 2012, “Modern Managment of Mine Producing,
Geology and Environmental Protection” Conference Proceedings, Volume IV, 355-362,
2012.
• Climate and Agro-Climatic Atlas of Georgia, Institute of Hydrometeorology at the
Georgian Technical University, p.120, 2011.
• E. S. Im, I. W. Jung and D. H. Bae. The temporal and spatial structures of recent and
future trends in extreme indices over Korea from a regional climate Projection.
INTERNATIONAL JOURNAL OF CLIMATOLOGY. Int. J. Climatol. 31: 72–86, 2011.
Thank you for your attention!

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