Regional Climatic Model (RegCM) and Georgia

Bagrat Kikvadzea_kikvadze@yahoo.com

PhD Student of Geography Ivane Javakhishvili Tbilisi State University, Georgia

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 important for the regional stability.

Introduction

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 less than one day .

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.

GeorgiaThe Black Sea

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

• 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.

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Variable Abbreviation (unit)

Definition of extreme indices

Precipitation PN80 (days) Number of days with precipitation above 80 mm intensity

PX1D (mm) Greatest 1-day total precipitationMDRY (days) Maximum duration of consecutive dry days,

precipitation ≤ 0.1mmMWET (days) Maximum duration of consecutive wet days,

precipitation ≥ 0.1mm

Extreme Precipitation Indices

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.

Abbreviation and definition of the indices

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)

Results

Model-predicted distribution of number of days with precipitation above 80 mm intensity for 1982-1996 time period.

Model-predicted distribution of greatest 1-day total precipitationfor 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 number of MWET days for 1982-1996 time period.

Model-predicted distribution of number of MDRY 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.

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!