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A-2337

Climate Change Studies and Regional Scale Modeling in the South Caucasus

Project Status: 3 Approved without Funding
Duration in months: 24 months

Objective

The Climate change is one of the most serious problems raised in the 20st century which threatens the sustainability of the world and becomes interdisciplinary scientific issue covering ecological, social and economic areas of the development.

The semi-isolated South Caucasus region is highly sensitive to climate driven global environmental changes especially the global warming problem. The region is characterized by great spatiotemporal variability in temperature and precipitation as a result of highly variable atmospheric circulation regime and significant topography. The studies showed that it is challenging to reproduce highly variable climate and weather conditions in the South Caucasus region using coarse resolution General Circulation Models (GCMs), while application of dynamically downscaled Regional Climate Models (RCMs) provides significant local added value.


Previous studies have demonstrated that South Caucasus region has experienced significant temperature increase in the last decades, particularly in Summer season. In particular, climate extremes have increased dramatically. The temperature increase is expected to persist and enhance in the 21st century.
The above listed problems and challenges need to be tackled in different ways, but one of the most important aspect is to have high-resolution climate system models and Earth system models that better simulate the interactions and feedbacks among the physical, chemical and biological component processes, and to build and implement an effective regional and global climate models. Currently available numerical models are already providing more accurate prediction of different aspects of climate such as weather, precipitation etc. Earth system models are becoming high quality for shorter periods. Regional-scale projections of climatic change also require an increase in the spatial resolution of climate models and Earth system models and an acceleration of computational throughput with a combination of software and hardware advances.
There is statistically increasing trends in annual temperature in South Caucasus region, and there is also an increase of precipitation in some areas and the opposite in some other areas. All these aspects will cause very different ecological problems in South Caucasus region.
Currently available numerical models are already providing more accurate prediction of different aspects of climate such as weather, precipitation etc. Earth system models are becoming high quality for shorter periods. Regional-scale projections of climatic change also require an increase in the spatial resolution of climate models and Earth system models and an acceleration of computational throughput with a combination of software and hardware advances.
Responding to climate change problems is crucial for the region and the role of science and scientific computing is very important in this domain. And it is a great scientific challenge is to predict how climate will change locally and in the region. This challenge is particularly critical because reliable and high-quality forecasts are needed to prepare and protect our civilization for climate change.
To achieve advance in the understanding of future climate trends there is an effective way to evaluate robust climate modeling system. However, prediction of regional climate variability by numerical modeling is inherently probabilistic, due to uncertainties in initial and boundary conditions, representation of key processes within models, and climatic forcing factors. Hence, to increase degree of prediction of regional climate variability by numerical modeling can only be made through ensemble integrations of climatic models in which these uncertainties are explicitly incorporated. Thus the key objective of the project is to develop a high resolution (up-to 10 km.) regional ensemble climate forecast system for prediction of both natural climate variability and the human impact on climate above the territory of South Caucasus. The climate ensemble system will be constructed by existing global and regional climate earth-system models, dynamically downscaled to the Caucasus region.
As the complexity of climate simulation grows and also an enormous data to be deal with all these will soon require greater computing capabilities. To deal and tackle climate change challenges there is a need for scientific computing at extreme scales ranges. In the past few years, a number of Projects have been executed ameliorating the state of e-Infrastructures in the region [27-28] through the series of Projects funded by ISTC (A-1606: Development of Armenian-Georgian Grid Infrastructure and Applications in the Fields of High Energy Physics, Astrophysics and Quantum Physics; A-1451: Development of Scientific Computing Grid on the Base of Armcluster for South Caucasus Region A-823: ArmCluster: Creation of High-Performance Computation Cluster and Databases in Armenia) and European Commission (INARMERA-ICT: Integrating Armenia into ERA: Information and Communication Technologies; EGI-InSPIRE (Integrated Sustainable Pan-European Infrastructure for Researchers in Europe;HP-SEE: High-Performance Computing Infrastructure for South East Europe’s Research Communities; SEE-GRID-SCI: South East European GRID e-Infrastructure for Regional eScience).
The overall aim of the project is to group all countries in the region in order to have cooperative regional effort to understand and predict the local implications of climate change based on state-of-the-science regional climate modeling. It is planed to develop and maintain a regional climate forecast model for the entire region, and there is a very good potential to do that for many reasons. The existence of a very big number of global climate models, which allows the prediction of climate changes in large scale systems. The improvement and combine technologies of different atmospheric, hydrological and air quality models. In order to hide the complexity of the e-infrastructures, several services for weather forecasting and visualization will be developed for end users (stakeholders, research organisations, policymakers, government emergency management agencies and, e.g., the insurance industry, structural and wind engineers, the transport sector, electricity utilities, agriculture, environmental managers and the media).

Participating Institutions

LEADING

Institute for informatics and automation problems

PARTICIPATING

I. Javakhishvili Tbilisi State University (TSU)

PARTICIPATING

Service of the Hydrometeorology and Active Influence on Atmospheric Phenomena

PARTICIPATING

Georgian Research and Educational Networking Association (GRENA)

COLLABORATOR

National Centre for Nuclear Research

COLLABORATOR

Technical University of Cluj-Napoca

COLLABORATOR

Leibniz Supercomputing Centre of the Bavarian Academy

COLLABORATOR

University of Cologne / Rhenish Institute for Environmental Research (RIU)

COLLABORATOR

CSC-IT Center for Science

COLLABORATOR

National Oceanic and Atmospheric Administration at the US Department of Commerce (NOAA)

COLLABORATOR

Aarhus University

COLLABORATOR

University of California Riverside

COLLABORATOR

NOAA Satellite and Information Service

COLLABORATOR

Deutsches Klimarechenzentrum

COLLABORATOR

Robert-Koch-Institute

COLLABORATOR

Institute de Recherche en Informatique de Toulouse

COLLABORATOR

Bergische Universität Gesamthochschule Wuppertal