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WP2 Description of work

Task 2.1: Model simulated climate baselines

MPI Hamburg [S. Kotlarski, D. Jacob]

This task of WP2 will aim at setting up and managing a project data base containing climate model results carried out within the ACQWA project. Use will be made of the existing infrastructure at the World Data Center for Climate (WDCC). There is a wealth of model-generated climate data that is available at horizontal scales ranging from 25-50 km. For example, the data from the EU-FP6 “ENSEMBLES” project is regularly updating its climate data base with results from the ensembles GCM and RCM simulations. The ACQWA data base will provide links to these already existing data sources. Specific climate scenarios focusing on the near and mid-term future (in practice until 2050) carried out within the present study will be stored in the data base and shared within the consortium for the project time and to the broad scientific community at the end of it. The data will be available in a user-friendly manner, accessible through the Internet.

 

Task 2.2: Past and current climatic baselines

University of Bern, Switzerland [J. Luterbacher]

The investigations proposed in Task 2.2 will provide the necessary information for the validation of the modelling activities planned in WP3 and WP4 with respect to recent past and current climate.

Local to regional climate anomalies at different time scales (daily-monthly) are to a large extent determined by the state of the atmospheric circulation. Thus, advective (and convective) processes exerted by the atmospheric circulation are a crucial factor controlling local to regional changes of precipitation and temperature. The large-scale interrelation between the circulation and local to regional climate arises because they are both associated with change in the quasi-stationary planetary waves and other factors, including the role of advection given by the mean flow and the planetary waves. Within this Task synoptic studies will be performed relating daily and monthly large scale pressure (including sea-level pressure – SLP - and geopotential height) for the last approximately 60 years to regional climate (precipitation, temperature, etc.) of the Alpine area, with particular emphasis on the Rhone and Po valleys. These types of synoptic analyses will also be applied to the other case-studies located in the Aconcagua and Kyrgyzstan regions.

In addition, this Task will also document and investigate the current space-time distribution and diagnosis of trends/variability of extreme events (e.g., floods, drought, heat waves, etc.) at different time and space scales for the regions selected will also. Methods will be developed and applied to classify circulation patterns at the daily to monthly scale and statistical analyses to relate sea level pressure to extremes in current climate. These results will be used to validate the specific regional climate scenarios generated for the project in WP3, Task 3.1. Changes identified in regional climates will also be investigated to detect whether the observed climate evolution is due to internal climate variability or to external forcing combining natural and anthropogenic sources of variability.

 

Task 2.3: Remote-sensing data

Laboratoire EDYTEM, CNRS, France [J.-P. Dedieu]

Because the proposal concentrates on modelling the response of snow and ice dominated mountain regions, a specific Task is foreseen to generate remote sensing optical products, which will be used for validation of both climatic and hydrological models, used in Task 3.1 and 3.2 respectively, with respect to the spatiotemporal evolution of snow cover and the surface characteristics (e.g. the snow grain size) of the snowpack in the present climate at the regional, basin and local scales. Such validation is necessary to verify that both the climate and the hydrological models can capture the variability observed, and, particularly, that which has characterized extreme years with rapidly evolving snow cover.

Accordingly, enhanced snow cover products will be produced from daily large scale image, i.e. 500m to 250m MODIS/TERRA database, and validated to local scale representative case using monthly ASTER vs SPOT HRVIR data (respectively 15m and 10m). Specific MODIS products such as the surface reflectance (MOD09, Bands 1-7, 500 m), the cloud mask (MOD35), the geometry (MODMGGAD) will be used, jointly with the DISORT Snow Spectral Library (Bands 1-7) and the relevant Digital Elevation Models (DEMs) of the investigated areas.

 

Task 2.4: Socio-economic drivers of change

HEID, Geneva, Switzerland [U. Luterbacher]

Numerous socially-generated processes interact with climate and are therefore essential to our understanding of future conditions. Water availability and use will be affected not only by changes in the climate but also by differential evolution of economic sectors (agriculture, energy, tourism, etc) trade and financial flows, the opening of energy markets and greater movement of the labor force and people in general. These trends will impinge on mountain regions especially since urban concentrations will increase and, if one follows the trends in the Alps, mountain areas will become increasingly urbanized. Using the model Climsocwater (ref) and the system SPARE (Luterbacher 1987, Luterbacher and Wiegandt 1995), these driving forces will be formally specified in order to track their own evolution and potential impact on climate and hydrological processes but, more important, to define points of contact where climatic and social processes interact. Subsequently, outputs from the climate scenarios deriving from Task 2.1 and hydrological outputs from Task 3.2 will be taken into account to allow for the construction of an integrated model which includes the representation of socio-economic drivers such as land use changes, energy demand, agricultural policies, financial and trade liberalization particularly for energy markets, population movements and concentration of people in urban areas, and urbanization of mountain areas. In particular the WP will include:

1. A socio-economic model that includes industrial and rural sectors, demography, energy, finance, trade and government expenses and revenues and in addition is open to climate change and hydrological inputs. It incorporates a water sector influencing both rural and industrialized sectors and which will determine:

  1. Supply of water
  2. Demand and consumption of water by the diverse economic activities represented in the model, in particular, agriculture, industry including hydropower and households. Coordination with the Task 3.2.3 on agriculture will be indispensable to set up this part of the model.

2. A supply and demand sector for land which depends upon its value as an asset used for either agriculture, forestry, dwelling, or industry. Same remark for WP as above.

This model, will in the course of the project incorporate the results of the focused Work Packages in order to be used to carry out cost benefit analyses and risk assessments. Risk assessments will benefit from inputs from hydrological and climate models. Expected loss and damage as well as benefits will be undertaken. Risk assessments will be done in close coordination with the Columbia University team (Graciela Chichilnisky and Peter Eisenberger), evaluate policy responses and adaptation in a second phase included in Task 4.3.

Data Issues: By now a substantial data base exists for the issues evoked above in the World Bank Develoment indicators, an in depth compendium of socio-economic indicators for each country and region of the world. Contacts with relevant local institutions such as the Instituto Torcuato de Tella in Buenos Aires and the Kyrgyz Academy of Science Institute for Water and Hydropower will bring I additional data bases for regional questions.

 

Task 2.5: ACQWA Data Warehouse

UNEP/DEWA GRID-Europe [B. Chatenoux]; University of Geneva [A. Lehmann]

The complexity inherent to the chain of processes involved from climatic, to cryospheric and hydrologic models, all of them impacting on different compartments of human and natural systems, all this through different scenarios and across several regions, as described in the other project WPs, justifies the definition of a well organized data warehouse for the ACQWA project. Based on the long experience in managing data and metadata through the Internet from many international programs, developed by GRID-Europe as part of the Division of Early Warnings of UNEP, the first task of the ACQWA Data Warehouse (ACQWA-DW) will be to install a Spatial Direct server to:

  • define standards of data exchange formats and needs among partners using existing international standards such as ISO19115 for metadata of geographic data;
  • help with data transformation between groups
  • store data and metadata in a PostgreSQL relational database and postGIS database;
  • gather and distribute data (geographic layers, remote sensing images, climatic and hydrological time series,…) through an Internet GIS MapServer (ACQWA IMS);

The second main task is to build an Internet GIS MapServer (ACQWA IMS), in order to:

  • visualize outputs from different scenarios on different impacts (ACQWA IMS);
  • communicate results of the project through maps (ACQWA IMS).

T2.5 will interact with all of the other work packages. It will provide a service, first, in defining the structure of the outputs of WP2 (Climatic and socio-economic drivers of change) by matching the input needs of the models predicting changes in water quality and quantity (WP3) at the basin and local/point scales. Outputs from WP3 will also match the needs of the work package on impacts (WP4) through the ACQWA-DW. It will finally provide outputs from all work packages for Education and Outreach (WP5).