WP 1 - Climatic boundary conditions and scenarios

WP1 will use the latest global climate change scenarios as boundary conditions to regional atmospheric models (RAMs) and simulate high resolution (25km) regional climate for the India and Himalaya region. The format of these simulations is designed to assess the inter-model uncertainty in Global Climate Models (GCM) and Regional Atmospheric Models (RAM) estimates of current and future temperature, evaporation and precipitation associated with monsoon climate regimes. The snowfall and temperatures will be used in WP2 to calculate the run-off from snow and glaciers. fffeeww

The approach taken will be to use two RAM (PRECIS and REMO) driven by 6 hourly data from 3 sources.

  1. Reanalysis data (ERA40)
  2. The global climate model HadCM3.from MOHC
  3. The global climate model ECHAM5 from MPI

The simulations using reanalysis data will produce the climate and variability most closely approaching 'truth'. However, the RAM physics will distort the 'truth' allowing an assessment of the model error. The global climate models simulate recent climate history as was a future predictions. The quality of the simulation of the past climate may be assessed against the simulations using the reanalysis data. This will allow an assessment of the ability of the climate models to produce observed climate and variability.

Climate models applied within HighNoon need a reasonably accurate volume of glaciers as input. Information on glacier volumes for the Himalaya is missing and currently a major drawback for the understanding of climate change impacts. The HighNoon project makes an effort to inventory the current spatial distribution of glaciers, including their area and an estimate of their volumes. Both of them are highly relevant for climate and water resource projections.

WP1 will benefit from large-scale regional climate scenarios generated in the WATCH project for the larger Indian region. WATCH will also provide methods to correct climate model biases and to transfer uncertainties from climate model data into hydrological models, which may be applied in HighNoon to the RAM simulations if considered appropriate.

Output, in the form of spatial and temporally varying climatic variables, from the RAM simulations will be provided to WP2.