DOWNSCALING FROM GLOBAL CLIMATE MODELS TO REGIONAL CLIMATE MODELS FOR USE IN MULTI-SCALE MODELING OF RIVERINE ECOSYSTEMS AND RESPONSES OF FISH POPULATIONS

Increasingly, evidence has emerged documenting ecological changes due to climate change (for example, Walther and others, 2005). Although much of this evidence comes from field observations there is increasing reliance on models that relate climate variables to biological systems for understanding sensitivity of biological systems to scenarios of change in climate variability. Typically, climate scenarios are implemented in global climate models (GCMs). The main limitation of addressing ecological effects of global climate change is the exceedingly difficult task of quantifying sources of uncertainty (in data, models, and parameters) given the highly nonlinear nature of interactions between climate variables and community-level ecological processes. While a complete climate prediction may be intractable at this time -- for instance, the climate projections may not incorporate land-use changes and solar fluctuations into the boundary conditions -- we illustrate a framework to quantify uncertainty, using multi-scale climate models, that is also flexible enough to adapt to advances in climate predictions.

Downscaled GCM simulations from the North American Regional Climate Change Assessment Program (NARCCAP) (http://www.narccap.ucar.edu/) provide temperature and precipitation time series suitable for analysis of Missouri River Basin hydrology. NARCCAP simulations are produced by regional climate models (RCMs) driven by GCMs over a domain covering most of North America. Ultimately, this program will feature simulation results from 6 RCMs and 4 GCMs.

Currently, results are available from all 6 RCMs forced with National Center for Environmental Prediction (NCEP) reanalysis data for 1979-2004. Such runs can give insight into potential model biases relative to observed climatology. Future climate change scenarios are based on the A2 emissions scenario (less international cooperation) developed through the Intergovernmental Panel on Climate Change (IPCC) as described in Nakicenvoic and others (2000) in the Special Report on Emissions Scenarios (SRES) that was commissioned by the IPCC. This scenario is one of the higher SRES emissions scenarios. Thus, it is considered to be important for studying realistic impacts and adaptation strategies.

We will present results from the NARCCAP reanalysis driven simulations. Our presentation will discuss biases in variables used as input to the hydrological model.

Nakicenvoic, N., Alcomo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin, S., Gregory, K., Grubler, A., Yong Jung, T., Kram, T., Lebre La Rovere, E., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L., Riahi, K., Roehrl, A., Rogner, H., Sankovski, A., Schlesinger, M., Shukla, P., Smith, S., Swart, R., van Rooijen, S., Victor, N., Dadi, Z., 2000, Special Report on Emissions Scenarios, A Special Report of Working Group III of the Intergovernmental Panel on Climate Change: Cambridge, MA, Cambridge University Press, p. 599.

Walther, G.R., Berger, S., and Sykes, M. T., 2005, An ecological ‘footprint’ of climate change: Proceedings of the Royal Society, Biological Sciences, v. 272, no.1571 p. 1427-1432.