Due to the predicted changes in climate, the effects of climate change have increasingly become a central focus of many regional and landscape-scale ecological/hydrological impact assessments. From evapotranspiration and photosynthesis to decomposition and respiration, climate is a key driver of many ecosystem-related processes.  Thus, climate-related variables are the most important set of input variables for ecosystem computer models and analyses.  Modeling studies within smaller regions present a challenge, however, due to the mismatch in scale between many of the general climate models (GCMs) and more local climate-forcing factors and related ecological/hydrological processes. The limitations of GCM projections are especially apparent in topographically complex landscapes where terrain features frequently drive rapid changes in temperature and precipitation over relatively small spatial scales. Consequently, smaller scale historical spatial climate datasets that account for local terrain influences are necessary to downscale GCM climate projections and drive ecosystem/hydrology models at regional and landscape scales.

While several smaller scale conterminous United States climate datasets are currently available (e.g.—PRISM, Daymet) they do not contain all the necessary climate variables for process-based models, do not have the required temporal extent and resolution, or do not properly account for local terrain influences. Given these limitations, development of a new climate dataset, TopoMet, is currently underway. TopoMet will build upon previous MT-CLIM and Daymet logic, but also incorporate atmospheric reanalysis data and empirical-statistical downscaling (ESD) techniques to model not only elevation lapse rates, but also other regional and landscape-scale terrain forcings such as cold air drainage and slope/aspect variations. TopoMet will cover the conterminous United States from 1950 to present at a 1 km spatial scale and a daily time step. The following variables will be included: daily minimum/maximum temperature, precipitation, humidity, and solar radiation.

Crown of the Continent Climatology

To prepare for TopoMet development, a prototype spatial climate dataset (1970-present, 1 km resolution) was created for the Crown of the Continent Ecosystem (CCE) in western Montana. While this prototype did not integrate atmospheric reanalysis data, terrain climate forcings were still modeled by combining the daily interpolation logic of Daymet with the monthly PRISM dataset. Projected changes in Pacific Northwest temperature and precipitation (Climate Impacts Group, University of Washington) were then applied to the dataset to drive the Biome-BGC ecosystem model into the future and assess possible future climate impacts in the CCE.

Example Images