MicroMet Drives CIRA Contribution to International Polar Year

A high-resolution meteorological distribution model – MicroMet – developed by researchers at the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University is being used to support the 2007-2008 International Polar Year (IPY) – an international coordinated campaign of research in the Polar Regions. MicroMet is being used to support CIRA IPY projects that range from the first-ever systematic snow measurements across the Arctic Canada Barrenlands that will improve satellite algorithms used to map global snow distributions, to the development of a prototype international network to measure and model snowfall and snow on the ground, thereby improving knowledge of the contribution of arctic precipitation to global climate variability, to a joint US-Norwegian project whose primary goal is to enhance understanding East Antarctic climate variability on time scales of years to centuries. Funding for MicroMet came to CIRA through the Climate Prediction Program for the Americas program at NOAA.

Background: The initial vision of MicroMet was to develop a state-of-the-art, physically based, micrometeorological model to serve as an interface between the relatively coarse-resolution atmospheric models (e.g., 50- to 5-km grid increment) and fine-resolution (e.g., 1-km to 100-m grid increment) hydrological and ecological models. Currently, there is only limited modeling capacity available to convert atmospheric forcing data to the sufficiently high spatial resolution required to drive terrestrial models operating at realistic spatial scales. This lack of available high-resolution atmospheric forcing data has hindered the development of spatially- and physically-realistic hydrological and ecological models.

Significance: Further development of MicroMet will lay the groundwork for substantial improvements to existing hydrological and ecological models. This need is particularly acute in the western mountain States where topographic variations lead to significant variations in winter snow precipitation, snow-depth distribution, spring snowmelt, and runoff rates. This, in turn, will lead to increased accuracy of operational weather, hydrologic, and water-resource forecasts. This research supports NOAA Mission Goal 2 - Understand Climate Variability and Change to Enhance Society's Ability to Plan and Respond and NOAA Mission Goal 3 - Serve Society's Needs for Weather and Water Information.