DOI: 10.5443/11399
title: TAWEPI - Thorpex Arctic Weather and Environment Prediction Initiative

description: TAWEPI's research activities started in April 2007 and large progress has been made in the development of Polar-GEM since then. A new version of the CMC regional NWP model became operational in the spring of 2009, including a northward extension of its high-resolution domain, which now covers most of the Arctic and shares various features with Polar-GEM. A research version of the model is being used to study the representation of radiative and cloud processes in weather forecasts. A multi-layer snow model coupled to sea-ice and blowing-snow parameterizations, describing processes over the various types of surfaces of the Arctic environment, such as sea-ice, tundra, glaciers and ice caps, was tested and evaluated. A methodology to validate model forecasts of cloud and radiation using satellite hyperspectral radiances was developed. Using a stratospheric extension of the GEM model, analyses of the stratosphere were extended and now cover the entire IPY period of 2007/2009, including estimates of the ozone field.
description: Purpose: Weather and Environmental Prediction (WEP) constitutes one of the most important technological and societal successes of the last century. The positive impact of WEP on health, safety and economic competitiveness is recognized worldwide. The benefit of WEP applications in polar regions has been somewhat delayed due the higher priority of forecasting in the more densely populated southern regions. Concerns about an amplification of anthropogenic climate change at higher latitudes combined with an increasing interest of the federal Government in exerting Canadian sovereignty throughout the Arctic requires a better understanding of weather and climate processes in this region so as to improve our ability to make reliable, quantitative predictions. The International Polar Year provides the important international context for a Canadian-led initiative to improve WEP capabilities for the Arctic. In a significantly changing Arctic climate it will be more and more difficult to rely on traditional and climatological knowledge to predict day-to-day to seasonal environmental variability. Indeed, experienced elders and hunters who have been able to predict the weather for most of their lives are finding that recently their prediction skills no longer work and the weather changes they are witnessing are unprecedented. It will be essential to rely on science-based forecasting technologies to reduce the impact of weather and related hazards on health, safety and the economy. The primary objective of TAWEPI is to develop and validate a regional Numerical Weather Prediction (NWP) model over the Arctic during the IPY observational period. The proposed experimental model, called Polar-GEM, is a twin of the Environment Canada (EC) operational regional GEM (Global Environmental Multiscale) model, used for one- to two-day weather forecasts. This initiative includes modelling research and data assimilation studies that will help enhance our weather and environmental forecasting capabilities in polar regions and improve our understanding of the Arctic and its influence on world weather. These research activities and studies are taking place in various research divisions of Environment Canada, in collaboration with the Canadian Meteorological Centre (CMC), the Canadian Ice Service (CIS), the Department of Fisheries and Oceans (DFO), various Canadian universities and other IPY projects. Canadian SPARC model outputs (CCIN#10906) were shared with TAWEPI.
description: Summary: Being able to predict the weather is important for the health, safety and economy of communities throughout the world. However, the technology to predict weather in the Arctic has not been well developed. This project is producing comprehensive weather maps of the Arctic stratosphere that include features like temperature, wind and various atmospheric chemicals. Numerical weather prediction models for one- to two-day regional weather forecasts for the Canadian Arctic are also being developed and validated. All models are being evaluated against ongoing weather with additional features on how disturbances, like extreme storms, from other regions affect weather in the North, how snow moves across different surfaces and how clouds and solar processes can be better represented in forecast models.