S-290 Unit 7: Wind Systems
S-290 Unit 7: Wind Systems will outline general and local winds and their processes. Detailed information will be provided on critical fire weather winds, including frontal winds, Foehn winds, and thunderstorm winds and the effects of these winds on wildland fires. The module will also describe topographic influences on winds, and will provide guidelines for estimating winds based on location and fuel sheltering. The module will be part of the Intermediate Wildland Fire Behavior Course "http://www.meted.ucar.edu/dl_courses/S290".
posted on September 22, 2009
Toward an Advanced Sounder on GOES?
Using recorded interviews from a number of meteorologists and leading satellite experts, this module describes how a high spectral resolution IR sounder in geostationary orbit could lead to significant improvements in mesoscale and severe weather forecasting. The module begins with a discussion of how the capabilities and products of the current GOES sounder (GOES I-P) will be extended to the initial next generation GOES-R satellites that will not include a dedicated sounder and any potential impacts. The discussion then focuses on the outstanding need for an advanced sounder for improved characterization of the atmosphere's vertical moisture and temperature structure and the potential contributions of a future hyperspectral sounder in geostationary orbit. The audience for this module includes forecasters and decision makers.
posted on September 22, 2009
Precipitation Estimates, Part 2: Analysis
"Precipitation Estimates, Part 2: Analysis" is the 2nd of a two-module series on measuring and analyzing observed precipitation. This module will review the science behind the products and tools available through the NWS Multisensor Precipitation Estimation (MPE) program and related programs. The products and tools allow the forecaster to review, assess, and edit precipitation data from precipitation gauges, radar, satellite, and climatology. The end goal is to provide the best possible analysis of observed precipitation which includes using information from multiple sensors. Detailed graphics, animations, interactive exercises and real MPE data will be used to enhance the learning experience.
posted on September 23, 2009
