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Abstract
In late April 2001, an unprecedented late-season flight to Amundsen–Scott South Pole Station was made in the evacuation of Dr. Ronald Shemenski, a medical doctor seriously ill with pancreatitis. This case study analyzes the performance of four of the numerical weather prediction models that aided meteorologists in forecasting weather throughout the operation: 1) the Antarctic Mesoscale Prediction System (AMPS) Polar MM5 (fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model), 2) the National Centers for Environmental Prediction Aviation Model (AVN), 3) the European Centre for Medium-Range Weather Forecasts (ECMWF) global forecast model, and 4) the NCAR Global MM5. To identify specific strengths and weaknesses, key variables for each model are statistically analyzed for all forecasts initialized between 21 and 25 April for several points over West Antarctica at the surface and at 500- and 700-hPa levels. The ECMWF model performs with the highest overall skill, generally having the lowest bias and rms errors and highest correlations for the examined fields. The AMPS Polar MM5 exhibits the next best skill, followed by AVN and Global MM5. For the surface variables, all of the models show high skill in predicting surface pressure but demonstrate modest skill in predicting temperature, wind speed, and wind direction. In the free atmosphere, the models show high skill in forecasting geopotential height, considerable skill in predicting temperature and wind direction, and good skill in predicting wind speed. In general, the models produce very useful forecasts in the free atmosphere, but substantial efforts are still needed to improve the surface prediction. The spatial resolution of each model exerts an important influence on forecast accuracy, especially in the complex topography of the Antarctic coastal regions. The initial and boundary conditions for the AMPS Polar MM5 exert a significant influence on forecasts.
Abstract
In late April 2001, an unprecedented late-season flight to Amundsen–Scott South Pole Station was made in the evacuation of Dr. Ronald Shemenski, a medical doctor seriously ill with pancreatitis. This case study analyzes the performance of four of the numerical weather prediction models that aided meteorologists in forecasting weather throughout the operation: 1) the Antarctic Mesoscale Prediction System (AMPS) Polar MM5 (fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model), 2) the National Centers for Environmental Prediction Aviation Model (AVN), 3) the European Centre for Medium-Range Weather Forecasts (ECMWF) global forecast model, and 4) the NCAR Global MM5. To identify specific strengths and weaknesses, key variables for each model are statistically analyzed for all forecasts initialized between 21 and 25 April for several points over West Antarctica at the surface and at 500- and 700-hPa levels. The ECMWF model performs with the highest overall skill, generally having the lowest bias and rms errors and highest correlations for the examined fields. The AMPS Polar MM5 exhibits the next best skill, followed by AVN and Global MM5. For the surface variables, all of the models show high skill in predicting surface pressure but demonstrate modest skill in predicting temperature, wind speed, and wind direction. In the free atmosphere, the models show high skill in forecasting geopotential height, considerable skill in predicting temperature and wind direction, and good skill in predicting wind speed. In general, the models produce very useful forecasts in the free atmosphere, but substantial efforts are still needed to improve the surface prediction. The spatial resolution of each model exerts an important influence on forecast accuracy, especially in the complex topography of the Antarctic coastal regions. The initial and boundary conditions for the AMPS Polar MM5 exert a significant influence on forecasts.
The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system.
CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research.
Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.
The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system.
CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research.
Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.