Evaluation of the Rapid Refresh Numerical Weather Prediction Model over Arctic Alaska

Matthew T. Bray aSchool of Meteorology, University of Oklahoma, Norman, Oklahoma

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David D. Turner bGlobal Systems Laboratory, NOAA, Boulder, Colorado

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Gijs de Boer cCooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
dPhysical Sciences Laboratory, NOAA, Boulder, Colorado

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Abstract

Despite a need for accurate weather forecasts for societal and economic interests in the U.S. Arctic, thorough evaluations of operational numerical weather prediction in the region have been limited. In particular, the Rapid Refresh Model (RAP), which plays a key role in short-term forecasting and decision-making, has seen very limited assessment in northern Alaska, with most evaluation efforts focused on lower latitudes. In the present study, we verify forecasts from version 4 of the RAP against radiosonde, surface meteorological, and radiative flux observations from two Arctic sites on the northern Alaskan coastline, with a focus on boundary layer thermodynamic and dynamic biases, model representation of surface inversions, and cloud characteristics. We find persistent seasonal thermodynamic biases near the surface that vary with wind direction, and may be related to the RAP’s handling of sea ice and ocean interactions. These biases seem to have diminished in the latest version of the RAP (version 5), which includes refined handling of sea ice, among other improvements. In addition, we find that despite capturing boundary layer temperature profiles well overall, the RAP struggles to consistently represent strong, shallow surface inversions. Further, while the RAP seems to forecast the presence of clouds accurately in most cases, there are errors in the simulated characteristics of these clouds, which we hypothesize may be related to the RAP’s treatment of mixed-phase clouds.

Significance Statement

Human activities continue to expand into northern high latitudes, including shipping and other commercial activities, energy exploration, tourism, and defense. Conducting these activities safely requires accurate weather forecasting tools capable of handling a harsh and complex environment. This work evaluates the performance of one of the primary weather forecasting models used in the United States for short-term decision-making, the Rapid Refresh (RAP) model, run operationally by the National Weather Service. This effort illustrates some promising results, while at the same time bringing some shortcomings to light. Importantly, it highlights some areas in which the RAP can improve to support northern communities and commercial entities through the development of accurate weather forecasts.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew Bray, matthewbray1@ou.edu

Abstract

Despite a need for accurate weather forecasts for societal and economic interests in the U.S. Arctic, thorough evaluations of operational numerical weather prediction in the region have been limited. In particular, the Rapid Refresh Model (RAP), which plays a key role in short-term forecasting and decision-making, has seen very limited assessment in northern Alaska, with most evaluation efforts focused on lower latitudes. In the present study, we verify forecasts from version 4 of the RAP against radiosonde, surface meteorological, and radiative flux observations from two Arctic sites on the northern Alaskan coastline, with a focus on boundary layer thermodynamic and dynamic biases, model representation of surface inversions, and cloud characteristics. We find persistent seasonal thermodynamic biases near the surface that vary with wind direction, and may be related to the RAP’s handling of sea ice and ocean interactions. These biases seem to have diminished in the latest version of the RAP (version 5), which includes refined handling of sea ice, among other improvements. In addition, we find that despite capturing boundary layer temperature profiles well overall, the RAP struggles to consistently represent strong, shallow surface inversions. Further, while the RAP seems to forecast the presence of clouds accurately in most cases, there are errors in the simulated characteristics of these clouds, which we hypothesize may be related to the RAP’s treatment of mixed-phase clouds.

Significance Statement

Human activities continue to expand into northern high latitudes, including shipping and other commercial activities, energy exploration, tourism, and defense. Conducting these activities safely requires accurate weather forecasting tools capable of handling a harsh and complex environment. This work evaluates the performance of one of the primary weather forecasting models used in the United States for short-term decision-making, the Rapid Refresh (RAP) model, run operationally by the National Weather Service. This effort illustrates some promising results, while at the same time bringing some shortcomings to light. Importantly, it highlights some areas in which the RAP can improve to support northern communities and commercial entities through the development of accurate weather forecasts.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew Bray, matthewbray1@ou.edu
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