Matthew E. Higgins

Performance of the Weather Research and Forecasting Model for Month-Long Pan-Arctic Simulations

AbstractThe performance of the Weather Research and Forecasting (WRF) model was evaluated for month-long simulations over a large pan-Arctic model domain. The evaluation of seven different WRF (version 3.1) configurations for four months (January, April, July, and October 2007) indicated that WRF produces reasonable simulations of the Arctic atmosphere. Ranking of the model error statistics, calculated relative to the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2), for sea level pressure, 500- and 300-hPa geopotential height, 2-m air temperature, and precipitation identified the model configurations that consistently produced the best pan-Arctic simulations. For all WRF configurations considered, large errors in circulation are evident in the North Pacific. The errors in the North Pacific are manifested as an overly weak and westward-shifted Aleutian low and overly strong subtropical Pacific high simulated by WRF. These circulation errors are nearly barotropic, with a slight increase in magnitude ...

Effects of Spectral Nudging in WRF on Arctic Temperature and Precipitation Simulations

AbstractSpectral (interior) nudging is a way of constraining a model to be more consistent with observed behavior. However, such control over model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events since nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes: what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, case studies were performed using a six-member ensemble of the Pan-Arctic Weather Research and Forecasting model (WRF) with varying spectral nudging strength, using WRF’s standard nudging as a reference point. Two periods were simulated, one in a cold season (January 2007) and one in a warm season (July 2007).Precipitation and 2-m temperature were analyzed to determine how changing spectral nudging strength impacts temperature and precipitation extremes and selected percentiles. R...

Northern Alaskan land surface response to reduced Arctic sea ice extent

With Arctic sea ice extent at near-record lows, an improved understanding of the relationship between sea ice and the land surface is warranted. We examine the land surface response to changing sea ice by first conducting a simulation using the Community Atmospheric Model version 3.1 with end of the twenty-first century sea ice extent. This future atmospheric response is then used to force the Weather and Research Forecasting Model version 3.1 to examine the terrestrial land surface response at high resolution over the North Slope of Alaska. Similar control simulations with twentieth century sea ice projections are also performed, and in both simulations only sea ice extent is altered. In the future sea ice extent experiment, atmospheric temperature increases significantly due to increases in latent and sensible heat flux, particularly in the winter season. Precipitation and snow pack increase significantly, and the increased snow pack contributes to warmer soil temperatures for most seasons by insulating the land surface. In the summer, however, soil temperatures are reduced due to increased albedo. Despite warmer near-surface atmospheric temperatures, it is found that spring melt is delayed throughout much of the North Slope due to the increased snow pack, and the growing season length is shortened.

Development of the Regional Arctic System Model (RASM): Near-Surface Atmospheric Climate Sensitivity

AbstractThe near-surface climate, including the atmosphere, ocean, sea ice, and land state and fluxes, in the initial version of the Regional Arctic System Model (RASM) are presented. The sensitivity of the RASM near-surface climate to changes in atmosphere, ocean, and sea ice parameters and physics is evaluated in four simulations. The near-surface atmospheric circulation is well simulated in all four RASM simulations but biases in surface temperature are caused by biases in downward surface radiative fluxes. Errors in radiative fluxes are due to biases in simulated clouds with different versions of RASM simulating either too much or too little cloud radiative impact over open ocean regions and all versions simulating too little cloud radiative impact over land areas. Cold surface temperature biases in the central Arctic in winter are likely due to too few or too radiatively thin clouds. The precipitation simulated by RASM is sensitive to changes in evaporation that were linked to sea surface temperature...