Mark W. Seefeldt

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 ...

An Analysis of Low-Level Jets in the Greater Ross Ice Shelf Region Based on Numerical Simulations

Abstract An analysis of the presence and location of low-level jets (LLJs) across the Ross Ice Shelf region in Antarctica is presented based on the analysis of archived output from the real-time Antarctic Mesoscale Prediction System (AMPS). The method of self-organizing maps (SOMs) is used to objectively identify different patterns in column-averaged wind speed (over the approximately lowest 1200 m of the atmosphere) as an identifier to the location of LLJs. The results indicate three primary LLJs in the region. The largest and most dominant LLJ is along the Transantarctic Mountains by the Siple Coast and the southern end of the Ross Ice Shelf. The second LLJ extends from the base of Byrd Glacier and curves to the north passing by the eastern extremes of Ross Island. The third LLJ extends from the base of Reeves Glacier and curves to the north across the western Ross Sea. A strong seasonality is observed in the frequency and intensity of the LLJs with the highest values for wind speed and the size of the ...

A high-resolution numerical simulation of the wind flow in the Ross Island region, Antarctica

Abstract A detailed description of the characteristics of the three-dimensional wind flow for the Ross Island region of Antarctica is presented. This region of Antarctica has complex topographic features, and the wind flow is dependent on the topography and the local meteorological conditions. High-resolution nonhydrostatic numerical simulations are conducted over a high-resolution domain in the Ross Island region. Two simulations are performed corresponding to the two dominant wind flow patterns in the Ross Island region. The first simulation is a light wind case with a stable lower atmosphere and the second is a high wind speed event. Froude number calculations, along with a study of the equation of motion, are included for a more complete understanding of the dynamics of the wind flow. The results of the simulations show a favorable correlation to past research results and observations, and provide a more complete understanding of the three-dimensional wind flow in the region. In addition to a more tho...

Dominant Regimes of the Ross Ice Shelf Surface Wind Field during Austral Autumn 2005

Abstract An analysis of the surface wind field across the Ross Ice Shelf, Antarctica, is conducted for austral autumn 2005. The airflow is divided into dominant wind regimes identifying similar wind patterns and the associated typical atmospheric forcing. The results of previous research and a seasonal analysis of the recently expanded network of automatic weather stations in the Ross Ice Shelf region are used to define the dominant wind regimes. Events composing each wind regime are identified by matching wind speed and wind direction observations at several automatic weather station sites for durations of at least 10 h. The four different dominant wind regimes are barrier wind, strong katabatic, weak katabatic, and light wind. Each wind regime is studied through the use of wind rose plots and sea level pressure fields from the Antarctic Mesoscale Prediction System. The sea level pressure fields are used to characterize the forcing of the surface wind field by synoptic pressure gradients. The four domina...

A Weather-Pattern-Based Approach to Evaluate the Antarctic Mesoscale Prediction System (AMPS) Forecasts: Comparison to Automatic Weather Station Observations

AbstractTypical model evaluation strategies evaluate models over large periods of time (months, seasons, years, etc.) or for single case studies such as severe storms or other events of interest. The weather-pattern-based model evaluation technique described in this paper uses self-organizing maps to create a synoptic climatology of the weather patterns present over a region of interest, the Ross Ice Shelf for this analysis. Using the synoptic climatology, the performance of the model, the Weather Research and Forecasting Model run within the Antarctic Mesoscale Prediction System, is evaluated for each of the objectively identified weather patterns. The evaluation process involves classifying each model forecast as matching one of the weather patterns from the climatology. Subsequently, statistics such as model bias, root-mean-square error, and correlation are calculated for each weather pattern. This allows for the determination of model errors as a function of weather pattern and can highlight if certai...

Synoptic conditions during wintertime temperature extremes in Alaska

The large-scale atmospheric state associated with widespread wintertime warm and cold extremes in southern Alaska was identified using 1989 to 2007 European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-I) data. Extremes were defined as days with the coldest and warmest 1% of daily temperatures. Widespread extreme events were identified for days when at least 25 50 km grid cells in the study domain met the extreme temperature criteria. A total of 55 cold and 74 warm extreme days were identified in 19 winters. Composites of the atmospheric state from 5days before through the day of the extreme events were analyzed to assess the large-scale atmospheric state associated with the extremes. The method of self-organizing maps (SOMs) was used to identify the range of sea level pressure (SLP) patterns present in the ERA-I December–February data, and these SLP patterns were then used to stratify the extreme days by their large-scale atmospheric circulation. Composites for all warm or cold extreme days showed less intense features than those for specific SLP patterns. In all of the composites temperature advection, strongest at 700 hPa, and anomalous longwave radiation were the primary factors that led to the extreme events. The anomalous downwelling longwave radiationwas due to either reduced cloud cover, during cold extremes, or to increased cloud cover, during warm extremes. The SOM composites provided additional insight into the temporal evolution of the extreme days and highlighted different portions of southern Alaska most likely to experience temperature extremes for a given SOM SLP pattern.

A Characterization of the Variation in Relative Humidity across West Africa during the Dry Season

AbstractThe variation of relative humidity across West Africa during the dry season is evaluated using the Modern Era Retrospective Analysis for Research and Applications (MERRA) dataset and the method of self-organizing maps. Interest in the dry season of West Africa is related to the connection between near-surface atmospheric moisture and the occurrence of meningitis across West Africa, most notably in the region known as the meningitis belt. The patterns in relative humidity are analyzed in terms of frequency of each pattern as well as the sequencing from one pattern to the next. The variations in relative humidity are characterized subannually for individual years from 1979 to 2009 as well as decadally over the entire 30-yr duration of dry seasons in West Africa. The progression from relatively moist patterns to relatively dry patterns and back to the moist patterns over the course of the dry season corresponds to the northward and then southward migration of the intertropical convergence zone. The r...

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...

Analysis of WRF extreme daily precipitation over Alaska using self-organizing maps

We analyze daily precipitation extremes from simulations of a polar-optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska’s topography also has important impacts on orographically forced precipitation. We use self-organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high-frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites producemore physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.