Development and Testing of Polar WRF. Part III: Arctic Land*

Hines, Keith M.; Bromwich, David H.; Bai, Long; Barlage, Michael; Slater, A. G.

doi:10.1175/2010jcli3460.1

Cited by 134 publications

(145 citation statements)

References 65 publications

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“…Of particular note is the large diurnal 2 m temperature range (greater than the midlatitude cycle), where significant differences between the model and observations occur near the highest and lowest solar angles. Hines et al [2011] show that clouds and radiation are sensitive to the choice of microphysics and boundary layer parameterizations when dealing with areas near the Arctic Ocean, but are not sensitive for areas inland. The result is an underrepresentation of (Arctic) stratus clouds over Arctic land in the summer.…”

Section: Diurnal Cycles Of Surface Variablesmentioning

confidence: 96%

“…Likewise, sea ice albedo was set as a function time and latitude to account for the strong seasonal cycle. Finally, Polar WRF was tested over Arctic land using version 3.0.1.1 and compared to observations from the North Slope of Alaska [Hines et al, 2011]. A sensitivity study using reduced soil heat conductivity was used during a January 2007 simulation in order to improve near surface air temperatures, which were previously too warm.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis

Wilson¹,

Bromwich²,

Hines³

2011

J. Geophys. Res.

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[1] The Polar version 3.1.1 of the Weather Research and Forecasting model (WRF), a high-resolution regional scale model, is used to simulate conditions for the year December 2006 to November 2007. The goal is to compare model output of near-surface and tropospheric variables to observational data sets. The domain mirrors that of the Arctic System Reanalysis (ASR), an assimilation of model fields with Arctic observations being conducted partly by the Polar Meteorology Group of the Byrd Polar Research Center at Ohio State University. A key development in this Polar WRF study is the extension of the seasonal progression of sea ice albedo to the entire Arctic Ocean. The boundary conditions are specified by the NCEP Final global gridded analysis archive (FNL), a 1°× 1°global grid updated every 6 h. The simulations are performed in 48 h increments initialized daily at 0000 UTC, with the first 24 h discarded for model spin-up of the hydrologic cycle and boundary layer processes. Model large-scale variables of atmospheric pressure and geopotential height show good agreement with observations. Spatial distribution of near-surface air temperatures compares well with ERA-Interim despite a small negative bias in the station analysis. Surface dewpoint temperatures and wind speeds show small biases, but model skill is modest for near-surface winds. Tropospheric temperatures and wind speeds, however, agree well with radiosonde observations. This examination provides a benchmark from which to improve the model and guidance for further development of Polar WRF as ASR's primary model.

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Section: Diurnal Cycles Of Surface Variablesmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis

Wilson¹,

Bromwich²,

Hines³

2011

J. Geophys. Res.

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“…RRTMG accounts for all major gaseous absorbers at long and short wavelengths along with the radiative effects of clouds and aerosols as well as a statistical technique for representing subgrid-scale cloud variability. Hines et al [2011] recently performed four simulations to assess the sensitivity of the various microphysics options in Polar WRF and found only a small sensitivity over Arctic land. Thus in Antarctica (which is mostly land ice) the impact of using the WRF Single Moment 5-class microphysics (WSM5) instead of the Morrison scheme that is used in the Arctic System Reanalysis is presumed to be small.…”

Section: Experimental Strategymentioning

confidence: 99%

“…Not only did the AMPS model change but, as computer capability has increased, also has the resolution used by AMPS, which now stands at 1.67 km around McMurdo Station, where the USAP hub is located. However, the WRF model was originally developed for the Northern Hemisphere midlatitudes, and for polar regions WRF has been tested primarily in Arctic environments [Bromwich et al, 2009;Hines and Bromwich, 2008;Hines et al, 2011;Cassano et al, 2011]. Therefore, it is necessary for advancing Antarctic modeling to benchmark its performance in Antarctica.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic

et al. 2013

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[1] Recent versions of the Polar Weather Research and Forecasting model are evaluated over the Antarctic to assess the impact of model improvements, resolution, large-scale circulation variability, and uncertainty in initial and lateral boundary conditions. The model skill differs more between forecasts using different sources of lateral boundary data than between forecasts from different model versions or simulated years. Using the ERA-Interim reanalysis for initial and lateral boundary conditions produces the best skill. The forecasts have a cold summer and a warm winter bias in 2 m air temperatures, with similar but smaller bias in dew point temperatures. Upper air temperature biases are small and remain less than 1 C except at the tropopause in summer. Geopotential height biases increase with height in both seasons. Deficient downward longwave radiation in all seasons and an under representation of clouds enhance radiative loss, leading to the cold summer bias. Excess summer surface incident shortwave radiation plays a secondary role, because 80% of it is reflected, leading to greater skill for clear compared with cloudy skies. The positive wind speed bias produces a warm surface bias in winter resulting from anomalously large downward flux of sensible heat toward the surface. Low temperatures on the continent limit sublimation and hence the precipitable water amounts over the ice sheet. ERA-Interim experiments with higher precipitable water showed reduced biases in downwelling shortwave and longwave radiation. Increasing horizontal resolution from 60 to 15 km improves the skill of surface wind forecasts.

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“…We then test whether marine air intrusions play a key role in warm events exceeding melting point at Syowa and explore atmospheric process responsible for warm events using air mass trajectory analysis and regional atmospheric model simulations. (Hines et al 2008;Bromwich et al 2009;Hines et al 2011). Initial and boundary conditions for AMPS forecasts are taken from the National Centers for Environmental Prediction Global Forecast System.…”

Section: Introductionmentioning

confidence: 99%

Identification of Air Masses Responsible for Warm Events on the East Antarctic Coast

Kurita

Hirasawa

Koga

et al. 2016

SOLA

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Warm events, periods when rising surface air temperatures can trigger surface melt, have been recorded during the austral summer at Syowa station on the East Antarctic coast. This study identifies air masses responsible for summer warm events at Syowa. Air masses arriving at Syowa are classified into marine and glacial sources based on their isotopic characteristics. Warm events are not associated with moist marine air intrusion, but with the downward flow of dry glacial air along the west side slope of the mountains in Enderby Land (EL). We use simulations from the Antarctic Mesoscale Prediction System (AMPS) to explore the atmospheric process responsible for the warmest event at Syowa. The model output illustrates several foehn-associated features such as low-level blocking, precipitation on the mountain's windward side, and mountain wave activity, with warm air ascending on the upstream slope and descending to Syowa. The foehn warming is caused by an easterly cross-mountain flow associated with a low-pressure system to the north of the EL coast. Future changes in synoptic cyclonic activity off the EL coast may have a significant impact on the frequency and intensity of foehn events at Syowa and the associated coastal warm events.(Citation: Kurita, N., N. Hirasawa, S. Koga, J. Matsushita, H. C. Steen-Larsen, V. Masson-Delmotte, and Y. Fujiyoshi, 2016: Identification of air mass responsible for warm events on the East

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Development and Testing of Polar WRF. Part III: Arctic Land*

Cited by 134 publications

References 65 publications

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis

Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic

Identification of Air Masses Responsible for Warm Events on the East Antarctic Coast

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