scholarly journals The Climate of the McMurdo, Antarctica, Region as Represented by One Year of Forecasts from the Antarctic Mesoscale Prediction System*

2005 ◽  
Vol 18 (8) ◽  
pp. 1174-1189 ◽  
Author(s):  
Andrew J. Monaghan ◽  
David H. Bromwich ◽  
Jordan G. Powers ◽  
Kevin W. Manning
Keyword(s):  
Ross Sea ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Cloud Fraction ◽  
Important Influence ◽  
Limited Area ◽  
Dry Valleys ◽  
Prediction System ◽  
Near Surface ◽  
The Antarctic

Abstract In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program’s Antarctic field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs a limited-area model, the Polar fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), optimized for use over ice sheets. Twice-daily forecasts from the 3.3-km resolution domain of AMPS are joined together to study the climate of the McMurdo region from June 2002 to May 2003. Annual and seasonal distributions of wind direction and speed, 2-m temperature, mean sea level pressure, precipitation, and cloud fraction are presented. This is the first time a model adapted for polar use and with relatively high resolution is used to study the climate of the rugged McMurdo region, allowing several important climatological features to be investigated with unprecedented detail. Orographic effects exert an important influence on the near-surface winds. Time-mean vortices occur in the lee of Ross Island, perhaps a factor in the high incidence of mesoscale cyclogenesis noted in this area. The near-surface temperature gradient is oriented northwest to southeast with the warmest temperatures in the northwest near McMurdo and the gradient being steepest in winter. The first-ever detailed precipitation maps of the region are presented. Orographic precipitation maxima occur on the southerly slopes of Ross Island and in the mountains to the southwest. The source of the moisture is primarily from the large synoptic systems passing to the northeast and east of Ross Island. A precipitation-shadow effect appears to be an important influence on the low precipitation amounts observed in the McMurdo Dry Valleys. Total cloud fraction primarily depends on the amount of open water in the Ross Sea; the cloudiest region is to the northeast of Ross Island in the vicinity of the Ross Sea polynya.

Real-Time Forecasting for the Antarctic: An Evaluation of the Antarctic Mesoscale Prediction System (AMPS)*

2005 ◽  
Vol 133 (3) ◽  
pp. 579-603 ◽  
Author(s):  
David H. Bromwich ◽  
Andrew J. Monaghan ◽  
Kevin W. Manning ◽  
Jordan G. Powers
Keyword(s):  
Surface Pressure ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Surface Wind ◽  
Windward Side ◽  
Prediction System ◽  
Free Atmosphere ◽  
Near Surface ◽  
The Antarctic ◽  
The Impact

Abstract In response to the need for improved weather prediction capabilities in support of the U.S. Antarctic Program’s field operations, the Antarctic Mesoscale Prediction System (AMPS) was implemented in October 2000. AMPS employs the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model optimized for use over ice sheets. The modeling system consists of several domains ranging in horizontal resolution from 90 km covering a large part of the Southern Hemisphere to 3.3 km over the complex terrain surrounding McMurdo, the hub of U.S. operations. The performance of the 30-km AMPS domain versus observations from manned and automatic weather stations is statistically evaluated for a 2-yr period from September 2001 through August 2003. The simulated 12–36-h surface pressure and near-surface temperature at most sites have correlations of r > 0.95 and r > 0.75, respectively, and small biases. Surface wind speeds reflect the complex topography and generally have correlations between 0.5 and 0.6, and positive biases of 1–2 m s−1. In the free atmosphere, r > 0.95 (geopotential height), r > 0.9 (temperature), and r > 0.8 (wind speed) at most sites. Over the annual cycle, there is little interseasonal variation in skill. Over the length of the forecast, a gradual decrease in skill is observed from hours 0–72. One exception is the surface pressure, which improves slightly in the first few hours, due in part to the model adjusting from surface pressure biases that are caused by the initialization technique over the high, cold terrain. The impact of the higher-resolution model domains over the McMurdo region is also evaluated. It is shown that the 3.3-km domain is more sensitive to spatial and temporal changes in the winds than the 10-km domain, which represents an overall improvement in forecast skill, especially on the windward side of the island where the Williams Field and Pegasus runways are situated, and in the lee of Ross Island, an important area of mesoscale cyclogenesis (although the correlation coefficients in these regions are still relatively low).

scholarly journals Reexamination of the Near-Surface Airflow over the Antarctic Continent and Implications on Atmospheric Circulations at High Southern Latitudes*

2007 ◽  
Vol 135 (5) ◽  
pp. 1961-1973 ◽  
Author(s):  
Thomas R. Parish ◽  
David H. Bromwich
Keyword(s):  
Mesoscale Model ◽  
Numerical Models ◽  
Weather Prediction ◽  
Ice Sheets ◽  
Lower Atmosphere ◽  
Diagnostic Model ◽  
Near Surface ◽  
Antarctic Continent ◽  
The Mean ◽  
The Antarctic

Abstract Previous work has shown that winds in the lower atmosphere over the Antarctic continent are among the most persistent on earth with directions coupled to the underlying ice topography. In 1987, Parish and Bromwich used a diagnostic model to depict details of the Antarctic near-surface airflow. A radially outward drainage pattern off the highest elevations of the ice sheets was displayed with wind speeds that generally increase from the high interior to the coast. These winds are often referred to as “katabatic,” with the implication that they are driven by radiational cooling of near-surface air over the sloping ice terrain. It has been shown that the Antarctic orography constrains the low-level wind regime through other forcing mechanisms as well. Dynamics of the lower atmosphere have been investigated increasingly by the use of numerical models since the observational network over the Antarctic remains quite sparse. Real-time numerical weather prediction for the U.S. Antarctic Program has been ongoing since the 2000–01 austral summer season via the Antarctic Mesoscale Prediction System (AMPS). AMPS output, which is based on a polar optimized version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model, is used for a 1-yr period from June 2003 to May 2004 to investigate the mean annual and seasonal airflow patterns over the Antarctic continent to compare with previous streamline depictions. Divergent outflow from atop the continental interior implies that subsidence must exist over the continent and a direct thermal circulation over the high southern latitudes results. Estimates of the north–south mass fluxes are obtained from the mean airflow patterns to infer the influence of the elevated ice sheets on the mean meridional circulation over Antarctica.

scholarly journals A Self-Organizing-Map-Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica

2017 ◽  
Vol 32 (1) ◽  
pp. 223-242 ◽  
Author(s):  
Melissa A. Nigro ◽  
John J. Cassano ◽  
Jonathan Wille ◽  
David H. Bromwich ◽  
Matthew A. Lazzara
Keyword(s):  
Weather Prediction ◽  
Atmospheric Stability ◽  
Static Stability ◽  
Prediction System ◽  
Ice Shelf ◽  
Mechanical Mixing ◽  
Near Surface ◽  
Ross Ice Shelf ◽  
Stable Conditions ◽  
The Antarctic

Abstract Accurate representation of the stability of the surface layer in numerical weather prediction models is important because of the impact it has on forecasts of surface energy, moisture, and momentum fluxes. It also impacts boundary layer processes such as the generation of turbulence, the creation of near-surface flows, and fog formation. This paper uses observations from a 30-m automatic weather station on the Ross Ice Shelf, Antarctica, to evaluate the near-surface layer in the Antarctic Mesoscale Prediction System (AMPS), a numerical weather prediction system used for forecasting in Antarctica. The method of self-organizing maps (SOM) is used to identify characteristic potential temperature anomaly profiles observed at the 30-m tower. The SOM-identified profiles are then used to evaluate the performance of AMPS as a function of atmospheric stability. The results indicate AMPS underpredicts the frequency of near-neutral profiles and instead overpredicts the frequency of weakly unstable and weak to moderately stable profiles. AMPS does not forecast the strongest statically stable patterns observed by Tall Tower, but in the median, the AMPS forecasts are more statically stable across all wind speeds, indicating a possible mechanical mixing error or a negative radiation bias. The SOM analysis identifies a negative radiation bias under near-neutral to weakly stable conditions, causing an overrepresentation of the static stability in AMPS. AMPS has a positive wind speed bias in moderate to strongly stable conditions, which generates too much mechanical mixing and an underrepresentation of the static stability. Model errors increase with increasing atmospheric stability.

scholarly journals Identifying the Characteristics of Strong Southerly Wind Events at Casey Station in East Antarctica Using a Numerical Weather Prediction System

2005 ◽  
Vol 133 (12) ◽  
pp. 3548-3561 ◽  
Author(s):  
Neil Adams
Keyword(s):  
Surface Layer ◽  
Weather Prediction ◽  
East Antarctica ◽  
Katabatic Wind ◽  
Limited Area ◽  
Prediction System ◽  
Layer Flow ◽  
Wind Events ◽  
The Antarctic ◽  
Casey Station

Abstract Casey Station in East Antarctica is not often subject to strong southerly flow off the Antarctic continent but when such events occur, operations at the station are often adversely impacted. Not only are the dynamics of such events poorly understood, but the forecasting of such occurrences is difficult. The following study uses model output from a 12-month experiment using the Antarctic Limited-Area Prediction System (ALAPS) to advance the understanding of the dynamics of such events and postulates that what are often described as katabatic wind events are more likely to be synoptic in scale, with mid- and upper-level tropospheric dynamics forcing the surface layer flow. Strong surface layer flows that have a katabatic signature commonly develop on the steep Antarctic escarpment but rarely extend out over the coast in the Casey area, most probably as a result of cold air damming. However, the development of a strong south-southwesterly jet over Casey provides a mechanism whereby the katabatic can move out off the coast.

scholarly journals Southern High-Latitude Ensemble Data Assimilation in the Antarctic Mesoscale Prediction System

2005 ◽  
Vol 133 (12) ◽  
pp. 3431-3449 ◽  
Author(s):  
D. M. Barker
Keyword(s):  
Data Assimilation ◽  
Sampling Error ◽  
Forecast Error ◽  
Weather Prediction ◽  
Forecast Errors ◽  
Prediction System ◽  
Spatial Covariance ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
The Antarctic

Abstract Ensemble data assimilation systems incorporate observations into numerical models via solution of the Kalman filter update equations, and estimates of forecast error covariances derived from ensembles of model integrations. In this paper, a particular algorithm, the ensemble square root filter (EnSRF), is tested in a limited-area, polar numerical weather prediction (NWP) model: the Antarctic Mesoscale Prediction System (AMPS). For application in the real-time AMPS, the number of model integrations that can be run to provide forecast error covariances is limited, resulting in an ensemble sampling error that degrades the analysis fit to observations. In this work, multivariate, climatologically plausible forecast error covariances are specified via averaged forecast difference statistics. Ensemble representations of the “true” forecast errors, created using randomized control variables of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) three-dimensional variational (3DVAR) data assimilation system, are then used to assess the dependence of sampling error on ensemble size, data density, and localization of covariances using simulated observation networks. Results highlight the detrimental impact of ensemble sampling error on the analysis increment structure of correlated, but unobserved fields—an issue not addressed by the spatial covariance localization techniques used to date. A 12-hourly cycling EnSRF/AMPS assimilation/forecast system is tested for a two-week period in December 2002 using real, conventional (surface, rawinsonde, satellite retrieval) observations. The dependence of forecast scores on methods used to maintain ensemble spread and the inclusion of perturbations to lateral boundary conditions are studied.

scholarly journals Microphysics of summer clouds in central West Antarctica simulated by the Polar Weather Research and Forecasting Model (WRF) and the Antarctic Mesoscale Prediction System (AMPS)

2019 ◽  
Vol 19 (19) ◽  
pp. 12431-12454 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich ◽  
Sheng-Hung Wang ◽  
Israel Silber ◽  
Johannes Verlinde ◽  
...  
Keyword(s):  
Liquid Water ◽  
Radiative Forcing ◽  
Weather Prediction ◽  
The Arctic ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Prediction System ◽  
West Antarctic ◽  
The Antarctic ◽  
Weather Research

Abstract. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) provided a highly detailed set of remote-sensing and surface observations to study Antarctic clouds and surface energy balance, which have received much less attention than for the Arctic due to greater logistical challenges. Limited prior Antarctic cloud observations have slowed the progress of numerical weather prediction in this region. The AWARE observations from the West Antarctic Ice Sheet (WAIS) Divide during December 2015 and January 2016 are used to evaluate the operational forecasts of the Antarctic Mesoscale Prediction System (AMPS) and new simulations with the Polar Weather Research and Forecasting Model (WRF) 3.9.1. The Polar WRF 3.9.1 simulations are conducted with the WRF single-moment 5-class microphysics (WSM5C) used by the AMPS and with newer generation microphysics schemes. The AMPS simulates few liquid clouds during summer at the WAIS Divide, which is inconsistent with observations of frequent low-level liquid clouds. Polar WRF 3.9.1 simulations show that this result is a consequence of WSM5C. More advanced microphysics schemes simulate more cloud liquid water and produce stronger cloud radiative forcing, resulting in downward longwave and shortwave radiation at the surface more in agreement with observations. Similarly, increased cloud fraction is simulated with the more advanced microphysics schemes. All of the simulations, however, produce smaller net cloud fractions than observed. Ice water paths vary less between the simulations than liquid water paths. The colder and drier atmosphere driven by the Global Forecast System (GFS) initial and boundary conditions for AMPS forecasts produces lesser cloud amounts than the Polar WRF 3.9.1 simulations driven by ERA-Interim.

scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 205
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Real Time ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

The direct radiative effect of aerosols is taken into account in many limited-area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We studied the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single-column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA simple broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud–radiation–aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and the vertical distribution of the aerosol species. In such cases, regional weather models should use external real-time aerosol data for radiation parametrizations. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust.

scholarly journals A Practical Approach to Sequential Estimation of Systematic Error on Near-Surface Mesoscale Grids

2007 ◽  
Vol 22 (6) ◽  
pp. 1257-1273 ◽  
Author(s):  
Joshua P. Hacker ◽  
Daran L. Rife
Keyword(s):  
Statistical Analysis ◽  
Systematic Error ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Time Of Day ◽  
Isotropic Case ◽  
Observation Error ◽  
Localization Operators ◽  
Near Surface ◽  
Covariance Functions

Abstract Statistical analysis arguments are used to construct an estimation algorithm for systematic error of near-surface temperatures on a mesoscale grid. The systematic error is defined as the observed running-mean error, and an averaging length of 7 days is shown to be acceptable. Those errors are spread over a numerical weather prediction model grid via the statistical analysis equation. Two covariance models are examined: 1) a stationary, isotropic function tuned with the observed running-mean errors and 2) dynamic estimates derived from a recent history of running-mean forecasts. Prediction of error is possible with a diurnal persistence model, where the error at one time of day can be estimated from data with lags of 24-h multiples. The approach is tested on 6 months of 6-h forecasts with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) over New Mexico. Results show that for a quantity such as 2-m temperature, the systematic component of error can be effectively predicted on the grid. The gridded estimates fit the observed running-mean errors well. Cross validation shows that predictions of systematic error result in a substantial error reduction where observations are not available. The error estimates show a diurnal evolution, and are not strictly functions of terrain elevation. Observation error covariances, localization operators, and covariance functions in the isotropic case must be tuned for a specific forecast system and observing network, but the process is straightforward. Taken together, the results suggest an effective method for systematic error estimation on near-surface mesoscale grids in the absence of a useful ensemble. Correction for those errors may provide benefits to forecast users.

scholarly journals Microscale Numerical Prediction over Montreal with the Canadian External Urban Modeling System

2011 ◽  
Vol 50 (12) ◽  
pp. 2410-2428 ◽  
Author(s):  
Sylvie Leroyer ◽  
Stéphane Bélair ◽  
Jocelyn Mailhot ◽  
Ian B. Strachan
Keyword(s):  
Land Surface ◽  
Deterministic Model ◽  
Weather Prediction ◽  
Grid Size ◽  
Metropolitan Region ◽  
Balance Model ◽  
Surface Model ◽  
Limited Area ◽  
Computational Domain ◽  
Near Surface

AbstractThe Canadian urban and land surface external modeling system (known as urban GEM-SURF) has been developed to provide surface and near-surface meteorological variables to improve numerical weather prediction and to become a tool for environmental applications. The system is based on the Town Energy Balance model for the built-up covers and on the Interactions between the Surface, Biosphere, and Atmosphere land surface model for the natural covers. It is driven by coarse-resolution forecasts from the 15-km Canadian regional operational model. This new system was tested for a 120-m grid-size computational domain covering the Montreal metropolitan region from 1 May to 30 September 2008. The numerical results were first evaluated against local observations of the surface energy budgets, air temperature, and humidity taken at the Environmental Prediction in Canadian Cities (EPiCC) field experiment tower sites. As compared with the regional deterministic 15-km model, important improvements have been achieved with this system over urban and suburban sites. GEM-SURF’s ability to simulate the Montreal surface urban heat island was also investigated, and the radiative surface temperatures from this system and from two systems operational at the Meteorological Service of Canada were compared, that is, the 15-km regional deterministic model and the so-called limited-area model with 2.5-km grid size. Comparison of urban GEM-SURF outputs with remotely sensed observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals relatively good agreement for urban and natural areas.

Real-Time Mesoscale Modeling Over Antarctica: The Antarctic Mesoscale Prediction System*

2003 ◽  
Vol 84 (11) ◽  
pp. 1533-1546 ◽  
Author(s):  
Jordan G. Powers ◽  
Andrew J. Monaghan ◽  
Arthur M. Cayette ◽  
David H. Bromwich ◽  
Ying-Hwa Kuo ◽  
...  
Keyword(s):  
Real Time ◽  
Mesoscale Model ◽  
The United States ◽  
Mesoscale Modeling ◽  
Polar Regions ◽  
Prediction System ◽  
State University ◽  
Medical Evacuation ◽  
The Ohio State University ◽  
The Antarctic

In support of the United States Antarctic Program (USAP), the National Center for Atmospheric Research and the Byrd Polar Research Center of The Ohio State University have created the Antarctic Mesoscale Prediction System (AMPS): an experimental, real-time mesoscale modeling system covering Antarctica. AMPS has been designed to serve flight forecasters at McMurdo Station, to support science and operations around the continent, and to be a vehicle for the development of physical parameterizations suitable for polar regions. Since 2000, AMPS has been producing high-resolution forecasts (grids to 3.3 km) with the “Polar MM5,” a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model tuned for the polar atmosphere. Beyond its basic mission of serving the USAP flight forecasters at McMurdo, AMPS has assisted both in emergency operations to save lives and in programs to explore the extreme polar environment. The former have included a medical evacuation from the South Pole and a marine rescue from the continental margin. The latter have included scientific field campaigns and the daily activities of international Antarctic forecasters and researchers. The AMPS program has been a success in terms of advancing polar mesoscale NWP, serving critical logistical operations of the USAP, and, most visibly, assisting in emergency rescue missions to save lives. The history and performance of AMPS are described and the successes of this unique real-time mesoscale modeling system in crisis support are detailed.

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