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 A Decade of Antarctic Science Support Through Amps

2012 ◽  
Vol 93 (11) ◽  
pp. 1699-1712 ◽  
Author(s):  
Jordan G. Powers ◽  
Kevin W. Manning ◽  
David H. Bromwich ◽  
John J. Cassano ◽  
Arthur M. Cayette
Keyword(s):  
Real Time ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Prediction System ◽  
Numerical Weather ◽  
The Antarctic ◽  
The U.S ◽  
Weather Research

The Antarctic Mesoscale Prediction System (AMPS) is a real-time numerical weather prediction (NWP) system covering Antarctica that has served a remarkable range of groups and activities for a decade. It employs the Weather Research and Forecasting model (WRF) on varying-resolution grids to generate numerical guidance in a variety of tailored products. While its priority mission has been to support the forecasters of the U.S. Antarctic Program, AMPS has evolved to assist a host of scientific and logistical needs for an international user base. The AMPS effort has advanced polar NWP and Antarctic science and looks to continue this into another decade. To inform those with Antarctic scientific and logistical interests and needs, the history, applications, and capabilities of AMPS are discussed.

scholarly journals Microphysics of Summer Clouds in Central West Antarctica Simulated by Polar WRF and AMPS

2019 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich ◽  
Sheng-Hung Wang ◽  
Israel Silber ◽  
Johannes Verlinde ◽  
...  
Keyword(s):  
Liquid Water ◽  
Radiative Forcing ◽  
Weather Prediction ◽  
Shortwave Radiation ◽  
The Arctic ◽  
West Antarctic ◽  
Operational Forecasts ◽  
Single Moment ◽  
Atmospheric Radiation Measurement ◽  
Ice Water

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 has slowed the progress of numerical weather prediction in this region. The AWARE observations from 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 Polar WRF 3.9.1. The Polar WRF 3.9.1 simulations are conducted with advanced microphysics schemes and with the WRF single-moment 5-class microphysics (WSM5C) also used by AMPS. AMPS simulates few liquid clouds during summer at WAIS Divide, 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 GFS initial and boundary conditions for AMPS forecasts produces lesser cloud amounts than the Polar WRF 3.9.1 simulations driven by ERA-Interim.

Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model

2014 ◽  
Vol 31 (9) ◽  
pp. 2008-2014 ◽  
Author(s):  
Xin Zhang ◽  
Ying-Hwa Kuo ◽  
Shu-Ya Chen ◽  
Xiang-Yu Huang ◽  
Ling-Feng Hsiao
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Observation Operator ◽  
Gps Radio Occultation ◽  
Phase Observation ◽  
Excess Phase ◽  
Weather Research

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

scholarly journals Regional Climate–Weather Research and Forecasting Model

2012 ◽  
Vol 93 (9) ◽  
pp. 1363-1387 ◽  
Author(s):  
Xin-Zhong Liang ◽  
Min Xu ◽  
Xing Yuan ◽  
Tiejun Ling ◽  
Hyun I. Choi ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Regional Climate ◽  
Weather Forecast ◽  
Ecosystem Model ◽  
Climate Prediction ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Physical Processes ◽  
Terrestrial Hydrology ◽  
Weather Research

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

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

2013 ◽  
Vol 118 (2) ◽  
pp. 274-292 ◽  
Author(s):  
David H. Bromwich ◽  
Francis O. Otieno ◽  
Keith M. Hines ◽  
Kevin W. Manning ◽  
Elad Shilo
Keyword(s):  
Comprehensive Evaluation ◽  
Model Performance ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
The Antarctic ◽  
Weather Research

scholarly journals Time-dependent 3D simulations of tropospheric ozone depletion events in the Arctic spring using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem)

2021 ◽  
Vol 21 (10) ◽  
pp. 7611-7638
Author(s):  
Maximilian Herrmann ◽  
Holger Sihler ◽  
Udo Frieß ◽  
Thomas Wagner ◽  
Ulrich Platt ◽  
...  
Keyword(s):  
Ozone Depletion ◽  
Heterogeneous Reactions ◽  
The Arctic ◽  
Optical Absorption Spectroscopy ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Time Interval ◽  
Good Prediction ◽  
Weather Research

Abstract. Tropospheric bromine release and ozone depletion events (ODEs) as they commonly occur in the Arctic spring are studied using a regional model based on the open-source software package Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, the MOZART (Model for Ozone and Related chemical Tracers)–MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) chemical reaction mechanism is extended by bromine and chlorine reactions as well as an emission mechanism for reactive bromine via heterogeneous reactions on snow surfaces. The simulation domain covers an area of 5040 km×4960 km, centered north of Utqiaġvik (formerly Barrow), Alaska, and the time interval from February through May 2009. Several simulations for different strengths of the bromine emission are conducted and evaluated by comparison with in situ and ozone sonde measurements of ozone mixing ratios as well as by comparison with tropospheric BrO vertical column densities (VCDs) from the Global Ozone Monitoring Experiment-2 (GOME-2) satellite instrument. The base bromine emission scheme includes the direct emission of bromine due to bromide oxidation by ozone. Results of simulations with the base emission rate agree well with the observations; however, a simulation with 50 % faster emissions performs somewhat better. The bromine emission due to bromide oxidation by ozone is found to be important to provide an initial seed for the bromine explosion. Bromine release due to N2O5 was found to be important from February to mid March but irrelevant thereafter. A comparison of modeled BrO with in situ and multi-axis differential optical absorption spectroscopy (MAX-DOAS) data hints at missing bromine release and recycling mechanisms on land or near coasts. A consideration of halogen chemistry substantially improves the prediction of the ozone mixing ratio with respect to the observations. Meteorological nudging is essential for a good prediction of ODEs over the 3-month period.

PRACTICAL ASPECTS OF APPLICATION OF METEOROLOGICAL WEATHER PREDICTION MODELS FOR THE NEED OF AGRICULTURAL SECTOR OF ECONOMY

2017 ◽  
Author(s):  
Mykhailo Frolov ◽  
Keyword(s):  
Negative Impact ◽  
Weather Prediction ◽  
Mesoscale Modeling ◽  
Extreme Weather Events ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Medium Term ◽  
Short Term ◽  
The Impact ◽  
Weather Research

Different aspects of the application of short-term and long-term meteorological forecasting in the work of agricultural companies of different scales were investigated in this paper. Systematic assessment and consideration of weather factors in the work of agricultural companies of various scales is very important on the way to effective management and increase profits, especially in today's climate change. The use of existing global meteorological models does not always allow to obtain a detailed and qualitative forecast for individual areas, which is important for assessing the impact of weather on crops. The advantages of using the mesoscale Weather Research and Forecasting Model (WRF) for agricultural companies are considered. The results of short-term and medium- term WRF modeling can be used by agricultural campaigns to assess the potential negative impact of weather conditions on crops, as well as in preventive decisions to reduce the negative impact of extreme weather events on crops. The problem of the need for significant computing resources for mesoscale modeling can be solved by using commercial Cloud platforms, which are more cost-effective than purchasing high-performance computer systems (HPC). The scheme of application of short-term and medium-term weather forecasting in agricultural companies by realization of mesoscale modeling with Weather Research and Forecasting Model (WRF) and with application of cloud technologies was developed. The result of the proposed scheme are graphic products of meteorological quantities and weather maps of the modeling area (where crops are located), which is a ready product for analysis by agricultural companies for further agricultural and technical decision making process.

scholarly journals Land-Use Improvements in the Weather Research and Forecasting Model over Complex Mountainous Terrain and Comparison of Different Grid Sizes

2021 ◽  
Author(s):  
Alessio Golzio ◽  
Silvia Ferrarese ◽  
Claudio Cassardo ◽  
Gugliemina Adele Diolaiuti ◽  
Manuela Pelfini
Keyword(s):  
Boundary Layer ◽  
Land Use ◽  
Land Cover ◽  
Mixing Layer ◽  
Local Area ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Mountainous Terrain ◽  
Weather Research

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.

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