scholarly journals Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology*

2008 ◽  
Vol 136 (6) ◽  
pp. 1971-1989 ◽  
Author(s):  
Keith M. Hines ◽  
David H. Bromwich
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
Ice Sheet ◽  
Wrf Model ◽  
Greenland Ice Sheet ◽  
Forecast Skill ◽  
Weather Research And Forecasting ◽  
Surface Model ◽  
Weather Research

Abstract A polar-optimized version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was developed to fill climate and synoptic needs of the polar science community and to achieve an improved regional performance. To continue the goal of enhanced polar mesoscale modeling, polar optimization should now be applied toward the state-of-the-art Weather Research and Forecasting (WRF) Model. Evaluations and optimizations are especially needed for the boundary layer parameterization, cloud physics, snow surface physics, and sea ice treatment. Testing and development work for Polar WRF begins with simulations for ice sheet surface conditions using a Greenland-area domain with 24-km resolution. The winter month December 2002 and the summer month June 2001 are simulated with WRF, version 2.1.1, in a series of 48-h integrations initialized daily at 0000 UTC. The results motivated several improvements to Polar WRF, especially to the Noah land surface model (LSM) and the snowpack treatment. Different physics packages for WRF are evaluated with December 2002 simulations that show variable forecast skill when verified with the automatic weather station observations. The WRF simulation with the combination of the modified Noah LSM, the Mellor–Yamada–Janjić boundary layer parameterization, and the WRF single-moment microphysics produced results that reach or exceed the success standards of a Polar MM5 simulation for December 2002. For summer simulations of June 2001, WRF simulates an improved surface energy balance, and shows forecast skill nearly equal to that of Polar MM5.

scholarly journals Using the Weather Research and Forecasting (WRF) Model for Precipitation Forecasting in an Andean Region with Complex Topography

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 304 ◽  
Author(s):  
Gonzalo Yáñez-Morroni ◽  
Jorge Gironás ◽  
Marta Caneo ◽  
Rodrigo Delgado ◽  
René Garreaud
Keyword(s):  
Land Surface ◽  
Weather Prediction ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Lead Times ◽  
Complex Topography ◽  
Front Range ◽  
Meteorological Forcing ◽  
Rainfall Events ◽  
Weather Research

The Weather Research and Forecasting (WRF) model has been successfully used in weather prediction, but its ability to simulate precipitation over areas with complex topography is not optimal. Consequently, WRF has problems forecasting rainfall events over Chilean mountainous terrain and foothills, where some of the main cities are located, and where intense rainfall occurs due to cutoff lows. This work analyzes an ensemble of microphysics schemes to enhance initial forecasts made by the Chilean Weather Agency in the front range of Santiago. We first tested different vertical levels resolution, land use and land surface models, as well as meteorological forcing (GFS/FNL). The final ensemble configuration considered three microphysics schemes and lead times over three rainfall events between 2015 and 2017. Cutoff low complex meteorological characteristics impede the temporal simulation of rainfall properties. With three days of lead time, WRF properly forecasts the rainiest N-hours and temperatures during the event, although more accuracy is obtained when the rainfall is caused by a meteorological frontal system. Finally, the WSM6 microphysics option had the best performance, although further analysis using other storms and locations in the area are needed to strengthen this result.

scholarly journals EVAPOTRANSPIRAÇÃO DE REFERÊNCIA ESTIMADA PELO MÉTODO DE PENMAN-MONTEITH FAO-56 EM FUNÇÃO DAS SIMULAÇÕES DO MODELO ATMOSFÉRICO DE MESOESCALA WRF - WEATHER RESEARCH AND FORECASTING

Irriga ◽  
2015 ◽  
Vol 20 (4) ◽  
pp. 762-775
Author(s):  
José Leonaldo De Souza ◽  
Gustavo Bastos Lyra ◽  
Valesca Rodrigues Fernandes ◽  
Rosiberto Salustiano Silva-Junior ◽  
Guilherme Bastos Lyra ◽  
...  
Keyword(s):  
Mesoscale Model ◽  
Meteorological Data ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Simulated Data ◽  
Absolute Error ◽  
Atmospheric Model ◽  
Atmospheric Modeling ◽  
Weather Research And Forecasting ◽  
Weather Research

EVAPOTRANSPIRAÇÃO DE REFERÊNCIA ESTIMADA PELO MÉTODO DE PENMAN-MONTEITH FAO-56 EM FUNÇÃO DAS SIMULAÇÕES DO MODELO ATMOSFÉRICO DE MESOESCALA WRF - WEATHER RESEARCH AND FORECASTING  JOSÉ LEONALDO DE SOUZA1; GUSTAVO BASTOS LYRA2; VALESCA RODRIGUES FERNADES1; ROSEBERTO SALUSTIANO DA SILVA JUNIOR1; GUILHERME BASTOS LYRA3; VINICIUS BANDA SPERLING1; RICARDO ARAUJO FERREIRA JUNIOR3 E IÊDO TEODORO3 1Instituto de Ciências Atmosférica (ICAT), Universidade Federal de Alagoas (UFAL), Campus A.C. Simões, Av. Lourival Melo Mota, s/n,  Tabuleiro dos Martins, CEP:57072-900, Maceió - AL, [email protected]/[email protected]/[email protected]/ [email protected] de Florestas, Dep. de Ciências Ambientais, Universidade Federal Rural do Rio de Janeiro, Seropédica - RJ, [email protected] de Ciências Agrarias (CECA), Universidade Federal de Alagoas (UFAL), Rio Largo - AL, [email protected]/[email protected]/[email protected]        1 RESUMO O objetivo do trabalho foi avaliar a estimativa da evapotranspiração de referência (ETo) pelo método de Penman-Monteith parametrizado no boletim FAO-56 (PM-FAO56) utilizando dados meteorológicos observados e os simulados pelo modelo atmosférico Weather Research and Forecasting (WRF). Na estimativa de ETo utilizaram-se dados meteorológicos observados (extremos da temperatura e umidade do ar, radiação solar e velocidade do vento) e simulados pelo WRF no período seco (janeiro a março e de outubro a dezembro de 2008) da região de Rio Largo - AL (9°28’02’’ S, 35º49’44’’ W e 127 m). As estimativas foram avaliadas pelo coeficiente de determinação (r2) entre ETo obtida com os dados observados e simulados, pelo índice de concordância de Willmott (dr) e pelo erro médio absoluto (MAE). O método PM-FAO56 apresentou maior sensibilidade ao saldo de radiação, em relação aos seus termos aerodinâmicos. As estimativas de ETo apresentaram baixa precisão (r2 = 0,41) e acurácia moderada (dr = 0,77 e MAE = 0,79 mm d-1). É necessário melhorar as simulações dos componentes de radiação do WRF para melhor estimar ETo pelo método de PM-FAO56 na região de Rio Largo, AL. Palavras Chave: Dados Meteorológicos, Modelagem Atmosférica, Penman-Monteith  DE SOUZA, J. L.; LYRA, G. B.; FERNADES,V. R.; SILVA-JUNIOR, R. S.; LYRA, G. B.; SPERLING, V. B.; FERREIRA JUNIOR, R. A.; TEODORO, I.REFERENCE EVAPOTRANSPIRATION BY PENMAN-MONTEITH METHOD  FAO56 USING THE ATMOSPHERIC MESOSCALE MODEL WRF- WEATHER RESEARCH AND FORECASTING    2 ABSTRACT The objective of this study was to assess the Reference evapotranspiration (ETo) by the Penman-Monteith method, described in FAO paper No 56 (PM-FAO56) using observed meteorological data and those simulated by the atmospheric model Weather Research and Forecasting (WRF).  For ETo estimate,  meteorological data were collected   (extreme temperature and air humidity, solar radiation and wind speed)   and  data were  simulated  by the WRF in the dry period (January to March and October to December 2008) in Rio Largo region, AL (9°28’02’’ S, 35º49’44’’ W and 127 m). The estimates were evaluated using the determination coefficient (r2) between ETo from observed and simulated data, by the Willmott concordance index (dr) and mean absolute error (MAE). The PM-FAO56 method showed higher sensitivity to net radiation in relation to the aerodynamic terms.  Estimates of ETo were of low precision (r2 = 0.41) and moderate accuracy (dr = 0.77 and MAE = 0.79 mm d-1). Simulations of the radiation components of the WRF model   have to be improved in order to better estimate ETo by the PM-FAO56 method for  the Rio Largo region,  AL. Keywords: Meteorological data, atmospheric modeling, Penman-Monteith.  

Assessment of Planetary Boundary-Layer Schemes in the Weather Research and Forecasting Mesoscale Model Using MATERHORN Field Data

2015 ◽  
Vol 159 (3) ◽  
pp. 589-609 ◽  
Author(s):  
Reneta Dimitrova ◽  
Zachariah Silver ◽  
Tamas Zsedrovits ◽  
Christopher M. Hocut ◽  
Laura S. Leo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Field Data ◽  
Mesoscale Model ◽  
Weather Research And Forecasting ◽  
Weather Research

scholarly journals Evaluating Weather Research and Forecasting (WRF) Model Predictions of Turbulent Flow Parameters in a Dry Convective Boundary Layer

2011 ◽  
Vol 50 (12) ◽  
pp. 2429-2444 ◽  
Author(s):  
Jeremy A. Gibbs ◽  
Evgeni Fedorovich ◽  
Alexander M. J. van Eijk
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Convective Boundary ◽  
Parameterization Schemes ◽  
Model Predictions ◽  
Horizontal Grid ◽  
Weather Research

AbstractWeather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern Great Plains (SGP). The first studied case exhibited a dryline passage during the simulation window, and the second studied case was used to examine the CBL in a post-cold-frontal environment. The model runs were conducted with three boundary layer parameterization schemes (Yonsei University, Mellor–Yamada–Janjić, and asymmetrical convective) commonly employed within the WRF model environment to represent effects of small-scale turbulent transport. A study domain was centered over the Atmospheric Radiation Measurement Program SGP site in Lamont, Oklahoma. Results show that near-surface flow and turbulence parameters are predicted reasonably well with all tested horizontal grid spacings (1, 2, and 4 km) and that value added through refining grid spacing was minimal at best for conditions considered in this study. In accord with this result, it was suggested that the 16-fold increase in computing overhead associated with changing from 4- to 1-km grid spacing was not justified. Therefore, only differences among schemes at 4-km spacing were presented in detail. WRF model predictions generally overestimated the contribution to turbulence generation by mechanical forcing over buoyancy forcing in both studied CBL cases. Nonlocal parameterization schemes were found to match observational data more closely than did the local scheme, although differences among the predictions with all three schemes were relatively small.

Performance Assessment of New Land Surface and Planetary Boundary Layer Physics in the WRF-ARW

2010 ◽  
Vol 49 (4) ◽  
pp. 760-774 ◽  
Author(s):  
Robert C. Gilliam ◽  
Jonathan E. Pleim
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Mesoscale Model ◽  
New Physics ◽  
The Other ◽  
Surface Model ◽  
Temperature Structure ◽  
Near Surface

Abstract The Pleim–Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and have been used extensively by the air quality modeling community, so there was a need based on several factors to extend these parameterizations to WRF. Simulations executed with the new WRF physics are compared with simulations produced with the MM5 and another WRF configuration with a focus on the replication of near-surface meteorological conditions and key planetary boundary layer features. The new physics in WRF is recommended for retrospective simulations, in particular, those used to drive air quality simulations. In the summer, the error of all variables analyzed was slightly lower across the domain in the WRF simulation that used the new physics than in the similar MM5 configuration. This simulation had an even lower error than the other more common WRF configuration. For the cold season case, the model simulation was not as accurate as the other simulations overall, but did well in terms of lower 2-m temperature error in the western part of the model domain (plains and Rocky Mountains) and most of the Northeast. Both MM5 and the other WRF configuration had lower errors across much of the southern and eastern United States in the winter. The 2-m water vapor mixing ratio and 10-m wind were generally well simulated by the new physics suite in WRF when contrasted with the other simulations and modeling studies. Simulated planetary boundary layer features were compared with both wind profiler and aircraft observations, and the new WRF physics results in a more precise wind and temperature structure not only in the stable boundary layer, but also within most of the convective boundary layer. These results suggest that the WRF performance is now at or above the level of MM5. It is thus recommended to drive future air quality applications.

scholarly journals Study of the Thermal Internal Boundary Layer in Sea Breeze Conditions Using Different Parameterizations: Application of the WRF Model in the Greater Vitória Region

2016 ◽  
Vol 31 (4 suppl 1) ◽  
pp. 593-609 ◽  
Author(s):  
Nadir Salvador ◽  
◽  
Ayres G. Loriato ◽  
Alexandre Santiago ◽  
Taciana T.A. Albuquerque ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Wrf Model ◽  
Coastal Region ◽  
Sea Breeze ◽  
Internal Boundary Layer ◽  
Internal Boundary ◽  
Surface Model ◽  
Thermal Internal Boundary Layer ◽  
Local Closure

Abstract In the present study, the physical parameterizations of the Weather Research and Forecasting (WRF) model are verified for making accurate inferences about the dynamics of the Thermal Internal Boundary Layer (TIBL) generated by sea breeze in an urban center with an island in a bay along a coastal region with rugged topography. The simulations were performed using parameterizations from Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ) and Asymmetric Convective Model version 2 (ACM2) for the atmospheric boundary layer (ABL) and Noah and Rapid Update Cycle (RUC) for the Land Surface Model (LSM). The data inferred by the WRF model were compared with those obtained by a Surface Meteorological Station (SMS) and by measurements generated using Light Detection and Ranging (LIDAR), Sonic Detection and Ranging (SODAR) and radiosonde. The simulations showed that although the object of this research was a region with high geographical complexity, the YSU parameterization set (non-local closure) for the ABL and the Noah parameterization for the LSM presented satisfactory results in determining ABL height generated by the sea breeze on the day in question.

scholarly journals Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites

2021 ◽  
Author(s):  
Noéle Bissoli Perini Souza ◽  
Erick Giovani Sperandio Nascimento ◽  
Davidson Martins Moreira
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Weather Research And Forecasting ◽  
Tropical Region ◽  
Surface Model ◽  
Dry And Rainy Seasons

In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.

scholarly journals The Impacts of Soil Moisture Initialization on the Forecasts of Weather Research and Forecasting Model: A Case Study in Xinjiang, China

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1892
Author(s):  
Hailiang Zhang ◽  
Junjian Liu ◽  
Huoqing Li ◽  
Xianyong Meng ◽  
Ablimitijan Ablikim
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Wrf Model ◽  
Specific Humidity ◽  
Water Evaporation ◽  
Weather Research And Forecasting ◽  
Soil Moisture Initialization ◽  
Weather Research

Soil moisture is a critical parameter in numerical weather prediction (NWP) models because it plays a fundamental role in the exchange of water and energy cycles between the atmosphere and the land surface through evaporation. To improve the forecast skills of the Weather Research and Forecasting (WRF) model in Xinjiang, China, this study investigated the impacts of soil moisture initialization on the WRF forecasts by performing a series of simulations. A group of simulations was conducted using the single-column model (SCM) from 1200 UTC on 15 to 18 August 2019, at Urumchi, Xinjiang (43.78° N, 87.6° E); another was performed using the WRF model for a real weather case in Xinjiang from 0000 UTC 15 August to 1200 UTC 18 August 2019, which included an episode of heavy precipitation and gales. Our most notable findings are as follows. Specific humidity increases and potential temperature decreases persistently when soil moisture increases because of soil water evaporation. Soil moisture initialization could impact the energy budget and modulate the partition of the total available energy at the land surface significantly through evaporation and the greenhouse effect. Replacing the soil moisture with a proper multiple of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) soil moisture data could significantly improve the critical success index (CSI) and frequency bias (FBIAS) of precipitation and the root-mean-squared errors (RMSEs) of 2-m specific humidity and 2-m temperature. These findings indicate the prospect of a new way to improve the forecast skills of WRF in Xinjiang or other similar regions.

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