scholarly journals Advances in the WRF model for convection-resolving forecasting

2006 ◽  
Vol 7 ◽  
pp. 25-29 ◽  
Author(s):  
J. B. Klemp
Keyword(s):  
Wrf Model ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Cumulus Parameterization ◽  
Weather Research And Forecasting ◽  
Convective Systems ◽  
Convective Processes ◽  
Forecast Models ◽  
Good Potential ◽  
Mesh Spacing

Abstract. The Weather Research and Forecasting (WRF) Model has been designed to be an efficient and flexible simulation system for use across a broad range of weather-forecast and idealized-research applications. Of particular interest is the use of WRF in nonhydrostatic applications in which moist-convective processes are treated explicitly, thereby avoiding the ambiguities of cumulus parameterization. To evaluate the capabilities of WRF for convection-resolving applications, real-time forecasting experiments have been conducted with 4 km horizontal mesh spacing for both convective systems in the central U.S. and for hurricanes approaching landfall in the southeastern U.S. These forecasts demonstrate a good potential for improving the forecast accuracy of the timing and location of these systems, as well as providing more detailed information on their structure and evolution that is not available in current coarser resolution operational forecast models.

Gravity Waves and Other Mechanisms Modulating the Diurnal Precipitation over One of the Rainiest Spots on Earth: Observations and Simulations in 2016

2020 ◽  
Vol 148 (9) ◽  
pp. 3933-3950
Author(s):  
Johanna Yepes ◽  
John F. Mejía ◽  
Brian Mapes ◽  
Germán Poveda
Keyword(s):  
Diurnal Cycle ◽  
Wrf Model ◽  
Early Morning ◽  
Weather Research And Forecasting ◽  
Near Surface ◽  
Additional Hypothesis ◽  
Convective Systems ◽  
Earth Observations ◽  
Diurnal Rainfall ◽  
Static Energy

ABSTRACT The diurnal cycle of precipitation and thermodynamic profiles over western Colombia are examined in new GPM satellite rainfall products, first-ever research balloon launches during 2016 over both sea and land, and numerical simulations with the Weather Research and Forecasting (WRF) Model. This paper evaluates the Mapes et al. mechanism for midnight–early morning coastal convection that propagates offshore: reduction of inhibition in the crests of lower-tropospheric internal waves. Shipborne balloon launches confirm the evening development of such inhibition by a warm overhang in saturation moist static energy (SMSE) near 700–800 hPa. This feature relaxes overnight, consistent with the disinhibition hypothesis for early morning rains. Over the coastal plain, soundings also show late afternoon increases in near-surface MSE large enough to predominate over the overhang’s inhibition effect, driving a second peak in the rainfall diurnal cycle. Parameterized convection simulations fail to simulate the observed coastal rainfall. Still, during a November 2016 wet spell, a cloud-permitting one-way nested 4 km simulation performs better, simulating morning coastal rainfall. In that simulation, however, early morning cooling in the 700–800 hPa layer appears mainly as a standing signal resembling the local radiative effect rather than as a propagating wave. We consider the additional hypothesis that the offshore propagation of that morning convection could involve advection or wind shear effects on organized convective systems. Strong easterlies at mountaintop level were indeed simulated, but that is one of the model’s strongest biases, so the mechanisms of the model’s partial success in simulating diurnal rainfall remain ambiguous.

Exploring the potential of vegetation information for improving weather forecast performance

2021 ◽  
Author(s):  
Melissa Ruiz ◽  
Sungmin Oh ◽  
Rene Orth ◽  
Gianpaolo Balsamo
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Weather Forecasting ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Spatial And Temporal Variation ◽  
Forecast Errors ◽  
Forecast Performance ◽  
Forecast Models ◽  
Moderate Resolution Imaging Spectroradiometer

<p>The quality of weather forecasts is continuously improving for decades. However, increases in forecast skills have slowed down in recent years. This highlights the importance of exploring new avenues towards future forecast system improvements. Until now, (near) real-time information on vegetation anomalies is not used in most forecasting models. Addressing this gap, we explore the potential of the vegetation state for explaining the spatial and temporal variation in forecast accuracy globally across climate regions, seasons, and vegetation types. For this purpose, we employ re-forecasts from the European Centre of Medium-Range Weather Forecasting (ECMWF) and infer the vegetation status through the Enhanced Vegetation Index derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite observations during the 2000-2019 period. In particular, we focus on land surface variables such as evaporation and temperature to study the relationship between forecast errors and vegetation anomalies.</p><p>The results show a stronger correlation between forecast errors and vegetation anomalies in semi-arid and sub-humid regions during the growing season, which highlights that vegetation information has the potential to help advance weather forecast performance. To put these results into perspective, we will further perform a multivariate analysis to determine the relative roles of vegetation, hydrology and climate in explaining weather forecast errors. Thereby, our results can inform the future development of weather forecast models and underlying data assimilation schemes.</p>

WRF model moisture adjustment method; a case study with winter-time cloudy biases in Xinjiang, China.

2021 ◽  
Author(s):  
Guiting Song ◽  
Robert Huva ◽  
Yu Xing ◽  
Xiaohui Zhong
Keyword(s):  
Weather Prediction ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Adjustment Method ◽  
Surface Irradiance ◽  
Convective Processes ◽  
Systematic Biases ◽  
Nwp Model ◽  
Winter Time

AbstractFor most locations on Earth the ability of a Numerical Weather Prediction (NWP) model to accurately simulate surface irradiance relies heavily on the NWP model being able to resolve cloud coverage and thickness. At horizontal resolutions at or below a few kilometres NWP models begin to explicitly resolve convection and the clouds that arise from convective processes. However, even at high resolutions, biases may remain in the model and result in under- or over-prediction of surface irradiance. In this study we explore the correction of such systematic biases using a moisture adjustment method in tandem with the Weather Research and Forecasting model (WRF) for a location in Xinjiang, China. After extensive optimisation of the configuration of the WRF model we show that systematic biases still exist—in particular for wintertime in Xinjiang. We then demonstrate the moisture adjustment method with cloudy days for January 2019. Adjusting the relative humidity by 12% through the vertical led to a Root Mean Square Error (RMSE) improvement of 57.8% and a 90.5% reduction in bias for surface irradiance.

Lightning super-bolts in Eastern Mediterranean winter thunderstorms

2020 ◽  
Author(s):  
Yoav Yair ◽  
Barry Lynn ◽  
Baruch Ziv ◽  
Mordecai Yaffe
Keyword(s):  
Eastern Mediterranean ◽  
Winter Season ◽  
Wrf Model ◽  
Temporal Distribution ◽  
Weather Forecast ◽  
Global Distribution ◽  
Winter Storms ◽  
Potential Index ◽  
Forecast Models ◽  
Bin Microphysics

<p>Superbolts are defined as lightning flashes that are a thousand times stronger than normal ones, and their occurrence is estimated to be less than 0.001% of total number of lightning on earth. The global distribution of these extremely powerful lightning flashes is remarkably different than that of regular lightning, which are concentrated in the well-known convective "chimneys" in tropical Africa, South-America and the maritime continent in South-East Asia. The physical mechanisms producing these powerful flashes remain unknown, and the puzzle is exacerbated by the fact that they are discovered mostly over oceans, in maritime winter storms.</p><p>The Mediterranean Sea is one of the most prolific regions where super-bolts occur, especially in the months November-January (Holzworth et al., 2019). We analyzed 8 years of lightning data obtained from the Israeli Lightning Detection Network (ILDN), defining a 200kA peak current threshold for superbolts. We mapped the spatial and temporal distribution of superbolts and their monthly frequency in winter season thunderstorms (DJF) in the eastern Mediterranean, and identified the meteorological and microphysical circumstances in such storms.</p><p>Our working hypothesis is that large amounts of desert dust aerosols, coming from the Sahara Desert, are ingested into maritime winter storms over the eastern Mediterranean. The large dust contributes to convective invigoration, enhanced freezing and efficient charge separation, implying that superbolts are more likely to occur in the presence of large dust. We will present the results of simulation conducted using the WRF-ELEC numerical model, and WRF with spectral bin microphysics coupled with Lynn et al.'s (2012) Dynamic Lightning Scheme (DLS) and the Lightning Potential Index (Yair et al., 2010; LPI), for selected case studies when an enhanced fraction of superbolts was observed.</p><p> </p><p>Holzworth, R. H., McCarthy, M. P., Brundell, J. B., Jacobson, A. R., and Rodger, C. J. (2019). Global distribution of superbolts. J. Geophys. Res. Atmos., 124., doi:10.1029/2019JD030975.</p><p>Lynn, B., Y. Yair, C. Price, G. Kelman and A. J. Clark (2012). Predicting cloud-to-ground and intracloud lightning in weather forecast models. Weather and Forecasting, 27, 1470-1488, doi:10.1175/WAF-D-11-00144.1.</p><p>Yair, Y., B. Lynn, C. Price, V. Kotroni, K. Lagouvardos, E. Morin, A. Mugnai, and M. d. C. Llasat (2010). Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields, J. Geophys. Res., 115, D04205, doi:10.1029/2008JD010868</p>

scholarly journals Influences of Horizontal Grid Spacing and Microphysics on WRF Forecasts of Convective Morphology Evolution for Nocturnal MCSs in Weakly Forced Environments

2019 ◽  
Vol 34 (5) ◽  
pp. 1495-1517 ◽  
Author(s):  
Jonathan E. Thielen ◽  
William A. Gallus
Keyword(s):  
Wrf Model ◽  
Forecast Accuracy ◽  
Warm Season ◽  
Grid Spacing ◽  
Convective Systems ◽  
Model Configuration ◽  
Mesoscale Convective ◽  
Microphysical Parameterization ◽  
The Impact ◽  
Horizontal Grid

Abstract Nocturnal mesoscale convective systems (MCSs) are important phenomena because of their contributions to warm-season precipitation and association with severe hazards. Past studies have shown that their morphology remains poorly forecast in current convection-allowing models operating at 3–4-km horizontal grid spacing. A total of 10 MCS cases occurring in weakly forced environments were simulated using the Weather Research and Forecasting (WRF) Model at 3- and 1-km horizontal grid spacings to investigate the impact of increased resolution on forecasts of convective morphology and its evolution. These simulations were conducted using four microphysics schemes to account for additional sensitivities to the microphysical parameterization. The observed and corresponding simulated systems were manually classified into detailed cellular and linear modes, and the overall morphology depiction and the forecast accuracy of each model configuration were evaluated. In agreement with past studies, WRF was found to underpredict the occurrence of linear modes and overpredict cellular modes at 3-km horizontal grid spacing with all microphysics schemes tested. When grid spacing was reduced to 1 km, the proportion of linear systems increased. However, the increase was insufficient to match observations throughout the evolution of the systems, and the accuracy scores showed no statistically significant improvement. This suggests that the additional linear modes may have occurred in the wrong subtypes, wrong systems, and/or at the wrong times. Accuracy scores were also shown to decrease with forecast length, with the primary decrease in score generally occurring during upscale growth in the early nocturnal period.

Object-Based Verification of Precipitation Forecasts. Part II: Application to Convective Rain Systems

2006 ◽  
Vol 134 (7) ◽  
pp. 1785-1795 ◽  
Author(s):  
Christopher Davis ◽  
Barbara Brown ◽  
Randy Bullock
Keyword(s):  
Intensity Distribution ◽  
Wrf Model ◽  
Stage Iv ◽  
Cumulus Parameterization ◽  
High Plains ◽  
Mississippi Valley ◽  
Convective Systems ◽  
Critical Success ◽  
Object Based ◽  
Mesoscale Convective

Abstract The authors develop and apply an algorithm to define coherent areas of precipitation, emphasizing mesoscale convection, and compare properties of these areas with observations obtained from NCEP stage-IV precipitation analyses (gauge and radar combined). In Part II, fully explicit 12–36-h forecasts of rainfall from the Weather Research and Forecasting model (WRF) are evaluated. These forecasts are integrated on a 4-km mesh without a cumulus parameterization. Rain areas are defined similarly to Part I, but emphasize more intense, smaller areas. Furthermore, a time-matching algorithm is devised to group spatially and temporally coherent areas into rain systems that approximate mesoscale convective systems. In general, the WRF model produces too many rain areas with length scales of 80 km or greater. Rain systems typically last too long, and are forecast to occur 1–2 h later than observed. The intensity distribution among rain systems in the 4-km forecasts is generally too broad, especially in the late afternoon, in sharp contrast to the intensity distribution obtained on a coarser grid with parameterized convection in Part I. The model exhibits the largest positive size and intensity bias associated with systems over the Midwest and Mississippi Valley regions, but little size bias over the High Plains, Ohio Valley, and the southeast United States. For rain systems lasting 6 h or more, the critical success index for matching forecast and observed rain systems agrees closely with that obtained in a related study using manually determined rain systems.

scholarly journals Study of NWP parameterizations on extreme precipitation events over Basque Country

2016 ◽  
Vol 13 ◽  
pp. 137-144 ◽  
Author(s):  
Iván R. Gelpi ◽  
Santiago Gaztelumendi ◽  
Sheila Carreño ◽  
Roberto Hernández ◽  
Joseba Egaña
Keyword(s):  
Extreme Precipitation ◽  
Numerical Models ◽  
Basque Country ◽  
Wrf Model ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The Weather Research and Forecasting model (WRF), like other numerical models, can make use of several parameterization schemes. The purpose of this study is to determine how available cumulus parameterization (CP) and microphysics (MP) schemes in the WRF model simulate extreme precipitation events in the Basque Country. Possible combinations among two CP schemes (Kain–Fritsch and Betts–Miller–Janjic) and five MP (WSM3, Lin, WSM6, new Thompson and WDM6) schemes were tested. A set of simulations, corresponding to 21st century extreme precipitation events that have caused significant flood episodes have been compared with point observational data coming from the Basque Country Automatic Weather Station Mesonetwork. Configurations with Kain–Fritsch CP scheme produce better quantity of precipitation forecast (QPF) than BMJ scheme configurations. Depending on the severity level and the river basin analysed different MP schemes show the best behaviours, demonstrating that there is not a unique configuration that solve exactly all the studied events.

scholarly journals Predicting Cloud-to-Ground and Intracloud Lightning in Weather Forecast Models

2012 ◽  
Vol 27 (6) ◽  
pp. 1470-1488 ◽  
Author(s):  
Barry H. Lynn ◽  
Yoav Yair ◽  
Colin Price ◽  
Guy Kelman ◽  
Adam J. Clark
Keyword(s):  
Initial Conditions ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Electrical Energy ◽  
Supercooled Liquid ◽  
Probability Of Detection ◽  
Skill Scores ◽  
Forecast Models ◽  
Cloud To Ground Lightning ◽  
The Impact

Abstract A new prognostic, spatially and temporally dependent variable is introduced to the Weather Research and Forecasting Model (WRF). This variable is called the potential electrical energy (Ep). It was used to predict the dynamic contribution of the grid-scale-resolved microphysical and vertical velocity fields to the production of cloud-to-ground and intracloud lightning in convection-allowing forecasts. The source of Ep is assumed to be the noninductive charge separation process involving collisions of graupel and ice particles in the presence of supercooled liquid water. The Ep dissipates when it exceeds preassigned threshold values and lightning is generated. An analysis of four case studies is presented and analyzed. On the 4-km simulation grid, a single cloud-to-ground lightning event was forecast with about equal values of probability of detection (POD) and false alarm ratio (FAR). However, when lighting was integrated onto 12-km and then 36-km grid overlays, there was a large improvement in the forecast skill, and as many as 10 cloud-to-ground lighting events were well forecast on the 36-km grid. The impact of initial conditions on forecast accuracy is briefly discussed, including an evaluation of the scheme in wintertime, when lightning activity is weaker. The dynamic algorithm forecasts are also contrasted with statistical lightning forecasts and differences are noted. The scheme is being used operationally with the Rapid Refresh (13 km) data; the skill scores in these operational runs were very good in clearly defined convective situations.

scholarly journals The Impact of Cumulus Parameterization Schemes on the Simulation of Tropical Cyclone “Roanu” Over the Bay of Bengal Using WRF Model

2020 ◽  
Vol 68 (1) ◽  
pp. 87-94
Author(s):  
Saifullah ◽  
Md Idris Ali ◽  
Ashik Imran
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
Absolute Error ◽  
Sensitivity Study ◽  
Cumulus Parameterization ◽  
Weather Research And Forecasting ◽  
Sea Level Pressure ◽  
Cumulus Parameterization Schemes ◽  
The Impact

A sensitivity study has been made on cumulus parameterization (CP) schemes of Weather Research and Forecasting (WRF) model for the simulation of tropical cyclone Roanu which formed over Bay of Bengal during May 2016. The model was run for 72 hours with different CP schemes such as Kain–Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell–Freit as Ensemble (GFE), Grell 3D Ensemble (G3E) and Grell–Devenyi (GD) Ensemble schemes to study the variation in track, intensity. The landfall position error is minimum for BMJ scheme but the time delayed only 1.5-5 hours for all schemes except GD scheme. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of minimum sea level pressure and maximum wind speed is smaller for BMJ, GFE, GD schemes. The RMSE-MAE of rainfall is minimum for BMJ and G3E schemes. Except GD scheme all the other schemes give the better result. Dhaka Univ. J. Sci. 68(1): 87-94, 2020 (January)

scholarly journals Precipitation Forecast Experiments Using the Weather Research and Forecasting (WRF) Model at Gray-Zone Resolutions

2018 ◽  
Vol 33 (6) ◽  
pp. 1605-1616 ◽  
Author(s):  
Ji-Young Han ◽  
Song-You Hong
Keyword(s):  
High Resolution ◽  
Model Simulation ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Grid Size ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Gray Zone ◽  
Weather Research

Abstract In the Weather Research and Forecasting (WRF) community, a standard model setup at a grid size smaller than 5 km excludes cumulus parameterization (CP), although it is unclear how to determine a cutoff grid size where convection permitting can be assumed adequate. Also, efforts to improve high-resolution precipitation forecasts in the range of 1–10 km (the so-called gray zone for parameterized precipitation physics) have recently been made. In this study, we attempt to statistically evaluate the skill of a gray-zone CP with a focus on the quantitative precipitation forecast (QPF) in the summertime. A WRF Model simulation with the gray-zone simplified Arakawa–Schubert (GSAS) CP at 3-km spatial resolution over East Asia is evaluated for the summer of 2013 and compared with the results from a conventional setup without CP. A statistical evaluation of the 3-month simulations shows that the GSAS demonstrates a typical distribution of the QPF skill, with high (low) scores and bias in the light (heavy) precipitation category. The WRF without CP seriously suppresses light precipitation events, but its skill for heavier categories is better. Meanwhile, a new set of precipitation data, which is simply averaged precipitation from the two simulations, demonstrates the best skill in all precipitation categories. Bearing in mind that high-resolution QPF requires essential challenges in model components, along with complexity in precipitating convection mechanisms over geographically different regions, this proposed method can serve as an alternative for improving the QPF for practical usage.

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