scholarly journals Approaches toward improving the modelling of midlatitude cyclones entering at the lateral boundary corner in the limited area WRF model

2020 ◽  
Vol 146 (732) ◽  
pp. 3225-3244
Author(s):  
Marc Imberger ◽  
Xiaoli Guo Larsén ◽  
Neil Davis ◽  
Jianting Du
Keyword(s):  
Wrf Model ◽  
Limited Area ◽  
Lateral Boundary ◽  
Midlatitude Cyclones

scholarly journals Limited-are a modelling of stratocumulus over South-Eastern Pacific

2012 ◽  
Vol 12 (7) ◽  
pp. 3511-3526 ◽  
Author(s):  
M. Andrejczuk ◽  
W. W. Grabowski ◽  
A. Gadian ◽  
R. Burton
Keyword(s):  
Boundary Layer ◽  
Boundary Conditions ◽  
Vertical Velocity ◽  
Wrf Model ◽  
Eastern Pacific ◽  
Limited Area ◽  
Computational Domain ◽  
Lateral Boundary ◽  
South Eastern ◽  
Lateral Boundary Conditions

Abstract. This paper presents application of the Weather Research and Forecasting (WRF) model to limited-area modeling of atmospheric processes over the subtropical south-eastern Pacific, with the emphasis on the stratocumulus-topped boundary layer. The simulations cover a domain from the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) field project conducted in the subtropical south-eastern Pacific in October and November 2008. We focus on a day where the UK's BAe-146 research aircraft encountered Pockets of Open Cells (POCs) at the very western edge of its flight track, rather than on the entire campaign as investigated in previous limited-area modeling studies. Model results are compared to aircraft observations with the main conclusion that the simulated stratocumulus-topped boundary layer is significantly too shallow. This appears to be a combination of an already too shallow boundary layer in the dataset used to provide initial and lateral boundary conditions, and the inability of the WRF model to increase the boundary-layer height. Several sensitivity simulations, applying different subgrid-scale parameterizations available in the model, a larger computational domain and longer simulations, as well as a different dataset providing initial and lateral boundary conditions were all tried to improve the simulation. These changes appeared to have a rather small effect on the results. The model does simulate the formation of mesoscale cloud-free regions that one might consider similar to Pockets of Open Cells observed in nature. However, formation of these regions does not seem to be related to drizzle-induced transition from open- to closed-cell circulations as simulated by LES models. Instead, the cloud-free regions appear to result from mesoscale variations of the lower-tropspheric vertical velocity. Areas of negative vertical velocity with minima (a few cm s−1) near the boundary layer top seem to induce direct evaporation of the cloud layer. It remains to be seen in LES studies whether the mechanism seen in the model is realistic or if it is simply an artifact of interactions between resolved and parameterized processes.

scholarly journals Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1727
Author(s):  
Valerio Capecchi ◽  
Andrea Antonini ◽  
Riccardo Benedetti ◽  
Luca Fibbi ◽  
Samantha Melani ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Flash Floods ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Heavy Precipitation Event ◽  
The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

Downscaling of a seasonal ensemble forecast at the convection-permitting resolution over the Horn of Africa using the WRF model

2021 ◽  
Author(s):  
Paolo Mori ◽  
Thomas Schwitalla ◽  
Markos Ware ◽  
Kirsten Warrach-Sagi ◽  
Volker Wulfmeyer
Keyword(s):  
Boundary Conditions ◽  
Wrf Model ◽  
Added Value ◽  
Limited Area ◽  
Horn Of Africa ◽  
Ensemble Spread ◽  
Rain Belt ◽  
Physics Ensemble ◽  
June July ◽  
The Right

<p>Studies have shown the benefits of convection-permitting downscaling at the seasonal scale using limited-area models. To evaluate the performance with real forecasts as boundary conditions, four members of the SEAS5 global ensemble were dynamically downscaled over Ethiopia during June, July, and August 2018 at a 3-km resolution. We used a multi‐physics ensemble based on the WRF model to compare the effects of boundary conditions and physics <span><span>parametrization</span></span> producing 16 ensemble members. With ECMWF analyses as a reference, SEAS5 averaged to a +0.17°C bias over Ethiopia whereas WRF resulted in +1.14°C. With respect to precipitation, the WRF model simulated 264 mm compared to 248 mm for SEAS5 and 236 mm for GPM-IMERG. The maximum northward extension of the tropical rain belt decreased by about 2° in both models. Downscaling enhanced the ensemble spread in precipitation by 60% on average, correcting the SEAS5 underdispersion. The WRF ensemble spread over Ethiopia was mostly generated by the perturbed boundary conditions, as their effect is often 50% larger than the physics‐induced variability. The results indicate that boundary condition perturbations are necessary, although not always sufficient, to generate the right amount of ensemble spread in a limited-area model with complex topography. The next step is to use specific methods to calculate the added value provided by the downscaling.</p>

scholarly journals Synoptic-scale conditions and convection-resolving hindcast experiments of a cold-season derecho on 3 January 2014 in western Europe

2019 ◽  
Vol 19 (5) ◽  
pp. 1023-1040 ◽  
Author(s):  
Luca Mathias ◽  
Patrick Ludwig ◽  
Joaquim G. Pinto
Keyword(s):  
Boundary Conditions ◽  
Surface Pressure ◽  
Large Scale ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Cold Season ◽  
Limited Area ◽  
Convective System ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions

Abstract. A major linear mesoscale convective system caused severe weather over northern France, Belgium, the Netherlands and northwestern Germany on 3 January 2014. The storm was classified as a cold-season derecho with widespread wind gusts exceeding 25 m s−1. While such derechos occasionally develop along cold fronts of extratropical cyclones, this system formed in a postfrontal air mass along a baroclinic surface pressure trough and was favoured by a strong large-scale air ascent induced by an intense mid-level jet. The lower-tropospheric environment was characterised by weak latent instability and strong vertical wind shear. Given the poor operational forecast of the storm, we analyse the role of initial and lateral boundary conditions to the storm's development by performing convection-resolving limited-area simulations with operational analysis and reanalysis datasets. The storm is best represented in simulations with high temporally and spatially resolved initial and lateral boundary conditions derived from ERA5, which provide the most realistic development of the essential surface pressure trough. Moreover, simulations at convection-resolving resolution enable a better representation of the observed derecho intensity. This case study is testimony to the usefulness of ensembles of convection-resolving simulations in overcoming the current shortcomings of forecasting cold-season convective storms, particularly for cases not associated with a cold front.

Intercomparison of an Ensemble Kalman Filter with Three- and Four-Dimensional Variational Data Assimilation Methods in a Limited-Area Model over the Month of June 2003

2011 ◽  
Vol 139 (2) ◽  
pp. 566-572 ◽  
Author(s):  
Meng Zhang ◽  
Fuqing Zhang ◽  
Xiang-Yu Huang ◽  
Xin Zhang
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Forecast Error ◽  
Wrf Model ◽  
Warm Season ◽  
Variational Data Assimilation ◽  
Lead Times ◽  
Limited Area ◽  
Forecast Errors

Abstract This study compares the performance of an ensemble Kalman filter (EnKF) with both the three-dimensional and four-dimensional variational data assimilation (3DVar and 4DVar) methods of the Weather Research and Forecasting (WRF) model over the contiguous United States in a warm-season month (June) of 2003. The data assimilated every 6 h include conventional sounding and surface observations as well as data from wind profilers, ships and aircraft, and the cloud-tracked winds from satellites. The performances of these methods are evaluated through verifying the 12- to 72-h forecasts initialized twice daily from the analysis of each method against the standard sounding observations. It is found that 4DVar has consistently smaller error than that of 3DVar for winds and temperature at all forecast lead times except at 60 and 72 h when their forecast errors become comparable in amplitude, while the two schemes have similar performance in moisture at all lead times. The forecast error of the EnKF is comparable to that of the 4DVar at 12–36-h lead times, both of which are substantially smaller than that of the 3DVar, despite the fact that 3DVar fits the sounding observations much more closely at the analysis time. The advantage of the EnKF becomes even more evident at 48–72-h lead times; the 72-h forecast error of the EnKF is comparable in magnitude to the 48-h error of 3DVar/4DVar.

scholarly journals Soil Field Model Interoperability: Challenges and Impact on Screen Temperature Forecast Skill during the Nordic Winter

2012 ◽  
Vol 13 (4) ◽  
pp. 1215-1232 ◽  
Author(s):  
Jørn Kristiansen ◽  
Dag Bjørge ◽  
John M. Edwards ◽  
Gabriel G. Rooney
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Boundary Conditions ◽  
Limited Area ◽  
Lateral Boundary ◽  
Error Source ◽  
Main Error ◽  
Lateral Boundary Conditions ◽  
The Impact ◽  
Grid Length

Abstract The high-resolution (4-km grid length) Met Office (UKMO) Unified Model forecasts driven by the coarser-resolution (8-km grid length) High-Resolution Limited-Area Model (HIRLAM), UM4, often produce significantly colder screen-level (2 m) temperatures in winter over Norway than forecast with HIRLAM itself. To diagnose the main error source of this cold bias this study focuses on the forecast initial and lateral boundary conditions, particularly the initialization of soil moisture and temperature. The soil variables may be used differently by land surface schemes of varying complexity, representing a challenge to model interoperability. In a set of five experiments, daily UM4 forecasts are driven by alternating initial and lateral boundary conditions from two different parent models: HIRLAM and Met Office North Atlantic and Europe (NAE). The experiment period is November 2007. Points for scientific examination into the topics of model interoperability and sensitivity to soil initial conditions are identified. The soil moisture is the main error source and is therefore important also in winter, rather than being a challenge only in summer. The day-to-day variability in the forecast error is large with the larger errors on days with strong longwave heat loss at the surface (i.e., the forecast sensitivity to soil moisture content is significant but variable). The much drier soil in HIRLAM compared to NAE reduces the heat capacity of the soil layers and affects the heat flux from the surface soil layer to the surface. Normalizing the respective soil moisture fields reduces these differences. The impact of ground snow is quite limited.

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