scholarly journals Ensemble Hydrometeorological Forecasts Using WRF Hourly QPF and TopModel for a Middle Watershed

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Leonardo Calvetti ◽  
Augusto José Pereira Filho
Keyword(s):  
Hydrological Model ◽  
Wrf Model ◽  
Relevant Information ◽  
Southern Brazil ◽  
Synoptic Scale ◽  
Ensemble Forecasts ◽  
Rainfall Events ◽  
Phase Errors ◽  
Similar Phase ◽  
Iguaçu River

Quantitative precipitation forecasts (QPFs) were obtained from ensembles of the weather and research forecasting (WRF) model for the Iguaçu river watershed (IRW) in southern Brazil. Thirty-two rainfall events between 2005 and 2010 were simulated with ten configurations of WRF. These rainfall events range from local to synoptic scale convection and caused a significant increase in the level of the Iguaçu river. In the average, the ensembles yielded up to 20% better skill than single WRF forecasts for the events analyzed. WRF ensembles also allow estimating the predictability through the dispersion of the forecasts providing relevant information for decision-making. Phase errors of ensemble forecasts are larger than amplitude errors. More complex microphysics parameterizations yielded better QPFs with smaller phase errors. QPFs were fed to IRW hydrological model with similar phase and amplitude errors. It is suggested that lagged QPFs might reduce phase errors.

scholarly journals Downscaling of seasonal ensemble forecasts to the convection‐permitting scale over the Horn of Africa using the WRF model

2020 ◽  
Author(s):  
Paolo Mori ◽  
Thomas Schwitalla ◽  
Markos Budusa Ware ◽  
Kirsten Warrach‐Sagi ◽  
Volker Wulfmeyer
Keyword(s):  
Wrf Model ◽  
Horn Of Africa ◽  
Ensemble Forecasts

scholarly journals Relationship between the Track and Structural Evolution of Hurricane Sandy (2012) Using a Regional Ensemble

2018 ◽  
Vol 146 (12) ◽  
pp. 4279-4302 ◽  
Author(s):  
Alex M. Kowaleski ◽  
Jenni L. Evans
Keyword(s):  
Large Scale ◽  
Wrf Model ◽  
Structural Evolution ◽  
Hurricane Sandy ◽  
Weather Research And Forecasting ◽  
Extratropical Transition ◽  
Ensemble Forecasts ◽  
High Predictability ◽  
Regression Mixture ◽  
The Relationship

Abstract An ensemble of 72 Weather Research and Forecasting (WRF) Model simulations is evaluated to examine the relationship between the track of Hurricane Sandy (2012) and its structural evolution. Initial and boundary conditions are obtained from ECMWF and GEFS ensemble forecasts initialized at 0000 UTC 25 October. The 5-day WRF simulations are initialized at 0000 UTC 27 October, 48 h into the global model forecasts. Tracks and cyclone phase space (CPS) paths from the 72 simulations are partitioned into 6 clusters using regression mixture models; results from the 4 most populous track clusters are examined. The four analyzed clusters vary in mean landfall location from southern New Jersey to Maine. Extratropical transition timing is the clearest difference among clusters; more eastward clusters show later Sandy–midlatitude trough interaction, warm seclusion formation, and extratropical transition completion. However, the intercluster variability is much smaller when examined relative to the landfall time of each simulation. In each cluster, a short-lived warm seclusion forms and contracts through landfall while lower-tropospheric potential vorticity concentrates at small radii. Despite the large-scale similarity among the clusters, relevant intercluster differences in landfall-relative extratropical transition are observed. In the easternmost cluster the Sandy–trough interaction is least intense and the warm seclusion decays the most by landfall. In the second most eastward cluster Sandy retains the most intact warm seclusion at landfall because of a slightly later (relative to landfall) and weaker trough interaction compared to the two most westward clusters. Nevertheless, the remarkably similar large-scale evolution of Sandy among the four clusters indicates the high predictability of Sandy’s warm seclusion extratropical transition before landfall.

scholarly journals Trends in the Frequency of Intense Precipitation Events in Southern and Southeastern Brazil during 1960–2004

2011 ◽  
Vol 24 (7) ◽  
pp. 1913-1921 ◽  
Author(s):  
Mateus da Silva Teixeira ◽  
Prakki Satyamurty
Keyword(s):  
Extreme Rainfall ◽  
Southeastern Brazil ◽  
Extreme Rainfall Event ◽  
Southern Brazil ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Annual Frequency ◽  
Long Term Trends ◽  
Increasing Trends

Abstract A new approach to define heavy and extreme rainfall events based on cluster analysis and area-average rainfall series is presented. The annual frequency of the heavy and extreme rainfall events is obtained for the southeastern and southern Brazil regions. In the 1960–2004 period, 510 (98) and 466 (77) heavy (extreme) rainfall events are identified in the two regions. Monthly distributions of the events closely follow the monthly climatological rainfall in the two regions. In both regions, annual heavy and extreme rainfall event frequencies present increasing trends in the 45-yr period. However, only in southern Brazil is the trend statistically significant. Although longer time series are necessary to ensure the existence of long-term trends, the positive trends are somewhat alarming since they indicate that climate changes, in terms of rainfall regimes, are possibly under way in Brazil.

scholarly journals Evaluation of WRF Model Simulations of Tornadic and Nontornadic Outbreaks Occurring in the Spring and Fall

2010 ◽  
Vol 138 (11) ◽  
pp. 4098-4119 ◽  
Author(s):  
Chad M. Shafer ◽  
Andrew E. Mercer ◽  
Lance M. Leslie ◽  
Michael B. Richman ◽  
Charles A. Doswell
Keyword(s):  
Wrf Model ◽  
Severe Weather ◽  
Weather Research And Forecasting ◽  
Synoptic Scale ◽  
Sea Level Pressure ◽  
Significant Events ◽  
Skill Scores ◽  
Time Of Year ◽  
Tornado Outbreaks ◽  
Thermodynamic Instability

Abstract Recent studies, investigating the ability to use the Weather Research and Forecasting (WRF) model to distinguish tornado outbreaks from primarily nontornadic outbreaks when initialized with synoptic-scale data, have suggested that accurate discrimination of outbreak type is possible up to three days in advance of the outbreaks. However, these studies have focused on the most meteorologically significant events without regard to the season in which the outbreaks occurred. Because tornado outbreaks usually occur during the spring and fall seasons, whereas the primarily nontornadic outbreaks develop predominantly during the summer, the results of these studies may have been influenced by climatological conditions (e.g., reduced shear, in the mean, in the summer months), in addition to synoptic-scale processes. This study focuses on the impacts of choosing outbreaks of severe weather during the same time of year. Specifically, primarily nontornadic outbreaks that occurred during the summer have been replaced with outbreaks that do not occur in the summer. Subjective and objective analyses of the outbreak simulations indicate that the WRF’s capability of distinguishing outbreak type correctly is reduced when the seasonal constraints are included. However, accuracy scores exceeding 0.7 and skill scores exceeding 0.5 using 1-day simulation fields of individual meteorological parameters, show that precursor synoptic-scale processes play an important role in the occurrence or absence of tornadoes in severe weather outbreaks. Low-level storm-relative helicity parameters and synoptic parameters, such as geopotential heights and mean sea level pressure, appear to be most helpful in distinguishing outbreak type, whereas thermodynamic instability parameters are noticeably both less accurate and less skillful.

scholarly journals Roles of the Synoptic-Scale Wave Train, the Intraseasonal Oscillation, and High-Frequency Eddies in the Genesis of Typhoon Manyi (2001)*

2014 ◽  
Vol 71 (10) ◽  
pp. 3706-3722 ◽  
Author(s):  
Yamei Xu ◽  
Tim Li ◽  
Melinda Peng
Keyword(s):  
High Frequency ◽  
Development Process ◽  
Wave Train ◽  
Wrf Model ◽  
Intraseasonal Oscillation ◽  
Wave Activity ◽  
Weather Research And Forecasting ◽  
Synoptic Scale ◽  
Energy Dispersion ◽  
Multiple Episodes

Abstract Experiments using the Weather Research and Forecasting (WRF) Model were conducted to investigate the effects of multiscale motions on the genesis of Typhoon Manyi (2001) in the western North Pacific. The precursor signal associated with this typhoon genesis was identified as a northwest–southeast-oriented synoptic-scale wave train (SWT). The model successfully simulated the genesis of the typhoon in the wake of the SWT. Further experiments were conducted to isolate the effects of the SWT, the intraseasonal oscillation (ISO), and high-frequency (shorter than 3 days) eddies in the typhoon formation. Removing the SWT in the initial and boundary conditions eliminates the typhoon genesis. This points out the importance of the SWT in the typhoon genesis. It was noted that the SWT strengthened the wake cyclone through southeastward energy dispersion. The strengthening wake cyclone triggered multiple episodes of strong sustained convective updrafts, leading to aggregation of vertical vorticity and formation of a self-amplified mesoscale core vortex through a “bottom up” development process. Removing the ISO flow eliminates the typhoon genesis, as the ISO significantly modulated the strength of the SWT through accumulation of wave activity. In the absence of SWT–ISO-scale interaction, the southeastward energy dispersion was weakened significantly, and thus the strengthening of the wake cyclone did not occur. As a result, the successive strong sustained convective updrafts disappeared. Removing the high-frequency eddies did not eliminate the typhoon genesis but postponed the genesis for about 36 h.

scholarly journals The Use of Moist Potential Vorticity Vector as Diagnostic Variable of Rainfall Events in Tanzania

2017 ◽  
Vol 9 (5) ◽  
pp. 1
Author(s):  
Philbert Modest Luhunga ◽  
Agnes Kijazi ◽  
Ladislaus Chang a ◽  
Chuki A Sangalugembe ◽  
Doreen Mwara Anande ◽  
...  
Keyword(s):  
Potential Vorticity ◽  
Wrf Model ◽  
Lower Troposphere ◽  
Topographic Effects ◽  
New Paradigm ◽  
Rainfall Events ◽  
North Eastern ◽  
Vorticity Vector ◽  
Moist Potential Vorticity ◽  
Thermodynamic Variables

The work of this paper is a first step of the new paradigm, to use the Moist Potential Vorticity Vector (MPVV) as a diagnostic variable of rainfall events in Tanzania. The paper aims at computing and assessing the usefulness of MPVV in the diagnosis of rainfall events that occurred on 08th and 09th May 2017 over different regions in Tanzania. The relative contributions of horizontal, vertical components and the magnitude of MPVV on diagnosis of rainfall events are assessed. Hourly dynamic and thermodynamic variables of wind speed, temperature, atmospheric pressure and relative humidity from the numerical output generated by the Weather Research and Forecasting (WRF) Model, running at Tanzania Meteorological Agency (TMA) are used in computation of MPVV. The computed MPVV is then compared with WRF model forecasts and observed rainfall. It is found that in most parts of the country, particularly over coastal areas and North-Eastern Highlands, MPVV exhibited positive values in the lower troposphere (925hPa) and (850hPa) indicating local instability possibly associated with topographic effects, and continent/ocean contrast. MPVV is mostly positive with slightly negative values indicating instabilities (due to possible convective instability). Moreover, MPVV provides remarkably accurate tracking of the locations received rainfall, suggesting its potential use as a dynamic diagnostic variable of rainfall events in Tanzania.

scholarly journals Impact of a Stochastic Kinetic Energy Backscatter Scheme on Warm Season Convection-Allowing Ensemble Forecasts

2016 ◽  
Vol 144 (5) ◽  
pp. 1887-1908 ◽  
Author(s):  
Jeffrey D. Duda ◽  
Xuguang Wang ◽  
Fanyou Kong ◽  
Ming Xue ◽  
Judith Berner
Keyword(s):  
Kinetic Energy ◽  
Wrf Model ◽  
Warm Season ◽  
Weather Research And Forecasting ◽  
Potential Utility ◽  
Ensemble Forecasts ◽  
Probabilistic Forecasts ◽  
Ensemble Mean ◽  
Central United States ◽  
Surface Observations

The efficacy of a stochastic kinetic energy backscatter (SKEB) scheme to improve convection-allowing probabilistic forecasts was studied. While SKEB has been explored for coarse, convection-parameterizing models, studies of SKEB for convective scales are limited. Three ensembles were compared. The SKMP ensemble used mixed physics with the SKEB scheme, whereas the MP ensemble was configured identically but without using the SKEB scheme. The SK ensemble used the SKEB scheme with no physics diversity. The experiment covered May 2013 over the central United States on a 4-km Weather Research and Forecasting (WRF) Model domain. The SKEB scheme was successful in increasing the spread in all fields verified, especially mid- and upper-tropospheric fields. Additionally, the rmse of the ensemble mean was maintained or reduced, in some cases significantly. Rank histograms in the SKMP ensemble were flatter than those in the MP ensemble, indicating the SKEB scheme produces a less underdispersive forecast distribution. Some improvement was seen in probabilistic precipitation forecasts, particularly when examining Brier scores. Verification against surface observations agree with verification against Rapid Refresh (RAP) model analyses, showing that probabilistic forecasts for 2-m temperature, 2-m dewpoint, and 10-m winds were also improved using the SKEB scheme. The SK ensemble gave competitive forecasts for some fields. The SK ensemble had reduced spread compared to the MP ensemble at the surface due to the lack of physics diversity. These results suggest the potential utility of mixed physics plus the SKEB scheme in the design of convection-allowing ensemble forecasts.

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