Ensemble Variability in Rainfall Forecasts of Hurricane Irene (2011)

2020 ◽  
Vol 35 (5) ◽  
pp. 1761-1781
Author(s):  
Molly B. Smith ◽  
Ryan D. Torn ◽  
Kristen L. Corbosiero ◽  
Philip Pegion
Keyword(s):  
New York ◽  
Initial Conditions ◽  
Storm Track ◽  
Wrf Model ◽  
Moisture Flux ◽  
Weather Research And Forecasting ◽  
Ensemble Forecasts ◽  
Hurricane Irene ◽  
Forecasting System ◽  
Topographic Forcing

AbstractTropical cyclones (TCs) moving into the midlatitudes can produce extreme precipitation, as was the case with Hurricane Irene (2011). Despite the high-impact nature of these events, relatively few studies have explored the sensitivity of TC precipitation forecasts to model initial conditions. Here, the physical processes that modulate precipitation forecasts over the Northeast United States during Irene are investigated using an 80-member 0.5° Global Forecasting System (GFS) ensemble. The members that forecast the highest total precipitation over the Catskill Mountains in New York (i.e., wet members) are compared with the members that predicted the least precipitation (i.e., dry members). Results indicate that the amount of rainfall is tied to storm track, with the wetter members forecast to move farther west than the dry members. This variability in storm track appears to be associated with variability in analyzed upper-tropospheric potential vorticity (PV), such that the wetter members feature greater cyclonic PV southwest of Irene when Irene is off the Carolina coast. By contrast, the wetter members of a 3-km Weather Research and Forecasting (WRF) Model ensemble, initialized from the same GFS ensemble forecasts, show little sensitivity to track. Instead, the wetter members are characterized by stronger lower-tropospheric winds perpendicular to the eastern face of the Catskills, allowing maximum upslope forcing and horizontal moisture flux convergence during the period of heaviest rainfall. The drier members, on the other hand, have the greatest quasigeostrophic forcing for ascent, implying that the members’ differences in mesoscale topographic forcing are the dominant influence on rainfall rate.

Initial Condition Sensitivity of Western Pacific Extratropical Transitions Determined Using Ensemble-Based Sensitivity Analysis

2009 ◽  
Vol 137 (10) ◽  
pp. 3388-3406 ◽  
Author(s):  
Ryan D. Torn ◽  
Gregory J. Hakim
Keyword(s):  
Sensitivity Analysis ◽  
Tropical Cyclone ◽  
Initial Conditions ◽  
Forecast Error ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Initial Condition ◽  
Ensemble Forecasts ◽  
The Relationship

Abstract An ensemble Kalman filter based on the Weather Research and Forecasting (WRF) model is used to generate ensemble analyses and forecasts for the extratropical transition (ET) events associated with Typhoons Tokage (2004) and Nabi (2005). Ensemble sensitivity analysis is then used to evaluate the relationship between forecast errors and initial condition errors at the onset of transition, and to objectively determine the observations having the largest impact on forecasts of these storms. Observations from rawinsondes, surface stations, aircraft, cloud winds, and cyclone best-track position are assimilated every 6 h for a period before, during, and after transition. Ensemble forecasts initialized at the onset of transition exhibit skill similar to the operational Global Forecast System (GFS) forecast and to a WRF forecast initialized from the GFS analysis. WRF ensemble forecasts of Tokage (Nabi) are characterized by relatively large (small) ensemble variance and greater (smaller) sensitivity to the initial conditions. In both cases, the 48-h forecast of cyclone minimum SLP and the RMS forecast error in SLP are most sensitive to the tropical cyclone position and to midlatitude troughs that interact with the tropical cyclone during ET. Diagnostic perturbations added to the initial conditions based on ensemble sensitivity reduce the error in the storm minimum SLP forecast by 50%. Observation impact calculations indicate that assimilating approximately 40 observations in regions of greatest initial condition sensitivity produces a large, statistically significant impact on the 48-h cyclone minimum SLP forecast. For the Tokage forecast, assimilating the single highest impact observation, an upper-tropospheric zonal wind observation from a Mongolian rawinsonde, yields 48-h forecast perturbations in excess of 10 hPa and 60 m in SLP and 500-hPa height, respectively.

scholarly journals Sensitivity of Northern Great Plains Convection Forecasts to Upstream and Downstream Forecast Errors

2017 ◽  
Vol 145 (6) ◽  
pp. 2141-2163 ◽  
Author(s):  
Jeremy D. Berman ◽  
Ryan D. Torn ◽  
Glen S. Romine ◽  
Morris L. Weisman
Keyword(s):  
South Dakota ◽  
Great Plains ◽  
Initial Conditions ◽  
Potential Temperature ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Northern Great Plains ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Convective Initiation

Abstract The role of earlier forecast errors on subsequent convection forecasts is evaluated for a northern Great Plains severe convective event on 11–12 June 2013 during the Mesoscale Predictability Experiment (MPEX) by applying the ensemble-based sensitivity technique to Weather Research and Forecasting (WRF) Model ensemble forecasts with explicit convection. This case was characterized by two distinct modes of convection located 150 km apart in western Nebraska and South Dakota, which formed on either side of an axis of high, lower-tropospheric equivalent potential temperature . Convection forecasts over both regions are found to be sensitive to the position of this axis. The convection in Nebraska is sensitive to the position of the western edge of the axis near an upstream dryline, which modulates the preconvective prior to the diurnal maximum. In contrast, the convection in South Dakota is sensitive to the position of the eastern edge of the axis near a cold front, which also modulates the preconvective in that location. The position of the axis is modulated by the positions of both upstream and downstream mid- to upper-tropospheric potential vorticity anomalies, and can be traced backward in time to the initial conditions. Dropsondes sampling the region prior to convective initiation indicate that ensemble members with better representations of upstream conditions in sensitive regions are associated with better convective forecasts over Nebraska.

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 Assessing the Potential of a Long-Term Climate Forecast for Cuba Using the WRF Model

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lourdes Álvarez-Escudero ◽  
Yandy G. Mayor ◽  
Israel Borrajero-Montejo ◽  
Arnoldo Bezanilla-Morlot
Keyword(s):  
Mesoscale Model ◽  
Initial Conditions ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Weather Research And Forecasting ◽  
Tropical Storms ◽  
Precipitation Regime ◽  
Wide Debate ◽  
One Year ◽  
Cumulative Precipitation

Seasonal climatic prediction studies are a matter of wide debate all over the world. Cuba, a mainly agricultural nation, should greatly benefit from the knowledge, which is available months in advance of the precipitation regime and allows for the proper management of water resources. In this work, a series of six experiments were made with a mesoscale model WRF (Weather Research and Forecasting Model) that produced a 15-month forecast for each month of cumulative precipitation starting at two dates, and for three non-consecutive years with different meteorological characteristics: one dry year (2004), one year that started dry and turned rainy (2005), and one year where several tropical storms occurred (2008). ERA-Interim reanalysis data were used for the initial and border conditions and experiments started 1 month before the beginning of the rainy and the dry seasons, respectively. In a general sense, the experience of using WRF indicated that it was a valid resource for seasonal forecast, since the results obtained were in the same range as those reported by the literature for similar cases. Several limitations were revealed by the results: the forecasts underestimated the monthly cumulative precipitation figures, tropical storms entering through the borders sometimes followed courses different from the real courses inside the working domain, storms that developed inside the domain were not reproduced by WRF, and differences in initial conditions led to significantly different forecasts for the corresponding time steps (nonlinearity). Changing the model parameterizations and initial conditions of the ensemble forecast experiments was recommended.

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.

Impact of Soil Moisture Initialization on Temperature Extreme Detection in the context of Regional Climate Modeling

2020 ◽  
Author(s):  
Matilde García-Valdecasas Ojeda ◽  
Juan José Rosa-Cánovas ◽  
Emilio Romero-Jiménez ◽  
Patricio Yeste ◽  
Sonia R. Gámiz-Fortis ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Weather Research And Forecasting ◽  
Temperature Extremes ◽  
Temperature Extreme ◽  
The Impact

<p>Land surface-related processes play an essential role in the climate conditions at a regional scale. In this study, the impact of soil moisture (SM) initialization on regional climate modeling has been explored by using a dynamical downscaling experiment. To this end, the Weather Research and Forecasting (WRF) model was used to generate a set of high-resolution climate simulations driven by the ERA-Interim reanalysis for a period from 1989 to 2009. As the spatial configuration, two one-way nested domains were used, with the finer domain being centered over the Iberian Peninsula (IP) at a spatial resolution of about 10 km, and nested over a coarser domain that covers the Euro-CORDEX region at 50 km of spatial resolution.</p><p>The sensitivity experiment consisted of two control runs (CTRL) performed using as SM initial conditions those provided by ERA-Interim, and initialized for two different dates times (January and June). Additionally, another set of runs was completed driven by the same climate data but using as initial conditions prescribed SM under wet and dry scenarios.</p><p>The study is based on assessing the WRF performance by comparing the CTRL simulations with those performed with the different prescribed SM, and also, comparing them with the observations from the Spanish Temperature At Daily scale (STEAD) dataset. In this sense, we used two temperature extreme indices within the framework of decadal predictions: the warm spell index (WSDI) and the daily temperature range (DTR).</p><p>These results provide valuable information about the impact of the SM initial conditions on the ability of the WRF model to detect temperature extremes, and how long these affect the regional climate in this region. Additionally, these results may provide a source of knowledge about the mechanisms involved in the occurrence of extreme events such as heatwaves, which are expected to increase in frequency, duration, and magnitude under the context of climate change.</p><p><strong>Keywords</strong>: soil moisture initial conditions, temperature extremes, regional climate, Weather Research and Forecasting model</p><p>Acknowledgments: This work has been financed by the project CGL2017-89836-R (MINECO-Spain, FEDER). The WRF simulations were performed in the Picasso Supercomputer at the University of Málaga, a member of the Spanish Supercomputing Network.</p>

scholarly journals Impact of Coupling an Ocean Model to WRF Nor’easter Simulations

2015 ◽  
Vol 143 (12) ◽  
pp. 4997-5016 ◽  
Author(s):  
Stephen D. Nicholls ◽  
Steven G. Decker
Keyword(s):  
Storm Track ◽  
Wrf Model ◽  
Ocean Model ◽  
Weather Research And Forecasting ◽  
Model Coupling ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Simulated Precipitation ◽  
Ocean Atmosphere ◽  
The Impact

Abstract The impact of ocean–atmosphere coupling and its possible seasonal dependence upon Weather Research and Forecasting (WRF) Model simulations of seven, wintertime cyclone events was investigated. Model simulations were identical aside from the degree of ocean model coupling (static SSTs, 1D mixed layer model, full-physics 3D ocean model). Both 1D and 3D ocean model coupling simulations show that SSTs following the passage of a nor’easter did tend to cool more strongly during the early season (October–December) and were more likely to warm late in the season (February–April). Model simulations produce SST differences of up to 1.14 K, but this change did not lead to significant changes in storm track (<100 km), maximum 10-m winds (<2 m s−1), or minimum sea level pressure (≤5 hPa). Simulated precipitation showed little sensitivity to model coupling, but all simulations did tend to overpredict precipitation extent (bias > 1) and have low-to-moderate threat scores (0.31–0.59). Analysis of the storm environment and the overall simulation failed to reveal any statistically significant differences in model error attributable to ocean–atmosphere coupling. Despite this result, ocean model coupling can reduce dynamical field error at a single level by up to 20%, and this was slightly greater (1%–2%) with 3D ocean model coupling as compared to 1D ocean model coupling. Thus, while 3D ocean model coupling tended to generally produce more realistic simulations, its impact would likely be more profound for longer-term simulations.

Diagnosing Initial Condition Sensitivity of Typhoon Sinlaku (2008) and Hurricane Ike (2008)

2011 ◽  
Vol 139 (10) ◽  
pp. 3224-3242 ◽  
Author(s):  
William A. Komaromi ◽  
Sharanya J. Majumdar ◽  
Eric D. Rappin
Keyword(s):  
Initial Conditions ◽  
Storm Track ◽  
Wrf Model ◽  
Short Wave ◽  
Track Forecast ◽  
Hurricane Ike ◽  
Control Simulation ◽  
Wave Trough ◽  
Local Perturbations ◽  
First Case

Abstract The response of Weather Research and Forecasting (WRF) model predictions of two tropical cyclones to perturbations in the initial conditions is investigated. Local perturbations to the vorticity field in the synoptic environment are created in features considered subjectively to be of importance to the track forecast. The rebalanced analysis is then integrated forward and compared with an unperturbed “control” simulation possessing similar errors to those in the corresponding operational model forecasts. In the first case, Typhoon Sinlaku (2008), the premature recurvature in the control simulation is found to be corrected by a variety of initial perturbations; in particular, the weakening of an upper-level low directly to its north, and the weakening of a remote short-wave trough in the midlatitude storm track. It is suggested that one or both of the short waves may have been initialized too strongly. In the second case, the forecasts for Hurricane Ike (2008) initialized 4 days prior to its landfall in Texas were not sensitive to most remote perturbations. The primary corrections to the track of Ike arose from a weakening of a midlevel ridge directly to its north, and the strengthening of a short-wave trough in the midlatitudes. For both storms, the targets selected by the ensemble transform Kalman filter (ETKF) were often, but not always, consistent with the most sensitive regions found in this study. Overall, the results can be used to retrospectively diagnose features in which the initial conditions require improvement, in order to improve forecasts of tropical cyclone track.

Sensitivity of 24-h Forecast Dryline Position and Structure to Boundary Layer Parameterizations in Convection-Allowing WRF Model Simulations

2015 ◽  
Vol 30 (3) ◽  
pp. 613-638 ◽  
Author(s):  
Adam J. Clark ◽  
Michael C. Coniglio ◽  
Brice E. Coffer ◽  
Greg Thompson ◽  
Ming Xue ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Initial Conditions ◽  
Layer Structure ◽  
Vertical Mixing ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
The North ◽  
Boundary Layer Processes ◽  
Moisture Profiles ◽  
Dry Bias

Abstract Recent NOAA Hazardous Weather Testbed Spring Forecasting Experiments have emphasized the sensitivity of forecast sensible weather fields to how boundary layer processes are represented in the Weather Research and Forecasting (WRF) Model. Thus, since 2010, the Center for Analysis and Prediction of Storms has configured at least three members of their WRF-based Storm-Scale Ensemble Forecast (SSEF) system specifically for examination of sensitivities to parameterizations of turbulent mixing, including the Mellor–Yamada–Janjić (MYJ); quasi-normal scale elimination (QNSE); Asymmetrical Convective Model, version 2 (ACM2); Yonsei University (YSU); and Mellor–Yamada–Nakanishi–Niino (MYNN) schemes (hereafter PBL members). In postexperiment analyses, significant differences in forecast boundary layer structure and evolution have been observed, and for preconvective environments MYNN was found to have a superior depiction of temperature and moisture profiles. This study evaluates the 24-h forecast dryline positions in the SSEF system PBL members during the period April–June 2010–12 and documents sensitivities of the vertical distribution of thermodynamic and kinematic variables in near-dryline environments. Main results include the following. Despite having superior temperature and moisture profiles, as indicated by a previous study, MYNN was one of the worst-performing PBL members, exhibiting large eastward errors in forecast dryline position. During April–June 2010–11, a dry bias in the North American Mesoscale Forecast System (NAM) initial conditions largely contributed to eastward dryline errors in all PBL members. An upgrade to the NAM and assimilation system in October 2011 apparently fixed the dry bias, reducing eastward errors. Large sensitivities of CAPE and low-level shear to the PBL schemes were found, which were largest between 1.0° and 3.0° to the east of drylines. Finally, modifications to YSU to decrease vertical mixing and mitigate its warm and dry bias greatly reduced eastward dryline errors.

scholarly journals The Impact of Assimilating Atmospheric Infrared Sounder Observation on the Forecast of Typhoon Tracks

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Chien-Ben Chou ◽  
Huei-Ping Huang
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Atmospheric Infrared Sounder ◽  
Background Error ◽  
Forecasting System ◽  
Typhoon Tracks ◽  
The Impact ◽  
Decorrelation Scale

This work assesses the effects of assimilating atmospheric infrared sounder (AIRS) observations on typhoon prediction using the three-dimensional variational data assimilation (3DVAR) and forecasting system of the weather research and forecasting (WRF) model. Two major parameters in the data assimilation scheme, the spatial decorrelation scale and the magnitude of the covariance matrix of the background error, are varied in forecast experiments for the track of typhoon Sinlaku over the Western Pacific. The results show that within a wide parameter range, the inclusion of the AIRS observation improves the prediction. Outside this range, notably when the decorrelation scale of the background error is set to a large value, forcing the assimilation of AIRS data leads to degradation of the forecast. This illustrates how the impact of satellite data on the forecast depends on the adjustable parameters for data assimilation. The parameter-sweeping framework is potentially useful for improving operational typhoon prediction.

Sign in / Sign up

Export Citation Format

Share Document