Showing papers in "Weather and Forecasting in 2012"
TL;DR: In this paper, three radar-based convective modes were assigned to a sample of tornadoes and significant severe thunderstorms reported in the contiguous United States (CONUS) during 2003-11.
Abstract: Radar-based convective modes were assigned to a sample of tornadoes and significant severe thunderstorms reported in the contiguous United States (CONUS) during 2003–11. The significant hail (≥2-in. diameter), significant wind (≥65-kt thunderstorm gusts), and tornadoes were filtered by the maximum event magnitude per hour on a 40-km Rapid Update Cycle model horizontal grid. The filtering process produced 22 901 tornado and significant severe thunderstorm events, representing 78.5% of all such reports in the CONUS during the sample period. The convective mode scheme presented herein begins with three radar-based storm categories: 1) discrete cells, 2) clusters of cells, and 3) quasi-linear convective systems (QLCSs). Volumetric radar data were examined for right-moving supercell (RM) and left-moving supercell characteristics within the three radar reflectivity designations. Additional categories included storms with marginal supercell characteristics and linear hybrids with a mix of supercell and Q...
275 citations
TL;DR: In this article, a sample of 22 901 tornado and significant severe thunderstorm events, filtered on an hourly 40-km grid, was collected for the period 2003-11 across the contiguous United States (CONUS).
Abstract: A sample of 22 901 tornado and significant severe thunderstorm events, filtered on an hourly 40-km grid, was collected for the period 2003–11 across the contiguous United States (CONUS). Convective mode was assigned to each case via manual examination of full volumetric radar data (Part I of this study), and environmental information accompanied each grid-hour event from the hourly objective analyses calculated and archived at the Storm Prediction Center (SPC). Sounding-derived parameters related to supercells and tornadoes formed the basis of this investigation owing to the dominance of right-moving supercells in tornado production and the availability of supercell-related convective parameters in the SPC environmental archive. The tornado and significant severe thunderstorm events were stratified by convective mode and season. Measures of buoyancy discriminated most strongly between supercell and quasi-linear convective system (QLCS) tornado events during the winter, while bulk wind differences ...
235 citations
TL;DR: In this paper, the authors quantify the spatial and temporal characteristics of contiguous United States (CONUS) hail fall, derived from multiradar multisensor (MRMS) algorithms for several years during the Next-Generation Weather Radar (NEXRAD) era, leveraging the Multiyear Reanalysis of Remotely Sensed Storms (MYRORSS) dataset at NOAA's National Severe Storms Laboratory (NSSL).
Abstract: The threat of damaging hail from severe thunderstorms affects many communities and industries on a yearly basis, with annual economic losses in excess of $1 billion (U.S. dollars). Past hail climatology has typically relied on the National Oceanic and Atmospheric Administration/National Climatic Data Center’s (NOAA/NCDC) Storm Data publication, which has numerous reporting biases and nonmeteorological artifacts. This research seeks to quantify the spatial and temporal characteristics of contiguous United States (CONUS) hail fall, derived from multiradar multisensor (MRMS) algorithms for several years during the Next-Generation Weather Radar (NEXRAD) era, leveraging the Multiyear Reanalysis of Remotely Sensed Storms (MYRORSS) dataset at NOAA’s National Severe Storms Laboratory (NSSL). The primary MRMS product used in this study is the maximum expected size of hail (MESH). The preliminary climatology includes 42 months of quality controlled and reprocessed MESH grids, which spans the warm seasons fo...
166 citations
TL;DR: In this paper, an attempt is made to quantify the position uncertainty using National Hurricane Center (NHC) advisory information, as well as intensity uncertainty during times without aircraft data, by verifying Dvorak minimum sea level pressure (SLP) and maximum wind speed estimates during times with aircraft reconnaissance information during 2000-09.
Abstract: With the growing use of tropical cyclone (TC) best-track information for weather and climate applications, it isimportanttounderstandthe uncertaintiesthatare containedin the TCpositionandintensityinformation. Here, an attempt is made to quantify the position uncertainty using National Hurricane Center (NHC) advisory information, as well as intensity uncertainty during times without aircraft data, by verifying Dvorak minimum sea level pressure (SLP) and maximum wind speed estimates during times with aircraft reconnaissanceinformationduring2000‐09.Inaclimatologicalsense,TCpositionuncertaintydecreasesformore intense TCs, while the uncertainty of intensity, measured by minimum SLP or maximum wind speed, increases with intensity. The standard deviation of satellite-based TC intensity estimates can be used as a predictor of the consensus intensity error when that consensus includes both Dvorak and microwave-based estimates, but not when it contains only Dvorak-based values. Whereas there has been a steady decrease in seasonal TC position uncertainty overthe past 10 yr, whichis likely due toadditionaldata available toNHC forecasters, the seasonal TC minimum SLP and maximum wind speed values are fairly constant, with year-to-year variability due to the mean intensity of all TCs during that season and the frequency of aircraft reconnaissance.
141 citations
TL;DR: In this paper, an experimental version of the Hurricane Weather Research and Forecasting system (HWRFX) for 87 cases of Atlantic tropical cyclones during the 2005, 2007, and 2009 hurricane seasons was used to study the influence of model grid resolution, initial conditions and physics.
Abstract: This paper provides an account of the performance of an experimental version of the Hurricane Weather Research and Forecasting system (HWRFX) for 87 cases of Atlantic tropical cyclones during the 2005, 2007, and 2009 hurricane seasons. The HWRFX system was used to study the influence of model grid resolution, initialconditions, andphysics.For eachcase,themodelwasruntoproduce126 hofforecastwithtwoversions of horizontal resolution, namely, (i) a parent domain at a resolution of about 27 km with a 9-km moving nest (27:9) and (ii) a parent domain at a resolution of 9 km with a 3-km moving nest (9:3). The former was selected to be consistentwith the current operational resolution, while the latter is the first step in testing the impact of finer resolutions for future versions of the operational model. The two configurations were run with initial conditions for tropical cyclones obtained from the operational Geophysical Fluid Dynamics Laboratory (GFDL)and HWRF models.Sensitivity experimentswere also conductedwith the physical parameterization scheme. The study shows that the 9:3 HWRFX system using the GFDL initial conditions and a system of physics similar to the operational version (HWRF) provides the best results in terms of both track and intensity prediction. Use of the HWRF initial conditions in the HWRFX model provides reasonable skill, particularly when used in cases with initially strong storms (hurricane strength). However, initially weak storms (below hurricane strength) posed special challenges for the models. For the weaker storm cases, none of the predictions from the HWRFX runs or the operational GFDL forecasts provided any consistent improvement when compared to the operational Statistical Hurricane Intensity Prediction Scheme with an inland decay component (DSHIPS).
129 citations
TL;DR: In this article, a sample of 448 significant tornado events was collected, representing a population of 1072 individual tornadoes across the contiguous United States from 2000 to 2008, with the majority classified as discrete cells compared to quasi-linear convective systems and clusters.
Abstract: A sample of 448 significant tornado events was collected, representing a population of 1072 individual tornadoes across the contiguous United States from 2000 to 2008. Classification of convective mode was assessed from radar mosaics for each event with the majority classified as discrete cells compared to quasi-linear convective systems and clusters. These events were further stratified by season and region and compared with a null-tornado database of 911 significant hail and wind events that occurred without nearby tornadoes. These comparisons involved 1) environmental variables that have been used through the past 25–50 yr as part of the approach to tornado forecasting, 2) recent sounding-based parameter evaluations, and 3) convective mode. The results show that composite and kinematic parameters (whether at standard pressure levels or sounding derived), along with convective mode, provide greater discrimination than thermodynamic parameters between significant tornado versus either significant...
117 citations
TL;DR: A gridded, hourly, three-dimensionalenvironmental mesoanalysis database at the Storm Prediction Center (SPC), based on objectively analyzed surface observations blended with the Rapid Update Cycle (RUC) model-analysis fields and described in Parts I and II of this series, is applied to a 2003-11 subset of the SPC tropical cyclone (TC) tornado records as mentioned in this paper.
Abstract: A gridded, hourly, three-dimensionalenvironmental mesoanalysis databaseat the Storm Prediction Center (SPC), based on objectively analyzed surface observations blended with the Rapid Update Cycle (RUC) model-analysis fields and described in Parts I and II of this series, is applied to a 2003‐11 subset of the SPC tropical cyclone (TC) tornado records. Distributions of environmental convective parameters, derived from SPC hourly mesoanalysis fields that have been related to supercells and tornadoes in the midlatitudes, are evaluated for their pertinence to TC tornado occurrence. The main factor differentiating TC from non-TC tornadoenvironments ismuchgreater deep-troposphericmoisture,associatedwith reducedlapserates,lower CAPE, and smaller and more compressed distributions of parameters derived from CAPE and vertical shear. For weak and strong TC tornado categories (EF0‐EF1 and EF2‐EF3 on the enhanced Fujita scale, respectively), little distinction is evident across most parameters. Radar reflectivity and velocity data also are examined for the same subset of TC tornadoes, in order to determine parent convective modes (e.g., discrete, linear, clustered, supercellular vs nonsupercellular), and the association of those modes with several mesoanalysis parameters. Supercellular TC tornadoes are accompanied by somewhat greater vertical shear than those occurring from other modes. Tornadoes accompanying nonsupercellular radar echoes tend to occur closer to the TC center, where CAPE and shear tend to weaken relative to the outer TC envelope, though there is considerable overlap of their respective radial distributions and environmental parameter spaces.
106 citations
TL;DR: A comparison between the operational and the bias-corrected reforecast ensembles shows that the climate mean bias correction can add value, especially for week-2 probability forecasts.
Abstract: The main task of this study is to introduce a statistical postprocessing algorithm to reduce the bias in the National Centers for Environmental Prediction (NCEP) and Meteorological Service of Canada (MSC) ensemble forecasts before they are merged to form a joint ensemble within the North American Ensemble Forecast System (NAEFS). This statistical postprocessing method applies a Kalman filter type algorithm to accumulate the decaying averaging bias and produces bias-corrected ensembles for 35 variables. NCEP implemented this bias-correction technique in 2006. NAEFS is a joint operational multimodel ensemble forecast system that combines NCEP and MSC ensemble forecasts after bias correction. According to operational statistical verification, both the NCEP and MSC bias-corrected ensemble forecast products are enhanced significantly. In addition to the operational calibration technique, three other experiments were designed to assess and mitigate ensemble biases on the model grid: a decaying averaging bias calibration method with short samples, a climate mean bias calibration method, and a bias calibration method using dependent data. Preliminary results show that the decaying averaging method works well for the first few days. After removing the decaying averaging bias, the calibrated NCEP operational ensemble has improved probabilistic performance for all measures until day 5. The reforecast ensembles from the Earth System Research Laboratory’s Physical Sciences Division with and without the climate mean bias correction were also examined. A comparison between the operational and the bias-corrected reforecast ensembles shows that the climate mean bias correction can add value, especially for week-2 probability forecasts.
89 citations
TL;DR: In this article, the performance of the Weather Research and Forecasting Model (WRF) in forecasting precipitation, hurricane track, and landfall time using various microphysics and cumulus schemes was investigated.
Abstract: Numerical weather prediction models play a major role in weather forecasting, especially in cases of extreme events. The Weather Research and Forecasting Model (WRF), among others, is extensively used for both research and practical applications. Previous studies have highlighted the sensitivity of this model to microphysics and cumulus schemes. This study investigated the performance of the WRF in forecasting precipitation, hurricane track, and landfall time using various microphysics and cumulus schemes. A total of 20 combinations of microphysics and cumulus schemes were used, and the model outputs were validated against ground-based observations. While the choice of microphysics and cumulus schemes can significantly impact model output, it is not the case that any single combination can be considered “ideal” for modeling all characteristics of a hurricane, including precipitation amount, areal extent, hurricane track, and the time of landfall. For example, the model’s ability to simulate precip...
85 citations
TL;DR: In this paper, the authors evaluated the impact of outer loop and partial cycling with the Weather Research and Forecasting Model's (WRF) three-dimensional variational data assimilation system (3DVAR) by analyzing 78 forecasts for three typhoons during 2008 for which Taiwan's Central Weather Bureau (CWB) issued typhoon warnings, including Sinlaku, Hagupit, and Jangmi.
Abstract: In this paper, the impact of outer loop and partial cycling with the Weather Research and Forecasting Model’s (WRF) three-dimensional variational data assimilation system (3DVAR) is evaluated by analyzing 78 forecasts for three typhoons during 2008 for which Taiwan’s Central Weather Bureau (CWB) issued typhoon warnings, including Sinlaku, Hagupit, and Jangmi. The use of both the outer loop and the partial cycling approaches in WRF 3DVAR are found to reduce typhoon track forecast errors by more than 30%, averaged over a 72-h period. The improvement due to the outer loop approach, which can be more than 42%, was particularly significant in the early phase of the forecast. The use of the outer loop allows more observations to be assimilated and produces more accurate analyses. The assimilation of additional nonlinear GPS radio occultation (RO) observations over the western North Pacific Ocean, where traditional observational data are lacking, is particularly useful. With the lack of observations over...
84 citations
TL;DR: In this article, a 3D object identification algorithm is applied to high-resolution forecasts of hourly maximum updraft helicity (UH) with the goal of diagnosing the relationship between forecast UH objects and observed tornado pathlengths.
Abstract: A three-dimensional (in space and time) object identification algorithm is applied to high-resolution forecasts of hourly maximum updraft helicity (UH)—a diagnostic that identifies simulated rotating storms—with the goal of diagnosing the relationship between forecast UH objects and observed tornado pathlengths. UH objects are contiguous swaths of UH exceeding a specified threshold. Including time allows tracks to span multiple hours and entire life cycles of simulated rotating storms. The object algorithm is applied to 3 yr of 36-h forecasts initialized daily from a 4-km grid-spacing version of the Weather Research and Forecasting Model (WRF) run in real time at the National Severe Storms Laboratory (NSSL), and forecasts from the Storm Scale Ensemble Forecast (SSEF) system run by the Center for Analysis and Prediction of Storms for the 2010 NOAA Hazardous Weather Testbed Spring Forecasting Experiment. Methods for visualizing UH object attributes are presented, and the relationship between pathlen...
TL;DR: Wang et al. as discussed by the authors used the China Meteorological Administration (CMA) and National Centers for Environmental Prediction (NCEP) reanalysis datasets to examine the large-scale characteristics of rapidly intensifying western North Pacific tropical cyclones (TCs).
Abstract: The China Meteorological Administration (CMA) and the National Centers for Environmental Prediction (NCEP) reanalysis datasets are employed to examine the large-scale characteristics of rapidly intensifying western North Pacific tropical cyclones (TCs). The results show that of all 27 581 samples for the period 1970–2007, 85%, 65%, and 47% of all tropical depressions (TDs), tropical storms (TSs), and typhoons (TYs), respectively, intensify. Of the 1214 TCs, 18%, 70%, 30%, and 10% of all tropical cyclones, supertyphoons, severe typhoons, and typhoons, respectively, underwent rapid intensification (RI) at least once during their lifetime. Three kinds of cases—RI, slow change in intensity (SC), and rapid decay (RD)—during the period 1982–2007 are used to analyze the large-scale conditions associated with them. The comparison shows that the RI cases tend to occur farther south and east than the non-RI cases. In addition, the RI cases have a more westerly component of motion and intensify more during t...
TL;DR: In this paper, two statistical prediction schemes were developed to include the interannual increment approach to improve the seasonal prediction of the EASM strength, and the schemes were applied to three models [i.e., the Centre National de Recherches Meteorologiques (CNRM), the Met Office (UKMO), and the European Centre for Medium-Range Weather Forecasts (ECMWF)] and the Multimodel Ensemble (MME) from the Development of a European Multi-Modeling Ensemble System for Seasonal-to-Interannual
Abstract: East Asian summer monsoon (EASM) prediction is difficult because of the summer monsoon’s weak and unstable linkage with El Nino–Southern Oscillation (ENSO) interdecadal variability and its complicated association with high-latitude processes. Two statistical prediction schemes were developed to include the interannual increment approach to improve the seasonal prediction of the EASM’s strength. The schemes were applied to three models [i.e., the Centre National de Recherches Meteorologiques (CNRM), the Met Office (UKMO), and the European Centre for Medium-Range Weather Forecasts (ECMWF)] and the Multimodel Ensemble (MME) from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) results for 1961–2001. The inability of the three dynamical models to reproduce the weakened East Asian monsoon at the end of the 1970s leads to low prediction ability for the interannual variability of the EASM. Therefore, the interannual increment prediction approach wa...
TL;DR: In this article, the authors evaluated the performance of flash-flood guidance (FFG) values and recently developed gridded FFG (GFFG), used by the National Weather Service (NWS) to monitor and predict imminent flash flooding, which is the leading stormrelated cause of death in the United States.
Abstract: This paper evaluates, for the first time, flash-flood guidance (FFG) values and recently developed gridded FFG (GFFG) used by the National Weather Service (NWS) to monitor and predict imminent flash flooding, which is the leading storm-related cause of death in the United States. It is envisioned that results from this study will be used 1) to establish benchmark performance of existing operational flash-flood prediction tools and2)to provideinformation toNWSforecastersthatrevealshow theexistingtools canbe readilyoptimized. Sources used to evaluate the products include official reports of flash floods from the NWS Storm Data database, discharge measurements on small basins available from the U.S. Geological Survey, and witness reports of flash flooding collected during the Severe Hazards Analysis and Verification Experiment. Results indicated that the operational guidance values, with no calibration, were marginally skillful, with the highest criticalsuccessindexof0.20 occurringwith3-h GFFG.Thefalse-alarm ratesfell andtheskill improvedto0.34 when the rainfall was firstspatially averaged within basins and then reached 50% of FFG for 1-h accumulation and exceeded 3-h FFG. Although the skill of the GFFG values was generally lower than that of their FFG counterparts,GFFGwascapableofdetectingthespatialvariabilityofreportedflashfloodingbetterthanFFG was for a case study in an urban setting.
TL;DR: In this paper, an objective satellite-based overshooting-top (OT) detection product has been developed using 11-mm infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager.
Abstract: Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-mm infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (,200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April‐September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severeweatherreportshadeitheranOTdetectedbeforeasevereweatherwarningor nowarningissuedat all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.
TL;DR: In this paper, the ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST) was compared with two-tiered systems where prescribed sea surface temperature (SST) anomalies were used to force the atmospheric general circulation model.
Abstract: Forecast performance by coupled ocean–atmosphere or one-tiered models predicting seasonal rainfall totals over South Africa is compared with forecasts produced by computationally less demanding two-tiered systems where prescribed sea surface temperature (SST) anomalies are used to force the atmospheric general circulation model. Two coupled models and one two-tiered model are considered here, and they are, respectively, the ECHAM4.5–version 3 of the Modular Ocean Model (MOM3-DC2), the ECHAM4.5-GML–NCEP Coupled Forecast System (CFSSST), and the ECHAM4.5 atmospheric model that is forced with SST anomalies predicted by a statistical model. The 850-hPa geopotential height fields of the three models are statistically downscaled to South African Weather Service district rainfall data by retroactively predicting 3-month seasonal rainfall totals over the 14-yr period from 1995/96 to 2008/09. Retroactive forecasts are produced for lead times of up to 4 months, and probabilistic forecast performance is evaluated for three categories with the outer two categories, respectively, defined by the 25th and 75th percentile values of the climatological record. The resulting forecast skill levels are also compared with skill levels obtained by downscaling forecasts produced by forcing the atmospheric model with simultaneously observed SST in order to produce a reference forecast set. Downscaled forecasts from the coupled systems generally outperform the downscaled forecasts from the twotiered system, but neither of the two systems outscores the reference forecasts, suggesting that further improvement in operational seasonal rainfall forecast skill for South Africa is still achievable.
TL;DR: In this article, a new variable called the potential electrical energy (Ep) was introduced 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.
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.
TL;DR: In this paper, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region, and the results showed that the predictability achieved from the MAPLE model depends on the spatial structure of the precipitation patterns.
Abstract: In this study, a Lagrangian radar echo extrapolation scheme (MAPLE) was tested for use in very short-term forecasting of precipitation over a complex orographic region. The high-resolution forecasts from MAPLE for lead times of 5 min–5 h are evaluated against the radar observations for 20 summer rainfall events by employing a series of categorical, continuous, and neighborhood evaluation techniques. The verification results are then compared with those from Eulerian persistence and high-resolution numerical weather prediction model [the Consortium for Small-scale Modeling model (COSMO2)] forecasts. The forecasts from the MAPLE model clearly outperformed Eulerian persistence forecasts for all the lead times, and had better skill compared to COSMO2 up to lead time of 3 h on average. The results also showed that the predictability achieved from the MAPLE model depends on the spatial structure of the precipitation patterns. This study is a first implementation of the MAPLE model over a complex Alpine ...
TL;DR: In this paper, two parallel experiments were designed to evaluate whether assimilating microwave radiances with a cyclic, limited-area ensemble adjustment Kalman filter (EAKF) could improve track, intensity, and precipitation forecasts of Typhoon Morakot (2009).
Abstract: Two parallel experiments were designed to evaluate whether assimilating microwave radiances with a cyclic, limited-area ensemble adjustment Kalman filter (EAKF) could improve track, intensity, and precipitation forecasts of Typhoon Morakot (2009). The experiments were configured identically, except that one assimilated microwave radiances and the other did not. Both experiments produced EAKF analyses every 6 h between 1800 UTC 3 August and 1200 UTC 9 August 2009, and the mean analyses initialized 72-h Weather Research and Forecasting model forecasts. Examination of individual forecasts and average error statistics revealed that assimilating microwave radiances ultimately resulted in better intensity forecasts compared to when radiances were withheld. However, radiance assimilation did not substantially impact track forecasts, and the impact on precipitation forecasts was mixed. Overall, net positive results suggest that assimilating microwave radiances with a limited-area EAKF system is beneficial...
TL;DR: In this article, an improvement to the objective deviation angle variance technique to estimate the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic basin has been described, where the major change described here is to use the National Hurricane Center's best-track database to constrain the technique.
Abstract: This paper describes results from an improvement to the objective deviation angle variance technique to estimate the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic basin. The technique quantifies the level of organization of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The major change described here is to use the National Hurricane Center’s best-track database to constrain the technique. Results are shown for the 2004–10 North Atlantic hurricane seasons and include an overall root-mean-square intensity error of 12.9 kt (6.6 m s−1, where 1 kt = 0.514 m s−1) and annual root-mean-square intensity errors ranging from 10.3 to 14.1 kt. A direct comparison between the previous version and the one reported here shows root-mean-square intensity error improvements in all years with a best improvement in 2009 from 17.9 to 10.6 kt and an overall improvement from 14.8 to 12.9 kt. In addition, samples from the 7-y...
TL;DR: Analysis of rapid-scan weather radars revealed that teams examining the same data sometimes came to different conclusions about whether and when to...
Abstract: Rapid-scan weather radars, such as the S-band phased array radar at the National Weather Radar Testbed in Norman, Oklahoma, improve precision in the depiction of severe storm processes. To explore potential impacts of such data on forecaster warning decision making, 12 National Weather Service forecasters participated in a preliminary study with two control conditions: 1) when radar scan time was similar to volume coverage pattern 12 (4.5 min) and 2) when radar scan time was faster (43 s). Under these control conditions, forecasters were paired and worked a tropical tornadic supercell case. Their decision processes were observed and audio was recorded, interactions with data displays were video recorded, and the products were archived. A debriefing was conducted with each of the six teams independently and jointly, to ascertain the forecaster decision-making process. Analysis of these data revealed that teams examining the same data sometimes came to different conclusions about whether and when to...
TL;DR: In this paper, the authors compared methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium for Small-Scale Modeling (COSMO-DE) time-lagged ensemble.
Abstract: Statistical postprocessing is an integral part of an ensemble prediction system. This study compares methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium for Small-Scale Modeling (COSMO-DE) time-lagged ensemble (COSMO-DE-TLE). The investigation covers the period from July 2008 to June 2011 for a region over northern Germany with rain gauge measurements from 445 stations. The investigated methods provide pointwise estimates of the predictive distribution using logistic and quantile regression, and full predictive distributions using parametric mixture models. All mixture models use a point mass at zero to represent the probability of precipitation. The amount of precipitation is modeled by either a gamma, lognormal, or inverse Gaussian distribution. Furthermore, an adaptive tail using a generalized Pareto distribution (GPD) accounts for a better representation of extreme precipitation. The predictive probabil...
TL;DR: The authors examined the environmental factors controlling the frequency, occurrence, and morphology of GSLE precipitation events using WSR-88D imagery, radiosonde soundings, and MesoWest surface observations from 1997/98 to 2009/10.
Abstract: This climatology examines the environmental factors controlling the frequency, occurrence, and morphology of Great Salt Lake–effect (GSLE) precipitation events using cool season (16 September–15 May) Weather Surveillance Radar-1988 Doppler (WSR-88D) imagery, radiosonde soundings, and MesoWest surface observations from 1997/98 to 2009/10. During this period, the frequency of GSLE events features considerable interannual variability that is more strongly correlated to large-scale circulation changes than lake-area variations. Events are most frequent in fall and spring, with a minimum in January when the climatological lake surface temperature is lowest. Although forecasters commonly use a 16°C lake–700-hPa temperature difference (ΔT) as a threshold for GSLE occurrence, GSLE was found to occur in winter when ΔT was only 12.4°C. Conversely, GSLE is associated with much higher values of ΔT in the fall and spring. Therefore, a seasonally varying threshold based on a quadratic fit to the monthly minimum...
TL;DR: The authors used radiosonde observations obtained during the second phase of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) to verify base-state variables and severe-weather-related parameters calculated from Rapid Update Cycle (RUC) analyses and 1-h forecasts, as well as those calculated from the operational surface objective analysis system used at the Storm Prediction Center (the SFCOA).
Abstract: This study uses radiosonde observations obtained during the second phase of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) to verify base-state variables and severe-weather-related parameters calculated from Rapid Update Cycle (RUC) analyses and 1-h forecasts, as well as those calculated from the operational surface objective analysis system used at the Storm Prediction Center (the SFCOA). The rapid growth in temperature, humidity, and wind errors from 0 to 1 h seen at all levels in a past RUC verification study by Benjamin et al. is not seen in the present study. This could be because the verification observations are also assimilated into the RUC in the Benjamin et al. study, whereas the verification observations in the present study are not. In the upper troposphere, the present study shows large errors in relative humidity, mostly related to a large moist bias. The planetary boundary layer tends to be too shallow in the RUC analyses and 1-h forecasts. Wind speeds...
TL;DR: In this paper, the sensitivity of 0-12h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and without radar data, is investigated for a 6-day period during the International H2O Project.
Abstract: Sensitivity of 0–12-h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and without radar data, is investigated for a 6-day period during the International H2O Project. Neighborhood-based precipitation verification is used to compare forecasts made with the Advanced Research core of the Weather Research and Forecasting Model (ARW-WRF). Three significant convective episodes are examined by comparing the precipitation patterns and locations from different forecast experiments. From two of these three case studies, causes for the success and failure of the RC data assimilation in improving forecast skill are shown. Results indicate that the use of higher-resolution analysis in the initialization, rapid update cycling via WRF 3DVAR data assimilation, and the additional assimilation of radar observations each play a role in shortening th...
TL;DR: In this paper, the beneficial impacts of high-resolution (in space and time) wind and temperature observations from aircraft on very short-range numerical weather forecasting are presented, where the observations are retrieved using the tracking and ranging radar from the air traffic control facility at Schiphol Airport, Amsterdam, the Netherlands.
Abstract: In this paper the beneficial impacts of high-resolution (in space and time) wind and temperature observations from aircraft on very short-range numerical weather forecasting are presented. The observations are retrieved using the tracking and ranging radar from the air traffic control facility at Schiphol Airport, Amsterdam, the Netherlands. This enhanced surveillance radar tracks all aircraft in sight every 4 s, generating one million wind and temperature observations per day in a radius of 270 km around the radar. Nowcasting applications will benefit from improved three-dimensional wind fields. When these observations are assimilated into a numerical model with an hourly update cycle, the short-range three-dimensional wind field forecasts match the observations better than those from an operational forecast cycle, which is updated every 3 h. The positive impact on wind in the first hours of the forecast gradually turns into a neutral impact, when compared to other wind and temperature observatio...
TL;DR: In this article, the authors used synthetic infrared satellite imagery to characterize model-simulated large-scale precursors to the formation of deep-convective storms as well as the subsequent development of storm systems.
Abstract: Output from a real-time high-resolution numerical model is used to generate synthetic infrared satellite imagery. It is shown that this imagery helps to characterize model-simulated large-scale precursors to the formation of deep-convective storms as well as the subsequent development of storm systems. A strategy for using this imagery in the forecasting of severe convective weather is presented. This strategy involves comparing model-simulated precursors to their observed counterparts to help anticipate model errors in the timing and location of storm formation, while using the simulated storm evolution as guidance.
TL;DR: The TCVitals’ limitations must first be quantitatively understood so that model developers can take them into account, and that is the motivation for the present study, which compares theTCVitals storm location and structure information.
Abstract: This study analyzes the Tropical Cyclone Vitals Database (TCVitals), which contains cyclone location, intensity, and structure information, generated in real time by forecasters. These data are used to initialize cyclones in several NCEP operational forecasting models via bogusing and vortex relocation methods. In many situations, time is of the essence and the TCVitals database represents the best real-time estimate of the cyclone state possible in real time, given the limitations of available data and time constraints inherent in real-time forecasting. NCEP and other users of TCVitals have a responsibility to work around the inevitable limitations of what forecasters can do for TCVitals in real time. With ensemble systems becoming available, a way to do that will soon be available. However, the TCVitals’ limitations must first be quantitatively understood so that model developers can take them into account. That is the motivation for the present study, which compares the TCVitals storm location ...
TL;DR: In this article, the authors assess the impact of assimilating Atmospheric Infrared Sounder (AIRS) profiles on high-resolution ensemble forecasts of southern plains severe weather events occurring on 26 May 2009 and 10 May 2010 by comparing two ensemble forecasts.
Abstract: One satellite data product that has received great interest in the numerical weather prediction community is the temperature and mixing ratio profiles derived from the Atmospheric Infrared Sounder (AIRS) instrument on board the Aqua satellite. This research assesses the impact of assimilating AIRS profiles on high-resolution ensemble forecasts of southern plains severe weather events occurring on 26 May 2009 and 10 May 2010 by comparing two ensemble forecasts. In one ensemble, the 1830 and 2000 UTC level 2 AIRS temperature and dewpoint profiles are assimilated with all other routine observations into a 36-member, 15-km Weather and Research Forecast Model (WRF) ensemble using a Kalman filter approach. The other ensemble is identical, except that only routine observations are assimilated. In addition, 3-km one-way nested-grid ensemble forecasts are produced during the periods of convection. Results indicate that over the contiguous United States, the AIRS profiles do not measurably improve the ensem...
TL;DR: In this article, an analysis and verification of 15 years of Climate Prediction Center (CPC) operational seasonal surface temperature and precipitation climate outlooks over the United States is presented for the shortest and most commonly used lead time of 0.5 months.
Abstract: An analysis and verification of 15 years of Climate Prediction Center (CPC) operational seasonal surface temperature and precipitation climate outlooks over the United States is presented for the shortest and most commonly used lead time of 0.5 months. The analysis is intended to inform users of the characteristics and skill of the outlooks, and inform the forecast producers of specific biases or weaknesses to help guide development of improved forecast tools and procedures. The forecast assessments include both categorical and probabilistic verification diagnostics and their seasonalities, and encompass both temporal and spatial variations in forecast skill. A reliability analysis assesses the correspondence between the forecast probabilities and their corresponding observed relative frequencies. Attribution of skill to specific physical sources is discussed. ENSO and long-term trends are shown to be the two dominant sources of seasonal forecast skill. Higher average skill is found for temperatur...