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The extraction of atmospheric motion vectors (AMVs) from cloud and moisture features from successive geostationary satellite images is an established and important data source for numerical weather prediction (NWP). So far the extraction of AMVs has been confined to the main synoptic times only, which grossly underutilizes the potential of these satellite-derived data. The advent of four-dimensional variational assimilation techniques provides the opportunity to utilize data derived at asynoptic times. This will enhance the capabilities of geostationary satellite systems that can provide continuous and near-real time observations. The new assimilation schemes are able to digest data representing various scales and with variable quality, which further enhances the usefulness of the satellite data. In order to fully exploit the AMVs derived with satellite data, it is imperative to accurately assess the quality and representativeness of individual wind vectors and to provide this information to the NWP centers as an integral part of the observations in near real time. The required high production and dissemination frequency cannot be met if manual intervention is required; hence, the emphasis has to be on fully automated schemes. This paper will describe the automatic quality control scheme implemented at EUMETSAT. It is based on the statistical properties of the derived AMVs and it provides a quality indicator (QI), describing the expected quality of every individual vector. The derived QIs are currently disseminated together with the derived vectors. The paper will also provide validation results based on collocated radiosonde statistics and report on first experiences by ECMWF in utilizing the QIs. [ABSTRACT FROM AUTHOR]

The early season rainfall (ESR) over southern China, usually occurring from April to June, is a prominent meteorological phenomenon of the East Asian monsoon system. In this paper, output from the 45-day hindcast by the NCEP Climate Forecast System, version 2 (CFSv2), and various observational datasets are analyzed to assess the predictability of the ESR and associated atmospheric circulation. Results show that CFSv2 can successfully predict the ESR and associated circulation patterns over southern China. The lower-tropospheric convergence and upper-tropospheric divergence as well as the local upward motion over southern China lead to the formation of ESR. Analysis of bias shows small differences and close relationships between the predicted and observed ESR values when the forecast lead time is less than 2 weeks. The skill in the ESR predictions by CFSv2 decreases significantly when the lead time is longer than 2 weeks. Overall, CFSv2 has a higher level of skill when predicting the southern China ESR compared to the rainfall over other Asian regions during the same period of time. [ABSTRACT FROM AUTHOR]

During the summer, strong surface heating combines with the terrain and land-water contrasts of the northwest United States to create a complex array of diurnal circulations. Though observational and modeling studies have described some of these circulations, advances in high-resolution numerical modeling allow for a more comprehensive and three-dimensional examination. To simulate typical summer conditions over the Pacific Northwest, 3-hourly Global Forecast System (GFS) model output for July and August 2009-11 was used to initialize and provide boundary conditions for a high-resolution Weather Research and Forecasting (WRF) Model run. To ensure the realism of the simulation, it was compared to observations from a collection of days representing typical summer conditions. Generally, it was found that the simulated diurnal wind, relative humidity, and temperature were close to the observations. It is shown that regional diurnal circulations over the Pacific Northwest occur on a number of interacting scales, ranging from upslope/downslope winds on local terrain features to larger-scale circulations such as between the Pacific Ocean and the western Oregon and Washington interiors. Such multiscale diurnal circulations occur concurrently, with the interactions producing complex structures, several of which are described in this paper. Wind speeds in the Strait of Juan de Fuca and downstream of the major Cascade Mountain gaps reach maxima between 2100 and 2400 local daylight time (LDT), while most other areas have peak winds earlier in the day. Localized nocturnal low-level wind maxima are described, including one over the northern Willamette Valley and another over the high plateau of eastern Oregon. [ABSTRACT FROM AUTHOR]

Transverse cirrus bands have commonly been observed in the outflow of thunderstorms, though little literature exists on the subject. The primary objective of this paper is to characterize the transverse band signature in satellite imagery with references to storm location, movement, and life cycle. The transverse band signature was observed in nearly half of all convective systems analyzed between May and August 2006, commonly in the mature and decay stages of the system. Storm size and propagation did not appear to influence transverse bands, though the bands did appear to be associated with negative 300-hPa relative vorticity and positive divergence. Transverse bands lasted an average duration of 9 h and generally occurred during the nighttime hours. The satellite analysis was combined with eddy dissipation rate (EDR) atmospheric turbulence observations collected by commercial aircraft. At least one observation of light (moderate) turbulence was found within transverse bands for 93% (44%) of events, indicating that the presence of transverse bands in satellite imagery is a strong indicator for aviation turbulence. [ABSTRACT FROM AUTHOR]

Extreme rainfall events contribute a large portion of wintertime precipitation to northern California. The motivations of this paper were to study the observed differences in the patterns between extreme and more commonly occurring lighter rainfall events, and to study whether anomaly fields might be used to discriminate between them. Daily (1200–1200 UTC) precipitation amounts were binned into three progressively heavier categories (12.5–50.0 mm, light; 50–100 mm, moderate; and >100 mm, heavy) in order to help identify the physical processes responsible for extreme precipitation in the Sierra Nevada range between 37.5° and 41.0°N. The composite fields revealed marked differences between the synoptic patterns associated with the three different groups. The heavy composites showed a much stronger, larger-scale, and slower-moving negative geopotential height anomaly off the Pacific coast of Oregon and Washington than was revealed in either of the other two composites. The heavy rainfall events were also typically associated with an atmospheric river with anomalously high precipitable water (PW) and 850-hPa moisture flux (MF) within it. The standardized PW and MF anomalies associated with the heavy grouping were higher and were slower moving than in either of the lighter bins. Three multiday heavy rainfall events were closely examined in order to ascertain whether anomaly patterns could provide forecast utility. Each of the multiday extreme rainfall events investigated was associated with atmospheric rivers that contained highly anomalous 850-hPa MF and PW within it. Each case was also associated with an unusually intense negative geopotential height anomaly that was similarly located off of the west coast of the United States. The similarities in the anomaly pattern among the three multiday extreme events suggest that standardized anomalies might be useful in predicting extreme multiday rainfall events in the northern Sierra range. [ABSTRACT FROM AUTHOR]

This work assesses the contribution of assimilating AMSU-A satellite-based radiance measurements to a global data assimilation system based on an atmospheric general circulation model and the local ensemble transform Kalman filter (LETKF). The radiance measurements were from three channels that are sensitive to the upper troposphere and lower stratosphere. The contribution of these measurements, or AMSU-A observation impact, was estimated both through ensemble-based forecast sensitivity to observations (EFSO) and observing system experiments (OSEs). Two streams of data-denial experiments for the AMSU-A observations were performed for about one month during winter in each hemisphere. The OSEs quantified the accumulated observation impact by cycling (repeating) data denials: including AMSU-A observations reduced the total observation impact for all observations of each data assimilation cycle. In contrast, EFSO estimated AMSU-A to increase the total observation impact. The opposing effects were attributed to the accumulated observation impact in the OSEs; the accumulation could stabilize the data assimilation cycles. In both experiments, the accumulated observation impact of AMSU-A was strongest in the upper troposphere, particularly in the austral midlatitudes where westerly jets exist and observations of other types are sparse. EFSO also assessed AMSU-A to have the most beneficial observation impact in similar locations. The AMSU-A observation impact tended to accumulate just downstream of where EFSO estimated the beneficial observation impact signals. The accumulated AMSU-A observation impact was tied to dynamic processes in the upper-tropospheric and general stratospheric circulation. Therefore, EFSO helps estimate the beneficial distributions of AMSU-A accumulated observation impact by considering their dynamical propagation. [ABSTRACT FROM AUTHOR]

An ensemble-based forecast sensitivity to observations (EFSO) diagnosis has been implemented in an atmospheric general circulation model–ensemble Kalman filter data assimilation system to estimate the impacts of specific observations from the quasi-operational global observing system on weekly short-range forecasts. It was examined whether EFSO reasonably approximates the impacts of a subset of observations from specific geographical locations for 6-h forecasts, and how long the 6-h observation impacts can be retained during the 7-day forecast period. The reference for these forecasts was obtained from 12 data-denial experiments in each of which a subset of three radiosonde observations launched from a geographical location was excluded. The 12 locations were selected from three latitudinal bands comprising (i) four Arctic regions, (ii) four midlatitude regions in the Northern Hemisphere, and (iii) four tropical regions during the Northern Hemisphere winter of 2015/16. The estimated winter-averaged EFSO-derived observation impacts well corresponded to the 6-h observation impacts obtained by the data denials and EFSO could reasonably estimate the observation impacts by the data denials on short-range (from 6 h to 2 day) forecasts. Furthermore, during the medium-range (4–7 day) forecasts, it was found that the Arctic observations tend to seed the broadest impacts and their short-range observation impacts could be projected to beneficial impacts in Arctic and midlatitude North American areas. The midlatitude area was located just downstream of dynamical propagation from the Arctic toward the midlatitudes. Results obtained by repeated Arctic data-denial experiments were found to be generally common to those from the non-repeated experiments. [ABSTRACT FROM AUTHOR]

In this study, the impacts of different augmented observations on forecasts of Typhoon Wutip’s (2013) formation are examined. Using the local ensemble transformed Kalman filter (LETKF) implemented for the Weather Research and Forecasting (WRF) Model, it is found that the prediction of Wutip’s formation location and timing is strongly governed by the strength of a monsoon trough that extends from the Bay of Bengal to the Philippine Sea. By properly capturing the strength of the monsoon trough after assimilating augmented observations available during Wutip’s early stage, the WRF Model could provide better forecasts of Wutip’s formation location and timing as compared to the forecasts initialized directly from global model analyses. Among different types of augmented observations, the satellite atmospheric motion wind vector (AMV) maintained by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) appears to be the most critical in enhancing the large-scale representation of the monsoon trough. The benefit of augmented observations in Wutip’s formation forecast is most apparent at about 36 h prior to the observed formation time. At the shorter 24-h lead time, there is, however, no clear benefit of augmented observations in predicting the timing and the location of Wutip’s formation due to better global analyses. The results obtained in this study demonstrate the vital role of the CIMSS-AMV data in improving the large-scale environment required for TC formation that one should take into account for real-time TC forecasts. [ABSTRACT FROM AUTHOR]

Skillful forecasts of the Indian summer monsoon rainfall (ISMR) at long lead times (4–5 months in advance) pose great challenges due to strong internal variability of the monsoon system and nonstationarity of climatic drivers. Here, we use an advanced causal discovery algorithm coupled with a response-guided detection step to detect low-frequency, remote processes that provide sources of predictability for the ISMR. The algorithm identifies causal precursors without any a priori assumptions, apart from the selected variables and lead times. Using these causal precursors, a statistical hindcast model is formulated to predict seasonal ISMR that yields valuable skill with correlation coefficient (CC) ~0.8 at a 4-month lead time. The causal precursors identified are generally in agreement with statistical predictors conventionally used by the India Meteorological Department (IMD); however, our methodology provides precursors that are automatically updated, providing emerging new patterns. Analyzing ENSO-positive and ENSO-negative years separately helps to identify the different mechanisms at play during different years and may help to understand the strong nonstationarity of ISMR precursors over time. We construct operational forecasts for both shorter (2-month) and longer (4-month) lead times and show significant skill over the 1981–2004 period (CC ~0.4) for both lead times, comparable with that of IMD predictions (CC ~0.3). Our method is objective and automatized and can be trained for specific regions and time scales that are of interest to stakeholders, providing the potential to improve seasonal ISMR forecasts. [ABSTRACT FROM AUTHOR]

The assimilation of atmospheric motion vectors (AMVs) provides important wind information to conventional data-lacking oceanic regions, where tropical cyclones spend most of their lifetimes. Three new AMV types, shortwave infrared (SWIR), clear-air water vapor (CAWV), and visible (VIS), are produced hourly by NOAA/NESDIS and are assimilated in operational NWP systems. The new AMV data types are added to the hourly infrared (IR) and cloud-top water vapor (CTWV) AMV data in the 2016 operational version of the HWRF Model. In this study, we update existing quality control (QC) procedures and add new procedures specific to tropical cyclone assimilation. We assess the impact of the three new AMV types on tropical cyclone forecasts by conducting assimilation experiments for 25 Atlantic tropical cyclones from the 2015 and 2016 hurricane seasons. Forecasts are analyzed by considering all tropical cyclones as a group and classifying them into strong/weak storm vortices based on their initial model intensity. Metrics such as track error, intensity error, minimum central pressure error, and storm size are used to assess the data impact from the addition of the three new AMV types. Positive impact is obtained for these metrics, indicating that assimilating SWIR-, CAWV-, and VIS-type AMVs are beneficial for tropical cyclone forecasting. Given the results presented here, the new AMV types were accepted into NOAA/NCEP's operational HWRF for the 2017 hurricane season. [ABSTRACT FROM AUTHOR]

The variability of the North Atlantic Oscillation (NAO) is a key aspect of Northern Hemisphere atmospheric circulation and has a profound impact upon the weather of the surrounding landmasses. Recent success with dynamical forecasts predicting the winter NAO at lead times of a few months has the potential to deliver great socioeconomic impacts. Here, a linear regression model is found to provide skillful predictions of the winter NAO based on a limited number of statistical predictors. Identified predictors include El Niño, Arctic sea ice, Atlantic SSTs, and tropical rainfall. These statistical models can show significant skill when used to make out-of-sample forecasts, and the method is extended to produce probabilistic predictions of the winter NAO. The statistical hindcasts can achieve similar levels of skill to state-of-the-art dynamical forecast models, although out-of-sample predictions are less skillful, albeit over a small period. Forecasts over a longer out-of-sample period suggest there is true skill in the statistical models, comparable with that of dynamical forecasting models. They can be used both to help evaluate and to offer insight into the sources of predictability and limitations of dynamical models. [ABSTRACT FROM AUTHOR]

On 28 November 2012, a multivortex EF3 tornado occurred in southeastern Italy causing one fatality and estimated damage of 60 million euros. At approximately 1050 LT (0950 UTC), this tornado, which initially formed in association with a supercell thunderstorm over the Ionian Sea, moved inland. The environment where the tornadic supercell developed was characterized by large vertical wind shear in the lowest 1 km of the atmosphere and moderate conditional instability. Mesoscale-model numerical simulations show that it is possible to produce a simulated supercell thunderstorm with a track, change in intensity, and evolution similar to the actual one that spawned the tornado in Taranto, southern Italy. The genesis of the simulated supercell is due to a combination of mesoscale meteorological features: warm low-level air advected toward the Ionian Sea, combined with midlevel cooling due to an approaching trough, increased the potential instability; the intense vertical shear favored the possibility of supercell development; and boundary layer rolls over the Ionian Sea moved in phase with the cells produced by the orography of Calabria to supply ascent, moisture, and heat to the convection. An unusual feature of the present case is the central role of the orography, which was verified in a sensitivity experiment where it was reduced by 80%. [ABSTRACT FROM AUTHOR]

Official forecasts of tropical cyclone (TC) tracks issued by the China Meteorological Administration (CMA); the Regional Specialized Meteorological Centre in Tokyo, Japan; and the Joint Typhoon Warning Center (JTWC) were used to evaluate the accuracies, biases, and trends of TC track forecasts during 2005-14 over the western North Pacific. Overall, the JTWC demonstrated the best forecasting performance. However, the CMA showed the most significant rate of improvement. Two main zones were discovered in the regional distribution of forecast errors: a low-latitude zone that comprises the South China Sea and the sea region east of the Philippines, and a midlatitude zone comprising the southern Sea of Japan and the sea region east of Japan. When TCs moved into the former zone, there were both translational speed and direction biases in the forecast tracks, whereas slow biases were predominated in the latter zone. Twelve synoptic flow patterns of TCs with the largest error have been identified based on the steering flow theory. Among them, the most two common pattern are the pattern with the combination of cyclonic circulations, subtropical ridges, and midlatitude troughs (CRT, 26 TCs), and the pattern of the TCs' track that cannot be explained by steering flow (NSF, 6 TCs). In the CRT pattern, TCs move northwestward forced by the cyclonic circulations and the subtropical ridges and then turn poleward and eastward under the influence of the midlatitude troughs. In the NSF pattern, storms embedded in the southwest flow by the cyclonic circulation and the steering flow suggest TCs should turn to the right and move northeastward but instead TCs persisted in moving northwestward. [ABSTRACT FROM AUTHOR]

Winter storms in the southern United States can significantly impact infrastructure and the economy. In this study, National Centers for Environmental Information Storm Event Database and local climate summaries, are used to develop a spatial climatology of freezing precipitation (freezing rain and ice pellets) and snow over the southern Great Plains, 1993-2011. Principal component analysis is performed on the 500-hPa height field, at the approximate onset time of precipitation, for 33 freezing precipitation and 42 snow case studies, to differentiate common synoptic flow fields associated with precipitation type. The five leading patterns for each precipitation type are retained. Composites of temperature, moisture, pressure, and wind fields are constructed and extended 24 h before and after precipitation initiation to track the storm system evolution. Many 500-hPa flow fields are similar for both precipitation types. However, snow-dominant events have stronger and/or more frequent surface cyclone development. Freezing precipitation is associated with the southward propagation of an Arctic anticyclone well ahead of precipitation, weak or absent surface cyclone formation, and a more western trough axis. High-impact ice storms in the region often have slow-moving upper-level flow, persistent isentropic ascent over a surface quasi-stationary front with strongly positive moisture anomalies, and warm layer airmass trajectories originating over the Gulf of Mexico. The results here are based on a relatively small sample size. However, this work is intended to be useful for forecasters, in particular as a pattern recognition aid in predicting the evolution of precipitation within southern Great Plains winter storms. [ABSTRACT FROM AUTHOR]

This study uses data from a survey of coastal Miami-Dade County, Florida, residents to explore how different types of forecast and warning messages influence evacuation decisions, in conjunction with other factors. The survey presented different members of the public with different test messages about the same hypothetical hurricane approaching Miami. Participants' responses to the information were evaluated using questions about their likelihood of evacuating and their perceptions of the information and the information source. Recipients of the test message about storm surge height and the message about extreme impacts from storm surge had higher evacuation intentions, compared to nonrecipients. However, recipients of the extreme-impacts message also rated the information as more overblown and the information source as less reliable. The probabilistic message about landfall location interacted with the other textual messages in unexpected ways, reducing the other messages' effects on evacuation intentions. These results illustrate the importance of considering trade-offs, unintended effects, and information interactions when deciding how to convey weather information. Recipients of the test message that described the effectiveness of evacuation had lower perceptions that the information was overblown, suggesting the potential value of efficacy messaging. In addition, respondents with stronger individualist worldviews rated the information as significantly more overblown and had significantly lower evacuation intentions. This illustrates the importance of understanding how and why responses to weather messages vary across subpopulations. Overall, the analysis demonstrates the potential value of systematically investigating how different people respond to different types of weather risk messages. [ABSTRACT FROM AUTHOR]

Based on daily rainfall observations and Japanese 25-year Reanalysis Project data during ~1981-2010, a three-dimensional circulation structure that formed before heavy summer rainfall in central north China (CNC) is revealed in this study. Composite analyses of circulation in advance of 225 heavy rain days show that the circulation structure is characterized by a remarkable upper-tropospheric warm anomaly (UTWA), which covers most of northern China with a center at ~300 hPa. Under hydrostatic and geostrophic equilibriums, the UTWA contributes to the generation of an anticyclonic (cyclonic) anomaly above (below). The anticyclonic anomaly strengthens (weakens) westerly winds to the north (south) of the warm center and pushes the high-level westerly jet to the north. The cyclonic anomaly deepens the trough upstream of CNC and intensifies lower southwesterly winds to the mideast of the warm center. As a result, the northerly stretched high-level jet produces upper divergence in its right-front side and the intensified southwesterly winds induce lower moisture convergence in its left-front side, causing heavy rainfall in CNC. Correlation analyses further confirm the close connections between UTWA and circulation in the upper and lower troposphere. The correlation coefficients between UTWA and the upper geopotential height, upper westerly jet, and lower southerly flow reach 0.95, 0.70, and 0.39, implying that the two critical factors leading to intense rainfall in CNC, the high-level jet and the low-level southerly flow, are closely connected with the UTWA. Consequently, in the future analyses and forecasts of heavy rainfall over northern China, more attention should be paid to the temperature in the upper troposphere. [ABSTRACT FROM AUTHOR]

A statistical downscaling scheme based on time-scale decomposition is adapted for summer rainfall prediction over the Yangtze-Huai River region of east China. The predictors are selected from atmospheric circulation variables outputted from the dynamic system models attending the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction program (DEMETER) or observational datasets. Both the predictand and the predictors are decomposed into interannual and decadal components. Two distinct statistical downscaling models are built for the separated time scales and the predicted results are combined to represent the total prediction. The efficiency of this approach was assessed through comparisons with the models' raw hindcasts as well as that from one parallel statistical downscaling scheme without time-scale decomposition. The results display that the time-scale decomposition scheme leads to significant improvements in the spatial and temporal correlation coefficients (CCs) and the root-mean-square errors (RMSEs) as well. The multiyear averaged spatial CCs reach up to 0.49 for all the individual models and their multimodel ensemble (MME), and the temporal CCs at each station are significantly higher with the coefficients from 0.46 to 0.7. Furthermore, two cases, the years 1998 and 1999, are selected for comparison. The former is a relatively easy predictable case and nearly all models predicted successfully, whereas the latter is a difficult case and nearly all models failed. The results suggest significant improvements for both cases. Thus, the present statistical downscaling scheme with time-scale decomposition may be appropriate for operational predictions. [ABSTRACT FROM AUTHOR]

Winter storms, namely snowstorms and ice storms, are a major hazard and forecasting challenge across central North Carolina. This study employed a trajectory approach to analyze the ingredients (i.e., temperature, moisture, and lift) associated with heavy snowstorms and ice storms that occurred within the Raleigh, North Carolina, National Weather Service forecast region from 2000 to 2010. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) tool was used to calculate 72-h backward (i.e., upstream) air parcel trajectories from three critical vertical pressure levels at the time and location of heaviest precipitation for each storm. Analysis of composite trajectories revealed the source regions and meteorological properties of air parcels associated with heavy winter storms. Adiabatic and diabatic contributions to air parcel temperature and moisture content were also estimated along each trajectory to assess the physical processes connected with heavy winter precipitation in the region. Results indicate that diabatic warming and cooling contribute significantly to the vertical temperature profile during heavy winter storms and therefore dictate the resulting precipitation type. The main source of diabatic warming is fluxes of sensible and latent heat within the marine atmospheric boundary layer over the Gulf Stream. These fluxes contribute to a warming and moistening of air parcels associated with heavy ice storms. In contrast, heavy snowstorms are characterized by diabatic cooling in the lower troposphere above the marine atmospheric boundary layer. The most significant moisture source for heavy snowfall is the Caribbean Sea, while heavy ice storms entrain moisture from the Gulf of Mexico and Gulf Stream region near the Carolina coast. [ABSTRACT FROM AUTHOR]

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 two-tiered 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. [ABSTRACT FROM AUTHOR]

The kinematics and thermodynamics of wake lows have been extensively examined in the literature. However, there has been relatively little focus on the widespread, sometimes very strong winds associated with wake lows. Some wake lows are, essentially, severe local storms, producing widespread and sometimes intense damage, similar to that of a derecho, but they occur in environments supporting elevated convection, a phenomenon not often perceived as a significant wind damage threat. Three significant wake lows that affected Alabama and/or Georgia, producing widespread (25 000-50 000 km2) wind damage, and local wind gusts near 25 m s−1, are reviewed in detail. The environments and morphology of the wake lows are addressed, using radar, surface, and upper-air data. [ABSTRACT FROM AUTHOR]

Daily values of forecast scores are evaluated for students in a weather analysis and forecasting class (ATMS 452) offered by the Department of Atmospheric Sciences of the University of Washington during the spring terms of 1997–2007. The objective of this study is to determine the rate at which senior-level undergraduate students develop proficiency at short-term (next day) weather forecasting. Separate analyses are carried out for different categories of forecast parameters. Time series of the average skill achieved over the course of the quarter are presented for the median and the best–worst two student forecasters each year. An overall improvement in student forecast skill occurs over roughly the first 6 weeks of the quarter, followed by minimal systematic changes. Negligible trends in average forecast skill have occurred over the past 10 yr. The correlation coefficient between the students’ overall forecast performance and test scores in ATMS 452 is about 0.4. The results are relevant to the design of effective instructional programs for weather forecasting. [ABSTRACT FROM AUTHOR]

Two months of Lubbock, Texas, radar reflectivity data and West Texas Mesonet data are examined to detect dryline finelines and to describe their thermodynamic and propagation characteristics. Before sunset the moist air mass east of the dryline was consistently denser than the dry air mass. This air density difference waned and even reversed after sunset, because of more rapid cooling on the dry side. This study provides further evidence that the formation and propagation of the dryline convergence zone is driven by the daytime air density difference, that is, that the dryline behaves as a density current. The implication for forecasters is that the air density (or virtual potential temperature) difference across the dryline should be monitored, as a measure of dryline strength and as an additional indicator for the likelihood of convective initiation along the dryline. [ABSTRACT FROM AUTHOR]

The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation. [ABSTRACT FROM AUTHOR]

A high wind event (14–15 February 2001) over the Hawaiian Islands associated with a cold front is simulated using the National Centers for Environmental Prediction (NCEP) Mesoscale Spectral Model (MSM) coupled with an advanced land surface model (LSM). During this period, a strong high pressure cell moved to the northeast of the Hawaiian Islands following the passage of the cold front. The cell then merged with the semipermanent subtropical high and resulted in windy conditions across the state of Hawaii. Analyses of soundings from Lihue on Kauai and Hilo on the Big Island reveal a mean-state critical level below 400 hPa, a strong cross-barrier flow (∼13 m s-1), and the presence of a trade wind inversion. The MSM–LSM predicts downslope windstorms on the lee sides of mountains or ridges with tops beneath the trade wind inversion and within ocean channels between islands. In the case of high mountains with a peak height above the trade wind inversion, weak winds are simulated on the lee side. Around the corners of the islands and in gaps between mountains, gap winds and downslope windstorms are both important for the development of localized leeside windstorms. The localized windstorms over the Hawaiian Islands develop as a result of interactions between large-scale airflow and the complex local topography. Since the terrain is not adequately resolved by the 10-km RSM–LSM, it is no surprise that these windstorms are better simulated by the high-resolution nonhydrostatic MSM–LSM than the 10-km RSM–LSM. [ABSTRACT FROM AUTHOR]

The fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State– NCAR) Mesoscale Model (MM5) was run for seven cases from 2001 in which a sea breeze develops along the eastern New England coast. The results from model runs with 36-, 12-, and 4-km grid spacing are compared with observations as well as output from the National Centers for Environmental Prediction (NCEP) Eta Model on a 40-km grid. As expected, analysis of the individual cases shows that the higher-resolution grids are able to resolve realistic details in the flow, details that the 36-km grids and the 40-km NCEP Eta Model miss entirely. Contrary to expectations, the error statistics show that the ability to forecast specific variables at specific locations does not improve very much when using higher resolution. Even more surprisingly, the 4-km grids produced the biggest errors in forecasting surface dewpoint. [ABSTRACT FROM AUTHOR]

This study identifies the common large-scale environments associated with the development of derecho- producing convective systems (DCSs) from a large number of events. Patterns are identified using statistical clustering of the 500-mb geopotential heights as guidance. The majority of the events (72%) fall into three main patterns that include a well-defined upstream trough (40%), a ridge (20%), and a zonal, low-amplitude flow (12%), which is identified as an additional warm-season pattern. Consequently, the environmental large-scale patterns idealized in past studies only depict a portion of the full spectrum of the possibilities associated with the development of DCSs. In addition, statistics of derecho proximity-sounding parameters are presented relative to the derecho life cycle as well as relative to the forcing for upward motion. It is found that the environments ahead of maturing derechos tend to moisten at low levels while remaining relatively dry aloft. In addition, derechos tend to decay as they move into environments with less instability and smaller deep-layer shear. Low-level shear (instability) is found to be significantly higher (lower) for the more strongly forced events, while the low-level storm-relative inflow tends to be much deeper for the more weakly forced events. Furthermore, discrepancies are found in both low- level and deep-tropospheric shear parameters between observations and the shear profiles considered favorable for strong, long-lived convective systems in idealized simulations. This study highlights the need to examine DCS simulations within more realistic environments to help reconcile these disparities in observations and idealized models and to provide improved information to forecasters. [ABSTRACT FROM AUTHOR]

The primary factors that affect the direction of propagation and overall movement of surface-based mesoscale convective systems (MCSs) are discussed. It is shown that although propagation is indeed related to the strength and direction of the low-level jet as previous studies have shown, it is more specifically dependent upon the degree of cold-pool-relative flow and to the distribution of conditional instability present along a system's gust front. An updated technique that may be used to forecast the short-term (3–6 h) motion of MCS centroids based on these concepts is introduced. The procedure builds on the long-established observation that MCS motion is a function of 1) the advection of existing cells by the mean wind and 2) the propagation of new convection relative to existing storms. Observed wind and thermodynamic data, in conjunction with anticipated cold-pool motion and orientation, are used to assess the speed and direction of cell propagation, that is, whether propagation will be upwind, downwind, or some combination of the two. The technique ultimately yields an estimate of overall system movement and has application regardless of scale, season, or synoptic regime. [ABSTRACT FROM AUTHOR]

Relationships between a previously developed U.S. East Coast winter storm (ECWS) climatology and atmospheric circulation patterns derived from the NCEP–NCAR reanalysis data during 1958–97 have been investigated. Composites of normalized height difference, defined as the difference in monthly mean standardized 500-mb height anomalies between active and inactive ECWS seasons, reveal two dipoles, one over the eastern North Pacific Ocean and the other over the central North Atlantic Ocean, which may have seasonal forecasting utility. An October-mean dipolar pattern yielding stronger (weaker) than normal 500-mb geostrophic westerlies over the eastern Pacific (North Atlantic) skillfully predicts, in the data, greater than normal ECWS activity during the following November–April period. Active ECWS seasons follow other combinations of October-mean dipoles in the data, depending upon the phase of the El Niño–Southern Oscillation. On shorter time scales, 7-day-mean ECWS activity was positively (negatively) correlated with antecedent 7-day-mean 500-mb geostrophic westerly wind anomalies over the eastern Pacific (North Atlantic) under El Niño conditions. Otherwise, the lag correlations indicated that 500-mb geostrophic westerly winds decreased (increased) in magnitude with time over the eastern Pacific (North Atlantic) prior to the start of an active 7-day ECWS period. The results suggest that downstream energy propogation from the eastern Pacific to the western Atlantic may influence ECWS activity, and that this in turn may be modulated by the El Niño–Southern Oscillation. [ABSTRACT FROM AUTHOR]

The nonhydrostatic version of the NCEP Meso-Eta Model is used to perform simulations that differ by only the vertical coordinate to determine the differences in forecasted valley circulations associated with the step-mountain and terrain-following vertical coordinates and whether one coordinate produces consistently superior forecasts at meso-γ and micro-α scales. A horizontal grid spacing of 850 m is used. The model forecasts are evaluated using data from the October 2000 Vertical Transport and Mixing (VTMX) field campaign in the Salt Lake valley. The forecasts of the diurnal evolution of the dominant circulations in the Salt Lake valley, including valley, slope, and canyon flows, and their modification by synoptic forcing during five intensive observation periods, were qualitatively similar to the measurements. Forecasts produced by the step-mountain and terrain-following vertical coordinates each have their own advantages and disadvantages and neither vertical coordinate outperformed the other overall. In general, the terrain-following coordinate simulations reproduced the observed surface wind directions over the valley sidewalls better, while the step-mountain coordinate simulations of nighttime near-surface temperatures and wind speeds were closer to the observations. Significant differences in wind speed and direction between the simulations were also produced in the middle valley atmosphere at night, with the terrain-following coordinate simulations somewhat better than the step-mountain coordinate simulations. Similar forecast errors produced by both simulations probably resulted from the physical parameterizations, rather than the choice of vertical coordinate. [ABSTRACT FROM AUTHOR]

A long-lived highly organized squall line moved rapidly across the middle Mississippi and Ohio Valleys on 15 April 1994 within a moderately unstable, strongly sheared environment. Over Kentucky and southern Indiana, the line contained several bowing segments (bow echoes) that resulted in widespread wind damage, numerous shear vortices/rotational circulations, and several tornadoes that produced F0-F2 damage. In this study, the Louisville-Fort Knox WSR-88D is used to present a thorough discussion of a particularly long-tracked bowing line segment over central Kentucky that exhibited a very complex and detailed evolution, more so than any other segment throughout the life span of the squall line. Specifically, this segment produced abundant straightline wind damage; cyclic, multiple core cyclonic circulations, some of which met mesocyclone criteria; several tornadoes; and embedded high precipitation supercell-like structure that evolved into a rotating comma head-comma tail pattern. The bowing segment also is examined for the presence of bookend vortices aloft and midaltitude radial convergence. In addition, the structure of other bowing segments and their attendant circulations within the squall line are discussed and compared with existing documentation. Radar sampling issues and ramifications of the squall line's complicated structure on the warning process of future similar severe weather events are touched upon as well. [ABSTRACT FROM AUTHOR]