Short-range Forecasts Research Articles

Model Rain and Clouds over Oceans: Comparison with SSM/I Observations

Abstract A comparison of global model cloud and rain parameterization output with satellite observed radiances was carried out. Hydrometeor profiles from ECMWF operational short-range forecasts were combined with a microwave radiative transfer model to generate observation-equivalent radiances simulating the Special Sensor Microwave Imager (SSM/I) measurements. These were generated for two 15-day periods in January and July 2001 to be compared to SSM/I observations from three DMSP satellites, namely F-13, F-14, and F-15. The simulations were analyzed to isolate the relative contributions of water vapor, cloud water, rain, and snow to the total signal given their frequency of occurrence in the global fields. The 19.35-GHz channel has the great advantage of being less sensitive to cloud geometry and model-generated snow, thus providing a more unique relationship between cloud–rainwater and blackbody equivalent brightness temperatures (TBs). The 37.0-GHz channel showed great skill in separating cloud and (mo...

Analyses of gust fronts by means of limited area NWP model outputs

Two convective cases accompanied with propagating gust fronts and recorded over the Czech Republic (CR) in the year 2000 are numerically studied. The experimental integration of the Lokal Modell of the German Weather Service (LM DWD) is used in computations with the horizontal resolution 2.8 km. The prognostic fields of basic thermodynamic quantities as well as the fields of vertical velocities and precipitation rates are presented at various levels/cross-sections and at different times in order to clarify the effect of the cold evaporative outflow on the organization of severe convection. The position and movement of an outflow leading edge (a gust front) are determined with the aid of objective techniques based on a simple model of objective frontal analysis. The techniques include both mathematical and graphical tools. They allow for the automatic identification of gust fronts in atmospheric cross-sections by means of one locating equation and two masking criteria. The equation and criteria employ the moist potential temperature as an input thermal parameter. The appropriate regimes of outflow propagation, which may provide information about outflow dynamics, are assigned subjectively to examined gust fronts according to the properties of ambient flow. As compared with radar, the LM DWD runs prove to forecast precipitation in nearly the right subregions. The results of the numerical study confirm that the LM DWD, together with the objective techniques for gust front analyses, are capable of simulating thermodynamic processes associated with convective outflows. Thereby, they can represent the potential for improving the nowcasting and short-range forecasting of hazardous weather phenomena.

The Delphi method, impeachment and terrorism: Accuracies of short-range forecasts for volatile world events

Two experiments examined the effects of iterated polling and feedback on prediction accuracy for volatile world events using the Delphi paradigm. In both experiments, participants predicted rapidly changing geopolitical events. The first experiment occurred during the litigation surrounding the Clinton/Lewinsky affair in 1998. Results indicated that feedback improved individual and group accuracy for predictions of whether an event would occur. These types of predictions derived from group consensus were approximately 90% accurate, which was significantly higher than the average individual participant's accuracy. Neither polling nor feedback had much effect on time course predictions. The second experiment occurred during the American military action against the Taliban regime in Afghanistan in 2001. In Experiment 2, participants were polled three times to determine if increasing the number of iterated polls would improve Delphi accuracy. The results showed that accuracy improved from the first to the second poll but not from the second to the third. The groups predicted whether these scenarios would occur with approximately 75% accuracy, which was significantly higher than the accuracy of any individual participant. Once again, the Delphi procedure did not enhance time course predictions in Experiment 2.

Impact of a consistent height reassignment method for INSAT derived cloud motion vectors

¶Cloud Motion Vector wind (CMV) data is one of the major products derived from current day operational geostationary satellites and continues to be a useful source of information for global data assimilation systems. The CMV fields result basically from the apparent cloud motion estimated through a sequence of very high resolution radiometer (VHRR) images and the corresponding cloud level is inferred from observed brightness temperatures (BT) in the infrared window channel. The main problem in CMV production is associated with the assignment of correct height to the cloud tracked motions in view of the known limitations associated with the cloud emissivity characteristics and estimation of BTs. Despite these inherent uncertainties satellite derived CMVs are widely used to augment the conventional upper air wind data especially over the oceanic regions. In this study, an attempt is made to improve the quality of INSAT derived CMVs through an appropriate height re-assignment by employing first guess fields (short range forecasts) of a global forecast model.

Short-Range Ensemble Forecasts and Initial Conditions: The 6–7 January 2002 Northeast Snowstorm

Short-Range Ensemble Forecasts and Initial Conditions: The 6–7 January 2002 Northeast Snowstorm

Pyramidal rain field decomposition using radial basis function neural networks for tracking and forecasting purposes

In this paper, we present how we used neural networks (NNs) and a pyramidal approach to model the data obtained by a weather radar and to short-range forecast the rainfall behavior. Very short-range forecasting useful, for instance, for estimating the path attenuation in terrestrial point-to-point communications. Radial basis function NNs are used both to approximate the rain field and to forecast the parameters of this approximation in order to anticipate the movements and changes in geometric characteristics of significant meteorological structures. The procedure is validated by applying it to actual weather radar data and comparing the outcome with a linear forecasting method, the steady-state method, and the persistence method. The same approach is probably useful also for predicting the behavior of other meteorological phenomena like clusters of clouds observed from satellites.

Short-Range Prediction of Tropospheric Ozone Concentrations and Exceedances for Baton Rouge, Louisiana

Abstract Previous research has been focused on improving forecasts of the daily maximum 1-h concentration of tropospheric ozone, which was based on criteria used by the U.S. Environmental Protection Agency (EPA). However, in 2001, EPA began implementing standards based on daily maximum 8-h mean concentrations rather than the former 1-h period. This study uses principal components analysis and multiple-regression analysis to forecast daily maximum 8-h ozone concentrations in the Baton Rouge, Louisiana, nonattainment zone. Although model performance for values at individual stations proved unsuccessful, likely because of the effects of local nonmeteorological conditions, a model for prediction of “exceedances” of the standards at three or more stations explains 46.2% of the variance in tropospheric ozone concentrations. Furthermore, a decision-making tree is proposed for short-range forecasting of whether an exceedance is expected. Results represent a first attempt to forecast 8-h peak tropospheric ozone co...

Precipition Simulation Associated with Typhoon Sinlaku (2002) in Taiwan Area Using the LAPS Diabatic Initialization for MM5

A precipitation simulation associated with Typhoon Sinlaku using the fifth-generation Pennsylvania State University – National Center for Atmospheric Research Mesoscale Model (MM5) initialized diabatically with the Local Analysis and Prediction System (LAPS) is evaluated over the Taiwan area. Two purposes of this paper are to test the performance of the LAPS diabatic data assimilation technique and investigate the impact of the Doppler radar data on the short-range quantitative precipitation forecasts for the typhoon. Typhoon Sinlaku was selected because Doppler radar is one of the most important data sources for an accurate analysis of typhoons and Sinlaku was located close to the Wu-Fen-Shan (WSR-88D) Doppler radar station at north tip of Taiwan during part of its lifetime on 6-7 September 2002. The observed rainfall distribution associated with Sinlaku was closely related to the topography in northern Taiwan. Simulation results show that the MM5 initialized diabatically with LAPS has higher skill for precipitation simulation than the non-LAPS cold start experiment, especially for the higher thresholds in the early portion of model integration (?10 mm in 0-6 h). The assimilation of the Wu-Fen-Shan Doppler radar data played a key role in the improvement of precipitation simulation owing to improvement in the presentation of typhoon hydrometeorological features, such as clouds and the outer rainband, in the model initial conditions. The presence of these initial hydrometeor species had a beneficial impact on reduced precipitation spin-up time. The use of Doppler radar data also can enhance the forecast definition of typhoon structure and rainband simulations. However, these radar data only play a minor role on the typhoon track simulations. However, these radar data only play a minor role on the typhoon track simulation in this case study. Overall, the mesoscale model initialized diabatically with LAPS data assimilation shows improved capability on the typhoon short-range quantitative precipitation forecasts, especially when the Doppler radar data is included.

A variational assimilation technique in a hybrid isentropic-sigma coordinate

¶A three-dimensional variational (3dVAR) analysis set in a generalized vertical coordinate is described. This analysis technique has been applied to the Rapid Update Cycle (RUC), a mesoscale analysis/model system in the United States providing high-frequency, short-range forecasts. The RUC 3dVAR analysis is, in fact, set in a hybrid isentropic-sigma coordinate, but without loss of generality or applicability to other coordinate systems. The use of this coordinate provides an adaptive analysis space, with sloping of background error covariances in the proximity of baroclinic systems, and a stability-dependence for vertical error covariances. The basic characteristics of the RUC are described briefly, with special attention to its vertical coordinate. A detailed description of observation operators is provided. The 3dVAR algorithm, including stream function and velocity potential as control variables for the multivariate aspect, is described in detail. A few examples of analysis results are provided. The RUC 3dVAR in hybrid-isentropic-sigma coordinates is being implemented at the National Centers for Environmental Prediction (NCEP) in 2001.

A new approach to the cumulus parameterization issue

Can the superensemble methodology provide improved precipitation forecasts by combining existing physical parameterizations? We recently addressed this question in the context of Numerical Weather Prediction (NWP).We feel, however, that the information provided here may be useful for seasonal climate modeling as well. In theNWPcontext, we have developed multi-model forecasts from six versions of the Florida State University global spectral model (at a horizontal resolution of 170 waves, triangular truncation). These different versions deployed six different cumulus parameterization schemes; these models were identical in all other aspects, including the initial states. Making the assumption that differences in short-range (one day) forecasts of precipitation arise largely from differences in the cumulus parameterization, a superensemble methodology, following a recent study, was deployed to assign geographically distributed weights to convective heating for the different cumulus parameterization schemes. This was done after completion of some 85 experiments for each model for the training phase of the superensemble. A new single spectral model was next designed that included the weighted sum of the six cumulus parameterization schemes strung out within this model. This model was next shown to outperform in NWP forecasts of precipitation compared to any of those models that used a single cumulus parameterization scheme. This merely suggests that no single, present scheme is superior to all other schemes over the entire tropical belt; they all seem to have some virtues over different geographical regions. This Unified collective scheme is physically based since it does carry mechanisms such as mass flux, moisture convergence, cloud detrainment, downdrafts, effects of sea surface temperature etc. that are explicitly carried within one or the other schemes. This collective scheme is, however, based on optimized weights for these processes that vary geographically. It is our premise that even if a new breakthrough in cumulus parameterization were to occur from the development of a new scheme, that scheme, at best, may only achieve a skill ranking of number three for precipitation forecasts. The first place, we noted, still belongs to a multi-model superensemble, based on the optimal combination of six separate models. The second place belongs to the single model that utilizes a strung out weighted sum of many cumulus parameterization schemes within it. The individual member models have larger precipitation forecast errors compared to the two above. The skills, here, are evaluated using standard metrics such as correlations, root mean square errors and the equitable threat scores; finally we also present the vertical profiles of the apparent heat source and the apparent moisture sink that also confirm these above findings.

OBJECTIVE FRONTAL ANALYSIS TECHNIQUES APPLIED TO EXTREME/NON-EXTREME PRECIPITATION EVENTS

A simple method of the objective frontal analysis (OFA) based on a thermal definition of atmospheric fronts is proposed for the area of Central Europe with the aid of gridded numerical weather prediction model (NWP model) outputs. The OFA includes both mathematical and graphical techniques that enable a computer to draw fronts entirely automatically in atmospheric cross-sections by means of one locating equation and four masking criteria. The OFA also enables to analyse the frontal wave position and the type, activity, and future development of fronts. The OFA is applied to two synoptically analogous cold-frontal situations, which occurred over the Czech Republic in summer season and were characterised by quite different precipitation amounts. The outputs (12h, 18h, and 24h forecasts) of the NWP model Europa Modell/Deutschland Modell are used in computations. The equivalent potential temperature is considered as an input thermal parameter of the OFA. The impact of applying and changing the OFA masking criteria is various and among others also depends on synoptic situation. The comparison between the objective and subjective analysed fronts subserves to evaluate the values of masking threshold constants. Some obtained results of the analysis of the extreme precipitation situation support the possibility of enhanced precipitation amounts. The analysis of the second non-extreme precipitation situation revealed a few different features that do not support the forecast of enhanced precipitation amounts. The results show the OFA could contribute to the improvement of the general short-range weather forecast.

A 4D‐Var re‐analysis of FASTEX

AbstractA complete re‐analysis of the Fronts and Atlantic Storm‐Track EXperiment (5 January–27 February 1997) is performed. It provides a reference description of the life cycle of an ensemble of cyclogeneses over the north Atlantic. Many aspects make this re‐analysis noteworthy. In particular, the FASTEX period is characterized by an exceptional increase in the number of dropsoundings or radiosoundings concentrated on the storm track. Another striking point of the re‐analysis is the use of a four‐dimensional variational (4D‐Var) assimilation scheme on such a long period associated with the French Arpège (Action des Recherche Petite Echelle et Grand Echelle) global stretched model, that allows a locally high resolution in the area where dense networks of dropsondes were deployed. A twin re‐analysis with the same characteristics but without any FASTEX data is also performed. It shows that the impact of the special FASTEX data is quite noticeable in the resulting analyses and is lower, but still perceptible, in the associated short‐range forecasts (6 h–36 h). The impact of FASTEX observations on a particular FASTEX case is also shown. Copyright © 2003 Royal Meteorological Society

Use of adjoint sensitivity analysis to diagnose the CMC global analysis performance: A case study

The sensitivity of forecast errors to initial conditions obtained from the adjoint of a numerical weather prediction model provides new insights into the analysis errors responsible for poor short‐range to mediumrange forecasts. In recent years, we have developed a sensitivity analysis system based on the tangent linear and adjoint of the Global Environmental Multiscale model, in which an iterative procedure minimizing the shortrange forecast errors leads to the so‐called key analysis errors. These errors are dominated by a small number of atmospheric structures, those growing the most rapidly. The algorithm has proven very useful in understanding improvements to the three‐dimensional variational data assimilation (3D‐Var) system implemented in the Canadian Meteorological Centre operational suite in December 2001. The main difference between the old and the new 3D‐Var systems is the assimilation of temperature and surface pressure from surface and upper air stations as opposed to geopotential heights, additional Tiros Operational Vertical Sounder channels, new sources of observations such as temperature observations from aircraft, and wind and temperature from dropsondes. In this paper, we examine key analysis errors of the old 3D‐Var analysis, which led to a very poor 3‐day forecast of a severe winter storm that struck eastern Canada on 10 February 2001. In this case, the same 3‐day forecast from the new 3D‐Var analysis is much better. We compare the difference between the two 3D‐Var analyses and the key analysis errors. We find that the main key analysis errors, in terms of potential vorticity, is located along the west shore of southern California and is characterized by a strong baroclinic structure that has its maximum amplitude in the upper part of the troposphere. The difference between the two analyses is three times more energetic than the key analysis errors and its structure is much more barotropic in the troposphere. However, we show that the large improvement in the new 3D‐Var analysis stems mainly from the reduction of the analysis errors that project onto the key analysis structures.

Fine-scale atmospheric modelling and predictability

numerical modelling of small-scale atmospheric features requires an accurate description of the large-scale atmosphere, explicit representation of appropriate physical mechanisms, and assimilation of relevant meteorological data. This allows analysis and forecasting of important weather phenomena such as thunderstorms, floods, fog, orographically-induced winds, or urban weather and pollution. Depending on the situation, local weather may be more or less predictable than large-scale weather, and short-range forecasts may be harder to produce than longer-range ones.

Development of a Limited-Area Model for Operational Weather Forecasting around a Power Plant: The Need for Specialized Forecasts

A hydrostatic meteorological model, ‘‘PMETEO,’’ was developed for short-range forecasts for a high-resolution limited area located in the northwest region of Spain. Initial and lateral boundary conditions are externally provided by a coarse-mesh model that has much poorer horizontal and vertical resolution than the fine PMETEO grid. Limitations of limited-area models due to lateral boundary conditions are widely known, given that they can have a large impact on the evolution of the predicted fields through the propagation of errors into the interior of the domain. The guidelines to minimize this problem depend on the particular circumstances of the model application. In this case, a specific treatment of the initial and time-dependent boundary conditions is presented that obtains the best accuracy in the model results, because PMETEO is run operationally to predict air quality levels around a power plant.

A Climatology of Surface Baroclinic Zones

Analyses of surface potential temperature for one year over the contiguous United States, southern Canada, northern Mexico, and adjacent oceanic areas showed three regions of relatively high frequency of strong gradients. These were the Atlantic and Gulf coasts, the Pacific coast, and the eastern slopes of the North American Cordillera. The Atlantic and Gulf zone was most pronounced at 1200 UTC during winter. The Pacific coast zone was most frequent at 0000 UTC in summer. The zone on the eastern slopes was present at both times and during all seasons but was most pronounced at 1200 UTC in winter. The locations of the maxima and the pronounced diurnal changes provide circumstantial evidence that the horizontal variation of diabatic heating and cooling due to surface heat flux is a more important physical mechanism than confluence is in the creation of surface baroclinic zones. An example is shown of the importance of the East Coast zone for weather forecasting during the cold season. In January of 2000 a low pressure center propagated along the surface baroclinic zone, separating cold air over land from warm air over the water, rather than following the deep baroclinic zone in the troposphere. During the warm season, the ‘‘backdoor cold front,’’ separating cool air over the water from hot air over land, presents a challenging forecast problem. Many analyzed fronts are not associated with significant horizontal density gradients. Because of these and other surface analysis issues, short-range forecasting might benefit from routine analysis of the surface temperature field.

Model Clouds as Seen from Space: Comparison with Geostationary Imagery in the 11-μm Window Channel

Abstract A monitoring of the European Centre for Medium-Range Weather Forecasts (ECMWF) model with the Meteosat infrared window channel during December 2000 is presented. The Meteosat images are simulated every 3 h during the 31 days of the month from the model fields, at a resolution of 35 km. The study of both the spatial and the temporal variabilities of the model cloudiness is based on forecasts, from 3 to 48 h, as well as on analyses. Despite a reduced cloud forcing in the model, the variations of the extratropical cyclones are shown to be well represented in the short-range (up to 1 day) forecasts. The intertropical convergence zone (ITCZ) is well located but the representation of its temporal variations significantly differs from the observations, in particular over land. The variability of the Meteosat brightness temperature time series usually differs by more than 10% from one model grid point to another, whereas the structures described by the model have scales of about three to four grid points...

Local Data Integration over East-Central Florida Using the ARPS Data Analysis System

The Applied Meteorology Unit has configured the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) to support operational short-range weather forecasting over east-central Florida, including the Kennedy Space Center and Cape Canaveral Air Force Station. The ADAS was modified to assimilate nationally and locally available in situ and remotely sensed observational data into a series of high-resolution gridded analyses every 15 min. The goal for running ADAS over east-central Florida is to generate real-time analysis products that may enhance weather nowcasts and short-range (<6 h) forecasts issued by the 45th Weather Squadron (45 WS), the Spaceflight Meteorology Group (SMG), and the National Weather Service (NWS) at Melbourne, Florida (MLB). The locally configured ADAS has the potential to provide added value because it ingests all operationally available data into a single grid analysis at high spatial and temporal resolutions. ADAS-generated grid analyses can provide forecasters with a tool to develop a more comprehensive understanding of evolving fine-scale weather features than could be obtained by individually examining the disparate data sources. The potential utility of this ADAS configuration to operational forecasters is demonstrated through a postanalysis case study of a thunderstorm outflow boundary that postponed an Atlas space launch mission, and a Florida cool-season squall line event. In the Atlas case study, a thunderstorm outflow boundary generated strong winds that exceeded the Atlas vehicle limits. A diagnosis of this event, using analysis products during the decaying phase of a Florida summer thunderstorm, illustrates the potential benefits that may be provided to forecasters supporting space launch and landing operations, and to NWS MLB meteorologists generating short-range forecast products. The evolution of analyzed cloud fields from the squall line event were used to track the areal coverage and tendencies of cloud ceiling and cloud-top heights that impact the evaluation of space operation weather constraints and NWS aviation products. These cases also illustrate how the analyses can provide guidance for nowcasts and short-range forecasts of Florida warm-season convection and fire-weather parameters. In addition, some of the sensitivities of the ADAS analyses to selected observational data sources are discussed. Recently, a real-time version of ADAS was implemented at both SMG and the NWS MLB forecast offices. Future plans of this ADAS configuration include incorporating additional observational datasets and designing visualization products for specific forecast tasks. Finally, the ultimate goal is to use these ADAS analyses to initialize a high-resolution numerical weather prediction model run locally at SMG and the NWS MLB, in order to develop a cycling scheme that preserves fine-scale features such as convective outflow boundaries in short-range numerical forecasts.

Satellite Observations of a Severe Supercell Thunderstorm on 24 July 2000 Made during theGOES-11Science Test

Abstract This paper utilizes a severe thunderstorm case from 24 July 2000 to demonstrate the relevance of Geostationary Operational Environmental Satellite (GOES) rapid-scan imagery and sounder data in the short-range forecasting and nowcasting time frames. Results show how these data can be employed quickly and effectively during the warning decision-making process. Various aspects of the severe storm environment are identified that could only be diagnosed in this case using satellite data. The data used in this study are unique in that the imager and sounder input both come from one of the newest of the geostationary satellites, GOES-11. The datasets were collected as a part of the satellite's 6-week science test. During this test period, continuous 1-min imagery and 30-min sounder data were available. The new satellite has now been placed on standby and will be put in service when either GOES-East or GOES-West fails. Two new high-resolution satellite products are presented that are currently in the dev...

Evaluation of Flash-Flood Discharge Forecasts in Complex Terrain Using Precipitation

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar–Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.