Short-range weather forecasting as a hydrodynamic problem

1966 ◽  
pp. 779-789 ◽  
Author(s):  
I. A. Kibel
1959 ◽  
Vol 40 (2) ◽  
pp. 56-72 ◽  
Author(s):  
Morris Tepper

Mesometeorology is the study of atmospheric motions of characteristic dimensions too small to make them readily identifiable on the macroscale synoptic maps in use today. Results of mesoanalysis reveal systems which have definite order, pattern, and chronological continuity, and with which most pertinent local weather seems to be associated. The role of mesometeorology in local weather forecasting is analyzed. Nine senior meteorologists with considerable experience and stature in the field of forecasting participated in a forecasting experiment wherein three were given mesometeorological analyses and six were given the regular analyses available at a forecasting center. The results showed that the former group was able to identify and forecast the short-range significant variations in wind, temperature, and precipitation in time and place while the others in general could not.


1948 ◽  
Vol 1 (3) ◽  
pp. 219-240
Author(s):  
P. G. Satow

AbstractThe paper is divided into two parts.Part 1, under the heading of Non-standard Propagation, concerns variations in the apparent performance of marine navigational radar in its use for detecting shipping and land targets. The effects of changes in the density of the lower layers of the atmosphere on radar transmissions, their distortion of radar coverage for better or for worse, and resultant errors in the evaluation of echoes are here examined.Part 2 describes the way in which weather echoes may influence and restrict radar-assisted navigation. The attenuation of field strength with various types and intensities of precipitation, and the effects of these factors on the navigational and collision-warning uses of radar are examined. The detection, tracking, and application of weather echoes as an aid to short-range weather forecasting are also covered.


1998 ◽  
Vol 3 (2) ◽  
pp. 45
Author(s):  
C., Dawson ◽  
J.F.V. Vincent ◽  
A-M. Rocca

2014 ◽  
Vol 119 (6) ◽  
pp. 2764-2780 ◽  
Author(s):  
Prashant Kumar ◽  
Bimal K. Bhattacharya ◽  
Rahul Nigam ◽  
C. M. Kishtawal ◽  
P. K. Pal

2007 ◽  
Vol 22 (3) ◽  
pp. 580-595 ◽  
Author(s):  
Chungu Lu ◽  
Huiling Yuan ◽  
Barry E. Schwartz ◽  
Stanley G. Benjamin

Abstract A time-lagged ensemble forecast system is developed using a set of hourly initialized Rapid Update Cycle model deterministic forecasts. Both the ensemble-mean and probabilistic forecasts from this time-lagged ensemble system present a promising improvement in the very short-range weather forecasting of 1–3 h, which may be useful for aviation weather prediction and nowcasting applications. Two approaches have been studied to combine deterministic forecasts with different initialization cycles as the ensemble members. The first method uses a set of equally weighted time-lagged forecasts and produces a forecast by taking the ensemble mean. The second method adopts a multilinear regression approach to select a set of weights for different time-lagged forecasts. It is shown that although both methods improve short-range forecasts, the unequally weighted method provides the best results for all forecast variables at all levels. The time-lagged ensembles also provide a sample of statistics, which can be used to construct probabilistic forecasts.


2004 ◽  
Vol 85 (12) ◽  
pp. 1871-1886 ◽  
Author(s):  
Stanley G. Benjamin ◽  
Barry E. Schwartz ◽  
Edward J. Szoke ◽  
Steven E. Koch

An assessment of the value of data from the NOAA Profiler Network (NPN) on weather forecasting is presented. A series of experiments was conducted using the Rapid Update Cycle (RUC) model/assimilation system in which various data sources were denied in order to assess the relative importance of the profiler data for short-range wind forecasts. Average verification statistics from a 13-day cold-season test period indicate that the profiler data have a positive impact on short-range (3–12 h) forecasts over the RUC domain containing the lower 48 United States, which are strongest at the 3-h projection over a central U.S. subdomain that includes most of the profiler sites, as well as downwind of the profiler observations over the eastern United States. Overall, profiler data reduce wind forecast errors at all levels from 850 to 150 hPa, especially below 300 hPa where there are relatively few automated aircraft observations. At night when fewer commercial aircraft are flying, profiler data also contribute strongly to more accurate 3-h forecasts, including near-tropopause maximum wind levels. For the test period, the profiler data contributed up to 20%–30% (at 700 hPa) of the overall reduction of 3-h wind forecast error by all data sources combined. Inclusion of wind profiler data also reduced 3-h errors for height, relative humidity, and temperature by 5%-15%, averaged over different vertical levels. Time series and statistics from large-error events demonstrate that the impact of profiler data may be much larger in peak error situations. Three data assimilation case studies from cold and warm seasons are presented that illustrate the value of the profiler observations for improving weather forecasts. The first case study indicates that inclusion of profiler data in the RUC model runs for the 3 May 1999 Oklahoma tornado outbreak improved model guidance of convective available potential energy (CAPE), 300-hPa wind, and precipitation in southwestern Oklahoma at the onset of the event. In the second case study, inclusion of profiler data led to better RUC precipitation forecasts associated with a severe snow and ice storm that occurred over the central plains of the United States in February 2001. A third case study describes the effect of profiler data for a tornado event in Oklahoma on 8 May 2003. Summaries of National Weather Service (NWS) forecaster use of profiler data in daily operations, although subjective, support the results from these case studies and the statistical forecast model impact study in the broad sense that profiler data contribute significantly to improved short-range forecasts over the central United States where these observations currently exist.


2008 ◽  
Vol 12 (4) ◽  
pp. 1039-1051 ◽  
Author(s):  
J. Younis ◽  
S. Anquetin ◽  
J. Thielen

Abstract. In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of loss of human life and infrastructures. Over the last two decades, flash floods have caused damage costing a billion Euros in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available short-range numerical weather forecasts together with a rainfall-runoff model can be used for early indication of the occurrence of flash floods. One of the challenges in flash flood forecasting is that the watersheds are typically small, and good observational networks of both rainfall and discharge are rare. Therefore, hydrological models are difficult to calibrate and the simulated river discharges cannot always be compared with ground measurements. The lack of observations in most flash flood prone basins, therefore, necessitates the development of a method where the excess of the simulated discharge above a critical threshold can provide the forecaster with an indication of potential flood hazard in the area, with lead times of the order of weather forecasts. This study is focused on the Cévennes-Vivarais region in the Southeast of the Massif Central in France, a region known for devastating flash floods. This paper describes the main aspects of using numerical weather forecasting for flash flood forecasting, together with a threshold – exceedance. As a case study the severe flash flood event which took place on 8–9 September 2002 has been chosen. Short-range weather forecasts, from the Lokalmodell of the German national weather service, are used as input for the LISFLOOD model, a hybrid between a conceptual and physically based rainfall-runoff model. Results of the study indicate that high resolution operational weather forecasting combined with a rainfall-runoff model could be useful to determine flash floods more than 24 h in advance.


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