scholarly journals Simulating the 20 May 2013 Moore, Oklahoma tornado with a 100‐metre grid‐length NWP model

2016 ◽  
Vol 17 (8) ◽  
pp. 453-461 ◽  
Author(s):  
Kirsty E. Hanley ◽  
Andrew I. Barrett ◽  
Humphrey W. Lean
Keyword(s):  

2011 ◽  
Vol 139 (6) ◽  
pp. 1960-1971 ◽  
Author(s):  
Jakob W. Messner ◽  
Georg J. Mayr

Abstract Three methods to make probabilistic weather forecasts by using analogs are presented and tested. The basic idea of these methods is that finding similar NWP model forecasts to the current one in an archive of past forecasts and taking the corresponding analyses as prediction should remove all systematic errors of the model. Furthermore, this statistical postprocessing can convert NWP forecasts to forecasts for point locations and easily turn deterministic forecasts into probabilistic ones. These methods are tested in the idealized Lorenz96 system and compared to a benchmark bracket formed by ensemble relative frequencies from direct model output and logistic regression. The analog methods excel at longer lead times.



2002 ◽  
Vol 27 (4-5) ◽  
pp. 341-346 ◽  
Author(s):  
M. Tomassini ◽  
G. Gendt ◽  
G. Dick ◽  
M. Ramatschi ◽  
C. Schraff


2012 ◽  
Vol 140 (3) ◽  
pp. 1014-1022 ◽  
Author(s):  
Tuomo Lauri ◽  
Jarmo Koistinen ◽  
Dmitri Moisseev

When making radar-based precipitation products, a radar measurement is commonly taken to represent the geographical location vertically below the contributing volume of the measurement sample. However, when wind is present during the fall of the hydrometeors, precipitation will be displaced horizontally from the geographical location of the radar measurement. Horizontal advection will introduce discrepancies between the radar-measured and ground level precipitation fields. The significance of the adjustment depends on a variety of factors related to the characteristics of the observed precipitation as well as those of the desired end product. In this paper the authors present an advection adjustment scheme for radar precipitation observations using estimated hydrometeor trajectories obtained from the High-Resolution Limited-Area Model (HIRLAM) MB71 NWP model data. They use the method to correct the operational Finnish radar composite and evaluate the significance of precipitation advection in typical Finnish conditions. The results show that advection distances on the order of tens of kilometers are consistently observed near the edge of the composite at ranges of 100–250 km from the nearest radar, even when using a low elevation angle of 0.3°. The Finnish wind climatology suggests that approximately 15% of single radar measurement areas are lost on average when estimating ground level rainfall if no advection adjustment is applied. For the Finnish composite, area reductions of approximately 10% have been observed, while the measuring area is extended downstream by a similar amount. Advection becomes increasingly important at all ranges in snowfall with maximum distances exceeding 100 km.





2021 ◽  
Vol 94 (2) ◽  
pp. 237-249
Author(s):  
Martin Novák

The article includes a summary of basic information about the Universal Thermal Climate Index (UTCI) calculation by the numerical weather prediction (NWP) model ALADIN of the Czech Hydrometeorological Institute (CHMI). Examples of operational outputs for weather forecasters in the CHMI are shown in the first part of this work. The second part includes results of a comparison of computed UTCI values by ALADIN for selected place with UTCI values computed from real measured meteorological data from the same place.



2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà

Abstract. Tropical-like cyclones rarely affect the Mediterranean region but they can produce strong winds and heavy precipitations. These warm-core cyclones, called MEDICANES (MEDIterranean hurriCANES), are small in size, develop over the sea and are infrequent. For these reasons, the detection and forecast of medicanes are a difficult task and many efforts have been devoted to identify them. The goals of this work are to contribute to a proper description of these structures and to develop some criteria to identify medicanes from numerical weather prediction (NWP) model outputs. To do that, existing methodologies for detecting, characterizating and tracking cyclones have been adapted to small-scale intense cyclonic perturbations. First, a mesocyclone detection and tracking algorithm has been modified to select intense cyclones. Next, the parameters that define the Hart's cyclone phase diagram are tuned and calculated to examine their thermal structure. Four well-known medicane events have been described from numerical simulation outputs of the European Centre for Medium-Range Weather Forecast (ECMWF) model. The predicted cyclones and their evolution have been validated against available observational data and numerical analyses from the literature.



Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.





2007 ◽  
Vol 22 (2) ◽  
pp. 255-277 ◽  
Author(s):  
Kelly M. Mahoney ◽  
Gary M. Lackmann

Abstract Operational forecasters in the southeast and mid-Atlantic regions of the United States have noted a positive quantitative precipitation forecast (QPF) bias in numerical weather prediction (NWP) model forecasts downstream of some organized, cold-season convective systems. Examination of cold-season cases in which model QPF guidance exhibited large errors allowed identification of two representative cases for detailed analysis. The goals of the case study analyses are to (i) identify physical mechanisms through which the upstream convection (UC) alters downstream precipitation amounts, (ii) determine why operational models are challenged to provide accurate guidance in these situations, and (iii) suggest future research directions that would improve model forecasts in these situations and allow forecasters to better anticipate such events. Two primary scenarios are identified during which downstream precipitation is altered in the presence of UC for the study region: (i) a fast-moving convective (FC) scenario in which organized convective systems oriented parallel to the lower-tropospheric flow are progressive relative to the parent synoptic system, and appear to disrupt poleward moisture transport, and (ii) a situation characterized by slower-moving convection (SC) relative to the parent system. Analysis of a representative FC case indicated that moisture consumption, stabilization via convective overturning, and modification of the low-level flow to a more westerly direction in the postconvective environment all appear to contribute to the reduction of downstream precipitation. In the FC case, operational Eta Model forecasts moved the organized UC too slowly, resulting in an overestimate of downstream moisture transport. A 4-km explicit convection model forecast from the Weather Research and Forecasting model produced a faster-moving upstream convective system and improved downstream QPF. In contrast to the FC event, latent heat release in the primary rainband is shown to enhance the low-level jet ahead of the convection in the SC case, thereby increasing moisture transport into the downstream region. A negative model QPF bias was observed in Eta Model forecasts for the SC event. Suggestions are made for precipitation forecasting in UC situations, and implications for NWP model configuration are discussed.



Sign in / Sign up

Export Citation Format

Share Document