The Use of High Horizontal Resolution Satellite Temperature and Moisture Profiles to Initialize a Mesoscale Numerical Weather Prediction Model—A Severe Weather Event Case Study

Abstract. Seven of the infrared channels from the Spinning Enhanced Visible and Infrared Imagery (SEVIRI) instrument, on board the Meteosat Second Generation (MSG), are used to retrieve Layer Precipitable Water (LPW) and Stability Analysis Imagery (SAI) in the SAFNWC framework. Both products are retrieved using a statistical retrieval based on neural networks; they are routinely generated every fifteen minutes at a satellite horizontal resolution of 3 km in NADIR only in cloud-free areas. Many factors are involved in the development of severe weather and these parameters are only some of the indicators. However, due to the high resolution of these products, the use of them in conjunction with satellite and radar images can help to identify mesoscale features related to convection. The MSG moisture and parcel instability time trend fields are especially useful during the period previous to convection. Once the outbreak of convection occurs, the products calculated in the clear air pixels surrounding the convective system can give us hints to anticipate its evolution. SAFNWC LPW and SAI were analyzed for a severe weather event during August 2004. A thunderstorm over Teruel (Spain) produced intense precipitation and hail; a tornado developed while this thunderstorm was moving towards SE. The pre-convective parcel potential buoyancy and moisture SAFNWC products changed in a way that was consistent with the observed intense convective activity. In previous studies, the atmospheric moisture in medium levels, which has been proven to be relevant in some cases, was represented by only one level parameter (ML: middle layer LPW). However, it was observed that this layer is too thick to do an adequate analysis of moisture available for convection. Hence, an improvement on the LPW algorithm has been carried out by splitting the middle layer into two new sub-layers (approximately separated at 700 hPa) and training two new neural networks. The impact of monitoring moisture in the new sub-layers separately in this severe weather event has been tested, and the improvements achieved have been evaluated.

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The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

Meteorology Hydrology and Water Management ◽

10.26491/mhwm/143877 ◽

2021 ◽

Author(s):

Mariusz Figurski ◽

Grzegorz Nykiel ◽

Adam Jaczewski ◽

Zofia Baldysz ◽

Marcin Wdowikowski

Keyword(s):

High Resolution ◽

Boundary Conditions ◽

Wrf Model ◽

Severe Weather ◽

Weather Event ◽

Model Case ◽

The Impact ◽

Event Simulations ◽

Severe Weather Event

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National Mosaic and Multi-Sensor QPE (NMQ) System: Description, Results, and Future Plans

Bulletin of the American Meteorological Society ◽

10.1175/2011bams-d-11-00047.1 ◽

2011 ◽

Vol 92 (10) ◽

pp. 1321-1338 ◽

Cited By ~ 293

Author(s):

Jian Zhang ◽

Kenneth Howard ◽

Carrie Langston ◽

Steve Vasiloff ◽

Brian Kaney ◽

...

Keyword(s):

High Resolution ◽

Real Time ◽

Water Resource Management ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Horizontal Resolution ◽

Severe Weather ◽

Model Verification ◽

Automated System ◽

Test Bed

The National Mosaic and Multi-sensor QPE (Quantitative Precipitation Estimation), or “NMQ”, system was initially developed from a joint initiative between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the Federal Aviation Administration's Aviation Weather Research Program, and the Salt River Project. Further development has continued with additional support from the National Weather Service (NWS) Office of Hydrologic Development, the NWS Office of Climate, Water, and Weather Services, and the Central Weather Bureau of Taiwan. The objectives of NMQ research and development (R&D) are 1) to develop a hydrometeorological platform for assimilating different observational networks toward creating high spatial and temporal resolution multisensor QPEs for f lood warnings and water resource management and 2) to develop a seamless high-resolution national 3D grid of radar reflectivity for severe weather detection, data assimilation, numerical weather prediction model verification, and aviation product development. Through about ten years of R&D, a real-time NMQ system has been implemented (http://nmq.ou.edu). Since June 2006, the system has been generating high-resolution 3D reflectivity mosaic grids (31 vertical levels) and a suite of severe weather and QPE products in real-time for the conterminous United States at a 1-km horizontal resolution and 2.5 minute update cycle. The experimental products are provided in real-time to end users ranging from government agencies, universities, research institutes, and the private sector and have been utilized in various meteorological, aviation, and hydrological applications. Further, a number of operational QPE products generated from different sensors (radar, gauge, satellite) and by human experts are ingested in the NMQ system and the experimental products are evaluated against the operational products as well as independent gauge observations in real time. The NMQ is a fully automated system. It facilitates systematic evaluations and advances of hydrometeorological sciences and technologies in a real-time environment and serves as a test bed for rapid science-to-operation infusions. This paper describes scientific components of the NMQ system and presents initial evaluation results and future development plans of the system.

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Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Water ◽

10.3390/w13060873 ◽

2021 ◽

Vol 13 (6) ◽

pp. 873

Author(s):

Yakob Umer ◽

Janneke Ettema ◽

Victor Jetten ◽

Gert-Jan Steeneveld ◽

Reinder Ronda

Keyword(s):

High Intensity ◽

Flood Hazard ◽

Weather Prediction ◽

Wrf Model ◽

Numerical Weather Prediction Model ◽

Rainfall Event ◽

Weather Research And Forecasting ◽

Event Triggering ◽

Rain Events

Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.

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Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

10.5194/nhess-2017-291 ◽

2017 ◽

Author(s):

Paul W. Miller ◽

Thomas L. Mote

Keyword(s):

United States ◽

High Resolution ◽

Numerical Model ◽

Model Error ◽

Severe Weather ◽

Forecasting Model ◽

Weather Event ◽

Southeast United States ◽

Accurate Representation ◽

Severe Weather Event

Abstract. Weakly forced thunderstorms (WFTs), short-lived convection forming in synoptically quiescent regimes, are a contemporary forecasting challenge. The convective environments that support severe WFTs are often similar to those that yield only nonsevere WFTs, and additionally, only a small proportion individual WFTs will ultimately produce severe weather. The purpose of this study is to better characterize the relative severe weather potential in these settings as a function of the convective environment. Thirty near-storm convective parameters for > 200 000 WFTs in the Southeast United States are calculated from a high-resolution numerical forecasting model, the Rapid Refresh (RAP). For each parameter, the relative likelihood of WFT days with at least one severe weather event is assessed along a moving threshold. Parameters (and the values of them) that reliably separate severe-weather-supporting from nonsevere WFT days are highlighted. Only two convective parameters, vertical totals (VT) and total totals (TT), appreciably differentiate severe-wind-supporting and severe-hail-supporting days from nonsevere WFT days. When VTs exceeded values between 24.6–25.1 °C or TTs between 46.5–47.3 °C, severe-wind days were roughly 5 × more likely. Meanwhile, severe-hail days became roughly 10 × more likely when VTs exceeded 24.4–26.0 °C or TTs exceeded 46.3–49.2 °C. The stronger performance of VT and TT is partly attributed to the more accurate representation of these parameters in the numerical model. Under-reporting of severe weather and model error are posited to exacerbate the forecasting challenge by obscuring the subtle convective environmental differences enhancing storm severity.

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Analysis of Catania Flash Flood Case Study by Using Combined Microwave and Infrared Technique

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-092.1 ◽

2014 ◽

Vol 15 (5) ◽

pp. 1989-1998 ◽

Cited By ~ 26

Author(s):

Francesco Di Paola ◽

Elisabetta Ricciardelli ◽

Domenico Cimini ◽

Filomena Romano ◽

Mariassunta Viggiano ◽

...

Keyword(s):

Real Time ◽

Flash Flood ◽

Weather Prediction ◽

Rapid Evolution ◽

Cell Formation ◽

Winter Season ◽

National Research Council ◽

Severe Weather ◽

Synoptic Situation

Abstract In this paper, the analysis of an extreme convective event atypical for the winter season, which occurred on 21 February 2013 on the east coast of Sicily and caused a flash flood over Catania, is presented. In just 1 h, more than 50 mm of precipitation was recorded, but it was not forecast by numerical weather prediction (NWP) models and, consequently, no severe weather warnings were sent to the population. The case study proposed is first examined with respect to the synoptic situation and then analyzed by means of two algorithms based on satellite observations: the Cloud Mask Coupling of Statistical and Physical Methods (MACSP) and the Precipitation Evolving Technique (PET), developed at the National Research Council of Italy. Both of the algorithms show their ability in the near-real-time monitoring of convective cell formation and their rapid evolution. As quantitative precipitation forecasts by NWP could fail, especially for atypical convective events like in Catania, tools like MACSP and PET shall be adopted by civil protection centers to monitor the real-time evolution of deep convection events in aid to the severe weather warning service.

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Numerical simulations of June 7, 2020 convective precipitation over Slovakia using deterministic, probabilistic, and convection-permitting approaches

Időjárás ◽

10.28974/idojaras.2021.4.3 ◽

2021 ◽

Vol 125 (4) ◽

pp. 571-607

Author(s):

André Simon ◽

Martin Belluš ◽

Katarína Čatlošová ◽

Mária Derková ◽

Martin Dian ◽

...

Keyword(s):

Satellite Imagery ◽

Weather Prediction ◽

Severe Weather ◽

Precipitation Forecast ◽

Convective Precipitation ◽

Small Scale ◽

Limited Area ◽

Systematic Effect ◽

The Impact

The paper presented is dedicated to the evaluation of the influence of various improvements to the numerical weather prediction (NWP) systems exploited at the Slovak Hydrometeorological Institute (SHMÚ). The impact was illustrated in a case study with multicell thunderstorms and the results were confronted with the reference analyses from the INCA nowcasting system, regional radar reflectivity data, and METEOSAT satellite imagery. The convective cells evolution was diagnosed in non-hydrostatic dynamics experiments to study weak mesoscale vortices and updrafts. The growth of simulated clouds and evolution of the temperature at their top were compared with the brightness temperature analyzed from satellite imagery. The results obtained indicated the potential for modeling and diagnostics of small-scale structures within the convective cloudiness, which could be related to severe weather. Furthermore, the non-hydrostatic dynamics experiments related to the stability and performance improvement of the time scheme led to the formulation of a new approach to linear operator definition for semi-implicit scheme (in text referred as NHHY). We demonstrate that the execution efficiency has improved by more than 20%. The exploitation of several high resolution measurement types in data assimilation contributed to more precise position of predicted patterns and precipitation representation in the case study. The non-hydrostatic dynamics provided more detailed structures. On the other hand, the potential of a single deterministic forecast of prefrontal heavy precipitation was not as high as provided by the ensemble system. The prediction of a regional ensemble system A-LAEF (ALARO Limited Area Ensemble Forecast) enhanced the localization of precipitation patterns. Though, this was rather due to the simulation of uncertainty in the initial conditions and also because of the stochastic perturbation of physics tendencies. The various physical parameterization setups of A-LAEF members did not exhibit a systematic effect on precipitation forecast in the evaluated case. Moreover, the ensemble system allowed an estimation of uncertainty in a rapidly developing severe weather case, which was high even at very short range.

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A warm-front triggered nocturnal tornado outbreak near Kiama, NSW, Australia

Journal of Southern Hemisphere Earth System Science ◽

10.1071/es18008 ◽

2018 ◽

Vol 68 (1) ◽

pp. 147

Author(s):

Simon A. Louis

Keyword(s):

New South ◽

Severe Weather ◽

South Coast ◽

Horizontal Shear ◽

Weather Event ◽

Pressure System ◽

Warm Front ◽

South Wales ◽

Low Pressure System ◽

Severe Weather Event

This paper documents the case of a nocturnal outbreak of tornadoes on the New South Wales (NSW) south coast on 23 February 2013, and provides an analysis of the conditions that led to the outbreak. These tornadoes were associated with the passage of a warm front which had developed on the eastern flank of a mature extratropical cyclone.The damage from the tornadoes is discussed, and an analysis of the synoptic and mesoscale conditions that led to the event is provided. An analysis of radar at the time of the event shows a series of vortices developing within a zone of horizontal shear just prior to the tornadoes developing. The tornadoes were difficult for operational forecasters to predict, partly due to the infrequent occurrence of nocturnal tornadoes of this type in NSW, and in part due to operational demands from the broader scale severe weather event that resulted from the low-pressure system. This paper presents an analysis of the event that may assist forecasters in identifying similar events in the future.

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Analysis of the Algerian severe weather event in November 2001 and its impact on ozone and nitrogen dioxide distributions

Tellus B ◽

10.3402/tellusb.v55i5.16392 ◽

2011 ◽

Vol 55 (5) ◽

pp. 993-1006

Author(s):

W. Thomas ◽

F. Baier ◽

T. Erbertseder ◽

M. Kaästner

Keyword(s):

Nitrogen Dioxide ◽

Severe Weather ◽

Weather Event ◽

Severe Weather Event

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