Coupling Advanced Modeling and Visualization to Improve High-Impact Tropical Weather Prediction

2011 ◽  
Vol 13 (5) ◽  
pp. 56-67 ◽  
Author(s):  
Bo-Wen Shen ◽  
Wei-Kuo Tao ◽  
Bryan Green
2020 ◽  
Author(s):  
Marvin Kähnert ◽  
Teresa M. Valkonen ◽  
Harald Sodemann

<p>Numerical weather prediction (NWP) models generally display comparatively low predictive skill in the Arctic. Particularly, the large impact of sub-grid scale, parameterised processes, such as surface fluxes, radiation or cloud microphysics during high-latitude weather events pose a substantial challenge for numerical modelling. Such processes are most influential during mesoscale weather events, such as polar lows, often embedded in cold air outbreaks (CAO), some of which cause high impact weather. Uncertainty in Arctic weather forecasts is thus critically dependent on parameterised processes. The strong influence from several parameterised processes also makes model forecasts particularly susceptible to compensation of errors from different parameterisations, which potentially limits model improvement.<br>Here we analyse model output of individual parameterised tendencies of wind, temperature and humidity during Arctic high-impact weather in AROME-Arctic, the operational NWP model used by the Norwegian Meteorological Institute Norway for the European Arctic. Individual tendencies describe the contribution of each applied physical parameterisation to a respective variable per model time step. We study a CAO-event taking place during 24 - 27 December 2015. This intense and widespread CAO event, reaching from the Fram Straight to Norway and affecting a particularly large portion of the Nordic seas at a time, was characterised by strong heat fluxes along the sea ice edge. <br>Model intern definitions for boundary layer type become apparent as a decisive factor in tendency contributions. Especially the interplay between the dual mass flux and the turbulence scheme is of essence here. Furthermore, sensitivity experiments, featuring a run without shallow convection and a run with a new statistical cloud scheme, show how a physically similar result is obtained by substantially different tendencies in the model.</p>


2016 ◽  
Vol 32 (1) ◽  
pp. 27-46 ◽  
Author(s):  
Daniel J. Halperin ◽  
Robert E. Hart ◽  
Henry E. Fuelberg ◽  
Joshua H. Cossuth

Abstract The National Hurricane Center (NHC) has stated that guidance on tropical cyclone (TC) genesis is an operational forecast improvement need, particularly since numerical weather prediction models produce TC-like features and operationally required forecast lead times recently have increased. Using previously defined criteria for TC genesis in global models, this study bias corrects TC genesis forecasts from global models using multiple logistic regression. The derived regression equations provide 48- and 120-h probabilistic genesis forecasts for each TC genesis event that occurs in the Environment Canada Global Environmental Multiscale Model (CMC), the NCEP Global Forecast System (GFS), and the Met Office's global model (UKMET). Results show select global model output variables are good discriminators between successful and unsuccessful TC genesis forecasts. Independent verification of the regression-based probabilistic genesis forecasts during 2014 and 2015 are presented. Brier scores and reliability diagrams indicate that the forecasts generally are well calibrated and can be used as guidance for NHC’s Tropical Weather Outlook product. The regression-based TC genesis forecasts are available in real time online.


2017 ◽  
Vol 98 (4) ◽  
pp. 807-830 ◽  
Author(s):  
D. B. Parsons ◽  
M. Beland ◽  
D. Burridge ◽  
P. Bougeault ◽  
G. Brunet ◽  
...  

Abstract The Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.


2012 ◽  
Vol 27 (5) ◽  
pp. 1217-1234 ◽  
Author(s):  
Claudia Frick ◽  
Heini Wernli

Abstract Accurate numerical weather prediction of intense snowfall events requires the correct representation of dynamical and physical processes on various scales. In this study, a specific event of high-impact wet snowfall is examined that occurred in the northwestern part of Germany in November 2005. First, the synoptic evolution is presented, together with observations of precipitation type and vertical temperature profiles, which reveal the existence of a so-called potential melting layer during the early period of wet snowfall. During the main part, the performance of the operational forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) is investigated. It is shown that only the short-term predictions captured the snowfall event, whereas earlier forecasts were in error concerning the phase and/or amount of precipitation. However, even the short-term forecasts produced the onset of surface snowfall too late (i.e., during the dry snowfall period). Reasons for the misforecasts are errors on various scales. For the early forecasts, they include an inaccurate representation of the upper-level trough and a misplacement of the surface cyclone. For the later forecasts, a slight overestimation of the depth of the potential melting layer and a potentially too fast snow melting process in the model lead to the erroneous prediction of surface rainfall during the wet snowfall period. Hindcast experiments with the high-resolution Consortium for Small-Scale Modeling (COSMO) model also point to the necessity of improving its snow melting parameterization in order to provide useful predictions of potentially high-impact wet snowfall events.


2020 ◽  
Vol 35 (5) ◽  
pp. 2083-2097 ◽  
Author(s):  
Forest Cannon ◽  
Nina S. Oakley ◽  
Chad W. Hecht ◽  
Allison Michaelis ◽  
Jason M. Cordeira ◽  
...  

AbstractShort-duration, high-intensity rainfall in Southern California, often associated with narrow cold-frontal rainbands (NCFR), threaten life and property. While the mechanisms that drive NCFRs are relatively well understood, their regional characteristics, specific contribution to precipitation hazards, and their predictability in the western United States have received little research attention relative to their impact. This manuscript presents observations of NCFR physical processes made during the Atmospheric River Reconnaissance field campaign on 2 February 2019 and investigates the predictability of the observed NCFR across spatiotemporal scales and forecast lead time. Dropsonde data collected along transects of an atmospheric river (AR) and its attendant cyclone during rapid cyclogenesis, and radiosonde observations during landfall 24 h later, are used to demonstrate that a configuration of the Weather Research and Forecasting (WRF) Model skillfully reproduces the physical processes responsible for the development and maintenance of the impactful NCFR. Ensemble simulations provide quantitative uncertainty information on the representation of these features in numerical weather prediction and instill confidence in the utility of WRF as a forecast guidance tool for short- to medium-range prediction of mesoscale precipitation processes in landfalling ARs. This research incorporates novel data and methodologies to improve forecast guidance for NCFRs impacting Southern California. While this study focuses on a single event, the outlined approach to observing and predicting high-impact weather across a range of spatial and temporal scales will support regional water management and hazard mitigation, in general.


2011 ◽  
Vol 26 (2) ◽  
pp. 243-249 ◽  
Author(s):  
Jacob R. Carley ◽  
Benjamin R. J. Schwedler ◽  
Michael E. Baldwin ◽  
Robert J. Trapp ◽  
John Kwiatkowski ◽  
...  

Abstract A feature-specific forecasting method for high-impact weather events that takes advantage of high-resolution numerical weather prediction models and spatial forecast verification methodology is proposed. An application of this method to the prediction of a severe convective storm event is given.


2021 ◽  
Author(s):  
Alfons Callado-Pallarès

<p>SRNWP-EPS module/project into EUMETNET NWP Cooperation Programme has as main goals facilitating and coordinating the cooperation on developing reliable mesoscale convection-permitting ensemble systems (LAM-EPS) in Europe, and, at the same time, grouping efforts developing tools which can be smoothly applied to any LAM-EPS. This is motivated by the fact that the development of LAM-EPS capabilities in Europe is crucial for forecasting a range of weather phenomena and in particular for improving HIW (High Impact Weather) prediction. Due   to the latter, the current SRNWP-EPS 2019-2023 phase is focused on extreme events.</p><p>The project results as a survey on products for high-impact weather forecasting and the R2O (Research to Operations) LAM-EPS applications will be presented. The three main R2O forecasting tools developed as project requirements are: calibration of daily and  12 hours extremes for variables such as 10 metres maximum wind gusts, maximum accumulated precipitation, maximum and minimum2m temperatures; the forecasting post-processing LAM-EPS products devoted to HIW forecasting and focused on aeronautics such as icing, thunderstorms’ diagnostic and classification, clear-air turbulence and fog; and tools to apply in an affordable way an Extreme Forecast Index (EFI) and Shift of Tales Index (SOT) on LAM-EPSs.</p><p>Moreover, an off-line database of European convection-permitting LAM-EPS ensembles has been established at ECMWF, which archives convection related parameters close to the surface. The aim of LAM-EPS database is to foster coordinate research and collaborations around LAM-EPSs in order to improve HIW events bringing together all European LAM-NWP consortia (ALADIN, HIRLAM, COSMO, LACE, MetOffice partners, etc.). At the time of writing, nine participants are currently archiving since 1<sup>st</sup> of June of 2020: MOGREPS-UK (MetOffice), MEPS (MetCoOp), <em>γ</em>SREPS (AEMET), IT-EPS (ItAF-REMET), IREPS (Met Éireann), COMEPS (DMI), MF-AromeEps (MétéoFrance), RMI-EPS (RMI) and ICON-D2-EPS (DWD). The SRNWP-EPS convection-permitting LAM-EPS database is currently being used by project research sub-groups, for example to check multi-ensemble performance or comparing two LAM-EPSs in their common overlapping area.</p>


2021 ◽  
Author(s):  
Valéry Masson ◽  
Estelle de Coning ◽  
Alexander Baklanov ◽  
Jorge Amorim ◽  
Clotilde Augros ◽  
...  

<p>The WMO World Weather Research Programme (WWRP) “promotes international and interdisciplinary research for more accurate and reliable forecasts from minutes to seasons, expanding the frontiers of weather science to enhance society’s resilience to high-impact weather and the value of weather information for users. In the 2016-2023 WWRP implementation plan, activities focus on 4 challenges: High-Impact Weather, Water, Urbanization, Evolving technologies. Furthermore, the WMO Global Atmosphere Watch Urban Research Meteorology and Environment (GURME) focus on the development of models and associated research activities to enhance the capabilities in providing urban-environmental forecasting and air quality services, illustrating the linkages between meteorology and air quality (https://public.wmo.int/en/programmes).</p><p>This talk presents an international Research Demonstration Project (RDP), that will focus on international research on scientific urban issues addressed by both WWRP and GURME. The strategic objective of this RDP is to focus on the Olympic Games of Paris in 2024 in order to advance research on the theme of the “future Meteorological Forecasting systems at 100m (or finer) resolution for urban areas”. Such systems would prefigure the numerical weather prediction at the horizon 2030. The focus will be on themes related to extreme weather events in summer which both are influenced by and impacts urbanization: thunderstorms and strong Urban Heat Islands, and their consequences.</p><p>There are 5 scientific questions that will be addressed during this Paris RDP:</p><ul><li>Nowcasting & Numerical Weather Prediction in cities at order 100m resolution</li> <li>High resolution thunderstorm nowcasting (probabilistic and deterministic) in the urban environment,  Urban heat islands, cool areas and air quality</li> <li>Nowcasting and forecast in coastal cities (for the Marseilles site)</li> <li>How to improve and better use observational networks in urban areas, including (big) non-conventional data</li> <li>Conception and Communication of tailored weather, climate, environmental information at infra-urban resolution.</li> </ul><p>Several High-Impact weather case studies were selected. Storm cases (starting with one the 10th July 2017) will allow to evaluate the role of the urban area on their enhancement. Extreme Heat wave aggravated by a strong Urban Heat Island are also studied (July 2019). Open urban data describing the agglomerations at very high resolution are provided. New innovative methods to produce maps of urban form characteristics (e.g. from street images) and meteorological data (from personal meteorological stations) will be explored.</p><p>This talk will describe these scientific questions, as well as the common methodology approach that is being discussed within the partners. A focus will be the international experimental campaign that will take place in 2022 over the Paris agglomeration, with an Intensive Observation Period in the summer 2022. Interactions between urban surface and the atmospheric boundary layer, the interactions between air quality and aerosols between city and biogenic plumes, and the local effect of urban trees on micro-climate and chemistry are some of the axes of the campaign. It will provide additional meteorological and air quality observations, to both help to improve the nowcasting and NWP systems at urban scale, and aim to define the required additional instrumentation that should be deployed during the Olympics games themselves.</p>


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