scholarly journals Dynamical contribution of mean potential vorticity pseudo-observations derived from MetOp/GOME2 ozone data into short-range weather forecast during high precipitation events

2015 ◽  
Vol 4 (2) ◽  
pp. 206
Author(s):  
Siham Sbii ◽  
Mimoun Zazoui ◽  
Noureddine Semane
Keyword(s):  
Potential Vorticity ◽  
Short Range ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Dynamical Behavior ◽  
Heavy Precipitation ◽  
Limited Area ◽  
Total Column Ozone ◽  
Ozone Data ◽  
Precipitation Events

<p>Satellites are uniquely capable of providing uniform data coverage globally. Motivated by such capability, this study builds on a previously described methodology that generates numerical weather prediction initial conditions from satellite total column ozone data. The methodology is based on two principal steps. Firstly, the studied linear regression between vertical (100hPa-500hPa) Mean Potential Vorticity (MPV) and MetOp/GOME2 total ozone data (O3) generates MPV pseudo-observations. Secondly, the 3D variational (3D-Var) assimilation method is designed to take into account MPV pseudo-observations in addition to conventional observations.</p><p>After a successful assimilation of MPV pseudo-observations using a 3D-Var approach within the Moroccan version of the ALADIN limited-area model, the present study aims to assess the dynamical behavior of the short-range forecast at upper levels during heavy precipitation events (HPEs). It is found that MPV assimilation offers the possibility to internally monitor the model upper-level dynamics in addition to the use of Water Vapor Satellite images.</p>

scholarly journals Short-Range Numerical Weather Prediction of Extreme Precipitation Events Using Enhanced Surface Data Assimilation

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 587
Author(s):  
Magnus Lindskog ◽  
Tomas Landelius
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Short Range ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Numerical Weather ◽  
Extreme Precipitation Events ◽  
Surface Data ◽  
Enhanced Surface ◽  
Precipitation Events

A limited-area kilometre scale numerical weather prediction system is applied to evaluate the effect of refined surface data assimilation on short-range heavy precipitation forecasts. The refinements include a spatially dependent background error representation, use of a flow-dependent data assimilation technique, and use of data from a satellite-based scatterometer instrument. The effect of the enhancements on short-term prediction of intense precipitation events is confirmed through a number of case studies. Verification scores and subjective evaluation of one particular case points at a clear impact of the enhanced surface data assimilation on short-range heavy precipitation forecasts and suggest that it also tends to slightly improve them. Although this is not strictly statistically demonstrated, it is consistent with the expectation that a better surface state should improve rainfall forecasts.

scholarly journals Perturbing the potential vorticity field in mesoscale forecasts of two Mediterranean heavy precipitation events

2012 ◽  
Vol 64 (1) ◽  
pp. 17224 ◽  
Author(s):  
Maria-Del-Mar Vich ◽  
Romualdo Romero ◽  
Evelyne Richard ◽  
Philippe Arbogast ◽  
Karine Maynard
Keyword(s):  
Potential Vorticity ◽  
Heavy Precipitation ◽  
Vorticity Field ◽  
Precipitation Events

scholarly journals Dynamical and Physical Processes Leading to Tropical Cyclone Intensification under Upper-Level Trough Forcing

2013 ◽  
Vol 70 (8) ◽  
pp. 2547-2565 ◽  
Author(s):  
Marie-Dominique Leroux ◽  
Matthieu Plu ◽  
David Barbary ◽  
Frank Roux ◽  
Philippe Arbogast
Keyword(s):  
Angular Momentum ◽  
Tropical Cyclone ◽  
Potential Vorticity ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
Thick Layer ◽  
Limited Area ◽  
Southwest Indian Ocean ◽  
Upper Level

Abstract The rapid intensification of Tropical Cyclone (TC) Dora (2007, southwest Indian Ocean) under upper-level trough forcing is investigated. TC–trough interaction is simulated using a limited-area operational numerical weather prediction model. The interaction between the storm and the trough involves a coupled evolution of vertical wind shear and binary vortex interaction in the horizontal and vertical dimensions. The three-dimensional potential vorticity structure associated with the trough undergoes strong deformation as it approaches the storm. Potential vorticity (PV) is advected toward the tropical cyclone core over a thick layer from 200 to 500 hPa while the TC upper-level flow turns cyclonic from the continuous import of angular momentum. It is found that vortex intensification first occurs inside the eyewall and results from PV superposition in the thick aforementioned layer. The main pathway to further storm intensification is associated with secondary eyewall formation triggered by external forcing. Eddy angular momentum convergence and eddy PV fluxes are responsible for spinning up an outer eyewall over the entire troposphere, while spindown is observed within the primary eyewall. The 8-km-resolution model is able to reproduce the main features of the eyewall replacement cycle observed for TC Dora. The outer eyewall intensifies further through mean vertical advection under dynamically forced upward motion. The processes are illustrated and quantified using various diagnostics.

scholarly journals Limited-area short-range ensemble predictions targeted for heavy rain in Europe

2005 ◽  
Vol 9 (4) ◽  
pp. 300-312 ◽  
Author(s):  
K. Sattler ◽  
H. Feddersen
Keyword(s):  
Short Range ◽  
Weather Prediction ◽  
Heavy Rain ◽  
River Basins ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Target Area ◽  
Extreme Rainfall Events ◽  
Ensemble Prediction System ◽  
Area Of Interest

Abstract. Inherent uncertainties in short-range quantitative precipitation forecasts (QPF) from the high-resolution, limited-area numerical weather prediction model DMI-HIRLAM (LAM) are addressed using two different approaches to creating a small ensemble of LAM simulations, with focus on prediction of extreme rainfall events over European river basins. The first ensemble type is designed to represent uncertainty in the atmospheric state of the initial condition and at the lateral LAM boundaries. The global ensemble prediction system (EPS) from ECMWF serves as host model to the LAM and provides the state perturbations, from which a small set of significant members is selected. The significance is estimated on the basis of accumulated precipitation over a target area of interest, which contains the river basin(s) under consideration. The selected members provide the initial and boundary data for the ensemble integration in the LAM. A second ensemble approach tries to address a portion of the model-inherent uncertainty responsible for errors in the forecasted precipitation field by utilising different parameterisation schemes for condensation and convection in the LAM. Three periods around historical heavy rain events that caused or contributed to disastrous river flooding in Europe are used to study the performance of the LAM ensemble designs. The three cases exhibit different dynamic and synoptic characteristics and provide an indication of the ensemble qualities in different weather situations. Precipitation analyses from the Deutsche Wetterdienst (DWD) are used as the verifying reference and a comparison of daily rainfall amounts is referred to the respective river basins of the historical cases.

scholarly journals Impact Assessment of Daily Satellite-Derived Surface Albedo in a Limited-Area NWP Model

2012 ◽  
Vol 51 (10) ◽  
pp. 1835-1854 ◽  
Author(s):  
Jure Cedilnik ◽  
Dominique Carrer ◽  
Jean-François Mahfouf ◽  
Jean-Louis Roujean
Keyword(s):  
Land Surface ◽  
Short Range ◽  
Surface Albedo ◽  
Weather Prediction ◽  
A Priori ◽  
Limited Area ◽  
Model Biases ◽  
Nwp Model ◽  
The Impact ◽  
Range Forecasts

AbstractThis study examines the impact of daily satellite-derived albedos on short-range forecasts in a limited-area numerical weather prediction (NWP) model over Europe. Contrary to previous studies in which satellite products were used to derive monthly “climatologies,” a daily surface (snow free) albedo is analyzed by a Kalman filter. The filter combines optimally a satellite product derived from the Meteosat Second Generation geostationary satellite [and produced by the Land Surface Analyses–Satellite Application Facility of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], an albedo climatology, and a priori information given by “persistence.” The surface albedo analyzed for a given day is used as boundary conditions of the NWP model to run forecasts starting the following day. Results from short-range forecasts over a 1-yr period reveal the capacity of satellite information to reduce model biases and RMSE in screen-level temperature (during daytime and intermediate seasons). The impact on forecast scores is larger when considering the analyzed surface albedo rather than another climatologically based albedo product. From comparisons with measurements from three flux-tower stations over mostly homogeneous French forests, it is seen that the model biases in surface net radiation are significantly reduced. An impact on the whole planetary boundary layer, particularly in summer, results from the use of an observed surface albedo. An unexpected behavior produced in summer by the satellite-derived albedo on surface temperature is also explained. The forecast runs presented here, performed in dynamical adaptation mode, will be complemented later on by data assimilation experiments over typically monthly periods.

Impact of FORMOSAT-7/COSMIC-2 RO on High-Resolution Hybrid 3DEnVar System at Central Weather Bureau of Taiwan

2020 ◽  
Author(s):  
Jing-Shan Hong ◽  
Wen-Jou Chen ◽  
Ying-Jhen Chen ◽  
Siou-Ying Jiang ◽  
Chin-Tzu Fong
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Precipitation Forecast ◽  
Preliminary Evaluation ◽  
Satellite Mission ◽  
Background Error ◽  
Weather Bureau ◽  
Central Weather Bureau ◽  
Precipitation Events

&lt;p&gt;The FORMOSAT-7/COSMIC-2 (simplified as FS-7/C-2 in the following descriptions) is the constellation of satellites for meteorology, ionosphere, climatology, and space weather research. FS-7/C-2 was a joint Taiwan-U.S. satellite mission that makes use of the radio occultation (RO) measurement technique. FORMOSAT-7 is the successor of FORMOSAT-3 which was launched in 2006. the FORMOSAT-3 RO data has been shown to be extremely valuable for numerical weather prediction, such as improving the prediction of tropical cyclogenesis and reducing the typhoon track error. The follow-on FS-7/C-2 mission was launched on 25 June 2019, and is currently going through preliminary testing and evaluation. After it is fully deployed, FS-7/C-2 is expected to provide 6,000 GNSS (Global Navigation Satellite System) RO profiles per day between 40S and 40N. &amp;#160;&lt;/p&gt;&lt;p&gt;In this study, we conduct a preliminary evaluation of FS-7/C-2 GNSS RO data on heavy precipitation events associated with typhoon and southwesterly monsoon flows based on the operational NWP system of the Central Weather Bureau (CWB) in Taiwan. The FS-7/C-2 GNSS RO data are assimilated using a dual-resolution hybrid 3DEnVare system with a 15-3 km nested-grid configuration. In the 15km resolution domain, flow-dependent background error covariances (BECs) derived from the perturbation of ensemble adjustment Kalman filter (EAKF), will be used to conduct hybrid 3DEnVar analysis. In the 3 km resolution domain, the 15 km resolution flow-dependent BECs will be inserted to the 3 km grid using a Dual-Resolution (DR) technique, and then combined with 3 km resolution static BECs, to perform the high-resolution 3DEnVar analysis. The performance of the CWB operational NWP system on quantitative precipitation forecast of significant precipitation events with and without the assimilation of FS-7/C-2 GNSS RO data will be evaluated.&lt;/p&gt;

LIMITED AREA WEATHER PREDICTION MODELS VIEWED AS DYNAMICAL SYSTEMS

1999 ◽  
Vol 09 (05) ◽  
pp. 831-842 ◽  
Author(s):  
F. CHOMÉ ◽  
C. NICOLIS
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Dynamical Behavior ◽  
Limited Area ◽  
Initial State ◽  
Weather Forecasts ◽  
Fine Mesh ◽  
Area Of Interest ◽  
Variable Mesh ◽  
High Resolution Models

Different strategies for building high-resolution models providing a more detailed description of a limited area of interest as for example, in regional weather forecasts are developed. They are subsequently compared, on the basis of the dynamical behavior generated by the corresponding models. The statistical properties of the relevant fields are analyzed, and predictability experiments are performed on statistical ensembles of close lying trajectories whose mean distance represents the uncertainty in the initial state of the system. The results show that a global, variable-mesh model performs much better than a limited area fine mesh one embedded into a coarser global model.

scholarly journals A case study carried out with two different NWP systems

2006 ◽  
Vol 6 (5) ◽  
pp. 755-760
Author(s):  
P. Kållberg ◽  
A. Montani
Keyword(s):  
Weather Prediction ◽  
Heavy Precipitation ◽  
Northern Italy ◽  
Limited Area ◽  
Model Intercomparison ◽  
Atmospheric Models ◽  
Screen Level ◽  
Prediction Systems ◽  
Surface Fields

Abstract. A model intercomparison between two atmospheric models, the non–hydrostatic Lokal Modell (LM) and the hydrostatic HIgh Resolution Limited Area Model (HIRLAM) is carried out for a one-week period, including a case of cyclogeneis leading to heavy precipitation over Northern Italy. The two models, very different in terms of data-assimilation and numerics, provide different results in terms of forecasts of surface fields. Opposite diurnal biases for the two models are found in terms of screen level temperatures. HIRLAM wind speed forecasts are too strong, while LM precipitation forecasts have larger extremes. The intercomparison exercise identifies some systematic differences in the weather products generated by the two systems and sheds some light on the biases of the two numerical weather prediction systems.

scholarly journals Regionally Enhanced Global (REG) 4D-Var

2018 ◽  
Vol 146 (12) ◽  
pp. 4015-4038
Author(s):  
Michael A. Herrera ◽  
Istvan Szunyogh ◽  
Adam Brainard ◽  
David D. Kuhl ◽  
Karl Hoppel ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Computational Cost ◽  
Limited Area ◽  
Atmospheric Flow ◽  
Forecast Performance ◽  
Limited Area Model ◽  
Area Model

Abstract A regionally enhanced global (REG) data assimilation (DA) method is proposed. The technique blends high-resolution model information from a single or multiple limited-area model domains with global model and observational information to create a regionally enhanced analysis of the global atmospheric state. This single analysis provides initial conditions for both the global and limited-area model forecasts. The potential benefits of the approach for operational data assimilation are (i) reduced development cost, (ii) reduced overall computational cost, (iii) improved limited-area forecast performance from the use of global information about the atmospheric flow, and (iv) improved global forecast performance from the use of more accurate model information in the limited-area domains. The method is tested by an implementation on the U.S. Navy’s four-dimensional variational global data assimilation system and global and limited-area numerical weather prediction models. The results of the monthlong forecast experiments suggest that the REG DA approach has the potential to deliver the desired benefits.

scholarly journals Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations

2020 ◽  
Author(s):  
Alexane Lovat ◽  
Béatrice Vincendon ◽  
Véronique Ducrocq
Keyword(s):  
Emergency Services ◽  
Flash Flood ◽  
Weather Prediction ◽  
Coupled System ◽  
Heavy Precipitation ◽  
Point Of View ◽  
Lead Times ◽  
Numerical Weather ◽  
Weather Model ◽  
Precipitation Events

Abstract. Heavy precipitation events and subsequent flash floods regularly affect the Mediterranean coastal regions. In these situations, forecasting rainfall and river discharges is crucial especially up to six hours, which is a relevant lead time for emergency services in crisis time. The present study investigates the hydrometeorological skills of two new nowcasting systems: a numerical weather model AROME-NWC and a nowcasting system blending numerical weather prediction and extrapolation of radar estimation called PIAF. Their performance is assessed for 10 past heavy precipitation events that occured in southeastern France. Precipitation forecasts are evaluated at a 15 min time resolution and the availability times of forecasts, based on the operational Météo-France suites, are taken into account when performing the evaluation. Rainfall observations and forecasts were first compared using a point-to-point approach. Then the evaluation was conducted from an hydrologic point of view, by comparing observed and forecast precipitation over watersheds affected by floods. In general, the results led to the same conclusions for both evaluations. On the very first lead times, up to 1 h 15/1 h 30 of forecast, the performance of PIAF is higher than AROME-NWC. For longer lead times (up to 3 h) their performance are equivalent in general. An assessment of river discharges simulated with the ISBA-TOP coupled system, which is dedicated to Mediterranean flash-flood simulations, forced by AROME-NWC and PIAF rainfall forecasts, was also performed on two exceptional past flash flood events. The results obtained for these two events show that using AROME-NWC or PIAF rainfall forecasts is promising for flash-flood forecasting in terms of peak intensity, timing, and first rise of discharge, with an anticipation of these phenomena that can reach several hours.

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