Role of initial condition and parametric uncertainty in a severe hailstorm forecast

2021 ◽  
Author(s):  
Patrick Kuntze ◽  
Annette Miltenberger ◽  
Corinna Hoose ◽  
Michael Kunz
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Parametric Uncertainty ◽  
Radar Data ◽  
Cloud Microphysics ◽  
Initial Condition ◽  
Relative Contribution ◽  
Cloud Properties ◽  
Set Up ◽  
The Impact

<p>Forecasting high impact weather events is a major challenge for numerical weather prediction. Initial condition uncertainty plays a major role but so potentially do uncertainties arising from the representation of physical processes, e.g. cloud microphysics. In this project, we investigate the impact of these uncertainties for the forecast of cloud properties, precipitation and hail of a selected severe convective storm over South-Eastern Germany.<br>To investigate the joint impact of initial condition and parametric uncertainty a large ensemble including perturbed initial conditions and systematic variations in several cloud microphysical parameters is conducted with the ICON model (at 1 km grid-spacing). The comparison of the baseline, unperturbed simulation to satellite, radiosonde, and radar data shows that the model reproduces the key features of the storm and its evolution. In particular also substantial hail precipitation at the surface is predicted. Here, we will present first results including the simulation set-up, the evaluation of the baseline simulation, and the variability of hail forecasts from the ensemble simulation.<br>In a later stage of the project we aim to assess the relative contribution of the introduced model variations to changes in the microphysical evolution of the storm and to the fore- cast uncertainty in larger-scale meteorological conditions.</p>

scholarly journals Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress

2018 ◽  
Vol 33 (2) ◽  
pp. 599-607 ◽  
Author(s):  
John R. Lawson ◽  
John S. Kain ◽  
Nusrat Yussouf ◽  
David C. Dowell ◽  
Dustan M. Wheatley ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Initial Conditions ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Radar Data ◽  
Model Systems ◽  
Deterministic Systems ◽  
Forecast Lead Time ◽  
The Impact

Abstract The Warn-on-Forecast (WoF) program, driven by advanced data assimilation and ensemble design of numerical weather prediction (NWP) systems, seeks to advance 0–3-h NWP to aid National Weather Service warnings for thunderstorm-induced hazards. An early prototype of the WoF prediction system is the National Severe Storms Laboratory (NSSL) Experimental WoF System for ensembles (NEWSe), which comprises 36 ensemble members with varied initial conditions and parameterization suites. In the present study, real-time 3-h quantitative precipitation forecasts (QPFs) during spring 2016 from NEWSe members are compared against those from two real-time deterministic systems: the operational High Resolution Rapid Refresh (HRRR, version 1) and an upgraded, experimental configuration of the HRRR. All three model systems were run at 3-km horizontal grid spacing and differ in initialization, particularly in the radar data assimilation methods. It is the impact of this difference that is evaluated herein using both traditional and scale-aware verification schemes. NEWSe, evaluated deterministically for each member, shows marked improvement over the two HRRR versions for 0–3-h QPFs, especially at higher thresholds and smaller spatial scales. This improvement diminishes with forecast lead time. The experimental HRRR model, which became operational as HRRR version 2 in August 2016, also provides added skill over HRRR version 1.

scholarly journals Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

2014 ◽  
Vol 18 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Katarzyna Ośródka ◽  
Jan Szturc ◽  
Bogumił Jakubiak ◽  
Anna Jurczyk
Keyword(s):  
Quality Control ◽  
Data Assimilation ◽  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Weather Radar ◽  
Radar Data ◽  
Field Pattern ◽  
The Impact ◽  
Radar Data Assimilation

Abstract The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.

The Effect of Topographic Variability on Initial Condition Sensitivity of Low-Level Wind Forecasts. Part II: Experiments Using Real Terrain and Observations

2013 ◽  
Vol 141 (7) ◽  
pp. 2156-2172 ◽  
Author(s):  
Paul E. Bieringer ◽  
Peter S. Ray ◽  
Andrew J. Annunzio
Keyword(s):  
Doppler Radar ◽  
Initial Conditions ◽  
Surface Wind ◽  
Forecast Accuracy ◽  
Radar Data ◽  
Model Verification ◽  
Initial Condition ◽  
Terrain Elevation ◽  
The Impact ◽  
Topographic Variability

Abstract A study by Bieringer et al., which is Part I of this two-part study, demonstrated analytically using the shallow-water equations and numerically in controlled experiments that the presence of terrain can result in an enhancement of sensitivities to initial condition adjustments. The increased impact of adjustments to initial conditions corresponds with gradients in the flow field induced by the presence of the terrain obstacle. In cross-barrier flow situations the impact of the initial condition adjustments on the final forecast increases linearly as the height of the terrain obstacle increases. While this property associated with initial condition perturbations may be present in an analytic and controlled numerical environment, it is often difficult to realize these benefits in a more operationally realistic setting. This study extends the prior work to a situation with actual terrain, Doppler radar wind observations over the terrain, and observations from a surface mesonet for model verification. The results indicate that the downstream surface wind forecast was improved more when the initial conditions adjusted through the assimilation of Doppler radar data originated from areas with terrain gradients than from regions where the terrain was relatively flat. This result is consistent with the findings presented in Part I and suggests that when varying terrain elevation is present upstream of a target forecast area, a greater benefit (in terms of forecast accuracy) can be made by targeting additional observations in the regions containing variable terrain than regions where the terrain is relatively flat.

scholarly journals Effects of Multiple Doppler Radar data assimilation on the numerical simulation of a Flash Flood Event during the HyMeX campaign

2016 ◽  
Author(s):  
Ida Maiello ◽  
Sabrina Gentile ◽  
Rossella Ferretti ◽  
Luca Baldini ◽  
Nicoletta Roberto ◽  
...  
Keyword(s):  
Hydrological Cycle ◽  
Initial Conditions ◽  
Flash Flood ◽  
Weather Prediction ◽  
Central Italy ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Horizontal Resolution ◽  
Precipitation Event ◽  
The Impact

Abstract. An analysis to evaluate the impact of assimilating multiple radar data with a three dimensional variational (3D-Var) system on a heavy precipitation event is presented. The main goal is to establish a general methodology to quantitatively assess the performance of flash-flood numerical weather prediction at mesoscale. In this respect, during the first Special Observation Period (SOP1) of HyMeX (Hydrological cycle in the Mediterranean Experiment) campaign several Intensive Observing Periods (IOPs) were launched and nine occurred in Italy. Among them IOP4 is chosen for this study because of its low predictability. This event hit central Italy on 14 September 2012 producing heavy precipitation and causing several damages. Data taken from three C-band radars running operationally during the event are assimilated to improve high resolution initial conditions. In order to evaluate the impact of the assimilation procedure at different horizontal resolution and to assess the impact of assimilating multiple radars data, several experiments using Weather Research and Forecasting (WRF) model are performed. Finally, the statistical indexes as accuracy, equitable threat score, false alarm ratio and frequency bias are used to objectively compare the experiments, using rain gauges data as benchmark.

scholarly journals On Kaufmann's theory of the impact of the pianoforte hammer

1920 ◽  
Vol 97 (682) ◽  
pp. 99-110 ◽  
Keyword(s):  
Initial Conditions ◽  
Practical Importance ◽  
Prima Facie ◽  
Point Of View ◽  
Infinite Length ◽  
Modes Of Vibration ◽  
Rigorous Treatment ◽  
The Subject ◽  
Set Up ◽  
The Impact

The theory of the vibrations of the pianoforte string put forward by Kaufmann in a well-known paper has figured prominently in recent discussions on the acoustics of this instrument. It proceeds on lines radically different from those adopted by Helmholtz in his classical treatment of the subject. While recognising that the elasticity of the pianoforte hammer is not a negligible factor, Kaufmann set out to simplify the mathematical analysis by ignoring its effect altogether, and treating the hammer as a particle possessing only inertia without spring. The motion of the string following the impact of the hammer is found from the initial conditions and from the functional solutions of the equation of wave-propagation on the string. On this basis he gave a rigorous treatment of two cases: (1) a particle impinging on a stretched string of infinite length, and (2) a particle impinging on the centre of a finite string, neither of which cases is of much interest from an acoustical point of view. The case of practical importance treated by him is that in which a particle impinges on the string near one end. For this case, he gave only an approximate theory from which the duration of contact, the motion of the point struck, and the form of the vibration-curves for various points of the string could be found. There can be no doubt of the importance of Kaufmann’s work, and it naturally becomes necessary to extend and revise his theory in various directions. In several respects, the theory awaits fuller development, especially as regards the harmonic analysis of the modes of vibration set up by impact, and the detailed discussion of the influence of the elasticity of the hammer and of varying velocities of impact. Apart from these points, the question arises whether the approximate method used by Kaufmann is sufficiently accurate for practical purposes, and whether it may be regarded as applicable when, as in the pianoforte, the point struck is distant one-eighth or one-ninth of the length of the string from one end. Kaufmann’s treatment is practically based on the assumption that the part of the string between the end and the point struck remains straight as long as the hammer and string remain in contact. Primâ facie , it is clear that this assumption would introduce error when the part of the string under reference is an appreciable fraction of the whole. For the effect of the impact would obviously be to excite the vibrations of this portion of the string, which continue so long as the hammer is in contact, and would also influence the mode of vibration of the string as a whole when the hammer loses contact. A mathematical theory which is not subject to this error, and which is applicable for any position of the striking point, thus seems called for.

scholarly journals Application of Adjoint-Derived Forecast Sensitivities to the 24–25 January 2000 U.S. East Coast Snowstorm

2005 ◽  
Vol 133 (11) ◽  
pp. 3148-3175 ◽  
Author(s):  
Daryl T. Kleist ◽  
Michael C. Morgan
Keyword(s):  
Response Function ◽  
Initial Conditions ◽  
Forecast Error ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Initial Condition ◽  
Response Functions ◽  
Eastern United States ◽  
Surface Cyclone

Abstract The 24–25 January 2000 eastern United States snowstorm was noteworthy as operational numerical weather prediction (NWP) guidance was poor for lead times as short as 36 h. Despite improvements in the forecast of the surface cyclone position and intensity at 1200 UTC 25 January 2000 with decreasing lead time, NWP guidance placed the westward extent of the midtropospheric, frontogenetically forced precipitation shield too far to the east. To assess the influence of initial condition uncertainties on the forecast of this event, an adjoint model is used to evaluate forecast sensitivities for 36- and 48-h forecasts valid at 1200 UTC 25 January 2000 using as response functions the energy-weighted forecast error, lower-tropospheric circulation about a box surrounding the surface cyclone, 750-hPa frontogenesis, and vertical motion. The sensitivities with respect to the initial conditions for these response functions are in general very similar: geographically isolated, maximized in the middle and lower troposphere, and possessing an upshear vertical tilt. The sensitivities are maximized in a region of enhanced low-level baroclinicity in the vicinity of the surface cyclone’s precursor upper trough. However, differences in the phase and structure of the gradients for the four response functions are evident, which suggests that perturbations could be constructed to alter one response function but not necessarily the others. Gradients of the forecast error response function with respect to the initial conditions are used in an iterative procedure to construct initial condition perturbations that reduce the forecast error. These initial condition perturbations were small in terms of both spatial scale and magnitude. Those initial condition perturbations that were confined primarily to the midtroposphere grew rapidly into much larger amplitude upper-and-lower tropospheric perturbations. The perturbed forecasts were not only characterized by reduced final time forecast error, but also had a synoptic evolution that more closely followed analyses and observations.

scholarly journals Flash-flood early warning using weather radar data: from nowcasting to forecasting

2013 ◽  
Vol 10 (1) ◽  
pp. 1289-1331 ◽  
Author(s):  
K. Liechti ◽  
L. Panziera ◽  
U. Germann ◽  
M. Zappa
Keyword(s):  
Early Warning ◽  
Initial Conditions ◽  
Flash Flood ◽  
Weather Prediction ◽  
Probabilistic Approach ◽  
Radar Data ◽  
Swiss Alps ◽  
Probabilistic Forecasting ◽  
Orographic Rainfall ◽  
Forecasting System

Abstract. This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel probabilistic radar-based forecasting chains for flash-flood early warning are investigated in three catchments in the Southern Swiss Alps and set in relation to deterministic discharge forecast for the same catchments. The first probabilistic radar-based forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second probabilistic forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialized with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. We found a clear preference for the probabilistic approach. Discharge forecasts perform better when forced by NORA rather than by a persistent radar QPE for lead times up to eight hours and for all discharge thresholds analysed. The best results were, however, obtained with the REAL-C2 forecasting chain, which was also remarkably skilful even with the highest thresholds. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

Investigating triggering mechanisms for the large hailstorm event of July 10th, 2019 on the Adriatic Sea

2021 ◽  
Author(s):  
Antonio Ricchi ◽  
Vincenzo Mazzarella ◽  
Lorenzo Sangelantoni ◽  
Gianluca Redaelli ◽  
Rossella Ferretti
Keyword(s):  
Adriatic Sea ◽  
Initial Conditions ◽  
Central Italy ◽  
Radar Data ◽  
Sensitivity Study ◽  
Convective Cell ◽  
Sea Surface ◽  
Microphysics Scheme ◽  
The Balkans ◽  
The Impact

<div> <p><span>A severe weather events hit Italy on July 9-10, 2019 causing heavy damages by the falling of large-size hail. A trough from Northern Europe affected Italy and the Balkans advecting cold air on the Adriatic Sea. The intrusion of relatively cold and dry air on the Adriatic Sea, in a first stage through the "Bora jets" generated by the Dinaric Alps gave rise to a frontal structure on the ground, which rapidly moved from North to South Adriatic. The large thermal gradient (also with the sea surface), the interaction with the complex orography and the coastal zone, generated several storm structures along the eastern Italian coast. In particular, on 10 July 2019 between 8UTC and 12UTC a deep convective cell (probably a supercell) developed along the coast North of the city of Pescara, producing intense rainfall (accumulated rainfall reaching 130 mm/3h) and a violent hailstorm with hailstones larger than 10 cm in diameter. The storm quickly moved southward, evolving into a complex multicellular structure clearly visible by observing radar data. In this work the frontal dynamics and the genesis of the storm cell are investigated using the numerical model WRF (Weather Research and Forecasting system). Numerical experiments are carried out using a 1 km grid on Central Italy, initialized using the ECMWF dataset and the Sea Surface Temperature (SST) taken by MFS-CMEMS Copernicus dataset. The sensitivity study investigated both the impact of the initial conditions, the quality and the anomaly of the SST on the Adriatic basin in those days. Furthermore, in order to quantify the importance of the use of different microphysics, Planetary boundary Layer (PBL) and radiative schemes, several experiments are performed. The role of orography in the development and location of the convective cell is also investigated. Preliminary results show that initialization and SST played a fundamental role. In particular, the initialization several hours before the event, coupled with a detailed SST allows to correctly reproduce the atmospheric fields. The microphysics scheme turned out to play a key role for this event by showing a significant greater impact than the PBL, in terms of frontal genesis on both the synoptic and local scale. </span></p> </div>

scholarly journals Evaluation of Combined Satellite and Radar Data Assimilation with POD-4DEnVar Method on Rainfall Forecast

2020 ◽  
Vol 10 (16) ◽  
pp. 5493 ◽  
Author(s):  
Jingnan Wang ◽  
Lifeng Zhang ◽  
Jiping Guan ◽  
Mingyang Zhang
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Radar Data ◽  
Precipitation Forecast ◽  
Rainfall Forecast ◽  
Skill Scores ◽  
The Individual ◽  
The Impact ◽  
Radar Data Assimilation

Satellite and radar observations represent two fundamentally different remote sensing observation types, providing independent information for numerical weather prediction (NWP). Because the individual impact on improving forecast has previously been examined, combining these two resources of data potentially enhances the performance of weather forecast. In this study, satellite radiance, radar radial velocity and reflectivity are simultaneously assimilated with the Proper Orthogonal Decomposition (POD)-based ensemble four-dimensional variational (4DVar) assimilation method (referred to as POD-4DEnVar). The impact is evaluated on continuous severe rainfall processes occurred from June to July in 2016 and 2017. Results show that combined assimilation of satellite and radar data with POD-4DEnVar has the potential to improve weather forecast. Averaged over 22 forecasts, RMSEs indicate that though the forecast results are sensitive to different variables, generally the improvement is found in different pressure levels with assimilation. The precipitation skill scores are generally increased when assimilation is carried out. A case study is also examined to figure out the contributions to forecast improvement. Better intensity and distribution of precipitation forecast is found in the accumulated rainfall evolution with POD-4DEnVar assimilation. These improvements are attributed to the local changes in moisture, temperature and wind field. In addition, with radar data assimilation, the initial rainwater and cloud water conditions are changed directly. Both experiments can simulate the strong hydrometeor in the precipitation area, but assimilation spins up faster, strengthening the initial intensity of the heavy rainfall. Generally, the combined assimilation of satellite and radar data results in better rainfall forecast than without data assimilation.

scholarly journals Impacts of Assimilating ATMS Radiances on Heavy Rainfall Forecast in RMAPS-ST

2020 ◽  
Vol 12 (7) ◽  
pp. 1147
Author(s):  
Yanhui Xie ◽  
Min Chen ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Jing He ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Added Value ◽  
Rainfall Forecast ◽  
Hourly Rainfall ◽  
Radiance Data ◽  
The Impact

The Advanced Technology Microwave Sounder (ATMS) mounted on the Suomi National Polar-Orbiting Partnership (NPP) satellite can provide both temperature and humidity information for a weather prediction model. Based on the rapid-refresh multi-scale analysis and prediction system—short-term (RMAPS-ST), we investigated the impact of ATMS radiance data assimilation on strong rainfall forecasts. Two groups of experiments were conducted to forecast heavy precipitation over North China between 18 July and 20 July 2016. The initial conditions and forecast results from the two groups of experiments have been compared and evaluated against observations. In comparison with the first group of experiments that only assimilated conventional observations, some added value can be obtained for the initial conditions of temperature, humidity, and wind fields after assimilating ATMS radiance observations in the system. For the forecast results with the assimilation of ATMS radiances, the score skills of quantitative forecast rainfall have been improved when verified against the observed rainfall. The Heidke skill score (HSS) skills of 6-h accumulated precipitation in the 24-h forecasts were overall increased, more prominently so for the heavy rainfall above 25 mm in the 0–6 h of forecasts. Assimilating ATMS radiance data reduced the false alarm ratio of quantitative precipitation forecasting in the 0–12 h of the forecast range and thus improved the threat scores for the heavy rainfall storm. Furthermore, the assimilation of ATMS radiances improved the spatial distribution of hourly rainfall forecast with observations compared with that of the first group of experiments, and the mean absolute error was reduced in the 10-h lead time of forecasts. The inclusion of ATMS radiances provided more information for the vertical structure of features in the temperature and moisture profiles, which had an indirect positive impact on the forecasts of the heavy rainfall in the RMAPS-ST system. However, the deviation in the location of the heavy rainfall center requires future work.

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