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

Időjárás ◽  
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.

scholarly journals The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

2021 ◽  
Author(s):  
Alberto Caldas-Alvarez ◽  
Samiro Khodayar ◽  
Peter Knippertz
Keyword(s):  
High Resolution ◽  
Temporal Resolution ◽  
Hydrological Cycle ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Small Scale ◽  
High Temporal Resolution ◽  
The Impact

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System-Zenith Total Delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ~700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 h to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological Cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the COnsortium for Small scale MOdelling (COSMO) model assimilating GPS, high- and low vertical resolution radiosoundings in model resolutions of 7 km, 2.8 km and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity, but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nimes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent three hours. This precipitation increase is brought about by the moistening of the 700  hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type, however the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. In follow-up experiments the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its numerical and physics updates, compared to its predecessor COSMO, are able to improve the quality of the simulations.

scholarly journals The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

2021 ◽  
Vol 2 (3) ◽  
pp. 561-580
Author(s):  
Alberto Caldas-Alvarez ◽  
Samiro Khodayar ◽  
Peter Knippertz
Keyword(s):  
High Resolution ◽  
Temporal Resolution ◽  
Hydrological Cycle ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Small Scale ◽  
High Temporal Resolution ◽  
The Impact

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation, and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System (GPS)-derived zenith total delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ∼ 700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the Consortium for Small-scale Modeling (COSMO) model assimilating GPS, high- and low-vertical-resolution radiosoundings in model resolutions of 7 km, 2.8 km, and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate for errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nîmes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent 3 h. This precipitation increase is brought about by the moistening of the 700 hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type; however, the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. Future work will aim at a generalization of these conclusions, investigating further cases of the autumn 2012, and the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its updates are able to improve the quality of the simulations.

scholarly journals Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Flood Prediction ◽  
Meteorological Model ◽  
The Impact ◽  
Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

scholarly journals Predicting Small-Scale, Short-Lived Downbursts: Case Study with the NWP Limited-Area ALARO Model for the Pukkelpop Thunderstorm

2015 ◽  
Vol 143 (3) ◽  
pp. 742-756 ◽  
Author(s):  
Pieter De Meutter ◽  
Luc Gerard ◽  
Geert Smet ◽  
Karim Hamid ◽  
Rafiq Hamdi ◽  
...  
Keyword(s):  
Prediction Models ◽  
Deep Convection ◽  
Weather Prediction ◽  
Parameterization Scheme ◽  
Small Scale ◽  
Limited Area ◽  
Operational Model ◽  
Music Festival ◽  
Forecast Models

Abstract The authors consider a thunderstorm event in 2011 during a music festival in Belgium that produced a short-lived downburst of a diameter of less than 100 m. This is far too small to be resolved by the kilometric resolutions of today’s operational numerical weather prediction models. Operational forecast models will not run at hectometric resolutions in the foreseeable future. The storm caused five casualties and raised strong societal questions regarding the predictability of such a traumatic weather event. In this paper it is investigated whether the downdrafts of a parameterization scheme of deep convection can be used as proxies for the unresolved downbursts. To this end the operational model ALARO [a version of the Action de Recherche Petite Echelle Grande Echelle-Aire Limitée Adaptation Dynamique Développement International (ARPEGE-ALADIN) operational limited area model with a revised and modular structure of the physical parameterizations] of the Royal Meteorological Institute of Belgium is used. While the model in its operational configuration at the time of the event did not give a clear hint of a downburst event, it has been found that (i) the use of unsaturated downdrafts and (ii) some adaptations of the features of this downdraft parameterization scheme, specifically the sensitivity to the entrainment and friction, can make the downdrafts sensitive enough to the surrounding resolved-scale conditions to make them useful as indicators of the possibility of such downbursts.

scholarly journals Impact of Assimilating China Precipitation Analysis Data Merging with Remote Sensing Products Using the 4DVar Method on the Prediction of Heavy Rainfall

2019 ◽  
Vol 11 (8) ◽  
pp. 973 ◽  
Author(s):  
Yuanbing Wang ◽  
Yaodeng Chen ◽  
Jinzhong Min
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Weather Prediction ◽  
Eastern China ◽  
Wrf Model ◽  
Analysis Data ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Precipitation Analysis ◽  
The Impact

In this study, the China Hourly Merged Precipitation Analysis (CHMPA) data which combines the satellite-retrieved Climate Prediction Center Morphing (CMORPH) with the automatic weather station precipitation observations is firstly assimilated into the Weather Research and Forecasting (WRF) model using the Four-Dimensional Variational (4DVar) method. The analyses and subsequent forecasts of heavy rainfall during Meiyu season occurred in July 2013 over eastern China is evaluated. Besides, the sensitivity of rainfall forecast skill of assimilating the CHMPA data to the rainfall error, the rainfall thinning distance, and the rainfall accumulation time within assimilation window are investigated in this study. Then, the impact of 4DVar data assimilation with and without CHMPA rainfall data is evaluated to show how the assimilation of CHMPA impacts the precipitation simulations. It is found that assimilation of the CHMPA data helps to produce a better short-range precipitation forecast in this study. The rainfall fields after assimilation of CHMPA is closer to observations in terms of quantity and pattern. However, the leading time of improved forecast is limited to about 18 hours. It is also found that CHMPA data assimilation produces stronger realistic moisture divergence, precipitabale water field and the vertical wind field in the forecasting fields, which eventually contributes to the improved forecast of heavy rainfall. This study can provide references for the assimilation of CHMPA data into the WRF model using 4DVar, which is valuable for limited-area numerical weather prediction and hydrological applications.

scholarly journals Data assimilation of radar reflectivity volumes in a LETKF scheme

2018 ◽  
Vol 25 (4) ◽  
pp. 747-764 ◽  
Author(s):  
Thomas Gastaldo ◽  
Virginia Poli ◽  
Chiara Marsigli ◽  
Pier Paolo Alberoni ◽  
Tiziana Paccagnella
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Skill Score ◽  
Radar Reflectivity ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Observational Error ◽  
The Impact

Abstract. Quantitative precipitation forecast (QPF) is still a challenge for numerical weather prediction (NWP), despite the continuous improvement of models and data assimilation systems. In this regard, the assimilation of radar reflectivity volumes should be beneficial, since the accuracy of analysis is the element that most affects short-term QPFs. Up to now, few attempts have been made to assimilate these observations in an operational set-up, due to the large amount of computational resources needed and due to several open issues, like the rise of imbalances in the analyses and the estimation of the observational error. In this work, we evaluate the impact of the assimilation of radar reflectivity volumes employing a local ensemble transform Kalman filter (LETKF), implemented for the convection-permitting model of the COnsortium for Small-scale MOdelling (COSMO). A 4-day test case on February 2017 is considered and the verification of QPFs is performed using the fractions skill score (FSS) and the SAL technique, an object-based method which allows one to decompose the error in precipitation fields in terms of structure (S), amplitude (A) and location (L). Results obtained assimilating both conventional data and radar reflectivity volumes are compared to those of the operational system of the Hydro-Meteo-Climate Service of the Emilia-Romagna Region (Arpae-SIMC), in which only conventional observations are employed and latent heat nudging (LHN) is applied using surface rainfall intensity (SRI) estimated from the Italian radar network data. The impact of assimilating reflectivity volumes using LETKF in combination or not with LHN is assessed. Furthermore, some sensitivity tests are performed to evaluate the effects of the length of the assimilation window and of the reflectivity observational error (roe). Moreover, balance issues are assessed in terms of kinetic energy spectra and providing some examples of how these affect prognostic fields. Results show that the assimilation of reflectivity volumes has a positive impact on QPF accuracy in the first few hours of forecast, both when it is combined with LHN or not. The improvement is further slightly enhanced when only observations collected close to the analysis time are assimilated, while the shortening of cycle length worsens QPF accuracy. Finally, the employment of too small a value of roe introduces imbalances into the analyses, resulting in a severe degradation of forecast accuracy, especially when very short assimilation cycles are used.

scholarly journals A case study of the impact of INSAT derived humidity profiles on precipitation forecast by limited area model

MAUSAM ◽  
2022 ◽  
Vol 52 (4) ◽  
pp. 647-654
Author(s):  
Y .V. RAMA RAO ◽  
K. PRASAD ◽  
SANT PRASAD
Keyword(s):  
Regional Analysis ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Forecast System ◽  
Rainfall Prediction ◽  
Moisture Analysis ◽  
Analysis Scheme ◽  
The Impact ◽  
Humidity Profiles

The impact of humidity profiles estimated from INSAT digital IR cloud imagery data on initial moisture analysis in the IMD's operational limited area forecast system has been investigated. Method for assimilation of humidity profiles data as pseudo observations in the analysis scheme has been developed and implemented in the regional analysis scheme. Verification of humidity analysis with this data has shown substantial improvements in the moisture analysis over the data sparse region of tropics. Impact of the improved humidity analysis on model predicted rainfall is examined. The experiments show improved rainfall prediction.

scholarly journals A Numerical Sensitivity Study on the Impact of Soil Moisture on Convection-Related Parameters and Convective Precipitation over Complex Terrain

2011 ◽  
Vol 68 (12) ◽  
pp. 2971-2987 ◽  
Author(s):  
Christian Barthlott ◽  
Norbert Kalthoff
Keyword(s):  
Soil Moisture ◽  
Complex Terrain ◽  
Weather Prediction ◽  
Sensitivity Study ◽  
Convective Precipitation ◽  
Small Scale ◽  
Near Surface ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
The Impact

Abstract The impact of soil moisture on convection-related parameters and convective precipitation over complex terrain is studied by numerical experiments using the nonhydrostatic Consortium for Small-Scale Modeling (COSMO) model. For 1 day of the Convective and Orographically Induced Precipitation Study (COPS) conducted during summer 2007 in southwestern Germany and eastern France, initial soil moisture is varied from −50% to +50% of the reference run in steps of 5%. As synoptic-scale forcing is weak on the day under investigation, the triggering of convection is mainly due to soil–atmosphere interactions and boundary layer processes. Whereas a systematic relationship to soil moisture exists for a number of variables (e.g., latent and sensible fluxes at the ground, near-surface temperature, and humidity), a systematic increase of 24-h accumulated precipitation with increasing initial soil moisture is only present in the simulations that are drier than the reference run. The time evolution of convective precipitation can be divided into two regimes with different conditions to initiate and foster convection. Furthermore, the impact of soil moisture is different for the initiation and modification of convective precipitation. The results demonstrate the high sensitivity of numerical weather prediction to initial soil moisture fields.

scholarly journals An idealized model sensitivity study on Dead Sea desertification with a focus on the impact on convection

2020 ◽  
Vol 20 (20) ◽  
pp. 12011-12031
Author(s):  
Samiro Khodayar ◽  
Johannes Hoerner
Keyword(s):  
Weather Prediction ◽  
Lower Boundary ◽  
Heavy Precipitation ◽  
Bare Soil ◽  
Dead Sea ◽  
Small Scale ◽  
Limited Area ◽  
Decadal Scale ◽  
The Dead ◽  
The Impact

Abstract. The Dead Sea desertification-threatened region is affected by continual lake level decline and occasional but life-endangering flash floods. Climate change has aggravated such issues in the past decades. In this study, the impact on local conditions leading to heavy precipitation from the changing conditions of the Dead Sea is investigated. Idealized sensitivity simulations with the high-resolution COSMO-CLM (COnsortium for Small-scale MOdelling and Climate Limited-area Modelling) and several numerical weather prediction (NWP) runs on an event timescale are performed on the Dead Sea area. The simulations are idealized in the sense that the Dead Sea model representation does not accurately represent the real conditions but those given by an external dataset. A reference or Dead Sea simulation covering the 2003–2013 period and a twin sensitivity or bare soil simulation in which the Dead Sea is set to bare soil are compared. NWP simulations focus on heavy precipitation events exhibiting relevant differences between the Dead Sea and the bare soil decadal realization to assess the impact on the underlying convection-related processes. The change in the conditions of the Dead Sea is seen to affect the atmospheric conditions leading to convection in two ways. (a) The local decrease in evaporation reduces moisture availability in the lower boundary layer locally and in the neighbouring regions, directly affecting atmospheric stability. Weaker updraughts characterize the drier and more stable atmosphere of the simulations in which the Dead Sea has been dried out. (b) Thermally driven wind system circulations and resulting divergence/convergence fields are altered, preventing in many occasions the initiation of convection because of the omission of convergence lines. On a decadal scale, the difference between the simulations suggests a weak decrease in evaporation, higher air temperatures and less precipitation (less than 0.5 %).

scholarly journals Data assimilation of radar reflectivity volumes in a LETKF scheme

2018 ◽  
Author(s):  
Thomas Gastaldo ◽  
Virginia Poli ◽  
Chiara Marsigli ◽  
Pier Paolo Alberoni ◽  
Tiziana Paccagnella
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Radar Reflectivity ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Test Case ◽  
Observational Error ◽  
Structure Amplitude ◽  
Emilia Romagna Region ◽  
The Impact

Abstract. Quantitative precipitation forecast (QPF) is still a challenge for numerical weather prediction (NWP), despite the continuous improvement of models and data assimilation systems. In this regard, the assimilation of radar reflectivity volumes should be beneficial, since the accuracy of analysis is the element that most affects short-term QPFs. Up to now, very fewattempts have been made to assimilate these observations in an operational set-up, due to the large amount of computational resources needed and to several open issues, like the arise of imbalances in the analyses and the estimation of the observational error. In this work, it is evaluated the impact of the assimilation of radar reflectivity volumes employing a Local Ensemble Transform Kalman Filter (LETKF), implemented for the convection permitting model of the COnsortium for Small-scale Modelling (COSMO). A 4 days test case on February 2017 is considered and QPF is evaluated in terms of the SAL technique, an object-based method which allows to evaluate structure, amplitude and location of precipitation fields Results obtained assimilating radar reflectivity volumes are compared to those of the operational system of the Hydro-Meteo-Climate Service of the Emilia-Romagna region (Arpae-SIMC), in which only conventional data are employed. Furthermore, some sensitivity tests are performed to evaluate the impact of the additive inflation, of the lenght of assimilation windows and of the reflectivity observational error. Finally, balance issues are assessed in terms of kinetic energy spectra and providing some examples of how these affect prognostic fields.

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