scholarly journals Verification of precipitation forecasts of MM5 model over Epirus, NW Greece, for various convective parameterization schemes

2012 ◽  
Vol 12 (5) ◽  
pp. 1393-1405 ◽  
Author(s):  
O. A. Sindosi ◽  
A. Bartzokas ◽  
V. Kotroni ◽  
K. Lagouvardos
Keyword(s):  
Horizontal Resolution ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Meteorological Model ◽  
Convective Parameterization ◽  
Parameterization Schemes ◽  
Mm5 Model ◽  
Convective Parameterization Scheme ◽  
High Precipitation Events ◽  
High Precipitation

Abstract. The mesoscale meteorological model MM5 is applied to 22 selected days with intense precipitation in the region of Epirus, NW Greece. At first, it was investigated whether and to what extend an increased horizontal resolution (from 8 to 2 km) improves the quantitative precipitation forecasts. The model skill was examined for the 12-h accumulated precipitation recorded at 14 meteorological stations located in Epirus and by using categorical and descriptive statistics. Then, the precipitation forecast skill for the 2 km grid was studied: (a) without and (b) with the activation of a convective parameterization scheme. From the above study, the necessity of the use of a scheme at the 2 km grid is assessed. Furthermore, three different convective parameterization schemes are compared: (a) Betts-Miller, (b) Grell and (c) Kain-Fritsch-2 in order to reveal the scheme, resulting in the best precipitation forecast skill in Epirus. Kain-Fritsch-2 and Grell give better results with the latter being the best for the high precipitation events.

scholarly journals Evaluation of MM5 High-Resolution Real-Time Forecasts over the Urban Area of Athens, Greece

2004 ◽  
Vol 43 (11) ◽  
pp. 1666-1678 ◽  
Author(s):  
V. Kotroni ◽  
K. Lagouvardos
Keyword(s):  
Surface Temperature ◽  
Heat Waves ◽  
Thunderstorm Activity ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Parameterization Scheme ◽  
Cold Bias ◽  
Near Surface ◽  
Convective Parameterization ◽  
Convective Parameterization Scheme

Abstract In this paper the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) forecast skill over an area of complex terrain is evaluated. Namely, the model is verified over a period of 1 yr (2002) over the greater area of Athens, Greece, for its near-surface temperature and wind forecasts, at 8- and 2-km grid spacing, but also over a 15-day period for the summer thunderstorm activity forecasts. For the near-surface temperature a cold bias is evident. The model is, in general, unable to reproduce the summer heat waves observed in the area. The increase of the grid resolution, from 8 to 2 km, results in an improvement of the forecast skill. Postprocessing of the forecasts by applying a Kalman-filtering correction method was very effective for both the 8- and the 2-km forecasts. For the forecast skill of wind, the analysis showed that there is not any net increase of the errors with increasing forecast time for the 48-h forecast period, the mean absolute errors, in general, present the lowest values at noontime, and the increase in resolution, from 8 to 2 km, results in a slight decrease of these errors. The analysis of the model skill to accurately forecast summertime precipitation showed that the 2-km simulations, without activation of the convective parameterization scheme, were unable to reproduce the observed thunderstorm activity. Sensitivity tests for the same period with simulations in which the convective parameterization was not activated for both the 8- and the 2-km simulations were still inaccurate, while activation of the convective parameterization scheme at all grids (even at 2 km) considerably increased the precipitation forecast skill.

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 Using Betts-Miller-Janjic convective parameterization scheme in H14-31 model to forecast heavy rainfall in Vietnam

2007 ◽  
Vol 29 (2) ◽  
pp. 83-97
Author(s):  
Vu Thanh Hang ◽  
Kieu Thi Xin
Keyword(s):  
Heavy Rainfall ◽  
Precipitation Forecast ◽  
Parameterization Scheme ◽  
Model Resolution ◽  
Convective Parameterization ◽  
Rainfall Forecast ◽  
Quantitative Precipitation Forecast ◽  
Convective Adjustment ◽  
Convective Parameterization Scheme ◽  
The Tropics

According to Krishnamurti, improvements of physical parameterizations will mainly affect simulations for the tropics [10]. The study of William A. Gallus Jr. showed that the higher the model resolution and more detailed convective parameterizations, the better the skill in quantitative precipitation forecast (QPF) in general [16]. The quality of precipitation forecast is so sensitive to convective parameterization scheme (CPS) used in the model as well as model resolution. The fact shows that for high resolution regional model like H14-31 CPS based on low-level moisture convergence as Tiedtke did not give good heavy rainfall forecast in Vietnam. In this paper we used the scheme of Betts-Miller-Janjic (BMJ) based on the convective adjustment toward tropical observationally structures in reality instead of Tiedtke in Hl4-31. Statistical verification results and verification using CRA method of Hl4-31 of two CPSs for seperated cases and for three rain seasons (2003-2005) shows that heavy rainfall forecast of Hl4-31/BMJ is better than one of H14-31/TK for Vietnam-South China Sea. CRA verification also shows that it is possible to say that heavy rainfall forecast skill of l-I14-31/BMJ in tropics is nearly similar to the skill of LAPS of Australia.

scholarly journals Study of a dynamic downscaling scheme for quantitative precipitation forecasting

2015 ◽  
Vol 368 ◽  
pp. 108-113 ◽  
Author(s):  
Y. Li ◽  
G. H. Lu ◽  
Z. Y. Wu ◽  
J. Shi
Keyword(s):  
Forecast Accuracy ◽  
Domain Size ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Dynamic Downscaling ◽  
Precipitation Forecasting ◽  
Model Domain ◽  
High Horizontal Resolution ◽  
High Precipitation ◽  
The Stability

Abstract. Dynamic downscaling is the best way to get high resolution quantitative precipitation forecasts. The Weather Research and Forecasting Model (WRF) was utilized as a dynamic downscaling tool in this study. The influence of the horizontal resolutions and the model domains on precipitation forecasts has been analysed to establish an optimized dynamic downscaling scheme. Three precipitation events over Xijiang basin, China, were simulated with different horizontal resolutions and domains. The results indicate that both the horizontal resolution and model domain have an influence on the precipitation forecast. However, the correlation between high precipitation forecast accuracy and the high horizontal resolution or the large model domain were not very strong. Comprehensive consideration of the results shows that the accuracy of forecast is best when the horizontal resolution is 20-km. Although the model domain size has no significant influence on the precipitation forecast, a larger domain may improve the stability of forecasting.

scholarly journals Sensitivity of precipitation forecasts to convective parameterization in the October 2007 Flash Flood in the Valencia Region (Eastern Spain)

2010 ◽  
Vol 26 ◽  
pp. 7-11
Author(s):  
I. Gómez ◽  
F. Pastor ◽  
M. Estrela
Keyword(s):  
Flash Flood ◽  
Mediterranean Coast ◽  
Atmospheric Modeling ◽  
Precipitation Forecast ◽  
Economic Losses ◽  
Rain Event ◽  
Convective Parameterization ◽  
The North ◽  
Accumulated Rainfall ◽  
Convective Parameterization Scheme

Abstract. The Valencia region, on the Mediterranean coast of the Iberian Peninsula, is an area prone to torrential rains, especially the north of Alicante province and the south of Valencia province. In October 2007, a torrential rain event with accumulated rainfall values exceeding 400 mm in less than 24 h affected the aforementioned areas, producing flash floods that caused extensive economic losses and human casualties. Several simulations of this rain event have been performed with the Regional Atmospheric Modeling System (RAMS) to test the influence of the different convective parameterization scheme implemented in the model on the precipitation forecast.

Simulation of karst floods with a hydrological model improved by meteorological model coupling

2021 ◽  
Keyword(s):  
Flood Control ◽  
Underground Structure ◽  
Wrf Model ◽  
Precipitation Forecast ◽  
Karst Area ◽  
Peak Time ◽  
Flood Prediction ◽  
Meteorological Model ◽  
Flood Peak ◽  
Flood Warning

Abstract Karst basins are prone to rapid flooding because of their geomorphic complexity and exposed karst landforms with low infiltration rates. Accordingly, simulating and forecasting floods in karst regions can provide important technical support for local flood control. The study area, the Liujiang karst river basin, is the most well-developed karst area in South China, and its many mountainous areas lack rainfall gauges, limiting the availability of precipitation information. Quantitative precipitation forecast (QPF) from the Weather Research and Forecasting model (WRF) and quantitative precipitation estimation (QPE) from remote sensing information by an artificial neural network cloud classification system (PERSIANN-CCS) can offer reliable precipitation estimates. Here, the distributed Karst-Liuxihe (KL) model was successfully developed from the terrestrial Liuxihe model, as reflected in improvements to its underground structure and confluence algorithm. Compared with other karst distributed models, the KL model has a relatively simple structure and small modeling data requirements, which are advantageous for flood prediction in karst areas lacking hydrogeological data. Our flood process simulation results suggested that the KL model agrees well with observations and outperforms the Liuxihe model. The average Nash coefficient, correlation coefficient, and water balance coefficient increased by 0.24, 0.19, and 0.20, respectively, and the average flood process error, flood peak error, and peak time error decreased by 13%, 11%, and 2 hours, respectively. Coupling the WRF model and PERSIANN-CCS with the KL model yielded a good performance in karst flood simulation and prediction. Notably, coupling the WRF and KL models effectively predicted the karst flood processes and provided flood prediction results with a lead time of 96 hours, which is important for flood warning and control.

scholarly journals Analysis of intense rainfall events on Madeira Island during the 2009/2010 winter

2012 ◽  
Vol 12 (7) ◽  
pp. 2225-2240 ◽  
Author(s):  
F. T. Couto ◽  
R. Salgado ◽  
M. J. Costa
Keyword(s):  
Precipitable Water ◽  
Heavy Precipitation ◽  
Rain Gauge ◽  
Horizontal Resolution ◽  
Pressure System ◽  
Orographic Effects ◽  
Madeira Island ◽  
High Rainfall ◽  
High Precipitation Events ◽  
Precipitation Events

Abstract. This paper constitutes a step towards the understanding of some characteristics associated with high rainfall amounts and flooding on Madeira Island. The high precipitation events that occurred during the winter of 2009/2010 have been considered with three main goals: to analyze the main atmospheric characteristics associated with the events; to expand the understanding of the interaction between the island and the atmospheric circulations, mainly the effects of the island on the generation or intensification of orographic precipitation; and to evaluate the performance of high resolution numerical modeling in simulating and forecasting heavy precipitation events over the island. The MESO-NH model with a horizontal resolution of 1 km is used, as well as rain gauge data, synoptic charts and measurements of precipitable water obtained from the Atmospheric InfraRed Sounder (AIRS). The results confirm the influence of the orographic effects on precipitation over Madeira as well as the tropical–extratropical interaction, since atmospheric rivers were detected in six out of the seven cases analyzed, acting as a low level moisture supplier, which together with the orographic lifting induced the high rainfall amounts. Only in one of the cases the presence of a low pressure system was identified over the archipelago.

scholarly journals Verification of surface minimum, mean, and maximum temperature forecasts in Calabria for summer 2008

2011 ◽  
Vol 11 (2) ◽  
pp. 487-500 ◽  
Author(s):  
S. Federico
Keyword(s):  
Forecast Error ◽  
Background Field ◽  
Horizontal Resolution ◽  
Atmospheric Modeling ◽  
Forecast Skill ◽  
Maximum Temperature ◽  
Model Forecast ◽  
Maximum Temperatures ◽  
Analysis Error ◽  
The Impact

Abstract. Since 2005, one-hour temperature forecasts for the Calabria region (southern Italy), modelled by the Regional Atmospheric Modeling System (RAMS), have been issued by CRATI/ISAC-CNR (Consortium for Research and Application of Innovative Technologies/Institute for Atmospheric and Climate Sciences of the National Research Council) and are available online at http://meteo.crati.it/previsioni.html (every six hours). Beginning in June 2008, the horizontal resolution was enhanced to 2.5 km. In the present paper, forecast skill and accuracy are evaluated out to four days for the 2008 summer season (from 6 June to 30 September, 112 runs). For this purpose, gridded high horizontal resolution forecasts of minimum, mean, and maximum temperatures are evaluated against gridded analyses at the same horizontal resolution (2.5 km). Gridded analysis is based on Optimal Interpolation (OI) and uses the RAMS first-day temperature forecast as the background field. Observations from 87 thermometers are used in the analysis system. The analysis error is introduced to quantify the effect of using the RAMS first-day forecast as the background field in the OI analyses and to define the forecast error unambiguously, while spatial interpolation (SI) analysis is considered to quantify the statistics' sensitivity to the verifying analysis and to show the quality of the OI analyses for different background fields. Two case studies, the first one with a low (less than the 10th percentile) root mean square error (RMSE) in the OI analysis, the second with the largest RMSE of the whole period in the OI analysis, are discussed to show the forecast performance under two different conditions. Cumulative statistics are used to quantify forecast errors out to four days. Results show that maximum temperature has the largest RMSE, while minimum and mean temperature errors are similar. For the period considered, the OI analysis RMSEs for minimum, mean, and maximum temperatures vary from 1.8, 1.6, and 2.0 °C, respectively, for the first-day forecast, to 2.0, 1.9, and 2.6 °C, respectively, for the fourth-day forecast. Cumulative statistics are computed using both SI and OI analysis as reference. Although SI statistics likely overestimate the forecast error because they ignore the observational error, the study shows that the difference between OI and SI statistics is less than the analysis error. The forecast skill is compared with that of the persistence forecast. The Anomaly Correlation Coefficient (ACC) shows that the model forecast is useful for all days and parameters considered here, and it is able to capture day-to-day weather variability. The model forecast issued for the fourth day is still better than the first-day forecast of a 24-h persistence forecast, at least for mean and maximum temperature. The impact of using the RAMS first-day forecast as the background field in the OI analysis is quantified by comparing statistics computed with OI and SI analyses. Minimum temperature is more sensitive to the change in the analysis dataset as a consequence of its larger representative error.

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