scholarly journals Performance of IMD multi-model ensemble and WRF (ARW) based sub-basin wise rainfall forecast for Mahanadi basin during flood season 2009 and 2010

MAUSAM ◽  
2021 ◽  
Vol 64 (4) ◽  
pp. 625-644
Author(s):  
ASHOK KUMARDAS ◽  
SURINDER KAUR
Keyword(s):  
Heavy Rainfall ◽  
India Meteorological Department ◽  
Model Ensemble ◽  
Rainfall Events ◽  
Flood Season ◽  
Rainfall Forecast ◽  
Mahanadi Basin ◽  
Heavy Rainfall Events

egkunh ds csflu esa 2009 o 2010 ds ck<+ ds ekSle ds nkSjku micsfluokj o"kkZ ds iwokZuqeku rFkk 2010 esa ck<+ ds ekSle ds le; izpkyukRed ¼9 fd-eh- × 9 fd-eh-½ fun'kZ ¼vkb-Z ,e- Mh-½ dk vkdyu djus ds fy, Hkkjr ekSle foKku foHkkx  ¼vkb-Z ,e- Mh-½ ds izpkyukRed cgq&fun'kZ bUlSacy ¼,e-,e-bZ-½  ¼27 fd-eh- × 27 fd-eh-½ ds vk/kkj ij o"kkZ ds iwokZuqeku dk mi;ksx fd;k x;k gSA micsflu Lrj ij ,e-,e-bZ- vkSj MCY;w-vkj-,Q- ds dk;Z fu"iknu dk foLr`r v/;;u fd;k x;k gSA blls irk pyk gS fd lkekU;r% Hkkjh o"kkZ dh ?kVukvksa dks ekWMyksa }kjk de djds vkdfyr fd;k tkrk gSA  Operational Multi-model Ensemble (MME) (27 km × 27 km) based rainfall forecast of India Meteorological Department (IMD) are utilized to compute rainfall forecast sub-basin wise for Mahanadi basin during flood season 2009 & 2010 and operational WRF (ARW) (9 km × 9 km)  model (IMD) during flood season 2010. The performance of the MME and WRF at the sub-basin level are studied in detail. It is observed that generally heavy rainfall events are under estimated by the models.

scholarly journals Verification of heavy rainfall warning over Bihar and Uttar Pradesh

MAUSAM ◽  
2021 ◽  
Vol 60 (2) ◽  
pp. 175-184
Author(s):  
M. MOHAPATRA ◽  
H. R. HATWAR ◽  
S. R. KALSI
Keyword(s):  
False Alarm ◽  
Heavy Rainfall ◽  
Spatial Scales ◽  
Uttar Pradesh ◽  
India Meteorological Department ◽  
Probability Of Detection ◽  
Rain Event ◽  
Rainfall Events ◽  
Synoptic Conditions ◽  
Heavy Rainfall Events

India Meteorological Department (IMD) issues heavy rainfall warning for a meteorological sub-division when the expected 24 hours rainfall over any rain gauge station in that sub-division is likely to be 64.5 mm or more. Though these warnings have been provided since long and are also now being issued for smaller spatial scales, very few attempts have been made for quantitative evaluation of these warnings.  Hence, a study is undertaken to verify the heavy rainfall warning over the representative meteorological sub-divisions of east Uttar Pradesh (UP), west UP and Bihar during main monsoon months of July and August. For this purpose data of the recent 5 years (2001-2005) and also for another epoch of 5 years in the early 1970s has been taken into consideration. In this connection, the day when heavy rainfall is recorded over atleast two stations in a sub-division, has been considered as a heavy rainfall day for that sub-division.   This study of verification shows that probability of detection of heavy rainfall is 64% over Bihar, 52% over east UP and 53% over west UP for the recent 5 years. Compared to early 1970s, there has been slight improvement in the forecast skill during 2001-2005 with probability of detection increasing by about 10-20% and with decrease in missing rate and false alarm rate. However, the false alarm rates are still large indicating higher bias towards over-prediction. The synoptic conditions associated with the heavy rainfall events have been collected for the period 2001-05 and analysed. The analysis of the unanticipated heavy rainfall events suggests that though proper interpretation of synoptic charts and NWP outputs could improve the warnings, the forecast system available even today is still not capable to capture every heavy rain event in advance.

scholarly journals Extreme Floods in the Eastern Part of Europe: Large-Scale Drivers and Associated Impacts

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1122
Author(s):  
Monica Ionita ◽  
Viorica Nagavciuc
Keyword(s):  
Water Vapor ◽  
Heavy Rainfall ◽  
Large Scale ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Flood Events ◽  
Rainfall Events ◽  
Catchment Areas ◽  
Large Scale Atmospheric Circulation ◽  
Heavy Rainfall Events

The role of the large-scale atmospheric circulation in producing heavy rainfall events and floods in the eastern part of Europe, with a special focus on the Siret and Prut catchment areas (Romania), is analyzed in this study. Moreover, a detailed analysis of the socio-economic impacts of the most extreme flood events (e.g., July 2008, June–July 2010, and June 2020) is given. Analysis of the largest flood events indicates that the flood peaks have been preceded up to 6 days in advance by intrusions of high Potential Vorticity (PV) anomalies toward the southeastern part of Europe, persistent cut-off lows over the analyzed region, and increased water vapor transport over the catchment areas of Siret and Prut Rivers. The vertically integrated water vapor transport prior to the flood peak exceeds 300 kg m−1 s−1, leading to heavy rainfall events. We also show that the implementation of the Flood Management Plan in Romania had positive results during the 2020 flood event compared with the other flood events, when the authorities took several precaution measurements that mitigated in a better way the socio-economic impact and risks of the flood event. The results presented in this study offer new insights regarding the importance of large-scale atmospheric circulation and water vapor transport as drivers of extreme flooding in the eastern part of Europe and could lead to a better flood forecast and flood risk management.

scholarly journals Mesoscale Analysis of Heavy Rainfall Episodes from SoWMEX/TiMREX

2012 ◽  
Vol 69 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Christopher A. Davis ◽  
Wen-Chau Lee
Keyword(s):  
Heavy Rainfall ◽  
Southwest Monsoon ◽  
Rainfall Events ◽  
Mesoscale Analysis ◽  
Mesoscale Structure ◽  
Profound Influence ◽  
Moist Condition ◽  
Virtual Temperature ◽  
Convection Initiation ◽  
Heavy Rainfall Events

Abstract The authors analyze the mesoscale structure accompanying two multiday periods of heavy rainfall during the Southwest Monsoon Experiment and the Terrain-Induced Mesoscale Rainfall Experiment conducted over and near Taiwan during May and June 2008. Each period is about 5–6 days long with episodic heavy rainfall events within. These events are shown to correspond primarily to periods when well-defined frontal boundaries are established near the coast. The boundaries are typically 1 km deep or less and feature contrasts of virtual temperature of only 2°–3°C. Yet, owing to the extremely moist condition of the upstream conditionally unstable air, these boundaries appear to exert a profound influence on convection initiation or intensification near the coast. Furthermore, the boundaries, once established, are long lived, possibly reinforced through cool downdrafts and prolonged by the absence of diurnal heating over land in generally cloudy conditions. These boundaries are linked phenomenologically with coastal fronts that occur at higher latitudes.

scholarly journals An Improved Weighting Method of Time-Lag-Ensemble Averaging for Hourly Precipitation Forecasts and Its Application in a Typhoon-Induced Heavy Rainfall Event

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 875
Author(s):  
Li Zhou ◽  
Lin Xu ◽  
Mingcai Lan ◽  
Jingjing Chen
Keyword(s):  
Heavy Rainfall ◽  
Time Lag ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Ensemble Averaging ◽  
Weighting Method ◽  
Prediction Ability ◽  
Rainfall Events ◽  
Hourly Precipitation ◽  
Heavy Rainfall Events

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall.

Diverse synoptic weather patterns of warm-season heavy rainfall events in South Korea

2021 ◽  
Author(s):  
Chanil Park ◽  
Seok-Woo Son ◽  
Joowan Kim ◽  
Eun-Chul Chang ◽  
Jung-Hoon Kim ◽  
...  
Keyword(s):  
North Pacific ◽  
Moisture Transport ◽  
Heavy Rainfall ◽  
Eastern China ◽  
Warm Season ◽  
Sea Level Pressure ◽  
Rainfall Events ◽  
Weather Patterns ◽  
Synoptic Weather ◽  
Heavy Rainfall Events

AbstractThis study identifies diverse synoptic weather patterns of warm-season heavy rainfall events (HREs) in South Korea. The HREs not directly connected to tropical cyclones (TCs) (81.1%) are typically associated with a midlatitude cyclone from eastern China, the expanded North Pacific high and strong southwesterly moisture transport in between. They are frequent both in the first (early summer) and second rainy periods (late summer) with impacts on the south coast and west of the mountainous region. In contrast, the HREs resulting from TCs (18.9%) are caused by the synergetic interaction between the TC and meandering midlatitude flow, especially in the second rainy period. The strong south-southeasterly moisture transport makes the southern and eastern coastal regions prone to the TC-driven HREs. By applying a self-organizing map algorithm to the non-TC HREs, their surface weather patterns are further classified into six clusters. Clusters 1 and 3 exhibit frontal boundary between the low and high with differing relative strengths. Clusters 2 and 5 feature an extratropical cyclone migrating from eastern China under different background sea-level pressure patterns. Cluster 4 is characterized by the expanded North Pacific high with no organized negative sea-level pressure anomaly, and cluster 6 displays a development of a moisture pathway between the continental and oceanic highs. Each cluster exhibits a distinct spatio-temporal occurrence distribution. The result provides useful guidance for predicting the HREs by depicting important factors to be differently considered depending on their synoptic categorization.

scholarly journals Brief communication "Climatic covariates for the frequency analysis of heavy rainfall in the Mediterranean region"

2011 ◽  
Vol 11 (9) ◽  
pp. 2463-2468 ◽  
Author(s):  
Y. Tramblay ◽  
L. Neppel ◽  
J. Carreau
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Extreme Event ◽  
Generalized Pareto Distribution ◽  
Climatic Conditions ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Future ◽  
Heavy Rainfall Events

Abstract. In Mediterranean regions, climate studies indicate for the future a possible increase in the extreme rainfall events occurrence and intensity. To evaluate the future changes in the extreme event distribution, there is a need to provide non-stationary models taking into account the non-stationarity of climate. In this study, several climatic covariates are tested in a non-stationary peaks-over-threshold modeling approach for heavy rainfall events in Southern France. Results indicate that the introduction of climatic covariates could improve the statistical modeling of extreme events. In the case study, the frequency of southern synoptic circulation patterns is found to improve the occurrence process of extreme events modeled via a Poisson distribution, whereas for the magnitude of the events, the air temperature and sea level pressure appear as valid covariates for the Generalized Pareto distribution scale parameter. Covariates describing the humidity fluxes at monthly and seasonal time scales also provide significant model improvements for the occurrence and the magnitude of heavy rainfall events. With such models including climatic covariates, it becomes possible to asses the risk of extreme events given certain climatic conditions at monthly or seasonal timescales. The future changes in the heavy rainfall distribution can also be evaluated using covariates computed by climate models.

scholarly journals Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

2021 ◽  
Author(s):  
Frederik Wolf ◽  
Ugur Ozturk ◽  
Kevin Cheung ◽  
Reik V. Donner
Keyword(s):  
System Dynamics ◽  
East Asia ◽  
Heavy Rainfall ◽  
Spatial Organization ◽  
Monsoon Season ◽  
Spatiotemporal Patterns ◽  
Extreme Weather Events ◽  
Earth System ◽  
Rainfall Events ◽  
Heavy Rainfall Events

&lt;p&gt;Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events.&lt;/p&gt;&lt;p&gt;To thoroughly expand on previous works employing the latter framework to the East Asian Summer Monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates with &lt;span&gt;a spatial resolution of 0.25&amp;#176; &lt;/span&gt;between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way.&lt;/p&gt;&lt;p&gt;Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help improving future forecasts of the Baiu onset in different regions of East Asia.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Further details: F. Wolf, U. Ozturk, K. Cheung, R.V. Donner: Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season. Earth System Dynamics (in review). Discussion Paper: Earth System Dynamics Discussions, (2020)&lt;/p&gt;

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