Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing

Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.

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

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.

Performance of IMD multi-model ensemble and WRF (ARW) model for sub-basin wise rainfall forecast during monsoon 2012

The Numerical Weather Prediction models, Multi-model Ensemble (MME) (27 km × 27 km) and WRF (ARW) (9 km × 9 km) operationally run by India Meteorological Department (IMD) have been utilized to estimate sub-basin wise rainfall forecast. The sub-basin wise operational Quantitative Precipitation Forecast (QPF) have been issued by 10 field offices named Flood Meteorological Offices (FMOs) of IMD located at different flood prone areas of the country. The daily sub-basin wise NWP model rainfall forecast for 122 sub basins under these 10 FMOs for the flood season 2012 have been estimated on operational basis which are used by forecasters at FMOs as a guidance for the issue of operational sub-basin QPF for flood forecasting purposes. The performance of the MME and WRF (ARW) models rainfall at the sub-basin level have been studied in detail. The performance of WRF (ARW) and MME models is compared in the heavy rainfall case over the river basins (Mahanadi etc.) falls under FMO, Bhubaneswar and it is found that WRF (ARW) model gives better result than MME. It is also found that performance of WRF (ARW) is little better than MME when compared over all the flood prone river sub basins of India. For high rainfall categories (51-100, >100 mm), generally these leads to floods, the success rate of model rainfall forecasts are less and false alarms are more. The NWP models are able to capture the rainfall events but there is difference in magnitudes of sub basin wise rainfall estimates.

Block level weather forecast using direct model output from NWP models during monsoon season in India

The forecast for 655 districts and 6500 blocks had been prepared and implemented on 1st June, 2014. The procedure for getting forecast for the districts and blocks in India including altitude corrections is based upon regular (0.25 × 0.25) grid output from the T-574 Model and output from 9 km WRF model. A verification study for rainfall forecast at 0.25 × 0.25 degree grid for Indian Window (0-40° N and 60-100° N) is also conducted, which had indicated that skill of the rainfall forecast is good for all parts of the country except oceanic islands and high terrain regions and one can down scale to any level, down to the blocks, the skill scores will not differ much. A detailed verification study for the skill of the forecast at block level for all the eight weather parameters for which the forecast was issued is conducted. The skill of the rainfall forecast is obtained for categorical forecast and as well as for yes/no forecast. The skill scores for rainfall had indicated that highest value of Hanssen and Kuiper (HK) score is 0.44, Hanssen and Kuiper score for quantitative rainfall (HKQ) is 0.18, Ratio score for yes/no forecast is 90 percent and Hit rate (HR) is 0.83. The detailed verification study for the block level weather forecast for monsoon 2014 is presented in the paper and the skill found is good. The study indicates that model forecast has the potential to be used for the block level forecast after making the quick value additions for which hints are given in the conclusion part.

Verification of operational rainfall forecast over eastern India during southwest monsoon season

The Indian summer monsoon rainfall forecast and its verification has a direct impact on various sectors of public interest besides economy of the country. The present study highlights the verification of distribution forecast of synoptic method issued daily for six met subdivisions, comprising of five states of eastern India namely West Bengal, Sikkim, Bihar, Jharkhand and Odisha. Three years monsoon season rainfall data from 2011 through 2013 are used for the study area. The distribution-oriented verification is done for different rainfall classes like dry, isolated, scattered, fairly widespread and widespread to understand the usefulness of the synoptic method. Statistics are presented for both combined classes of Percentage Correct (PC) and Heidke Skill Score (HSS) of the met subdivision wise forecast and PC, POD and CSI for individual classes. It has been observed that among the met subdivision the efficiency of the method is highest in Sub Himalayan West Bengal (SHWB) & Sikkim followed by Gangetic West Bengal (GWB), Odisha, Jharkhand and Bihar.