Error Analysis of TMPA Near Real-Time Precipitation Estimates for an Indian Monsoon Region

2021 ◽  
pp. 529-540
Author(s):  
Ashish Kumar ◽  
RAAJ Ramsankaran
Keyword(s):  
Error Analysis ◽  
Real Time ◽  
Indian Monsoon ◽  
Monsoon Region ◽  
Precipitation Estimates ◽  
Indian Monsoon Region

scholarly journals Dynamical-Empirical forecast for the Indian monsoon rainfall using the NCEP Coupled Modelling System – Application for real time monsoon forecast

MAUSAM ◽  
2022 ◽  
Vol 63 (3) ◽  
pp. 433-448
Author(s):  
D.R. PATTANAIK ◽  
AJIT TYAGI ◽  
ARUN KUMAR
Keyword(s):  
Real Time ◽  
Correlation Coefficient ◽  
Monsoon Rainfall ◽  
Indian Monsoon ◽  
Monsoon Region ◽  
The Real ◽  
Time Prediction ◽  
Indian Land ◽  
Land Mass ◽  
Indian Monsoon Region

The performance of the National Centre for Environmental Prediction’s (NCEP) operational coupled modeling system known as the Climate Forecast System (CFS) is evaluated for the prediction of all India summer monsoon rainfall (AISMR) during June to September (JJAS). The evaluation is based on the hindcast initialized during March, April and May with 15 ensemble members each for 25 years period from 1981 to 2005.The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of observed climatology with both the rainfall maxima (over the west-coast of India and over the head Bay of Bengal region) well captured, with a signification correlation coefficient between the forecast and observed climatology over the Indian monsoon region (bounded by 50°E-110°E and 10°S-35°N) covering Indian land mass and adjoining oceanic region. Although the CFS forecast rainfall is overestimated over the Indian monsoon region, the land only rainfall amount is underestimated compared to observation. The skill of the prediction of monsoon rainfall over the Indian land mass is found to be relatively weak, although it is significant at 95% with a correlation coefficient (CC) of 0.44 with April ensembles.By using CFS predicted JJAS rainfall over the regions of significant CCs, a hybrid dynamical-empirical model is developed for the real time prediction of AISMR, whose skill is found to be much higher (CC significant above 99% level) than the raw CFS forecasts. The dynamical-empirical hybrid forecast applied on real time for 2009 and 2010 monsoons are found to be much closer to the observed AISMR. Thus, when the hybrid model is used there is a correction not only to the sign of the actual forecast as in the case of 2009 monsoon but also to its magnitude and hence can be used as a better tool for the real time prediction of AISMR.

scholarly journals Diurnal variability of the atmospheric boundary layer height over a tropical station in the Indian monsoon region

2017 ◽  
Vol 17 (1) ◽  
pp. 531-549 ◽  
Author(s):  
Sanjay Kumar Mehta ◽  
Madineni Venkat Ratnam ◽  
Sukumarapillai V. Sunilkumar ◽  
Daggumati Narayana Rao ◽  
Boddapaty V. Krishna Murthy
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Diurnal Variation ◽  
Indian Monsoon ◽  
Winter Season ◽  
Monsoon Region ◽  
Diurnal Variability ◽  
The Mean ◽  
Indian Monsoon Region ◽  
Tropical Station

Abstract. The diurnal variation of atmospheric boundary layer (ABL) height is studied using high-resolution radiosonde observations available at 3 h intervals for 3 days continuously from 34 intensive campaigns conducted during the period December 2010–March 2014 over a tropical station Gadanki (13.5° N, 79.2° E; 375 m), in the Indian monsoon region. The heights of the ABL during the different stages of its diurnal evolution, namely, the convective boundary layer (CBL), the stable boundary layer (SBL), and the residual layer (RL) are obtained to study the diurnal variabilities. A clear diurnal variation is observed in 9 campaigns out of the 34 campaigns. In 7 campaigns the SBL did not form in the entire day and in the remaining 18 campaigns the SBL formed intermittently. The SBL forms for 33–55 % of the time during nighttime and 9 and 25 % during the evening and morning hours, respectively. The mean SBL height is within 0.3 km above the surface which increases slightly just after midnight (02:00 IST) and remains almost constant until the morning. The mean CBL height is within 3.0 km above the surface, which generally increases from morning to evening. The mean RL height is within 2 km above the surface which generally decreases slowly as the night progresses. The diurnal variation of the ABL height over the Indian region is stronger during the pre-monsoon and weaker during winter season. The CBL is higher during the summer monsoon and lower during the winter season while the RL is higher during the winter season and lower during the summer season. During all the seasons, the ABL height peaks during the afternoon (∼ 14:00 IST) and remains elevated until evening (∼ 17:00 IST). The ABL suddenly collapses at 20:00 IST and increases slightly in the night. Interestingly, it is found that the low level clouds have an effect on the ABL height variability, but the deep convective clouds do not. The lifting condensation level (LCL) is generally found to occur below the ABL for the majority of the database and they are randomly related.

scholarly journals High-resolution gridded soil moisture and soil temperature datasets for the Indian monsoon region

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
H. P. Nayak ◽  
K. K. Osuri ◽  
Palash Sinha ◽  
Raghu Nadimpalli ◽  
U. C. Mohanty ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Soil Temperature ◽  
Indian Monsoon ◽  
Monsoon Region ◽  
Indian Monsoon Region

Performance Optimization of Operational WRF Model Configured for Indian Monsoon Region

2019 ◽  
Vol 3 (2) ◽  
pp. 231-239 ◽  
Author(s):  
Pavani Andraju ◽  
A Lakshmi Kanth ◽  
K Vijaya Kumari ◽  
S. Vijaya Bhaskara Rao
Keyword(s):  
Performance Optimization ◽  
Indian Monsoon ◽  
Wrf Model ◽  
Monsoon Region ◽  
Indian Monsoon Region

scholarly journals Comparison of the Long-Range Climate Memory in Outgoing Longwave Radiation over the Tibetan Plateau and the Indian Monsoon Region

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongping Shen ◽  
Jun Shi ◽  
Yadong Lei
Keyword(s):  
Time Series ◽  
Outgoing Longwave Radiation ◽  
Cloud Cover ◽  
Indian Monsoon ◽  
Longwave Radiation ◽  
The Tibetan Plateau ◽  
Monsoon Region ◽  
Scaling Exponents ◽  
High Cloud ◽  
Indian Monsoon Region

Based on the detrended fluctuation analysis (DFA) method, scaling behaviors of the daily outgoing longwave radiation (OLR) from 1979 to 2015 over the Tibetan Plateau (TP) and the Indian Monsoon Region (IMR) are analyzed. The results show that there is long-term memory for the OLR time series over the TP and IMR. The long-range memory behaviors of OLR over TP are stronger than those over IMR. The averaged values of the scaling exponents over TP and IMR are 0.71 and 0.64; the maximum values in the two regions are 0.81 and 0.75; the minimum values are 0.59 and 0.58. The maximum frequency counts for scaling exponents occur in the range of 0.625 and 0.675 both in TP and in IMR. The spatial distribution of the scaling exponents of the OLR sequence is closely related to the conditions of climatic high cloud cover in the two areas. The high cloud cover over TP is obviously less than that of IMR. In addition, the scaling behaviors of OLR over TP and IMR are caused by the fractal characteristics of time series, which is further proved by randomly disrupting the time series to remove trends and correlation.

scholarly journals Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model RegCM4.6

2021 ◽  
Author(s):  
Sudipta Ghosh ◽  
Sagnik Dey ◽  
Sushant Das ◽  
Nicole Riemer ◽  
Graziano Giuliani ◽  
...  
Keyword(s):  
Life Cycle ◽  
Regional Climate Model ◽  
Climate Model ◽  
Indian Monsoon ◽  
Regional Climate ◽  
Carbonaceous Aerosols ◽  
Monsoon Region ◽  
Gangetic Plain ◽  
Emission Fluxes ◽  
Indian Monsoon Region

Abstract. Mitigation of carbonaceous aerosol emissions is expected to provide climate and health co-benefits. The accurate representation of carbonaceous aerosols in climate models is critical for reducing uncertainties in their climate feedbacks. In this regard, emission fluxes and aerosol life-cycle processes are the two primary sources of uncertainties. Here we demonstrate that incorporating a dynamic ageing scheme and emission estimates that are updated for the local sources improve the representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model, RegCM, compared to its default configuration. The mean BC and OC surface concentrations in 2010 are estimated to be 4.25 and 10.35 μg m−3, respectively, over the Indo-Gangetic Plain (IGP), in the augmented model. The BC column burden over the polluted IGP is found to be 2.47 mg m−2, 69.95 % higher than in the default model configuration and much closer to available observations. The anthropogenic AOD increases by more than 19 % over the IGP due to the model enhancement, also leading to a better agreement with observed AOD. The top-of-the-atmosphere, surface, and atmospheric anthropogenic aerosol shortwave radiative forcing are estimated at −0.3, −9.3, and 9.0 W m−2, respectively, over the IGP and −0.89, −5.33, and 4.44 W m−2, respectively, over Peninsular India. Our results suggest that both the accurate estimates of emission fluxes and a better representation of aerosol processes are required to improve the aerosol life cycle representation in the climate model.

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