Development of a new high spatial resolution (0.25° × 0.25°) long period  (1901-2010) daily gridded rainfall data set over India and its  comparison with existing data sets over the region

Pai, D. S.; Sridhar, Latha; Rajeevan, M.; Sreejith, O. P.; Satbhai, N. S.; Mukhopadhyay, Biswajit

doi:10.54302/mausam.v65i1.851

Cited by 1,402 publications

(352 citation statements)

References 16 publications

Supporting

Mentioning

349

Contrasting

Order By: Relevance

“…The rainfall observations are obtained from the India Meteorological Department (IMD). We use IMD daily gridded rainfall product for 1901-2013, available at 0.25 • × 0.25 • resolution over the Indian land region (Pai et al 2014). The IMD climatological June-July-August (JJA) total rainfall averaged across the period 1901-2013 is 690.4 mm.…”

Section: Methodsmentioning

confidence: 99%

How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

Jain

Scaife

2022

Environ. Res. Lett.

View full text Add to dashboard Cite

We provide a methodology to estimate possible extreme changes in seasonal rainfall for the coming decades. We demonstrate this methodology using Indian summer monsoon rainfall as an example however it can be extended to other climate variables, regions and timescale conditional to the model forecasts being a good representative of the observations in current climate. We use an ensemble of ~1600 initialized climate simulations from selected seasonal prediction systems to estimate internal variability and how it can exacerbate or alleviate forced climate change. Our estimates show that for the next decade there is a ~60% chance of wetting trends whereas the chance of drying is ~40%. Wetting trends are systematically more favoured than drying with increasing length of the period. This provides a quantitative explanation for the varying trends in the past observational record of rainfall over India. We also quantify the likelihood of extreme trends and show that there is at least a 1% chance that monsoon rainfall could increase or decrease by one fifth over the next decade and that more extreme trends, though unlikely, are possible. We find that monsoon rainfall trends are influenced by trends in sea-surface temperatures over the Niño3.4 region and tropical Indian Ocean, and ~1.5° cooling or warming of these regions can approximately double or negate the influence of climate change on rainfall over the next two decades. We also investigate the time-of-emergence of climate change signals in rainfall trends and find that it is unlikely for a climate change signal to emerge by the year 2050 due to the large internal variability of monsoon rainfall. The estimates of extreme rainfall change provided here could be useful for governments to prepare for worst-case scenarios and therefore aid disaster preparedness and decision-making.

show abstract

Section: Methodsmentioning

confidence: 99%

How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

Jain

Scaife

2022

Environ. Res. Lett.

View full text Add to dashboard Cite

show abstract

“…Precipitation data with 0.25°Â0.25°spatial resolution are available from the Indian Meteorological Department (IMD), which are taken as a reference dataset for the current study. The major advantage of this precipitation dataset is that it is compiled from 6,955 rain gauge stations (Pai et al 2014) and has no missing value, and the data can be accessed from https://www. imdpune.gov.in/.…”

Section: Gridded Precipitation Datamentioning

confidence: 99%

Deciphering the projected changes in CMIP-6 based precipitation simulations over the Krishna River Basin

Anil

2022

Journal of Water and Climate Change

View full text Add to dashboard Cite

The impact of climate change on the Krishna River Basin (KRB) is significant due to the semi-arid nature of the basin. Herein, 21 global climate models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) were examined to simulate the historical monthly precipitation over the 1951–2014 period in the KRB. The symmetrical uncertainty (SU) method and the multi-criteria decision method (MCDM) were employed to select the suitable GCMs for projecting possible changes in precipitation over the KRB. The biases in the climate projections were removed by using the empirical quantile mapping method. The reliability ensemble averaging (REA) method was used to generate the multi-model ensemble (MME) mean of projections and to analyse the spatio-temporal changes of precipitation under different shared socioeconomic pathways (SSPs). BCC-CSM2-MR, IPSL-CM6A-LR, MIROC6, INM-CM5-0, and MPI-ESM1-2-HR were found to be the most suitable GCMs for the KRB. The MME mean of the chosen GCMs showed significant changes in precipitation projection that occurs for a far future period (2071–2100) over the KRB. The projection changes of precipitation range from −36.72 to 83.05% and −37.68 to 95.75% for the annual and monsoon periods, respectively, for various SSPs. Monsoon climate projections show higher changes compared with the annual climate projections, which reveals that precipitation concentration is more during the monsoon period over the KRB.

show abstract

“…The downscaled rainfall and its variability during the three investigated monsoon seasons are evaluated against the IMD observed rainfall (Pai et al, 2014) available on a 0.25 × 0.25 • grid. The simulated monsoon characteristics, including the mean circulation patterns at different pressure levels (950, 850, and 100 hPa), vertical wind shear (difference between 200 and 850 hPa), the monsoon inversion (temperature difference between 850 and 950 hPa) over the Arabian Sea, tropospheric temperature gradients (temperature between 850 and 300 hPa), and moist static energy (MSE) for the studied normal, excess, and drought ISM seasons, are assessed and compared to those of the fifth-generation ECMWF reanalysis (ERA5) dataset (Copernicus Climate Change Service, 2017;Hersbach et al, 2020).…”

Section: Model and Datasetsmentioning

confidence: 99%

Enhanced Simulation of the Indian Summer Monsoon Rainfall Using Regional Climate Modeling and Continuous Data Assimilation

et al. 2022

View full text Add to dashboard Cite

This study assesses a Continuous Data Assimilation (CDA) dynamical-downscaling algorithm for enhancing the simulation of the Indian summer monsoon (ISM) system. CDA is a mathematically rigorous technique that has been recently introduced to constrain the large-scale features of high-resolution atmospheric models with coarse spatial scale data. It is similar to spectral nudging but does not require any spectral decomposition for scales separation. This is expected to be particularly relevant for ISM, which involves various interactions between large-scale circulations and regional physical processes. Along with a control simulation, several downscaling simulations were conducted with the Weather Research and Forecasting (WRF) model configured over the Indian monsoon region at 10 km horizontal resolution using CDA, spectral (retaining different wavenumbers) and grid nudging for three contrasting ISM rainfall seasons: normal (2016), excess (2013), and drought (2009). The simulations are nested within the global NCEP Final Analysis data available at 1 × 1° horizontal resolution. The model outputs are evaluated against the India Meteorological Department (IMD) gridded precipitation and the fifth generation ECMWF atmospheric reanalysis (ERA-5). Compared to grid and spectral nudging, the simulations using CDA produce enhanced ISM features over the Indian subcontinent including the low-level jet, tropical easterly jet, easterly wind shear, and rainfall distributions for all investigated ISM seasons. The major ISM processes, in particular the monsoon inversion over the Arabian Sea, tropospheric temperature gradients and moist static energy over central India, and zonal wind shear over the monsoon region, are all better simulated with CDA. Spectral nudging outputs are found to be sensitive to the choice of the wavenumber, requiring careful tuning to provide robust simulations of the ISM system. In contrast, control and grid nudging generally fail to well-reproduce some of the main ISM features.

show abstract

Development of a new high spatial resolution (0.25° × 0.25°) long period (1901-2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region

Cited by 1,402 publications

References 16 publications

How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

How extreme could the near term evolution of the Indian Summer Monsoon rainfall be?

Deciphering the projected changes in CMIP-6 based precipitation simulations over the Krishna River Basin

Enhanced Simulation of the Indian Summer Monsoon Rainfall Using Regional Climate Modeling and Continuous Data Assimilation

Contact Info

Product

Resources

About