Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India
Abstract
:1. Introduction
- (1)
- How will the emission, land use, and social changes affect the drought situation in the future?
- (2)
- How will the simulated drought change in terms of severity, length, and spatial extent?
2. Study Area
2.1. Study Area 1— the Araveli Region
2.2. Study Area 2—Bundelkhand Region
2.3. Study Area 3—Kansabati River Basin
3. Data and Methodology
3.1. Data
3.2. Methodology
3.2.1. Bias Correction of Climate Variables
- m = MME mean of CMIP6 data
- f = future observations from CMIP6 (2015 to 2044)
- o = historical observations from CMIP6 (1985 to 2014)
- h = observed historical data from gridded data (1985 to 2014)
- X = climate variables (Tasmax, Tasmin, and Pr)
- F = cumulative distributive function (CDF)
- F−1 = inverse cumulative distributive function
3.2.2. Potential Evapotranspiration
3.2.3. scPDSI Drought Index
3.2.4. Future Duration of Drought
4. Results
4.1. Araveli Region
4.2. Bundelkhand Region
4.3. Kansabati River Basin
5. Discussion
6. Conclusions
- (1)
- Prolonged durations of severe drought (scPDSI ≤ −3) can be expected under the SSP2-4.5 and SSP 5-8.5 scenarios between 2015 and 2044.
- (2)
- The period of a possible lengthy spell of worse drought situation can be identified as the period between the mid-2030s and early 2040s for the Araveli and Bundelkhand regions.
- (3)
- Distinct drought durations, even in the smallest of the vulnerable areas, were identified due to fine spatial resolution of the obtained drought index dataset.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Model | Modeling Institution | Spatial Resolution (km) |
---|---|---|
BCC-ESM1 | Beijing Climate Center Earth System Model | 250 × 250 |
CanESM5 | Canadian Centre for Climate Modelling and Analysis | 500 × 500 |
CNRM-CM6-1 | National Centre for Meteorological Research | 250 × 250 |
CNRM-ESM2-1 | Centre National de Recherches Meteorologiques | 250 × 250 |
GISS-E2-1-G | Goddard Institute for Space Studies | 250 × 250 |
GISS-E2-1-H | Goddard Institute for Space Studies | 250 × 250 |
MIROC6 | Model for Interdisciplinary Research on Climate | 500 × 500 |
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Shrestha, A.; Rahaman, M.M.; Kalra, A.; Jogineedi, R.; Maheshwari, P. Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India. Forecasting 2020, 2, 59-84. https://doi.org/10.3390/forecast2020004
Shrestha A, Rahaman MM, Kalra A, Jogineedi R, Maheshwari P. Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India. Forecasting. 2020; 2(2):59-84. https://doi.org/10.3390/forecast2020004
Chicago/Turabian StyleShrestha, Alen, Md Mafuzur Rahaman, Ajay Kalra, Rohit Jogineedi, and Pankaj Maheshwari. 2020. "Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India" Forecasting 2, no. 2: 59-84. https://doi.org/10.3390/forecast2020004
APA StyleShrestha, A., Rahaman, M. M., Kalra, A., Jogineedi, R., & Maheshwari, P. (2020). Climatological Drought Forecasting Using Bias Corrected CMIP6 Climate Data: A Case Study for India. Forecasting, 2(2), 59-84. https://doi.org/10.3390/forecast2020004