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. 2017 Oct 3;8(1):708.
doi: 10.1038/s41467-017-00744-9.

A threefold rise in widespread extreme rain events over central India

M K Roxy  1 , Subimal Ghosh  2 , Amey Pathak  2 , R Athulya  3   4 , Milind Mujumdar  3 , Raghu Murtugudde  5 , Pascal Terray  6   7 , M Rajeevan  3   8
Affiliations

A threefold rise in widespread extreme rain events over central India

M K Roxy et al. Nat Commun. .

Abstract

Socioeconomic challenges continue to mount for half a billion residents of central India because of a decline in the total rainfall and a concurrent rise in the magnitude and frequency of extreme rainfall events. Alongside a weakening monsoon circulation, the locally available moisture and the frequency of moisture-laden depressions from the Bay of Bengal have also declined. Here we show that despite these negative trends, there is a threefold increase in widespread extreme rain events over central India during 1950-2015. The rise in these events is due to an increasing variability of the low-level monsoon westerlies over the Arabian Sea, driving surges of moisture supply, leading to extreme rainfall episodes across the entire central subcontinent. The homogeneity of these severe weather events and their association with the ocean temperatures underscores the potential predictability of these events by two-to-three weeks, which offers hope in mitigating their catastrophic impact on life, agriculture and property.Against the backdrop of a declining monsoon, the number of extreme rain events is on the rise over central India. Here the authors identify a threefold increase in widespread extreme rains over the region during 1950-2015, driven by an increasing variability of the low-level westerlies over the Arabian Sea.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Fig. 1
Fig. 1
Trends in summer mean and extreme precipitation during 1950–2015. Observed trend in summer a mean precipitation anomalies (mm day−1 66 year−1) and b the frequency (66 year−1) of extreme precipitation events (precipitation ≥ 150 mm day−1). Mean precipitation for the season is 8.1 mm day−1. Time series of c of precipitation (mm day−1), d specific humidity (1000–200 hPa) anomalies (g kg−1), and the number of days with low-pressure systems over central India and e frequency of extreme rain events (number of grid cells exceeding 150 mm day−1 per year) over central Indian subcontinent (75°–85° E, 19°–26° N, inset boxes in a, d). f Time series of the frequency of widespread extreme events (number of days when the extreme events simultaneously cover ten grid cells or more). Stippling indicates trend values significant at 95% confidence level. The trend lines shown in the figures are significant at 95% confidence level. The smoothed curves on the time series analyses represent 10-year moving averages. The entire analysis is for the northern summer (June-September), for the years 1950–2015. The precipitation and cyclone data is based on IMD observations, and the specific humidity is based on NCEP reanalysis. See the “Methods” section for more information regarding the data
Fig. 2
Fig. 2
Evolution of moisture transport leading to widespread extreme precipitation events. Composite evolution of moisture transport (kg m−1 s−1, vectors) and a, b specific humidity (g kg−1, colors), c moisture advection (10−6 g kg−1 s−1, colors) and d moisture convergence (10−5 g kg−1 s−1, colors), leading to widespread extreme precipitation events (more than ten grid cells with daily rainfall ≥ 150 mm) over central India (on 0-day). Daily data for the period 1982–2015 is used for the composite analysis, based on NCEP (a, c, d) and ERA-Interim reanalysis (b). The analysis is for vertically integrated (1000–200 hPa) values for summer (June–September)
Fig. 3
Fig. 3
Variability in moisture transport vs widespread extreme precipitation events. a Correlation between the number of extreme precipitation events over central Indian subcontinent (75°–85° E, 19°–26° N, inset boxes in Fig. 1) and vertically integrated (1000–200 hPa) moisture transport (vectors), for the years 1950–2015. The color shades indicate the correlation with the zonal component of the moisture transport at each grid point. b Trend in the frequency of extreme precipitation events (66 year−1), for the years 1950–2015. Trend in the standard deviations (S.D.) of c daily precipitation (mm day−1 66 year−1) and d daily vertically integrated moisture transport (kg m−1 s−1 34 year−1, vectors) during 1982–2015. The color shades indicate the trend in the S.D. of zonal component of the moisture transport at each grid point (kg m−1 s−1 34 year−1). e Time series of the surface temperatures averaged over north of Arabian Sea (50°–65° E, 15°–35° N, °C, black line), and cross-equatorial pressure gradient (Pa, blue line), which is estimated as the difference of mean sea level pressure (MSLP) between (20°–35° N, 40–80° E) and (35°–10° S, 40°–80° E). f Time series of standard deviations of daily zonal moisture transport (moist westerlies, kg m−1 s−1). Color shades in a, d and stippling in b, c indicates correlation/trends significant at 95% confidence level. The trend lines shown in the figures are significant at 95% confidence level. Analysis of daily data is restricted to the satellite era. The precipitation data is based on IMD observations, the moisture transport and MSLP is obtained from NCEP reanalysis, and the surface temperatures from CRU/HadISST. See the “Methods” section for more information regarding the data
Fig. 4
Fig. 4
Moisture contribution from ocean and terrestrial sources. Contribution of a Arabian Sea (50°–75° E, 5° S–30° N), b Bay of Bengal (80°–100° E, 5° S–30° N), c central Indian Ocean (50°–100° E, 25°–5° S) and d central Indian subcontinent (73°–83° E, 16°–28° N) in supplying moisture for the extreme precipitation events over central Indian subcontinent. The moisture contribution is estimated using the Dynamic Recycling Model. The colors indicate individual source’s contribution to the precipitation anomaly in mm day−1. The negative precipitation anomalies (mm day−1) south of the subcontinent indicate deficient rainfall because of the northward shift in rainfall bands during extreme rainfall events over central India. The anomaly is calculated as deviation from the seasonal mean precipitation. The percentages in the subheadings show the fractional contributions of moisture to the extreme precipitation over the selected region in central India from different sources
Fig. 5
Fig. 5
Evolution of temperature, pressure and winds leading to widespread extreme precipitation events. Composite evolution of a sea surface temperature (SST) and b air temperature (850–500 hPa) anomalies (colors, °C), c mean sea level pressure (MSLP, colors, Pa) and wind (vectors, m s−1), leading to widespread extreme precipitation events over central India (on 0-day). Daily data from OISST and NCEP reanalysis, for the period 1982–2015 is used for the composite analysis
Fig. 6
Fig. 6
Lead–lag analysis of sea surface temperature vs moisture transport and precipitation. Lead-lag correlation between sea surface temperature (SST) and the zonal component of the vertically integrated moisture flux (VIMFU, moist westerlies) and precipitation. SST is averaged over the northern Arabian Sea (55°–70° E, 15°–23° N), and VIMFU (70°–80° E, 18°–22° N) and the precipitation (76°–86° E, 19°–26° N) over central India where it shows the maximum correlation with the SST. The SST anomalies show maximum correlation with the moist westerlies and rain events over central India at 2–3 weeks lead
Fig. 7
Fig. 7
Precipitation distribution during the recent floods over central India. a Precipitation (mm day−1) on 2nd August 2016, which resulted in widespread floods across India. Precipitation values are based on the TRMM Multi-satellite Precipitation Analysis (TMPA, 3b42). b Observed trend in the number of extreme precipitation events during 1950–2015. Dashed line indicates the central Indian belt where the widespread extreme rain events are increasing
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