Risk assessment of extreme Indian summer monsoon precipitation on agro-ecosystem of northern and central-east India

Risk of extreme precipitation anomaly of Indian summer monsoon (ISM) on agro-ecosystems of Indo-Gangetic Plain (IGP) and central-east India regions has been assessed in the present study. Using monthly gridded precipitation data, standardized precipitation index (SPI) has been computed as the hazard component of the standard risk computation. The agro-ecosystems of IGP are exposed to higher risk due to extreme ISM precipitation anomaly than that of the central-east India. IGP being an irrigated region and central-east India being a rainfed region would be affected differentially due to the increasing negative anomaly in precipitation (i.e., drought risk) in the two regions. Overall the risk score and the prevalent agricultural practice suggest that the Central plateau and hill region in the rainfed region and the Upper Gangetic plain in the irrigated region are the most drought risk pone agroclimatic zones. Exceedance probability (EP) curve and the return period (RP) curve of drought risk quantification revealed that the Upper Gangetic plain of the IGP is conspicuously exposed to a higher drought risk unlike any other region. Increasing drought risk is coupled with increasing cloud cover in Upper Gangetic plain. Surface wind, temperature or the outgoing longwave radiation of this zone could not completely explain the cause of this risk. Changing role of average aerosol index (AAI) hinted to the presence of aerosol altered cloud micro-system in Upper Gangetic plain and may be one of the major reasons for increasing non-precipitating cloud in this zone and thus contributing to the drought risk even with increasing cloud cover trend.

Global to regional overview of floods fatality: the 1951–2020 period

Floods are among the most devastating natural hazards. Human interferences along with climate change cause a lot of human and financial losses every year following the occurrence of floods. In this research, flooding events that have killed more than 10 people in the 1951–2020 period have been studied, analysing the EM-DAT database. The results show that the severity of flood-related deaths is equally distributed worldwide, but present some specific geographical patterns. The flood fatality coefficient, calculated for different countries, identified that Southern, Eastern, and South-Eastern regions of Asia have the deadliest floods in the world. The number of flood events has been increasing since 1951 and peaked in 2007, following a relatively declining trend since then. However, the number of death tolls does not follow a statistically significant trend. An examination of the number of flood events in different decades shows that the highest number of events occurred in the 2001–2010 decade, which corresponds to the largest precipitation anomaly in the world. The most casualties occurred in the decade 1991–2000. However, the lethality of floods has decreased over time, from 412 per flood in 1951–1960 to 67 in the 2011–2020 decade, probably as a consequence of a more resilient environment and better risk reduction strategies. In addition, a direct correlation was found between the number of flood events and the number of casualties with the world’s population.

Mechanisms determining diversity of ENSO-driven equatorial precipitation anomalies

The longitudinal location of precipitation anomalies over the equatorial Pacific shows a distinctive feature with the westernmost location for La Niña, the easternmost location for eastern-Pacific (EP) El Niño and somewhere between for central-Pacific (CP) El Niño, even though the center of the sea surface temperature anomaly (SSTA) for La Niña is located slightly east of that of CP El Niño. The mechanisms for such a precipitation diversity were investigated through idealized model simulations and moisture and moist static energy budget analyses. It is revealed that the boundary layer convergence anomalies associated with the precipitation diversity are mainly induced by underlying SSTA through the Lindzen-Nigam mechanism, that is, their longitudinal locations are mainly controlled by the meridional and zonal distributions of the ENSO SSTA. The westward shift of the precipitation anomaly center during La Niña relative to that during CP El Niño is primarily caused by the combined effects of nonlinear zonal moist enthalpy advection anomalies and the Lindzen-Nigam mechanism mentioned above. Such a zonal diversity is further enhanced by the “convection-cloud-longwave radiation” feedback, the SST-induced latent heat flux anomalies and the advection of mean moist enthalpy by anomalous winds. This diversity in the longitudinal location of precipitation anomalies has contributions to the diversities in the longitudinal locations of anomalous Walker Circulation and western North Pacific anomalous anticyclone/cyclone among the three types of ENSO.

Using the Local Drought Data and GRACE/GRACE-FO Data to Characterize the Drought Events in Mainland China from 2002 to 2020

Accurate quantification of drought characteristics helps to achieve an objective and comprehensive analysis of drought events and to achieve early warning of drought and disaster loss assessment. In our study, a drought characterization approach based on drought severity index derived from Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to quantify drought characteristics. In order to improve drought detection capability, we used the local drought data as calibration criteria to improve the accuracy of the drought characterization approach to determine the onset of drought. Additionally, the local precipitation data was used to test drought severity determined by the calibrated drought characterization approach. Results show that the drought event probability of detection (POD) of this approach in the four study regions increased by 61.29%, 25%, 94.29%, and 66.86%, respectively, after calibration. We used the calibrated approach to detect the drought events in Mainland China (MC) during 2016 and 2019. The results show that CAR of the four study regions is 100.00%, 92.31%, 100.00%, and 100.00%. Additionally, the precipitation anomaly index (PAI) data was used to evaluate the severity of drought from 2002 to 2020 determined by the calibrated approach. The results indicate that both have a strong similar spatial distribution. Our analysis demonstrates that the proposed approach can serve a useful tool for drought monitoring and characterization.

Change of East-Asian Summer Precipitation Associated With Strong El Niño Under the Future Emission Scenarios

Strong Eastern-Pacific type El Niño (EP-El Niño) events have significant impacts on the decaying-summer precipitation over East Asia (EA). It has been demonstrated that frequency of strong EP-El Niños will increase and associated precipitation will become more severe and complex under future high emission scenarios. In this study, using simulations of CMIP5 and CMIP6, changes of the summer precipitation pattern related to strong EP-El Niño during its decay phase and the possible mechanism as responding to high emission scenarios are examined. Precipitation anomaly patterns over EA of strong EP events show a large inter-model spread in historical simulations between the CMIP models where CMIP6 is not superior to CMIP5. Under high emission scenarios, changes of summer precipitation anomalies related to strong EP events tend to increase over the southern EA and decrease around the northern EA from CMIP5, while there is an overall increase in the whole EA from CMIP6. The common change is featured by the increase of precipitation over southeastern China under high emission scenarios. This could be mainly attributed to the anticyclonic circulation from the South China Sea to the western North Pacific as a delayed response to more frequent strong EP-El Niños, which favors an increase in water vapor fluxes converging into the southeastern China.

Evaluating The Sensitivity and Applicability of Precipitation-Based and Precipitation-Evapotranspiration-Based Drought Indices To Different Record Periods

As drought indices are generally calculated based on multi-year historical data spanning periods of at least 30 years, different drought index values at certain times are therefore calculated due to different record lengths, making it difficult to accurately define dry or wet periods in a studied region or station. This investigation assessed the sensitivity and applicability of precipitation-based and precipitation-evapotranspiration-based drought indices, such as the Generalized extreme value drought index (GEVI), Homogeneity index of precipitation and temperature (HI), the K index (K), Precipitation anomaly percentage (Pa), Standardized precipitation evapotranspiration index (SPEI), Standardized precipitation index (SPI), and the China Z index (CZI), to different record lengths on monthly, seasonal and annual time scales. By using monthly, seasonal and annual precipitation and evapotranspiration data from a research station over the period 1961–2017, data over periods of 55, 50, 45, 40, 35 and 30 years were extracted. Analysis of correlation coefficient of all indices, match and non-match, and actual drought and no-drought recognition rate of the indices indicated that K, Pa and SPEI indices recorded better time stability compared to other indices at all time scales across different climatic zones in the study region; the GEVI index recorded the lowest time stability compared to other indices. Results also indicated that the majority of optimal lengths for all stations having the lowest non-match were 41–45 years, with some indices at different time scales being 36–40 years and 46–50 years. In addition, the HI index had the highest actual drought and no-drought recognition rate at almost all climate zones, followed by Pa and SPEI indices. Results from this study indicate that more priority should be given to precipitation-evapotranspiration-based indices when studying a large region; indices with concrete results should be selected when analyzing relatively small regions.

The significance of monitoring high mountain environments to detect heavy precipitation hotspots: a case study in Gredos, Central Spain

In 2015, a new automatic weather station (AWS) was installed in a high elevation site in Gredos mountains (Central System, Spain). Since then, a surprisingly high number of heavy precipitation events have been recorded (55 days with precipitation over 50 mm, and a maximum daily precipitation of 446.9 mm), making this site a hotspot in Spain in terms of annual precipitation (2177 mm year) and extreme precipitation events. The neighboring stations available in the region with longer data series, including the closest ones, already informed of wet conditions in the area, but not comparable with such anomaly behavior detected in the new station (51% higher). In this study, we present the temporal variability of detected heavy precipitation events in this mountain area, and its narrow relation with atmospheric patterns over the Iberian Peninsula. Results revealed that 65% of the events occurred during advections from West, Southwest, South and cyclonic situations. A regression analysis showed that the precipitation anomaly is mostly explained by the location windward to the Atlantic wet air masses and the elevation. However, the variance explained by the models is rather low (average R2 for all events > 50 mm is 0.21). The regression models underestimate on average a 60% intensity of rainfall events. Oppositely, the high-resolution weather forecast model AROME at 0.025° was able to point out the extraordinary character of precipitation at this site, and the underestimation of observed precipitation in the AWS was about 26%. This result strongly suggests the usefulness of weather models to improve the knowledge of climatic extremes over large areas, and to improve the design of currently available observational networks.

Precipitation Changes in the Three Gorges Reservoir Area and the Relationship with Water Level Change

As the largest hydroelectric project worldwide, previous studies indicate that the Three Gorges Dam (TGD) affects the local climate because of the changes of hydrological cycle caused by the impounding and draining of the TGD. However, previous studies do not analyze the long-term precipitation changes before and after the impoundment, and the variation characteristics of local precipitation remain elusive. In this study, we use precipitation anomaly data derived from the CN05.1 precipitation dataset between 1988 and 2017 to trace the changes of precipitation before and after the construction of the TGD (i.e., 1988–2002 and 2003–2017), in the Three Gorges Reservoir Area (TGRA). Results showed that the annual and dry season precipitation anomaly in the TGRA presented an increasing trend, and the precipitation anomaly showed a slight decrease during the flood season. After the impoundment of TGD, the precipitation concentration degree in the TGRA decreased, indicating that the precipitation became increasingly uniform, and the precipitation concentration period insignificantly increased. A resonance phenomenon between the monthly average water level and precipitation anomaly occurred in the TGRA after 2011 and showed a positive correlation. Our findings revealed the change of local precipitation characteristics before and after the impoundment of TGD and showed strong evidence that this change had a close relationship with the water level.