Middle east warming in spring enhances summer rainfall over Pakistan.

The edge of a monsoon region is usually highly sensitive to climate change. Pakistan, which is located on the northern edge of the Indian monsoon, is highly vulnerable to heavy rainfall and has witnessed several debilitating floods exacerbated by global warming in recent years. However, the mechanisms for the frequent Pakistan floods are yet not fully understood. Here, we show that the Middle East is undergoing an increase in land heating during spring, which is responsible for 46% of the intensified rainfall over Pakistan and northwestern India during 1979-2022. This springtime land warming causes a decline in sea level pressure (SLP), which strengthens the meridional SLP gradient between the Middle East and the southern Arabian Sea and drives the changes of low-level jet (LLJ) subsequently. The impact persists into summer and results in a northward shift of the monsoonal LLJ, accompanied by strong positive vorticity in the atmosphere and enhanced moisture supply to Pakistan. Consequently, the transition region between the summer monsoon in South Asia and the desert climate in West Asia is shifted northwestward, posing significantly enhanced risk of floods over Pakistan and northwestern India.

Remote sensing and climate services improve irrigation water management at farm scale in Western-Central India.

The enormous progress in weather and extended range predictions for the Indian monsoon over the last decade has not been translated to operationalized irrigation water management tools despite many agricultural advisories from operational agencies. The limited implementation is mainly due to the resolution mismatches of forecasts and decision-needs and a lack of soil moisture monitoring networks. Sustained soil moisture monitoring suffers from the high cost to farmers in installing distributed sensors. Here we develop an irrigation water management tool for the farmers at farm scale, which starts with utilizing and merging a few available soil moisture sensors and L-band satellite observations of surface soil moisture using machine learning. Such derived soil moisture field is used as the initial condition with the multi-ensemble future rainfall for the following few weeks given the weather/extended range forecasts in a farm-scale ecohydrological model. This ecohydrological model is integrated with Monte-Carlo simulations within a stochastic optimization framework to minimize water use while not allowing the soil moisture to drop below a threshold level with a certain probability. The optimization results in water arrangement decisions 2 weeks in advance and water application decisions 1-7 days in advance. We also estimate the water storage capacity needed at farm scale for effective water utilization. We find that 20-45 % and 17-35 % water savings were achievable for Kharif and Rabi seasons, respectively, without losing any yield when applied to grape farms of Nashik, Maharashtra, India. The proposed framework is co-developed with the farmers and can be used in any region for any crops, since it is generalized and easy to transfer. This is an extension of our earlier work to an end-to-end system using satellite data for soil moisture.

Soil-vegetation moisture capacitor maintains dry season vegetation productivity over India.

India receives more than 70% of its annual rainfall in the summer monsoon from June to September. The rainfall is scanty and scattered for the rest of the year. Combining satellite data and model simulations, we show that the soil-vegetation continuum works as a natural capacitor of water, storing the monsoon pulse and releasing the moisture to the atmosphere through evapotranspiration over approximately 135 days when the moisture supply from precipitation is less than the evapotranspiration losses. The total Gross Primary Productivity of vegetation in India during the capacitor period accounts for almost 35% of the total annual GPP value. It primarily depends on the soil moisture at the beginning of the period, a measure of moisture capacitance of soil, with a correlation of 0.6. Given that India is the second largest contributor to recent global greening, its soil-vegetation water capacitance plays a significant role in the global carbon balance.

Unexpected limitation of tropical cyclone genesis by subsurface tropical central-north Pacific during El Niño.

The vast tropical Pacific is home to the majority of tropical cyclones (TCs) which threaten the rim countries every year. The TC genesis is nourished by warm sea surface temperatures (SSTs). During El Niño, the western Pacific warm pool extends eastward. However, the number of TCs does not increase significantly with the expanding warm pool and it remains comparable between El Niño and La Niña. Here, we show that the subsurface heat content change counteracts the favorable SSTs in the tropical central-north Pacific. Due to the anomalous positive wind stress curl, the 26 °C isotherm shoals during El Niño over this region and the heat content diminishes in the tropical central-north Pacific, even though warm SST anomalies prevail. This negative correlation between SST and 26 °C isotherm depth anomalies is opposite to the positive correlation in the tropical eastern and western Pacific. This is critical because quantifying the dynamics of the subsurface ocean provides insight into TC genesis. The trend in TC genesis continues to be debated. Future projections must account for the net effect of the surface-subsurface dynamics on TCs, especially given the expected El Niño-like pattern over the tropical Pacific under global warming.

El Niño Southern Oscillation, monsoon anomaly, and childhood diarrheal disease morbidity in Nepal.

Climate change is adversely impacting the burden of diarrheal diseases. Despite significant reduction in global prevalence, diarrheal disease remains a leading cause of morbidity and mortality among young children in low- and middle-income countries. Previous studies have shown that diarrheal disease is associated with meteorological conditions but the role of large-scale climate phenomena such as El Niño-Southern Oscillation (ENSO) and monsoon anomaly is less understood. We obtained 13 years (2002-2014) of diarrheal disease data from Nepal and investigated how the disease rate is associated with phases of ENSO (El Niño, La Niña, vs. ENSO neutral) monsoon rainfall anomaly (below normal, above normal, vs. normal), and changes in timing of monsoon onset, and withdrawal (early, late, vs. normal). Monsoon season was associated with a 21% increase in diarrheal disease rates (Incident Rate Ratios [IRR]: 1.21; 95% CI: 1.16-1.27). El Niño was associated with an 8% reduction in risk while the La Niña was associated with a 32% increase in under-5 diarrheal disease rates. Likewise, higher-than-normal monsoon rainfall was associated with increased rates of diarrheal disease, with considerably higher rates observed in the mountain region (IRR 1.51, 95% CI: 1.19-1.92). Our findings suggest that under-5 diarrheal disease burden in Nepal is significantly influenced by ENSO and changes in seasonal monsoon dynamics. Since both ENSO phases and monsoon can be predicted with considerably longer lead time compared to weather, our findings will pave the way for the development of more effective early warning systems for climate sensitive infectious diseases.

Food insecurity and compound environmental shocks in Nepal: Implications for a changing climate.

Food insecurity is a key global health challenge that is likely to be exacerbated by climate change. Though climate change is associated with an increased frequency of extreme weather events, little is known about how multiple environmental shocks in close succession interact to impact household health and well-being. In this paper, we assess how earthquake exposure followed by monsoon rainfall anomalies affect food insecurity in Nepal. We link food security data from the 2016 Nepal Demographic and Health Survey to data on shaking intensity during the 2015 Gorkha earthquake and rainfall anomalies during the 2015 monsoon season. We then exploit spatial variation in exposure to the earthquake and monsoon rainfall anomalies to isolate their independent and compound effects. We find that earthquake exposure alone was not associated with an increased likelihood of food insecurity, likely due in part to effective food aid distribution. However, the effects of rainfall anomalies differed by severity of earthquake exposure. Among households minimally impacted by the earthquake, low rainfall was associated with increased food insecurity, likely due to lower agricultural productivity in drought conditions. Among households that experienced at least moderate shaking, greater rainfall was positively associated with food insecurity, particularly in steep, mountainous areas. In these locations, rainfall events disproportionately increased landslides, which damaged roads, disrupted distribution of food aid, and destroyed agricultural land and assets. Additional research on the social impacts of compound environmental shocks is needed to inform adaptation strategies that work to improve well-being in the face of climate change.

Global Population Exposed to Extreme Events in the 150 Most Populated Cities of the World: Implications for Public Health.

Climate change driven increases in the frequency of extreme heat events (EHE) and extreme precipitation events (EPE) are contributing to both infectious and non-infectious disease burden, particularly in urban city centers. While the share of urban populations continues to grow, a comprehensive assessment of populations impacted by these threats is lacking. Using data from weather stations, climate models, and urban population growth during 1980-2017, here, we show that the concurrent rise in the frequency of EHE, EPE, and urban populations has resulted in over 500% increases in individuals exposed to EHE and EPE in the 150 most populated cities of the world. Since most of the population increases over the next several decades are projected to take place in city centers within low- and middle-income countries, skillful early warnings and community specific response strategies are urgently needed to minimize public health impacts and associated costs to the global economy.

Role of extreme weather events and El Niño Southern Oscillation on incidence of Enteric Fever in Ahmedabad and Surat, Gujarat, India.

INTRODUCTION: Enteric Fever (EF) affects over 14.5 million people every year globally, with India accounting for the largest share of this burden. The water-borne nature of the disease makes it prone to be influenced as much by unsanitary living conditions as by climatic factors. The detection and quantification of the climatic effect can lead to improved public health measures which would in turn reduce this burden. METHODOLOGY: We obtained a list of monthly Widal positive EF cases from 1995 to 2017 from Ahmedabad and Surat Municipalities. We obtained population data, daily weather data, and Oceanic Niño Index values from appropriate sources. We quantified the association between extreme weather events, phases of El Niño Southern Oscillations (ENSO) and incidence of EF. RESULTS: Both cities showed a seasonal pattern of EF, with cases peaking in early monsoon. Risk of EF was affected equally in both cities by the monsoon season -- Ahmedabad (35%) and Surat (34%). Extreme precipitation was associated with 5% increase in EF in Ahmedabad but not in Surat. Similarly, phases of ENSO had opposite effects on EF across the two cities. In Ahmedabad, strong El Niño months were associated with 64% increase in EF risk while strong La Niña months with a 41% reduction in risk. In Surat, strong El Niño was associated with 25% reduction in risk while moderate La Niña with 21% increase in risk. CONCLUSIONS: Our results show that the risk of EF incidence in Gujarat is highly variable, even between the two cities only 260 kms apart. In addition to improvements in water supply and sewage systems, preventive public health measures should incorporate variability in risk across season and phases of ENSO. Further studies are needed to characterize nationwide heterogeneity in climate-mediated risk, and to identify most vulnerable populations that can benefit through early warning systems.

Snowfall Variability Dictates Glacier Mass Balance Variability in Himalaya-Karakoram.

Glaciers in the Himalaya-Karakoram (HK) are critical for ensuring water-security of a large fraction of world's population that is vulnerable to climate impacts. However, the sensitivity of HK glaciers to changes in meteorological forcing remains largely unknown. We analyzed modelled interannual variability of mass balance (MB) that is validated against available observations, to quantify the sensitivity of MB to meteorological factors over the HK. Within the model, snowfall variability (0.06 m/yr) explains ~60% of the MB variability (0.28 m/yr), implying a sensitivity of MB on snowfall to the tune of several hundreds of percent. This stunningly high sensitivity of MB to snowfall offers crucial insights into the mechanism of the recent divergent glacier response over the HK. Our findings underscore the need for sustained measurements and model representations of the spatiotemporal variability of snowfall, one of the least-studied factors over the glacierized HK, for capturing the large-scale and yet region-specific glacier changes taking place over the HK.

Associations between alteration in plant phenology and hay fever prevalence among US adults: Implication for changing climate.

Plant phenology (e.g. timing of spring green-up, flowering) is among the most sensitive indicator of ecological response to ongoing climate variability and change. While previous studies have documented changes in the timing of spring green-up and flowering across different parts of the world, empirical evidence regarding how such ongoing ecological changes impact allergic disease burden at population level is lacking. Because earlier spring green-up may increase season length for tree pollen, we hypothesized that early onset of spring (negative anomaly in start of season (SOS)) will be associated with increased hay fever burden. To test this, we first calculated a median cardinal date for SOS for each county within the contiguous US for the years 2001-2013 using phenology data from the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer (MODIS). We categorized yearly deviations in SOS for each county from their respective long-term averages as: very early (>3 wks early), early (1-3 wks early), average (within 1 wk), late (1-3 wks late) and very late (> 3 wks late). We linked these data to 2002-2013 National Health Interview Survey data, and investigated the association between changes in SOS and hay fever prevalence using logistic regression. We observed that adults living in counties with a very early onset of SOS had a 14% higher odds of hay fever compared to the reference group, i.e. those living in counties where onset of spring was within the normal range (Odds Ratios (OR): 1.14. 95% Confidence Interval (CI): 1.03-1.27). Likewise, adults living in counties with very late onset of SOS had a 18% higher odds hay fever compared to the reference group (OR: 1.18, CI: 1.05-1.32). Our data provides the first-ever national scale assessment of the impact of changing plant phenology-linked to ongoing climate variability and change-on hay fever prevalence. Our findings are likely tied to changes in pollen dynamics, i.e early onset of spring increases the duration of exposure to tree pollen, while very late onset of spring increases the propensity of exposure because of simultaneous blooming.

Role of Oceanic and Terrestrial Atmospheric Moisture Sources in Intraseasonal Variability of Indian Summer Monsoon Rainfall.

Summer Monsoon Rainfall over the Indian subcontinent displays a prominent variability at intraseasonal timescales with 10-60 day periods of high and low rainfall, known as active and break periods, respectively. Here, we study moisture transport from the oceanic and terrestrial sources to the Indian landmass at intraseasonal timescales using a dynamic recycling model, based on a Lagrangian trajectory approach applied to the ECMWF-ERA-interim reanalysis data. Intraseasonal variation of monsoon rainfall is associated with both a north-south pattern from the Indian landmass to the Indian Ocean and an east-west pattern from the Core Monsoon Zone (CMZ) to eastern India. We find that the oceanic sources of moisture, namely western and central Indian Oceans (WIO and CIO) contribute to the former, while the major terrestrial source, Ganga basin (GB) contributes to the latter. The formation of the monsoon trough over Indo-Gangetic plain during the active periods results in a high moisture transport from the Bay of Bengal and GB into the CMZ in addition to the existing southwesterly jet from WIO and CIO. Our results indicate the need for the correct representation of both oceanic and terrestrial sources of moisture in models for simulating the intraseasonal variability of the monsoon.

A threefold rise in widespread extreme rain events over central India.

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.

Lack of Dependence of Indian Summer Monsoon Rainfall Extremes on Temperature: An Observational Evidence.

The intensification of precipitation extremes in a warming world has been reported on a global scale and is traditionally explained with the Clausius-Clapeyron (C-C) relation. The relationship is observed to be valid in mid-latitudes; however, the debate persists in tropical monsoon regions, with the extremes of the Indian Summer Monsoon Rainfall (ISMR) being a prime example. Here, we present a comprehensive study on the dependence of ISMR extremes on both the 2 m surface air temperature over India and on the sea surface temperature over the tropical Indian Ocean. Remarkably, the ISMR extremes exhibit no significant association with temperature at either spatial scale: neither aggregated over the entire India/Tropical Indian Ocean area nor at the grid levels. We find that the theoretical C-C relation overestimates the positive changes in precipitation extremes, which is also reflected in the Coupled Model Intercomparison Project 5 (CMIP5) simulations. We emphasize that the changing patterns of extremes over the Indian subcontinent need a scientific re-evaluation, which is possible due to availability of the unique long-term in-situ data. This can aid bias correction of model projections of extremes whose value for climate adaptation can hardly be overemphasized, especially for the developing tropical countries.

Extreme precipitation events and increased risk of campylobacteriosis in Maryland, U.S.A.

Consumption of contaminated poultry, raw milk and water are significant risk factors for Campylobacter infection. Previous studies also have investigated the association between weather (temperature and precipitation) and increased risk of campylobacteriosis, but limited information exists regarding the impacts of extreme heat and precipitation events on campylobacteriosis risk, and how such risk may differentially impact coastal communities. We obtained Campylobacter case data 2002-2012; n=4804) from the Maryland Foodborne Diseases Active Surveillance Network (FoodNet). We identified extreme heat and extreme precipitation events during this time (2002-2012) using location and calendar day specific thresholds (95th percentile for extreme heat and 90th percentile for extreme precipitation) that were computed based on a 30-year baseline (1960-1989). We linked these datasets using GIS and used negative binomial generalized estimating equations adjusted for demographic confounders to calculate the association between exposure to extreme events and risk of campylobacteriosis in Maryland. We observed that a one-day increase in exposure to extreme precipitation events was associated with a 3% increase in risk of campylobacteriosis in coastal areas of Maryland (Incidence Rate Ratio (IRR): 1.03, 95% confidence interval (CI): 1.01, 1.05), but such an association was not observed in noncoastal areas. Furthermore, the risk associated with extreme precipitation events was considerably higher during La Niña periods (IRR: 1.09, 95% CI: 1.05, 1.13), while there was no evidence of elevated risk during El Niño or ENSO Neutral periods. Exposure to extreme heat events was not associated with an increased risk of campylobacteriosis, except during La Niña periods (IRR: 1.04, 95% CI: 1.01, 1.08). Extreme precipitation events could result in flooding within coastal areas that may bring water contaminated with bacterial pathogens (originating from sources such as septic systems, municipal wastewater treatment plants and concentrated animal feeding operations) into close proximity with individuals, where frequency of contact may be higher.

Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land-sea thermal gradient.

There are large uncertainties looming over the status and fate of the South Asian summer monsoon, with several studies debating whether the monsoon is weakening or strengthening in a changing climate. Our analysis using multiple observed datasets demonstrates a significant weakening trend in summer rainfall during 1901-2012 over the central-east and northern regions of India, along the Ganges-Brahmaputra-Meghna basins and the Himalayan foothills, where agriculture is still largely rain-fed. Earlier studies have suggested an increase in moisture availability and land-sea thermal gradient in the tropics due to anthropogenic warming, favouring an increase in tropical rainfall. Here we show that the land-sea thermal gradient over South Asia has been decreasing, due to rapid warming in the Indian Ocean and a relatively subdued warming over the subcontinent. Using long-term observations and coupled model experiments, we provide compelling evidence that the enhanced Indian Ocean warming potentially weakens the land-sea thermal contrast, dampens the summer monsoon Hadley circulation, and thereby reduces the rainfall over parts of South Asia.

Climate change, extreme events and increased risk of salmonellosis in Maryland, USA: Evidence for coastal vulnerability.

BACKGROUND: Salmonella is a leading cause of acute gastroenteritis worldwide. Patterns of salmonellosis have been linked to weather events. However, there is a dearth of data regarding the association between extreme events and risk of salmonellosis, and how this risk may disproportionately impact coastal communities. METHODS: We obtained Salmonella case data from the Maryland Foodborne Diseases Active Surveillance Network (2002-2012), and weather data from the National Climatic Data Center (1960-2012). We developed exposure metrics related to extreme temperature and precipitation events using a 30 year baseline (1960-1989) and linked them with county-level salmonellosis data. Data were analyzed using negative binomial Generalized Estimating Equations. RESULTS: We observed a 4.1% increase in salmonellosis risk associated with a 1 unit increase in extreme temperature events (incidence rate ratio (IRR):1.041; 95% confidence interval (CI):1.013-1.069). This increase in risk was more pronounced in coastal versus non-coastal areas (5.1% vs 1.5%). Likewise, we observed a 5.6% increase in salmonellosis risk (IRR:1.056; CI:1.035-1.078) associated with a 1 unit increase in extreme precipitation events, with the impact disproportionately felt in coastal areas (7.1% vs 3.6%). CONCLUSIONS: To our knowledge, this is the first empirical evidence showing that extreme temperature/precipitation events-that are expected to be more frequent and intense in coming decades-are disproportionately impacting coastal communities with regard to salmonellosis. Adaptation strategies need to account for this differential burden, particularly in light of ever increasing coastal populations.

On understanding the land-ocean CO2 contrast over the Bay of Bengal: a case study during 2009 summer monsoon.

Ship-based observations of atmospheric carbon dioxide (CO2) concentration over the Bay of Bengal (BoB) between 17 July 2009 and 17 Aug 2009 offered an excellent opportunity to evaluate the land-ocean contrast of surface CO2 and facilitated its comparison with model simulated CO2 concentrations. Elevated values of CO2 with large variability near the coastal region and relatively low values with correspondingly lower variability over the open ocean suggest that this observed CO2 variability over the ocean essentially captures the differences in terrestrial and oceanic CO2 fluxes. Although the region under investigation is well known for its atmospheric intraseasonal oscillations of Indian summer monsoon during July and August, the limited duration of observations performed from a moving ship in a research cruise, is not able to capture any high-frequency variability of atmospheric CO2 concentrations. But band-passed sea surface temperature and wind anomalies do indicate strong intraseasonal variability over the study region during the observational period. The synoptic data, albeit quite short in duration, thus offer a clear benchmark for abrupt variability of CO2 concentration between land and ocean.

Cholera outbreak in Senegal in 2005: was climate a factor?

Cholera is an acute diarrheal illness caused by Vibrio cholerae and occurs as widespread epidemics in Africa. In 2005, there were 31,719 cholera cases, with 458 deaths in the Republic of Senegal. We retrospectively investigated the climate origin of the devastating floods in mid-August 2005, in the Dakar Region of Senegal and the subsequent outbreak of cholera along with the pattern of cholera outbreaks in three other regions of that country. We compared rainfall patterns between 2002 and 2005 and the relationship between the sea surface temperature (SST) gradient in the tropical Atlantic Ocean and precipitation over Senegal for 2005. Results showed a specific pattern of rainfall throughout the Dakar region during August, 2005, and the associated rainfall anomaly coincided with an exacerbation of the cholera epidemic. Comparison of rainfall and epidemiological patterns revealed that the temporal dynamics of precipitation, which was abrupt and heavy, was presumably the determining factor. Analysis of the SST gradient showed that the Atlantic Ocean SST variability in 2005 differed from that of 2002 to 2004, a result of a prominent Atlantic meridional mode. The influence of this intense precipitation on cholera transmission over a densely populated and crowded region was detectable for both Dakar and Thiès, Senegal. Thus, high resolution rainfall forecasts at subseasonal time scales should provide a way forward for an early warning system in Africa for cholera and, thereby, trigger epidemic preparedness. Clearly, attention must be paid to both natural and human induced environmental factors to devise appropriate action to prevent cholera and other waterborne disease epidemics in the region.

Temporal and spatial variability in the distribution of Vibrio vulnificus in the Chesapeake Bay: a hindcast study.

Vibrio vulnificus, an estuarine bacterium, is the causative agent of seafood-related gastroenteritis, primary septicemia, and wound infections worldwide. It occurs as part of the normal microflora of coastal marine environments and can be isolated from water, sediment, and oysters. Hindcast prediction was undertaken to determine spatial and temporal variability in the likelihood of occurrence of V. vulnificus in surface waters of the Chesapeake Bay. Hindcast predictions were achieved by forcing a multivariate habitat suitability model with simulated sea surface temperature and salinity in the Bay for the period between 1991 and 2005 and the potential hotspots of occurrence of V. vulnificus in the Chesapeake Bay were identified. The likelihood of occurrence of V. vulnificus during high and low rainfall years was analyzed. From results of the study, it is concluded that hindcast prediction yields an improved understanding of environmental conditions associated with occurrence of V. vulnificus in the Chesapeake Bay.