This paper describes a publicly available, long-term , hydrologically consistent dataset for the conterminous United States, intended to aid in studies of water and energy exchanges at the land surface. These data are gridded at a spatial resolution of 1 /168 latitude/longitude and are derived from daily temperature and precipitation observations from approximately 20 000 NOAA Cooperative Observer (COOP) stations. The available meteorological data include temperature, precipitation, and wind, as well as derived humidity and downwelling solar and infrared radiation estimated via algorithms that index these quantities to the daily mean temperature, temperature range, and precipitation, and disaggregate them to 3-hourly time steps. Furthermore, the authors employ the variable infiltration capacity (VIC) model to produce 3-hourly estimates of soil moisture, snow water equivalent, discharge, and surface heat fluxes. Relative to an earlier similar dataset by Maurer and others, the improved dataset has 1) extended the period of analysis (1915-2011 versus 1950-2000), 2) increased the spatial resolution from 1 /88 to 1 /168, and 3) used an updated version of VIC. The previous dataset has been widely used in water and energy budget studies, climate change assessments, drought reconstructions, and for many other purposes. It is anticipated that the spatial refinement and temporal extension will be of interest to a wide cross section of the scientific community.

The depletion of groundwater resources threatens food and water security in India. However, the relative influence of groundwater pumping and climate variability on groundwater availability and storage remains unclear. Here we show from analyses of satellite and local well data spanning the past decade that long-term changes in monsoon precipitation are driving groundwater storage variability in most parts of India either directly by changing recharge or indirectly by changing abstraction. We find that groundwater storage has declined in northern India at the rate of 2 cm yr in southern India between 2002 and 2013. We find that a large fraction of the total variability in groundwater storage in north-central and southern India can be explained by changes in precipitation. Groundwater storage variability in northwestern India can be explained predominantly by variability in abstraction for irrigation, which is in turn influenced by changes in precipitation. Declining precipitation in northern India is linked to Indian Ocean warming, suggesting a previously unrecognized teleconnection between ocean temperatures and groundwater storage. S ignificant depletion of groundwater storage in a number Changes in groundwater storage 32We estimated groundwater storage anomalies from GRACE for visible at GRACE resolution. However, standardized anomalies of groundwater level and GRACE-based groundwater storage change showed a close correspondence for north and south India, with correlation coefficients of 0.46 and 0.77 respectively (Fig. 1i,j). GRACE groundwater anomalies show a large pattern of declining groundwater in north India, but increasing groundwater level in south India. However, it is unclear if these patterns of changes in groundwater anomalies in north and south India are driven by groundwater abstraction for irrigation or long-term changes in precipitation. Trends were estimated using the non-parametric Mann-Kendall test and Sen's slope method. Monthly anomalies for January, May, August, and November were estimated from GRACE and in situ observations after removing the monthly mean. In situ groundwater well observations from the CGWB are available only for four months (January, May, August, and November). i,j, Area-averaged standardized departure (after removing mean and dividing by the standard deviation) from GRACE and in situ well observations for north (above 1996-2013 in a majority of observation wells located in north 1 India (23 • north, Fig. 2a-d). Moreover, we find that the number is a major crop-growing period ( Supplementary Fig. 2). In India, located in south India, which is consistent with GRACE data (Fig. 1). 13However, a minority of wells in each region show opposite trends 14 of decreasing groundwater levels in southern India and increasing 15 groundwater levels in northern India, highlighting the complexity 16 and heterogeneity of the data and localized influence of groundwater 17 pumping and recharge (Fig. 2). (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(...

The dominant patterns of Indian Summer Monsoon Rainfall (ISMR) and their relationships with the sea surface temperature and 850-hPa wind fields are examined using gridded datasets from 1900 on. The two leading empirical orthogonal functions (EOFs) of ISMR over India are used as basis functions for elucidating these relationships. EOF1 is highly correlated with all India rainfall and El Niño-Southern Oscillation indices. EOF2 involves rainfall anomalies of opposing polarity over the Gangetic Plain and peninsular India. The spatial pattern of the trends in ISMR from 1950 on shows drying over the Gangetic Plain projects onto EOF2, with an expansion coefficient that exhibits a pronounced trend during this period. EOF2 is coupled with the dominant pattern of sea surface temperature variability over the Indian Ocean sector, which involves in-phase fluctuations over the Arabian Sea, the Bay of Bengal, and the South China Sea, and it is correlated with the previous winter's El Niño-Southern Oscillation indices. The circulation anomalies observed in association with fluctuations in the time-varying indices of EOF1 and EOF2 both involve distortions of the low-level monsoon flow. EOF1 in its positive polarity represents a southward deflection of moist, westerly monsoon flow from the Arabian Sea across India, resulting in a smaller flux of moisture to the Himalayas. EOF2 in its positive polarity represents a weakening of the monsoon trough over northeastern India and the westerly monsoon flow across southern India, reminiscent of the circulation anomalies observed during break periods within the monsoon season.T he importance of Indian Summer Monsoon Rainfall (ISMR) for agricultural production, water availability, and food security is well-documented (1). Interannual monsoon variability strongly affects agricultural production, which accounts for about 22% of the Indian gross domestic product (2). Disruptions in the ISMR can lead to substantial losses in crop production that, in turn, may affect the food security of the large and growing population of India.July through September ISMR averaged over the entire Indian subcontinent is remarkably steady from one year to the next, with a coefficient of variation of only 9%. However, even these small variations have important consequences for food production. Rainfall over India as a whole is known to be negatively correlated with sea surface temperature (SST) anomalies over the equatorial eastern Pacific Ocean: it tends to be enhanced during the cold years and suppressed during the warm years of the El Niño-Southern Oscillation (ENSO) cycle (2-9). Rainfall during the monsoon season over India has also been linked with SST variability in the Indian Ocean: the Indian Ocean Dipole mode (10, 11) and a more general warming (cooling) of the tropical Indian Ocean during El Niño (La Niña) events through the socalled atmospheric bridge that persists into the following summer (12-14).Here, we identify a prominent pattern of year-to-year ISMR variability in which the anomalies exhibit a ...

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Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (pvalue <0.05) in the number of heat waves during the period 1973-2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations.