Season of the drought: The Indian monsoon is a critical source of water for hundreds of millions of people, and when it fails to deliver its normal quantity of rain, enormous human, economic, and ecological costs can be incurred. Monsoon droughts are not always seasonal, however. Borah et al. found that nearly half of all monsoonal droughts were subseasonal and characterized by a steep decline in late-season rainfall. Moreover, this type of subseasonal drought appears to be related to a distinct cold anomaly in the North Atlantic Ocean, raising the possibility that monsoon droughts may be more predictable. Science , this issue p. 1335

[1] In this study, we analyze satellite-based daily rainfall observations to compare and contrast the wet and dry spell characteristics of tropical rainfall. Defining a wet (dry) spell as the number of consecutive rainy (nonrainy) days, we find that the distributions of wet spells appear to exhibit universality in the following sense. While both ocean and land regions with high seasonal rainfall accumulation (humid regions; e.g., India, Amazon, Pacific Ocean) show a predominance of 2–4 day wet spells, those regions with low seasonal rainfall accumulation (arid regions; e.g., South Atlantic, South Australia) exhibit a wet spell duration distribution that is essentially exponential in nature, with a peak at 1 day. The behavior that we observed for wet spells is reversed for the dry spell characteristics. In other words, the main contribution to the dry part of the season, in terms of the number of nonrainy days, appears to come from 3–4 day dry spells in the arid regions, as opposed to 1 day dry spells in the humid regions. The total rainfall accumulated in each wet spell has also been analyzed, and we find that the major contribution to seasonal rainfall for arid regions comes from 1–5 day wet spells; however, for humid regions, this contribution comes from wet spells of duration as long as 30 days. We also explore the role of chance as well as the influence of organized convection in determining some of the observed features.

Surface water storage is a key component of the terrestrial hydrological and biogeochemical cycles that also plays a major role in water resources management. In this study, surface water storage (SWS) variations are estimated at monthly time-scale over 15 years (1993–2007) using a hypsographic approach based on the combination of topographic information from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hydrological Modeling and Analysis Platform (HyMAP)-based Global Digital Elevation Models (GDEM) and the Global Inundation Extent Multi-Satellite (GIEMS) product in the Ganges-Brahmaputra basin. The monthly variations of the surface water storage are in good accordance with precipitation from Global Precipitation Climatology Project (GPCP), river discharges at the outlet of the Ganges and the Brahmaputra, and terrestrial water storage (TWS) from the Gravity Recovery And Climate Experiment (GRACE), with correlations higher than 0.85. Surface water storage presents a strong seasonal signal (~496 km³ estimated by GIEMS/ASTER and ~378 km³ by GIEMS/HyMAPs), representing ~51% and ~41% respectively of the total water storage signal and it exhibits a large inter-annual variability with strong negative anomalies during the drought-like conditions of 1994 or strong positive anomalies such as in 1998. This new dataset of SWS is a new, highly valuable source of information for hydrological and climate modeling studies of the Ganges-Brahmaputra river basin.

The climatology of annual mean tropical rain rate is investigated based on merged Tropical Rainfall Measuring Mission (TRMM) 3B42 data. At 0.25° × 0.25° spatial resolution, and 3‐hourly temporal resolution, half the rain is concentrated within only ∼1% of the area of the tropics at any given instant. When plotted as a function of logarithm of rain rate, the cumulative contribution of rate‐ranked rain occurrences to the annual mean rainfall in each grid box is S shaped and its derivative, the contribution‐weighted rain rate spectrum, is Gaussian shaped. The 50% intercept of the cumulative contribution R₅₀ is almost equivalent to the contribution‐weighted mean logarithmic rain rate based on all significant rain occurrences. The spatial patterns of R₅₀ and are similar to those obtained by mapping the fraction of the annual accumulation explained by rain occurrences with rates above various specified thresholds. The geographical distribution of R₅₀ confirms the existence of patterns noted in prior analyses based on TRMM precipitation radar data and reveals several previously unnoticed features.