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This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Winter storms in California's Sierra Nevada increase seasonal snowpack and provide critical water resources and hydropower for the state. Thus, the mechanisms influencing precipitation in this region have been the subject of research for decades. Previous studies suggest Asian dust enhances cloud ice and precipitation, whereas few studies consider biological aerosols as an important global source of ice nuclei (IN). Here, we show that dust and biological aerosols transported from as far as the Sahara were present in glaciated high-altitude clouds coincident with elevated IN concentrations and ice-induced precipitation. This study presents the first direct cloud and precipitation measurements showing that Saharan and Asian dust and biological aerosols probably serve as IN and play an important role in orographie precipitation processes over the western United States.

The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized precipitation index (SPI), but it includes the role of temperature. Because the SPEI is based on a water balance, it can be compared to the self-calibrated Palmer drought severity index (sc-PDSI). Time series of the three indices were compared for a set of observatories with different climate characteristics, located in different parts of the world. Under global warming conditions, only the sc-PDSI and SPEI identified an increase in drought severity associated with higher water demand as a result of evapotranspiration. Relative to the sc-PDSI, the SPEI has the advantage of being multiscalar, which is crucial for drought analysis and monitoring.

Because of the scarcity of meteorological observations, the precipitation climate on the Tibetan Plateau and surrounding regions (TP) has been insufficiently documented so far. In this study, the characteristics and basic features of precipitation on the TP during an 11-yr period (2001–11) are described on monthly-to-annual time scales. For this purpose, a new high-resolution atmospheric dataset is analyzed, the High Asia Reanalysis (HAR), generated by dynamical downscaling of global analysis data using the Weather Research and Forecasting (WRF) model. The HAR precipitation data at 30- and 10-km resolutions are compared with both rain gauge observations and satellite-based precipitation estimates from the Tropical Rainfall Measurement Mission (TRMM). It is found that the HAR reproduces previously reported spatial patterns and seasonality of precipitation and that the high-resolution data add value regarding snowfall retrieval, precipitation frequency, and orographic precipitation. It is demonstrated that this process-based approach, despite some unavoidable shortcomings, can improve the understanding of the processes that lead to precipitation on the TP. Analysis focuses on precipitation amounts, type, seasonality, and interannual variability. Special attention is given to the links between the observed patterns and regional atmospheric circulation. As an example of an application of the HAR, a new classification of glaciers on the TP according to their accumulation regimes is proposed, which illustrates the strong spatial variability of precipitation seasonality. Finally, directions for future research are identified based on the HAR, which has the potential to be a useful dataset for climate, glaciological, and hydrological impact studies.

An analysis of the relative effects of transpiration and evaporation, which can be distinguished by how they affect isotope ratios in water, shows that transpiration is by far the largest water flux from Earth’s continents, representing 80 to 90 per cent of terrestrial evapotranspiration and using half of all solar energy absorbed by land surfaces. Plants dominant in water-flux calculations Water fluxes from the land surface to the atmosphere are divided between evaporation, and transpiration from leaf stomata. Although a seemingly basic division between the physical and biological, there is still no consensus on the global partitioning between the two fluxes, resulting in uncertainties as to responses to future climate variations. Now, Scott Jasechko and colleagues use the isotopic signatures of transpiration and evaporation from a global data set of large lakes and reveal that enormous quantities of water — as much as 90% of total terrestrial evapotranspiration — are cycled through vegetation via transpiration. One conclusion to be drawn from this study is that the accuracy of biological — rather than physical — fluxes should be prioritized in work to improve climate models. Renewable fresh water over continents has input from precipitation and losses to the atmosphere through evaporation and transpiration. Global-scale estimates of transpiration from climate models are poorly constrained owing to large uncertainties in stomatal conductance and the lack of catchment-scale measurements required for model calibration, resulting in a range of predictions spanning 20 to 65 per cent of total terrestrial evapotranspiration (14,000 to 41,000 km 3 per year) (refs 1 , 2 , 3 , 4 , 5 ). Here we use the distinct isotope effects of transpiration and evaporation to show that transpiration is by far the largest water flux from Earth’s continents, representing 80 to 90 per cent of terrestrial evapotranspiration. On the basis of our analysis of a global data set of large lakes and rivers, we conclude that transpiration recycles 62,000 ± 8,000 km 3 of water per year to the atmosphere, using half of all solar energy absorbed by land surfaces in the process. We also calculate CO 2 uptake by terrestrial vegetation by connecting transpiration losses to carbon assimilation using water-use efficiency ratios of plants, and show the global gross primary productivity to be 129 ± 32 gigatonnes of carbon per year, which agrees, within the uncertainty, with previous estimates 6 . The dominance of transpiration water fluxes in continental evapotranspiration suggests that, from the point of view of water resource forecasting, climate model development should prioritize improvements in simulations of biological fluxes rather than physical (evaporation) fluxes.

A physically based approach to drought modelling shows that there has been little change in drought from 1950 to 2008, contradicting previous work that suggested an increase in recent years. New figures for global drought trend Published assessments of historic changes in drought during recent decades have suggested that the frequency and area of droughts have been increasing. Here Justin Sheffield et al . show that this prior work was flawed, because of an inappropriate calculation of drought metrics. Using a more physically based approach, the team shows that there has in fact been little change in drought during the period 1950 to 2008. Drought is expected to increase in frequency and severity in the future as a result of climate change, mainly as a consequence of decreases in regional precipitation but also because of increasing evaporation driven by global warming 1 , 2 , 3 . Previous assessments of historic changes in drought over the late twentieth and early twenty-first centuries indicate that this may already be happening globally. In particular, calculations of the Palmer Drought Severity Index (PDSI) show a decrease in moisture globally since the 1970s with a commensurate increase in the area in drought that is attributed, in part, to global warming 4 , 5 . The simplicity of the PDSI, which is calculated from a simple water-balance model forced by monthly precipitation and temperature data, makes it an attractive tool in large-scale drought assessments, but may give biased results in the context of climate change 6 . Here we show that the previously reported increase in global drought is overestimated because the PDSI uses a simplified model of potential evaporation 7 that responds only to changes in temperature and thus responds incorrectly to global warming in recent decades. More realistic calculations, based on the underlying physical principles 8 that take into account changes in available energy, humidity and wind speed, suggest that there has been little change in drought over the past 60 years. The results have implications for how we interpret the impact of global warming on the hydrological cycle and its extremes, and may help to explain why palaeoclimate drought reconstructions based on tree-ring data diverge from the PDSI-based drought record in recent years 9 , 10 .

Fundamental thermodynamics and climate models suggest that dry regions will become drier and wet regions will become wetter in response to warming. Efforts to detect this long-term response in sparse surface observations of rainfall and evaporation remain ambiguous. We show that ocean salinity patterns express an identifiable fingerprint of an intensifying water cycle. Our 50-year observed global surface salinity changes, combined with changes from global climate models, present robust evidence of an intensified global water cycle at a rate of 8 ± 5% per degree of surface warming. This rate is double the response projected by current-generation climate models and suggests that a substantial (16 to 24%) intensification of the global water cycle will occur in a future 2° to 3° warmer world.

Analysis of observations on six continents reveals a global preference for afternoon rain to fall on locally drier soils—contrary to the predictions of large-scale climate models, and suggesting that such models may exaggerate the occurrence of droughts. Rain in the afternoon Soil moisture is known to influence precipitation across a range of scales in time and space, and most models suggest that wetter soils promote higher atmospheric moisture content and favour the local development of storms. But this analysis of global precipitation data from a combination of weather satellites shows that — especially in semi-arid regions — afternoon precipitation is more likely over dry soil than over wet soil. The findings suggest that current climate models may be missing fundamental processes regulating convection and land–atmosphere interactions. Land surface properties, such as vegetation cover and soil moisture, influence the partitioning of radiative energy between latent and sensible heat fluxes in daytime hours. During dry periods, soil-water deficit can limit evapotranspiration, leading to warmer and drier conditions in the lower atmosphere 1 , 2 . Soil moisture can influence the development of convective storms through such modifications of low-level atmospheric temperature and humidity 1 , 3 , which in turn feeds back on soil moisture. Yet there is considerable uncertainty in how soil moisture affects convective storms across the world, owing to a lack of observational evidence and uncertainty in large-scale models 4 . Here we present a global-scale observational analysis of the coupling between soil moisture and precipitation. We show that across all six continents studied, afternoon rain falls preferentially over soils that are relatively dry compared to the surrounding area. The signal emerges most clearly in the observations over semi-arid regions, where surface fluxes are sensitive to soil moisture, and convective events are frequent. Mechanistically, our results are consistent with enhanced afternoon moist convection driven by increased sensible heat flux over drier soils, and/or mesoscale variability in soil moisture. We find no evidence in our analysis of a positive feedback—that is, a preference for rain over wetter soils—at the spatial scale (50–100 kilometres) studied. In contrast, we find that a positive feedback of soil moisture on simulated precipitation does dominate in six state-of-the-art global weather and climate models—a difference that may contribute to excessive simulated droughts in large-scale models.

In 1989, the need for reliable gridded land surface precipitation data sets, in view of the large uncertainties in the assessment of the global energy and water cycle, has led to the establishment of the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst on invitation of the WMO. The GPCC has calculated a precipitation climatology for the global land areas for the target period 1951–2000 by objective analysis of climatological normals of about 67,200 rain gauge stations from its data base. GPCC's new precipitation climatology is compared to several other station-based precipitation climatologies as well as to precipitation climatologies derived from the GPCP V2.2 data set and from ECMWF's model reanalyses ERA-40 and ERA-Interim. Finally, how GPCC's best estimate for terrestrial mean precipitation derived from the precipitation climatology of 786 mm per year (equivalent to a water transport of 117,000 km³) is fitting into the global water cycle context is discussed.

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) robustly predict that the rate of increase in global-mean precipitation with global-mean surface temperature increase is much less than the rate of increase of water vapor. The goal of this paper is to explain in detail the mechanisms by which precipitation increase is constrained by radiative cooling. Changes in clear-sky atmospheric radiative cooling resulting from changes in temperature and humidity in global warming simulations are in good agreement with the multimodel, global-mean precipitation increase projected by GCMs (∼1.1 W m−2K−1). In an atmosphere with fixed specific humidity, radiative cooling from the top of the atmosphere (TOA) increases in response to a uniform temperature increase of the surface and atmosphere, while atmospheric cooling by exchange with the surface decreases because the upward emission of longwave radiation from the surface increases more than the downward longwave radiation from the atmosphere. When a fixed relative humidity (RH) assumption is made, however, uniform warming causes a much smaller increase of cooling at the TOA, and the surface contribution reverses to an increase in net cooling rate due to increased downward emission from water vapor. Sensitivity of precipitation changes to lapse rate changes is modest when RH is fixed. Carbon dioxide reduces TOA emission with only weak effects on surface fluxes, and thus suppresses precipitation. The net atmospheric cooling response and thereby the precipitation response to CO₂-induced warming at fixed RH are mostly contributed by changes in surface fluxes. The role of clouds is discussed. Intermodel spread in the rate of precipitation increase across the CMIP5 simulations is attributed to differences in the atmospheric cooling.