Showing papers on "Precipitation published in 2016"

More extreme precipitation in the world’s dry and wet regions

Abstract: Extreme precipitation over land has increased over the wettest and driest regions and is likely to keep intensifying over the twenty-first century. This has key implications for dry regions, which may be unprepared for the potential related flooding.

Climatologies at high resolution for the earth's land surface areas

Abstract: High resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA Climatologies at high resolution for the earths land surface areas data of downscaled model output temperature and precipitation estimates of the ERA Interim climatic reanalysis to a high resolution of 30 arc seconds. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height with a subsequent bias correction. The resulting data consist of a monthly temperature and precipitation climatology for the years 1979 to 2013. We compare the data derived from the CHELSA algorithm with other standard gridded products and station data from the Global Historical Climate Network. We compare the performance of the new climatologies in species distribution modelling and show that we can increase the accuracy of species range predictions. We further show that CHELSA climatological data has a similar accuracy as other products for temperature but that its predictions of precipitation patterns are better.

Aerosol and monsoon climate interactions over Asia

Abstract: The increasing severity of droughts/floods and worsening air quality from increasing aerosols in Asia monsoon regions are the two gravest threats facing over 60% of the world population living in Asian monsoon regions. These dual threats have fueled a large body of research in the last decade on the roles of aerosols in impacting Asian monsoon weather and climate. This paper provides a comprehensive review of studies on Asian aerosols, monsoons, and their interactions. The Asian monsoon region is a primary source of emissions of diverse species of aerosols from both anthropogenic and natural origins. The distributions of aerosol loading are strongly influenced by distinct weather and climatic regimes, which are, in turn, modulated by aerosol effects. On a continental scale, aerosols reduce surface insolation and weaken the land-ocean thermal contrast, thus inhibiting the development of monsoons. Locally, aerosol radiative effects alter the thermodynamic stability and convective potential of the lower atmosphere leading to reduced temperatures, increased atmospheric stability, and weakened wind and atmospheric circulations. The atmospheric thermodynamic state, which determines the formation of clouds, convection, and precipitation, may also be altered by aerosols serving as cloud condensation nuclei or ice nuclei. Absorbing aerosols such as black carbon and desert dust in Asian monsoon regions may also induce dynamical feedback processes, leading to a strengthening of the early monsoon and affecting the subsequent evolution of the monsoon. Many mechanisms have been put forth regarding how aerosols modulate the amplitude, frequency, intensity, and phase of different monsoon climate variables. A wide range of theoretical, observational, and modeling findings on the Asian monsoon, aerosols, and their interactions are synthesized. A new paradigm is proposed on investigating aerosol-monsoon interactions, in which natural aerosols such as desert dust, black carbon from biomass burning, and biogenic aerosols from vegetation are considered integral components of an intrinsic aerosol-monsoon climate system, subject to external forcing of global warming, anthropogenic aerosols, and land use and change. Future research on aerosol-monsoon interactions calls for an integrated approach and international collaborations based on long-term sustained observations, process measurements, and improved models, as well as using observations to constrain model simulations and projections.

Storm track processes and the opposing influences of climate change

Abstract: Extratropical storms contribute to precipitation, wind and temperature extremes. A synthesis of the influences of a changing climate on storm tracks reveals competing effects on meridional temperature gradients, which make projections difficult.

Water balance creates a threshold in soil pH at the global scale

Abstract: Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems. However, soil pH is not an independent regulator of soil fertility-rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients. Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate.

Observed heavy precipitation increase confirms theory and early model

Abstract: It has been predicted, by theory and models, that heavy precipitation will increase with climate change and this is now being seen in observations. Emergence of signals such as this will enable testing of predictions, which should increase confidence in them. Environmental phenomena are often observed first, and then explained quantitatively. The complexity of processes, the range of scales involved, and the lack of first principles make it challenging to predict conditions beyond the ones observed. Here we use the intensification of heavy precipitation as a counterexample, where seemingly complex and potentially computationally intractable processes manifest themselves to first order in simple ways: heavy precipitation intensification is now emerging in the observed record across many regions of the world, confirming both theory and model predictions made decades ago. As the anthropogenic climate signal strengthens, there will be more opportunities to test climate predictions for other variables against observations and across a hierarchy of different models and theoretical concepts.

Substantial proportion of global streamflow less than three months old

Abstract: Streamflow is a mixture of precipitation of various ages. Oxygen isotope data suggests that a third of global river discharge is sourced from rainfall within the past few months, which accounts for less than 0.1% of global groundwater.

Validation and comparison of a new gauge-based precipitation analysis over mainland China

Abstract: Through optimizing the daily precipitation climatology, a new high-resolution (0.25° × 0.25° lat./lon.) gridded daily precipitation analysis over Mainland China was developed based on the optimal interpolation (OI) method. This product, based on about 2400 gauge stations over Mainland China from 1955 to the present, is called the China Gauge-based Daily Precipitation Analysis (CGDPA). In this study, using independent precipitation observations as the benchmark, CGDPA and the Climate Prediction Center Unified gauge dataset (CPC_UNI) from the National Oceanic and Atmospheric Administration (NOAA) are validated from May to September of 2008–2010 on a 0.5° × 0.5° lat./lon. grid. The CGDPA has smaller bias and root mean square error, and higher spatial correlation with the validation data than CPC_UNI. Further investigation indicates that this improvement is mainly owing to the larger number of gauges used in the CGDPA. The East Asia gauge analysis (EA_Gauge) is also introduced to comparatively evaluate the capabilities of monitoring precipitation events with different rainfall rates over Mainland China. CGDPA can capture more strong rainfall events while CPC_UNI and EA_Gauge tend to smooth the precipitation structure and miss more local strong rainfall events with precipitation larger than 25 mm day−1 over Mainland China. The long-term precipitation time series described by the CGDPA and EA_Gauge agree very well while CPC_UNI substantially underestimates precipitation especially over the sparse-gauged regions and after 1982. CGDPA is thus suggested as a readily available input to applications over Mainland China, whenever possible.

Anthropogenic and natural contributions to the Southeast Pacific precipitation decline and recent megadrought in central Chile

Abstract: Within large uncertainties in the precipitation response to greenhouse gas forcing, the Southeast Pacific drying stands out as a robust signature within climate models. A precipitation decline, of consistent direction but of larger amplitude than obtained in simulations with historical climate forcing, has been observed in central Chile since the late 1970s. To attribute the causes of this trend, we analyze local rain gauge data and contrast them to a large ensemble of both fully coupled and sea surface temperature-forced simulations. We show that in concomitance with large-scale circulation changes, the Pacific Decadal Oscillation explains about half of the precipitation trend observed in central Chile. The remaining fraction is unlikely to be driven exclusively by natural phenomena but rather consistent with the simulated regional effect of anthropogenic climate change. We particularly estimate that a quarter of the rainfall deficit affecting this region since 2010 is of anthropogenic origin. An increased persistence and recurrence of droughts in central Chile emerges then as a realistic scenario under the current socioeconomic pathway.

Delaying precipitation and lightning by air pollution over the Pearl River Delta. Part I: Observational analyses

Abstract: The radiative and microphysical effects of aerosols can affect the development of convective clouds. The objective of this study is to reveal if the overall aerosol effects have any discernible impact on the diurnal variations in precipitation and lightning by means of both observational analysis and modeling. As the first part of two companion studies, this paper is concerned with analyzing hourly PM10, precipitation, and lightning data collected during the summers of 2008–2012 in the Pearl River Delta region. Daily PM10 data were categorized as clean, medium, or polluted so that any differences in the diurnal variations in precipitation and lightning could be examined. Heavy precipitation and lightning were found to occur more frequently later in the day under polluted conditions than under clean conditions. Analyses of the diurnal variations in several meteorological factors such as air temperature, vertical velocity, and wind speed were also performed. They suggest that the influence of aerosol radiative and microphysical effects serve to suppress and enhance convective activities, respectively. Under heavy pollution conditions, the reduction in solar radiation reaching the surface delays the occurrence of strong convection and postpones heavy precipitation to late in the day when the aerosol invigoration effect more likely comes into play. Although the effect of aerosol particles can be discernible on the heavy precipitation through the daytime, the influence of concurrent atmospheric dynamics and thermodynamics cannot be ruled out.

Changes in temperature and precipitation extreme indices over China: analysis of a high‐resolution grid dataset

Abstract: Based on the high-resolution gridding data (CN05) from 2416 station observations, a grid dataset of temperature and precipitation extreme indices with the resolution of 05° × 05° for China region was developed using the approach recommended by the Expert Team on Climate Change Detection and Indices This article comprehensively presents temporal and spatial changes of these indices for the time period 1961–2010 Results showed widespread significant changes in temperature extremes consistent with warming, for instance, decreases in cold extremes and increases in warm extremes over China The warming in the coldest day and night is larger than the warmest day and night, respectively, which is concurrent with the coldest night larger than the coldest day and the warmest night larger than the warmest day Changes in the number of the cold and warm nights are more remarkable than the cold and warm days Changes in precipitation extremes are, in general, spatially more complex and exhibit a less widespread spatial coverage than the temperature indices, for instance, the patterns of annual total precipitation amount, average daily precipitation rate, and the proportion of heavy precipitation in total annual precipitation are similar with negative trends in a southwest–northeast belt from Southwest China to Northeast China while positive trends in eastern China and northwestern China The consistency of changes in climate extremes from the CN05 with other datasets based on the stations and reanalyses is also analysed

Proportions of convective and stratiform precipitation revealed in water isotope ratios

Abstract: Distinguishing convective and stratiform rainfall is key to understanding how the water cycle responds to climate change. An analysis of satellite and surface data shows that rain isotope ratios reflect the proportions of these types of rain.

A cross-biome synthesis of soil respiration and its determinants under simulated precipitation changes.

Abstract: Soil respiration (Rs) is the second-largest terrestrial carbon (C) flux. Although Rs has been extensively studied across a broad range of biomes, there is surprisingly little consensus on how the spatiotemporal patterns of Rs will be altered in a warming climate with changing precipitation regimes. Here, we present a global synthesis Rs data from studies that have manipulated precipitation in the field by collating studies from 113 increased precipitation treatments, 91 decreased precipitation treatments, and 14 prolonged drought treatments. Our meta-analysis indicated that when the increased precipitation treatments were normalized to 28% above the ambient level, the soil moisture, Rs, and the temperature sensitivity (Q10) values increased by an average of 17%, 16%, and 6%, respectively, and the soil temperature decreased by -1.3%. The greatest increases in Rs and Q10 were observed in arid areas, and the stimulation rates decreased with increases in climate humidity. When the decreased precipitation treatments were normalized to 28% below the ambient level, the soil moisture and Rs values decreased by an average of -14% and -17%, respectively, and the soil temperature and Q10 values were not altered. The reductions in soil moisture tended to be greater in more humid areas. Prolonged drought without alterations in the amount of precipitation reduced the soil moisture and Rs by -12% and -6%, respectively, but did not alter Q10. Overall, our synthesis suggests that soil moisture and Rs tend to be more sensitive to increased precipitation in more arid areas and more responsive to decreased precipitation in more humid areas. The responses of Rs and Q10 were predominantly driven by precipitation-induced changes in the soil moisture, whereas changes in the soil temperature had limited impacts. Finally, our synthesis of prolonged drought experiments also emphasizes the importance of the timing and frequency of precipitation events on ecosystem C cycles. Given these findings, we urge future studies to focus on manipulating the frequency, intensity, and seasonality of precipitation with an aim to improving our ability to predict and model feedback between Rs and climate change.

The Influences of Climate Change and Human Activities on Vegetation Dynamics in the Qinghai-Tibet Plateau

Abstract: Grasslands occupy nearly three quarters of the land surface of the Qinghai-Tibet plateau (QTP) and play a critical role in regulating the ecological functions of the QTP. Ongoing climate change and human interference have greatly affected grasslands on the QTP. Differentiating human-induced and climate-driven vegetation changes is vital for both ecological understanding and the management of husbandry. In this study, we employed statistical analysis of annual records, various sources of remote sensing data, and an ecosystem process model to calculate the relative contribution of climate and human activities to vegetation vigor on the QTP. The temperature, precipitation and the intensity and spatial pattern of livestock grazing differed between the periods prior to and after the year 2000, which led to different vegetation dynamics. Overall, increased temperature and enhanced precipitation favored vegetation growth. However, their combined effects exhibited strong spatial heterogeneity. Specifically, increased temperature restrained vegetation growth in dry steppe regions during a period of slightly increasing precipitation from 1986 to 2000 and in meadow regions during a period of precipitation decline during 2000–2011, thereby making precipitation a dominant factor. An increase in precipitation tended to enhance vegetation growth in wet meadow regions during warm periods, and temperature was the limiting factor in Tibet during dry periods. The dominant role played by climate and human activities differed with location and targeted time period. Areas dominated by human activities are much smaller than those dominated by climate. The effects of grazing on grassland pasture were more obvious under unfavorable climate conditions than under suitable ones.

Enhanced summer convective rainfall at Alpine high elevations in response to climate warming

Abstract: Summer rainfall is projected to decline in the European Alps. Regional high-resolution simulations suggest that at the highest elevations, precipitation may instead increase as a result of enhanced potential instability and convective rainfall.

Fuel moisture sensitivity to temperature and precipitation: climate change implications

Abstract: The objective of this paper is to examine the sensitivity of fuel moisture to changes in temperature and precipitation and explore the implications under a future climate. We use the Canadian Forest Fire Weather Index System components to represent the moisture content of fine surface fuels (Fine Fuel Moisture Code, FFMC), upper forest floor (duff) layers (Duff Moisture Code, DMC) and deep organic soils (Drought Code, DC). We obtained weather data from 12 stations across Canada for the fire season during the 1971–2000 period and with these data we created a set of modified weather streams from the original data by varying the daily temperatures by 0 to +5 °C in increments of 1 °C and the daily precipitation from −40 to 40 % in increments of 10 %. The fuel moistures were calculated for all the temperature and precipitation combinations. When temperature increases we find that for every degree of warming, precipitation has to increase by more than 15 % for FFMC, about 10 % for DMC and about 5 % for DC to compensate for the drying caused by warmer temperatures. Also, we find in terms of the number of days equal to or above an FFMC of 91, a critical value for fire spread, that no increase in precipitation amount alone could compensate for a temperature increase of 1 °C. Results from three General Circulation Models (GCMs) and three emission scenarios suggest that this sensitivity to temperature increases will result in a future with drier fuels and a higher frequency of extreme fire weather days.

Evaluation and comparison of satellite-based rainfall products in Burkina Faso, West Africa

Abstract: The performance of seven operational high-resolution satellite-based rainfall products – Africa Rainfall Estimate Climatology ARC 2.0, Climate Hazards Group InfraRed Precipitation with Stations CHIRPS, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks PERSIANN, African Rainfall Estimation RFE 2.0, Tropical Applications of Meteorology using SATellite TAMSAT, African Rainfall Climatology and Time-series TARCAT, and Tropical Rainfall Measuring Mission TRMM daily and monthly estimates – was investigated for Burkina Faso. These were compared to ground data for 2001–2014 on a point-to-pixel basis at daily to annual time steps. Continuous statistics was used to assess their performance in estimating and reproducing rainfall amounts, and categorical statistics to evaluate rain detection capabilities. The north–south gradient of rainfall was captured by all products, which generally detected heavy rainfall events, but showed low correlation for rainfall amounts. At daily scale they performed poorly. As the time step increased, the performance improved. All except TARCAT provided excellent scores for Bias and Nash–Sutcliffe Efficiency coefficients, and overestimated rainfall amounts at the annual scale. RFE performed the best, whereas TARCAT was the weakest. Choice of product depends on the specific application: ARC, RFE, and TARCAT for drought monitoring, and PERSIANN, CHIRPS, and TRMM daily for flood monitoring in Burkina Faso.

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover.

Abstract: Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation.

The past, present and future of African dust

Abstract: African dust emission and transport exhibits variability on diurnal to decadal timescales and is known to influence processes such as Amazon productivity, Atlantic climate modes, regional atmospheric composition and radiative balance and precipitation in the Sahel. To elucidate the role of African dust in the climate system, it is necessary to understand the factors governing its emission and transport. However, African dust is correlated with seemingly disparate atmospheric phenomena, including the El Nino/Southern Oscillation, the North Atlantic Oscillation, the meridional position of the intertropical convergence zone, Sahelian rainfall and surface temperatures over the Sahara Desert, all of which obfuscate the connection between dust and climate. Here we show that the surface wind field responsible for most of the variability in North African dust emission reflects the topography of the Sahara, owing to orographic acceleration of the surface flow. As such, the correlations between dust and various climate phenomena probably arise from the projection of the winds associated with these phenomena onto an orographically controlled pattern of wind variability. A 161-year time series of dust from 1851 to 2011, created by projecting this wind field pattern onto surface winds from a historical reanalysis, suggests that the highest concentrations of dust occurred from the 1910s to the 1940s and the 1970s to the 1980s, and that there have been three periods of persistent anomalously low dust concentrations--in the 1860s, 1950s and 2000s. Projections of the wind pattern onto climate models give a statistically significant downward trend in African dust emission and transport as greenhouse gas concentrations increase over the twenty-first century, potentially associated with a slow-down of the tropical circulation. Such a dust feedback, which is not represented in climate models, may be of benefit to human and ecosystem health in West Africa via improved air quality and increased rainfall. This feedback may also enhance warming of the tropical North Atlantic, which would make the basin more suitable for hurricane formation and growth.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multimodel study.

Abstract: Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change

Abstract: . A stationary low pressure system and elevated levels of precipitable water provided a nearly continuous source of precipitation over Louisiana, United States (US), starting around 10 August 2016. Precipitation was heaviest in the region broadly encompassing the city of Baton Rouge, with a 3-day maximum found at a station in Livingston, LA (east of Baton Rouge), from 12 to 14 August 2016 (648.3 mm, 25.5 inches). The intense precipitation was followed by inland flash flooding and river flooding and in subsequent days produced additional backwater flooding. On 16 August, Louisiana officials reported that 30 000 people had been rescued, nearly 10 600 people had slept in shelters on the night of 14 August and at least 60 600 homes had been impacted to varying degrees. As of 17 August, the floods were reported to have killed at least 13 people. As the disaster was unfolding, the Red Cross called the flooding the worst natural disaster in the US since Super Storm Sandy made landfall in New Jersey on 24 October 2012. Before the floodwaters had receded, the media began questioning whether this extreme event was caused by anthropogenic climate change. To provide the necessary analysis to understand the potential role of anthropogenic climate change, a rapid attribution analysis was launched in real time using the best readily available observational data and high-resolution global climate model simulations. The objective of this study is to show the possibility of performing rapid attribution studies when both observational and model data and analysis methods are readily available upon the start. It is the authors' aspiration that the results be used to guide further studies of the devastating precipitation and flooding event. Here, we present a first estimate of how anthropogenic climate change has affected the likelihood of a comparable extreme precipitation event in the central US Gulf Coast. While the flooding event of interest triggering this study occurred in south Louisiana, for the purposes of our analysis, we have defined an extreme precipitation event by taking the spatial maximum of annual 3-day inland maximum precipitation over the region of 29–31° N, 85–95° W, which we refer to as the central US Gulf Coast. Using observational data, we find that the observed local return time of the 12–14 August precipitation event in 2016 is about 550 years (95 % confidence interval (CI): 450–1450). The probability for an event like this to happen anywhere in the region is presently 1 in 30 years (CI 11–110). We estimate that these probabilities and the intensity of extreme precipitation events of this return time have increased since 1900. A central US Gulf Coast extreme precipitation event has effectively become more likely in 2016 than it was in 1900. The global climate models tell a similar story; in the most accurate analyses, the regional probability of 3-day extreme precipitation increases by more than a factor of 1.4 due to anthropogenic climate change. The magnitude of the shift in probabilities is greater in the 25 km (higher-resolution) climate model than in the 50 km model. The evidence for a relation to El Nino half a year earlier is equivocal, with some analyses showing a positive connection and others none.

Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use

Abstract: . When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

Abstract: . On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basins on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. The evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.

The residence time of water in the atmosphere revisited

Abstract: . This paper revisits the knowledge on the residence time of water in the atmosphere. Based on state-of-the-art data of the hydrological cycle we derive a global average residence time of 8.9 ± 0.4 days (uncertainty given as 1 standard deviation). We use two different atmospheric moisture tracking models (WAM-2layers and 3D-T) to obtain atmospheric residence time characteristics in time and space. The tracking models estimate the global average residence time to be around 8.5 days based on ERA-Interim data. We conclude that the statement of a recent study that the global average residence time of water in the atmosphere is 4–5 days, is not correct. We derive spatial maps of residence time, attributed to evaporation and precipitation, and age of atmospheric water, showing that there are different ways of looking at temporal characteristics of atmospheric water. Longer evaporation residence times often indicate larger distances towards areas of high precipitation. From our analysis we find that the residence time over the ocean is about 2 days less than over land. It can be seen that in winter, the age of atmospheric moisture tends to be much lower than in summer. In the Northern Hemisphere, due to the contrast in ocean-to-land temperature and associated evaporation rates, the age of atmospheric moisture increases following atmospheric moisture flow inland in winter, and decreases in summer. Looking at the probability density functions of atmospheric residence time for precipitation and evaporation, we find long-tailed distributions with the median around 5 days. Overall, our research confirms the 8–10-day traditional estimate for the global mean residence time of atmospheric water, and our research contributes to a more complete view of the characteristics of the turnover of water in the atmosphere in time and space.

Empirical evidence of contrasting soil moisture–precipitation feedbacks across the United States

Abstract: Soil moisture influences fluxes of heat and moisture originating at the land surface, thus altering atmospheric humidity and temperature profiles. However, empirical and modeling studies disagree on how this affects the propensity for precipitation, mainly owing to the difficulty in establishing causality. We use Granger causality to estimate the relationship between soil moisture and occurrence of subsequent precipitation over the contiguous United States using remotely sensed soil moisture and gauge-based precipitation observations. After removing potential confounding effects of daily persistence, and seasonal and interannual variability in precipitation, we find that soil moisture anomalies significantly influence rainfall probabilities over 38% of the area with a median factor of 13%. The feedback is generally positive in the west and negative in the east, suggesting dependence on regional aridity.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

Abstract: The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).