Showing papers on "Precipitation published in 2015"

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

Abstract: The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

Anthropogenic warming has increased drought risk in California

Abstract: California is currently in the midst of a record-setting drought. The drought began in 2012 and now includes the lowest calendar-year and 12-mo precipitation, the highest annual temperature, and the most extreme drought indicators on record. The extremely warm and dry conditions have led to acute water shortages, groundwater overdraft, critically low streamflow, and enhanced wildfire risk. Analyzing historical climate observations from California, we find that precipitation deficits in California were more than twice as likely to yield drought years if they occurred when conditions were warm. We find that although there has not been a substantial change in the probability of either negative or moderately negative precipitation anomalies in recent decades, the occurrence of drought years has been greater in the past two decades than in the preceding century. In addition, the probability that precipitation deficits co-occur with warm conditions and the probability that precipitation deficits produce drought have both increased. Climate model experiments with and without anthropogenic forcings reveal that human activities have increased the probability that dry precipitation years are also warm. Further, a large ensemble of climate model realizations reveals that additional global warming over the next few decades is very likely to create ∼100% probability that any annual-scale dry period is also extremely warm. We therefore conclude that anthropogenic warming is increasing the probability of co-occurring warm–dry conditions like those that have created the acute human and ecosystem impacts associated with the “exceptional” 2012–2014 drought in California.

Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes

Abstract: The contribution of human-induced climate change to global heavy precipitation and hot extreme events is quantified. The results show that of the moderate extremes, 18% of precipitation and 75% of high-temperature events are attributable to warming.

PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies

Abstract: A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S–60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset ...

East Asian summer monsoon precipitation variability since the last deglaciation

Abstract: The lack of a precisely-dated, unequivocal climate proxy from northern China, where precipitation variability is traditionally considered as an East Asian summer monsoon (EASM) indicator, impedes our understanding of the behaviour and dynamics of the EASM. Here we present a well-dated, pollen-based, ~20-yr-resolution quantitative precipitation reconstruction (derived using a transfer function) from an alpine lake in North China, which provides for the first time a direct record of EASM evolution since 14.7 ka (ka = thousands of years before present, where the "present" is defined as the year AD 1950). Our record reveals a gradually intensifying monsoon from 14.7-7.0 ka, a maximum monsoon (30% higher precipitation than present) from ~7.8-5.3 ka, and a rapid decline since ~3.3 ka. These insolation-driven EASM trends were punctuated by two millennial-scale weakening events which occurred synchronously to the cold Younger Dryas and at ~9.5-8.5 ka, and by two centennial-scale intervals of enhanced (weakened) monsoon during the Medieval Warm Period (Little Ice Age). Our precipitation reconstruction, consistent with temperature changes but quite different from the prevailing view of EASM evolution, points to strong internal feedback processes driving the EASM, and may aid our understanding of future monsoon behaviour under ongoing anthropogenic climate change.

ERA-Interim/Land: a global land surface reanalysis data set

Abstract: ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

Precipitation Extremes Under Climate Change.

Abstract: The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate. However, the sensitivity of precipitation extremes to warming remains uncertain when convection is important, and it may be higher in the tropics than the extratropics. Several physical contributions govern the response of precipitation extremes. The thermodynamic contribution is robust and well understood, but theoretical understanding of the microphysical and dynamical contributions is still being developed. Orographic precipitation extremes and snowfall extremes respond differently from other precipitation extremes and require particular attention. Outstanding research challenges include the influence of mesoscale convective organization, the dependence on the duration considered, and the need to better constrain the sensitivity of tropical precipitation extremes to warming.

Detection of atmospheric rivers: Evaluation and application of an algorithm for global studies

Abstract: Atmospheric rivers (ARs) are narrow, elongated, synoptic jets of water vapor that play important roles in the global water cycle and regional weather/hydrology. A technique is developed for objective detection of ARs on the global domain based on characteristics of the integrated water vapor transport (IVT). AR detection involves thresholding 6-hourly fields of ERA-Interim IVT based on the 85th percentile specific to each season and grid cell and a fixed lower limit of 100 kg m−1 s−1 and checking for the geometry requirements of length >2000 km, length/width ratio >2, and other considerations indicative of AR conditions. Output of the detection includes the AR shape, axis, landfall location, and basic statistics of each detected AR. The performance of the technique is evaluated by comparison to AR detection in the western North America, Britain, and East Antarctica with three independently conducted studies using different techniques, with over ~90% agreement in AR dates. Among the parameters tested, AR detection shows the largest sensitivity to the length criterion in terms of changes in the resulting statistical distribution of AR intensity and geometry. Global distributions of key AR characteristics are examined, and the results highlight the global footprints of ARs and their potential importance on global and regional scales. Also examined are seasonal dependence of AR frequency and precipitation and their modulation by four prominent modes of large-scale climate variability. The results are in broad consistency with previous studies that focused on landfalling ARs in the west coasts of North America and Europe.

Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia

Abstract: Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment. Although there are enough historical evidence to support the theory that climate change is a natural phenomenon, many research scientists are widely in agreement that the increase in temperature in the 20th century is anthropologically related. The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally. In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness. This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia. The comparison of decadal variation of precipitation and temperature anomalies before the 1970s found general increases which were mostly varying. But beyond the 1970s, global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period. There are frequent changes and a shift westward of the Indian summer monsoon. Although precipitation is observed to be 70% below normal levels, in some areas the topography affects the intensity of rainfall. These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future. The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human, financial, infrastructure and food security of the region.

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau

Abstract: The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite-derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long-term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm−1. Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C−1 (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.

Climate and southern Africa's water-energy-food nexus

Abstract: In southern Africa, the connections between climate and the water–energy–food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven, for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and gross domestic product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose: the Southern African Development Community, the Southern African Power Pool and trade of agricultural products amounting to significant transfers of embedded water.

Impacts of altered precipitation regimes on soil communities and biogeochemistry in arid and semi-arid ecosystems.

Abstract: Altered precipitation patterns resulting from climate change will have particularly significant consequences in water-limited ecosystems, such as arid to semi-arid ecosystems, where discontinuous inputs of water control biological processes. Given that these ecosystems cover more than a third of Earth's terrestrial surface, it is important to understand how they respond to such alterations. Altered water availability may impact both aboveground and belowground communities and the interactions between these, with potential impacts on ecosystem functioning; however, most studies to date have focused exclusively on vegetation responses to altered precipitation regimes. To synthesize our understanding of potential climate change impacts on dryland ecosystems, we present here a review of current literature that reports the effects of precipitation events and altered precipitation regimes on belowground biota and biogeochemical cycling. Increased precipitation generally increases microbial biomass and fungal:bacterial ratio. Few studies report responses to reduced precipitation but the effects likely counter those of increased precipitation. Altered precipitation regimes have also been found to alter microbial community composition but broader generalizations are difficult to make. Changes in event size and frequency influences invertebrate activity and density with cascading impacts on the soil food web, which will likely impact carbon and nutrient pools. The long-term implications for biogeochemical cycling are inconclusive but several studies suggest that increased aridity may cause decoupling of carbon and nutrient cycling. We propose a new conceptual framework that incorporates hierarchical biotic responses to individual precipitation events more explicitly, including moderation of microbial activity and biomass by invertebrate grazing, and use this framework to make some predictions on impacts of altered precipitation regimes in terms of event size and frequency as well as mean annual precipitation. While our understanding of dryland ecosystems is improving, there is still a great need for longer term in situ manipulations of precipitation regime to test our model.

Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

Abstract: . Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash–Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

Heavy precipitation in a changing climate: Does short‐term summer precipitation increase faster?

Abstract: Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6–7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.

The variable nature of convection in the tropics and subtropics: A legacy of 16 years of the Tropical Rainfall Measuring Mission satellite.

Abstract: For over 16 years, the Precipitation Radar of the Tropical Rainfall Measuring Mission (TRMM) satellite detected the three-dimensional structure of significantly precipitating clouds in the tropics and subtropics. This paper reviews and synthesizes studies using the TRMM radar data to present a global picture of the variation of convection throughout low latitudes. The multiyear data set shows convection varying not only in amount but also in its very nature across the oceans, continents, islands, and mountain ranges of the tropics and subtropics. Shallow isolated raining clouds are overwhelmingly an oceanic phenomenon. Extremely deep and intense convective elements occur almost exclusively over land. Upscale growth of convection into mesoscale systems takes a variety of forms. Oceanic cloud systems generally have less intense embedded convection but can form very wide stratiform regions. Continental mesoscale systems often have more intense embedded convection. Some of the most intense convective cells and mesoscale systems occur near the great mountain ranges of low latitudes. The Maritime Continent and Amazonia exhibit convective clouds with maritime characteristics although they are partially or wholly land. Convective systems containing broad stratiform areas manifest most strongly over oceans. The stratiform precipitation occurs in various forms. Often it occurs as quasi-uniform precipitation with strong melting layers connected with intense convection. In monsoons and the Intertropical Convergence Zone, it takes the form of closely packed weak convective elements. Where fronts extend into the subtropics, broad stratiform regions are larger and have lower and sloping melting layers related to the baroclinic origin of the precipitation.

The key role of dry days in changing regional climate and precipitation regimes

Abstract: Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability.

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

Abstract: Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6–7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.

Reconciling high-altitude precipitation in the upper Indus basin with glacier mass balances and runoff

Abstract: . Mountain ranges in Asia are important water suppliers, especially if downstream climates are arid, water demands are high and glaciers are abundant. In such basins, the hydrological cycle depends heavily on high-altitude precipitation. Yet direct observations of high-altitude precipitation are lacking and satellite derived products are of insufficient resolution and quality to capture spatial variation and magnitude of mountain precipitation. Here we use glacier mass balances to inversely infer the high-altitude precipitation in the upper Indus basin and show that the amount of precipitation required to sustain the observed mass balances of large glacier systems is far beyond what is observed at valley stations or estimated by gridded precipitation products. An independent validation with observed river flow confirms that the water balance can indeed only be closed when the high-altitude precipitation on average is more than twice as high and in extreme cases up to a factor of 10 higher than previously thought. We conclude that these findings alter the present understanding of high-altitude hydrology and will have an important bearing on climate change impact studies, planning and design of hydropower plants and irrigation reservoirs as well as the regional geopolitical situation in general.

Frequency of occurrence of rain from liquid-, mixed-, and ice-phase clouds derived from A-Train satellite retrievals.

Abstract: A climatology of thermodynamic phase of precipitating cloud is presented derived from global, land and ocean, retrievals from Cloudsat, CALIPSO, and MODIS. Like precipitation rate, precipitation frequency is dominated by warm rain, defined as rain produced via the liquid phase only, over the tropical oceans outside the ITCZ and by cold rain, produced via the ice phase, over the midlatitude oceans and continents. Warm rain is very infrequent over the continents, with significant warm rain found only in onshore flow in the tropics, and over India, China, and Indochina. Comparison of the properties of precipitating and non-precipitating warm clouds shows that the scarcity of warm rain over land can be explained by smaller effective radii in continental clouds that delay the onset of precipitation. The results highlight the importance of ice-phase processes for the global hydrological cycle and may lead to an improved parameterization of precipitation in general circulation models.

Characterizing differences in precipitation regimes of extreme wet and dry years: implications for climate change experiments.

Abstract: Climate change is intensifying the hydrologic cycle and is expected to increase the frequency of extreme wet and dry years. Beyond precipitation amount, extreme wet and dry years may differ in other ways, such as the number of precipitation events, event size, and the time between events. We assessed 1614 long-term (100 year) precipitation records from around the world to identify key attributes of precipitation regimes, besides amount, that distinguish statistically extreme wet from extreme dry years. In general, in regions where mean annual precipitation (MAP) exceeded 1000 mm, precipitation amounts in extreme wet and dry years differed from average years by ~40% and 30%, respectively. The magnitude of these deviations increased to >60% for dry years and to >150% for wet years in arid regions (MAP 99th percentile of all events); these occurred twice as often in extreme wet years compared to average years. In contrast, these large precipitation events were rare in extreme dry years. Less important for distinguishing extreme wet from dry years were mean event size and frequency, or the number of dry days between events. However, extreme dry years were distinguished from average years by an increase in the number of dry days between events. These precipitation regime attributes consistently differed between extreme wet and dry years across 12 major terrestrial ecoregions from around the world, from deserts to the tropics. Thus, we recommend that climate change experiments and model simulations incorporate these differences in key precipitation regime attributes, as well as amount into treatments. This will allow experiments to more realistically simulate extreme precipitation years and more accurately assess the ecological consequences.

Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

Abstract: Satellite precipitation products (SPPs) potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation However, applications of these products are still limited due to the lack of robust quality assessment This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH) and a ground-based precipitation product (APHRODITE) The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R2, ME, MAE, and RB) and categorical (ACC, POD, FAR, CSI, and HSS) statistical approaches Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 47%, and 21%, respectively By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 197% and 132%, respectively, whereas GPCP-1DD only slightly underestimated by 28% All six precipitation products performed better in the northeast monsoon than in the southwest monsoon The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia All precipitation products underestimated the no/tiny (<1 mm/day) and extreme (≥20 mm/day) rainfall events, while they overestimated low (1–20 mm/day) rainfall events 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (036) Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R2 value ranging from 049 to 088 and 052 to 086, respectively These results on SPPs’ uncertainties and their potential controls might allow sensor and algorithm developers to deliver better products for improved rainfall estimation and thus improved water management

Observed Trends in Canada’s Climate and Influence of Low-Frequency Variability Modes

Abstract: Trends in Canada’s climate are analyzed using recently updated data to provide a comprehensive view of climate variability and long-term changes over the period of instrumental record. Trends in surface air temperature, precipitation, snow cover, and streamflow indices are examined along with the potential impact of low-frequency variability related to large-scale atmospheric and oceanic oscillations on these trends. The results show that temperature has increased significantly in most regions of Canada over the period 1948–2012, with the largest warming occurring in winter and spring. Precipitation has also increased, especially in the north. Changes in other climate and hydroclimatic variables, including a decrease in the amount of precipitation falling as snow in the south, fewer days with snow cover, an earlier start of the spring high-flow season, and an increase in April streamflow, are consistent with the observed warming and precipitation trends. For the period 1900–2012, there are suffici...

Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China

Abstract: This study evaluates the performance of a newly developed daily precipitation climate data record, called Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), in capturing the behavior of daily extreme precipitation events in China during the period of 1983–2006. Different extreme precipitation indices, in the three categories of percentile, absolute threshold, and maximum indices, are studied and compared with the same indices from the East Asia (EA) ground-based gridded daily precipitation dataset. The results show that PERSIANN-CDR depicts similar precipitation behavior as the ground-based EA product in terms of capturing the spatial and temporal patterns of daily precipitation extremes, particularly in the eastern China monsoon region, where the intensity and frequency of heavy rainfall events are very high. However, the agreement between the datasets in dry regions such as the Tibetan Plateau in the west and the Taklama...

Enhanced precipitation variability decreases grass- and increases shrub-productivity

Abstract: Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society.

Warming-induced northwestward migration of the East Asian monsoon rain belt from the Last Glacial Maximum to the mid-Holocene.

Abstract: Glacial-interglacial changes in the distribution of C3/C4 vegetation on the Chinese Loess Plateau have been related to East Asian summer monsoon intensity and position, and could provide insights into future changes caused by global warming. Here, we present δ(13)C records of bulk organic matter since the Last Glacial Maximum (LGM) from 21 loess sections across the Loess Plateau. The δ(13)C values (range: -25‰ to -16‰) increased gradually both from the LGM to the mid-Holocene in each section and from northwest to southeast in each time interval. During the LGM, C4 biomass increased from 40% in the southeast. The spatial pattern of C4 biomass in both the LGM and the mid-Holocene closely resembles that of modern warm-season precipitation, and thus can serve as a robust analog for the contemporary East Asian summer monsoon rain belt. Using the 10-20% isolines for C4 biomass in the cold LGM as a reference, we derived a minimum 300-km northwestward migration of the monsoon rain belt for the warm Holocene. Our results strongly support the prediction that Earth's thermal equator will move northward in a warmer world. The southward displacement of the monsoon rain belt and the drying trend observed during the last few decades in northern China will soon reverse as global warming continues.

Benefit of convection permitting climate model simulations in the representation of convective precipitation

Abstract: A major source of uncertainty in regional climate model (RCM) simulations arises from the parameterisation of sub-grid scale convection. With increasing model resolution, approaching the so-called convection permitting scale, it is possible to switch off most of the convection parameterisations. A set of simulations using COSMO-CLM model has been carried out at different resolutions in order to investigate possible improvements and limitations resulting from increased horizontal resolution. For our analysis, 30 years were simulated in a triple nesting setup with 50, 7 and 2.8 km resolutions, with ERA40 reanalysis data at the lateral boundaries of the coarsest nest. The investigation area covers the state of Baden-Wurttemberg in southwestern Germany, which is a region known for abundant orographically induced convective precipitation. A very dense network of high temporal resolution rain gauges is used for evaluation of the model simulations. The purpose of this study is to examine the differences between the 7 and 2.8 km resolutions in the representation of precipitation at sub-daily timescales, and the atmospheric conditions leading to convection. Our results show that the highest resolution of RCM simulations significantly improves the representation of both hourly intensity distribution and diurnal cycle of precipitation. In addition, at convection permitting scale the atmospheric fields related to convective precipitation show a better agreement with each other. The results imply that higher spatial resolution partially improves the representation of the precipitation field, which must be the way forward for regional climate modelling.

Dynamical downscaling of CMIP5 global circulation models over CORDEX-Africa with COSMO-CLM: evaluation over the present climate and analysis of the added value

Abstract: In this work we present the results of the application of the consortium for small-scale modeling (COSMO) regional climate model (COSMO-CLM, hereafter, CCLM) over Africa in the context of the coordinated regional climate downscaling experiment. An ensemble of climate change projections has been created by downscaling the simulations of four global climate models (GCM), namely: MPI-ESM-LR, HadGEM2-ES, CNRM-CM5, and EC-Earth. Here we compare the results of CCLM to those of the driving GCMs over the present climate, in order to investigate whether RCMs are effectively able to add value, at regional scale, to the performances of GCMs. It is found that, in general, the geographical distribution of mean sea level pressure, surface temperature and seasonal precipitation is strongly affected by the boundary conditions (i.e. driving GCMs), and seasonal statistics are not always improved by the downscaling. However, CCLM is generally able to better represent the annual cycle of precipitation, in particular over Southern Africa and the West Africa monsoon (WAM) area. By performing a singular spectrum analysis it is found that CCLM is able to reproduce satisfactorily the annual and sub-annual principal components of the precipitation time series over the Guinea Gulf, whereas the GCMs are in general not able to simulate the bimodal distribution due to the passage of the WAM and show a unimodal precipitation annual cycle. Furthermore, it is shown that CCLM is able to better reproduce the probability distribution function of precipitation and some impact-relevant indices such as the number of consecutive wet and dry days, and the frequency of heavy rain events.