1,721,198 research outputs found
Evapotranspiration partitioning in CMIP5 models: Uncertainties and future projections
No full textEvapotranspiration (ET) is a key process affecting terrestrial hydroclimate, as it modulates the land surface carbon, energy, and water budgets. Evapotranspiration mainly consists of the sum of three components: plant transpiration, soil evaporation, and canopy interception. Here we investigate how the partitioning of ET into these three main components is represented in CMIP5 model simulations of present and future climate. A large spread exists between models in the simulated mean present-day partitioning; even the ranking of the different components in the global mean differs between models. Differences in the simulation of the vegetation leaf area index appear to be an important cause of this spread. Although ET partitioning is not accurately known globally, existing global estimates suggest that CMIP5 models generally underestimate the relative contribution of transpiration. Differences in ET partitioning lead to differences in climate characteristics over land, such as land–atmosphere fluxes and near-surface air temperature. On the other hand, CMIP5 models simulate robust patterns of future changes in ET partitioning under global warming, notably a marked contrast between decreased transpiration and increased soil evaporation in the tropics, whereas transpiration and evaporation both increase at higher latitudes and both decrease in the dry subtropics. Idealized CMIP5 simulations from a subset of models show that the decrease in transpiration in the tropics largely reflects the stomatal closure effect of increased atmospheric CO2 on plants (despite increased vegetation from CO2 fertilization), whereas changes at higher latitudes are dominated by radiative CO2 effects, with warming and increased precipitation leading to vegetation increase and simultaneous (absolute) increases in all three ET components
Changes in the low flow regime over the eastern United States (1962–2011): variability, trends, and attributions
No full textWe examine trends and variability in low flows over the eastern U.S. (S. Carolina to Maine) and their attribution in a changing climate. We select 149 out of 4878 USGS stations over the eastern U.S., taking into account data availability and minimal direct management. Annual 7-day low flows (Q7) are computed from the series of daily streamflow records for 1962–2011 and compared to an antecedent precipitation (AP) index calculated over the corresponding basin for each station. In general, a north–south (increasing-decreasing) dipole pattern in low flow trends is associated with trends in AP. The exception is in the southern part of the study area including Virginia and the Carolinas, where moderate increasing trends in AP may have been offset by water withdrawals and increasing potential evapotranspiration (PET) as driven by increasing temperature and vapor pressure deficit. A principal component analysis (PCA) of Q7 and AP indicates that the North Atlantic Oscillation (NAO) and Pacific North America (PNA) pattern show statistically significant correlations for Q7 at 1 and 2 month lead time, respectively, via large-scale pressure patterns. Our findings suggest that the inter-annual variability of low flows has increased due to significant anti-correlation between the NAO and PNA during recent decades, and the future risk of low flow extremes may be further enhanced with temperature driven increases in PET and persistence of the multi-decadal relationship between NAO and PNA.</p
Global trends and variability in soil moisture and drought characteristics, 1950-2000, from observation-driven simulations of the terrestrial hydrologic cycle
No full textGlobal and regional trends in drought for 1950-2000 are analyzed using a soil moisture-based drought index over global terrestrial areas, excluding Greenland and Antarctica. The soil moisture fields are derived from a simulation of the terrestrial hydrologic cycle driven by a hybrid reanalysis-observation forcing dataset. Drought is described in terms of various statistics that summarize drought duration, intensity, and severity. There is an overall small wetting trend in global soil moisture, forced by increasing precipitation, which is weighted by positive soil moisture trends over the Western Hemisphere and especially in North America. Regional variation is nevertheless apparent, and significant drying over West Africa, as driven by decreasing Sahel precipitation, stands out. Elsewhere, Europe appears to have not experienced significant changes in soil moisture, a trait shared by Southeast and southern Asia. Trends in drought duration, intensity, and severity are predominantly decreasing, but statistically significant changes are limited in areal extent, of the order of 1.0%-7.0% globally, depending on the variable and drought threshold, and are generally less than 10% of continental areas. Concurrent changes in drought spatial extent are evident, with a global decreasing trend of between -0.021% and -0.035% yr-1. Regionally, drought spatial extent over Africa has increased and is dominated by large increases over West Africa. Northern and East Asia show positive trends, and central Asia and the Tibetan Plateau show decreasing trends. In South Asia all trends are insignificant. Drought extent over Australia has decreased. Over the Americas, trends are uniformly negative and mostly significant. Within the long-term trends there are considerable interannual and decadal variations in soil moisture and drought characteristics for most regions, which impact the robustness of the trends. Analysis of detrended and smoothed soil moisture time series reveals that the leading modes of variability are associated with sea surface temperatures, primarily in the equatorial Pacific and secondarily in the North Atlantic. Despite the overall wetting trend there is a switch since the 1970s to a drying trend, globally and in many regions, especially in high northern latitudes. This is shown to be caused, in part, by concurrent increasing temperatures. Although drought is driven primarily by variability in precipitation, projected continuation of temperature increases during the twenty-first century indicate the potential for enhanced drought occurrence.</p
Characteristics of global and regional drought, 1950-2000: analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle
No full textDrought occurrence is analyzed over global land areas for 1950-2000 using soil moisture data from a simulation of the terrestrial water cycle with the Variable Infiltration Capacity (VIC) land surface model, which is forced by an observation based meteorological data set. A monthly drought index based on percentile soil moisture values relative to the 50-year climatology is analyzed in terms of duration, intensity and severity at global and regional scales. Short-term droughts (<= 6 months) are prevalent in the Tropics and midlatitudes, where inter-annual climate variability is highest. Medium term droughts (7-12 months) are more frequent in mid- to high-latitudes. Long term (12+ months) droughts are generally restricted to sub-Saharan Africa and higher northern latitudes. The Sahel region stands out for having experienced long-term and severe drought conditions. Severe regional drought events are systematically identified in terms of spatial coverage, based on different thresholds of duration and intensity. For example, in northern Europe, 1996 and 1975 were the years of most extensive 3- and 12-month duration drought, respectively. In northern Asia, severe drought events are characterized by persistent soil moisture anomalies over the wintertime. The drought index identifies several well-known events, including the 1988 US, 1982/83 Australian, 1983/4 Sahel and 1965/66 Indian droughts which are generally ranked as the severest and most spatially extensive in the record. Comparison with the PDSI shows general agreement at global scales and for these major events but they diverge considerably in cooler regions and seasons, and especially in latter years when the PDSI shows a larger drying trend.</p
Uncertainties in future projections of summer droughts and heatwaves over the contiguous United States
No full textDrought: Past problems and future scenarios
No full textDrought is one of the likely consequences of climate change in many regions of the world. Together with an increased demand for water resources to supply the world's growing population, it represents a potentially disastrous threat to water supplies, agriculture and food production, leading to famine and environmental degradation. Yet predicting drought is fraught with difficulty. The aim of this book is to provide a review of the historical occurrence of global drought, particularly during the 20th century and assess the likely potential changes over the 21st century under climate change. This includes documentation of the occurrence and impacts of major 20th century drought events and analysis of the contributing climatic and environmental factors that act to force, prolong and dissipate drought. Contemporary drought is placed in the context of climate variability since the last ice age, including the many severe and lengthy drought events that contributed to the demise of great civilizations, the disappearance of lakes and rivers, and the conversion of forests to deserts. The authors discuss the developing field of drought monitoring and seasonal forecasting and describe how this is vital for identifying emerging droughts and for providing timely warning to help reduce the impacts. The book provides a broad overview of large scale drought, from historic events such as the US Dust Bowl and African Sahel, and places this in the context of climate variability and change. The work is soundly based on detailed research that has looked at drought occurrence over the 20th century, global drought monitoring, modelling and seasonal prediction, and future projections from climate models
Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations
No full textRecent and potential future increases in global temperatures are likely to be associated with impacts on the hydrologic cycle, including changes to precipitation and increases in extreme events such as droughts. We analyze changes in drought occurrence using soil moisture data for the SRES B1, A1B and A2 future climate scenarios relative to the PICNTRL pre-industrial control and 20C3M twentieth century simulations from eight AOGCMs that participated in the IPCC AR4. Comparison with observation forced land surface model estimates indicates that the models do reasonably well at replicating our best estimates of twentieth century, large scale drought occurrence, although the frequency of long-term (more than 12-month duration) droughts are over-estimated. Under the future projections, the models show decreases in soil moisture globally for all scenarios with a corresponding doubling of the spatial extent of severe soil moisture deficits and frequency of short-term (4-6-month duration) droughts from the mid-twentieth century to the end of the twenty-first. Long-term droughts become three times more common. Regionally, the Mediterranean, west African, central Asian and central American regions show large increases most notably for long-term frequencies as do mid-latitude North American regions but with larger variation between scenarios. In general, changes under the higher emission scenarios, A1B and A2 are the greatest, and despite following a reduced emissions pathway relative to the present day, the B1 scenario shows smaller but still substantial increases in drought, globally and for most regions. Increases in drought are driven primarily by reductions in precipitation with increased evaporation from higher temperatures modulating the changes. In some regions, increases in precipitation are offset by increased evaporation. Although the predicted future changes in drought occurrence are essentially monotonic increasing globally and in many regions, they are generally not statistically different from contemporary climate (as estimated from the 1961-1990 period of the 20C3M simulations) or natural variability (as estimated from the PICNTRL simulations) for multiple decades, in contrast to primary climate variables, such as global mean surface air temperature and precipitation. On the other hand, changes in annual and seasonal means of terrestrial hydrologic variables, such as evaporation and soil moisture, are essentially undetectable within the twenty-first century. Changes in the extremes of climate and their hydrological impacts may therefore be more detectable than changes in their means.</p
Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching
No full textA new quantile-based mapping method is developed for the bias correction of monthly global circulation model outputs. Compared to the widely used quantile-based matching method that assumes stationarity and only uses the cumulative distribution functions (CDFs) of the model and observations for the baseline period, the proposed method incorporates and adjusts the model CDF for the projection period on the basis of the difference between the model and observation CDFs for the training (baseline) period. Thus, the method explicitly accounts for distribution changes for a given model between the projection and baseline periods. We demonstrate the use of the new method over northern Eurasia. We fit a four-parameter beta distribution to monthly temperature fields and discuss the sensitivity of the results to the choice of distribution range parameters. For monthly precipitation data, a mixed gamma distribution is used that accounts for the intermittent nature of rainfall. To test the fidelity of the proposed method, we choose 1970-1999 as the baseline training period and then randomly select 30 years from 1901-1999 as the projection test period. The bootstrapping is repeated 30 times to mimic different climate conditions that may occur, and the results suggest that both methods are comparable when applied to the 20th century for both temperature and precipitation for the examined quartiles. We also discuss the dependence of the bias correction results on the choice of time period for training. This indicates that the remaining biases in the bias-corrected time series are directly tied to the model's performance during the training period, and therefore care should be taken when using a particular training time period. When applied to the Intergovernmental Panel on Climate Change fourth assessment report (AR4) A2 climate scenario projection, the data time series after bias correction from both methods exhibit similar spatial patterns. However, over regions where the climate model shows large changes in projected variability, there are discernable differences between the methods. The proposed method is more sensitive to a reduction in variability, exemplified by wintertime temperature. Further synthetic experiments using the lower 33% and upper 33% of the full data set as the validation data suggest that the proposed equidistance quantile-matching method is more efficient in reducing biases than the traditional CDF mapping method for changing climates, especially for the tails of the distribution. This has important consequences for the occurrence and intensity of future projected extreme events such as heat waves, floods, and droughts. As the new method is simple to implement and does not require substantial computational time, it can be used to produce auxiliary ensemble scenarios for various climate impact-oriented applications
Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling
No full textUnderstanding the variability of the terrestrial hydrologic cycle is central to determining the potential for extreme events and susceptibility to future change. In the absence of long-term, large-scale observations of the components of the hydrologic cycle, modeling can provide consistent fields of land surface fluxes and states. This paper describes the creation of a global, 50-yr, 3-hourly, 1.0° dataset of meteorological forcings that can be used to drive models of land surface hydrology. The dataset is constructed by combining a suite of global observation-based datasets with the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis. Known biases in the reanalysis precipitation and near-surface meteorology have been shown to exert an erroneous effect on modeled land surface water and energy budgets and are thus corrected using observation-based datasets of precipitation, air temperature, and radiation. Corrections are also made to the rain day statistics of the reanalysis precipitation, which have been found to exhibit a spurious wavelike pattern in high-latitude wintertime. Wind-induced undercatch of solid precipitation is removed using the results from the World Meteorological Organization (WMO) Solid Precipitation Measurement Intercomparison. Precipitation is disaggregated in space to 1.0° by statistical downscaling using relationships developed with the Global Precipitation Climatology Project (GPCP) daily product. Disaggregation in time from daily to 3 hourly is accomplished similarly, using the Tropical Rainfall Measuring Mission (TRMM) 3-hourly real-time dataset. Other meteorological variables (downward short- and longwave radiation, specific humidity, surface air pressure, and wind speed) are downscaled in space while accounting for changes in elevation. The dataset is evaluated against the bias-corrected forcing dataset of the second Global Soil Wetness Project (GSWP2). The final product provides a long-term, globally consistent dataset of near-surface meteorological variables that can be used to drive models of the terrestrial hydrologic and ecological processes for the study of seasonal and interannual variability and for the evaluation of coupled models and other land surface prediction schemes.</p
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