Showing papers in "Journal of Hydrometeorology in 2012"
TL;DR: The three state-of-the-art global atmospheric reanalysis models, namely, ECMWF Interim Re-Analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA; NASA), and Climate Forecast System Reanalysis (CFSR; NCEP), are analyzed and compared with independent observations in the period between 1989 and 2006 as mentioned in this paper.
Abstract: The three state-of-the-art global atmospheric reanalysis models—namely, ECMWF Interim Re-Analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA; NASA), and Climate Forecast System Reanalysis (CFSR; NCEP)—are analyzed and compared with independent observations in the period between 1989 and 2006. Comparison of precipitation and temperature estimates from the three models with gridded observations reveals large differences between the reanalyses and also of the observation datasets. A major source of uncertainty in the observations is the spatial distribution and change of the number of gauges over time. In South America, active measuring stations were reduced from 4267 to 390. The quality of precipitation estimates from the reanalyses strongly depends on the geographic location, as there are significant differences especially in tropical regions. The closure of the water cycle in the three reanalyses is analyzed by estimating long-term mean values for precipi...
334 citations
TL;DR: In this article, preliminary results are presented showing that the two record-setting extreme events during 2010 summer (i.e., the Russian heat wave-wildfires and Pakistan flood) were physically connected.
Abstract: In this paper, preliminary results are presented showing that the two record-setting extreme events during 2010 summer (i.e., the Russian heat wave-wildfires and Pakistan flood) were physically connected. It is found that the Russian heat wave was associated with the development of an extraordinarily strong and prolonged extratropical atmospheric blocking event in association with the excitation of a large-scale atmospheric Rossby wave train spanning western Russia, Kazakhstan, and the northwestern China-Tibetan Plateau region. The southward penetration of upper-level vorticity perturbations in the leading trough of the Rossby wave was instrumental in triggering anomalously heavy rain events over northern Pakistan and vicinity in mid- to late July. Also shown are evidences that the Russian heat wave was amplified by a positive feedback through changes in surface energy fluxes between the atmospheric blocking pattern and an underlying extensive land region with below-normal soil moisture. The Pakistan heavy rain events were amplified and sustained by strong anomalous southeasterly flow along the Himalayan foothills and abundant moisture transport from the Bay of Bengal in connection with the northward propagation of the monsoonal intraseasonal oscillation.
327 citations
TL;DR: In this paper, satellite-based rainfall estimates (SRFE) were validated against 205 rain gauge stations over four African river basins (Zambezi, Volta, Juba-Shabelle, and Baro-Akobo).
Abstract: Six satellite-based rainfall estimates (SRFE)—namely, Climate Prediction Center (CPC) morphing technique (CMORPH), the Rainfall Estimation Algorithm, version 2 (RFE2.0), Tropical Rainfall Measuring Mission (TRMM) 3B42, Goddard profiling algorithm, version 6 (GPROF 6.0), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Global Satellite Mapping of Precipitation moving vector with Kalman filter (GSMap MVK), and one reanalysis product [the interim ECMWF Re-Analysis (ERA-Interim)]—were validated against 205 rain gauge stations over four African river basins (Zambezi, Volta, Juba–Shabelle, and Baro–Akobo). Validation focused on rainfall characteristics relevant to hydrological applications, such as annual catchment totals, spatial distribution patterns, seasonality, number of rainy days per year, and timing and volume of heavy rainfall events. Validation was done at three spatially aggregated levels: point-to-pixel, subcatchment, and river basin for ...
271 citations
TL;DR: In this article, the authors examined the frequency of very heavy and extreme precipitation events in the central United States during the past 31 years and found that up to 40% increase in frequency of days and multiday extreme rain events.
Abstract: In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipit...
245 citations
TL;DR: In this paper, the impacts of anthropogenic activities on the terrestrial water cycle using the framework of land surface models (LSMs) and global terrestrial hydrological models (GHMs) are simulated.
Abstract: Anthropogenic activities have been significantly perturbing global freshwater flows and groundwater reserves. Despite numerous advances in the development of land surface models (LSMs) and global terrestrial hydrological models (GHMs), relatively few studies have attempted to simulate the impacts of anthropogenic activities on the terrestrial water cycle using the framework of LSMs. From the comparison of simulated terrestrial water storage with the Gravity Recovery and Climate Experiment (GRACE) satellite observations it is found that a process-based LSM, the Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO), outperforms the bucket-model-based GHM called H08 in simulating hydrologic variables, particularly in water-limited regions. Therefore, the water regulation modules of H08 are incorporated into MATSIRO. Further, a new irrigation scheme based on the soil moisture deficit is developed. Incorporation of anthropogenic water regulation modules significantly improves river di...
245 citations
TL;DR: In this article, daily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908-2009.
Abstract: Daily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908–2009. Each event was assigned a meteorological cause, categorized as extratropical cyclone near a front (FRT), extratropical cyclone near center of low (ETC), tropical cyclone (TC), mesoscale convective system (MCS), air mass (isolated) convection (AMC), North American monsoon (NAM), and upslope flow (USF). The percentage of events ascribed to each cause were 54% for FRT, 24% for ETC, 13% for TC, 5% for MCS, 3% for NAM, 1% for AMC, and 0.1% for USF. On a national scale, there are upward trends in events associated with fronts and tropical cyclones, but no trends for other meteorological causes. On a regional scale, statistically significant upward trends in the frontal category are found in five of the nine regions. For ETCs, there are statistically significant upward trends in the Northeast and east north central. For the ...
242 citations
TL;DR: In this article, a number of commonly available satellite-derived high-resolution precipitation products (HRPPs) covering northwest Europe over a 6-yr period were evaluated and compared with the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products.
Abstract: Satellite-derived high-resolution precipitation products (HRPP) have been developed to address the needs of the user community and are now available with 0.25° × 0.25° (or less) subdaily resolutions. This paper evaluates a number of commonly available satellite-derived HRPPs covering northwest Europe over a 6-yr period. Precipitation products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing (CMORPH) technique, the CPC merged microwave technique, the Naval Research Laboratory (NRL) blended technique, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) technique. In addition, the Geosynchronous Operational Environmental Satellite (GOES) precipitation index (GPI) and the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products are included for comparison. Surface reference data from the European radar network...
219 citations
TL;DR: The authors assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia and conclude that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall-runoff models.
Abstract: This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–...
203 citations
TL;DR: In this paper, the authors reported that the severity of the 2009 and 2010 China drought was particularly severe in southwestern and northern China, where the accumulated precipitation from May 2009 to April 2010 was about 25% less than normal.
Abstract: Several provinces of China experienced an intense drought episode during 2009 and 2010. The drought was particularly severe in southwestern and northern China, where the accumulated precipitation from May 2009 to April 2010 was about 25% less than normal. The decline of accumulated precipitation over northern China was mostly noticeable during the summer season of 2009 and it was comparable to recent dry episodes. The southwestern China drought resulted from a sequence of dry months from summer 2009 to winter 2010, corresponding to the driest event since at least 1951. The suppression of rainfall in summer over both regions was in agreement with a weakened broad-scale South Asian summer monsoon, possibly influenced by an El Nino developing phase, whereas the extremely negative phases of the Arctic Oscillation during the winter of 2010 may have contributed to the persistence of the drought in southwestern China. The assessment of the associated impacts indicates that water reservoirs were severely ...
196 citations
TL;DR: A real-time global flood monitoring system (GFMS) driven by tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall has been developed and implemented using a physically based hydrologic model as mentioned in this paper.
Abstract: A new version of a real-time global flood monitoring system (GFMS) driven by Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall has been developed and implemented using a physically based hydrologic model The purpose of this paper is to evaluate the performance of this new version of the GFMS in terms of flood event detection against flood event archives to establish a baseline of performance and directions for improvement This new GFMS is quantitatively evaluated in terms of flood event detection during the TRMM era (1998‐2010) using a global retrospective simulation(3-hourlyand 1 /88spatialresolution)withtheTMPA3B42V6rainfallFourmethodswereexplored todefinefloodthresholds fromthemodelresults, includingthreepercentile-basedstatistical methodsandaLog Pearson type-III flood frequency curve method The evaluation showed the GFMS detection performance improves [increasing probability ofdetection (POD)] with longerflood durationsand largeraffected areas The impactofdams wasdetectedinthevalidationstatistics,withthepresenceofdamstendingtoresultinmorefalse alarms and greater false-alarm duration The GFMS validation statistics for flood durations 3 days and for areas without dams vary across the four methods, but center around a POD of ;070 and a false-alarm rate (FAR) of ;065 The generally positive results indicate the value of this approach for monitoring and researching floods on a global scale, but also indicate limitations and directions for improvement of such approaches These directions include improving the rainfall estimates, utilizing higher resolution in the runoffrouting model, taking into account the presence of dams, and improving the method for flood identification
185 citations
TL;DR: In this paper, the authors evaluated variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities) through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at 1/88 latitude by longitude spatial resolution.
Abstract: The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at 1/88 latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitationand/orrunoffregimes;hence,the highestvaluesare formodelsbiasedlow in runoffproduction,and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.
TL;DR: In this paper, the carbon cycle and water budget of terrestrial ecosystems were simulated using a process-based ecosystem model called Vegetation Integrative Simulator for Trace Gases (VISIT), and WUE was evaluated.
Abstract: Carbon and water cycles are intimately coupled in terrestrial ecosystems, and water-use efficiency (WUE; carbon gain at the expense of unit water loss) is one of the key parameters of ecohydrology and ecosystem management. In this study, the carbon cycle and water budget of terrestrial ecosystems were simulated using a process-based ecosystem model called Vegetation Integrative Simulator for Trace Gases (VISIT), and WUE was evaluated: WUEC, defined as gross primary production (GPP) divided by transpiration; and WUES, defined as net primary production (NPP) divided by actual evapotranspiration. Total annual WUEC and WUES of the terrestrial biosphere were estimated as 8.0 and 0.92 g C kg−1 H2O, respectively, for the period 1995–2004. Spatially, WUEC and WUES were only weakly correlated. WUES ranged from 1.5 g C kg−1 H2O in boreal and alpine ecosystems. The historical simulation implied that biospheric WUE increased from 1901 to 2005 (WUEC, +7%; WUES, +12%) ma...
TL;DR: In this article, the performance of the Weather Research and Forecasting Model (WRF) as a tool for multiscale atmospheric simulations is evaluated in real and idealized cases with multiple configurations and with resolutions ranging from the mesoscale (gridcell size ~10 km) for the real cases to local scales (gridcells size ~50 m).
Abstract: This paper assesses the performance of the Weather Research and Forecasting Model (WRF) as a tool for multiscale atmospheric simulations. Tests are performed in real and idealized cases with multiple configurations and with resolutions ranging from the mesoscale (gridcell size ~10 km) for the real cases to local scales (gridcell size ~50 m) for both real and idealized cases. All idealized simulations and the finest real-case simulations use the turbulence-resolving large-eddy simulation mode of WRF (WRF-LES). Tests in neutral conditions and with idealized forcing are first performed to assess the model’s sensitivity to grid resolutions and subgrid-scale parameterizations and to optimize the setup of the real cases. An increase in horizontal model resolution is found to be more beneficial than an increase in vertical resolution. WRF-LES is then tested, using extensive observational data, in real-world cases over complex terrain through nested simulations in which the mesoscale domains drive the LES...
TL;DR: In this paper, the authors evaluated four widely used global high-resolution satellite rainfall products [the Climate Prediction Center's morphing technique (CMORPH) product, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) near real-time product (3B42RT), the TMPA method post-real-time research version product ( 3B42), and the PERSIANN product] with a spatial resolution of 0.25° and temporal resolution of 3 h through their streamflow simulations in the Soil and Water
Abstract: This study focuses on evaluating four widely used global high-resolution satellite rainfall products [the Climate Prediction Center’s morphing technique (CMORPH) product, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) near-real-time product (3B42RT), the TMPA method post-real-time research version product (3B42), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product] with a spatial resolution of 0.25° and temporal resolution of 3 h through their streamflow simulations in the Soil and Water Assessment Tool (SWAT) hydrologic model of a 299-km2 mountainous watershed in Ethiopia. Results show significant biases in the satellite rainfall estimates. The 3B42RT and CMORPH products perform better than the 3B42 and PERSIANN. The predictive ability of each of the satellite rainfall was examined using a SWAT model calibrated in two different approaches: with rain gauge rainfall as input, and with each...
TL;DR: In this paper, a multimodel ensemble of nine large-scale hydrological models was compared to observed runoff from 426 small catchments in Europe, and it was concluded that the ensemble mean is a pragmatic and reliable estimator of spatially aggregated time series of annual low, mean, and high flows across Europe.
Abstract: Large-scale hydrological models describing the terrestrial water balance at continental and global scales are increasingly being used in earth system modeling and climate impact assessments. However, because of incomplete process understanding and limits of the forcing data, model simulations remain uncertain. To quantify this uncertainty a multimodel ensemble of nine large-scale hydrological models was compared to observed runoff from 426 small catchments in Europe. The ensemble was built within the framework of the European Union Water and Global Change (WATCH) project. The models were driven with the same atmospheric forcing data. Models were evaluated with respect to their ability to capture the interannual variability of spatially aggregated annual time series of five runoff percentiles--derived from daily time series--including annual low and high flows. Overall, the models capture the interannual variability of low, mean, and high flows well. However, errors in the mean and standard deviation, as well as differences in performance between the models, became increasingly pronounced for low runoff percentiles, reflecting the uncertainty associated with the representation of hydrological processes, such as the depletion of soil moisture stores. The large spread in model performance implies that any single model should be applied with caution as there is a great risk of biased conclusions. However, this large spread is contrasted by the good overall performance of the ensemble mean. It is concluded that the ensemble mean is a pragmatic and reliable estimator of spatially aggregated time series of annual low, mean, and high flows across Europe.
TL;DR: In situ soil moisture from 117 stations across the world and under different biome and climate conditions are used to evaluate two soil moisture products from the European Centre for Medium-Range Weather Forecasts (ECMWF) as discussed by the authors.
Abstract: In situ soil moisture from 117 stations across the world and under different biome and climate conditions are used to evaluate two soil moisture products from the European Centre for Medium-Range Weather Forecasts (ECMWF)—namely, the operational analysis and the interim reanalysis [ECMWF Re-Analysis Interim (ERA-Interim)]. ECMWF’s operational Integrated Forecasting System (IFS) is based on a continuous effort to improve the analysis and modeling systems, resulting in frequent updates (a few times a year). The ERA-Interim reanalysis is produced by a fixed IFS version (for the main component of the atmospheric model and data assimilation). It has the advantage of being consistent over the whole period from 1979 onward and by design, reanalysis products are more suitable than their operational counterparts for use in climate studies. Although the two analyses show good skills in capturing surface soil moisture variability, they tend to overestimate soil moisture, particularly for dry land. Over the 2...
TL;DR: In this article, the contributions of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates were investigated for a number of U.S. river basins.
Abstract: Land surface model experiments are used to quantify, for a number of U.S. river basins, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Snow initialization has a major impact on skill during the spring melting season. Soil moisture initialization has a smaller but still statistically significant impact during this season, and in other seasons, its contribution to skill dominates. Realistic soil moisture initialization can contribute to skill at long leads (over 6 months) for certain basins and seasons. Skill levels in all seasons are found to be related to the ratio of initial total water storage (soil water plus snow) variance to the forecast period precipitation variance, allowing estimates of the potential for skill in areas outside the verification basins.
TL;DR: In this article, the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground is investigated.
Abstract: Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the error structure of NASA’s Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar‐based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a 3-month data sample in the southern part of the United States. The primary contribution of this study is the presentation of the detailed steps required to derive a trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relies on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors are revealed and quantified including sensitivitytothe processing stepswith thereferencerainfall,comparisonsof rainfalldetectabilityandrainfallrate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall-rate estimates from other sensors on board low-earth-orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.
TL;DR: In this paper, an extensive evaluation of two global-scale high-resolution satellite rainfall products is performed using 8 yr (2003-10) of reference rainfall data derived from a network of rain gauges over Europe.
Abstract: An extensive evaluation of two global-scale high-resolution satellite rainfall products is performed using 8 yr (2003–10) of reference rainfall data derived from a network of rain gauges over Europe. The comparisons are performed at a daily temporal scale and 0.25° spatial grid resolution. The satellite rainfall techniques investigated in this study are the Tropical Rainfall Measuring Mission (TRMM) 3B42 V6 (gauge-calibrated version) and the Climate Prediction Center morphing technique (CMORPH). The intercomparison and validation of these satellite products is performed both qualitatively and quantitatively. In the qualitative part of the analysis, error maps of various validation statistics are shown, whereas the quantitative analysis provides information about the performance of the satellite products relative to the rainfall magnitude or ground elevation. Moreover, a time series analysis of certain error statistics is used to depict the temporal variations of the accuracy of the two satellite t...
TL;DR: In this article, a wavelet and fuzzy logic (WFL) combination model was developed for long lead time drought forecasting. And the strongest-frequency bands of predictors and predictand were determined from the average wavelet spectra.
Abstract: Drought forecasting is important for drought risk management. Considering the El Nino–Southern Oscillation (ENSO) variability and persistence in drought characteristics, this study developed a wavelet and fuzzy logic (WFL) combination model for long lead time drought forecasting. The idea of WFL is to separate each predictor and predictand into their frequency bands and then reconstruct the predictand series by using its predicted bands. The strongest-frequency bands of predictors and predictand were determined from the average wavelet spectra. Applying this combination model to the state of Texas, it was found that WFL had a significant improvement over the fuzzy logic model that did not use wavelet banding. Comparison with an artificial neural network (ANN) model and a coupled wavelet and ANN (WANN) model showed that WFL was more accurate for drought forecasting. Also, it should be noted that the ENSO variability is not a global precursor of drought. For this reason, prior to an application of s...
TL;DR: HyMAP as discussed by the authors is a global flow routing scheme specifically designed to bridge the gap between current state-of-the-art flow routing schemes by combining their main features and introducing new features to better capture floodplain dynamics.
Abstract: Recent advances in global flow routing schemes have shown the importance of using high-resolution topography for representing floodplain inundation dynamics more reliably. This study presents and evaluates the Hydrological Modeling and Analysis Platform (HyMAP), which is a global flow routing scheme specifically designed to bridge the gap between current state-of-the-art global flow routing schemes by combining their main features and introducing new features to better capture floodplain dynamics. The ultimate goals of HyMAP are to provide the scientific community with a novel scheme suited to the assimilation of satellite altimetry data for global water discharge forecasts and a model that can be potentially coupled with atmospheric models. In this first model evaluation, HyMAP is coupled with the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model in order to simulate the surface water dynamics in the Amazon basin. The model is evaluated over the 1986–2006 period against an ...
TL;DR: In this article, the European Centre for Medium-Range Weather Forecasts operational model run at T1279 resolution for multiple decades representing climate from the late twentieth and late twenty-first centuries is examined, focusing on variations at short time scales.
Abstract: Global simulations have been conducted with the European Centre for Medium-Range Weather Forecasts operational model run at T1279 resolution for multiple decades representing climate from the late twentieth and late twenty-first centuries. Changes in key components of the water cycle are examined, focusing on variations at short time scales. Metrics of coupling and feedbacks between soil moisture and surface fluxes and between surface fluxes and properties of the planetary boundary layer (PBL) are inspected. Features of precipitation and other water cycle trends from coupled climate model consensus projections are well simulated. Extreme 6-hourly rainfall totals become more intense over much of the globe, suggesting an increased risk for flash floods. Seasonal-scale droughts are projected to escalate over much of the subtropics and midlatitudes during summer, while tropical and winter droughts become less likely. These changes are accompanied by an increase in the responsiveness of surface evapotr...
TL;DR: In this paper, the authors evaluated the performance of the CMORPH at fine space-time resolutions (1 h and 8 km) during a 28-month period from 2004 to 2006 using a high-quality experimental rain gauge network in southern Louisiana, United States.
Abstract: This study focuses on the evaluation of the NOAA–NCEP Climate Prediction Center (CPC) morphing technique (CMORPH) satellite-based rainfall product at fine space–time resolutions (1 h and 8 km). The evaluation was conducted during a 28-month period from 2004 to 2006 using a high-quality experimental rain gauge network in southern Louisiana, United States. The dense arrangement of rain gauges allowed for multiple gauges to be located within a single CMORPH pixel and provided a relatively reliable approximation of pixel-average surface rainfall. The results suggest that the CMORPH product has high detection skills: the probability of successful detection is ~80% for surface rain rates >2 mm h−1 and probability of false detection <3%. However, significant and alarming missed-rain and false-rain volumes of 21% and 22%, respectively, were reported. The CMORPH product has a negligible bias when assessed for the entire study period. On an event scale it has significant biases that exceed 100%. The fine-re...
TL;DR: In this paper, the authors used the Weather Research and Forecasting Model (WRF) to simulate the effects of irrigation on precipitation in the Great Plains and found that a strong increase in latent heating drives near-surface cooling and an increase in humidity, which has opposing impacts on convective precipitation.
Abstract: Since World War II, the expansion of irrigation throughout the Great Plains has resulted in a significant decline in the water table of the Ogallala Aquifer, threatening its long-term sustainability. The addition of near-surface water for irrigation has previously been shown to impact the surface energy and water budgets by modifying the partitioning of latent and sensible heating. A strong increase in latent heating drives near-surface cooling and an increase in humidity, which has opposing impacts on convective precipitation. In this study, the Weather Research and Forecasting Model (WRF) was modified to simulate the effects of irrigation on precipitation. Using a satellite-derived fractional irrigation dataset, grid cells were divided into irrigated and nonirrigated segments and the near-surface soil layer within irrigated segments was held at saturation. Nine April–October periods (three drought, three normal, and three pluvial) were simulated over the Great Plains. Averaging over all simulati...
TL;DR: In this paper, a series of numerical simulations, including soil moisture sensitivity experiments, have been performed for the Indian summer monsoon season (ISM), and the results show that the premonsoonal soil moisture has a significant influence on the monsoonal precipitation, and thus confirmed that modeling of soil moisture is essential for reliable simulatio...
Abstract: Soil moisture can influence precipitation through a feedback loop with land surface evapotranspiration. A series of numerical simulations, including soil moisture sensitivity experiments, have been performed for the Indian summer monsoon season (ISM). The simulations were carried out with the nonhydrostatic regional climate model Consortium for Small-Scale Modeling (COSMO) in climate mode (COSMO-CLM), driven by lateral boundary conditions derived from the ECMWF Interim reanalysis (ERA-Interim). Positive as well as negative feedback processes through local and remote effects are shown to be important. The regional moisture budget studies have exposed that changes in precipitable water and changes in precipitation efficiency vary in importance, in time, and in space in the simulations for India. Overall, the results show that the premonsoonal soil moisture has a significant influence on the monsoonal precipitation, and thus confirmed that modeling of soil moisture is essential for reliable simulatio...
TL;DR: In this paper, a simple method was developed to forecast 3 and 6-month standardized precipitation indices (SPIs) for the prediction of meteorological drought over the contiguous United States based on precipitation seasonal forecasts from the NCEP Climate Forecast System (CFS).
Abstract: A simple method was developed to forecast 3- and 6-month standardized precipitation indices (SPIs) for the prediction of meteorological drought over the contiguous United States based on precipitation seasonal forecasts from the NCEP Climate Forecast System (CFS). Before predicting SPI, the precipitation (P) forecasts from the coarse-resolution CFS global model were bias corrected and downscaled to a regional grid of 50 km. The downscaled CFS P forecasts, out to 9 months, were appended to the P analyses to form an extended P dataset. The SPIs were calculated from this new time series. Five downscaling methods were tested: 1) bilinear interpolation; 2) a bias correction and spatial downscaling (BCSD) method based on the probability distribution functions; 3) a conditional probability estimation approach using the mean P ensemble forecasts developed by J. Schaake, 4) a Bayesian approach that bias corrects and downscales P using all ensemble forecast members, as developed by the Princeton University ...
TL;DR: In this article, the authors used Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture, multisensor remote sensing (RS) evaporative fraction (EF), and Atmospheric Infrared Sounder (AIRS) lifting condensation level (LCL) to evaluate the realism of coupling in the Global Land Data Assimilation System (GLDAS) suite of land surface models (LSMs), Princeton Global Forcing Variable Variable...
Abstract: Land–atmosphere coupling strength or the degree to which land surface anomalies influence boundary layer development—and in extreme cases, rainfall—is arguably the single most fundamental criterion for evaluating hydrological model performance. The Global Land–Atmosphere Coupling Experiment (GLACE) showed that strength of coupling and its representation can affect a model’s ability to simulate climate predictability at the seasonal time scale. And yet, the lack of sufficient observations of coupling at appropriate temporal and spatial scales has made achieving “true” coupling in models an elusive goal. This study uses Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) soil moisture (SM), multisensor remote sensing (RS) evaporative fraction (EF), and Atmospheric Infrared Sounder (AIRS) lifting condensation level (LCL) to evaluate the realism of coupling in the Global Land Data Assimilation System (GLDAS) suite of land surface models (LSMs), Princeton Global Forcing Variable ...
TL;DR: In this paper, triple collocation is used to determine the spatial and temporal error characteristics of three precipitation datasets over Europe, that is, the precipitation properties visible/near infrared (PP-VNIR) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board Meteosat Second Generation (MSG), weather radar observations fromtheEuropean integrated weatherradarsystem,and griddedraingaugeobservationsfromthe datasets of the Global Precipitation Climatology Centre (GPCC) and the
Abstract: Quantitative information on the spatial and temporal error structures in large-scale (regional or global) precipitation datasets is essential for hydrologic and climatic studies. A powerful tool to quantify error structures in large-scale datasets is triple collocation. In this paper, triple collocation is used to determine the spatial and temporal error characteristics of three precipitation datasets over Europe—that is, the precipitationproperties visible/near infrared (PP-VNIR) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board Meteosat Second Generation (MSG), weather radar observations fromtheEuropean integrated weatherradarsystem,and griddedraingaugeobservationsfromthe datasets of the Global Precipitation Climatology Centre (GPCC) and the European Climate Assessment and Dataset (ECA&D) project. For these datasets the spatial and temporal error characteristics are evaluated and their performance is discussed. Finally, weather radar and PP-VNIR retrievals are used to evaluate the diurnal cycles of precipitation occurrence and intensity during daylight hours for different European climate regions. The results suggest that the triple collocation method provides realistic error estimates. The spatial and temporal error structures agree with the findings of earlier studies and reveal the strengths and weaknesses of the datasets, such as inhomogeneity of weather radar practices across Europe, the effect of sampling density in the gridded rain gauge dataset, and the sensitivity to retrieval assumptions in the PP-VNIR dataset. This study can help us in developing satisfactory strategies for combining various precipitation datasets—for example, for improved monitoring of diurnal variations or for detecting temporal trends in precipitation.
TL;DR: In this article, the authors used satellite and gridded meteorological data to estimate evaporation (E) from land surfaces using simple diagnostic models, such as a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation.
Abstract: Satellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation an...
TL;DR: This paper presented the climate change impact on mean annual runoff across continental Australia estimated using the Budyko and Fu equations informed by projections from 15 global climate models and compared the estimates with those from extensive hydrological modeling.
Abstract: This paper presents the climate change impact on mean annual runoff across continental Australia estimated using the Budyko and Fu equations informed by projections from 15 global climate models and compares the estimates with those from extensive hydrological modeling. The results show runoff decline in southeast and far southwest Australia, but elsewhere across the continent there is no clear agreement between the global climate models in the direction of future precipitation and runoff change. Averaged across large regions, the estimates from the Budyko and Fu equations are reasonably similar to those from the hydrological models. The simplicity of the Budyko equation, the similarity in the results, and the large uncertainty in global climate model projections of future precipitation suggest that the Budyko equation is suitable for estimating climate change impact on mean annual runoff across large regions. The Budyko equation is particularly useful for data-limited regions, for studies where o...