This study analyzes the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) precipitation products for assessment of meteorological drought. Two versions of the ...TMPA research datasets (3B42V6 and 3B42V7) and one real-time dataset (3B42RTV7) are considered. The TMPA datasets are evaluated against a merged precipitation product which is estimated by merging four non-TMPA global satellite-gauge based datasets (non-TMPA merged). Comparisons are made over global land areas between 50° S and 50° N at monthly and 0.25° spatial resolution from 2000 to 2009 (ten years). All the TMPA precipitation datasets show similar spatial patterns; however quantitatively they disagree considerably, especially over tropical regions. 3B42V7 and 3B42RTV7 show the lowest and highest differences with the non-TMPA merged product, respectively. The Standardized Precipitation Index (SPI) at various time scales (1month to 12months) is calculated for each dataset for detecting drought events, with drought defined as when monthly SPI<−1.0 and severe drought when monthly SPI<−1.5. The SPI results complement the spatial patterns found in the precipitation statistics. The non-TMPA merged and the 3B42V7 precipitation datasets simultaneously identify months under drought more frequently than any other pair (i.e., non-TMPA merged — 3B42V6 and non-TMPA merged — 3B42RTV7) of precipitation datasets. We consider four severe drought events: (a) 2007 southeastern US drought, (b) 2003 western European heat wave and drought, (c) 2005 Amazon drought and (d) 2006 Kenyan drought as case studies. All precipitation products are able to identify the drought events in time and space except a few cases. The spatial correlation of drought area is the highest (>0.8) for the 2007 southeastern US drought and the lowest (<0.62) for the 2006 Kenyan drought. For severe drought (SPI<−1.5), all three TMPA products and the non-TMPA merged product show more than 50% area under severe drought for the four drought events with few exceptions.
Our results show that major differences among datasets are found over many sparse gauge density regions which suggests that the skill of the datasets primarily depends on the differential performance of the respective processing algorithms in different geographic and climatic regions, density of the underlying rain-gauge station networks and the quality of the input data used from non-gauge data sources. Even though the 3B42V7 product performs the best, the 3B42V6 product also performs reasonably well during our study period and domain. The 3B42RTV7 real-time data perform the worst and are not comparable with the two TMPA research products, due to lack of corrections from gauge observations. Therefore, caution should be applied when using this product for real-time monitoring of the drought conditions. Our evaluation of the TMPA research products indicates that they can provide useful information for drought monitoring and as input to hydrological modeling applications for assessment of land surface conditions.
•TMPA rainfall data are evaluated against non-TMPA data for detecting droughts.•Monthly Standardized Precipitation Index (SPI) is used for detecting drought events.•Differential performance of the processing algorithms controls the skill of datasets.•Both TMPA research products (3B42V7 and 3B42V6) perform reasonably well.•Caution should be applied when using real-time product (3B42RTV7) for drought study.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Near surface soil moisture is being estimated from space-borne passive microwave observations through inverting a physically-based radiative transfer model (RTM), the land surface microwave emission ...model (LSMEM) at Princeton University for the past several years. The existing retrieval scheme utilizes only the horizontal (H) polarization measurement from a single channel (10.65GHz). This physically-based approach requires a relatively large number of parameters, and it generally suffers from large biases/errors due to the difficulty in determining the correct parameters. This study characterizes these errors in order to improve the retrieval performance. Through model sensitivity analysis, this study finds that a dual polarization approach (using both horizontal and vertical polarizations) is needed to infer the correct vegetation opacity and correct polarization mixing measured by the space-borne sensor. Revisions are then made to the LSMEM formulations and soil moisture retrieval algorithm by 1) combining two vegetation parameters and one roughness parameter into one effective vegetation optical depth (VOD) value; and 2) providing an additional model equation that estimates the effective VOD from both polarizations and an initial guess of soil moisture value. The new retrieval algorithm is implemented to produce a daily 0.25° gridded soil moisture dataset based on observations from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E). Validations are performed globally against land surface model simulations and at local/point scale against in-situ data within the continental United States. The new retrievals are shown to have good and robust performance over most parts of the world in terms of reproducing the spatial and temporal dynamics of soil moisture.
•Global AMSR-E based soil moisture retrieval•Improved land surface microwave emission model (LSMEM) based retrieval algorithm•Dual polarization in 10.65GHZ channel•Simultaneously estimated vegetation optical depth (VOD)•Validation against ground measurements and land surface model (LSM)
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation ...techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984–2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Soil Moisture and Ocean Salinity (SMOS) satellite has opened the era of soil moisture products from passive L-band observations. In this paper, validation of SMOS products over continental U.S. ...is done by using the Soil Climate Analysis Network (SCAN)/SNOwpack TELemetry (SNOTEL) soil moisture monitoring stations. The SMOS operational products and the SMOS reprocessing products are both used and compared over year 2010. First, a direct node-to-site comparison is performed by taking advantage of the oversampling of the SMOS product grid. The comparison is performed over several adjacent nodes to site, and several representative couples of site-node are identified. The impact of forest fraction is shown through the analysis of different cases across the U.S. Also, the impact of water fraction is shown through two examples in Florida and in Utah close to Great Salt Lake. A radiometric aggregation approach based on the antenna footprint and spatial description is used. A global comparison of the SCAN/SNOTEL versus SMOS is made. Statistics show an underestimation of the soil moisture from SMOS compared to the SCAN/SNOTEL local measurements. The results suggest that SMOS meets the mission requirement of 0.04 m 3 /m 3 over specific nominal cases, but differences are observed over many sites and need to be addressed.
Recent retrievals of multiple satellite products for each component of the terrestrial water cycle provide an opportunity to estimate the water budget globally. In this study, we estimate the water ...budget from satellite remote sensing over ten global river basins for 2003–2006. We use several satellite and non-satellite precipitation (
P) and evapo-transpiration (
ET) products in this study. The satellite precipitation products are the GPCP, TRMM, CMORPH and PERSIANN. For
ET, we use four products generated from three retrieval models (Penman–Monteith (PM), Priestley–Taylor (PT) and the Surface Energy Balance System (SEBS)) with data inputs from the Earth Observing System (EOS) or the International Satellite Cloud Climatology Project (ISCCP) products. GPCP precipitation and PM (ISCCP)
ET have less bias and errors over most of the river basins. To estimate the total water budget from satellite data for each basin, we generate merged products for
P and
ET by combining the four
P and four
ET products using weighted values based on their errors with respect to non-satellite merged product. The water storage change component is taken from GRACE satellite data, which are used directly with a single pre-specified error value. In the absence of satellite retrievals of river discharge, we use in-situ gauge measurements. Closure of the water budget over the river basins from the combined satellite and in-situ discharge products is not achievable with errors of the order of 5–25% of mean annual precipitation. A constrained ensemble Kalman filter is used to close the water budget and provide a constrained best-estimate of the water budget. The non-closure error from each water budget component is estimated and it is found that the merged satellite precipitation product carries most of the non-closure error.
► Water budget is estimated from satellite only products over ten river basins. ► Water budget non-closure error is the greatest over the Amazon. ► A water budget constraint scheme is applied to close the water budget. ► The precipitation products provide the largest source of the non-closure error. ► Impact of bias correction depends on the skill of the target estimates.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
► In this study we analyze the performance of a 3-D EnKF technique. ► Both 1-D and 3-D algorithms improve model forecast soil moisture over our study area. ► Surface moisture assimilation impacts ...deep layer moisture and water cycle variables. ► EnKF speeds up the state balancing relative to the open loop integration.
A three dimensional Ensemble Kalman filter (3-D EnKF) and a one dimensional EnKF (1-D EnKF) are used in this study to assimilate Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) coarse grid (25km) soil moisture retrievals into the Noah land surface model for fine-scale (1km) surface soil moisture estimation over the Little River Experimental Watershed (LREW), Georgia, USA. For the 1-D EnKF integration, the satellite observations are a priori partitioned to the model fine scale resolution, whereas in the 3-D EnKF integration, the original coarse grid satellite observations are directly used and downscaling is accomplished within the 3-D EnKF update step. In both cases, a first order a priori forecast bias correction is applied. Validation against in situ observations shows that both EnKF algorithms improve the soil moisture estimates, but the 3-D EnKF algorithm better preserves the spatial coherence. It is illustrated how surface soil moisture assimilation affects the deeper layer soil moisture and other water budget variables. Through sensitivity experiments, it is shown that data assimilation accelerates the moisture redistribution compared to the model integrations without assimilation, as surface soil moisture updates are effectively propagated over the entire profile. In the absence of data assimilation, the atmospheric conditions (especially the ratio of evapotranspiration to precipitation) control the model state balancing.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Magnetic gears, being contactless, offer distinct advantages over mechanical gears. Transient simulations are required for the evaluation of dynamic performance, but the complex geometry of magnetic ...gears makes them computationally intensive with high simulation time. This paper proposes a method to perform a time-domain transient analysis on a coaxial magnetic gear. The proposed method is derived by an appropriate and timely modification of specific terms in the magnetostatic solution, to result in a computationally efficient transient simulation. The proposed method also doesn’t necessitate individual magnetostatic solutions for different time instances. The transient speed and torque performance of a coaxial magnetic gear can be predicted much faster with the proposed analytical approach (up-to 60 times faster for the configuration used in this article) compared to a finite element method (FEM)-based simulation. Accuracy of the proposed method is verified by comparing the results with those obtained from FEM simulations (COMSOL).
Background and Aims: Colloids modify the vascular endothelium and prevent contact activation of various substances. Pre-administration of colloids may prevent contact activation of vascular ...endothelium by propofol. The objective of this study was to evaluate the effect of 6% hydroxyethyl starch (HES) 130/0.4 pre-administration on propofol injection pain. Methods: Adult patients of the American Society of Anesthesiologists physical status I and II patients, 18-65 years old, of either gender and undergoing elective surgery were randomised into two groups. 100 mL bolus of HES or 0.9% normal saline (NS) was administered over three to five minutes through an 18 G cannula placed in the hand or forearm vein, followed by induction with 1% propofol premixed with 2% lidocaine. Pain during propofol injection was assessed every 10 seconds before the loss of verbal contact as 0- no pain; 1- mild pain evident only on questioning after 10 seconds without any obvious discomfort; 2-moderate pain self-reported by patients within 10 seconds with some discomfort; and 3- severe pain accompanied by withdrawing of hand, and behavioural signs. Results: 126 patients completed the study. Overall incidence of pain was significantly higher in the NS group vs HES group (53% vs 28%; P = 0.004; relative risk 1.54, 95% confidence interval 1.13-2.09). Incidence of severe (8% vs 0%) and moderate pain (16% vs 5%) was higher in the NS group, while the incidence of mild pain was comparable (29% vs 23%; NS vs HES). A significant difference was seen in the severity of pain between the groups (P = 0.002). Conclusion: Pre-administration of 100 mL bolus of 6% HES 130/0.4 significantly reduced propofol injection pain.
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