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Sample records for estimated local precipitation

  1. A test for Improvement of high resolution Quantitative Precipitation Estimation for localized heavy precipitation events

    Science.gov (United States)

    Lee, Jung-Hoon; Roh, Joon-Woo; Park, Jeong-Gyun

    2017-04-01

    Accurate estimation of precipitation is one of the most difficult and significant tasks in the area of weather diagnostic and forecasting. In the Korean Peninsula, heavy precipitations are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. In addition to, various geographical and topographical elements make production of temporal and spatial distribution of precipitation is very complicated. Especially, localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances. In weather radar data with high temporal and spatial resolution, accurate estimation of rain rate from radar reflectivity data is too difficult. Z-R relationship (Marshal and Palmer 1948) have adapted representatively. In addition to, several methods such as support vector machine (SVM), neural network, Fuzzy logic, Kriging were utilized in order to improve the accuracy of rain rate. These methods show the different quantitative precipitation estimation (QPE) and the performances of accuracy are different for heavy precipitation cases. In this study, in order to improve the accuracy of QPE for localized heavy precipitation, ensemble method for Z-R relationship and various techniques was tested. This QPE ensemble method was developed by a concept based on utilizing each advantage of precipitation calibration methods. The ensemble members were produced for a combination of different Z-R coefficient and calibration method.

  2. Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

    KAUST Repository

    Camilo, Daniela Castro

    2017-10-02

    In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

  3. Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

    KAUST Repository

    Camilo, Daniela Castro; Huser, Raphaë l

    2017-01-01

    In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

  4. Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

    Science.gov (United States)

    Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

    2016-01-01

    Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

  5. Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation

    International Nuclear Information System (INIS)

    Zorita, E.; Hughes, J.P.

    1993-01-01

    Two statistical approaches for linking large-scale atmospheric circulation patterns and daily local rainfall are described and applied to several GCM (general circulation model) climate simulations. The ultimate objective is to simulate local precipitation associated with alternative climates. The index stations are located near the West and East North American coasts. The first method is based on CART analysis (Classification and Regression trees). It finds the classification of observed daily SLR (sea level pressure) fields in weather types that are most strongly associated with the presence/absence of rainfall in a set of index stations. The best results were obtained for winter rainfall for the West Coast, where a set of physically reasonable weather types could be identified, whereas for the East Coast the rainfall process seemed to be spatially less coherent. The GCM simulations were validated against observations in terms of probability of occurrence and survival time of these weather states. Some discrepancies werefound but there was no systematic bias, indicating that this behavior depends on the particular dynamics of each model. This classification method was then used for the generation of daily rainfall time series from the daily SLP fields from historical observation and from the GCM simulations. Whereas the mean rainfall and probability distributions were rather well replicated, the simulated dry periods were in all cases shorter than in the rainfall observations. The second rainfall generator is based on the analog method and uses information on the evolution of the SLP field in several previous days. It was found to perform reasonably well, although some downward bias in the simulated rainfall persistence was still present. Rainfall changes in a 2xCO 2 climate were investigated by applying both methods to the output of a greenhouse-gas experiment. The simulated precipitation changes were small. (orig.)

  6. Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

    Directory of Open Access Journals (Sweden)

    Basile Pauthier

    2016-01-01

    Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

  7. Satellite precipitation estimation over the Tibetan Plateau

    Science.gov (United States)

    Porcu, F.; Gjoka, U.

    2012-04-01

    Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

  8. Estimating Tropical Cyclone Precipitation from Station Observations

    Institute of Scientific and Technical Information of China (English)

    REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing

    2007-01-01

    In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.

  9. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  10. Augmenting Satellite Precipitation Estimation with Lightning Information

    Energy Technology Data Exchange (ETDEWEB)

    Mahrooghy, Majid [Mississippi State University (MSU); Anantharaj, Valentine G [ORNL; Younan, Nicolas H. [Mississippi State University (MSU); Petersen, Walter A. [NASA Marshall Space Flight Center, Huntsville, AL; Hsu, Kuo-Lin [University of California, Irvine; Behrangi, Ali [Jet Propulsion Laboratory, Pasadena, CA; Aanstoos, James [Mississippi State University (MSU)

    2013-01-01

    We have used lightning information to augment the Precipitation Estimation from Remotely Sensed Imagery using an Artificial Neural Network - Cloud Classification System (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from GOES-12 infrared data, into either electrified (EL) or non-electrified (NEL) patches. A set of features is extracted separately for the EL and NEL cloud patches. The features for the EL cloud patches include new features based on the lightning information. The cloud patches are classified and clustered using self-organizing maps (SOM). Then brightness temperature and rain rate (T-R) relationships are derived for the different clusters. Rain rates are estimated for the cloud patches based on their representative T-R relationship. The Equitable Threat Score (ETS) for daily precipitation estimates is improved by almost 12% for the winter season. In the summer, no significant improvements in ETS are noted.

  11. Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Yuxiang He

    2018-01-01

    Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

  12. Connecting Satellite-Based Precipitation Estimates to Users

    Science.gov (United States)

    Huffman, George J.; Bolvin, David T.; Nelkin, Eric

    2018-01-01

    Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

  13. Opportunities and challenges for evaluating precipitation estimates during GPM mission

    Energy Technology Data Exchange (ETDEWEB)

    Amitai, E. [George Mason Univ. and NASA Goddard Space Flight Center, Greenbelt, MD (United States); NASA Goddard Space Flight Center, Greenbelt, MD (United States); Llort, X.; Sempere-Torres, D. [GRAHI/Univ. Politecnica de Catalunya, Barcelona (Spain)

    2006-10-15

    Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the tropical rainfall measuring mission (TRMM) era to the global precipitation measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides (1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; (2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and (3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions. (orig.)

  14. Comparing NEXRAD Operational Precipitation Estimates and Raingage Observations of Intense Precipitation in the Missouri River Basin.

    Science.gov (United States)

    Young, C. B.

    2002-05-01

    Accurate observation of precipitation is critical to the study and modeling of land surface hydrologic processes. NEXRAD radar-based precipitation estimates are increasingly used in field experiments, hydrologic modeling, and water and energy budget studies due to their high spatial and temporal resolution, national coverage, and perceived accuracy. Extensive development and testing of NEXRAD precipitation algorithms have been carried out in the Southern Plains. Previous studies (Young et al. 2000, Young et al. 1999, Smith et al. 1996) indicate that NEXRAD operational products tend to underestimate precipitation at light rain rates. This study investigates the performance of NEXRAD precipitation estimates of high-intensity rainfall, focusing on flood-producing storms in the Missouri River Basin. NEXRAD estimates for these storms are compared with data from multiple raingage networks, including NWS recording and non-recording gages and ALERT raingage data for the Kansas City metropolitan area. Analyses include comparisons of gage and radar data at a wide range of temporal and spatial scales. Particular attention is paid to the October 4th, 1998, storm that produced severe flooding in Kansas City. NOTE: The phrase `NEXRAD operational products' in this abstract includes precipitation estimates generated using the Stage III and P1 algorithms. Both of these products estimate hourly accumulations on the (approximately) 4 km HRAP grid.

  15. Sources of uncertainty in future changes in local precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Rowell, David P. [Met Office Hadley Centre, Exeter (United Kingdom)

    2012-10-15

    This study considers the large uncertainty in projected changes in local precipitation. It aims to map, and begin to understand, the relative roles of uncertain modelling and natural variability, using 20-year mean data from four perturbed physics or multi-model ensembles. The largest - 280-member - ensemble illustrates a rich pattern in the varying contribution of modelling uncertainty, with similar features found using a CMIP3 ensemble (despite its limited sample size, which restricts it value in this context). The contribution of modelling uncertainty to the total uncertainty in local precipitation change is found to be highest in the deep tropics, particularly over South America, Africa, the east and central Pacific, and the Atlantic. In the moist maritime tropics, the highly uncertain modelling of sea-surface temperature changes is transmitted to a large uncertain modelling of local rainfall changes. Over tropical land and summer mid-latitude continents (and to a lesser extent, the tropical oceans), uncertain modelling of atmospheric processes, land surface processes and the terrestrial carbon cycle all appear to play an additional substantial role in driving the uncertainty of local rainfall changes. In polar regions, inter-model variability of anomalous sea ice drives an uncertain precipitation response, particularly in winter. In all these regions, there is therefore the potential to reduce the uncertainty of local precipitation changes through targeted model improvements and observational constraints. In contrast, over much of the arid subtropical and mid-latitude oceans, over Australia, and over the Sahara in winter, internal atmospheric variability dominates the uncertainty in projected precipitation changes. Here, model improvements and observational constraints will have little impact on the uncertainty of time means shorter than at least 20 years. Last, a supplementary application of the metric developed here is that it can be interpreted as a measure

  16. Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

    Science.gov (United States)

    Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

    2018-01-01

    A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

  17. Improving precipitation estimates over the western United States using GOES-R precipitation data

    Science.gov (United States)

    Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

    2017-12-01

    Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

  18. Estimation of precipitable water from surface dew point temperature

    International Nuclear Information System (INIS)

    Abdel Wahab, M.; Sharif, T.A.

    1991-09-01

    The Reitan (1963) regression equation which is of the form lnw=a+bT d has been examined and tested to estimate precipitable water content from surface dew point temperature at different locations. The study confirms that the slope of this equation (b) remains constant at the value of .0681 deg. C., while the intercept (a) changes rapidly with the latitude. The use of the variable intercept can improve the estimated result by 2%. (author). 6 refs, 4 figs, 3 tabs

  19. Assessment of satellite-based precipitation estimates over Paraguay

    Science.gov (United States)

    Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

    2018-04-01

    Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

  20. Pareto-Optimal Estimates of California Precipitation Change

    Science.gov (United States)

    Langenbrunner, Baird; Neelin, J. David

    2017-12-01

    In seeking constraints on global climate model projections under global warming, one commonly finds that different subsets of models perform well under different objective functions, and these trade-offs are difficult to weigh. Here a multiobjective approach is applied to a large set of subensembles generated from the Climate Model Intercomparison Project phase 5 ensemble. We use observations and reanalyses to constrain tropical Pacific sea surface temperatures, upper level zonal winds in the midlatitude Pacific, and California precipitation. An evolutionary algorithm identifies the set of Pareto-optimal subensembles across these three measures, and these subensembles are used to constrain end-of-century California wet season precipitation change. This methodology narrows the range of projections throughout California, increasing confidence in estimates of positive mean precipitation change. Finally, we show how this technique complements and generalizes emergent constraint approaches for restricting uncertainty in end-of-century projections within multimodel ensembles using multiple criteria for observational constraints.

  1. Pareto-optimal estimates that constrain mean California precipitation change

    Science.gov (United States)

    Langenbrunner, B.; Neelin, J. D.

    2017-12-01

    Global climate model (GCM) projections of greenhouse gas-induced precipitation change can exhibit notable uncertainty at the regional scale, particularly in regions where the mean change is small compared to internal variability. This is especially true for California, which is located in a transition zone between robust precipitation increases to the north and decreases to the south, and where GCMs from the Climate Model Intercomparison Project phase 5 (CMIP5) archive show no consensus on mean change (in either magnitude or sign) across the central and southern parts of the state. With the goal of constraining this uncertainty, we apply a multiobjective approach to a large set of subensembles (subsets of models from the full CMIP5 ensemble). These constraints are based on subensemble performance in three fields important to California precipitation: tropical Pacific sea surface temperatures, upper-level zonal winds in the midlatitude Pacific, and precipitation over the state. An evolutionary algorithm is used to sort through and identify the set of Pareto-optimal subensembles across these three measures in the historical climatology, and we use this information to constrain end-of-century California wet season precipitation change. This technique narrows the range of projections throughout the state and increases confidence in estimates of positive mean change. Furthermore, these methods complement and generalize emergent constraint approaches that aim to restrict uncertainty in end-of-century projections, and they have applications to even broader aspects of uncertainty quantification, including parameter sensitivity and model calibration.

  2. The nonstationary impact of local temperature changes and ENSO on extreme precipitation at the global scale

    Science.gov (United States)

    Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun

    2017-12-01

    The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.

  3. Estimation of the characteristic energy of electron precipitation

    Directory of Open Access Journals (Sweden)

    C. F. del Pozo

    2002-09-01

    Full Text Available Data from simultaneous observations (on 13 February 1996, 9 November 1998, and 12 February 1999 with the IRIS, DASI and EISCAT systems are employed in the study of the energy distribution of the electron precipitation during substorm activity. The estimation of the characteristic energy of the electron precipitation over the common field of view of IRIS and DASI is discussed. In particular, we look closely at the physical basis of the correspondence between the characteristic energy, the flux-averaged energy, as defined below, and the logarithm of the ratio of the green-light intensity to the square of absorption. This study expands and corrects results presented in the paper by Kosch et al. (2001. It is noticed, moreover, that acceleration associated with diffusion processes in the magnetosphere long before precipitation may be controlling the shape of the energy spectrum. We propose and test a "mixed" distribution for the energy-flux spectrum, exponential at the lower energies and Maxwellian or modified power-law at the higher energies, with a threshold energy separating these two regimes. The energy-flux spectrum at Tromsø, in the 1–320 keV range, is derived from EISCAT electron density profiles in the 70–140 km altitude range and is applied in the "calibration" of the optical intensity and absorption distributions, in order to extrapolate the flux and characteristic energy maps.Key words. Ionosphere (auroral ionosphere; particle precipitation; particle acceleration

  4. Estimation of the characteristic energy of electron precipitation

    Directory of Open Access Journals (Sweden)

    C. F. del Pozo

    Full Text Available Data from simultaneous observations (on 13 February 1996, 9 November 1998, and 12 February 1999 with the IRIS, DASI and EISCAT systems are employed in the study of the energy distribution of the electron precipitation during substorm activity. The estimation of the characteristic energy of the electron precipitation over the common field of view of IRIS and DASI is discussed. In particular, we look closely at the physical basis of the correspondence between the characteristic energy, the flux-averaged energy, as defined below, and the logarithm of the ratio of the green-light intensity to the square of absorption. This study expands and corrects results presented in the paper by Kosch et al. (2001. It is noticed, moreover, that acceleration associated with diffusion processes in the magnetosphere long before precipitation may be controlling the shape of the energy spectrum. We propose and test a "mixed" distribution for the energy-flux spectrum, exponential at the lower energies and Maxwellian or modified power-law at the higher energies, with a threshold energy separating these two regimes. The energy-flux spectrum at Tromsø, in the 1–320 keV range, is derived from EISCAT electron density profiles in the 70–140 km altitude range and is applied in the "calibration" of the optical intensity and absorption distributions, in order to extrapolate the flux and characteristic energy maps.

    Key words. Ionosphere (auroral ionosphere; particle precipitation; particle acceleration

  5. Uncertainty Estimation using Bootstrapped Kriging Predictions for Precipitation Isoscapes

    Science.gov (United States)

    Ma, C.; Bowen, G. J.; Vander Zanden, H.; Wunder, M.

    2017-12-01

    Isoscapes are spatial models representing the distribution of stable isotope values across landscapes. Isoscapes of hydrogen and oxygen in precipitation are now widely used in a diversity of fields, including geology, biology, hydrology, and atmospheric science. To generate isoscapes, geostatistical methods are typically applied to extend predictions from limited data measurements. Kriging is a popular method in isoscape modeling, but quantifying the uncertainty associated with the resulting isoscapes is challenging. Applications that use precipitation isoscapes to determine sample origin require estimation of uncertainty. Here we present a simple bootstrap method (SBM) to estimate the mean and uncertainty of the krigged isoscape and compare these results with a generalized bootstrap method (GBM) applied in previous studies. We used hydrogen isotopic data from IsoMAP to explore these two approaches for estimating uncertainty. We conducted 10 simulations for each bootstrap method and found that SBM results in more kriging predictions (9/10) compared to GBM (4/10). Prediction from SBM was closer to the original prediction generated without bootstrapping and had less variance than GBM. SBM was tested on different datasets from IsoMAP with different numbers of observation sites. We determined that predictions from the datasets with fewer than 40 observation sites using SBM were more variable than the original prediction. The approaches we used for estimating uncertainty will be compiled in an R package that is under development. We expect that these robust estimates of precipitation isoscape uncertainty can be applied in diagnosing the origin of samples ranging from various type of waters to migratory animals, food products, and humans.

  6. The estimation of probable maximum precipitation: the case of Catalonia.

    Science.gov (United States)

    Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel

    2008-12-01

    A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.

  7. GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2011-01-01

    Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

  8. Improving Frozen Precipitation Density Estimation in Land Surface Modeling

    Science.gov (United States)

    Sparrow, K.; Fall, G. M.

    2017-12-01

    The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in

  9. GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

    Science.gov (United States)

    Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory

    2013-01-01

    Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

  10. Antecedent precipitation index determined from CST estimates of rainfall

    Science.gov (United States)

    Martin, David W.

    1992-01-01

    This paper deals with an experimental calculation of a satellite-based antecedent precipitation index (API). The index is also derived from daily rain images produced from infrared images using an improved version of GSFC's Convective/Stratiform Technique (CST). API is a measure of soil moisture, and is based on the notion that the amount of moisture in the soil at a given time is related to precipitation at earlier times. Four different CST programs as well as the Geostationary Operational Enviroment Satellite (GOES) Precipitation Index developed by Arkin in 1979 are compared to experimental results, for the Mississippi Valley during the month of July. Rain images are shown for the best CST code and the ARK program. Comparisons are made as to the accuracy and detail of the results for the two codes. This project demonstrates the feasibility of running the CST on a synoptic scale. The Mississippi Valley case is well suited for testing the feasibility of monitoring soil moisture by means of CST. Preliminary comparisons of CST and ARK indicate significant differences in estimates of rain amount and distribution.

  11. Radar-derived quantitative precipitation estimation in complex terrain over the eastern Tibetan Plateau

    Science.gov (United States)

    Gou, Yabin; Ma, Yingzhao; Chen, Haonan; Wen, Yixin

    2018-05-01

    Quantitative precipitation estimation (QPE) is one of the important applications of weather radars. However, in complex terrain such as Tibetan Plateau, it is a challenging task to obtain an optimal Z-R relation due to the complex spatial and temporal variability in precipitation microphysics. This paper develops two radar QPE schemes respectively based on Reflectivity Threshold (RT) and Storm Cell Identification and Tracking (SCIT) algorithms using observations from 11 Doppler weather radars and 3264 rain gauges over the Eastern Tibetan Plateau (ETP). These two QPE methodologies are evaluated extensively using four precipitation events that are characterized by different meteorological features. Precipitation characteristics of independent storm cells associated with these four events, as well as the storm-scale differences, are investigated using short-term vertical profile of reflectivity (VPR) clusters. Evaluation results show that the SCIT-based rainfall approach performs better than the simple RT-based method for all precipitation events in terms of score comparison using validation gauge measurements as references. It is also found that the SCIT-based approach can effectively mitigate the local error of radar QPE and represent the precipitation spatiotemporal variability better than the RT-based scheme.

  12. Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

    Science.gov (United States)

    Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

    2017-12-01

    Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

  13. Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes

    Science.gov (United States)

    Pegram, G. G. S.; Bardossy, A.

    2016-12-01

    Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and

  14. Low-latitude particle precipitation and associated local magnetic disturbances

    International Nuclear Information System (INIS)

    Rassoul, H.K.; Rohrbaugh, R.P.; Tinsley, B.A.

    1992-01-01

    The time variations of optical emissions during low-latitude auroral events have been shown to correlate well with those of magnetograms in the region where the aurorae are observed. Two events not previously reported are analyzed and are shown to confirm the nature of the correlations found for two earlier events. The maximum optical emissions at mid-latitudes occur in concert with the maximum positive (northward) excursions in the H trace and with rapid fluctuations in the D trace of nearby magnetograms. The fluctuation in ΔD is usually from the east (positive) to the west (negative) in the vicinity of the ΔH perturbation. The positive excursions in H at low-latitude observatories at the time of the maximum optical emissions are associated with negative H excursions at high latitude observatories in the same longitude sector. The source of the particles has been inferred to be the ring current, with precipitation occurring when the |Dst| index is large at the time of the large short term excursions in the local magnetic field. This result is consistent with the funding of Voss and Smith (1979), derived from a series of rocket measurements of precipitating heavy particles, that the flux correlates better with the product of |Dst| and the exponential of K p than with either alone. In the present case it is shown that the product of |Dst| and the amplitude of the short term excursions in the horizontal component in local magnetograms has better time resolution and better correlation with the observed emission rates than the index using K p

  15. Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR upon TRMM Precipitation Radar (PR in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

    Directory of Open Access Journals (Sweden)

    Jinyu Gao

    2017-11-01

    Full Text Available Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR, was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM. This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku and single frequency (Ku methods performed similarly. In both inner (the central 25 beams and outer swaths (1–12 beams and 38–49 beams of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02% of stratiform (convective precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne

  16. Site Specific Probable Maximum Precipitation Estimates and Professional Judgement

    Science.gov (United States)

    Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.

    2015-12-01

    State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially

  17. Global Precipitation Measurement. Report 7; Bridging from TRMM to GPM to 3-Hourly Precipitation Estimates

    Science.gov (United States)

    Shepherd, J. Marshall; Smith, Eric A.; Adams, W. James (Editor)

    2002-01-01

    Historically, multi-decadal measurements of precipitation from surface-based rain gauges have been available over continents. However oceans remained largely unobserved prior to the beginning of the satellite era. Only after the launch of the first Defense Meteorological Satellite Program (DMSP) satellite in 1987 carrying a well-calibrated and multi-frequency passive microwave radiometer called Special Sensor Microwave/Imager (SSM/I) have systematic and accurate precipitation measurements over oceans become available on a regular basis; see Smith et al. (1994, 1998). Recognizing that satellite-based data are a foremost tool for measuring precipitation, NASA initiated a new research program to measure precipitation from space under its Mission to Planet Earth program in the 1990s. As a result, the Tropical Rainfall Measuring Mission (TRMM), a collaborative mission between NASA and NASDA, was launched in 1997 to measure tropical and subtropical rain. See Simpson et al. (1996) and Kummerow et al. (2000). Motivated by the success of TRMM, and recognizing the need for more comprehensive global precipitation measurements, NASA and NASDA have now planned a new mission, i.e., the Global Precipitation Measurement (GPM) mission. The primary goal of GPM is to extend TRMM's rainfall time series while making substantial improvements in precipitation observations, specifically in terms of measurement accuracy, sampling frequency, Earth coverage, and spatial resolution. This report addresses four fundamental questions related to the transition from current to future global precipitation observations as denoted by the TRMM and GPM eras, respectively.

  18. Enhancement of regional wet deposition estimates based on modeled precipitation inputs

    Science.gov (United States)

    James A. Lynch; Jeffery W. Grimm; Edward S. Corbett

    1996-01-01

    Application of a variety of two-dimensional interpolation algorithms to precipitation chemistry data gathered at scattered monitoring sites for the purpose of estimating precipitation- born ionic inputs for specific points or regions have failed to produce accurate estimates. The accuracy of these estimates is particularly poor in areas of high topographic relief....

  19. Comparison of direct and precipitation methods for the estimation of ...

    African Journals Online (AJOL)

    Background: There is increase in use of direct assays for analysis of high and low density lipoprotein cholesterol by clinical laboratories despite differences in performance characteristics with conventional precipitation methods. Calculation of low density lipoprotein cholesterol in precipitation methods is based on total ...

  20. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling

    Directory of Open Access Journals (Sweden)

    Hyojin Lee

    2015-01-01

    Full Text Available Precipitation is the main factor that drives hydrologic modeling; therefore, missing precipitation data can cause malfunctions in hydrologic modeling. Although interpolation of missing precipitation data is recognized as an important research topic, only a few methods follow a regression approach. In this study, daily precipitation data were interpolated using five different kernel functions, namely, Epanechnikov, Quartic, Triweight, Tricube, and Cosine, to estimate missing precipitation data. This study also presents an assessment that compares estimation of missing precipitation data through Kth nearest neighborhood (KNN regression to the five different kernel estimations and their performance in simulating streamflow using the Soil Water Assessment Tool (SWAT hydrologic model. The results show that the kernel approaches provide higher quality interpolation of precipitation data compared with the KNN regression approach, in terms of both statistical data assessment and hydrologic modeling performance.

  1. Where Does the Irrigation Water Go? An Estimate of the Contribution of Irrigation to Precipitation Using MERRA

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Wisser, Dominik; Bosilovich, Michael G.; Mocko, David M.

    2013-01-01

    Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.

  2. Component Analysis of Errors on PERSIANN Precipitation Estimates over Urmia Lake Basin, IRAN

    Science.gov (United States)

    Ghajarnia, N.; Daneshkar Arasteh, P.; Liaghat, A. M.; Araghinejad, S.

    2016-12-01

    In this study, PERSIANN daily dataset is evaluated from 2000 to 2011 in 69 pixels over Urmia Lake basin in northwest of Iran. Different analytical approaches and indexes are used to examine PERSIANN precision in detection and estimation of rainfall rate. The residuals are decomposed into Hit, Miss and FA estimation biases while continues decomposition of systematic and random error components are also analyzed seasonally and categorically. New interpretation of estimation accuracy named "reliability on PERSIANN estimations" is introduced while the changing manners of existing categorical/statistical measures and error components are also seasonally analyzed over different rainfall rate categories. This study yields new insights into the nature of PERSIANN errors over Urmia lake basin as a semi-arid region in the middle-east, including the followings: - The analyzed contingency table indexes indicate better detection precision during spring and fall. - A relatively constant level of error is generally observed among different categories. The range of precipitation estimates at different rainfall rate categories is nearly invariant as a sign for the existence of systematic error. - Low level of reliability is observed on PERSIANN estimations at different categories which are mostly associated with high level of FA error. However, it is observed that as the rate of precipitation increase, the ability and precision of PERSIANN in rainfall detection also increases. - The systematic and random error decomposition in this area shows that PERSIANN has more difficulty in modeling the system and pattern of rainfall rather than to have bias due to rainfall uncertainties. The level of systematic error also considerably increases in heavier rainfalls. It is also important to note that PERSIANN error characteristics at each season varies due to the condition and rainfall patterns of that season which shows the necessity of seasonally different approach for the calibration of

  3. Atmospheric water vapor transport: Estimation of continental precipitation recycling and parameterization of a simple climate model. M.S. Thesis

    Science.gov (United States)

    Brubaker, Kaye L.; Entekhabi, Dara; Eagleson, Peter S.

    1991-01-01

    The advective transport of atmospheric water vapor and its role in global hydrology and the water balance of continental regions are discussed and explored. The data set consists of ten years of global wind and humidity observations interpolated onto a regular grid by objective analysis. Atmospheric water vapor fluxes across the boundaries of selected continental regions are displayed graphically. The water vapor flux data are used to investigate the sources of continental precipitation. The total amount of water that precipitates on large continental regions is supplied by two mechanisms: (1) advection from surrounding areas external to the region; and (2) evaporation and transpiration from the land surface recycling of precipitation over the continental area. The degree to which regional precipitation is supplied by recycled moisture is a potentially significant climate feedback mechanism and land surface-atmosphere interaction, which may contribute to the persistence and intensification of droughts. A simplified model of the atmospheric moisture over continents and simultaneous estimates of regional precipitation are employed to estimate, for several large continental regions, the fraction of precipitation that is locally derived. In a separate, but related, study estimates of ocean to land water vapor transport are used to parameterize an existing simple climate model, containing both land and ocean surfaces, that is intended to mimic the dynamics of continental climates.

  4. Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

    Directory of Open Access Journals (Sweden)

    Saoussen Dhib

    2017-06-01

    Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly

  5. A spatial approach to the modelling and estimation of areal precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Skaugen, T

    1996-12-31

    In hydroelectric power technology it is important that the mean precipitation that falls in an area can be calculated. This doctoral thesis studies how the morphology of rainfall, described by the spatial statistical parameters, can be used to improve interpolation and estimation procedures. It attempts to formulate a theory which includes the relations between the size of the catchment and the size of the precipitation events in the modelling of areal precipitation. The problem of estimating and modelling areal precipitation can be formulated as the problem of estimating an inhomogeneously distributed flux of a certain spatial extent being measured at points in a randomly placed domain. The information contained in the different morphology of precipitation types is used to improve estimation procedures of areal precipitation, by interpolation (kriging) or by constructing areal reduction factors. A new approach to precipitation modelling is introduced where the analysis of the spatial coverage of precipitation at different intensities plays a key role in the formulation of a stochastic model for extreme areal precipitation and in deriving the probability density function of areal precipitation. 127 refs., 30 figs., 13 tabs.

  6. Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa

    Science.gov (United States)

    Hodnebrog, Øivind; Myhre, Gunnar; Forster, Piers M.; Sillmann, Jana; Samset, Bjørn H.

    2016-01-01

    Observations indicate a precipitation decline over large parts of southern Africa since the 1950s. Concurrently, atmospheric concentrations of greenhouse gases and aerosols have increased due to anthropogenic activities. Here we show that local black carbon and organic carbon aerosol emissions from biomass burning activities are a main cause of the observed decline in southern African dry season precipitation over the last century. Near the main biomass burning regions, global and regional modelling indicates precipitation decreases of 20–30%, with large spatial variability. Increasing global CO2 concentrations further contribute to precipitation reductions, somewhat less in magnitude but covering a larger area. Whereas precipitation changes from increased CO2 are driven by large-scale circulation changes, the increase in biomass burning aerosols causes local drying of the atmosphere. This study illustrates that reducing local biomass burning aerosol emissions may be a useful way to mitigate reduced rainfall in the region. PMID:27068129

  7. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  8. Oxygen and Hydrogen Isotopes of Precipitation in a Rocky Mountainous Area of Beijing to Distinguish and Estimate Spring Recharge

    Directory of Open Access Journals (Sweden)

    Ziqiang Liu

    2018-05-01

    Full Text Available Stable isotopes of oxygen and hydrogen were used to estimate seasonal contributions of precipitation to natural spring recharge in Beijing’s mountainous area. Isotopic compositions were shown to be more positive in the dry season and more negative in the wet season, due to the seasonal patterns in the amount of precipitation. The local meteoric water line (LMWL was δ2H = 7.0 δ18O − 2.3 for the dry season and δ2H = 5.9 δ18O − 10.4 for the wet season. LMWL in the two seasons had a lower slope and intercept than the Global Meteoric Water Line (p < 0.01. The slope and intercept of the LMWL in the wet season were lower than that in the dry season because of the effect of precipitation amount during the wet season (p < 0.01. The mean precipitation effects of −15‰ and −2‰ per 100 mm change in the amount of precipitation for δ2H and δ18O, respectively, were obtained from the monthly total precipitation and its average isotopic value. The isotopic composition of precipitation decreased when precipitation duration increased. Little changes in the isotopic composition of the natural spring were found. By employing isotope conservation of mass, it could be derived that, on average, approximately 7.2% of the natural spring came from the dry season precipitation and the rest of 92.8% came from the wet season precipitation.

  9. Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-01-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  10. Estimating mountain basin-mean precipitation from streamflow using Bayesian inference

    Science.gov (United States)

    Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.

    2015-10-01

    Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.

  11. Effects of large-scale deforestation on precipitation in the monsoon regions: remote versus local effects.

    Science.gov (United States)

    Devaraju, N; Bala, Govindasamy; Modak, Angshuman

    2015-03-17

    In this paper, using idealized climate model simulations, we investigate the biogeophysical effects of large-scale deforestation on monsoon regions. We find that the remote forcing from large-scale deforestation in the northern middle and high latitudes shifts the Intertropical Convergence Zone southward. This results in a significant decrease in precipitation in the Northern Hemisphere monsoon regions (East Asia, North America, North Africa, and South Asia) and moderate precipitation increases in the Southern Hemisphere monsoon regions (South Africa, South America, and Australia). The magnitude of the monsoonal precipitation changes depends on the location of deforestation, with remote effects showing a larger influence than local effects. The South Asian Monsoon region is affected the most, with 18% decline in precipitation over India. Our results indicate that any comprehensive assessment of afforestation/reforestation as climate change mitigation strategies should carefully evaluate the remote effects on monsoonal precipitation alongside the large local impacts on temperatures.

  12. Impact of time displaced precipitation estimates for on-line updated models

    DEFF Research Database (Denmark)

    Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

    2012-01-01

    When an online runoff model is updated from system measurements the requirements to the precipitation estimates change. Using rain gauge data as precipitation input there will be a displacement between the time where the rain intensity hits the gauge and the time where the rain hits the actual...

  13. Using damage data to estimate the risk from summer convective precipitation extremes

    Science.gov (United States)

    Schroeer, Katharina; Tye, Mari

    2017-04-01

    model to test whether the relationship between extreme rainfall events and damages is robust enough to estimate a potential underrepresentation of high intensity rainfall events in ungauged areas. Risk-relevant factors of socio-economic vulnerability, land cover, streamflow data, and weather type information are included to improve and sharpen the analysis. Within this study, we first aim to identify which rainfall events are most damaging and which factors affect the damages - seen as a proxy for the vulnerability - related to summer convective rainfall extremes in different catchment types. Secondly, we aim to detect potentially unreported damaging rainfall events and estimate the likelihood of such cases. We anticipate this damage perspective on summertime extreme convective precipitation to be beneficial for risk assessment, uncertainty management, and decision making with respect to weather and climate extremes on the regional-to-local level.

  14. Estimators for local non-Gaussianities

    International Nuclear Information System (INIS)

    Creminelli, P.; Senatore, L.; Zaldarriaga, M.

    2006-05-01

    We study the Likelihood function of data given f NL for the so-called local type of non-Gaussianity. In this case the curvature perturbation is a non-linear function, local in real space, of a Gaussian random field. We compute the Cramer-Rao bound for f NL and show that for small values of f NL the 3- point function estimator saturates the bound and is equivalent to calculating the full Likelihood of the data. However, for sufficiently large f NL , the naive 3-point function estimator has a much larger variance than previously thought. In the limit in which the departure from Gaussianity is detected with high confidence, error bars on f NL only decrease as 1/ln N pix rather than N pix -1/2 as the size of the data set increases. We identify the physical origin of this behavior and explain why it only affects the local type of non- Gaussianity, where the contribution of the first multipoles is always relevant. We find a simple improvement to the 3-point function estimator that makes the square root of its variance decrease as N pix -1/2 even for large f NL , asymptotically approaching the Cramer-Rao bound. We show that using the modified estimator is practically equivalent to computing the full Likelihood of f NL given the data. Thus other statistics of the data, such as the 4-point function and Minkowski functionals, contain no additional information on f NL . In particular, we explicitly show that the recent claims about the relevance of the 4-point function are not correct. By direct inspection of the Likelihood, we show that the data do not contain enough information for any statistic to be able to constrain higher order terms in the relation between the Gaussian field and the curvature perturbation, unless these are orders of magnitude larger than the size suggested by the current limits on f NL . (author)

  15. Rainfall estimation in SWAT: An alternative method to simulate orographic precipitation

    Science.gov (United States)

    Galván, L.; Olías, M.; Izquierdo, T.; Cerón, J. C.; Fernández de Villarán, R.

    2014-02-01

    The input of water from precipitation is one of the most important aspects of a hydrologic model because it controls the basin's water budget. The model should reproduce the amount and distribution of rainfall in the basin, spatially and temporally. SWAT (Soil and Water Assessment Tool) is one of the most widely used hydrologic models. In this paper the rainfall estimation in SWAT is revised, focusing on the treatment of orographic precipitation. SWAT was applied to the Odiel river basin (SW Spain), with a surface of 2300 km2. Results show that SWAT does not reflect reallisticaly the spatial distribution of rainfall in the basin. In relation to orographic precipitation, SWAT estimates the daily precipitation in elevation bands by adding a constant amount to the recorded precipitation in the rain gauge, which depends on the increase in precipitation with altitude and the difference between the mean elevation of each band and the elevation of the recording gauge. This does not reflect rainfall in the subbasin because the increase in precipitation with altitude actually it is not constant, but depends on the amount of rainfall. An alternative methodology to represent the temporal distribution of orographic precipitation is proposed. After simulation, the deviation of runoff volume using the SWAT elevation bands was appreciably higher than that obtained with the proposed methodology.

  16. Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

    Science.gov (United States)

    Adler, Robert; Gu, Guojun; Huffman, George

    2012-01-01

    A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a

  17. The Role of Localized Compressional Ultra-low Frequency Waves in Energetic Electron Precipitation

    Science.gov (United States)

    Rae, I. Jonathan; Murphy, Kyle R.; Watt, Clare E. J.; Halford, Alexa J.; Mann, Ian R.; Ozeke, Louis G.; Sibeck, David G.; Clilverd, Mark A.; Rodger, Craig J.; Degeling, Alex W.; Forsyth, Colin; Singer, Howard J.

    2018-03-01

    Typically, ultra-low frequency (ULF) waves have historically been invoked for radial diffusive transport leading to acceleration and loss of outer radiation belt electrons. At higher frequencies, very low frequency waves are generally thought to provide a mechanism for localized acceleration and loss through precipitation into the ionosphere of radiation belt electrons. In this study we present a new mechanism for electron loss through precipitation into the ionosphere due to a direct modulation of the loss cone via localized compressional ULF waves. We present a case study of compressional wave activity in tandem with riometer and balloon-borne electron precipitation across keV-MeV energies to demonstrate that the experimental measurements can be explained by our new enhanced loss cone mechanism. Observational evidence is presented demonstrating that modulation of the equatorial loss cone can occur via localized compressional wave activity, which greatly exceeds the change in pitch angle through conservation of the first and second adiabatic invariants. The precipitation response can be a complex interplay between electron energy, the localization of the waves, the shape of the phase space density profile at low pitch angles, ionospheric decay time scales, and the time dependence of the electron source; we show that two pivotal components not usually considered are localized ULF wave fields and ionospheric decay time scales. We conclude that enhanced precipitation driven by compressional ULF wave modulation of the loss cone is a viable candidate for direct precipitation of radiation belt electrons without any additional requirement for gyroresonant wave-particle interaction. Additional mechanisms would be complementary and additive in providing means to precipitate electrons from the radiation belts during storm times.

  18. Long-Term Precipitation Analysis and Estimation of Precipitation Concentration Index Using Three Support Vector Machine Methods

    Directory of Open Access Journals (Sweden)

    Milan Gocic

    2016-01-01

    Full Text Available The monthly precipitation data from 29 stations in Serbia during the period of 1946–2012 were considered. Precipitation trends were calculated using linear regression method. Three CLINO periods (1961–1990, 1971–2000, and 1981–2010 in three subregions were analysed. The CLINO 1981–2010 period had a significant increasing trend. Spatial pattern of the precipitation concentration index (PCI was presented. For the purpose of PCI prediction, three Support Vector Machine (SVM models, namely, SVM coupled with the discrete wavelet transform (SVM-Wavelet, the firefly algorithm (SVM-FFA, and using the radial basis function (SVM-RBF, were developed and used. The estimation and prediction results of these models were compared with each other using three statistical indicators, that is, root mean square error, coefficient of determination, and coefficient of efficiency. The experimental results showed that an improvement in predictive accuracy and capability of generalization can be achieved by the SVM-Wavelet approach. Moreover, the results indicated the proposed SVM-Wavelet model can adequately predict the PCI.

  19. Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

    Science.gov (United States)

    Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

    2016-12-01

    Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

  20. REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region

    OpenAIRE

    Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano

    2009-01-01

    An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...

  1. Local short-duration precipitation extremes in Sweden: observations, forecasts and projections

    Science.gov (United States)

    Olsson, Jonas; Berg, Peter; Simonsson, Lennart

    2015-04-01

    Local short-duration precipitation extremes (LSPEs) are a key driver of hydrological hazards, notably in steep catchments with thin soils and in urban environments. The triggered floodings, landslides, etc., have large consequences for society in terms of both economy and health. Accurate estimations of LSPEs on both climatological time-scales (past, present, future) and in real-time is thus of great importance for improved hydrological predictions as well as design of constructions and infrastructure affected by hydrological fluxes. Analysis of LSPEs is, however, associated with various limitations and uncertainties. These are to a large degree associated with the small-scale nature of the meteorological processes behind LSPEs and the associated requirements on observation sensors as well as model descriptions. Some examples of causes for the limitations involved are given in the following. - Observations: High-resolution data sets available for LSPE analyses are often limited to either relatively long series from one or a few stations or relatively short series from larger station networks. Radar data have excellent resolutions in both time and space but the estimated local precipitation intensity is still highly uncertain. New and promising techniques (e.g. microwave links) are still in their infancy. - Weather forecasts (short-range): Although forecasts with the required spatial resolution for potential generation of LSPEs (around 2-4 km) are becoming operationally available, the actual forecast precision of LSPEs is largely unknown. Forecasted LSPEs may be displaced in time or, more critically, in space which strongly affects the possibility to assess hydrological risk. - Climate projections: The spatial resolution of the current RCM generation (around 25 km) is not sufficient for proper description of LSPEs. Statistical post-processing (i.e. downscaling) is required which adds substantial uncertainty to the final result. Ensemble generation of sufficiently

  2. The concurrent multiplicative-additive approach for gauge-radar/satellite multisensor precipitation estimates

    Science.gov (United States)

    Garcia-Pintado, J.; Barberá, G. G.; Erena Arrabal, M.; Castillo, V. M.

    2010-12-01

    Objective analysis schemes (OAS), also called ``succesive correction methods'' or ``observation nudging'', have been proposed for multisensor precipitation estimation combining remote sensing data (meteorological radar or satellite) with data from ground-based raingauge networks. However, opposite to the more complex geostatistical approaches, the OAS techniques for this use are not optimized. On the other hand, geostatistical techniques ideally require, at the least, modelling the covariance from the rain gauge data at every time step evaluated, which commonly cannot be soundly done. Here, we propose a new procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) for operational rainfall estimation using rain gauges and meteorological radar, which does not require explicit modelling of spatial covariances. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on the OAS, whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The approach considers radar estimates as background a priori information (first guess), so that nudging to observations (gauges) may be relaxed smoothly to the first guess, and the relaxation shape is obtained from the sequential

  3. Precipitation evidences on X-Band Synthetic Aperture Radar imagery: an approach for quantitative detection and estimation

    Science.gov (United States)

    Mori, Saverio; Marzano, Frank S.; Montopoli, Mario; Pulvirenti, Luca; Pierdicca, Nazzareno

    2017-04-01

    al. 2014 and Mori et al. 2012); ancillary data, such as local incident angle and land cover, are used. This stage is necessary to tune the precipitation map stage and to avoid severe misinterpretations on the precipitation map routines. The second stage consist of estimating the local cloud attenuation. Finally the precipitation map is estimated, using the the retrieval algorithm developed by Marzano et al. (2011), applied only to pixels where rain is known to be present. Within the FP7 project EartH2Observe we have applied this methodology to 14 study cases, acquired within TSX and CSK missions over Italy and United States. This choice allows analysing both hurricane-like intense events and continental mid-latitude precipitations, with the possibility to verify and validate the proposed methodology through the available weather radar networks. Moreover it allows in same extent analysing the contribution of orography and quality of ancillary data (i.e. landcover). In this work we will discuss the results obtained until now in terms of improved rain cell localization and precipitation quantification.

  4. GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

    Science.gov (United States)

    Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

    2017-12-01

    Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of

  5. Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

    Science.gov (United States)

    Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

    Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

  6. Estimation of the impact of climate change-induced extreme precipitation events on floods

    Science.gov (United States)

    Hlavčová, Kamila; Lapin, Milan; Valent, Peter; Szolgay, Ján; Kohnová, Silvia; Rončák, Peter

    2015-09-01

    In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981-2010 period, 20 events of the basin's most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.

  7. Evaluating the applicability of four recent satellite–gauge combined precipitation estimates for extreme precipitation and streamflow predictions over the upper Yellow river basin in China

    Science.gov (United States)

    This study aimed to statistically and hydrologically assess the performance of four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT, BLD, 3B42CDR, and 3B42 for the extreme precipitation and stream'ow scenarios over the upper Yellow river basin (UYRB) in ch...

  8. Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

    Energy Technology Data Exchange (ETDEWEB)

    Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

    2016-02-01

    To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

  9. Disdrometer-based C-Band Radar Quantitative Precipitation Estimation (QPE) in a highly complex terrain region in tropical Colombia.

    Science.gov (United States)

    Sepúlveda, J.; Hoyos Ortiz, C. D.

    2017-12-01

    An adequate quantification of precipitation over land is critical for many societal applications including agriculture, hydroelectricity generation, water supply, and risk management associated with extreme events. The use of rain gauges, a traditional method for precipitation estimation, and an excellent one, to estimate the volume of liquid water during a particular precipitation event, does not allow to fully capture the highly spatial variability of the phenomena which is a requirement for almost all practical applications. On the other hand, the weather radar, an active remote sensing sensor, provides a proxy for rainfall with fine spatial resolution and adequate temporary sampling, however, it does not measure surface precipitation. In order to fully exploit the capabilities of the weather radar, it is necessary to develop quantitative precipitation estimation (QPE) techniques combining radar information with in-situ measurements. Different QPE methodologies are explored and adapted to local observations in a highly complex terrain region in tropical Colombia using a C-Band radar and a relatively dense network of rain gauges and disdrometers. One important result is that the expressions reported in the literature for extratropical locations are not representative of the conditions found in the tropical region studied. In addition to reproducing the state-of-the-art techniques, a new multi-stage methodology based on radar-derived variables and disdrometer data is proposed in order to achieve the best QPE possible. The main motivation for this new methodology is based on the fact that most traditional QPE methods do not directly take into account the different uncertainty sources involved in the process. The main advantage of the multi-stage model compared to traditional models is that it allows assessing and quantifying the uncertainty in the surface rain rate estimation. The sub-hourly rainfall estimations using the multi-stage methodology are realistic

  10. Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

    Science.gov (United States)

    Yi, J.; Choi, C.

    2014-12-01

    Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

  11. Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

    NARCIS (Netherlands)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.

    2011-01-01

    Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar

  12. Improving real-time estimation of heavy-to-extreme precipitation using rain gauge data via conditional bias-penalized optimal estimation

    Science.gov (United States)

    Seo, Dong-Jun; Siddique, Ridwan; Zhang, Yu; Kim, Dongsoo

    2014-11-01

    A new technique for gauge-only precipitation analysis for improved estimation of heavy-to-extreme precipitation is described and evaluated. The technique is based on a novel extension of classical optimal linear estimation theory in which, in addition to error variance, Type-II conditional bias (CB) is explicitly minimized. When cast in the form of well-known kriging, the methodology yields a new kriging estimator, referred to as CB-penalized kriging (CBPK). CBPK, however, tends to yield negative estimates in areas of no or light precipitation. To address this, an extension of CBPK, referred to herein as extended conditional bias penalized kriging (ECBPK), has been developed which combines the CBPK estimate with a trivial estimate of zero precipitation. To evaluate ECBPK, we carried out real-world and synthetic experiments in which ECBPK and the gauge-only precipitation analysis procedure used in the NWS's Multisensor Precipitation Estimator (MPE) were compared for estimation of point precipitation and mean areal precipitation (MAP), respectively. The results indicate that ECBPK improves hourly gauge-only estimation of heavy-to-extreme precipitation significantly. The improvement is particularly large for estimation of MAP for a range of combinations of basin size and rain gauge network density. This paper describes the technique, summarizes the results and shares ideas for future research.

  13. Estimation of precipitable water at different locations using surface dew-point

    Science.gov (United States)

    Abdel Wahab, M.; Sharif, T. A.

    1995-09-01

    The Reitan (1963) regression equation of the form ln w = a + bT d has been examined and tested to estimate precipitable water vapor content from the surface dew point temperature at different locations. The results of this study indicate that the slope b of the above equation has a constant value of 0.0681, while the intercept a changes rapidly with latitude. The use of the variable intercept technique can improve the estimated result by about 2%.

  14. Evaluation of spatial and spatiotemporal estimation methods in simulation of precipitation variability patterns

    Science.gov (United States)

    Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen

    2013-08-01

    Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.

  15. Future increases in Arctic precipitation linked to local evaporation and sea-ice retreat.

    Science.gov (United States)

    Bintanja, R; Selten, F M

    2014-05-22

    Precipitation changes projected for the end of the twenty-first century show an increase of more than 50 per cent in the Arctic regions. This marked increase, which is among the highest globally, has previously been attributed primarily to enhanced poleward moisture transport from lower latitudes. Here we use state-of-the-art global climate models to show that the projected increases in Arctic precipitation over the twenty-first century, which peak in late autumn and winter, are instead due mainly to strongly intensified local surface evaporation (maximum in winter), and only to a lesser degree due to enhanced moisture inflow from lower latitudes (maximum in late summer and autumn). Moreover, we show that the enhanced surface evaporation results mainly from retreating winter sea ice, signalling an amplified Arctic hydrological cycle. This demonstrates that increases in Arctic precipitation are firmly linked to Arctic warming and sea-ice decline. As a result, the Arctic mean precipitation sensitivity (4.5 per cent increase per degree of temperature warming) is much larger than the global value (1.6 to 1.9 per cent per kelvin). The associated seasonally varying increase in Arctic precipitation is likely to increase river discharge and snowfall over ice sheets (thereby affecting global sea level), and could even affect global climate through freshening of the Arctic Ocean and subsequent modulations of the Atlantic meridional overturning circulation.

  16. Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

    Science.gov (United States)

    Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

    2018-03-01

    The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.

  17. Local control on precipitation in a fully coupled climate-hydrology model.

    Science.gov (United States)

    Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

    2016-03-10

    The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

  18. Precipitation areal-reduction factor estimation using an annual-maxima centered approach

    Science.gov (United States)

    Asquith, W.H.; Famiglietti, J.S.

    2000-01-01

    The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima. (C) 2000 Elsevier Science B.V.The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are

  19. An "Ensemble Approach" to Modernizing Extreme Precipitation Estimation for Dam Safety Decision-Making

    Science.gov (United States)

    Cifelli, R.; Mahoney, K. M.; Webb, R. S.; McCormick, B.

    2017-12-01

    To ensure structural and operational safety of dams and other water management infrastructure, water resources managers and engineers require information about the potential for heavy precipitation. The methods and data used to estimate extreme rainfall amounts for managing risk are based on 40-year-old science and in need of improvement. The need to evaluate new approaches based on the best science available has led the states of Colorado and New Mexico to engage a body of scientists and engineers in an innovative "ensemble approach" to updating extreme precipitation estimates. NOAA is at the forefront of one of three technical approaches that make up the "ensemble study"; the three approaches are conducted concurrently and in collaboration with each other. One approach is the conventional deterministic, "storm-based" method, another is a risk-based regional precipitation frequency estimation tool, and the third is an experimental approach utilizing NOAA's state-of-the-art High Resolution Rapid Refresh (HRRR) physically-based dynamical weather prediction model. The goal of the overall project is to use the individual strengths of these different methods to define an updated and broadly acceptable state of the practice for evaluation and design of dam spillways. This talk will highlight the NOAA research and NOAA's role in the overarching goal to better understand and characterizing extreme precipitation estimation uncertainty. The research led by NOAA explores a novel high-resolution dataset and post-processing techniques using a super-ensemble of hourly forecasts from the HRRR model. We also investigate how this rich dataset may be combined with statistical methods to optimally cast the data in probabilistic frameworks. NOAA expertise in the physical processes that drive extreme precipitation is also employed to develop careful testing and improved understanding of the limitations of older estimation methods and assumptions. The process of decision making in the

  20. Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.

    2011-02-01

    Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study, the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed which corrects the radar data for errors related to attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR), and advection. No final bias correction with respect to rain gauge data was implemented because such an adjustment would not add to a better understanding of the quality of the radar data. The impact of the different corrections is assessed using rainfall information sampled by 42 hourly rain gauges. The largest improvement in the quality of the radar data is obtained by correcting for ground clutter. The impact of VPR correction and advection depends on the spatial variability and velocity of the precipitation system. Overall during the winter period, the radar underestimates the amount of precipitation as compared to the rain gauges. Remaining differences between both instruments can be attributed to spatial and temporal variability in the type of precipitation, which has not been taken into account.

  1. Estimating Mutual Information by Local Gaussian Approximation

    Science.gov (United States)

    2015-07-13

    proposed a variety of methods to overcome the bias, such as the reflection method (Schuster, 1985), ( Silverman , 1986); the boundary kernel method...Stephen Marron and David Ruppert. Transformations to reduce boundary bias in kernel density estimation. Journal of the Royal Statistical Society. Series B...estimation with applications to machine learning on distributions. In Proceedings of Uncertainty in Artificial In- telligence (UAI), 2011. David N Reshef

  2. Local polynomial Whittle estimation covering non-stationary fractional processes

    DEFF Research Database (Denmark)

    Nielsen, Frank

    to the non-stationary region. By approximating the short-run component of the spectrum by a polynomial, instead of a constant, in a shrinking neighborhood of zero we alleviate some of the bias that the classical local Whittle estimators is prone to. This bias reduction comes at a cost as the variance is in...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....

  3. The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

    Science.gov (United States)

    Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

    2017-08-01

    Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

  4. Impact of deforestation on local precipitation patterns over the Da River basin, Vietnam

    Science.gov (United States)

    Anghileri, Daniela; Spartà, Daniele; Castelletti, Andrea; Boschetti, Mirco

    2014-05-01

    Change in land cover, e.g. from forest to bare soil, might severely impact the hydrological cycle at the river basin scale by altering the balance between rainfall and evaporation, ultimately affecting streamflow dynamics. These changes generally occur over decades, but they might be much more rapid in developing countries, where economic growth and growing population may cause abrupt changes in landscape and ecosystem. Detecting, analysing and modelling these changes is an essential step to design mitigation strategies and adaptation plans, balancing economic development and ecosystem protection. In this work we investigate the impact of land cover changes on the water cycle in the Da River basin, Vietnam. More precisely, the objective is to evaluate the interlink between deforestation and precipitation. The case study is particularly interesting because Vietnam is one of the world fastest growing economies and natural resources have been considerably exploited to support after-war development. Vietnam has the second highest rate of deforestation of primary forests in the world, second to only Nigeria (FAO 2005), with associated problems like abrupt change in run-off, erosion, sediment transport and flash floods. We performed land cover evaluation by combining literature information and Remote Sensing techniques, using Landsat images. We then analysed time series of precipitation observed on the period 1960-2011 in several stations located in the catchment area. We used multiple trend detection techniques, both state-of-the-art (e.g., Linear regression and Mann-Kendall) and novel trend detection techniques (Moving Average on Shifting Horizon), to investigate trends in seasonal pattern of precipitation. Results suggest that deforestation may induce a negative trend in the precipitation volume. The effect is mainly recognizable at the beginning and at the end of the monsoon season, when the local mechanisms of precipitation formation prevail over the large scale

  5. Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

    Directory of Open Access Journals (Sweden)

    Qiutong Jin

    2016-06-01

    Full Text Available Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK and geographically weighted regression Kriging (GWRK methods were employed using precipitation data from the period 1980–2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM, normalized difference vegetation index (NDVI, solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

  6. Estimating Probable Maximum Precipitation by Considering Combined Effect of Typhoon and Southwesterly Air Flow

    Directory of Open Access Journals (Sweden)

    Cheng-Chin Liu

    2016-01-01

    Full Text Available Typhoon Morakot hit southern Taiwan in 2009, bringing 48-hr of heavy rainfall [close to the Probable Maximum Precipitation (PMP] to the Tsengwen Reservoir catchment. This extreme rainfall event resulted from the combined (co-movement effect of two climate systems (i.e., typhoon and southwesterly air flow. Based on the traditional PMP estimation method (i.e., the storm transposition method, STM, two PMP estimation approaches, i.e., Amplification Index (AI and Independent System (IS approaches, which consider the combined effect are proposed in this work. The AI approach assumes that the southwesterly air flow precipitation in a typhoon event could reach its maximum value. The IS approach assumes that the typhoon and southwesterly air flow are independent weather systems. Based on these assumptions, calculation procedures for the two approaches were constructed for a case study on the Tsengwen Reservoir catchment. The results show that the PMP estimates for 6- to 60-hr durations using the two approaches are approximately 30% larger than the PMP estimates using the traditional STM without considering the combined effect. This work is a pioneer PMP estimation method that considers the combined effect of a typhoon and southwesterly air flow. Further studies on this issue are essential and encouraged.

  7. The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-11-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the

  8. Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

    Science.gov (United States)

    Hou, Arthur

    2012-01-01

    satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder (SAPHIR) on the French-Indian Megha- Tropiques satellite, (4) the Microwave Humidity Sounder (MHS) on the National Oceanic and Atmospheric Administration (NOAA)-19, (5) MHS instruments on MetOp satellites launched by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), (6) the Advanced Technology Microwave Sounder (ATMS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), and (7) ATMS instruments on the NOAA-NASA Joint Polar Satellite System (JPSS) satellites. Data from Chinese and Russian microwave radiometers may also become available through international collaboration under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). The current generation of global rainfall products combines observations from a network of uncoordinated satellite missions using a variety of merging techniques. GPM will provide next-generation precipitation products characterized by: (1) more accurate instantaneous precipitation estimate (especially for light rain and cold-season solid precipitation), (2) intercalibrated microwave brightness temperatures from constellation radiometers within a consistent framework, and (3) unified precipitation retrievals from constellation radiometers using a common a priori hydrometeor database constrained by combined radar/radiometer measurements provided by the GPM Core Observatory.

  9. Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

    Science.gov (United States)

    Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

    2013-12-01

    Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so

  10. GPM SLH: Convective Latent Heating Estimated with GPM Dual-frequency Precipitation Radar Data

    Science.gov (United States)

    Takayabu, Y. N.; Hamada, A.; Yokoyama, C.; Ikuta, Y.; Shige, S.; Yamaji, M.; Kubota, T.

    2017-12-01

    Three dimensional diabatic heating distribution plays essential roles to determine large-scale circulation, as well as to generate mesoscale circulation associated with tropical convection (e.g. Hartmann et al., 1984; Houze et al. 1982). For mid-latitude systems also, diabatic heating contributes to generate PVs resulting in, for example, explosive intensifications of mid-lattitude storms (Boettcher and Wernli, 2011). Previously, with TRMM PR data, we developed a Spectral Latent Heating algorithm (SLH; Shige et al. 2004, etc.) for 36N-36S region. It was based on the spectral LH tables produced from a simulation utilizing the Goddard Cloud Ensemble Model forced with the TOGA-COARE data. With GPM DPR, the observation region is extended to 65N-65S. Here, we introduce a new version of SLH algorithm which is applicable also to the mid-latitude precipitation. A new global GPM SLH ver.5 product is released as one of NASA/JAXA GPM standard products on July 11, 2017. For GPM SLH mid-latitude algorithm, we employ the Japan Meteorological Agency (JMA)'s high resolution (horizontally 2km) Local Forecast Model (LFM) to construct the LUTs. With collaborations of JMA's forecast group, forecast data for 8 extratropical cyclone cases are collected and utilized. For mid-latitude precipitation, we have to deal with large temperature gradients and complex relationship between the freezing level and cloud base levels. LUTs are constructed for LH, Q1-QR, and Q2 (Yanai et al. 1973), for six different precipitation types: Convective and shallow stratiform LUTs are made against precipitation top heights. For deep stratiform and other precipitation, LUTs are made against maximum precipitation to handle the unknown cloud-bases. Finally, three-dimensional convective latent heating is retrieved, utilizing the LUTs and precipitation profile data from GPM 2AKu. We can confirm that retrieved LH looks very similar to simulated LH, for a consistency check. We also confirm a good continuities of

  11. Single event upset threshold estimation based on local laser irradiation

    International Nuclear Information System (INIS)

    Chumakov, A.I.; Egorov, A.N.; Mavritsky, O.B.; Yanenko, A.V.

    1999-01-01

    An approach for estimation of ion-induced SEU threshold based on local laser irradiation is presented. Comparative experiment and software simulation research were performed at various pulse duration and spot size. Correlation of single event threshold LET to upset threshold laser energy under local irradiation was found. The computer analysis of local laser irradiation of IC structures was developed for SEU threshold LET estimation. The correlation of local laser threshold energy with SEU threshold LET was shown. Two estimation techniques were suggested. The first one is based on the determination of local laser threshold dose taking into account the relation of sensitive area to local irradiated area. The second technique uses the photocurrent peak value instead of this relation. The agreement between the predicted and experimental results demonstrates the applicability of this approach. (authors)

  12. Errors and parameter estimation in precipitation-runoff modeling: 1. Theory

    Science.gov (United States)

    Troutman, Brent M.

    1985-01-01

    Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.

  13. Combining C- and X-band Weather Radars for Improving Precipitation Estimates over Urban Areas

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk

    of future system state. Accurate and reliable weather radar measurements are, therefore, important for future developments and achievements within urban drainage. This PhD study investigates two types of weather radars. Both systems are in operational use in Denmark today. A network of meteorological C...... individually and owned by local water utility companies. Although the two radar systems use similar working principles, the systems have significant differences regarding technology, temporal resolution, spatial resolution, range and scanning strategy. The focus of the research was to combine the precipitation...

  14. Global estimate of lichen and bryophyte contributions to forest precipitation interception

    Science.gov (United States)

    Van Stan, John; Porada, Philipp; Kleidon, Axel

    2017-04-01

    Interception of precipitation by forest canopies plays an important role in its partitioning to evaporation, transpiration and runoff. Field observations show arboreal lichens and bryophytes can substantially enhance forests' precipitation storage and evaporation. However, representations of canopy interception in global land surface models currently ignore arboreal lichen and bryophyte contributions. This study uses the lichen and bryophyte model (LiBry) to provide the first process-based modelling approach estimating these organisms' contributions to canopy water storage and evaporation. The global mean value of forest water storage capacity increased significantly from 0.87 mm to 1.33 mm by the inclusion of arboreal poikilohydric organisms. Global forest canopy evaporation of intercepted precipitation was also greatly enhanced by 44%. Ratio of total versus bare canopy global evaporation exceeded 2 in many forested regions. This altered global patterns in canopy water storage, evaporation, and ultimately the proportion of rainfall evaporated. A sensitivity analysis was also performed. Results indicate rainfall interception is of larger magnitude than previously reported by global land surface modelling work because of the important role of lichen and bryophytes in rainfall interception.

  15. The Relative Performance of High Resolution Quantitative Precipitation Estimates in the Russian River Basin

    Science.gov (United States)

    Bytheway, J. L.; Biswas, S.; Cifelli, R.; Hughes, M.

    2017-12-01

    The Russian River carves a 110 mile path through Mendocino and Sonoma counties in western California, providing water for thousands of residents and acres of agriculture as well as a home for several species of endangered fish. The Russian River basin receives almost all of its precipitation during the October through March wet season, and the systems bringing this precipitation are often impacted by atmospheric river events as well as the complex topography of the region. This study will examine the performance of several high resolution (hourly, products and forecasts over the 2015-2016 and 2016-2017 wet seasons. Comparisons of event total rainfall as well as hourly rainfall will be performed using 1) rain gauges operated by the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Division (PSD), 2) products from the Multi-Radar/Multi-Sensor (MRMS) QPE dataset, and 3) quantitative precipitation forecasts from the High Resolution Rapid Refresh (HRRR) model at 1, 3, 6, and 12 hour lead times. Further attention will be given to cases or locations representing large disparities between the estimates.

  16. Validation of Satellite Precipitation Products Using Local Rain Gauges to Support Water Assessment in Cochabamba, Bolivia

    Science.gov (United States)

    Saavedra, O.

    2017-12-01

    The metropolitan region of Cochabamba has been struggling for a consistent water supply master plan for years. The limited precipitation intensities and growing water demand have led to severe water conflicts since 2000 when the fight for water had international visibility. A new dam has just placed into operation, located at the mountain range north of the city, which is the hope to fulfill partially water demand in the region. Looking for feasible water sources and projects are essential to fulfill demand. However, the limited monitoring network composed by conventional rain gauges are not enough to come up with the proper aerial precipitation patterns. This study explores the capabilities of GSMaP-GPM satellite products combined with local rain gauge network to obtain an enhanced product with spatial and temporal resolution. A simple methodology based on penalty factors is proposed to adjust GSMaP-GPM intensities on grid-by-grid basis. The distance of an evaluated grid to the surrounding rain gauges was taken into account. The final correcting factors were obtained by iteration, at this particular case of study four iterations were enough to reduce the relative error. A distributed hydrological model was forced with the enhanced precipitation product to simulate the inflow to the new operating dam. Once the model parameters were calibrated and validated, forecast simulations were run. For the short term, the precipitation trend was projected using exponential equation. As for the long term projection, precipitation and temperature from the hadGEM2 and MIROC global circulation model outputs were used where the last one was found in closer agreement of predictions in the past. Overall, we found out that the amount of 1000 l/s for water supply to the region should be possible to fulfill till 2030. Beyond this year, the intake of two neighboring basins should be constructed to increase the stored volume. This is study was found particularly useful to forecast river

  17. Multiple leakage localization and leak size estimation in water networks

    NARCIS (Netherlands)

    Abbasi, N.; Habibi, H.; Hurkens, C.A.J.; Klabbers, M.D.; Tijsseling, A.S.; Eijndhoven, van S.J.L.

    2012-01-01

    Water distribution networks experience considerable losses due to leakage, often at multiple locations simultaneously. Leakage detection and localization based on sensor placement and online pressure monitoring could be fast and economical. Using the difference between estimated and measured

  18. Precipitation estimates and comparison of satellite rainfall data to in situ rain gauge observations to further develop the watershed-modeling capabilities for the Lower Mekong River Basin

    Science.gov (United States)

    Dandridge, C.; Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

    2017-12-01

    This study focuses on the lower region of the Mekong River Basin (MRB), an area including Burma, Cambodia, Vietnam, Laos, and Thailand. This region is home to expansive agriculture that relies heavily on annual precipitation over the basin for its prosperity. Annual precipitation amounts are regulated by the global monsoon system and therefore vary throughout the year. This research will lead to improved prediction of floods and management of floodwaters for the MRB. We compare different satellite estimates of precipitation to each other and to in-situ precipitation estimates for the Mekong River Basin. These comparisons will help us determine which satellite precipitation estimates are better at predicting precipitation in the MRB and will help further our understanding of watershed-modeling capabilities for the basin. In this study we use: 1) NOAA's PERSIANN daily 0.25° precipitation estimate Climate Data Record (CDR), 2) NASA's Tropical Rainfall Measuring Mission (TRMM) daily 0.25° estimate, and 3) NASA's Global Precipitation Measurement (GPM) daily 0.1 estimate and 4) 488 in-situ stations located in the lower MRB provide daily precipitation estimates. The PERSIANN CDR precipitation estimate was able to provide the longest data record because it is available from 1983 to present. The TRMM precipitation estimate is available from 2000 to present and the GPM precipitation estimates are available from 2015 to present. It is for this reason that we provide several comparisons between our precipitation estimates. Comparisons were done between each satellite product and the in-situ precipitation estimates based on geographical location and date using the entire available data record for each satellite product for daily, monthly, and yearly precipitation estimates. We found that monthly PERSIANN precipitation estimates were able to explain up to 90% of the variability in station precipitation depending on station location.

  19. Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

    Science.gov (United States)

    Xie, Pingping; Joyce, Robert; Wu, Shaorong

    2015-04-01

    As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

  20. Relating Local to Global Spatial Knowledge: Heuristic Influence of Local Features on Direction Estimates

    Science.gov (United States)

    Phillips, Daniel W.; Montello, Daniel R.

    2015-01-01

    Previous research has examined heuristics--simplified decision-making rules-of-thumb--for geospatial reasoning. This study examined at two locations the influence of beliefs about local coastline orientation on estimated directions to local and distant places; estimates were made immediately or after fifteen seconds. This study goes beyond…

  1. Downscaling global precipitation for local applications - a case for the Rhine basin

    Science.gov (United States)

    Sperna Weiland, Frederiek; van Verseveld, Willem; Schellekens, Jaap

    2017-04-01

    Within the EU FP7 project eartH2Observe a global Water Resources Re-analysis (WRR) is being developed. This re-analysis consists of meteorological and hydrological water balance variables with global coverage, spanning the period 1979-2014 at 0.25 degrees resolution (Schellekens et al., 2016). The dataset can be of special interest in regions with limited in-situ data availability, yet for local scale analysis particularly in mountainous regions, a resolution of 0.25 degrees may be too coarse and downscaling the data to a higher resolution may be required. A downscaling toolbox has been made that includes spatial downscaling of precipitation based on the global WorldClim dataset that is available at 1 km resolution as a monthly climatology (Hijmans et al., 2005). The input of the down-scaling tool are either the global eartH2Observe WRR1 and WRR2 datasets based on the WFDEI correction methodology (Weedon et al., 2014) or the global Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (Beck et al., 2016). Here we present a validation of the datasets over the Rhine catchment by means of a distributed hydrological model (wflow, Schellekens et al., 2014) using a number of precipitation scenarios. (1) We start by running the model using the local reference dataset derived by spatial interpolation of gauge observations. Furthermore we use (2) the MSWEP dataset at the native 0.25-degree resolution followed by (3) MSWEP downscaled with the WorldClim dataset and final (4) MSWEP downscaled with the local reference dataset. The validation will be based on comparison of the modeled river discharges as well as rainfall statistics. We expect that down-scaling the MSWEP dataset with the WorldClim data to higher resolution will increase its performance. To test the performance of the down-scaling routine we have added a run with MSWEP data down-scaled with the local dataset and compare this with the run based on the local dataset itself. - Beck, H. E. et al., 2016. MSWEP

  2. Extreme Precipitation Estimation with Typhoon Morakot Using Frequency and Spatial Analysis

    Directory of Open Access Journals (Sweden)

    Hone-Jay Chu

    2011-01-01

    Full Text Available Typhoon Morakot lashed Taiwan and produced copious amounts of precipitation in 2009. From the point view of hydrological statistics, the impact of the precipitation from typhoon Morakot using a frequency analysis can be analyzed and discussed. The frequency curve, which was fitted mathematically to historical observed data, can be used to estimate the probability of exceedance for runoff events of a certain magnitude. The study integrates frequency analysis and spatial analysis to assess the effect of Typhoon Morakot event on rainfall frequency in the Gaoping River basin of southern Taiwan. First, extreme rainfall data are collected at sixteen stations for durations of 1, 3, 6, 12, and 24 hours and then an appropriate probability distribution was selected to analyze the impact of the extreme hydrological event. Spatial rainfall patterns for a return period of 200-yr with 24-hr duration with and without Typhoon Morakot are estimated. Results show that the rainfall amount is significantly different with long duration with and without the event for frequency analysis. Furthermore, spatial analysis shows that extreme rainfall for a return period of 200-yr is highly dependent on topography and is smaller in the southwest than that in the east. The results not only demonstrate the distinct effect of Typhoon Morakot on frequency analysis, but also could provide reference in future planning of hydrological engineering.

  3. Quantifying the effects of LUCCs on local temperatures, precipitation, and wind using the WRF model.

    Science.gov (United States)

    Lian, Lishu; Li, Baofu; Chen, Yaning; Chu, Cuicui; Qin, Yanhua

    2017-09-11

    Land use/cover changes (LUCCs) are an important cause of regional climate changes, but the contribution of LUCCs to regional climate changes is not clear. In this study, the Weather Research and Forecasting (WRF) model and statistical methods were used to investigate changes in meteorologic variables in January, April, July, and October 2013 due to local LUCCs from 1990 to 2010 in southern Shandong province, China. The results indicate that the WRF model simulates temperatures in the region well, with high correlation coefficients (0.86-0.97, p wind speed and direction substantially during these four months: average wind speeds increased by 0.02 and 0.01 m/s in January and October, respectively, and decreased by 0.02 and 0.05 m/s in April and July, respectively. Overall, The LUCCs affected spring temperatures the least and summer precipitation the most.

  4. Unstable volatility functions: the break preserving local linear estimator

    DEFF Research Database (Denmark)

    Casas, Isabel; Gijbels, Irene

    The objective of this paper is to introduce the break preserving local linear (BPLL) estimator for the estimation of unstable volatility functions. Breaks in the structure of the conditional mean and/or the volatility functions are common in Finance. Markov switching models (Hamilton, 1989......) and threshold models (Lin and Terasvirta, 1994) are amongst the most popular models to describe the behaviour of data with structural breaks. The local linear (LL) estimator is not consistent at points where the volatility function has a break and it may even report negative values for finite samples...

  5. Local time, substorm, and seasonal dependence of electron precipitation at L≅4 inferred from riometer measurements

    International Nuclear Information System (INIS)

    Rosenberg, T.J.; Dudeney, J.R.

    1986-01-01

    We have examined the variations of electron precipitation at L≅4 as inferred from riometer measurements of cosmic radio noise absorption made during 1975 at Siple Station and Halley Bay, Antarctica. The results are presented in the form of annual and seasonal averages of 1/2-hourly values for two geomagnetic activity subsets, AE>140 nT (disturbed) and AE≤ 140 nT (quiet). Monthly quiet day curves were used to remove the diurnal and seasonal variations in the background noise levels. Generally, the local time characteristics of the absorption were the same at both stations; the highest absorption occurred in the 0400--1600 MLT sector during disturbed conditions and in the 1200--2000 MLT sector during quiet conditions. For high AE, the highest correlation was obtained at a lag equal to the magnetic local time difference (1.5 hours) between the two stations. On the other hand, for low AE, the highest correlation occurred for a lag of 3.0 hours, nearer the local solar time difference (3.8 hours). Consistently higher absorption was measured at Halley on the average during both levels of magnetic disturbance and in all seasons. At both locations, and for both geomagnetic activity subsets, more absorption was observed in summer and equinox than in winter. This is in contrast to earlier studies for L≥6, and suggests that a meridional reversal of seasonal behavior occurs between L = 4 and L = 6

  6. Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates

    Science.gov (United States)

    McEnery, J. A.; Jitkajornwanich, K.

    2012-12-01

    This presentation will describe the methodology and overall system development by which a benchmark dataset of precipitation information has been used to characterize the depth-area-duration relations in heavy rain storms occurring over regions of Texas. Over the past two years project investigators along with the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) have developed and operated a gateway data system to ingest, store, and disseminate NWS multi-sensor precipitation estimates (MPE). As a pilot project of the Integrated Water Resources Science and Services (IWRSS) initiative, this testbed uses a Standard Query Language (SQL) server to maintain a full archive of current and historic MPE values within the WGRFC service area. These time series values are made available for public access as web services in the standard WaterML format. Having this volume of information maintained in a comprehensive database now allows the use of relational analysis capabilities within SQL to leverage these multi-sensor precipitation values and produce a valuable derivative product. The area of focus for this study is North Texas and will utilize values that originated from the West Gulf River Forecast Center (WGRFC); one of three River Forecast Centers currently represented in the holdings of this data system. Over the past two decades, NEXRAD radar has dramatically improved the ability to record rainfall. The resulting hourly MPE values, distributed over an approximate 4 km by 4 km grid, are considered by the NWS to be the "best estimate" of rainfall. The data server provides an accepted standard interface for internet access to the largest time-series dataset of NEXRAD based MPE values ever assembled. An automated script has been written to search and extract storms over the 18 year period of record from the contents of this massive historical precipitation database. Not only can it extract site-specific storms, but also duration-specific storms and

  7. Error Estimation for the Linearized Auto-Localization Algorithm

    Directory of Open Access Journals (Sweden)

    Fernando Seco

    2012-02-01

    Full Text Available The Linearized Auto-Localization (LAL algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs, using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL, the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.

  8. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    Science.gov (United States)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

  9. Estimating and forecasting the precipitable water vapor from GOES satellite data at high altitude sites

    Science.gov (United States)

    Marín, Julio C.; Pozo, Diana; Curé, Michel

    2015-01-01

    In this work, we describe a method to estimate the precipitable water vapor (PWV) from Geostationary Observational Environmental Satellite (GOES) data at high altitude sites. The method was applied at Atacama Pathfinder Experiment (APEX) and Cerro Toco sites, located above 5000 m altitude in the Chajnantor plateau, in the north of Chile. It was validated using GOES-12 satellite data over the range 0-1.2 mm since submillimeter/millimeter astronomical observations are only useful within this PWV range. The PWV estimated from GOES and the Final Analyses (FNL) at APEX for 2007 and 2009 show root mean square error values of 0.23 mm and 0.36 mm over the ranges 0-0.4 mm and 0.4-1.2 mm, respectively. However, absolute relative errors of 51% and 33% were shown over these PWV ranges, respectively. We recommend using high-resolution thermodynamic profiles from the Global Forecast System (GFS) model to estimate the PWV from GOES data since they are available every three hours and at an earlier time than the FNL data. The estimated PWV from GOES/GFS agrees better with the observed PWV at both sites during night time. The largest errors are shown during daytime. Short-term PWV forecasts were implemented at both sites, applying a simple persistence method to the PWV estimated from GOES/GFS. The 12 h and 24 h PWV forecasts evaluated from August to October 2009 indicates that 25% of them show a very good agreement with observations whereas 50% of them show reasonably good agreement with observations. Transmission uncertainties calculated for PWV estimations and forecasts over the studied sites are larger over the range 0-0.4 mm than over the range 0.4-1.2 mm. Thus, the method can be used over the latter interval with more confidence.

  10. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2014-10-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

  11. Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

    Science.gov (United States)

    Tan, Elcin

    A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

  12. Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast

    Directory of Open Access Journals (Sweden)

    Y. H. Lee

    2006-12-01

    Full Text Available In this study, optimal parameter estimations are performed for both physical and computational parameters in a mesoscale meteorological model, and their impacts on the quantitative precipitation forecasting (QPF are assessed for a heavy rainfall case occurred at the Korean Peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when the two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

  13. An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

    DEFF Research Database (Denmark)

    He, Xin; Vejen, Flemming; Stisen, Simon

    2011-01-01

    of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

  14. Improving Radar Quantitative Precipitation Estimation over Complex Terrain in the San Francisco Bay Area

    Science.gov (United States)

    Cifelli, R.; Chen, H.; Chandrasekar, V.

    2017-12-01

    A recent study by the State of California's Department of Water Resources has emphasized that the San Francisco Bay Area is at risk of catastrophic flooding. Therefore, accurate quantitative precipitation estimation (QPE) and forecast (QPF) are critical for protecting life and property in this region. Compared to rain gauge and meteorological satellite, ground based radar has shown great advantages for high-resolution precipitation observations in both space and time domain. In addition, the polarization diversity shows great potential to characterize precipitation microphysics through identification of different hydrometeor types and their size and shape information. Currently, all the radars comprising the U.S. National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) network are operating in dual-polarization mode. Enhancement of QPE is one of the main considerations of the dual-polarization upgrade. The San Francisco Bay Area is covered by two S-band WSR-88D radars, namely, KMUX and KDAX. However, in complex terrain like the Bay Area, it is still challenging to obtain an optimal rainfall algorithm for a given set of dual-polarization measurements. In addition, the accuracy of rain rate estimates is contingent on additional factors such as bright band contamination, vertical profile of reflectivity (VPR) correction, and partial beam blockages. This presentation aims to improve radar QPE for the Bay area using advanced dual-polarization rainfall methodologies. The benefit brought by the dual-polarization upgrade of operational radar network is assessed. In addition, a pilot study of gap fill X-band radar performance is conducted in support of regional QPE system development. This paper also presents a detailed comparison between the dual-polarization radar-derived rainfall products with various operational products including the NSSL's Multi-Radar/Multi-Sensor (MRMS) system. Quantitative evaluation of various rainfall products is achieved

  15. Estimating spatially and temporally varying recharge and runoff from precipitation and urban irrigation in the Los Angeles Basin, California

    Science.gov (United States)

    Hevesi, Joseph A.; Johnson, Tyler D.

    2016-10-17

    A daily precipitation-runoff model, referred to as the Los Angeles Basin watershed model (LABWM), was used to estimate recharge and runoff for a 5,047 square kilometer study area that included the greater Los Angeles area and all surface-water drainages potentially contributing recharge to a 1,450 square kilometer groundwater-study area underlying the greater Los Angeles area, referred to as the Los Angeles groundwater-study area. The recharge estimates for the Los Angeles groundwater-study area included spatially distributed recharge in response to the infiltration of precipitation, runoff, and urban irrigation, as well as mountain-front recharge from surface-water drainages bordering the groundwater-study area. The recharge and runoff estimates incorporated a new method for estimating urban irrigation, consisting of residential and commercial landscape watering, based on land use and the percentage of pervious land area.The LABWM used a 201.17-meter gridded discretization of the study area to represent spatially distributed climate and watershed characteristics affecting the surface and shallow sub-surface hydrology for the Los Angeles groundwater study area. Climate data from a local network of 201 monitoring sites and published maps of 30-year-average monthly precipitation and maximum and minimum air temperature were used to develop the climate inputs for the LABWM. Published maps of land use, land cover, soils, vegetation, and surficial geology were used to represent the physical characteristics of the LABWM area. The LABWM was calibrated to available streamflow records at six streamflow-gaging stations.Model results for a 100-year target-simulation period, from water years 1915 through 2014, were used to quantify and evaluate the spatial and temporal variability of water-budget components, including evapotranspiration (ET), recharge, and runoff. The largest outflow of water from the LABWM was ET; the 100-year average ET rate of 362 millimeters per year (mm

  16. The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-05-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective

  17. Estimation and prediction under local volatility jump-diffusion model

    Science.gov (United States)

    Kim, Namhyoung; Lee, Younhee

    2018-02-01

    Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

  18. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Science.gov (United States)

    Zhang, Ying; Moges, Semu; Block, Paul

    2018-01-01

    Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  19. Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

    Science.gov (United States)

    Meneghini, R.; Jones, J. A.; Iguchi, T.; Okamoto, K.; Liao, L.; Busalacchi, Antonio J. (Technical Monitor)

    2000-01-01

    The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by

  20. Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar

    Science.gov (United States)

    Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.

    2013-09-01

    This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.

  1. Correlation Dimension Estimates of Global and Local Temperature Data.

    Science.gov (United States)

    Wang, Qiang

    1995-11-01

    The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

  2. Quantitative precipitation estimation in complex orography using quasi-vertical profiles of dual polarization radar variables

    Science.gov (United States)

    Montopoli, Mario; Roberto, Nicoletta; Adirosi, Elisa; Gorgucci, Eugenio; Baldini, Luca

    2017-04-01

    Weather radars are nowadays a unique tool to estimate quantitatively the rain precipitation near the surface. This is an important task for a plenty of applications. For example, to feed hydrological models, mitigate the impact of severe storms at the ground using radar information in modern warning tools as well as aid the validation studies of satellite-based rain products. With respect to the latter application, several ground validation studies of the Global Precipitation Mission (GPM) products have recently highlighted the importance of accurate QPE from ground-based weather radars. To date, a plenty of works analyzed the performance of various QPE algorithms making use of actual and synthetic experiments, possibly trained by measurement of particle size distributions and electromagnetic models. Most of these studies support the use of dual polarization variables not only to ensure a good level of radar data quality but also as a direct input in the rain estimation equations. Among others, one of the most important limiting factors in radar QPE accuracy is the vertical variability of particle size distribution that affects at different levels, all the radar variables acquired as well as rain rates. This is particularly impactful in mountainous areas where the altitudes of the radar sampling is likely several hundred of meters above the surface. In this work, we analyze the impact of the vertical profile variations of rain precipitation on several dual polarization radar QPE algorithms when they are tested a in complex orography scenario. So far, in weather radar studies, more emphasis has been given to the extrapolation strategies that make use of the signature of the vertical profiles in terms of radar co-polar reflectivity. This may limit the use of the radar vertical profiles when dual polarization QPE algorithms are considered because in that case all the radar variables used in the rain estimation process should be consistently extrapolated at the surface

  3. Local gradient estimate for harmonic functions on Finsler manifolds

    OpenAIRE

    Xia, Chao

    2013-01-01

    In this paper, we prove the local gradient estimate for harmonic functions on complete, noncompact Finsler measure spaces under the condition that the weighted Ricci curvature has a lower bound. As applications, we obtain Liouville type theorem on Finsler manifolds with nonnegative Ricci curvature.

  4. Local polynomial Whittle estimation of perturbed fractional processes

    DEFF Research Database (Denmark)

    Frederiksen, Per; Nielsen, Frank; Nielsen, Morten Ørregaard

    We propose a semiparametric local polynomial Whittle with noise (LPWN) estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the spectrum of the perturbation as well as that of the short-memory component...... of the signal by two separate polynomials. Including these polynomials we obtain a reduction in the order of magnitude of the bias, but also in‡ate the asymptotic variance of the long memory estimate by a multiplicative constant. We show that the estimator is consistent for d 2 (0; 1), asymptotically normal...... for d ε (0, 3/4), and if the spectral density is infinitely smooth near frequency zero, the rate of convergence can become arbitrarily close to the parametric rate, pn. A Monte Carlo study reveals that the LPWN estimator performs well in the presence of a serially correlated perturbation term...

  5. Impact of the ongoing Amazonian deforestation on local precipitation: A GCM simulation study

    Science.gov (United States)

    Walker, G. K.; Sud, Y. C.; Atlas, R.

    1995-01-01

    Numerical simulation experiments were conducted to delineate the influence of in situ deforestation data on episodic rainfall by comparing two ensembles of five 5-day integrations performed with a recent version of the Goddard Laboratory for Atmospheres General Circulation Model (GCM) that has a simple biosphere model (SiB). The first set, called control cases, used the standard SiB vegetation cover (comprising 12 biomes) and assumed a fully forested Amazonia, while the second set, called deforestation cases, distinguished the partially deforested regions of Amazonia as savanna. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both sets of integrations. The differential analyses of these five cases show the following local effects of deforestation. (1) A discernible decrease in evapotranspiration of about 0.80 mm/d (roughly 18%) that is quite robust in the averages for 1-, 2-, and 5-day forecasts. (2) A decrease in precipitation of about 1.18 mm/d (roughly 8%) that begins to emerge even in 1-2 day averages and exhibits complex evolution that extends downstream with the winds. (3) A significant decrease in the surface drag force (as a consequence of reduced surface roughness of deforested regions) that, in turn, affects the dynamical structure of moisture convergence and circulation. The surface winds increase significantly during the first day, and thereafter the increase is well maintained even in the 2- and 5-day averages.

  6. Anisotropic localized surface plasmon resonances in CuS nanoplates prepared by size-selective precipitation

    Science.gov (United States)

    Hamanaka, Yasushi; Yamada, Kaoru; Hirose, Tatsunori; Kuzuya, Toshihiro

    2018-05-01

    CuS nanoplates were synthesized by a colloidal method and separated into four fractions of nanoplates with different aspect ratios by a size-selective precipitation. In addition to a strong near infrared absorption band ascribed to the in-plane mode of the localized surface plasmon resonance (LSPR), we found a weak absorption band on the high frequency tail of the in-plane LSPR band. The frequency of the weak absorption band was almost constant and independent of the aspect ratio, while the in-plane LSPR band exhibited a strong aspect ratio dependence. These characteristics suggested that the weak absorption band is ascribed to the out-of-plane LSPR. Although the out-of-plane LSPR was expected to be difficult to observe for CuS nanoplates due to its low intensity and overlap with the strong in-plane resonance, we could successfully identify the out-of-plane mode by reducing the width of the size distribution and spectral broadening caused thereby.

  7. Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

    Science.gov (United States)

    Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

    2018-02-01

    Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

  8. ESTIMATION OF PHASE DELAY DUE TO PRECIPITABLE WATER FOR DINSARBASED LAND DEFORMATION MONITORING

    Directory of Open Access Journals (Sweden)

    J. Susaki

    2017-09-01

    Full Text Available In this paper, we present a method for using the estimated precipitable water (PW to mitigate atmospheric phase delay in order to improve the accuracy of land-deformation assessment with differential interferometric synthetic aperture radar (DInSAR. The phase difference obtained from multi-temporal synthetic aperture radar images contains errors of several types, and the atmospheric phase delay can be an obstacle to estimating surface subsidence. In this study, we calculate PW from external meteorological data. Firstly, we interpolate the data with regard to their spatial and temporal resolutions. Then, assuming a range direction between a target pixel and the sensor, we derive the cumulative amount of differential PW at the height of the slant range vector at pixels along that direction. The atmospheric phase delay of each interferogram is acquired by taking a residual after a preliminary determination of the linear deformation velocity and digital elevation model (DEM error, and by applying high-pass temporal and low-pass spatial filters. Next, we estimate a regression model that connects the cumulative amount of PW and the atmospheric phase delay. Finally, we subtract the contribution of the atmospheric phase delay from the phase difference of the interferogram, and determine the linear deformation velocity and DEM error. The experimental results show a consistent relationship between the cumulative amount of differential PW and the atmospheric phase delay. An improvement in land-deformation accuracy is observed at a point at which the deformation is relatively large. Although further investigation is necessary, we conclude at this stage that the proposed approach has the potential to improve the accuracy of the DInSAR technique.

  9. Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

    Science.gov (United States)

    Schroeer, K.; Kirchengast, G.

    2018-06-01

    Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

  10. Investigation of Weather Radar Quantitative Precipitation Estimation Methodologies in Complex Orography

    Directory of Open Access Journals (Sweden)

    Mario Montopoli

    2017-02-01

    Full Text Available Near surface quantitative precipitation estimation (QPE from weather radar measurements is an important task for feeding hydrological models, limiting the impact of severe rain events at the ground as well as aiding validation studies of satellite-based rain products. To date, several works have analyzed the performance of various QPE algorithms using actual and synthetic experiments, possibly trained by measurement of particle size distributions and electromagnetic models. Most of these studies support the use of dual polarization radar variables not only to ensure a good level of data quality but also as a direct input to rain estimation equations. One of the most important limiting factors in radar QPE accuracy is the vertical variability of particle size distribution, which affects all the acquired radar variables as well as estimated rain rates at different levels. This is particularly impactful in mountainous areas, where the sampled altitudes are likely several hundred meters above the surface. In this work, we analyze the impact of the vertical profile variations of rain precipitation on several dual polarization radar QPE algorithms when they are tested in a complex orography scenario. So far, in weather radar studies, more emphasis has been given to the extrapolation strategies that use the signature of the vertical profiles in terms of radar co-polar reflectivity. This may limit the use of the radar vertical profiles when dual polarization QPE algorithms are considered. In that case, all the radar variables used in the rain estimation process should be consistently extrapolated at the surface to try and maintain the correlations among them. To avoid facing such a complexity, especially with a view to operational implementation, we propose looking at the features of the vertical profile of rain (VPR, i.e., after performing the rain estimation. This procedure allows characterization of a single variable (i.e., rain when dealing with

  11. Cooperative Robot Localization Using Event-Triggered Estimation

    Science.gov (United States)

    Iglesias Echevarria, David I.

    It is known that multiple robot systems that need to cooperate to perform certain activities or tasks incur in high energy costs that hinder their autonomous functioning and limit the benefits provided to humans by these kinds of platforms. This work presents a communications-based method for cooperative robot localization. Implementing concepts from event-triggered estimation, used with success in the field of wireless sensor networks but rarely to do robot localization, agents are able to only send measurements to their neighbors when the expected novelty in this information is high. Since all agents know the condition that triggers a measurement to be sent or not, the lack of a measurement is therefore informative and fused into state estimates. In the case agents do not receive either direct nor indirect measurements of all others, the agents employ a covariance intersection fusion rule in order to keep the local covariance error metric bounded. A comprehensive analysis of the proposed algorithm and its estimation performance in a variety of scenarios is performed, and the algorithm is compared to similar cooperative localization approaches. Extensive simulations are performed that illustrate the effectiveness of this method.

  12. Estimating monotonic rates from biological data using local linear regression.

    Science.gov (United States)

    Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

    2017-03-01

    Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

  13. Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

    Science.gov (United States)

    Bera, Maitreyee; Ortel, Terry W.

    2018-01-12

    The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

  14. Estimating preferences for local public services using migration data.

    Science.gov (United States)

    Dahlberg, Matz; Eklöf, Matias; Fredriksson, Peter; Jofre-Monseny, Jordi

    2012-01-01

    Using Swedish micro data, the paper examines the impact of local public services on community choice. The choice of community is modelled as a choice between a discrete set of alternatives. It is found that, given taxes, high spending on child care attracts migrants. Less conclusive results are obtained with respect to the role of spending on education and elderly care. High local taxes deter migrants. Relaxing the independence of the irrelevant alternatives assumption, by estimating a mixed logit model, has a significant impact on the results.

  15. From neurons to circuits: linear estimation of local field potentials

    Science.gov (United States)

    Rasch, Malte; Logthetis, Nikos K.; Kreiman, Gabriel

    2010-01-01

    Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons. PMID:19889990

  16. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Directory of Open Access Journals (Sweden)

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  17. Quantitative Precipitation Estimation over Ocean Using Bayesian Approach from Microwave Observations during the Typhoon Season

    Directory of Open Access Journals (Sweden)

    Jen-Chi Hu

    2009-01-01

    Full Text Available We have developed a new Bayesian approach to retrieve oceanic rain rate from the Tropical Rainfall Measuring Mission (TRMM Microwave Imager (TMI, with an emphasis on typhoon cases in the West Pacific. Retrieved rain rates are validated with measurements of rain gauges located on Japanese islands. To demonstrate improvement, retrievals are also compared with those from the TRMM/Precipitation Radar (PR, the Goddard Profiling Algorithm (GPROF, and a multi-channel linear regression statistical method (MLRS. We have found that qualitatively, all methods retrieved similar horizontal distributions in terms of locations of eyes and rain bands of typhoons. Quantitatively, our new Bayesian retrievals have the best linearity and the smallest root mean square (RMS error against rain gauge data for 16 typhoon over passes in 2004. The correlation coefficient and RMS of our retrievals are 0.95 and ~2 mm hr-1, respectively. In particular, at heavy rain rates, our Bayesian retrievals out perform those retrieved from GPROF and MLRS. Over all, the new Bayesian approach accurately retrieves surface rain rate for typhoon cases. Ac cu rate rain rate estimates from this method can be assimilated in models to improve forecast and prevent potential damages in Taiwan during typhoon seasons.

  18. On-line estimation of the dissolved zinc concentration during ZnS precipitation in a CSTR

    NARCIS (Netherlands)

    Grootscholten, T.I.M.; Keesman, K.J.; Lens, P.N.L.

    2007-01-01

    Abstract In this paper a method is presented to estimate the reaction term of zinc sulphide precipitation and the zinc concentration in a CSTR, using the read-out signal of a sulphide selective electrode. The reaction between zinc and sulphide is described by a non-linear model and therefore

  19. Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models

    DEFF Research Database (Denmark)

    Borup, Morten; Mikkelsen, Peter Steen; Borup, Morten

    2013-01-01

    When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due...

  20. Modelling and on-line estimation of zinc sulphide precipitation in

    NARCIS (Netherlands)

    Grootscholten, T.I.M.; Keesman, K.J.; Lens, P.N.L.

    2008-01-01

    In this paper the ZnS precipitation in a continuously stirred tank reactor (CSTR) is modelled using mass balances. The dynamics analysis of the model reveals that the ZnS precipitation shows a two time-scales behaviour with inherent numerical stability problems, which therefore needs special

  1. A localized surface plasmon resonance (LSPR) immunosensor for CRP detection using 4-chloro-1-naphtol (4-CN) precipitation

    Science.gov (United States)

    Ha, Su-Ji; Park, Jin-Ho; Byun, Ju-Young; Ahn, Young-Deok; Kim, Min-Gon

    2017-07-01

    In this study, C-reactive protein (CRP) was detected by monitoring of LSPR shift promoted by precipitation of 4-chloro-1-naphthol (4-CN). The precipitation occurred by horseradish peroxide (HRP) catalyst which is modified at CRP-detection antibody utilized in sandwich enzyme-linked immunosorbent assay (ELISA) on gold nano bipyramid (GNBP) substrate. Due to 4-CN precipitates which are located nearby the surface of GNBP, local refractive index (RI) and molecular density were greatly increased. This phenomenon eventually induced strong spectral red-shift of absorption band of GNBP. An excellent linear relationship (R2=0.9895) between the LSPR shift and CRP concentration was obtained in the range from 100 pg/mL to 100 ng/mL and limit of detection (LOD) was reached to 87 pg/mL.

  2. The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

    Science.gov (United States)

    Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

    2018-01-01

    Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

  3. Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

    Science.gov (United States)

    Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

    2018-04-01

    In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

  4. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2018-01-01

    Full Text Available Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS values of up to 0.5 and 33 %, respectively. The general skill (after bias correction of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  5. The effect of a local source on the composition of precipitation in south-central Maine

    Science.gov (United States)

    Scott D. Boyce; Samuel S. Butcher

    1976-01-01

    Bulk precipitation samples were collected from ten sites in south-central Maine during the period 18 June to 30 September 1974. Data from the chemical analyses of the precipitation were used to determine regional deposition patterns of the ionic constituents. Acidic pH values ranging from 3.8 to 5.0 are characteristic of the region, but relatively alkaline pH values of...

  6. Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches

    Science.gov (United States)

    Fehlmann, Michael; Gascón, Estíbaliz; Rohrer, Mario; Schwarb, Manfred; Stoffel, Markus

    2018-05-01

    The snowfall limit has important implications for different hazardous processes associated with prolonged or heavy precipitation such as flash floods, rain-on-snow events and freezing precipitation. To increase preparedness and to reduce risk in such situations, early warning systems are frequently used to monitor and predict precipitation events at different temporal and spatial scales. However, in alpine and pre-alpine valleys, the estimation of the snowfall limit remains rather challenging. In this study, we characterize uncertainties related to snowfall limit for different lead times based on local measurements of a vertically pointing micro rain radar (MRR) and a disdrometer in the Zulg valley, Switzerland. Regarding the monitoring, we show that the interpolation of surface temperatures tends to overestimate the altitude of the snowfall limit and can thus lead to highly uncertain estimates of liquid precipitation in the catchment. This bias is much smaller in the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which integrates surface station and remotely sensed data as well as outputs of a numerical weather prediction model. To reduce systematic error, we perform a bias correction based on local MRR measurements and thereby demonstrate the added value of such measurements for the estimation of liquid precipitation in the catchment. Regarding the nowcasting, we show that the INCA system provides good estimates up to 6 h ahead and is thus considered promising for operational hydrological applications. Finally, we explore the medium-range forecasting of precipitation type, especially with respect to rain-on-snow events. We show for a selected case study that the probability for a certain precipitation type in an ensemble-based forecast is more persistent than the respective type in the high-resolution forecast (HRES) of the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF IFS). In this case study, the

  7. FEH Local: Improving flood estimates using historical data

    Directory of Open Access Journals (Sweden)

    Prosdocimi Ilaria

    2016-01-01

    Full Text Available The traditional approach to design flood estimation (for example, to derive the 100-year flood is to apply a statistical model to time series of peak river flow measured by gauging stations. Such records are typically not very long, for example in the UK only about 10% of the stations have records that are more than 50 years in length. Along-explored way to augment the data available from a gauging station is to derive information about historical flood events and paleo-floods, which can be obtained from careful exploration of archives, old newspapers, flood marks or other signs of past flooding that are still discernible in the catchment, and the history of settlements. The inclusion of historical data in flood frequency estimation has been shown to substantially reduce the uncertainty around the estimated design events and is likely to provide insight into the rarest events which might have pre-dated the relatively short systematic records. Among other things, the FEH Local project funded by the Environment Agency aims to develop methods to easily incorporate historical information into the standard method of statistical flood frequency estimation in the UK. Different statistical estimation procedures are explored, namely maximum likelihood and partial probability weighted moments, and the strengths and weaknesses of each method are investigated. The project assesses the usefulness of historical data and aims to provide practitioners with useful guidelines to indicate in what circumstances the inclusion of historical data is likely to be beneficial in terms of reducing both the bias and the variability of the estimated flood frequency curves. The guidelines are based on the results of a large Monte Carlo simulation study, in which different estimation procedures and different data availability scenarios are studied. The study provides some indication of the situations under which different estimation procedures might give a better performance.

  8. Spatial estimation of mean temperature and precipitation in areas of scarce meteorological information

    Energy Technology Data Exchange (ETDEWEB)

    Gomez, J.D. [Universidad Autonoma Chapingo, Chapingo (Mexico)]. E-mail: dgomez@correo.chapingo.mx; Etchevers, J.D. [Instituto de Recursos Naturales, Colegio de Postgraduados, Montecillo, Edo. de Mexico (Mexico); Monterroso, A.I. [departamento de Suelos, Universidad Autonoma Chapingo, Chapingo (Mexico); Gay, G. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico); Campo, J. [Instituto de Ecologia, Universidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico); Martinez, M. [Instituto de Recursos Naturales, Montecillo, Edo. de Mexico (Mexico)

    2008-01-15

    In regions of complex relief and scarce meteorological information it becomes difficult to implement techniques and models of numerical interpolation to elaborate reliable maps of climatic variables essential for the study of natural resources using the new tools of the geographic information systems. This paper presents a method for estimating annual and monthly mean values of temperature and precipitation, taking elements from simple interpolation methods and complementing them with some characteristics of more sophisticated methods. To determine temperature, simple linear regression equations were generated associating temperature with altitude of weather stations in the study region, which had been previously subdivided in accordance with humidity conditions and then applying such equations to the area's digital elevation model to obtain temperatures. The estimation of precipitation was based on the graphic method through the analysis of the meteorological systems that affect the regions of the study area throughout the year and considering the influence of mountain ridges on the movement of prevailing winds. Weather stations with data in nearby regions were analyzed according to their position in the landscape, exposure to humid winds, and false color associated with vegetation types. Weather station sites were used to reference the amount of rainfall; interpolation was attained using analogies with satellite images of false color to which a model of digital elevation was incorporated to find similar conditions within the study area. [Spanish] En las regiones de relieve complejo y con escasa informacion meteorologica se dificulta la aplicacion de las diferentes tecnicas y modelos de interpolacion numericos para elaborar mapas de variables climaticas confiables, indispensables para realizar estudios de los recursos naturales, con la utilizacion de las nuevas herramientas de los sistemas de informacion geografica. En este trabajo se presenta un metodo para

  9. Estimating drizzle drop size and precipitation rate using two-colour lidar measurements

    Directory of Open Access Journals (Sweden)

    C. D. Westbrook

    2010-06-01

    Full Text Available A method to estimate the size and liquid water content of drizzle drops using lidar measurements at two wavelengths is described. The method exploits the differential absorption of infrared light by liquid water at 905 nm and 1.5 μm, which leads to a different backscatter cross section for water drops larger than ≈50 μm. The ratio of backscatter measured from drizzle samples below cloud base at these two wavelengths (the colour ratio provides a measure of the median volume drop diameter D0. This is a strong effect: for D0=200 μm, a colour ratio of ≈6 dB is predicted. Once D0 is known, the measured backscatter at 905 nm can be used to calculate the liquid water content (LWC and other moments of the drizzle drop distribution.

    The method is applied to observations of drizzle falling from stratocumulus and stratus clouds. High resolution (32 s, 36 m profiles of D0, LWC and precipitation rate R are derived. The main sources of error in the technique are the need to assume a value for the dispersion parameter μ in the drop size spectrum (leading to at most a 35% error in R and the influence of aerosol returns on the retrieval (≈10% error in R for the cases considered here. Radar reflectivities are also computed from the lidar data, and compared to independent measurements from a colocated cloud radar, offering independent validation of the derived drop size distributions.

  10. Ranking GCM Estimates of Twentieth Century Precipitation Seasonality in the Western U.S. and its Influence on Floristic Provinces.

    Science.gov (United States)

    Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Ironside, K.; Cobb, N. S.

    2008-12-01

    Floristic provinces of the western United States (west of 100W) can be segregated into three regions defined by significant seasonal precipitation during the months of: 1) November-March (Mediterranean); 2) July- September (Monsoonal); or, 3) May-June (Rocky Mountain). This third region is best defined by the absence of the late spring-early summer drought that affects regions 1 and 2. Each of these precipitation regimes is characterized by distinct vegetation types and fire seasonality adapted to that particular cycle of seasonal moisture availability and deficit. Further, areas where these regions blend from one to another can support even more complex seasonal patterns and resulting distinctive vegetation types. As a result, modeling the effects of climates on these ecosystems requires confidence that GCMs can at least approximate these sub- continental seasonal precipitation patterns. We evaluated the late Twentieth Century (1950-1999 AD) estimates of annual precipitation seasonality produced by 22 GCMs contained within the IPCC Fourth Assessment (AR4). These modeled estimates were compared to values from the PRISM dataset, extrapolated from station data, over the same historical period for the 3 seasonal periods defined above. The correlations between GCM estimates and PRISM values were ranked using 4 measures: 1) A map pattern relationship based on the correlation coefficient, 2) A map pattern relationship based on the congruence coefficient, 3) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation amounts, and, 4) The ratio of simulated/observed area averaged precipitation based on the seasonal precipitation percentages of the annual total. For each of the four metrics, the rank order of models was very similar. The ranked order of the performance of the different models quantified aspects of the model performance visible in the mapped results. While some models represented the seasonal patterns very well, others

  11. Towards local progression estimation of pulmonary emphysema using CT.

    Science.gov (United States)

    Staring, M; Bakker, M E; Stolk, J; Shamonin, D P; Reiber, J H C; Stoel, B C

    2014-02-01

    Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying linearity assumption

  12. Towards local progression estimation of pulmonary emphysema using CT

    International Nuclear Information System (INIS)

    Staring, M.; Bakker, M. E.; Shamonin, D. P.; Reiber, J. H. C.; Stoel, B. C.; Stolk, J.

    2014-01-01

    Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying

  13. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    Science.gov (United States)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2017-09-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  14. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    Science.gov (United States)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2018-06-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  15. Multilinear approach to the precipitation-lightning relationship: a case study of summer local electrical storms in the northern part of Spain during 2002-2009 period

    Science.gov (United States)

    Herrero, I.; Ezcurra, A.; Areitio, J.; Diaz-Argandoña, J.; Ibarra-Berastegi, G.; Saenz, J.

    2013-11-01

    Storms developed under local instability conditions are studied in the Spanish Basque region with the aim of establishing precipitation-lightning relationships. Those situations may produce, in some cases, flash flood. Data used correspond to daily rain depth (mm) and the number of CG flashes in the area. Rain and lightning are found to be weakly correlated on a daily basis, a fact that seems related to the existence of opposite gradients in their geographical distribution. Rain anomalies, defined as the difference between observed and estimated rain depth based on CG flashes, are analysed by PCA method. Results show a first EOF explaining 50% of the variability that linearly relates the rain anomalies observed each day and that confirms their spatial structure. Based on those results, a multilinear expression has been developed to estimate the rain accumulated daily in the network based on the CG flashes registered in the area. Moreover, accumulates and maximum values of rain are found to be strongly correlated, therefore making the multilinear expression a useful tool to estimate maximum precipitation during those kind of storms.

  16. Three-dimensional nanometer scale analyses of precipitate structures and local compositions in titanium aluminide engineering alloys

    Science.gov (United States)

    Gerstl, Stephan S. A.

    Titanium aluminide (TiAl) alloys are among the fastest developing class of materials for use in high temperature structural applications. Their low density and high strength make them excellent candidates for both engine and airframe applications. Creep properties of TiAl alloys, however, have been a limiting factor in applying the material to a larger commercial market. In this research, nanometer scale compositional and structural analyses of several TiAl alloys, ranging from model Ti-Al-C ternary alloys to putative commercial alloys with 10 components are investigated utilizing three dimensional atom probe (3DAP) and transmission electron microscopies. Nanometer sized borides, silicides, and carbide precipitates are involved in strengthening TiAl alloys, however, chemical partitioning measurements reveal oxygen concentrations up to 14 at. % within the precipitate phases, resulting in the realization of oxycarbide formation contributing to the precipitation strengthening of TiAl alloys. The local compositions of lamellar microstructures and a variety of precipitates in the TiAl system, including boride, silicide, binary carbides, and intermetallic carbides are investigated. Chemical partitioning of the microalloying elements between the alpha2/gamma lamellar phases, and the precipitate/gamma-matrix phases are determined. Both W and Hf have been shown to exhibit a near interfacial excess of 0.26 and 0.35 atoms nm-2 respectively within ca. 7 nm of lamellar interfaces in a complex TiAl alloy. In the case of needle-shaped perovskite Ti3AlC carbide precipitates, periodic domain boundaries are observed 5.3+/-0.8 nm apart along their growth axis parallel to the TiAl[001] crystallographic direction with concomitant composition variations after 24 hrs. at 800°C.

  17. GPS/DR Error Estimation for Autonomous Vehicle Localization.

    Science.gov (United States)

    Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In

    2015-08-21

    Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

  18. GPS/DR Error Estimation for Autonomous Vehicle Localization

    Directory of Open Access Journals (Sweden)

    Byung-Hyun Lee

    2015-08-01

    Full Text Available Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.

  19. Estimation of local rainfall erosivity using artificial neural network

    Directory of Open Access Journals (Sweden)

    Paulo Tarso Sanches Oliveira

    2011-08-01

    Full Text Available The information retrieval of local values of rainfall erosivity is essential for soil loss estimation with the Universal Soil Loss Equation (USLE, and thus is very useful in soil and water conservation planning. In this manner, the objective of this study was to develop an Artificial Neural Network (ANN with the capacity of estimating, with satisfactory accuracy, the rainfall erosivity in any location of the Mato Grosso do Sul state. We used data from rain erosivity, latitude, longitude, altitude of pluviometric and pluviographic stations located in the state to train and test an ANN. After training with various network configurations, we selected the best performance and higher coefficient of determination calculated on the basis of data erosivity of the sample test and the values estimated by ANN. In evaluating the results, the confidence and the agreement indices were used in addition to the coefficient of determination. It was found that it is possible to estimate the rainfall erosivity for any location in the state of Mato Grosso do Sul, in a reliable way, using only data of geographical coordinates and altitude.

  20. Local control on precipitation in a fully coupled climate-hydrology model

    DEFF Research Database (Denmark)

    Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin

    2016-01-01

    simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface...

  1. Increased Rotavirus Prevalence in Diarrheal Outbreak Precipitated by Localized Flooding, Solomon Islands, 2014.

    Science.gov (United States)

    Jones, Forrest K; Ko, Albert I; Becha, Chris; Joshua, Cynthia; Musto, Jennie; Thomas, Sarah; Ronsse, Axelle; Kirkwood, Carl D; Sio, Alison; Aumua, Audrey; Nilles, Eric J

    2016-05-01

    Flooding on 1 of the Solomon Islands precipitated a nationwide epidemic of diarrhea that spread to regions unaffected by flooding and caused >6,000 cases and 27 deaths. Rotavirus was identified in 38% of case-patients tested in the city with the most flooding. Outbreak potential related to weather reinforces the need for global rotavirus vaccination.

  2. Systematical estimation of GPM-based global satellite mapping of precipitation products over China

    Science.gov (United States)

    Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

    2018-03-01

    As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

  3. Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

    Science.gov (United States)

    Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

    2016-12-01

    Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

  4. New 2012 precipitation frequency estimation analysis for Alaska : musings on data used and the final product.

    Science.gov (United States)

    2013-06-01

    The major product of this study was a precipitation frequency atlas for the entire state of Alaska; this atlas is available at : http://dipper.nws.noaa.gov/hdsc/pfds/. The process of contributing to this study provided an opportunity to (1) evaluate ...

  5. A model for estimating understory vegetation response to fertilization and precipitation in loblolly pine plantations

    Science.gov (United States)

    Curtis L. VanderSchaaf; Ryan W. McKnight; Thomas R. Fox; H. Lee Allen

    2010-01-01

    A model form is presented, where the model contains regressors selected for inclusion based on biological rationale, to predict how fertilization, precipitation amounts, and overstory stand density affect understory vegetation biomass. Due to time, economic, and logistic constraints, datasets of large sample sizes generally do not exist for understory vegetation. Thus...

  6. Estimates of run off, evaporation and precipitation for the Bay of Bengal on seasonal basis

    Digital Repository Service at National Institute of Oceanography (India)

    Varkey, M.J.; Sastry, J.S.

    Mean seasonal river discharge rates (R) of the major rivers along the east coast of India, Bangla Desh and Burma; evaporation rates (E) computed for 5 degrees lat-long. Squares from data on heat loss and mean yearly precipitation (P) values at 5...

  7. Precipitation and measurements of precipitation

    NARCIS (Netherlands)

    Schmidt, F.H.; Bruin, H.A.R. de; Attmannspacher, W.; Harrold, T.W.; Kraijenhoff van de Leur, D.A.

    1977-01-01

    In Western Europe, precipitation is normal phenomenon; it is of importance to all aspects of society, particularly to agriculture, in cattle breeding and, of course, it is a subject of hydrological research. Precipitation is an essential part in the hydrological cycle. How disastrous local

  8. Towards local progression estimation of pulmonary emphysema using CT

    Energy Technology Data Exchange (ETDEWEB)

    Staring, M., E-mail: m.staring@lumc.nl; Bakker, M. E.; Shamonin, D. P.; Reiber, J. H. C.; Stoel, B. C. [Department of Radiology, Division of Image Processing, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden (Netherlands); Stolk, J. [Department of Pulmonology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden (Netherlands)

    2014-02-15

    Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying

  9. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  10. Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA

    Directory of Open Access Journals (Sweden)

    Haramis Linn

    2010-03-01

    Full Text Available Abstract Background Models of the effects of environmental factors on West Nile virus disease risk have yielded conflicting outcomes. The role of precipitation has been especially difficult to discern from existing studies, due in part to habitat and behavior characteristics of specific vector species and because of differences in the temporal and spatial scales of the published studies. We used spatial and statistical modeling techniques to analyze and forecast fine scale spatial (2000 m grid and temporal (weekly patterns of West Nile virus mosquito infection relative to changing weather conditions in the urban landscape of the greater Chicago, Illinois, region for the years from 2004 to 2008. Results Increased air temperature was the strongest temporal predictor of increased infection in Culex pipiens and Culex restuans mosquitoes, with cumulative high temperature differences being a key factor distinguishing years with higher mosquito infection and higher human illness rates from those with lower rates. Drier conditions in the spring followed by wetter conditions just prior to an increase in infection were factors in some but not all years. Overall, 80% of the weekly variation in mosquito infection was explained by prior weather conditions. Spatially, lower precipitation was the most important variable predicting stronger mosquito infection; precipitation and temperature alone could explain the pattern of spatial variability better than could other environmental variables (79% explained in the best model. Variables related to impervious surfaces and elevation differences were of modest importance in the spatial model. Conclusion Finely grained temporal and spatial patterns of precipitation and air temperature have a consistent and significant impact on the timing and location of increased mosquito infection in the northeastern Illinois study area. The use of local weather data at multiple monitoring locations and the integration of mosquito

  11. New method to estimate paleoprecipitation using fossil amphibians and reptiles and the middle and late Miocene precipitation gradients in Europe

    Science.gov (United States)

    Böhme, M.; Ilg, A.; Ossig, A.; Küchenhoff, H.

    2006-06-01

    Existing methods for determining paleoprecipitation are subject to large errors (±350 400 mm or more using mammalian proxies), or are restricted to wet climate systems due to their strong facies dependence (paleobotanical proxies). Here we describe a new paleoprecipitation tool based on an indexing of ecophysiological groups within herpetological communities. In recent communities these indices show a highly significant correlation to annual precipitation (r2 = 0.88), and yield paleoprecipitation estimates with average errors of ±250 280 mm. The approach was validated by comparison with published paleoprecipitation estimates from other methods. The method expands the application of paleoprecipitation tools to dry climate systems and in this way contributes to the establishment of a more comprehensive paleoprecipitation database. This method is applied to two high-resolution time intervals from the European Neogene: the early middle Miocene (early Langhian) and the early late Miocene (early Tortonian). The results indicate that both periods show significant meridional precipitation gradients in Europe, these being stronger in the early Langhian (threefold decrease toward the south) than in the early Tortonian (twofold decrease toward the south). This pattern indicates a strengthening of climatic belts during the middle Miocene climatic optimum due to Southern Hemisphere cooling and an increased contribution of Arctic low-pressure cells to the precipitation from the late Miocene onward due to Northern Hemisphere cooling.

  12. Estimating Preferences for Treatments in Patients With Localized Prostate Cancer

    International Nuclear Information System (INIS)

    Ávila, Mónica; Becerra, Virginia; Guedea, Ferran; Suárez, José Francisco; Fernandez, Pablo; Macías, Víctor; Mariño, Alfonso

    2015-01-01

    Purpose: Studies of patients' preferences for localized prostate cancer treatments have assessed radical prostatectomy and external radiation therapy, but none of them has evaluated brachytherapy. The aim of our study was to assess the preferences and willingness to pay of patients with localized prostate cancer who had been treated with radical prostatectomy, external radiation therapy, or brachytherapy, and their related urinary, sexual, and bowel side effects. Methods and Materials: This was an observational, prospective cohort study with follow-up until 5 years after treatment. A total of 704 patients with low or intermediate risk localized prostate cancer were consecutively recruited from 2003 to 2005. The estimation of preferences was conducted using time trade-off, standard gamble, and willingness-to-pay methods. Side effects were measured with the Expanded Prostate Index Composite (EPIC), a prostate cancer-specific questionnaire. Tobit models were constructed to assess the impact of treatment and side effects on patients' preferences. Propensity score was applied to adjust for treatment selection bias. Results: Of the 580 patients reporting preferences, 165 were treated with radical prostatectomy, 152 with external radiation therapy, and 263 with brachytherapy. Both time trade-off and standard gamble results indicated that the preferences of patients treated with brachytherapy were 0.06 utilities higher than those treated with radical prostatectomy (P=.01). Similarly, willingness-to-pay responses showed a difference of €57/month (P=.004) between these 2 treatments. Severe urinary incontinence presented an independent impact on the preferences elicited (P<.05), whereas no significant differences were found by bowel and sexual side effects. Conclusions: Our findings indicate that urinary incontinence is the side effect with the highest impact on preferences and that brachytherapy and external radiation therapy are more valued than radical

  13. Estimating Preferences for Treatments in Patients With Localized Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Ávila, Mónica [Health Services Research Unit, IMIM (Hospital del Mar Medical Research Institute), Barcelona (Spain); CIBER en Epidemiología y Salud Pública (CIBERESP) (Spain); Universitat Pompeu Fabra, Barcelona (Spain); Becerra, Virginia [Health Services Research Unit, IMIM (Hospital del Mar Medical Research Institute), Barcelona (Spain); Guedea, Ferran [Servicio de Oncología Radioterápica, Institut Català d' Oncologia, L' Hospitalet de Llobregat (Spain); Suárez, José Francisco [Servicio de Urología, Hospital Universitari de Bellvitge, L' Hospitalet de Llobregat (Spain); Fernandez, Pablo [Servicio de Oncología Radioterápica, Instituto Oncológico de Guipúzcoa, San Sebastián (Spain); Macías, Víctor [Servicio de Oncología Radioterápica, Hospital Clínico Universitario de Salamanca, Salamanca (Spain); Servicio de Oncología Radioterápica, Institut Oncologic del Valles-Hospital General de Catalunya, Sant Cugat del Vallès (Spain); Mariño, Alfonso [Servicio de Oncología Radioterápica, Centro Oncológico de Galicia, A Coruña (Spain); and others

    2015-02-01

    Purpose: Studies of patients' preferences for localized prostate cancer treatments have assessed radical prostatectomy and external radiation therapy, but none of them has evaluated brachytherapy. The aim of our study was to assess the preferences and willingness to pay of patients with localized prostate cancer who had been treated with radical prostatectomy, external radiation therapy, or brachytherapy, and their related urinary, sexual, and bowel side effects. Methods and Materials: This was an observational, prospective cohort study with follow-up until 5 years after treatment. A total of 704 patients with low or intermediate risk localized prostate cancer were consecutively recruited from 2003 to 2005. The estimation of preferences was conducted using time trade-off, standard gamble, and willingness-to-pay methods. Side effects were measured with the Expanded Prostate Index Composite (EPIC), a prostate cancer-specific questionnaire. Tobit models were constructed to assess the impact of treatment and side effects on patients' preferences. Propensity score was applied to adjust for treatment selection bias. Results: Of the 580 patients reporting preferences, 165 were treated with radical prostatectomy, 152 with external radiation therapy, and 263 with brachytherapy. Both time trade-off and standard gamble results indicated that the preferences of patients treated with brachytherapy were 0.06 utilities higher than those treated with radical prostatectomy (P=.01). Similarly, willingness-to-pay responses showed a difference of €57/month (P=.004) between these 2 treatments. Severe urinary incontinence presented an independent impact on the preferences elicited (P<.05), whereas no significant differences were found by bowel and sexual side effects. Conclusions: Our findings indicate that urinary incontinence is the side effect with the highest impact on preferences and that brachytherapy and external radiation therapy are more valued than radical

  14. Quantitative precipitation estimation based on high-resolution numerical weather prediction and data assimilation with WRF – a performance test

    Directory of Open Access Journals (Sweden)

    Hans-Stefan Bauer

    2015-04-01

    Full Text Available Quantitative precipitation estimation and forecasting (QPE and QPF are among the most challenging tasks in atmospheric sciences. In this work, QPE based on numerical modelling and data assimilation is investigated. Key components are the Weather Research and Forecasting (WRF model in combination with its 3D variational assimilation scheme, applied on the convection-permitting scale with sophisticated model physics over central Europe. The system is operated in a 1-hour rapid update cycle and processes a large set of in situ observations, data from French radar systems, the European GPS network and satellite sensors. Additionally, a free forecast driven by the ECMWF operational analysis is included as a reference run representing current operational precipitation forecasting. The verification is done both qualitatively and quantitatively by comparisons of reflectivity, accumulated precipitation fields and derived verification scores for a complex synoptic situation that developed on 26 and 27 September 2012. The investigation shows that even the downscaling from ECMWF represents the synoptic situation reasonably well. However, significant improvements are seen in the results of the WRF QPE setup, especially when the French radar data are assimilated. The frontal structure is more defined and the timing of the frontal movement is improved compared with observations. Even mesoscale band-like precipitation structures on the rear side of the cold front are reproduced, as seen by radar. The improvement in performance is also confirmed by a quantitative comparison of the 24-hourly accumulated precipitation over Germany. The mean correlation of the model simulations with observations improved from 0.2 in the downscaling experiment and 0.29 in the assimilation experiment without radar data to 0.56 in the WRF QPE experiment including the assimilation of French radar data.

  15. Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

    2015-12-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

  16. Search-free license plate localization based on saliency and local variance estimation

    Science.gov (United States)

    Safaei, Amin; Tang, H. L.; Sanei, S.

    2015-02-01

    In recent years, the performance and accuracy of automatic license plate number recognition (ALPR) systems have greatly improved, however the increasing number of applications for such systems have made ALPR research more challenging than ever. The inherent computational complexity of search dependent algorithms remains a major problem for current ALPR systems. This paper proposes a novel search-free method of localization based on the estimation of saliency and local variance. Gabor functions are then used to validate the choice of candidate license plate. The algorithm was applied to three image datasets with different levels of complexity and the results compared with a number of benchmark methods, particularly in terms of speed. The proposed method outperforms the state of the art methods and can be used for real time applications.

  17. Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation

    Science.gov (United States)

    Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.

    2012-04-01

    The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.

  18. Deriving local demand for stumpage from estimates of regional supply and demand.

    Science.gov (United States)

    Kent P. Connaughton; Gerard A. Majerus; David H. Jackson

    1989-01-01

    The local (Forest-level or local-area) demand for stumpage can be derived from estimates of regional supply and demand. The derivation of local demand is justified when the local timber economy is similar to the regional timber economy; a simple regression of local on nonlocal prices can be used as an empirical test of similarity between local and regional economies....

  19. Comparing the impact of time displaced and biased precipitation estimates for online updated urban runoff models.

    Science.gov (United States)

    Borup, Morten; Grum, Morten; Mikkelsen, Peter Steen

    2013-01-01

    When an online runoff model is updated from system measurements, the requirements of the precipitation input change. Using rain gauge data as precipitation input there will be a displacement between the time when the rain hits the gauge and the time where the rain hits the actual catchment, due to the time it takes for the rain cell to travel from the rain gauge to the catchment. Since this time displacement is not present for system measurements the data assimilation scheme might already have updated the model to include the impact from the particular rain cell when the rain data is forced upon the model, which therefore will end up including the same rain twice in the model run. This paper compares forecast accuracy of updated models when using time displaced rain input to that of rain input with constant biases. This is done using a simple time-area model and historic rain series that are either displaced in time or affected with a bias. The results show that for a 10 minute forecast, time displacements of 5 and 10 minutes compare to biases of 60 and 100%, respectively, independent of the catchments time of concentration.

  20. Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution vs. long-range transported dust

    Science.gov (United States)

    Fan, J.; Leung, L. R.; DeMott, P. J.; Comstock, J. M.; Singh, B.; Rosenfeld, D.; Tomlinson, J. M.; White, A.; Prather, K. A.; Minnis, P.; Ayers, J. K.; Min, Q.

    2013-07-01

    Mineral dust aerosols often observed over California in winter/spring, associated with long-range transport from Asia and Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model, to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases with contrasting meteorology and cloud dynamics that occurred on 16 February (FEB16) and 2 March (MAR02) from the CalWater 2011 field campaign. In both cases, observations show the presence of dust or dust/biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust/biological aerosol layers increase the accumulated precipitation by 10-20% from the Central Valley to the Sierra Nevada Mountains for both FEB16 and MAR02 due to a 40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by few percent due to increased snow formation when dust is present but reduces precipitation by 5-8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology including the strength of the Sierra Barrier Jet, and cloud dynamics. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for

  1. Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution versus long-range transported dust

    Science.gov (United States)

    Fan, J.; Leung, L. R.; DeMott, P. J.; Comstock, J. M.; Singh, B.; Rosenfeld, D.; Tomlinson, J. M.; White, A.; Prather, K. A.; Minnis, P.; Ayers, J. K.; Min, Q.

    2014-01-01

    Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and the Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model in order to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases (from the CalWater 2011 field campaign) with contrasting meteorology and cloud dynamics that occurred on 16 February (FEB16) and 2 March (MAR02). In both cases, observations show the presence of dust and biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust and biological aerosol layers increase the accumulated precipitation by 10-20% from the Central Valley to the Sierra Nevada for both FEB16 and MAR02 due to a ~40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by a few percent due to increased snow formation when dust is present, but reduces precipitation by 5-8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology, including cloud dynamics and the strength of the Sierra Barrier Jet. This study further underscores the importance of the interactions between local pollution, dust, and environmental

  2. Estimation of trace metal contents in locally-baked breads

    International Nuclear Information System (INIS)

    Khalid, N.; Rehman, S.

    2013-01-01

    In order to establish base line levels, estimation of some essential trace metals (Cu, Fe, Mn and Zn) has been conducted in four brands of fifteen locally baked breads of Rawalpindi /Islamabad area employing Atomic Absorption Spectrophotometry (AAS). The samples were digested in a mixture of nitric acid and perchloric acid and the analysis was done with air-acetylene flame. The reliability of the procedure employed was verify by analyzing Standard Reference Material, i.e., wheat flour (NBS-SRM-1567) for its Cu, Fe, Mn and Zn contents which were in good agreement with the certified values. The results revealed that brown breads contained higher amount of Fe 177.3 micro g g/sup -1/and Zn 19.27 micro g g/sup -1/while levels of Cu 21.90 micro g g/-sup 1/was found higher in the samples of plain bread. The determined metal concentrations in the bread samples were compared with the reported values for other countries. The effect of kneading/baking/slicing processes on the concentration levels of these metals was also studied. The daily intake of these metals through this source was calculated and compared with the recommended dietary allowance. (author)

  3. CMORPH 8 Km: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors...

  4. Comparison Of Quantitative Precipitation Estimates Derived From Rain Gauge And Radar Derived Algorithms For Operational Flash Flood Support.

    Science.gov (United States)

    Streubel, D. P.; Kodama, K.

    2014-12-01

    To provide continuous flash flood situational awareness and to better differentiate severity of ongoing individual precipitation events, the National Weather Service Research Distributed Hydrologic Model (RDHM) is being implemented over Hawaii and Alaska. In the implementation process of RDHM, three gridded precipitation analyses are used as forcing. The first analysis is a radar only precipitation estimate derived from WSR-88D digital hybrid reflectivity, a Z-R relationship and aggregated into an hourly ¼ HRAP grid. The second analysis is derived from a rain gauge network and interpolated into an hourly ¼ HRAP grid using PRISM climatology. The third analysis is derived from a rain gauge network where rain gauges are assigned static pre-determined weights to derive a uniform mean areal precipitation that is applied over a catchment on a ¼ HRAP grid. To assess the effect of different QPE analyses on the accuracy of RDHM simulations and to potentially identify a preferred analysis for operational use, each QPE was used to force RDHM to simulate stream flow for 20 USGS peak flow events. An evaluation of the RDHM simulations was focused on peak flow magnitude, peak flow timing, and event volume accuracy to be most relevant for operational use. Results showed RDHM simulations based on the observed rain gauge amounts were more accurate in simulating peak flow magnitude and event volume relative to the radar derived analysis. However this result was not consistent for all 20 events nor was it consistent for a few of the rainfall events where an annual peak flow was recorded at more than one USGS gage. Implications of this indicate that a more robust QPE forcing with the inclusion of uncertainty derived from the three analyses may provide a better input for simulating extreme peak flow events.

  5. Skill Assessment of An Hybrid Technique To Estimate Quantitative Precipitation Forecast For Galicia (nw Spain)

    Science.gov (United States)

    Lage, A.; Taboada, J. J.

    Precipitation is the most obvious of the weather elements in its effects on normal life. Numerical weather prediction (NWP) is generally used to produce quantitative precip- itation forecast (QPF) beyond the 1-3 h time frame. These models often fail to predict small-scale variations of rain because of spin-up problems and their coarse spatial and temporal resolution (Antolik, 2000). Moreover, there are some uncertainties about the behaviour of the NWP models in extreme situations (de Bruijn and Brandsma, 2000). Hybrid techniques, combining the benefits of NWP and statistical approaches in a flexible way, are very useful to achieve a good QPF. In this work, a new technique of QPF for Galicia (NW of Spain) is presented. This region has a percentage of rainy days per year greater than 50% with quantities that may cause floods, with human and economical damages. The technique is composed of a NWP model (ARPS) and a statistical downscaling process based on an automated classification scheme of at- mospheric circulation patterns for the Iberian Peninsula (J. Ribalaygua and R. Boren, 1995). Results show that QPF for Galicia is improved using this hybrid technique. [1] Antolik, M.S. 2000 "An Overview of the National Weather Service's centralized statistical quantitative precipitation forecasts". Journal of Hydrology, 239, pp:306- 337. [2] de Bruijn, E.I.F and T. Brandsma "Rainfall prediction for a flooding event in Ireland caused by the remnants of Hurricane Charley". Journal of Hydrology, 239, pp:148-161. [3] Ribalaygua, J. and Boren R. "Clasificación de patrones espaciales de precipitación diaria sobre la España Peninsular". Informes N 3 y 4 del Servicio de Análisis e Investigación del Clima. Instituto Nacional de Meteorología. Madrid. 53 pp.

  6. Local and regional factors affecting the chemistry of precipitation in the spanish basque country

    International Nuclear Information System (INIS)

    Ezcurra, A.; Durana, N.; Casado, H.; Lacaux, J.P.; Pham Van Dinh; Garcia, C.

    1991-01-01

    The study deals with near 300 rain events sampled by means of a network of five automatic devices operating from January 1986 to November 1988. The results show that, on a local-scale, the rain chemistry is affected by the marine source of gases and particles. On a regional-scale, values of pH ranging from 5.5 to 4.8 are noticed. The acidity of rain has an anthropogenic origin that is mainly linked to the NO 3 - content. The acidity is reinforced by air flow from continental Europe. By contrast, rain water with a basic character is related to the air fluxes from Southern Spain that increase the rain content in Ca 2+ [fr

  7. Enhancing Global Land Surface Hydrology Estimates from the NASA MERRA Reanalysis Using Precipitation Observations and Model Parameter Adjustments

    Science.gov (United States)

    Reichle, Rolf; Koster, Randal; DeLannoy, Gabrielle; Forman, Barton; Liu, Qing; Mahanama, Sarith; Toure, Ally

    2011-01-01

    The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides. in addition to atmospheric fields. global estimates of soil moisture, latent heat flux. snow. and runoff for J 979-present. This study introduces a supplemental and improved set of land surface hydrological fields ('MERRA-Land') generated by replaying a revised version of the land component of the MERRA system. Specifically. the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameters in the rainfall interception model, changes that effectively correct for known limitations in the MERRA land surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim reanalysis. MERRA-Land and ERA-Interim root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 15 basins in the western US) of MERRA and MERRA-Land is typically higher than that of ERA-Interim. With a few exceptions. the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using '\\-tERRA output for land surface hydrological studies.

  8. Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution vs. long-range transported dust

    OpenAIRE

    J. Fan; L. R. Leung; P. J. DeMott; J. M. Comstock; B. Singh; D. Rosenfeld; J. M. Tomlinson; A. White; K. A. Prather; P. Minnis; J. K. Ayers; Q. Min

    2013-01-01

    Mineral dust aerosols often observed over California in winter/spring, associated with long-range transport from Asia and Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical mode...

  9. Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution versus long-range transported dust

    OpenAIRE

    Fan, J.; Leung, L. R.; DeMott, P. J.; Comstock, J. M.; Singh, B.; Rosenfeld, D.; Tomlinson, J. M.; White, A.; Prather, K. A.; Minnis, P.; Ayers, J. K.; Min, Q.

    2014-01-01

    Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and the Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical mod...

  10. EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

    Directory of Open Access Journals (Sweden)

    J. C. Bergès

    2010-01-01

    Full Text Available This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

  11. Evaluation of two "integrated" polarimetric Quantitative Precipitation Estimation (QPE) algorithms at C-band

    Science.gov (United States)

    Tabary, Pierre; Boumahmoud, Abdel-Amin; Andrieu, Hervé; Thompson, Robert J.; Illingworth, Anthony J.; Le Bouar, Erwan; Testud, Jacques

    2011-08-01

    SummaryTwo so-called "integrated" polarimetric rate estimation techniques, ZPHI ( Testud et al., 2000) and ZZDR ( Illingworth and Thompson, 2005), are evaluated using 12 episodes of the year 2005 observed by the French C-band operational Trappes radar, located near Paris. The term "integrated" means that the concentration parameter of the drop size distribution is assumed to be constant over some area and the algorithms retrieve it using the polarimetric variables in that area. The evaluation is carried out in ideal conditions (no partial beam blocking, no ground-clutter contamination, no bright band contamination, a posteriori calibration of the radar variables ZH and ZDR) using hourly rain gauges located at distances less than 60 km from the radar. Also included in the comparison, for the sake of benchmarking, is a conventional Z = 282 R1.66 estimator, with and without attenuation correction and with and without adjustment by rain gauges as currently done operationally at Météo France. Under those ideal conditions, the two polarimetric algorithms, which rely solely on radar data, appear to perform as well if not better, pending on the measurements conditions (attenuation, rain rates, …), than the conventional algorithms, even when the latter take into account rain gauges through the adjustment scheme. ZZDR with attenuation correction is the best estimator for hourly rain gauge accumulations lower than 5 mm h -1 and ZPHI is the best one above that threshold. A perturbation analysis has been conducted to assess the sensitivity of the various estimators with respect to biases on ZH and ZDR, taking into account the typical accuracy and stability that can be reasonably achieved with modern operational radars these days (1 dB on ZH and 0.2 dB on ZDR). A +1 dB positive bias on ZH (radar too hot) results in a +14% overestimation of the rain rate with the conventional estimator used in this study (Z = 282R1.66), a -19% underestimation with ZPHI and a +23

  12. Direct estimation of functionals of density operators by local operations and classical communication

    International Nuclear Information System (INIS)

    Alves, Carolina Moura; Horodecki, Pawel; Oi, Daniel K. L.; Kwek, L. C.; Ekert, Artur K.

    2003-01-01

    We present a method of direct estimation of important properties of a shared bipartite quantum state, within the ''distant laboratories'' paradigm, using only local operations and classical communication. We apply this procedure to spectrum estimation of shared states, and locally implementable structural physical approximations to incompletely positive maps. This procedure can also be applied to the estimation of channel capacity and measures of entanglement

  13. Estimation of microwave source location in precipitating electron fluxes according to Viking satellite data

    International Nuclear Information System (INIS)

    Khrushchinskij, A.A.; Ostapenko, A.A.; Gustafsson, G.; Eliasson, L.; Sandal, I.

    1989-01-01

    According to the Viking satellite data on electron fluxes in the 0.1-300 keV energy range, the microburst source location is estimated. On the basis of experimental delays in detected peaks in different energy channels and theoretical calculations of these delays within the dipole field model (L∼ 4-5.5), it is shown that the most probable source location is the equatorial region with the centre, 5-10 0 shifted towards the ionosphere

  14. Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

    Science.gov (United States)

    di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

    2009-04-01

    Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is

  15. Improving Weather Radar Precipitation Estimates by Combining two Types of Radars

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    This paper presents a demonstration of how Local Area Weather Radar (LAWR) X-band measurements can be combined with meteorological C–band measurements into a single radar product. For this purpose, a blending method has been developed which combines the strengths of the two radar systems. Combining...... the two radar types achieves a radar product with both long range and high temporal resolution. It is validated that the blended radar product performs better than the individual radars based on ground observations from laser disdrometers. However, the data combination is challenged by lower performance...... of the LAWR. Although both radars benefits from the data combination, it is also found that advection based temporal interpolation is a more favourable method for increasing the temporal resolution of meteorological C–band measurements....

  16. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

  17. Estimates of increased black carbon emissions from electrostatic precipitators during powdered activated carbon injection for mercury emissions control.

    Science.gov (United States)

    Clack, Herek L

    2012-07-03

    The behavior of mercury sorbents within electrostatic precipitators (ESPs) is not well-understood, despite a decade or more of full-scale testing. Recent laboratory results suggest that powdered activated carbon exhibits somewhat different collection behavior than fly ash in an ESP and particulate filters located at the outlet of ESPs have shown evidence of powdered activated carbon penetration during full-scale tests of sorbent injection for mercury emissions control. The present analysis considers a range of assumed differential ESP collection efficiencies for powdered activated carbon as compared to fly ash. Estimated emission rates of submicrometer powdered activated carbon are compared to estimated emission rates of particulate carbon on submicrometer fly ash, each corresponding to its respective collection efficiency. To the extent that any emitted powdered activated carbon exhibits size and optical characteristics similar to black carbon, such emissions could effectively constitute an increase in black carbon emissions from coal-based stationary power generation. The results reveal that even for the low injection rates associated with chemically impregnated carbons, submicrometer particulate carbon emissions can easily double if the submicrometer fraction of the native fly ash has a low carbon content. Increasing sorbent injection rates, larger collection efficiency differentials as compared to fly ash, and decreasing sorbent particle size all lead to increases in the estimated submicrometer particulate carbon emissions.

  18. Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

    Science.gov (United States)

    Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

    2017-09-01

    In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7

  19. Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

    KAUST Repository

    Douglas, Craig C.; Lee, Hyoseop; Sheen, Dongwoo

    2010-01-01

    We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Fréchet derivative when calculating the Jacobian matrix. We analyze

  20. Localization of periodic orbits of polynomial systems by ellipsoidal estimates

    International Nuclear Information System (INIS)

    Starkov, Konstantin E.; Krishchenko, Alexander P.

    2005-01-01

    In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered

  1. A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem

    KAUST Repository

    Delaigle, Aurore

    2009-03-01

    Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.

  2. Localization of periodic orbits of polynomial systems by ellipsoidal estimates

    Energy Technology Data Exchange (ETDEWEB)

    Starkov, Konstantin E. [CITEDI-IPN, Avenue del Parque 1310, Mesa de Otay, Tijuana, BC (Mexico)]. E-mail: konst@citedi.mx; Krishchenko, Alexander P. [Bauman Moscow State Technical University, 2nd Baumanskaya Street, 5, Moscow 105005 (Russian Federation)]. E-mail: apkri@999.ru

    2005-02-01

    In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered.

  3. Improving quantitative precipitation nowcasting with a local ensemble transform Kalman filter radar data assimilation system: observing system simulation experiments

    Directory of Open Access Journals (Sweden)

    Chih-Chien Tsai

    2014-03-01

    Full Text Available This study develops a Doppler radar data assimilation system, which couples the local ensemble transform Kalman filter with the Weather Research and Forecasting model. The benefits of this system to quantitative precipitation nowcasting (QPN are evaluated with observing system simulation experiments on Typhoon Morakot (2009, which brought record-breaking rainfall and extensive damage to central and southern Taiwan. The results indicate that the assimilation of radial velocity and reflectivity observations improves the three-dimensional winds and rain-mixing ratio most significantly because of the direct relations in the observation operator. The patterns of spiral rainbands become more consistent between different ensemble members after radar data assimilation. The rainfall intensity and distribution during the 6-hour deterministic nowcast are also improved, especially for the first 3 hours. The nowcasts with and without radar data assimilation have similar evolution trends driven by synoptic-scale conditions. Furthermore, we carry out a series of sensitivity experiments to develop proper assimilation strategies, in which a mixed localisation method is proposed for the first time and found to give further QPN improvement in this typhoon case.

  4. Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12

    Science.gov (United States)

    Spies, Ryan R.; Over, Thomas M.; Ortel, Terry W.

    2018-05-21

    In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix

  5. Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

    KAUST Repository

    Douglas, Craig C.

    2010-01-01

    We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Fréchet derivative when calculating the Jacobian matrix. We analyze the existence of the Fréchet derivative and its numerical computation. To reduce the computational time of the inverse problem, a GP-GPU environment is considered for parallel computation. Numerical results confirm the validity and efficiency of the proposed method. ©2010 IEEE.

  6. FEH Local: improving flood estimates using historical data

    OpenAIRE

    Prosdocimi, Ilaria; Stewart, Lisa; Faulkner, Duncan; Mitchell, Chrissy

    2016-01-01

    The traditional approach to design flood estimation (for example, to derive the 100-year flood) is to apply a statistical model to time series of peak river flow measured by gauging stations. Such records are typically not very long, for example in the UK only about 10% of the stations have records that are more than 50 years in length. Along-explored way to augment the data available from a gauging station is to derive information about historical flood events and paleo-floods, which can be ...

  7. Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations (PDMMA-USESGO) for Hydrological Modeling — A Case Study over the Tibetan Plateau

    Science.gov (United States)

    Yang, Z.; Hsu, K. L.; Sorooshian, S.; Xu, X.

    2017-12-01

    Precipitation in mountain regions generally occurs with high-frequency-intensity, whereas it is not well-captured by sparsely distributed rain-gauges imposing a great challenge on water management. Satellite-based Precipitation Estimation (SPE) provides global high-resolution alternative data for hydro-climatic studies, but are subject to considerable biases. In this study, a model named PDMMA-USESGO for Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations is developed to support precipitation mapping and hydrological modeling in mountainous catchments. The PDMMA-USESGO framework includes two calculating steps—adjusting SPE biases and merging satellite-gauge estimates—using the quantile mapping approach, a two-dimensional Gaussian weighting scheme (considering elevation effect), and an inverse root mean square error weighting method. The model is applied and evaluated over the Tibetan Plateau (TP) with the PERSIANN-CCS precipitation retrievals (daily, 0.04°×0.04°) and sparse observations from 89 gauges, for the 11-yr period of 2003-2013. To assess the data merging effects on streamflow modeling, a hydrological evaluation is conducted over a watershed in southeast TP based on the Soil and Water Assessment Tool (SWAT). Evaluation results indicate effectiveness of the model in generating high-resolution-accuracy precipitation estimates over mountainous terrain, with the merged estimates (Mer-SG) presenting consistently improved correlation coefficients, root mean square errors and absolute mean biases from original satellite estimates (Ori-CCS). It is found the Mer-SG forced streamflow simulations exhibit great improvements from those simulations using Ori-CCS, with coefficient of determination (R2) and Nash-Sutcliffe efficiency reach to 0.8 and 0.65, respectively. The presented model and case study serve as valuable references for the hydro-climatic applications using remote sensing-gauge information in

  8. Multi-person localization and orientation estimation in volumetric scene reconstructions

    NARCIS (Netherlands)

    Liem, M.C.

    2014-01-01

    Accurate localization of persons and estimation of their pose are important topics in current-day computer vision research. As part of the pose estimation, estimating the body orientation of a person (i.e. rotation around torso major axis) conveys important information about the person's current

  9. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2015-04-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

  10. Empirical model for mean temperature for Indian zone and estimation of precipitable water vapor from ground based GPS measurements

    Directory of Open Access Journals (Sweden)

    C. Suresh Raju

    2007-10-01

    Full Text Available Estimation of precipitable water (PW in the atmosphere from ground-based Global Positioning System (GPS essentially involves modeling the zenith hydrostatic delay (ZHD in terms of surface Pressure (Ps and subtracting it from the corresponding values of zenith tropospheric delay (ZTD to estimate the zenith wet (non-hydrostatic delay (ZWD. This further involves establishing an appropriate model connecting PW and ZWD, which in its simplest case assumed to be similar to that of ZHD. But when the temperature variations are large, for the accurate estimate of PW the variation of the proportionality constant connecting PW and ZWD is to be accounted. For this a water vapor weighted mean temperature (Tm has been defined by many investigations, which has to be modeled on a regional basis. For estimating PW over the Indian region from GPS data, a region specific model for Tm in terms of surface temperature (Ts is developed using the radiosonde measurements from eight India Meteorological Department (IMD stations spread over the sub-continent within a latitude range of 8.5°–32.6° N. Following a similar procedure Tm-based models are also evolved for each of these stations and the features of these site-specific models are compared with those of the region-specific model. Applicability of the region-specific and site-specific Tm-based models in retrieving PW from GPS data recorded at the IGS sites Bangalore and Hyderabad, is tested by comparing the retrieved values of PW with those estimated from the altitude profile of water vapor measured using radiosonde. The values of ZWD estimated at 00:00 UTC and 12:00 UTC are used to test the validity of the models by estimating the PW using the models and comparing it with those obtained from radiosonde data. The region specific Tm-based model is found to be in par with if not better than a

  11. An improved export coefficient model to estimate non-point source phosphorus pollution risks under complex precipitation and terrain conditions.

    Science.gov (United States)

    Cheng, Xian; Chen, Liding; Sun, Ranhao; Jing, Yongcai

    2018-05-15

    To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports and identify sources of pollution. Precipitation and terrain have large impacts on the export and transport of NPS pollutants. We established an improved export coefficient model (IECM) to estimate the amount of agricultural and rural NPS total phosphorus (TP) exported from the Luanhe River Basin (LRB) in northern China. The TP concentrations of rivers from 35 selected catchments in the LRB were used to test the model's explanation capacity and accuracy. The simulation results showed that, in 2013, the average TP export was 57.20 t at the catchment scale. The mean TP export intensity in the LRB was 289.40 kg/km 2 , which was much higher than those of other basins in China. In the LRB topographic regions, the TP export intensity was the highest in the south Yanshan Mountains and was followed by the plain area, the north Yanshan Mountains, and the Bashang Plateau. Among the three pollution categories, the contribution ratios to TP export were, from high to low, the rural population (59.44%), livestock husbandry (22.24%), and land-use types (18.32%). Among all ten pollution sources, the contribution ratios from the rural population (59.44%), pigs (14.40%), and arable land (10.52%) ranked as the top three sources. This study provides information that decision makers and planners can use to develop sustainable measures for the prevention and control of NPS pollution in semi-arid regions.

  12. On-line estimation of the dissolved zinc concentration during ZnS precipitation in a continuous stirred tank reactor (CSTR)

    NARCIS (Netherlands)

    Grootscholten, T.I.M.; Keesman, K.J.; Lens, P.N.L.

    2008-01-01

    In this paper a method is presented to estimate the reaction term of zinc sulphide precipitation and the zinc concentration in a CSTR, using the read-out signal of a sulphide selective electrode. The reaction between zinc and sulphide is described by a non-linear model and therefore classical

  13. Noise measurement from magnitude MRI using local estimates of variance and skewness

    International Nuclear Information System (INIS)

    Rajan, Jeny; Poot, Dirk; Juntu, Jaber; Sijbers, Jan

    2010-01-01

    In this note, we address the estimation of the noise level in magnitude magnetic resonance (MR) images in the absence of background data. Most of the methods proposed earlier exploit the Rayleigh distributed background region in MR images to estimate the noise level. These methods, however, cannot be used for images where no background information is available. In this note, we propose two different approaches for noise level estimation in the absence of the image background. The first method is based on the local estimation of the noise variance using maximum likelihood estimation and the second method is based on the local estimation of the skewness of the magnitude data distribution. Experimental results on synthetic and real MR image datasets show that the proposed estimators accurately estimate the noise level in a magnitude MR image, even without background data. (note)

  14. A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2017-11-01

    Precipitation plays an important role in determining the climate of a region. Precise estimation of precipitation is required to manage and plan water resources, as well as other related applications such as hydrology, climatology, meteorology and agriculture. Time series of hydrologic variables such as precipitation are composed of deterministic and stochastic parts. Despite this fact, the stochastic part of the precipitation data is not usually considered in modeling of precipitation process. As an innovation, the present study introduces three new hybrid models by integrating soft computing methods including multivariate adaptive regression splines (MARS), Bayesian networks (BN) and gene expression programming (GEP) with a time series model, namely generalized autoregressive conditional heteroscedasticity (GARCH) for modeling of the monthly precipitation. For this purpose, the deterministic (obtained by soft computing methods) and stochastic (obtained by GARCH time series model) parts are combined with each other. To carry out this research, monthly precipitation data of Babolsar, Bandar Anzali, Gorgan, Ramsar, Tehran and Urmia stations with different climates in Iran were used during the period of 1965-2014. Root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute error (MAE) and determination coefficient (R2) were employed to evaluate the performance of conventional/single MARS, BN and GEP, as well as the proposed MARS-GARCH, BN-GARCH and GEP-GARCH hybrid models. It was found that the proposed novel models are more precise than single MARS, BN and GEP models. Overall, MARS-GARCH and BN-GARCH models yielded better accuracy than GEP-GARCH. The results of the present study confirmed the suitability of proposed methodology for precise modeling of precipitation.

  15. Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.

    Science.gov (United States)

    Ding, A Adam; Wu, Hulin

    2014-10-01

    We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.

  16. Distancing from experienced self: how global versus local perception affects estimation of psychological distance

    NARCIS (Netherlands)

    Liberman, N.; Förster, J.

    2009-01-01

    In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition).

  17. An age estimation method using brain local features for T1-weighted images.

    Science.gov (United States)

    Kondo, Chihiro; Ito, Koichi; Kai Wu; Sato, Kazunori; Taki, Yasuyuki; Fukuda, Hiroshi; Aoki, Takafumi

    2015-08-01

    Previous statistical analysis studies using large-scale brain magnetic resonance (MR) image databases have examined that brain tissues have age-related morphological changes. This fact indicates that one can estimate the age of a subject from his/her brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features extracted from T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into local regions defined by the automated anatomical labeling atlas. The proposed method selects optimal local regions to improve the performance of age estimation. We evaluate performance of the proposed method using 1,146 T1-weighted images from a Japanese MR image database. We also discuss the medical implication of selected optimal local regions.

  18. Characterizing floodplain evolution by joint analysis of SAR, GOES IR and local precipitation data: Case study of Rio Colorado, Bolivia

    Science.gov (United States)

    Koenders, R.; Oyen, A. M.; Weltje, G.; Sarna, K.; Donselaar, R.

    2013-12-01

    Dryland rivers in an endorheic basin experience downstream decrease of channel width and depth as the consequence of transmission losses by percolation and evapo-transpiration. Major changes in the river morphology take place during short peak discharge periods when the volume of water and sediment by far exceeds the river capacity and, as a consequence, meander bends are cut off, and the river path may change position by avulsion. Successive avulsions create a complex network of cross-cutting abandoned river channels. The Río Colorado, located in the southeast part of the Altiplano basin in Bolivia, is such a river system. This system consists of a very low-gradient lacustrine coastal plain onto which is deposited a 400 km2 sheet of fluvial sediment over the last 4000 year. Traditional studies to monitor the morphological changes at the terminus of the river system are based on field data acquisition of the fluvial sediments. This is time consuming and only covers a small area of the total fluvial morphology. The combination of field measurements and remote sensing imagery allows for the analysis of the development of the entire river system terminus at a longer temporal scale. Changes of alluvial surfaces affect the reflectance of objects and patterns on the ground, which is recorded by satellite images. In this study we show the response of the delta to rainfall events of various intensities in the Rio Colorado watershed. We combine precipitation data in the watershed with spaceborne synthetic aperture radar (SAR) data. We use two data sets that contain precipitation information: rainfall estimates based on Geostationary Operational Environmental Satellite (GOES) weather satellite IR window brightness temperatures and direct measures of rainfall from rain gauges in the vicinity of the delta. To detect changes on the surface water content we use the backscatter intensity or amplitude images from the European Remote Sensing Satellite (ERS) Synthetic Aperture

  19. Optimal Attitude Estimation and Filtering Without Using Local Coordinates Part I: Uncontrolled and Deterministic Attitude Dynamics

    OpenAIRE

    Sanyal, Amit K.

    2005-01-01

    There are several attitude estimation algorithms in existence, all of which use local coordinate representations for the group of rigid body orientations. All local coordinate representations of the group of orientations have associated problems. While minimal coordinate representations exhibit kinematic singularities for large rotations, the quaternion representation requires satisfaction of an extra constraint. This paper treats the attitude estimation and filtering problem as an optimizati...

  20. First estimates of the contribution of CaCO3 precipitation to the release of CO2 to the atmosphere during young sea ice growth

    Science.gov (United States)

    Geilfus, N.-X.; Carnat, G.; Dieckmann, G. S.; Halden, N.; Nehrke, G.; Papakyriakou, T.; Tison, J.-L.; Delille, B.

    2013-01-01

    report measurements of pH, total alkalinity, air-ice CO2 fluxes (chamber method), and CaCO3 content of frost flowers (FF) and thin landfast sea ice. As the temperature decreases, concentration of solutes in the brine skim increases. Along this gradual concentration process, some salts reach their solubility threshold and start precipitating. The precipitation of ikaite (CaCO3.6H2O) was confirmed in the FF and throughout the ice by Raman spectroscopy and X-ray analysis. The amount of ikaite precipitated was estimated to be 25 µmol kg-1 melted FF, in the FF and is shown to decrease from 19 to 15 µmol kg-1 melted ice in the upper part and at the bottom of the ice, respectively. CO2 release due to precipitation of CaCO3 is estimated to be 50 µmol kg-1 melted samples. The dissolved inorganic carbon (DIC) normalized to a salinity of 10 exhibits significant depletion in the upper layer of the ice and in the FF. This DIC loss is estimated to be 2069 µmol kg-1 melted sample and corresponds to a CO2 release from the ice to the atmosphere ranging from 20 to 40 mmol m-2 d-1. This estimate is consistent with flux measurements of air-ice CO2 exchange. Our measurements confirm previous laboratory findings that growing young sea ice acts as a source of CO2 to the atmosphere. CaCO3 precipitation during early ice growth appears to promote the release of CO2 to the atmosphere; however, its contribution to the overall release by newly formed ice is most likely minor.

  1. Estimating organic, local, and other price premiums in the Hawaii fluid milk market.

    Science.gov (United States)

    Loke, Matthew K; Xu, Xun; Leung, PingSun

    2015-04-01

    With retail scanner data, we applied hedonic price modeling to explore price premiums for organic, local, and other product attributes of fluid milk in Hawaii. Within the context of revealed preference, this analysis of organic and local attributes, under a single unified framework, is significant, as research in this area is deficient in the existing literature. This paper finds both organic and local attributes delivered price premiums over imported, conventional, whole fluid milk. However, the estimated price premium for organic milk (24.6%) is significantly lower than findings in the existing literature. Likewise, the price premium for the local attribute is estimated at 17.4%, again substantially lower compared with an earlier, stated preference study in Hawaii. Beyond that, we estimated a robust price premium of 19.7% for nutritional benefits claimed. The magnitude of this estimated coefficient reinforces the notion that nutrition information on food is deemed beneficial and valuable. Finally, package size measures the influence of product weight. With each larger package size, the estimate led to a corresponding larger price discount. This result is consistent with the practice of weight discounting that retailers usually offer with fresh packaged food. Additionally, we estimated a fairly high Armington elasticity of substitution, which suggests a relatively high degree of substitution between local and imported fluid milk when their relative price changes. Overall, this study establishes price premiums for organic, local, and nutrition benefits claimed for fluid milk in Hawaii. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  2. Estimating the financial resources needed for local public health departments in Minnesota: a multimethod approach.

    Science.gov (United States)

    Riley, William; Briggs, Jill; McCullough, Mac

    2011-01-01

    This study presents a model for determining total funding needed for individual local health departments. The aim is to determine the financial resources needed to provide services for statewide local public health departments in Minnesota based on a gaps analysis done to estimate the funding needs. We used a multimethod analysis consisting of 3 approaches to estimate gaps in local public health funding consisting of (1) interviews of selected local public health leaders, (2) a Delphi panel, and (3) a Nominal Group Technique. On the basis of these 3 approaches, a consensus estimate of funding gaps was generated for statewide projections. The study includes an analysis of cost, performance, and outcomes from 2005 to 2007 for all 87 local governmental health departments in Minnesota. For each of the methods, we selected a panel to represent a profile of Minnesota health departments. The 2 main outcome measures were local-level gaps in financial resources and total resources needed to provide public health services at the local level. The total public health expenditure in Minnesota for local governmental public health departments was $302 million in 2007 ($58.92 per person). The consensus estimate of the financial gaps in local public health departments indicates that an additional $32.5 million (a 10.7% increase or $6.32 per person) is needed to adequately serve public health needs in the local communities. It is possible to make informed estimates of funding gaps for public health activities on the basis of a combination of quantitative methods. There is a wide variation in public health expenditure at the local levels, and methods are needed to establish minimum baseline expenditure levels to adequately treat a population. The gaps analysis can be used by stakeholders to inform policy makers of the need for improved funding of the public health system.

  3. Bio-precipitation of uranium by two bacterial isolates recovered from extreme environments as estimated by potentiometric titration, TEM and X-ray absorption spectroscopic analyses.

    Science.gov (United States)

    Merroun, Mohamed L; Nedelkova, Marta; Ojeda, Jesus J; Reitz, Thomas; Fernández, Margarita López; Arias, José M; Romero-González, María; Selenska-Pobell, Sonja

    2011-12-15

    This work describes the mechanisms of uranium biomineralization at acidic conditions by Bacillus sphaericus JG-7B and Sphingomonas sp. S15-S1 both recovered from extreme environments. The U-bacterial interaction experiments were performed at low pH values (2.0-4.5) where the uranium aqueous speciation is dominated by highly mobile uranyl ions. X-ray absorption spectroscopy (XAS) showed that the cells of the studied strains precipitated uranium at pH 3.0 and 4.5 as a uranium phosphate mineral phase belonging to the meta-autunite group. Transmission electron microscopic (TEM) analyses showed strain-specific localization of the uranium precipitates. In the case of B. sphaericus JG-7B, the U(VI) precipitate was bound to the cell wall. Whereas for Sphingomonas sp. S15-S1, the U(VI) precipitates were observed both on the cell surface and intracellularly. The observed U(VI) biomineralization was associated with the activity of indigenous acid phosphatase detected at these pH values in the absence of an organic phosphate substrate. The biomineralization of uranium was not observed at pH 2.0, and U(VI) formed complexes with organophosphate ligands from the cells. This study increases the number of bacterial strains that have been demonstrated to precipitate uranium phosphates at acidic conditions via the activity of acid phosphatase. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Influences of Mo and W on the precipitation of secondary phases and the associated localized corrosion and embrittlement in 29%Cr ferritic stainless steels

    International Nuclear Information System (INIS)

    Park, Chan Jin; Ahn, Myung Kyu; Kwon, Hyuk Sang

    2005-01-01

    Influences of molybdenum (Mo) substitution by tungsten (W) on the formation kinetics of secondary phases and the associated localized corrosion and embrittlement of Fe-29Cr-4Mo. Fe-29Cr-4W, and Fe-29Cr-8W ferritic stainless steels were investigated. Fine χ phase formed first in grain boundaries in an early stage of aging and it was gradually substituted by σ phase with further aging. The precipitation rate of σ phase appears to be determined by both the diffusion rates of W and Mo for the formation of the σ phase as well as by the affinity of χ phase, as a competitor, for the elements. Due to the high affinity of χ phase for W with a slow diffusion rate, the nucleation of σ phase was significantly delayed in Fe-29Cr-4W and Fe-29Cr-8W alloys compared with that in Fe-29Cr-4Mo alloy. In addition, the deterioration of ductility and localized corrosion resistance by the precipitation of secondary phases was significantly retarded in Fe-29Cr-4W alloy compared with that in Fe-29Cr-4Mo alloy, due to the delayed precipitation of secondary phases in Fe-29Cr-4W alloy. In particular, retardation of degradation in localized corrosion resistance by the formation of σ phase, which induced significant depletion of Cr and W (or Mo) around the phase, was prominent in the W-containing alloys. The W-containing alloys exhibited effective delay of σ phase formation

  5. Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

    Science.gov (United States)

    Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

    2015-04-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to

  6. Estimating 3D tilt from local image cues in natural scenes

    OpenAIRE

    Burge, Johannes; McCann, Brian C.; Geisler, Wilson S.

    2016-01-01

    Estimating three-dimensional (3D) surface orientation (slant and tilt) is an important first step toward estimating 3D shape. Here, we examine how three local image cues from the same location (disparity gradient, luminance gradient, and dominant texture orientation) should be combined to estimate 3D tilt in natural scenes. We collected a database of natural stereoscopic images with precisely co-registered range images that provide the ground-truth distance at each pixel location. We then ana...

  7. Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

    Science.gov (United States)

    Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.

    2013-01-01

    The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

  8. Estimating local noise power spectrum from a few FBP-reconstructed CT scans

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Rongping, E-mail: rongping.zeng@fda.hhs.gov; Gavrielides, Marios A.; Petrick, Nicholas; Sahiner, Berkman; Li, Qin; Myers, Kyle J. [Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH, FDA, Silver Spring, Maryland 20993 (United States)

    2016-01-15

    Purpose: Traditional ways to estimate 2D CT noise power spectrum (NPS) involve an ensemble average of the power spectrums of many noisy scans. When only a few scans are available, regions of interest are often extracted from different locations to obtain sufficient samples to estimate the NPS. Using image samples from different locations ignores the nonstationarity of CT noise and thus cannot accurately characterize its local properties. The purpose of this work is to develop a method to estimate local NPS using only a few fan-beam CT scans. Methods: As a result of FBP reconstruction, the CT NPS has the same radial profile shape for all projection angles, with the magnitude varying with the noise level in the raw data measurement. This allows a 2D CT NPS to be factored into products of a 1D angular and a 1D radial function in polar coordinates. The polar separability of CT NPS greatly reduces the data requirement for estimating the NPS. The authors use this property and derive a radial NPS estimation method: in brief, the radial profile shape is estimated from a traditional NPS based on image samples extracted at multiple locations. The amplitudes are estimated by fitting the traditional local NPS to the estimated radial profile shape. The estimated radial profile shape and amplitudes are then combined to form a final estimate of the local NPS. We evaluate the accuracy of the radial NPS method and compared it to traditional NPS methods in terms of normalized mean squared error (NMSE) and signal detectability index. Results: For both simulated and real CT data sets, the local NPS estimated with no more than six scans using the radial NPS method was very close to the reference NPS, according to the metrics of NMSE and detectability index. Even with only two scans, the radial NPS method was able to achieve a fairly good accuracy. Compared to those estimated using traditional NPS methods, the accuracy improvement was substantial when a few scans were available

  9. Estimating long-term statistics for annual precipitation for six regions of the United States from tree-ring data

    International Nuclear Information System (INIS)

    Fritts, H.C.; DeWitt, E.; Gordon, G.A.; Hunt, J.H.; Lofgren, G.R.

    1979-12-01

    Spatial anomalies of seasonal precipitation for the United States and southwestern Canada have been reconstructed from 1602 through 1961 using dendrochronological and multivariate techniques on 65 arid-site tree-ring chronologies from western North America. Seasonal reconstructions are averaged to obtain mean annual precipitation values for six regions of importance to the Nuclear Regulatory Commission (NRC) Nuclear Waste Management Program (NWMP). Statistics calculated from the regionally averaged annual values for 25-year and longer intervals show annual precipitation in the seventeenth through nineteenth centuries to be lower than in the twentieth century for three regions in the American Southwest and higher for one region in the Northwest and two regions in the East. The variability of precipitation generally was higher in the past three centuries than in the present century. Twenty-five-year intervals with noteworthy statistics are identified and important results are summarized and tabulated for use in the hydrologic modeling of the NWMP. Additional research is recommended to incorporate temperature and precipitation into a single hydrologic parameter

  10. Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

    Science.gov (United States)

    Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

    2017-10-01

    A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3

  11. Bio-precipitation of uranium by two bacterial isolates recovered from extreme environments as estimated by potentiometric titration, TEM and X-ray absorption spectroscopic analyses

    Energy Technology Data Exchange (ETDEWEB)

    Merroun, Mohamed L., E-mail: merroun@ugr.es [Institute of Radiochemistry, Helmholtz Centre Dresden-Rossendorf, Dresden (Germany); Departamento de Microbiologia, Universidad de Granada, Campus Fuentenueva s/n 18071, Granada (Spain); Nedelkova, Marta [Institute of Radiochemistry, Helmholtz Centre Dresden-Rossendorf, Dresden (Germany); Ojeda, Jesus J. [Cell-Mineral Interface Research Programme, Kroto Research Institute, University of Sheffield, Broad Lane, Sheffield S3 7HQ (United Kingdom); Experimental Techniques Centre, Brunel University, Uxbridge, Middlesex UB8 3PH (United Kingdom); Reitz, Thomas [Institute of Radiochemistry, Helmholtz Centre Dresden-Rossendorf, Dresden (Germany); Fernandez, Margarita Lopez; Arias, Jose M. [Departamento de Microbiologia, Universidad de Granada, Campus Fuentenueva s/n 18071, Granada (Spain); Romero-Gonzalez, Maria [Cell-Mineral Interface Research Programme, Kroto Research Institute, University of Sheffield, Broad Lane, Sheffield S3 7HQ (United Kingdom); Selenska-Pobell, Sonja [Institute of Radiochemistry, Helmholtz Centre Dresden-Rossendorf, Dresden (Germany)

    2011-12-15

    Highlights: Black-Right-Pointing-Pointer Precipitation of uranium as U phosphates by natural bacterial isolates. Black-Right-Pointing-Pointer The uranium biomineralization involves the activity of acidic phosphatase. Black-Right-Pointing-Pointer Uranium bioremediation could be achieved via the biomineralization of U(VI) in phosphate minerals. - Abstract: This work describes the mechanisms of uranium biomineralization at acidic conditions by Bacillus sphaericus JG-7B and Sphingomonas sp. S15-S1 both recovered from extreme environments. The U-bacterial interaction experiments were performed at low pH values (2.0-4.5) where the uranium aqueous speciation is dominated by highly mobile uranyl ions. X-ray absorption spectroscopy (XAS) showed that the cells of the studied strains precipitated uranium at pH 3.0 and 4.5 as a uranium phosphate mineral phase belonging to the meta-autunite group. Transmission electron microscopic (TEM) analyses showed strain-specific localization of the uranium precipitates. In the case of B. sphaericus JG-7B, the U(VI) precipitate was bound to the cell wall. Whereas for Sphingomonas sp. S15-S1, the U(VI) precipitates were observed both on the cell surface and intracellularly. The observed U(VI) biomineralization was associated with the activity of indigenous acid phosphatase detected at these pH values in the absence of an organic phosphate substrate. The biomineralization of uranium was not observed at pH 2.0, and U(VI) formed complexes with organophosphate ligands from the cells. This study increases the number of bacterial strains that have been demonstrated to precipitate uranium phosphates at acidic conditions via the activity of acid phosphatase.

  12. Precipitation-induced runoff and leaching from milled peat mining mires by peat types : a comparative method for estimating the loading of water bodies during peat pruduction

    OpenAIRE

    Svahnbäck, Lasse

    2007-01-01

    Precipitation-induced runoff and leaching from milled peat mining mires by peat types: a comparative method for estimating the loading of water bodies during peat production. This research project in environmental geology has arisen out of an observed need to be able to predict more accurately the loading of watercourses with detrimental organic substances and nutrients from already existing and planned peat production areas, since the authorities capacity for insisting on such predicti...

  13. Object-Based Assessment of Satellite Precipitation Products

    Directory of Open Access Journals (Sweden)

    Jingjing Li

    2016-06-01

    Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

  14. Improved infrared precipitation estimation approaches based on k-means clustering: Application to north Algeria using MSG-SEVIRI satellite data

    Science.gov (United States)

    Mokdad, Fatiha; Haddad, Boualem

    2017-06-01

    In this paper, two new infrared precipitation estimation approaches based on the concept of k-means clustering are first proposed, named the NAW-Kmeans and the GPI-Kmeans methods. Then, they are adapted to the southern Mediterranean basin, where the subtropical climate prevails. The infrared data (10.8 μm channel) acquired by MSG-SEVIRI sensor in winter and spring 2012 are used. Tests are carried out in eight areas distributed over northern Algeria: Sebra, El Bordj, Chlef, Blida, Bordj Menael, Sidi Aich, Beni Ourthilane, and Beni Aziz. The validation is performed by a comparison of the estimated rainfalls to rain gauges observations collected by the National Office of Meteorology in Dar El Beida (Algeria). Despite the complexity of the subtropical climate, the obtained results indicate that the NAW-Kmeans and the GPI-Kmeans approaches gave satisfactory results for the considered rain rates. Also, the proposed schemes lead to improvement in precipitation estimation performance when compared to the original algorithms NAW (Nagri, Adler, and Wetzel) and GPI (GOES Precipitation Index).

  15. Combining weather radar nowcasts and numerical weather prediction models to estimate short-term quantitative precipitation and uncertainty

    DEFF Research Database (Denmark)

    Jensen, David Getreuer

    The topic of this Ph.D. thesis is short term forecasting of precipitation for up to 6 hours called nowcasts. The focus is on improving the precision of deterministic nowcasts, assimilation of radar extrapolation model (REM) data into Danish Meteorological Institutes (DMI) HIRLAM numerical weather...

  16. Distancing from experienced self: how global-versus-local perception affects estimation of psychological distance.

    Science.gov (United States)

    Liberman, Nira; Förster, Jens

    2009-08-01

    In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition). Relative to the control condition, global processing made participants estimate larger psychological distances in time (Study 1), space (Study 2), social distance (Study 3), and hypotheticality (Study 4). Local processing had the opposite effect. Consistent with CLT, all studies show that the effect of global-versus-local processing did emerge when participants estimated egocentric distances, which are distances from the experienced self in the here and now, but did not emerge with temporal distances not from now (Study 1), spatial distances not from here (Study 2), social distances not from the self (Study 3), or hypothetical events that did not involve altering an experienced reality (Study 4).

  17. LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions

    Directory of Open Access Journals (Sweden)

    Weihua An

    2016-07-01

    Full Text Available LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement are binary. The method (Abadie 2003 involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects.

  18. Indoor Localization and Radio Map Estimation using Unsupervised Manifold Alignment with Geometry Perturbation

    KAUST Repository

    Majeed, Khaqan; Sorour, Sameh; Al-Naffouri, Tareq Y.; Valaee, Shahrokh

    2015-01-01

    The Received Signal Strength (RSS) based fingerprinting approaches for indoor localization pose a need for updating the fingerprint databases due to dynamic nature of the indoor environment. This process is hectic and time-consuming when the size of the indoor area is large. The semi-supervised approaches reduce this workload and achieve good accuracy around 15% of the fingerprinting load but the performance is severely degraded if it is reduced below this level. We propose an indoor localization framework that uses unsupervised manifold alignment. It requires only 1% of the fingerprinting load, some crowd sourced readings and plan coordinates of the indoor area. The 1% fingerprinting load is used only in perturbing the local geometries of the plan coordinates. The proposed framework achieves less than 5m mean localization error, which is considerably better than semi-supervised approaches at very small amount of fingerprinting load. In addition, the few location estimations together with few fingerprints help to estimate the complete radio map of the indoor environment. The estimation of radio map does not demand extra workload rather it employs the already available information from the proposed indoor localization framework. The testing results for radio map estimation show almost 50% performance improvement by using this information as compared to using only fingerprints.

  19. Application of Matrix Pencil Algorithm to Mobile Robot Localization Using Hybrid DOA/TOA Estimation

    Directory of Open Access Journals (Sweden)

    Lan Anh Trinh

    2012-12-01

    Full Text Available Localization plays an important role in robotics for the tasks of monitoring, tracking and controlling a robot. Much effort has been made to address robot localization problems in recent years. However, despite many proposed solutions and thorough consideration, in terms of developing a low-cost and fast processing method for multiple-source signals, the robot localization problem is still a challenge. In this paper, we propose a solution for robot localization with regards to these concerns. In order to locate the position of a robot, both the coordinate and the orientation of a robot are necessary. We develop a localization method using the Matrix Pencil (MP algorithm for hybrid detection of direction of arrival (DOA and time of arrival (TOA. TOA of the signal is estimated for computing the distance between the mobile robot and a base station (BS. Based on the distance and the estimated DOA, we can estimate the mobile robot's position. The characteristics of the algorithm are examined through analysing simulated experiments and the results demonstrate the advantages of our method over previous works in dealing with the above challenges. The method is constructed based on the low-cost infrastructure of radio frequency devices; the DOA/TOA estimation is performed with just single value decomposition for fast processing. Finally, the MP algorithm combined with tracking using a Kalman filter allows our proposed method to locate the positions of multiple source signals.

  20. Indoor Localization and Radio Map Estimation using Unsupervised Manifold Alignment with Geometry Perturbation

    KAUST Repository

    Majeed, Khaqan

    2015-12-22

    The Received Signal Strength (RSS) based fingerprinting approaches for indoor localization pose a need for updating the fingerprint databases due to dynamic nature of the indoor environment. This process is hectic and time-consuming when the size of the indoor area is large. The semi-supervised approaches reduce this workload and achieve good accuracy around 15% of the fingerprinting load but the performance is severely degraded if it is reduced below this level. We propose an indoor localization framework that uses unsupervised manifold alignment. It requires only 1% of the fingerprinting load, some crowd sourced readings and plan coordinates of the indoor area. The 1% fingerprinting load is used only in perturbing the local geometries of the plan coordinates. The proposed framework achieves less than 5m mean localization error, which is considerably better than semi-supervised approaches at very small amount of fingerprinting load. In addition, the few location estimations together with few fingerprints help to estimate the complete radio map of the indoor environment. The estimation of radio map does not demand extra workload rather it employs the already available information from the proposed indoor localization framework. The testing results for radio map estimation show almost 50% performance improvement by using this information as compared to using only fingerprints.

  1. Estimating local atmosphere-surface fluxes using eddy covariance and numerical Ogive optimization

    DEFF Research Database (Denmark)

    Sievers, Jakob; Papakyriakou, Tim; Larsen, Søren

    2014-01-01

    Estimating representative surface-fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modeling efforts, low-frequency cont......Estimating representative surface-fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modeling efforts, low...

  2. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection.

    OpenAIRE

    Kim, Sanghong; Kano, Manabu; Nakagawa, Hiroshi; Hasebe, Shinji

    2011-01-01

    Development of quality estimation models using near infrared spectroscopy (NIRS) and multivariate analysis has been accelerated as a process analytical technology (PAT) tool in the pharmaceutical industry. Although linear regression methods such as partial least squares (PLS) are widely used, they cannot always achieve high estimation accuracy because physical and chemical properties of a measuring object have a complex effect on NIR spectra. In this research, locally weighted PLS (LW-PLS) wh...

  3. Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

    2014-12-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar

  4. A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments

    Directory of Open Access Journals (Sweden)

    Zakir Ullah

    2018-05-01

    Full Text Available A novel approach is proposed for the path tracking of a Wheeled Mobile Robot (WMR in the presence of an unknown lateral slip. Much of the existing work has assumed pure rolling conditions between the wheel and ground. Under the pure rolling conditions, the wheels of a WMR are supposed to roll without slipping. Complex wheel-ground interactions, acceleration and steering system noise are the factors which cause WMR wheel slip. A basic research problem in this context is localization and slip estimation of WMR from a stream of noisy sensors data when the robot is moving on a slippery surface, or moving at a high speed. DecaWave based ranging system and Particle Filter (PF are good candidates to estimate the location of WMR indoors and outdoors. Unfortunately, wheel-slip of WMR limits the ultimate performance that can be achieved by real-world implementation of the PF, because location estimation systems typically partially rely on the robot heading. A small error in the WMR heading leads to a large error in location estimation of the PF because of its cumulative nature. In order to enhance the tracking and localization performance of the PF in the environments where the main reason for an error in the PF location estimation is angular noise, two methods were used for heading estimation of the WMR (1: Reinforcement Learning (RL and (2: Location-based Heading Estimation (LHE. Trilateration is applied to DecaWave based ranging system for calculating the probable location of WMR, this noisy location along with PF current mean is used to estimate the WMR heading by using the above two methods. Beside the WMR location calculation, DecaWave based ranging system is also used to update the PF weights. The localization and tracking performance of the PF is significantly improved through incorporating heading error in localization by applying RL and LHE. Desired trajectory information is then used to develop an algorithm for extracting the lateral slip along

  5. Quantitative estimation of orographic precipitation over the Himalayas by using TRMM/PR and a dense network of rain gauges

    Science.gov (United States)

    Yatagai, A.

    2009-04-01

    Precipitation Radar (PR) data acquired by the Tropical Rainfall Measuring Mission (TRMM) over 10 years of observation were used to show the monthly rainfall patterns over the Himalayas. To validate and adjust these patterns, we used a dense network of rain gauges to measure daily precipitation over Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and China. We then compared TRMM/PR and rain gauge data in 0.05-degree grid cells (an approximately 5.5-km mesh). Compared with the rain gauge observations, the PR systematically underestimated precipitation by 28-38% in summer (July-September).Significant correlation between TRMM/PR and RG data was found for all months, but the correlation is relatively low in winter. The relationship is investigated for different elevation zones, and the PR was found to underestimate RG data in most zones, except for certain zones in February (250-1000m), March (0-1000m), and April (0-1500m). Monthly PR climatology was adjusted on the basis of monthly regressions between the two sets of data and depicted.

  6. Mean precipitation estimation, rain gauge network evaluation and quantification of the hydrologic balance in the River Quito basin in Choco, state of Colombia

    International Nuclear Information System (INIS)

    Cordoba, Samir; Zea, Jorge A; Murillo, W

    2006-01-01

    In this work the calculation of the average precipitation in the Quito River basin, state of Choco, Colombia, is presents through diverse techniques, among which are those suggested by Thiessen and those based on the isohyets analysis, in order to select the one appropriate to quantification of rainwater available to the basin. Also included is an estimation of the error with which the average precipitation in the zone studied is fraught when measured, by means of the methodology proposed by Gandin (1970) and Kagan (WMO, 1966), which at the same time allows to evaluate the representativeness of each one of the stations that make up the rain gauge network in the area. The study concludes with a calculation of the hydrologic balance for the Quito river basin based on the pilot procedure suggested in the UNESCO publication on the study of the South America hydrologic balance, from which the great contribution of rainfall to a greatly enhanced run-off may be appreciated

  7. Estimation of local concentration from measurements of stochastic adsorption dynamics using carbon nanotube-based sensors

    International Nuclear Information System (INIS)

    Jang, Hong; Lee, Jay H.; Braatz, Richard D.

    2016-01-01

    This paper proposes a maximum likelihood estimation (MLE) method for estimating time varying local concentration of the target molecule proximate to the sensor from the time profile of monomolecular adsorption and desorption on the surface of the sensor at nanoscale. Recently, several carbon nanotube sensors have been developed that can selectively detect target molecules at a trace concentration level. These sensors use light intensity changes mediated by adsorption or desorption phenomena on their surfaces. The molecular events occurring at trace concentration levels are inherently stochastic, posing a challenge for optimal estimation. The stochastic behavior is modeled by the chemical master equation (CME), composed of a set of ordinary differential equations describing the time evolution of probabilities for the possible adsorption states. Given the significant stochastic nature of the underlying phenomena, rigorous stochastic estimation based on the CME should lead to an improved accuracy over than deterministic estimation formulated based on the continuum model. Motivated by this expectation, we formulate the MLE based on an analytical solution of the relevant CME, both for the constant and the time-varying local concentrations, with the objective of estimating the analyte concentration field in real time from the adsorption readings of the sensor array. The performances of the MLE and the deterministic least squares are compared using data generated by kinetic Monte Carlo (KMC) simulations of the stochastic process. Some future challenges are described for estimating and controlling the concentration field in a distributed domain using the sensor technology.

  8. First Evaluation of the Climatological Calibration Algorithm in the Real-time TMPA Precipitation Estimates over Two Basins at High and Low Latitudes

    Science.gov (United States)

    Yong, Bin; Ren, Liliang; Hong, Yang; Gourley, Jonathan; Tian, Yudong; Huffman, George J.; Chen, Xi; Wang, Weiguang; Wen, Yixin

    2013-01-01

    The TRMM Multi-satellite Precipitation Analysis (TMPA) system underwent a crucial upgrade in early 2009 to include a climatological calibration algorithm (CCA) to its realtime product 3B42RT, and this algorithm will continue to be applied in the future Global Precipitation Measurement era constellation precipitation products. In this study, efforts are focused on the comparison and validation of the Version 6 3B42RT estimates before and after the climatological calibration is applied. The evaluation is accomplished using independent rain gauge networks located within the high-latitude Laohahe basin and the low-latitude Mishui basin, both in China. The analyses indicate the CCA can effectively reduce the systematic errors over the low-latitude Mishui basin but misrepresent the intensity distribution pattern of medium-high rain rates. This behavior could adversely affect TMPA's hydrological applications, especially for extreme events (e.g., floods and landslides). Results also show that the CCA tends to perform slightly worse, in particular, during summer and winter, over the high-latitude Laohahe basin. This is possibly due to the simplified calibration-processing scheme in the CCA that directly applies the climatological calibrators developed within 40 degrees latitude to the latitude belts of 40 degrees N-50 degrees N. Caution should therefore be exercised when using the calibrated 3B42RT for heavy rainfall-related flood forecasting (or landslide warning) over high-latitude regions, as the employment of the smooth-fill scheme in the CCA bias correction could homogenize the varying rainstorm characteristics. Finally, this study highlights that accurate detection and estimation of snow at high latitudes is still a challenging task for the future development of satellite precipitation retrievals.

  9. Automotive FMCW Radar-Enhanced Range Estimation via a Local Resampling Fourier Transform

    Directory of Open Access Journals (Sweden)

    Cailing Wang

    2016-02-01

    Full Text Available In complex traffic scenarios, more accurate measurement and discrimination for an automotive frequency-modulated continuous-wave (FMCW radar is required for intelligent robots, driverless cars and driver-assistant systems. A more accurate range estimation method based on a local resampling Fourier transform (LRFT for a FMCW radar is developed in this paper. Radar signal correlation in the phase space sees a higher signal-noise-ratio (SNR to achieve more accurate ranging, and the LRFT - which acts on a local neighbour as a refinement step - can achieve a more accurate target range. The rough range is estimated through conditional pulse compression (PC and then, around the initial rough estimation, a refined estimation through the LRFT in the local region achieves greater precision. Furthermore, the LRFT algorithm is tested in numerous simulations and physical system experiments, which show that the LRFT algorithm achieves a more precise range estimation than traditional FFT-based algorithms, especially for lower bandwidth signals.

  10. Precipitable water and vapor flux between Belem and Manaus

    International Nuclear Information System (INIS)

    Marques, J.

    1977-01-01

    The water vapor flux and precipitable water was computated over the natural Amazon forest in the stretch between Belem and Manaus for 1972. The atmospheric branch of hidrological cycle theory was applied and the most significant conclusions on an annual basis are: Atlantic Ocean water vapor contributes 52% to the regional precipitation and is significant the role played by local evapotranspiration in the precipitation in the area; there were signs of the phenomenon of water vapor recycling nearly throughout the year. Evapotranspiration contributes to 48% of the precipitations in the area studied. The real evapotranspiration estimated by this method was 1,000mm year - 1 [pt

  11. Experimental Verification of a Vehicle Localization based on Moving Horizon Estimation Integrating LRS and Odometry

    International Nuclear Information System (INIS)

    Sakaeta, Kuniyuki; Nonaka, Kenichiro; Sekiguchi, Kazuma

    2016-01-01

    Localization is an important function for the robots to complete various tasks. For localization, both internal and external sensors are used generally. The odometry is widely used as the method based on the internal sensors, but it suffers from cumulative errors. In the method using the laser range sensor (LRS) which is a kind of external sensor, the estimation accuracy is affected by the number of available measurement data. In our previous study, we applied moving horizon estimation (MHE) to the vehicle localization for integrating the LRS measurement data and the odometry information where the weightings of them are balanced relatively adapting to the number of the available LRS measurement data. In this paper, the effectiveness of the proposed localization method is verified through both numerical simulations and experiments using a 1/10 scale vehicle. The verification is conducted in the situations where the vehicle position cannot be localized uniquely on a certain direction using the LRS measurement data only. We achieve accurate localization even in such a situation by integrating the odometry and LRS based on MHE. We also show the superiority of the method through comparisons with a method using extended Kalman filter (EKF). (paper)

  12. ALTERNATIVE METHODOLOGIES FOR THE ESTIMATION OF LOCAL POINT DENSITY INDEX: MOVING TOWARDS ADAPTIVE LIDAR DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-07-01

    Full Text Available Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification. Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for

  13. Estimating the Seasonal Importance of Precipitation to Plant Source Water over Time and Space with Water Isotopes

    Science.gov (United States)

    Nelson, D. B.; Kahmen, A.

    2017-12-01

    The stable isotopic composition of hydrogen and oxygen are physical properties of water molecules that can carry information on their sources or transport histories. This provides a useful tool for assessing the importance of rainfall at different times of the year for plant growth, provided that rainwater values vary over time and that waters do not partially evaporate after deposition. We tested the viability of this approach using data from samples collected at nineteen sites throughout Europe at monthly intervals over two consecutive growing seasons in 2014 and 2015. We compared isotope measurements of plant xylem water with soil water from multiple depths, and measured and modeled precipitation isotope values. Paired analyses of oxygen and hydrogen isotope values were used to screen out a limited number of water samples that were influenced by evaporation, with the majority of all water samples indicating meteoric sources. The isotopic composition of soil and xylem waters varied over the course of an individual growing season, with many trending towards more enriched values, suggesting integration of the plant-relevant water pool at a timescale shorter than the annual mean. We then quantified how soil water residence times varied at each site by calculating the interval between measured xylem water and the most recently preceding match in modeled precipitation isotope values. Results suggest a generally increasing interval between rainfall and plant uptake throughout each year, with source water corresponding to dates in the spring, likely reflecting a combination of spring rain, and mixing with winter and summer precipitation. The seasonally evolving spatial distribution of source water-precipitation lag values was then modeled as a function of location and climatology to develop continental-scale predictions. This spatial portrait of the average date for filling the plant source water pool provides insights on the seasonal importance of rainfall for plant

  14. Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Gregersen, Ida Bülow; Rosbjerg, Dan

    2015-01-01

    change method for extreme events, a weather generator combined with a disaggregation method and a climate analogue method. All three methods rely on different assumptions and use different outputs from the regional climate models (RCMs). The results of the three methods point towards an increase...... in extreme precipitation but the magnitude of the change varies depending on the RCM used and the spatial location. In general, a similar mean change is obtained for the three methods. This adds confidence in the results as each method uses different information from the RCMs. The results of this study...

  15. Constraining frequency–magnitude–area relationships for rainfall and flood discharges using radar-derived precipitation estimates: example applications in the Upper and Lower Colorado River basins, USA

    Directory of Open Access Journals (Sweden)

    C. A. Orem

    2016-11-01

    Full Text Available Flood-envelope curves (FECs are useful for constraining the upper limit of possible flood discharges within drainage basins in a particular hydroclimatic region. Their usefulness, however, is limited by their lack of a well-defined recurrence interval. In this study we use radar-derived precipitation estimates to develop an alternative to the FEC method, i.e., the frequency–magnitude–area-curve (FMAC method that incorporates recurrence intervals. The FMAC method is demonstrated in two well-studied US drainage basins, i.e., the Upper and Lower Colorado River basins (UCRB and LCRB, respectively, using Stage III Next-Generation-Radar (NEXRAD gridded products and the diffusion-wave flow-routing algorithm. The FMAC method can be applied worldwide using any radar-derived precipitation estimates. In the FMAC method, idealized basins of similar contributing area are grouped together for frequency–magnitude analysis of precipitation intensity. These data are then routed through the idealized drainage basins of different contributing areas, using contributing-area-specific estimates for channel slope and channel width. Our results show that FMACs of precipitation discharge are power-law functions of contributing area with an average exponent of 0.82 ± 0.06 for recurrence intervals from 10 to 500 years. We compare our FMACs to published FECs and find that for wet antecedent-moisture conditions, the 500-year FMAC of flood discharge in the UCRB is on par with the US FEC for contributing areas of  ∼ 102 to 103 km2. FMACs of flood discharge for the LCRB exceed the published FEC for the LCRB for contributing areas in the range of  ∼ 103 to 104 km2. The FMAC method retains the power of the FEC method for constraining flood hazards in basins that are ungauged or have short flood records, yet it has the added advantage that it includes recurrence-interval information necessary for estimating event probabilities.

  16. Estimating the Health and Economic Impacts of Changes in Local Air Quality

    Science.gov (United States)

    Carvour, Martha L.; Hughes, Amy E.; Fann, Neal

    2018-01-01

    Objectives. To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration–response and health–economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences. Methods. We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas–Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level. Results. Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data. Conclusions. BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities. PMID:29698094

  17. Local scattering property scales flow speed estimation in laser speckle contrast imaging

    International Nuclear Information System (INIS)

    Miao, Peng; Chao, Zhen; Feng, Shihan; Ji, Yuanyuan; Yu, Hang; Thakor, Nitish V; Li, Nan

    2015-01-01

    Laser speckle contrast imaging (LSCI) has been widely used in in vivo blood flow imaging. However, the effect of local scattering property (scattering coefficient µ s ) on blood flow speed estimation has not been well investigated. In this study, such an effect was quantified and involved in relation between speckle autocorrelation time τ c and flow speed v based on simulation flow experiments. For in vivo blood flow imaging, an improved estimation strategy was developed to eliminate the estimation bias due to the inhomogeneous distribution of the scattering property. Compared to traditional LSCI, a new estimation method significantly suppressed the imaging noise and improves the imaging contrast of vasculatures. Furthermore, the new method successfully captured the blood flow changes and vascular constriction patterns in rats’ cerebral cortex from normothermia to mild and moderate hypothermia. (letter)

  18. Using local multiplicity to improve effect estimation from a hypothesis-generating pharmacogenetics study.

    Science.gov (United States)

    Zou, W; Ouyang, H

    2016-02-01

    We propose a multiple estimation adjustment (MEA) method to correct effect overestimation due to selection bias from a hypothesis-generating study (HGS) in pharmacogenetics. MEA uses a hierarchical Bayesian approach to model individual effect estimates from maximal likelihood estimation (MLE) in a region jointly and shrinks them toward the regional effect. Unlike many methods that model a fixed selection scheme, MEA capitalizes on local multiplicity independent of selection. We compared mean square errors (MSEs) in simulated HGSs from naive MLE, MEA and a conditional likelihood adjustment (CLA) method that model threshold selection bias. We observed that MEA effectively reduced MSE from MLE on null effects with or without selection, and had a clear advantage over CLA on extreme MLE estimates from null effects under lenient threshold selection in small samples, which are common among 'top' associations from a pharmacogenetics HGS.

  19. Improvement of least-squares collocation error estimates using local GOCE Tzz signal standard deviations

    DEFF Research Database (Denmark)

    Tscherning, Carl Christian

    2015-01-01

    outside the data area. On the other hand, a comparison of predicted quantities with observed values show that the error also varies depending on the local data standard deviation. This quantity may be (and has been) estimated using the GOCE second order vertical derivative, Tzz, in the area covered...... by the satellite. The ratio between the nearly constant standard deviations of a predicted quantity (e.g. in a 25° × 25° area) and the standard deviations of Tzz in smaller cells (e.g., 1° × 1°) have been used as a scale factor in order to obtain more realistic error estimates. This procedure has been applied...

  20. THE EVOLUTION OF ANNUAL MEAN TEMPERATURE AND PRECIPITATION QUANTITY VARIABILITY BASED ON ESTIMATED CHANGES BY THE REGIONAL CLIMATIC MODELS

    Directory of Open Access Journals (Sweden)

    Paula Furtună

    2013-03-01

    Full Text Available Climatic changes are representing one of the major challenges of our century, these being forcasted according to climate scenarios and models, which represent plausible and concrete images of future climatic conditions. The results of climate models comparison regarding future water resources and temperature regime trend can become a useful instrument for decision makers in choosing the most effective decisions regarding economic, social and ecologic levels. The aim of this article is the analysis of temperature and pluviometric variability at the closest grid point to Cluj-Napoca, based on data provided by six different regional climate models (RCMs. Analysed on 30 year periods (2001-2030,2031-2060 and 2061-2090, the mean temperature has an ascending general trend, with great varability between periods. The precipitation expressed trough percentage deviation shows a descending general trend, which is more emphazied during 2031-2060 and 2061-2090.

  1. A simulation study of the recession coefficient for antecedent precipitation index. [soil moisture and water runoff estimation

    Science.gov (United States)

    Choudhury, B. J.; Blanchard, B. J.

    1981-01-01

    The antecedent precipitation index (API) is a useful indicator of soil moisture conditions for watershed runoff calculations and recent attempts to correlate this index with spaceborne microwave observations have been fairly successful. It is shown that the prognostic equation for soil moisture used in some of the atmospheric general circulation models together with Thornthwaite-Mather parameterization of actual evapotranspiration leads to API equations. The recession coefficient for API is found to depend on climatic factors through potential evapotranspiration and on soil texture through the field capacity and the permanent wilting point. Climatologial data for Wisconsin together with a recently developed model for global isolation are used to simulate the annual trend of the recession coefficient. Good quantitative agreement is shown with the observed trend at Fennimore and Colby watersheds in Wisconsin. It is suggested that API could be a unifying vocabulary for watershed and atmospheric general circulation modelars.

  2. Local Recurrence of Hepatocellular Carcinoma after Segmental Transarterial Chemoembolization: Risk Estimates Based on Multiple Prognostic Factors

    International Nuclear Information System (INIS)

    Park, Seung Hyun; Cho, Yun Ku; Ahn, Yong Sik; Park, Yoon Ok; Kim, Jae Kyun; Chung, Jin Wook

    2007-01-01

    To determine the prognostic factors for local recurrence of nodular hepatocellular carcinoma after segmental transarterial chemoembolization. Seventy-four nodular hepatocellular carcinoma tumors ≤5 cm were retrospectively analyzed for local recurrence after segmental transarterial chemoembolization using follow-up CT images (median follow-up of 17 months, 4 77 months in range). The tumors were divided into four groups (IA, IB, IIA, and IIB) according to whether the one-month follow-up CT imaging, after segmental transarterial chemoembolization, showed homogeneous (Group I) or inhomogeneous (Group II) iodized oil accumulation, or whether the tumors were located within the liver segment (Group A) or in a segmental border zone (Group B). Comparison of tumor characteristics between Group IA and the other three groups was performed using the chi-square test. Local recurrence rates were compared among the groups using the Kaplan-Meier estimation and log rank test. Local tumor recurrence occurred in 19 hepatocellular carcinoma tumors (25.7%). There were: 28, 18, 17, and 11 tumors in Group IA, IB, IIA, and IIB, respectively. One of 28 (3.6%) tumors in Group IA, and 18 of 46 (39.1%) tumors in the other three groups showed local recurrence. Comparisons between Group IA and the other three groups showed that the tumor characteristics were similar. One-, two-, and three-year estimated local recurrence rates in Group IA were 0%, 11.1%, and 11.1%, respectively. The difference between Group IA and the other three groups was statistically significant (p 0.000). An acceptably low rate of local recurrence was observed for small or intermediate nodular tumors located within the liver segment with homogeneous iodized oil accumulation

  3. Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

    Science.gov (United States)

    Yang, Song; Olson, William S.; Wang, Jian-Jian; Bell, Thomas L.; Smith, Eric A.; Kummerow, Christian D.

    2006-01-01

    Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5 deg. -resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5 -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5 deg. -resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated

  4. Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 2; Evaluation of Estimates Using Independent Data

    Science.gov (United States)

    Yang, Song; Olson, William S.; Wang, Jian-Jian; Bell, Thomas L.; Smith, Eric A.; Kummerow, Christian D.

    2004-01-01

    Rainfall rate estimates from space-borne k&ents are generally accepted as reliable by a majority of the atmospheric science commu&y. One-of the Tropical Rainfall Measuring Mission (TRh4M) facility rain rate algorithms is based upon passive microwave observations fiom the TRMM Microwave Imager (TMI). Part I of this study describes improvements in the TMI algorithm that are required to introduce cloud latent heating and drying as additional algorithm products. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, OP5resolution estimates of surface rain rate over ocean fiom the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over forerunning algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm, and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly, 2.5 deg. -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data are limited, TMI estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with: (a) additional contextual information brought to the estimation problem, and/or; (b) physically-consistent and representative databases supporting the algorithm. A model of the random error in instantaneous, 0.5 deg-resolution rain rate estimates appears to be consistent with the levels of error determined from TMI comparisons to collocated radar

  5. Simultaneous imaging of aurora on small scale in OI (777.4 nm and N21P to estimate energy and flux of precipitation

    Directory of Open Access Journals (Sweden)

    N. Ivchenko

    2009-07-01

    Full Text Available Simultaneous images of the aurora in three emissions, N21P (673.0 nm, OII (732.0 nm and OI (777.4 nm, have been analysed; the ratio of atomic oxygen to molecular nitrogen has been used to provide estimates of the changes in energy and flux of precipitation within scale sizes of 100 m, and with temporal resolution of 32 frames per second. The choice of filters for the imagers is discussed, with particular emphasis on the choice of the atomic oxygen line at 777.4 nm as one of the three emissions measured. The optical measurements have been combined with radar measurements and compared with the results of an auroral model, hence showing that the ratio of emission rates OI/N2 can be used to estimate the energy within the smallest auroral structures. In the event chosen, measurements were made from mainland Norway, near Tromso, (69.6 N, 19.2 E. The peak energies of precipitation were between 1–15 keV. In a narrow curling arc, it was found that the arc filaments resulted from energies in excess of 10 keV and fluxes of approximately 7 mW/m2. These filaments of the order of 100 m in width were embedded in a region of lower energies (about 5–10 keV and fluxes of about 3 mW/m2. The modelling results show that the method promises to be most powerful for detecting low energy precipitation, more prevalent at the higher latitudes of Svalbard where the multispectral imager, known as ASK, is now installed.

  6. Simultaneous imaging of aurora on small scale in OI (777.4 nm and N21P to estimate energy and flux of precipitation

    Directory of Open Access Journals (Sweden)

    B. S. Lanchester

    2009-07-01

    Full Text Available Simultaneous images of the aurora in three emissions, N21P (673.0 nm, OII (732.0 nm and OI (777.4 nm, have been analysed; the ratio of atomic oxygen to molecular nitrogen has been used to provide estimates of the changes in energy and flux of precipitation within scale sizes of 100 m, and with temporal resolution of 32 frames per second. The choice of filters for the imagers is discussed, with particular emphasis on the choice of the atomic oxygen line at 777.4 nm as one of the three emissions measured. The optical measurements have been combined with radar measurements and compared with the results of an auroral model, hence showing that the ratio of emission rates OI/N2 can be used to estimate the energy within the smallest auroral structures. In the event chosen, measurements were made from mainland Norway, near Troms\\o, (69.6 N, 19.2 E. The peak energies of precipitation were between 1–15 keV. In a narrow curling arc, it was found that the arc filaments resulted from energies in excess of 10 keV and fluxes of approximately 7 mW/m2. These filaments of the order of 100 m in width were embedded in a region of lower energies (about 5–10 keV and fluxes of about 3 mW/m2. The modelling results show that the method promises to be most powerful for detecting low energy precipitation, more prevalent at the higher latitudes of Svalbard where the multispectral imager, known as ASK, is now installed.

  7. Using LUCAS topsoil database to estimate soil organic carbon content in local spectral libraries

    Science.gov (United States)

    Castaldi, Fabio; van Wesemael, Bas; Chabrillat, Sabine; Chartin, Caroline

    2017-04-01

    The quantification of the soil organic carbon (SOC) content over large areas is mandatory to obtain accurate soil characterization and classification, which can improve site specific management at local or regional scale exploiting the strong relationship between SOC and crop growth. The estimation of the SOC is not only important for agricultural purposes: in recent years, the increasing attention towards global warming highlighted the crucial role of the soil in the global carbon cycle. In this context, soil spectroscopy is a well consolidated and widespread method to estimate soil variables exploiting the interaction between chromophores and electromagnetic radiation. The importance of spectroscopy in soil science is reflected by the increasing number of large soil spectral libraries collected in the world. These large libraries contain soil samples derived from a consistent number of pedological regions and thus from different parent material and soil types; this heterogeneity entails, in turn, a large variability in terms of mineralogical and organic composition. In the light of the huge variability of the spectral responses to SOC content and composition, a rigorous classification process is necessary to subset large spectral libraries and to avoid the calibration of global models failing to predict local variation in SOC content. In this regard, this study proposes a method to subset the European LUCAS topsoil database into soil classes using a clustering analysis based on a large number of soil properties. The LUCAS database was chosen to apply a standardized multivariate calibration approach valid for large areas without the need for extensive field and laboratory work for calibration of local models. Seven soil classes were detected by the clustering analyses and the samples belonging to each class were used to calibrate specific partial least square regression (PLSR) models to estimate SOC content of three local libraries collected in Belgium (Loam belt

  8. An operational procedure for precipitable and cloud liquid water estimate in non-raining conditions over sea Study on the assessment of the nonlinear physical inversion algorithm

    CERN Document Server

    Nativi, S; Mazzetti, P

    2004-01-01

    In a previous work, an operative procedure to estimate precipitable and liquid water in non-raining conditions over sea was developed and assessed. The procedure is based on a fast non-linear physical inversion scheme and a forward model; it is valid for most of satellite microwave radiometers and it also estimates water effective profiles. This paper presents two improvements of the procedure: first, a refinement to provide modularity of the software components and portability across different computation system architectures; second, the adoption of the CERN MINUIT minimisation package, which addresses the problem of global minimisation but is computationally more demanding. Together with the increased computational performance that allowed to impose stricter requirements on the quality of fit, these refinements improved fitting precision and reliability, and allowed to relax the requirements on the initial guesses for the model parameters. The re-analysis of the same data-set considered in the previous pap...

  9. Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels.

    Science.gov (United States)

    Schwartz, Joel; Bind, Marie-Abele; Koutrakis, Petros

    2017-01-01

    Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking. We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations. Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed. We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50). We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA

  10. The impact of local public services and geographical cost of living differences on poverty estimates

    OpenAIRE

    Aaberge, Rolf; Langørgen, Audun; Mogstad, Magne; Østensen, Marit

    2008-01-01

    Abstract: Despite a broad consensus on the need to account for the value of public services and geographical cost of living differences on the measurement of poverty, there is little reliable evidence on how these factors actually affect poverty estimates. Unlike the standard approach in studies of the distribution of public services, this paper employs a method for valuing sector-specific local public services that accounts for differences between municipalities in the costs and capacity ...

  11. Methodology for estimation of secondary meteorological variables to be used in local dispersion of air pollutants

    International Nuclear Information System (INIS)

    Turtos, L.; Sanchez, M.; Roque, A.; Soltura, R.

    2003-01-01

    Methodology for estimation of secondary meteorological variables to be used in local dispersion of air pollutants. This paper include the main works, carried out into the frame of the project Atmospheric environmental externalities of the electricity generation in Cuba, aiming to develop methodologies and corresponding software, which will allow to improve the quality of the secondary meteorological data used in atmospheric pollutant calculations; specifically the wind profiles coefficient, urban and rural mixed high and temperature gradients

  12. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

    Science.gov (United States)

    Sills, Erin O; Herrera, Diego; Kirkpatrick, A Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

    2015-01-01

    Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on policies

  13. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation

    Science.gov (United States)

    Sills, Erin O.; Herrera, Diego; Kirkpatrick, A. Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

    2015-01-01

    Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts’ selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal “blacklist” that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on

  14. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

    Directory of Open Access Journals (Sweden)

    Erin O Sills

    Full Text Available Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012. This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and

  15. Maximum likelihood estimation-based denoising of magnetic resonance images using restricted local neighborhoods

    International Nuclear Information System (INIS)

    Rajan, Jeny; Jeurissen, Ben; Sijbers, Jan; Verhoye, Marleen; Van Audekerke, Johan

    2011-01-01

    In this paper, we propose a method to denoise magnitude magnetic resonance (MR) images, which are Rician distributed. Conventionally, maximum likelihood methods incorporate the Rice distribution to estimate the true, underlying signal from a local neighborhood within which the signal is assumed to be constant. However, if this assumption is not met, such filtering will lead to blurred edges and loss of fine structures. As a solution to this problem, we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels. To this end, a reference image is created from the noisy image using a recently proposed nonlocal means algorithm. This reference image is used as a prior for further noise reduction. A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated. Experimental results based on the peak signal to noise ratio, structural similarity index matrix, Bhattacharyya coefficient and mean absolute difference from synthetic and real MR images demonstrate the superior performance of the proposed method over other state-of-the-art methods.

  16. Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaoxue Feng

    2014-11-01

    Full Text Available Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS, which gets better filtering performance than NILS without constraint.

  17. Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

    Science.gov (United States)

    Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

    2014-01-01

    Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

  18. Constrained state estimation for individual localization in wireless body sensor networks.

    Science.gov (United States)

    Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

    2014-11-10

    Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint.

  19. Synthesizing Global and Local Datasets to Estimate Jurisdictional Forest Carbon Fluxes in Berau, Indonesia.

    Science.gov (United States)

    Griscom, Bronson W; Ellis, Peter W; Baccini, Alessandro; Marthinus, Delon; Evans, Jeffrey S; Ruslandi

    2016-01-01

    Forest conservation efforts are increasingly being implemented at the scale of sub-national jurisdictions in order to mitigate global climate change and provide other ecosystem services. We see an urgent need for robust estimates of historic forest carbon emissions at this scale, as the basis for credible measures of climate and other benefits achieved. Despite the arrival of a new generation of global datasets on forest area change and biomass, confusion remains about how to produce credible jurisdictional estimates of forest emissions. We demonstrate a method for estimating the relevant historic forest carbon fluxes within the Regency of Berau in eastern Borneo, Indonesia. Our method integrates best available global and local datasets, and includes a comprehensive analysis of uncertainty at the regency scale. We find that Berau generated 8.91 ± 1.99 million tonnes of net CO2 emissions per year during 2000-2010. Berau is an early frontier landscape where gross emissions are 12 times higher than gross sequestration. Yet most (85%) of Berau's original forests are still standing. The majority of net emissions were due to conversion of native forests to unspecified agriculture (43% of total), oil palm (28%), and fiber plantations (9%). Most of the remainder was due to legal commercial selective logging (17%). Our overall uncertainty estimate offers an independent basis for assessing three other estimates for Berau. Two other estimates were above the upper end of our uncertainty range. We emphasize the importance of including an uncertainty range for all parameters of the emissions equation to generate a comprehensive uncertainty estimate-which has not been done before. We believe comprehensive estimates of carbon flux uncertainty are increasingly important as national and international institutions are challenged with comparing alternative estimates and identifying a credible range of historic emissions values.

  20. Robust Non-Local TV-L1 Optical Flow Estimation with Occlusion Detection.

    Science.gov (United States)

    Zhang, Congxuan; Chen, Zhen; Wang, Mingrun; Li, Ming; Jiang, Shaofeng

    2017-06-05

    In this paper, we propose a robust non-local TV-L1 optical flow method with occlusion detection to address the problem of weak robustness of optical flow estimation with motion occlusion. Firstly, a TV-L1 form for flow estimation is defined using a combination of the brightness constancy and gradient constancy assumptions in the data term and by varying the weight under the Charbonnier function in the smoothing term. Secondly, to handle the potential risk of the outlier in the flow field, a general non-local term is added in the TV-L1 optical flow model to engender the typical non-local TV-L1 form. Thirdly, an occlusion detection method based on triangulation is presented to detect the occlusion regions of the sequence. The proposed non-local TV-L1 optical flow model is performed in a linearizing iterative scheme using improved median filtering and a coarse-to-fine computing strategy. The results of the complex experiment indicate that the proposed method can overcome the significant influence of non-rigid motion, motion occlusion, and large displacement motion. Results of experiments comparing the proposed method and existing state-of-the-art methods by respectively using Middlebury and MPI Sintel database test sequences show that the proposed method has higher accuracy and better robustness.

  1. Multiobjective Memetic Estimation of Distribution Algorithm Based on an Incremental Tournament Local Searcher

    Directory of Open Access Journals (Sweden)

    Kaifeng Yang

    2014-01-01

    Full Text Available A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  2. Multiobjective memetic estimation of distribution algorithm based on an incremental tournament local searcher.

    Science.gov (United States)

    Yang, Kaifeng; Mu, Li; Yang, Dongdong; Zou, Feng; Wang, Lei; Jiang, Qiaoyong

    2014-01-01

    A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  3. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Directory of Open Access Journals (Sweden)

    Xujun Han

    Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  4. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Science.gov (United States)

    Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

    2015-01-01

    The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  5. Estimating rates of local species extinction, colonization and turnover in animal communities

    Science.gov (United States)

    Nichols, James D.; Boulinier, T.; Hines, J.E.; Pollock, K.H.; Sauer, J.R.

    1998-01-01

    Species richness has been identified as a useful state variable for conservation and management purposes. Changes in richness over time provide a basis for predicting and evaluating community responses to management, to natural disturbance, and to changes in factors such as community composition (e.g., the removal of a keystone species). Probabilistic capture-recapture models have been used recently to estimate species richness from species count and presence-absence data. These models do not require the common assumption that all species are detected in sampling efforts. We extend this approach to the development of estimators useful for studying the vital rates responsible for changes in animal communities over time; rates of local species extinction, turnover, and colonization. Our approach to estimation is based on capture-recapture models for closed animal populations that permit heterogeneity in detection probabilities among the different species in the sampled community. We have developed a computer program, COMDYN, to compute many of these estimators and associated bootstrap variances. Analyses using data from the North American Breeding Bird Survey (BBS) suggested that the estimators performed reasonably well. We recommend estimators based on probabilistic modeling for future work on community responses to management efforts as well as on basic questions about community dynamics.

  6. Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

    Science.gov (United States)

    Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

    2017-09-01

    Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

  7. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Science.gov (United States)

    Zhu, Aichun; Wang, Tian; Snoussi, Hichem

    2018-03-01

    This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  8. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Directory of Open Access Journals (Sweden)

    Aichun Zhu

    2018-03-01

    Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  9. Estimating local, organic, and other price premiums of shell eggs in Hawaii.

    Science.gov (United States)

    Loke, Matthew K; Xu, Xun; Leung, PingSun

    2016-05-01

    Hedonic modeling and retail scanner data were utilized to investigate the influence of local, organic, nutrition benefits, and other attributes of shell eggs on retail price premium in Hawaii. Within a revealed preference framework, the analysis of local and organic attributes, simultaneously, under a single unified setting is important, as such work is highly deficient in the published literature. This paper finds high to moderate price premiums in four key attributes of shell eggs - organic (64%), local (40%), nutrition benefits claimed (33%), and brown shell (18.4%). Large and extra-large sized eggs also experience price premiums over medium sized eggs. With each larger packing size, the estimated coefficients were negative, indicating a price discount, relative to the baseline packing size. However, there is no evidence to support the overwhelming influence of "local" over "organic", as hypothesized in other research work. Overall, the findings in this paper suggest industry producers and retailers should highlight and market effusively the primary attributes of their shell eggs, including "local", to remain competitive in the marketplace. Effective communication channels are crucial to delivering the product information, capturing the attention of consumers, and securing retail sales. © 2016 Poultry Science Association Inc.

  10. Estimating the mass of the Local Group using machine learning applied to numerical simulations

    Science.gov (United States)

    McLeod, M.; Libeskind, N.; Lahav, O.; Hoffman, Y.

    2017-12-01

    We present a new approach to calculating the combined mass of the Milky Way (MW) and Andromeda (M31), which together account for the bulk of the mass of the Local Group (LG). We base our work on an ensemble of 30,190 halo pairs from the Small MultiDark simulation, assuming a ΛCDM (Cosmological Constant and Cold Dark Matter) cosmology. This is used in conjunction with machine learning methods (artificial neural networks, ANN) to investigate the relationship between the mass and selected parameters characterising the orbit and local environment of the binary. ANN are employed to take account of additional physics arising from interactions with larger structures or dynamical effects which are not analytically well understood. Results from the ANN are most successful when the velocity shear is provided, which demonstrates the flexibility of machine learning to model physical phenomena and readily incorporate new information. The resulting estimate for the Local Group mass, when shear information is included, is 4.9×1012Msolar, with an error of ±0.8×1012Msolar from the 68% uncertainty in observables, and a r.m.s. scatter interval of +1.7‑1.3×1012Msolar estimated scatter from the differences between the model estimates and simulation masses for a testing sample of halo pairs. We also consider a recently reported large relative transverse velocity of M31 and the Milky Way, and produce an alternative mass estimate of 3.6±0.3+2.1‑1.3×1012Msolar. Although the methods used predict similar values for the most likely mass of the LG, application of ANN compared to the traditional Timing Argument reduces the scatter in the log mass by approximately half when tested on samples from the simulation.

  11. Behaviour of model particles of local precipitations of surface nuclear explosion in food chain and digestive tract of farm animals

    International Nuclear Information System (INIS)

    Koz'min, G.V.; Epimakhov, V.G.; Sanzharova, N.I.

    2016-01-01

    The behaviour regularities of radioactive particles - simulators of nuclear surface explosion local fall outs in food chain and gastrointestinal tract (GIT) of farm animals are analyzed. The results show that there is a large difference in transport regularities of radioactive silicate particles and radioactive solutions in GIT. At intake of young fission products high concentrations of radionuclides in GIT content deal with sorption and concentrating of radionuclides on food particles and observe in third stomach, blind gut, terminals of middle and bung guts. Transport regularities of fused radioactive particles depend on digestive apparatus mobility, content consistency and morphological peculiarities of mucosa, which work towards transport slowing and storage of such particles in the part of sheep GIT with minimal dry substance content - abomasum [ru

  12. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection.

    Science.gov (United States)

    Kim, Sanghong; Kano, Manabu; Nakagawa, Hiroshi; Hasebe, Shinji

    2011-12-15

    Development of quality estimation models using near infrared spectroscopy (NIRS) and multivariate analysis has been accelerated as a process analytical technology (PAT) tool in the pharmaceutical industry. Although linear regression methods such as partial least squares (PLS) are widely used, they cannot always achieve high estimation accuracy because physical and chemical properties of a measuring object have a complex effect on NIR spectra. In this research, locally weighted PLS (LW-PLS) which utilizes a newly defined similarity between samples is proposed to estimate active pharmaceutical ingredient (API) content in granules for tableting. In addition, a statistical wavelength selection method which quantifies the effect of API content and other factors on NIR spectra is proposed. LW-PLS and the proposed wavelength selection method were applied to real process data provided by Daiichi Sankyo Co., Ltd., and the estimation accuracy was improved by 38.6% in root mean square error of prediction (RMSEP) compared to the conventional PLS using wavelengths selected on the basis of variable importance on the projection (VIP). The results clearly show that the proposed calibration modeling technique is useful for API content estimation and is superior to the conventional one. Copyright © 2011 Elsevier B.V. All rights reserved.

  13. A constrained polynomial regression procedure for estimating the local False Discovery Rate

    Directory of Open Access Journals (Sweden)

    Broët Philippe

    2007-06-01

    Full Text Available Abstract Background In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR, which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The lFDR not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (FDR for subsets of genes. Results In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the lFDR is described. The results of a simulation study indicated good performances for the proposed estimator in comparison to four published ones. The five different procedures were applied to real datasets. Conclusion A novel and efficient procedure for estimating lFDR was developed and evaluated.

  14. Anxiety and dysthymia: local prevalence estimates based on drug prescriptions by general practitioners in Turin (Italy).

    Science.gov (United States)

    Mamo, C; Farina, E; Cicio, R; Fanì, M

    2014-01-01

    The aim of the study was to obtain local estimates of the prevalence of anxiety and dysthymic disorders among attendees of primary care at local level, useful to pursue a better management of the health care services. The study was conducted in the Health District no. 2 of Turin (industrial town in northwest Italy). The criteria for identification of cases were based on the drugs prescriptions made by general practitioners (GPs), selected in order to assure high specificity. The study involved 86 physicians (with 87,885 attendees). As expected, the crude and standardized prevalences were higher in women (anxiety: 2.9% vs 1.3% in men; dysthymia: 3.8% vs 1.7% in men), with a peak in women aged over 75 yrs (anxiety: 4.8%; dysthymia: 6.2%). In comparison to male GPs, female GPs had an higher prevalence of patients with anxious disorders, whereas the prevalences of dysthymia were similar. Despite the discussed limitations, the used methodology allows to obtain sufficiently reliable estimates of prevalence of common mental disorders at local level, providing informations useful for organizing the primary care in the Health district.

  15. Fatigue Strength Estimation Based on Local Mechanical Properties for Aluminum Alloy FSW Joints

    Directory of Open Access Journals (Sweden)

    Kittima Sillapasa

    2017-02-01

    Full Text Available Overall fatigue strengths and hardness distributions of the aluminum alloy similar and dissimilar friction stir welding (FSW joints were determined. The local fatigue strengths as well as local tensile strengths were also obtained by using small round bar specimens extracted from specific locations, such as the stir zone, heat affected zone, and base metal. It was found from the results that fatigue fracture of the FSW joint plate specimen occurred at the location of the lowest local fatigue strength as well as the lowest hardness, regardless of microstructural evolution. To estimate the fatigue strengths of aluminum alloy FSW joints from the hardness measurements, the relationship between fatigue strength and hardness for aluminum alloys was investigated based on the present experimental results and the available wide range of data from the references. It was found as: σa (R = −1 = 1.68 HV (σa is in MPa and HV has no unit. It was also confirmed that the estimated fatigue strengths were in good agreement with the experimental results for aluminum alloy FSW joints.

  16. Position Estimation and Local Mapping Using Omnidirectional Images and Global Appearance Descriptors

    Directory of Open Access Journals (Sweden)

    Yerai Berenguer

    2015-10-01

    Full Text Available This work presents some methods to create local maps and to estimate the position of a mobile robot, using the global appearance of omnidirectional images. We use a robot that carries an omnidirectional vision system on it. Every omnidirectional image acquired by the robot is described only with one global appearance descriptor, based on the Radon transform. In the work presented in this paper, two different possibilities have been considered. In the first one, we assume the existence of a map previously built composed of omnidirectional images that have been captured from previously-known positions. The purpose in this case consists of estimating the nearest position of the map to the current position of the robot, making use of the visual information acquired by the robot from its current (unknown position. In the second one, we assume that we have a model of the environment composed of omnidirectional images, but with no information about the location of where the images were acquired. The purpose in this case consists of building a local map and estimating the position of the robot within this map. Both methods are tested with different databases (including virtual and real images taking into consideration the changes of the position of different objects in the environment, different lighting conditions and occlusions. The results show the effectiveness and the robustness of both methods.

  17. The estimation of local marine dispersion of radionuclides from hydrographic survey data

    International Nuclear Information System (INIS)

    Maul, P.R.

    1985-05-01

    One of the most important stages in the assessment of the radiological impact of routine discharges of activity to the sea is the estimation of the local dispersion characteristics. Existing methods for defining the parameters required by the computer program CODAR2 are expanded to take into account the significance of the turbulence generated by the discharge, the effect of a shelving sea bed and the variation with time of the lateral dispersion coefficient. These methods also enable the importance of the timing of discharges and the variation of radionuclide concentrations along the coast to be considered. Calculations of local marine dispersion depend directly upon the information that is available from hydrographic surveys. Detailed consideration is given to the definition of model parameter values from data that are generally available from such surveys. The uncertainties involved in mathematical modelling and parameter specification suggest that the long term average radionuclide concentration in the vicinity of the release can be estimated to within a factor of 2 or 3, with estimates more likely to be greater than, rather than less than the actual value. This uncertainty will contribute to the net uncertainty in any radiological assessment of critical group exposure. (author)

  18. MicroRadarNet: A network of weather micro radars for the identification of local high resolution precipitation patterns

    Science.gov (United States)

    Turso, S.; Paolella, S.; Gabella, M.; Perona, G.

    2013-01-01

    In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network. Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors and optimizing the data loads to be transmitted. Network servers perform the final post-elaboration steps on the data streams coming from each unit. Final network products are meteorological mappings of weather events, monitored with high spatial and temporal resolution, and lastly served to the end user through any Web browser. This networked approach is shown to imply a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range monitoring strategy. Adoption of the TITAN storm identification and nowcasting engine is also here evaluated for in-loop integration within the MicroRadarNet data processing chain. A brief description of the engine workflow is provided, to present preliminary feasibility results and performance estimates. The outcomes were not so predictable, taking into account relevant operational differences between a Western Alps micro radar scenario and the long range radar context in the Denver region of Colorado. Finally, positive results from a set of case studies are discussed, motivating further refinements and integration activities.

  19. The variance of the locally measured Hubble parameter explained with different estimators

    DEFF Research Database (Denmark)

    Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

    2017-01-01

    We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

  20. Estimating risks of importation and local transmission of Zika virus infection

    Directory of Open Access Journals (Sweden)

    Kyeongah Nah

    2016-04-01

    Full Text Available Background. An international spread of Zika virus (ZIKV infection has attracted global attention. ZIKV is conveyed by a mosquito vector, Aedes species, which also acts as the vector species of dengue and chikungunya viruses. Methods. Arrival time of ZIKV importation (i.e., the time at which the first imported case was diagnosed in each imported country was collected from publicly available data sources. Employing a survival analysis model in which the hazard is an inverse function of the effective distance as informed by the airline transportation network data, and using dengue and chikungunya virus transmission data, risks of importation and local transmission were estimated. Results. A total of 78 countries with imported case(s have been identified, with the arrival time ranging from 1 to 44 weeks since the first ZIKV was identified in Brazil, 2015. Whereas the risk of importation was well explained by the airline transportation network data, the risk of local transmission appeared to be best captured by additionally accounting for the presence of dengue and chikungunya viruses. Discussion. The risk of importation may be high given continued global travel of mildly infected travelers but, considering that the public health concerns over ZIKV infection stems from microcephaly, it is more important to focus on the risk of local and widespread transmission that could involve pregnant women. The predicted risk of local transmission was frequently seen in tropical and subtropical countries with dengue or chikungunya epidemic experience.

  1. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    Science.gov (United States)

    Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

    2011-01-01

    Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

  2. Estimation of precipitation rates by measurements of {sup 36}Cl in the GRIP ice core with the PSI/ETH tandem accelerator

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, G.; Baumgartner, S.; Beer, J. [EAWAG, Duebendorf (Switzerland); Synal, H.A. [Paul Scherrer Inst. (PSI), Villigen (Switzerland); Suter, M. [Eidgenoessische Technische Hochschule, Zurich (Switzerland)

    1997-09-01

    Within the European Greenland ice core project (GRIP) {sup 36}Cl AMS measurements have been performed on ice core samples from Summit (Greenland, 73{sup o}N, 37{sup o}W). Most data analysed so far are from the lower part of the ice core. The {sup 36}Cl concentration is well correlated with {delta}{sup 18}O, which is considered as a proxy for paleotemperatures. Assuming that the deposition rate of radionuclides is independent of {delta}{sup 18}O, {sup 36}Cl is used to estimate the relationship between accumulation and {delta}{sup 18}O. The results confirm that the rapid changes of {delta}{sup 18}O, the so-called Dansgaard-Oeschger events, are also reflected in the precipitation rate. (author) 1 fig., 3 refs.

  3. A Local Stable Bootstrap for Power Variations of Pure-Jump Semimartingales and Activity Index Estimation

    DEFF Research Database (Denmark)

    Hounyo, Ulrich; Varneskov, Rasmus T.

    We provide a new resampling procedure - the local stable bootstrap - that is able to mimic the dependence properties of realized power variations for pure-jump semimartingales observed at different frequencies. This allows us to propose a bootstrap estimator and inference procedure for the activity...... index of the underlying process, β, as well as a bootstrap test for whether it obeys a jump-diffusion or a pure-jump process, that is, of the null hypothesis H₀: β=2 against the alternative H₁: βbootstrap power variations, activity index...... estimator, and diffusion test for H0. Moreover, the finite sample size and power properties of the proposed diffusion test are compared to those of benchmark tests using Monte Carlo simulations. Unlike existing procedures, our bootstrap test is correctly sized in general settings. Finally, we illustrate use...

  4. A method for estimating the local area economic damages of Superfund waste sites

    International Nuclear Information System (INIS)

    Walker, D.R.

    1992-01-01

    National Priority List (NPL) sites, or more commonly called Superfund sites, are hazardous waste sites (HWS) deemed by the Environmental Protection Agency (EPA) to impose the greatest risks to human health or welfare or to the environment. HWS are placed and ranked for cleanup on the NPL based on a score derived from the Hazard Ranking System (HRS), which is a scientific assessment of the health and environmental risks posed by HWS. A concern of the HRS is that the rank of sites is not based on benefit-cost analysis. The main objective of this dissertation is to develop a method for estimating the local area economic damages associated with Superfund waste sites. Secondarily, the model is used to derive county-level damage estimates for use in ranking the county level damages from Superfund sites. The conceptual model used to describe the damages associated with Superfund sites is a household-firm location decision model. In this model assumes that households and firms make their location choice based on the local level of wages, rents and amenities. The model was empirically implemented using 1980 census microdata on households and workers in 253 counties across the US. The household sample includes data on the value and structural characteristics of homes. The worker sample includes the annual earnings of workers and a vector worker attributes. The microdata was combined with county level amenity data, including the number of Superfund sites. The hedonic pricing technique was used to estimate the effect of Superfund sites on average annual wages per household and on monthly expenditures on housing. The results show that Superfund sites impose statistically significant damages on households. The annual county damages from Superfund sites for a sample of 151 counties was over 14 billion dollars. The ranking of counties using the damage estimates is correlated with the rank of counties using the HRS

  5. Evaluation of radar-derived precipitation estimates using runoff simulation : report for the NFR Energy Norway funded project 'Utilisation of weather radar data in atmospheric and hydrological models'

    Energy Technology Data Exchange (ETDEWEB)

    Abdella, Yisak; Engeland, Kolbjoern; Lepioufle, Jean-Marie

    2012-11-01

    This report presents the results from the project called 'Utilisation of weather radar data in atmospheric and hydrological models' funded by NFR and Energy Norway. Three precipitation products (radar-derived, interpolated and combination of the two) were generated as input for hydrological models. All the three products were evaluated by comparing the simulated and observed runoff at catchments. In order to expose any bias in the precipitation inputs, no precipitation correction factors were applied. Three criteria were used to measure the performance: Nash, correlation coefficient, and bias. The results shows that the simulations with the combined precipitation input give the best performance. We also see that the radar-derived precipitation estimates give reasonable runoff simulation even without a region specific parameters for the Z-R relationship. All the three products resulted in an underestimation of the estimated runoff, revealing a systematic bias in measurements (e.g. catch deficit, orographic effects, Z-R relationships) that can be improved. There is an important potential of using radar-derived precipitation for simulation of runoff, especially in catchments without precipitation gauges inside.(Author)

  6. NOAA Climate Data Record (CDR) of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), Version 1 Revision 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — PERSIANN Precipitation Climate Data Record (PERSIANN-CDR) is a daily quasi-global precipitation product for the period of 1982 to 2011. The data covers from 60...

  7. A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution.

    Science.gov (United States)

    Lee, Duncan; Rushworth, Alastair; Sahu, Sujit K

    2014-06-01

    Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models. © 2014, The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  8. Distributed Input and State Estimation Using Local Information in Heterogeneous Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dzung Tran

    2017-07-01

    Full Text Available A new distributed input and state estimation architecture is introduced and analyzed for heterogeneous sensor networks. Specifically, nodes of a given sensor network are allowed to have heterogeneous information roles in the sense that a subset of nodes can be active (that is, subject to observations of a process of interest and the rest can be passive (that is, subject to no observation. Both fixed and varying active and passive roles of sensor nodes in the network are investigated. In addition, these nodes are allowed to have non-identical sensor modalities under the common underlying assumption that they have complimentary properties distributed over the sensor network to achieve collective observability. The key feature of our framework is that it utilizes local information not only during the execution of the proposed distributed input and state estimation architecture but also in its design in that global uniform ultimate boundedness of error dynamics is guaranteed once each node satisfies given local stability conditions independent from the graph topology and neighboring information of these nodes. As a special case (e.g., when all nodes are active and a positive real condition is satisfied, the asymptotic stability can be achieved with our algorithm. Several illustrative numerical examples are further provided to demonstrate the efficacy of the proposed architecture.

  9. Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

    Science.gov (United States)

    Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

    2017-09-01

    Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

  10. Nonlinear estimation-based dipole source localization for artificial lateral line systems

    International Nuclear Information System (INIS)

    Abdulsadda, Ahmad T; Tan Xiaobo

    2013-01-01

    As a flow-sensing organ, the lateral line system plays an important role in various behaviors of fish. An engineering equivalent of a biological lateral line is of great interest to the navigation and control of underwater robots and vehicles. A vibrating sphere, also known as a dipole source, can emulate the rhythmic movement of fins and body appendages, and has been widely used as a stimulus in the study of biological lateral lines. Dipole source localization has also become a benchmark problem in the development of artificial lateral lines. In this paper we present two novel iterative schemes, referred to as Gauss–Newton (GN) and Newton–Raphson (NR) algorithms, for simultaneously localizing a dipole source and estimating its vibration amplitude and orientation, based on the analytical model for a dipole-generated flow field. The performance of the GN and NR methods is first confirmed with simulation results and the Cramer–Rao bound (CRB) analysis. Experiments are further conducted on an artificial lateral line prototype, consisting of six millimeter-scale ionic polymer–metal composite sensors with intra-sensor spacing optimized with CRB analysis. Consistent with simulation results, the experimental results show that both GN and NR schemes are able to simultaneously estimate the source location, vibration amplitude and orientation with comparable precision. Specifically, the maximum localization error is less than 5% of the body length (BL) when the source is within the distance of one BL. Experimental results have also shown that the proposed schemes are superior to the beamforming method, one of the most competitive approaches reported in literature, in terms of accuracy and computational efficiency. (paper)

  11. Static roll-tilt over 5 minutes locally distorts the internal estimate of direction of gravity.

    Science.gov (United States)

    Tarnutzer, A A; Bockisch, C J; Straumann, D; Marti, S; Bertolini, G

    2014-12-01

    The subjective visual vertical (SVV) indicates perceived direction of gravity. Even in healthy human subjects, roll angle-dependent misestimations, roll overcompensation (A-effect, head-roll > 60° and head-roll tilt, SVV estimates when upright are biased toward the preceding roll position, which indicates that perceived vertical (PV) is shifted by the prior tilt (Tarnutzer AA, Bertolini G, Bockisch CJ, Straumann D, Marti S. PLoS One 8: e78079, 2013). Hypothetically, PV in any roll position could be biased toward the previous roll position. We asked whether such a "global" bias occurs or whether the bias is "local". The SVV of healthy human subjects (N = 9) was measured in nine roll positions (-120° to +120°, steps = 30°) after 5 min of roll-tilt in one of two adaptation positions (±90°) and compared with control trials without adaptation. After adapting, adjustments were shifted significantly (P tilted positions (±30°, ±60°) and upright only. We computationally simulated errors based on the sum of a monotonically increasing function (producing roll undercompensation) and a mixture of Gaussian functions (representing roll overcompensation centered around PV). In combination, the pattern of A- and E-effects could be generated. By shifting the function representing local overcompensation toward the adaptation position, the experimental postadaptation data could be fitted successfully. We conclude that prolonged roll-tilt locally distorts PV rather than globally shifting it. Short-term adaptation of roll overcompensation may explain these shifts and could reflect the brain's strategy to optimize SVV estimates around recent roll positions. Thus postural stability can be improved by visually-mediated compensatory responses at any sustained body-roll orientation. Copyright © 2014 the American Physiological Society.

  12. MHODE: a local-homogeneity theory for improved source-parameter estimation of potential fields

    Science.gov (United States)

    Fedi, Maurizio; Florio, Giovanni; Paoletti, Valeria

    2015-08-01

    We describe a multihomogeneity theory for source-parameter estimation of potential fields. Similar to what happens for random source models, where the monofractal scaling-law has been generalized into a multifractal law, we propose to generalize the homogeneity law into a multihomogeneity law. This allows a theoretically correct approach to study real-world potential fields, which are inhomogeneous and so do not show scale invariance, except in the asymptotic regions (very near to or very far from their sources). Since the scaling properties of inhomogeneous fields change with the scale of observation, we show that they may be better studied at a set of scales than at a single scale and that a multihomogeneous model is needed to explain its complex scaling behaviour. In order to perform this task, we first introduce fractional-degree homogeneous fields, to show that: (i) homogeneous potential fields may have fractional or integer degree; (ii) the source-distributions for a fractional-degree are not confined in a bounded region, similarly to some integer-degree models, such as the infinite line mass and (iii) differently from the integer-degree case, the fractional-degree source distributions are no longer uniform density functions. Using this enlarged set of homogeneous fields, real-world anomaly fields are studied at different scales, by a simple search, at any local window W, for the best homogeneous field of either integer or fractional-degree, this yielding a multiscale set of local homogeneity-degrees and depth estimations which we call multihomogeneous model. It is so defined a new technique of source parameter estimation (Multi-HOmogeneity Depth Estimation, MHODE), permitting retrieval of the source parameters of complex sources. We test the method with inhomogeneous fields of finite sources, such as faults or cylinders, and show its effectiveness also in a real-case example. These applications show the usefulness of the new concepts, multihomogeneity and

  13. Estimation of genetic parameters for milk traits in Romanian local sheep breed

    Directory of Open Access Journals (Sweden)

    Pelmus RS

    2014-03-01

    Full Text Available Objective. Estimate the genetic parameters for milk traits in a Romanian local sheep population Teleorman Black Head. Material and methods. Records of 262 sheep belonging to 17 rams and 139 ewes were used in the study. The following traits were investigated: milk yield, fat yield, protein yield, fat percentage and protein percentage. The genetic parameters were estimated using the Restricted Maximum Likelihood method, with a model including maternal effects. Results. The results from our study revealed that direct heritability estimates were moderate for milk yield (0.449, fat yield (0.442, protein yield (0.386 while for protein percentage (0.708 and fat percentage (0.924 were high. The high direct and maternal genetic correlation was between milk yield and protein yield (0.979, 0.973 and between protein yield and fat yield (0.952, 0.913 while the phenotypic correlation between the milk yield and fat yield (0.968, the milk yield and protein yield (0.967, fat yield and protein yield (0.936 was high and positive. Conclusions. The genetic parameters are important in selection program on this breed for genetic improvement.

  14. Estimating soil hydrological response by combining precipitation-runoff modeling and hydro-functional soil homogeneous units

    Science.gov (United States)

    Aroca-Jimenez, Estefania; Bodoque, Jose Maria; Diez-Herrero, Andres

    2015-04-01

    Flash floods constitute one of the natural hazards better able to generate risk, particularly with regard to Society. The complexity of this process and its dependence on various factors related to the characteristics of the basin and rainfall make flash floods are difficult to characterize in terms of their hydrological response.To do this, it is essential a proper analysis of the so called 'initial abstractions'. Among all of these processes, infiltration plays a crucial role in explaining the occurrence of floods in mountainous basins.For its characterization the Green-Ampt model , which depends on the characteristics of rainfall and physical properties of soil has been used in this work.This is a method enabling to simulate floods in mountainous basins where hydrological response is sub-daily. However, it has the disadvantage that it is based on physical properties of soil which have a high spatial variability. To address this difficulty soil mapping units have been delineated according to the geomorphological landforms and elements. They represent hydro-functional mapping units that are theoretically homogeneous from the perspective of the pedostructure parameters of the pedon. So the soil texture of each homogeneous group of landform units was studied by granulometric analyses using standarized sieves and Sedigraph devices. In addition, uncertainty associated with the parameterization of the Green-Ampt method has been estimated by implementing a Monte Carlo approach, which required assignment of the proper distribution function to each parameter.The suitability of this method was contrasted by calibrating and validating a hydrological model, in which the generation of runoff hydrograph has been simulated using the SCS unit hydrograph (HEC-GeoHMS software), while flood wave routing has been characterized using the Muskingum-Cunge method. Calibration and validation of the model was from the use of an automatic routine based on the employ of the search algorithm

  15. Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12

    Science.gov (United States)

    Thompson, Ryan F.; Wattier, Chelsea M.; Liggett, Richard R.; Truax, Ryan A.

    2014-01-01

    In 2009, the U.S. Geological Survey and South Dakota Department of Transportation (SDDOT) began a study to estimate potential scour at selected bridges on local government (county, township, and municipal) roads in South Dakota. A rapid scour-estimation method (level-1.5) and a more detailed method (level-2) were used to develop estimates of contraction, abutment, and pier scour. Data from 41 level-2 analyses completed for this study were combined with data from level-2 analyses completed in previous studies to develop new South Dakota-specific regression equations: four regional equations for main-channel velocity at the bridge contraction to account for the widely varying stream conditions within South Dakota, and one equation for head change. Velocity data from streamgages also were used in the regression for average velocity through the bridge contraction. Using these new regression equations, scour analyses were completed using the level-1.5 method on 361 bridges on local government roads. Typically, level-1.5 analyses are completed at flows estimated to have annual exceedance probabilities of 1 percent (100-year flood) and 0.2 percent (500-year flood); however, at some sites the bridge would not pass these flows. A level-1.5 analysis was then completed at the flow expected to produce the maximum scour. Data presented for level-1.5 scour analyses at the 361 bridges include contraction, abutment, and pier scour. Estimates of potential contraction scour ranged from 0 to 32.5 feet for the various flows evaluated. Estimated potential abutment scour ranged from 0 to 40.9 feet for left abutments, and from 0 to 37.7 feet for right abutments. Pier scour values ranged from 2.7 to 31.6 feet. The scour depth estimates provided in this report can be used by the SDDOT to compare with foundation depths at each bridge to determine if abutments or piers are at risk of being undermined by scour at the flows evaluated. Replicate analyses were completed at 24 of the 361 bridges

  16. Precipitation Indices Low Countries

    Science.gov (United States)

    van Engelen, A. F. V.; Ynsen, F.; Buisman, J.; van der Schrier, G.

    2009-09-01

    (+2): Wide scale river flooding, marshy acres and meadows.-Farmers cope with poor harvests of hay, grains, fruit etc. resulting in famines.-Late grape harvests, poor yield quantity and quality of wine. Wet period (+1): High water levels cq discharges of major rivers, tributaries and brooks, local river floodings, marshy acres and meadows in the low lying areas.-Wearisome and hampered agriculture. Normal (0) Dry period (-1): Low water levels cq discharges of major rivers, tributaries and brooks. Some brooks may dry up.-Summer half year: local short of yield of grass, hay and other forage.-Summer half year: moor-, peat- and forest fires. Very dry period (-2): Very low water levels cq discharges of major rivers and tributaries. Brooks and wells dry up. Serious shortage of drinking water; especially in summer.-Major agricultural damage, shortage of water, mortality stock of cattle. Shortage of grain. Flour can not be produced due to water mills running out of water, shortage of bread, bread riots, famines.-Large scale forest and peat areas, resulting in serious air pollution. Town fires. By verifying the historical evidence on these criterions, a series of 5 step indices ranging from very dry to very wet for summer and winter half year of the Low Countries was obtained. Subsequently these indices series were compared with the instrumentally observed seasonal precipitation sums for De Bilt (1735-2008), which is considered to be representative for the Central Netherlands. For winter (Oct-March) and summer half year (Apr.-Sept.) the accumulated precipitation amounts are calculated; these amounts are approximately normally distributed. Based on this distribution, the cumulative frequency distribution is calculated. By tabulating the number of summers in the pre-instrumental period 1201-1750 for each of the drought classes, a distribution is calculated which is then related to the modern accumulated precipitation distribution. Assuming that the accumulated precipitation amount

  17. Factors controlling stable isotope composition of European precipitation

    International Nuclear Information System (INIS)

    Rozanski, K.; Sonntag, C.; Muennich, K.O.

    1982-01-01

    The seasonal and spatial variations of stable isotope ratios in present day European precipitation are simulated with a simple multibox model of the mean west-east horizontal transport of the atmospheric water vapour across the European continent. Isotope fractionation during the formation of precipitation leads to an increasing depletion of heavy isotopes in the residual air moisture as it moves towards the centre of the continent. This isotopic depletion is partly compensated, particularly in summer, by evapotranspiration, which is assumed to transfer soil water into the atmosphere without isotope fractionation. The model estimates are based on horizontal water vapour flux data, varying seasonally between 88 and 130 kg m -1 s -1 for the Atlantic coast region, and on the monthly precipitation, evapotranspiration and surface air temperature data available for various locations in Europe. Both continental and seasonal temperature effects observed in the stable isotope composition of European precipitation are fairly well reproduced by the model. The calculations show that the isotopic composition of local precipitation is primarily controlled by regional scale processes, i.e. by the water vapour transport patterns into the continent, and by the average precipitation-evapotranspiration history of the air masses precipitating at a given place. Local parameters such as the surface and/or cloud base temperature or the amount of precipitation modify the isotope ratios only slightly. Implications of the model predictions for the interpretation of stable isotope ratios in earlier periods as they are preserved in ice cores and in groundwater are also discussed. (Auth.)

  18. The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model.

    Science.gov (United States)

    de Graaf-Ruizendaal, Willemijn A; de Bakker, Dinny H

    2013-10-27

    This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match. National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands. Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P 1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions. The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can make a considerable contribution to a primary care system which provides care when and where people need it.

  19. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  20. Estimation of combined sewer overflow discharge: a software sensor approach based on local water level measurements.

    Science.gov (United States)

    Ahm, Malte; Thorndahl, Søren; Nielsen, Jesper E; Rasmussen, Michael R

    2016-12-01

    Combined sewer overflow (CSO) structures are constructed to effectively discharge excess water during heavy rainfall, to protect the urban drainage system from hydraulic overload. Consequently, most CSO structures are not constructed according to basic hydraulic principles for ideal measurement weirs. It can, therefore, be a challenge to quantify the discharges from CSOs. Quantification of CSO discharges are important in relation to the increased environmental awareness of the receiving water bodies. Furthermore, CSO discharge quantification is essential for closing the rainfall-runoff mass-balance in combined sewer catchments. A closed mass-balance is an advantage for calibration of all urban drainage models based on mass-balance principles. This study presents three different software sensor concepts based on local water level sensors, which can be used to estimate CSO discharge volumes from hydraulic complex CSO structures. The three concepts were tested and verified under real practical conditions. All three concepts were accurate when compared to electromagnetic flow measurements.

  1. Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

    Science.gov (United States)

    Casas, R.; Marco, A.; Guerrero, J. J.; Falcó, J.

    2006-12-01

    Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.

  2. Deoxyglucose method for the estimation of local myocardial glucose metabolism with positron computed tomography

    International Nuclear Information System (INIS)

    Ratib, O.; Phelps, M.E.; Huang, S.C.; Henze, E.; Selin, C.E.; Schelbert, H.R.

    1981-01-01

    The deoxyglucose method originally developed for measurements of the local cerebral metabolic rate for glucose has been investigated in terms of its application to studies of the heart with positron computed tomography (PCT) and FDG. Studies were performed in dogs to measure the tissue kinetics of FDG with PCT and by direct arterial-venous sampling. The operational equation developed in our laboratory as an extension of the Sokoloff model was used to analyze the data. The FDG method accurately predicted the true MMRGlc even when the glucose metabolic rate was normal but myocardial blood flow (MBF) was elevated 5 times the control value or when metabolism was reduced to 10% of normal and MBF increased 5 times normal. Improvements in PCT resolution are required to improve the accuracy of the estimates of the rate constants and the MMRGlc

  3. A novel cost-effective parallel narrowband ANC system with local secondary-path estimation

    Science.gov (United States)

    Delegà, Riccardo; Bernasconi, Giancarlo; Piroddi, Luigi

    2017-08-01

    Many noise reduction applications are targeted at multi-tonal disturbances. Active noise control (ANC) solutions for such problems are generally based on the combination of multiple adaptive notch filters. Both the performance and the computational cost are negatively affected by an increase in the number of controlled frequencies. In this work we study a different modeling approach for the secondary path, based on the estimation of various small local models in adjacent frequency subbands, that greatly reduces the impact of reference-filtering operations in the ANC algorithm. Furthermore, in combination with a frequency-specific step size tuning method it provides a balanced attenuation performance over the whole controlled frequency range (and particularly in the high end of the range). Finally, the use of small local models is greatly beneficial for the reactivity of the online secondary path modeling algorithm when the characteristics of the acoustic channels are time-varying. Several simulations are provided to illustrate the positive features of the proposed method compared to other well-known techniques.

  4. Estimating local scaling properties for the classification of interstitial lung disease patterns

    Science.gov (United States)

    Huber, Markus B.; Nagarajan, Mahesh B.; Leinsinger, Gerda; Ray, Lawrence A.; Wismueller, Axel

    2011-03-01

    Local scaling properties of texture regions were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honeycombing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and the estimation of local scaling properties with Scaling Index Method (SIM). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions including the Bonferroni correction. The best classification results were obtained by the set of SIM features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers with the highest accuracy (94.1%, 93.7%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced texture features using local scaling properties can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

  5. Precipitation Nowcast using Deep Recurrent Neural Network

    Science.gov (United States)

    Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

    2016-12-01

    An accurate precipitation nowcast (0-6 hours) with a fine temporal and spatial resolution has always been an important prerequisite for flood warning, streamflow prediction and risk management. Most of the popular approaches used for forecasting precipitation can be categorized into two groups. One type of precipitation forecast relies on numerical modeling of the physical dynamics of atmosphere and another is based on empirical and statistical regression models derived by local hydrologists or meteorologists. Given the recent advances in artificial intelligence, in this study a powerful Deep Recurrent Neural Network, termed as Long Short-Term Memory (LSTM) model, is creatively used to extract the patterns and forecast the spatial and temporal variability of Cloud Top Brightness Temperature (CTBT) observed from GOES satellite. Then, a 0-6 hours precipitation nowcast is produced using a Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) algorithm, in which the CTBT nowcast is used as the PERSIANN algorithm's raw inputs. Two case studies over the continental U.S. have been conducted that demonstrate the improvement of proposed approach as compared to a classical Feed Forward Neural Network and a couple simple regression models. The advantages and disadvantages of the proposed method are summarized with regard to its capability of pattern recognition through time, handling of vanishing gradient during model learning, and working with sparse data. The studies show that the LSTM model performs better than other methods, and it is able to learn the temporal evolution of the precipitation events through over 1000 time lags. The uniqueness of PERSIANN's algorithm enables an alternative precipitation nowcast approach as demonstrated in this study, in which the CTBT prediction is produced and used as the inputs for generating precipitation nowcast.

  6. Precipitous Birth

    Directory of Open Access Journals (Sweden)

    Jennifer Yee

    2017-09-01

    Full Text Available Audience: This scenario was developed to educate emergency medicine residents on the management of a precipitous birth in the emergency department (ED. The case is also appropriate for teaching of medical students and advanced practice providers, as well as reviewing the principles of crisis resource management, teamwork, and communication. Introduction: Patients with precipitous birth require providers to manage two patients simultaneously with limited time and resources. Crisis resource management skills will be tested once baby is delivered, and the neonate will require assessment for potential neonatal resuscitation. Objectives: At the conclusion of the simulation session, learners will be able to manage women who have precipitous deliveries, as well as perform neonatal assessment and management. Method: This session was conducted using high-fidelity simulation, followed by a debriefing session and lecture on precipitous birth management and neonatal evaluation.

  7. Microdiamond grade as a regionalised variable - some basic requirements for successful local microdiamond resource estimation of kimberlites

    Science.gov (United States)

    Stiefenhofer, Johann; Thurston, Malcolm L.; Bush, David E.

    2018-04-01

    Microdiamonds offer several advantages as a resource estimation tool, such as access to deeper parts of a deposit which may be beyond the reach of large diameter drilling (LDD) techniques, the recovery of the total diamond content in the kimberlite, and a cost benefit due to the cheaper treatment cost compared to large diameter samples. In this paper we take the first step towards local estimation by showing that micro-diamond samples can be treated as a regionalised variable suitable for use in geostatistical applications and we show examples of such output. Examples of microdiamond variograms are presented, the variance-support relationship for microdiamonds is demonstrated and consistency of the diamond size frequency distribution (SFD) is shown with the aid of real datasets. The focus therefore is on why local microdiamond estimation should be possible, not how to generate such estimates. Data from our case studies and examples demonstrate a positive correlation between micro- and macrodiamond sample grades as well as block estimates. This relationship can be demonstrated repeatedly across multiple mining operations. The smaller sample support size for microdiamond samples is a key difference between micro- and macrodiamond estimates and this aspect must be taken into account during the estimation process. We discuss three methods which can be used to validate or reconcile the estimates against macrodiamond data, either as estimates or in the form of production grades: (i) reconcilliation using production data, (ii) by comparing LDD-based grade estimates against microdiamond-based estimates and (iii) using simulation techniques.

  8. TCA precipitation.

    Science.gov (United States)

    Koontz, Laura

    2014-01-01

    Trichloroacetic acid (TCA) precipitation of proteins is commonly used to concentrate protein samples or remove contaminants, including salts and detergents, prior to downstream applications such as SDS-PAGE or 2D-gels. TCA precipitation denatures the protein, so it should not be used if the protein must remain in its folded state (e.g., if you want to measure a biochemical activity of the protein). © 2014 Elsevier Inc. All rights reserved.

  9. STRONTIUM PRECIPITATION

    Science.gov (United States)

    McKenzie, T.R.

    1960-09-13

    A process is given for improving the precipitation of strontium from an aqueous phosphoric-acid-containing solution with nickel or cobalt ferrocyanide by simultaneously precipitating strontium or calcium phosphate. This is accomplished by adding to the ferrocyanide-containing solution calcium or strontium nitrate in a quantity to yield a concentration of from 0.004 to 0.03 and adjusting the pH of the solution to a value of above 8.

  10. Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Takamiya, Masanori [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan and Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Nakamura, Mitsuhiro, E-mail: m-nkmr@kuhp.kyoto-u.ac.jp; Akimoto, Mami; Ueki, Nami; Yamada, Masahiro; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Tanabe, Hiroaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047 (Japan); Kokubo, Masaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047, Japan and Department of Radiation Oncology, Kobe City Medical Center General Hospital, Kobe 650-0047 (Japan); Itoh, Akio [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501 (Japan)

    2016-04-15

    Purpose: To assess the target localization error (TLE) in terms of the distance between the target and the localization point estimated from the surrogates (|TMD|), the average of respiratory motion for the surrogates and the target (|aRM|), and the number of fiducial markers used for estimating the target (n). Methods: This study enrolled 17 lung cancer patients who subsequently underwent four fractions of real-time tumor tracking irradiation. Four or five fiducial markers were implanted around the lung tumor. The three-dimensional (3D) distance between the tumor and markers was at maximum 58.7 mm. One of the markers was used as the target (P{sub t}), and those markers with a 3D |TMD{sub n}| ≤ 58.7 mm at end-exhalation were then selected. The estimated target position (P{sub e}) was calculated from a localization point consisting of one to three markers except P{sub t}. Respiratory motion for P{sub t} and P{sub e} was defined as the root mean square of each displacement, and |aRM| was calculated from the mean value. TLE was defined as the root mean square of each difference between P{sub t} and P{sub e} during the monitoring of each fraction. These procedures were performed repeatedly using the remaining markers. To provide the best guidance on the answer with n and |TMD|, fiducial markers with a 3D |aRM ≥ 10 mm were selected. Finally, a total of 205, 282, and 76 TLEs that fulfilled the 3D |TMD| and 3D |aRM| criteria were obtained for n = 1, 2, and 3, respectively. Multiple regression analysis (MRA) was used to evaluate TLE as a function of |TMD| and |aRM| in each n. Results: |TMD| for n = 1 was larger than that for n = 3. Moreover, |aRM| was almost constant for all n, indicating a similar scale for the marker’s motion near the lung tumor. MRA showed that |aRM| in the left–right direction was the major cause of TLE; however, the contribution made little difference to the 3D TLE because of the small amount of motion in the left–right direction. The TLE

  11. Estimating concentration of fluoride in edible leaves locally grown around Raipur, Chhattisgarh

    Directory of Open Access Journals (Sweden)

    Anubhuti Jain

    2017-01-01

    Full Text Available Introduction: Fluorine is the 13th most abundant element in the earth crust and is available in various environmental, clinical, and food samples in varied concentrations. Aim: To estimate concentration of fluoride in five medicinal and five nonmedicinal edible leaves locally grown around Raipur, Chhattisgarh, India. Materials and Methods: Samples of ten medicinal and nonmedicinal edible leaves, namely, spinach (Spinacia oleracea, coriander leaves (Coriandrum sativum, chawli bhaji (Amaranthus spinach, lal bhaji (Alternanthera bettzickiana, mooli bhaji (Raphanus sativus, neem (Azadirachta indica, tulsi (Ocimum tenuiflorum, mint leaves (Mentha longifolia, betel leaves (Piper betle, and bael leaves (Aegle marmelos were collected in the clean polyethene bags. After thorough washing with water, leaves were left to dry in ambient temperature and crushed into powder using a mixer grinder. One gram of each of the powdered samples was taken and analyzed for fluoride concentration using a 2-(4-sulfophenylazo 1,8-dihydroxy-3,6-naphthalenedisulfonic acid trisodium salt spectrophotometric method. Results: The presence of fluoride in varied concentrations in locally grown edible leaves were analyzed. The highest concentration of fluoride was reported in tulsi (6.0 μg/g and lowest in mint leaves (1.1 μg/g. Two edible leaves, neem and bael, showed fluoride concentration below detection limit. Conclusion: Knowledge regarding the importance of edible leaves may be lost in the near future unless efforts are made to educate younger generations about their importance. Hence, the time has come to make good use of centuries-old knowledge through modern approaches for their better economic and therapeutic utilization.

  12. Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

    Energy Technology Data Exchange (ETDEWEB)

    Tadayyon, Hadi [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Sadeghi-Naini, Ali; Czarnota, Gregory, E-mail: Gregory.Czarnota@sunnybrook.ca [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario M5T 1P5 (Canada); Wirtzfeld, Lauren [Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Wright, Frances C. [Division of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada)

    2014-01-15

    Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor

  13. Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

    International Nuclear Information System (INIS)

    Tadayyon, Hadi; Sadeghi-Naini, Ali; Czarnota, Gregory; Wirtzfeld, Lauren; Wright, Frances C.

    2014-01-01

    Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor

  14. Spatial variability in photosynthetic and heterotrophic activity drives localized δ13C org fluctuations and carbonate precipitation in hypersaline microbial mats.

    Science.gov (United States)

    Houghton, J; Fike, D; Druschel, G; Orphan, V; Hoehler, T M; Des Marais, D J

    2014-11-01

    Modern laminated photosynthetic microbial mats are ideal environments to study how microbial activity creates and modifies carbon and sulfur isotopic signatures prior to lithification. Laminated microbial mats from a hypersaline lagoon (Guerrero Negro, Baja California, Mexico) maintained in a flume in a greenhouse at NASA Ames Research Center were sampled for δ(13) C of organic material and carbonate to assess the impact of carbon fixation (e.g., photosynthesis) and decomposition (e.g., bacterial respiration) on δ(13) C signatures. In the photic zone, the δ(13) C org signature records a complex relationship between the activities of cyanobacteria under variable conditions of CO2 limitation with a significant contribution from green sulfur bacteria using the reductive TCA cycle for carbon fixation. Carbonate is present in some layers of the mat, associated with high concentrations of bacteriochlorophyll e (characteristic of green sulfur bacteria) and exhibits δ(13) C signatures similar to DIC in the overlying water column (-2.0‰), with small but variable decreases consistent with localized heterotrophic activity from sulfate-reducing bacteria (SRB). Model results indicate respiration rates in the upper 12 mm of the mat alter in situ pH and HCO3- concentrations to create both phototrophic CO2 limitation and carbonate supersaturation, leading to local precipitation of carbonate minerals. The measured activity of SRB with depth suggests they variably contribute to decomposition in the mat dependent on organic substrate concentrations. Millimeter-scale variability in the δ(13) C org signature beneath the photic zone in the mat is a result of shifting dominance between cyanobacteria and green sulfur bacteria with the aggregate signature overprinted by heterotrophic reworking by SRB and methanogens. These observations highlight the impact of sedimentary microbial processes on δ(13) C org signatures; these processes need to be considered when attempting to relate

  15. Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation

    Science.gov (United States)

    Pasaniuc, Bogdan; Sankararaman, Sriram; Torgerson, Dara G.; Gignoux, Christopher; Zaitlen, Noah; Eng, Celeste; Rodriguez-Cintron, William; Chapela, Rocio; Ford, Jean G.; Avila, Pedro C.; Rodriguez-Santana, Jose; Chen, Gary K.; Le Marchand, Loic; Henderson, Brian; Reich, David; Haiman, Christopher A.; Gonzàlez Burchard, Esteban; Halperin, Eran

    2013-01-01

    Motivation: Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging. Results: Here, we use 489 nuclear families from the mainland USA, Puerto Rico and Mexico in conjunction with 3204 unrelated Latinos from the Multiethnic Cohort study to provide the first empirical characterization of local ancestry inference accuracy in Latinos. Our approach for identifying errors does not rely on simulations but on the observation that local ancestry in families follows Mendelian inheritance. We measure the rate of local ancestry assignments that lead to Mendelian inconsistencies in local ancestry in trios (MILANC), which provides a lower bound on errors in the local ancestry estimates. We show that MILANC rates observed in simulations underestimate the rate observed in real data, and that MILANC varies substantially across the genome. Second, across a wide range of methods, we observe that loci with large deviations in local ancestry also show enrichment in MILANC rates. Therefore, local ancestry estimates at such loci should be interpreted with caution. Finally, we reconstruct ancestral haplotype panels to be used as reference panels in local ancestry inference and show that ancestry inference is significantly improved by incoroprating these reference panels. Availability and implementation: We provide the reconstructed reference panels together with the maps of MILANC rates as a public resource for researchers analyzing local ancestry in Latinos at http://bogdanlab.pathology.ucla.edu. Contact: bpasaniuc@mednet.ucla.edu Supplementary information: Supplementary data are

  16. A hybrid downscaling procedure for estimating the vertical distribution of ambient temperature in local scale

    Science.gov (United States)

    Yiannikopoulou, I.; Philippopoulos, K.; Deligiorgi, D.

    2012-04-01

    The vertical thermal structure of the atmosphere is defined by a combination of dynamic and radiation transfer processes and plays an important role in describing the meteorological conditions at local scales. The scope of this work is to develop and quantify the predictive ability of a hybrid dynamic-statistical downscaling procedure to estimate the vertical profile of ambient temperature at finer spatial scales. The study focuses on the warm period of the year (June - August) and the method is applied to an urban coastal site (Hellinikon), located in eastern Mediterranean. The two-step methodology initially involves the dynamic downscaling of coarse resolution climate data via the RegCM4.0 regional climate model and subsequently the statistical downscaling of the modeled outputs by developing and training site-specific artificial neural networks (ANN). The 2.5ox2.5o gridded NCEP-DOE Reanalysis 2 dataset is used as initial and boundary conditions for the dynamic downscaling element of the methodology, which enhances the regional representivity of the dataset to 20km and provides modeled fields in 18 vertical levels. The regional climate modeling results are compared versus the upper-air Hellinikon radiosonde observations and the mean absolute error (MAE) is calculated between the four grid point values nearest to the station and the ambient temperature at the standard and significant pressure levels. The statistical downscaling element of the methodology consists of an ensemble of ANN models, one for each pressure level, which are trained separately and employ the regional scale RegCM4.0 output. The ANN models are theoretically capable of estimating any measurable input-output function to any desired degree of accuracy. In this study they are used as non-linear function approximators for identifying the relationship between a number of predictor variables and the ambient temperature at the various vertical levels. An insight of the statistically derived input

  17. Local power peaking factor estimation in nuclear fuel by artificial neural networks

    International Nuclear Information System (INIS)

    Montes, Jose Luis; Francois, Juan Luis; Ortiz, Juan Jose; Martin-del-Campo, Cecilia; Perusquia, Raul

    2009-01-01

    This paper presents the training of an artificial neural network (ANN) to accurately predict, in very short time, a physical parameter used in nuclear fuel reactor optimization: the local power peaking factor (LPPF) in a typical boiling water reactor (BWR) fuel lattice. The ANN training patterns are distribution of fissile and burnable poison materials in the fuel lattice and their associated LPPF. These data were obtained by modeling the fuel lattices with a neutronic simulator: the HELIOS transport code. The combination of the pin U 235 enrichment and the Gd 2 O 3 (gadolinia) concentration, inside the 10 x 10 fuel lattice array, was encoded by three different methods. However, the only encoding method that was able to give a good prediction of the LPPF was the method which added the U 235 enrichment and the gadolinia concentration. The results show that the relative error in the estimation of the LPPF, obtained by the trained ANN, ranged from 0.022% to 0.045%, with respect to the HELIOS results

  18. Observation of aftershocks of the 2003 Tokachi-Oki earthquake for estimation of local site effects

    Science.gov (United States)

    Yamanaka, Hiroaki; Motoki, Kentaro; Etoh, Kiminobu; Murayama, Masanari; Komaba, Nobuhiko

    2004-03-01

    Observation of aftershocks of the 2003 Tokachi-Oki earthquake was conducted in the southern part of the Tokachi basin in Hokkaido, Japan for estimation of local site effects. We installed accelerographs at 12 sites in Chokubetsu, Toyokoro, and Taiki areas, where large strong motion records were obtained during the main shock at stations of the K-NET and KiK-net. The stations of the aftershock observation are situated with different geological conditions and some of the sites were installed on Pleistocene layers as reference sites. The site amplifications are investigated using spectral ratio of S-waves from the aftershocks. The S-wave amplification factor is dominant at a period of about 1 second at the site near the KiK-net site in Toyokoro. This amplification fits well with calculated 1D amplification of S-wave in alluvial layers with a thickness of 50 meters. In addition to the site effects, we detected nonlinear amplification of the soft soils only during the main shock. The site effects at the strong motion site of the K-NET at Chokubetsu have a dominate peak at a period of 0.4 seconds. This amplification is due to soft soils having a thickness of about 13 meters. Contrary to the results at the two areas, site effects are not significantly different at the stations in the Taiki area, because of similarity on surface geological conditions.

  19. Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

    Directory of Open Access Journals (Sweden)

    Marco A

    2006-01-01

    Full Text Available Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.. In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS, even when nearly half the measures suffered from NLOS or other coarse errors.

  20. A simulation of Earthquake Loss Estimation in Southeastern Korea using HAZUS and the local site classification Map

    Science.gov (United States)

    Kang, S.; Kim, K.

    2013-12-01

    Regionally varying seismic hazards can be estimated using an earthquake loss estimation system (e.g. HAZUS-MH). The estimations for actual earthquakes help federal and local authorities develop rapid, effective recovery measures. Estimates for scenario earthquakes help in designing a comprehensive earthquake hazard mitigation plan. Local site characteristics influence the ground motion. Although direct measurements are desirable to construct a site-amplification map, such data are expensive and time consuming to collect. Thus we derived a site classification map of the southern Korean Peninsula using geologic and geomorphologic data, which are readily available for the entire southern Korean Peninsula. Class B sites (mainly rock) are predominant in the area, although localized areas of softer soils are found along major rivers and seashores. The site classification map is compared with independent site classification studies to confirm our site classification map effectively represents the local behavior of site amplification during an earthquake. We then estimated the losses due to a magnitude 6.7 scenario earthquake in Gyeongju, southeastern Korea, with and without the site classification map. Significant differences in loss estimates were observed. The loss without the site classification map decreased without variation with increasing epicentral distance, while the loss with the site classification map varied from region to region, due to both the epicentral distance and local site effects. The major cause of the large loss expected in Gyeongju is the short epicentral distance. Pohang Nam-Gu is located farther from the earthquake source region. Nonetheless, the loss estimates in the remote city are as large as those in Gyeongju and are attributed to the site effect of soft soil found widely in the area.

  1. Convenience Sampling of Children Presenting to Hospital-Based Outpatient Clinics to Estimate Childhood Obesity Levels in Local Surroundings.

    Science.gov (United States)

    Gilliland, Jason; Clark, Andrew F; Kobrzynski, Marta; Filler, Guido

    2015-07-01

    Childhood obesity is a critical public health matter associated with numerous pediatric comorbidities. Local-level data are required to monitor obesity and to help administer prevention efforts when and where they are most needed. We hypothesized that samples of children visiting hospital clinics could provide representative local population estimates of childhood obesity using data from 2007 to 2013. Such data might provide more accurate, timely, and cost-effective obesity estimates than national surveys. Results revealed that our hospital-based sample could not serve as a population surrogate. Further research is needed to confirm this finding.

  2. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    Science.gov (United States)

    Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  3. Radar-based quantitative precipitation estimation for the identification of debris flow occurrence over earthquake-affected regions in Sichuan, China

    Science.gov (United States)

    Shi, Zhao; Wei, Fangqiang; Chandrasekar, Venkatachalam

    2018-03-01

    Both Ms 8.0 Wenchuan earthquake on 12 May 2008 and Ms 7.0 Lushan earthquake on 20 April 2013 occurred in the province of Sichuan, China. In the earthquake-affected mountainous area, a large amount of loose material caused a high occurrence of debris flow during the rainy season. In order to evaluate the rainfall intensity-duration (I-D) threshold of the debris flow in the earthquake-affected area, and to fill up the observational gaps caused by the relatively scarce and low-altitude deployment of rain gauges in this area, raw data from two S-band China New Generation Doppler Weather Radar (CINRAD) were captured for six rainfall events that triggered 519 debris flows between 2012 and 2014. Due to the challenges of radar quantitative precipitation estimation (QPE) over mountainous areas, a series of improvement measures are considered: a hybrid scan mode, a vertical reflectivity profile (VPR) correction, a mosaic of reflectivity, a merged rainfall-reflectivity (R - Z) relationship for convective and stratiform rainfall, and rainfall bias adjustment with Kalman filter (KF). For validating rainfall accumulation over complex terrains, the study areas are divided into two kinds of regions by the height threshold of 1.5 km from the ground. Three kinds of radar rainfall estimates are compared with rain gauge measurements. It is observed that the normalized mean bias (NMB) is decreased by 39 % and the fitted linear ratio between radar and rain gauge observation reaches at 0.98. Furthermore, the radar-based I-D threshold derived by the frequentist method is I = 10.1D-0.52 and is underestimated by uncorrected raw radar data. In order to verify the impacts on observations due to spatial variation, I-D thresholds are identified from the nearest rain gauge observations and radar observations at the rain gauge locations. It is found that both kinds of observations have similar I-D thresholds and likewise underestimate I-D thresholds due to undershooting at the core of convective

  4. Avaliação de estimativas de campos de precipitação para modelagem hidrológica distribuída Assessment of estimated precipitation fields for distributed hydrologic modeling

    Directory of Open Access Journals (Sweden)

    Adriano Rolim da Paz

    2011-03-01

    Full Text Available É crescente a disponibilidade e utilização de campos de chuva estimados por sensoriamento remoto ou calculados por modelos de circulação da atmosfera, os quais são freqüentemente utilizados como entrada para modelos hidrológicos distribuídos. A distribuição espacial dos campos de chuva estimados é altamente relevante e deve ser avaliada frente aos campos de chuva observados. Este artigo propõe um método de comparação espaço-temporal entre campos de chuva observados e estimados baseado na comparação pixel a pixel e na construção de tabelas de contingência. Duas abordagens são utilizadas: (i a análise integrada no espaço gera índices de performance que retratam a qualidade do campo de chuva estimada em reproduzir a ocorrência de chuva observada ao longo do tempo; (ii a análise integrada no tempo produz mapas dos índices de performance que resumem a destreza das estimativas de ocorrência de chuva em cada pixel. Como exemplo de aplicação, é analisada a chuva estimada na climatologia do modelo global de circulação da atmosfera CPTEC/COLA sobre a bacia do Rio Grande. Utilizando-se cinco índices de performance, o método proposto permitiu identificar variações sazonais e padrões espaciais na performance das estimativas de chuva em relação a campos de chuva derivados de observações em pluviômetros.There is an increasing availability and application of precipitation fields estimated by remote sensing or calculated by atmospheric circulation models, which are frequently used as input for distributed hydrological models. The spatial distribution of the estimated precipitation fields is extremely important and must be verified against observed precipitation fields. This paper proposes a method for spatiotemporal comparison between observed and estimated precipitation fields based on a pixel by pixel comparison and on contingency tables. Two distinct approaches are carried out: (i the spatial integrated analysis

  5. Precipitation Matters

    Science.gov (United States)

    McDuffie, Thomas

    2007-01-01

    Although weather, including its role in the water cycle, is included in most elementary science programs, any further examination of raindrops and snowflakes is rare. Together rain and snow make up most of the precipitation that replenishes Earth's life-sustaining fresh water supply. When viewed individually, raindrops and snowflakes are quite…

  6. Identification and Quantification of Uncertainties Related to Using Distributed X-band Radar Estimated Precipitation as input in Urban Drainage Models

    DEFF Research Database (Denmark)

    Pedersen, Lisbeth

    The Local Area Weather Radar (LAWR) is a small scale weather radar providing distributed measurements of rainfall primarily for use as input in hydrological applications. As any other weather radar the LAWR measurement of the rainfall is an indirect measurement since it does not measure the rainf......The Local Area Weather Radar (LAWR) is a small scale weather radar providing distributed measurements of rainfall primarily for use as input in hydrological applications. As any other weather radar the LAWR measurement of the rainfall is an indirect measurement since it does not measure...... are quantified using statistical methods. Furthermore, the present calibration method is reviewed and a new extended calibration method has been developed and tested resulting in improved rainfall estimates. As part of the calibration analysis a number of elements affecting the LAWR performance were identified...... in connection with boundary assignment besides general improved understanding of the benefits and pitfalls in using distributed rainfall data as input to models. In connection with the use of LAWR data in urban drainage context, the potential for using LAWR data for extreme rainfall statistics has been studied...

  7. Seasonal to Interannual Variability of Satellite-Based Precipitation Estimates in the Pacific Ocean Associated with ENSO from 1998 to 2014

    Directory of Open Access Journals (Sweden)

    Xueyan Hou

    2016-10-01

    Full Text Available Based on a widely used satellite precipitation product (TRMM Multi-satellite Precipitation Analysis 3B43, we analyzed the spatiotemporal variability of precipitation over the Pacific Ocean for 1998–2014 at seasonal and interannual timescales, separately, using the conventional empirical orthogonal function (EOF and investigated the seasonal patterns associated with El Niño–Southern Oscillation (ENSO cycles using season-reliant empirical orthogonal function (SEOF analysis. Lagged correlation analysis was also applied to derive the lead/lag correlations of the first two SEOF modes for precipitation with Pacific Decadal Oscillation (PDO and two types of El Niño, i.e., central Pacific (CP El Niño and eastern Pacific (EP El Niño. We found that: (1 The first two seasonal EOF modes for precipitation represent the annual cycle of precipitation variations for the Pacific Ocean and the first interannual EOF mode shows the spatiotemporal variability associated with ENSO; (2 The first SEOF mode for precipitation is simultaneously associated with the development of El Niño and most likely coincides with CP El Niño. The second SEOF mode lagged behind ENSO by one year and is associated with post-El Niño years. PDO modulates precipitation variability significantly only when ENSO occurs by strengthening and prolonging the impacts of ENSO; (3 Seasonally evolving patterns of the first two SEOF modes represent the consecutive precipitation patterns associated with the entire development of EP El Niño and the following recovery year. The most significant variation occurs over the tropical Pacific, especially in the Intertropical Convergence Zone (ITCZ and South Pacific Convergence Zone (SPCZ; (4 Dry conditions in the western basin of the warm pool and wet conditions along the ITCZ and SPCZ bands during the mature phase of El Niño are associated with warm sea surface temperatures in the central tropical Pacific, and a subtropical anticyclone dominating

  8. Steps toward a CONUS-wide reanalysis with archived NEXRAD data using National Mosaic and Multisensor Quantitative Precipitation Estimation (NMQ/Q2) algorithms

    Science.gov (United States)

    Stevens, S. E.; Nelson, B. R.; Langston, C.; Qi, Y.

    2012-12-01

    The National Mosaic and Multisensor QPE (NMQ/Q2) software suite, developed at NOAA's National Severe Storms Laboratory (NSSL) in Norman, OK, addresses a large deficiency in the resolution of currently archived precipitation datasets. Current standards, both radar- and satellite-based, provide for nationwide precipitation data with a spatial resolution of up to 4-5 km, with a temporal resolution as fine as one hour. Efforts are ongoing to process archived NEXRAD data for the period of record (1996 - present), producing a continuous dataset providing precipitation data at a spatial resolution of 1 km, on a timescale of only five minutes. In addition, radar-derived precipitation data are adjusted hourly using a wide variety of automated gauge networks spanning the United States. Applications for such a product range widely, from emergency management and flash flood guidance, to hydrological studies and drought monitoring. Results are presented from a subset of the NEXRAD dataset, providing basic statistics on the distribution of rainrates, relative frequency of precipitation types, and several other variables which demonstrate the variety of output provided by the software. Precipitation data from select case studies are also presented to highlight the increased resolution provided by this reanalysis and the possibilities that arise from the availability of data on such fine scales. A previously completed pilot project and steps toward a nationwide implementation are presented along with proposed strategies for managing and processing such a large dataset. Reprocessing efforts span several institutions in both North Carolina and Oklahoma, and data/software coordination are key in producing a homogeneous record of precipitation to be archived alongside NOAA's other Climate Data Records. Methods are presented for utilizing supercomputing capability in expediting processing, to allow for the iterative nature of a reanalysis effort.

  9. Variant selection during α precipitation in Ti–6Al–4V under the influence of local stress – A simulation study

    International Nuclear Information System (INIS)

    Shi, R.; Wang, Y.

    2013-01-01

    Variant selection of α (hexagonal close-packed, hcp) phase during its precipitation from β (body-centered cubic, bcc) matrix plays a key role in determining the microstructural state and mechanical properties of α/β titanium alloys. In this work, we develop a three-dimensional quantitative phase field model to predict variant selection and microstructural evolution during β → α transformation in Ti–6Al–4V (wt.%) under the influence of both external and internal stresses. The model links its inputs directly to thermodynamic and mobility databases, and incorporates the crystallography of bcc to hcp transformation, elastic anisotropy and defects within semi-coherent α/β interfaces in its total free energy formulation. It is found that, for a given undercooling, the development of a transformation texture (also called microtexture) of the α phase due to variant selection during precipitation is determined by the interplay between externally applied stress or strain and internal stress generated by the precipitation reaction itself. For example, the growth of pre-existing α precipitates is accompanied by selective nucleation and growth of secondary α plates of certain variants that may not be the ones preferred by the initially applied stress. Possible measures to reduce transformation texture are discussed

  10. local

    Directory of Open Access Journals (Sweden)

    Abílio Amiguinho

    2005-01-01

    Full Text Available The process of socio-educational territorialisation in rural contexts is the topic of this text. The theme corresponds to a challenge to address it having as main axis of discussion either the problem of social exclusion or that of local development. The reasons to locate the discussion in this last field of analysis are discussed in the first part of the text. Theoretical and political reasons are there articulated because the question is about projects whose intentions and practices call for the political both in the theoretical debate and in the choices that anticipate intervention. From research conducted for several years, I use contributions that aim at discuss and enlighten how school can be a potential locus of local development. Its identification and recognition as local institution (either because of those that work and live in it or because of those that act in the surrounding context are crucial steps to progressively constitute school as a partner for development. The promotion of the local values and roots, the reconstruction of socio-personal and local identities, the production of sociabilities and the equation and solution of shared problems were the dimensions of a socio-educative intervention, markedly globalising. This scenario, as it is argued, was also, intentionally, one of transformation and of deliberate change of school and of the administration of the educative territoires.

  11. Supervised local error estimation for nonlinear image registration using convolutional neural networks

    NARCIS (Netherlands)

    Eppenhof, Koen A.J.; Pluim, Josien P.W.; Styner, M.A.; Angelini, E.D.

    2017-01-01

    Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation

  12. Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

    Science.gov (United States)

    Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

    2006-01-01

    We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

  13. Local digital algorithms for estimating the mean integrated curvature of r-regular sets

    DEFF Research Database (Denmark)

    Svane, Anne Marie

    , no asymptotically unbiased estimator of this type exists in dimension greater than or equal to three, while for stationary isotropic lattices, asymptotically unbiased estimators are plenty. Both results follow from a general formula that we state and prove, describing the asymptotic behavior of hit...

  14. Local dark matter and dark energy as estimated on a scale of ~1 Mpc in a self-consistent way

    Science.gov (United States)

    Chernin, A. D.; Teerikorpi, P.; Valtonen, M. J.; Dolgachev, V. P.; Domozhilova, L. M.; Byrd, G. G.

    2009-12-01

    Context: Dark energy was first detected from large distances on gigaparsec scales. If it is vacuum energy (or Einstein's Λ), it should also exist in very local space. Here we discuss its measurement on megaparsec scales of the Local Group. Aims: We combine the modified Kahn-Woltjer method for the Milky Way-M 31 binary and the HST observations of the expansion flow around the Local Group in order to study in a self-consistent way and simultaneously the local density of dark energy and the dark matter mass contained within the Local Group. Methods: A theoretical model is used that accounts for the dynamical effects of dark energy on a scale of ~1 Mpc. Results: The local dark energy density is put into the range 0.8-3.7ρv (ρv is the globally measured density), and the Local Group mass lies within 3.1-5.8×1012 M⊙. The lower limit of the local dark energy density, about 4/5× the global value, is determined by the natural binding condition for the group binary and the maximal zero-gravity radius. The near coincidence of two values measured with independent methods on scales differing by ~1000 times is remarkable. The mass ~4×1012 M⊙ and the local dark energy density ~ρv are also consistent with the expansion flow close to the Local Group, within the standard cosmological model. Conclusions: One should take into account the dark energy in dynamical mass estimation methods for galaxy groups, including the virial theorem. Our analysis gives new strong evidence in favor of Einstein's idea of the universal antigravity described by the cosmological constant.

  15. The Approach to an Estimation of a Local Area Network Functioning Efficiency

    Directory of Open Access Journals (Sweden)

    M. M. Taraskin

    2010-09-01

    Full Text Available In the article authors call attention to a choice of system of metrics, which permits to take a qualitative assessment of local area network functioning efficiency in condition of computer attacks.

  16. Local linear density estimation for filtered survival data, with bias correction

    DEFF Research Database (Denmark)

    Nielsen, Jens Perch; Tanggaard, Carsten; Jones, M.C.

    2009-01-01

    it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a 'pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias-correction methods...... within our framework. The multiplicative bias-correction method proves to be the best in a simulation study comparing the performance of the considered estimators. An example concerning old-age mortality demonstrates the importance of the improvements provided....

  17. Local Linear Density Estimation for Filtered Survival Data with Bias Correction

    DEFF Research Database (Denmark)

    Tanggaard, Carsten; Nielsen, Jens Perch; Jones, M.C.

    it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a ‘pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias correction methods...... within our framework. The multiplicative bias correction method proves to be best in a simulation study comparing the performance of the considered estimators. An example concerning old age mortality demonstrates the importance of the improvements provided....

  18. Estimate of whole body doses for Lynette Tew and Becky Farnsworth from Nevada Test Site local fallout

    International Nuclear Information System (INIS)

    Anspaugh, L.R.; Ng, Y.C.

    1985-01-01

    Lynette Tew and Becky Farnsworth are decendents whose relatives are litigants in Timothy vs US. The litigants allege that the decendents were harmed by radiation doses received as a result of local fallout from the testing of nuclear weapons at the Nevada Test Site. We have calculated a best estimate of the whole body dose received by each decendent from external exposure and the ingestion of radionuclides with food. In each case the dose via ingestion is trivial compared to the external dose. For Lynette Tew the dose estimate is 0.28 rads. For Becky Farnsworth it is 0.0035 rads. 23 references, 4 tables

  19. Real-time approaches to the estimation of local wind velocity for a fixed-wing unmanned air vehicle

    International Nuclear Information System (INIS)

    Chan, W L; Lee, C S; Hsiao, F B

    2011-01-01

    Three real-time approaches to estimating local wind velocity for a fixed-wing unmanned air vehicle are presented in this study. All three methods work around the navigation equations with added wind components. The first approach calculates the local wind speed by substituting the ground speed and ascent rate data given by the Global Positioning System (GPS) into the navigation equations. The second and third approaches utilize the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), respectively. The results show that, despite the nonlinearity of the navigation equations, the EKF performance is proven to be on a par with the UKF. A time-varying noise estimation method based on the Wiener filter is also discussed. Results are compared with the average wind speed measured on the ground. All three approaches are proven to be reliable with stated advantages and disadvantages

  20. Contribution of long-term accounting for raindrop size distribution variations on quantitative precipitation estimation by weather radar: Disdrometers vs parameter optimization

    Science.gov (United States)

    Hazenberg, P.; Uijlenhoet, R.; Leijnse, H.

    2015-12-01

    Volumetric weather radars provide information on the characteristics of precipitation at high spatial and temporal resolution. Unfortunately, rainfall measurements by radar are affected by multiple error sources, which can be subdivided into two main groups: 1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, vertical profile of reflectivity, attenuation, etc.), and 2) errors related to the conversion of the observed reflectivity (Z) values into rainfall intensity (R) and specific attenuation (k). Until the recent wide-scale implementation of dual-polarimetric radar, this second group of errors received relatively little attention, focusing predominantly on precipitation type-dependent Z-R and Z-k relations. The current work accounts for the impact of variations of the drop size distribution (DSD) on the radar QPE performance. We propose to link the parameters of the Z-R and Z-k relations directly to those of the normalized gamma DSD. The benefit of this procedure is that it reduces the number of unknown parameters. In this work, the DSD parameters are obtained using 1) surface observations from a Parsivel and Thies LPM disdrometer, and 2) a Monte Carlo optimization procedure using surface rain gauge observations. The impact of both approaches for a given precipitation type is assessed for 45 days of summertime precipitation observed within The Netherlands. Accounting for DSD variations using disdrometer observations leads to an improved radar QPE product as compared to applying climatological Z-R and Z-k relations. However, overall precipitation intensities are still underestimated. This underestimation is expected to result from unaccounted errors (e.g. transmitter calibration, erroneous identification of precipitation as clutter, overshooting and small-scale variability). In case the DSD parameters are optimized, the performance of the radar is further improved, resulting in the best performance of the radar QPE product. However

  1. Instantaneous local wave vector estimation from multi-spacecraft measurements using few spatial points

    Directory of Open Access Journals (Sweden)

    T. D. Carozzi

    2004-07-01

    Full Text Available We introduce a technique to determine instantaneous local properties of waves based on discrete-time sampled, real-valued measurements from 4 or more spatial points. The technique is a generalisation to the spatial domain of the notion of instantaneous frequency used in signal processing. The quantities derived by our technique are closely related to those used in geometrical optics, namely the local wave vector and instantaneous phase velocity. Thus, this experimental technique complements ray-tracing. We provide example applications of the technique to electric field and potential data from the EFW instrument on Cluster. Cluster is the first space mission for which direct determination of the full 3-dimensional local wave vector is possible, as described here.

  2. Estimating Aquifer Storage and Recovery (ASR Regional and Local Suitability: A Case Study in Washington State, USA

    Directory of Open Access Journals (Sweden)

    Maria T. Gibson

    2018-01-01

    Full Text Available Developing aquifers as underground water supply reservoirs is an advantageous approach applicable to meeting water management objectives. Aquifer storage and recovery (ASR is a direct injection and subsequent withdrawal technology that is used to increase water supply storage through injection wells. Due to site-specific hydrogeological quantification and evaluation to assess ASR suitability, limited methods have been developed to identify suitability on regional scales that are also applicable at local scales. This paper presents an ASR site scoring system developed to qualitatively assess regional and local suitability of ASR using 9 scored metrics to determine total percent of ASR suitability, partitioned into hydrogeologic properties, operational considerations, and regulatory influences. The development and application of a qualitative water well suitability method was used to assess the potential groundwater response to injection, estimate suitability based on predesignated injection rates, and provide cumulative approximation of statewide and local storage prospects. The two methods allowed for rapid assessment of ASR suitability and its applicability to regional and local water management objectives at over 280 locations within 62 watersheds in Washington, USA. It was determined that over 50% of locations evaluated are suitable for ASR and statewide injection potential equaled 6400 million liters per day. The results also indicate current limitations and/or potential benefits of developing ASR systems at the local level with the intent of assisting local water managers in strategic water supply planning.

  3. The local forest management associations as estimators of the fuelwood market in Finland

    International Nuclear Information System (INIS)

    Salakari, M.

    1996-01-01

    The Finnish Forest Research Institute inquired of the local forest management associations for their opinions about fuelwood consumption in their area. A further purpose was to establish a register of local fuelwood dealers. According to the inquiry the consumption of fuelwood has increased during the last five years and the increase will continue during the next three years. Although in some areas demand of fuelwood is greater than its supply, principally the fuelwood supply is sufficient. In Finland there seems to be 500 - 550 fuelwood dealers with sales over 50 m 3 /a. Half of them acquired the sold fuelwood from their own farm. (3 refs.)

  4. Illuminant direction estimation for a single image based on local region complexity analysis and average gray value.

    Science.gov (United States)

    Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Compare, Angelo

    2014-01-10

    Illuminant direction estimation is an important research issue in the field of image processing. Due to low cost for getting texture information from a single image, it is worthwhile to estimate illuminant direction by employing scenario texture information. This paper proposes a novel computation method to estimate illuminant direction on both color outdoor images and the extended Yale face database B. In our paper, the luminance component is separated from the resized YCbCr image and its edges are detected with the Canny edge detector. Then, we divide the binary edge image into 16 local regions and calculate the edge level percentage in each of them. Afterward, we use the edge level percentage to analyze the complexity of each local region included in the luminance component. Finally, according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model, we calculate the illuminant directions of the luminance component's three local regions, which meet the requirements of lower complexity and larger average gray value, and synthesize them as the final illuminant direction. Unlike previous works, the proposed method requires neither all of the information of the image nor the texture that is included in the training set. Experimental results show that the proposed method works better at the correct rate and execution time than the existing ones.

  5. Kinetics of cadmium hydroxide precipitation

    International Nuclear Information System (INIS)

    Patterson, J.W.; Marani, D.; Luo, B.; Swenson, P.

    1987-01-01

    This paper presents some preliminary results on the kinetics of Cd(OH)/sub 2/ precipitation, both in the absence and the presence of citric acid as an inhibiting agent. Batch and continuous stirred tank reactor (CSTR) precipitation studies are performed by mixing equal volumes of NaOH and Cd(NO/sub 3/)/sub 2/ solutions, in order to avoid localized supersaturation conditions. The rate of metal removal from the soluble phase is calculated from the mass balance for the CSTR precipitation tests. In addition, precipitation kinetics are studied in terms of nucleation and crystal growth rates, by means of a particle counter that allows a population balance analysis for the precipitation reactor at steady state conditions

  6. Comparison of region-of-influence methods for estimating high quantiles of precipitation in a dense dataset in the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Gaál, Ladislav; Kyselý, Jan

    2009-01-01

    Roč. 13, č. 11 (2009), s. 2203-2219 ISSN 1027-5606 R&D Projects: GA AV ČR KJB300420801 Institutional research plan: CEZ:AV0Z30420517 Keywords : heavy precipitation * extreme value analysis * region-of-influence method * central Europe Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.462, year: 2009 http://www.hydrol-earth-syst-sci.net/13/2203/2009/

  7. Probability estimates of heavy precipitation events in a flood-prone central-European region with enhanced influence of Mediterranean cyclones

    Czech Academy of Sciences Publication Activity Database

    Kyselý, Jan; Picek, J.

    2007-01-01

    Roč. 12, - (2007), s. 43-50 ISSN 1680-7340 R&D Projects: GA AV ČR KJB300420601 Institutional research plan: CEZ:AV0Z30420517 Keywords : extreme precipitation event * region al frequency analysis * Generalized Extreme Value distribution * Generalized Logistic distribution * central Europe * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology www.adv-geosci.net/12/43/2007/

  8. Distributed push-pull estimation for node localization in wireless sensor networks

    NARCIS (Netherlands)

    Dang, Viet-Hung; Le Viet Duc, L Duc; Lee, Young-Koo; Lee, Sungyoung

    A great deal of research achievements on localization in wireless sensor networks (WSNs) has been obtained in recent years. Nevertheless, its interesting challenges in terms of cost-reduction, accuracy improvement, scalability, and distributed ability design have led to the development of a new

  9. A statistical model to estimate the local vulnerability to severe weather

    Science.gov (United States)

    Pardowitz, Tobias

    2018-06-01

    We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

  10. Estimation of local and regional components of drain - flow from an irrigated field

    International Nuclear Information System (INIS)

    Eching, S.O.; Hopmans, J.W.; Wallender, W.W.; Macyntyre, J.L.; Peters, D.

    1995-01-01

    The contribution of regional ground water and deep percolation from a furrow irrigated field to total drain flow was estimated using salt load analysis. It was found that 64% of the drain flow comes from regional ground water flow. The electrical conductivity of the drain water was highly correlated with the drain flow rate. From the field water balance with deep percolation as estimated from the salt load analysis, using yield function derived evapotranspiration, and measured changes in root zone water storage, it was shown that 14% of the crop evapotranspiration comes from ground water during the study period. 8 figs; 5 tabs; 15 refs ( Author )

  11. Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

    Science.gov (United States)

    Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

    2017-12-01

    A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

  12. Wegner estimate and localization for alloy-type models with sign-changing exponentially decaying single-site potentials

    Science.gov (United States)

    Leonhardt, Karsten; Peyerimhoff, Norbert; Tautenhahn, Martin; Veselić, Ivan

    2015-05-01

    We study Schrödinger operators on L2(ℝd) and ℓ2(ℤd) with a random potential of alloy-type. The single-site potential is assumed to be exponentially decaying but not necessarily of fixed sign. In the continuum setting, we require a generalized step-function shape. Wegner estimates are bounds on the average number of eigenvalues in an energy interval of finite box restrictions of these types of operators. In the described situation, a Wegner estimate, which is polynomial in the volume of the box and linear in the size of the energy interval, holds. We apply the established Wegner estimate as an ingredient for a localization proof via multiscale analysis.

  13. An Iterative Maximum a Posteriori Estimation of Proficiency Level to Detect Multiple Local Likelihood Maxima

    Science.gov (United States)

    Magis, David; Raiche, Gilles

    2010-01-01

    In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its…

  14. Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection data

    Science.gov (United States)

    Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin

    2016-01-01

    Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic

  15. Estimation of the electric conductivity from scalp measurements: Feasibility and application to source localization

    NARCIS (Netherlands)

    van Burik, M.J.; Peters, M.J.

    2000-01-01

    Objectives: The accuracy of electrical impedance tomography was investigated. - Methods: The conductivities of the different compartments of the volume conductor were estimated by utilizing the boundary element method. The approach was tested for realistic head models with either 3 or 4

  16. River flooding due to intense precipitation

    International Nuclear Information System (INIS)

    Lin, James C.

    2014-01-01

    River stage can rise and cause site flooding due to local intense precipitation (LIP), dam failures, snow melt in conjunction with precipitation or dam failures, etc. As part of the re-evaluation of the design basis as well as the PRA analysis of other external events, the likelihood and consequence of river flooding leading to the site flooding need to be examined more rigorously. To evaluate the effects of intense precipitation on site structures, the site watershed hydrology and pond storage are calculated. To determine if river flooding can cause damage to risk-significant systems, structures, and components (SSC), water surface elevations are analyzed. Typically, the amount and rate of the input water is determined first. For intense precipitation, the fraction of the rainfall in the watershed drainage area not infiltrated into the ground is collected in the river and contributes to the rise of river water elevation. For design basis analysis, the Probable Maximum Flood (PMF) is evaluated using the Probable Maximum Precipitation (PMP) based on the site topography/configuration. The peak runoff flow rate and water surface elevations resulting from the precipitation induced flooding can then be estimated. The runoff flow hydrograph and peak discharge flows can be developed using the synthetic hydrograph method. The standard step method can then be used to determine the water surface elevations along the river channel. Thus, the flood water from the local intense precipitation storm and excess runoff from the nearby river can be evaluated to calculate the water surface elevations, which can be compared with the station grade floor elevation to determine the effects of site flooding on risk-significant SSCs. The analysis needs to consider any possible diversion flow and the effects of changes to the site configurations. Typically, the analysis is performed based on conservative peak rainfall intensity and the assumptions of failure of the site drainage facilities

  17. Key drivers of precipitation isotopes in Windhoek, Namibia (2012-2016)

    Science.gov (United States)

    Kaseke, K. F.; Wang, L.; Wanke, H.

    2017-12-01

    Southern African climate is characterized by large variability with precipitation model estimates varying by as much as 70% during summer. This difference between model estimates is partly because most models associate precipitation over Southern Africa with moisture inputs from the Indian Ocean while excluding inputs from the Atlantic Ocean. However, growing evidence suggests that the Atlantic Ocean may also contribute significant amounts of moisture to the region. This four-year (2012-2016) study investigates the isotopic composition (δ18O, δ2H and δ17O) of event-scale precipitation events, the key drivers of isotope variations and the origins of precipitation experienced in Windhoek, Namibia. Results indicate large storm-to-storm isotopic variability δ18O (25‰), δ2H (180‰) and δ17O (13‰) over the study period. Univariate analysis showed significant correlations between event precipitation isotopes and local meteorological parameters; lifted condensation level, relative humidity (RH), precipitation amount, average wind speed, surface and air temperature (p < 0.05). The number of significant correlations between local meteorological parameters and monthly isotopes was much lower suggesting loss of information through data aggregation. Nonetheless, the most significant isotope driver at both event and monthly scales was RH, consistent with the semi-arid classification of the site. Multiple linear regression analysis suggested RH, precipitation amount and air temperature were the most significant local drivers of precipitation isotopes accounting for about 50% of the variation implying that about 50% could be attributed to source origins. HYSLPIT trajectories indicated that 78% of precipitation originated from the Indian Ocean while 21% originated from the Atlantic Ocean. Given that three of the four study years were droughts while two of the three drought years were El Niño related, our data also suggests that δ'17O-δ'18O could be a useful tool to

  18. GNSS-SLR satellite co-location for the estimate of local ties

    Science.gov (United States)

    Bruni, Sara; Zerbini, Susanna; Errico, Maddalena; Santi, Efisio

    2013-04-01

    The current realization of the International Terrestrial Reference Frame (ITRF) is based on four different space-geodetic techniques, so that the benefits brought by each observing system to the definition of the frame can compensate for the drawbacks of the others and technique-specific systematic errors might be identified. The strategy used to combine the observations from the different techniques is then of prominent importance for the realization of a precise and stable reference frame. This study concentrates, in particular, on the combination of Satellite Laser Ranging (SLR) and Global Navigation Satellite System (GNSS) observations by exploiting satellite co-locations. This innovative approach is based on the fact that laser tracking of GNSS satellites, carrying on board laser reflector arrays, allows for the combination of optical and microwave signals in the determination of the spacecraft orbit. Besides, the use of satellite co-locations differs quite significantly from the traditional combination method in which each single technique solution is carried out autonomously and is interrelated in a second step. One of the benefits of the approach adopted in this study is that it allows for an independent validation of the local tie, i.e. of the vector connecting the SLR and GNSS reference points in a multi-techniques station. Typically, local ties are expressed by a single value, measured with ground-based geodetic techniques and taken as constant. In principle, however, local ties might show time variations likely caused by the different monumentation characteristics of the GNSS antennas with respect to those of a SLR system. This study evaluates the possibility of using the satellite co-location approach to generate local-ties time series by means of observations available for a selected network of ILRS stations. The data analyzed in this study were acquired as part of the NASA's Earth Science Data Systems and are archived and distributed by the Crustal

  19. Estimating the Cumulative Ecological Effect of Local Scale Landscape Changes in South Florida

    Science.gov (United States)

    Hogan, Dianna M.; Labiosa, William; Pearlstine, Leonard; Hallac, David; Strong, David; Hearn, Paul; Bernknopf, Richard

    2012-01-01

    Ecosystem restoration in south Florida is a state and national priority centered on the Everglades wetlands. However, urban development pressures affect the restoration potential and remaining habitat functions of the natural undeveloped areas. Land use (LU) planning often focuses at the local level, but a better understanding of the cumulative effects of small projects at the landscape level is needed to support ecosystem restoration and preservation. The South Florida Ecosystem Portfolio Model (SFL EPM) is a regional LU planning tool developed to help stakeholders visualize LU scenario evaluation and improve communication about regional effects of LU decisions. One component of the SFL EPM is ecological value (EV), which is evaluated through modeled ecological criteria related to ecosystem services using metrics for (1) biodiversity potential, (2) threatened and endangered species, (3) rare and unique habitats, (4) landscape pattern and fragmentation, (5) water quality buffer potential, and (6) ecological restoration potential. In this article, we demonstrate the calculation of EV using two case studies: (1) assessing altered EV in the Biscayne Gateway area by comparing 2004 LU to potential LU in 2025 and 2050, and (2) the cumulative impact of adding limestone mines south of Miami. Our analyses spatially convey changing regional EV resulting from conversion of local natural and agricultural areas to urban, industrial, or extractive use. Different simulated local LU scenarios may result in different alterations in calculated regional EV. These case studies demonstrate methods that may facilitate evaluation of potential future LU patterns and incorporate EV into decision making.

  20. Estimating yellow potato (Solanum phureja Juz. et Buk.) solar radiation interception in three Colombian localities

    International Nuclear Information System (INIS)

    Cabezas, M; Corchuelo, G

    2005-01-01

    Three experiments were simultaneously carried out in three Colombian localities (Firavitoba, Carmen de Carupa y Bogotá) to measure and compare photosynthetically active radiation (PAR) interception patterns in Solanum phureja. Three random complete block design planting densities (8,33, 4.17 and 2.67 plants/m 2 ) were evaluated, having four replicates and an experimental unit consisting of five four-metre-long rows or planting lines. Overall PAR, reflected PAR, transmitted PAR and absorbed PAR were determined. The Monsie and Saeky model was used for establishing the PAR k extinction coefficient in canopies. Results revealed statistically significant differences within localities and plant densities, but not for LAI interaction. There was a higher overall incidence of radiation in those localities situated at high altitudes. PAR distribution was similar in high and low stratum in all cases, proving that plant architecture allows a suitable distribution of PAR within the canopy. The k extinction coefficient was mainly affected by leaf development. Values ranged from 0.39 to 0.61. It was revealed that plants may become quickly saturated above 2,800 m a.s.l. due to effects of luminescence, thus inducing stressful conditions interfering with leaf development and therefore distribution of tuber photo- assimilation, so affecting agronomic yield. (author) [es

  1. Climate Prediction Center(CPC)Daily GOES Precipitation Index (GPI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GOES Precipitation Index (GPI) is a precipitation estimation algorithm. The GPI technique estimates tropical rainfall using cloud-top temperature as the sole...

  2. A single frequency component-based re-estimated MUSIC algorithm for impact localization on complex composite structures

    International Nuclear Information System (INIS)

    Yuan, Shenfang; Bao, Qiao; Qiu, Lei; Zhong, Yongteng

    2015-01-01

    The growing use of composite materials on aircraft structures has attracted much attention for impact monitoring as a kind of structural health monitoring (SHM) method. Multiple signal classification (MUSIC)-based monitoring technology is a promising method because of its directional scanning ability and easy arrangement of the sensor array. However, for applications on real complex structures, some challenges still exist. The impact-induced elastic waves usually exhibit a wide-band performance, giving rise to the difficulty in obtaining the phase velocity directly. In addition, composite structures usually have obvious anisotropy, and the complex structural style of real aircrafts further enhances this performance, which greatly reduces the localization precision of the MUSIC-based method. To improve the MUSIC-based impact monitoring method, this paper first analyzes and demonstrates the influence of measurement precision of the phase velocity on the localization results of the MUSIC impact localization method. In order to improve the accuracy of the phase velocity measurement, a single frequency component extraction method is presented. Additionally, a single frequency component-based re-estimated MUSIC (SFCBR-MUSIC) algorithm is proposed to reduce the localization error caused by the anisotropy of the complex composite structure. The proposed method is verified on a real composite aircraft wing box, which has T-stiffeners and screw holes. Three typical categories of 41 impacts are monitored. Experimental results show that the SFCBR-MUSIC algorithm can localize impact on complex composite structures with an obviously improved accuracy. (paper)

  3. Estimating and localizing the algebraic and total numerical errors using flux reconstructions

    Czech Academy of Sciences Publication Activity Database

    Papež, Jan; Strakoš, Z.; Vohralík, M.

    2018-01-01

    Roč. 138, č. 3 (2018), s. 681-721 ISSN 0029-599X R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : numerical solution of partial differential equations * finite element method * a posteriori error estimation * algebraic error * discretization error * stopping criteria * spatial distribution of the error Subject RIV: BA - General Mathematics Impact factor: 2.152, year: 2016

  4. Acidity of Scandinavian precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Barrett, E; Bordin, G

    1955-01-01

    Data on the pH of the total monthly precipitation at stations of a Swedish network for sampling and chemical analysis of precipitation and atmospheric aerosols during the year July 1953 to June 1954 are presented and discussed, together with the pH data from the first two months of operation of a large pan-Scandinavian net. It is found that well-defined regions of acidity and alkalinity relative to the pH of water in equilibrium with atmospheric carbon dioxide exist, and that these regions persist to such an extent that the monthly deviations from the pattern of the annual mean pH at stations unaffected by local pollution show persistently high acidity, while inland northern stations show equally persistent alkalinity. Some possible reasons for the observed distributions are considered.

  5. Pinsker estimators for local helioseismology: inversion of travel times for mass-conserving flows

    International Nuclear Information System (INIS)

    Fournier, Damien; Holzke, Martin; Hohage, Thorsten; Gizon, Laurent

    2016-01-01

    A major goal of helioseismology is the three-dimensional reconstruction of the three velocity components of convective flows in the solar interior from sets of wave travel-time measurements. For small amplitude flows, the forward problem is described in good approximation by a large system of convolution equations. The input observations are highly noisy random vectors with a known dense covariance matrix. This leads to a large statistical linear inverse problem. Whereas for deterministic linear inverse problems several computationally efficient minimax optimal regularization methods exist, only one minimax-optimal linear estimator exists for statistical linear inverse problems: the Pinsker estimator. However, it is often computationally inefficient because it requires a singular value decomposition of the forward operator or it is not applicable because of an unknown noise covariance matrix, so it is rarely used for real-world problems. These limitations do not apply in helioseismology. We present a simplified proof of the optimality properties of the Pinsker estimator and show that it yields significantly better reconstructions than traditional inversion methods used in helioseismology, i.e. regularized least squares (Tikhonov regularization) and SOLA (approximate inverse) methods. Moreover, we discuss the incorporation of the mass conservation constraint in the Pinsker scheme using staggered grids. With this improvement we can reconstruct not only horizontal, but also vertical velocity components that are much smaller in amplitude. (paper)

  6. Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames.

    Science.gov (United States)

    Singh, Ajay V; Gollner, Michael J

    2016-06-01

    Modeling the realistic burning behavior of condensed-phase fuels has remained out of reach, in part because of an inability to resolve the complex interactions occurring at the interface between gas-phase flames and condensed-phase fuels. The current research provides a technique to explore the dynamic relationship between a combustible condensed fuel surface and gas-phase flames in laminar boundary layers. Experiments have previously been conducted in both forced and free convective environments over both solid and liquid fuels. A unique methodology, based on the Reynolds Analogy, was used to estimate local mass burning rates and flame heat fluxes for these laminar boundary layer diffusion flames utilizing local temperature gradients at the fuel surface. Local mass burning rates and convective and radiative heat feedback from the flames were measured in both the pyrolysis and plume regions by using temperature gradients mapped near the wall by a two-axis traverse system. These experiments are time-consuming and can be challenging to design as the condensed fuel surface burns steadily for only a limited period of time following ignition. The temperature profiles near the fuel surface need to be mapped during steady burning of a condensed fuel surface at a very high spatial resolution in order to capture reasonable estimates of local temperature gradients. Careful corrections for radiative heat losses from the thermocouples are also essential for accurate measurements. For these reasons, the whole experimental setup needs to be automated with a computer-controlled traverse mechanism, eliminating most errors due to positioning of a micro-thermocouple. An outline of steps to reproducibly capture near-wall temperature gradients and use them to assess local burning rates and heat fluxes is provided.

  7. Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

    Directory of Open Access Journals (Sweden)

    O. Henneberg

    2018-05-01

    Full Text Available Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale.We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil

  8. Understanding SMAP-L4 soil moisture estimation skill and their dependence with topography, precipitation and vegetation type using Mesonet and Micronet networks.

    Science.gov (United States)

    Moreno, H. A.; Basara, J. B.; Thompson, E.; Bertrand, D.; Johnston, C. S.

    2017-12-01

    Soil moisture measurements using satellite information can benefit from a land data assimilation model Goddard Earth Observing System (GEOS-5) and land data assimilation system (LDAS) to improve the representation of fine-scale dynamics and variability. This work presents some advances to understand the predictive skill of L4-SM product across different land-cover types, topography and precipitation totals, by using a dense network of multi-level soil moisture sensors (i.e. Mesonet and Micronet) in Oklahoma. 130 soil moisture stations are used across different precipitation gradients (i.e. arid vs wet), land cover (e.g. forest, shrubland, grasses, crops), elevation (low, mid and high) and slope to assess the improvements by the L4_SM product relative to the raw SMAP L-band brightness temperatures. The comparisons are conducted between July 2015 and July 2016 at the daily time scale. Results show the highest L4-SM overestimations occur in pastures and cultivated crops, during the rainy season and at higher elevation lands (over 800 meters asl). The smallest errors occur in low elevation lands, low rainfall and developed lands. Forested area's soil moisture biases lie in between pastures (max biases) and low intensity/developed lands (min biases). Fine scale assessment of L4-SM should help GEOS-5 and LDAS teams refine model parameters in light of observed differences and improve assimilation techniques in light of land-cover, topography and precipitation regime. Additionally, regional decision makers could have a framework to weight the utility of this product for water resources applications.

  9. Atmospheric balance of the humidity and estimate of the precipitation recycled in Colombia according to the re-analysis NCEP/NCAR

    International Nuclear Information System (INIS)

    Cuartas, Adriana; Poveda, German

    2002-01-01

    The magnitudes of the entrance humidity flows and exit are considered and the amount of precipitable water at different levels from the atmospheric column on Colombia. The water balance is quantified in the Colombian atmosphere; the regions and the atmospheric levels of entrance and exit of humidity are identified. The hypothesis that in the long term the net atmospheric humidity influence must be equal to the average of long term of the net run-off is verified. In addition, the percentage of recycled precipitation is considered on the Colombian territory. The variability during the two phases of the ENSO is analyzed. The calculations are made with the information of the climatic project Reanalysis developed by the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR), with the collaboration of the National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite of the U.S.A. For this work it was counted on monthly information of 41 years between 1958-1998. The hydrological information was obtained from the project Balances Hidrologicos de Colombia, 1999, made by the Posgrado de Recursos Hidraulicos, de la Universidad Nacional, with the support of COLCIENCIAS and the Unidad de Planeacion Minero Energetica-UPME. The results showed the average value of the net influence of humidity to the atmosphere of Colombia is of 5716 mm/year, with a great variability in both phases of the ENSO. The greater humidity advection towards Colombia occurs in the low levels of pressure (between 1000 and 850 hPa), and originating of all the directions, mainly of trade winds of the east and trade winds of the west. Also one was that the greater humidity transport towards Colombia occurs in trimesters DJF and MAM, with average values 505,1 and 606,6 mm/year, respectively. It was observed that the hypothesis that in the long term, the net atmospheric flux, is equal to the net terrestrial run-off, reasonably is adapted for

  10. Assessing the importance of spatio-temporal RCM resolution when estimating sub-daily extreme precipitation under current and future climate conditions

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Luchner, J.; Onof, C.

    2017-01-01

    extreme precipitation over Denmark generated by the regional climate model (RCM) HIRHAM-ECEARTH at different spatial resolutions (8, 12, 25 and 50km), three RCM from the RiskChange project at 8km resolution and three RCMs from ENSEMBLES at 25km resolution at temporal aggregations from 1 to 48h...... are more skewed than the observational dataset, which leads to an overestimation by the higher spatial resolution simulations. Nevertheless, in general, under current conditions RCM simulations at high spatial resolution represent extreme events and high-order moments better. The changes projected...

  11. Airborne DoA estimation of gunshot acoustic signals using drones with application to sniper localization systems

    Science.gov (United States)

    Fernandes, Rigel P.; Ramos, António L. L.; Apolinário, José A.

    2017-05-01

    Shooter localization systems have been subject of a growing attention lately owing to its wide span of possible applications, e.g., civil protection, law enforcement, and support to soldiers in missions where snipers might pose a serious threat. These devices are based on the processing of electromagnetic or acoustic signatures associated with the firing of a gun. This work is concerned with the latter, where the shooter's position can be obtained based on the estimation of the direction-of-arrival (DoA) of the acoustic components of a gunshot signal (muzzle blast and shock wave). A major limitation of current commercially available acoustic sniper localization systems is the impossibility of finding the shooter's position when one of these acoustic signatures is not detected. This is very likely to occur in real-life situations, especially when the microphones are not in the field of view of the shockwave or when the presence of obstacles like buildings can prevent a direct-path to sensors. This work addresses the problem of DoA estimation of the muzzle blast using a planar array of sensors deployed in a drone. Results supported by actual gunshot data from a realistic setup are very promising and pave the way for the development of enhanced sniper localization systems featuring two main advantages over stationary ones: (1) wider surveillance area; and (2) increased likelihood of a direct-path detection of at least one of the gunshot signals, thereby adding robustness and reliability to the system.

  12. Regional estimation of geomagnetically induced currents based on the local magnetic or electric field

    Directory of Open Access Journals (Sweden)

    Viljanen Ari

    2015-01-01

    Full Text Available Previous studies have demonstrated a close relationship between the time derivative of the horizontal geomagnetic field vector (dH/dt and geomagnetically induced currents (GIC at a nearby location in a power grid. Similarly, a high correlation exists between GIC and the local horizontal geoelectric field (E, typically modelled from a measured magnetic field. Considering GIC forecasting, it is not feasible to assume that detailed prediction of time series will be possible. Instead, other measures summarising the activity level over a given period are preferable. In this paper, we consider the 30-min maximum of dH/dt or E as a local activity indicator (|dH/dt|30 or |E|30. Concerning GIC, we use the sum of currents through the neutral leads at substations and apply its 30-min maximum as a regional activity measure (GIC30. We show that |dH/dt|30 at a single point yields a proxy for GIC activity in a larger region. A practical consequence is that if |dH/dt|30 can be predicted at some point then it is also possible to assess the expected GIC level in the surrounding area. As is also demonstrated, |E|30 and GIC30 depend linearly on |dH/dt|30, so there is no saturation with increasing geomagnetic activity contrary to often used activity indices.

  13. An Extension to a Filter Implementation of Local Quadratic Surface for Image Noise Estimation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    1999-01-01

    Based on regression analysis this paper gives a description for simple image filter design. Specifically 3x3 filter implementations of a quadratic surface, residuals from this surface, gradients and the Laplacian are given. For the residual a 5x5 filter is given also. It is shown that the 3x3......) it is concluded that if striping is to be considered as a part of the noise, the residual from a 3x3 median filter seems best. If we are interested in a salt-and-pepper noise estimator the proposed extension to the 3x3 filter for the residual from a quadratic surface seems best. Simple statistics...

  14. Use of Thermal Data to Estimate Infiltration in Pagany Wash Associated with the winter of 1997-1998 El Nino Precipitation, Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    LeCain, G.D.; Lu, N.; Kurzmack, M.

    2000-01-01

    Temperature and air-pressure monitoring in a vertical borehole located in Pagany Wash, a normally dry stream-carved channel northeast of Yucca Mountain, Nevada, indicated that the annual temperature wave was measurable to a depth of 11.1 m. Temperature depressions were measured at depths of 3.1, 6.1, 9.2, and 11.1 m below ground surface. The temperature depressions were interpreted to be the result of infiltration associated with the 1997-1998 El Nino precipitation. A pressure differential, of approximately 2 kiloPascals, between stations located 11.1 and 24.5 m below ground surface was interpreted to be the result of compressed air ahead of the wetting front. The pressure differences between stations indicated that the wetting front migrated deeper than 35.2 m and that the Yucca Mountain Tuff retarded the downward movement of the wetting front. An analytical method indicated that the infiltration flux through the Pagany Wash alluvium due to the 1997-1998 El Nino precipitation was approximately 940 mm. A one-dimensional numerical model indicated that the infiltration flux was approximately 1000 mm. Sensitivity analysis indicated that the potential temperature decrease due to conduction was minimal and that cooler surface temperatures could not account for the measured subsurface temperature depressions

  15. Estimating the Counterparty Risk Exposure by Using the Brownian Motion Local Time

    Directory of Open Access Journals (Sweden)

    Bonollo Michele

    2017-06-01

    Full Text Available In recent years, the counterparty credit risk measure, namely the default risk in over-the-counter (OTC derivatives contracts, has received great attention by banking regulators, specifically within the frameworks of Basel II and Basel III. More explicitly, to obtain the related risk figures, one is first obliged to compute intermediate output functionals related to the mark-to-market position at a given time no exceeding a positive and finite time horizon. The latter implies an enormous amount of computational effort is needed, with related highly time consuming procedures to be carried out, turning out into significant costs. To overcome the latter issue, we propose a smart exploitation of the properties of the (local time spent by the Brownian motion close to a given value.

  16. Preliminary Estimation of Local Bypass Flow Gap Sizes for a Prismatic VHTR Core

    International Nuclear Information System (INIS)

    Kim, Min Hwan; Jo, Chang Keun; Lee, Won Jae

    2009-01-01

    The Very High Temperature Reactor (VHTR) has been selected for the Nuclear Hydrogen Development and Demonstration (NHDD) project. In the VHTR design, core bypass flow has been one of key issues for core thermal margins and target temperature of the core outlet. The core bypass flow in the prismatic VHTR varies with the core life due to the irradiation shrinkage/ swelling and thermal expansion of the graphite blocks, which could be a significant proportion of the total core flow. Thus, accurate prediction of the bypass flow is of major importance in assuring the core thermal margin. To predict the bypass flow, first of all, local gap sizes between graphite blocks in the core should be determined. The objectives of this work are to develop a methodology for determining the gap sizes and to perform a preliminary evaluation for a reference reactor

  17. Ultrasensitivity in signaling cascades revisited: Linking local and global ultrasensitivity estimations.

    Directory of Open Access Journals (Sweden)

    Edgar Altszyler

    Full Text Available Ultrasensitive response motifs, capable of converting graded stimuli into binary responses, are well-conserved in signal transduction networks. Although it has been shown that a cascade arrangement of multiple ultrasensitive modules can enhance the system's ultrasensitivity, how a given combination of layers affects a cascade's ultrasensitivity remains an open question for the general case. Here, we introduce a methodology that allows us to determine the presence of sequestration effects and to quantify the relative contribution of each module to the overall cascade's ultrasensitivity. The proposed analysis framework provides a natural link between global and local ultrasensitivity descriptors and it is particularly well-suited to characterize and understand mathematical models used to study real biological systems. As a case study, we have considered three mathematical models introduced by O'Shaughnessy et al. to study a tunable synthetic MAPK cascade, and we show how our methodology can help modelers better understand alternative models.

  18. The influence of local mechanisms on large scale seismic vulnerability estimation of masonry building aggregates

    Science.gov (United States)

    Formisano, Antonio; Chieffo, Nicola; Milo, Bartolomeo; Fabbrocino, Francesco

    2016-12-01

    The current paper deals with the seismic vulnerability evaluation of masonry constructions grouped in aggregates through an "ad hoc" quick vulnerability form based on new assessment parameters considering local collapse mechanisms. First, a parametric kinematic analysis on masonry walls with different height (h) / thickness (t) ratios has been developed with the purpose of identifying the collapse load multiplier for activation of the main four first-order failure mechanisms. Subsequently, a form initially conceived for building aggregates suffering second-mode collapse mechanisms, has been expanded on the basis of the achieved results. Tre proposed quick vulnerability technique has been applied to one case study within the territory of Arsita (Teramo, Italy) and, finally, it has been also validated by the comparison of results with those deriving from application of the well-known FaMIVE procedure.

  19. A saliva molecular imprinted localized surface plasmon resonance biosensor for wine astringency estimation.

    Science.gov (United States)

    Guerreiro, J Rafaela L; Teixeira, Natércia; De Freitas, Victor; Sales, M Goreti F; Sutherland, Duncan S

    2017-10-15

    Wine astringency was evaluated based on the interaction of two complex matrices (red wine and saliva) by combining localized surface plasmon resonance (LSPR) and molecular imprinted polymers (MIP) at gold nanodisks as an alternative to sensorial analysis. The main objective of the work was to simulate wine astringency inside the mouth by mimicking this biological system. The LSPR/MIP sensor provided a linear response for astringency expressed in pentagalloyl glucose (PGG) units in concentrations ranging from 1 to 140μmol/L. The sensor was also applied to wine samples correlating well with sensorial analysis obtained by a trained panel. The correlation of astringency and wine composition was also evaluated showing that anthocyanins may have an important role, not only for pigmentation but also in astringency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. A long-term variation of chemical composition in precipitation

    International Nuclear Information System (INIS)

    Yoshioka, Ryuma; Okimura, Takashi; Okumura, Takenobu

    1991-01-01

    Precipitation samples are collected at the six localities in the southwestern Japan weekly or monthly over a long period of time (1978-1989) in order to estimate chemical weathering rates and amount of weathered materials through chemical composition in natural waters. Major chemical composition is determined for the precipitation samples. Together with the data available in the literature, the following characteristics are recognized : 1) Most pH values fall in the narrow range of 4.4 to 5.4, 2) Systematic variations in pH values are observed among the precipitation samples of different geologic environments, 3) pH values become almost constant from 1984 to 1989, 4) NO 3 - concentrations gradually decrease to an almost constant value with time, and 5) ΔSO 4 2- concentrations gradually have a tendency to decrease from 1978 to 1985. The mechanism of phenomena described above is also presented. (author)

  1. Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

    Science.gov (United States)

    Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

    2012-10-12

    Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

  2. Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali

    Directory of Open Access Journals (Sweden)

    Minetti Andrea

    2012-10-01

    Full Text Available Abstract Background Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS approach has been proposed as an alternative, as smaller sample sizes are required. Methods We explored (i the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. Results VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i health areas not requiring supplemental activities; ii health areas requiring additional vaccination; iii health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3, standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Conclusions Small sample cluster surveys (10 × 15 are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

  3. The concept of estimation of elevator shaft control measurement results in the local 3D coordinate system

    Directory of Open Access Journals (Sweden)

    Filipiak-Kowszyk Daria

    2018-01-01

    Full Text Available Geodetic control measurements play an important part because they provide information about the current state of repair of the construction, which has a direct impact on the safety assessment of its exploitation. Authors in this paper have focused on control measurements of the elevator shaft. The article discusses the problem of determining the deviation of elevator shaft walls from the vertical plane in the local 3D coordinate system. It presents a concept of estimation of measurements results base on the parametric method with conditions on parameters. The simulated measurement results were used to verify the concept presented in the paper.

  4. ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models.

    Science.gov (United States)

    Maghrabi, Ali H A; McGuffin, Liam J

    2017-07-03

    Methods that reliably estimate the likely similarity between the predicted and native structures of proteins have become essential for driving the acceptance and adoption of three-dimensional protein models by life scientists. ModFOLD6 is the latest version of our leading resource for Estimates of Model Accuracy (EMA), which uses a pioneering hybrid quasi-single model approach. The ModFOLD6 server integrates scores from three pure-single model methods and three quasi-single model methods using a neural network to estimate local quality scores. Additionally, the server provides three options for producing global score estimates, depending on the requirements of the user: (i) ModFOLD6_rank, which is optimized for ranking/selection, (ii) ModFOLD6_cor, which is optimized for correlations of predicted and observed scores and (iii) ModFOLD6 global for balanced performance. The ModFOLD6 methods rank among the top few for EMA, according to independent blind testing by the CASP12 assessors. The ModFOLD6 server is also continuously automatically evaluated as part of the CAMEO project, where significant performance gains have been observed compared to our previous server and other publicly available servers. The ModFOLD6 server is freely available at: http://www.reading.ac.uk/bioinf/ModFOLD/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Dispersive estimates for rational symbols and local well-posedness of the nonzero energy NV equation. II

    Science.gov (United States)

    Kazeykina, Anna; Muñoz, Claudio

    2018-04-01

    We continue our study on the Cauchy problem for the two-dimensional Novikov-Veselov (NV) equation, integrable via the inverse scattering transform for the two dimensional Schrödinger operator at a fixed energy parameter. This work is concerned with the more involved case of a positive energy parameter. For the solution of the linearized equation we derive smoothing and Strichartz estimates by combining new estimates for two different frequency regimes, extending our previous results for the negative energy case [18]. The low frequency regime, which our previous result was not able to treat, is studied in detail. At non-low frequencies we also derive improved smoothing estimates with gain of almost one derivative. Then we combine the linear estimates with a Fourier decomposition method and Xs,b spaces to obtain local well-posedness of NV at positive energy in Hs, s > 1/2. Our result implies, in particular, that at least for s > 1/2, NV does not change its behavior from semilinear to quasilinear as energy changes sign, in contrast to the closely related Kadomtsev-Petviashvili equations. As a complement to our LWP results, we also provide some new explicit solutions of NV at zero energy, generalizations of the lumps solutions, which exhibit new and nonstandard long time behavior. In particular, these solutions blow up in infinite time in L2.

  6. An approach to estimate the freshwater contribution from glacial melt and precipitation in East Greenland shelf waters using colored dissolved organic matter (CDOM)

    DEFF Research Database (Denmark)

    Stedmon, Colin; Granskog, Mats A.; Dodd, Paul A.

    2015-01-01

    Changes in the supply and storage of freshwater in the Arctic Ocean and its subsequent export to the North Atlantic can potentially influence ocean circulation and climate. In order to understand how the Arctic freshwater budget is changing and the potential impacts, it is important to develop......, and precipitation) and sea ice melt. We develop this approach further and investigate the use of an additional tracer, colored dissolved organic matter (CDOM), which is largely specific to freshwater originating from Arctic rivers. A robust relationship between the freshwater contribution from meteoric water...... processes (riverine input and sea ice formation), while previously, these waters where thought to be derived from open sea processes (cooling and sea ice formation) in the northern Barents and Kara Seas. In Greenlandic coastal waters the meteoric water contribution is influenced by Greenland ice sheet...

  7. Estimation of chromium (VI) in various body parts of local chicken

    International Nuclear Information System (INIS)

    Mahmud, T.; Rehman, R.; Anwar, J.; Abbas, A.; Farooq, M.

    2011-01-01

    Chicken is a common type of meat source in our food. It is fed with the feed containing small pieces of leather having Cr (VI) which persisted in it during chrome tanning process. The core purpose of present study was to determine the concentration of Cr (VI) in different body parts of chicken like leg, arm, head, heart, liver and bone. Estimation of Cr (VI) was done by preparing the sample solutions after ashing and digestion with nitric acid, by atomic absorption spectrophotometer. The results depicted that the meat part of leg had higher mean concentration (1.266 mg/kg) with 0.037 mg/kg standard error while the lowest average concentration was found in arm (0.233 mg/kg) with standard error as 0.019 mg/kg. In case of bones, the maximum mean concentration was found in head (1.433 mg/kg) with standard error as 0.670 mg/kg. The concentration of Cr (VI) was not found similar in meat and bones of chicken by employing Kruskal Wallis Test. (author)

  8. Average Estimates of Water-Budget Components Based on Hydrograph Separation and PRISM Precipitation for Gaged Basins in the Appalachian Plateaus Region, 1900-2011

    Data.gov (United States)

    Department of the Interior — As part of the U.S. Geological Survey’s Groundwater Resources Program study of the Appalachian Plateaus aquifers, estimates of annual water-budget components were...

  9. Annual Estimates of Water-Budget Components Based on Hydrograph Separation and PRISM Precipitation for Gaged Basins in the Appalachian Plateaus Region, 1900-2011

    Data.gov (United States)

    Department of the Interior — As part of the U.S. Geological Survey’s Groundwater Resources Program study of the Appalachian Plateaus aquifers, estimates of annual water-budget components were...

  10. Estimate of main local sources to ambient ultrafine particle number concentrations in an urban area

    Science.gov (United States)

    Rahman, Md Mahmudur; Mazaheri, Mandana; Clifford, Sam; Morawska, Lidia

    2017-09-01

    Quantifying and apportioning the contribution of a range of sources to ultrafine particles (UFPs, D oil refineries, and seaport) sources to the total ambient particle number concentration (PNC) in a busy, inner-city area in Brisbane, Australia using Bayesian statistical modelling and other exploratory tools. The Bayesian model was trained on the PNC data on days where NP formations were known to have not occurred, hourly traffic counts, solar radiation data, and smooth daily trend. The model was applied to apportion and quantify the contribution of NP formations and local traffic and non-traffic sources to UFPs. The data analysis incorporated long-term measured time-series of total PNC (D ≥ 6 nm), particle number size distributions (PSD, D = 8 to 400 nm), PM2.5, PM10, NOx, CO, meteorological parameters and traffic counts at a stationary monitoring site. The developed Bayesian model showed reliable predictive performances in quantifying the contribution of NP formation events to UFPs (up to 4 × 104 particles cm- 3), with a significant day to day variability. The model identified potential NP formation and no-formations days based on PNC data and quantified the sources contribution to UFPs. Exploratory statistical analyses show that total mean PNC during the middle of the day was up to 32% higher than during peak morning and evening traffic periods, which were associated with NP formation events. The majority of UFPs measured during the peak traffic and NP formation periods were between 30-100 nm and smaller than 30 nm, respectively. To date, this is the first application of Bayesian model to apportion different sources contribution to UFPs, and therefore the importance of this study is not only in its modelling outcomes but in demonstrating the applicability and advantages of this statistical approach to air pollution studies.

  11. Studying precipitation recycling over the Tibetan Plateau using evaporation-tagging and back-trajectory analysis

    Science.gov (United States)

    Gao, Y.

    2017-12-01

    Regional precipitation recycling (i.e., the contribution of local evaporation to local precipitation) is an important component of water cycle over the Tibetan Plateau (TP). Two methods were used to investigate regional precipitation recycling: 1) tracking of tagged atmospheric water parcels originating from evaporation in a source region (i.e., E-tagging), and 2) back-trajectory approach to track the evaporative sources contributed to precipitation in a specific region. These two methods were applied to Weather Research and Forecasting (WRF) regional climate simulations to quantify the precipitation recycling ratio in the TP for three selected years: climatologically normal, dry and wet year. The simulation region is characterized by high average elevation above 4000 m and complex terrain. The back-trajectory approach is also calculated over three sub-regions over the TP: namely western, northeastern and southeastern TP, and the E-tagging approach could provide recycling-ratio distributions over the whole TP. Three aspects are investigated to characterize the precipitation recycling: annual mean, seasonal variations and spatial distributions. Averaged over the TP, the precipitation recycling ratio estimated by the E-tagging approach is higher than that from the back-trajectory method. The back-trajectory approach uses a precipitation threshold as total precipitation in five days divided by a random number, and this number was set to 500 as a tread off between equilibrium and computational efficiency. Lower recycling ratio derived from the back-trajectory approach is related to the precipitation threshold used. The E-tagging, however, tracks every air parcel of evaporation regardless of the precipitation amount. There is no obvious seasonal variation in the recycling ratio using both methods. The E-tagging approach shows high recycling ratios in the center TP, indicating stronger land-atmospheric interactions than elsewhere.

  12. Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

    Science.gov (United States)

    Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

    2017-01-01

    The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

  13. Conditional estimation of local pooled dispersion parameter in small-sample RNA-Seq data improves differential expression test.

    Science.gov (United States)

    Gim, Jungsoo; Won, Sungho; Park, Taesung

    2016-10-01

    High throughput sequencing technology in transcriptomics studies contribute to the understanding of gene regulation mechanism and its cellular function, but also increases a need for accurate statistical methods to assess quantitative differences between experiments. Many methods have been developed to account for the specifics of count data: non-normality, a dependence of the variance on the mean, and small sample size. Among them, the small number of samples in typical experiments is still a challenge. Here we present a method for differential analysis of count data, using conditional estimation of local pooled dispersion parameters. A comprehensive evaluation of our proposed method in the aspect of differential gene expression analysis using both simulated and real data sets shows that the proposed method is more powerful than other existing methods while controlling the false discovery rates. By introducing conditional estimation of local pooled dispersion parameters, we successfully overcome the limitation of small power and enable a powerful quantitative analysis focused on differential expression test with the small number of samples.

  14. Estimation of aortic valve leaflets from 3D CT images using local shape dictionaries and linear coding

    Science.gov (United States)

    Liang, Liang; Martin, Caitlin; Wang, Qian; Sun, Wei; Duncan, James

    2016-03-01

    Aortic valve (AV) disease is a significant cause of morbidity and mortality. The preferred treatment modality for severe AV disease is surgical resection and replacement of the native valve with either a mechanical or tissue prosthetic. In order to develop effective and long-lasting treatment methods, computational analyses, e.g., structural finite element (FE) and computational fluid dynamic simulations, are very effective for studying valve biomechanics. These computational analyses are based on mesh models of the aortic valve, which are usually constructed from 3D CT images though many hours of manual annotation, and therefore an automatic valve shape reconstruction method is desired. In this paper, we present a method for estimating the aortic valve shape from 3D cardiac CT images, which is represented by triangle meshes. We propose a pipeline for aortic valve shape estimation which includes novel algorithms for building local shape dictionaries and for building landmark detectors and curve detectors using local shape dictionaries. The method is evaluated on real patient image dataset using a leave-one-out approach and achieves an average accuracy of 0.69 mm. The work will facilitate automatic patient-specific computational modeling of the aortic valve.

  15. Estimation of methane emissions from local and crossbreed beef cattle in Daklak province of Vietnam

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Ramírez-Restrepo

    2017-07-01

    Full Text Available Objective This study was aimed at evaluating effects of cattle breed resources and alternative mixed-feeding practices on meat productivity and emission intensities from household farming systems (HFS in Daklak Province, Vietnam. Methods Records from Local Yellow×Red Sindhi (Bos indicus; Lai Sind and 1/2 Limousin, 1/2 Drought Master, and 1/2 Red Angus cattle during the growth (0 to 21 months and fattening (22 to 25 months periods were used to better understand variations on meat productivity and enteric methane emissions. Parameters were determined by the ruminant model. Four scenarios were developed: (HFS1 grazing from birth to slaughter on native grasses for approximately 10 h plus 1.5 kg dry matter/d (0.8% live weight [LW] of a mixture of guinea grass (19%, cassava (43% powder, cotton (23% seed, and rice (15% straw; (HFS2 growth period fed with elephant grass (1% of LW plus supplementation (1.5% of LW of rice bran (36%, maize (33%, and cassava (31% meals; and HFS3 and HFS4 computed elephant grass, but concentrate supplementation reaching 2% and 1% of LW, respectively. Results Results show that compared to HFS1, emissions (72.3±0.96 kg CH4/animal/life; least squares means± standard error of the mean were 15%, 6%, and 23% lower (p<0.01 for the HFS2, HFS3, and HFS4, respectively. The predicted methane efficiencies (CO2eq per kg of LW at slaughter (4.3±0.15, carcass weight (8.8±0.25 kg and kg of edible protein (44.1±1.29 were also lower (p<0.05 in the HFS4. In particular, irrespective of the HSF, feed supply and ratio changes had a more positive impact on emission intensities when crossbred 1/2 Red Angus cattle were fed than in their crossbred counterparts. Conclusion Modest improvements on feeding practices and integrated modelling frameworks may offer potential trade-offs to respond to climate change in Vietnam.

  16. Using velocity dispersion to estimate halo mass: Is the Local Group in tension with ΛCDM?

    Science.gov (United States)

    Elahi, Pascal J.; Power, Chris; Lagos, Claudia del P.; Poulton, Rhys; Robotham, Aaron S. G.

    2018-06-01

    Satellite galaxies are commonly used as tracers to measure the line-of-sight (LOS)velocity dispersion (σLOS) of the dark matter halo associated with their central galaxy, and thereby to estimate the halo's mass. Recent observational dispersion estimates of the Local Group, including the Milky Way and M31, suggest σ ˜50 km s-1, which is surprisingly low when compared to the theoretical expectation of σ ˜100 km s-1 for systems of their mass. Does this pose a problem for Lambda cold dark matter (ΛCDM)? We explore this tension using the SURFS suite of N-body simulations, containing over 10000 (sub)haloes with well tracked orbits. We test how well a central galaxy's host halo velocity dispersion can be recovered by sampling σLOS of subhaloes and surrounding haloes. Our results demonstrate that σLOS is biased mass proxy. We define an optimal window in vLOS and projected distance (Dp) - 0.5 ≲ Dp/Rvir ≲ 1.0 and vLOS ≲ 0.5Vesc, where Rvir is the virial radius and Vesc is the escape velocity - such that the scatter in LOS to halo dispersion is minimized - σLOS = (0.5 ± 0.1)σv, H. We argue that this window should be used to measure LOS dispersions as a proxy for mass, as it minimises scatter in the σLOS-Mvir relation. This bias also naturally explains the results from McConnachie (2012), who used similar cuts when estimating σLOS, LG, producing a bias of σLG = (0.44 ± 0.14)σv, H. We conclude that the Local Group's velocity dispersion does not pose a problem for ΛCDM and has a mass of log M_{LG, vir}/M_{⊙}=12.0^{+0.8}_{-2.0}.

  17. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  18. Estimating live fuel status by drought indices: an approach for assessing local impact of climate change on fire danger

    Science.gov (United States)

    Pellizzaro, Grazia; Dubrovsky, Martin; Bortolu, Sara; Ventura, Andrea; Arca, Bachisio; Masia, Pierpaolo; Duce, Pierpaolo

    2014-05-01

    Mediterranean shrubs are an important component of both Mediterranean vegetation communities and understorey vegetation. They also constitute the surface fuels primarily responsible for the ignition and the spread of wildland fires in Mediterranean forests. Although fire spread and behaviour are dependent on several factors, the water content of live fuel plays an important role in determining fire occurrence and spread, especially in the Mediterranean shrubland, where live fuel is often the main component of the available fuel which catches fire. According to projections on future climate, an increase in risk of summer droughts is likely to take place in Southern Europe. More prolonged drought seasons induced by climatic changes are likely to influence general flammability characteristics of fuel, affecting load distribution in vegetation strata, floristic composition, and live and dead fuel ratio. In addition, variations in precipitation and mean temperature could directly affect fuel water status, and consequently flammability, and length of critical periods of high ignition danger for Mediterranean ecosystems. The main aim of this work was to propose a methodology for evaluating possible impacts of future climate change on moisture dynamic and length of fire danger period at local scale. Specific objectives were: i) evaluating performances of meteorological drought indices in describing seasonal pattern of live fuel moisture content (LFMC), and ii) simulating the potential impacts of future climate changes on the duration of fire danger period. Measurements of LFMC seasonal pattern of three Mediterranean shrub species were performed in North Western Sardinia (Italy) for 8 years. Seasonal patterns of LFMC were compared with the Drought Code of the Canadian Forest Fire Weather Index and the Keetch-Byram Drought Index. Analysis of frequency distribution and cumulative distribution curves were carried out in order to evaluate performance of codes and to identify

  19. Variabilidade local e regional da evapotranspiração estimada pelo algoritmo SEBAL Local and regional variability of evapotranspiration estimated by SEBAL algorithm

    Directory of Open Access Journals (Sweden)

    Luis C. J. Moreira

    2010-12-01

    Full Text Available Em face da importância em conhecer a evapotranspiração (ET para uso racional da água na irrigação no contexto atual de escassez desse recurso, algoritmos de estimativa da ET a nível regional foram desenvolvidos utilizando-se de ferramentas de sensoriamento remoto. Este estudo objetivou aplicar o algoritmo SEBAL (Surface Energy Balance Algorithms for Land em três imagens do satélite Landsat 5, do segundo semestre de 2006. As imagens correspondem a áreas irrigadas, floresta nativa densa e a Caatinga do Estado do Ceará (Baixo Acaraú, Chapada do Apodi e Chapada do Araripe. Este algoritmo calcula a evapotranspiração horária a partir do fluxo de calor latente, estimado como resíduo do balanço de energia na superfície. Os valores de ET obtidos nas três regiões foram superiores a 0,60 mm h-1 nas áreas irrigadas ou de vegetação nativa densa. As áreas de vegetação nativa menos densa apresentaram taxa da ET horária de 0,35 a 0,60 mm h-1, e valores quase nulos em áreas degradadas. A análise das médias de evapotranspiração horária pelo teste de Tukey a 5% de probabilidade permitiu evidenciar uma variabilidade significativa local, bem como regional no Estado do Ceará.In the context of water resources scarcity, the rational use of water for irrigation is necessary, implying precise estimations of the actual evapotranspiration (ET. With the recent progresses of remote-sensed technologies, regional algorithms estimating evapotranspiration from satellite observations were developed. This work aimed at applying the SEBAL algorithm (Surface Energy Balance Algorithms for Land at three Landsat-5 images during the second semester of 2006. These images cover irrigated areas, dense native forest areas and caatinga areas in three regions of the state of Ceará (Baixo Acaraú, Chapada do Apodi and Chapada do Araripe. The SEBAL algorithm calculates the hourly evapotranspiration from the latent heat flux, estimated from the surface energy

  20. Life expectancy estimation in small administrative areas with non-uniform population sizes: application to Australian New South Wales local government areas

    OpenAIRE

    Stephens, Alexandre S; Purdie, Stuart; Yang, Baohui; Moore, Helen

    2013-01-01

    Objective To determine a practical approach for deriving life expectancy estimates in Australian New South Wales local government areas which display a large diversity in population sizes. Design Population-based study utilising mortality and estimated residential population data. Setting 153 local government areas in New South Wales, Australia. Outcome measures Key performance measures of Chiang II, Silcocks, adjusted Chiang II and Bayesian random effects model methodologies of life expectan...

  1. Retrospective Analog Year Analyses Using NASA Satellite Precipitation and Soil Moisture Data to Improve USDA's World Agricultural Supply and Demand Estimates

    Science.gov (United States)

    Teng, William; Shannon, Harlan; Mladenova, Iliana; Fang, Fan

    2010-01-01

    A primary goal of the U.S. Department of Agriculture (USDA) is to expand markets for U.S. agricultural products and support global economic development. The USDA World Agricultural Outlook Board (WAOB) supports this goal by coordinating monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Because weather has a significant impact on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments, in a GIS-based, Global Agricultural Decision Support Environment (GLADSE). The main goal of this project, thus, is to improve WAOB's estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE (See diagram below). Soil moisture is currently a primary data gap at WAOB.

  2. Improving the Estimation of Local Welfare Costs of Conservation in Low-Income Countries Using Choice Experiments

    DEFF Research Database (Denmark)

    Rakotonarivo, Onjamirindra Sarobidy

    and comprises a systematic review and three field tests of DCE in a new REDD+ (Reducing Emissions from Deforestation and forest Degradation) project and national park in eastern Madagascar. I first conducted a systematic review of empirical evidence on the reliability and validity of DCEs when valuing non-market...... the validity of DCE in estimating the costs of conservation restrictions ex-ante. I found that experience of forest protection matters; households who have been exposed to forest protection for a comparatively longer period had significantly higher welfare costs for restricting forest clearance than those who...... techniques. It also has major implications for how forest conservation policy may be devised in low-income countries, including devolution of secure forestland tenure to local people and genuinely negotiating conservation with forest users....

  3. Inter- and intra-storm variability of the isotope composition of precipitation in Southern Israel: Are local or large-scale factors responsible?

    International Nuclear Information System (INIS)

    Gat, J.R.; Adar, E.; Alpert, P.

    2002-01-01

    A detailed sequential rain sampling of rainstorms was carried out during the 1989/90 and 1990/91 rainy season in the coastal plain of Israel with an annual average of 530 mm of rain and in the western Negev where the average annual rainfall is 93 mm. On four occasions, rain was concurrently available at both stations. The variability of the isotope composition within a rainy spell is quite considerable but falls short of the range of isotopic values encountered during the total season. Different rainy episodes show distinguishable isotope compositions, which evidently are characteristic of a larger time/space niche than that of the momentary, local, rain event. This is confirmed by the good correlation between the mean isotope composition of concurrently sampled events at both stations. A 'rain amount effect' is not apparent when the amount-weighted data for each complete rain episode are compared, because any possible effect is masked by the inter-storm variability. However by singling out the data within each storm sequence separately, a moderate effect is seen. On the whole, the results seem to support the notion that the isotope data are determined by the large, synoptic scale, situation. However within the range of values characteristic of the origin of the air masses there is a pronounced dependence of the isotope composition on the extent of the cloud field associated with each event, which is interpreted as a measure of the degree of rainout from the air mass, i.e. a typical Rayleigh effect. Local effects related to momentary rain intensity contribute only to a residual modulation of the above-mentioned effects. (author)

  4. The Impact of Star Formation Histories on Stellar Mass Estimation: Implications from the Local Group Dwarf Galaxies

    Science.gov (United States)

    Zhang, Hong-Xin; Puzia, Thomas H.; Weisz, Daniel R.

    2017-11-01

    Building on the relatively accurate star formation histories (SFHs) and metallicity evolution of 40 Local Group (LG) dwarf galaxies derived from resolved color-magnitude diagram modeling, we carried out a comprehensive study of the influence of SFHs, metallicity evolution, and dust extinction on the UV-to-near-IR color-mass-to-light ratio (color-{log}{{{\\Upsilon }}}\\star (λ)) distributions and M ⋆ estimation of local universe galaxies. We find that (1) the LG galaxies follow color-{log}{{{\\Upsilon }}}\\star (λ) relations that fall in between the ones calibrated by previous studies; (2) optical color-{log}{{{\\Upsilon }}}\\star (λ) relations at higher [M/H] are generally broader and steeper; (3) the SFH “concentration” does not significantly affect the color-{log}{{{\\Upsilon }}}\\star (λ) relations; (4) light-weighted ages }λ and metallicities }λ together constrain {log}{{{\\Upsilon }}}\\star (λ) with uncertainties ranging from ≲0.1 dex for the near-IR up to 0.2 dex for the optical passbands; (5) metallicity evolution induces significant uncertainties to the optical but not near-IR {{{\\Upsilon }}}\\star (λ) at a given }λ and }λ ; (6) the V band is the ideal luminance passband for estimating {{{\\Upsilon }}}\\star (λ) from single colors, because the combinations of {{{\\Upsilon }}}\\star (V) and optical colors such as B - V and g - r exhibit the weakest systematic dependences on SFHs, metallicities, and dust extinction; and (7) without any prior assumption on SFHs, M ⋆ is constrained with biases ≲0.3 dex by the optical-to-near-IR SED fitting. Optical passbands alone constrain M ⋆ with biases ≲0.4 dex (or ≲0.6 dex) when dust extinction is fixed (or variable) in SED fitting. SED fitting with monometallic SFH models tends to underestimate M ⋆ of real galaxies. M ⋆ tends to be overestimated (or underestimated) at the youngest (or oldest) }{mass}.

  5. Estimation of efficiency of new local rehabilitation method at the early post-operative period after dental implantation

    Directory of Open Access Journals (Sweden)

    A. V. Pasechnik

    2017-01-01

      Summary Despite of success of dental implantation, there are often complications at the early post-operative period of implant placing associated with wound damage and aseptic inflammation. Purpose of the work is studying clinical efficiency of combined local application of new mucosal gel “Apior” and magnetotherapy at the early post-operative period after dental implantation. Combined local application of the mucosal gel “Apior” and pulsating low-frequency electromagnetic field in the complex medical treatment of patients after conducting an operation of setting dental implants favourably affects the common state of patients and clinical symptoms of inflammation in the area of operating wound. As compared with patients who had traditional anti-inflammatory therapy, the patients treated with local application of apigel and magnetoterapy had decline of edema incidence, of gingival mucosa hyperemia, of discomfort in the area of conducted operation. There occurred more rapid improvement of inflammation painfulness, which correlated with the improvement of hygienic state of oral cavity and promoted to prevention of bacterial content of damaged mucous surfaces. Estimation of microvasculatory blood stream by the method of ultrasonic doppler flowmetry revealed more rapid normalization of volume and linear high systole speed of blood stream in the periimplant tissues in case of use of new complex local rehabilitation method, that testified to the less pronounced inflammation of oral mucosa after the operation. The authors came to conclusion that the local application of the offered method of medical treatment of early post-operative complications of dental implantation reduces terms of renewal of structural-functional integrity of oral mucosa, helps in preventing development of inflammatory complications and strengthening endosseus implant. The inclusion in the treatment management of a new combined method of application of mucosal gel “Apior” and

  6. The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model

    NARCIS (Netherlands)

    de Graaf-Ruizendaal, Willemijn A.; de Bakker, Dinny H.

    2013-01-01

    Background This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary

  7. Estimation of mercury emissions from forest fires, lakes, regional and local sources using measurements in Milwaukee and an inverse method

    Directory of Open Access Journals (Sweden)

    B. de Foy

    2012-10-01

    Full Text Available Gaseous elemental mercury is a global pollutant that can lead to serious health concerns via deposition to the biosphere and bio-accumulation in the food chain. Hourly measurements between June 2004 and May 2005 in an urban site (Milwaukee, WI show elevated levels of mercury in the atmosphere with numerous short-lived peaks as well as longer-lived episodes. The measurements are analyzed with an inverse model to obtain information about mercury emissions. The model is based on high resolution meteorological simulations (WRF, hourly back-trajectories (WRF-FLEXPART and a chemical transport model (CAMx. The hybrid formulation combining back-trajectories and Eulerian simulations is used to identify potential source regions as well as the impacts of forest fires and lake surface emissions. Uncertainty bounds are estimated using a bootstrap method on the inversions. Comparison with the US Environmental Protection Agency's National Emission Inventory (NEI and Toxic Release Inventory (TRI shows that emissions from coal-fired power plants are properly characterized, but emissions from local urban sources, waste incineration and metal processing could be significantly under-estimated. Emissions from the lake surface and from forest fires were found to have significant impacts on mercury levels in Milwaukee, and to be underestimated by a factor of two or more.

  8. Effective assimilation of global precipitation: simulation experiments

    Directory of Open Access Journals (Sweden)

    Guo-Yuan Lien

    2013-07-01

    Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and

  9. Properties of Extreme Precipitation and Their Uncertainties in 3-year GPM Precipitation Radar Data

    Science.gov (United States)

    Liu, N.; Liu, C.

    2017-12-01

    Extreme high precipitation rates are often related to flash floods and have devastating impacts on human society and the environments. To better understand these rare events, 3-year Precipitation Features (PFs) are defined by grouping the contiguous areas with nonzero near-surface precipitation derived using Global Precipitation Measurement (GPM) Ku band Precipitation Radar (KuPR). The properties of PFs with extreme precipitation rates greater than 20, 50, 100 mm/hr, such as the geographical distribution, volumetric precipitation contribution, seasonal and diurnal variations, are examined. In addition to the large seasonal and regional variations, the rare extreme precipitation rates often have a larger contribution to the local total precipitation. Extreme precipitation rates occur more often over land than over ocean. The challenges in the retrieval of extreme precipitation might be from the attenuation correction and large uncertainties in the Z-R relationships from near-surface radar reflectivity to precipitation rates. These potential uncertainties are examined by using collocated ground based radar reflectivity and precipitation retrievals.

  10. GPM, DPR Level 2A Ka Precipitation V03

    Data.gov (United States)

    National Aeronautics and Space Administration — The 2AKa algorithm provides precipitation estimates from the Ka radar of the Dual-Frequency Precipitation Radar on the core GPM spacecraft. The product contains two...

  11. GPM, DPR Level 2A Ku Precipitation V03

    Data.gov (United States)

    National Aeronautics and Space Administration — The 2AKu algorithm provides precipitation estimates from the Ku radar of the Dual-Frequency Precipitation Radar on the core GPM spacecraft. The product contains one...

  12. Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

    Science.gov (United States)

    Funk, Christopher C.; Verdin, James; Adams Chavula,; Gregory J. Husak,; Harikishan Jayanthi,; Tamuka Magadzire,

    2013-01-01

    During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAID, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were upscaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi.

  13. Precipitation-induced runoff and leaching from milled peat mining mires by peat types: A comparative method for estimating the loading of water bodies during peat production

    Energy Technology Data Exchange (ETDEWEB)

    Svahnbaeck, L.

    2007-07-01

    Finland has some 10 million hectares of peatland, accounting for almost a third of its total area. Macroclimatic conditions have varied in the course of the Holocene growth and development of this peatland, and with them the habitats of the peat-forming plants. Temperatures and moisture conditions have played a significant role in determining the dominant species of mire plants growing there at any particular time, the resulting mire types and the accumulation and deposition of plant remains to form the peat. While in a natural state the mires of Finland have functioned as carbon dioxide sinks throughout the post-glacial period, but the ditching of peatland for forestry and agriculture, amounting to some 5,7 million hectares in Finland, has affected their water balance, especially over the last hundred years, and has thereby altered the quantity and species composition of the mire vegetation. The invasion of trees and woody plants to replace the typical mire plants following ditching for forestry purposes has stimulated the decomposition of the already accumulated peat and promoted the humification of the microbiologically active root system layer. The above climatic, environmental and mire development factors, together with ditching, have contributed, and continue to contribute, to the existence of peat horizons that differ in their physical and chemical properties, leading to differences in material transport between peatlands in a natural state and mires that have been ditched or prepared for forestry and peat production. Watercourse loading from the ditching of mires or their use for peat production can have detrimental effects on river and lake environments and their recreational use, especially where oxygen-consuming organic solids and soluble organic substances and nutrients are concerned. It has not previously been possible, however, to estimate in advance the watercourse loading likely to arise from ditching and peat production on the basis of the

  14. Estimation of the local and long-range contributions to particulate matter levels using continuous measurements in a single urban background site

    Science.gov (United States)

    Diamantopoulou, Marianna; Skyllakou, Ksakousti; Pandis, Spyros N.

    2016-06-01

    The Particulate Matter Source Apportionment Technology (PSAT) algorithm is used together with PMCAMx, a regional chemical transport model, to develop a simple observation-based method (OBM) for the estimation of local and regional contributions of sources of primary and secondary pollutants in urban areas. We test the hypothesis that the minimum of the diurnal average concentration profile of the pollutant is a good estimate of the average contribution of long range transport levels. We use PMCAMx to generate "pseudo-observations" for four different European cities (Paris, London, Milan, and Dusseldorf) and PSAT to estimate the corresponding "true" local and regional contributions. The predictions of the proposed OBM are compared to the "true" values for different definitions of the source area. During winter, the estimates by the OBM for the local contributions to the concentrations of total PM2.5, primary pollutants, and sulfate are within 25% of the "true" contributions of the urban area sources. For secondary organic aerosol the OBM overestimates the importance of the local sources and it actually estimates the contributions of sources within 200 km from the receptor. During summer for primary pollutants and cities with low nearby emissions (ratio of emissions in an area extending 100 km from the city over local emissions lower than 10) the OBM estimates correspond to the city emissions within 25% or so. For cities with relatively high nearby emissions the OBM estimates correspond to emissions within 100 km from the receptor. For secondary PM2.5 components like sulfate and secondary organic aerosol the OBM's estimates correspond to sources within 200 km from the receptor. Finally, for total PM2.5 the OBM provides approximately the contribution of city emissions during the winter and the contribution of sources within 100 km from the receptor during the summer.

  15. A Novel Differential Time-of-Arrival Estimation Technique for Impact Localization on Carbon Fiber Laminate Sheets

    Directory of Open Access Journals (Sweden)

    Eugenio Marino Merlo

    2017-10-01

    Full Text Available Composite material structures are commonly used in many industrial sectors (aerospace, automotive, transportation, and can operate in harsh environments where impacts with other parts or debris may cause critical safety and functionality issues. This work presents a method for improving the accuracy of impact position determination using acoustic source triangulation schemes based on the data collected by piezoelectric sensors attached to the structure. A novel approach is used to estimate the Differential Time-of-Arrival (DToA between the impact response signals collected by a triplet of sensors, overcoming the limitations of classical methods that rely on amplitude thresholds calibrated for a specific sensor type. An experimental evaluation of the proposed technique was performed with specially made circular piezopolymer (PVDF sensors designed for Structural Health Monitoring (SHM applications, and compared with commercial piezoelectric SHM sensors of similar dimensions. Test impacts at low energies from 35 mJ to 600 mJ were generated in a laboratory by free-falling metal spheres on a 500 mm × 500 mm × 1.25 mm quasi-isotropic Carbon Fiber Reinforced Polymer (CFRP laminate plate. From the analysis of many impact signals, the resulting localization error was improved for all types of sensors and, in particular, for the circular PVDF sensor an average error of 20.3 mm and a standard deviation of 8.9 mm was obtained.

  16. Global precipitations and climate change. Proceedings

    International Nuclear Information System (INIS)

    Desbois, M.; Desalmand, F.

    1994-01-01

    The workshop reviewed the present status of knowledge concerning the past and present evolution of the distribution of precipitations at global scale, related to climate evolution at different time scales. This review was intended to assess the availability and quality of data which could help, through validation and initialization of model studies, to improve our understanding of the processes determining these precipitation changes. On another hand, the modelling specialists presented their actual use of precipitation data. Exchanges of views between the modelling and observing communities were thus made possible, leading to a set of recommendations for future studies. Sessions were then devoted to specific themes: 1) Paleoclimatology, 2) data collection, history and statistics, programmes, 3) methodologies and accuracy of large scale estimation of precipitation from conventional data, 4) estimation of precipitation from satellite data, 5) modelling studies. (orig.)

  17. New estimates of direct N2O emissions from Chinese croplands from 1980 to 2007 using localized emission factors

    Directory of Open Access Journals (Sweden)

    F. S. Zhang

    2011-10-01

    Full Text Available Nitrous oxide (N2O is a long-lived greenhouse gas with a large radiation intensity and it is emitted mainly from agricultural land. Accurate estimates of total direct N2O emissions from croplands on a country scale are important for global budgets of anthropogenic sources of N2O emissions and for the development of effective mitigation strategies. The objectives of this study were to re-estimate direct N2O emissions using localized emission factors and a database of measurements from Chinese croplands. We obtained N2O emission factors for paddy fields (0.41 ± 0.04% and uplands (1.05 ± 0.02% from a normalization process through cube root transformation of the original data. After comparing the results of normalization from the original values, Logarithmic and cube root transformations were used because the frequency of the original data was not normally distributed. Direct N2O emissions from Chinese croplands from 1980 to 2007 were estimated using IPCC (2006 guidelines combined with separate localized emission factors for paddy fields and upland areas. Direct N2O emissions from paddy fields showed little change, increasing by 10.5% with an annual rate of increase of 0.4% from 32.3 Gg N2O-N in 1980 to 35.7 Gg N2O-N in 2007. In contrast, emissions from uplands changed dramatically, increasing by 308% with an annual rate of 11% from 68.0 Gg N2O-N in 1980 to 278 Gg N2O-N in 2007. Total direct N2O emissions from Chinese croplands increased by 213% with an annual rate of 7.6% from 100 Gg N2O-N in 1980 to 313 Gg N2O-N in 2007, and were determined mainly by upland emissions (accounting for 67.8–88.6% of total emissions from 1980 to 2007. Synthetic N fertilizers played a major role in N2O emissions from agricultural land, and the magnitude of the contributions to total direct N2O emissions made by different amendments was synthetic N fertilizer > manure > straw, representing about 78, 15, and 6% of total direct N2O emissions, respectively, between

  18. Modelled Precipitation Over Greenland

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the annual total precipitation from 1985 to 1999 and monthly total precipitation from January 1985 to December 1999. The data is derived from...

  19. Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

    International Nuclear Information System (INIS)

    Grimm, J.W.; Lynch, J.A.

    2005-01-01

    Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8 km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8 km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate. - A linear least-squares regression approach was used to develop daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

  20. Upper Estimates on the Higher-dimensional Multifractal Spectrum of Local Entropy%局部熵高维重分形谱的上界估计

    Institute of Scientific and Technical Information of China (English)

    严珍珍; 陈二才

    2008-01-01

    We discuss the problem of higher-dimensional multifractal spectrum of lo-cal entropy for arbitrary invariant measures. By utilizing characteristics of a dynam-ical system, namely, higher-dimensional entropy capacities and higher-dimensional correlation entropies, we obtain three upper estimates on the higher-dimensional mul-tifractal spectrum of local entropies. We also study the domain of higher-dimensional multifractal spetrum of entropies.

  1. Using stochastic space-time models to map extreme precipitation in southern Portugal

    Directory of Open Access Journals (Sweden)

    A. C. Costa

    2008-07-01

    Full Text Available The topographic characteristics and spatial climatic diversity are significant in the South of continental Portugal where the rainfall regime is typically Mediterranean. Direct sequential cosimulation is proposed for mapping an extreme precipitation index in southern Portugal using elevation as auxiliary information. The analysed index (R5D can be considered a flood indicator because it provides a measure of medium-term precipitation total. The methodology accounts for local data variability and incorporates space-time models that allow capturing long-term trends of extreme precipitation, and local changes in the relationship between elevation and extreme precipitation through time. Annual gridded datasets of the flood indicator are produced from 1940 to 1999 on 800 m×800 m grids by using the space-time relationship between elevation and the index. Uncertainty evaluations of the proposed scenarios are also produced for each year. The results indicate that the relationship between elevation and extreme precipitation varies locally and has decreased through time over the study region. In wetter years the flood indicator exhibits the highest values in mountainous regions of the South, while in drier years the spatial pattern of extreme precipitation has much less variability over the study region. The uncertainty of extreme precipitation estimates also varies in time and space, and in earlier decades is strongly dependent on the density of the monitoring stations network. The produced maps will be useful in regional and local studies related to climate change, desertification, land and water resources management, hydrological modelling, and flood mitigation planning.

  2. Chemical and isotopic composition of precipitations in Syria

    International Nuclear Information System (INIS)

    Abou Zakhem, B.; Hafez, R.

    2008-01-01

    13 meteoric stations were selected in syria for cumulative monthly rainfall sampling during two hydrological cycles; 1991-1992 and 1992-1993. The chemical and isotopic compositions of monthly precipitation were studied. The winter and spring rainfall isotopic characteristics were determined, in addition to the syrian or local meteoric line (SMWL) was estimated with a slope of 6.63 and that of both syria and Jordan of 6.73. The effect of climatic factors as temperature and relative air humidity on oxygen-18, deuterium and d-excess were studied and it was found that the relationship between temperature and oxygen-18 and deuterium is a positive linear correlation; however, it is a negative correlation with d-excess. The mean seasonal variation amplitude was determined by 6%, and the amount effect on isotopic content of precipitation was studied. The geographic factors and its affect on isotopic contents of precipitation such as altitude were considered, furthermore, the isotopic gradient with altitude was determined for both oxygen-18 and deuterium (-0.14% and - 0.84%/100 m elevation respectively). The spatial variability of oxygen-18, deuterium, tritium and d-excess indicted the effect of mountain chains and gaps between mountains on the isotopic content of precipitation, the continental effect on tritium build-up by about 33% per 100 Km from the coast. The increase of d-excess values towards the south west proves the eastern mediterranean climate type over this region. (author)

  3. Life expectancy estimation in small administrative areas with non-uniform population sizes: application to Australian New South Wales local government areas.

    Science.gov (United States)

    Stephens, Alexandre S; Purdie, Stuart; Yang, Baohui; Moore, Helen

    2013-12-02

    To determine a practical approach for deriving life expectancy estimates in Australian New South Wales local government areas which display a large diversity in population sizes. Population-based study utilising mortality and estimated residential population data. 153 local government areas in New South Wales, Australia. Key performance measures of Chiang II, Silcocks, adjusted Chiang II and Bayesian random effects model methodologies of life expectancy estimation including agreement analysis of life expectancy estimates and comparison of estimate SEs. Chiang II and Silcocks methods produced almost identical life expectancy estimates across a large range of population sizes but calculation failures and excessively large SEs limited their use in small populations. A population of 25 000 or greater was required to estimate life expectancy with SE of 1 year or less using adjusted Chiang II (a composite of Chiang II and Silcocks methods). Data aggregation offered some remedy for extending the use of adjusted Chiang II in small populations but reduced estimate currency. A recently developed Bayesian random effects model utilising the correlation in mortality rates between genders, age groups and geographical areas markedly improved the precision of life expectancy estimates in small populations. We propose a hybrid approach for the calculation of life expectancy using the Bayesian random effects model in populations of 25 000 or lower permitting the precise derivation of life expectancy in small populations. In populations above 25 000, we propose the use of adjusted Chiang II to guard against violations of spatial correlation, to benefit from a widely accepted method that is simpler to communicate to local health authorities and where its slight inferior performance compared with the Bayesian approach is of minor practical significance.

  4. Acid precipitation literature review

    Energy Technology Data Exchange (ETDEWEB)

    Seip, H M; Andersen, B; Andersson, G; Hov, Oe; Kucera, V; Moseholm, L

    1986-01-01

    There is an increasing number of publications on acid deposition and related phenomena. Interest in these topics has also been reflected in a considerable number of meetings and conferences in this field. The largest of these in 1985 was the ''International Symposium on Acidic Precipitation'' (Muskoka, Ontario). Most work so far has been carried out in North America and Europe. There is, however, an increasing interest in obtaining a better picture of sensitive areas and possible acidification in other parts of the world. Anthropogenic SO/sub 2/ emissions have been estimated to be (in TgSyr/sup -1/): 2.4 (Africa), 4.1 (South America), 0.7 (Ocenia), and 18.3 (Asia). The largest increase during the last decade has been in Asia. Based on Studies of precipitation in remote areas it has been suggested that the natural background concentration for sulphate in many areas should be about 6 ..mu..eq 1/sup -1/. A new study of sulphate and nitrate in Greenland snow showed that both ions increased by a factor of about 2 from 1895 to 1978. The concentrations of SO/sub 2/ at Norwegian rural sites show a decreasing trend since late 1970s, while concentrations of sulphate in air show no clear trend. More reliable models for transformation, transport and deposition of chemicals are being developed, including three-dimensional grid models to describe episodes of elevated pollution levels lasting for a few days. Model calculations indicate that control of hydrocarbon (HC) emissions is much more efficient in reducing the ozone level in southern Scandinavia in episodes influenced by long-range transported pollutants than NO/sub x/ control of combined NO/sub x/ and HC control. 36 refs. (EG).

  5. The tritium content of precipitation and groundwater at Yola, Nigeria ...

    African Journals Online (AJOL)

    Tritium is a radioactive isotope of hydrogen which occurs in precipitation. In groundwater studies tritium measurements give information on the time of recharge to the system; the tritium content of precipitation being used to estimate the input of tritium to the groundwater system. At Yola, the tritium ontents in precipitation and ...

  6. A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy.

    Science.gov (United States)

    Corbett-Detig, Russell; Nielsen, Rasmus

    2017-01-01

    Admixture-the mixing of genomes from divergent populations-is increasingly appreciated as a central process in evolution. To characterize and quantify patterns of admixture across the genome, a number of methods have been developed for local ancestry inference. However, existing approaches have a number of shortcomings. First, all local ancestry inference methods require some prior assumption about the expected ancestry tract lengths. Second, existing methods generally require genotypes, which is not feasible to obtain for many next-generation sequencing projects. Third, many methods assume samples are diploid, however a wide variety of sequencing applications will fail to meet this assumption. To address these issues, we introduce a novel hidden Markov model for estimating local ancestry that models the read pileup data, rather than genotypes, is generalized to arbitrary ploidy, and can estimate the time since admixture during local ancestry inference. We demonstrate that our method can simultaneously estimate the time since admixture and local ancestry with good accuracy, and that it performs well on samples of high ploidy-i.e. 100 or more chromosomes. As this method is very general, we expect it will be useful for local ancestry inference in a wider variety of populations than what previously has been possible. We then applied our method to pooled sequencing data derived from populations of Drosophila melanogaster on an ancestry cline on the east coast of North America. We find that regions of local recombination rates are negatively correlated with the proportion of African ancestry, suggesting that selection against foreign ancestry is the least efficient in low recombination regions. Finally we show that clinal outlier loci are enriched for genes associated with gene regulatory functions, consistent with a role of regulatory evolution in ecological adaptation of admixed D. melanogaster populations. Our results illustrate the potential of local ancestry

  7. Orographic Impacts on Liquid and Ice-Phase Precipitation Processes during OLYMPEX

    Science.gov (United States)

    Petersen, W. A.; Hunzinger, A.; Gatlin, P. N.; Wolff, D. B.

    2017-12-01

    The Global Precipitation Measurement (GPM) mission Olympic Mountains Experiment (OLYMPEX) focused on physical validation of GPM products in cold-season, mid-latitude frontal precipitation occurring over the Olympic Mountains of Washington State. Herein, we use data collected by the NASA S-band polarimetric radar (NPOL) to quantify and examine ice (IWP), liquid (LWP) and total water paths (TWP) relative to surface precipitation rates and column hydrometeor types for several cases occurring in different synoptic and/or Froude number regimes. These quantities are compared to coincident precipitation properties measured or estimated by GPM's Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR). Because ice scattering is the dominant radiometric signature used by the GMI for estimating precipitation over land, and because the DPR is greatly affected by ground clutter in the lowest 1 - 2 km above ground, measurement limitations combined with orographic forcing may impact the degree to which DPR and/or GMI algorithms are able to adequately observe and estimate precipitation over and around orography.Preliminary case results suggest: 1) as expected, the Olympic Mountains force robust enhancements in the liquid and ice microphysical processes on windward slopes, especially in atmospheric river events; 2) localized orographic enhancements alter the balance of liquid and frozen precipitation contributions (IWP/TWP, LWP/TWP) to near surface rain rate, and for two cases examined thus far the balance seems to be sensitive to flow direction at specific intersections with the terrain orientation; and 3) GPM measurement limitations related to the depth of surface clutter impact for the DPR, and degree to which ice processes are coupled to the orographic rainfall process (DPR and GMI), especially along windward mountain slopes, may constrain the ability of retrieval algorithms to properly estimate near-surface precipitation quantities over complex terrain. Ongoing

  8. Interannual variation of annual precipitation and urban effect on precipitation in the Beijing region

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The large scale character of the interannual variation of precipitation and the urban effect on local annual precipitation anomaly are investigated in this paper based on the 1960-2000 annual precipitation observations at 20 stations in the Beijing region. The results show that: the annual precipitation in the Beijing region possesses the large scale variation character with the linear trend of - 1.197/10 yr, which corresponds to a total reduction of 27.82 mm in annual precipitation in the 41 years; the local annual precipitation anomalies (percent of the normal 1960-2000) show a positive center near the urban area, i.e. urban precipitation island (UPI), whose intensity increases with the linear trend of 0. 6621%/10 yr, opposite to the interannual trend of large scale precipitation over the Beijing region; changes in the UPI are also associated with the intensity of synoptic processes of precipitation, and when the synoptic processes are strong (wet years), the intensity of UPI strengthens, while the synoptic processes are weak (dry years), and the UPI disappears in the Beijing region.

  9. Spatial interpolation of hourly precipitation and dew point temperature for the identification of precipitation phase and hydrologic response in a mountainous catchment

    Science.gov (United States)

    Garen, D. C.; Kahl, A.; Marks, D. G.; Winstral, A. H.

    2012-12-01

    In mountainous catchments, it is well known that meteorological inputs, such as precipitation, air temperature, humidity, etc. vary greatly with elevation, spatial location, and time. Understanding and monitoring catchment inputs is necessary in characterizing and predicting hydrologic response to these inputs. This is true all of the time, but it is the most dramatically critical during large storms, when the input to the stream system due to rain and snowmelt creates the potential for flooding. Besides such crisis events, however, proper estimation of catchment inputs and their spatial distribution is also needed in more prosaic but no less important water and related resource management activities. The first objective of this study is to apply a geostatistical spatial interpolation technique (elevationally detrended kriging) to precipitation and dew point temperature on an hourly basis and explore its characteristics, accuracy, and other issues. The second objective is to use these spatial fields to determine precipitation phase (rain or snow) during a large, dynamic winter storm. The catchment studied is the data-rich Reynolds Creek Experimental Watershed near Boise, Idaho. As part of this analysis, precipitation-elevation lapse rates are examined for spatial and temporal consistency. A clear dependence of lapse rate on precipitation amount exists. Certain stations, however, are outliers from these relationships, showing that significant local effects can be present and raising the question of whether such stations should be used for spatial interpolation. Experiments with selecting subsets of stations demonstrate the importance of elevation range and spatial placement on the interpolated fields. Hourly spatial fields of precipitation and dew point temperature are used to distinguish precipitation phase during a large rain-on-snow storm in December 2005. This application demonstrates the feasibility of producing hourly spatial fields and the importance of doing

  10. Cerium oxalate precipitation

    International Nuclear Information System (INIS)

    Chang, T.P.

    1987-02-01

    Cerium, a nonradioactive, common stand-in for plutonium in development work, has been used to simulate several plutonium precipitation processes at the Savannah River Laboratory. There are similarities between the plutonium trifluoride and the cerium oxalate precipitations in particle size and extent of plating, but not particle morphology. The equilibrium solubility, precipitation kinetics, particle size, extent of plating, and dissolution characteristics of cerium oxalate have been investigated. Interpretations of particle size and plating based on precipitation kinetics (i.e., nucleation and crystal growth) are presented. 16 refs., 7 figs., 6 tabs

  11. Risk assessment of precipitation extremes in northern Xinjiang, China

    Science.gov (United States)

    Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

    2018-05-01

    This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.

  12. 18O, 2H and 3H isotopic composition of precipitation and shallow groundwater in Olkiluoto

    International Nuclear Information System (INIS)

    Hendriksson, N.; Karhu, J.; Niinikoski, P.

    2014-12-01

    The isotopic composition of oxygen and hydrogen in local precipitation is a key parameter in the modelling of local water circulation. This study was initiated in order to provide systematic monthly records of the isotope content of atmospheric precipitation in the Olkiluoto area and to establish the relation between local rainfall and newly formed groundwater. During January 2005 - December 2012, a total of 85 cumulative monthly rainfall samples and 68 shallow groundwater samples were collected and the isotopic composition of oxygen and hydrogen was recorded for all those samples. Tritium values are available for 79 precipitation and 65 groundwater samples. Based on the 8-year monitoring, the long-term weighted annual mean isotope values of precipitation and the mean values of shallow groundwater are -11.59 per mille and -11.27 per mille for δ 18 O, - 82.3 per mille and -80.3 per mille for δ 2 H and 9.8 and 9.1 TU for tritium, respectively. Based on these data, the mean stable isotope ratios of groundwater represent the long-term mean annual isotopic composition of local precipitation. The precipitation data were used to establish the local meteoric water line (LMWL) for the Olkiluoto area. The line is formulated as: δ 2 H = 7.45 star δ 18 O + 3.82. The isotope time series reveal a change in time. The increasing trend for the δ 18 O and δ 2 H values may be related to climatic variability while the gradual decline observed in the 3 H data is attributed to the still continuing decrease in atmospheric 3 H activity in the northern hemisphere. The systematic seasonal and long-term tritium trends suggest that any potential ground-level tritium release from the Olkiluoto nuclear power plants is insignificant. The d-excess values of Olkiluoto precipitation during the summer period indicated that a notable amount of re-cycled Baltic Sea water may have contributed to precipitation in the Finnish southern coast. Preliminary estimates of the evaporated Baltic Sea water

  13. Understanding the Role of Reservoir Size on Probable Maximum Precipitation

    Science.gov (United States)

    Woldemichael, A. T.; Hossain, F.

    2011-12-01

    This study addresses the question 'Does surface area of an artificial reservoir matter in the estimation of probable maximum precipitation (PMP) for an impounded basin?' The motivation of the study was based on the notion that the stationarity assumption that is implicit in the PMP for dam design can be undermined in the post-dam era due to an enhancement of extreme precipitation patterns by an artificial reservoir. In addition, the study lays the foundation for use of regional atmospheric models as one way to perform life cycle assessment for planned or existing dams to formulate best management practices. The American River Watershed (ARW) with the Folsom dam at the confluence of the American River was selected as the study region and the Dec-Jan 1996-97 storm event was selected for the study period. The numerical atmospheric model used for the study was the Regional Atmospheric Modeling System (RAMS). First, the numerical modeling system, RAMS, was calibrated and validated with selected station and spatially interpolated precipitation data. Best combinations of parameterization schemes in RAMS were accordingly selected. Second, to mimic the standard method of PMP estimation by moisture maximization technique, relative humidity terms in the model were raised to 100% from ground up to the 500mb level. The obtained model-based maximum 72-hr precipitation values were named extreme precipitation (EP) as a distinction from the PMPs obtained by the standard methods. Third, six hypothetical reservoir size scenarios ranging from no-dam (all-dry) to the reservoir submerging half of basin were established to test the influence of reservoir size variation on EP. For the case of the ARW, our study clearly demonstrated that the assumption of stationarity that is implicit the traditional estimation of PMP can be rendered invalid to a large part due to the very presence of the artificial reservoir. Cloud tracking procedures performed on the basin also give indication of the

  14. Stable isotopic characteristic of Taiwan's precipitation: A case study of western Pacific monsoon region

    Science.gov (United States)

    Peng, Tsung-Ren; Wang, Chung-Ho; Huang, Chi-Chao; Fei, Li-Yuan; Chen, Chen-Tung Arthur; Hwong, Jeen-Lian

    2010-01-01

    The stable oxygen and hydrogen isotopic features of precipitation in Taiwan, an island located at the western Pacific monsoon area, are presented from nearly 3,500 samples collected during the past decade for 20 stations. Results demonstrate that moisture sources from diverse air masses with different isotopic signals are the main parameter in controlling the precipitation's isotope characteristics. The air mass from polar continental (Pc) region contributes the precipitation with high deuterium excess values (up to 23‰) and relatively enriched isotope compositions (e.g., - 3.2‰ for δ 18O) during the winter with prevailing northeasterly monsoon. By contrast, air masses from equatorial maritime (Em) and tropical maritime (Tm) supply the precipitation with low deuterium excess values (as low as about 7‰) and more depleted isotope values (e.g., - 8.9‰ and - 6.0‰ for δ 18O of Tm and Em, respectively) during the summer with prevailing southwesterly monsoon. Thus seasonal differences in terms of δ 18O, δD, and deuterium excess values are primarily influenced by the interactions among various precipitation sources. While these various air masses travel through Taiwan, secondary evaporation effects further modify the isotope characteristics of the inland precipitation, such as raindrop evaporation (reduces the deuterium excess of winter precipitation) and moisture recycling (increases the deuterium excess of summer precipitation). The semi-quantitative estimations in terms of evaluation for changes in the deuterium excess suggest that the raindrop evaporation fractions for winter precipitation range 7% to 15% and the proportions of recycling moisture in summer precipitation are less than 5%. Additionally, the isotopic altitude gradient in terms of δ 18O for summer precipitation is - 0.22‰/100 m, greater than - 0.17‰/100 m of winter precipitation. The greater isotopic gradient in summer can be attributed to a higher temperature vs. altitude gradient

  15. PRECIPITATION OF PROTACTINIUM

    Science.gov (United States)

    Moore, R.L.

    1958-07-15

    An lmprovement in the separation of protactinium from aqueous nitric acid solutions is described. 1t covers the use of lead dioxide and tin dioxide as carrier precipitates for the protactinium. In carrying out the process, divalent lead or divalent tin is addcd to the solution and oxidized, causing formation of a carrier precipitate of lead dioxide or stannic oxide, respectively.

  16. Global Precipitation Measurement Poster

    Science.gov (United States)

    Azarbarzin, Art

    2010-01-01

    This poster presents an overview of the Global