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1

The ENSEMBLES Statistical Downscaling Portal  

NASA Astrophysics Data System (ADS)

The demand for high-resolution seasonal and ACC predictions is continuously increasing due to the multiple end-user applications in a variety of sectors (hydrology, agronomy, energy, etc.) which require regional meteorological inputs. To fill the gap between the coarse-resolution grids used by global weather models and the regional needs of applications, a number of statistical downscaling techniques have been proposed. Statistical downscaling is a complex multi-disciplinary problem which requires a cascade of different scientific tools to access and process different sources of data, from GCM outputs to local observations and to run complex statistical algorithms. Thus, an end-to-end approach is needed in order to link the outputs of the ensemble prediction systems to a range of impact applications. To accomplish this task in an interactive and user-friendly form, a Web portal has been developed within the European ENSEMBLES project, integrating the necessary tools and providing the appropriate technology for distributed data access and computing. In this form, users can obtain their downscaled data testing and validating different statistical methods (from the categories weather typing, regression or weather generators) in a transparent form, not worrying about the details of the downscaling techniques and the data formats and access.

Cofino, Antonio S.; San-Martín, Daniel; Gutiérrez, Jose M.

2010-05-01

2

Hydro-meteorological evaluation of downscaled global ensemble rainfall forecasts  

NASA Astrophysics Data System (ADS)

Ensemble rainfall forecasts are of high interest for decision making, as they provide an explicit and dynamic assessment of the uncertainty in the forecast (Ruiz et al. 2009). However, for hydrological forecasting, their low resolution currently limits their use to large watersheds (Maraun et al. 2010). In order to bridge this gap, various implementations of the statistic-stochastic multi-fractal downscaling technique presented by Perica and Foufoula-Georgiou (1996) were compared, bringing Environment Canada's global ensemble rainfall forecasts from a 100 by 70-km resolution down to 6 by 4-km, while increasing each pixel's rainfall variance and preserving its original mean. For comparison purposes, simpler methods were also implemented such as the bi-linear interpolation, which disaggregates global forecasts without modifying their variance. The downscaled meteorological products were evaluated using different scores and diagrams, from both a meteorological and a hydrological view points. The meteorological evaluation was conducted comparing the forecasted rainfall depths against nine days of observed values taken from Québec City rain gauge database. These 9 days present strong precipitation events occurring during the summer of 2009. For the hydrologic evaluation, the hydrological models SWMM5 and (a modified version of) GR4J were implemented on a small 6 km2 urban catchment located in the Québec City region. Ensemble hydrologic forecasts with a time step of 3 hours were then performed over a 3-months period of the summer of 2010 using the original and downscaled ensemble rainfall forecasts. The most important conclusions of this work are that the overall quality of the forecasts was preserved during the disaggregation procedure and that the disaggregated products using this variance-enhancing method were of similar quality than bi-linear interpolation products. However, variance and dispersion of the different members were, of course, much improved for the variance-enhanced products, compared to the bi-linear interpolation, which is a decisive advantage. The disaggregation technique of Perica and Foufoula-Georgiou (1996) hence represents an interesting way of bridging the gap between the meteorological models' resolution and the high degree of spatial precision sometimes required by hydrological models in their precipitation representation. References Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and Thiele-Eich, I. 2010. Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Reviews of Geophysics, 48 (3): RG3003, [np]. Doi: 10.1029/2009RG000314. Perica, S., and Foufoula-Georgiou, E. 1996. Model for multiscale disaggregation of spatial rainfall based on coupling meteorological and scaling descriptions. Journal Of Geophysical Research, 101(D21): 26347-26361. Ruiz, J., Saulo, C. and Kalnay, E. 2009. Comparison of Methods Used to Generate Probabilistic Quantitative Precipitation Forecasts over South America. Weather and forecasting, 24: 319-336. DOI: 10.1175/2008WAF2007098.1 This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.

Gaborit, Étienne; Anctil, François; Fortin, Vincent; Pelletier, Geneviève

2013-04-01

3

Downscaling a perturbed physics ensemble over the CORDEX Africa domain  

NASA Astrophysics Data System (ADS)

We present here the methodology and the results of 5-member ensemble simulation of the climate of Africa for the period 1950-2100 using climate modelling system PRECIS over the CORDEX Africa domain. The boundary conditions for the regional model simulations were selected from a 17-member perturbed physics ensemble based on the HadCM3 global climate model (Murphy et al. 2007) following the methodology described in McSweeney et al 2012. Such an approach was selected in order to provide a good representation of the overall ensemble spread over a number of sub regions while at the same time avoiding members which have demonstrate particularly unrealistic characteristics in their baseline climate. In the simulations a special attention was given to the representation of some inland water bodies, such as lake Victoria, whose impact on the regional climate was believed to be significant thus allowing for the representation of some regional processes (e.g. land-lake breezes) that were not represented in the global models. In particular the SSTs of the lakes were corrected to better represent the local climatological values. The results suggest that RCM simulations improve the fit to observations of precipitation and temperature in most of the African sub-regions (e.g. North Africa, West Sahel). Also, the range of RCM projections is often different to those from the GCMs in these regions. We discuss the reasons for and links between these results and their implications for use in informing adaptation policy at regional level.

Buontempo, Carlo; Williams, Karina; McSweeney, Carol; Jones, Richard; Mathison, Camilla; Wang, Chang

2014-05-01

4

Dynamical downscaling of snow trends in Nothern Iberia based on ENSEMBLES regional simulations  

NASA Astrophysics Data System (ADS)

A recent study reported a significant decreasing trend of snow occurrence (-4.6 days/decade) in the Northern Iberian Peninsula since the mid seventies (Pons et al. 2009). This study was based on observations of annual snow frequency (measured as the annual number of snow days) from a network of 33 stations ranging from 60 to 1350 meters. In the present work we analyze the skill of dynamical downscaling methods to reproduce this trend in present climate conditions and also to further project it into the future from A1B-scenario global simulations. In particular, we consider the regional simulation dataset from the ENSEMBLES project, consisting in ten state-of-the-art Regional Climate Models (RCMs) at 25km resolution run with different forcing/boundary conditions. To this aim we first test the regional models with perfect boundaries considering ERA40; it is shown that after correcting the bias, all the RCMs appropriately reproduce the interannual variability and the observed trends (e.g., the ensemble mean presents a trend of -5.8 days/decade). Then we analyze the results for the present climate 20c3m-scenario global simulations. In this case, the results are quite variable with the larger uncertainty being associated with the particular GCM used (ECHAM5, CNRM or HadCM) with trend ranging from -6.7 to -1.8 days/decade. Finally, the trends obtained for the future 2010-2040 A1B runs ranged from -5.7 to -1.4 days/decade, indicating a continuous decreasing of snow frequency in this region. References: Pons, M.R., D. San-Martín, S. Herrera and J.M. Gutiérrez (2009), Snow Trends in Northern Spain. Analysis and simulation with statistical downscaling methods, International Journal of Climatology, DOI. 10.1002/joc.2016A recent study reported a significant decreasing trend of snow occurrence (-4.6 days/decade) in the Northern Iberian Peninsula since the mid seventies (Pons et al. 2009). This study was based on observations of annual snow frequency (measured as the annual number of snow days) from a network of 33 stations ranging from 60 to 1350 meters. In the present work we analyze the skill of dynamical downscaling methods to reproduce this trend in present climate conditions and also to further project it into the future from A1B-scenario global simulations. In particular, we consider the regional simulation dataset from the ENSEMBLES project, consisting in ten state-of-the-art Regional Climate Models (RCMs) at 25km resolution run with different forcing/boundary conditions. To this aim we first test the regional models with perfect boundaries considering ERA40; it is shown that after correcting the bias, all the RCMs appropriately reproduce the interannual variability and the observed trends (e.g., the ensemble mean presents a trend of -5.8 days/decade). Then we analyze the results for the present climate 20c3m-scenario global simulations. In this case, the results are quite variable with the larger uncertainty being associated with the particular GCM used (ECHAM5, CNRM or HadCM) with trends ranging from -6.7 to -1.8 days/decade. Finally, the trends obtained for the future 2010-2040 A1B runs range from -5.7 to -1.4 days/decade, indicating a continuous decrease of snow frequency in this region. References: Pons, M.R., D. San-Martín, S. Herrera and J.M. Gutiérrez (2009), Snow Trends in Northern Spain. Analysis and simulation with statistical downscaling methods, International Journal of Climatology, DOI. 10.1002/joc.2016

Herrera, S.; Pons, M. R.; Sordo, C. M.; Gutiérrez, J. M.

2010-05-01

5

Dynamical downscaling of the ERA-40 reanalysis and ARPEGE GCM with the WRF regional climate model in complex terrain in Norway - comparison with ENSEMBLES  

NASA Astrophysics Data System (ADS)

We present a supplement to the recently finished EU-project ENSEMBLES project employing the WRF regional climate model (www.wrf-model.org). Results are presented from a dynamical downscaling of the ERA-40 reanalysis to 30 km and 10 km resolution as well as the ARPEGE global model simulations in Europe for the 30-year period from 1961 to 1990. In addition some preliminary results from a WRF downscaling of the ARPEGE R1b future prediction (2020-2050) will be shown. A relatively weak spectral nudging is used in all experiments. The model evaluation focuses on complex terrain in Norway. The results are evaluated against daily mean observations of precipitation, 2-meter temperature and 10-meter wind speed for the 30-year period. We find that the WRF downscaling of the ERA-40 reanalysis is reproducing the distributions of the observed daily mean parameters reasonably well. Also the frequency of wet days as well as the occurrence of extreme events are improved in the downscaled data set. A significant improvement of the extreme events as well as the distributions is found when the horizontal resolution is further refined from 30 km to 10 km. The spectral nudging procedure is not found to suppress the extreme events but to significantly improve the phase of precipitation. Model intercomparison with some of the regional model runs of the ENSEMBLES project reveals that the WRF downscaling ranks high within the individual models. The ENSEMBLES mean is producing the best results in most cases.

Heikkilä, U.; Sandvik, A. D.; Sorteberg, A.

2010-09-01

6

Simulation of SEU Cross-sections using MRED under Conditions of Limited Device Information  

NASA Technical Reports Server (NTRS)

This viewgraph presentation reviews the simulation of Single Event Upset (SEU) cross sections using the membrane electrode assembly (MEA) resistance and electrode diffusion (MRED) tool using "Best guess" assumptions about the process and geometry, and direct ionization, low-energy beam test results. This work will also simulate SEU cross-sections including angular and high energy responses and compare the simulated results with beam test data for the validation of the model. Using MRED, we produced a reasonably accurate upset response model of a low-critical charge SRAM without detailed information about the circuit, device geometry, or fabrication process

Lauenstein, J. M.; Reed, R. A.; Weller, R. A.; Mendenhall, M. H.; Warren, K. M.; Pellish, J. A.; Schrimpf, R. D.; Sierawski, B. D.; Massengill, L. W.; Dodd, P. E.; Shaneyfelt, M. R.; Felix, J. A.; Schwank, J. R.

2007-01-01

7

Ensemble  

NSDL National Science Digital Library

Ensemble is a new NSF NSDL Pathways project working to establish a national, distributed digital library for computing education. Our project is building a distributed portal providing access to a broad range of existing educational resources for computing while preserving the collections and their associated curation processes. We want to encourage contribution, use, reuse, review and evaluation of educational materials at multiple levels of granularity and we seek to support the full range of computing education communities including computer science, computer engineering, software engineering, information science, information systems and information technology as well as other areas often called "computing + X" or 'X informatics."

8

New statistical downscaling for Canada  

NASA Astrophysics Data System (ADS)

This poster will document the production of a set of statistically downscaled future climate projections for Canada based on the latest available RCM and GCM simulations - the North American Regional Climate Change Assessment Program (NARCCAP; Mearns et al. 2007) and the Coupled Model Intercomparison Project Phase 5 (CMIP5). The main stages of the project included (1) downscaling method evaluation, (2) scenarios selection, (3) production of statistically downscaled results, and (4) applications of results. We build upon a previous downscaling evaluation project (Bürger et al. 2012, Bürger et al. 2013) in which a quantile-based method (Bias Correction/Spatial Disaggregation - BCSD; Werner 2011) provided high skill compared with four other methods representing the majority of types of downscaling used in Canada. Additional quantile-based methods (Bias-Correction/Constructed Analogues; Maurer et al. 2010 and Bias-Correction/Climate Imprint ; Hunter and Meentemeyer 2005) were evaluated. A subset of 12 CMIP5 simulations was chosen based on an objective set of selection criteria. This included hemispheric skill assessment based on the CLIMDEX indices (Sillmann et al. 2013), historical criteria used previously at the Pacific Climate Impacts Consortium (Werner 2011), and refinement based on a modified clustering algorithm (Houle et al. 2012; Katsavounidis et al. 1994). Statistical downscaling was carried out on the NARCCAP ensemble and a subset of the CMIP5 ensemble. We produced downscaled scenarios over Canada at a daily time resolution and 300 arc second (~10 km) spatial resolution from historical runs for 1951-2005 and from RCP 2.6, 4.5, and 8.5 projections for 2006-2100. The ANUSPLIN gridded daily dataset (McKenney et al. 2011) was used as a target. It has national coverage, spans the historical period of interest 1951-2005, and has daily time resolution. It uses interpolation of station data based on thin-plate splines. This type of method has been shown to have superior skill in interpolating RCM data over North America (McGinnis et al. 2012). An early application of the new dataset was to provide projections of climate extremes for adaptation planning by the British Columbia Ministry of Transportation and Infrastructure. Recently, certain stretches of highway have experienced extreme precipitation events resulting in substantial damage to infrastructure. As part of the planning process to refurbish or replace components of these highways, information about the magnitude and frequency of future extreme events are needed to inform the infrastructure design. The increased resolution provided by downscaling improves the representation of topographic features, particularly valley temperature and precipitation effects. A range of extreme values, from simple daily maxima and minima to complex multi-day and threshold-based climate indices were computed and analyzed from the downscaled output. Selected results from this process and how the projections of precipitation extremes are being used in the context of highway infrastructure planning in British Columbia will be presented.

Murdock, T. Q.; Cannon, A. J.; Sobie, S.

2013-12-01

9

Downscaling of NWP Data  

NSDL National Science Digital Library

Forecasters utilize downscaled NWP products when producing forecasts of predictable features, such as terrain-related and coastal features, at finer resolution than provided by most NWP models directly. This module is designed to help the forecaster determine which downscaled products are most appropriate for a given forecast situation and the types of further corrections the forecaster will have to create. This module engages the learner through interactive case examples illustrating and comparing the major capabilities and limitations of some commonly-used downscaled products for 2-m temperatures and 10-m winds. Products covered include Gridded MOS, PRISM, NCEP downscaling for NAM and for NAEFS, downscaling in the AWIPS Graphical Forecast Editor, and the use of high-resolution models to perform downscaling.

Comet

2010-11-09

10

A review on regional dynamical downscaling in intraseasonal to seasonal simulation/prediction and major factors that affect downscaling ability  

NASA Astrophysics Data System (ADS)

Regional climate models (RCMs) have been developed and extensively applied for dynamically downscaling coarse resolution information from different sources, such as general circulation models (GCMs) and reanalyses, for different purposes including past climate simulations and future climate projection. Thus far, the nature, the methods, and a number of crucial issues concerning the use of dynamic downscaling are still not well understood. The most important issue is whether, and if so, under what conditions dynamic downscaling is really capable of adding more information at different scales compared to the GCM or reanalysis that imposes lateral boundary conditions (LBCs) to the RCMs. There are controversies regarding the downscaling ability. In this review paper we present several factors that have consistently demonstrated strong impact on dynamic downscaling ability in intraseasonal and seasonal simulations/predictions and future projection. Those factors include setting of the RCM experiment (e.g. imposed LBC quality, domain size and position, LBC coupling, and horizontal resolution); as well as physical processes, mainly convective schemes and vegetation and soil processes that include initializations, vegetation specifications, and planetary boundary layer and surface coupling. These studies indicate that RCMs have downscaling ability in some aspects but only under certain conditions. Any significant weaknesses in one of these aspects would cause an RCM to lose its dynamic downscaling ability. This paper also briefly presents challenges faced in current RCM dynamic downscaling and future prospective, which cover the application of coupled ocean-atmosphere RCMs, ensemble applications, and future projections.

Xue, Yongkang; Janjic, Zavisa; Dudhia, Jimy; Vasic, Ratko; De Sales, Fernando

2014-10-01

11

Downscaling in remote sensing  

NASA Astrophysics Data System (ADS)

Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise.

Atkinson, Peter M.

2013-06-01

12

Multifractal models for space-time rainfall downscaling  

NASA Astrophysics Data System (ADS)

It is well know that rainfall fields display fluctuations in space and time that increase as the scale of observation decreases. Multifractal theory represents a solid base to characterize scale-invariance properties observed in rainfall fields as well as to develop downscaling models able to reproduce observed statistics. The availability of such downscaling tools allows forecasting of floods in small basins by coupling meteorological and hydrological models working on different space-time grid resolution. In this talk multifractal theory will be reviewed highlighting the most relevant aspects for rainfall downscaling (e.g., the concept of scale-invariance in rainfall fields displaying space-time self-similarity or self-affinity, the role of orography). The main results of the scale-invariance analysis of rainfall retrieved by remote sensors will be discussed. Finally the application of multifractal models for rainfall downscaling will be presented and some new ideas for ensemble verification will be argued.

Deidda, Roberto

2013-04-01

13

An application of hybrid downscaling model to forecast summer precipitation at stations in China  

NASA Astrophysics Data System (ADS)

A pattern prediction hybrid downscaling method was applied to predict summer (June-July-August) precipitation at China 160 stations. The predicted precipitation from the downscaling scheme is available one month before. Four predictors were chosen to establish the hybrid downscaling scheme. The 500-hPa geopotential height (GH5) and 850-hPa specific humidity (q85) were from the skillful predicted output of three DEMETER (Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction) general circulation models (GCMs). The 700-hPa geopotential height (GH7) and sea level pressure (SLP) were from reanalysis datasets. The hybrid downscaling scheme (HD-4P) has better prediction skill than a conventional statistical downscaling model (SD-2P) which contains two predictors derived from the output of GCMs, although two downscaling schemes were performed to improve the seasonal prediction of summer rainfall in comparison with the original output of the DEMETER GCMs. In particular, HD-4P downscaling predictions showed lower root mean square errors than those based on the SD-2P model. Furthermore, the HD-4P downscaling model reproduced the China summer precipitation anomaly centers more accurately than the scenario of the SD-2P model in 1998. A hybrid downscaling prediction should be effective to improve the prediction skill of summer rainfall at stations in China.

Liu, Ying; Fan, Ke

2014-06-01

14

Downscaling of inundation extents  

NASA Astrophysics Data System (ADS)

The Global Inundation Extent from Multi-Satellite (GIEMS) provides multi-year monthly variations of the global surface water extent at about 25 kmx25 km resolution, from 1993 to 2007. It is derived from multiple satellite observations. Its spatial resolution is usually compatible with climate model outputs and with global land surface model grids but is clearly not adequate for local applications that require the characterization of small individual water bodies. There is today a strong demand for high-resolution inundation extent datasets, for a large variety of applications such as water management, regional hydrological modeling, or for the analysis of mosquitos-related diseases. This paper present three approaches to do downscale GIEMS: The first one is based on a image-processing technique using neighborhood constraints. The third approach uses a PCA representation to perform an algebraic inversion. The PCA-representation is also very convenient to perform temporal and spatial interpolation of complexe inundation fields. The third downscaling method uses topography information from Hydroshed Digital Elevation Model (DEM). Information such as the elevation, distance to river and flow accumulation are used to define a ``flood ability index'' that is used by the downscaling. Three basins will be considered for illustrative purposes: Amazon, Niger and Mekong. Aires, F., F. Papa, C. Prigent, J.-F. Cretaux and M. Berge-Nguyen, Characterization and downscaling of the inundation extent over the Inner Niger delta using a multi-wavelength retrievals and Modis data, J. of Hydrometeorology, in press, 2014. Aires, F., F. Papa and C. Prigent, A long-term, high-resolution wetland dataset over the Amazon basin, downscaled from a multi-wavelength retrieval using SAR, J. of Hydrometeorology, 14, 594-6007, 2013. Prigent, C., F. Papa, F. Aires, C. Jimenez, W.B. Rossow, and E. Matthews. Changes in land surface water dynamics since the 1990s and relation to population pressure. Geophys. Res. Lett., 39(L08403), 2012.

Aires, Filipe; Prigent, Catherine; Papa, Fabrice

2014-05-01

15

Climate variability and projected change in the western United States: regional downscaling and drought statistics  

Microsoft Academic Search

Climate change in the twenty-first century, projected by a large ensemble average of global coupled models forced by a mid-range\\u000a (A1B) radiative forcing scenario, is downscaled to Climate Divisions across the western United States. A simple empirical\\u000a downscaling technique is employed, involving model-projected linear trends in temperature or precipitation superimposed onto\\u000a a repetition of observed twentieth century interannual variability. This

David S. GutzlerTessia; Tessia O. Robbins

16

Correlation of Tc-99m-red blood cell phleboscintigraphy with clinical severity of chronic venous disease.  

PubMed

Equilibrium red blood cell phleboscintigraphy of the lower limbs for the diagnostic management of chronic venous disease has been proposed. The aim of this study was to verify the correlation of the phleboscintigraphic assessment of chronic venous disease with the clinical grading of the severity of the disease, since other diagnostic modalities have been recently demonstrated a poor and only partial correlation. Equilibrium Tc-99m-red blood cell phleboscintigraphy was performed in 27 patients with chronic venous disease. Scintigraphic images of 52 limbs were classified according to a four-class qualitative grading of the severity of the venous disease, and a quantitative scintigraphic index (saphena /femoral ratio) was assigned to each limb. The scintigraphic qualitative grading showed a highly significant correlation with the clinical grading (Rs=0.82, p<0.01), a good interobserver and intraobserver agreement (86.5% and 92.3%, respectively) and more than 90% sensitivity and specificity to identify the categories "minimal or no chronic venous disease" or "more significant disease" (assessed according to the Bayes theorem). Sensitivity and specificity results for the quantitative assessment were not as good. Phleboscintigraphy correlates well with the clinical grading of the severity of chronic venous disease of the lower limbs and may have potential as a valuable diagnostic tool for the noninvasive assessment of chronic venous disease. PMID:11586453

Giordano, A; Calcagni, M L; Rulli, F; Muzi, M; Martino, G; D'Andrea, G; Galli, M; Zanella, E

2001-01-01

17

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe  

NASA Astrophysics Data System (ADS)

Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods often used in climate change impact studies. Four methods are based on change factors, three are bias correction methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from fifteen regional climate models (RCMs) from the ENSEMBLES project for eleven catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the statistical downscaling methods vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between change factor and bias correction methods. The performance of the bias correction methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and statistical downscaling methods indicates that up to half of the total variance is derived from the statistical downscaling methods. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need of considering an ensemble of both statistical downscaling methods and climate models.

Sunyer, M. A.; Hundecha, Y.; Lawrence, D.; Madsen, H.; Willems, P.; Martinkova, M.; Vormoor, K.; Bürger, G.; Hanel, M.; Kriau?i?nien?, J.; Loukas, A.; Osuch, M.; Yücel, I.

2014-06-01

18

Downscaling precipitation extremes in a complex Alpine catchment  

NASA Astrophysics Data System (ADS)

Climate change is expected to have significant effects on the frequency and intensity of heavy precipitation events. Assessing the impacts of climate change on precipitation extremes is a challenging task. On the one hand, the output of Regional Climate Models (RCMs) is subjected to systematic biases in the case of precipitation, especially in a complex mountain topography, and on the other hand, yet only a few statistical downscaling techniques are known to downscale precipitation extremes reliably. In this investigation two statistical downscaling approaches were applied to simulate precipitation extremes in the Alpine part of the Lech catchment. The first one, Expanded Downscaling (EDS), is a perfect prognosis approach that is based on regression. EDS has been calibrated and validated using large-scale predictor variables derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset and local station data. The EDS model was then applied to downscale the output of two GCMs (ECHAM5, HadGEM2) for current (1971-2000) and future (2071-2100) time horizons, forced with the SRES A1B emission scenario. The second approach is the Long Ashton Research Station Weather Generator (LARS-WG) which can be characterized as a change factor conditioned weather generator. LARS-WG was calibrated on local station data only and then applied to downscale the output of five different GCM-RCM combinations to meteorological stations. The RCMs have a horizontal resolution of ~25 km and were obtained from the ENSEMBLES project of the European Union. In order to assess precipitation extremes with higher return values, a generalized extreme value distribution was applied to the data. Confidence intervals were calculated by using the non-parametric bootstrapping technique. The results show that both downscaling approaches reproduce observed precipitation extremes fairly well. Even for very extreme precipitation events such as the 20-year event a good agreement between observation and simulation is obtained. When studying the effects of climate change on precipitation extremes, a wide range of results with both projected increases and decreases in precipitation extremes can be found. However, the number of climate simulations which indicates statistically significant increases is by far larger than that showing decreases. Very robust signals can be found for spring and autumn, in which almost all climate scenarios indicate increases in the intensity of precipitation extremes.

Dobler, C.

2012-04-01

19

Ensembl 2009  

Microsoft Academic Search

The Ensembl project (http:\\/\\/www.ensembl.org) is a comprehensive genome information system fea- turing an integrated set of genome annotation, data- bases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have pre- liminary support. New species in the past year include orangutan and

Tim J. P. Hubbard; B. L. Aken; Sarah C. Ayling; Benoit Ballester; Kathryn Beal; E. Bragin; S. Brent; Yuan Chen; P. Clapham; Laura Clarke; G. Coates; S. Fairley; S. Fitzgerald; J. Fernandez-banet; L. Gordon; Stefan Gräf; Syed Haider; Martin Hammond; Richard C. G. Holland; Kevin L. Howe; Andrew M. Jenkinson; N. Johnson; Andreas Kähäri; Damian Keefe; S. Keenan; R. Kinsella; Felix Kokocinski; Eugene Kulesha; Daniel Lawson; I. Longden; Karine Megy; Patrick Meidl; B. Overduin; A. Parker; B. Pritchard; D. Rios; M. Schuster; Guy Slater; Damian Smedley; William Spooner; G. Spudich; S. Trevanion; Albert J. Vilella; J. Vogel; S. White; S. Wilder; Arek Zadissa; Ewan Birney; Fiona Cunningham; Val Curwen; Richard Durbin; X. M. Fernandez-suarez; Javier Herrero; Arek Kasprzyk; Glenn Proctor; James Smith; Stephen M. J. Searle; Paul Flicek

2009-01-01

20

Statistical downscaling of river flows  

NASA Astrophysics Data System (ADS)

SummaryAn extensive statistical 'downscaling' study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily 'integrated approach'. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

Tisseuil, Clement; Vrac, Mathieu; Lek, Sovan; Wade, Andrew J.

2010-05-01

21

Evaluating Downscaling Methods for Seasonal Climate Forecasts over East Africa  

NASA Astrophysics Data System (ADS)

The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in impact modeling within hub regions including East Africa, the Hindu Kush-Himalayan (HKH) region and Mesoamerica. One of the participating models in NMME is the NASA Goddard Earth Observing System (GEOS5). This work will present an intercomparison of downscaling methods using the GEOS5 seasonal forecasts of temperature and precipitation over East Africa. The current seasonal forecasting system provides monthly averaged forecast anomalies. These anomalies must be spatially downscaled and temporally disaggregated for use in application modeling (e.g. hydrology, agriculture). There are several available downscaling methodologies that can be implemented to accomplish this goal. Selected methods include both a non-homogenous hidden Markov model and an analogue based approach. A particular emphasis will be placed on quantifying the ability of different methods to capture the intermittency of precipitation within both the short and long rain seasons. Further, the ability to capture spatial covariances will be assessed. Both probabilistic and deterministic skill measures will be evaluated over the hindcast period.

Roberts, J. B.; Robertson, F. R.; Bosilovich, M. G.; Lyon, B.

2013-12-01

22

A combined statistical and dynamical approach for downscaling large-scale footprints of European windstorms  

NASA Astrophysics Data System (ADS)

The occurrence of mid-latitude windstorms is related to strong socio-economic effects. For detailed and reliable regional impact studies, large datasets of high-resolution wind fields are required. In this study, a statistical downscaling approach in combination with dynamical downscaling is introduced to derive storm related gust speeds on a high-resolution grid over Europe. Multiple linear regression models are trained using reanalysis data and wind gusts from regional climate model simulations for a sample of 100 top ranking windstorm events. The method is computationally inexpensive and reproduces individual windstorm footprints adequately. Compared to observations, the results for Germany are at least as good as pure dynamical downscaling. This new tool can be easily applied to large ensembles of general circulation model simulations and thus contribute to a better understanding of the regional impact of windstorms based on decadal and climate change projections.

Haas, Rabea; Pinto, Joaquim G.

2013-04-01

23

A combined statistical and dynamical approach for downscaling large-scale footprints of European windstorms  

NASA Astrophysics Data System (ADS)

The occurrence of mid-latitude windstorms is related to strong socio-economic effects. For detailed and reliable regional impact studies, large datasets of high-resolution wind fields are required. In this study, a statistical downscaling approach in combination with dynamical downscaling is introduced to derive storm related gust speeds on a high-resolution grid over Europe. Multiple linear regression models are trained using reanalysis data and wind gusts from regional climate model simulations for a sample of 100 top ranking windstorm events. The method is computationally inexpensive and reproduces individual windstorm footprints adequately. Compared to observations, the results for Germany are at least as good as pure dynamical downscaling. This new tool can be easily applied to large ensembles of general circulation model simulations and thus contribute to a better understanding of the regional impact of windstorms based on decadal and climate change projections.

Haas, R.; Pinto, J. G.

2012-12-01

24

Ensembl 2013  

PubMed Central

The Ensembl project (http://www.ensembl.org) provides genome information for sequenced chordate genomes with a particular focus on human, mouse, zebrafish and rat. Our resources include evidenced-based gene sets for all supported species; large-scale whole genome multiple species alignments across vertebrates and clade-specific alignments for eutherian mammals, primates, birds and fish; variation data resources for 17 species and regulation annotations based on ENCODE and other data sets. Ensembl data are accessible through the genome browser at http://www.ensembl.org and through other tools and programmatic interfaces. PMID:23203987

Flicek, Paul; Ahmed, Ikhlak; Amode, M. Ridwan; Barrell, Daniel; Beal, Kathryn; Brent, Simon; Carvalho-Silva, Denise; Clapham, Peter; Coates, Guy; Fairley, Susan; Fitzgerald, Stephen; Gil, Laurent; García-Girón, Carlos; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah; Juettemann, Thomas; Kähäri, Andreas K.; Keenan, Stephen; Komorowska, Monika; Kulesha, Eugene; Longden, Ian; Maurel, Thomas; McLaren, William M.; Muffato, Matthieu; Nag, Rishi; Overduin, Bert; Pignatelli, Miguel; Pritchard, Bethan; Pritchard, Emily; Riat, Harpreet Singh; Ritchie, Graham R. S.; Ruffier, Magali; Schuster, Michael; Sheppard, Daniel; Sobral, Daniel; Taylor, Kieron; Thormann, Anja; Trevanion, Stephen; White, Simon; Wilder, Steven P.; Aken, Bronwen L.; Birney, Ewan; Cunningham, Fiona; Dunham, Ian; Harrow, Jennifer; Herrero, Javier; Hubbard, Tim J. P.; Johnson, Nathan; Kinsella, Rhoda; Parker, Anne; Spudich, Giulietta; Yates, Andy; Zadissa, Amonida; Searle, Stephen M. J.

2013-01-01

25

An ensemble climate projection for Africa  

NASA Astrophysics Data System (ADS)

The Met Office Hadley Centre's PRECIS regional climate modelling system has been used to generate a five member ensemble of climate projections for Africa over the 50 km resolution Coordinated Regional climate Downscaling Experiment-Africa domain. The ensemble comprises the downscaling of a subset of the Hadley Centre's perturbed physics global climate model (GCM) ensemble chosen to exclude ensemble members unable to represent the African climate realistically and then to capture the spread in outcomes from the projections of the remaining models. The PRECIS simulations were run from December 1949 to December 2100. The regional climate model (RCM) ensemble captures the annual cycle of temperatures well both for Africa as a whole and the sub-regions. It slightly overestimates precipitation over Africa as a whole and captures the annual cycle of rainfall for most of the African regions. The RCM ensemble substantially improve the patterns and magnitude of precipitation simulation compared to their driving GCM which is particularly noticeable in the Sahel for both the magnitude and timing of the wet season. Present-day simulations of the RCM ensemble are more similar to each other than those of the driving GCM ensemble which indicates that their climatologies are influenced significantly by the RCM formulation and less so by their driving GCMs. Consistent with this, the spread and magnitudes of the large-scale responses of the RCMs are often different than the driving GCMs and arguably more credible given the improved performance of the RCM. This also suggests that local climate forcing will be a significant driver of the regional response to climate change over Africa.

Buontempo, Carlo; Mathison, Camilla; Jones, Richard; Williams, Karina; Wang, Changgui; McSweeney, Carol

2014-09-01

26

Ensembl 2009  

PubMed Central

The Ensembl project (http://www.ensembl.org) is a comprehensive genome information system featuring an integrated set of genome annotation, databases, and other information for chordate, selected model organism and disease vector genomes. As of release 51 (November 2008), Ensembl fully supports 45 species, and three additional species have preliminary support. New species in the past year include orangutan and six additional low coverage mammalian genomes. Major additions and improvements to Ensembl since our previous report include a major redesign of our website; generation of multiple genome alignments and ancestral sequences using the new Enredo-Pecan-Ortheus pipeline and development of our software infrastructure, particularly to support the Ensembl Genomes project (http://www.ensemblgenomes.org/). PMID:19033362

Hubbard, T. J. P.; Aken, B. L.; Ayling, S.; Ballester, B.; Beal, K.; Bragin, E.; Brent, S.; Chen, Y.; Clapham, P.; Clarke, L.; Coates, G.; Fairley, S.; Fitzgerald, S.; Fernandez-Banet, J.; Gordon, L.; Graf, S.; Haider, S.; Hammond, M.; Holland, R.; Howe, K.; Jenkinson, A.; Johnson, N.; Kahari, A.; Keefe, D.; Keenan, S.; Kinsella, R.; Kokocinski, F.; Kulesha, E.; Lawson, D.; Longden, I.; Megy, K.; Meidl, P.; Overduin, B.; Parker, A.; Pritchard, B.; Rios, D.; Schuster, M.; Slater, G.; Smedley, D.; Spooner, W.; Spudich, G.; Trevanion, S.; Vilella, A.; Vogel, J.; White, S.; Wilder, S.; Zadissa, A.; Birney, E.; Cunningham, F.; Curwen, V.; Durbin, R.; Fernandez-Suarez, X. M.; Herrero, J.; Kasprzyk, A.; Proctor, G.; Smith, J.; Searle, S.; Flicek, P.

2009-01-01

27

Stochastic Lagrangian Method for Downscaling Problems in Computational Fluid Dynamics  

E-print Network

Stochastic Lagrangian Method for Downscaling Problems in Computational Fluid Dynamics Fr downscaling technique applied to computational fluid dynamics. Our method consists in building a local model for the downscaling in Computational Fluid Dynamics (CFD). For numerous practical reasons (computational cost

Paris-Sud XI, Université de

28

A Stochastic Technique for Error Correction and Spatial Downscaling of Global Gridded Precipitation Products  

NASA Astrophysics Data System (ADS)

Deriving flood maps requires an accurate characterization of precipitation variability at high spatio-temporal resolution. Most of the available global-scale gridded precipitation products are available at resolutions (e.g., 25 km) not directly applicable to flood modeling. An error correction and spatial downscaling method based on a two-dimensional satellite rainfall error model (SREM2D) is tested in this study based on a long-term (2001-2010) dataset. Specifically, the model is applied on two rainfall datasets: a satellite precipitation product (TRMM-3B42.V7 at 0.25 degree) and a global land-atmosphere re-analysis product (GLDAS-CLM at 1 degree), to produce error corrected rainfall ensembles at 0.05 degree spatial resolution. The NCEP hourly, 4-km resolution multi-sensor precipitation product (WSR-88D stage IV gauge-adjusted radar-rainfall product) is used as the reference rainfall dataset. The Hillslope River Routing (HRR) hydrologic model is forced with the downscaled ensemble rainfall data to produce an ensemble of runoff values. The Susquehanna River basin is the study area, consisting of 1000 sub-basins ranging from 39 to 67,000 square kilometers including complex terrain and high latitude locations. There are 437 significant storm events selected over the study area based on the 10-year database. The analysis performed is based on 60 percent of events in each season kept for model calibration and 40 percent for validation. The statistical analysis consists of two parts: (1) evaluation of error metrics (relative standard deviation and efficiency coefficient) to quantify improvements in rainfall and runoff simulations as function of basin size and storm severity, and (2) ensemble verification (exceedance probability and mean uncertainty ratio) of the rainfall and runoff ensembles to assess the accuracy of the ensemble-based uncertainty characterization. The study investigates how well the ensemble of downscaled and error-corrected rainfall data performs relative to reference radar-rainfall data in terms of hydrologic simulations. The results will demonstrate the basin scale dependence of downscaled precipitation ensemble as well as the effect of seasonality on the method's performance.

Seyyedi, H.; Kaheil, Y.; Anagnostou, E. N.; McCollum, J.; Beighley, E.

2013-12-01

29

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications  

NASA Astrophysics Data System (ADS)

Deriving flood hazard maps for ungauged basins typically requires simulating a long record of annual maximum discharges. To improve this approach, precipitation from global reanalysis systems must be downscaled to a spatial and temporal resolution applicable for flood modeling. This study evaluates such downscaling and error correction approaches for improving hydrologic applications using a combination of NASA's Global Land Data Assimilation System (GLDAS) precipitation dataset and a higher resolution multi-satellite precipitation product (TRMM). The study focuses on 437 flood-inducing storm events that occurred over a period of ten years (2002-2011) in the Susquehanna River basin located in the northeast US. A validation strategy was devised for assessing error metrics in rainfall and simulated runoff as function of basin area, storm severity and season. The WSR-88D gauge-adjusted radar-rainfall (stage IV) product was used as the reference rainfall dataset, while runoff simulations forced with the stage IV precipitation dataset were considered as the runoff reference. Results show that the generated rainfall ensembles from the downscaled reanalysis products encapsulate the reference rainfall. The statistical analysis, including frequency and quantile plots plus mean relative error and root mean square error statistics, demonstrated improvements in the precipitation and runoff simulation error statistics of the satellite-driven downscaled reanalysis dataset compared to the original reanalysis precipitation product. Results vary by season and less by basin scale. In the fall season specifically, the downscaled product has three times lower mean relative error than the original product; this ratio increases to four times for the simulated runoff values. The proposed downscaling scheme is modular in design and can be applied on gridded satellite and reanalysis dataset.

Seyyedi, H.; Anagnostou, E. N.; Beighley, E.; McCollum, J.

2014-07-01

30

Ensembl 2011.  

PubMed

The Ensembl project (http://www.ensembl.org) seeks to enable genomic science by providing high quality, integrated annotation on chordate and selected eukaryotic genomes within a consistent and accessible infrastructure. All supported species include comprehensive, evidence-based gene annotations and a selected set of genomes includes additional data focused on variation, comparative, evolutionary, functional and regulatory annotation. The most advanced resources are provided for key species including human, mouse, rat and zebrafish reflecting the popularity and importance of these species in biomedical research. As of Ensembl release 59 (August 2010), 56 species are supported of which 5 have been added in the past year. Since our previous report, we have substantially improved the presentation and integration of both data of disease relevance and the regulatory state of different cell types. PMID:21045057

Flicek, Paul; Amode, M Ridwan; Barrell, Daniel; Beal, Kathryn; Brent, Simon; Chen, Yuan; Clapham, Peter; Coates, Guy; Fairley, Susan; Fitzgerald, Stephen; Gordon, Leo; Hendrix, Maurice; Hourlier, Thibaut; Johnson, Nathan; Kähäri, Andreas; Keefe, Damian; Keenan, Stephen; Kinsella, Rhoda; Kokocinski, Felix; Kulesha, Eugene; Larsson, Pontus; Longden, Ian; McLaren, William; Overduin, Bert; Pritchard, Bethan; Riat, Harpreet Singh; Rios, Daniel; Ritchie, Graham R S; Ruffier, Magali; Schuster, Michael; Sobral, Daniel; Spudich, Giulietta; Tang, Y Amy; Trevanion, Stephen; Vandrovcova, Jana; Vilella, Albert J; White, Simon; Wilder, Steven P; Zadissa, Amonida; Zamora, Jorge; Aken, Bronwen L; Birney, Ewan; Cunningham, Fiona; Dunham, Ian; Durbin, Richard; Fernández-Suarez, Xosé M; Herrero, Javier; Hubbard, Tim J P; Parker, Anne; Proctor, Glenn; Vogel, Jan; Searle, Stephen M J

2011-01-01

31

Downscaling and its use in ocean  

E-print Network

: Statistical Downscaling · SLP - surge (Albin et al., 2009) · Wind - surge (van den Brink et al., 2004) #12;A. Sterl, ICES workshop, 12.01.2010 (Albin et. al, submitted) 90%-ile of surge in Oostende from

Haak, Hein

32

Wave model downscaling for coastal applications  

Microsoft Academic Search

Downscaling is a suitable technique for obtaining high-resolution estimates from relatively coarse-resolution global models. Dynamical and statistical downscaling has been applied to the multidecadal simulations of ocean waves. Even as large-scale variability might be plausibly estimated from these simulations, their value for the small scale applications such as design of coastal protection structures and coastal risk assessment is limited due

Nikolay Valchev; Georgi Davidan; Ekaterina Trifonova; Nataliya Andreeva

2010-01-01

33

Ensembl 2007  

PubMed Central

The Ensembl () project provides a comprehensive and integrated source of annotation of chordate genome sequences. Over the past year the number of genomes available from Ensembl has increased from 15 to 33, with the addition of sites for the mammalian genomes of elephant, rabbit, armadillo, tenrec, platypus, pig, cat, bush baby, common shrew, microbat and european hedgehog; the fish genomes of stickleback and medaka and the second example of the genomes of the sea squirt (Ciona savignyi) and the mosquito (Aedes aegypti). Some of the major features added during the year include the first complete gene sets for genomes with low-sequence coverage, the introduction of new strain variation data and the introduction of new orthology/paralog annotations based on gene trees. PMID:17148474

Hubbard, T. J. P.; Aken, B. L.; Beal, K.; Ballester, B.; Caccamo, M.; Chen, Y.; Clarke, L.; Coates, G.; Cunningham, F.; Cutts, T.; Down, T.; Dyer, S. C.; Fitzgerald, S.; Fernandez-Banet, J.; Graf, S.; Haider, S.; Hammond, M.; Herrero, J.; Holland, R.; Howe, K.; Howe, K.; Johnson, N.; Kahari, A.; Keefe, D.; Kokocinski, F.; Kulesha, E.; Lawson, D.; Longden, I.; Melsopp, C.; Megy, K.; Meidl, P.; Ouverdin, B.; Parker, A.; Prlic, A.; Rice, S.; Rios, D.; Schuster, M.; Sealy, I.; Severin, J.; Slater, G.; Smedley, D.; Spudich, G.; Trevanion, S.; Vilella, A.; Vogel, J.; White, S.; Wood, M.; Cox, T.; Curwen, V.; Durbin, R.; Fernandez-Suarez, X. M.; Flicek, P.; Kasprzyk, A.; Proctor, G.; Searle, S.; Smith, J.; Ureta-Vidal, A.; Birney, E.

2007-01-01

34

Ensemble teleportation  

E-print Network

The possibility of teleportation is by sure the most interesting consequence of quantum non-separability. So far, however, teleportation schemes have been formulated by use of state vectors and considering individual entities only. In the present article the feasibility of teleportation is examined on the basis of the rigorous ensemble interpretation of quantum mechanics (not to be confused with a mere treatment of noisy EPR pairs) leading to results which are unexpected from the usual point of view.

Thomas Krüger

2004-04-15

35

The requirement for pneumococcal MreC and MreD is relieved by inactivation of the gene encoding PBP1a.  

PubMed

MreC and MreD, along with the actin homologue MreB, are required to maintain the shape of rod-shaped bacteria. The depletion of MreCD in rod-shaped bacteria leads to the formation of spherical cells and the accumulation of suppressor mutations. Ovococcus bacteria, such as Streptococcus pneumoniae, lack MreB homologues, and the functions of the S. pneumoniae MreCD (MreCD(Spn)) proteins are unknown. mreCD are located upstream from the pcsB cell division gene in most Streptococcus species, but we found that mreCD and pcsB are transcribed independently. Similarly to rod-shaped bacteria, we show that mreCD are essential in the virulent serotype 2 D39 strain of S. pneumoniae, and the depletion of MreCD results in cell rounding and lysis. In contrast, laboratory strain R6 contains suppressors that allow the growth of ?mreCD mutants, and bypass suppressors accumulate in D39 ?mreCD mutants. One class of suppressors eliminates the function of class A penicillin binding protein 1a (PBP1a). Unencapsulated ?pbp1a D39 mutants have smaller diameters than their pbp1a(+) parent or ?pbp2a and ?pbp1b mutants, which lack other class A PBPs and do not show the suppression of ?mreCD mutations. Suppressed ?mreCD ?pbp1a double mutants form aberrantly shaped cells, some with misplaced peptidoglycan (PG) biosynthesis compared to that of single ?pbp1a mutants. Quantitative Western blotting showed that MreC(Spn) is abundant (?8,500 dimers per cell), and immunofluorescent microscopy (IFM) located MreCD(Spn) to the equators and septa of dividing cells, similarly to the PBPs and PG pentapeptides indicative of PG synthesis. These combined results are consistent with a model in which MreCD(Spn) direct peripheral PG synthesis and control PBP1a localization or activity. PMID:21685290

Land, Adrian D; Winkler, Malcolm E

2011-08-01

36

Methodology for Air Quality Forecast Downscaling from Regional- to Street-Scale  

NASA Astrophysics Data System (ADS)

The most serious air pollution events occur in cities where there is a combination of high population density and air pollution, e.g. from vehicles. The pollutants can lead to serious human health problems, including asthma, irritation of the lungs, bronchitis, pneumonia, decreased resistance to respiratory infections, and premature death. In particular air pollution is associated with increase in cardiovascular disease and lung cancer. In 2000 WHO estimated that between 2.5 % and 11 % of total annual deaths are caused by exposure to air pollution. However, European-scale air quality models are not suited for local forecasts, as their grid-cell is typically of the order of 5 to 10km and they generally lack detailed representation of urban effects. Two suites are used in the framework of the EC FP7 project MACC (Monitoring of Atmosphere Composition and Climate) to demonstrate how downscaling from the European MACC ensemble to local-scale air quality forecast will be carried out: one will illustrate capabilities for the city of Copenhagen (Denmark); the second will focus on the city of Bucharest (Romania). This work is devoted to the first suite, where methodological aspects of downscaling from regional (European/ Denmark) to urban scale (Copenhagen), and from the urban down to street scale. The first results of downscaling according to the proposed methodology are presented. The potential for downscaling of European air quality forecasts by operating urban and street-level forecast models is evaluated. This will bring a strong support for continuous improvement of the regional forecast modelling systems for air quality in Europe, and underline clear perspectives for the future regional air quality core and downstream services for end-users. At the end of the MACC project, requirements on "how-to-do" downscaling of European air-quality forecasts to the city and street levels with different approaches will be formulated.

Baklanov, Alexander; Nuterman, Roman; Mahura, Alexander; Amstrup, Bjarne; Hansen Saas, Bent; Havskov Sørensen, Jens; Lorenzen, Thomas; Weismann, Jakob

2010-05-01

37

Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden  

NASA Astrophysics Data System (ADS)

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.

Hellström, Cecilia; Chen, Deliang

2003-11-01

38

A hybrid downscaling procedure for estimating the vertical distribution of ambient temperature in local scale  

NASA Astrophysics Data System (ADS)

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-output transfer functions is obtained by utilizing the ANN weights method, which quantifies the relative importance of the predictor variables in the estimation procedure. The overall downscaling performance evaluation incorporates a set of correlation and statistical measures along with appropriate statistical tests. The hybrid downscaling method presented in this work can be extended to various locations by training different site-specific ANN models and the results, depending on the application, can be used for assisting the understanding of the past, present and future climatology. ____________________________ This research has been co-financed by the European Union and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II: Investing in knowledge society through the European Social Fund.

Yiannikopoulou, I.; Philippopoulos, K.; Deligiorgi, D.

2012-04-01

39

Improving GEFS Weather Forecasts for Indian Monsoon with Statistical Downscaling  

NASA Astrophysics Data System (ADS)

Weather forecast has always been a challenging research problem, yet of a paramount importance as it serves the role of 'key input' in formulating modus operandi for immediate future. Short range rainfall forecasts influence a wide range of entities, right from agricultural industry to a common man. Accurate forecasts actually help in minimizing the possible damage by implementing pre-decided plan of action and hence it is necessary to gauge the quality of forecasts which might vary with the complexity of weather state and regional parameters. Indian Summer Monsoon Rainfall (ISMR) is one such perfect arena to check the quality of weather forecast not only because of the level of intricacy in spatial and temporal patterns associated with it, but also the amount of damage it can cause (because of poor forecasts) to the Indian economy by affecting agriculture Industry. The present study is undertaken with the rationales of assessing, the ability of Global Ensemble Forecast System (GEFS) in predicting ISMR over central India and the skill of statistical downscaling technique in adding value to the predictions by taking them closer to evidentiary target dataset. GEFS is a global numerical weather prediction system providing the forecast results of different climate variables at a fine resolution (0.5 degree and 1 degree). GEFS shows good skills in predicting different climatic variables but fails miserably over rainfall predictions for Indian summer monsoon rainfall, which is evident from a very low to negative correlation values between predicted and observed rainfall. Towards the fulfilment of second rationale, the statistical relationship is established between the reasonably well predicted climate variables (GEFS) and observed rainfall. The GEFS predictors are treated with multicollinearity and dimensionality reduction techniques, such as principal component analysis (PCA) and least absolute shrinkage and selection operator (LASSO). Statistical relationship is established between the principal components and observed rainfall over training period and predictions are obtained for testing period. The validations show high improvements in correlation coefficient between observed and predicted data (0.25 to 0.55). The results speak in favour of statistical downscaling methodology which shows the capability to reduce the gap between observed data and predictions. A detailed study is required to be carried out by applying different downscaling techniques to quantify the improvements in predictions.

Agrawal, Ankita; Salvi, Kaustubh; Ghosh, Subimal

2014-05-01

40

Transient climate rainfall downscaling using a combined dynamic-stochastic methodology  

NASA Astrophysics Data System (ADS)

Managers of water resource systems need downscaled climate change projections that are relevant at the catchment scale and at a range of future time horizons. However, the uncertainty in future climate projections and the natural variability of the climate system affect the robustness of their decisions. Dynamic downscaling of discrete future time-slices also limits the analysis of the temporal development of climate change impacts, as only steady state scenarios are widely available. Addressing these issues a new transient (i.e. temporally non-stationary) rainfall simulation methodology has been developed which combines dynamical and statistical downscaling to generate a multi-model ensemble of transient daily point-scale rainfall timeseries. Each timeseries is sampled from a continuous stochastic simulation of the control-future time period and exhibits climatic non-stationarity in accordance with GCM/RCM projections. The ensemble as a whole represents aspects of both climate model uncertainty and natural variability and provides a basis for probabilistic time-horizon analyses such as when a particular impact will occur or when a particular threshold will be reached. The methodology is demonstrated for a case study raingauge located near the Brévilles spring in Northern France. Thirteen RCM projections from the PRUDENCE project for both control (1961-1990) and future (2071-2100) time-slices were obtained to form the basis of a multi-model representation of climate change. Each dynamically downscales the climate from either the ECHAM4/OPYC or the HadCM3 GCM. Multiplicative ‘change factors' were evaluated for a set of statistics of daily rainfall for each RCM. These quantify the future value of each statistic as a multiple of the control value for each calendar month in turn. Multiplying the case study raingauge statistics by the change factors provides future projections with an implicit correction for biases in the RCM control runs and a representation of the variability exhibited between the RCMs. In the absence of transient RCM projections a ‘scale factor' approach was adopted to estimate climate change throughout the transient period. Future changes were assumed to occur in proportion to global annual average temperature change. Scale factors were evaluated for four 30-year time-slice integrations of the GCMs, for which global average temperatures were available. These were linearly interpolated for the intervening years. Transient change factors were then estimated in proportion to the scale factors. Applying these to the observed rainfall statistics gave a transient projection of the daily rainfall statistics for the case study location, for each RCM for a continuous period from 1997 to 2085. A new transient formulation of the Neyman-Scott Rectangular Pulses (NSRP) stochastic rainfall model has been developed. This model was used for stochastic downscaling to the point scale and to model natural rainfall variability at the daily scale. A piecewise smoothly varying transient NSRP parameterization was obtained by fitting to the transient projected rainfall statistics. Transient NSRP simulations then produced continuous daily rainfall time series which exhibit climatic non-stationarity. The simulation was realized 100 times to generate an ensemble, which models natural climate variability. Repeating for each RCM in turn generates a multi-model ensemble of 1300 transient downscaled daily rainfall timeseries. The ensemble improves on RCM simulations of the present-day climate and exhibits a time varying decrease in annual and summer rainfall and a time varying increase in winter rainfall amounts. The 10-year return period daily extreme rainfall is also likely to increase over the simulated period.

Burton, Aidan; Blenkinsop, Stephen; Fowler, Hayley J.; Kilsby, Chris G.

2010-05-01

41

Precipitation Downscaling Products for Hydrologic Applications (Invited)  

NASA Astrophysics Data System (ADS)

Hydrologists and engineers require climate data on high-resolution grids (4-12km) for many water resources applications. To get such data from climate models, users have traditionally relied on statistical downscaling techniques, with only limited use of dynamic downscaling techniques. Statistical techniques utilize a variety of assumptions, data, and methodologies that result in statistical artifacts that may impact hydroclimate representations. These impacts are often pronounced when downscaling precipitation. We will discuss four major statistical downscaling techniques: Bias Corrected Constructed Analogue (BCCA), Asynchronous Regression (AR), and two forms of Bias Corrected Spatial Disaggregation (BCSD.) The hydroclimate representations within many statistical methods often have too much drizzle, too small extreme events, and an improper representation of spatial scaling characteristics. These scaling problems lead some statistical methods substantially over estimate extreme events at hydrologically important scales (e.g., basin totals.) This can lead to large errors in future hydrologic predictions. In contrast, high-resolution dynamic downscaling using the Weather Research and Forecasting model (WRF) provides a better representation of precipitation in many respects, but at a much higher computational cost. This computational constraint prevents the use of high-resolution WRF simulations when examining the range of possible future scenarios generated as part of the Coupled Model Intercomparison Project (CMIP.) Finally, we will present a next generation psuedo-dynamical model that provides dynamic downscaling information for a fraction of the computational requirements. This simple weather model uses large scale circulation patterns from a GCM, for example wind, temperature and humidity, but performs advection and microphysical calculations on a high-resolution grid, thus permitting topography to be adequately represented. This model is capable of generating changes in spatial patterns of precipitation related to atmospheric processes in a future climate. The pseudo-dynamical model may provide both the opportunity to better represent precipitation as well as being efficient in application to utilize a range of potential futures in a manner that would support water resources planning and management in the future.

Gutmann, E. D.; Pruitt, T.; Liu, C.; Clark, M. P.; Brekke, L. D.; Arnold, J.; Raff, D. A.; Rasmussen, R.

2013-12-01

42

Regional Climate Downscaling Intercomparison over the Philippines  

E-print Network

Regional Climate Downscaling Intercomparison over the Philippines J.H. Qian, A.W. Robertson, M: PAGASA, the Philippines #12;#12;#12;#12;Analysis of r a i n f a l l fluctuations in the Philippines 237 Figure 1 Climatological map (after "Philippines Water Resources", 1976). Vigan, Legaspi, Zamboanga

Qian, Jian-Hua "Joshua"

43

Comparison of two analog-based downscaling methods for regional reference evapotranspiration forecasts  

NASA Astrophysics Data System (ADS)

SummaryThe objective of this study was to compare the performance of natural analog (NA) and constructed analog (CA) methods to produce both probabilistic and deterministic downscaled daily reference evapotranspiration (ETo) forecasts in the southeastern United States. The 1-15 day, 15-member ETo forecasts were produced from 1979 to 2009 using the Penman-Monteith equation and a forecast analog approach with a combination of the Global Forecast System (GFS) reforecasts and NCEP-DOE Reanalysis 2 climatology, and were downscaled using the North American Regional Reanalysis (NARR). The Pearson correlation coefficient (R), mean squared error skill score (MSESS), and Bias were used to evaluate the skill of downscaled deterministic forecasts. The Linear Error in Probability Space (LEPS) skill score, Brier Skill Score (BSS), relative operating characteristic, and reliability diagrams were used to evaluate the skill of downscaled probabilistic forecasts. Overall, CA showed slightly higher skill than NA in terms of the metrics for deterministic forecasts, while for probabilistic forecasts NA showed higher skill than CA regarding the BSS in five categories (terciles, and 10th and 90th percentiles) and lower skill than CA regarding the LEPS skill score. Both CA and NA produced skillful deterministic results in the first 3 lead days, while the skill was higher for CA than for NA. Probabilistic NA forecasts exhibited higher resolution and reliability than CA, likely due to a larger ensemble size. Forecasts by both methods showed the lowest skill in the Florida peninsula and in mountainous areas, likely due to the fact that these features were not well-resolved in the model forecast.

Tian, Di; Martinez, Christopher J.

2012-12-01

44

Quantifying the impact of small scale unmeasured rainfall variability on urban runoff through multifractal downscaling: A case study  

NASA Astrophysics Data System (ADS)

SummaryThis paper aims at quantifying the uncertainty on urban runoff associated with the unmeasured small scale rainfall variability, i.e. at a resolution finer than 1 km × 1 km × 5 min which is usually available with C-band radar networks. A case study is done on the 900 ha urban catchment of Cranbrook (London). A frontal and a convective rainfall event are analysed. An ensemble prediction approach is implemented, that is to say an ensemble of realistic downscaled rainfall fields is generated with the help of universal multifractals, and the corresponding ensemble of hydrographs is simulated. It appears that the uncertainty on the simulated peak flow is significant, reaching for some conduits 25% and 40% respectively for the frontal and the convective events. The flow corresponding the 90% quantile, the one simulated with radar distributed rainfall, and the spatial resolution are power law related.

Gires, A.; Onof, C.; Maksimovic, C.; Schertzer, D.; Tchiguirinskaia, I.; Simoes, N.

2012-06-01

45

Downscaling of global solar irradiation in R  

E-print Network

A methodology for downscaling solar irradiation from satellite-derived databases is described using R software. Different packages such as raster, parallel, solaR, gstat, sp and rasterVis are considered in this study for improving solar resource estimation in areas with complex topography, in which downscaling is a very useful tool for reducing inherent deviations in satellite-derived irradiation databases, which lack of high global spatial resolution. A topographical analysis of horizon blocking and sky-view is developed with a digital elevation model to determine what fraction of hourly solar irradiation reaches the Earth's surface. Eventually, kriging with external drift is applied for a better estimation of solar irradiation throughout the region analyzed. This methodology has been implemented as an example within the region of La Rioja in northern Spain, and the mean absolute error found is a striking 25.5% lower than with the original database.

Antonanzas-Torres, F; Antonanzas, J; Perpiñán, O

2013-01-01

46

Introduction to Ensemble Prediction  

NSDL National Science Digital Library

This webcast is a shorter companion to the Ensemble Prediction Explained module, focusing more directly on immediate operational needs. Introductory content includes the role of ensemble forecasts, presentation of basic ensemble forecasting terms, and discussion of how ensemble prediction systems (EPSs) are created. The largest section is focused on common ensemble forecast products, including how they differ from traditional NWP products, how we interpret ensemble forecast products, the advantages and limitations of each product, how EPS products are verified, and how to use ensemble products in conjunction with one another to increase your understanding of forecast uncertainty. Finally, three brief cases from cold and warm seasons illustrate the use of ensemble products in the forecast process.

Comet

2005-06-27

47

Hydrological responses to dynamically and statistically downscaled climate model output  

USGS Publications Warehouse

Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

2000-01-01

48

Producing information for Vulnerability, Impacts and Adaptation work: The COordinated Regional Downscaling EXperiment (CORDEX) (Invited)  

NASA Astrophysics Data System (ADS)

Regional climate information is needed for use in Vulnerability, Impacts and Adaptation (VIA) studies. This information can be obtained either from Global Climate Model (GCM) simulations or from different downscaling techniques that regionally enhance the GCM fields to produce fine scale climate information. Downscaling techniques include both dynamical (i.e. Regional Climate Models, or RCMs) and statistical methods, and can be applied in a variety of contexts, such as process studies and regional to local climate change projections. One of the key issues in producing climate information for VIA application is that of suitably characterizing underlying uncertainties. In fact, there are several sources of uncertainty in climate projections: limitations and systematic errors in GCMs and downscaling tools, greenhouse gas (GHG) emission and concentration scenarios, response of different models (physics and configurations) to GHG forcing, internal decadal to multidecadal variability of the climate system. In order to characterize these uncertainties, large ensembles of model projections are needed, a task that is best approached in a mullti-model, multi-laboratory international context. These premises have lead to the inception of the COordinated Regional Downscaling EXperiment (CORDEX), under the auspices of the World Climate Research program (WGRP). The purpose of CORDEX is threefold: 1) to evaluate and possibly improve regional downscaling techniques (both dynamical and statistical); 2) to produce a new generation of regional climate change projections for regions worldwide based on a multi-model approach; 3) to foster the interactions across the climate and VIA research communites. The CORDEX Phase I framework has been designed and implemented, and related activities have been strongly growing in the last 1-2 years with a wide international participation. This paper will review the status of CORDEX, especially drawing from the results of a major pan-CORDEX conference taking place on 4-7 November 2013 in Brussels. In particular, the paper will summarize lessons learned from the CORDEX Phase I activities and discuss future directions and areas in need of strengthening in view of the development of the CORDEX Phase II framework.

Giorgi, F.

2013-12-01

49

Validation of a Universal Multifractal downscaling process with the help of dense networks of disdrometers  

NASA Astrophysics Data System (ADS)

The resolution of the rainfall data usually provided by operational C-band radar networks of Western European meteorological services is 1 km in space and 5 min in time. It has been shown that higher resolutions are needed for various applications, notably in the field of urban hydrology. A way of dealing with this unmeasured small scale rainfall variability is to input stochastically downscaled rainfall fields to urban hydrological models and simulate not a single response for the studied catchment but an ensemble. In this paper we suggest to discuss a downscaling procedure for the rainfall field. It relies on the Universal Multifractals which have been extensively used to model and simulate geophysical fields extremely variable over a wide range of spatio-temporal scales such as rainfall. Here this standard framework of multiplicative cascades has been modified in a discrete case to better take into account the numerous zeros of the rainfall field (i.e. a pixel with no rainfall recorded). More precisely the zeros are introduced at each scale within the cascade process in a probabilistic scale invariant way. The downscaling suggested here consists in retrieving the scaling properties of the rainfall field on the available range of scales and stochastically continuing the underlying process below the scale of observation. Rainfall data coming from a dense network of 16 optical disdrometers (Particle Size and Velocity, PARSIVEL, 1st generation) that was deployed for 16 month over an area of approximately 1 km2 in the campus of Ecole Polytechnique Federale de Lausanne (Switzerland) will be used to validate this downscaling procedure. Preliminary results with a network of second generation PARSIVEL currently under construction in Ecole des Ponts ParisTech (France) will also be shown. The methodology implemented consists in downscaling a rainfall field with a resolution of 1 km and 5 min to a resolution comparable with the disdrometers' one (few tens of cm and 1 min). The variability among the generated "virtual" disdrometers is then compared with the observed one. The impact of these results on the comparisons commonly performed between radar and rain gauge / disdrometer rainfall data will finally be briefly discussed.

Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Berne, Alexis; Lovejoy, Shaun

2013-04-01

50

"Going the Extra Mile in Downscaling: Why Downscaling is not jut "Plug-and-Play"  

EPA Science Inventory

This presentation provides an example of doing additional work for preprocessing global climate model data for use in regional climate modeling simulations with the Weather Research and Forecasting (WRF) model. In this presentation, results from 15 months of downscaling the Comm...

51

Empirical Downscaling of Windfields for Hydrodynamic Modeling of Lakes  

Microsoft Academic Search

Aiming for the fine spatial and temporal discretization required for hydrodynamic modeling of lakes, wind vectors from General Circulation Models (GCMs) are downscaled stochastically. Instead of dynamic downscaling methods, empirical ones are used here because they are more likely to reproduce the variability and the frequency of extreme values existent in natural winds. Generally GCMs are good predictors of large

Dirk Schlabing; Andras Bardossy

2010-01-01

52

Convolutional Neural Networks for Climate Downscaling Ranjini Swaminathan+  

E-print Network

Convolutional Neural Networks for Climate Downscaling Ranjini Swaminathan+ , Mohan Sridharan of convolutional neural networks (CNNs), a benchmark for visual recognition tasks [6]. A CNN is a multilayered downscaling, e.g., Bayesian frameworks, artificial neural networks, support vector machines, mul- tilayer

Gelfond, Michael

53

Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States  

Microsoft Academic Search

To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research\\/Department of Energy (NCAR\\/DOE) Parallel Climate Model (PCM). The Penn State\\/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (20 years) and three future(2040–2060) climate simulations to yield ensemble regional climate simulations at

L. Ruby Leung; Yun Qian; Xindi Bian; Warren M. Washington; Jongil Han; John O. Roads

2004-01-01

54

The Personal Software Process: Downscaling the factory  

NASA Technical Reports Server (NTRS)

It is argued that the next wave of software process improvement (SPI) activities will be based on a people-centered paradigm. The most promising such paradigm, Watts Humphrey's personal software process (PSP), is summarized and its advantages are listed. The concepts of the PSP are shown also to fit a down-scaled version of Basili's experience factory. The author's data and lessons learned while practicing the PSP are presented along with personal experience, observations, and advice from the perspective of a consultant and teacher for the personal software process.

Roy, Daniel M.

1994-01-01

55

Ensemble Applications in Winter  

NSDL National Science Digital Library

This lesson provides an introduction to ensemble forecast systems using an operational case study of the Blizzard of 2013 in Southern Ontario. The module uses models available to forecasters in the Meteorological Service of Canada, including Canadian and U.S. global and regional ensembles. After briefly discussing the rationale for ensemble forecasting, the module presents small lessons on probabilistic ensemble products useful in winter weather forecasting, immediately followed by forecast applications to a southern Ontario case. The learner makes forecasts for the Ontario Storm Prediction Center area and, in the short range, for the Toronto metropolitan area. An additional section applies a probabilistic aviation product to forecasts for Toronto Pearson International Airport.

Comet

2014-04-22

56

The Ensemble Canon  

NASA Technical Reports Server (NTRS)

Ensemble is an open architecture for the development, integration, and deployment of mission operations software. Fundamentally, it is an adaptation of the Eclipse Rich Client Platform (RCP), a widespread, stable, and supported framework for component-based application development. By capitalizing on the maturity and availability of the Eclipse RCP, Ensemble offers a low-risk, politically neutral path towards a tighter integration of operations tools. The Ensemble project is a highly successful, ongoing collaboration among NASA Centers. Since 2004, the Ensemble project has supported the development of mission operations software for NASA's Exploration Systems, Science, and Space Operations Directorates.

MIittman, David S

2011-01-01

57

High resolution probabilistic precipitation forecast over Spain combining the statistical downscaling tool PROMETEO and the AEMET short range EPS system (AEMET/SREPS)  

NASA Astrophysics Data System (ADS)

The Short-Range Ensemble Prediction System (SREPS) is a multi-LAM (UM, HIRLAM, MM5, LM and HRM) multi analysis/boundary conditions (ECMWF, UKMetOffice, DWD and GFS) run twice a day by AEMET (72 hours lead time) over a European domain, with a total of 5 (LAMs) x 4 (GCMs) = 20 members. One of the main goals of this project is analyzing the impact of models and boundary conditions in the short-range high-resolution forecasted precipitation. A previous validation of this method has been done considering a set of climate networks in Spain, France and Germany, by interpolating the prediction to the gauge locations (SREPS, 2008). In this work we compare these results with those obtained by using a statistical downscaling method to post-process the global predictions, obtaining an "advanced interpolation" for the local precipitation using climate network precipitation observations. In particular, we apply the PROMETEO downscaling system based on analogs and compare the SREPS ensemble of 20 members with the PROMETEO statistical ensemble of 5 (analog ensemble) x 4 (GCMs) = 20 members. Moreover, we will also compare the performance of a combined approach post-processing the SREPS outputs using the PROMETEO system. References: SREPS 2008. 2008 EWGLAM-SRNWP Meeting (http://www.aemet.es/documentos/va/divulgacion/conferencias/prediccion/Ewglam/PRED_CSantos.pdf)

Cofino, A. S.; Santos, C.; Garcia-Moya, J. A.; Gutierrez, J. M.; Orfila, B.

2009-04-01

58

Extreme winds over Europe in the ENSEMBLES regional climate models  

NASA Astrophysics Data System (ADS)

Extreme winds cause vast amounts of damage every year and represent a major concern for numerous industries including construction, afforestation, wind energy and many others. Under a changing climate, the intensity and frequency of extreme events are expected to change, and accurate projections of these changes will be invaluable to decision makers and society as a whole. This work examines four regional climate model downscalings over Europe following the SRES A1B scenario from the "ENSEMBLE-based Predictions of Climate Changes and their Impacts" project (ENSEMBLES). It investigates the projected changes in the 50 yr return wind speeds and the associated uncertainties. This is accomplished by employing the peaks-over-threshold method with the use of the generalised Pareto distribution. The models show that, for much of Europe, the 50 yr return wind is projected to change by less than 2 m s-1, while the uncertainties associated with the statistical estimates are larger than this. In keeping with previous works in this field, the largest source of uncertainty is found to be the inter-model spread, with some locations showing differences in the 50 yr return wind of over 20 m s-1 between two different downscalings.

Outten, S. D.; Esau, I.

2013-05-01

59

Extreme winds over Europe in the ENSEMBLES regional climate models  

NASA Astrophysics Data System (ADS)

Extreme winds cause vast amounts of damage every year and represent a major concern for numerous industries including construction, afforestation, wind energy and many others. Under a changing climate, the intensity and frequency of extreme events are expected to change, and accurate predictions of these changes will be invaluable to decision makers and society as a whole. This work examines four regional climate model downscalings over Europe from the "ENSEMBLE-based Predictions of Climate Changes and their Impacts" project (ENSEMBLES), and investigates the predicted changes in the 50 yr return wind speeds and the associated uncertainties. This is accomplished by employing the peaks-over-threshold method with the use of the Generalised Pareto Distribution. The models show that for much of Europe the 50 yr return wind is projected to change by less than 2 m s-1, while the uncertainties associated with the statistical estimates are larger than this. In keeping with previous works in this field, the largest source of uncertainty is found to be the inter-model spread, with some locations showing differences in the 50 yr return wind of over 20 m s-1 between two different downscalings.

Outten, S. D.; Esau, I.

2013-01-01

60

Assimilation of Downscaled SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions in Brazil  

NASA Astrophysics Data System (ADS)

Reliable soil moisture (SM) information in the root zone (RZSM) is critical for quantification of agricultural drought impacts on crop yields and for recommending management and adaptation strategies for crop management, commodity trading and food security.The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future National Aeronautics and Space Administration-Soil Moisture Active Passive (NASA-SMAP) missions provide SM at unprecedented spatial resolutions of 10-25 km, but these resolutions are still too coarse for agricultural applications in heterogeneous landscapes, making downscaling a necessity. This downscaled near-surface SM can be merged with crop growth models in a data assimilation framework to provide optimal estimates of RZSM and crop yield. The objectives of the study include: 1) to implement a novel downscalingalgorithm based on the Information theoretical learning principlesto downscale SMOS soil moisture at 25 km to 1km in the Brazilian La Plata Basin region and2) to assimilate the 1km-soil moisture in the crop model for a normal and a drought year to understand the impact on crop yield. In this study, a novel downscaling algorithm based on the Principle of Relevant Information (PRI) was applied to in-situ and remotely sensed precipitation, SM, land surface temperature and leaf area index in the Brazilian Lower La Plata region in South America. An Ensemble Kalman Filter (EnKF) based assimilation algorithm was used to assimilate the downscaled soil moisture to update both states and parameters. The downscaled soil moisture for two growing seasons in2010-2011 and 2011-2012 was assimilated into the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model over 161 km2 rain-fed region in the Brazilian LPB regionto improve the estimates of soybean yield. The first season experienced normal precipitation, while the second season was impacted by drought. Assimilation improved yield during both the seasons compared to the open-loop and matched well with the published yield statistics in the region.

Chakrabarti, S.; Bongiovanni, T. E.; Judge, J.; Principe, J. C.; Fraisse, C.

2013-12-01

61

Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation  

NASA Astrophysics Data System (ADS)

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.

Zhang, Hua; Huang, Guo H.

2013-02-01

62

AMIC Project: Comparison of WRF High Resolution Dynamical Downscaling of ERA-Interim and EC-Earth for Azores Islands  

NASA Astrophysics Data System (ADS)

Project AMIC integrates the Portuguese members of the new EC-Earth climate modeling consortium. The aim is to contribute to the IPCC fifth report with a significant set of simulations with a state of the art model, while giving the group timely access to the complete ensemble of simulations for diagnostic studies, and regional downscaling. Additionally, Project AMIC will produce a new set of high resolution simulations of the Portuguese islands climate, using a state of the art model (WRF) at 6km horizontal resolution, with boundary conditions from the new ERA-Interim reanalysis (1989-2009) and from the EC-Earth decadal (20 year) runs. These simulations will allow for validation of the downscaling methodology, and will characterize both the current and near future climate. This study aims to compare two present day climate high resolution dynamical downscaling WRF simulations for the Portuguese islands of Azores using the ECMWF ERA-Interim reanalysis and the EC-Earth v2.3 boundary conditions for the period 1989-2010. In small volcanic islands the local scale climate is influenced by the regional scale climate and by the orography and orientation of air masses over the islands. In these environments the climatological conditions are a vital importance for the local agriculture and water management. With this study we aim to see how well the dynamical downscaling using EC-Earth v2.3 behaves when put against to the ERA-Interim reanalysis. To achieve this goal results from both simulations are compared against with the available observation network in both islands. This study results will show us what kind of deviations we can expect for the future scenarios runs using EC-Earth boundaries currently being made in IDL.

Tomé, Ricardo; Miranda, Pedro; Azevedo, Eduardo; Santo, Fátima

2013-04-01

63

Ensemble Forecasting Explained  

NSDL National Science Digital Library

This module, the latest in our series on Numerical Weather Prediction, covers the theory and use of ensemble prediction systems (EPSs). The module will help forecasters develop an understanding of the basis for EPSs, the skills to interpret ensemble products, and strategies for their use in the forecast process. It contains six sections: an Introduction that briefly presents background theory; Generation, which describes how ensemble systems are constructed; Statistical Concepts, which provides a brief refresher on knowledge required for ensemble product interpretation; Summarizing Data, which describes common ensemble forecast products; Verification, which discusses how EPSs performance is assessed and documented; and Case Applications, which provides links to a number of forecast cases illustrating the use of EPSs in the forecast process. Questions and Exercises are offered throughout to help you test your learning and provide practical examples. The module also includes a pre-assessment and module final quiz.

Comet

2004-09-27

64

Bias-corrected short-range Member-to-Member ensemble forecasts of reservoir inflow  

NASA Astrophysics Data System (ADS)

A Member-to-Member ensemble forecasting system is developed for inflows to hydroelectric reservoirs that incorporates multiple numerical weather prediction models and multiple distributed hydrological models linked by a variety of downscaling schemes. Each hydrological model uses multiple differently-optimized parameter sets and begins each daily forecast from several different initial conditions. The ensemble thereby attempts to sample all sources of error in the modeling chain. The importance of sampling all sources of error is illustrated by comparing this ensemble with an ensemble comprised of single 'best' parameterization for each hydrological model. Degree-of-mass-balance bias correction schemes trained using data windows of varying lengths are applied to the individual ensemble members. Based on examination of various verification metrics, we determine that a bias corrector that uses a linearly-weighted combination of past errors calculated over a three-day moving window is able to significantly improve forecast quality for the flashy case study watershed in southwestern British Columbia, Canada. Incorporation of all sources of modeling uncertainty is found to greatly improve ensemble resolution and discrimination. The full potential for these improvements using ensembles is only realized after removal of bias.

Bourdin, Dominique R.; Stull, Roland B.

2013-10-01

65

Global ensemble forecasting  

NASA Astrophysics Data System (ADS)

During the past 10 years ensemble forecasting has established itself as an important component in numerical weather prediction. Global ensemble prediction systems have been operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) and at the National Meteorological Center for Environmental Prediction (NOAA/NWS/NCEP) since December 1992, and at the Meterological Service of Canada (MSC/CMC) since February 1998. In this talk, the similarities and differences among the three operational global ensemble forecast systems are discussed. The performance of the three systems is illustrated and compared over a three month period (May-July) in 2002. Also reviewed are open issues, ongoing research projects, and future directions related to ensemble forecasting efforts at the three centers.

Toth, Z.; Buizza, R.; Houtekamer, P.

2003-04-01

66

Ensemble Data Mining Methods  

NASA Technical Reports Server (NTRS)

Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

Oza, Nikunj C.

2004-01-01

67

An Overview of Ensembl  

PubMed Central

Ensembl (http://www.ensembl.org/) is a bioinformatics project to organize biological information around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of individual genomes, and of the synteny and orthology relationships between them. It is also a framework for integration of any biological data that can be mapped onto features derived from the genomic sequence. Ensembl is available as an interactive Web site, a set of flat files, and as a complete, portable open source software system for handling genomes. All data are provided without restriction, and code is freely available. Ensembl's aims are to continue to “widen” this biological integration to include other model organisms relevant to understanding human biology as they become available; to “deepen” this integration to provide an ever more seamless linkage between equivalent components in different species; and to provide further classification of functional elements in the genome that have been previously elusive. PMID:15078858

Birney, Ewan; Andrews, T. Daniel; Bevan, Paul; Caccamo, Mario; Chen, Yuan; Clarke, Laura; Coates, Guy; Cuff, James; Curwen, Val; Cutts, Tim; Down, Thomas; Eyras, Eduardo; Fernandez-Suarez, Xose M.; Gane, Paul; Gibbins, Brian; Gilbert, James; Hammond, Martin; Hotz, Hans-Rudolf; Iyer, Vivek; Jekosch, Kerstin; Kahari, Andreas; Kasprzyk, Arek; Keefe, Damian; Keenan, Stephen; Lehvaslaiho, Heikki; McVicker, Graham; Melsopp, Craig; Meidl, Patrick; Mongin, Emmanuel; Pettett, Roger; Potter, Simon; Proctor, Glenn; Rae, Mark; Searle, Steve; Slater, Guy; Smedley, Damian; Smith, James; Spooner, Will; Stabenau, Arne; Stalker, James; Storey, Roy; Ureta-Vidal, Abel; Woodwark, K. Cara; Cameron, Graham; Durbin, Richard; Cox, Anthony; Hubbard, Tim; Clamp, Michele

2004-01-01

68

A cooperative ensemble learning system  

Microsoft Academic Search

This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles. The idea behind CELS is to encourage different individual networks in an ensemble to learn different parts or aspects of the training data so that the ensemble can learn the whole training data better. Rather than producing unbiased individual networks whose errors are uncorrelated, CELS

Yong Liu; Xin Yao

1998-01-01

69

Downscaling of slip distribution for strong earthquakes  

NASA Astrophysics Data System (ADS)

We intend to develop a downscaling model to enhance the earthquake slip distribution resolution. Slip distributions have been obtained by other researchers using various inversion methods. As a downscaling model, we are discussing fractal models that include mono-fractal models (fractional Brownian motion, fBm; fractional Lévy motion, fLm) and multi-fractal models as candidates. Log - log-linearity of k (wave number) versus E (k) (power spectrum) is the necessary condition for fractality: the slip distribution is expected to satisfy log - log-linearity described above if we can apply fractal model to a slip distribution as a downscaling model. Therefore, we conducted spectrum analyses using slip distributions of 11 earthquakes as explained below. 1) Spectrum analyses using one-dimensional slip distributions (strike direction) were conducted. 2) Averaging of some results of power spectrum (dip direction) was conducted. Results show that, from the viewpoint of log - log-linearity, applying a fractal model to slip distributions can be inferred as valid. We adopt the filtering method after Lavallée (2008) to generate fBm/ fLm. In that method, generated white noises (random numbers) are filtered using a power law type filter (log - log-linearity of the spectrum). Lavallée (2008) described that Lévy white noise that generates fLm is more appropriate than the Gaussian white noise which generates fBm. In addition, if the 'alpha' parameter of the Lévy law, which governs the degree of attenuation of tails of the probability distribution, is 2.0, then the Lévy distribution is equivalent to the Gauss distribution. We analyzed slip distributions of 11 earthquakes: the Tohoku earthquake (Wei et al., 2011), Haiti earthquake (Sladen, 2010), Simeulue earthquake (Sladen, 2008), eastern Sichuan earthquake (Sladen, 2008), Peru earthquake (Konca, 2007), Tocopilla earthquake (Sladen, 2007), Kuril earthquake (Sladen, 2007), Benkulu earthquake (Konca, 2007), and southern Java earthquake (Konca, 2006)). We obtained the following results. 1) Log - log-linearity (slope of the linear relationship is ' - ?') of k versus E(k) holds for all earthquakes. 2) For example, ? = 3.70 and ? = 1.96 for the Tohoku earthquake (2011) and ? = 4.16 and ? = 2.00 for the Haiti earthquake (2010). For these cases, the Gauss' law is appropriate because alpha is almost 2.00. 3) However, ? = 5.25 and ? = 1.25 for the Peru earthquake (2007) and ? = 2.24 and ? = 1.57 for the Simeulue earthquake (2008). For these earthquakes, the Lévy law is more appropriate because ? is far from 2.0. 4) Although Lavallée (2003, 2008) concluded that the Lévy law is more appropriate than the Gauss' law for white noise, which is later filtered, our results show that the Gauss law is appropriate for some earthquakes. Lavallée and Archuleta, 2003, Stochastic modeling of slip spatial complexities for the 1979 Imperial Valley, California, earthquake, GEOPHYSICAL RESEARCH LETTERS, 30(5). Lavallée, 2008, On the random nature of earthquake source and ground motion: A unified theory, ADVANCES IN GEOPHYSICS, 50, Chap 16.

Yoshida, T.; Oya, S.; Kuzuha, Y.

2013-12-01

70

Optimal signal ensembles  

E-print Network

Classical messages can be sent via a noisy quantum channel in various ways, corresponding to various choices of signal states of the channel. Previous work by Holevo and by Schumacher and Westmoreland relates the capacity of the channel to the properties of the signal ensemble. Here we describe some properties characterizing the ensemble that maximizes the capacity, using the relative entropy "distance" between density operators to give the results a geometric flavor.

Benjamin Schumacher; Michael D. Westmoreland

1999-12-31

71

Ensembl variation resources  

PubMed Central

Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org. PMID:20459805

2010-01-01

72

The reweighted path ensemble.  

PubMed

We introduce a reweighting scheme for the path ensembles in the transition interface sampling framework. The reweighting allows for the analysis of free energy landscapes and committor projections in any collective variable space. We illustrate the reweighting scheme on a two dimensional potential with a nonlinear reaction coordinate and on a more realistic simulation of the Trp-cage folding process. We suggest that the reweighted path ensemble can be used to optimize possible nonlinear reaction coordinates. PMID:21054008

Rogal, Jutta; Lechner, Wolfgang; Juraszek, Jarek; Ensing, Bernd; Bolhuis, Peter G

2010-11-01

73

Regional climate change projections over South America based on the CLARIS-LPB RCM ensemble  

NASA Astrophysics Data System (ADS)

CLARIS-LPB was an EU FP7 financed Europe-South America Network for Climate Change Assessment and Impact Studies in La Plata Basin. CLARIS-LPB has created the first ensemble ever of RCM downscalings over South America. Here we present the climate change scenarios for a near future period (2011-2040) and for a far future period (2071-2100). The ensemble is based on seven RCMs driven by three CMIP3 GCMs for emission scenario SRES A1B. The RCM model domains cover all of South America, with a horizontal resolution of approximately 50 km, but project focus has been on results over the La Plata Basin. The ensemble mean for temperature change shows more warming over tropical South America than over the southern part of the continent. During summer (DJF) the Low-Parana and Uruguay regions show less warming than the surrounding regions. For the ensemble mean of precipitation changes the patterns are almost the same for near and far future but with larger values for far future. Thus overall trends do not change with time. The near future shows in general small changes over large areas (less than ±10%). For JJA a dry tendency is seen over eastern Brazil that becomes stronger and extends geographically with time. In near future most models show a drying trend over this area. In far future almost all models agree on the drying. For DJF a wet tendency is seen over the La Plata basin area which becomes stronger with time. In near future almost all downscalings agree on this wet tendency and in far future all downscalings agree on the sign. The RCM ensemble is unbalanced with respect to forcing GCMs. 6 out of 11(10) simulations use ECHAM5 for the near(far) future period while 4(3) use HadCM3 and only one IPSL. Thus, all ensemble mean values will be tilted towards ECHAM5. It is of course possible to compensate for this imbalance among GCMs by some weighting but no such weighting has been applied for the current analysis. The north-south gradient in warming is in general stronger in the ECHAM5 downscalings and is also more evident during JJA than during DJF. The HadCM3 and IPSL downscalings give larger warming in near future than ECHAM5 downscalings. This tendency is still present in far future but differences connected to GCMs are then much less evident. For precipitation the spread in trends and amounts of changes between different downscalings are much larger than for temperature. In contrast to temperature the precipitation patterns are in general more similar for the same RCM than for the same GCM. Thus, the results are sensitive for how precipitation processes are parameterized and/or for how local surface-atmosphere feedback mechanisms are simulated. Looking at a certain RCM and period the patterns for near and far futures are similar but stronger for the far future period.

Samuelsson, Patrick; Solman, Silvina; Sanchez, Enrique; Rocha, Rosmeri; Li, Laurent; Marengo, José; Remedio, Armelle; Berbery, Hugo

2013-04-01

74

High resolution ensemble error growth and dimensionality in tropical cyclone genesis environments  

NASA Astrophysics Data System (ADS)

Over the last several decades, ensemble forecasts of atmospheric phenomena have become increasingly popular, not only because they provide an improved mean forecast of various events, but also because they render an estimate of the accompanying forecast uncertainty. Research into high-resolution ensembles based in the Tropics and in terms of tropical cyclone (TC) genesis mechanisms has been relatively sparse, even though such disturbances are notoriously difficult to forecast. In this study, we couple several popular ensemble perturbation methods to the mesoscale Weather Research and Forecasting (WRF) model at high resolution to examine the predictability of genesis, error growth characteristics, and underdispersion issues in forecasts of Hurricane Ernesto (2006) and Typhoon Nuri (2008). In order to examine the effects of model resolution on TC genesis forecasts, a downscaled 5-km resolution regional control ensemble, based on a downscaling of the National Centers for Environmental Prediction's Global Ensemble Forecast System (GEFS), is compared against the standard GEFS simulations. To analyze the effect of the various perturbation methods on genesis and forecast characteristics, we compare results from the regional GEFS-based simulation to several implementations of the breeding of growing modes (BGM), wherein we vary the variables perturbed, cycling period durations, and boundary conditions. While the global GEFS forecast failed to predict a well-developed Ernesto in any of its members, the high-resolution GEFS-based ensemble contained several intense TCs by actual genesis time. Based on a sample of 154 ensemble member forecasts, the impact of environmental precursors on TC genesis likelihood is investigated. Despite the large number of easterly waves that do not develop into TCs and the large amount of water vapor in the summer Tropics, we find that the strength of the preexisting wave and initial 850 hPa water vapor are significant determining factors for TC genesis. Finally, we create several ensemble forecasts of Ernesto using the stochastic kinetic-energy backscatter scheme (SKEBS) and find that the standard SKEBS ensemble has more dispersion per unit error compared with both the BGM and GEFS-based ensembles. In addition, SKEBS shows notably lower vapor bias and larger theta bias compared with the initial condition-based ensembles.

Thatcher, Levi Sterling

75

A multimodel ensemble approach to assessment of climate change impacts on the hydrology and water resources of the Colorado River basin  

NASA Astrophysics Data System (ADS)

Implications of 21st century climate change on the hydrology and water resources of the Colorado River basin were assessed using a multimodel ensemble approach in which downscaled and bias corrected output from 11 General Circulation Models (GCMs) was used to drive macroscale hydrology and water resources models. Downscaled climate scenarios (ensembles) were used as forcings to the Variable Infiltration Capacity (VIC) macroscale hydrology model, which in turn forced the Colorado River Reservoir Model (CRMM). Ensembles of downscaled precipitation and temperature, and derived streamflows and reservoir system performance were assessed through comparison with current climate simulations for the 1950-1999 historical period. For each of the 11 GCMs, two emissions scenarios (IPCC SRES A2 and B1, corresponding to relatively unconstrained growth in emissions, and elimination of global emissions increases by 2100) were represented. Results for the A2 and B1 climate scenarios were divided into period 1 (2010-2039), period 2 (2040-2069), and period 3 (2070-2099). The mean temperature change averaged over the 11 ensembles for the Colorado basin for the A2 emission scenario ranged from 1.2 to 4.4°C for periods 1-3, and for the B1 scenario from 1.3 to 2.7°C. Precipitation changes were modest, with ensemble mean changes ranging from -1 to -2 percent for the A2 scenario, and from +1 to -1 percent for the B1 scenario. An analysis of seasonal precipitation patterns showed that most GCMs had modest reductions in summer precipitation and increases in winter precipitation. Derived 1 April snow water equivalent declined for all ensemble members and time periods, with maximum (ensemble mean) reductions of 38 percent for the A2 scenario in period 3. Runoff changes were mostly the result of a dominance of increased evapotranspiration over the seasonal precipitation shifts, with ensemble mean runoff reductions of -1, -6, and -11 percent for the A2 ensembles, and 0, -7, and -8 percent for the B1 ensembles. These hydrological changes were reflected in reservoir system performance. Average total basin reservoir storage generally declined, however there was a large range across the ensembles. Releases from Glen Canyon Dam to the Lower Basin (mandated by the Colorado River Compact) were reduced for all periods and both emissions scenarios in the ensemble mean. The fraction of years in which shortages occurred increased by approximately 20% by period 3 in for both emissions scenarios, and the average shortage increased to a maximum of 3.7 BCM/yr for the period 3 A2 ensemble average. Hydropower output was reduced in the ensemble mean for all time periods and both emissions scenarios.

Christensen, N.; Lettenmaier, D. P.

2006-12-01

76

Seasonal River Flow Forecasting Using Multi-model Ensemble Climate Data  

NASA Astrophysics Data System (ADS)

Developing skilful seasonal forecasting of river flows is important for many societal applications. Long-lead forecasts have potential to aid water management decision making and preparation for human response to hydrological extremes. The seasonal prediction of river flows has been a topic of increasing interest due to the recent 2004-06 drought and 2007 floods experienced in the UK. We compare the relative skill of predictions of river flow using: (1) a multi-Global Climate Model (GCM) ensemble data set and (2) downscaled multi-GCM data as input to a hydrological model. The period considered is 1980- 2001. The River Dyfi basin in West Wales, UK is the focus of this research. This basin is near natural, hence the climate-flow signal should be clearer. The DEMETER project is the source of the multi-model climate data, and this consists of 7 GCMs each with 9 ensemble members. Hindcasts with lead times up to 6 months are available from 1st February, 1st May, 1st August and 1st November initial conditions. Each hindcast was split into the first 3 and last 3 months, and the subsequent concatenation of the split hindcasts produced 2 time series (total of 7×9×2 ensemble series), which were run through the Probability Distributed Model (PDM). PDM is a lumped rainfall-runoff model that transforms rainfall and potential evaporation data to river flow at the basin outlet. PDM was calibrated with observations from 1980-1990, and then validated from 1991-2001. The coarse resolution of the DEMETER data (standardised to 2.5° × 2.5° resolution) means that the atmospheric motions at sub-grid scales are not captured by the models. The large spatial disparity between the GCM grids and the scale of the study (471.3 km2) lead to underestimation of precipitation by DEMETER models. This difference is addressed through the use of a statistical downscaling tool, the Statistical Downscaling Model (SDSM). The SDSM was calibrated on the ERA-40 re-analysis data set (from the ECMWF), as it provides one of the best estimates of the real atmosphere (a spatial resolution comparable to that of DEMETER models was used for this calibration). Multiple linear regression models (one per month) were used to link DEMETER predictors with basin scale rainfall, and a stochastic weather generator produced downscaled rainfall time series. These new downscaled series are designed to more closely represent catchment rainfall. DEMETER precipitation data and downscaled data are inputted to the PDM to determine their relative river flow modelling skill. Preliminary results show that simulated river flows driven by DEMETER do underestimate the observed flow. The downscaled series improves the hindcast skill, and little reduction in skill is seen when using a longer lead time hindcast. The results drawn from this research will have major implications for assessing (1) the potential skill expected from large scale GCM output, and (2) the relative improvement in skill of using downscaled versus non- downscaled precipitation data. Also, it will be possible to ascertain any degradation in the seasonal hindcast skill when using longer lead times.

Lavers, D.; Prudhomme, C.; Hannah, D.; Troccoli, A.

2007-12-01

77

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research  

NASA Astrophysics Data System (ADS)

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

78

'Lazy' quantum ensembles  

NASA Astrophysics Data System (ADS)

We compare different strategies aimed to prepare an ensemble with a given density matrix ?. Preparing the ensemble of eigenstates of ? with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ?, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ?. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error.

Parfionov, George; Zapatrin, Romàn

2006-08-01

79

Input Decimated Ensembles  

NASA Technical Reports Server (NTRS)

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

2001-01-01

80

Morphing Ensemble Kalman Filters  

E-print Network

A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. The ensemble members are represented as the composition of one common state with a spatial transformation, called registration mapping, plus a residual. A fully automatic registration method is used that requires only gridded data, so the features in the model state do not need to be identified by the user. The morphing EnKF operates on a transformed state consisting of the registration mapping and the residual. Essentially, the morphing EnKF uses intermediate states obtained by morphing instead of linear combinations of the states.

Beezley, Jonathan D

2007-01-01

81

Downscaling the chemical oxygen demand test.  

PubMed

The usefulness of the standard chemical oxygen demand (COD) test for water characterization is offset to some extent by its requirement for highly toxic or expensive Cr, Ag, and Hg species. In addition, oxidation of the target samples by chromate requires a 2-3 h heating step. We have downscaled this method to obtain a reduction of up to ca. 80% in the use and generation of toxic residues and a time reduction of up to ca. 67%. This also translates into considerable energy savings by reducing the time required for heating as well as costly labour time. Such reductions can be especially important for analytical laboratories with heavy loads of COD analyses. Numerical results obtained with the standard COD method for laboratory KHP samples (potassium hydrogen phthalate) show an average relative error of 1.41% vs. an average of 2.14% obtained with the downsized or small-scale version. The average % standard deviation when using the former is 2.16% vs. 3.24% obtained with the latter. When analysing municipal wastewater samples, the relative error is smaller for the proposed small-scale method than for the standard method (0.05 vs. 0.58, respectively), and the % std. dev. is 1.25% vs. 1.06%. The results obtained with various industrial wastewaters show good agreement with those obtained using the standard method. Chloride ions do not interfere at concentrations below 2000 mg Nacl/L. This highly encouraging proof-of-concept offers a potentially alternative greener approach to COD analysis. PMID:24701932

Carbajal-Palacios, Patricia; Balderas-Hernandez, Patricia; Ibanez, Jorge G; Roa-Morales, Gabriela

2014-01-01

82

UNCORRECTEDPROOF 1 Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil  

E-print Network

UNCORRECTEDPROOF 1 Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil online xxxx Keywords: Downscaling Disaggregation Soil moisture Evaporative fraction NAFE SMOS MODIS 10 11 A deterministic approach for downscaling 40 km resolution Soil Moisture and Ocean Salinity (SMOS) 12 observations

Boyer, Edmond

83

Validating a regional climate model's downscaling ability for East Asian summer monsoonal interannual variability  

E-print Network

Validating a regional climate model's downscaling ability for East Asian summer monsoonal of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based-level meridional moisture transport in the East Asian summer monsoon. For precip- itation downscaling, the RCM

Xue, Yongkang

84

Downscaling Thermal Infrared Radiance for Subpixel Land Surface Temperature Retrieval  

PubMed Central

Land surface temperature (LST) retrieved from satellite thermal sensors often consists of mixed temperature components. Retrieving subpixel LST is therefore needed in various environmental and ecological studies. In this paper, we developed two methods for downscaling coarse resolution thermal infrared (TIR) radiance for the purpose of subpixel temperature retrieval. The first method was developed on the basis of a scale-invariant physical model on TIR radiance. The second method was based on a statistical relationship between TIR radiance and land cover fraction at high spatial resolution. The two methods were applied to downscale simulated 990-m ASTER TIR data to 90-m resolution. When validated against the original 90-m ASTER TIR data, the results revealed that both downscaling methods were successful in capturing the general patterns of the original data and resolving considerable spatial details. Further quantitative assessments indicated a strong agreement between the true values and the estimated values by both methods.

Liu, Desheng; Pu, Ruiliang

2008-01-01

85

On regional dynamical downscaling for the assessment and projection of temperature and precipitation extremes across Tasmania, Australia  

NASA Astrophysics Data System (ADS)

The ability of an ensemble of six GCMs, downscaled to a 0.1° lat/lon grid using the Conformal Cubic Atmospheric Model over Tasmania, Australia, to simulate observed extreme temperature and precipitation climatologies and statewide trends is assessed for 1961-2009 using a suite of extreme indices. The downscaled simulations have high skill in reproducing extreme temperatures, with the majority of models reproducing the statewide averaged sign and magnitude of recent observed trends of increasing warm days and warm nights and decreasing frost days. The warm spell duration index is however underestimated, while variance is generally overrepresented in the extreme temperature range across most regions. The simulations show a lower level of skill in modelling the amplitude of the extreme precipitation indices such as very wet days, but simulate the observed spatial patterns and variability. In general, simulations of dry extreme precipitation indices are underestimated in dryer areas and wet extremes indices are underestimated in wetter areas. Using two SRES emissions scenarios, the simulations indicate a significant increase in warm nights compared to a slightly more moderate increase in warm days, and an increase in maximum 1- and 5- day precipitation intensities interspersed with longer consecutive dry spells across Tasmania during the twenty-first century.

White, Christopher J.; McInnes, Kathleen L.; Cechet, Robert P.; Corney, Stuart P.; Grose, Michael R.; Holz, Gregory K.; Katzfey, Jack J.; Bindoff, Nathaniel L.

2013-12-01

86

Beta-ensembles with covariance  

E-print Network

This thesis presents analytic samplers for the [beta]-Wishart and [beta]-MANOVA ensembles with diagonal covariance. These generalize the [beta]-ensembles of Dumitriu-Edelman, Lippert, Killip-Nenciu, Forrester-Rains, and ...

Dubbs, Alexander

2014-01-01

87

Sampling unitary invariant ensembles  

E-print Network

We develop an algorithm for sampling from the unitary invariant random matrix ensembles. The algorithm is based on the representation of their eigenvalues as a determinantal point process whose kernel is given in terms of orthogonal polynomials. Using this algorithm, statistics beyond those known through analysis are calculable through Monte Carlo simulation. Unexpected phenomena are observed in the simulations.

Sheehan Olver; Raj Rao Nadakuditi; Thomas Trogdon

2014-04-01

88

A multimodel ensemble approach to assessment of climate change impacts on the hydrology and water resources of the Colorado River Basin  

NASA Astrophysics Data System (ADS)

Implications of 21st century climate change on the hydrology and water resources of the Colorado River Basin were assessed using a multimodel ensemble approach in which downscaled and bias corrected output from 11 General Circulation Models (GCMs) was used to drive macroscale hydrology and water resources models. Downscaled climate scenarios (ensembles) were used as forcings to the Variable Infiltration Capacity (VIC) macroscale hydrology model, which in turn forced the Colorado River Reservoir Model (CRMM). Ensembles of downscaled precipitation and temperature, and derived streamflows and reservoir system performance were assessed through comparison with current climate simulations for the 1950-1999 historical period. For each of the 11 GCMs, two emissions scenarios (IPCC SRES A2 and B1, corresponding to relatively unconstrained growth in emissions, and elimination of global emissions increases by 2100) were represented. Results for the A2 and B1 climate scenarios were divided into three periods: 2010-2039, 2040-2069, and 2070-2099. The mean temperature change averaged over the 11 ensembles for the Colorado basin for the A2 emission scenario ranged from 1.2 to 4.4°C for periods 1-3, and for the B1 scenario from 1.3 to 2.7°C. Precipitation changes were modest, with ensemble mean changes ranging from -1 to -2% for the A2 scenario, and from +1 to -1% for the B1 scenario. An analysis of seasonal precipitation patterns showed that most GCMs had modest reductions in summer precipitation and increases in winter precipitation. Derived April 1 snow water equivalent declined for all ensemble members and time periods, with maximum (ensemble mean) reductions of 38% for the A2 scenario in period 3. Runoff changes were mostly the result of a dominance of increased evapotranspiration over the seasonal precipitation shifts, with ensemble mean runoff changes of -1, -6, and -11% for the A2 ensembles, and 0, -7, and -8% for the B1 ensembles. These hydrological changes were reflected in reservoir system performance. Average total basin reservoir storage and average hydropower production generally declined, however there was a large range across the ensembles. Releases from Glen Canyon Dam to the Lower Basin were reduced for all periods and both emissions scenarios in the ensemble mean. The fraction of years in which shortages occurred increased by approximately 20% by period 3 for both emissions scenarios.

Christensen, N. S.; Lettenmaier, D. P.

2007-07-01

89

Downscaling pollentransport networks to the level of individuals  

E-print Network

Downscaling pollen­transport networks to the level of individuals Cristina Tur1 *, Beatriz at the individual level. In fact, nodes in traditional species- based interaction networks are aggregates of individuals establishing the actual links observed in nature. Thus, emergent properties of interaction

Traveset, Anna

90

Downscaling, Data Fusion, and Data Assimilation in Hydro-meteorology  

E-print Network

Downscaling, Data Fusion, and Data Assimilation in Hydro-meteorology of precipitation #12;Multi-sensor Data Fusion Problem · Optimal merging of multi-sensor precipitation observations for fusion of rainfall data ( e.g. Gorenburg, McLaughlin, and Entekhabi 2001; Tustison, Harris and Foufoula

91

Downscaling modeling of the aggressiveness of mosquitoes vectors of diseases  

Microsoft Academic Search

The aggressiveness of mosquitoes towards humans is often measured on different time scales but never continuously because of the amount of work required in practice. We developed a general downscaling method to simulate the aggressiveness of mosquitoes over short and long time periods based on a series of imbricated generalized linear models that link aggressiveness with explicative environmental variables according

Karine Chalvet-Monfray; Philippe Sabatier; Dominique J. Bicout

2007-01-01

92

Evaluating the utility of dynamical downscaling in agricultural impacts projections  

NASA Astrophysics Data System (ADS)

The need to understand the future impacts of climate change has driven the increasing use of dynamical downscaling to produce fine-spatial-scale climate projections for impacts models. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield. Our results suggest that it does not. We simulate U.S. maize yields under current and future CO2 concentrations with the widely-used DSSAT crop model, driven by a variety of climate inputs including two general circulation models (GCMs), each in turn downscaled by two regional climate models (RCMs). We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven yields are essentially indistinguishable in all scenarios (<10% discrepancy in national yield, equivalent to error from observations). While RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kms) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the added value of dynamically downscaling raw GCM output for impacts assessments may not justify its computational demands, and that some rethinking of downscaling methods is warranted.

Glotter, M.; Elliott, J. W.; McInerney, D. J.; Moyer, E. J.

2013-12-01

93

ORIGINAL ARTICLE Climate downscaling effects on predictive ecological models  

E-print Network

the scale of climate change and sea-level rise threats to human and natural systems (IPCC 2007), forecasting envelope model Á Downscaling Á Species distribution model Á Florida Á Endangered species Introduction Given Research and Education Center, University of Florida, 3205 College Avenue, Fort Lauderdale, FL 33314, USA e

Mazzotti, Frank

94

Evaluation of a vector autoregressive approach for downscaling  

NASA Astrophysics Data System (ADS)

Statisical downscaling has become a well-established tool in regional and local impact assessments over the last few years. Robust and universal downscaling methods are required to reliably correct the spatial and temporal structures from coarse models. In this study we set up and evaluate the application of VAR-models for automated temperature and precipitation downscaling. VAR-models belong to the vectorial regression-techniques, that include autoregressive effects of the considered time series. They might be seen as an extension of univariate time-series analysis to multivariate perspective. Including autoregressive effects is one of the great advantages of this method, but also includes some pitfalls. Before the model can be applied the structure of the data must be carfully examined and require appropriate data preprocessing. We study in detail different preprocessing techniques and the possibility of the automatization. The proposed method has been applied and evaluated to temperature and precipitation data in the Rhineland region (Germany) and Svalbard. The large-scale atmospheric data are derived from ERA-40 as NCEP/NCAR reanalysis. These datasets offer the possibility to determine the applicability of VAR-models in a downscaling approach, their need for data-preparation techniques and the possibility of an automatization of an approach based on these models.

Salonen, Sebastian; Sauter, Tobias

2014-05-01

95

Stepwise analogue downscaling for hydrology (SANDHY): validation experiments over France  

NASA Astrophysics Data System (ADS)

Statistical downscaling aims at finding relationships between local precipitation (predictand) and large-scale predictor fields, in various contexts, from medium-term forecasting to climate change impact studies. One of the challenges of statistical downscaling in a climate change context is that the predictor-predictand relationship should still be valid under climate change conditions. A minimum requirement is therefore to test the performance of the downscaling method on independent data under current climate conditions. The downscaling method considered is the Stepwise ANalog Downscaling method for HYdrology (SANDHY). ERA-40 reanalysis data are used as large scale predictors and daily precipitation from the French near surface reanalysis (Safran) as predictand. Two 20-year periods have been selected from the common archive period of the two data sources: 1958-1978 ('early') and 1982-2002 ('late'). SANDHY has been optimised over the late period in terms of geopotential predictor domains individually for 608 target zones covering France. The validation setup consists of 4 experiments, that all use the parameters as optimised for the late period and that are compared in terms of continous ranked probability skill score (CRPSS) with climatology as reference: Reference simulation. A simulation of the late period is performed using the late period as an archive for searching the analogue dates, thus representing the best possible case. The CRPSS shows a spatial distribution similar to the one of the mean precipitation. Out-of-sample validation. The early period is simulated using the late period as an archive for searching the analogue dates. The idea is to simulate a period whose local data is not 'known' by the model as it would be the case in any application. The average skill loss compared to the reference simulation is reasonable with some more skill loss in the northern part of the country and no loss in the southeastern part. Alternative archive. The late period is simulated using the early period as an archive for the analogue search. Using the alternative archive leads to small and spatially uniform skill loss compared to the reference simulation. Imperfect predictor domains. The early period is simulated using the early period as an archive for the analogue search. The results are very similar to the out-of-sample validation in terms of mean skill loss and spatial distribution. The results of experiment 2 indicate that SANDHY is quite robust at most locations. Experiment 3 shows that both archives are suitable for downscaling. Experiment 4 shows that the skill loss observed in experiment 2 stems rather from the imperfect predictor domains than from the imperfect archive. Overall the results increase the confidence in applying SANDHY for downscaling in various contexts over France.

Radanovics, Sabine; Vidal, Jean-Philippe; Sauquet, Eric; Ben Daoud, Aurélien; Bontron, Guillaume

2014-05-01

96

An approximate energy cycle for inter-member variability in ensemble simulations of a regional climate model  

NASA Astrophysics Data System (ADS)

The presence of internal variability (IV) in ensembles of nested regional climate model (RCM) simulations is now widely acknowledged in the community working on dynamical downscaling. IV is defined as the inter-member spread between members in an ensemble of simulations performed by a given RCM driven by identical lateral boundary conditions (LBC), where different members are being initialised at different times. The physical mechanisms responsible for the time variations and structure of such IV have only recently begun to receive attention. Recent studies have shown empirical evidence of a close parallel between the energy conversions associated with the time fluctuations of IV in ensemble simulations of RCM and the energy conversions taking place in weather systems. Inspired by the classical work on global energetics of weather systems, we sought a formulation of an energy cycle for IV that would be applicable for limited-area domain. We develop here a novel formalism based on local energetics that can be applied to further our understanding IV. Prognostic equations for ensemble-mean kinetic energy and available enthalpy are decomposed into contributions due to ensemble-mean variables (EM) and those due to deviations from the ensemble mean (IV). Together these equations constitute an energy cycle for IV in ensemble simulations of RCM. Although the energy cycle for IV was developed in a context entirely different from that of energetics of weather systems, the exchange terms between the various reservoirs have a rather similar mathematical form, which facilitates some interpretations of their physical meaning.

Nikiéma, Oumarou; Laprise, René

2013-08-01

97

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.  

NASA Astrophysics Data System (ADS)

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

98

The Ensembl Analysis Pipeline  

PubMed Central

The Ensembl pipeline is an extension to the Ensembl system which allows automated annotation of genomic sequence. The software comprises two parts. First, there is a set of Perl modules (“Runnables” and “RunnableDBs”) which are `wrappers' for a variety of commonly used analysis tools. These retrieve sequence data from a relational database, run the analysis, and write the results back to the database. They inherit from a common interface, which simplifies the writing of new wrapper modules. On top of this sits a job submission system (the “RuleManager”) which allows efficient and reliable submission of large numbers of jobs to a compute farm. Here we describe the fundamental software components of the pipeline, and we also highlight some features of the Sanger installation which were necessary to enable the pipeline to scale to whole-genome analysis. PMID:15123589

Potter, Simon C.; Clarke, Laura; Curwen, Val; Keenan, Stephen; Mongin, Emmanuel; Searle, Stephen M.J.; Stabenau, Arne; Storey, Roy; Clamp, Michele

2004-01-01

99

Validation of WRF Downscaling Capabilities Over Western Australia to Detect Rainfall and Temperature Extremes  

NASA Astrophysics Data System (ADS)

When evaluating the merits of regional climate simulations, one of the most compelling arguments for this high resolution, dynamical downscaling approach is its ability to simulate the extremes of temperature and precipitation with greater skill than lower resolution models. A historical (1970-2000), ensemble regional climate simulation using WRF was performed over Western Australia at a 50km, 10km and 5km resolution in order to evaluate the effectiveness of the model in simulating annually extreme climate events as defined by the core climate indices of the CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI). Five temperature and five precipitation indices were chosen and the capacity of the simulation to detect the temporal and spatial structure of these indices was assessed. Validation took place through comparisons to observational CSIRO Australia Water Availability Project (AWAP) daily gridded minimum and maximum temperature and precipitation data and RCM simulations driven by ERA-Interim lateral boundary conditions over the same area. The study is part one of a two part project to examine future changes in extreme temperature and precipitation in the region and the influence of land cover change and anthropogenic greenhouse gases on these changes.

Andrys, J.; Lyons, T.; Kala, J.

2013-12-01

100

Downscaling an Eddy-Resolving Global Model for the Continental Shelf off South Eastern Australia  

NASA Astrophysics Data System (ADS)

The Australian Bluelink collaboration between CSIRO, the Bureau of Meteorology and the Royal Australian Navy has made available to the research community the output of BODAS (Bluelink ocean data assimilation system), an ensemble optimal interpolation reanalysis system with ~10 km resolution around Australia. Within the Bluelink project, BODAS fields are assimilated into a dynamic ocean model of the same resolution to produce BRAN (BlueLink ReANalysis, a hindcast of water properties around Australia from 1992 to 2004). In this study, BODAS hydrographic fields are assimilated into a ~ 3 km resolution Princeton Ocean Model (POM) configuration of the coastal ocean off SE Australia. Experiments were undertaken to establish the optimal strength and duration of the assimilation of BODAS fields into the 3 km resolution POM configuration for the purpose of producing hindcasts of ocean state. It is shown that the resultant downscaling of Bluelink products is better able to reproduce coastal features, particularly velocities and hydrography over the continental shelf off south eastern Australia. The BODAS-POM modelling system is used to provide a high-resolution simulation of the East Australian Current over the period 1992 to 2004. One of the applications that we will present is an investigation of the seasonal and inter-annual variability in the dispersion of passive particles in the East Australian Current. The practical outcome is an estimate of the connectivity of estuaries along the coast of southeast Australia, which is relevant for the dispersion of marine pests.

Roughan, M.; Baird, M.; MacDonald, H.; Oke, P.

2008-12-01

101

Input decimated ensembles  

Microsoft Academic Search

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many\\u000a pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the\\u000a errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers’ performance levels high\\u000a is an important area of research. In

Kagan Tumer; Nikunj C. Oza

2003-01-01

102

Downscaling of land surface temperatures from SEVIRI  

NASA Astrophysics Data System (ADS)

Land surface temperature (LST) determines the radiance emitted by the surface and hence is an important boundary condition of the energy balance. In urban areas, detailed knowledge about the diurnal cycle in LST can contribute to understand the urban heat island (UHI). Although the increased surface temperatures compared to the surrounding rural areas (surface urban heat island, SUHI) have been measured by satellites and analysed for several decades, an operational SUHI monitoring is still not available due to the lack of sensors with appropriate spatiotemporal resolution. While sensors on polar orbiting satellites are still restricted to approx. 100 m spatial resolution and coarse temporal coverage (about 1-2 weeks), sensors on geostationary platforms have high temporal (several times per hour) and poor spatial resolution (>3 km). Further, all polar orbiting satellites have a similar equator crossing time and hence the SUHI can at best be observed at two times a day. A downscaling DS scheme for LST from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) sensor onboard the geostationary meteorological Meteosat 8 to spatial resolutions between 100 and 1000 m was developed and tested for Hamburg. Various data were tested as predictors, including multispectral data and derived indices, morphological parameters from interferometric SAR and multitemporal thermal data. All predictors were upscaled to the coarse resolution approximating the point spread function of SEVIRI. Then empirical relationships between the predictors and LST were derived which are then transferred to the high resolution domain, assuming they are scale invariant. For validation LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Enhanced Thematic Mapper Plus (ETM+) for two dates were used. Aggregated parameters from multi-temporal thermal data (in particular annual cycle parameters and principal components) proved particularly suitable. The results for the highest resolution of 100 m showed a high explained variance (R^2 = 0.71) and relatively low root mean square errors (RMSE = 2.2 K) for the ASTER scene and slightly higher errors (R^2 = 0.73, RMSE = 2.53) for the ETM+ scene. A considerable percentage of the error was systematic due to the different viewing geometry of the sensors (the high resolution LST was overestimated about 1.3 K for ASTER and 0.66 K for ETM+). This shows that DS of SEVIRI LST is possible up to a resolution of 100 m for urban areas and that multitemporal thermal data are particularly suitable as predictors. Further, the scheme was used to produce an entire diurnal cycle in high resolution. While essential characteristics of the diurnal cycle were well reproduced, certain artefacts resulting from the multitemporal predictors from different seasons (like phenology and different water surface temperatures) were generated. Eventually, the bias and its dependence on the viewing geometry and topography are currently investigated.

Bechtel, B.; Zaksek, K.

2013-12-01

103

Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain  

NASA Astrophysics Data System (ADS)

Global Climate Models (GCMs) suggest that rising concentrations of greenhouse gases will have significant implications for climate at global and regional scales. Less certain is the extent to which meteorological processes at individual sites will be affected. So-called downscaling techniques are used to bridge the spatial and temporal resolution gaps between what climate modelers are currently able to provide and what decision-makers require. Among the most important impacts of regional-scale prediction of climate change is to assess how food production and security will be affected. Regional scale precipitation and temperature simulations are crucial to understand how global warming will affect fresh water storage and the ability to grow agricultural crops. Precipitation and temperature downscaling improve the coarse resolution and poor local representation of global climate models and help decision-makers to assess the likely hydrological impacts of climate change, and it would also help crop modelers to generate more realistic climatic-change scenarios. Thus, a spatial downscaling method was developed based on the multiplicative random cascade disaggregation theory, considering a ?-lognormal model describing the rainfall precipitation distribution and using the Mandelbrot-Kahane-Peyriere (MKP) function. In this paper, gridded 15 km resolution rainfall data over a 220 x 220 km section of the Andean Plateau and surroundings, generated by the Weather Research and Forecasting model (WRF), were downscaled to gridded 1 km layers with the Multifractal downscaling technique, complemented by a local heterogeneity filter. The process was tested for daily data over a period of five years (01/01/2001 - 12/31/2005). Specifically, The model parameters were estimated from 5 years of observed daily rainfall data from 18 rain gauges located in the region. A detailed testing of the model was undertaken on the basis of a comparison of the statistical characteristics of the spatial and temporal variability of rainfall between the rainfall fields obtained from the rain gauge network and those generated by the simulation model. The potential advantages of this methodology are discussed.Stochastic Cascade Dynamical Downscaling of Precipitation over Complex Terrain

Posadas, A.; Duffaut, L. E.; Jones, C.; Carvalho, L. V.; Carbajal, M.; Heidinger, H.; Quiroz, R.

2013-12-01

104

Ensemble: Computing Pathway  

NSDL National Science Digital Library

Ensemble is a NSDL Pathways project working to establish a national, distributed digital library for computing education. The project is building a distributed portal providing access to a broad range of existing educational resources for computing while preserving the collections and their associated curation processes. The developers want to encourage contribution, use, reuse, review and evaluation of educational materials at multiple levels of granularity and seek to support the full range of computing education communities including computer science, computer engineering, software engineering, information science, information systems and information technology as well as other areas often called computing + X, or X informatics.

2011-01-05

105

Critical behavior in topological ensembles  

E-print Network

We consider the relation between three physical problems: 2D directed lattice random walks in an external magnetic field, ensembles of torus knots, and 5d Abelian SUSY gauge theory with massless hypermultiplet in $\\Omega$ background. All these systems exhibit the critical behavior typical for the "area+length" statistics of grand ensembles of 2D directed paths. In particular, using the combinatorial description, we have found the new critical behavior in the ensembles of the torus knots and in the instanton ensemble in 5d gauge theory. The relation with the integrable model is discussed.

Bulycheva, K; Nechaev, S

2014-01-01

106

An Introduction to the Downscaled Climate and Hydrology Projections Website  

NSDL National Science Digital Library

These two videos serve as an introduction to the Downscaled Climate and Hydrology Projections website. This website, the result of a collaboration between several federal and non-federal partners, provides access to downscaled climate and hydrology projections for the contiguous United States and parts of Canada and Mexico, derived from contemporary global climate models. In the first video, Dr. Subhrendu Gangopadhyay, hydrologic engineer at the Bureau of Reclamation's Technical Service Center in Denver, introduces the website and provides an overview of the MetEd lesson Preparing Hydro-climate Inputs for Climate Change in Water Resources Planning. This lesson provides necessary background information needed to use the projections site effectively to retrieve climate and hydrology projections data for impacts analysis. In the second video, Dr. Gangopadhyay steps through the process of retrieving projections data using the website. This resource, produced in cooperation between the Bureau of Reclamation and The COMET® Program, is hosted on COMET's YouTube Channel.

Comet

2014-01-28

107

Developing Regionally Downscaled Probabilistic Climate Change Projections for the Southeast Regional Assessment Project  

NASA Astrophysics Data System (ADS)

The Southeast US contains the highest levels of biodiversity in North America outside of the tropics. This is partly due to the climate over the last few millennia, characterized by abundant precipitation, mild temperatures, and low climatic variability. Recently, the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) concluded that it is very likely that humans are largely responsible for increasing the global average surface temperature by 1.0 oC in the 20th century through the release of greenhouse gasses (GHG) such as CO2 into the atmosphere. This warming is expected to continue well into the future and is projected to cause sizeable impacts on managed and unmanaged ecosystems. Thus, mitigation of, and adaptation to the impacts of climate change on ecosystems in the Southeast will likely be the key challenge confronting natural resource managers in the coming decades. Central to this is how to best implement an adaptive management strategy given the large uncertainty associated with climate change projections. This requires a careful treatment of this uncertainty as well as methods to downscale climate projections to the scale of ecosystem processes because of the coarse spatial resolution of the models. To date, most studies use the range of GCM output to represent the full range of projection uncertainty; thus increasing the risk of underestimating structural and parametric uncertainty associated with these projections. This underestimation will then propagate through associated integrated assessments that use climate change projections, leading to overconfident predictions. As a result, decision-makers may insufficiently hedge against the risks associated with extreme climatic events that have a low probability of occurrence, but are high impact events. We address this by developing a suite of regional probabilistic climate change projections for the Southeast Regional Assessment Project (SERAP). Two core climatic datasets are used for base projections: (1) GCM simulations from the IPCC AR4 for fully coupled global-scale climate simulations; and (2) an Earth Model of Intermediate Complexity (EMIC) to sample the parametric uncertainty of key climate system variables such as ocean diffusivity. These datasets are further post-processed through: (1) Bayesian ensemble dressing methods to estimate structural uncertainty and the accuracy of the GCMs; and (2) statistically downscaled simulations forced by boundary conditions from the GCM and EMIC runs. The probabilistic projections generated through these methods form the basis for projecting ecosystem changes in the Southeast over the next century.

Terando, A. J.; Bhat, S.; Haran, M.; Hayhoe, K.; Keller, K.; Tonkonojenkov, R.; Urban, N.

2010-12-01

108

Combining Upscaling and Downscaling of Methane Emissions from Rice Fields: Methodologies and Preliminary Results  

Microsoft Academic Search

The uncertainty in the methane (CH4) source strength of rice fields is among the highest of all sources in the global CH4 budget. Methods to estimate the source strength of rice fields can be divided into two scaling categories: bottom-up (upscaling) and top-down (downscaling). A brief review of upscaling and downscaling methodologies is presented. The combination of upscaling and downscaling

H. A. C. Denier van der Gon; P. M. van Bodegom; S. Houweling; P. H. Verburgt; N. van Breemen

2000-01-01

109

Evaluating the utility of dynamical downscaling in agricultural impacts projections.  

PubMed

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling--nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output--to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections. PMID:24872455

Glotter, Michael; Elliott, Joshua; McInerney, David; Best, Neil; Foster, Ian; Moyer, Elisabeth J

2014-06-17

110

Constrained dynamical downscaling for assessment of climate impacts  

NASA Astrophysics Data System (ADS)

AbstractTo assess climate change impacts on hydrology, conservation biology, and air quality, impact studies typically require future climate data with spatial resolution high enough to resolve urban-rural gradients, complex topography, and sub-synoptic atmospheric phenomena. We present here an approach to dynamical <span class="hlt">downscaling</span> using analysis nudging, where the entire domain is constrained to coarser-resolution parent data. Here meteorology from the North American Regional Reanalysis and the North American Regional Climate Change Assessment Program data archive are used as parent data and <span class="hlt">downscaled</span> with the Advanced Research version of the Weather Research and Forecasting model to a 12 km × 12 km horizontal resolution over the Eastern U.S. Our results show when analysis nudging is applied to all variables at all levels, mean fractional errors relative to parent data are less than 2% for maximum 2 m temperatures, less than 15% for minimum 2 m temperatures, and less than 18% for10 m wind speeds. However, the skill of representing fields that are not nudged, such as boundary layer height and precipitation, is less clear. Our results indicate that though nudging can be a useful tool for consistent, comparable studies of <span class="hlt">downscaling</span> climate for regional and local impacts, which variables are nudged and at what levels should be carefully considered based on the climate impact(s) of study.</p> <div class="credits"> <p class="dwt_author">Harkey, M.; Holloway, T.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">111</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012AGUFMGC41B0966G"> <span id="translatedtitle">Comparative Assessment of Statistical <span class="hlt">Downscaling</span> Methods for Precipitation in Florida</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Several statistical <span class="hlt">downscaling</span> models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by General Circulation Models (GCMs). GCMs in general are capable in capturing the large-scale circulation patterns and correctly model smoothly varying fields such as surface pressure, but it is extremely unlikely that these models properly reproduce non-smooth fields such as precipitation. This paper presents and compares different statistical <span class="hlt">downscaling</span> methods involving Multiple Linear Regression (MLR), Positive Coefficient Regression (PCR), Stepwise Regression (SWR) and Support Vector Machine (SVM) for estimation of rainfall in the state of Florida, USA, which is considered to be a climatically sensitive region. The explanatory variables/predictors used in the current study are mean sea-level pressure, air temperature, geo-potential height, specific humidity, U-wind and V-wind. Principal Component Analysis (PCA) and Fuzzy C-Means (FCM) clustering techniques are used to reduce the dimensionality of the dataset and identify the circulation patterns on precipitation in different clusters. <span class="hlt">Downscaled</span> precipitation data obtained from widely used Bias-Correction Spatial Disaggregation (BCSD) <span class="hlt">downscaling</span> technique is compared along with the other <span class="hlt">downscaling</span> methods. The performance of the models is evaluated using various performance measures and it was found that the SVM model performed better than all the other models in reproducing most monthly rainfall statistics at 18 locations. Output from the third generation Canadian Global Climate Model (CGCM3) GCM for A1B scenario was used for future precipitation projection. For the projection period 2001-2010, MLR was used and evaluated as a substitute to the traditional spatial interpolation linking the variables at the GCM grid to NCEP grid scale. It has been found that the choice of linking variables from GCM to NCEP grid by MLR yielded superior statistics at most of the stations (12 out of 18) and show a better reproduction of the monthly precipitation.</p> <div class="credits"> <p class="dwt_author">Goly, A.; Teegavarapu, R. S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">112</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014CMaPh.332..261B"> <span id="translatedtitle">Edge Universality of Beta <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We prove the edge universality of the beta <span class="hlt">ensembles</span> for any , provided that the limiting spectrum is supported on a single interval, and the external potential is and regular. We also prove that the edge universality holds for generalized Wigner matrices for all symmetry classes. Moreover, our results allow us to extend bulk universality for beta <span class="hlt">ensembles</span> from analytic potentials to potentials in class.</p> <div class="credits"> <p class="dwt_author">Bourgade, Paul; Erdös, László; Yau, Horng-Tzer</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">113</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.umass.edu/music/Choral%20Auditions.UMass.Fall%202009.ver2.pdf"> <span id="translatedtitle">UMassAmherst Choral <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Women's Choir Keep yourself in the music! Make new friends. Be part of our musical family and enrich and women) open to all students. Composed of undergraduate and graduate music majors and non Choir, an <span class="hlt">ensemble</span> of 32-36 singers, is the premier choral <span class="hlt">ensemble</span> in the Department of Music & Dance</p> <div class="credits"> <p class="dwt_author">Massachusetts at Amherst, University of</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">114</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AGUFM.H33E0922B"> <span id="translatedtitle">Expansion of the On-line Archive "Statistically <span class="hlt">Downscaled</span> WCRP CMIP3 Climate Projections"</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Presentation highlights status and plans for a public-access archive of <span class="hlt">downscaled</span> CMIP3 climate projections. Incorporating climate projection information into long-term evaluations of water and energy resources requires analysts to have access to projections at "basin-relevant" resolution. Such projections would ideally be bias-corrected to account for climate model tendencies to systematically simulate historical conditions different than observed. In 2007, the U.S. Bureau of Reclamation, Santa Clara University and Lawrence Livermore National Laboratory (LLNL) collaborated to develop an archive of 112 bias-corrected and spatially disaggregated (BCSD) CMIP3 temperature and precipitation projections. These projections were generated using 16 CMIP3 models to simulate three emissions pathways (A2, A1b, and B1) from one or more initializations (runs). Projections are specified on a monthly time step from 1950-2099 and at 0.125 degree spatial resolution within the North American Land Data Assimilation System domain (i.e. contiguous U.S., southern Canada and northern Mexico). Archive data are freely accessible at LLNL Green Data Oasis (url). Since being launched, the archive has served over 3500 data requests by nearly 500 users in support of a range of planning, research and educational activities. Archive developers continue to look for ways to improve the archive and respond to user needs. One request has been to serve the intermediate datasets generated during the BCSD procedure, helping users to interpret the relative influences of the bias-correction and spatial disaggregation on the transformed CMIP3 output. This request has been addressed with intermediate datasets now posted at the archive web-site. Another request relates closely to studying hydrologic and ecological impacts under climate change, where users are asking for projected diurnal temperature information (e.g., projected daily minimum and maximum temperature) and daily time step resolution. In response, archive developers are adding content in 2010, teaming with Scripps Institution of Oceanography (through their NOAA-RISA California-Nevada Applications Program and the California Climate Change Center) to apply a new daily <span class="hlt">downscaling</span> technique to a sub-<span class="hlt">ensemble</span> of the archive’s CMIP3 projections. The new technique, Bias-Corrected Constructed Analogs, combines the BC part of BCSD with a recently developed technique that preserves the daily sequencing structure of CMIP3 projections (Constructed Analogs, or CA). Such data will more easily serve hydrologic and ecological impacts assessments, and offer an opportunity to evaluate projection uncertainty associated with <span class="hlt">downscaling</span> technique. Looking ahead to the arrival CMIP5 projections, archive collaborators have plans apply both BCSD and BCCA over the contiguous U.S. consistent with CMIP3 applications above, and also apply BCSD globally at a 0.5 degree spatial resolution. The latter effort involves collaboration with U.S. Army Corps of Engineers (USACE) and Climate Central.</p> <div class="credits"> <p class="dwt_author">Brekke, L. D.; Pruitt, T.; Maurer, E. P.; Das, T.; Duffy, P.; White, K.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">115</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.5772N"> <span id="translatedtitle">Stochastic <span class="hlt">downscaling</span> of numerically simulated spatial rain and cloud fields using a transient multifractal approach</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Atmospheric fields can be extremely variable over wide ranges of spatial scales, with a scale ratio of 109-1010 between largest (planetary) and smallest (viscous dissipation) scale. Furthermore atmospheric fields with strong variability over wide ranges in scale most likely should not be artificially split apart into large and small scales, as in reality there is no scale separation between resolved and unresolved motions. Usually the effects of the unresolved scales are modeled by a deterministic bulk formula representing an <span class="hlt">ensemble</span> of incoherent subgrid processes on the resolved flow. This is a pragmatic approach to the problem and not the complete solution to it. These models are expected to underrepresent the small-scale spatial variability of both dynamical and scalar fields due to implicit and explicit numerical diffusion as well as physically based subgrid scale turbulent mixing, resulting in smoother and less intermittent fields as compared to observations. Thus, a fundamental change in the way we formulate our models is required. Stochastic approaches equipped with a possible realization of subgrid processes and potentially coupled to the resolved scales over the range of significant scale interactions range provide one alternative to address the problem. Stochastic multifractal models based on the cascade phenomenology of the atmosphere and its governing equations in particular are the focus of this research. Previous results have shown that rain and cloud fields resulting from both idealized and realistic numerical simulations display multifractal behavior in the resolved scales. This result is observed even in the absence of scaling in the initial conditions or terrain forcing, suggesting that multiscaling is a general property of the nonlinear solutions of the Navier-Stokes equations governing atmospheric dynamics. Our results also show that the corresponding multiscaling parameters for rain and cloud fields exhibit complex nonlinear behavior depending on large scale parameters such as terrain forcing and mean atmospheric conditions at each location, particularly mean wind speed and moist stability. A particularly robust behavior found is the transition of the multiscaling parameters between stable and unstable cases, which has a clear physical correspondence to the transition from stratiform to organized (banded) convective regime. Thus multifractal diagnostics of moist processes are fundamentally transient and should provide a physically robust basis for the <span class="hlt">downscaling</span> and sub-grid scale parameterizations of moist processes. Here, we investigate the possibility of using a simplified computationally efficient multifractal <span class="hlt">downscaling</span> methodology based on turbulent cascades to produce statistically consistent fields at scales higher than the ones resolved by the model. Specifically, we are interested in producing rainfall and cloud fields at spatial resolutions necessary for effective flash flood and earth flows forecasting. The results are examined by comparing <span class="hlt">downscaled</span> field against observations, and tendency error budgets are used to diagnose the evolution of transient errors in the numerical model prediction which can be attributed to aliasing.</p> <div class="credits"> <p class="dwt_author">Nogueira, M.; Barros, A. P.; Miranda, P. M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">116</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFM.A11F0122D"> <span id="translatedtitle">Comparing the skill of precipitation forecasts from high resolution simulations and statistically <span class="hlt">downscaled</span> products in the Australian Snowy Mountains</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Statistically significant improvements to a 'Poor Man's <span class="hlt">Ensemble</span>' (PME) of coarse-resolution numeral precipitation forecast for the Australian Snowy Mountains can be achieved using a clustering algorithm. Daily upwind soundings are classified according to one of four clusters, which are employed to adjust the precipitation forecasts using a linear regression. This approach is a type of 'statistical <span class="hlt">downscaling</span>', in that it relies on a historical relationship between observed and forecast precipitation amounts, and is a computationally cheap and fast way to improve forecast skill. For the 'wettest' class, the root-mean-square error for the one-day forecast was reduced from 26.98 to 17.08 mm, and for the second 'wet' class the improvement was from 8.43 to 5.57 mm. Regressions performed for the two 'dry' classes were not shown to significantly improve the forecast. Statistical measures of the probability of precipitation and the quantitative precipitation forecast were evaluated for the whole of the 2011 winter (May-September). With a 'hit rate' (fraction of correctly-forecast rain days) of 0.9, and a 'false alarm rate' (fraction of forecast rain days which did not occur) of 0.16 the PME forecast performs well in identifying rain days. The precipitation amount is, however systematically under-predicted, with a mean bias of -5.76 mm and RMSE of 12.86 mm for rain days during the 2011 winter. To compare the statistically <span class="hlt">downscaled</span> results with the capabilities of a state of the art numerical prediction system, the WRF model was run at 4 km resolution over the Australian Alpine region for the same period, and precipitation forecasts analysed in a similar manner. It had a hit rate of 0.955 and RMSE of 5.16 mm for rain days. The main reason for the improved performance relative to the PME is that the high resolution of the simulations better captures the orographic forcing due to the terrain, and consequently resolves the precipitation processes more realistically, but case studies of individual events also showed that the choice microphysical parameterisation was very important to precipitation amounts. The WRF model is capable of reasonably good forecasts of the sounding 'class' for Wagga Wagga, with an accuracy of 80% for the first day and 65% for the third day of the forecast, facilitating the use of the PME <span class="hlt">downscaling</span> for a number of forecast days instead of only the day of the sounding.</p> <div class="credits"> <p class="dwt_author">Dai, J.; Chubb, T.; Manton, M.; Siems, S. T.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">117</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://evunix.uevora.pt/~mba/index.html/Araujo_et_al_2005GEB.pdf"> <span id="translatedtitle"><span class="hlt">Downscaling</span> European species atlas distributions to a finer resolution: implications for conservation planning</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Aim One of the limitations to using species' distribution atlases in conservation planning is their coarse resolution relative to the needs of local planners. In this study, a simple approach to <span class="hlt">downscale</span> original species atlas distributions to a finer resolution is outlined. If such a procedure yielded accurate <span class="hlt">downscaled</span> predictions, then it could be an aid to using available distribution</p> <div class="credits"> <p class="dwt_author">Miguel B. Araujo; Wilfried Thuiller; Paul H. Williams; Isabelle Reginster</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">118</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cgd.ucar.edu/cas/adai/papers/Liang_etal_JGR06.pdf"> <span id="translatedtitle">Regional climate model <span class="hlt">downscaling</span> of the U.S. summer climate and future change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">has important consequences for future projections of regional climate changes. For both the presentRegional climate model <span class="hlt">downscaling</span> of the U.S. summer climate and future change Xin-Zhong Liang,1 the <span class="hlt">downscaling</span> impact on regional climate changes. It is shown that the CMM5 generates climate change patterns</p> <div class="credits"> <p class="dwt_author">Dai, Aiguo</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">119</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/991999"> <span id="translatedtitle"><span class="hlt">Downscaling</span> socioeconomic and emissions scenarios for global environmental change research:a review</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Abstract: Global change research encompasses global to local scale analysis. Impacts analysis in particular often requires spatial <span class="hlt">downscaling</span>, whereby socio-economic and emissions variables specified at relatively large spatial scales are translated to values at a country or grid level. The methods used for spatial <span class="hlt">downscaling</span> are reviewed, classified, and current applications discussed.</p> <div class="credits"> <p class="dwt_author">Van Vuuren, Detlet; Smith, Steven J.; Riahi, Keywan</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">120</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.engr.colostate.edu/~ramirez/ce_old/projects/Kang-Ramirez-Downscaling.pdf"> <span id="translatedtitle">A coupled stochastic spacetime intermittent random cascade model for rainfall <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">is applied to <span class="hlt">downscale</span> summer daily rainfall for the central United States from a scale of 256 km to a scaleA coupled stochastic spacetime intermittent random cascade model for rainfall <span class="hlt">downscaling</span> Boosik; published 21 October 2010. [1] Analysis of Next Generation Weather Radar rainfall data indicates</p> <div class="credits"> <p class="dwt_author">Ramírez, Jorge A.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_5");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return 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<img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">121</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.agu.org/journals/wr/wr1007/2009WR008423/2009WR008423.pdf"> <span id="translatedtitle">Development and Application of a Multisite Rainfall Stochastic <span class="hlt">Downscaling</span> Framework for Climate Change Impact Assessment</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The coarse resolution of general circulation models (GCMs) necessitates use of <span class="hlt">downscaling</span> approaches for transfer of GCM output to finer spatial resolutions for climate change impact assessment studies. This paper presents a stochastic <span class="hlt">downscaling</span> framework for simulation of multisite daily rainfall occurrences and amounts that strive to maintain persistence attributes that are consistent with the observed record. At site, rainfall</p> <div class="credits"> <p class="dwt_author">R. Mehrotra; Ashish Sharma</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">122</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.nrcse.washington.edu/pdf/trs21_markov.pdf"> <span id="translatedtitle">A hidden Markov model for <span class="hlt">downscaling</span> synoptic atmospheric patterns to precipitation amounts</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">. The presence of the hidden states simpli es the spatio-temporal structure of the precipitation process. WeA hidden Markov model for <span class="hlt">downscaling</span> synoptic atmospheric patterns to precipitation amounts Enrica;A hidden Markov model for <span class="hlt">downscaling</span> synoptic atmospheric patterns to precipitation amounts Enrica</p> <div class="credits"> <p class="dwt_author">Washington at Seattle, University of</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">123</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cerfacs.fr/globc/publication/technicalreport/2009/dsclim_doc.pdf"> <span id="translatedtitle">dsclim: A software package to <span class="hlt">downscale</span> climate scenarios at regional scale using a weather-typing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">dsclim: A software package to <span class="hlt">downscale</span> climate scenarios at regional scale using a weather et al. (2006). This methodology has already been used to provide <span class="hlt">downscaled</span> climate scenarios over this methodology in an easier-to-use and configurable software package. This report presents the first version</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">124</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://hal.archives-ouvertes.fr/docs/00/39/04/30/PDF/merlin_ieee08_preprint.pdf"> <span id="translatedtitle">Passive microwave soil moisture <span class="hlt">downscaling</span> using evaporative fraction Olivier Merlin1</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">DRAFT 1 Passive microwave soil moisture <span class="hlt">downscaling</span> using evaporative fraction Olivier Merlin1 approaches for <span class="hlt">downscaling</span> (disaggregation) passive microwave derived soil moisture from coarse resolution L to generate a 500m "coarse-scale" passive microwave pixel. The coarse-scale derived soil moisture</p> <div class="credits"> <p class="dwt_author">Paris-Sud XI, Université de</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">125</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.atmos.washington.edu/~salathe/papers/downscale/yakima.pdf"> <span id="translatedtitle">Comparison of Various Precipitation <span class="hlt">Downscaling</span> Methods for the Simulation of Streamflow in a Rainshadow River Basin*</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Comparison of Various Precipitation <span class="hlt">Downscaling</span> Methods for the Simulation of Streamflow simulations of precipitation from climate models lack sufficient resolution and contain large biases that make, the effectiveness of several methods to <span class="hlt">downscale</span> large-scale precipitation is examined. To facilitate comparisons</p> <div class="credits"> <p class="dwt_author">Salathé Jr., Eric P.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">126</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48897043"> <span id="translatedtitle">Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and <span class="hlt">downscaling</span> methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the <span class="hlt">downscaling</span> relationship (DSR) used for such regional predictions has been assumed</p> <div class="credits"> <p class="dwt_author">Deepashree Raje; P. P. Mujumdar</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">127</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42394577"> <span id="translatedtitle">Estimating Climate-Change Impacts on Colorado Plateau Snowpack Using <span class="hlt">Downscaling</span> Methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This study develops observed climate-based <span class="hlt">downscaling</span> transfer functions that are used with general circulation model (GCM) output to assess potential global-change impacts on Upper Colorado Plateau, USA, water resources. Daily automated snow water equivalent stations are used with 700 mb atmospheric circulation to determine empirical transfer functions. <span class="hlt">Downscaling</span> methodologies using multiple regression and neural networks are evaluated, with the neural</p> <div class="credits"> <p class="dwt_author">David L. McGinnis</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">128</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.7362B"> <span id="translatedtitle"><span class="hlt">Downscaling</span> of rainfall in Peru using Generalised Linear Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the <span class="hlt">downscaling</span> model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim <span class="hlt">downscaling</span> model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim <span class="hlt">downscaling</span> model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.</p> <div class="credits"> <p class="dwt_author">Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">129</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.2551I"> <span id="translatedtitle">A new project on development and application of comprehensive <span class="hlt">downscaling</span> methods over Hokkaido.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A new project on development and application of comprehensive <span class="hlt">downscaling</span> methods over Hokkaido started as one of the branches of "Research Program on climate change adaptation" funded by Ministry of Education, Sports, Culture, Science, and Technology of Japan in 2010. Our group will develop two new <span class="hlt">downscaling</span> algorithms in order to get more information on the uncertainty of high/low temperatures or heavy rainfall. Both of the algorithms called "sampling <span class="hlt">downscaling</span>" and "hybrid <span class="hlt">downscaling</span>" are based upon the mixed use of statistical and dynamical <span class="hlt">downscaling</span> ideas. Another point of the project is to evaluate the effect of land-use changes in Hokkaido, where the major pioneering began only about a century ago. Scientific outcomes on climate changes in Hokkaido from the project will be provided to not only public sectors in Hokkaido but also people who live in Hokkaido through a graphical-user-interface system just like a weather forecast system in a forecast-center's webpage.</p> <div class="credits"> <p class="dwt_author">Inatsu, M.; Yamada, T. J.; Sato, T.; Nakamura, K.; Matsuoka, N.; Komatsu, A.; Pokhrel, Y. N.; Sugimoto, S.; Miyazaki, S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">130</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/750094"> <span id="translatedtitle"><span class="hlt">Ensembl</span> 2002: accommodating comparative genomics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">ABSTRACT The,<span class="hlt">Ensembl,(http:\\/\\/www.ensembl</span>.org\\/) database project,provides,a,bioinformatics,framework,to organise,biology,around,the,sequences,of large genomes.,It is a comprehensive,source,of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web,site or as,flat files. <span class="hlt">Ensembl</span>,also,integrates manually,annotated,gene,structures,from,external sources,where,available. As well as being,one,of the leading sources of genome annotation, <span class="hlt">Ensembl</span> is an,open,source,software,engineering,project,to develop,a portable,system,able to handle,very large genomes,and associated,requirements.,These range from,sequence,analysis,to data storage,and,visua- lisation and,installations,exist around,the world,in</p> <div class="credits"> <p class="dwt_author">Michele E. Clamp; T. Daniel Andrews; Daniel Barker; Paul Bevan; Graham Cameron; Yuan Chen; Laura Clarke; Tony Cox; James A. Cuff; Val Curwen; Thomas Down; Richard Durbin; Eduardo Eyras; James Gilbert; Martin Hammond; Tim J. P. Hubbard; Arek Kasprzyk; Damian Keefe; Heikki Lehväslaiho; V. Iyer; Craig Melsopp; Emmanuel Mongin; Roger Pettett; Simon C. Potter; Alastair Rust; Esther Schmidt; Stephen M. J. Searle; Guy Slater; James Smith; William Spooner; Arne Stabenau; Jim Stalker; Elia Stupka; Abel Ureta-vidal; Imre Vastrik; Ewan Birney</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">131</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhLA..378..319O"> <span id="translatedtitle">Deformed Ginibre <span class="hlt">ensembles</span> and integrable systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We consider three Ginibre <span class="hlt">ensembles</span> (real, complex and quaternion-real) with deformed measures and relate them to known integrable systems by presenting partition functions of these <span class="hlt">ensembles</span> in form of fermionic expectation values. We also introduce double deformed Dyson-Wigner <span class="hlt">ensembles</span> and compare their fermionic representations with those of Ginibre <span class="hlt">ensembles</span>.</p> <div class="credits"> <p class="dwt_author">Orlov, A. Yu.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">132</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=music+AND+education+AND+funding&pg=3&id=EJ640050"> <span id="translatedtitle">Is It Curtains for Traditional <span class="hlt">Ensembles</span>?</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">Focuses on traditional music <span class="hlt">ensembles</span> (orchestra, bands, and choir) discussing such issues as the affects of block scheduling and how to deal with scheduling issues, the effects of funding on large <span class="hlt">ensemble</span> programs, nontraditional <span class="hlt">ensembles</span> in music programs, and trying to teach the National Standards for Music Education within a large <span class="hlt">ensemble</span>.…</p> <div class="credits"> <p class="dwt_author">Van Zandt, Kathryn</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">133</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://faculty.arts.ubc.ca/afisher/EME/EME_syllabus_2012W.pdf"> <span id="translatedtitle">Music 157A, 557: Early Music <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Music 157A, 557: Early Music <span class="hlt">Ensemble</span> 2012 Early Music <span class="hlt">Ensemble</span> is a mixed instrumental/vocal <span class="hlt">ensemble</span> specializing in the performance of music's musical strengths and to help assign each student to an appropriate <span class="hlt">ensemble</span>. We will ask each student</p> <div class="credits"> <p class="dwt_author">Pulfrey, David L.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">134</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFMGC51A0729P"> <span id="translatedtitle">New Daily <span class="hlt">Downscaled</span> Information at the "Bias-Corrected <span class="hlt">Downscaled</span> WCRP CMIP3 Climate Projections" online archive</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recent efforts have generated a new empirical <span class="hlt">downscaling</span> technique that is well-positioned to inform climate change vulnerability assessments for ecosystems as well as studies on future storm and flood frequency. The technique combines bias-correction (BC) of general circulation model (GCM) outputs with a constructed analogs approach (CA) for spatially <span class="hlt">downscale</span> the daily solutions from GCM simulations. These combined steps are referred to as BCCA. A recent methods intercomparison (Maurer et al. 2010, HESS, 14:1125-1139) shows that BCCA outperforms CA and the archive's current underlying methodology (BCSD, Wood et al. 2002) when applied to NCEP/NCAR Reanalysis. Given how BCCA is designed to translate daily sequences from GCM simulations, it offers the opportunity to provide <span class="hlt">downscaled</span> projection information on diurnal temperature range (relevant to ecohydrological investigations) and interarrival frequencies of daily to multi-day precipitation events. The information on diurnal temperature range also has significance to watershed hydrologic studies in arid to semi-arid regions, where evapotranspiration (ET) is the dominant fate of precipitation and simulation of ET processes is sensitive to diurnal temperature range. Recognizing these benefits, archive collaborators initiated an effort to develop a daily BCCA CMIP3 data archive that complements the archive's existing monthly BCSD CMIP3 dataset. The two datasets' have the following attributes: -- Space: BCSD coverage = NLDAS domain), resolution = 1/8°; BCCA has same attributes -- Time: BCSD period = GCM-simulated 1950-2099, BCCA has three nested periods based on common availability of daily GCM outputs at PCMDI (1961-2000, 2045-2064, and 2080-2099) -- Variables: BCSD has been performed for monthly mean temperature and precipitation; BCCA has been performed for daily minimum and maximum temperature and precipitation. Presentation highlights BCCA implementation for archive expansions, illustrates key differences in BCCA and BCSD data products and highlights the archive collaborators' future hydrologic assessment plans informed by the BCCA products.</p> <div class="credits"> <p class="dwt_author">Pruitt, T.; Thrasher, B.; Das, T.; Maurer, E. P.; Duffy, P.; Long, J.; Brekke, L. D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">135</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014JChPh.141k4110F"> <span id="translatedtitle">Quantum Gibbs <span class="hlt">ensemble</span> Monte Carlo</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs <span class="hlt">ensemble</span> Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs <span class="hlt">ensemble</span> Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of 4He in two dimensions.</p> <div class="credits"> <p class="dwt_author">Fantoni, Riccardo; Moroni, Saverio</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">136</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012AGUFMGC31D..02K"> <span id="translatedtitle">Century long observation constrained global dynamic <span class="hlt">downscaling</span> and hydrologic implication</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">It has been suggested that greenhouse gas induced warming climate causes the acceleration of large scale hydrologic cycles, and, indeed, many regions on the Earth have been suffered by hydrologic extremes getting more frequent. However, historical observations are not able to provide enough information in comprehensive manner to understand their long-term variability and/or global distributions. In this study, a century long high resolution global climate data is developed in order to break through existing limitations. 20th Century Reanalysis (20CR) which has relatively low spatial resolution (~2.0°) and longer term availability (140 years) is dynamically <span class="hlt">downscaled</span> into global T248 (~0.5°) resolution using Experimental Climate Prediction Center (ECPC) Global Spectral Model (GSM) by spectral nudging data assimilation technique. Also, Global Precipitation Climatology Centre (GPCC) and Climate Research Unit (CRU) observational data are adopted to reduce model dependent uncertainty. <span class="hlt">Downscaled</span> product successfully represents realistic geographical detail keeping low frequency signal in mean state and spatiotemporal variability, while previous bias correction method fails to reproduce high frequency variability. Newly developed data is used to investigate how long-term large scale terrestrial hydrologic cycles have been changed globally and how they have been interacted with various climate modes, such as El-Niño Southern Oscillation (ENSO) and Atlantic Multidecadal Oscillation (AMO). As a further application, it will be used to provide atmospheric boundary condition of multiple land surface models in the Global Soil Wetness Project Phase 3 (GSWP3).</p> <div class="credits"> <p class="dwt_author">Kim, H.; Yoshimura, K.; Chang, E.; Famiglietti, J. S.; Oki, T.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">137</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://dspace.mit.edu/handle/1721.1/47844"> <span id="translatedtitle"><span class="hlt">Ensemble</span> regression : using <span class="hlt">ensemble</span> model output for atmospheric dynamics and prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary"><span class="hlt">Ensemble</span> regression (ER) is a linear inversion technique that uses <span class="hlt">ensemble</span> statistics from atmospheric model output to make dynamical inferences and forecasts. ER defines a multivariate regression operator using <span class="hlt">ensemble</span> ...</p> <div class="credits"> <p class="dwt_author">Gombos, Daniel (Daniel Lawrence)</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">138</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/ofr20141190"> <span id="translatedtitle"><span class="hlt">Downscaled</span> climate projections for the Southeast United States: evaluation and use for ecological applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several <span class="hlt">downscaled</span> climate projections (or <span class="hlt">downscaled</span> datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these <span class="hlt">downscaled</span> datasets, known as <span class="hlt">downscaling</span>, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for <span class="hlt">downscaling</span> and the number of <span class="hlt">downscaled</span> datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available <span class="hlt">downscaled</span> datasets, how do these model outputs compare to each other? Which variables are available, and are certain <span class="hlt">downscaled</span> datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these <span class="hlt">downscaled</span> datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.</p> <div class="credits"> <p class="dwt_author">Wooten, Adrienne; Smith, Kara; Boyles, Ryan; Terando, Adam J.; Stefanova, Lydia; Misra, Vasru; Smith, Tom; Blodgett, David L.; Semazzi, Fredrick</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">139</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3614370"> <span id="translatedtitle">Comparative Visualization of <span class="hlt">Ensembles</span> Using <span class="hlt">Ensemble</span> Surface Slicing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">By definition, an <span class="hlt">ensemble</span> is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity. The understanding and identification of visual similarities and differences among the shapes of members of an <span class="hlt">ensemble</span> is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging. This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. We present a novel single-image view and sampling technique which we call <span class="hlt">Ensemble</span> Surface Slicing (ESS). ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators. PMID:23560167</p> <div class="credits"> <p class="dwt_author">Alabi, Oluwafemi S.; Wu, Xunlei; Harter, Jonathan M.; Phadke, Madhura; Pinto, Lifford; Petersen, Hannah; Bass, Steffen; Keifer, Michael; Zhong, Sharon; Healey, Chris; Taylor, Russell M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">140</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/22093453"> <span id="translatedtitle">Estimating preselected and postselected <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">In analogy with the usual quantum state-estimation problem, we introduce the problem of state estimation for a pre- and postselected <span class="hlt">ensemble</span>. The problem has fundamental physical significance since, as argued by Y. Aharonov and collaborators, pre- and postselected <span class="hlt">ensembles</span> are the most basic quantum <span class="hlt">ensembles</span>. Two new features are shown to appear: (1) information is flowing to the measuring device both from the past and from the future; (2) because of the postselection, certain measurement outcomes can be forced never to occur. Due to these features, state estimation in such <span class="hlt">ensembles</span> is dramatically different from the case of ordinary, preselected-only <span class="hlt">ensembles</span>. We develop a general theoretical framework for studying this problem and illustrate it through several examples. We also prove general theorems establishing that information flowing from the future is closely related to, and in some cases equivalent to, the complex conjugate information flowing from the past. Finally, we illustrate our approach on examples involving covariant measurements on spin-1/2 particles. We emphasize that all state-estimation problems can be extended to the pre- and postselected situation. The present work thus lays the foundations of a much more general theory of quantum state estimation.</p> <div class="credits"> <p class="dwt_author">Massar, Serge [Laboratoire d'Information Quantique, C.P. 225, Universite libre de Bruxelles (U.L.B.), Av. F. D. Rooselvelt 50, B-1050 Bruxelles (Belgium); Popescu, Sandu [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Hewlett-Packard Laboratories, Stoke Gifford, Bristol BS12 6QZ (United Kingdom)</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-11-15</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_6");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' 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showDiv("page_9");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">141</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70124278"> <span id="translatedtitle">Projections of the Ganges-Brahmaputra precipitation: <span class="hlt">downscaled</span> from GCM predictors</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> Global Climate Model (GCM) projections of future climate is critical for impact studies. <span class="hlt">Downscaling</span> enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical <span class="hlt">Downscaling</span> Model (SDSM) to <span class="hlt">downscale</span> 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in <span class="hlt">downscaling</span> the precipitation. <span class="hlt">Downscaling</span> was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the <span class="hlt">downscaled</span> precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 <span class="hlt">downscaled</span> precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change. Precipitation during and after the monsoon is likely to increase in both basins under the A1B and A2 emission scenarios; whereas, the pre-monsoon precipitation is likely to decrease. Peak monsoon precipitation is likely to shift from July to August, and may impact the livelihoods of large rural populations linked to subsistence agriculture in the basins. Uncertainty analysis of the <span class="hlt">downscaled</span> precipitation indicated that the uncertainty in the <span class="hlt">downscaled</span> precipitation was less than the uncertainty in the original CGCM3.1 precipitation; hence, the CGCM3.1 <span class="hlt">downscaled</span> precipitation was a better input for the regional hydrological impact studies. However, <span class="hlt">downscaled</span> precipitation from multiple GCMs is suggested for comprehensive impact studies.</p> <div class="credits"> <p class="dwt_author">Pervez, Md Shahriar; Henebry, Geoffrey M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">142</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H41I..01G"> <span id="translatedtitle">A Comparison of Statistical and Dynamical <span class="hlt">Downscaling</span> of Winter Precipitation Over Complex Terrain</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Statistical <span class="hlt">downscaling</span> is widely used to improve spatial and or temporal distributions of meteorological variables from regional and global climate models. This <span class="hlt">downscaling</span> is important because climate models are spatially coarse (50-200km), and often misrepresent extremes in meteorological variables such as temperature and precipitation that are important to hydrologic models. However, these <span class="hlt">downscaling</span> methods rely on current estimates of the spatial distributions of these variables, and largely assume that the small-scale spatial distribution will not change significantly in a modified climate. Here we compare data typically used to derive spatial distributions of precipitation (PRISM) to a high-resolution (2km) weather model (WRF) under current climate in the mountains of Colorado. We show that there are regions of significant difference in November-May precipitation totals (~100%) between the two, and discuss possible causes for these differences, including a new observation which shows WRF to be substantially more accurate in at least one location. We then present a simple statistical <span class="hlt">downscaling</span> based on the 2km WRF data applied to a series of regional climate models from the North American Regional Climate Change Assessment Program (NARCCAP), and validate the <span class="hlt">downscaled</span> precipitation data with observations at 65 SNOw TELemetry (SNOTEL) sites throughout Colorado for the winter seasons from 1988 to 2000. Finally, we use this statistical <span class="hlt">downscaling</span> method to compare precipitation from a 36km model under an imposed warming scenario to dynamically <span class="hlt">downscaled</span> data from a 2km model using the same boundary conditions. While the statistical <span class="hlt">downscaling</span> improved the domain average precipitation and spatial distribution compared to the original 36km model, the changes in the spatial pattern of precipitation did not match the changes in the dynamically <span class="hlt">downscaled</span> 2km model (r^2=0.05). This points to a serious deficiency in current statistical <span class="hlt">downscaling</span> techniques. We suggest that it is possible to derive a better statistical <span class="hlt">downscaling</span> from a dynamically <span class="hlt">downscaled</span> model than it is from observations alone by leveraging additional model data such as the 500mb height, upper level wind direction, and vertical temperature gradients.</p> <div class="credits"> <p class="dwt_author">Gutmann, E. D.; Rasmussen, R.; Liu, C.; Ikeda, K.; Gochis, D. J.; Clark, M. P.; Dudhia, J.; Thompson, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">143</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..1412222S"> <span id="translatedtitle">Stochastic <span class="hlt">Downscaling</span> for Hydrodynamic and Ecological Modeling of Lakes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Weather generators are of interest in climate impact studies, because they allow different modi operandi: (1) More realizations of the past, (2) possible futures as defined by the modeler and (3) possible futures according to the combination of greenhouse gas emission scenarios and their Global Circulation Model (GCM) consequences. Climate modeling has huge inherently unquantifiable uncertainties, yet the results present themselves as single point values without any measure of uncertainty. Given this reduction of risk-relevant information, stochastic <span class="hlt">downscaling</span> offers itself as a tool to recover the variability present in local measurements. One should bear in mind that the lake models that are fed with <span class="hlt">downscaling</span> results are themselves deterministic and single runs may prove to be misleading. Especially population dynamics simulated by ecological models are sensitive to very particular events in the input data. A way to handle this sensitivity is to perform Monte Carlo studies with varying meteorological driving forces using a weather generator. For these studies, the Vector-Autoregressive Weather generator (VG), which was first presented at the EGU 2011, was developed further. VG generates daily air temperature, humidity, long- and shortwave radiance and wind. Wind and shortwave radiation is subsequently disaggregated to hourly values, because their short term variability has proven important for the application. Changes relative to the long-term values are modeled as disturbances that act during the autoregressive generation of the synthetic time series. The method preserves the dependence structure between the variables, as changes in the disturbed variable, say temperature, are propagated to the other variables. The approach is flexible because the disturbances can be chosen freely. Changes in mean can be represented as constant disturbance, changes in variability as episodes of certain length and amplitude. The disturbances can also be extracted from GCMs with the help of QQ-<span class="hlt">downscaled</span> time series. Results of water-quality and ecological modeling using data from VG is contributed by Marieke Anna Frassl under the title "Simulating the effect of meteorological variability on a lake ecosystem". Maria Magdalena Eder contributes three dimensional hydrodynamic lake simulations using VG data in a poster entitled "Advances in estimating the climate sensibility of a large lake using scenario simulations". Both posters can be found in the Session "Lakes and Inland Seas" (HS10.1).</p> <div class="credits"> <p class="dwt_author">Schlabing, D.; Eder, M.; Frassl, M.; Rinke, K.; Bárdossy, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">144</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.5597B"> <span id="translatedtitle">Impacts of high resolution model <span class="hlt">downscaling</span> in coastal regions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">With model development and cheaper computational resources ocean forecasts are becoming readily available, high resolution coastal forecasting is now a reality. This can only be achieved, however, by <span class="hlt">downscaling</span> global or basin-scale products such as the MyOcean reanalyses and forecasts. These model products have resolution ranging from 1/16th - 1/4 degree, which are often insufficient for coastal scales, but can provide initialisation and boundary data. We present applications of <span class="hlt">downscaling</span> the MyOcean products for use in shelf-seas and the nearshore. We will address the question 'Do coastal predictions improve with higher resolution modelling?' with a few focused examples, while also discussing what is meant by an improved result. Increasing resolution appears to be an obvious route for getting more accurate forecasts in operational coastal models. However, when models resolve finer scales, this may lead to the introduction of high-frequency variability which is not necessarily deterministic. Thus a flow may appear more realistic by generating eddies but the simple statistics like rms error and correlation may become less good because the model variability is not exactly in phase with the observations (Hoffman et al., 1995). By deciding on a specific process to simulate (rather than concentrating on reducing rms error) we can better assess the improvements gained by <span class="hlt">downscaling</span>. In this work we will select two processes which are dominant in our case-study site: Liverpool Bay. Firstly we consider the magnitude and timing of a peak in tide-surge elevations, by separating out the event into timing (or displacement) and intensity (or amplitude) errors. The model can thus be evaluated on how well it predicts the timing and magnitude of the surge. The second important characteristic of Liverpool Bay is the position of the freshwater front. To evaluate model performance in this case, the location, sharpness, and temperature difference across the front will be considered. We will show that by using intelligent metrics designed with a physical process in mind, we can learn more about model performance than by considering 'bulk' statistics alone. R. M. Hoffman and Z. Liu and J-F. Louic and C. Grassotti (1995) 'Distortion Representation of Forecast Errors' Monthly Weather Review 123: 2758-2770</p> <div class="credits"> <p class="dwt_author">Bricheno, Lucy; Wolf, Judith</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">145</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.meted.ucar.edu/training_module.php?id=201"> <span id="translatedtitle"><span class="hlt">Ensemble</span> Prediction System Matrix: Characteristics of Operational <span class="hlt">Ensemble</span> Prediction Systems (EPS)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This one-stop <span class="hlt">Ensemble</span> Model Matrix provides information on the configurations of the NCEP Short-Range <span class="hlt">Ensemble</span> Forecast (SREF) and Medium-Range <span class="hlt">Ensemble</span> Forecast (MREF) systems. Information on <span class="hlt">ensemble</span> perturbation methods; NWP model resolution, dynamics, physics (precipitation, radiation, land surface and turbulence); and <span class="hlt">ensemble</span> post-processing and verification links are provided. As the <span class="hlt">ensemble</span> prediction systems (EPSs) are improved, the information in the <span class="hlt">Ensemble</span> Model Matrix will be updated. Additionally, as new EPSs are added to AWIPS, we will add new columns to the <span class="hlt">Ensemble</span> Model Matrix.</p> <div class="credits"> <p class="dwt_author">Comet</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-04-05</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">146</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014GeoRL..41.4013K"> <span id="translatedtitle">Uncertainty resulting from multiple data usage in statistical <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">downscaling</span> (SD), used for regional climate projections with coarse resolution general circulation model (GCM) outputs, is characterized by uncertainties resulting from multiple models. Here we observe another source of uncertainty resulting from the use of multiple observed and reanalysis data products in model calibration. In the training of SD, for Indian Summer Monsoon Rainfall (ISMR), we use two reanalysis data as predictors and three gridded data products for ISMR from different sources. We observe that the uncertainty resulting from six possible training options is comparable to that resulting from multiple GCMs. Though the original GCM simulations project spatially uniform increasing change of ISMR, at the end of 21st century, the same is not obtained with SD, which projects spatially heterogeneous and mixed changes of ISMR. This is due to the differences in statistical relationship between rainfall and predictors in GCM simulations and observed/reanalysis data, and SD considers the latter.</p> <div class="credits"> <p class="dwt_author">Kannan, S.; Ghosh, Subimal; Mishra, Vimal; Salvi, Kaustubh</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">147</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012AGUFM.A34E..04L"> <span id="translatedtitle">Dynamically <span class="hlt">Downscaled</span> Future Climate Change over East Asia</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study assesses the future climate change over East Asia using the Global/Regional Integrated Model System (GRIMs) - Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2; the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios of Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Analyses for the current (1980-2005) climate are performed to evaluate the RMP's ability to reproduce precipitation and temperature. Two different future (2006-2050) simulations are compared with the current climatology to investigate the climatic change. The RMP reproduces the observed seasonal mean and variation of precipitation and temperature satisfactorily. The spatial distribution of the simulated climatology is generally worse in RMP than those from the HG2, but the distributions of monsoonal precipitation are adequately captured. Furthermore, the RMP shows higher reproducibility of climate extreme accompanying excessive heat wave and precipitation. In the future, the strong warming is distinct with intensified monsoonal precipitation. In particular, extreme weather conditions are increased and intensified over South Korea. The heat wave is increased by twice with decreased variability. In RCP 8.5 <span class="hlt">downscaling</span>, frequency and variability of heavy rainfall are increased by 24% and 31.5%, while they are similar to current climate in RCP 4.5 <span class="hlt">downscaling</span>. This study indicates that future climate projection accompanying climate extreme and its variability over East Asia can be adequately addressed on the RMP test-bed, and the climatic change progressed without stabilization increases occurrence and intensity of extreme weather conditions.</p> <div class="credits"> <p class="dwt_author">Lee, J.; Hong, S.; Chang, E.; Suh, M.; Kang, H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">148</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/quant-ph/9907067v1"> <span id="translatedtitle">Algorithms on <span class="hlt">Ensemble</span> Quantum Computers</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">In <span class="hlt">ensemble</span> (or bulk) quantum computation, measurements of qubits in an individual computer cannot be performed. Instead, only expectation values can be measured. As a result of this limitation on the model of computation, various important algorithms cannot be processed directly on such computers, and must be modified. We provide modifications of various existing protocols, including algorithms for universal fault--tolerant computation, Shor's factorization algorithm (which can be extended to any algorithm computing an NP function), and some search algorithms to enable processing them on <span class="hlt">ensemble</span> quantum computers.</p> <div class="credits"> <p class="dwt_author">P. Oscar Boykin; Tal Mor; Vwani Roychowdhury; Farrokh Vatan</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-07-21</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">149</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4224315"> <span id="translatedtitle">The <span class="hlt">ensemble</span> nature of allostery</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Allostery is the process by which biological macromolecules (mostly proteins) transmit the effect of binding at one site to another, often distal, functional site, allowing for regulation of activity. Recent experimental observations demonstrating that allostery can be facilitated by dynamic and intrinsically disordered proteins have resulted in a new paradigm for understanding allosteric mechanisms, which focuses on the conformational <span class="hlt">ensemble</span> and the statistical nature of the interactions responsible for the transmission of information. Analysis of allosteric <span class="hlt">ensembles</span> reveals a rich spectrum of regulatory strategies, as well as a framework to unify the description of allosteric mechanisms from different systems. PMID:24740064</p> <div class="credits"> <p class="dwt_author">Motlagh, Hesam N.; Wrabl, James O.; Li, Jing; Hilser, Vincent J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">150</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21450714"> <span id="translatedtitle">Quantum metrology with molecular <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The field of quantum metrology promises measurement devices that are fundamentally superior to conventional technologies. Specifically, when quantum entanglement is harnessed, the precision achieved is supposed to scale more favorably with the resources employed, such as system size and time required. Here, we consider measurement of magnetic-field strength using an <span class="hlt">ensemble</span> of spin-active molecules. We identify a third essential resource: the change in <span class="hlt">ensemble</span> polarization (entropy increase) during the metrology experiment. We find that performance depends crucially on the form of decoherence present; for a plausible dephasing model, we describe a quantum strategy, which can indeed beat the standard strategy.</p> <div class="credits"> <p class="dwt_author">Schaffry, Marcus; Gauger, Erik M. [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Morton, John J. L. [CAESR, Clarendon Laboratory, Department of Physics, University of Oxford, OX1 3PU (United Kingdom); Fitzsimons, Joseph [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Institute for Quantum Computing, University of Waterloo, Waterloo, Ontario (Canada); Benjamin, Simon C. [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore 117543 (Singapore); Lovett, Brendon W. [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom)</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-10-15</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">151</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010ems..confE.373F"> <span id="translatedtitle">Evolution of the Canadian regional <span class="hlt">ensemble</span> prediction system</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A regional <span class="hlt">ensemble</span> prediction system (REPS) over North America is expected to become operational at the Canadian Meteorological Centre (CMC) in late 2010 or early 2011. Different configurations of the REPS have already been tested and verified at different locations and time periods. The system was used during the Beijing 2008 summer Olympics and for the North American domain with a focus over southern British Columbia, Canada, during the 2010 Vancouver Olympics. It will also provide forecasts for tropical storms and hurricanes for the Haïti area during the summer and autumn of 2010. The Canadian Global Environmental Multiscale (GEM) model has been designed with the possibility to be run as a limited area model (GEM-LAM). The Canadian REPS is composed of 20 members running the GEM-LAM at a near 33 km grid spacing and with the same physical parameterizations as those present in the operational global deterministic prediction system at CMC. Two initial perturbation strategies (moist targeted singular vectors [SV] and the <span class="hlt">ensemble</span> Kalman filter [EnKF]), as well as two stochastic methods for perturbations of parameterizations were verified against surface and upper air (rawinsondes) observations during summer and winter periods to determine which system has the best forecast abilities. For the SV-based REPS, 20 initial conditions (IC) are generated using a targeted SV perturbation method. These ICs are then used to run 20 global GEMs that will provide the lateral boundary conditions (LBCs) for each GEM-LAM. For the EnKF-based REPS, the 20 LBCs are built by <span class="hlt">downscaling</span> the 20 members of the Canadian global <span class="hlt">ensemble</span> prediction system (GEPS) to the resolution of the REPS. Verifications indicate that the EnKF approach gives better skill for summer and winter periods. The skill difference between the two systems comes mainly from the reliability attribute (smaller bias and reduced under-dispersion). Stochastic perturbations on model physical tendencies and on physical parameters were both tested. These two perturbation methods show a significant improvement in the reliability skill but tend to slightly degrade the resolution. Nevertheless, both systems show an overall improvement in the skill. The physical tendencies perturbation method showed the best scores and was chosen. Research to improve the system using surface parameter perturbations is presently ongoing. Initial results show improved skill for surface during the summer season when perturbations are done on fields related to the land surface scheme such as the albedo, soil temperature and moisture.</p> <div class="credits"> <p class="dwt_author">Frenette, R.; Charron, M.; Li, X.; Gagnon, N.; Lavaysse, C.; Belair, S.; Carrera, M.; Yau, P.; Candille, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">152</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFMGC41E..07W"> <span id="translatedtitle">SDSM-DC: A smarter approach to <span class="hlt">downscaling</span> for decision-making? (Invited)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">General Circulation Model (GCM) output has been used for <span class="hlt">downscaling</span> and impact assessments for at least 25 years. <span class="hlt">Downscaling</span> methods raise awareness about risks posed by climate variability and change to human and natural systems. However, there are relatively few instances where these analyses have translated into actionable information for adaptation. One reason is that conventional ';top down' <span class="hlt">downscaling</span> typically yields very large uncertainty bounds in projected impacts at regional and local scales. Consequently, there are growing calls to use <span class="hlt">downscaling</span> tools in smarter ways that refocus attention on the decision problem rather than on the climate modelling per se. The talk begins with an overview of various application of the Statistical <span class="hlt">DownScaling</span> Model (SDSM) over the last decade. This sample offers insights to <span class="hlt">downscaling</span> practice in terms of regions and sectors of interest, modes of application and adaptation outcomes. The decision-centred rationale and functionality of the latest version of SDSM is then explained. This new <span class="hlt">downscaling</span> tool does not require GCM input but enables the user to generate plausible daily weather scenarios that may be informed by climate model and/or palaeoenvironmental information. Importantly, the tool is intended for stress-testing adaptation options rather than for exhaustive analysis of uncertainty components. The approach is demonstrated by <span class="hlt">downscaling</span> multi-basin, multi-elevation temperature and precipitation scenarios for the Upper Colorado River Basin. These scenarios are used alongside other narratives of future conditions that might potential affect the security of water supplies, and for evaluating steps that can be taken to manage these risks.</p> <div class="credits"> <p class="dwt_author">Wilby, R. L.; Dawson, C. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">153</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.agu.org/journals/jd/jd0912/2008JD010933/2008JD010933.pdf"> <span id="translatedtitle">Dynamical <span class="hlt">downscaling</span> of short-term climate fluctuations: On the benefits of precipitation assimilation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Regional <span class="hlt">downscaling</span> has proven useful in adding details to the global solution. However, the parameterized physical processes can systematically deviate the large-scale features in the regional solution. To demonstrate the precipitation assimilation beneficial impact on the dynamical <span class="hlt">downscaling</span>, a regional spectral model driven by the National Centers for Environmental Prediction\\/Department of Energy Atmospheric Model Intercomparison Project II (NCEP\\/DOE AMIP-II) Reanalysis</p> <div class="credits"> <p class="dwt_author">Ana M. B. Nunes; John O. Roads</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">154</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48028469"> <span id="translatedtitle">Estimation of future precipitation change in the Yangtze River basin by using statistical <span class="hlt">downscaling</span> method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this study, the applicability of the statistical <span class="hlt">downscaling</span> model (SDSM) in <span class="hlt">downscaling</span> precipitation in the Yangtze River\\u000a basin, China was investigated. The investigation includes the calibration of the SDSM model by using large-scale atmospheric\\u000a variables encompassing NCEP\\/NCAR reanalysis data, the validation of the model using independent period of the NCEP\\/NCAR reanalysis\\u000a data and the general circulation model (GCM) outputs</p> <div class="credits"> <p class="dwt_author">Jin Huang; Jinchi Zhang; Zengxin Zhang; ChongYu Xu; Baoliang Wang; Jian Yao</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">155</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/quant-ph/0611148v1"> <span id="translatedtitle">Localization of atomic <span class="hlt">ensembles</span> via superfluorescence</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">The sub-wavelength localization of an <span class="hlt">ensemble</span> of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the <span class="hlt">ensemble</span> with a standing wave laser field. The light scattered in the interaction of standing wave field and atom <span class="hlt">ensemble</span> depends on the position of the <span class="hlt">ensemble</span> relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters, the <span class="hlt">ensemble</span> properties, and which is modified due to collective effects in the <span class="hlt">ensemble</span> of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an <span class="hlt">ensemble</span> fixed at a certain position in the standing wave field. Second, we discuss localization of an <span class="hlt">ensemble</span> passing through the standing wave field.</p> <div class="credits"> <p class="dwt_author">M. Macovei; J. Evers; C. H. Keitel; M. S. Zubairy</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-11-14</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">156</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54133902"> <span id="translatedtitle"><span class="hlt">Ensemble</span> treatments of thermal pairing in nuclei</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical <span class="hlt">ensembles</span>, namely the grandcanonical <span class="hlt">ensemble</span>, canonical <span class="hlt">ensemble</span> and microcanonical <span class="hlt">ensemble</span>, as well as the unprojected (FTBCS1+SCQRPA) and Lipkin-Nogami projected (FTLN1+SCQRPA) theories that include the quasiparticle number fluctuation and coupling to pair</p> <div class="credits"> <p class="dwt_author">Nguyen Quang Hung; Nguyen Dinh Dang</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">157</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4041546"> <span id="translatedtitle">Measuring Similarity Between Dynamic <span class="hlt">Ensembles</span> of Biomolecules</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Methods for comparing <span class="hlt">ensembles</span> of biomolecules assess the population overlap between distributions but fail to fully quantify structural similarity. We present a simple and general approach for quantifying population overlap and structural similarity between <span class="hlt">ensembles</span>. This approach captures improvements in the quality of <span class="hlt">ensembles</span> determined using increasing input experimental data that go undetected using conventional methods and reveals unexpected similarities between RNA <span class="hlt">ensembles</span> determined using NMR and molecular dynamics simulations. PMID:24705474</p> <div class="credits"> <p class="dwt_author">Yang, Shan; Salmon, Loic; Al-Hashimi, Hashim M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">158</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JHyd..492....1N"> <span id="translatedtitle">Performance assessment of different data mining methods in statistical <span class="hlt">downscaling</span> of daily precipitation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this paper, nonlinear Data-Mining (DM) methods have been used to extend the most cited statistical <span class="hlt">downscaling</span> model, SDSM, for <span class="hlt">downscaling</span> of daily precipitation. The proposed model is Nonlinear Data-Mining <span class="hlt">Downscaling</span> Model (NDMDM). The four nonlinear and semi-nonlinear DM methods which are included in NDMDM model are cubic-order Multivariate Adaptive Regression Splines (MARS), Model Tree (MT), k-Nearest Neighbor (kNN) and Genetic Algorithm-optimized Support Vector Machine (GA-SVM). The daily records of 12 rain gauge stations scattered in basins with various climates in Iran are used to compare the performance of NDMDM model with statistical <span class="hlt">downscaling</span> method. Comparison between statistical <span class="hlt">downscaling</span> and NDMDM results in the selected stations indicates that combination of MT and MARS methods can provide daily rain estimations with less mean absolute error and closer monthly standard deviation and skewness values to the historical records for both calibration and validation periods. The results of the future projections of precipitation in the selected rain gauge stations using A2 and B2 SRES scenarios show significant uncertainty of the NDMDM and statistical <span class="hlt">downscaling</span> models.</p> <div class="credits"> <p class="dwt_author">Nasseri, M.; Tavakol-Davani, H.; Zahraie, B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">159</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFMGC43C1070A"> <span id="translatedtitle">Applying <span class="hlt">downscaled</span> climate data to wildlife areas in Washington State, USA</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Conservation and natural resource managers require information about potential climate change effects for the species and ecosystems they manage. We evaluated potential future climate and bioclimate changes for wildlife areas in Washington State (USA) using five climate simulations for the 21st century from the Coupled Model Intercomparison Project phase 3 (CMIP3) dataset run under the A2 greenhouse gases emissions scenario. These data were <span class="hlt">downscaled</span> to a 30-arc-second (~1-km) grid encompassing the state of Washington by calculating and interpolating future climate anomalies, and then applying the interpolated data to observed historical climate data. This climate data <span class="hlt">downscaling</span> technique (also referred to as the 'delta' method) is relatively simple and makes a number of assumptions that affect how the <span class="hlt">downscaled</span> data can be used and interpreted. We used the <span class="hlt">downscaled</span> climate data to calculate bioclimatic variables (e.g., growing degree days) that represent important physiological and environmental limits for Washington species and habitats of management concern. Multivariate descriptive plots and maps were used to evaluate the direction, magnitude, and spatial patterns of projected future climate and bioclimatic changes. The results indicate which managed areas experience the largest climate and bioclimatic changes under each of the potential future climate simulations. We discuss these changes while accounting for some of the limitations of our <span class="hlt">downscaling</span> technique and the uncertainties associated with using these <span class="hlt">downscaled</span> data for conservation and natural resource management applications.</p> <div class="credits"> <p class="dwt_author">Allan, A.; Shafer, S. L.; Bartlein, P. J.; Helbrecht, L.; Pelltier, R.; Thompson, B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">160</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ti.arc.nasa.gov/m/profile/oza/files/oza01.pdf"> <span id="translatedtitle">Online <span class="hlt">Ensemble</span> Learning Nikunj Chandrakant Oza</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Date Date Date University of California at Berkeley 2001 #12;Online <span class="hlt">Ensemble</span> Learning Copyright 2001Online <span class="hlt">Ensemble</span> Learning by Nikunj Chandrakant Oza B.S. (Massachusetts Institute of Technology by Nikunj Chandrakant Oza #12;1 Abstract Online <span class="hlt">Ensemble</span> Learning by Nikunj Chandrakant Oza Doctor</p> <div class="credits"> <p class="dwt_author">Oza, Nikunj C.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_7");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> 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showDiv("page_10");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">161</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010PhDT.......137H"> <span id="translatedtitle">A standardized framework for evaluating the skill of regional climate <span class="hlt">downscaling</span> techniques</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Regional climate impact assessments require high-resolution projections to resolve local factors that modify the impact of global-scale forcing. To generate these projections, global climate model simulations are commonly <span class="hlt">downscaled</span> using a variety of statistical and dynamical techniques. Despite the essential role of <span class="hlt">downscaling</span> in regional assessments, there is no standard approach to evaluating various <span class="hlt">downscaling</span> methods. Hence, impact communities often have little awareness of limitations and uncertainties associated with <span class="hlt">downscaled</span> projections. To develop a standardized framework for evaluating and comparing <span class="hlt">downscaling</span> approaches, I first identify three primary characteristics of a distribution directly relevant to impact analyses that can be used to evaluate a simulated variable such as temperature or precipitation at a given location: (1) annual, seasonal, and monthly mean values; (2) thresholds, extreme values, and accumulated quantities such as 24h precipitation or degree-days; and (3) persistence, reflecting multi-day events such as heat waves, cold spells, and wet periods. Based on a survey of the literature and solicitation of expert opinion, I select a set of ten statistical tests to evaluate these characteristics, including measures of error, skill, and correlation. I apply this framework to evaluate the skill of four <span class="hlt">downscaling</span> methods, from a simple delta approach to a complex asynchronous quantile regression, in simulating daily temperature at twenty stations across North America. Identical global model fields force each <span class="hlt">downscaling</span> method, and the historical observational record at each location is randomly divided by year into two equal parts, such that each statistical method is trained on one set of historical observations, and evaluated on an entirely independent set of observations. Biases relative to observations are calculated for the historical evaluation period, and differences between projections for the future. Application of the framework to this broad range of <span class="hlt">downscaling</span> methods and locations is successful in that: (1) the <span class="hlt">downscaling</span> method used is identified as a more important determinant of data quality than station location or GCM; and (2) key differences between <span class="hlt">downscaling</span> methods are made apparent. For tests focusing on the general distribution of the variable, all methods except bias correction are relatively successful in simulating observed climate, suggesting that if an impact is most sensitive to changes in the mean, even a relatively simple <span class="hlt">downscaling</span> approach such as "delta" will significantly improve simulation of local-scale climate. For tests that focus on the tails of the distribution, however, differences do arise between simple vs. quantile-based <span class="hlt">downscaling</span> methods. Specifically, the latter appears less sensitive to location and more consistently able to reproduce observed climate. In terms of future projections, the most notable differences between <span class="hlt">downscaling</span> methods becomes apparent at the right-hand tail of the distribution, where simple methods tend to simulate much greater increases (up to double the extreme heat days, for some locations) than more complex <span class="hlt">downscaling</span> methods. I conclude by discussing how a standardized evaluation framework may advance our understanding of regional climate impact studies in understanding biases and limitations in results, as well as providing critical input into the selection of <span class="hlt">downscaling</span> methods for future assessments. Given the potential exhibited by this initial test, I explore how this evaluation framework could be expanded in the future to make it even more useful: to the regional scale, for example, by including tests for spatial correlations and forcing relationships; or across variables, to capture interactions directly relevant to impact studies, such as heat waves (a function of temperature and humidity, affecting human health, energy demand, and agriculture) or snow amounts (a function of precipitation and temperature, affecting infrastructure and ecosystems); or to evaluate a broader selection of clim</p> <div class="credits"> <p class="dwt_author">Hayhoe, Katharine Anne</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">162</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.meted.ucar.edu/training_module.php?id=1029"> <span id="translatedtitle">Introduction to <span class="hlt">Ensembles</span>: Forecasting Hurricane Sandy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This module provides an introduction to <span class="hlt">ensemble</span> forecast systems with an operational case study of Hurricane Sandy. The module concentrates on models from NCEP and FNMOC available to forecasters in the U.S. Navy, including NAEFS (North American <span class="hlt">Ensemble</span> Forecast System), and NUOPC (National Unified Operational Prediction Capability). Probabilistic forecasts of winds and waves developed from these <span class="hlt">ensemble</span> forecast systems are applied to a ship transit and coastal resource protection. Lessons integrated in the case study provide information on <span class="hlt">ensemble</span> statistics, products, bias correction and verification. Additional lessons address multimodel <span class="hlt">ensembles</span>, extreme events, and automated forecasting.</p> <div class="credits"> <p class="dwt_author">Comet</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-28</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">163</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014ClDy...43.2297H"> <span id="translatedtitle">On the generation of climate model <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Climate model <span class="hlt">ensembles</span> are used to estimate uncertainty in future projections, typically by interpreting the <span class="hlt">ensemble</span> distribution for a particular variable probabilistically. There are, however, different ways to produce climate model <span class="hlt">ensembles</span> that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the <span class="hlt">ensemble</span> distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate <span class="hlt">ensembles</span>: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 <span class="hlt">ensemble</span> for comparison, we show that initial conditions <span class="hlt">ensembles</span>, in theory representing internal variability, significantly underestimate observed variance. Structural <span class="hlt">ensembles</span>, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model <span class="hlt">ensembles</span> may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where <span class="hlt">ensembles</span> are over- or under-dispersive, such as for the CMIP5 <span class="hlt">ensemble</span>, estimates of uncertainty need to be treated with care.</p> <div class="credits"> <p class="dwt_author">Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">164</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFMGC43C1053X"> <span id="translatedtitle">A Dynamical <span class="hlt">Downscaling</span> Approach with GCM Bias Corrections and Spectral Nudging</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">To reduce the biases in the regional climate <span class="hlt">downscaling</span> simulations, a dynamical <span class="hlt">downscaling</span> approach with GCM bias corrections and spectral nudging is developed and assessed over North America. Regional climate simulations are performed with the Weather Research and Forecasting (WRF) model embedded in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). To reduce the GCM biases, the GCM climatological means and the variances of interannual variations are adjusted based on the National Centers for Environmental Prediction-NCAR global reanalysis products (NNRP) before using them to drive WRF which is the same as our previous method. In this study, we further introduce spectral nudging to reduce the RCM-based biases. Two sets of WRF experiments are performed with and without spectral nudging. All WRF experiments are identical except that the initial and lateral boundary conditions are derived from the NNRP, the original GCM output, and the bias corrected GCM output, respectively. The GCM-driven RCM simulations with bias corrections and spectral nudging (IDDng) are compared with those without spectral nudging (IDD) and North American Regional Reanalysis (NARR) data to assess the additional reduction in RCM biases relative to the IDD approach. The results show that the spectral nudging introduces the effect of GCM bias correction into the RCM domain, thereby minimizing the climate drift resulting from the RCM biases. The GCM bias corrections and spectral nudging significantly improve the <span class="hlt">downscaled</span> mean climate and extreme temperature simulations. Our results suggest that both GCM bias corrections or spectral nudging are necessary to reduce the error of <span class="hlt">downscaled</span> climate. Only one of them does not guarantee better <span class="hlt">downscaling</span> simulation. The new dynamical <span class="hlt">downscaling</span> method can be applied to regional projection of future climate or <span class="hlt">downscaling</span> of GCM sensitivity simulations. Annual mean RMSEs. The RMSEs are computed over the verification region by monthly mean data over 1981-2010. Experimental design</p> <div class="credits"> <p class="dwt_author">Xu, Z.; Yang, Z.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">165</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1614315G"> <span id="translatedtitle">Comparison among different <span class="hlt">downscaling</span> approaches in building water scarcity scenarios in an Alpine basin.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Various <span class="hlt">downscaling</span> techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Although statistical <span class="hlt">downscaling</span> (SD) has been traditionally seen as an alternative to dynamical <span class="hlt">downscaling</span> (DD), recent works on statistical <span class="hlt">downscaling</span> have aimed to combine the benefits of these two approaches. The overall objective of this study is to assess whether a DD processing performed before the SD is able to provide more reliable climate forcing for crop water demand models. The case study presented here focuses on the Maggiore Lake (Alpine region), with a watershed of approximately 4750 km2 and whose waters are mainly used for irrigation purposes in the Lombardia and Piemonte regions. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile correction of the precipitation data collected in the period 1950-2012 by the 19 rainfall gauges located in the watershed area (some of them operating not continuously during the study period). The relationship between the precipitation regime and the inflow to the reservoir is obtained through a simple multilinear regression model, validated using both precipitation data and inflow measurements to the lake in the period 1996-2012 then, the same relation has been applied to the control (20c) and scenario (a1b) simulations <span class="hlt">downscaled</span> by means of the different <span class="hlt">downscaling</span> approaches (DD, SD and combined DD-SD). The resulting forcing has been used as input to a daily water balance model taking into account the inflow to the lake, the demand for irrigation and the reservoir management policies. The impact of the different <span class="hlt">downscaling</span> approaches on the water budget scenarios has been evaluated in terms of occurrence, duration and intensity of water scarcity periods.</p> <div class="credits"> <p class="dwt_author">Guyennon, Nicolas; Romano, Emanuele; Mariani, Davide; Bruna Petrangeli, Anna; Portoghese, Ivan</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">166</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2003APS..MAR.R1003M"> <span id="translatedtitle"><span class="hlt">Ensemble</span> Dynamics with Quantum Forces</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a new methodology for approximating the solutions of the time-dependent Schrödinger equation. Our approach is rooted in the de Broglie Bohm interpretation of the quantum theory in which the evolution of a quantum system is characterized by an <span class="hlt">ensemble</span> of particle trajectories. The paths of these ``Bohmian'' particles are analogous to hydrodynamic trajectories and are determined by the presence of both classical and quantum forces in the system. The quantum force is due to the nonlocal interactions between particles and is related to the curvature of the quantum density. In the present study we invoke an expectation-maximization algorithm to approximate a functional form for the density of a finite <span class="hlt">ensemble</span> of Bohmian particles. From this density information we then calculate a quantum force and propagate the system forward in time using a Verlet type integration. In what follows we will describe the details of this approach and present some numerical results.</p> <div class="credits"> <p class="dwt_author">Maddox, Jeremy; Bittner, Eric</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">167</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20110011613&hterms=precipitation+dependent+hydrologic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dprecipitation%2Bdependent%2Bhydrologic"> <span id="translatedtitle"><span class="hlt">Downscaling</span> NASA Climatological Data to Produce Detailed Climate Zone Maps</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of <span class="hlt">downscaling</span> NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.</p> <div class="credits"> <p class="dwt_author">Chandler, William S.; Hoell, James M.; Westberg, David J.; Whitlock, Charles H.; Zhang, Taiping; Stackhouse, P. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">168</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFMGC53A1041A"> <span id="translatedtitle"><span class="hlt">Downscaling</span> MODIS Land Surface Temperature for Urban Public Health Applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heat-related mortality data. The current HWWS do not take into account intra-urban spatial variations in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with land surface temperature (LST) estimates derived from thermal remote sensing data. In order to further improve the assessment of intra-urban variations in risk from extreme heat, we developed and evaluated a number of spatial statistical techniques for <span class="hlt">downscaling</span> the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. We will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.</p> <div class="credits"> <p class="dwt_author">Al-Hamdan, M. Z.; Crosson, W. L.; Estes, M. G., Jr.; Estes, S. M.; Quattrochi, D. A.; Johnson, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">169</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014CSR....87....7B"> <span id="translatedtitle">Impacts of high resolution model <span class="hlt">downscaling</span> in coastal regions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The issue of appropriate resolution of coastal models is addressed in this paper. The quality of coastal predictions from three different spatial resolutions of a coastal ocean model is assessed in the context of simulation of the freshwater front in Liverpool Bay. Model performance is examined during the study period February 2008 using a 3-D baroclinic hydrodynamic model. Some characteristic lengthscales and non-dimensional numbers are introduced to describe the coastal plume and freshwater front. Metrics based on these lengthscales and the governing physical processes are used to assess model performance and these metrics have been calculated for the suite of <span class="hlt">downscaled</span> models and compared with observations. Increased model resolution was found to better capture the position and strength of the freshwater front. However, instabilities along the front such as the tidal excursion led to large temporal and spatial variability in its position in the highest resolution model. By examining the spatial structure of the baroclinic Rossby radius in each model we identify which lengthscales are being resolved at different resolutions. In this dynamic environment it is more valuable to represent the governing time and space scales, rather than relying on strict point by point tests when evaluating model skill.</p> <div class="credits"> <p class="dwt_author">Bricheno, Lucy M.; Wolf, Judith M.; Brown, Jennifer M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">170</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24988779"> <span id="translatedtitle"><span class="hlt">Downscaling</span> the environmental associations and spatial patterns of species richness.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We introduce a method that enables the estimation of species richness environment association and prediction of geographic patterns of species richness at grains finer than the original grain of observation. The method is based on a hierarchical model that uses coarse-grain values of species richness and fine-grain environmental data as input. In the model, the (unobserved) fine-grain species richness is linked to the observed fine-grain environment and upscaled using a simple species-area relationship (SAR). The upscaled values are then stochastically linked to the observed coarse-grain species richness. We tested the method on Southern African Bird Atlas data by <span class="hlt">downscaling</span> richness from 2 degrees to 0.25 degrees (-250 km to -30 km) resolution. When prior knowledge of the SAR slope (average species turnover within coarse-grain cells) was available, the method predicted the fine-grain relationship between richness and environment and provided fine-grain predictions of richness that closely resembled results from native fine-grain models. Without the SAR knowledge the method still accurately quantified the richness-environment relationship, but accurately predicted only relative (rank) values of richness. The approach can be easily extended and it is a powerful path for cross-scale statistical modeling of richness-environment relationships, and for the provision of high-resolution maps for basic science and conservation. PMID:24988779</p> <div class="credits"> <p class="dwt_author">Keil, Petr; Jetz, Walter</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">171</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvE..90c2117K"> <span id="translatedtitle">Heat fluctuations and initial <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Time-integrated quantities such as work and heat increase incessantly in time during nonequilibrium processes near steady states. In the long-time limit, the average values of work and heat become asymptotically equivalent to each other, since they only differ by a finite energy change in average. However, the fluctuation theorem (FT) for the heat is found not to hold with the equilibrium initial <span class="hlt">ensemble</span>, while the FT for the work holds. This reveals an intriguing effect of everlasting initial memory stored in rare events. We revisit the problem of a Brownian particle in a harmonic potential dragged with a constant velocity, which is in contact with a thermal reservoir. The heat and work fluctuations are investigated with initial Boltzmann <span class="hlt">ensembles</span> at temperatures generally different from the reservoir temperature. We find that, in the infinite-time limit, the FT for the work is fully recovered for arbitrary initial temperatures, while the heat fluctuations significantly deviate from the FT characteristics except for the infinite initial-temperature limit (a uniform initial <span class="hlt">ensemble</span>). Furthermore, we succeed in calculating finite-time corrections to the heat and work distributions analytically, using the modified saddle point integral method recently developed by us. Interestingly, we find noncommutativity between the infinite-time limit and the infinite-initial-temperature limit for the probability distribution function (PDF) of the heat.</p> <div class="credits"> <p class="dwt_author">Kim, Kwangmoo; Kwon, Chulan; Park, Hyunggyu</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">172</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23288332"> <span id="translatedtitle"><span class="hlt">Ensemble</span> learning incorporating uncertain registration.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This paper proposes a novel approach for improving the accuracy of statistical prediction methods in spatially normalized analysis. This is achieved by incorporating registration uncertainty into an <span class="hlt">ensemble</span> learning scheme. A probabilistic registration method is used to estimate a distribution of probable mappings between subject and atlas space. This allows the estimation of the distribution of spatially normalized feature data, e.g., grey matter probability maps. From this distribution, samples are drawn for use as training examples. This allows the creation of multiple predictors, which are subsequently combined using an <span class="hlt">ensemble</span> learning approach. Furthermore, extra testing samples can be generated to measure the uncertainty of prediction. This is applied to separating subjects with Alzheimer's disease from normal controls using a linear support vector machine on a region of interest in magnetic resonance images of the brain. We show that our proposed method leads to an improvement in discrimination using voxel-based morphometry and deformation tensor-based morphometry over bootstrap aggregating, a common <span class="hlt">ensemble</span> learning framework. The proposed approach also generates more reasonable soft-classification predictions than bootstrap aggregating. We expect that this approach could be applied to other statistical prediction tasks where registration is important. PMID:23288332</p> <div class="credits"> <p class="dwt_author">Simpson, Ivor J A; Woolrich, Mark W; Andersson, Jesper L R; Groves, Adrian R; Schnabel, Julia A</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">173</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvD..90d4064B"> <span id="translatedtitle">Thermodynamic curvature and <span class="hlt">ensemble</span> nonequivalence</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this work we consider thermodynamic geometries defined as Hessians of different potentials and derive some useful formulas that show their complementary role in the description of thermodynamic systems with 2 degrees of freedom that show <span class="hlt">ensemble</span> nonequivalence. From the expressions derived for the metrics, we can obtain the curvature scalars in a very simple and compact form. We explain here the reason why each curvature scalar diverges over the line of divergence of one of the specific heats. This application is of special interest in the study of changes of stability in black holes as defined by Davies. From these results we are able to prove on a general footing a conjecture first formulated by Liu, Lü, Luo, and Shao stating that different Hessian metrics can correspond to different behaviors in the various <span class="hlt">ensembles</span>. We study the case of two thermodynamic dimensions. Moreover, comparing our result with the more standard turning point method developed by Poincaré, we obtain that the divergence of the scalar curvature of the Hessian metric of one potential exactly matches the change of stability in the corresponding <span class="hlt">ensemble</span>.</p> <div class="credits"> <p class="dwt_author">Bravetti, Alessandro; Nettel, Francisco</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">174</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.7194S"> <span id="translatedtitle">Development of new <span class="hlt">ensemble</span> methods based on the performace skills of regional climate models over South Korea</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">It is well known that multi-model <span class="hlt">ensembles</span> can reduce the uncertainties of the model results and increase the reliability of the model results. In this paper, the prediction skills for temperature and precipitation of five <span class="hlt">ensemble</span> methods were discussed by using the 20 years simulation results (from 1989 to 2008) by four regional climate models (RCMs : SNURCM, WRF, RegCM4, and RSM) driven by NCEP-DOE and ERA-interim boundary conditions. The simulation domain is CORDEX (COordinated Regional climate <span class="hlt">Downscaling</span> Experiment) East Asia and the number of grids is 197 x 233 grids with a 50-km horizontal resolution. The new three <span class="hlt">ensemble</span> methods, PEA_BRC, PEA_RAC and PEA_ROC, developed in this study, are performance based <span class="hlt">ensemble</span> averaging methods by using bias, RMSE (root mean square errors) and correlation, RMSE and absolute correlation, and RMSE and original correlation, respectively. The other two <span class="hlt">ensemble</span> methods are equal weighted averaging (EWA) and multivariate linear regression (Mul_Reg). Fifteen years and five years data from 20-year simulation data were used to derive the weighting coefficients and cross-validate the prediction skills of five <span class="hlt">ensemble</span> methods. The total number of training and evaluation is 20 times through a cyclic method from 20 years data. The Mul_Reg (EWA) method among the five <span class="hlt">ensemble</span> methods shows the best (worst) skill without regard to seasons and variables during the training period. And the PEA_RAC and PEA_ROC show very similar skills with Mul_Reg for all variables and seasons during training period. However, the skills and stabilities of Mul_Reg are drastically reduced when it applied to prediction regardless of variables and seasons. However, the skills and stabilities of PEA_RAC are slightly reduced. As a result, the PEA_RAC shows the best skill without regard to the seasons and variables during the prediction period. This result confirms that the new <span class="hlt">ensemble</span> methods developed in this study, the PEA_RAC, can be used for the prediction of regional climate without regard to the variables and averaging time scale. In addition, the simplicity of deriving process of weighting coefficients and applications are also the strong points of the <span class="hlt">ensemble</span> method, PEA_RAC.</p> <div class="credits"> <p class="dwt_author">Suh, M. S.; Oh, S. G.; Lee, D. K.; Cha, D. H.; Choi, S. J.; Hong, S. Y.; Kang, H. S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">175</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AtmEn..81....1A"> <span id="translatedtitle">Statistical <span class="hlt">downscaling</span> of an air quality model using Fitted Empirical Orthogonal Functions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). Statistical <span class="hlt">downscaling</span> methods in geophysics often rely on Empirical Orthogonal Functions (EOFs). EOFs are spatial Principal Components (PCs) that display space-time modes of variability of a quantity over a region. Here we present a novel statistical <span class="hlt">downscaling</span> method that employs Fitted Empirical Orthogonal Functions (F-EOFs) to provide local forecasts. F-EOFs differ from EOFs in that they represent space-time variations associated with a particular location through the use of inverse regression. We illustrate our <span class="hlt">downscaling</span> method, for ozone levels over the US, with the Regional chEmical trAnsport Model (REAM) whose outputs are over 70 by 70 km grid cells. We use ground level ozone observations from monitoring stations within the south-eastern US region to <span class="hlt">downscale</span> REAM. We select the first leading F-EOFs and regress our observations on the corresponding F-EOF loadings. We also compare our results to linear regression and PC regression. The regression on F-EOFs shows the best predictive ability. To examine the consistency of our results we repeat the analysis for different fitting and validation periods. Furthermore, in our application, PFC regression also outperforms PC regression as a dimension reduction technique.</p> <div class="credits"> <p class="dwt_author">Alkuwari, Farha A.; Guillas, Serge; Wang, Yuhang</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">176</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JHyd..488...84M"> <span id="translatedtitle">Assessing future rainfall projections using multiple GCMs and a multi-site stochastic <span class="hlt">downscaling</span> model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">SummaryImpact of global warming on daily rainfall is examined using atmospheric variables from five General Circulation Models (GCMs) and a stochastic <span class="hlt">downscaling</span> model. Daily rainfall at eleven raingauges over Malaprabha catchment of India and National Center for Environmental Prediction (NCEP) reanalysis data at grid points over the catchment for a continuous time period 1971-2000 (current climate) are used to calibrate the <span class="hlt">downscaling</span> model. The <span class="hlt">downscaled</span> rainfall simulations obtained using GCM atmospheric variables corresponding to the IPCC-SRES (Intergovernmental Panel for Climate Change - Special Report on Emission Scenarios) A2 emission scenario for the same period are used to validate the results. Following this, future <span class="hlt">downscaled</span> rainfall projections are constructed and examined for two 20 year time slices viz. 2055 (i.e. 2046-2065) and 2090 (i.e. 2081-2100). The model results show reasonable skill in simulating the rainfall over the study region for the current climate. The <span class="hlt">downscaled</span> rainfall projections indicate no significant changes in the rainfall regime in this catchment in the future. More specifically, 2% decrease by 2055 and 5% decrease by 2090 in monsoon (JJAS) rainfall compared to the current climate (1971-2000) under global warming conditions are noticed. Also, pre-monsoon (JFMAM) and post-monsoon (OND) rainfall is projected to increase respectively, by 2% in 2055 and 6% in 2090 and, 2% in 2055 and 12% in 2090, over the region. On annual basis slight decreases of 1% and 2% are noted for 2055 and 2090, respectively.</p> <div class="credits"> <p class="dwt_author">Mehrotra, R.; Sharma, Ashish; Nagesh Kumar, D.; Reshmidevi, T. V.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">177</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://civil.iisc.ernet.in/~nagesh/pubs/49_JoC_Anandhi_Temperature_Mar09.pdf"> <span id="translatedtitle">Role of predictors in <span class="hlt">downscaling</span> surface temperature to river basin in India for IPCC SRES scenarios using support vector machine</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, <span class="hlt">downscaling</span> models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (Tmax and Tmin) to river-basin scale. The effectiveness of the model is demonstrated through application to <span class="hlt">downscale</span> the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region.</p> <div class="credits"> <p class="dwt_author">Aavudai Anandhi; V. V. Srinivas; D. Nagesh Kumara; Ravi S. Nanjundiahb</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">178</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48915887"> <span id="translatedtitle">Subregional and <span class="hlt">downscaled</span> global scenarios of nutrient transfer in river basins: Seine-Somme-Scheldt case study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In an attempt to <span class="hlt">downscale</span> the global prospective scenarios established by the Millennium Ecosystem Assessment to the level of three individual watersheds (the Seine, Somme, and Scheldt rivers), we examined the application of the regional RIVERSTRAHLER model, based on a mechanistic representation of in-stream processes, in tandem with the semiempirical Global Nutrient Export from Watersheds (NEWS) model, by <span class="hlt">downscaling</span> the</p> <div class="credits"> <p class="dwt_author">Vincent Thieu; Emilio Mayorga; Gilles Billen; Josette Garnier</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">179</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.sscnet.ucla.edu/~yxue/pdf/2011GaoAAS.pdf"> <span id="translatedtitle">ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 28, NO. 5, 2011, 10771098 Assessment of Dynamic <span class="hlt">Downscaling</span> of the Extreme Rainfall</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">of the Extreme Rainfall over East Asia Using a Regional Climate Model GAO Yanhong 1 (Ã? ), Yongkang XUE2 , PENG This study investigates the capability of the dynamic <span class="hlt">downscaling</span> method (DDM) in an East Asian climate study of dynamic <span class="hlt">downscaling</span> of the extreme rainfall over East Asia using a regional climate model. Adv. Atmos. Sci</p> <div class="credits"> <p class="dwt_author">Xue, Yongkang</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">180</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1611713F"> <span id="translatedtitle">NARCliM regional <span class="hlt">downscaling</span> project in Australia: Long-term climatological analysis of the control period</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modeling project for the Australian area. It will provide a comprehensive dynamically <span class="hlt">downscaled</span> climate dataset for the CORDEX-AustralAsia region at 50km, and South-East Australia at a resolution of 10km. NARCliM data will be used by state governments to design their climate change adaptation plans. It runs an <span class="hlt">ensemble</span> of WRF simulations using three different physical configurations and four different GCMs for the present and future periods along three different time-windows (1990-2010, 2020-2040 and 2060-2080). We will present the validation of the control period (1950-2009) using the NNRP re-analysis. Simulated climatologies are compared with observed ones from a gridded data-set (AWAP) comparing observed and simulated seasonal climatologies and long-term series based on the climatological sensitivity to different climate indices (representing modes of variability including ENSO, the Indian Ocean Dipole, and the Southern Annular Mode which affect the Australia climate). Results show that the performance of the simulated climate presents a regional (from tropical to desert areas), seasonal and variable (precipitation and minimum/maximum daily temperatures) sensitivity without a clear outperforming physical configuration. Long-term analysis (mostly by means of correlations with the time-series of the indices) shows that increasing spatial resolution has a positive impact on how the model represents the continental climate response to the large scale and improves the results from the data providing the boundary conditions (NNRP) taking the response of the observations as the reference.</p> <div class="credits"> <p class="dwt_author">Fita, Lluís; Argüeso, Daniel; Evans, Jason P.; King, Andrew D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a 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href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_11");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">181</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014GMDD....7.7121M"> <span id="translatedtitle">Technical challenges and solutions in representing lakes when using WRF in <span class="hlt">downscaling</span> applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Weather Research and Forecasting (WRF) model is commonly used to make high resolution future projections of regional climate by <span class="hlt">downscaling</span> global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional <span class="hlt">downscaled</span> fields, inland lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for <span class="hlt">downscaling</span> simulations are presented and contrasted.</p> <div class="credits"> <p class="dwt_author">Mallard, M. S.; Nolte, C. G.; Spero, T. L.; Bullock, O. R.; Alapaty, K.; Herwehe, J. A.; Gula, J.; Bowden, J. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">182</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1614240H"> <span id="translatedtitle">Multivariate <span class="hlt">Ensemble</span> Sensitivity with Localization</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">So far in the literature, covariance localization (tapering) has not been applied when performing <span class="hlt">ensemble</span> sensitivity analysis. Sampling error in computing the sensitivities via lagged covariances leads to an over-estimation of the impact of a perturbation. Most commonly when computing sensitivities, the analysis covariance is approximated with the corresponding diagonal matrix. Two consequences follow: (1) the multi-variate sensitivity is approximated by a univariate sensitivity, and (2) sampling error in off-diagonal elements are obviated. It is unknown, however, how much information is lost by ignoring the off-diagonal elements in the full covariance. When forecasts depend on many details of the previous analysis, it is reasonable to expect that the diagonal approximation is too severe. The purpose of this presentation is to clarify the effects of the diagonal approximation, and investigate the need for localization when off-diagonal elements are considered. Motivated by examples arising from sensitivities estimated within a cycling mesoscale <span class="hlt">ensemble</span> data assimilation system, for easier interpretation we turn to the two-scale model first presented by Lorenz in 2005. We show that for most problems, an efficient matrix inversion is possible by finding a minimum-norm solution, and employing appropriate matrix factorization. Comparing the full inversion with off-diagonal elements, the fine-scale sensitivity estimates can be substantially different from those arising when the diagonal approximation is used. Localization on the sensitivity can be handled by an off-line empirical or Bayesian estimation technique. Because the sensitivity estimated from the full inversion is subject to sampling error, it is sensitive to the localization. The results show that compared to typical practices, more complete <span class="hlt">ensemble</span> sensitivity formulations may be needed to draw robust inferences in general.</p> <div class="credits"> <p class="dwt_author">Hacker, Joshua; Lei, Lili</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">183</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/quant-ph/0201128v2"> <span id="translatedtitle">Entangling many atomic <span class="hlt">ensembles</span> through laser manipulation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We propose an experimentally feasible scheme to generate Greenberger-Horne-Zeilinger (GHZ) type of maximal entanglement between many atomic <span class="hlt">ensembles</span> based on laser manipulation and single-photon detection. The scheme, with inherent fault tolerance to the dominant noise and efficient scaling of the efficiency with the number of <span class="hlt">ensembles</span>, allows to maximally entangle many atomic <span class="hlt">ensemble</span> within the reach of current technology. Such a maximum entanglement of many <span class="hlt">ensembles</span> has wide applications in demonstration of quantum nonlocality, high-precision spectroscopy, and quantum information processing.</p> <div class="credits"> <p class="dwt_author">L. -M. Duan</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-28</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">184</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014SGeo...35..765F"> <span id="translatedtitle"><span class="hlt">Downscaling</span> Satellite Precipitation with Emphasis on Extremes: A Variational ?1-Norm Regularization in the Derivative Domain</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for <span class="hlt">downscaling</span> and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for <span class="hlt">downscaling</span> satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the <span class="hlt">downscaling</span> problem as a discrete inverse problem and solve it via a regularized variational approach (variational <span class="hlt">downscaling</span>) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ?1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse <span class="hlt">downscaling</span> methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the <span class="hlt">downscaling</span> of a hurricane precipitation field.</p> <div class="credits"> <p class="dwt_author">Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">185</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012HESSD...9.9847G"> <span id="translatedtitle">Comparing dynamical, stochastic and combined <span class="hlt">downscaling</span> approaches - lessons from a case study in the Mediterranean region</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Various <span class="hlt">downscaling</span> techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Such techniques may be grouped into two <span class="hlt">downscaling</span> approaches: the deterministic dynamical <span class="hlt">downscaling</span> (DD) and the stochastic statistical <span class="hlt">downscaling</span> (SD). Although SD has been traditionally seen as an alternative to DD, recent works on statistical <span class="hlt">downscaling</span> have aimed to combine the benefits of these two approaches. The overall objective of this study is to examine the relative benefits of each <span class="hlt">downscaling</span> approach and their combination in making the GCM scenarios suitable for basin scale hydrological applications. The case study presented here focuses on the Apulia region (South East of Italy, surface area about 20 000 km2), characterized by a typical Mediterranean climate; the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined for the period 1953-2000. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile transform. The SD resulted efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but it was not able to correct the miss-modeled non-stationary components of the GCM dynamics. The DD provided a partial correction by enhancing the trend spatial heterogeneity and time evolution predicted by the GCM, although the comparison with observations resulted still underperforming. The best results were obtained through the combination of both DD and SD approaches.</p> <div class="credits"> <p class="dwt_author">Guyennon, N.; Romano, E.; Portoghese, I.; Salerno, F.; Calmanti, S.; Petrangeli, A. B.; Tartari, G.; Copetti, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">186</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..1213118B"> <span id="translatedtitle">Long-range Prediction of climatic Change in the Eastern Seaboard of Thailand over the 21st Century using various <span class="hlt">Downscaling</span> Approaches</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Triggered by a long drought, a huge water supply crisis took place at the Eastern Seaboard of Thailand (east of the Gulf of Thailand) in 2005. In that year no rainfall occurred for four months after the beginning of the rainy season which led to the situation that the industrial estates of the Eastern Seaboard were not able to fully operate. Normally, most of the urban and industrial water used in this coastal region along east of the Gulf of Thailand, which is part of the Pacific Ocean, is surface water stored in a large-scale reservoir-network across the main watershed in the region. Thus the three major reservoirs usually gather water from monsoon storms that blow from the South and provide accumulative 80% of the annual rainfall during the 6 months of the rainy season which normally lasts from May-October. During the dry season (November - April) the winds are blowing from northern Indo-China land mass and rain drops only a few days in a month. Because of this typical tropical climate system, surface water resources across most of the southeastern Asia-Pacific region and the Eastern Seaboard of Thailand, in particular, rely on the annual occurrence of the monsoon season. There is now sufficient evidence that the named extreme weather conditions of 2005 occurring in that part of Thailand are not a singularity, but might be another signal of recent ongoing climate change in that country as a whole. Because of this imminent threat to the water resources of the region, and for the set-up of appropriate water management schemes for the near future, a climate impact study is proposed here. More specifically, the water budget of the Khlong Yai basin, which is the main watershed of the Eastern Seaboard, is modeled using the distributed hydrological model SWAT. To that avail the watershed model is coupled sequentially to a global climate model (GCM), whereby the latter provides the input forcing parameters (e.g. precipitation and temperature) to the former. Because of the different scales of the hydrological (local to regional) and of the GCM (global), one is faced with the problem of '<span class="hlt">downscaling</span>' the coarse grid resolution output of the GCM to the fine grid of the hydrological model. Although there have been numerous <span class="hlt">downscaling</span> approaches proposed to that regard over the last decade, the jury is still out about the best method to use in a particular application. The focus here is on the <span class="hlt">downscaling</span> part of the investigation, i.e. the proper preparation of the GCM's output to serve as input, i.e. the driving force, to the hydrological model (which is not further discussed here). Daily <span class="hlt">ensembles</span> of climate variables computed by means of the CGCM3 model of the Canadian Climate Center which has a horizontal grid resolution of approximately the size of the whole study basin are used here, indicating clearly the need for <span class="hlt">downscaling</span>. Daily observations of local climate variables available since 1971 are used as additional input to the various <span class="hlt">downscaling</span> tools proposed which are, namely, the stochastic weather generator (LARS-WG), the statistical <span class="hlt">downscaling</span> model (SDSM), and a multiple linear regression model between the observed variables and the CGCM3 predictors. Both the 2D and the 3D versions of the CGCM3 model are employed to predict, 100 years ahead up to year 2100, the monthly rainfall and temperatures, based on the past calibration period (training period) 1971-2000. To investigate the prediction performance, multiple linear regression, autoregressive (AR) and autoregressive integrated moving average (ARIMA) models are applied to the time series of the observation data which are aggregated into monthly time steps to be able compare them with the <span class="hlt">downscaling</span> results above. Likewise, multiple linear regression and ARIMA models also executed on the CGCM3 predictors and the Pacific / Indian oceans indices as external regressors to predict short-term local climate variations. The results of the various <span class="hlt">downscaling</span> method are validated for years 2001-2006 at selected meteorological stations in the Khlong Yai basin, assuming t</p> <div class="credits"> <p class="dwt_author">Bejranonda, Werapol; Koch, Manfred; Koontanakulvong, Sucharit</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">187</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.risoe.dk/rispubl/NEI/NEI-DK-4552.pdf"> <span id="translatedtitle">PSO (FU 2101) <span class="hlt">Ensemble</span>-forecasts for wind power</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">PSO (FU 2101) <span class="hlt">Ensemble</span>-forecasts for wind power Wind Power <span class="hlt">Ensemble</span> Forecasting Using Wind Speed the problems of (i) transforming the meteorological <span class="hlt">ensembles</span> to wind power <span class="hlt">ensembles</span> and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of <span class="hlt">ensemble</span> forecast</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">188</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/19951698"> <span id="translatedtitle">Quasiparticle-<span class="hlt">Ensemble</span> Theory for a Normal Fermi Liquid</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A quasiparticle <span class="hlt">ensemble</span> (Q <span class="hlt">ensemble</span>) is constructed in which the number of quasiparticles with momentum k in the <span class="hlt">ensemble</span> is conserved. The thermodynamic properties of this <span class="hlt">ensemble</span> are related to those of the grand canonical <span class="hlt">ensemble</span>. By comparison with explicit microscopic predictions of the theory, it is shown that this formulation is necessary if the third law of thermodynamics is</p> <div class="credits"> <p class="dwt_author">F. Mohling; E. R. Tuttle</p> <p class="dwt_publisher"></p> <p class="publishDate">1967-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">189</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EOSTr..94..424B"> <span id="translatedtitle">The Practitioner's Dilemma: How to Assess the Credibility of <span class="hlt">Downscaled</span> Climate Projections</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections <span class="hlt">downscaled</span> from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web-based access to a proliferation of high-resolution climate projections derived with differing <span class="hlt">downscaling</span> methods.</p> <div class="credits"> <p class="dwt_author">Barsugli, Joseph J.; Guentchev, Galina; Horton, Radley M.; Wood, Andrew; Mearns, Linda O.; Liang, Xin-Zhong; Winkler, Julie A.; Dixon, Keith; Hayhoe, Katharine; Rood, Richard B.; Goddard, Lisa; Ray, Andrea; Buja, Lawrence; Ammann, Caspar</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">190</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H43A1168F"> <span id="translatedtitle">Statistical <span class="hlt">Downscaling</span> of Gridded Rainfall and Their Impacts on Hydrological Response Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Water resource management and planning increasingly need to incorporate the effects of global climate change on regional climate variability in order to accurately assess future water supplies. Therefore future climate projections, particularly of rainfall, are of utmost interest to water resource management and water-users. General circulation models (GCMs) are the primary tool used to simulate present climate and project future climate. The outputs of GCMs are useful in understanding how future global climate responds to prescribed greenhouse gases emission scenarios. However GCMs do not provide realistic daily rainfall at scales below about 200 km, at which hydrological processes are typically assessed. Statistical <span class="hlt">downscaling</span> techniques have been developed to resolve the scale discrepancy between GCM climate change scenarios and the resolution required for hydrological impact assessment, based on the assumption that large-scale atmospheric conditions have a strong influence on local-scale weather. Gridded rainfall is important for a variety of scientific and engineering applications, including climate change detection, the evaluation of climate models, the parameterization of stochastic weather generators, as well as assessment of climate change impacts on regional hydrological regimes and water availability, whereas statistical <span class="hlt">downscaling</span> has predominantly provided daily rainfall series at the site (point) scale. The first part of the study explores the application of statistical <span class="hlt">downscaling</span> to gridded rainfall datasets using three methods: 1) statistically <span class="hlt">downscaling</span> to sites and then post-processing to interpolate to gridded rainfall; 2) treating each grid cell as an "observed" site for statistical <span class="hlt">downscaling</span> directly; and 3) treating each sub-catchment as an "observed" site and statistically <span class="hlt">downscaling</span> to sub-catchment averaged rainfall. The statistical <span class="hlt">downscaling</span> Nonhomogeneous Hidden Markov Model (NHMM), which models multi-site patterns of daily rainfall as a finite number of 'hidden' (i.e. unobserved) weather states, is used for a study region comprising several catchments of the southern Murray-Darling Basin (MDB) in south-eastern Australia, which until this year has been experiencing a decade long drought. The second part of the study investigates the impacts of different gridded rainfall on the hydrological response analysis by inputting them in to the calibrated hydrological model. These research results can be used as reference for application of statistical <span class="hlt">downscaling</span> method to generate gridded daily rainfall to quantify the hydrological responses to climatic change for long-term water management strategies.</p> <div class="credits"> <p class="dwt_author">Fu, G.; Charles, S. P.; Chiew, F. H.; Teng, J.; Frost, A. J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">191</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70007520"> <span id="translatedtitle"><span class="hlt">Downscaling</span> future climate scenarios to fine scales for hydrologic and ecological modeling and analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the <span class="hlt">downscaling</span> while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale <span class="hlt">downscaling</span> to analyses of ecological processes influenced by topographic complexity.</p> <div class="credits"> <p class="dwt_author">Flint, Lorraine E.; Flint, Alan L.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">192</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010ems..confE.401T"> <span id="translatedtitle">Climate change scenarios of temperature and precipitation over five Italian regions for the period 2021-2050 obtained by statistical <span class="hlt">downscaling</span> models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Climate change scenarios of seasonal maximum, minimum temperature and precipitation in five Italian regions, over the period 2021-2050 against 1961-1990 are assessed. The regions selected by the AGROSCENARI project are important from the local agricultural practises and are situated as follows: in the Northern Italy - Po valley and hilly area of Faenza; in Central part of Italy- Marche, Beneventano and Destra Sele, and in Sardinia Island - Oristano. A statistical <span class="hlt">downscaling</span> technique applied to the <span class="hlt">ENSEMBLES</span> global climate simulations, A1B scenario, is used to reach this objective. The method consists of a multivariate regression, based on Canonical Correlation Analysis, using as possible predictors mean sea level pressure, geopotential height at 500hPa and temperature at 850 hPa. The observational data set (predictands) for the selected regions is composed by a reconstruction of minimum, maximum temperature and precipitation daily data on a regular grid with a spatial resolution of 35 km, for 1951-2009 period (managed by the Meteorological and Climatological research unit for agriculture - Agricultural Research Council, CRA - CMA). First, a set-up of statistical model has been made using predictors from ERA40 reanalysis and the seasonal indices of temperature and precipitation from local scale, 1958-2002 period. Then, the statistical <span class="hlt">downscaling</span> model has been applied to the predictors derived from the <span class="hlt">ENSEMBLES</span> global climate models, A1B scenario, in order to obtain climate change scenario of temperature and precipitation at local scale, 2021-2050 period. The projections show that increases could be expected to occur under scenario conditions in all seasons, in both minimum and maximum temperature. The magnitude of changes is more intense during summer when the changes could reach values around 2°C for minimum and maximum temperature. In the case of precipitation, the pattern of changes is more complex, different from season to season and over the regions, a reduction of precipitation could be expected to occur during summer. The temperature and precipitation projections from hilly area of Faenza are then used as input in a weather generator, in order to produce a synthetic series of daily data. These series feed a water balance and crop growth model (CRITERIA) to evaluate the impact of climate change scenario in irrigation crop water needs, for 2021-2050 period. As reference crop the kiwifruit, which is characterised by high water need and widespread in this area, has been selected.</p> <div class="credits"> <p class="dwt_author">Tomozeiu, R.; Tomei, F.; Villani, G.; Pasqui, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">193</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cdc.noaa.gov/people/jeffrey.s.whitaker/Manuscripts/hybridpaper.pdf"> <span id="translatedtitle">A Comparison of Hybrid <span class="hlt">Ensemble</span> Transform Kalman Filter-OI and <span class="hlt">Ensemble</span> Square-Root Filter</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">A Comparison of Hybrid <span class="hlt">Ensemble</span> Transform Kalman Filter- OI and <span class="hlt">Ensemble</span> Square-Root Filter) 497-4434 1 #12;Abstract A hybrid <span class="hlt">ensemble</span> transform Kalman filter (ETKF)-optimum interpolation (OI network was used, and the OI method utilized a static background error covariance constructed from a large</p> <div class="credits"> <p class="dwt_author">Whitaker, Jeffrey S.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">194</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JMP....54h3507D"> <span id="translatedtitle">The beta-Wishart <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We introduce a "broken-arrow" matrix model for the ?-Wishart <span class="hlt">ensemble</span>, which improves on the traditional bidiagonal model by generalizing to non-identity covariance parameters. We prove that its joint eigenvalue density involves the correct hypergeometric function of two matrix arguments, and a continuous parameter ? > 0. If we choose ? = 1, 2, 4, we recover the classical Wishart <span class="hlt">ensembles</span> of general covariance over the reals, complexes, and quaternions. Jack polynomials are often defined as the eigenfunctions of the Laplace-Beltrami operator. We prove that Jack polynomials are in addition eigenfunctions of an integral operator defined as an average over a ?-dependent measure on the sphere. When combined with an identity due to Stanley, we derive a definition of Jack polynomials. An efficient numerical algorithm is also presented for simulations. The algorithm makes use of secular equation software for broken arrow matrices currently unavailable in the popular technical computing languages. The simulations are matched against the cdfs for the extreme eigenvalues. The techniques here suggest that arrow and broken arrow matrices can play an important role in theoretical and computational random matrix theory including the study of corners processes. We provide a number of simulations illustrating the extreme eigenvalue distributions that are likely to be useful for applications. We also compare the n ? ? answer for all ? with the free-probability prediction.</p> <div class="credits"> <p class="dwt_author">Dubbs, Alexander; Edelman, Alan; Koev, Plamen; Venkataramana, Praveen</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">195</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/5206885"> <span id="translatedtitle">Forecast of iceberg <span class="hlt">ensemble</span> drift</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The objectives of the study are to gain a better understanding of the characteristics of iceberg motion and the factors controlling iceberg drift, and to develop an iceberg <span class="hlt">ensemble</span> drift forecast system to be operated by the Canadian Atmospheric Environment Service. An extensive review of field and theoretical studies on iceberg behaviour, and the factors controlling iceberg motion has been carried out. Long term and short term behaviour of icebergs are critically examined. A quantitative assessment of the effects of the factors controlling iceberg motion is presented. The study indicated that wind and currents are the primary driving forces. Coriolis Force and ocean surface slope also have significant effects. As for waves, only the higher waves have a significant effect. Iceberg drift is also affected by iceberg size characteristics. Based on the findings of the study a comprehensive computerized forecast system to predict the drift of iceberg <span class="hlt">ensembles</span> off Canada's east coast has been designed. The expected accuracy of the forecast system is discussed and recommendations are made for future improvements to the system.</p> <div class="credits"> <p class="dwt_author">El-Tahan, M.S.; El-Tahan, H.W.; Venkatesh, S.</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">196</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2990198"> <span id="translatedtitle">A Spatio-Temporal <span class="hlt">Downscaler</span> for Output From Numerical Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial coverage of the region of interest, high temporal resolution, no missing data but consequential calibration concerns. The second tends to be sparsely collected in space with coarser temporal resolution, often with missing data but, where recorded, provides, essentially, the true value. Accommodating the spatial misalignment between the two types of data is of fundamental importance for both improved predictions of exposure as well as for evaluation and calibration of the numerical model. In this article we propose a simple, fully model-based strategy to <span class="hlt">downscale</span> the output from numerical models to point level. The static spatial model, specified within a Bayesian framework, regresses the observed data on the numerical model output using spatially-varying coefficients which are specified through a correlated spatial Gaussian process. As an example, we apply our method to ozone concentration data for the eastern U.S. and compare it to Bayesian melding (Fuentes and Raftery 2005) and ordinary kriging (Cressie 1993; Chilès and Delfiner 1999). Our results show that our method outperforms Bayesian melding in terms of computing speed and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with our method are better calibrated and predictive intervals have empirical coverage closer to the nominal values. Moreover, our model can be easily extended to accommodate for the temporal dimension. In this regard, we consider several spatio-temporal versions of the static model. We compare them using out-of-sample predictions of ozone concentration for the eastern U.S. for the period May 1–October 15, 2001. For the best choice, we present a summary of the analysis. Supplemental material, including color versions of Figures 4, 5, 6, 7, and 8, and MCMC diagnostic plots, are available online. PMID:21113385</p> <div class="credits"> <p class="dwt_author">Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">197</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhDT.......191S"> <span id="translatedtitle">Climate Modeling & <span class="hlt">Downscaling</span> for Semi-Arid Regions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study performs numerical modeling for the climate of semi-arid regions by running a high-resolution atmospheric model constrained by large-scale climatic boundary conditions, a practice commonly called climate <span class="hlt">downscaling</span>. These investigations focus especially on precipitation and temperature, quantities that are critical to life in semi-arid regions. Using the Weather Research and Forecast (WRF) model, a non-hydrostatic geophysical fluid dynamical model with a full suite of physical parameterization, a series of numerical sensitivity experiments are conducted to test how the intensity and spatial/temporal distribution of precipitation change with grid resolution, time step size, the resolution of lower boundary topography and surface characteristics. Two regions, Arizona in U.S. and Aral Sea region in Central Asia, are chosen as the test-beds for the numerical experiments: The former for its complex terrain and the latter for the dramatic man-made changes in its lower boundary conditions (the shrinkage of Aral Sea). Sensitivity tests show that the parameterization schemes for rainfall are not resolution-independent, thus a refinement of resolution is no guarantee of a better result. But, simulations (at all resolutions) do capture the inter-annual variability of rainfall over Arizona. Nevertheless, temperature is simulated more accurately with refinement in resolution. Results show that both seasonal mean rainfall and frequency of extreme rainfall events increase with resolution. For Aral Sea, sensitivity tests indicate that while the shrinkage of Aral Sea has a dramatic impact on the precipitation over the confine of (former) Aral Sea itself, its effect on the precipitation over greater Central Asia is not necessarily greater than the inter-annual variability induced by the lateral boundary conditions in the model and large scale warming in the region. The numerical simulations in the study are cross validated with observations to address the realism of the regional climate model. The findings of this sensitivity study are useful for water resource management in semi-arid regions. Such high spatio-temporal resolution gridded-data can be used as an input for hydrological models for regions such as Arizona with complex terrain and sparse observations. Results from simulations of Aral Sea region are expected to contribute to ecosystems management for Central Asia.</p> <div class="credits"> <p class="dwt_author">Sharma, Ashish</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">198</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhRvA..86a2310B"> <span id="translatedtitle">Optimizing inhomogeneous spin <span class="hlt">ensembles</span> for quantum memory</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We propose a method to maximize the fidelity of quantum memory implemented by a spectrally inhomogeneous spin <span class="hlt">ensemble</span>. The method is based on preselecting the optimal spectral portion of the <span class="hlt">ensemble</span> by judiciously designed pulses. This leads to significant improvement of the transfer and storage of quantum information encoded in the microwave or optical field.</p> <div class="credits"> <p class="dwt_author">Bensky, Guy; Petrosyan, David; Majer, Johannes; Schmiedmayer, Jörg; Kurizki, Gershon</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">199</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4109431"> <span id="translatedtitle">Conductor gestures influence evaluations of <span class="hlt">ensemble</span> performance</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Previous research has found that listener evaluations of <span class="hlt">ensemble</span> performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of <span class="hlt">ensemble</span> performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber <span class="hlt">ensemble</span> in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the <span class="hlt">ensemble’s</span> articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the <span class="hlt">ensemble’s</span> performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall <span class="hlt">ensemble</span> expressivity. PMID:25104944</p> <div class="credits"> <p class="dwt_author">Morrison, Steven J.; Price, Harry E.; Smedley, Eric M.; Meals, Cory D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">200</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/0801.4219v1"> <span id="translatedtitle">Statistical <span class="hlt">Ensembles</span> with Fluctuating Extensive Quantities</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We suggest an extension of the standard concept of statistical <span class="hlt">ensembles</span>. Namely, we introduce a class of <span class="hlt">ensembles</span> with extensive quantities fluctuating according to an externally given distribution. As an example the influence of energy fluctuations on multiplicity fluctuations in limited segments of momentum space for a classical ultra-relativistic gas is considered.</p> <div class="credits"> <p class="dwt_author">M. I. Gorenstein; M. Hauer</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-28</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_9");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_12");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">201</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4183303"> <span id="translatedtitle">Visual stimuli recruit intrinsically generated cortical <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">The cortical microcircuit is built with recurrent excitatory connections, and it has long been suggested that the purpose of this design is to enable intrinsically driven reverberating activity. To understand the dynamics of neocortical intrinsic activity better, we performed two-photon calcium imaging of populations of neurons from the primary visual cortex of awake mice during visual stimulation and spontaneous activity. In both conditions, cortical activity is dominated by coactive groups of neurons, forming <span class="hlt">ensembles</span> whose activation cannot be explained by the independent firing properties of their contributing neurons, considered in isolation. Moreover, individual neurons flexibly join multiple <span class="hlt">ensembles</span>, vastly expanding the encoding potential of the circuit. Intriguingly, the same coactive <span class="hlt">ensembles</span> can repeat spontaneously and in response to visual stimuli, indicating that stimulus-evoked responses arise from activating these intrinsic building blocks. Although the spatial properties of stimulus-driven and spontaneous <span class="hlt">ensembles</span> are similar, spontaneous <span class="hlt">ensembles</span> are active at random intervals, whereas visually evoked <span class="hlt">ensembles</span> are time-locked to stimuli. We conclude that neuronal <span class="hlt">ensembles</span>, built by the coactivation of flexible groups of neurons, are emergent functional units of cortical activity and propose that visual stimuli recruit intrinsically generated <span class="hlt">ensembles</span> to represent visual attributes. PMID:25201983</p> <div class="credits"> <p class="dwt_author">Miller, Jae-eun Kang; Ayzenshtat, Inbal; Carrillo-Reid, Luis; Yuste, Rafael</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">202</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/186357"> <span id="translatedtitle">Decimated Input <span class="hlt">Ensembles</span> for Improved Generalization</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Using an <span class="hlt">ensemble</span> of classifiers instead ofa single classifier has been demonstrated to improve generalizationperformance in many difficult problems. However,for this improvement to take place it is necessary tomake the classifiers in an <span class="hlt">ensemble</span> more complementary.In this paper, we highlight the need to reduce the correlationamong the component classifiers and investigate one methodfor correlation reduction: input decimation. We elaborateon input</p> <div class="credits"> <p class="dwt_author">Kagan Tumer; Moffett Field; Ca Nikunj C. Oza</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">203</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/1093136"> <span id="translatedtitle">Image Change Detection via <span class="hlt">Ensemble</span> Learning</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work, we explore the use of <span class="hlt">ensemble</span> learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. <span class="hlt">Ensemble</span> learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the <span class="hlt">ensemble</span>. The strength of the <span class="hlt">ensemble</span> lies in the fact that the individual classifiers in the <span class="hlt">ensemble</span> create a mixture of experts in which the final classification made by the <span class="hlt">ensemble</span> classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of <span class="hlt">ensemble</span> learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the <span class="hlt">ensemble</span> method has approximately 11.5% higher change detection accuracy than an individual classifier.</p> <div class="credits"> <p class="dwt_author">Martin, Benjamin W [ORNL] [ORNL; Vatsavai, Raju [ORNL] [ORNL</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">204</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8743E..05M"> <span id="translatedtitle">Image change detection via <span class="hlt">ensemble</span> learning</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work, we explore the use of <span class="hlt">ensemble</span> learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. <span class="hlt">Ensemble</span> learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the <span class="hlt">ensemble</span>. The strength of the <span class="hlt">ensemble</span> lies in the fact that the individual classifiers in the <span class="hlt">ensemble</span> create a "mixture of experts" in which the final classification made by the <span class="hlt">ensemble</span> classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of <span class="hlt">ensemble</span> learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the <span class="hlt">ensemble</span> method has approximately 11.5% higher change detection accuracy than an individual classifier.</p> <div class="credits"> <p class="dwt_author">Martin, Benjamin W.; Vatsavai, Ranga R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">205</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://webspace.utexas.edu/err449/IEEE_Kaheil_Rosero_2007.pdf"> <span id="translatedtitle"><span class="hlt">Downscaling</span> and Forecasting of Evapotranspiration Using a Synthetic Model of Wavelets and Support Vector Machines</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Providing reliable forecasts of evapotranspiration (ET) at farm level is a key element toward efficient water manage- ment in irrigated basins. This paper presents an algorithm that provides a means to <span class="hlt">downscale</span> and forecast dependent variables such as ET images. Using the discrete wavelet transform (DWT) and support vector machines (SVMs), the algorithm finds multiple relationships between inputs and outputs</p> <div class="credits"> <p class="dwt_author">Yasir H. Kaheil; Enrique Rosero; M. Kashif Gill; Mac McKee; Luis A. Bastidas</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">206</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=ftp://texmex.mit.edu/pub/emanuel/PAPERS/Emanuel_PNAS_2013.pdf"> <span id="translatedtitle"><span class="hlt">Downscaling</span> CMIP5 climate models shows increased tropical cyclone activity over the 21st century</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">of global warming on tropical cyclones. climate change | natural hazards Some 90 tropical cyclones develop of these additional factors to global climate change generally results in a reduction of the global frequency of tropical cyclones as the climate warms, seen in many explicit and <span class="hlt">downscaled</span> simulations using global</p> <div class="credits"> <p class="dwt_author">Rothman, Daniel</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">207</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014JHyd..516..304W"> <span id="translatedtitle">Evaluation of sampling techniques to characterize topographically-dependent variability for soil moisture <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> methods have been proposed to estimate catchment-scale soil moisture patterns from coarser resolution patterns. These methods usually infer the fine-scale variability in soil moisture using variations in ancillary variables like topographic attributes that have relationships to soil moisture. Previously, such relationships have been observed in catchments using soil moisture observations taken on uniform grids at hundreds of locations on multiple dates, but collecting data in this manner limits the applicability of this approach. The objective of this paper is to evaluate the effectiveness of two strategic sampling techniques for characterizing the relationships between topographic attributes and soil moisture for the purpose of constraining <span class="hlt">downscaling</span> methods. The strategic sampling methods are conditioned Latin hypercube sampling (cLHS) and stratified random sampling (SRS). Each sampling method is used to select a limited number of locations or dates for soil moisture monitoring at three catchments with detailed soil moisture datasets. These samples are then used to calibrate two available <span class="hlt">downscaling</span> methods, and the effectiveness of the sampling methods is evaluated by the ability of the <span class="hlt">downscaling</span> methods to reproduce the known soil moisture patterns. cLHS outperforms random sampling in almost every case considered. SRS usually performs better than cLHS when very few locations are sampled, but it can perform worse than random sampling for intermediate and large numbers of locations.</p> <div class="credits"> <p class="dwt_author">Werbylo, Kevin L.; Niemann, Jeffrey D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">208</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/3978102"> <span id="translatedtitle">The use of weather types and air flow indices for GCM <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A variety of different methods have been proposed for <span class="hlt">downscaling</span> large-scale General Circulation Model (GCM) output to the time and space scales required for climate impact studies. Using weather types to achieve this goal provides greater understanding of the problems that are involved compared to the many “black box” techniques that have been proposed. Analyses using Lamb weather types, counts</p> <div class="credits"> <p class="dwt_author">D. Conway; P. D. Jones</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">209</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ce.umn.edu/~foufoula/papers/efg_135.pdf"> <span id="translatedtitle"><span class="hlt">Downscaling</span> Satellite Precipitation with Emphasis on Extremes: A Variational `1-Norm Regularization</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">misspecification and explore a previously proposed dictionary-based sparse inverse <span class="hlt">downscaling</span> methodology is one of the key components of the water cycle and, as such, it has been the subject of intense research and Schertzer 1990; Kumar and Foufoula-Georgiou 1993a, b; Deidda 2000; Harris et al. 2001; Venugopal et al. 2006</p> <div class="credits"> <p class="dwt_author">Foufoula-Georgiou, Efi</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">210</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFM.H43G1537C"> <span id="translatedtitle">Spatial <span class="hlt">Downscaling</span> of TRMM Precipitation using MODIS product in the Korean Peninsula</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a <span class="hlt">downscaling</span> technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the <span class="hlt">downscaled</span> precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The <span class="hlt">downscaled</span> precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial <span class="hlt">downscaling</span> of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.</p> <div class="credits"> <p class="dwt_author">Cho, H.; Choi, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">211</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://civil.iisc.ernet.in/~pradeep/downscaling_awr.pdf"> <span id="translatedtitle">Statistical <span class="hlt">downscaling</span> of GCM simulations to streamflow using relevance vector machine</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical <span class="hlt">downscaling</span> based on sparse Bayesian learning and Relevance Vector Machine (RVM) to</p> <div class="credits"> <p class="dwt_author">Subimal Ghosh; P. P. Mujumdar</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">212</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.atmo.arizona.edu/~castro/Reviewedpubs/R-17.pdf"> <span id="translatedtitle">Climate change projection of snowfall in the Colorado River Basin using dynamical <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Climate change projection of snowfall in the Colorado River Basin using dynamical <span class="hlt">downscaling</span>] Recent observations show a decrease in the fraction of precipitation falling as snowfall in the western United States. In this work we evaluate a historical and future climate simulation over the Colorado</p> <div class="credits"> <p class="dwt_author">Castro, Christopher L.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">213</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20140010385&hterms=change+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dchange%2Bclimate"> <span id="translatedtitle">Statistical <span class="hlt">Downscaling</span> and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">Statistical <span class="hlt">downscaling</span> can be used to efficiently <span class="hlt">downscale</span> a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically <span class="hlt">downscales</span> (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical <span class="hlt">Downscaling</span> and Bias Correction (SDBC) approach. Based on these <span class="hlt">downscaled</span> data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical <span class="hlt">downscaling</span> as an intermediate step does not lead to considerable differences in the results of statistical <span class="hlt">downscaling</span> for the study domain.</p> <div class="credits"> <p class="dwt_author">Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">214</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70048367"> <span id="translatedtitle">Climate <span class="hlt">downscaling</span> effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">High-resolution (<span class="hlt">downscaled</span>) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different <span class="hlt">downscaling</span> approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between <span class="hlt">downscaling</span> approaches and that the variation attributable to <span class="hlt">downscaling</span> technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between <span class="hlt">downscaling</span> techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of <span class="hlt">downscaling</span> applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative <span class="hlt">downscaling</span> methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.</p> <div class="credits"> <p class="dwt_author">Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">215</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..1410077G"> <span id="translatedtitle">Comparing dynamical, stochastic, and combined <span class="hlt">downscaling</span> approaches. Lessons from a case study in the Mediterranean</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Various <span class="hlt">downscaling</span> techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Two approaches to <span class="hlt">downscaling</span> exist. The deterministic dynamical <span class="hlt">downscaling</span> (DD) nests a regional climate model (RCM) into the GCM to represent the atmospheric physics with a higher grid box resolution within a limited area of interest. The stochastic statistical <span class="hlt">downscaling</span> (SD) establishes statistical links between large scale weather models and local scale observations available at a finer spatial resolution. SD is traditionally seen as an alternative to DD. With the increasing reliability and availability of RCM scenarios, recent works on statistical <span class="hlt">downscaling</span> have aimed to combine the benefits of these two approaches. The overall objective of this study is to examine the relative benefits of each <span class="hlt">downscaling</span> approach and their combination in making the GCM scenarios suitable to feed hydrological impact models. The case-study presented here focuses on the Apulia region (South East of Italy, about 20,000 km2), characterized by a typical Mediterranean climate: the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined during the period 1953-2000. The adopted GCM is the fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology, and the DD was carried out with the Protheus system (ENEA) as RCM. The SD was performed through a monthly quantile-quantile transform. A further common step of statistical interpolation (SI) was applied to obtain spatial homogenization of the different <span class="hlt">downscaling</span> combinations. The SD is efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but is not able to correct the mis-modeled non-stationary components of the GCM dynamics. The DD provides a partial correction by enhancing the trends spatial heterogeneity and time evolution predicted by the GCM. However, the comparison with observation is still underperforming. Best results were obtained through the combination of both DD and SD approaches.</p> <div class="credits"> <p class="dwt_author">Guyennon, N.; Romano, E.; Portoghese, I.; Salerno, F.; Calmanti, S.; Petrangeli, A. B.; Bruno, E.; Tartari, G.; Copetti, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">216</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012AGUFM.H11N..07N"> <span id="translatedtitle"><span class="hlt">Downscaling</span> Soil Moisture Product from SMOS for Monitoring Agricultural Droughts in South America</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Availability of reliable near-surface soil moisture (SM) estimates at fine spatial resolutions of 1 km and at temporal resolutions of a few days is critical for accurate quantification of drought impacts on crop yields and recommending meaningful management and adaptation strategies. The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future NASA-Soil Moisture Active Passive (SMAP) missions provide unprecedented, global SM product every 2-3 days at spatial resolutions of ~50 km. In addition, the SMAP will provide a SM product at 10 km . <span class="hlt">Downscaling</span> the above SM products to 1km is essential for any meaningful drought-related application in agricultural terrains. Optimal <span class="hlt">downscaling</span> should retain information from higher-order moments and leverage information from auxiliary remote sensing products that are available at fine resolutions. In this study, a novel <span class="hlt">downscaling</span> methodology based upon information theory was implemented to obtain distributed SM at 1 km every 3 days, using the SM product from SMOS. Observations of land surface temperature (LST), leaf area index (LAI) and land cover (LC) at 1 km from MODIS, and precipitation at 25 km from TRMM, were used as auxiliary information to facilitate the <span class="hlt">downscaling</span> process. The use of information-theory in <span class="hlt">downscaling</span> provides a hierarchical decomposition of image data that is optimal in terms of the transfer of information across scales and is therefore a better alternative to methods that use second-order statistics only. The <span class="hlt">downscaling</span> methodology was implemented over the agricultural regions in the lower La Plata Basin (L-LPB) in South America. The L-LPB region is of great economic value in South America, where agricultural cover makes up about 25% of the continent's land area and is vulnerable to high losses in crop yields due to agricultural drought . Both remote sensing and in situ observations (precipitation, temperature, and soil moisture) obtained during the drought period of 2007-2008 were used to train the <span class="hlt">downscaling</span> methodology. Observations obtained during the growing season of 2010, during which ESA-SMOS observations were available, was used to demonstrate the feasibility of the methodology for monitoring agricultural droughts.</p> <div class="credits"> <p class="dwt_author">Nagarajan, K.; Fu, C.; Judge, J.; Fraisse, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">217</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.9432H"> <span id="translatedtitle">Statistical <span class="hlt">Downscaling</span> of Large-Scale Wind Signatures Using a Two-Step Approach</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> global scale climate data is an important issue in order to obtain high-resolution data desired for most applications in meteorology and hydrology and to gain a better understanding of local climate variability. Statistical <span class="hlt">downscaling</span> transforms data from large to local scale by relating punctual climate observations, climate model outputs and high-resolution surface data. In this study, a statistical <span class="hlt">downscaling</span> approach is used in combination with dynamical <span class="hlt">downscaling</span> in order to produce gust characteristics of wind storms on a small-scale grid over Europe. The idea is to relate large-scale data, regional climate model (RCM) data and observations by transfer functions, which are calibrated using physically consistent features of the RCM model simulations. In comparison to purely dynamical <span class="hlt">downscaling</span> by a regional model, such a statistical <span class="hlt">downscaling</span> approach has several advantages. The computing time is much shorter and, therefore, such an approach can be easily applied on very large numbers of windstorm cases provided e.g. by long-term GCM model simulations, like millennium runs. The first step of the approach constructs a relation between observations and COSMO-CLM signatures with the aim of calibrating the modelled signatures to the observations in terms of model output statistics. For this purpose, parameters of the theoretical Weibull distribution, estimated from the observations at each test site, are interpolated to a 7km RCM grid with Gaussian weights and are compared to Weibull parameters from the COSMO-CLM modelled gust distributions. This allows for an evaluation and correction of gust signatures by quantile mapping. The second step links the RCM wind signatures and large-scale data by a multiple linear regression (MLR) model. One model per grid point is trained using the COSMO-CLM simulated and MOS-corrected gusts for selected wind storm events as predictands, and the according NCEP reanalysis wind speeds of the surrounding NCEP grid points as predictors. For validation purposes, the model is again applied on NCEP reanalysis data. The statistical model is able to reproduce well the observed regional scale wind signatures. Afterwards, the statistical model is applied to ECHAM5 climate simulation data to generate large numbers of <span class="hlt">downscaled</span> wind gust signatures at high spatial resolution. For further analyses, statistical values as mean, minimum and maximum wind gust speeds are compared at every grid point.</p> <div class="credits"> <p class="dwt_author">Haas, R.; Born, K.; Georgiadis, A.; Karremann, M. K.; Pinto, J. G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">218</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70131483"> <span id="translatedtitle">On the <span class="hlt">downscaling</span> of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary"> <span class="hlt">Downscaling</span> is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for <span class="hlt">downscaling</span> MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and <span class="hlt">downscaling</span>. The regression with intercept method does have limitations in <span class="hlt">downscaling</span> if the slope and intercept are computed over a large area. A good agreement was obtained between <span class="hlt">downscaled</span> monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from ?16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and <span class="hlt">downscaled</span> monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between <span class="hlt">downscaled</span> monthly AET using LinZI method and the gridded FLUXNET dataset. The <span class="hlt">downscaled</span> monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed <span class="hlt">downscaling</span> method will be very useful in advancing the application of remotely sensed images in water resources planning and management.</p> <div class="credits"> <p class="dwt_author">Singh, Ramesh K.; Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Verdin, James P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">219</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004PhRvE..69f6131T"> <span id="translatedtitle">Random matrix <span class="hlt">ensembles</span> from nonextensive entropy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The classical Gaussian <span class="hlt">ensembles</span> of random matrices can be constructed by maximizing Boltzmann-Gibbs-Shannon’s entropy, SBGS =-?dH[P(H)]ln[P(H)], with suitable constraints. Here, we construct and analyze random-matrix <span class="hlt">ensembles</span> arising from the generalized entropy Sq = { 1-?dH [P(H)]q } /(q-1) (thus, S1 = SBGS ). The resulting <span class="hlt">ensembles</span> are characterized by a parameter q measuring the degree of nonextensivity of the entropic form. Making q?1 recovers the Gaussian <span class="hlt">ensembles</span>. If q?1 , the joint probability distributions P(H) cannot be factorized, i.e., the matrix elements of H are correlated. In the limit of large matrices two different regimes are observed. When q<1 , P(H) has compact support, and the fluctuations tend asymptotically to those of the Gaussian <span class="hlt">ensembles</span>. Anomalies appear for q>1 : Both P(H) and the marginal distributions P( Hij ) show power-law tails. Numerical analyses reveal that the nearest-neighbor spacing distribution is also long-tailed (not Wigner-Dyson) and, after proper scaling, very close to the result for the 2×2 case — a generalization of Wigner’s surmise. We discuss connections of these “nonextensive” <span class="hlt">ensembles</span> with other non-Gaussian ones, such as the so-called Lévy <span class="hlt">ensembles</span> and those arising from soft confinement.</p> <div class="credits"> <p class="dwt_author">Toscano, Fabricio; Vallejos, Raúl O.; Tsallis, Constantino</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">220</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUFM.H21E0877R"> <span id="translatedtitle">Estimation of climate change impacts on river flow and catchment hydrological connectivity incorporating uncertainty from multiple climate models, stochastic <span class="hlt">downscaling</span> and hydrological model parameterisation error sources</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">When estimating climate change impacts, there are many sources of uncertainty which must be considered. The main sources of uncertainty arise from the structure and parameterisation of physically based simulation models, <span class="hlt">downscaling</span> methods, stochastic realisations of future weather time series and the underlying emission scenarios. This work focuses on the uncertainties resulting from the use of multiple climate models and the joint impact of the stochastic realisations of future weather time series from a weather generator, EARWIG, and from parameter estimation uncertainty of a hydrological model, CAS-Hydro. These tools have been applied to the River Rye, Yorkshire. A suite of model parameter sets and weather realisations have been used to project likely changes to the hydrological functioning under climate change. Results are presented on the projected changes in flow duration curves and the potential changes in the hydrological connectivity by overland flow within the catchment. The statistical sensitivity of the impact predictions to these sources of uncertainty and the use of a multi-model <span class="hlt">ensemble</span> to enable the production of probabilistic estimates of change is assessed. These estimates of potential changes in flow can then be used to inform the adaptation of water resources design and management.</p> <div class="credits"> <p class="dwt_author">Reaney, S. M.; Fowler, H. J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-12-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_10");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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style="font-weight: bold;">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_13");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">221</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/1409.5005v1"> <span id="translatedtitle">Diffusion for an <span class="hlt">ensemble</span> of Hamiltonians</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Two <span class="hlt">ensembles</span> of standard maps are studied analytically and numerically. In particular the diffusion coefficient is calculated. For one type of <span class="hlt">ensemble</span> the chaotic parameter is chosen at random from a Gaussian distribution and is then kept fixed, while for the other type it varies from step to step. The effect of averaging out the details is evaluated and in particular it is found to be much more effective in the process of the second type. The work may shed light on the possible properties of different <span class="hlt">ensembles</span> of mixed systems.</p> <div class="credits"> <p class="dwt_author">Or Alus; Shmuel Fishman</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-17</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">222</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=269553"> <span id="translatedtitle">An Observation-base investigation of nudging in WRF for <span class="hlt">downscaling</span> surface climate information to 12-km Grid Spacing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">Previous research has demonstrated the ability to use the Weather Research and Forecast (WRF) model and contemporary dynamical <span class="hlt">downscaling</span> methods to refine global climate modeling results to a horizontal resolution of 36 km. Environmental managers and urban planners have expre...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">223</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014JSP...tmp...64B"> <span id="translatedtitle">Statistical <span class="hlt">Ensembles</span> for Economic Networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Economic networks share with other social networks the fundamental property of sparsity. It is well known that the maximum entropy techniques usually employed to estimate or simulate weighted networks produce unrealistic dense topologies. At the same time, strengths should not be neglected, since they are related to core economic variables like supply and demand. To overcome this limitation, the exponential Bosonic model has been previously extended in order to obtain <span class="hlt">ensembles</span> where the average degree and strength sequences are simultaneously fixed (conditional geometric model). In this paper a new exponential model, which is the network equivalent of Boltzmann ideal systems, is introduced and then extended to the case of joint degree-strength constraints (conditional Poisson model). Finally, the fitness of these alternative models is tested against a number of networks. While the conditional geometric model generally provides a better goodness-of-fit in terms of log-likelihoods, the conditional Poisson model could nevertheless be preferred whenever it provides a higher similarity with original data. If we are interested instead only in topological properties, the simple Bernoulli model appears to be preferable to the correlated topologies of the two more complex models.</p> <div class="credits"> <p class="dwt_author">Bargigli, Leonardo</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">224</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://dspace.mit.edu/handle/1721.1/65554"> <span id="translatedtitle">Towards Dynamic Team Formation for Robot <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We present an investigation of dynamic team formation strategies for robot <span class="hlt">ensembles</span> performing a collection of single and two-robot tasks. Specifically, we consider the abstract “stick and pebble” problem, as a variation ...</p> <div class="credits"> <p class="dwt_author">Mather, T. William</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">225</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://as2.c.u-tokyo.ac.jp/archive/kek2012.03.pdf"> <span id="translatedtitle">Statistical Mechanics without <span class="hlt">Ensembles</span> Akira Shimizu</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Statistical Mechanics without <span class="hlt">Ensembles</span> Akira Shimizu Department of Basic Science, University. Introduction: Principles of statistical mechanics revisited. 2. Thermal Pure Quantum states (TPQs) 3. Formulation of statistical mechanics with TPQs (a) Construction of a new class of TPQs (b) Genuine</p> <div class="credits"> <p class="dwt_author">Shimizu, Akira</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">226</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20070023651&hterms=weight&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dweight"> <span id="translatedtitle"><span class="hlt">Ensemble</span> Weight Enumerators for Protograph LDPC Codes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length <span class="hlt">ensemble</span> weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining <span class="hlt">ensemble</span> average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular <span class="hlt">ensembles</span>, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on <span class="hlt">ensemble</span> weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.</p> <div class="credits"> <p class="dwt_author">Divsalar, Dariush</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">227</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009APS..HAW.BM003H"> <span id="translatedtitle"><span class="hlt">Ensemble</span> treatments of thermal pairing in nuclei</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A systematic comparison is conducted for pairing properties of finite systems at nonzero temperature as predicted by the exact solutions of the pairing problem embedded in three principal statistical <span class="hlt">ensembles</span>, namely the grandcanonical <span class="hlt">ensemble</span>, canonical <span class="hlt">ensemble</span> and microcanonical <span class="hlt">ensemble</span>, as well as the unprojected (FTBCS1+SCQRPA) and Lipkin-Nogami projected (FTLN1+SCQRPA) theories that include the quasiparticle number fluctuation and coupling to pair vibrations within the self-consistent quasiparticle random-phase approximation. The numerical calculations are performed for the pairing gap, total energy, heat capacity, entropy, and microcanonical temperature within the doubly-folded equidistant multilevel pairing model. The FTLN1+SCQRPA predictions are found to agree best with the exact grand-canonical results. In general, all approaches clearly show that the superfluid-normal phase transition is smoothed out in finite systems. A novel formula is suggested for extracting the empirical pairing gap in reasonable agreement with the exact canonical results.</p> <div class="credits"> <p class="dwt_author">Hung, Nguyen Quang; Dang, Nguyen Dinh</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">228</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://reports-archive.adm.cs.cmu.edu/anon/2014/CMU-CS-14-100.pdf"> <span id="translatedtitle">Anytime Prediction: Efficient <span class="hlt">Ensemble</span> Methods for Any</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Anytime Prediction: Efficient <span class="hlt">Ensemble</span> Methods for Any Computational Budget Alexander Grubb January for the degree of Doctor of Philosophy c 2014 Alexander Grubb This work supported by ONR MURI grant N00014</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">229</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/nt58nfq0wdn6lw72.pdf"> <span id="translatedtitle">Interpretations of some parameter dependent generalizations of classical matrix <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Two types of parameter dependent generalizations of classical matrix <span class="hlt">ensembles</span> are defined by their probability density functions (PDFs). As the parameter is varied, one interpolates between the eigenvalue PDF for the superposition of two classical <span class="hlt">ensembles</span> with orthogonal symmetry and the eigenvalue PDF for a single classical <span class="hlt">ensemble</span> with unitary symmetry, while the other interpolates between a classical <span class="hlt">ensemble</span> with</p> <div class="credits"> <p class="dwt_author">Peter J. Forrester; Eric M. Rains</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">230</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ams.sunysb.edu/~hahn/psfile/wave.pdf"> <span id="translatedtitle">A Weight-Adjusted Voting Algorithm for <span class="hlt">Ensemble</span> of Classifiers</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">A Weight-Adjusted Voting Algorithm for <span class="hlt">Ensemble</span> of Classifiers Hyunjoong Kima, , Hyeuk Kimb , Hojin present a new weighted voting classification <span class="hlt">ensemble</span> method, called WAVE, that uses two weight vectors of classifiers in an <span class="hlt">ensemble</span>. The final prediction of the <span class="hlt">ensemble</span> is obtained by the voting using the optimal</p> <div class="credits"> <p class="dwt_author">Ahn, Hongshik</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">231</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014AdSpR..54..655M"> <span id="translatedtitle">A comparison of different regression models for <span class="hlt">downscaling</span> Landsat and MODIS land surface temperature images over heterogeneous landscape</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (?1000 m) thermal images with high revisiting capability (?1 day) are freely available. To bridge this gap, present study attempts to <span class="hlt">downscale</span> coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression <span class="hlt">downscaling</span> (LMSDS) and (v) Pace regression <span class="hlt">downscaling</span> (PRDS) are applied to <span class="hlt">downscale</span> LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and <span class="hlt">downscaled</span> to 480 m and 240 m resolution. The <span class="hlt">downscale</span> accuracy is achieved using LMSDS and PRDS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data <span class="hlt">downscaled</span> from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMSDS and PRDS models, respectively. The LMSDS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. <span class="hlt">Downscaling</span> model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.</p> <div class="credits"> <p class="dwt_author">Mukherjee, Sandip; Joshi, P. K.; Garg, R. D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">232</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/47837059"> <span id="translatedtitle">Prediction of variability of precipitation in the Yangtze River Basin under the climate change conditions based on automated statistical <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Many impact studies require climate change information at a finer resolution than that provided by general circulation models\\u000a (GCMs). Therefore the outputs from GCMs have to be <span class="hlt">downscaled</span> to obtain the finer resolution climate change scenarios. In\\u000a this study, an automated statistical <span class="hlt">downscaling</span> (ASD) regression-based approach is proposed for predicting the daily precipitation\\u000a of 138 main meteorological stations in the</p> <div class="credits"> <p class="dwt_author">Jing GuoHua; Hua Chen; Chong-Yu Xu; Shenglian Guo; Jiali Guo</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">233</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/21355663"> <span id="translatedtitle">Memory for multiple visual <span class="hlt">ensembles</span> in infancy.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The number of individual items that can be maintained in working memory is limited. One solution to this problem is to store representations of <span class="hlt">ensembles</span> that contain summary information about large numbers of items (e.g., the approximate number or cumulative area of a group of many items). Here we explored the developmental origins of <span class="hlt">ensemble</span> representations by asking whether infants represent <span class="hlt">ensembles</span> and, if so, how many at one time. We habituated 9-month-old infants to arrays containing 2, 3, or 4 spatially intermixed colored subsets of dots, then asked whether they detected a numerical change to one of the subsets or to the superset of all dots. Experiment Series 1 showed that infants detected a numerical change to 1 of the subsets when the array contained 2 subsets but not 3 or 4 subsets. Experiment Series 2 showed that infants detected a change to the superset of all dots no matter how many subsets were presented. Experiment 3 showed that infants represented both the approximate number and the cumulative surface area of these <span class="hlt">ensembles</span>. Our results suggest that infants, like adults (Halberda, Sires, & Feigenson, 2006), can store quantitative information about 2 subsets plus the superset: a total of 3 <span class="hlt">ensembles</span>. This converges with the known limit on the number of individual objects infants and adults can store and suggests that, throughout development, an <span class="hlt">ensemble</span> functions much like an individual object for working memory. PMID:21355663</p> <div class="credits"> <p class="dwt_author">Zosh, Jennifer M; Halberda, Justin; Feigenson, Lisa</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">234</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25104944"> <span id="translatedtitle">Conductor gestures influence evaluations of <span class="hlt">ensemble</span> performance.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Previous research has found that listener evaluations of <span class="hlt">ensemble</span> performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of <span class="hlt">ensemble</span> performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber <span class="hlt">ensemble</span> in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the <span class="hlt">ensemble</span>'s articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the <span class="hlt">ensemble</span>'s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall <span class="hlt">ensemble</span> expressivity. PMID:25104944</p> <div class="credits"> <p class="dwt_author">Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">235</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFMGC12C..05G"> <span id="translatedtitle">Lessons learned from the National Climate Predictions and Projections (NCPP) platform Workshop on Quantitative Evaluation of <span class="hlt">Downscaling</span> 2013</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The mission of NCPP is to accelerate the provision of climate information on regional and local scale for use in adaptation planning and decision making through collaborative participation of a community of scientists and practitioners. A major focus is the development of a capability for objective and quantitative evaluation of <span class="hlt">downscaled</span> climate information in support of applications. NCPP recognizes the importance of focusing this evaluation effort on real-world applications and the necessity to work closely with the user community to deliver usable evaluations and guidance. This summer NCPP organized our first workshop on quantitative evaluation of <span class="hlt">downscaled</span> climate datasets (http://earthsystemcog.org/projects/<span class="hlt">downscaling</span>-2013/). Workshop participants included representatives from <span class="hlt">downscaling</span> efforts, applications partners from the health, ecological, agriculture and water resources impacts communities, and people working on data infrastructure, metadata, and standards development. The workshop exemplifies NCPP's approach of collaborative and participatory problem-solving where scientists are working together with practitioners to develop applications related evaluation. The set of observed and <span class="hlt">downscaled</span> datasets included for evaluation in the workshop were assessed using a variety of metrics to elucidate the statistical characteristics of temperature and precipitation time series. In addition, the <span class="hlt">downscaled</span> datasets were evaluated in terms of their representation of indices relevant to the participating applications working groups, more specifically related to human health and ecological impacts. The presentation will focus on sharing the lessons we learned from our workshop.</p> <div class="credits"> <p class="dwt_author">Guentchev, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">236</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1514085W"> <span id="translatedtitle">Attractor Learning In Interactive <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recently methods for model fusion by dynamically combining model components in an interactive <span class="hlt">ensemble</span> have been proposed. Although different in detail, these interactive <span class="hlt">ensembles</span> can be generally considered as a supermodel, which have the different original models as fixed basis functions, and which is parameterized by the fusion parameters. In most of the proposals, the fusion parameters are optimized based on a short time scale prediction error. In general this will improve weather prediction skill, but not necessarily climate projection skill. Expressed in terms of nonlinear dynamical systems, reducing error on the level of vector fields does not necessarily lead to a better attractor. We demonstrate this in a low dimensional dynamical system toy example. The example consists of three models. One model is the assumed ground truth. The other two are "imperfect models" of the ground truth. The ground truth is represented by a chaotically forced Lorenz 63 model. The chaotic forcing plays the role of unresolved scales and is assumed not directly observable. The two imperfect models, named model 1 and model 2, are both represented by a Lorenz 63 system with perturbed parameters and a constant forcing. The perturbations and forcings in model 1 and model 2 are such that the vector field of imperfect model 1 is closest to the true vector field. However the long term statistics of imperfect model 2 is closest to the true long term statistics. The two models, model 1 and 2, are fused into a single supermodel. The fusion parameters are optimized on the basis of a finite data set of observables generated by the ground truth dynamics, the so-called training set. After optimization, the resulting supermodel skills are evaluated on the basis of a test set, which is a second, larger data set of observables generated by the ground truth dynamics. If, in the example, vector field error is used as optimization criterion, optimization indeed leads to an improved short term prediction skill on the test set. However it turns out to strongly degrade the prediction skill of the long term statistics, e.g. the mean and the variance of the supermodel attractor are very different from the test set mean and variance. A notion of attractor (training/test) error is introduced by considering metrics between probability densities, one of which is estimated on the basis of the given (training/test) data set. The other density is estimated from the data generated by a long term (super) model simulation. With this notion we define attractor learning as the optimization of the attractor training error. Attractor learning is demonstrated in the example. Compared to vector field learning, attractor learning leads to a significantly reduced attractor test error and improved long term statistics of the supermodel, while the resulting vector field test error is hardly increased.</p> <div class="credits"> <p class="dwt_author">Wiegerinck, Wim; Basnarkov, Lasko</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">237</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013ClDy..tmp..439J"> <span id="translatedtitle">Rainfall anomaly prediction using statistical <span class="hlt">downscaling</span> in a multimodel superensemble over tropical South America</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical <span class="hlt">downscaling</span> along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric-ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of <span class="hlt">downscaling</span> and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well.</p> <div class="credits"> <p class="dwt_author">Johnson, Bradford; Kumar, Vinay; Krishnamurti, T. N.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">238</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014ClDy...43.1731J"> <span id="translatedtitle">Rainfall anomaly prediction using statistical <span class="hlt">downscaling</span> in a multimodel superensemble over tropical South America</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study addresses the predictability of rainfall variations over South America and the Amazon basin. A primary factor leading to model inaccuracy in precipitation forecasts is the coarse resolution data utilized by coupled models during the training phase. By using MERRA reanalysis and statistical <span class="hlt">downscaling</span> along with the superensemble methodology, it is possible to obtain more precise forecast of rainfall anomalies over tropical South America during austral fall. Selective inclusion (and exclusion) of member models also allows for increased accuracy of superensemble forecasts. The use of coupled atmospheric-ocean numerical models to predict the rainfall anomalies has had mixed results. Improvement in individual member models is also possible on smaller spatial scales and in regions where substantial topographical changes were not handled well under original model initial conditions. The combination of <span class="hlt">downscaling</span> and superensemble methodologies with other research methods presents the potential opportunity for increased accuracy not only in seasonal forecasts but on shorter temporal scales as well.</p> <div class="credits"> <p class="dwt_author">Johnson, Bradford; Kumar, Vinay; Krishnamurti, T. N.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">239</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55480154"> <span id="translatedtitle">Simulation of extreme precipitation indices in the Yangtze River basin by using statistical <span class="hlt">downscaling</span> method (SDSM)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this study, the applicability of the statistical <span class="hlt">downscaling</span> model (SDSM) in modeling five extreme precipitation indices including R10 (no. of days with precipitation >=10 mm day-1), SDI (simple daily intensity), CDD (maximum number of consecutive dry days), R1d (maximum 1-day precipitation total) and R5d (maximum 5-day precipitation total) in the Yangtze River basin, China was investigated. The investigation mainly</p> <div class="credits"> <p class="dwt_author">Jin Huang; Jinchi Zhang; Zengxin Zhang; Shanlei Sun; Jian Yao</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">240</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012NHESS..12.2769V"> <span id="translatedtitle">Dynamical and statistical <span class="hlt">downscaling</span> of the French Mediterranean climate: uncertainty assessment</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">ERA-40 reanalyses, and simulations from three regional climate models (RCMs) (ALADIN, LMDZ, and WRF) and from one statistical <span class="hlt">downscaling</span> model (CDF-t) are used to evaluate the uncertainty in <span class="hlt">downscaling</span> of wind, temperature, and rainfall cumulative distribution functions (CDFs) for eight stations in the French Mediterranean basin over 1991-2000. The uncertainty is quantified using the Cramer-von Mises score (CvM) to measure the "distance" between the simulated and observed CDFs. The ability of the three RCMs and CDF-t to simulate the "climate" variability is quantified with the explained variance, variance ratio and extreme occurrence. The study shows that despite their differences, the three RCMs display very similar performance. In terms of global distributions (i.e. CvM), all models perform better than ERA-40 for both seasons and variables. However, looking at variance criteria, RCMs are not always much better than ERA-40 reanalyses, whereas CDF-t produces accurate results when applied to ERA-40. In a second step, a combined statistical/dynamical <span class="hlt">downscaling</span> approach has been used, consisting in applying CDF-t to the RCM outputs. It shows that CDF-t applied to the RCM outputs does not necessarily produce better results than those from CDF-t directly applied to ERA-40. It also shows that CDF-t applied to RCMs generally improves the <span class="hlt">downscaled</span> CDFs and that the "additional" added value of CDF-t applied to the RCMs is independent of the performance of the RCMs in terms of CvM, explained variance, variance ratio and extreme occurrence.</p> <div class="credits"> <p class="dwt_author">Vrac, M.; Drobinski, P.; Merlo, A.; Herrmann, M.; Lavaysse, C.; Li, L.; Somot, S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-09-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_11");' href="#" 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onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_14");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">241</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.9429S"> <span id="translatedtitle">Sensitivity of Hydrological Model Simulations to Underling Assumptions in a Stochastic <span class="hlt">Downscaling</span> method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Climate Change Impacts Studies (CCIS) for Water Resources Management (WRM) are of crucial importance for the human community and especially for water scarce Mediterranean- like regions, where the available water is expected to decrease due to climate change. General Circulation Models (GCM) are one of the most valuable tools available to perform CCIS. However, they cannot be directly applied to water resources evaluations due to their coarse spatial resolution and bias in their simulation of certain outputs, especially precipitation. <span class="hlt">Downscaling</span> methods have been developed to address this problem, by defining statistical relationships between the variables simulated by GCMs and local observations. Once these relationships are defined and tested via post evaluation during a control period, the relationship is used to generate synthetic time series for the future, based on the different future climate scenarios simulated by the GCMs. For CCIS in WRM, synthetic time series of precipitation and temperature are applied as input variables to run hydrological models and obtain future projections of hydrological response. The main drawbacks of this procedure are: (1) inevitably we have to assume time stationary in the <span class="hlt">downscaling</span> parameters (which in principle can vary with climate change), and (2) The <span class="hlt">downscaling</span> parameterizations are another source of model uncertainties that must be quantified and communicated. Here, we evaluate the sensitivity of hydrological model simulations to assumptions underlying a <span class="hlt">downscaling</span> method based on a Stochastic Rainfall Generating process (SRGP). The method is used to demonstrate that exact daily rainfall sequences are not necessary for climate impacts assessment, and that the "stochastically equivalent" rainfall sequence simulations provided by the model are both sufficient, and provide important added value in terms of realistic assessments of uncertainty. The method also establishes which parameters of the rainfall generating process are primary controllers of the impacts caused by climate variability/change, and which must therefore be given special consideration during long-term climate simulations.</p> <div class="credits"> <p class="dwt_author">Sapriza, Gonzalo; Jodar, Jorge; Carrera, Jesús; Gupta, Hoshin V.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">242</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AGUFM.H33E0921N"> <span id="translatedtitle">A Procedure for Statistical <span class="hlt">Downscaling</span> of Precipitation with an Objective Method for Predictor Selection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> General Circulation Models’ (GCM) outputs to a finer grid cell size is an important step in climate change impact and adaptation studies in particular for hydrologic applications. Many investigations have been focused on presenting techniques to <span class="hlt">downscale</span> GCM data utilizing statistical approaches. Nevertheless there is currently the need to present techniques on predictor selection and also to compare different <span class="hlt">downscaling</span> models’ capabilities. Hence in this study an algorithm has been developed to select GCM predictors in a subseasonal to seasonal time scale. Independent component analysis was used to find the statistically independent signals of CGCM3 variables in the 4*7 grid cells covering the Willamette river basin in Oregon, USA. Using the multi-linear regression cross validation (MLR-CV) the GCM predictors were selected for each period. The selected predictors were then applied to train the ANFIS (Adaptive Network-based Fuzzy Inference System) and the SVM (Support Vector Machine) models, and their performances were assessed on the test data. To design more robust networks that are less dependent on training data set, the cross validation was performed. . Predictors with the best performance for each season in the test set (using both ANFIS and SVM models) were selected for that specific season. The comparison of ANFIS and SVM models using statistical measures showed that ANFIS presents better results suitable for climate impact studies. Also application of ICA allowed reducing the size of many dependent GCM variables in 28 grid cells considerably resulting in higher accuracy in <span class="hlt">downscaling</span> and more effectiveness in the procedure.</p> <div class="credits"> <p class="dwt_author">Najafi, M.; Moradkhani, H.; Wherry, S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">243</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFM.H31B0994H"> <span id="translatedtitle"><span class="hlt">Downscaling</span> of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image <span class="hlt">downscaling</span> has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform <span class="hlt">downscaling</span> of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for <span class="hlt">downscaling</span> problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the <span class="hlt">downscaled</span> 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.</p> <div class="credits"> <p class="dwt_author">Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">244</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24824947"> <span id="translatedtitle">Design of a <span class="hlt">downscaling</span> method to estimate continuous data from discrete pollen monitoring in Tunisia.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The study of microorganisms and biological particulate matter that transport passively through air is very important for an understanding of the real quality of air. Such monitoring is essential in several specific areas, such as public health, allergy studies, agronomy, indoor and outdoor conservation, and climate-change impact studies. Choosing the suitable monitoring method is an important step in aerobiological studies, so as to obtain reliable airborne data. In this study, we compare olive pollen data from two of the main air traps used in aerobiology, the Hirst and Cour air samplers, at three Tunisian sampling points, for 2009 to 2011. Moreover, a <span class="hlt">downscaling</span> method to perform daily Cour air sampler data estimates is designed. While Hirst air samplers can offer daily, and even bi-hourly data, Cour air samplers provide data for longer discrete sampling periods, which limits their usefulness for daily monitoring. Higher quantities of olive pollen capture were generally detected for the Hirst air sampler, and a <span class="hlt">downscaling</span> method that is developed in this study is used to model these differences. The effectiveness of this <span class="hlt">downscaling</span> method is demonstrated, which allows the potential use of Cour air sampler data series. These results improve the information that new Cour data and, importantly, historical Cour databases can provide for the understanding of phenological dates, airborne pollination curves, and allergenicity levels of air. PMID:24824947</p> <div class="credits"> <p class="dwt_author">Orlandi, Fabio; Oteros, Jose; Aguilera, Fátima; Ben Dhiab, Ali; Msallem, Monji; Fornaciari, Marco</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">245</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70095788"> <span id="translatedtitle">Applying <span class="hlt">downscaled</span> global climate model data to a hydrodynamic surface-water and groundwater model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Precipitation data from Global Climate Models have been <span class="hlt">downscaled</span> to smaller regions. Adapting this <span class="hlt">downscaled</span> precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The <span class="hlt">downscaled</span> rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.</p> <div class="credits"> <p class="dwt_author">Swain, Eric; Stefanova, Lydia; Smith, Thomas</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">246</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012JSemi..33g5008L"> <span id="translatedtitle">A high-speed mixed-signal <span class="hlt">down-scaling</span> circuit for DAB tuners</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A high-speed mixed-signal <span class="hlt">down-scaling</span> circuit with low power consumption and low phase noise for use in digital audio broadcasting tuners has been realized and characterized. Some new circuit techniques are adopted to improve its performance. A dual-modulus prescaler (DMP) with low phase noise is realized with a kind of improved source-coupled logic (SCL) D-flip-flop (DFF) in the synchronous divider and a kind of improved complementary metal oxide semiconductor master-slave (CMOS MS)-DFF in the asynchronous divider. A new more accurate wire-load model is used to realize the pulse-swallow counter (PS counter). Fabricated in a 0.18-?m CMOS process, the total chip size is 0.6 × 0.2 mm2. The DMP in the proposed <span class="hlt">down-scaling</span> circuit exhibits a low phase noise of -118.2 dBc/Hz at 10 kHz off the carrier frequency. At a supply voltage of 1.8 V, the power consumption of the <span class="hlt">down-scaling</span> circuit's core part is only 2.7 mW.</p> <div class="credits"> <p class="dwt_author">Lu, Tang; Zhigong, Wang; Jiahui, Xuan; Yang, Yang; Jian, Xu; Yong, Xu</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">247</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..1410829G"> <span id="translatedtitle">Application of statistical <span class="hlt">downscaling</span> technique for the production of wine grapes (Vitis vinifera L.) in Spain</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Climate and soil are two of the most important limiting factors for agricultural production. Nowadays climate change has been documented in many geographical locations affecting different cropping systems. The General Circulation Models (GCM) has become important tools to simulate the more relevant aspects of the climate expected for the XXI century in the frame of climatic change. These models are able to reproduce the general features of the atmospheric dynamic but their low resolution (about 200 Km) avoids a proper simulation of lower scale meteorological effects. <span class="hlt">Downscaling</span> techniques allow overcoming this problem by adapting the model outcomes to local scale. In this context, FIC (Fundación para la Investigación del Clima) has developed a statistical <span class="hlt">downscaling</span> technique based on a two step analogue methods. This methodology has been broadly tested on national and international environments leading to excellent results on future climate models. In a collaboration project, this statistical <span class="hlt">downscaling</span> technique was applied to predict future scenarios for the grape growing systems in Spain. The application of such model is very important to predict expected climate for the different growing crops, mainly for grape, where the success of different varieties are highly related to climate and soil. The model allowed the implementation of agricultural conservation practices in the crop production, detecting highly sensible areas to negative impacts produced by any modification of climate in the different regions, mainly those protected with protected designation of origin, and the definition of new production areas with optimal edaphoclimatic conditions for the different varieties.</p> <div class="credits"> <p class="dwt_author">Gaitán Fernández, E.; García Moreno, R.; Pino Otín, M. R.; Ribalaygua Batalla, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">248</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H21D1130R"> <span id="translatedtitle">Spatial <span class="hlt">downscaling</span> of precipitation from GCMs scenarios via random cascades for the Toce watershed, Italy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a Stochastic Space-Time Random Cascade approach to <span class="hlt">downscale</span> precipitation from a General Circulation Model (henceafter referred to as GCM). The study area is the Toce river basin of about 1800 sqKm in area, tributary to Lake Maggiore in Italy. Because the snowfed Toce river displays complex physiography and high environmental gradient, statistical <span class="hlt">downscaling</span> methods are required for climate change assessment, according to the Intergovernmental Panel on Climate Change (IPCC). The Stochastic Space-Time Random Cascade model is locally tuned to <span class="hlt">downscale</span> daily precipitation from NCAR Parallel Climate Model retrieved from the IPCC's data base. For the purpose, a 10 years series of observed daily precipitation data in 24 gaging location is used as ground truth reference. Model estimation is perfeormed using the Scale Recursive Estimation approach coupled with an explicit Expectation Maximization algorithm. Seasonal parameters of the multiplicative cascade are accommodated by statistical distributions conditioned upon climatic forcing, based on regression analysis. The major advantage of the Stochastic Space-Time Random Cascade approach deals with reproducing spatial clustering, intermittency, self-similarity of precipitation fields and their spatial correlation structure, with low computational burden. The approach is used in the Toce watershed in order to investigate water resources sensitivity to climate change.</p> <div class="credits"> <p class="dwt_author">Rosso, R.; Groppelli, B.; Soncini, A.; Bocchiola, D.; Colombo, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">249</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014NPGD....1..615D"> <span id="translatedtitle">Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Climate projections simulated by Global Climate Models (GCM) are often used for assessing the impacts of climate change. However, the relatively coarse resolutions of GCM outputs often precludes their application towards accurately assessing the effects of climate change on finer regional scale phenomena. <span class="hlt">Downscaling</span> of climate variables from coarser to finer regional scales using statistical methods are often performed for regional climate projections. Statistical <span class="hlt">downscaling</span> (SD) is based on the understanding that the regional climate is influenced by two factors - the large scale climatic state and the regional or local features. A transfer function approach of SD involves learning a regression model which relates these features (predictors) to a climatic variable of interest (predictand) based on the past observations. However, often a single regression model is not sufficient to describe complex dynamic relationships between the predictors and predictand. We focus on the covariate selection part of the transfer function approach and propose a nonparametric Bayesian mixture of sparse regression models based on Dirichlet Process (DP), for simultaneous clustering and discovery of covariates within the clusters while automatically finding the number of clusters. Sparse linear models are parsimonious and hence relatively more generalizable than non-sparse alternatives, and lends to domain relevant interpretation. Applications to synthetic data demonstrate the value of the new approach and preliminary results related to feature selection for statistical <span class="hlt">downscaling</span> shows our method can lead to new insights.</p> <div class="credits"> <p class="dwt_author">Das, D.; Dy, J.; Ross, J.; Obradovic, Z.; Ganguly, A. R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">250</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014ClDy...42.2899E"> <span id="translatedtitle">Uncertainty analysis of statistical <span class="hlt">downscaling</span> models using general circulation model over an international wetland</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Regression-based statistical <span class="hlt">downscaling</span> model (SDSM) is an appropriate method which broadly uses to resolve the coarse spatial resolution of general circulation models (GCMs). Nevertheless, the assessment of uncertainty propagation linked with climatic variables is essential to any climate change impact study. This study presents a procedure to characterize uncertainty analysis of two GCM models link with Long Ashton Research Station Weather Generator (LARS-WG) and SDSM in one of the most vulnerable international wetland, namely "Shadegan" in an arid region of Southwest Iran. In the case of daily temperature, uncertainty is estimated by comparing monthly mean and variance of <span class="hlt">downscaled</span> and observed daily data at a 95 % confidence level. Uncertainties were then evaluated from comparing monthly mean dry and wet spell lengths and their 95 % CI in daily precipitation <span class="hlt">downscaling</span> using 1987-2005 interval. The uncertainty results indicated that the LARS-WG is the most proficient model at reproducing various statistical characteristics of observed data at a 95 % uncertainty bounds while the SDSM model is the least capable in this respect. The results indicated a sequences uncertainty analysis at three different climate stations and produce significantly different climate change responses at 95 % CI. Finally the range of plausible climate change projections suggested a need for the decision makers to augment their long-term wetland management plans to reduce its vulnerability to climate change impacts.</p> <div class="credits"> <p class="dwt_author">Etemadi, H.; Samadi, S.; Sharifikia, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">251</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1612939D"> <span id="translatedtitle">Interactive <span class="hlt">Ensembles</span> Without Loss of Spread Information</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">If the members of an <span class="hlt">ensemble</span> of different models are allowed to interact with one another in run time, predictive skill can be improved as compared to that of any individual model or any average of indvidual model outputs. Inter-model connections in such an interactive <span class="hlt">ensemble</span> can be trained, using historical data, so that the resulting ``supermodel" synchronizes with reality when used in weather-prediction mode, where the individual models perform data assimilation from each other (with trainable inter-model "observation error") as well as from real observations. In climate-projection mode, parameters of the individual models are changed, as might occur from an increase in GHG levels, and one obtains relevant statistical properties of the new supermodel attractor. In simple cases, it has been shown that training of the inter-model connections with the old parameter values gives a supermodel that is still predictive when the parameter values are changed. It might seem that by allowing <span class="hlt">ensemble</span> members to interact and synchronize, we lose the advantage of using the <span class="hlt">ensemble</span> to estimate uncertainty in prediction/projection from <span class="hlt">ensemble</span> spread. Here we investigate the possibility of extending the machine learning scheme to estimate uncertainty in the trained connections, so as to effectively form an <span class="hlt">ensemble</span> of supermodels. A larger training set is generally required to learn the uncertainty in the values found, but the task can be reduced by restricting the possible connection values to a discrete set. An alternative strategy is simply to import the spread information from an ordinary, non-interactive <span class="hlt">ensemble</span>. We examine and compare the two strategies, using a variety of models, and reason about their applicability to the case of climate models that differ in their parameterizations of a sub-gridscale process.</p> <div class="credits"> <p class="dwt_author">Duane, Gregory; Shen, Mao-Lin; Wiegerinck, Wim</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">252</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.sci.utah.edu/publications/potter09/potterICDM09.pdf"> <span id="translatedtitle"><span class="hlt">Ensemble</span>-Vis: A Framework for the Statistical Visualization of <span class="hlt">Ensemble</span> Data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">to their complexity. In this article, we present <span class="hlt">Ensemble</span>-Vis, a framework consisting of a collection of overview of an <span class="hlt">ensemble</span> data set is to predict and quantify the range of outcomes that follow from a collection of simula- tion runs. These outcomes have both quantitative aspects, such as the probability of freezing rain</p> <div class="credits"> <p class="dwt_author">Utah, University of</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">253</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/16986543"> <span id="translatedtitle">Rotation forest: A new classifier <span class="hlt">ensemble</span> method.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We propose a method for generating classifier <span class="hlt">ensembles</span> based on feature extraction. To create the training data for a base classifier, the feature set is randomly split into K subsets (K is a parameter of the algorithm) and Principal Component Analysis (PCA) is applied to each subset. All principal components are retained in order to preserve the variability information in the data. Thus, K axis rotations take place to form the new features for a base classifier. The idea of the rotation approach is to encourage simultaneously individual accuracy and diversity within the <span class="hlt">ensemble</span>. Diversity is promoted through the feature extraction for each base classifier. Decision trees were chosen here because they are sensitive to rotation of the feature axes, hence the name "forest." Accuracy is sought by keeping all principal components and also using the whole data set to train each base classifier. Using WEKA, we examined the Rotation Forest <span class="hlt">ensemble</span> on a random selection of 33 benchmark data sets from the UCI repository and compared it with Bagging, AdaBoost, and Random Forest. The results were favorable to Rotation Forest and prompted an investigation into diversity-accuracy landscape of the <span class="hlt">ensemble</span> models. Diversity-error diagrams revealed that Rotation Forest <span class="hlt">ensembles</span> construct individual classifiers which are more accurate than these in AdaBoost and Random Forest, and more diverse than these in Bagging, sometimes more accurate as well. PMID:16986543</p> <div class="credits"> <p class="dwt_author">Rodríguez, Juan J; Kuncheva, Ludmila I; Alonso, Carlos J</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">254</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/1401.3095v2"> <span id="translatedtitle">Coupling spin <span class="hlt">ensembles</span> via superconducting flux qubits</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We study a hybrid quantum system consisting of spin <span class="hlt">ensembles</span> and superconducting flux qubits, where each spin <span class="hlt">ensemble</span> is realized using the nitrogen-vacancy centers in a diamond crystal and the nearest-neighbor spin <span class="hlt">ensembles</span> are effectively coupled via a flux qubit.We show that the coupling strengths between flux qubits and spin <span class="hlt">ensembles</span> can reach the strong and even ultrastrong coupling regimes by either engineering the hybrid structure in advance or tuning the excitation frequencies of spin <span class="hlt">ensembles</span> via external magnetic fields. When extending the hybrid structure to an array with equal coupling strengths, we find that in the strong-coupling regime, the hybrid array is reduced to a tight-binding model of a one-dimensional bosonic lattice. In the ultrastrong-coupling regime, it exhibits quasiparticle excitations separated from the ground state by an energy gap. Moreover, these quasiparticle excitations and the ground state are stable under a certain condition that is tunable via the external magnetic field. This may provide an experimentally accessible method to probe the instability of the system.</p> <div class="credits"> <p class="dwt_author">Yueyin Qiu; Wei Xiong; Lin Tian; J. Q. You</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-14</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">255</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012AGUFM.H43A1313W"> <span id="translatedtitle">The Hydrologic <span class="hlt">Ensemble</span> Prediction Experiment (HEPEX)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Hydrologic <span class="hlt">Ensemble</span> Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological <span class="hlt">ensemble</span> forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological <span class="hlt">ensemble</span> prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic <span class="hlt">ensemble</span> prediction enterprise: input and pre-processing, <span class="hlt">ensemble</span> techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.</p> <div class="credits"> <p class="dwt_author">Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">256</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/0804.0962v1"> <span id="translatedtitle">Scalable quantum computing with atomic <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Atomic <span class="hlt">ensembles</span>, comprising clouds of atoms addressed by laser fields, provide an attractive system for both the storage of quantum information, and the coherent conversion of quantum information between atomic and optical degrees of freedom. In a landmark paper, Duan et al. (DLCZ) [1] showed that atomic <span class="hlt">ensembles</span> could be used as nodes of a quantum repeater network capable of sharing pairwise quantum entanglement between systems separated by arbitrarily large distances. In recent years, a number of promising experiments have demonstrated key aspects of this proposal [2-7]. Here, we describe a scheme for full scale quantum computing with atomic <span class="hlt">ensembles</span>. Our scheme uses similar methods to those already demonstrated experimentally, and yet has information processing capabilities far beyond those of a quantum repeater.</p> <div class="credits"> <p class="dwt_author">S. D. Barrett; P. P. Rohde; T. M. Stace</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-04-07</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">257</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3680205"> <span id="translatedtitle">Optimized gold nanoshell <span class="hlt">ensembles</span> for biomedical applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">We theoretically study the properties of the optimal size distribution in the <span class="hlt">ensemble</span> of hollow gold nanoshells (HGNs) that exhibits the best performance at in vivo biomedical applications. For the first time, to the best of our knowledge, we analyze the dependence of the optimal geometric means of the nanoshells’ thicknesses and core radii on the excitation wavelength and the type of human tissue, while assuming lognormal fit to the size distribution in a real HGN <span class="hlt">ensemble</span>. Regardless of the tissue type, short-wavelength, near-infrared lasers are found to be the most effective in both absorption- and scattering-based applications. We derive approximate analytical expressions enabling one to readily estimate the parameters of optimal distribution for which an HGN <span class="hlt">ensemble</span> exhibits the maximum efficiency of absorption or scattering inside a human tissue irradiated by a near-infrared laser. PMID:23537206</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">258</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20130013812&hterms=avatar&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Davatar"> <span id="translatedtitle"><span class="hlt">Ensemble</span> Eclipse: A Process for Prefab Development Environment for the <span class="hlt">Ensemble</span> Project</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">This software simplifies the process of having to set up an Eclipse IDE programming environment for the members of the cross-NASA center project, <span class="hlt">Ensemble</span>. It achieves this by assembling all the necessary add-ons and custom tools/preferences. This software is unique in that it allows developers in the <span class="hlt">Ensemble</span> Project (approximately 20 to 40 at any time) across multiple NASA centers to set up a development environment almost instantly and work on <span class="hlt">Ensemble</span> software. The software automatically has the source code repositories and other vital information and settings included. The Eclipse IDE is an open-source development framework. The NASA (<span class="hlt">Ensemble</span>-specific) version of the software includes <span class="hlt">Ensemble</span>-specific plug-ins as well as settings for the <span class="hlt">Ensemble</span> project. This software saves developers the time and hassle of setting up a programming environment, making sure that everything is set up in the correct manner for <span class="hlt">Ensemble</span> development. Existing software (i.e., standard Eclipse) requires an intensive setup process that is both time-consuming and error prone. This software is built once by a single user and tested, allowing other developers to simply download and use the software</p> <div class="credits"> <p class="dwt_author">Wallick, Michael N.; Mittman, David S.; Shams, Khawaja, S.; Bachmann, Andrew G.; Ludowise, Melissa</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">259</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/39927"> <span id="translatedtitle"><span class="hlt">Ensemble</span> computing for the petroleum industry</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Computer downsizing is one of the most often used buzzwords in today`s competitive business, and the petroleum industry is at the forefront of this revolution. <span class="hlt">Ensemble</span> computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of <span class="hlt">ensemble</span> computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms.</p> <div class="credits"> <p class="dwt_author">Annaratone, M.; Dossa, D. [Digital Equipment Corp., Maynard, MA (United States)</p> <p class="dwt_publisher"></p> <p class="publishDate">1995-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">260</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014GMDD....7..217K"> <span id="translatedtitle">Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">EURO-CORDEX is an international climate <span class="hlt">downscaling</span> initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) <span class="hlt">ensemble</span> is presented. The study documents the performance of the individual models in representing the basic spatio-temporal patterns of the European climate for the period 1989-2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS dataset as observational reference. The <span class="hlt">ensemble</span> consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight sub-domains of the European continent. Results are compared to those for the ERA40-driven <span class="hlt">ENSEMBLES</span> simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies non-negligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 °C, while precipitation biases are typically located in the ±40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and south-eastern Europe reflect common model biases. For seasonal mean quantities averaged over large European sub-domains, no clear benefit of an increased spatial resolution (12 km vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX <span class="hlt">ensemble</span> mostly correspond to those of the <span class="hlt">ENSEMBLES</span> simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments.</p> <div class="credits"> <p class="dwt_author">Kotlarski, S.; Keuler, K.; Christensen, O. B.; Colette, A.; Déqué, M.; Gobiet, A.; Goergen, K.; Jacob, D.; Lüthi, D.; van Meijgaard, E.; Nikulin, G.; Schär, C.; Teichmann, C.; Vautard, R.; Warrach-Sagi, K.; Wulfmeyer, V.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_12");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return 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showDiv("page_15");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">261</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1611799K"> <span id="translatedtitle">Regional climate modeling on European scales: A joint standard evaluation of the EURO-CORDEX RCM <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">EURO-CORDEX is an international climate <span class="hlt">downscaling</span> initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) <span class="hlt">ensemble</span> is presented. The study documents the performance of the individual models in representing the basic spatio-temporal patterns of the European climate for the period 1989-2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS dataset as observational reference. The <span class="hlt">ensemble</span> consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight sub-domains of the European continent. Results are compared to those for the ERA40-driven <span class="hlt">ENSEMBLES</span> simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies non-negligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 °C, while precipitation biases are typically located in the +/- 40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and south-eastern Europe reflect common model biases. For seasonal mean quantities averaged over large European sub-domains, no clear benefit of an increased spatial resolution (12 km vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX <span class="hlt">ensemble</span> mostly correspond to those of the <span class="hlt">ENSEMBLES</span> simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments.</p> <div class="credits"> <p class="dwt_author">Kotlarski, Sven; Keuler, Klaus; Bossing Christensen, Ole; Colette, Augustin; Déqué, Michel; Gobiet, Andreas; Goergen, Klaus; Jacob, Daniela; Lüthi, Daniel; van Meijgaard, Erik; Nikulin, Grigory; Schär, Christoph; Teichmann, Claas; Vautard, Robert; Warrach-Sagi, Kirsten; Wulfmeyer, Volker</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">262</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013CG.....55....3E"> <span id="translatedtitle"><span class="hlt">Ensemble</span> smoother with multiple data assimilation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In the last decade, <span class="hlt">ensemble</span>-based methods have been widely investigated and applied for data assimilation of flow problems associated with atmospheric physics and petroleum reservoir history matching. This paper focuses entirely on the reservoir history-matching problem. Among the <span class="hlt">ensemble</span>-based methods, the <span class="hlt">ensemble</span> Kalman filter (EnKF) is the most popular for history-matching applications. However, the recurrent simulation restarts required in the EnKF sequential data assimilation process may prevent the use of EnKF when the objective is to incorporate the history matching in an integrated geo-modeling workflow. In this situation, the <span class="hlt">ensemble</span> smoother (ES) is a viable alternative. However, because ES computes a single global update, it may not result in acceptable data matches; therefore, the development of efficient iterative forms of ES is highly desirable. In this paper, we propose to assimilate the same data multiple times with an inflated measurement error covariance matrix in order to improve the results obtained by ES. This method is motivated by the equivalence between single and multiple data assimilation for the linear-Gaussian case. We test the proposed method for three synthetic reservoir history-matching problems. Our results show that the proposed method provides better data matches than those obtained with standard ES and EnKF, with a computational cost comparable with the computational cost of EnKF.</p> <div class="credits"> <p class="dwt_author">Emerick, Alexandre A.; Reynolds, Albert C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">263</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cbi.or.jp/cbi/CBIj/vol7/7_12-E.pdf"> <span id="translatedtitle">Implementation of the blue moon <span class="hlt">ensemble</span> method</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The blue moon <span class="hlt">ensemble</span> method (Carter et al., 1989, Chem. Phys. Lett. 156, 472; Sprik & Ciccotti, 1998, J. Chem. Phys. 109, 7737) calculates the free energy profile of a chemical reaction along a specified reaction coordinate. The explicit algorithms for two simple reaction coordinates (\\</p> <div class="credits"> <p class="dwt_author">Yuto Komeiji</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">264</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://files.eric.ed.gov/fulltext/ED294775.pdf"> <span id="translatedtitle">The Honolulu Symphony In-School <span class="hlt">Ensembles</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">The Honolulu (Hawaii) Symphony Orchestra's commitment to education includes young people's concerts and in-school <span class="hlt">ensembles</span>. The purpose of this booklet is to enhance the educational potential of in-school concerts through the presentation of information about the orchestra and music related concepts. Part 1 describes the orchestra's personnel,…</p> <div class="credits"> <p class="dwt_author">Higa, Harold</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">265</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50868873"> <span id="translatedtitle">The Joint <span class="hlt">Ensemble</span> Forecast System (JEFS) Experiment</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The Joint <span class="hlt">Ensemble</span> Forecast System (JEFS) Dedicated HPC Project Investment (DHPI) focuses on the creation and communication of environmental information in a timely, focused, useful, and reliable manner for the US Air Force and Navy. Currently, most environmental forecasts are created from a single best estimate analysis and forecast model. This deterministic process can provide imperfect results that result in</p> <div class="credits"> <p class="dwt_author">Evan L. Kuchera; Jeffrey G. Cunningham; S. A. Rentschler; S. A. Rugg; M. Sittel; Michael Sestak; Teddy Holt; James Hansen</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">266</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/hep-ph/0506210v1"> <span id="translatedtitle">Lorentz invariant <span class="hlt">ensembles</span> of vector backgrounds</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We consider gauge field theories in the presence of <span class="hlt">ensembles</span> of vector backgrounds. While Lorentz invariance is explicitely broken in the presence of any single background, here, the Lorentz invariance of the theory is restored by averaging over a Lorentz invariant <span class="hlt">ensemble</span> of backgrounds, i.e. a set of background vectors that is mapped onto itself under Lorentz transformations. This framewkork is used to study the effects of a non-trivial but Lorentz invariant vacuum structure or mass dimension two vector condensates by identifying the background with a shift of the gauge field. Up to now, the <span class="hlt">ensembles</span> used in the literature comprise configurations corresponding to non-zero field tensors together with such with vanishing field strength. We find that even when constraining the <span class="hlt">ensembles</span> to pure gauge configurations, the usual high-energy degrees of freedom are removed from the spectrum of asymptotic states in the presence of said backgrounds in euclidean and in Minkowski space. We establish this result not only for the propagators to all orders in the background and otherwise at tree level but for the full propagator.</p> <div class="credits"> <p class="dwt_author">Dennis D. Dietrich; Stefan Hofmann</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-06-22</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">267</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/23336205"> <span id="translatedtitle">Solving evolution equations using interacting trajectory <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we describe a general approach to solving evolution equations for probability densities using interacting trajectory <span class="hlt">ensembles</span>. Assuming the existence of a positive definite (probabilistic) description of the state of the system, we derive general equations of motion for the trajectories in the kinematic space (e.g., configuration or phase space). The vector field describing the time rate of</p> <div class="credits"> <p class="dwt_author">Patrick Hogan; Adam Van Wart; Arnaldo Donoso; Craig C. Martens</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">268</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/15271006"> <span id="translatedtitle">Equivalence of Julesz <span class="hlt">Ensembles</span> and FRAME Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In the past thirty years, research on textures has been pursued along two different lines. The first line of research, pioneered by Julesz (1962, IRE Transactions of Information Theory, IT-8:84–92), seeks essential ingredients in terms of features and statistics in human texture perception. This leads us to a mathematical definition of textures in terms of Julesz <span class="hlt">ensembles</span> (Zhu et al.,</p> <div class="credits"> <p class="dwt_author">Ying Nian Wu; Song Chun Zhu; Xiuwen Liu</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">269</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.bham.ac.uk/~wbl/biblio/cache/bin/cache.php?grosan:2006:GSP,http___www.cs.ubbcluj.ro__cgrosan_stock-chapter.pdf,http://www.cs.ubbcluj.ro/~cgrosan/stock-chapter.pdf"> <span id="translatedtitle">Stock Market Modeling Using Genetic Programming <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">1 Stock Market Modeling Using Genetic Programming <span class="hlt">Ensembles</span> Crina Grosan1 and Ajith Abraham2 1 for stock market predictions has been widely established. This chapter introduces two Genetic Programming of Nasdaq Stock Market and the S&P CNX NIFTY stock index as test data. Empirical results reveal that Genetic</p> <div class="credits"> <p class="dwt_author">Fernandez, Thomas</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">270</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://kea.princeton.edu/papers/tsgibbs_96/paper.ps"> <span id="translatedtitle">Thermodynamic Scaling Gibbs <span class="hlt">Ensemble</span> Monte Carlo</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Thermodynamic Scaling Gibbs <span class="hlt">Ensemble</span> Monte Carlo: A new method for determination of phase for correspondence. E­mail:azp2@cornell.edu #12; We combine Valleau's thermodynamic scaling Monte Carlo concept Monte Carlo simulations. There has been significant recent progress in molecular simulation method</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">271</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cs.gmu.edu/~carlotta/publications/NNensemble.pdf"> <span id="translatedtitle">Nearest Neighbor <span class="hlt">Ensemble</span> Carlotta Domeniconi Bojun Yan</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Department George Mason University, Fairfax, VA 22030 USA carlotta@ise.gmu.edu byan@gmu.edu Abstract Recent errors. If each classifier makes the same error, the voting carries that error into the decision of the <span class="hlt">ensemble</span>, thereby gaining no improvement. In addi- tion, accuracy is required to avoid poor classifiers</p> <div class="credits"> <p class="dwt_author">Domeniconi, Carlotta</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">272</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=music+AND+listening&pg=5&id=EJ744386"> <span id="translatedtitle">Developing Musical Listening in Performance <span class="hlt">Ensemble</span> Classes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">In this article, the author contends that in order to fulfill music education's purpose of developing a child's capacity to make and experience music, attention must be paid to developing listening in performance <span class="hlt">ensemble</span> classes. Music educators cannot assume that being involved in the refinement and performance of music contributes to becoming a…</p> <div class="credits"> <p class="dwt_author">Zerull, David S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">273</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/1203.6542v1"> <span id="translatedtitle">Black Hole Statistical Mechanics and The Angular Velocity <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">An new <span class="hlt">ensemble</span> - the angular velocity <span class="hlt">ensemble</span> - is derived using Jaynes' method of maximising entropy subject to prior information constraints. The relevance of the <span class="hlt">ensemble</span> to black holes is motivated by a discussion of external parameters in statistical mechanics and their absence from the Hamiltonian of general relativity. It is shown how this leads to difficulty in deriving entropy as a function of state and recovering the first law of thermodynamics from the microcanonical and canonical <span class="hlt">ensembles</span> applied to black holes.</p> <div class="credits"> <p class="dwt_author">Mitchell Thomson; Charles C. Dyer</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-03-29</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">274</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://hal.archives-ouvertes.fr/docs/00/30/46/03/PDF/hess-5-259-2001.pdf"> <span id="translatedtitle">Statistical atmospheric <span class="hlt">downscaling</span> for rainfall estimation in Kyushu Island, Japan Hydrology and Earth System Sciences, 5(2), 259271 (2001) EGS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">) the so- called Bai-u front which is responsible for the majority of summer rainfall, (2) the strongStatistical atmospheric <span class="hlt">downscaling</span> for rainfall estimation in Kyushu Island, Japan 259 Hydrology and Earth System Sciences, 5(2), 259­271 (2001) © EGS Statistical atmospheric <span class="hlt">downscaling</span> for rainfall</p> <div class="credits"> <p class="dwt_author">Paris-Sud XI, Université de</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">275</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://hal.archives-ouvertes.fr/docs/00/30/46/00/PDF/hess-5-245-2001.pdf"> <span id="translatedtitle"><span class="hlt">Downscaling</span> summer rainfall in the UK from North Atlantic ocean temperatures Hydrology and Earth System Sciences, 5(2), 245257 (2001) EGS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> summer rainfall in the UK from North Atlantic ocean temperatures 245 Hydrology Atlantic ocean temperatures R.L.Wilby Department of Geography, King's College London, Strand, London, WC2R occurrence process. Key words: North Atlantic, ocean temperatures, <span class="hlt">downscaling</span>, rainfall, forecasting, UK</p> <div class="credits"> <p class="dwt_author">Paris-Sud XI, Université de</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">276</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.rap.ucar.edu/~drife/rife_et_al_JAMC_2011.pdf"> <span id="translatedtitle">Toward Robust and Efficient Climate <span class="hlt">Downscaling</span>: Application to Wind1 Daran L. Rife, Emilie Vanvyve, James O. Pinto, Andrew J. Monaghan, Christopher A. Davis3</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">widely used within the wind energy industry for creating wind resource maps. The34 current approachToward Robust and Efficient Climate <span class="hlt">Downscaling</span>: Application to Wind1 Energy2 Daran L. Rife, Emilie at a location. The method is demonstrated for <span class="hlt">downscaling</span> wind fields to31 assess a location's wind energy</p> <div class="credits"> <p class="dwt_author">Rife, Daran L.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">277</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1511702H"> <span id="translatedtitle">Statistical and dynamical <span class="hlt">downscaling</span> in CORDEX-Africa: differing views on the regional climate</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The need for credible regional climate change projections for use in adaptation actions and decision making is well recognised. The CORDEX activity has evolved in large part as a response to this need. For the most part, CORDEX has so far been dominated by regional climate modelling (RCM) activities. However, implicit in CORDEX is the use of statistical <span class="hlt">downscaling</span> (SD) as a complement to RCMs, although the SD activities lag that of the RCMs. For Africa, the CORDEX RCM work is well advanced with the control climate simulations completed, and a number of RCM-based projections also available. The early results indicate the RCMs produce a credible representation of the regional climate when aggregated in time and/or space, and provide an initial multimodal suite of regional climate change projections for Africa. The SD activities are catching up with this process and the emerging challenge is how to integrate and compare the results from the two <span class="hlt">downscaling</span> methods. The two approaches, SD and RCMs, have respective strengths and weaknesses, but are considered in the literature to be of comparable overall skill. Where climate change stationarity is not considered a major issue, such as on timescales out to perhaps 2050, it is arguable that SD (comprehensively undertaken) may possibly be more skillful. From the perspective of users of regional scale projections, decision makers and policy developers, it is critical to compare, and assess the relative strengths of the methods on a regional basis. To avoid confusion the contradictions and/or robust messages emerging from the two methods needs to be clearly understood and articulated. The inter-comparison between the RCMs is already the subject of a number of papers, and here we present an initial comparison of early results between the SD and the envelope of RCM <span class="hlt">downscaling</span> for CORDEX-Africa. Using the available SD results, we consider where the overlap and/or marked differences lie between the two methods. The focus is primarily on the control climate, where the <span class="hlt">downscaling</span> is forced by the ERA-reanalysis data set, to avoid complicating factors possibly arising from non-stationarity issues with both SD and the RCMs. Following this we consider some early results of future climate projections based on the boundary conditions from CMIP5 GCM data. The primary consideration is how the statistical <span class="hlt">downscaling</span> results fall within the envelope of the regional climate models. In this we consider both the bias of the regional climate models, the seasonal cycle, and the shorter time scales of weather events and the histogram distribution of daily events including extremes. Of particular concern is how the <span class="hlt">downscaling</span> methods handle both the high and low frequency variance of the regional climate systems. The SD method uses daily data to derive the deterministic response to the large-scale forcing and adds the high-frequency variants or stochastic component. From this time and space aggregates comparable to the RCM data may be compiled. The primary difference between SD and RCMs lies in the fact that the SD is inherently bias corrected by virtue of the method. Thus the first major difference is accountable for by the RCM bias. Following this the differences are regionally and seasonally dependent and examples of these are presented from which preliminary conclusions about the two methods are drawn</p> <div class="credits"> <p class="dwt_author">Hewitson, Bruce; Lennard, Christopher; Jack, Christopher; Coop, Lisa</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">278</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H41C1049F"> <span id="translatedtitle">Developing a regional retrospective <span class="hlt">ensemble</span> precipitation dataset for watershed hydrology modeling, Idaho, USA</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically <span class="hlt">downscaled</span> using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. <span class="hlt">Downscaled</span> precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an <span class="hlt">ensemble</span>-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.</p> <div class="credits"> <p class="dwt_author">Flores, A. N.; Smith, K.; LaPorte, P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">279</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014JPRS...97...78W"> <span id="translatedtitle">Modeling diurnal land temperature cycles over Los Angeles using <span class="hlt">downscaled</span> GOES imagery</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Land surface temperature is a key parameter for monitoring urban heat islands, assessing heat related risks, and estimating building energy consumption. These environmental issues are characterized by high temporal variability. A possible solution from the remote sensing perspective is to utilize geostationary satellites images, for instance, images from Geostationary Operational Environmental System (GOES) and Meteosat Second Generation (MSG). These satellite systems, however, with coarse spatial but high temporal resolution (sub-hourly imagery at 3-10 km resolution), often limit their usage to meteorological forecasting and global climate modeling. Therefore, how to develop efficient and effective methods to disaggregate these coarse resolution images to a proper scale suitable for regional and local studies need be explored. In this study, we propose a least square support vector machine (LSSVM) method to achieve the goal of <span class="hlt">downscaling</span> of GOES image data to half-hourly 1-km LSTs by fusing it with MODIS data products and Shuttle Radar Topography Mission (SRTM) digital elevation data. The result of <span class="hlt">downscaling</span> suggests that the proposed method successfully disaggregated GOES images to half-hourly 1-km LSTs with accuracy of approximately 2.5 K when validated against with MODIS LSTs at the same over-passing time. The synthetic LST datasets were further explored for monitoring of surface urban heat island (UHI) in the Los Angeles region by extracting key diurnal temperature cycle (DTC) parameters. It is found that the datasets and DTC derived parameters were more suitable for monitoring of daytime- other than nighttime-UHI. With the <span class="hlt">downscaled</span> GOES 1-km LSTs, the diurnal temperature variations can well be characterized. An accuracy of about 2.5 K was achieved in terms of the fitted results at both 1 km and 5 km resolutions.</p> <div class="credits"> <p class="dwt_author">Weng, Qihao; Fu, Peng</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">280</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.risoe.dk/rispubl/NEI/NEI-DK-4800.pdf"> <span id="translatedtitle">WIND POWER <span class="hlt">ENSEMBLE</span> FORECASTING Henrik Aalborg Nielsen1</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">WIND POWER <span class="hlt">ENSEMBLE</span> FORECASTING Henrik Aalborg Nielsen1 , Henrik Madsen1 , Torben Skov Nielsen1. In this paper we address the problems of (i) transforming the mete- orological <span class="hlt">ensembles</span> to wind power <span class="hlt">ensembles</span> the uncertainty which follow from historical (climatological) data. However, quite often the actual wind power</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_13");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">281</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/32710735"> <span id="translatedtitle">Ergonomic comparison of a chem\\/bio prototype firefighter <span class="hlt">ensemble</span> and a standard <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Firefighter turnout gear and equipment protect the wearer against external hazards but, unfortunately, restrict mobility.\\u000a The aim of this study was to determine the ease of mobility and comfort while wearing a new prototype firefighter <span class="hlt">ensemble</span>\\u000a (PE) with additional chemical\\/biological hazard protection compared to a standard <span class="hlt">ensemble</span> (SE) by measuring static and dynamic\\u000a range of motion (ROM), job-related tasks, and</p> <div class="credits"> <p class="dwt_author">Aitor Coca; R. Roberge; A. Shepherd; J. B. Powell; J. O. Stull; W. J. Williams</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">282</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009EGUGA..1111255B"> <span id="translatedtitle">Statistical <span class="hlt">downscaling</span> of daily precipitation over Llobregat River Basin in Catalunya, Spain using analog method.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Since anthropogenic climate change has become an important issue, the need to provide regional climate change information has increased, both for impact assessment studies and policy making. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Statistical <span class="hlt">downscaling</span> technique is based on the view that regional climate may be seen to be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or ‘‘predictors'' for which GCMs are trustable to regional or local surface ‘‘predictands'' for which models are less skilful. The main advantage of these techniques is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. In dynamical <span class="hlt">downscaling</span> methods, a regional climate model (RCM) uses GCM outputs as its initial and boundary conditions. A statistical <span class="hlt">downscaling</span> procedure based on an analogue technique has been used to determine projections for future climate change in the Llobregat River Basin in Catalunya, Spain. Llobregat Basin is one of the most important of Catalonia because it provides a significant amount of water for numerous cities that make up including Barcelona. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. This poster presents the results of the <span class="hlt">downscaling</span> method and the next stages of the "Water Change" project. It details the use of historical data provided by 2 stakeholders involved in the project Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET) for the creation of future rainfall scenarios at the rain gauge location.</p> <div class="credits"> <p class="dwt_author">Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">283</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.uml.edu/docs/NEYWEsr2013Enroll_tcm18-61788.pdf"> <span id="translatedtitle">UMASS LOWELL'sUMASS LOWELL's New EnglandNew England SeniorSenior Wind <span class="hlt">Ensemble</span>Wind <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">UMASS LOWELL'sUMASS LOWELL's New EnglandNew England SeniorSenior Wind <span class="hlt">Ensemble</span>Wind <span class="hlt">Ensemble</span> (978 to participate, and that there is no objection to his or her participation, in the New England Youth Wind and responsibilities surrounding my / my child's participation in UMass Lowell's New England Youth Wind <span class="hlt">Ensemble</span> and</p> <div class="credits"> <p class="dwt_author">Massachusetts at Lowell, University of</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">284</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25283234"> <span id="translatedtitle">Hydrogen adsorption on bimetallic PdAu(111) surface alloys: minimum adsorption <span class="hlt">ensemble</span>, ligand and <span class="hlt">ensemble</span> effects, and <span class="hlt">ensemble</span> confinement.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The adsorption of hydrogen on structurally well defined PdAu-Pd(111) monolayer surface alloys was investigated in a combined experimental and theoretical study, aiming at a quantitative understanding of the adsorption and desorption properties of individual PdAu nanostructures. Combining the structural information obtained by high resolution scanning tunneling microscopy (STM), in particular on the abundance of specific adsorption <span class="hlt">ensembles</span> at different Pd surface concentrations, with information on the adsorption properties derived from temperature programmed desorption (TPD) spectroscopy and high resolution electron energy loss spectroscopy (HREELS) provides conclusions on the minimum <span class="hlt">ensemble</span> size for dissociative adsorption of hydrogen and on the adsorption energies on different sites active for adsorption. Density functional theory (DFT) based calculations give detailed insight into the physical effects underlying the observed adsorption behavior. Consequences of these findings for the understanding of hydrogen adsorption on bimetallic surfaces in general are discussed. PMID:25283234</p> <div class="credits"> <p class="dwt_author">Takehiro, Naoki; Liu, Ping; Bergbreiter, Andreas; Nørskov, Jens K; Behm, R Jürgen</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-11-21</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">285</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..16.1103H"> <span id="translatedtitle">Partitioning internal variability and model uncertainty components in a multireplicate multimodel <span class="hlt">ensemble</span> of hydrometeorological future projections</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A simple and robust framework was proposed by Hingray and Mériem (2013) for the partitioning of the different components of internal variability and model uncertainty in a multireplicate multimodel <span class="hlt">ensemble</span> (MRMME) of climate projections obtained for a suite of statistical <span class="hlt">downscaling</span> models (SDMs) and global climate models (GCMs). It is based on the quasi-ergodic assumption for transient climate simulations. Model uncertainty components are estimated from the noise-free signals of each modeling chain using a two-way ANOVA framework. The residuals from the noise-free signal are used to estimate the large and small scale internal variability (IV) components associated with each considered GCM/SDM configuration. This framework makes it possible to take into account all runs and replicates available from any climate <span class="hlt">ensemble</span> of opportunity. This quasi-ergodic ANOVA framework was applied to the MRMME of hydrometeorological simulations produced for the Upper Durance River basin (French Alps) over the 1860-2100 period within the RIWER2030 research project (http://www.lthe.fr/RIWER2030/). The different uncertainty sources were quantified as a function of lead time for projected changes in temperature, precipitation, evaporation losses, snow cover and discharges (Lafaysse et al., 2013). For temperature, GCM uncertainty prevails and, as opposed to IV, SDM uncertainty is non-negligible. Significant warming and in turn significant changes are predicted for evaporation, snow cover and seasonality of discharges. For precipitation, GCM and SDM uncertainty components are of the same order. Despite high model uncertainty, the non-zero climate change response of simulation chains is significant and annual precipitation is expected to decrease. However, high values are obtained for the large and small scale components of IV, inherited respectively from the GCMs and the different replicates of a given SDM. The same applies for annual discharge. The uncertainty in values that could be experienced for any given future period is therefore very high. For both discharge and precipitation, even the sign of future realizations is uncertain at a 90% confidence level. These findings have important implications. As for GCM uncertainty, SDM uncertainty cannot be neglected. The same applies for both components of internal variability. Climate change impact studies based on single SDM realizations are likely to be no more relevant than those based on single GCM runs (or small <span class="hlt">ensembles</span>). When they are intended to provide information for climate change adaptation, they may lead to poor decisions. In the present case, it would be better to adapt to IV of precipitation than to the precipitation decrease obtained from the mean climate change response of simulation chains. Hingray, B., Hendrickx, F., Bourqui M., Creutin, J.D., François, B., Gailhard, J., Lafaysse, M., Lemoine, N., Mathevet, T., Mezghani, A., Monteil, C., RIWER2030:Climats Régionaux et Incertitudes, Ressource en Eau et Gestion de 1860 à 2100.Projet ANR VMCS 2009-2012. Rapport Final. LTHE,EDF,Grenoble. Hingray, B., Saïd, M. (in revision). Partitioning internal variability and model uncertainty components in a multimodel multireplicate <span class="hlt">ensemble</span> of climate projections. J.Climate Lafaysse, M., Hingray, B., Gailhard, J., Mezghani, A., Terray, L. (in revision). Internal variability and model uncertainty components in a multireplicate multimodel <span class="hlt">ensemble</span> of hydrometeorological projections. Wat. Resour. Res.</p> <div class="credits"> <p class="dwt_author">Hingray, Benoit; Saïd, Mériem; Lafaysse, Matthieu; Gailhlard, Joël; Mezghani, Abdelkader</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">286</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005AGUFM.H33E1423V"> <span id="translatedtitle">A nonhomogeneous stochastic weather typing approach for statistical <span class="hlt">downscaling</span> of precipitation in Illinois</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Downscaling</span> methods try to derive local-scale values or characteristics from large-scale information such as AOGCM outputs. These methods can be useful to adress an issue of the climate change from a local point of view by understanding how this change will interact with existing local environmental features. Regional climate assessments require continuous time series for multiple scenarios and AOGCM drivers. This computational task is nowadays out of range of most of dynamical <span class="hlt">downscaling</span> models. Here, advanced statistical clustering methods are applied to define original atmospheric patterns, that will be included as the bases of a nonhomogeneous stochastic weather typing approach. This method provides accurate and rapid simulations of local-scale precipitation features for 37 raingauges in Illinois at low computational cost. Two different kinds of atmospheric states are defined: "circulation" patterns - developed by a model based method applied to large scale NCEP reanalysis data - and "precipitation" patterns - obtained through a hierarchical ascending clustering method applied directly to the observed rainfall amounts on Illinois with an original metric. By modelling the transition probabilities from one pattern to another by a nonhomogeneous Markov model - i.e. influenced by some large scale atmospheric variables such as geopotential heights, humidity and dew point temperature depression - we see that the precipitation states allow us to model conditional distributions of precipitation given the current weather state - and then to simulate local precipitation intensities - more accurately than with the traditional approach based on upper-air circulation patterns alone.</p> <div class="credits"> <p class="dwt_author">Vrac, M. R.; Hayhoe, K.; Stein, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">287</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014ClDy...43..375K"> <span id="translatedtitle">Development of sampling <span class="hlt">downscaling</span>: a case for wintertime precipitation in Hokkaido</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This study has developed sampling <span class="hlt">downscaling</span> (SmDS), in which dynamical <span class="hlt">downscaling</span> (DDS) is executed for a few of period selected from a long-term integration by general circulation model based on an observed statistical relationship between large-scale climate and regional-scale precipitation. SmDS expectedly produces climatology and frequency distribution of precipitation over a nested region with reducing computational cost, if a global-scale climate pattern mostly controls regional-scale weather statistics. Here SmDS was attempted for wintertime precipitation over Hokkaido, Japan, because a linkage between snowfall and sea-level pressure patterns has been known by Japanese synopticians and it can be detected by singular value decomposition (SVD) analysis on wintertime inter-annual variability during the period from 1980/1981 to 2009/2010 for precipitation over Hokkaido and moisture flux convergence around there. DDS for the full period over the same domain was also performed for comparison with SmDS. SmDS selected two winters from the top and two winters from the bottom of the projection onto the first SVD mode. It was found that, comparing with the full DDS, SmDS indeed provided unbiased statistics for average but exaggerated extreme statistics such as heavy rainfall frequency. It was also shown that the sampling in the SmDS method was much more effective than the random sampling.</p> <div class="credits"> <p class="dwt_author">Kuno, Ryusuke; Inatsu, Masaru</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">288</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFM.H14G..07O"> <span id="translatedtitle"><span class="hlt">Downscaling</span> Future Climate Change Projections for Water Resource Applications: A Case Study for Mesoamerica (Invited)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Mesoamerica is a region that is potentially at severe risk due to future climate change. This is especially true for the water resources required for agriculture, human consumption, and hydroelectric power generation. Yet global climate models cannot properly resolve surface climate in the region, due to it's complex topography and nearness to oceans. Precipitation in particular is poorly handled. Further, Mesoamerica is hardly the only region worldwide for which these issues exist. To address this deficiency, a series of high-resolution (4-12 km) dynamical <span class="hlt">downscaling</span> simulations of future climate change between now and 2060 have been made for Mesoamerica and the Caribbean. We used the Weather Research and Forecasting (WRF) regional climate model to <span class="hlt">downscale</span> results from the NCAR CCSM4 CMIP5 RCP8.5 global simulation. The entire region is covered at 12 km horizontal spatial resolution, with as much as possible (especially in mountainous regions) at 4 km. We compare a control period (2006-2010) with 50 years into the future (2056-2060). Basic results for surface climate will be presented, as well as a developing strategy for explicitly employing these results in projecting the implications for water resources in the region. Connections will also be made to other regions around the globe that could benefit from this type of integrated modeling and analysis.</p> <div class="credits"> <p class="dwt_author">Oglesby, R. J.; Rowe, C. M.; Munoz-Arriola, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">289</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2002EGSGA..27.4274B"> <span id="translatedtitle">Comparison of The <span class="hlt">Downscaling</span> Possibilities of Stochastic Pulse Models At Two Different Climatic Regions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Clustered rectangular pulse point process models are applied to reproduce temporal rainfall processes at different sites located in the UK and in Austria. The possibili- ties of <span class="hlt">downscaling</span> of daily rainfall series and the identification of limiting ranges of application are investigated. Various modifications of the fitting procedure are con- sidered like the incorporation of the scale of fluctuation. A different distribution of the cell depths, namely the generalized Pareto distribution is applied in order to better reproduce the variability of highly fluctuating rainfall processes at finer time scales. Furthermore a method called Wavelet Transform Modulus Maxima (WTMM) is taken into account to draw inferences about the scaling properties of the observed and the simulated rainfall data. The thorough analysis of the synthetically generated time- series shows a very good agreement with the properties of the observed precipitation processes in these different climatic regions. These results demonstrate the applicabil- ity of the rectangular pulse point process model approach for a range of time scales and for <span class="hlt">downscaling</span> purposes.</p> <div class="credits"> <p class="dwt_author">Bogner, K.; Onof, C.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">290</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1616395P"> <span id="translatedtitle">Combining artificial neural networks and circulation type classification: does it improve <span class="hlt">downscaling</span> models?</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Circulation type classifications may be used for <span class="hlt">downscaling</span> in so called reference class forecasting (RCF), i.e. to to assign atmospheric circulation predictors to a certain type of a circulation type classification and use the value for the target variable associated with this type in the past as a model value. Doing so often already leads to useful statistical assessment models. However a generally superior method is that of artificial neural networks (NNW). Using adequate configuration, the latter are able to outperform the RCF method in virtually all cases. However the adequate configuration of NNWs is often not easy to decide and the training of the network weights may be an extensive and slow process while RCF is relatively fast. In the context of a starting project dealing with alpine climate change studies (Virtual Alpine Observatory II, VAO2), this study evaluates if a combination of both statistical approaches (called neural networks of classification types, NNC) may lead to an improvement for statistical <span class="hlt">downscaling</span>. Preliminary results suggest that the gain in skill and the computational speed for the network training largely depends on the configuration of both: the circulation type classification and the network configuration regarding, topology, learning rate, predictors and so on. In this context it is important to consider the evolution of the learning process, where sometimes the NNW is superior and sometimes the NNC.</p> <div class="credits"> <p class="dwt_author">Philipp, Andreas; Beck, Christoph; Kaspar, Severin; Jacobeit, Jucundus</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">291</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20120016072&hterms=soil&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsoil"> <span id="translatedtitle">Two Topics in Seasonal Streamflow Forecasting: Soil Moisture Initialization Error and Precipitation <span class="hlt">Downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">Continental-scale offline simulations with a land surface model are used to address two important issues in the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which the <span class="hlt">downscaling</span> of seasonal precipitation forecasts, if it could be done accurately, would improve streamflow forecasts. The reduction in streamflow forecast skill (with forecasted streamflow measured against observations) associated with adding noise to a soil moisture field is found to be, to first order, proportional to the average reduction in the accuracy of the soil moisture field itself. This result has implications for streamflow forecast improvement under satellite-based soil moisture measurement programs. In the second and more idealized ("perfect model") analysis, precipitation <span class="hlt">downscaling</span> is found to have an impact on large-scale streamflow forecasts only if two conditions are met: (i) evaporation variance is significant relative to the precipitation variance, and (ii) the subgrid spatial variance of precipitation is adequately large. In the large-scale continental region studied (the conterminous United States), these two conditions are met in only a somewhat limited area.</p> <div class="credits"> <p class="dwt_author">Koster, Randal; Walker, Greg; Mahanama, Sarith; Reichle, Rolf</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">292</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014GMD.....7.2003B"> <span id="translatedtitle">Ice sheet dynamics within an earth system model: <span class="hlt">downscaling</span>, coupling and first results</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present first results from a coupled model setup, consisting of the state-of-the-art ice sheet model RIMBAY (Revised Ice Model Based on frAnk pattYn), and the community earth system model COSMOS. We show that special care has to be provided in order to ensure physical distributions of the forcings as well as numeric stability of the involved models. We demonstrate that a suitable statistical <span class="hlt">downscaling</span> is crucial for ice sheet stability, especially for southern Greenland where surface temperatures are close to the melting point. The <span class="hlt">downscaling</span> of net snow accumulation is based on an empirical relationship between surface slope and rainfall. The simulated ice sheet does not show dramatic loss of ice volume for pre-industrial conditions and is comparable with present-day ice orography. A sensitivity study with high CO2 level is used to demonstrate the effects of dynamic ice sheets onto climate compared to the standard setup with prescribed ice sheets.</p> <div class="credits"> <p class="dwt_author">Barbi, D.; Lohmann, G.; Grosfeld, K.; Thoma, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">293</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014ThApC.tmp..190D"> <span id="translatedtitle">Statistical <span class="hlt">downscaling</span> of temperature using three techniques in the Tons River basin in Central India</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this study, <span class="hlt">downscaling</span> models were developed for the projections of monthly maximum and minimum air temperature for three stations, namely, Allahabad, Satna, and Rewa in Tons River basin, which is a sub-basin of the Ganges River in Central India. The three <span class="hlt">downscaling</span> techniques, namely, multiple linear regression (MLR), artificial neural network (ANN), and least square support vector machine (LS-SVM), were used for the development of models, and best identified model was used for simulations of future predictand (temperature) using third-generation Canadian Coupled Global Climate Model (CGCM3) simulation of A2 emission scenario for the period 2001-2100. The performance of the models was evaluated based on four statistical performance indicators. To reduce the bias in monthly projected temperature series, bias correction technique was employed. The results show that all the models are able to simulate temperature; however, LS-SVM models perform slightly better than ANN and MLR. The best identified LS-SVM models are then employed to project future temperature. The results of future projections show the increasing trends in maximum and minimum temperature for A2 scenario. Further, it is observed that minimum temperature will increase at greater rate than maximum temperature.</p> <div class="credits"> <p class="dwt_author">Duhan, Darshana; Pandey, Ashish</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">294</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014JGRC..119.3497S"> <span id="translatedtitle">Climate change projection in the Northwest Pacific marginal seas through dynamic <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">study presents future climate change projections in the Northwest Pacific (NWP) marginal seas using dynamic <span class="hlt">downscaling</span> from global climate models (GCMs). A regional climate model (RCM) for the Northwest Pacific Ocean was setup and integrated over the period from 2001 to 2100. The model used forcing fields from three different GCM simulations to <span class="hlt">downscale</span> the effect of global climate change. MIROC, ECHAM, and HADCM were selected to provide climate change signals for the RCM. These signals were calculated from the GCMs using Cyclostationary Empirical Orthogonal Function analysis and added to the present lateral open boundary and the surface forcing. The RCM was validated by comparing hindcast result with the observation. It was able to project detailed regional climate change processes that GCMs were not able to resolve. A relatively large increases of water temperature were found in the marginal seas. However, only a marginal change was found along the Kuroshio path. Heat supply to the atmosphere decreases in most study areas due to a slower warming of the sea surface compared to the atmosphere. The RCM projection suggests that the temperature of the Yellow Sea Bottom Cold Water will gradually increase by 2100. Volume transports through major straits except the Taiwan Strait in the marginal seas are projected to increase slightly in future. Increased northeasterly wind stress in the East China Sea may also result in the transport change.</p> <div class="credits"> <p class="dwt_author">Seo, Gwang-Ho; Cho, Yang-Ki; Choi, Byoung-Ju; Kim, Kwang-Yul; Kim, Bong-guk; Tak, Yong-jin</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">295</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8890E..0ES"> <span id="translatedtitle">Optimum interpolation algorithms for ABI multiple channel radiance <span class="hlt">down-scaling</span> processing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Advanced Baseline Imager (ABI) is the primary instrument onboard GOES-R for imaging Earth's weather, climate, and environment and will be used for a wide range of applications related to weather, oceans, land, climate, and hazards (fires, volcanoes, hurricanes, and storms that spawn tornados). It will provide over 65% of all the mission data products currently defined. ABI views the Earth with 16 different spectral bands, including two visible channels, four nearinfrared channels and ten infrared channels at 0.5, 1, and 2 km spatial resolutions respectively. For most of the operational ABI retrieval algorithms, the collocated/co-registered radiance dataset are at 2 km resolution for all of the bands required. This requires <span class="hlt">down-scaling</span> of the radiance data from 0.5 or 1 km to 2 km for ABI visible and near-IR bands (2 or 1, 3 & 5 respectively), the reference of 2 km is the nominal resolution at the satellite sub-point. In this paper, the spatial resolution characteristic of the ABI fixed grid level1b radiance data is discussed. An optimum interpolation algorithm which has been developed for the ABI multiple channel radiance <span class="hlt">down-scaling</span> processing is present.</p> <div class="credits"> <p class="dwt_author">Sun, Haibing; Wolf, W.; King, T.; Maddy, Eric; Sampson, Shanna</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">296</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1514030H"> <span id="translatedtitle">Verifying and Postprocesing the <span class="hlt">Ensemble</span> Spread-Error Relationship</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">With the increased utilization of <span class="hlt">ensemble</span> forecasts in weather and hydrologic applications, there is a need to verify their benefit over less expensive deterministic forecasts. One such potential benefit of <span class="hlt">ensemble</span> systems is their capacity to forecast their own forecast error through the <span class="hlt">ensemble</span> spread-error relationship. The paper begins by revisiting the limitations of the Pearson correlation alone in assessing this relationship. Next, we introduce two new metrics to consider in assessing the utility an <span class="hlt">ensemble</span>'s varying dispersion. We argue there are two aspects of an <span class="hlt">ensemble</span>'s dispersion that should be assessed. First, and perhaps more fundamentally: is there enough variability in the <span class="hlt">ensembles</span> dispersion to justify the maintenance of an expensive <span class="hlt">ensemble</span> prediction system (EPS), irrespective of whether the EPS is well-calibrated or not? To diagnose this, the factor that controls the theoretical upper limit of the spread-error correlation can be useful. Secondly, does the variable dispersion of an <span class="hlt">ensemble</span> relate to variable expectation of forecast error? Representing the spread-error correlation in relation to its theoretical limit can provide a simple diagnostic of this attribute. A context for these concepts is provided by assessing two operational <span class="hlt">ensembles</span>: 30-member Western US temperature forecasts for the U.S. Army Test and Evaluation Command and 51-member Brahmaputra River flow forecasts of the Climate Forecast and Applications Project for Bangladesh. Both of these systems utilize a postprocessing technique based on quantile regression (QR) under a step-wise forward selection framework leading to <span class="hlt">ensemble</span> forecasts with both good reliability and sharpness. In addition, the methodology utilizes the <span class="hlt">ensemble</span>'s ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. We will describe both <span class="hlt">ensemble</span> systems briefly, review the steps used to calibrate the <span class="hlt">ensemble</span> forecast, and present verification statistics using error-spread metrics, along with figures from operational <span class="hlt">ensemble</span> forecasts before and after calibration.</p> <div class="credits"> <p class="dwt_author">Hopson, Tom; Knievel, Jason; Liu, Yubao; Roux, Gregory; Wu, Wanli</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">297</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008CMaPh.283..343L"> <span id="translatedtitle">Superbosonization of Invariant Random Matrix <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">‘Superbosonization’ is a new variant of the method of commuting and anti-commuting variables as used in studying random matrix models of disordered and chaotic quantum systems. We here give a concise mathematical exposition of the key formulas of superbosonization. Conceived by analogy with the bosonization technique for Dirac fermions, the new method differs from the traditional one in that the superbosonization field is dual to the usual Hubbard-Stratonovich field. The present paper addresses invariant random matrix <span class="hlt">ensembles</span> with symmetry group U n , O n , or USp n , giving precise definitions and conditions of validity in each case. The method is illustrated at the example of Wegner’s n-orbital model. Superbosonization promises to become a powerful tool for investigating the universality of spectral correlation functions for a broad class of random matrix <span class="hlt">ensembles</span> of non-Gaussian and/or non-invariant type.</p> <div class="credits"> <p class="dwt_author">Littelmann, P.; Sommers, H.-J.; Zirnbauer, M. R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">298</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cdsweb.cern.ch/record/1047937"> <span id="translatedtitle">Superbosonization of invariant random matrix <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Superbosonization is a new variant of the method of commuting and anti-commuting variables as used in studying random matrix models of disordered and chaotic quantum systems. We here give a concise mathematical exposition of the key formulas of superbosonization. Conceived by analogy with the bosonization technique for Dirac fermions, the new method differs from the traditional one in that the superbosonization field is dual to the usual Hubbard-Stratonovich field. The present paper addresses invariant random matrix <span class="hlt">ensembles</span> with symmetry group U(n), O(n), or USp(n), giving precise definitions and conditions of validity in each case. The method is illustrated at the example of Wegner's n-orbital model. Superbosonization promises to become a powerful tool for investigating the universality of spectral correlation functions for a broad class of random matrix <span class="hlt">ensembles</span> of non-Gaussian and/or non-invariant type.</p> <div class="credits"> <p class="dwt_author">Littelmann, P; Zirnbauer, M R</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">299</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/0707.2929v2"> <span id="translatedtitle">Superbosonization of invariant random matrix <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Superbosonization is a new variant of the method of commuting and anti-commuting variables as used in studying random matrix models of disordered and chaotic quantum systems. We here give a concise mathematical exposition of the key formulas of superbosonization. Conceived by analogy with the bosonization technique for Dirac fermions, the new method differs from the traditional one in that the superbosonization field is dual to the usual Hubbard-Stratonovich field. The present paper addresses invariant random matrix <span class="hlt">ensembles</span> with symmetry group U(n), O(n), or USp(n), giving precise definitions and conditions of validity in each case. The method is illustrated at the example of Wegner's n-orbital model. Superbosonization promises to become a powerful tool for investigating the universality of spectral correlation functions for a broad class of random matrix <span class="hlt">ensembles</span> of non-Gaussian and/or non-invariant type.</p> <div class="credits"> <p class="dwt_author">P. Littelmann; H. -J. Sommers; M. R. Zirnbauer</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-07-19</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">300</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvL.113j4102B"> <span id="translatedtitle">Dysonian Dynamics of the Ginibre <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We study the time evolution of Ginibre matrices whose elements undergo Brownian motion. The non-Hermitian character of the Ginibre <span class="hlt">ensemble</span> binds the dynamics of eigenvalues to the evolution of eigenvectors in a nontrivial way, leading to a system of coupled nonlinear equations resembling those for turbulent systems. We formulate a mathematical framework allowing simultaneous description of the flow of eigenvalues and eigenvectors, and we unravel a hidden dynamics as a function of a new complex variable, which in the standard description is treated as a regulator only. We solve the evolution equations for large matrices and demonstrate that the nonanalytic behavior of the Green's functions is associated with a shock wave stemming from a Burgers-like equation describing correlations of eigenvectors. We conjecture that the hidden dynamics that we observe for the Ginibre <span class="hlt">ensemble</span> is a general feature of non-Hermitian random matrix models and is relevant to related physical applications.</p> <div class="credits"> <p class="dwt_author">Burda, Zdzislaw; Grela, Jacek; Nowak, Maciej A.; Tarnowski, Wojciech; Warcho?, Piotr</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_14");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" 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onClick='return showDiv("page_6");' href="#">6</a> <a onClick='return showDiv("page_7");' href="#">7</a> <a onClick='return showDiv("page_8");' href="#">8</a> <a onClick='return showDiv("page_9");' href="#">9</a> <a onClick='return showDiv("page_10");' href="#">10</a> <a onClick='return showDiv("page_11");' href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a style="font-weight: bold;">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_17");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">301</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/1410.3941v1"> <span id="translatedtitle">Quantum Data Compression of a Qubit <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an <span class="hlt">ensemble</span> of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could provide a vast reduction in the amount of quantum memory required to store a quantum <span class="hlt">ensemble</span>, making even today's limited quantum memories far more powerful than previously recognized.</p> <div class="credits"> <p class="dwt_author">Lee A. Rozema; Dylan H. Mahler; Alex Hayat; Peter S. Turner; Aephraim M. Steinberg</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">302</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvL.113p0504R"> <span id="translatedtitle">Quantum Data Compression of a Qubit <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Data compression is a ubiquitous aspect of modern information technology, and the advent of quantum information raises the question of what types of compression are feasible for quantum data, where it is especially relevant given the extreme difficulty involved in creating reliable quantum memories. We present a protocol in which an <span class="hlt">ensemble</span> of quantum bits (qubits) can in principle be perfectly compressed into exponentially fewer qubits. We then experimentally implement our algorithm, compressing three photonic qubits into two. This protocol sheds light on the subtle differences between quantum and classical information. Furthermore, since data compression stores all of the available information about the quantum state in fewer physical qubits, it could allow for a vast reduction in the amount of quantum memory required to store a quantum <span class="hlt">ensemble</span>, making even today's limited quantum memories far more powerful than previously recognized.</p> <div class="credits"> <p class="dwt_author">Rozema, Lee A.; Mahler, Dylan H.; Hayat, Alex; Turner, Peter S.; Steinberg, Aephraim M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">303</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cdsweb.cern.ch/record/1387305"> <span id="translatedtitle">Face Recognition using Optimal Representation <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Recently, the face recognizers based on linear representations have been shown to deliver state-of-the-art performance. In real-world applications, however, face images usually suffer from expressions, disguises and random occlusions. The problematic facial parts undermine the validity of the linear-subspace assumption and thus the recognition performance deteriorates significantly. In this work, we address the problem in a learning-inference-mixed fashion. By observing that the linear-subspace assumption is more reliable on certain face patches rather than on the holistic face, some Bayesian Patch Representations (BPRs) are randomly generated and interpreted according to the Bayes' theory. We then train an <span class="hlt">ensemble</span> model over the patch-representations by minimizing the empirical risk w.r.t the "leave-one-out margins". The obtained model is termed Optimal Representation <span class="hlt">Ensemble</span> (ORE), since it guarantees the optimality from the perspective of Empirical Risk Minimization. To handle the unknown patterns in tes...</p> <div class="credits"> <p class="dwt_author">Li, Hanxi; Gao, Yongsheng</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">304</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013PhRvL.111j3601B"> <span id="translatedtitle">Feedback Cooling of an Atomic Spin <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We apply entropy removal by measurement and feedback to a cold atomic spin <span class="hlt">ensemble</span>. Using quantum nondemolition probing by Faraday rotation measurement, and feedback by weak optical pumping, we drive the initially random collective spin variable F^ toward the origin F^=0. We use input-output relations and <span class="hlt">ensemble</span> quantum noise models to describe this quantum control process and identify an optimal two-round control procedure. We observe 12 dB of spin noise reduction, or a factor-of-63 reduction in phase-space volume. The method offers a nonthermal route to generation of exotic entangled states in ultracold gases, including macroscopic singlet states and strongly correlated states of quantum lattice gases.</p> <div class="credits"> <p class="dwt_author">Behbood, N.; Colangelo, G.; Martin Ciurana, F.; Napolitano, M.; Sewell, R. J.; Mitchell, M. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">305</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25166664"> <span id="translatedtitle">Feedback cooling of an atomic spin <span class="hlt">ensemble</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We apply entropy removal by measurement and feedback to a cold atomic spin <span class="hlt">ensemble</span>. Using quantum nondemolition probing by Faraday rotation measurement, and feedback by weak optical pumping, we drive the initially random collective spin variable F toward the origin F=0. We use input-output relations and <span class="hlt">ensemble</span> quantum noise models to describe this quantum control process and identify an optimal two-round control procedure. We observe 12 dB of spin noise reduction, or a factor-of-63 reduction in phase-space volume. The method offers a nonthermal route to generation of exotic entangled states in ultracold gases, including macroscopic singlet states and strongly correlated states of quantum lattice gases. PMID:25166664</p> <div class="credits"> <p class="dwt_author">Behbood, N; Colangelo, G; Ciurana, F Martin; Napolitano, M; Sewell, R J; Mitchell, M W</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">306</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.meted.ucar.edu/training_module.php?id=246"> <span id="translatedtitle">An Introduction to <span class="hlt">Ensemble</span> Streamflow Prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">The âIntroduction to <span class="hlt">Ensemble</span> Streamflow Predictionâ module provides basic information on probabilistic streamflow forecasting. In this webcast, Dr. Richard Koehler, the National Hydrologic Sciences Training Coordinator for NOAA's NWS, presents information about the types of organizations that might use probabilistic streamflow forecasts as well as foundation concepts and background for ESP methods. The module begins with a brief review of hydrologic models including deterministic, stochastic, and scenario-based approaches. It then provides an overview of time-series approaches including a summary of traditional techniques such as flood frequency, flood analysis, statistical analysis, and trend analysis. Finally, the module presents the basics of ESP techniques including an explanation of its strengths, weaknesses, and appropriate application. The module also provides guidance on how to interpret <span class="hlt">ensemble</span> forecast products.</p> <div class="credits"> <p class="dwt_author">Comet</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-30</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">307</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25375711"> <span id="translatedtitle">Synchronization of two <span class="hlt">ensembles</span> of atoms.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We propose a system for observing the correlated phase dynamics of two mesoscopic <span class="hlt">ensembles</span> of atoms through their collective coupling to an optical cavity. We find a dynamical quantum phase transition induced by pump noise and cavity output coupling. The spectral properties of the superradiant light emitted from the cavity show that at a critical pump rate the system undergoes a transition from the behavior of two independent oscillators to the phase locking that is the signature of quantum synchronization. PMID:25375711</p> <div class="credits"> <p class="dwt_author">Xu, Minghui; Tieri, D A; Fine, E C; Thompson, James K; Holland, M J</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-10</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">308</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvL.113o4101X"> <span id="translatedtitle">Synchronization of Two <span class="hlt">Ensembles</span> of Atoms</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We propose a system for observing the correlated phase dynamics of two mesoscopic <span class="hlt">ensembles</span> of atoms through their collective coupling to an optical cavity. We find a dynamical quantum phase transition induced by pump noise and cavity output coupling. The spectral properties of the superradiant light emitted from the cavity show that at a critical pump rate the system undergoes a transition from the behavior of two independent oscillators to the phase locking that is the signature of quantum synchronization.</p> <div class="credits"> <p class="dwt_author">Xu, Minghui; Tieri, D. A.; Fine, E. C.; Thompson, James K.; Holland, M. J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">309</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/1409.6038v2"> <span id="translatedtitle">Loop Equation Analysis of the Circular $ ?$ <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We construct a hierarchy of loop equations for invariant circular <span class="hlt">ensembles</span>. These are valid for general classes of potentials and for arbitrary inverse temperatures $ {\\rm Re}\\,\\beta>0 $ and number of eigenvalues $ N $. Using matching arguments for the resolvent functions of linear statistics $ f(\\zeta)=(\\zeta+z)/(\\zeta-z) $ in a particular asymptotic regime, the global regime, we systematically develop the corresponding large $ N $ expansion and apply this solution scheme to the Dyson circular <span class="hlt">ensemble</span>. Currently we can compute the second resolvent function to ten orders in this expansion and also its general Fourier coefficient or moment $ m_{k} $ to an equivalent length. The leading large $ N $, large $ k $, $ k/N $ fixed form of the moments can be related to the small wave-number expansion of the structure function in the bulk, scaled Dyson circular <span class="hlt">ensemble</span>, known from earlier work. From the moment expansion we conjecture some exact partial fraction forms for the low $ k $ moments. For all of the forgoing results we have made a comparison with the exactly soluble cases of $ \\beta = 1,2,4 $, general $ N $ and even, positive $ \\beta $, $ N=2,3 $.</p> <div class="credits"> <p class="dwt_author">N. S. Witte; P. J. Forrester</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">310</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ntrs.nasa.gov/search.jsp?R=20000093260&hterms=diversity+training&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Ddiversity%2Btraining"> <span id="translatedtitle">Decimated Input <span class="hlt">Ensembles</span> for Improved Generalization</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p class="result-summary">Recently, many researchers have demonstrated that using classifier <span class="hlt">ensembles</span> (e.g., averaging the outputs of multiple classifiers before reaching a classification decision) leads to improved performance for many difficult generalization problems. However, in many domains there are serious impediments to such "turnkey" classification accuracy improvements. Most notable among these is the deleterious effect of highly correlated classifiers on the <span class="hlt">ensemble</span> performance. One particular solution to this problem is generating "new" training sets by sampling the original one. However, with finite number of patterns, this causes a reduction in the training patterns each classifier sees, often resulting in considerably worsened generalization performance (particularly for high dimensional data domains) for each individual classifier. Generally, this drop in the accuracy of the individual classifier performance more than offsets any potential gains due to combining, unless diversity among classifiers is actively promoted. In this work, we introduce a method that: (1) reduces the correlation among the classifiers; (2) reduces the dimensionality of the data, thus lessening the impact of the 'curse of dimensionality'; and (3) improves the classification performance of the <span class="hlt">ensemble</span>.</p> <div class="credits"> <p class="dwt_author">Tumer, Kagan; Oza, Nikunj C.; Norvig, Peter (Technical Monitor)</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">311</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.meted.ucar.edu/training_module.php?id=300"> <span id="translatedtitle">Wave <span class="hlt">Ensembles</span> in the Marine Forecast Process</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">The NCEP Marine Modeling and Analysis Branch (MMAB) <span class="hlt">Ensemble</span> Global Ocean Wave Forecast System (EGOWaFS) provides five-day forecasts of global winds, wind wave and swell conditions in probabilistic terms. This product became available early in 2007 both through an NCEP non-operational web page and, for raw data, through FTP for use by marine forecasters at NWS WFOs and other locations. The data from the EGOWaFS can be used in a number of ways, including: * As input to probabilistic marine forecasts for wind waves and swell * As input to a local wave <span class="hlt">ensemble</span>, such as Simulated Waves Nearshore (SWAN) * As input to develop probabilistic forecasts for rip current development This webcast has been developed to introduce the EGOWaFS to the marine forecasting community. Topics discussed include: The unique basis for <span class="hlt">ensemble</span> prediction of ocean waves Graphics of EGOWaFS product output and their interpretation Case examples showing examples of EGOWaFS, including: Potential for EGOWaFS forecast bias resulting from systematic errors in wind forcing, Use of EGOWaFS data to provide boundary conditions for local near-shore wave models, and Application of EGOWaFS data to create a probabilistic forecast for the occurrence of rip currents.</p> <div class="credits"> <p class="dwt_author">Comet</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-12-03</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">312</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23454721"> <span id="translatedtitle">Complementary <span class="hlt">ensemble</span> clustering of biomedical data.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The rapidly growing availability of electronic biomedical data has increased the need for innovative data mining methods. Clustering in particular has been an active area of research in many different application areas, with existing clustering algorithms mostly focusing on one modality or representation of the data. Complementary <span class="hlt">ensemble</span> clustering (CEC) is a recently introduced framework in which Kmeans is applied to a weighted, linear combination of the coassociation matrices obtained from separate <span class="hlt">ensemble</span> clustering of different data modalities. The strength of CEC is its extraction of information from multiple aspects of the data when forming the final clusters. This study assesses the utility of CEC in biomedical data, which often have multiple data modalities, e.g., text and images, by applying CEC to two distinct biomedical datasets (PubMed images and radiology reports) that each have two modalities. Referent to five different clustering approaches based on the Kmeans algorithm, CEC exhibited equal or better performance in the metrics of micro-averaged precision and Normalized Mutual Information across both datasets. The reference methods included clustering of single modalities as well as <span class="hlt">ensemble</span> clustering of separate and merged data modalities. Our experimental results suggest that CEC is equivalent or more efficient than comparable Kmeans based clustering methods using either single or merged data modalities. PMID:23454721</p> <div class="credits"> <p class="dwt_author">Fodeh, Samah Jamal; Brandt, Cynthia; Luong, Thai Binh; Haddad, Ali; Schultz, Martin; Murphy, Terrence; Krauthammer, Michael</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">313</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2654620"> <span id="translatedtitle">A Scalable Framework For Cluster <span class="hlt">Ensembles</span> *</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">An <span class="hlt">ensemble</span> of clustering solutions or partitions may be generated for a number of reasons. If the data set is very large, clustering may be done on tractable size disjoint subsets. The data may be distributed at different sites for which a distributed clustering solution with a final merging of partitions is a natural fit. In this paper, two new approaches to combining partitions, represented by sets of cluster centers, are introduced. The advantage of these approaches is that they provide a final partition of data that is comparable to the best existing approaches, yet scale to extremely large data sets. They can be 100,000 times faster while using much less memory. The new algorithms are compared against the best existing cluster <span class="hlt">ensemble</span> merging approaches, clustering all the data at once and a clustering algorithm designed for very large data sets. The comparison is done for fuzzy and hard k-means based clustering algorithms. It is shown that the centroid-based <span class="hlt">ensemble</span> merging algorithms presented here generate partitions of quality comparable to the best label vector approach or clustering all the data at once, while providing very large speedups. PMID:20160846</p> <div class="credits"> <p class="dwt_author">Hore, Prodip; Hall, Lawrence O.; Goldgof, Dmitry B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">314</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JHyd..399..281W"> <span id="translatedtitle">Generation of <span class="hlt">ensemble</span> precipitation forecast from single-valued quantitative precipitation forecast for hydrologic <span class="hlt">ensemble</span> prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">SummaryReliable and skillful precipitation <span class="hlt">ensemble</span> forecasts are necessary to produce reliable and skilful hydrologic <span class="hlt">ensemble</span> forecasts. It is well known that, in general, raw precipitation <span class="hlt">ensemble</span> forecasts from the numerical weather prediction (NWP) models are not very reliable and that, for short-range prediction, human forecasters add significant skill to the NWP-generated single-valued quantitative precipitation forecasts (QPF). In this paper, we describe and evaluate a statistical procedure for producing precipitation <span class="hlt">ensemble</span> forecasts from single-valued QPFs. The procedure is based on the bivariate probability distribution between the observed precipitation and the single-valued QPF. The distribution is modeled as a mixed-type in which the relationship between the positive observed precipitation and positive forecast precipitation is assumed to be bivariate meta-Gaussian. We also describe and comparatively evaluate a generalized meta-Gaussian model in which the model parameter is optimized by minimizing the mean Continuous Ranked Probability Score. The performance of these procedures is assessed through dependent and cross validation using data for selected river basins in the service areas of the Arkansas-Red Basin, California-Nevada and Middle-Atlantic River Forecast Centers of the National Weather Service. The validation results show that, overall, the precipitation <span class="hlt">ensembles</span> generated by the proposed procedures are reliable and capture the skill in the conditioning single-valued forecasts very well.</p> <div class="credits"> <p class="dwt_author">Wu, Limin; Seo, Dong-Jun; Demargne, Julie; Brown, James D.; Cong, Shuzheng; Schaake, John</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">315</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54733983"> <span id="translatedtitle">Comparison of statistical and dynamical <span class="hlt">downscaling</span> of extreme precipitations over France in present-day and future climate</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a comparison of two <span class="hlt">downscaling</span> methods of extreme precipitations over France at a climatic time scale : a dynamical one performed with the Regional Climate Model ALADIN-Climate used at a resolution of 12 km, and a statistical one based on the weather regime approach and using the analog methodology to reconstruct daily fields of precipitations at a 8</p> <div class="credits"> <p class="dwt_author">Jeanne Colin; Michel Déqué; Emila Sanchez Gomez; Samuel Somot</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">316</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014NPGeo..21..971C"> <span id="translatedtitle">Representing model error in <span class="hlt">ensemble</span> data assimilation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The paper investigates a method to represent model error in the <span class="hlt">ensemble</span> data assimilation (EDA) system. The ECMWF operational EDA simulates the effect of both observations and model uncertainties. Observation errors are represented by perturbations with statistics characterized by the observation error covariance matrix whilst the model uncertainties are represented by stochastic perturbations added to the physical tendencies to simulate the effect of random errors in the physical parameterizations (ST-method). In this work an alternative method (XB-method) is proposed to simulate model uncertainties by adding perturbations to the model background field. In this way the error represented is not just restricted to model error in the usual sense but potentially extends to any form of background error. The perturbations have the same correlation as the background error covariance matrix and their magnitude is computed from comparing the high-resolution operational innovation variances with the <span class="hlt">ensemble</span> variances when the <span class="hlt">ensemble</span> is obtained by perturbing only the observations (OBS-method). The XB-method has been designed to represent the short range model error relevant for the data assimilation window. Spread diagnostic shows that the XB-method generates a larger spread than the ST-method that is operationally used at ECMWF, in particular in the extratropics. Three-dimensional normal-mode diagnostics indicate that XB-EDA spread projects more than the spread from the other EDAs onto the easterly inertia-gravity modes associated with equatorial Kelvin waves, tropical dynamics and, in general, model error sources. The background error statistics from the above described EDAs have been employed in the assimilation system. The assimilation system performance showed that the XB-method background error statistics increase the observation influence in the analysis process. The other EDA background error statistics, when inflated by a global factor, generate analyses with 30-50% smaller degree of freedom of signal. XB-EDA background error variances have not been inflated. The presented EDAs have been used to generate the initial perturbations of the ECMWF <span class="hlt">ensemble</span> prediction system (EPS) of which the XB-EDA induces the largest EPS spread, also in the medium range, leading to a more reliable <span class="hlt">ensemble</span>. Compared to ST-EDA, XB-EDA leads to a small improvement of the EPS ignorance skill score at day 3 and 7.</p> <div class="credits"> <p class="dwt_author">Cardinali, C.; Žagar, N.; Radnoti, G.; Buizza, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">317</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013TCD.....7.3163G"> <span id="translatedtitle">The Greenland ice sheet: modelling the surface mass balance from GCM output with a new statistical <span class="hlt">downscaling</span> technique</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The aim of this study is to derive a realistic estimation of the Surface Mass Balance (SMB) of the Greenland ice sheet (GrIS) through statistical <span class="hlt">downscaling</span> of Global Coupled Model (GCM) outputs. To this end, climate simulations performed with the CNRM-CM5.1 Atmosphere-Ocean GCM within the CMIP5 (Coupled Model Intercomparison Project phase 5) framework are used for the period 1850-2300. From the year 2006, two different emission scenarios are considered (RCP4.5 and RCP8.5). Simulations of SMB performed with the detailed snowpack model Crocus driven by CNRM-CM5.1 surface atmospheric forcings serve as a reference. On the basis of these simulations, statistical relationships between total precipitation, snow-ratio, snowmelt, sublimation and near-surface air temperature are established. This leads to the formulation of SMB variation as a function of temperature variation. Based on this function, a <span class="hlt">downscaling</span> technique is proposed in order to refine 150 km horizontal resolution SMB output from CNRM-CM5.1 to a 15 km resolution grid. This leads to a much better estimation of SMB along the GrIS margins, where steep topography gradients are not correctly represented at low-resolution. For the recent past (1989-2008), the integrated SMB over the GrIS is respectively 309 and 243 Gt yr-1 for raw and <span class="hlt">downscaled</span> CNRM-CM5.1. In comparison, the Crocus snowpack model forced with ERA-Interim yields a value of 245 Gt yr-1. The major part of the remaining discrepancy between Crocus and <span class="hlt">downscaled</span> CNRM-CM5.1 SMB is due to the different snow albedo representation. The difference between the raw and the <span class="hlt">downscaled</span> SMB tends to increase with near-surface air temperature via an increase in snowmelt.</p> <div class="credits"> <p class="dwt_author">Geyer, M.; Salas Y Melia, D.; Brun, E.; Dumont, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">318</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70022771"> <span id="translatedtitle">A comparison of delta change and <span class="hlt">downscaled</span> GCM scenarios for three mountainous basins in the United States</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Simulated daily precipitation, temperature, and runoff time series were compared in three mountainous basins in the United States: (1) the Animas River basin in Colorado, (2) the East Fork of the Carson River basin in Nevada and California, and (3) the Cle Elum River basin in Washington State. Two methods of climate scenario generation were compared: delta change and statistical <span class="hlt">downscaling</span>. The delta change method uses differences between simulated current and future climate conditions from the Hadley Centre for Climate Prediction and Research (HadCM2) General Circulation Model (GCM) added to observed time series of climate variables. A statistical <span class="hlt">downscaling</span> (SDS) model was developed for each basin using station data and output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis regridded to the scale of HadCM2. The SDS model was then used to simulate local climate variables using HadCM2 output for current and future conditions. Surface climate variables from each scenario were used in a precipitation-runoff model. Results from this study show that, in the basins tested, a precipitation-runoff model can simulate realistic runoff series for current conditions using statistically <span class="hlt">downscaled</span> NCEP output. But, use of <span class="hlt">downscaled</span> HadCM2 output for current or future climate assessments are questionable because the GCM does not produce accurate estimates of the surface variables needed for runoff in these regions. Given the uncertainties in the GCMs ability to simulate current conditions based on either the delta change or <span class="hlt">downscaling</span> approaches, future climate assessments based on either of these approaches must be treated with caution.</p> <div class="credits"> <p class="dwt_author">Hay, L.E.; Wilby, R.L.; Leavesley, G.H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">319</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013HESS...17..705G"> <span id="translatedtitle">Benefits from using combined dynamical-statistical <span class="hlt">downscaling</span> approaches - lessons from a case study in the Mediterranean region</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Various <span class="hlt">downscaling</span> techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Such techniques may be grouped into two <span class="hlt">downscaling</span> approaches: the deterministic dynamical <span class="hlt">downscaling</span> (DD) and the statistical <span class="hlt">downscaling</span> (SD). Although SD has been traditionally seen as an alternative to DD, recent works on statistical <span class="hlt">downscaling</span> have aimed to combine the benefits of these two approaches. The overall objective of this study is to assess whether a DD processing performed before the SD permits to obtain more suitable climate scenarios for basin scale hydrological applications starting from GCM simulations. The case study presented here focuses on the Apulia region (South East of Italy, surface area about 20 000 km2), characterised by a typical Mediterranean climate; the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined for the period 1953-2000. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile correction. The SD resulted efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but it was not able to correct the miss-modelled non-stationary components of the GCM dynamics. The DD provided a partial correction by enhancing the spatial heterogeneity of trends and the long-term time evolution predicted by the GCM. The best results were obtained through the combination of both DD and SD approaches.</p> <div class="credits"> <p class="dwt_author">Guyennon, N.; Romano, E.; Portoghese, I.; Salerno, F.; Calmanti, S.; Petrangeli, A. B.; Tartari, G.; Copetti, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">320</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.1712G"> <span id="translatedtitle">Incorporation of seasonal climate forecasts in the <span class="hlt">ensemble</span> streamflow prediction system</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A technique for incorporating 0-3 months lead temperature and precipitation forecasts from two Canadian numerical weather prediction (NWP) models into the <span class="hlt">ensemble</span> streamflow prediction (ESP) system is presented. The technique involves <span class="hlt">downscaling</span> monthly NWP forecast outputs to station locations using the model output statistics (MOS) approach and then temporally disaggregating the monthly forecasts into daily input weather data suitable for driving a hydrologic model. The daily weather sequence for a desired month is generated by a nearest neighbor re-sampling of one of the years in the historical record, and then modifying the daily weather data for the same month of the re-sampled year so as to reproduce the MOS-based monthly forecast value. Streamflow forecasts from the MOS-based scheme are compared to pre-ESP and post-ESP re-sampling schemes without seasonal climate forecast guidance. In the pre-ESP scheme, daily weather inputs for the hydrologic model were conditionally re-sampled from historical records. In the post-ESP scheme, streamflow traces produced by the climatic ESP system were conditionally re-sampled. The three schemes were applied to the Bow and Castle rivers, both located in the headwaters of the South Saskatchewan River basin in the province of Alberta, Canada. Correlations between the MOS-based median forecast and observed flow for the Castle River were consistently higher than those based on the pre-ESP and post-ESP schemes. Other skill measures showed mixed results, with the MOS-based forecasts being more skillful in some cases and less skillful in others. All three schemes exhibited better skill for above-normal flow categories than for below-normal categories. It is also shown that considerable improvement in the ESP forecast skill could be achieved through more accurate simulation of streamflow, particularly for forecast issue dates late in the water year.</p> <div class="credits"> <p class="dwt_author">Gan, T. Y.; Gobena, A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_15");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">321</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..12.7496S"> <span id="translatedtitle">Future risk of global drought from <span class="hlt">downscaled</span>, bias corrected climate projections</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Understanding how changes in drought conditions will develop in the 21st century, including changes in severity, extent, and duration, is of great importance to many sectors such as water resources management and agricultural activity. There may also be profound implications for the occurrence of wildfires and heat waves that are associated with dry conditions. Recent severe droughts in the Western U.S., southeast Australia, Eastern Africa, Europe and northern China are testament to the impacts that large scale drought can have and are perhaps indicators of things to come. The direct use of climate model outputs for analysis of future drought however is problematic because of known model biases, particularly model simulated precipitation and temperature fields that have first order impact on droughts. Here we present a comprehensive statistical analysis of future drought conditions globally in a multi-model, multi-scenario based framework. The analysis is based on recently completed simulations using the Variable Infiltration Capacity land surface model (LSM), forced by <span class="hlt">downscaled</span>, bias corrected climate projections using a newly developed equidistant quantile matching method. This improves upon traditional quantile matching methods by taking into account changes in the future projection climate distribution and better represents extreme years that are most associated with the development of drought. We apply this to a suite of climate models for monthly precipitation and temperature but show how this can be extended to radiation, humidity and windspeed to capture associated changes and interplay among these associated drivers, although this is limited to a small set of climate models with available data. Further enhancements include improved temporal <span class="hlt">downscaling</span> to account for changes in, for example, storm intensities and diurnal temperature range. The bias corrected and <span class="hlt">downscaled</span> climate forcings are used to drive the LSM to generate future projections of the terrestrial water and energy cycles. These outputs are then analyzed to understand the propagation of projected drought, including frequency and severity, and to compare these projections with analyses based on 20th C observations. Individual drought events are identified using a cluster based tracking algorithm, which follows drought development through time and space and identifies the severest events based on severity-area-duration analysis. This work improves on previous future global drought analyses based directly on climate model output, by removing the biases associated with climate model simulations, focuses on higher spatial resolution to better represent topographic and vegetation heterogeneity and uses a comprehensive land surface model as the foundation of the analyzed information.</p> <div class="credits"> <p class="dwt_author">Sheffield, Justin; Li, Haibin; Wood, Eric</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">322</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012JHyd..472..111T"> <span id="translatedtitle">Assessment of an analogue <span class="hlt">downscaling</span> method for modelling climate change impacts on runoff</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Summary<span class="hlt">Downscaling</span> is a technique commonly used to transform the outputs of a low resolution climate model to a finer scale suitable for regional hydrological modelling. The technique is an important component in studies investigating the impact of climate change on runoff. This study assesses a simple analogue <span class="hlt">downscaling</span> method - the statistically based method of Timbal and McAvaney (2001) to provide daily rainfall series for modelling runoff across southeast Australia. Using 10 global climate models (GCMs), the historical and future rainfall and runoff generated by this method were compared with the results from an empirical scaling method. We find that the analogue method can be used with hydrological models to simulate long-term average runoff over large regions reasonably well provided a suitable 'inflation factor' is applied. Without the correction, biases are too large for direct input to hydrological models. Even with appropriate inflation, the daily rainfall distribution from the analogue method will not be the same as the observed distribution, and this may lead to unreliable simulations of daily runoff characteristics. Comparing the analogue method and the empirical scaling method on the basis of change in future runoff, averaged across the entire study region, the results are generally similar with large majority of the GCMs showing a decline in future runoff. In the cases when there are differences, the additional climatic response produced by the analogue method appears to be a consequence of using atmospheric moisture variable as a predictor in certain regions. The range in the future rainfall and runoff projections from the analogue method is smaller than that from the empirical scaling. This is because compared to the empirical scaling, which uses rainfall derived from as many as 10 different parameterisations in the GCMs, the analogue method uses a single relationship between synoptic atmospheric fields and rainfall for all the GCMs. This, and the fact that the analogue method models future changes at the relevant catchment scale and captures changes to a larger range of rainfall characteristics, are the advantages of the analogue method. Nevertheless, more research is required to improve daily rainfall series for direct input into hydrological models to fully realise the potential of analogue <span class="hlt">downscaling</span> for hydrological applications.</p> <div class="credits"> <p class="dwt_author">Teng, J.; Chiew, F. H. S.; Timbal, B.; Wang, Y.; Vaze, J.; Wang, B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">323</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1513442W"> <span id="translatedtitle">Development of incremental dynamical <span class="hlt">downscaling</span> and analysis system for regional scale climate change projections</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical <span class="hlt">downscaling</span> (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new <span class="hlt">downscaling</span> method is named as the incremental dynamical <span class="hlt">downscaling</span> and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.</p> <div class="credits"> <p class="dwt_author">Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">324</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.1592B"> <span id="translatedtitle">Building an <span class="hlt">ensemble</span> of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an <span class="hlt">ensemble</span> comprising 87 climate simulations. The climate data <span class="hlt">ensemble</span> is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for <span class="hlt">downscaling</span> and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.</p> <div class="credits"> <p class="dwt_author">Braun, Marco; Chaumont, Diane</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">325</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.meted.ucar.edu/training_module.php?id=548"> <span id="translatedtitle">Introduction to the North American <span class="hlt">Ensemble</span> Forecast System (NAEFS)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This webcast introduces the forecaster to the new multiple-forecast-center North American <span class="hlt">Ensemble</span> Forecast System (NAEFS). Beginning with a brief review of the theory behind <span class="hlt">ensemble</span> prediction, this presentation then introduces the elements of the NAEFS. These include the U.S. National Centers for Environmental Predictionâs Global <span class="hlt">Ensemble</span> Forecast System (GEFS) and the Canadian Meteorological Centerâs <span class="hlt">Ensemble</span> Forecast System (CEFS). A description of each separate <span class="hlt">ensemble</span> system is followed by a discussion of how the NAEFS improves the <span class="hlt">ensemble</span> forecast over either the GEFS or CEFS alone. Next, the post-processed statistical products from the NAEFS are described, with examples, and some caveats are provided about their use. Finally, cold and warm season case examples are presented in the final section.</p> <div class="credits"> <p class="dwt_author">Comet</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-08-25</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">326</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005GeoRL..32.7814P"> <span id="translatedtitle">A simple method to improve <span class="hlt">ensemble</span>-based ozone forecasts</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Forecasts from seven air quality models and ozone data collected over the eastern USA and southern Canada during July and August 2004 are used in creating a simple method to improve <span class="hlt">ensemble</span>-based forecasts of maximum daily 1-hr and 8-hr averaged ozone concentrations. The method minimizes least-square error of <span class="hlt">ensemble</span> forecasts by assigning weights for its members. The real-time ozone (O3) forecasts from this <span class="hlt">ensemble</span> of models are statistically evaluated against the ozone observations collected for the AIRNow database comprising more than 350 stations. Application of this method is shown to significantly improve overall statistics (e.g., bias, root mean square error, and index of agreement) of the weighted <span class="hlt">ensemble</span> compared to the averaged <span class="hlt">ensemble</span> or any individual <span class="hlt">ensemble</span> member. If a sufficient number of observations is available, we recommend that weights be calculated daily; if not, a longer training phase will still provide a positive benefit.</p> <div class="credits"> <p class="dwt_author">Pagowski, M.; Grell, G. A.; McKeen, S. A.; Dévényi, D.; Wilczak, J. M.; Bouchet, V.; Gong, W.; McHenry, J.; Peckham, S.; McQueen, J.; Moffet, R.; Tang, Y.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">327</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3733713"> <span id="translatedtitle"><span class="hlt">Downscaling</span> the Analysis of Complex Transmembrane Signaling Cascades to Closed Attoliter Volumes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Cellular signaling is classically investigated by measuring optical or electrical properties of single or populations of living cells. Here we show that ligand binding to cell surface receptors and subsequent activation of signaling cascades can be monitored in single, (sub-)micrometer sized native vesicles with single-molecule sensitivity. The vesicles are derived from live mammalian cells using chemicals or optical tweezers. They comprise parts of a cell’s plasma membrane and cytosol and represent the smallest autonomous containers performing cellular signaling reactions thus functioning like minimized cells. Using fluorescence microscopies, we measured in individual vesicles the different steps of G-protein-coupled receptor mediated signaling like ligand binding to receptors, subsequent G-protein activation and finally arrestin translocation indicating receptor deactivation. Observing cellular signaling reactions in individual vesicles opens the door for <span class="hlt">downscaling</span> bioanalysis of cellular functions to the attoliter range, multiplexing single cell analysis, and investigating receptor mediated signaling in multiarray format. PMID:23940670</p> <div class="credits"> <p class="dwt_author">Grasso, Luigino; Wyss, Romain; Piguet, Joachim; Werner, Michael; Hassaine, Gherici; Hovius, Ruud; Vogel, Horst</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">328</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFM.A41H0187F"> <span id="translatedtitle">Global and regional <span class="hlt">downscaling</span> study of climate and air quality under RCPs</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this study, we studied the climate and its impact on air quality using CAM-Chem and WRF/CMAQ. CAM-Chem was used to evaluate global climate change and its impact on air quality under RCP scenarios. Wide reduction of ozone concentrations over the troposphere was found in 2050s under RCP 4.5, resulting from the reduced anthropogenic emissions; In RCP 8.5, the increase of methane emissions results in large ozone increases in the troposphere. Dynamical <span class="hlt">downscaling</span> technique was applied to link CAM-Chem and WRF/CMAQ for evaluating the local climate impact on air quality over continental US. Regional climate showed extensive increases of heat waves and wide impact on ozone concentrations in particular in RCP 8.5. In addition, under both RCP 4.5 and 8.5, major cities show increase of ozone concentrations from the effect of NO titration.</p> <div class="credits"> <p class="dwt_author">Fu, J. S.; Gao, Y.; Drake, J.; Lamarque, J.; Liu, Y.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">329</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..1412765R"> <span id="translatedtitle">Towards <span class="hlt">downscaling</span> precipitation for Senegal - An approach based on generalized linear models and weather types</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Changes in precipitation patterns with potentially less precipitation and an increasing risk for droughts pose a threat to water resources and agricultural yields in Senegal. Precipitation in this region is dominated by the West-African Monsoon being active from May to October, a seasonal pattern with inter-annual to decadal variability in the 20th century which is likely to be affected by climate change. We built a generalized linear model for a full spatial description of rainfall in Senegal. The model uses season, location, and a discrete set of weather types as predictors and yields a spatially continuous description of precipitation occurrences and intensities. Weather types have been defined on NCEP/NCAR reanalysis using zonal and meridional winds, as well as relative humidity. This model is suitable for <span class="hlt">downscaling</span> precipitation, particularly precipitation occurrences relevant for drough risk mapping.</p> <div class="credits"> <p class="dwt_author">Rust, H. W.; Vrac, M.; Lengaigne, M.; Sultan, B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">330</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14..698C"> <span id="translatedtitle">Development of a Dynamic <span class="hlt">Downscaling</span> strategy for Ganga Basin and Investigation of the Hydrological Pattern</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The interaction between climate and hydrology is highly complex and non-linear. In India, the synoptic scale atmospheric flow, diversity of local topography, vegetation, climatic conditions, and high population density, etc., interact with one another to give a unique weather distribution. The interaction between the large scale climate and local scale hydrologic cycle is very important in regional scale hydrological modelling. The Weather Research and Forecasting (WRF) model is a numerical weather prediction and atmospheric simulation system designed to resolve this interaction at regional scale. WRF has been used earlier to investigate the <span class="hlt">downscaling</span> methodology over the United States (Lo et al., 2008). We study the impact of climatic condition on Ganga basin hydrologic cycle using WRF. A single domain with a resolution of 25 km was used to cover the whole of India and the region of interest and validation is the entire Ganga basin. We performed the <span class="hlt">downscaling</span> for the year 2010 with five configurations: (1) one continuous time integration with single initialization, (2) time integration with monthly reinitialization, (3) single initialization but with 3-D nudging without relaxation of PBL (4) same as 3 but with relaxation of PBL and (5) same as 4 but with spectral nudging relaxation. The results are compared against the synoptic observations taken over the Ganga basin. The 5th method has the best skill, followed by 4th, 3rd , 2nd and 1st . The results show that the nudging generates realistic regional climatic pattern which cannot be achieved simply by updating the boundary conditions. To find out the Hydrological interaction, trend and pattern over the Ganga Basin, the Hydrological fields of the best model (Spectral Nudging) are analysed. The rainfall patterns are compared with TRMM 3B42 daily data. The precipitation, surface temperature, and the regional wind pattern is reasonably simulated. The study reveals the power of WRF in resolving the climatic and hydrological interactions and also shows that the WRF can be used in making an accurate forecast. The rainfall distribution shows some degree of correlation with the TRMM at the middle Indo-Gangetic plane, along the foothills of Himalaya, and over some portion of Tibetian Plateau. The seasonality index of Hydrologic variables like Rainfall, Surface runoff and Soil moisture show a level of seasonal pattern over the Indo-Gangetic plane but the degree of seasonality pattern is weak at the foothills of Himalaya. The hydrological fields like surface run off, base flow, soil moisture distribution and soil temperature show the expected regional variations and seasonal patterns. The dynamical <span class="hlt">downscaling</span> outperforms the interpolation of climatic variables over space and time. This implies the suitability of WRF to study the hydrological cycle over a data sparse region and, probably, to study the effect of potential climate change on it. Reference: Jeff Chun-Fung Lo, Zong-Liang Yang, and Roger A. Pielke Sr., 2008, Assessment of three dynamical climate <span class="hlt">downscaling</span> methods using the Weather Research and Forecasting (WRF) model, Journal of Geophysical Research, Vol 113, D09112</p> <div class="credits"> <p class="dwt_author">Chaudhuri, C.; Srivastava, R.; Tripathi, S. N.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">331</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1510686L"> <span id="translatedtitle">A comparison of dynamical and statistical <span class="hlt">downscaling</span> methods for regional wave climate projections along French coastlines.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical <span class="hlt">downscaling</span> of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical <span class="hlt">downscaling</span> method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at 110 coastal locations along the French coast. The model, based on the BAJ parameterization of the source terms (Bidlot et al, 2007) was calibrated against ten years of GlobWave altimeter observations (2000-2009) and validated through deep and shallow water buoy observations. The dynamical <span class="hlt">downscaling</span> method has been performed with the same numerical wave model TOMAWAC used for building ANEMOC-2. Forecast simulations are forced by the 10m wind fields of ARPEGE-CLIMAT (A1B, A2, B1) from 2010 to 2100. The model covers the Atlantic Ocean and uses a spatial resolution along the French and European coast of 10 and 20 km respectively. The results of the model are stored with a time resolution of one hour. References: Benoit M., Marcos F., and F. Becq, (1996). Development of a third generation shallow-water wave model with unstructured spatial meshing. Proc. 25th Int. Conf. on Coastal Eng., (ICCE'1996), Orlando (Florida, USA), pp 465-478. Bidlot J-R, Janssen P. and Adballa S., (2007). A revised formulation of ocean wave dissipation and its model impact, technical memorandum ECMWF n°509. Menendez, M., Mendez, F.J., Izaguirre,C., Camus, P., Espejo, A., Canovas, V., Minguez, R., Losada, I.J., Medina, R. (2011). Statistical <span class="hlt">Downscaling</span> of Multivariate Wave Climate Using a Weather Type Approach, 12th International Workshop on Wave Hindcasting and Forecasting and 3rd Coastal Hazard Symposium, Kona (Hawaii).</p> <div class="credits"> <p class="dwt_author">Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">332</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014PhRvE..90d2144V"> <span id="translatedtitle">Spectral density of the noncentral correlated Wishart <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Wishart <span class="hlt">ensembles</span> of random matrix theory have been useful in modeling positive definite matrices encountered in classical and quantum chaotic systems. We consider nonzero means for the entries of the constituting matrix A which defines the correlated Wishart matrix as W =AA† , and refer to the <span class="hlt">ensemble</span> of such Wishart matrices as the noncentral correlated Wishart <span class="hlt">ensemble</span> (nc-CWE). We derive the Pastur self-consistent equation which describes the spectral density of nc-CWE at large matrix dimension.</p> <div class="credits"> <p class="dwt_author">Vinayak</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">333</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25248624"> <span id="translatedtitle"><span class="hlt">Ensemble</span> theory for slightly deformable granular matter.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Given a granular system of slightly deformable particles, it is possible to obtain different static and jammed packings subjected to the same macroscopic constraints. These microstates can be compared in a mathematical space defined by the components of the force-moment tensor (i.e. the product of the equivalent stress by the volume of the Voronoi cell). In order to explain the statistical distributions observed there, an athermal <span class="hlt">ensemble</span> theory can be used. This work proposes a formalism (based on developments of the original theory of Edwards and collaborators) that considers both the internal and the external constraints of the problem. The former give the density of states of the points of this space, and the latter give their statistical weight. The internal constraints are those caused by the intrinsic features of the system (e.g. size distribution, friction, cohesion). They, together with the force-balance condition, determine which the possible local states of equilibrium of a particle are. Under the principle of equal a priori probabilities, and when no other constraints are imposed, it can be assumed that particles are equally likely to be found in any one of these local states of equilibrium. Then a flat sampling over all these local states turns into a non-uniform distribution in the force-moment space that can be represented with density of states functions. Although these functions can be measured, some of their features are explored in this paper. The external constraints are those macroscopic quantities that define the <span class="hlt">ensemble</span> and are fixed by the protocol. The force-moment, the volume, the elastic potential energy and the stress are some examples of quantities that can be expressed as functions of the force-moment. The associated <span class="hlt">ensembles</span> are included in the formalism presented here. PMID:25248624</p> <div class="credits"> <p class="dwt_author">Tejada, Ignacio G</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">334</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.8188M"> <span id="translatedtitle">Application of a statistical <span class="hlt">downscaling</span> method to detect inhomogeneities in a temperature time series</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In the context of climate studies, the analysis of long homogeneous time series is of the utmost importance. A homogeneous climate series is defined as a series whose variations are caused only by changes in weather and climate (Conrad and Pollak, 1950). Unfortunately, a time series is often affected by one or more artificial inhomogeneities. Regardless of the type and the effect of inhomogeneities, the analysis of a non-homogeneous series can be misleading. Consequently, it is crucial to determine, assign and adjust any discontinuities in the data, especially in those reference series used in climate change studies. The Twentieth Century Reanalysis (20CR) data can provide an independent estimate of, among other variables, surface temperature. However, the difference in scale affects its potential use as a tool to detect non-climatic inhomogeneities in a local temperature time series. To avoid this limitation, we propose a new approach based on a parsimonious statistical <span class="hlt">downscaling</span> method to bridge the gap between reanalysis data and the local temperature time series. This method was applied to two high-quality international reference stations in the North-East of Spain (present in the ECA database, http://eca.knmi.nl/) whose temperature series are used, for example, in the report of climatic change in Catalonia, Cunillera et al., 2009: Ebre (Tortosa) and Fabra (Barcelona), for the periods 1940-2008 and 1914-2008, respectively. Both series show an anomalous period which is clearly identifiable by visual inspection. The statistical <span class="hlt">downscaling</span> model was calibrated for these stations and independently tested over the reliable periods with good results. The model was then applied to reproduce the doubtful years. The results of the study are in agreement with the metadata: for the Fabra series, the method proposed clearly identifies the artificial inhomogeneity; whilst for the Ebre Observatory, there is no documented change in the station and the suspicious period falls inside the error bands.</p> <div class="credits"> <p class="dwt_author">Marcos, R.; Turco, M.; Llasat, M. C.; Quintana-Seguí, P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">335</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4065210"> <span id="translatedtitle">Calibrating MODIS aerosol optical depth for predicting daily PM2.5 concentrations via statistical <span class="hlt">downscaling</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">There has been a growing interest in the use of satellite-retrieved aerosol optical depth (AOD) to estimate ambient concentrations of PM2.5 (particulate matter <2.5 ?m in aerodynamic diameter). With their broad spatial coverage, satellite data can increase the spatial–temporal availability of air quality data beyond ground monitoring measurements and potentially improve exposure assessment for population-based health studies. This paper describes a statistical <span class="hlt">downscaling</span> approach that brings together (1) recent advances in PM2.5 land use regression models utilizing AOD and (2) statistical data fusion techniques for combining air quality data sets that have different spatial resolutions. Statistical <span class="hlt">downscaling</span> assumes the associations between AOD and PM2.5 concentrations to be spatially and temporally dependent and offers two key advantages. First, it enables us to use gridded AOD data to predict PM2.5 concentrations at spatial point locations. Second, the unified hierarchical framework provides straightforward uncertainty quantification in the predicted PM2.5 concentrations. The proposed methodology is applied to a data set of daily AOD values in southeastern United States during the period 2003–2005. Via cross-validation experiments, our model had an out-of-sample prediction R2 of 0.78 and a root mean-squared error (RMSE) of 3.61 ?g/m3 between observed and predicted daily PM2.5 concentrations. This corresponds to a 10% decrease in RMSE compared with the same land use regression model without AOD as a predictor. Prediction performances of spatial–temporal interpolations to locations and on days without monitoring PM2.5 measurements were also examined. PMID:24368510</p> <div class="credits"> <p class="dwt_author">Chang, Howard H.; Hu, Xuefei; Liu, Yang</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">336</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2002HyPr...16.1215W"> <span id="translatedtitle">Prospects for <span class="hlt">downscaling</span> seasonal precipitation variability using conditioned weather generator parameters</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper explores the use of synoptic-scale predictor variables to <span class="hlt">downscale</span> both high- and low-frequency components of daily precipitation at sites across the British Isles. Part I investigates seasonal and inter-annual variations in three weather generator parameters with respect to concurrent variations in a North Atlantic Oscillation (NAO) index and area-average sea surface temperature (SST) anomalies. Marked spatial gradients were found in the strength of the associated correlation fields using rainfall data for the period 1961-90. For example, the persistence of winter wet-spells was most strongly correlated with the NAO index in NW Scotland, and the persistence of autumn dry-spells with SST anomalies in SE England. At such locations, North Atlantic conditioning accounted for over 40% of the inter-annual variability of precipitation occurrence. In Part II, three <span class="hlt">downscaling</span> models were compared using independent daily precipitation data for sites located in the regions of strongest North Atlantic forcing. The parameters of Model M were implicitly conditioned by three regional airflow indices; the parameters of Model X were explicitly conditioned by either the NAO index or SST anomalies and daily vorticity; and the parameters of Model U (a three-parameter stochastic rainfall model) were unconditional. Overall, the conditional models displayed greater skill for monthly rainfall statistics relative to Model U (the control), but still did not completely remove overdispersion. On comparing Models M and X, it was evident that explicit conditioning did bestow additional advantages for the chosen sites and seasons of greatest forcing. However, further research is required to determine the generality of these results for other regions and periods of the rainfall record.</p> <div class="credits"> <p class="dwt_author">Wilby, R. L.; Conway, D.; Jones, P. D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">337</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009CMaPh.288...43S"> <span id="translatedtitle">Conformal Radii for Conformal Loop <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The conformal loop <span class="hlt">ensembles</span> CLE ? , defined for 8/3 ? ? ? 8, are random collections of loops in a planar domain which are conjectured scaling limits of the O( n) loop models. We calculate the distribution of the conformal radii of the nested loops surrounding a deterministic point. Our results agree with predictions made by Cardy and Ziff and by Kenyon and Wilson for the O( n) model. We also compute the expectation dimension of the CLE ? gasket, which consists of points not surrounded by any loop, to be 2 - {(8 - kappa)(3kappa - 8)}/{32kappa} , which agrees with the fractal dimension given by Duplantier for the O( n) model gasket.</p> <div class="credits"> <p class="dwt_author">Schramm, Oded; Sheffield, Scott; Wilson, David B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">338</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AGUFM.H43I1582H"> <span id="translatedtitle">Probabilistic Flash Flood Forecasting using Stormscale <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars, but the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from a stormscale NWP <span class="hlt">ensemble</span> system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Rainfall error characteristics of the individual members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). Amplitude and structure errors are readily correctable due to their diurnal nature, and the fine scales represented by the CAPS QPF members are consistent with radar-observed rainfall, mainly showing larger errors with afternoon convection. To account for the spatial uncertainty of the QPFs, we use an elliptic smoother, as in Marsh et al. (2012), to produce probabilistic QPFs (PQPFs). The elliptic smoother takes into consideration underdispersion, which is notoriously associated with stormscale <span class="hlt">ensembles</span>, and thus, is good for targeting the approximate regions that may receive heavy rainfall. However, stormscale details contained in individual members are still needed to yield reasonable flash flood simulations. Therefore, on a case study basis, QPFs from individual members are then run through the hydrological model with their predicted structure and corrected amplitudes, but the locations of individual rainfall elements are perturbed within the PQPF elliptical regions using Monte Carlo sampling. This yields an <span class="hlt">ensemble</span> of flash flood simulations. These simulated flows are compared to historically-based flow thresholds at each grid point to identify basin scales most susceptible to flash flooding, therefore, deriving PFFF products. This new approach is shown to: 1) identify the specific basin scales within the broader regions that are forecast to be impacted by flash flooding based on cell movement, rainfall intensity, duration, and the basin's susceptibility factors such as initial soil moisture conditions; 2) yield probabilistic information about on the forecast hydrologic response; and 3) improve lead time by using stormscale NWP <span class="hlt">ensemble</span> forecasts.</p> <div class="credits"> <p class="dwt_author">Hardy, J.; Gourley, J. J.; Kain, J. S.; Clark, A.; Novak, D.; Hong, Y.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">339</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004HESS....8.1031K"> <span id="translatedtitle">Impact analysis of climate change for an Alpine catchment using high resolution dynamic <span class="hlt">downscaling</span> of ECHAM4 time slices</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Global climate change affects spatial and temporal patterns of precipitation and so has a major impact on surface and subsurface water balances. While global climate models are designed to describe climate change on global or continental scales, their resolution is too coarse for them to be suitable for describing regional climate change. Therefore, regional climate models are applied to <span class="hlt">downscale</span> the coarse meteorological fields to a much higher spatial resolution to take account of regional climate phenomena. The changes of atmospheric state due to regional climate change must be translated into surface and sub-surface water fluxes so that the impact on water balances in specific catchments can be investigated. This can be achieved by the coupled regional climatic/hydrological simulations presented here. The non-hydrostatic regional climate model MCCM was used for dynamic <span class="hlt">downscaling</span> for two time slices of a global climate model simulation with the GCM ECHAM4 (IPCC scenario IS92a, "business as usual") from 2.8° × 2.8° to 4 × 4 km2 resolution for the years 1991-1999 and 2031-2039. This allowed derivation of detailed maps showing changes in precipitation and temperature in a region of southern Germany and the central Alps. The performance of the <span class="hlt">downscaled</span> ECHAM4 to reproduce the seasonality of precipitation in central Europe for the recent climate was investigated by comparison with dynamically <span class="hlt">downscaled</span> ECMWF reanalyses in 20 × 20 km2 resolution. The <span class="hlt">downscaled</span> ECHAM4 fields underestimate precipitation significantly in summer. The ratio of mean monthly <span class="hlt">downscaled</span> ECHAM4 and ECMWF precipitation showed little variation, so it was used to adjust the course of precipitation for the ECHAM4/MCCM fields before it was applied in the hydrological model. The high resolution meteorological fields were aggregated to 8-hour time steps and applied to the distributed hydrological model WaSiM to simulate the water balance of the alpine catchment of the river Ammer (c. 700 km2) at 100 × 100 m2 resolution. To check the reliability of the coupled regional climatic/hydrological simulation results for the recent climate, they were compared with those of a station-based hydrological simulation for the period 1991-1999. This study shows the changes in the temperature and precipitation distributions in the catchment from the recent climate to the future climate scenario and how these will affect the frequency distribution of runoff.</p> <div class="credits"> <p class="dwt_author">Kunstmann, H.; Schneider, K.; Forkel, R.; Knoche, R.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">340</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/11046239"> <span id="translatedtitle">Path integrals for the quantum microcanonical <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Path integral representations for the quantum microcanonical <span class="hlt">ensemble</span> are presented. In the quantum microcanonical <span class="hlt">ensemble</span>, two operators are of primary interest. First, rhoinsertion mark=delta(E-Hinsertion mark) corresponds to the microcanonical density matrix and can be used to calculate expectation values. Second, Ninsertion mark=Theta(E-Hinsertion mark) can give the number of states with energy E(n)<E. We consider position matrix elements of both of these operators Omega(x,x('),E)=<x(')|delta(E-Hinsertion mark)|x> and Theta(x,x('),E)=<x(')|straight theta(E-Hinsertion mark)|x>. A path integral formalism leads to exact integral representations for Omega(x,x('),E) and Theta(x,x('),E). We present both phase space and configuration space forms. For simple systems, such as the free particle and harmonic oscillator, exact solutions are possible. For more complicated systems, expansion schemes or numerical evaluations are required. A perturbative calculation and numerical integration results are presented for the quantum anharmonic oscillator. PMID:11046239</p> <div class="credits"> <p class="dwt_author">Lawson</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_16");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">341</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2728059"> <span id="translatedtitle">Decoding Trajectories from Posterior Parietal Cortex <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">High-level cognitive signals in the posterior parietal cortex (PPC) have previously been used to decode the intended endpoint of a reach, providing the first evidence that PPC can be used for direct control of a neural prosthesis (Musallam et al., 2004). Here we expand on this work by showing that PPC neural activity can be harnessed to estimate not only the endpoint but also to continuously control the trajectory of an end effector. Specifically, we trained two monkeys to use a joystick to guide a cursor on a computer screen to peripheral target locations while maintaining central ocular fixation. We found that we could accurately reconstruct the trajectory of the cursor using a relatively small <span class="hlt">ensemble</span> of simultaneously recorded PPC neurons. Using a goal-based Kalman filter that incorporates target information into the state-space, we showed that the decoded estimate of cursor position could be significantly improved. Finally, we tested whether we could decode trajectories during closed-loop brain control sessions, in which the real-time position of the cursor was determined solely by a monkey’s neural activity in PPC. The monkey learned to perform brain control trajectories at 80% success rate(for 8 targets) after just 4–5 sessions. This improvement in behavioral performance was accompanied by a corresponding enhancement in neural tuning properties (i.e., increased tuning depth and coverage of encoding parameter space) as well as an increase in off-line decoding performance of the PPC <span class="hlt">ensemble</span>. PMID:19036985</p> <div class="credits"> <p class="dwt_author">Mulliken, Grant H.; Musallam, Sam; Andersen, Richard A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">342</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhRvD..86l4043G"> <span id="translatedtitle">Black holes in the conical <span class="hlt">ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We consider black holes in an “unsuitable box”: a finite cavity coupled to a thermal reservoir at a temperature different than the black hole’s Hawking temperature. These black holes are described by metrics that are continuous but not differentiable due to a conical singularity at the horizon. We include them in the Euclidean path integral sum over configurations, and analyze the effect this has on black hole thermodynamics in the canonical <span class="hlt">ensemble</span>. Black holes with a small deficit (or surplus) angle may have a smaller internal energy or larger density of states than the nearby smooth black hole, but they always have a larger free energy. Furthermore, we find that the ground state of the <span class="hlt">ensemble</span> never possesses a conical singularity. When the ground state is a black hole, the contributions to the canonical partition function from configurations with a conical singularity are comparable to the contributions from smooth fluctuations of the fields around the black hole background. Our focus is on highly symmetric black holes that can be treated as solutions of two-dimensional dilaton gravity models: examples include Schwarzschild, asymptotically anti-de Sitter, and stringy black holes.</p> <div class="credits"> <p class="dwt_author">Grumiller, Daniel; McNees, Robert; Zonetti, Simone</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">343</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3426488"> <span id="translatedtitle">Minimalist <span class="hlt">ensemble</span> algorithms for genome-wide protein localization prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several <span class="hlt">ensemble</span> algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist <span class="hlt">ensemble</span> algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing <span class="hlt">ensemble</span> algorithms. We applied the proposed minimalist logistic regression (LR) <span class="hlt">ensemble</span> algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current <span class="hlt">ensemble</span> algorithms. Experimental results showed that the minimalist <span class="hlt">ensemble</span> algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current <span class="hlt">ensemble</span> algorithms, which greatly reduces computational complexity and running time. It was found that the high performance <span class="hlt">ensemble</span> algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our <span class="hlt">ensemble</span> algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based <span class="hlt">ensemble</span> algorithms, our classifier-based <span class="hlt">ensemble</span> algorithms achieved much better performance without suffering from inclusion of too many individual predictors. Conclusions We proposed a method for rational design of minimalist <span class="hlt">ensemble</span> algorithms using feature selection and classifiers. The proposed minimalist <span class="hlt">ensemble</span> algorithm based on logistic regression can achieve equal or better prediction performance while using only half or one-third of individual predictors compared to other <span class="hlt">ensemble</span> algorithms. The results also suggested that meta-predictors that take advantage of a variety of features by combining individual predictors tend to achieve the best performance. The LR <span class="hlt">ensemble</span> server and related benchmark datasets are available at http://mleg.cse.sc.edu/LRensemble/cgi-bin/predict.cgi. PMID:22759391</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">344</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014EGUGA..1611409C"> <span id="translatedtitle">Multi-model <span class="hlt">ensemble</span> hydrometeorological modelling of the 4 November 2011 Genoa, Italy flash flood in the framework of the DRIHM project</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, www.drihm.eu, 2011-2015) project intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in Hydro-Meteorology Research (HMR). In particular, the project includes the delivery of experiment suites designed to prove the full extent of the DRIHM e-Science environment capability. These experiment suites address the interdisciplinary and international challenges of HMR in forecasting severe hydrometeorological events over regions with complex orography and assessing their impact. Here the emphasis will be put on two experiment suites that have been set up and tested for the flash-flood event that occurred in Genoa, Italy on 4 November 2011. The first experiment suite focuses on rainfall forecasting and combines different numerical weather prediction models to form a high-resolution multi-model <span class="hlt">ensemble</span> together with a stochastic <span class="hlt">downscaling</span> algorithm. The second experiment focuses on river discharge prediction and combines different hydrological models as well as different rainfall sources (either from the first experiment suite or from observations) to form a multi-model <span class="hlt">ensemble</span>. The composition of the first experiment suite with the second experiment suite represents a complete multi-model <span class="hlt">ensemble</span> hydrometeorological forecasting chain at the cutting edge of HMR. This presentation will demonstrate how progress beyond the state of the art has been achieved through the development and/or integration of tools that enable to easily discover, compare, combine, and visualize the different components of the hydrometeorological forecasting chain.</p> <div class="credits"> <p class="dwt_author">Caumont, Olivier</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">345</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.tutis.ca/NeuroMD/L5Motor/Nature%20Paper%20on%20Tetraplgia.pdf"> <span id="translatedtitle">2006 Nature Publishing Group Neuronal <span class="hlt">ensemble</span> control of prosthetic</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">© 2006 Nature Publishing Group Neuronal <span class="hlt">ensemble</span> control of prosthetic devices by a human neural control to open and close a prosthetic hand, and perform rudimentary actions with a multi- jointed robotic arm. These early results suggest that NMPs based upon intracortical neuronal <span class="hlt">ensemble</span> spiking</p> <div class="credits"> <p class="dwt_author">Vilis, Tutis</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">346</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.stat.washington.edu/raftery/Research/PDF/Berrocal2007.pdf"> <span id="translatedtitle">Combining Spatial Statistical and <span class="hlt">Ensemble</span> Information in Probabilistic Weather Forecasts</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Forecast <span class="hlt">ensembles</span> typically show a spread-skill relationship, but they are also often underdispersive, and therefore uncalibrated. Bayesian model averaging (BMA) is a statistical postprocessing method for forecast <span class="hlt">ensembles</span> that generates calibrated probabilistic forecast products for weather quantities at indi- vidual sites. This paper introduces the spatial BMA technique, which combines BMA and the geostatistical output perturbation (GOP) method, and extends</p> <div class="credits"> <p class="dwt_author">Veronica J. Berrocal; Adrian E. Raftery; Tilmann Gneiting</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">347</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.stat.washington.edu/raftery/Research/PDF/fadoua.pdf"> <span id="translatedtitle">Using Bayesian Model Averaging to Calibrate Forecast <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Ensembles</span> used for probabilistic weather forecasting often exhibit a spread-error correlation, but they tend to be underdispersive. This paper proposes a statistical method for postprocessing <span class="hlt">ensembles</span> based on Bayesian model averaging (BMA), which is a standard method for combining predictive distributions from different sources. The BMA predictive probability density function (PDF) of any quantity of interest is a weighted average</p> <div class="credits"> <p class="dwt_author">Adrian E. Raftery; Tilmann Gneiting; Fadoua Balabdaoui; Michael Polakowski</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">348</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=state+AND+art+AND+parallel&id=EJ714373"> <span id="translatedtitle">Conductor and <span class="hlt">Ensemble</span> Performance Expressivity and State Festival Ratings</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">This study is the second in a series examining the relationship between conducting and <span class="hlt">ensemble</span> performance. The purpose was to further examine the associations among conductor, <span class="hlt">ensemble</span> performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…</p> <div class="credits"> <p class="dwt_author">Price, Harry E.; Chang, E. Christina</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">349</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://hal.archives-ouvertes.fr/docs/00/00/29/87/PS/telep6.ps"> <span id="translatedtitle">ccsd00002401, Teleportation of an atomic <span class="hlt">ensemble</span> quantum state</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">ccsd­00002401, version 1 ­ 30 Jul 2004 Teleportation of an atomic <span class="hlt">ensemble</span> quantum state A. Dantan a protocol to achieve high #12;delity quantum state teleportation of a macroscopic atomic <span class="hlt">ensemble</span> using for a practical implementation [2]. Several continuous variable teleportation experiments with op- tical #12;elds</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">350</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://files.eric.ed.gov/fulltext/EJ996057.pdf"> <span id="translatedtitle">Preferences of and Attitudes toward Treble Choral <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">In choral <span class="hlt">ensembles</span>, a pursuit where females far outnumber males, concern exists that females are being devalued. Attitudes of female choral singers may be negatively affected by the gender imbalance that exists in mixed choirs and by the placement of the mixed choir as the most select <span class="hlt">ensemble</span> in a program. The purpose of this research was to…</p> <div class="credits"> <p class="dwt_author">Wilson, Jill M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">351</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51054992"> <span id="translatedtitle">Hippocampus segmentation using a stable maximum likelihood classifier <span class="hlt">ensemble</span> algorithm</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier <span class="hlt">ensemble</span> algorithm to correct segmentation errors produced by a multi-atlas based segmentation method. Our classifier <span class="hlt">ensemble</span> algorithm searches for the maximum likelihood solution via gradient ascent optimization. Compared to the additive regression based algorithm, LogitBoost, our algorithm avoids the numerical instability problem.</p> <div class="credits"> <p class="dwt_author">Hongzhi Wang; Jung Wook Suh; Sandhitsu Das; Murat Altinay; John Pluta; Paul Yushkevich</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">352</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cis.temple.edu/~latecki/Papers/EnsembleClusteringNIPS2010.pdf"> <span id="translatedtitle">Robust Clustering as <span class="hlt">Ensembles</span> of Affinity Relations Hairong Liu1</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">, 5] and affinity propagation [6]. These methods implicitly share an assumption: every data point mustRobust Clustering as <span class="hlt">Ensembles</span> of Affinity Relations Hairong Liu1 , Longin Jan Latecki2 , Shuicheng@gmail.com,latecki@temple.edu,eleyans@nus.edu.sg Abstract In this paper, we regard clustering as <span class="hlt">ensembles</span> of k-ary affinity relations and clusters</p> <div class="credits"> <p class="dwt_author">Latecki, Longin Jan</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">353</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.uu.nl/groups/MG/multimedia/publications/art/socpar09.pdf"> <span id="translatedtitle">An <span class="hlt">Ensemble</span> of Deep Support Vector Machines for Image Categorization</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">An <span class="hlt">Ensemble</span> of Deep Support Vector Machines for Image Categorization Azizi Abdullah, Remco C-Image categorization, support vector machines, <span class="hlt">ensemble</span> methods, product rule, deep architectures I. INTRODUCTION. These algorithms use descriptors for representing an image with feature vectors and then a machine learning</p> <div class="credits"> <p class="dwt_author">Veltkamp, Remco</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">354</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=music&pg=4&id=EJ919102"> <span id="translatedtitle">Idea Bank: Chamber Music within the Large <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">Many music educators incorporate chamber music in their <span class="hlt">ensemble</span> programs--an excellent way to promote musical independence. However, they rarely think of the large <span class="hlt">ensemble</span> as myriad chamber interactions. Rehearsals become more productive when greater responsibility for music-making is placed on the individual student. This article presents some…</p> <div class="credits"> <p class="dwt_author">Neidlinger, Erica</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">355</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=student+AND+motivation&pg=4&id=EJ1009350"> <span id="translatedtitle">Programming in the Zone: Repertoire Selection for the Large <span class="hlt">Ensemble</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">One of the great challenges <span class="hlt">ensemble</span> directors face is selecting high-quality repertoire that matches the musical and technical levels of their <span class="hlt">ensembles</span>. Thoughtful repertoire selection can lead to increased student motivation as well as greater enthusiasm for the music program from parents, administrators, teachers, and community members. Common…</p> <div class="credits"> <p class="dwt_author">Hopkins, Michael</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">356</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.bham.ac.uk/~xin/papers/ChenYaoICIC07.pdf"> <span id="translatedtitle">Evolutionary <span class="hlt">Ensemble</span> for In Silico Prediction of Ames Test Mutagenicity</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">of chemicals without animal testing. This paper de- scribes a novel machine learning <span class="hlt">ensemble</span> approach of in silico models as alternative approaches to mutagenicity assessment of chemicals without animal testingEvolutionary <span class="hlt">Ensemble</span> for In Silico Prediction of Ames Test Mutagenicity Huanhuan Chen and Xin Yao</p> <div class="credits"> <p class="dwt_author">Yao, Xin</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">357</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.eecs.umich.edu/~zmao/Papers/ensemble.pdf"> <span id="translatedtitle"><span class="hlt">Ensemble</span>: Community-based Anomaly Detection for Popular Applications</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary"><span class="hlt">Ensemble</span>: Community-based Anomaly Detection for Popular Applications Feng Qian, Zhiyun Qian, Z and social networking, we propose <span class="hlt">Ensemble</span>, a novel, automated approach based on a trusted community of users engine. The trust can be assumed in cases such as enterprise environments and can be further policed</p> <div class="credits"> <p class="dwt_author">Mao, Zhuoqing Morley</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">358</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=ftp://ftp.ams.sunysb.edu/pub/papers/2010/susb10_01.pdf"> <span id="translatedtitle">Iterative Weight-Adjusted Voting Algorithm for <span class="hlt">Ensemble</span> of Classifiers</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Iterative Weight-Adjusted Voting Algorithm for <span class="hlt">Ensemble</span> of Classifiers Hyunjoong Kima, , Hyeuk Kimb present a new weighted voting <span class="hlt">ensemble</span> method, called WAVE, that uses two weight vectors: a weight vector of classifiers and a weight vector of instances. The weight vector of classifiers assigns higher weights</p> <div class="credits"> <p class="dwt_author">New York at Stoney Brook, State University of</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">359</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.colostate.edu/~christos/papers/DIP-2004NASM-proceedings.pdf"> <span id="translatedtitle">NASM 2004 1 / 9 THE INTERNET FOR <span class="hlt">ENSEMBLE</span> PERFORMANCE?</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">for musicians) 1 Presenters at the panel session on "The Internet for <span class="hlt">Ensemble</span> Performance?" E-mail: {echewNASM 2004 1 / 9 THE INTERNET FOR <span class="hlt">ENSEMBLE</span> PERFORMANCE? Panel hosted by: Robert Cutietta; organized, CA 90089-2564 USA Synopsis The goal of Distributed Immersive Performance (DIP) is to allow musicians</p> <div class="credits"> <p class="dwt_author">Papadopoulos, Christos</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">360</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2434224"> <span id="translatedtitle">Time-Space <span class="hlt">Ensemble</span> Strategies for Automatic Music Genre Classification</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper we propose a novel time-space <span class="hlt">ensemble</span>-based approach for the task of automatic music genre classification. <span class="hlt">Ensemble</span> strategies employ several classifiers to dierent views of the problem- space, and combination rules in order to produce the final classification decision. In our approach we employ audio signal segmentation in time intervals and also problem space decomposition. Initially the music</p> <div class="credits"> <p class="dwt_author">Carlos Nascimento Silla Jr.; Celso A. A. Kaestner; Alessandro L. Koerich</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_17");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">361</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.bc.edu/content/dam/files/offices/bands/pdf/University%20Wind%20Ensemble%20Member%20Handbook.pdf"> <span id="translatedtitle">University Wind <span class="hlt">Ensemble</span> Member Handbook Academic Year 2013-2014</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">motivated student musician for whom music making is a personal priority. This <span class="hlt">ensemble</span> requires a fullUniversity Wind <span class="hlt">Ensemble</span> Member Handbook Academic Year 2013-2014 Conductor: Sebastian Bonaiuto musical literature written for winds and percussion. The typical member is a highly skilled and highly</p> <div class="credits"> <p class="dwt_author">Huang, Jianyu</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">362</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.math.ntnu.no/ure/SatPaper2008A.pdf"> <span id="translatedtitle">SCALE-CORRECTED <span class="hlt">ENSEMBLE</span> KALMAN FILTER FOR OBSERVATIONS OF PRODUCTION</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">-posed and non-linear inverse problem. The <span class="hlt">Ensemble</span> Kalman Filter (EnKF) is a sequential Bayesian solution ABSTRACT The <span class="hlt">Ensemble</span> Kalman Filter (EnKF) is a Bayesian method for performing automatic and sequential, stochastic column vectors and realisations of dimension n, and xT its transpose. Similarly, the notation Rm</p> <div class="credits"> <p class="dwt_author">Eidsvik, Jo</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">363</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/22080313"> <span id="translatedtitle">Heralded amplification for precision measurements with spin <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We propose a simple heralded amplification scheme for small rotations of the collective spin of an <span class="hlt">ensemble</span> of particles. Our protocol makes use of two basic primitives for quantum memories, namely, partial mapping of light onto an <span class="hlt">ensemble</span>, and conversion of a collective spin excitation into light. The proposed scheme should be realizable with current technology, with potential applications to atomic clocks and magnetometry.</p> <div class="credits"> <p class="dwt_author">Brunner, Nicolas [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Polzik, Eugene S. [Niels Bohr Institute, Danish Quantum Optics Center QUANTOP, Copenhagen University, Blegdamsvej 17, DK-2100 Copenhagen O (Denmark); Simon, Christoph [Institute for Quantum Information Science and Department of Physics and Astronomy, University of Calgary, Calgary T2N 1N4, Alberta (Canada)</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-10-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">364</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.risoe.dk/rispubl/NEI/NEI-DK-4551.pdf"> <span id="translatedtitle">PSO (FU 2101) <span class="hlt">Ensemble</span>-forecasts for wind power</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">PSO (FU 2101) <span class="hlt">Ensemble</span>-forecasts for wind power Analysis of the Results of an On-line Wind Power <span class="hlt">Ensemble</span>- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">365</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.risoe.dk/rispubl/VEA/veapdf/ris-r-1527.pdf"> <span id="translatedtitle">Ris-R-1527(EN) Wind Power Prediction using <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">Risø-R-1527(EN) Wind Power Prediction using <span class="hlt">Ensembles</span> Gregor Giebel (ed.), Jake Badger, Lars, Lars Voulund Title: Wind Power Prediction using <span class="hlt">Ensembles</span> Risø-R-1527(EN) September 2005 ISSN 0106 from the operational use - Elsam 35 5.2.1 Control room functions 35 5.2.2 Use of wind power predictions</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">366</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cdsweb.cern.ch/record/1648189"> <span id="translatedtitle">Exact <span class="hlt">ensemble</span> density-functional theory for excited states</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">We construct exact Kohn-Sham potentials for the <span class="hlt">ensemble</span> density-functional theory (EDFT) of excited states from the ground and excited states of helium. The exchange-correlation potential is compared with current approximations, which miss prominent features. The <span class="hlt">ensemble</span> derivative discontinuity is tested, and the virial theorem is proven and illustrated.</p> <div class="credits"> <p class="dwt_author">Yang, Zeng-hui; Pribram-Jones, Aurora; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">367</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56928239"> <span id="translatedtitle">Prediction of weather impacted airport capacity using <span class="hlt">ensemble</span> learning</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Ensemble</span> learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The <span class="hlt">ensemble</span> bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the</p> <div class="credits"> <p class="dwt_author">Yao Wang</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">368</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.H23G1367N"> <span id="translatedtitle"><span class="hlt">Downscaling</span> Satellite-based Passive Microwave Observations Using the Principle of Relevant Information and Auxiliary High Resolution Remote Sensing Products</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Hydrometeorological models simulate the atmospheric and hydrological processes at scales of 1- 10 km that are significantly influenced by the local and regional availability of soil moisture. Microwave observations at frequencies < 10 GHz are highly sensitive to changes in near-surface moisture and have been widely used to retrieve soil moisture information. While satellite-based active microwave observations are available at spatial resolutions of hundreds of meters, with temporal resolutions of several weeks, passive observations are obtained only at tens of kilometers with temporal resolutions of sub daily to 2-3 days. The European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future NASA-Soil Moisture Active Passive (SMAP) missions will provide unprecedented passive microwave observations of brightness temperatures (TB) at the L-band frequency of 1.4 GHz. These products will be available at spatial resolutions of about 40-50 km and need to be <span class="hlt">downscaled</span> to 1 km to merge them with models for data assimilation and to study the effects of land surface heterogeneity such as dynamic vegetation conditions. Very few studies have directly <span class="hlt">downscaled</span> coarse-resolution TB observations to match model scales. Since <span class="hlt">downscaling</span> is an ill-posed problem, additional information is required at the fine scales and some studies have leveraged auxiliary high-resolution remote sensing (RS) products in <span class="hlt">downscaling</span> TB. Most of the above studies involve a) physical models that are computationally intensive when extended to global scales, or b) multi-scale algorithms that impose hierarchical models on TB assuming spatial homogeneity, or c) statistical algorithms that are based on second-order statistics such as variances and correlations. These approaches are therefore sub-optimal when applied to the real data or extended to regional/global scales. Optimal <span class="hlt">downscaling</span> requires computationally-efficient algorithms that retain information from higher-order moments, especially under heterogeneous land surface conditions. Novel transformation functions leveraging physical relationships and recent advances in signal processing techniques can be used to transform information from high-resolution RS products into TB. In this study, a <span class="hlt">downscaling</span> methodology was developed using the Principle of Relevant Information (PRI) to <span class="hlt">downscale</span> observations of TB from 50 km to 200 m using observations of land surface temperature, leaf area index, and land cover at 200 m. The PRI provides a hierarchical decomposition of image data that is optimal in terms of the transfer of information across scales and is therefore a better alternative to methods that use second-order statistics only. Non-parametric probability density functions and Bayes' rule was used to transform information from the RS products into TB. An Observing System Simulation Experiment was developed under heterogeneous and dynamic vegetation conditions to generate synthetic observations at 200m to evaluate the <span class="hlt">downscaling</span> methodology and the transformation functions.</p> <div class="credits"> <p class="dwt_author">Nagarajan, K.; Judge, J.; Principe, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">369</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012ESSDD...5..475P"> <span id="translatedtitle">Future Flows Climate: an <span class="hlt">ensemble</span> of 1-km climate change projections for hydrological application in Great Britain</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">1. The dataset Future Flows Climate was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable for climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment. 2. Future Flows Climate is derived from the Hadley Centre's <span class="hlt">ensemble</span> Projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for) and potential evapotranspiration. It corresponds to an 11-member <span class="hlt">ensemble</span> of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation) and monthly (PE) time step as NetCDF files. 3. Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962-1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution) for precipitation followed by a spatial <span class="hlt">downscaling</span>. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman Montieth equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year. 4. Future Flows Climate is freely available for non commercial use under certain licensing conditions. It is the dataset used to generate Future Flows Hydrology, an <span class="hlt">ensemble</span> of transient projections of daily river flow and monthly groundwater time series for representative river basins and boreholes in Great Britain. 5. <a href="http://dx.doi.org/10.5285/bad1514f-119e-44a4-8e1e-442735bb9797"target="_blank">doi:10.5285/bad1514f-119e-44a4-8e1e-442735bb9797</a></p> <div class="credits"> <p class="dwt_author">Prudhomme, C.; Dadson, S.; Morris, D.; Williamson, J.; Goodsell, G.; Crooks, S.; Boelee, L.; Davies, H.; Buys, G.; Lafon, T.; Watts, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">370</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012ESSD....4..143P"> <span id="translatedtitle">Future Flows Climate: an <span class="hlt">ensemble</span> of 1-km climate change projections for hydrological application in Great Britain</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The dataset Future Flows Climate was developed as part of the project ''Future Flows and Groundwater Levels'' to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications, and to enable climate change uncertainty and climate variability to be accounted for in the assessment of their possible impacts on the environment. Future Flows Climate is derived from the Hadley Centre's <span class="hlt">ensemble</span> projection HadRM3-PPE that is part of the basis of UKCP09 and includes projections in available precipitation (water available to hydrological processes after snow and ice storages have been accounted for) and potential evapotranspiration. It corresponds to an 11-member <span class="hlt">ensemble</span> of transient projections from January 1950 to December 2098, each a single realisation from a different variant of HadRM3. Data are provided on a 1-km grid over the HadRM3 land areas at a daily (available precipitation) and monthly (PE) time step as netCDF files. Because systematic biases in temperature and precipitation were found between HadRM3-PPE and gridded temperature and precipitation observations for the 1962-1991 period, a monthly bias correction procedure was undertaken, based on a linear correction for temperature and a quantile-mapping correction (using the gamma distribution) for precipitation followed by a spatial <span class="hlt">downscaling</span>. Available precipitation was derived from the bias-corrected precipitation and temperature time series using a simple elevation-dependant snow-melt model. Potential evapotranspiration time series were calculated for each month using the FAO-56 Penman-Monteith equations and bias-corrected temperature, cloud cover, relative humidity and wind speed from HadRM3-PPE along with latitude of the grid and the day of the year. Future Flows Climate is freely available for non-commercial use under certain licensing conditions. It is the dataset used to generate Future Flows Hydrology, an <span class="hlt">ensemble</span> of transient projections of daily river flow and monthly groundwater time series for representative river basins and boreholes in Great Britain. <a href="http://dx.doi.org/10.5285/bad1514f-119e-44a4-8e1e-442735bb9797"target="_blank">doi:10.5285/bad1514f-119e-44a4-8e1e-442735bb9797</a>.</p> <div class="credits"> <p class="dwt_author">Prudhomme, C.; Dadson, S.; Morris, D.; Williamson, J.; Goodsell, G.; Crooks, S.; Boelee, L.; Davies, H.; Buys, G.; Lafon, T.; Watts, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">371</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://cdsweb.cern.ch/record/1664233"> <span id="translatedtitle">Excitations and benchmark <span class="hlt">ensemble</span> density functional theory for two electrons</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">A new method for extracting <span class="hlt">ensemble</span> Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact <span class="hlt">ensemble</span> density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet <span class="hlt">ensemble</span>, singlet-triplet-singlet <span class="hlt">ensemble</span>, and triplet bi-<span class="hlt">ensemble</span>.</p> <div class="credits"> <p class="dwt_author">Pribram-Jones, Aurora; Trail, John R; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">372</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013HESS...17..445A"> <span id="translatedtitle">An educational model for <span class="hlt">ensemble</span> streamflow simulation and uncertainty analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper presents the hands-on modeling toolbox, HBV-<span class="hlt">Ensemble</span>, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-<span class="hlt">Ensemble</span> can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an <span class="hlt">ensemble</span> simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, <span class="hlt">ensemble</span> simulation and model sensitivity. HBV-<span class="hlt">Ensemble</span> was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.</p> <div class="credits"> <p class="dwt_author">AghaKouchak, A.; Nakhjiri, N.; Habib, E.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">373</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/40757078"> <span id="translatedtitle"><span class="hlt">Down-scale</span> analysis for water scarcity in response to soil–water conservation on Loess Plateau of China</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Water scarcity is one of the most prominent issues of discussion worldwide concerned with sustainable development, especially in the arid and semi-arid areas. On the Loess Plateau of China, population growth and fast-growing cities and industries have caused ever-increasing competition for water. The present paper shows a <span class="hlt">down-scale</span> analysis on how the region wide mass action of soil–water conservation ecologically</p> <div class="credits"> <p class="dwt_author">He Xiubin; Li Zhanbin; Hao Mingde; Tang Keli; Zheng Fengli</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">374</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/2p464u6531854q84.pdf"> <span id="translatedtitle">Sensitivity of the Humboldt Current system to global warming: a <span class="hlt">downscaling</span> experiment of the IPSL-CM4 model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The impact of climate warming on the seasonal variability of the Humboldt Current system ocean dynamics is investigated. The\\u000a IPSL-CM4 large scale ocean circulation resulting from two contrasted climate scenarios, the so-called Preindustrial and quadrupling\\u000a CO2, are <span class="hlt">downscaled</span> using an eddy-resolving regional ocean circulation model. The intense surface heating by the atmosphere in\\u000a the quadrupling CO2 scenario leads to a</p> <div class="credits"> <p class="dwt_author">Vincent Echevin; Katerina Goubanova; Ali Belmadani; Boris Dewitte</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">375</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014AdAtS..31..559Z"> <span id="translatedtitle"><span class="hlt">Ensemble</span> retrieval of atmospheric temperature profiles from AIRS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmospheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an <span class="hlt">ensemble</span> methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function (PDF) is used to select the optimal profile from the <span class="hlt">ensemble</span> retrievals. The <span class="hlt">ensemble</span> retrieval algorithm contains four steps: (1) regression retrieval for original first guess; (2) perturbation of the original first guess to generate new first guesses (<span class="hlt">ensemble</span> first guesses); (3) using the <span class="hlt">ensemble</span> first guesses and nonlinear iterative physical retrieval to generate <span class="hlt">ensemble</span> physical results; and (4) the final optimal profile is selected from the <span class="hlt">ensemble</span> physical results by using PDF. Temperature eigenvectors (EVs) were used to generate the perturbation and generate the <span class="hlt">ensemble</span> first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder (AIRS), the <span class="hlt">ensemble</span> retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal (CombOpt) profile and a mean optimal (MeanOpt) profile of all <span class="hlt">ensemble</span> physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal (FinOpt) profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.</p> <div class="credits"> <p class="dwt_author">Zhang, Jie; Li, Zhenglong; Li, Jun; Li, Jinglong</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">376</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/52457977"> <span id="translatedtitle">The Impact of Horizontal Resolution and <span class="hlt">Ensemble</span> Size on Probabilistic Precipitation Forecasts by the ECMWF <span class="hlt">Ensemble</span> Prediction System</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The effect of horizontal resolution and <span class="hlt">ensemble</span> size on the performance of the ECMWF <span class="hlt">Ensemble</span> Prediction System (EPS) is assessed for probabilistic forecasts of 24-h accumulated precipitation. EPS forecasts are analyzed for three spectral truncations, total wavenumbers 159, 255 and 319. Results from two experiments are described. The primary experiment compares EPS performance at T159 and T255 for 57 winter</p> <div class="credits"> <p class="dwt_author">S. L. Mullen; R. Buizza</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">377</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2014GMD.....7.2333R"> <span id="translatedtitle">Multi-model <span class="hlt">ensemble</span>: technique and validation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this study, a method of numerical weather prediction by <span class="hlt">ensemble</span> for the South American region is proposed. This method takes into account combinations of the numerical predictions of various models, assigning greater weight to models that exhibit the best performance. Nine operational numerical models were used to perform this study. The main objective of the study is to obtain a weather forecasting product (short-to-medium range) that combines what is best in each of the nine models used in the study, thus producing more reliable predictions. The proposed method was evaluated during austral summer (December 2012, and January and February 2013) and winter (June, July and August 2013). The results show that the proposed method can significantly improve the results provided by the numerical models and consequently has promising potential for operational applications in any weather forecasting center.</p> <div class="credits"> <p class="dwt_author">Rozante, J. R.; Moreira, D. S.; Godoy, R. C. M.; Fernandes, A. A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">378</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21362155"> <span id="translatedtitle">Schur polynomials and biorthogonal random matrix <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The study of the average of Schur polynomials over a Stieltjes-Wigert <span class="hlt">ensemble</span> has been carried out by Dolivet and Tierz [J. Math. Phys. 48, 023507 (2007); e-print arXiv:hep-th/0609167], where it was shown that it is equal to quantum dimensions. Using the same approach, we extend the result to the biorthogonal case. We also study, using the Littlewood-Richardson rule, some particular cases of the quantum dimension result. Finally, we show that the notion of Giambelli compatibility of Schur averages, introduced by Borodin et al. [Adv. Appl. Math. 37, 209 (2006); e-print arXiv:math-ph/0505021], also holds in the biorthogonal setting.</p> <div class="credits"> <p class="dwt_author">Tierz, Miguel [Department de Fisica i Enginyeria Nuclear, Universitat Politecnica de Catalunya, Comte Urgell 187, E-08036 Barcelona (Spain)</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-06-15</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">379</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008APS..OSS.C2006R"> <span id="translatedtitle"><span class="hlt">Ensemble</span> Approach to Vicinal Crystal Surfaces</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recent studies of the Step Position Distribution (SPD) have made it clear that there exists a characteristic length LW (along the y-axis, parallel to the average step direction) at which the variance of the SPD is correctly predicted by the Pairwise Einstein Model. We extend this to the case when neighboring steps have different stiffnesses, in particular to the limiting case in which one set of steps has infinite stiffness. A similar characteristic length along y must be introduced to calculate average properties from an <span class="hlt">ensemble</span> of Gruber-Mullins models, subject to the constraint that the variance of the Terrace Width Distribution (TWD) is as given by the Pairwise Einstein Model. We discuss the relationship between these length scales for a range of step interactions, using TWDs calculated for the restricted terrace-step-kink model using numerical transfer matrix techniques.</p> <div class="credits"> <p class="dwt_author">Richards, Howard L.; Jacob, Ryan P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">380</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4030569"> <span id="translatedtitle">Global Optimization <span class="hlt">Ensemble</span> Model for Classification Methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization <span class="hlt">ensemble</span> model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382</p> <div class="credits"> <p class="dwt_author">Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_18");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">381</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://arxiv.org/pdf/math/0611687v4"> <span id="translatedtitle">Conformal radii for conformal loop <span class="hlt">ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/epsearch/">E-print Network</a></p> <p class="result-summary">The conformal loop <span class="hlt">ensembles</span> CLE(k), defined for k in [8/3, 8], are random collections of loops in a planar domain which are conjectured scaling limits of the O(n) loop models. We calculate the distribution of the conformal radii of the nested loops surrounding a deterministic point. Our results agree with predictions made by Cardy and Ziff and by Kenyon and Wilson for the O(n) model. We also compute the expectation dimension of the CLE(k) gasket, which consists of points not surrounded by any loop, to be 2-(8-k)(3k-8)/32k, which agrees with the fractal dimension given by Duplantier for the O(n) model gasket.</p> <div class="credits"> <p class="dwt_author">Oded Schramm; Scott Sheffield; David B. Wilson</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-11-22</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">382</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013PhRvL.110u0503V"> <span id="translatedtitle">Feedback Control of Trapped Coherent Atomic <span class="hlt">Ensembles</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We demonstrate how to use feedback to control the internal states of trapped coherent <span class="hlt">ensembles</span> of two-level atoms, and to protect a superposition state against the decoherence induced by a collective noise. Our feedback scheme is based on weak optical measurements with negligible backaction followed by coherent microwave manipulations. The efficiency of the feedback system is studied for a simple binary noise model and characterized in terms of the trade-off between information retrieval and destructivity from the optical probe. We also demonstrate the correction of more general types of collective noise. This technique can be used for the operation of atomic interferometers beyond the standard Ramsey scheme, opening the way towards improved atomic sensors.</p> <div class="credits"> <p class="dwt_author">Vanderbruggen, T.; Kohlhaas, R.; Bertoldi, A.; Bernon, S.; Aspect, A.; Landragin, A.; Bouyer, P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">383</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/25057195"> <span id="translatedtitle">Neuronal <span class="hlt">ensemble</span> synchrony during human focal seizures.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Seizures are classically characterized as the expression of hypersynchronous neural activity, yet the true degree of synchrony in neuronal spiking (action potentials) during human seizures remains a fundamental question. We quantified the temporal precision of spike synchrony in <span class="hlt">ensembles</span> of neocortical neurons during seizures in people with pharmacologically intractable epilepsy. Two seizure types were analyzed: those characterized by sustained gamma (?40-60 Hz) local field potential (LFP) oscillations or by spike-wave complexes (SWCs; ?3 Hz). Fine (<10 ms) temporal synchrony was rarely present during gamma-band seizures, where neuronal spiking remained highly irregular and asynchronous. In SWC seizures, phase locking of neuronal spiking to the SWC spike phase induced synchrony at a coarse 50-100 ms level. In addition, transient fine synchrony occurred primarily during the initial ?20 ms period of the SWC spike phase and varied across subjects and seizures. Sporadic coherence events between neuronal population spike counts and LFPs were observed during SWC seizures in high (?80 Hz) gamma-band and during high-frequency oscillations (?130 Hz). Maximum entropy models of the joint neuronal spiking probability, constrained only on single neurons' nonstationary coarse spiking rates and local network activation, explained most of the fine synchrony in both seizure types. Our findings indicate that fine neuronal <span class="hlt">ensemble</span> synchrony occurs mostly during SWC, not gamma-band, seizures, and primarily during the initial phase of SWC spikes. Furthermore, these fine synchrony events result mostly from transient increases in overall neuronal network spiking rates, rather than changes in precise spiking correlations between specific pairs of neurons. PMID:25057195</p> <div class="credits"> <p class="dwt_author">Truccolo, Wilson; Ahmed, Omar J; Harrison, Matthew T; Eskandar, Emad N; Cosgrove, G Rees; Madsen, Joseph R; Blum, Andrew S; Potter, N Stevenson; Hochberg, Leigh R; Cash, Sydney S</p> <p class="dwt_publisher"></p> <p class="publishDate">2014-07-23</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">384</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70035825"> <span id="translatedtitle">Assessing the impact of land use change on hydrology by <span class="hlt">ensemble</span> modelling (LUCHEM) II: <span class="hlt">Ensemble</span> combinations and predictions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various <span class="hlt">ensemble</span> predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model <span class="hlt">ensemble</span>. The 10 resulting single-model <span class="hlt">ensembles</span> are combined in various ways to produce multi-model <span class="hlt">ensemble</span> predictions. Both the single-model <span class="hlt">ensembles</span> and the multi-model <span class="hlt">ensembles</span> are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the <span class="hlt">ensembles</span> they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean <span class="hlt">ensemble</span> (with wei