Search Results - computing climate model parameter uncertainties in parallel

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  1. 1

    Data‐Directed Importance Sampling for Climate Model Parameter Uncertainty Estimation by Jackson, Charles S., Sen, Mrinal K., Stoffa, Paul L., Huerta, Gabriel

    ISBN: 9780470072943, 0470072946
    Published: Hoboken, NJ, USA John Wiley & Sons, Inc 09.12.2009
    “…This chapter contains sections titled: Introduction Computing Climate Model Parameter Uncertainties in Parallel Stochastic Inversion Application to Climate…”
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    Book Chapter
  2. 2

    A parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United States by Wang, Jiali, Wang, Cheng, Rao, Vishwas, Orr, Andrew, Yan, Eugene, Kotamarthi, Rao

    ISSN: 1991-9603, 1991-959X, 1991-962X, 1991-9603, 1991-962X
    Published: Katlenburg-Lindau Copernicus GmbH 13.08.2019
    Published in Geoscientific Model Development (13.08.2019)
    “…The Weather Research and Forecasting Hydrological (WRF-Hydro) system is a state-of-the-art numerical model that models the entire hydrological cycle based on physical principles…”
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    Journal Article
  3. 3

    The GAMIL3: Model Description and Evaluation by Li, Lijuan, Dong, Li, Xie, Jinbo, Tang, Yanli, Xie, Feng, Guo, Zhun, Liu, Hongbo, Feng, Tao, Wang, Lu, Pu, Ye, Sun, Wenqi, Xia, Kun, Liu, Li, Xie, Zhenghui, Wang, Yan, Wang, Longhuan, Shi, Xiangjun, Jia, Binghao, Liu, Juanjuan, Wang, Bin

    ISSN: 2169-897X, 2169-8996
    Published: Washington Blackwell Publishing Ltd 16.08.2020
    “…The Grid‐point Atmospheric Model of the IAP LASG version 3 (GAMIL3) has been developed by upgrading the horizontal resolution, methods of parallel computation…”
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    Journal Article
  4. 4

    Stochasticity of convection in Giga-LES data by De La Chevrotière, Michèle, Khouider, Boualem, Majda, Andrew J.

    ISSN: 0930-7575, 1432-0894
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2016
    Published in Climate dynamics (01.09.2016)
    “…The poor representation of tropical convection in general circulation models (GCMs) is believed to be responsible for much of the uncertainty in the predictions of weather and climate in the tropics…”
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    Journal Article
  5. 5

    Flood and drought hydrologic monitoring: the role of model parameter uncertainty by Chaney, N. W., Herman, J. D., Reed, P. M., Wood, E. F.

    ISSN: 1607-7938, 1027-5606, 1607-7938
    Published: Katlenburg-Lindau Copernicus GmbH 24.07.2015
    Published in Hydrology and earth system sciences (24.07.2015)
    “…, floods and droughts). However, uncertainties in the meteorological forcings, model structure, and parameter identifiability limit the reliability of model predictions…”
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    Journal Article
  6. 6

    Approximation of Metro Water District Basin Using Parallel Computing of Emulator Based Spatial Optimization (PCESO) by Budamala, Venkatesh, Mahindrakar, Amit Baburao

    ISSN: 0920-4741, 1573-1650
    Published: Dordrecht Springer Netherlands 01.01.2020
    Published in Water resources management (01.01.2020)
    “… 3.5 million people of Atlanta Metro Region. In this study, Parallel Computing of Emulator based Spatial Optimization ( PCESO…”
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    Journal Article
  7. 7

    Comparative analyses of covariance matrix adaptation and iterative ensemble smoother on high-dimensional inverse problems in high-resolution groundwater modeling by Yang, Shuo, Tsai, Frank T.-C., Bacopoulos, Peter, Kees, Christopher E.

    ISSN: 0022-1694, 1879-2707
    Published: Elsevier B.V 01.10.2023
    Published in Journal of hydrology (Amsterdam) (01.10.2023)
    “…•ES-LM outperforms the CMA-ES in calibrating high-resolution groundwater model. Parameter estimation is an inverse problem which is crucial to reliable groundwater model predictions and management…”
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    Journal Article
  8. 8

    Impacts of Permeability Uncertainty in a Coupled Surface‐Subsurface Flow Model Under Perturbed Recharge Scenarios by Engdahl, Nicholas B.

    ISSN: 0043-1397, 1944-7973
    Published: Washington John Wiley & Sons, Inc 01.03.2024
    Published in Water resources research (01.03.2024)
    “…” studies, but, as parallel computing continues to improve, IHMs are approaching the point where they might also be useful as predictive tools…”
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    Journal Article
  9. 9

    Efficient Calibration of a Conceptual Hydrological Model Based on the Enhanced Gauss–Levenberg–Marquardt Procedure by Vidmar, Andrej, Brilly, Mitja, Sapač, Klaudija, Kryžanowski, Andrej

    ISSN: 2076-3417, 2076-3417
    Published: Basel MDPI AG 01.06.2020
    Published in Applied sciences (01.06.2020)
    “… Models contain many parameters that cannot be directly measured. The values of most of these parameters are determined in the calibration process conditioning the efficiency of such models…”
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    Journal Article
  10. 10

    Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS by Matar, Christian, Cornet, Céline, Parol, Frédéric, C.-Labonnote, Laurent, Auriol, Frédérique, Nicolas, Marc

    ISSN: 1867-8548, 1867-1381, 1867-8548
    Published: Katlenburg-Lindau Copernicus GmbH 28.06.2023
    Published in Atmospheric measurement techniques (28.06.2023)
    “… as the corresponding uncertainties related to the measurement errors, the non-retrieved parameters, and the cloud model assumptions…”
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    Journal Article
  11. 11

    A dynamic agricultural prediction system for large-scale drought assessment on the Sunway TaihuLight supercomputer by Huang, Xiao, Yu, Chaoqing, Fang, Jiarui, Huang, Guorui, Ni, Shaoqiang, Hall, Jim, Zorn, Conrad, Huang, Xiaomeng, Zhang, Wenyuan

    ISSN: 0168-1699, 1872-7107
    Published: Amsterdam Elsevier B.V 01.11.2018
    Published in Computers and electronics in agriculture (01.11.2018)
    “…•Further acceleration of crop models and high-performance computing for large-scale crop modeling…”
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    Journal Article
  12. 12

    UNCERTAINTY MODELLING IN RAINFALL-RUNOFF SIMULATIONS BASED ON PARALLEL MONTE CARLO METHOD by Golasowski, M, Litschmannova, M, Kuchar, S, Podhorányi, M, Martinovic, J

    ISSN: 1210-0552, 2336-4335
    Published: Prague Institute of Information and Computer Technology 01.01.2015
    Published in Neural Network World (01.01.2015)
    “…This article describes statistical evaluation of the computational model for precipitation forecast and proposes a method for uncertainty modelling of rainfall-runoff models in the Floreon…”
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    Journal Article
  13. 13

    GDNDC: An integrated system to model water-nitrogen-crop processes for agricultural management at regional scales by Huang, Xiao, Ni, Shaoqiang, Wu, Chao, Zorn, Conrad, Zhang, Wenyuan, Yu, Chaoqing

    ISSN: 1364-8152, 1873-6726
    Published: Oxford Elsevier Ltd 01.12.2020
    “… However, few models are available that offer high computing efficiencies for region-scale simulations, integrated decision support tools, and a structure that allows for easy extension…”
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    Journal Article
  14. 14

    Aqua-MC as a simple open access code for uncountable runs of AquaCrop by Adabi, Vahid, Etedali, Hadi Ramezani, Azizian, Asghar, Gorginpaveh, Faraz, Salem, Ali, Elbeltagi, Ahmed

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 10.07.2025
    Published in Scientific reports (10.07.2025)
    “… Monte Carlo simulations are widely used for uncertainty and sensitivity analysis, but their application to closed-source models like AquaCrop presents significant challenges due to the lack of direct…”
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    Journal Article
  15. 15

    Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction by Lu, Dan, Ricciuto, Daniel

    ISSN: 2375-9259
    Published: IEEE 01.11.2019
    “… in complex forward models. This inversion-based prediction approach is infeasible for complex models with heterogeneous parameter uncertainties and incapable of rapid integration of streaming and multiple sources of data…”
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    Conference Proceeding
  16. 16

    Prediction of Climate Change using SVM and Naïve Bayes Machine Learning Algorithms by Karthikeyan, C, Sunitha, Gurram, Avanija, J, Madhavi, K Reddy, Madhan, E S

    ISSN: 1309-4653, 1309-4653
    Published: Gurgaon Ninety Nine Publication 11.04.2021
    “… implemented. We come across a continuous crashes in simulation of Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4…”
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    Journal Article
  17. 17

    Extreme precipitation risk assessment with improved WOA-Optimized copula model under composite conditions by Wang, Zhaocai, Ma, Chao, Wu, Junhao, Wu, Tunhua

    ISSN: 0177-798X, 1434-4483
    Published: Vienna Springer Vienna 01.08.2025
    Published in Theoretical and applied climatology (01.08.2025)
    “… This research presents a model using an enhanced whale optimization algorithm to estimate Copula parameters (CLCWOA-Copula…”
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    Journal Article
  18. 18

    A parallelization framework for calibration of hydrological models by Rouholahnejad, E., Abbaspour, K.C., Vejdani, M., Srinivasan, R., Schulin, R., Lehmann, A.

    ISSN: 1364-8152, 1873-6726
    Published: Elsevier Ltd 01.05.2012
    “…Large-scale hydrologic models are being used more and more in watershed management and decision making…”
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    Journal Article
  19. 19

    Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R by Schmidt-Walter, Paul, Trotsiuk, Volodymyr, Meusburger, Katrin, Zacios, Martina, Meesenburg, Henning

    ISSN: 0168-1923, 1873-2240
    Published: Elsevier B.V 15.09.2020
    Published in Agricultural and forest meteorology (15.09.2020)
    “…) models are important for the quantification of water fluxes, soil water availability, drought stress and their uncertainties under climate change…”
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    Journal Article
  20. 20

    Multivariate spatio-temporal modelling for assessing Antarctica's present-day contribution to sea-level rise by Zammit-Mangion, Andrew, Rougier, Jonathan, Schön, Nana, Lindgren, Finn, Bamber, Jonathan

    ISSN: 1180-4009, 1099-095X
    Published: England Blackwell Publishing Ltd 01.05.2015
    Published in Environmetrics (London, Ont.) (01.05.2015)
    “… Constraining the contribution of the ice sheets to present‐day SLR is vital both for coastal development and planning, and climate projections…”
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    Journal Article