Letteratura scientifica selezionata sul tema "Run-Time bias-Correction"
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Articoli di riviste sul tema "Run-Time bias-Correction"
Okui, Ryo. "Asymptotically Unbiased Estimation of Autocovariances and Autocorrelations with Panel Data in the Presence of Individual and Time Effects". Journal of Time Series Econometrics 6, n. 2 (1 luglio 2014): 129–81. http://dx.doi.org/10.1515/jtse-2013-0017.
Testo completoYan, Changxiang, e Jiang Zhu. "A Simple Bias Correction Scheme in Ocean Data Assimilation". Journal of Marine Science and Engineering 11, n. 1 (12 gennaio 2023): 205. http://dx.doi.org/10.3390/jmse11010205.
Testo completovon Auer, Ludwig, e Alena Shumskikh. "Substitution Bias in the Measurement of Import and Export Price Indices: Causes and Correction". Journal of Official Statistics 38, n. 1 (1 marzo 2022): 107–26. http://dx.doi.org/10.2478/jos-2022-0006.
Testo completoKrinner, Gerhard, Julien Beaumet, Vincent Favier, Michel Déqué e Claire Brutel-Vuilmet. "Empirical Run-Time Bias Correction for Antarctic Regional Climate Projections With a Stretched-Grid AGCM". Journal of Advances in Modeling Earth Systems 11, n. 1 (gennaio 2019): 64–82. http://dx.doi.org/10.1029/2018ms001438.
Testo completoOsuch, M., R. J. Romanowicz, D. Lawrence e W. K. Wong. "Assessment of the influence of bias correction on meteorological drought projections for Poland". Hydrology and Earth System Sciences Discussions 12, n. 10 (12 ottobre 2015): 10331–77. http://dx.doi.org/10.5194/hessd-12-10331-2015.
Testo completoRogers, Bruce, David Giles, Nick Draper, Laurent Mourot e Thomas Gronwald. "Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination". Sensors 21, n. 3 (26 gennaio 2021): 821. http://dx.doi.org/10.3390/s21030821.
Testo completoPhan Van, Tan, Hiep Van Nguyen, Long Trinh Tuan, Trung Nguyen Quang, Thanh Ngo-Duc, Patrick Laux e Thanh Nguyen Xuan. "Seasonal Prediction of Surface Air Temperature across Vietnam Using the Regional Climate Model Version 4.2 (RegCM4.2)". Advances in Meteorology 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/245104.
Testo completoGupta, Abhimanyu, e Myung Hwan Seo. "Robust Inference on Infinite and Growing Dimensional Time‐Series Regression". Econometrica 91, n. 4 (2023): 1333–61. http://dx.doi.org/10.3982/ecta17918.
Testo completoWei, Linyong, Shanhu Jiang, Liliang Ren, Linqi Zhang, Menghao Wang, Yi Liu e Zheng Duan. "Bias correction of GPM IMERG Early Run daily precipitation product using near real-time CPC global measurements". Atmospheric Research 279 (dicembre 2022): 106403. http://dx.doi.org/10.1016/j.atmosres.2022.106403.
Testo completoMa, Qiumei, Lihua Xiong, Jun Xia, Bin Xiong, Han Yang e Chong-Yu Xu. "A Censored Shifted Mixture Distribution Mapping Method to Correct the Bias of Daily IMERG Satellite Precipitation Estimates". Remote Sensing 11, n. 11 (4 giugno 2019): 1345. http://dx.doi.org/10.3390/rs11111345.
Testo completoTesi sul tema "Run-Time bias-Correction"
Balhane, Saloua. "Improving the dynamical downscaling over Morocco in the context of climate change". Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAX105.
Testo completoMorocco is one of the most vulnerable regions to climate change. Its climate is characterized by complex interactions between various geographical features, including the Atlantic Ocean, the Mediterranean Sea, the High Atlas Mountains, and the Sahara Desert. Understanding the spatiotemporal variability of climatic patterns in this region is crucial for effective climate change adaptation strategies, natural resource management, and sustainable development planning. Global climate models (GCMs) play a significant role within this context, as they are the only models to take into account all the water and energy reservoirs, including slow-moving reservoirs such as the oceans, which modulate the climate and its evolution. Yet, global climate models are still subject to systematic biases that constrain their performance and have generally coarse resolutions, limiting the assessment of local climate patterns. Regional climate models can improve the representation of certain processes (orographic processes, breezes, etc.). They do, however, have flaws that can significantly alter the credibility of climate change trajectories, as it is impossible to distinguish the impact of systematic biases in the forcing GCMs from the role of better small-scale description.This work explores different ways of overcoming these limitations.In the first part, we evaluate a range of different widely used high-resolution ensembles issued from statistical (NEXGDDP) and dynamical (Euro-CORDEX and bias-adjusted Euro-CORDEX) downscaling while investigating the potential added value that “a posteriori'' bias adjustment may have on the simulation of mean and extreme precipitation and temperature over Morocco.In the second part, we use the LMDZ model, the atmospheric component of the latest version of the IPSL model (IPSLCM6), in a coupled configuration with the ORCHIDEE land-surface model. We designed a refined-grid configuration of the model adapted for regional studies over Morocco that is numerically stable enough for running climate change simulations and allows i) a high resolution over the region and ii) a sufficient resolution on the outside of the zoom area to reproduce large-scale patterns. To deal with the systematic large-scale dynamical biases, a run-time bias correction approach, which consists of bias-correcting the systematic errors in large-scale atmospheric variables using the statistics of a nudged simulation towards climate reanalysis, is used. This method allows for high resolution at a moderate computational cost without compromising the coherence between the global and regional climates. Indeed, preserving this coherence is crucial for Morocco since large-scale circulation patterns play a vital role in shaping regional climate patterns in the region.The evaluation of the present climate (1979–2014) has shown significant improvements after grid refinement, particularly in the mean general circulation. The free refined-grid run compares favorably to precipitation and temperature observations at the local scale. The mean climate is considerably improved after bias correction compared to the uncorrected simulations, and improvements in moisture transport, precipitation and air temperature are observed.For future climate, sea surface temperature (SST) and sea ice concentration (SIC) deduced from four coupled CMIP6 models, forced by greenhouse gases and aerosols corresponding to the Shared Socioeconomic Pathway-8.5 (SSP-8.5) scenario, are used to force the corrected regional configuration of LMDZ6-OR. Twenty-year simulations are produced for a global warming level of 3 Kelvin to assess the response of mean regional climate, precipitation and temperature to changes in SST and SIC
Atti di convegni sul tema "Run-Time bias-Correction"
Ejdfors, Kristian, Erik Falkenberg, Siril Okkenhaug e Magnus Johannesen. "Analysis Guidance for Thruster Assisted Mooring". In Offshore Technology Conference. OTC, 2023. http://dx.doi.org/10.4043/32516-ms.
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