Relevant bibliographies by topics / Weather Generator (WG)

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  2. Dissertations / Theses

Academic literature on the topic 'Weather Generator (WG)'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Weather Generator (WG)"

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Fodor, Nándor, Ildikó Dobi, János Mika, and László Szeidl. "Applications of the MVWG Multivariable Stochastic Weather Generator." Scientific World Journal 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/571367.

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Weather generators (WG) became significant modules of crop models and decision support systems in the past decade. Using a large meteorological database from North America; two basic problems, related to the applicability of WGs in case of short or lacking data series, were investigated in the framework of the Multivariable weather generator (MVWG). First, the minimum data series length, required for adequate parameterization of the WG, was determined. Our results suggest that 15 years of observed data are enough for adequate parameterization of the MVWG. We then investigated a possibility of
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Fodor, Nándor, Ildikó Dobi, János Mika, and László Szeidl. "MV-WG: a new multi-variable weather generator." Meteorology and Atmospheric Physics 107, no. 3-4 (2010): 91–101. http://dx.doi.org/10.1007/s00703-010-0074-z.

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Ma, D., Q. Jing, YP Xu, et al. "Using ensemble-mean climate scenarios for future crop yield projections: a stochastic weather generator approach." Climate Research 83 (May 6, 2021): 161–71. http://dx.doi.org/10.3354/cr01646.

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Using climate scenarios from only 1 or a small number of global climate models (GCMs) in climate change impact studies may lead to biased assessment due to large uncertainty in climate projections. Ensemble means in impact projections derived from a multi-GCM ensemble are often used as best estimates to reduce bias. However, it is often time consuming to run process-based models (e.g. hydrological and crop models) in climate change impact studies using numerous climate scenarios. It would be interesting to investigate if using a reduced number of climate scenarios could lead to a reasonable es
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Sørup, Hjalte Jomo Danielsen, Ole Bøssing Christensen, Karsten Arnbjerg-Nielsen, and Peter Steen Mikkelsen. "Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator." Hydrology and Earth System Sciences 20, no. 4 (2016): 1387–403. http://dx.doi.org/10.5194/hess-20-1387-2016.

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Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km × 60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resol
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Jones, P. D., C. Harpham, C. M. Goodess, and C. G. Kilsby. "Perturbing a Weather Generator using change factors derived from Regional Climate Model simulations." Nonlinear Processes in Geophysics 18, no. 4 (2011): 503–11. http://dx.doi.org/10.5194/npg-18-503-2011.

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Abstract. The purpose of this paper is to provide a method for perturbing Weather Generators (WGs) for future decades and to assess its effectiveness. Here the procedure is applied to the WG implemented within the UKCP09 package and assessed using data from a Regional Climate Model (RCM) simulation which provides a significant "climate change" between a control run period and a distant future. The WG is normally calibrated on observed data. For this study, data from an RCM control period (1961–1990) was used, then perturbed using the procedure. Because only monthly differences between the RCM
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Sørup, H. J. D., O. B. Christensen, K. Arnbjerg-Nielsen, and P. S. Mikkelsen. "Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator." Hydrology and Earth System Sciences Discussions 12, no. 2 (2015): 2561–605. http://dx.doi.org/10.5194/hessd-12-2561-2015.

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Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a Spatio-Temporal Neyman–Scott Rectangular Pulses weather generator (WG). Precipitation time series for fitting the model are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 by 60 km model domain. The model simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from Regional Climate Models (RCMs) with spatial resolu
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Halabian, Amir Hossein, and M. S. Keikhosravi. "Exploring climate change over Khazar Basin based on LARSE-WG weather generator." Bioscience Biotechnology Research Communications 10, no. 3 (2017): 372–79. http://dx.doi.org/10.21786/bbrc/10.3/6.

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Semenov, MA, and RJ Brooks. "Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain." Climate Research 11 (1999): 137–48. http://dx.doi.org/10.3354/cr011137.

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Osman, Yassin, Nadhir Al-Ansari, Mawada Abdellatif, Sadeq B. Aljawad, and Sven Knutsson. "Expected Future Precipitation in Central Iraq Using LARS-WG Stochastic Weather Generator." Engineering 06, no. 13 (2014): 948–59. http://dx.doi.org/10.4236/eng.2014.613086.

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Gelfan, Alexander, Vsevolod Moreydo, Yury Motovilov, and Dimitri P. Solomatine. "Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios." Hydrology and Earth System Sciences 22, no. 4 (2018): 2073–89. http://dx.doi.org/10.5194/hess-22-2073-2018.

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Abstract. A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (W
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Dissertations / Theses on the topic "Weather Generator (WG)"

1

Alzahrani, Fahad. "An Approach to Quantifying Uncertainty in Estimates of Intensity Duration Frequency (IDF) Curves." Thesis, 2013. http://hdl.handle.net/10012/7735.

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Generally urban drainage systems are built to protect urban property and control runoff. Moreover, these systems collect the runoff for storage purposes to serve society through sufficient water supply to meet the needs of demand, irrigation, and drainage. Urban environments are exposed to risks of extreme hydrological events. Therefore, urban water systems and their management are critical. Precipitation data are crucial, but may be prone to errors due to the lack of information e.g., short length of records. In this thesis, a Monte Carlo simulation and regional frequency analysis based on L-
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Journal articles
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