WebApr 14, 2024 · In this study, the dataset of the coupled model intercomparison project phase 6 (CMIP6) was used to evaluate the future wind resources and wave conditions in the nearshore area of Guangdong of China. The long short-term memory (LSTM) algorithm was used to develop a statistical downscaling method to render high spatial resolution data. WebJun 26, 2024 · Downscaling methods Five methods have been applied to both temperature and precipitation; some of them under different configurations (see Table 2 ): Analog …
Atmosphere Free Full-Text Machine-Learning-Based Downscaling …
WebThe Statistical Downscaling Model (SDSM) [Wilby et al., 2002], which is a hybrid statistical downscaling method incorporating a weather generator and a multiple linear regression technique, is used in this study. The primary principle of SDSM is to establish the statistical relationship between the predictands and predictors and then determine ... WebMar 6, 2024 · The performance of the downscaling methods is closely linked to their specific structure and setup. All methods using parametric distributions require non-standard distributions to correctly represent marginal aspects of extremes. ... With respect to the marginal aspects of extremes the best performance is found for model output statistics … healthcare for the homeless pittsburgh
Downscaling long lead time daily rainfall ensemble forecasts …
WebMar 22, 2024 · This section presents different downscaling methods for soil moisture, which are broadly classified into the following three major groups: (1) satellite-based methods, (2) methods using geoinformation data, and (3) ... In statistical downscaling, the land surface model is used as a basis for describing the relationship between the soil moisture ... WebApr 14, 2024 · A simple comparison with two station-based statistical downscaling methods, an improved analogue method and ECPP, and one dynamic downscaling model CCAM on five representative weather stations has further demonstrated VDSD’s advantages. Compared with the CRPS skill score variabilities, the improvement of VDSD over VDSR or … WebJul 20, 2016 · Statistical downscaling is one of two methods (the other is dynamical downscaling) that uses climate data produced at a large scale (such as global) to make predictions about future climate at a smaller scale (such as a particular watershed). The downscaling process generates information that is useful for making decisions and … healthcare for the homeless santa fe