Comparison of Three Statistical Downscaling Methods and Ensemble Downscaling Method Based on Bayesian Model Averaging in Upper Hanjiang River Basin, China

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparison of Various Precipitation Downscaling Methods for the Simulation of Streamflow in a Rainshadow River Basin

Global simulations of precipitation from climate models lack sufficient resolution and contain large biases that make them unsuitable for regional studies, such as forcing hydrologic simulations. In this study, the effectiveness of several methods to downscale large-scale precipitation is examined. To facilitate comparisons with observations and to remove uncertainties in other fields, large-sc...

متن کامل

An NDVI-Based Statistical ET Downscaling Method

This study proposes a new method for downscaling ETWatch 1-km actual evapotranspiration (ET) products to a spatial resolution of 30 m using Landsat8 normalized difference vegetation index (NDVI) data. The NDVI is employed as an indicator of land-surface vegetation, which displays periodic spatial patterns on the land surface. A 30-m-resolution ten-day ET dataset is then calculated primarily usi...

متن کامل

Comparison of data-driven methods for downscaling ensemble weather forecasts

This study investigates dynamically different data-driven methods, specifically a statistical downscaling model (SDSM), a time lagged feedforward neural network (TLFN), and an evolutionary polynomial regression (EPR) technique for downscaling numerical weather ensemble forecasts generated by a medium range forecast (MRF) model. 5 Given the coarse resolution (about 200-km grid spacing) of the MR...

متن کامل

Statistical downscaling of precipitation

Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract Global Circulation Models (GCMs) are a major tool used for future projections of climate change using different emission scenarios. However, for assessing the hydrological impacts of climate change at the watershed and the regional scale, ...

متن کامل

Multi-Model Grand Ensemble Hydrologic Forecasting in the Fu River Basin Using Bayesian Model Averaging

Statistical post-processing for multi-model grand ensemble (GE) hydrologic predictions is necessary, in order to achieve more accurate and reliable probabilistic forecasts. This paper presents a case study which applies Bayesian model averaging (BMA) to statistically post-process raw GE runoff forecasts in the Fu River basin in China, at lead times ranging from 6 to 120 h. The raw forecasts wer...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Advances in Meteorology

سال: 2016

ISSN: 1687-9309,1687-9317

DOI: 10.1155/2016/7463963