Global‐Scale Prediction of Flood Timing Using Atmospheric Reanalysis

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

Historical isotope simulation using Reanalysis atmospheric data

[1] In this paper we present a multidecadal and global three-dimensional stable water isotope data set. This is accomplished by incorporating processes of the stable water isotopes into an atmospheric general circulation model and by applying a spectral nudging technique toward Reanalysis dynamical fields. Unlike the global model simulations forced only by sea surface temperature (SST), the dyn...

متن کامل

the crisis management of flood in isfahan using atmospheric system

heavy rains are one of the features of arid and semi arid climates which result in flood. this kind of rainfall originates from environmental and synoptic conditions. mediterranean cyclones are the major factor in heavy rainfall in iran, but these cyclones do not happen in some parts of iran such as southern and southeastern areas. in this study, it has been tried to pinpoint the synoptic reaso...

متن کامل

River Flood Prediction using Time Series Model

With the passage of time the impacts of natural hazards continue to increase around the world. The globalization and growth of human societies and their escalating complexity and river flooding will further increase the risks of natural hazards. Flood prediction and control are one of the greatest challenges facing the world today, which have become more frequent and severe due to the effects o...

متن کامل

Short-term prediction of atmospheric concentrations of ground-level ozone in Karaj using artificial neural network

Air pollution is a challenging issue in some of the large cities in developing countries. Air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. Several methods exist to analyze air quality. Among them, we applied the dynamic neural network (TDNN) and Radial Basis Function (RBF) methods to predict the concentrations of ground-level...

متن کامل

Short-term prediction of atmospheric concentrations of ground-level ozone in Karaj using artificial neural network

Air pollution is a challenging issue in some of the large cities in developing countries. Air quality monitoring and interpretation of data are two important factors for air quality management in urban areas. Several methods exist to analyze air quality. Among them, we applied the dynamic neural network (TDNN) and Radial Basis Function (RBF) methods to predict the concentrations of ground-level...

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: Water Resources Research

سال: 2020

ISSN: 0043-1397,1944-7973

DOI: 10.1029/2019wr024945