The land surface and the atmosphere can interact with each other through exchanges of energy, water, and momentum. With the capacity of long memory, land surface processes can contribute to long-term variability of atmospheric processes. Great efforts have been made in the past three decades to study land-atmosphere interactions and their importance to longterm variability. This paper reviews s...

precipitation regime refers to distribution of seasonal- monthly precipitation. by studying this character, it could be find out about the most important parts of mechanism(s) dominant in temporal distribution of precipitation. precipitation regime can have positive or negative effects on other environmental components performance. in the present research, the monthly data in 73 stations during...

The article proposes an approach to forecasting mean temperature and total precipitation for the upcoming month, based on study of regularities influence statistical characteristics previous periods them. Among predictors, along with basic characteristics, we use fractality index which is indicator randomness/ determinism climate series. Within framework this approach, have developed models dif...

There are a number of factors that lead to nonlinearity between precipitation anomalies and flood hazard; this nonlinearity is a pertinent issue for applications that use a precipitation forecast as a proxy for imminent flood hazard. We assessed the degree of this nonlinearity for the first time using a recently developed global-scale hydrological model driven by the ERA-Interim/Land precipitat...

Section 112(m) of the 1990 Clean Air Act Amendments, referred to as the Great Waters Program, mandated an assessment of atmospheric deposition of hazardous air pollutants (HAPs) to Lake Champlain. Mercury (Hg) was listed as a priority HAP and has continued to be a high priority for a number of national and international programs. An assessment of the magnitude and seasonal variation of atmosphe...

Simple stochastic models fit to time series of daily precipitation amount have a marked tendency to underestimate the observed (or interannual) variance of monthly (or seasonal) total precipitation. By considering extensions of one particular class of stochastic model known as a chain-dependent process, the extent to which this ‘‘overdispersion’’ phenomenon is attributable to an inadequate mode...

Accurate precipitation prediction is of great significance for regional flood control and disaster mitigation. This study introduced a model based on the least square support vector machine (LSSVM) optimized by genetic algorithm (GA). The was used to estimate each meteorological station over source region Yellow River (SRYE) in China 12 months. Ensemble empirical mode decomposition (EEMD) metho...

The impact of initial land-surface states on monthly to seasonal prediction skill of the Indian summer monsoon (June–September) is investigated using a suite of hindcasts made with the Climate Forecast System version 2 (CFSv2) operational forecast model. The modern paradigm of land-atmosphere coupling is applied to quantify biases in different components of the land-atmosphere coupled system an...