Seasonal forecasts run by the Eta Model over South America were evaluated with respect to precipitation predictability at different time scales, seasonal, monthly and weekly for one-year period runs. The model domain was configured over most of South America in 40 km horizontal resolution and 38 layers. The lateral boundary conditions were taken from CPTEC GCM forecasts at T62L28. The sea surfa...

We report on the development of a machine learning approach to improving sea surface temperature (SST) retrievals based satellite-based microwave channel measurements at frequencies higher than 23 GHz. The uses deep neural network (DNN) trained using Microwave Integrated Retrieval System physical as inputs and collocated European Centre for Medium-Range Weather Forecasts analyses training valid...

Dengue hemorrhagic fever (DHF) is one of the most widespread and deadly diseases in several parts Indonesia. An accurate forecast-based model required to reduce incidence rate this disease. Time-series methods such as autoregressive integrated moving average (ARIMA) models are used epidemiology statistical tools study forecast DHF other infectious diseases. The present attempted monthly confirm...

a prediction of maximum monthly rainfall is indispensable for management of agriculture and for management of water resources. previous studies have demonstrated that see surface temperatures affect rainfall in their surrounding regions. in this study the relationship between sea surface temperatures of persian gulf and that of red sea, and maximum monthly rainfalls recorded at illam meteorolog...

A complex autoregressive model was established based on the mathematic derivation of the least squares for the complex number domain which is referred to as the complex least squares. The model is different from the conventional way that the real number and the imaginary number are separately calculated. An application of this new model shows a better forecast than forecasts from other conventi...

Skillful seasonal streamflow forecasts obtained from climate and land surface conditions could significantly improve water and energy management. Since climate forecasts are updated on a monthly basis, we evaluate the potential in developing operational monthly streamflow forecasts on a continuous basis throughout the year. Further, basins in the rainfall–runoff regime critically depend on the ...

Predicting biodiversity responses to climate change remains a difficult challenge, especially in climatically complex regions where precipitation is a limiting factor. Though statistical climatic envelope models are frequently used to project future scenarios for species distributions under climate change, these models are rarely tested using empirical data. We used long-term data on bird distr...