because of the role of climate parameters in climate change and improve the efficiency of climate and rainfall prediction models, the study of these parameters are very important in the world. the study of clouds have special important, because the clouds make connection between the synoptic patters and surface climate conditions and any change in its properties, can start a chain reaction in o...

This study contributes to the estimation of the global mean and zonal distribution of oceanic precipitation rate using complementary information from advanced precipitation measuring sensors and provides an independent reference to assess current precipitation products. Precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and CloudSat cloud profil...

Six rainfall datasets are compared over the Amazon basin, Northeast Brazil, and the Congo basin. These datasets include three gauge-only precipitation products from the Climate Prediction Center (CPC), Global Precipitation Climatology Center (GPCC), and Brazilian Weather Forecast and Climate Studies Center (CLMNLS), and three combined gauge and satellite precipitation datasets from the CPC Merg...

A statistical approach is used to explore the variability of precipitation and meteorological drought in Mexico’s Rı́o Yaqui basin on seasonal-to-decadal timescales. For this purpose, a number of custom datasets have been developed, including a monthly 1900-2004 precipitation index for the Yaqui basin created by merging two gridded land-surface precipitation products, a 350-year tree-ring based ...

Abstract. A strategy to evaluate the suitability of different multiplicative random cascades produce rainfall time series, taking into account climate change, inputs for green infrastructures models. The reproduce a (multi)fractal distribution precipitation through an iterative and process. In current study, initial model, flexible cascade that deviates from multifractal scale invariance, was i...

In this study we present a technique to discriminate between climate or human-induced dryland degradation, based on evaluations of AVHRR NDVI data and rainfall data. Since dryland areas typically have high inter-annual rainfall variations and rainfall has a dominant role in determining vegetation growth, minor biomass trends imposed by human influences are difficult to verify. By performing man...

This paper describes a new approach for intensive rainfall data analysis. ITHACA’s Extreme Rainfall Detection System (ERDS) is conceived to provide near real-time alerts related to potential exceptional rainfalls worldwide, which can be used by WFP or other humanitarian assistance organizations to evaluate the event and understand the potentially floodable areas where their assistance is needed...