[1] This paper presents indirect observational evidence that desert dust can modulate the amplitude of easterly waves in the Atlantic Ocean. Twenty two years of NCEP/ NCAR reanalysis and dust from a global transport model are used to characterize the evolution of enhanced easterly waves. Lag composites of analysis increments (analysis minus first–guess) of geopotential height (700–hPa) anomalie...

Change detection is an important task in signal analysis, data mining, and image processing. In meteorology research, change is frequently associated with severe weather events or climate anomalies. Detecting change is crucial for weather and climate analysis. In this paper, we propose a wavelet based approach to analyze short term changes in the global meteorological data. We design a suite of...

In the atmospheric science, the scale of meteorological data is massive and growing rapidly. K-means is a fast and available cluster algorithm which has been used in many fields. However, for the large-scale meteorological data, the traditional K-means algorithm is not capable enough to satisfy the actual application needs efficiently. This paper proposes an improved MK-means algorithm (MK-mean...

solar radiation data play an important role in solar energy relevant researches. these data are not available for some locations due to the absence of the meteorological stations. therefore, solar radiation data have to be predicted by using solar radiation estimation models. this study presents an integrated artificial neural network (ann) approach for estimating solar radiation potential over...