Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we use time series from GNSS, European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data, and meteorological measurements to e...

The effect of climate change on wildfires constitutes a serious concern in fire-prone regions with complex fire behavior such as the Mediterranean. The coarse resolution of future climate projections produced by General Circulation Models (GCMs) prevents their direct use in local climate change studies. Statistical downscaling techniques bridge this gap using empirical models that link the syno...

ABSTRACT- Many fruits, vegetables and ornamental crops of tropical origin experience physiological damage when subjected to low temperatures. Protection of plants from the effects of lethally low temperatures is important in agriculture, especially in horticultural production of high value fruits and vegetables. The objective of this study was to develop a simple model to predict the daily mini...

This study developed a methodology to temporally classify large scale, upper level atmospheric conditions over North America, utilizing a newly-developed upper level synoptic classification (ULSC). Four meteorological variables: geopotential height, specific humidity, and u- and v-wind components, at the 500 hPa level over North America were obtained from the NCEP/NCAR Reanalysis Project datase...

Water-vapor feedback is one of the important factors that determine the response of the atmosphere to surface warming. To take into account the compensating drying e ects in downdraft regions, averaging over the whole tropics is necessary. However, this operation drastically reduces the number of degrees of freedom and raises question concerning the statistical signi cance of any correlative re...

Europe has been affected by record-breaking heat waves in recent decades. Using station data and a gridded reanalysis as input, four commonly used wave indices, the magnitude index daily (HWMId), excess factor (EHF), wet-bulb globe temperature (WBGT) universal thermal climate (UTCI), are computed. The extremeness of historical European between 1979 2019 using indices different metrics is ranked...

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality associations depending on the metric used. We employed a statistical learning method - random forests - to examine which of the various weather variables had the greatest impact on heat-related mortality. We compiled a summertim...

Characterizing typical meteorological conditions associated with extreme pollution events helps to better understand the role of local meteorology in governing the transport and distribution of pollutants in the atmosphere. The knowledge of their co-variability could further help to evaluate and constrain chemistry transport models. Hence, in this study, we investigate the statistical linkages ...

The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5° grid nested within 1° Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing P...

We used a land surface model constrained using data from flux tower sites, to analyze the biases in ecosystem energy and water fluxes arising due to the use of meteorological reanalysis datasets. Following site-level model calibration encompassing major vegetation types from the tropics to the northern high-latitudes, we repeated the site and global simulations using two reanalysis datasets: th...