Version 6 of the UAH MSU/AMSU global satellite temperature dataset is by far the most extensive revision of the procedures and computer code we have ever produced in over 25 years of global temperature monitoring. The two most significant changes from an end-user perspective are (1) a decrease in the global-average lower tropospheric (LT) temperature trend from +0.140 C/decade to +0.114 C/decad...

We examine the diurnal cycles of deep convection and precipitation in the Southern Amazon region, using mainly the Advanced Microwave Sounding Unit, contrasting a year of drought (2004-2005) with a “normal” year (2005-2006). MODIS 550nm aerosol optical thickness data and TRMM 3B42 precipitation products were also used to investigate whether a significant relationship between these two parameter...

The frequency and spatial distributions of precipitation extremes (PEs) deep convective clouds (DCC) across the Amazon region were assessed using satellite-derived data. For PEs, CHIRPS dataset for period 1981–2018 used to calculate a set absolute, threshold, duration, percentile-based threshold indices defined by Expert Team on Climate Change Detection Indices. DCC occurrence was based Advance...

Algorithms for retrieval of geophysical parameters from radiances measured by instruments onboard satellites play a large role in helping scientists monitor the state of the planet. Current retrieval algorithms based on neural networks are superior in accuracy and speed compared to physics-based algorithms like iterated minimum variance (IMV). However, they do not have any form of error estimat...

The National Polar-Orbiting Operational Environmental Satellite System (NPOESS) aircraft sounder testbed (NAST) has recently been developed and deployed on the NASA ER-2 high-altitude aircraft. The testbed consists of two co-located cross-track scanning instruments: a Fourier transform interferometer spectrometer (NAST-I) [1] with spectral coverage of 3.7–15.5 m and a passive microwave spectrom...

[1] This study presents various strategies to sample databases from large atmospheric data sets in high-dimensional spaces for satellite remote sensing applications. In particular, two sampling algorithms are examined: the traditional uniform sampling that lists all possible situations and the clustering sampling (K-means) that respects the natural variability probability distribution functions...

Estimating daily evapotranspiration is challenging when ground observation data are not available or scarce. Remote sensing can be used to estimate the meteorological data necessary for calculating reference evapotranspiration ETo. Here, we assessed the accuracy of daily ETo estimates derived from remote sensing (ETo-RS) compared with those derived from four ground-based stations (ETo-G) in Kur...