Prolongation of SMAP to spatiotemporally seamless coverage of continental US using a deep learning neural network

K Fang, C Shen, D Kifer, X Yang - Geophysical Research …, 2017 - Wiley Online Library
Abstract The Soil Moisture Active Passive (SMAP) mission has delivered valuable sensing of
surface soil moisture since 2015. However, it has a short time span and irregular revisit …

Machine learning approaches for spatial modeling of agricultural droughts in the south-east region of Queensland Australia

O Rahmati, F Falah, KS Dayal, RC Deo… - Science of the total …, 2020 - Elsevier
A quantitative understanding of the hydro-environmental factors that influence the
occurrence of agricultural drought events would enable more strategic climate change …

Determining and forecasting drought susceptibility in southwestern Iran using multi-criteria decision-making (MCDM) coupled with CA-Markov model

M Mokarram, HR Pourghasemi, M Hu… - Science of the Total …, 2021 - Elsevier
Forecasting drought and determining relevant data to predict drought are an important topic
for decision-makers and planners. It is critical to predicting drought in the south of Fars …

High accuracy of precipitation reanalyses resulted in good river discharge simulations in a semi-arid basin

MR Eini, S Javadi, M Delavar, JAF Monteiro… - Ecological …, 2019 - Elsevier
Hydrological modeling requires accurate climate data with high spatial resolution, what is
often unavailable in a large fraction of the world. As an alternative to scarce meteorological …

Understanding the dominant sources and tracks of moisture for summer rainfall in the southwest United States

S Jana, B Rajagopalan… - Journal of Geophysical …, 2018 - Wiley Online Library
We investigated the moisture sources and tracks that enable summer rainfall over the four‐
state southwestern US region of Arizona, New Mexico, Colorado, and Utah by employing a …

Simulating land-atmosphere coupling in the Central Valley, California: Investigating soil moisture impacts on boundary layer properties

GA Alexander, HA Holmes, X Sun, D Caputi… - Agricultural and Forest …, 2022 - Elsevier
Soil moisture links hydrologic and atmospheric processes and impacts important properties
of the atmospheric boundary layer via turbulent land-atmosphere exchange. Research on …

Using the US climate reference network to identify biases in near-and subsurface meteorological fields in the High-Resolution Rapid Refresh (HRRR) weather …

TR Lee, RD Leeper, T Wilson… - Weather and …, 2023 - journals.ametsoc.org
The ability of high-resolution mesoscale models to simulate near-surface and subsurface
meteorological processes is critical for representing land–atmosphere feedback processes …

A comparison of the US climate reference network precipitation data to the Parameter-Elevation Regressions on Independent Slopes Model (PRISM)

MS Buban, TR Lee, CB Baker - Journal of Hydrometeorology, 2020 - journals.ametsoc.org
Since drought and excessive rainfall can have significant socioeconomic impacts, it is
important to have accurate high-resolution gridded datasets that can help improve analysis …

Mapping the agricultural drought based on the long-term AVHRR NDVI and North American Regional Reanalysis (NARR) in the United States, 1981–2013

J Lu, GJ Carbone, P Gao - Applied geography, 2019 - Elsevier
To provide a long-term perspective of drought variability from 1981 to present, we develop a
new monthly agriculturally-based drought index called the Integrated Scaled Drought Index …

Impact of soil moisture on afternoon convection triggering over the Tibetan Plateau based on 1‐D boundary layer model

C Zhao, X Meng, Y Li, S Lyu, J Guo… - Journal of Geophysical …, 2022 - Wiley Online Library
The impact of soil moisture conditions on the triggering of afternoon convection over the
Tibetan Plateau (TP) was investigated by applying the convective triggering potential (CTP) …