Worldwide continuous gap-filled MODIS land surface temperature dataset
Satellite land surface temperature (LST) is vital for climatological and environmental studies.
However, LST datasets are not continuous in time and space mainly due to cloud cover …
However, LST datasets are not continuous in time and space mainly due to cloud cover …
Comparison of gap-filling methods for producing all-weather daily remotely sensed near-surface air temperature
Y Mo, Y Xu, Y Liu, Y Xin, S Zhu - Remote Sensing of Environment, 2023 - Elsevier
Thermal infrared remotely sensed near-surface air temperature (T a) can provide gridded
temperature information at relatively high spatial and temporal resolutions, and such …
temperature information at relatively high spatial and temporal resolutions, and such …
A new statistical downscaling approach for short‐term forecasting of summer air temperatures through a fusion of deep learning and spatial interpolation
Reliable early forecasting of extreme summer air temperatures is essential for effectively
managing and mitigating the socioeconomic damage caused by thermal disasters …
managing and mitigating the socioeconomic damage caused by thermal disasters …
Hydrological response of tropical catchments to climate change as modeled by the GR2M model: a case study in Costa Rica
This study aimed to assess the impacts of climate change on streamflow characteristics of
five tropical catchments located in Costa Rica. An ensemble of five General Circulation …
five tropical catchments located in Costa Rica. An ensemble of five General Circulation …
Random forest for spatialization of daily evapotranspiration (ET0) in watersheds in the Atlantic Forest
PFB Baratto, RA Cecílio, DB de Sousa Teixeira… - Environmental …, 2022 - Springer
The importance of daily data on reference evapotranspiration (ET0) has increased in recent
years due to its relevance in planning and decision making regarding irrigated agriculture …
years due to its relevance in planning and decision making regarding irrigated agriculture …
Dimensionality Reduction of the CORDEX-CA GCM-RCM Multimodel-Ensemble on Precipitation Using Principal Component Analysis (PCA) and Hierarchical …
M Mendez, LA Calvo-Valverde… - E3S Web of …, 2024 - e3s-conferences.org
Principal Component Analysis (PCA) and Hierarchical Clustering (HC) were applied to
reduce the dimensionality of a 19-member multimodel-ensemble combining different …
reduce the dimensionality of a 19-member multimodel-ensemble combining different …
Comparative Analysis of Deep Learning and ARIMA-based Models for Multi-Step Weather Forecasting in the city of Yaoundé, Cameroon
ETA Albert, NME Leonard - 2024 - authorea.com
Background: The environmental imbalance caused by climate change has significantly
complicated weather forecasting, a crucial activity in modern agriculture. Recent research …
complicated weather forecasting, a crucial activity in modern agriculture. Recent research …