Limited support from 2025-12-24 to 2026-01-01There will only be limited support during the time from wednesday, Dec 24th, to thursday, Jan 1st and creation of new WDCC account will take longer.
The SIGNAL project is dedicated to quantifying the impacts of climate change on dairy cattle, with a primary focus on the challenges posed by heat stress due to rising temperatures and humidity levels.
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data (https://doi.org/10.7917/OFSG3345)
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly
The experiment conducted aimed to enhance the temporal resolution of climate projections for agricultural applications by using machine learning to downscale daily NEX-GDDP-CMIP6 climate data to hourly