Reducing uncertainty in quantifying basin‐scale water‐budget components is one of the
most vexing problems for water‐resource managers. Although a vast literature addresses …

With the urgency of the transition to a resilient low-carbon economy, the monitoring and
prediction of regional renewable energy generation over time have become increasingly …

This study examines whether deep learning models can produce reliable future projections
of streamflow under warming. We train a regional long short‐term memory network (LSTM) …

Predicting crop yield before harvest and understanding the factors determining yield at a
regional scale is vital for global food security, supply chain management in agribusiness …

25 At no other time in history has the importance of understanding and reducing the impacts
of 26 extreme heat on health been so vital. Climate change, an aging population, urban …

Summary This dataset provides Daymet Version 3 model output data as gridded estimates
of daily weather parameters for North America and Hawaii: including Canada, Mexico, the …

The increasing frequency of severe wildfires demands a shift in landscape management to
mitigate their consequences. The role of managed, low-intensity fire as a driver of beneficial …

Near-surface air temperature (Ta) is a key variable in global climate studies. A global
gridded dataset of daily maximum and minimum Ta (Tmax and Tmin) is particularly valuable …

Large-sample datasets containing hydrometeorological time series and catchment attributes
for hundreds of catchments in a country, many of them known as “CAMELS”(Catchment …

We used a model for permafrost hydrology informed by detailed measurements of soil ice
content to better understand the potential risk of abrupt permafrost thaw triggered by melting …