HadCRUT5, the new version of the Met Office Hadley Centre/Climatic Research Unit global surface temperature dataset from 1850 to 2018, has extended and improved the previous temperature record.
Uncertainty assessment
Different Models, Different Answers in Water Resource Planning
The experimental design used in climate vulnerability assessments can strongly influence the assessments’ findings and skew decisions about which factors are most important for informing adaptation.
How Diverse Observations Improve Groundwater Models
Including diverse observations of exchange fluxes, tracer concentrations and residence times in groundwater model calibration results in more robust predictions than using only classical observations.
Are Soil Moisture and Latent Heat Overcoupled in Land Models?
A novel statistical approach demonstrates how to reduce bias in remote sensing estimates of soil moisture and latent heat flux coupling strength and clarifies the relationship between the variables.
Can We Predict River Flows from Just a Few Observations?
Improving Discharge Data for Water Resources Management—Hydraulic Modelling as a Tool for Rapid Rating Curve Estimation; Stockholm, Sweden, 8 November 2018
Exploring Uncertainty in Streamflow Estimates
A review of streamflow uncertainty estimation methods reveals that one method does not fit all situations and provides recommendations for how to improve streamflow estimates.
Humans to Blame for Higher Drought Risk in Some Regions
New observations and analysis dispel remaining doubts that anthropogenic climate change is expanding dry areas in northern midlatitudes.
Timothy A. Cohn (1957–2017)
Cohn emphasized the use of hydrologic science for the public good, to protect ordinary citizens from flood and pollution hazards and to reduce losses from natural disasters.
What Caused Record Water Level Rise in the Great Lakes?
A new modeling framework offers insight into how specific lakes' water levels respond to short- and long-term climate trends.
What Climate Information Is Most Useful for Predicting Floods?
Basing forecasts on data that preserve variations over space yield more reliable predictions than using standard numerical measures of climatic cycles' intensity.
