Recent work has shown that (sub-)seasonal variability in tropical Pacific convection, closely lin...
Subseasonal forecasts are challenging for numerical weather prediction (NWP) and machine learning...
Alongside mean increases in poleward moisture transport (PMT) to the Arctic, most climate models ...
Reliable subseasonal forecasts of high summer temperatures would be very valuable for society. Al...
National meteorological services (NMS) are limited by practical and financial boundaries in the n...
Statistical post-processing is an indispensable tool for providing accurate weather forecasts and...
Statistical postprocessing techniques are nowadays key components of the forecasting suites in ma...
The seasonal precipitation forecast is one of the essential inputs for economic and agricultural ...
Current statistical postprocessing methods for probabilistic weather forecasting are not capable ...
Flooding events associated with extreme precipitation have had large impacts in Norway. It is wel...
We apply a physical climate storyline approach to an autumn flood event in the West Coast of Norw...
The succession of European surface weather patterns has limited predictability because disturbanc...
The increased usage of solar energy places additional importance on forecasts of solar radiation....
Dynamical seasonal forecasts are afflicted with biases, including seasonal ensemble precipitation...
A comparison of statistical postprocessing methods is performed for high-resolution precipitation...
The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high...
Probabilistic forecasts, which communicate forecast uncertainties, enable users to make better we...
A stationary low pressure system and elevated levels of precipitable water provided a nearly cont...