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First 4186 results for ” and K. Whan”

1. GABLS 3 SCM intercomparison and evaluation, what did we learn?

   A weakly stable case is selected from the Cabauw long term archive. The case is used for an evalu...

   FC Bosveld, P Baas, GJ Steeneveld, AAM Holtslag | Conference: Workshop on Diurnal cycles and the stable boundary layer, | Organisation: ECMWF | Place: Reading, UK | Year: 2011 | First page: 0 | Last page: 0

   Publication

2. Calibration of ECMWF Seasonal Ensemble Precipitation Reforecasts in Java (Indonesia) Using Bias-Corrected Precipitation and Climate Indices

   The seasonal precipitation forecast is one of the essential inputs for economic and agricultural ...

   Ratri, D. N., Whan, K., and Schmeits, M. | Journal: Weather and Forecasting | Volume: 36 | Year: 2021 | First page: 1375 | Last page: 1386 | doi: 10.1175/WAF-D-20-0124.1

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3. Probabilistic Forecasting of Cloud-Base Height and Visibility Using Quantile Regression Forests, Based on NWP and Observation Features

   We have applied quantile regression forests (QRFs) to generate probabilistic forecasts of weather...

   D. Wolters, M. Schmeits, and K. Whan | Journal: Wea. Forecasting | Volume: 40 | Year: 2025 | First page: 543 | Last page: 559 | doi: https://doi.org/10.1175/WAF-D-23-0231.1

   Publication

4. What controls the vertical distribution of aerosol? Relationships between process sensitivity in HadGEM3–UKCA and inter-model variation from AeroCom Phase II

   The vertical profile of aerosol is important for its radiative effects, but weakly constrained by...

   Z Kipling, P Stier, CE Johnson, GW Mann, N Bellouin, SE Bauer, T Bergman, M Chin, T Diehl, SJ Ghan, T Iversen, A Kirkevåg, H Kokkola, X Liu, G Luo, T van Noije, KJ Pringle, K von Salzen, M Schulz, Ø Seland, RB Skeie, T Takemura, K Tsigaridis, K Zhang | Status: published | Journal: Atmos. Chem. Phys. | Volume: 16 | Year: 2016 | First page: 2221 | Last page: 2241 | doi: 10.5194/acp-16-2221-2016

   Publication

5. Statistical Postprocessing of Wind Speed Forecasts Using Convolutional Neural Networks

   Current statistical postprocessing methods for probabilistic weather forecasting are not capable ...

   Veldkamp, S., Whan, K., Dirksen, S., and Schmeits, M. | Journal: Monthly Weather Review | Volume: 149 | Year: 2021 | First page: 1141 | Last page: 1152 | doi: 10.1175/MWR-D-20-0219.1

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