WORKING GROUPS
In the IPWG activity during 2022-2024, we have formed 4 Working Groups in order to be more responsive to the discussions and sentiments expressed at the last IPWG meeting at Fort Collins in 2022.
We also have 5 Focus Groups, who’s primary aim is to act as a forum for individual research questions that are meant to facilitate the transition from research to operations.
We also have 5 Focus Groups, who’s primary aim is to act as a forum for individual research questions that are meant to facilitate the transition from research to operations.
Working Groups (WGs):
Baseline Surface Precipitation Network.
Co-leads: Pierre Kirstetter, Kazumasa Aonashi. Goal: Produce a document that outlines the steps needed to produce a Quantitative Precipitation Estimation (QPE) product of uniform quality from radars/radar networks for use in satellite data validation, and then help implement this by getting this uniform quality radar or radar network data from as many regimes as possible into a common database for use by satellite product and model developers.
Co-leads: Pierre Kirstetter, Kazumasa Aonashi. Goal: Produce a document that outlines the steps needed to produce a Quantitative Precipitation Estimation (QPE) product of uniform quality from radars/radar networks for use in satellite data validation, and then help implement this by getting this uniform quality radar or radar network data from as many regimes as possible into a common database for use by satellite product and model developers.
Satellite Precipitation WG.
Co-leads: Ali Behrangi, Daniel Vila. Goal: Produce a document that outlines (a) User needs from global product producers (b) Needs from global product producers from research community.
Co-leads: Ali Behrangi, Daniel Vila. Goal: Produce a document that outlines (a) User needs from global product producers (b) Needs from global product producers from research community.
Machine Learning WG.
Co-leads: Simon Pfreundschuh and Tomoo Ushio. Goal: Produce a standard training and independent test data set for individuals to test Machine Learning algorithm capabilities in a uniform fashion.
Co-leads: Simon Pfreundschuh and Tomoo Ushio. Goal: Produce a standard training and independent test data set for individuals to test Machine Learning algorithm capabilities in a uniform fashion.
CubeSat/SmallSat WG.
Co-leads: Chris Kidd, Joe Munchak. Goal: Produce a document outlining relative capabilities of various channel combinations/spatial resolutions for helping constellation requirements.
Co-leads: Chris Kidd, Joe Munchak. Goal: Produce a document outlining relative capabilities of various channel combinations/spatial resolutions for helping constellation requirements.
Focus Groups (FGs):
Orographic Precipitation FG.
Shoichi Shige; Yagmur Derin.
Shoichi Shige; Yagmur Derin.
Snowfall / Particle Scattering FG.
Huan Meng, Guosheng Liu, Nobuyuki Utsumi.
Huan Meng, Guosheng Liu, Nobuyuki Utsumi.
Data Assimilation FG.
Alan Geer, Ben Johnson, Yasutaka Ikuta.
Alan Geer, Ben Johnson, Yasutaka Ikuta.
Land Surface FG.
Joe Turk, Sarah Ringerud.
Joe Turk, Sarah Ringerud.