Roland Potthast Webhome

Our Division for Data Assimilation (FE12) of the German Weather Service (DWD), a part of the German Ministery of Transport and Digital Infrastructure (BMVI), is working on data assimilation for numerical weather prediction (NWP). Our main task is to provide

• operational data assimilation for the global ICON NWP-model (13km resolution, 90 layers 75km height), run every 3 hours 24/7,
• with its mesoscale two-way-nesting area over Europe (6.5km resolution) and the
• high-resolution convection-permitting COSMO model over central Europe (2.8/2.2km resolution, 24km height) every hour 24/7.

This includes ensemble data assimilation for the ensemble prediction systems ICON-EPS (40/20km resolution) as well as COSMO-DE-EPS (2.8/2.2km resolution) and a mean (best) state estimator for the deterministic runs (13/6.5km and 2.8/2.2km). A core goal is to replace COSMO by the ICON-LAM model with 2/1km resolution over central Europe operationally in about 2020/21. We run a hybrid ensemble-variational data assimilation scheme (EnVar) globally and a Local Ensemble Transform Kalman Filter (4D-LETKF) for our reginal data assimilation.

Data Assimilation includes the use of a broad varity of both direct and remote sensing measurements from

• Ground Stations and Ships (SYNOP),
• Radio Sondes (TEMP) and dropsondes,
• Buoys,
• Air Planes (AMDAR, AIREP, ACAR, …),
• Atmospheric Motion Vectors (AMV),
• Scatterometers (SCAT),
• Infrared Sounders (IR),
• Microwave Sounders (MW) and Microwave Radiometers (MWR),
• LIDAR including Clound Bottom Height (CBH), Cloud Top Height (CTH), Backscatter Profiles, Line-of-Sight Winds (AEOLUS), Ceilometers,
• RADAR including RADAR Radial Winds, RADAR Reflectivity and RADAR Dual Polarization,
• GPS/GNSS including Radio Occultations (RO), Zenith Total Delay (ZTD), Slant Total Delay (STD),
• Cameras,
• Cars.

Geostationary satellites and polar orbiting satellites are used operationally, while a lot of research is going into the better use of hyperspectral observations (many thousand frequencies per observed atmospheric column) in particular over land and in cloudy situations. The observation and reconstruction of snow, ice, sea surface temperature, land surface temperature, coverage, emissivity and soil moisture is a very active area of research. Also, the observation and data assimilation of clouds and convective processes with high-impact phenomena such as thunderstorms, heavy rain and wind gusts with lead times from minutes to days is a special focus of our research.

The research of our group at the University of Reading, UK, is concerned with inverse problems and data assimilation in three areas:

• numerical weather prediction (NWP),
• cognitive neuroscience / neural field theory (NFT),
• inverse scattering problems / remote sensing.

These are extremely exciting areas scientifically and very important for society, for example for air traffic control, severe weather warnings and national energy supply, in medicine by medical imaging and for many industrial and environmental questions.

• Nov 29-Dec 5, 2017, Darmstadt, Germany: 21st International TOVS Study Conference ITSC-XXI Web PDF
• Nov 9, 2017, Kobe, Japan: External Reviewer of RIKEN Data Assimilation Unit Web

• Oct 23-24, 2017, Bali, Indonesia: WMO Commission of Atmospheric Sciences (CAS) Meeting Web
• Oct 20-22, 2017, Bali, Indonesia: WMO Science Summit Web PDF Copy

• Sept 11-14, 2017, Jerusalem: COSMO (Consortium for Small Scale Modeling) General Meeting Cosmo Calender PDF Copy
• Sept 4-5, 2017, Dublin, Ireland: COST TOPROF Action Management Committee Meeting http://www.toprof.imaa.cnr.it/ as part of the EMS Annual Conference EMS Web

• July 3-5, 2017, Reading, UK, 4th International Conference on Neural Field Theory www.inverseproblems.info/icnft2017, Organizer and Tutorial Speaker
• May 31-Jun 2, 2017, Jeju Island, Korea. “International Workshop on Real Time NWP Forecast System” with a strong Data Assimilation component https://www.kiaps.org/eng/main.do, Invited Speaker
• May 30-June 2, 2017, Colorado, USA: International Conference on Mathematical Neuroscience 2017 Web (Programme Committee)

• May 23, 2017: Seminar Talk at the University of Karlsruhe, Ensemble Data Assimilation and Numerical Weather Prediction
• April 19, 2017: Seminar Talk at Eumetsat, Darmstadt, about Satellite Data and Numerical Weather Prediction

• March 28-30, 2017, Offenbach, Germany: HErZ General Meeting (Hans Ertel Center for Weather Research) General Structure PDF Open Talks
• March 27-29, 2017, Berlin, International conference on “Scaling Cascades in Complex Systems” by the Collaborative Research Center 1114, Minisymposium on “balanced data assimilation”

• Feb 27-March 2, 2017, 3rd Riken International Data Assimilation Symposium at Kobe, Japan, Scientific Organizing Committee PDF Copy
• Feb 19-26, 2017, Tokyo, Japan. Research Stay and invited talk at Tokyo University of Science, Miniworkshop on Inverse Problems programme_tus_miniworkshop.pdf

• Jan 26, 2017, Graz, Austria, Wegener Center for Klimate and Global Change, Wegener Center Seminar Talk Abstract PDF PDF Copy
• WAVES 2017 to be held in Minnesota, May 15-19, 2017, Member of Scientific Committee, Paper Submission is now open

For more news see IP News and IP Events!
Previous News can be found at News RP 2016.

My group consists of about 30 researchers on data assimilation and inverse problems in Frankfurt/Offenbach and Reading (UK), see group.

^{Jan 2017: Meetings DWD Data Assimilation Group with our partners from the HErZ Center on Data Assimilation from LMU Munich.}

Thinking about faith and life has always been a passion for me. I have become a Christian and have started to explore the world as someone who follows Jesus - that has turned out to be quite an adventure and highly exciting. In my daily blog I explore thoughts and arguments about faith, and monitor how faith works on a daily basis: Jesus Network

Recent publications can be found on publications. A book Inverse Modeling by Nakamura and Potthast with an introduction into data assimilation and inverse problems has recently appeared at IOP.

Working in an operational center, our focus is to develop state-of-the-art inversion methods which can be run in a reliable way on a supercomputer in near real-time. It includes codes on scattering of waves, propagation of light and radiation, tomography, large-scale optimization and uncertainty quanitfication, ensemble and particle methods.

(Our computer at Deutscher Wetterdienst is no 130 on the TOP-500 Supercomputer List Web)

However, the development of insight into the scientific problems we need to solve is an indispensible ingredient of our daily work. Part of this insight is based on mathematical analysis and the testing of computational methods for purpuse-built small-scale demonstration systems.

COST Action 1303 “TOPROF” Website;

• Inverse Problems in Science and Engineering Login
• Frontiers in Applied Mathematics and Statistics - Dynamical Systems
• Mathematical Inverse Problems