Differences

This shows you the differences between two versions of the page.

--- research [2014/05/09 10:19] – [Data Assimilation for Numerical Weather Prediction] potthast
+++ research [2023/03/28 09:14] (current) – external edit 127.0.0.1
@@ Line 5: / Line 5: @@
 **Inverse Problems and Data Assimilation**
-{{img018smsm.jpg?200}} {{img213smsm.jpg?200}} {{img285smsm.jpg?200}}
+{{research04.jpg?200}} {{research02.jpg?200}} {{research01.jpg?200}}
+Some notes on current research activities: [ [[research_notes]] ]
 ===== Algorithms and Analysis for Inverse Problems =====
-My research is concerned with inverse problems and data assimilation in three areas:
+Our research is concerned with inverse problems and data assimilation in three areas:
     numerical weather prediction (NWP),
@@ Line 19: / Line 21: @@
 Personally, my main focus is the development and analysis of efficient algorithms, the development of concepts and more general mathematical analysis and its interplay with key applications.
-At Reading, UK we have an intensive interdisciplinary collaboration with Meteorology in atmospheric applications and with the Centre for Integrative Neuroscience and Neurodynamics (CINN), with several PhD students and PostDocs. Reading has strongly invested into this area in 2012 and 2013, with several new lecturers and professors in the field.
+At Reading, UK we have an intensive interdisciplinary collaboration with Meteorology in atmospheric applications and with the Centre for Integrative Neuroscience and Neurodynamics (CINN), with several PhD students and PostDocs. Reading has strongly invested into this area since 2012, with several new lecturers and professors in the field.
-At DWD in Offenbach, Ger, our data assimilation unit FE12 consists of appr. 12 senior researchers and around 10 positions by externally funded projects (e.g. an Eumetsat fellowship or funds by the German transport ministery), it is part of a larger section FE1 for numerical weather prediction. Within the newly established Heinz Ertel Center for Atmospheric Research (HERZ) there are 6 positions (FTE) funded by the German government to work in intense collaboration with our group since 2011.
-At Göttingen currently two PhD students work on inversion in fluid dynamics and data assimilation for GPS tomography.
+At DWD in Offenbach, Ger, our data assimilation unit FE12 consists of 19 senior researchers and about 20 positions by externally funded projects (e.g. an Eumetsat fellowship or funds by the German transport ministery) plus several PhD students. It is part of a larger section FE1 for numerical weather prediction. Within the newly established Heinz Ertel Center for Atmospheric Research (HERZ) there are 6 positions (FTE) funded by the German government to work in intense collaboration with our group since 2011.
 {{img177smsm.jpg?300}} {{img178smsm.jpg?300}}
@@ Line 32: / Line 32: @@
 {{ fe12_chart_2013.png?400}}
-The main goal of data assimilation algorithms is to determine the state of some system from measurement data. For numerical weather forecast as it is used every day by millions of people, we use a broad range of measurements (see [[DWD NWP measurements]] ground stations, weather baloons, ships, commercial airplanes, radar, satellite radiances and GPS signals) in mathematical algorithms which are run on our supercomputers in Offenbach, Germany, 24/7. The state of the weather at time t0 is the basis for forecasts, which are calculated by running an ensemble of simulations forward in time. Our research and services are used by numerous institutions and businesses.
+The main goal of data assimilation algorithms is to determine the state of some system from measurement data. For numerical weather forecast as it is used every day by millions of people, we use a broad range of measurements (see [[http://www.inverseproblems.info/NWP_measurements/|NWP measurements]] ground stations, weather baloons, ships, commercial airplanes, radar, satellite radiances and GPS signals) in mathematical algorithms which are run on our supercomputers in Offenbach, Germany, 24/7. The state of the weather at time t0 is the basis for forecasts, which are calculated by running an ensemble of simulations forward in time. Our research and services are used by numerous institutions and businesses.
 Ensemble filters are very popular tools for data assimilation in large-scale applications. In several projects we develop the analysis for different convergence concepts, in particular for nonlinear systems and ill-posed observation operators. In particular, a **rigorous convergence analysis** for local ensemble transform filters (EnKF) and hybrid variational-ensemble filter (VarEnKF) approaches is a basis for further algorithmic progress.
@@ Line 71: / Line 71: @@
 The **time-domain probe method** sends a time-dependent pulse and reconstructs the full time-dependent scattered field. The generation of the scattered field when a pulse hits the object can be used to find the location and shape of scattering surfaces.
-**Orthogonality sampling** is the simple idea to superpose plane waves according to the measured far field amplitude for scattering of a time-harmonic field. This leads a stable technique which can be used to detect the location, shape and further properties of objects.
+**Orthogonality sampling** (P. 2010), also called Direct Sampling, is the simple idea to superpose plane waves according to the measured far field amplitude for scattering of a time-harmonic field. This leads a stable technique which can be used to detect the location, shape and further properties of objects.