See also AMS>Mathscinet>Potthast, R or R Potthast on Google Scolar or Scopus, ResearcherID: F-2265-2013, compare http://www.researcherid.com/rid/F-2265-2013 or Orcid: http://orcid.org/0000-0001-6794-2500.

Note that citation rates vary by a large factor between disciplines average citation rates.

• Kotsuki, S., Miyoshi, T., Kondo K., and Potthast R.: A Local Particle Filter and Its Gaussian Mixture Extension: Comparison with the LETKF using an Intermediate AGCM, under review.

• Maria Reinhardt, Sybille Y. Schoger, Frederik Kurzrock, Roland Potthast: Convective-scale Assimilation of Cloud Cover from Photographs using a Machine Learning Forward Operator, under review.

• Anne Walter, Nora Schenk, Peter-Jan van Leeuwen, Roland Potthast: Particle Filtering and Gaussian Mixtures - On a Localized Mixture Coefficients Particle Filter (LMCPF) for global NWP, under review.

• Peter Jan van Leeuwen, Dan Crisan, Oana Lang, Roland Potthast: Bayesian Inference for Fluid Dynamics: A Case Study for the Stochastic Rotating Shallow Water Model, under review. https://arxiv.org/abs/2112.15216 pdf

• Takashi Furuya and Roland Potthast: Inverse medium scattering problems with Kalman filter techniques“, under review.

• Bastian Harrach, Tim Jahn, Roland Potthast: Regularising linear inverse problems under unknown non-Gaussian white noise allowing repeated measurements, IMA Journal on Numerical Analysis 2021, accepted. https://arxiv.org/abs/2010.04519

• Klaus Vobig, Klaus Stephan, Ulrich Blahak, Kobra Khosravian, Roland Potthast: Targeted Covariance Inflation for 3D-Volume RADAR Reflectivity Assimilation with the LETKF”, QJRMS 2021. Web

• Silke Trömel, Christian Chwala, Carina Furusho, Cintia Carbajal Henken, Julius Polz, Roland Potthast, Ricardo Reinoso-Rondinel, and Clemens Simmer: Near-Realtime Quantitative Precipitation Estimation and Prediction (RealPEP), BAMS 2021. https://doi.org/10.1175/BAMS-D-21-0073.1

• Yi-Hsuan Lin, Gen Nakamura, Roland Potthast, Haibing Wang: Duality between range and no-response tests and its application for inverse problems, Inverse Problems and Imaging, 2021. PDF

• J. Otkin, R. Potthast and A. Lawless: Nonlinear Conditional Model Bias Estimation for Data Assimilation, SIADS 2021. PDF

• A. Hutt, M. Bocquet, A. Carrassi, L. Lei and R. Potthast: Data Assimilation of Nonlocal Observations in Complex Systems, Editorial, Front. Appl. Math. Stat., 28 May 2021 | https://doi.org/10.3389/fams.2021.658272, Web

• Axel Hutt , Wilhelm Stannat and Roland Potthast (Editors): Data Assimilation and Control: Theory and Applications in Life, 2019, Front. Appl. Math. Stat. doi: 10.3389/fams.2019.00025 Web and PDF

• J. Otkin and R. Potthast: Assimilation of All-Sky SEVIRI Infrared Brightness Temperatures in a regional-scale Ensemble Data Assimilation System“, MWR Monthly Weather Review, accepted for publication PDF

• Yves-Marie Saint-Drenan, Stephan Vogt, Sven Killinger, Jamie M.Bright, Rafael Fritz, Roland Potthast: Bayesian parameterisation of a regional photovoltaic model – Application to forecasting, Solar Energy 2019 PDF

• J. Waller, E. Bauernschubert, S.L. Dance, N.K. Nichols, R. Potthast and D. Simonin: Observation error statistics for Doppler Radar radial wind superobservations assimilated into the DWD COSMO-KENDA system, Monthly Weather Review 2019, PDF.

• Peter Jan van Leeuwen Hans R. Künsch Lars Nerger Roland Potthast Sebastian Reich: Particle filters for high‐dimensional geoscience applications: A review, QJRMS 2019 https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3551

• Roland Potthast, Anne Walter and Andreas Rhodin: A Localised Adaptive Particle Filter within an Operational NWP Framework. Monthly Weather Review 2018, https://doi.org/10.1175/MWR-D-18-0028.1.

• Meike Hellweg, Jens Nachtigall, Thomas Kratzsch, Roland Potthast, Hella Riede, Zoi Paschalidi, Alexandros Boura, Walter Acevedo, Christoph Stiller. Fleet Weather Map - A Project to Integrate Fleet Data into the Field of Automated Driving. In 2019 Joined Conference and Exhibition of Transportation Association Canada and Intelligent Transportation Systems Canada (TAC-ITSC), September 2019. Web PDF

• In-Hyuk Kwon, Ph.D.; Stephen English; William Bell; Roland Potthast; Andrew Collard; Benjamin Ruston: Assessment of Progress and Status of Data Assimilation in NWP, BAMS. Accepted. Web PDF

• Jason A Otkin; Roland Potthast; Amos Lawless: Nonlinear Bias Correction for Satellite Data Assimilation Using Taylor Series Polynomials MWR-D-17-0171, Monthly Weather Review, accepted. PDF

• Armin Geisinger, Andreas Behrendt, Volker Wulfmeyer, Jens Strohbach, Jochen Förstner, and Roland Potthast: Development and Application of a Backscatter Lidar Forward Operator for Quantitative Validation of Aerosol Dispersion Models and Future Data Assimilation, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-142, 2017, Revised manuscript accepted for AMT. Previously discussion paper: http://www.atmos-chem-phys-discuss.net/acp-2016-609/

• Aamir Nadeem, Roland Potthast and Andreas Rhodin: On Sequential Multiscale Inversion and Data Assimilation, Journal of Computational and Applied Mathematics (CAM), accepted. PDF

• T. Janjic, N. Bormann, M. Bocquet, J. A. Carton, S. N. Losa,S. L. Dance, N. K. Nichols, J. A. Waller, P. Weston, R. Potthast, S. E. Cohn: On the representation error, QJRMS accepted. Online PDF

• Gen Nakamura and Roland Potthast: Inverse Modeling - An introduction to the theory and methods of inverse problems and data assimilation, IOP Ebook Series 2015, 550 pages, 200 images, 170 codes. Web

• Annika Schomburg, Christoph Schraff and Roland Potthast: A concept for the assimilation of cloud information in a Local Ensemble Transform Kalman Filter at the convective scale, QJRMS Volume 141, Issue 688, pages 893–908, April 2015 Part A. Web

• Freitag, M. and Potthast, R.: Synergy of Inverse Problems and Data Assimilation Techniques, in “Large Scale Inverse Problems - Computational Methods and Applications in the Earth Sciences”, Radon Series on Computational and Applied Mathematics 13, Hrsg. v. Cullen, Mike / Freitag, Melina A / Kindermann, Stefan / Scheichl, Robert Contents, PDF

• Fatih Yaman, Valery G. Yakhno and Roland Potthast: A Survey on Inverse Problems for Applied Sciences, Mathematical Problems in Engineering, Mathematical Methods in Engineering, PDF

• N.L.H. Lowery, M.M. Vahdati, R.W.E. Potthast, W. Holderbaum: Classification and Fault Detection Methods for Fuel Cell Monitoring and Quality Control, J. Fuel Cell Sci. Technol 10(2), 021002 (Mar 21, 2013) doi:10.1115/1.4023565 Web

• Potthast, R: Dynamic Inverse Scattering, in “Direct and Inverse Problems in Wave Propagation and Applications” (2013), Radon Series on Computational and Applied Mathematics 14:, Hrsg. v. Graham, Ivan / Langer, Ulrich / Melenk, Jens Markus / Sini, Mourad http://www.degruyter.com/view/product/182029

• Alexander J.F. Moodey, Amos S. Lawless, Roland W.E. Potthast, Peter Jan van Leeuwen: Nonlinear error dynamics for cycled data assimilation methods, Inverse Problems 29 Vol 2 (2013) 025002 doi:10.1088/0266-5611/29/2/025002

• Stephane Hallegatte, World Bank; John Eyre, Met Office (UK); Tony McNally, ECMWF; Roland Potthast, DWD; Robert Husband, MSYS Ltd.: The case for THE EUMETSAT POLAR SYSTEM (EPS) Metop Second-Generation PROGRAMME: cost benefit analysis, European Space Policy Institute (ESPI) Yearbook, Springer Verlag, 2013, buy or see online at Springer Book Website

• Potthast, R.: An Iterative Contractive Framework for Probe Methods (LASSO), Radio Science, Volume 46, Issue 5, October 2011 PDF

• beim Graben, P. & Potthast, R.: A dynamic field account to language-related brain potentials. In M. Rabinovich, K. Friston, & P. Varona (Eds.) Principles of Brain Dynamics: Global State Interactions, MIT Press: Cambridge (MA). Book on Amazon

• Potthast, R and beim Graben, P.: Dimensional reduction for the inverse problem of neural Field theory, Front. Comput. Neurosci., 08 October 2009, https://doi.org/10.3389/neuro.10.017.2009 Web

• Potthast, R. and beim Graben, P.: Inverse Problems in Neural Field Theory, SIAM J. Appl. Dyn. Syst., Vol. 8, No. 4 (2009), 1405-1433. Web

• Burkard, C. and Potthast, R.: A Time-Domain Probe Method for Three-dimensional Rough Surface Reconstructions, Inverse Problems and Imaging, Volume 3, No. 2 (2009) 259274. Web

• Beim Graben, P. and Potthast, R.: Inverse Problems in Dynamic Cognitive Modeling, CHAOS 19, 015103 (2009). Web

• Potthast, R. and Wannert, M.: Uniqueness of Current Reconstructions for Magnetic Tomography in Multi-Layer Devices, SIAM J. Appl. Math. Volume 70, Issue 2, pp. 563- 578 (2009).

• Liu, Jijun and Potthast, Roland: On the duality of the potential method and the point source method in inverse scattering problems, J. Int. Eq. Appl, Vol.21, No.2, (2009) doi:10.1216/JIE-2009-21-2-1. Web

See also: J. Integral Equations Applications, Volume 21, Number 2 (2009), 149-151. Special issue dedicated to Rainer Kress Web

• Ben Hassen, F., Liu, J. and Potthast, R.: On Source Analysis by Wave Splitting with Applications in Inverse Scattering of Multiple Obstacles, J. Comput. Math. 25 (2007), no. 3, 266–281.

• Eckel, H. and Potthast, R.: An evolutionary Newton method for shape reconstruction, J. Integral Equations and Applications, Vol 19, No 3 (2007) 261-288. Web

• Potthast, R. and Schulz, J.: A multi-wave range test for obstacle reconstructions with unknown physical properties, J. Comput. Appl. Math. 205 (2007), no. 1, 53–71.

• Honda, N., Nakamura, R., Potthast, R. and Sini, M.: The no-response approach and its relation to non-iterative methods in inverse scattering, Annali di Matematica Pura ed Applicata (2007) Web

• Potthast, R.: On the convergence of the no response test, SIAM J. Math. Anal. 38 (2007), no. 6, 1808–1824.

• Liu, J., Nakamura, G. and Potthast, R.: A new approach and improved error analysis for reconstructing the scattered wave by the point source method, Journal of Computational Mathematics, Vol.25, No.2, 2007, pp113-130.

• Hauer, K.-H., Potthast, R., Stolton, D. and Wüster, T.: Magnetotomography - A New Method for Analysing Fuel Cell Performance and Quality. Journal of Power Sources 143 (2005), 67-74.

• Hauer, K.-H., Kühn, L. and Potthast, R.: On uniqueness and non-uniqueness for current reconstruction from magnetic fields, Inverse Problems 21 (2005) 1-13.

• Potthast, R.: Sampling and Probe Methods - An Algorithmical View, Computing 75 (2005) 215-236.

• Potthast, R. and Stratis, I.: The singular sources method for an inverse transmission problem, Computing 75 (2005), 237-255.

• Luke, D.R. and Potthast, R.: The no response test - a sampling method for inverse scattering problems. SIAM Journal of Applied Math No.4, Vol. 63 (2003), 1292–1312. Web

• Erhard, K. and Potthast, R.: Reconstructing an inclusion from boundary measurements in electrical impedance tomography and acoustic scattering. Inverse Problems, 19 (2003), 1139-1157.

• Potthast, R., Kusaik, S. and Sylvester, R.: A 'range test' for determining scatterers with unknown physical properties. Inverse Problems 19, 533-547 (2003). Web

• Potthast, R. and Stratis, I.: On the domain derivative for scattering by impenetrable obstacles in chiral media. IMA J. Appl. Math., 68 (2003) 621 - 635.

• Kühn, L. and Potthast, R.: On the convergence of the finite integration technique for the anisotropic boundary value problem of magnetic tomography Math. Meth. Appl. Sciences 26 (2003), 739-757.

• Potthast, R.: On the Convergence of Newton's Method in Inverse Scattering, Inverse Problems 17, 1419-1434 (2001).

• Potthast, R.: Point-sources and Multipoles in Inverse Scattering, Chapman & Hall, London 2001. Book on Web

• Colton, D. and Potthast, R.: The inverse electromagnetic scattering problem for an anisotropic medium, Q. J. Appl. Math 52 (3) (1999) 349-372

• Potthast, R.: Electromagnetic scattering from an orthotropic medium. Journal of Integral Equations and Applications 11 No. 2 (1999) 197-215. Web

• “Point-sources and Multipoles in Inverse Scattering”, Habilitation Thesis, University of Göttingen 1999. Book on Web

• Colton, D., Piana, M. and Potthast, R.: A simple method using Morozov's discrepancy principle for solving inverse scattering problems, Inverse Problems 13 (1997) 1477-1493.

• Potthast, R.: Fréchet differentiability of boundary integral operators in inverse acoustic scattering, Inverse Problems 10 (1994), 431-447. Web

• Potthast, R.: Fréchet Differenzierbarkeit von Randintegraloperatoren und Randwertproblemen zur Helmholtzgleichung und den zeithharmonischen Maxwellgleichungen, PHD-Thesis, Göttingen November 1994 (in German) PDF

• Potthast R., Fazi F.M., Nelson P.A. and Seo J.: Two Sound Field Reconstruction Techniques Based on Integral Equations, Hands-Free Speech Communication and Microphone Arrays, Trento, Italy, 2008.
• Burkard, C. and Potthast, R.: Field and Surface Reconstructions for 3d Rough Surface Problems, Institute of Acoustics Spring Conference Reading, UK, 2008.
• Potthast, R.: Acoustic Tomography by Orthogonality Sampling, Institute of Acoustics Spring Conference, Reading, UK 2008.
• Fazi F.M., Nelson P.A., Potthast R. and Seo J.: The Study of Sound Field Reconstruction as an Inverse Problem, Institute of Acoustics Spring Conference, Reading, UK 2008.
• Hauer, K.H. and Potthast, R.: Magnetic Tomography for Fuel Cells - Current Status and Problems. Proceedings of the international conference on inverse problems, Sapporo, Japan 2006.
• Nakamura G., Potthast R. and Sini M.: A comparative study between some non-iterative methods for inverse scattering. In {\em Inverse Problems, Multi-Scale Analysis and Homogenization.} Proceedings of the Workshop in Seoul, June 2005. Contemporary Mathematics Volume, AMS (Edition by H. Ammari and H. Kang), 2006.
• Nakamura, R., Potthast, R. and Sini, M.: The convergence of the no response test for localizing and inclusion. The 5th International Conference on Inverse Problems in Engineering - Theory and Practice, Oxford, UK 2005.
• Potthast, R. and Schulz, J.: From the Kirsch-Kress method via the range test to the singular sources method. The 2nd International Conference on Inverse Problems, Shanghai, China 2004.
• Erhard, K. and Potthast, R.: On Masking Operations for the Point-Source Method solving Inverse Boundary Value Problems. The Sixth International Conference on Mathematical and Numerical Aspects of Wave Propagation, Jyväskylä, Finland, June 30 - July 4, 2003.
• Luke, D.R. and Potthast, R.: The point source method in acoustic scattering: numerical reconstruction of the scattered field from far field measurements of inhomogeneous media., Int. Conf. on Acoustics, Speech and Signal Processing, Orlando, Florida, May 13-17, 2002.
• Potthast, R.: A Newton method for inverse scattering by a rough surface. European Symposium on Numerical Methods in Electrodynamics, Toulouse, March 2002.
• Akduman, I. and Potthast, R.: On the reconstruction of buried objects from surface measurements of electromagnetic fields., European Symposium on Numericl Methods in Electrodynamics, Toulouse 2002.
• Potthast, R.: On the Convergence of Newton's Method in Inverse Scattering. 5th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Technoloy, Corfu, Greece, October 18-19, 2001.
• Potthast, R.: Uniqueness and stability in inverse acoustic scattering for finite data with limited aperture. in {\em Inverse Problems and Experimental Design in Thermal and Mechanical Engineering} Petit, Ingham, Jarny and Plourde (Eds.) March 5-7, 2001, Poitiers, France.
• Potthast, R.: A point-source method in inverse electromagnetic scattering.“ Proceedings of the Fourth International Conference on Mathematical and Numerical Aspects of Wave Propagation, June 1-5, 1998, at Colorado School of Mines, Golden, Colorado.
• Potthast, R.: A point-source method in inverse acoustic scattering.” Proceedings of the International Symposium on Inverse Problems in Engineering Mechanics ISIP'98, March 23-28, 1998, Nagano, Japan.
• Potthast, R.: A fast new method in inverse scattering. “ Proceedings of the Conference on Inverse Problems in Engineering: Theory and Practice, held June 9-14, 1996 in Le Croisic, France
• Potthast, R.: On two new methods in inverse scattering. ” Proceedings of the Conference on Inverse Problems: Geophysical Applications, held Dec 1995 in Fish Camp, Yosemite, California