Apreda, C., J.-P. Schulz, A. Reder and P. Mercogliano.

Survey of land cover datasets for updating the imperviousness field in urban parameterisation scheme TERRA_URB for climate and weather applications. (info)

Urban Climate, 49, 101535.

Shuvalova, J.; Chubarova,N.; Shatunova, M.

Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow. (info)

Atmosphere 2022, 13, 1710.

Muskatel, H.B., Blahak, U., Khain, P., Levi, Y., Fu, Q.

Parametrizations of Liquid and Ice Clouds’ Optical Properties in Operational Numerical Weather Prediction Models. (info).

Atmosphere, 12, 89 (2021)

Gastaldo, T, Poli, V, Marsigli, C, Cesari, D, Alberoni, PP, Paccagnella, T.

Assimilation of radar reflectivity volumes in a pre‐operational framework. (info)

Q J R Meteorol Soc. 2021; 1– 24.

Garbero, V.; Milelli, M.; Bucchignani, E.; Mercogliano, P.; Varentsov, M.; Rozinkina, I.; Rivin, G.; Blinov, D.; Wouters, H.; Schulz, J.-P.; Schättler, U.; Bassani, F.; Demuzere, M.; Repola, F.

Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities. (info)

Atmosphere 2021, 12, 237. https://doi.org/10.3390/atmos12020237

Zeng Y, de Lozar A, Janjic T, Seifert A. 2021.

Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation.

Geosci. Model Dev. 14, 1295-1307, doi: 10.5194/gmd-14-1295-2021.

Zeng Y, Janjic T, de Lozar A, Welzbacher CA, Blahak U, Seifert A. 2021.

Assimilating radar radial wind and reflectivity data in an idealized setup of the COSMO-KENDA system

Atmos. Res. 249: 105282, doi: 10.1016/j.atmosres.2020.105282.

Zeng Y, Janjic T, Feng Y, Blahak U, de Lozar A, Bauernschubert E, Stephan K, Min J. 2021.

Interpreting estimated Observation Error Statistics of Weather Radar Measurements using the ICON-LAM-KENDA System.

Atmps.Measure. Tech., doi: 10.5194/amt-2021-95.

Machulskaya, E., D.V. Mironov (2020):

The stability functions and realizability of the Turbulent Kinetic Energy-Scalar Variance closure for moist atmospheric boundary-layer turbulence. (info)

Boundary-Layer Meteorol., 176, 197-228, doi: 10.1007/s10546-020-00528-7

Garbero, V., Milelli, M. (2020):

Reforecast of the November 1994 flood in Piedmont using ERA5 and COSMO model: an operational point of view. (info)

Bull. of Atmos. Sci. & Technol. 1, 339–354 (2020).

Hartmann, E., J-P. Schulz, R. Seibert, M. Schmidt, M. Zhang, J. Luterbacher and M.H. Tölle, (2020):

Impact of environmental conditions on grass phenology in the regional climate model COSMO-CLM. (info)

Atmosphere, 11, 1364.

Schulz, J.-P. and G. Vogel (2020):

Improving the processes in the land surface scheme TERRA: Bare soil evaporation and skin temperature (info).

Atmosphere, 11, 513

Hutt A, Schraff C, Anlauf H, Bach L, et al. 2020.

Assimilation of SEVIRI water vapor channels with an Ensemble Kalman Filter on the convective scale.

Front. Earth Sci. 8:70, doi: 10.3389/feart.2020.00070.

Ruckstuhl Y, Janjić T. 2020.

Combined State-Parameter Estimation with the LETKF for Convective-Scale Weather Forecasting

Mon.Wea. Rev. 148: 1607-1628, doi: 10.1175/MWR-D-19-0233.1.

Scheck L, Weissmann M, Bach L. 2020.

Assimilating visible satellite images for convective-scale numerical weather prediction: A case study

Q. J. R. Meteorol. Soc. 146: 3165-3186, doi: 10.1002/qj.3840.

Schroettle J, Weissmann M, Scheck L, Hutt A. 2020.

Assimilating visible and thermal radiances in idealized simulations of deep convection

Mon.Wea. Rev. 148: 4357-4375, doi: https://doi.org/10.1175/MWR-D-20-0002.1.

Sgoff C, Schomburg A, Schmidli J, Potthast R. 2020.

Assimilating synthetic land surface temperature in a coupled land-atmosphere model

Q. J. R. Meteorol. Soc. 146: 3980-3997, doi:10.1002/qj.3883.

Zeng Y, Janjic T, de Lozar A, Rasp S, Blahak U, Seifert A, Craig GC. 2020.

Comparison of methods accounting for subgrid-scale model error in convective-scale data assimilation

Mon. Wea. Rev. 148: 2457-2477, doi: 10.1175/MWR-D-19-0064.1.

Steger, C. and Bucchignani, E.

Regional Climate Modelling with COSMO-CLM: History and Perspectives (info).

Atmosphere, 11, 1250, 2020.

Baldauf, M. (2019):

Local time stepping for a mass-consistent and time-split advection scheme (info)

Quart. J. Roy. Met. Soc., DOI: 10.1002/qj.3434

Bachmann K, Keil C, Weissmann M. 2019.

Impact of radar data assimilation and orography on predictability of deep convection

Q. J. R. Meteorol. Soc. 145: 117-130, doi: 10.1002/qj.3412.

Otkin JA, Potthast R. 2019.

Assimilation of all-sky SEVIRI infrared brightness temperatures in a regional-scale ensemble data assmilation system

Mon.Wea. Rev. 147: 4481-4509, doi: 10.1175/MWR-D-19-0133.1

Potthast R, Walter A, Rhodin A. 2019.

A Localized Adaptive Particle Filter within an Operational NWP Framework

Mon.Wea. Rev. 147: 345-362, doi: 10.1175/MWR-D-18-0028.1.

Waller JA, Bauernschubert E, Dance SL, Nichols NK, Potthast R, Simonin D. 2019.

Observation error statistics for Doppler radar radial wind superobservations assimilated into the DWD COSMO-KENDA system

Mon.Wea. Rev. 147: 3351-3364, doi:10.1175/MWR-D-19-0104.1.

Zeng, Y., Janjic, T., Sommer, M., de Lozar, A., Blahak, U., and Seifert, A. 2019.

Representation of model error in convective-scale data assimilation: additive noise based on model truncation error

J. Adv. Mod. Earth Syst. 11: 752–770. doi: 10.1029/2018MS001546

Schulthess, T. C., P. Bauer, O. Fuhrer, T. Hoefler, C. Schar and N. Wedi (2018):

Reflecting on the goal and baseline for exascale computing: a roadmap based on weather and climate simulations (info).

Computing in Science & Engineering vol. 21, issue 1.

Goger, B., M. W. Rotach, A. Gohm, O. Fuhrer, I. Stiperski, and A. A. M. Holtslag (2018):

The impact of three-dimensional effects on the simulation of turbulence kinetic energy in a major alpine valley (info).

Boundary-Layer Meteorol, 168 (1), 1-27.

Sikoparija B., Mimic G., Panic M., Mark, O., Radisic P.,Pejak-Sikoparija T., Pauling A. (2018):

High temporal resolution of airborne Ambrosia pollen measurements above the source reveals emission characteristics (info).

Atmospheric Environment 192, 13-23.

Schulthess, T. C., P. Bauer, O. Fuhrer, T. Hoefler, Ch. Schär, N. Wedi (2018):

Reflecting on the goal and baseline for "Exascale Computing": a roadmap based on weather and climate simulations.

Submitted to IEEE Computing in Science & Engineering

Avgoustoglou Euripides, Jean-Marie Bettems, Antigoni Voudouri, Itzhak Carmona, Pavel Khain, Federico Grazzini, Pirmin Kaufmann (2018):

Optimization of high resolution COSMO model performance over Switzerland and Northern Italy (info).

Atmos. Res., 213, 70-85.

Horat Christoph, Manuel Antonetti, Katharina Liechti, Pirmin Kaufmann, Massimiliano Zappa (2018):

Ensemble flood forecasting considering dominant runoff processes: II. Benchmark against a state-of-the-art model-chain (Verzasca, Switzerland) (info).

Nat. Hazards Earth Syst. Sci. Discuss., in review

Shrestha, P., W. Kurtz, G. Vogel, J.‐P. Schulz, M. Sulis, H.‐J. Hendricks Franssen, S. Kollet and C. Simmer, (2018):

Connection Between Root Zone Soil Moisture and Surface Energy Flux Partitioning Using Modeling, Observations, and Data Assimilation for a Temperate Grassland Site in Germany (info).

Journal of Geophysical Research: Biogeosciences, 123, 2839-2862. doi:10.1029/2016JG003753

Chubarova N., Poliukhov A., Shatunova M., Rivin G., Becker R., Kinne S. (2018):

Clear-Sky Radiative and Temperature Effects of Different Aerosol Climatologies in the COSMO Model (info).

Geography, Environment, Sustainability, 2018;11(1):74-84. Doi:10.24057/2071-9388-2018-11-1-74-84.

Klasa, C., Arpagaus M., Walser A. and Wernli H., (2018):

An evaluation of the convection-permitting ensemble COSMO-E for three contrasting precipitation events in Switzerland (info).

Quart. J. Roy. Meteorol. Soc., 144, 744-764, doi:10.1002/qj.3245

Klasa, C., Arpagaus M., Walser A. and Wernli H., (2018):

On the time evolution of limited-area ensemble variance: Case studies with the convection-permitting ensemble COSMO-E (info).

J. Atmos. Sci. doi:10.1175/JAS-D-18-0013.1, in press.

Machulskaya, E., and D. Mironov (2018):

Boundary conditions for scalar (co)variances over heterogeneous surfaces (info).

Boundary-Layer Meteorol. 169, 139-150. doi: 10.1007/s10546-018-0354-6

Duniec, G. and Mazur, A. (2018):

Influence of parameterization of soil processes on numerical forecasts of vertical profiles of air potential temperature (info).

Meteorol. Appl. 25: 350-356. DOI: 10.1002/met.1701

Kunz, Blahak, et al. (2018):

The severe hailstorm in southwest Germany on 28 July 2013: characteristics, impacts and meteorological conditions (info).

Quarterly Journal of the Royal Meteorological Society, 21 February 2018, doi:10.1002/qj.3197

Voudouri A., Khain P., Carmona I., Avgoustoglou E., Kaufmann P., Grazzini F., and Bettems J.M (2018):

Optimization of high resolution COSMO model performance over Switzerland and Northern Italy (info).

Atm. Res. 213, 70-85, doi: 10.1016/j.atmosres.2018.05.026

Gastaldo T, Poli V, Marsigli C1, Alberoni PP, Paccagnella T. 2018.

Data assimilation of radar reflectivity volumes in a LETKF scheme

Nonlin. Proc. Geophys., 25, 747-764, doi:10.5194/npg-25-747-2018

Gustafsson N, Janjic T, Schraff C, Leuenberger D, Weissmann M, Reich H, Brousseau P, Montmerle T, Wattrelot E, Bucanek A, Mile M, Hamdi R, Lindskog M, Barkmeijer J, Dahlbom M, Macpherson B, Ballard S, Inverarity G, Carley J, Alexander C, Dowell D, Liu S, Ikuta Y, Fujita T. 2018.

Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres

Q. J. R. Meteorol. Soc. 144, 1218-1256, doi: 10.1002/qj.3179.

Necker T, Weissmann M, Sommer M. 2018.

The importance of appropriate verification metrics for the assessment of observation impact in a convection-permitting modelling system

Q. J. R. Meteor. Soc. 144: 1667–1680, doi: 10.1002/qj.3390.

Otkin JA, Potthast R, Lawless A. 2018.

Nonlinear Bias Correction for Satellite Data Assimilation Using Taylor Series Polynomials

Mon.Wea. Rev. 146: 263-285, doi: 10.1175/MWR-D-17-0171.1.

Robert S, Leuenberger D, Kuensch HR. 2018.

A local ensemble transform Kalman particle filter for convective-scale data assimilation

Q. J. R. Meteorol. Soc., 144: 1279-1296, doi:10.1002/qj.3116.

Zeng Y, Janjić T, de Lozar A, Blahak U, Reich H, Keil C, Seifert A. 2018.

Representation of model error in convective-scale data assimilation: additive noise, relaxation methods and combinations

J. Adv. Model. Earth Syst., 10 (2018), pp. 2889-2911, doi: 10.1029/2018MS001375.

Avgoustoglou E., A. Voudouri, P. Khain, F. Grazzini and J.M. Bettems (2017):

Design and Evaluation of Sensitivity Tests of COSMO Model Over the Mediterranean Area. (info)

Perspectives on Atmospheric Sciences, Vol1, Springer, pp49-55, doi :10.1007/978-3-319-35095-0

Voudouri A., Avgoustoglou E. and Kaufmann P (2017):

Impacts of Observational Data Assimilation on Operational Forecasts (info)

Perspectives on Atmospheric Sciences, Vol.1, Springer, pp 143-150, doi :10.1007/978-3-319-35095-0

Duniec G., Interewicz W., Mazur A. and Wyszogrodzki A., (2017):

Operational setup of the soil-perturbed, time-lagged Ensemble Prediction System at the Institute of Meteorology and Water Management - National Research Institute. (info)

Meteorol. Hydrol. Water Management, 5(2): 43-51, doi: 10.26491/mhwm/71048.

Keuler, K., Radtke, K., Kotlarski, S., and Lüthi, D.

Regional climate change over Europe in COSMO-CLM: Influence of emission scenario and driving global model (info).

Meteorol. Z., 25, 121–136, 2016.

Baldauf, M. and S. Brdar (2016):

3D diffusion in terrain-following coordinates: testing and stability of horizontally explicit, vertically implicit discretizations

Quart. J. Royal Met. Soc., 142, 2087-2101

Nuissier, O., Marsigli, C., Vincendon, B., Hally, A., Bouttier, F., Montani, A. and Paccagnella, T., 2016:

Evaluation of two convection-permitting ensemble systems in the HyMeX Special Observation Period (SOP1) framework.

Q.J.R. Meteorol. Soc., 142: 404–418. doi:10.1002/qj.2859

Davin, E.L., E. Maisonnave and S.I. Seneviratne (2016):

Is land surface processes representation a possible weak link in current Regional Climate Models?

Environmental Research Letters, 11(7), doi :10.1088/1748-9326/11/7/074027

Hendrik Wouters, Matthias Demuzere, Ulrich Blahak, Krzysztof Fortuniak, Bino Maiheu, Johan Camps, Daniël Tielemans and Nicole P. M. van Lipzig (2016):

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer (read)

Geosci. Model Dev., 9, 3027–3054, 2016, doi:10.5194/gmd-9-3027-2016

Grzegorz Duniec and Andrzej Mazur (2016):

Influence of parameterization of soil processes on meteorological forecasts of vertical profiles.

Ecol Chem Eng S. 2016; 23(3):493-503 DOI: 10.1515/eces-2016-0036

Schulz, J.-P., G. Vogel, C. Becker, S. Kothe, U. Rummel and B. Ahrens (2016):

Evaluation of the ground heat flux simulated by a multi-layer land surface scheme using high-quality observations at grass land and bare soil (info).

Meteorol. Z., 25, 607–620, 2016.

Smiatek, G., J. Helmert and E.-M. Gerstner (2016):

Impact of land use and soil data specifications on COSMO-CLM simulations in the CORDEX-MED area.

Meteor. Z., 25, 215-230, doi: 10.1127/metz/2015/0594

Kurowski M.J., Wojcik D.K., Ziemianski M.Z., Rosa, B., Piotrowski Z.P.:

Convection-Permitting Regional Weather Modeling with COSMO-EULAG: Compressible and Anelastic Solutions for a Typical Westerly Flow over the Alps.

Monthly Weather Review, 2016, Vol. 144, pp. 1961-1982, DOI 10.1175/MWR-D-15-0264.1

Mironov, D. V., and P. P. Sullivan (2016):

Second-moment budgets and mixing intensity in the stably stratified atmospheric boundary layer over thermally heterogeneous surfaces.

J.Atmos.Sci. 73, 449-464. doi: 10.1175/JAS-D-15-0075.1

Heinze, R., D. Mironov, and S. Raasch (2016):

Analysis of pressure-strain and pressure gradient-scalar covariances in cloud-topped boundary layers: A large-eddy simulation study.

J.Adv.Model.Earth Syst. 8, 3-30. doi: 10.1002/2015MS000508

Sullivan, P. P., J. C. Weil, E. G. Patton, H. J. J. Jonker, and D. V. Mironov, (2016):

Turbulent winds and temperature fronts in large-eddy simulations of the stable atmospheric boundary layer.

J.Atmos.Sci. 73, 1815-1840. doi: 10.1175/JAS-D-15-0339.1

Bach L, Schraff C, Keller JD, Hense A. 2016.

Towards a probabilistic regional reanalysis system for Europe: Evaluation of precipitation from experiments

Tellus A, 68, 32209, doi:10.3402/tellusa.v68.32209.

Bick T, Simmer C, Trömel S, Wapler K, Hendricks Franssen HJ, Stephan K, Blahak U, Schraff C, Reich H, Zeng Y, Potthast R. 2016.

Assimilation of 3D radar reflectivities with an ensemble Kalman filter on the convective scale

Q. J. R. Meteorol. Soc., 142, 1490-1504, doi:10.1002/qj.2751.

Harnisch F, Weissmann M, Periáñez A. 2016.

Error model for the assimilation of cloud-affected infrared satellite observations in an ensemble data assimilation system

Q. J. R. Meteorol. Soc., 142: 1797-1808, doi:10.1002/qj.2776.

Lange H, Janjic T. 2016.

Assimilation of Mode-S EHS aircraft observations in COSMO-KENDA

Mon. Weather Rev. 144: 1697-1711, doi:http://dx.doi.org/10.1175/MWR-D-15-0112.1.

Schraff C, Reich H, Rhodin A, Schomburg A, Stephan K, Periáñez A, Potthast R. 2016.

Kilometre-scale ensemble data assimilation for the COSMO model (KENDA)

Q. J. R. Meteorol. Soc., 142: 1453-1472, doi:10.1002/qj.2748.

Sommer M, Weissmann M. 2016.

Ensemble-based approximation of observation impact using an observation-based verification metric

Tellus A, 68, 27885, doi:10.3402/tellusa.v68.27885.

Zeng Y, Blahak U, Jerger D. 2016.

An efficient modular volume scanning radar forward operator for NWP-models: Description and coupling to the COSMO-model

Q. J. R. Meteorol. Soc., doi:10.1002/qj.2904.

Grzegorz Duniec and Andrzej Mazur (2015):

Modified description of soil processes vs. quality of numerical weather forecasts-"bare soil" case.

Ecol Chem Eng S. 2015; 22(4):659-673, DOI: 10.1515/eces-2015-0040

Shrestha, P., A. P. Dimri, A. Schomburg and C. Simmer (2015):

Improved understanding of an extreme rainfall event at the Himalayan foothills-a case study using COSMO.

Tellus A, 67, 26031 doi:10.3402/tellusa.v67.26031

Murav’ev A.V., Kiktev D.B., Bundel’ A.Y., Dmitrieva T.G., Smirnov A.V.:

Verification of High-Impact Weather Event Forecasts for the Region of the Sochi-2014 Olympic Games:
Part I: Deterministic Forecasts during the Test Period

Russian Meteorology and Hydrology. 2015. Vol. 40, No. 9. pp. 584-597, DOI 10.3103/S1068373915090034

M. V. Shatunova, G. S. Rivin, and I. A. Rozinkina:

Visibility Forecasting for February 16–18, 2014 for the Region of the Sochi-2014 Olympic Games Using the High-resolution COSMO-Ru1 Model.

Russian Meteorology and Hydrology, 2015, Vol. 40, No. 8, pp. 523–530. Ó Allerton Press, Inc., 2015, doi: 10.3103/S106837391508004X

Rivin G.S., Rozinkina I.A., Vil’fand R.M., Alferov D.Y., Astakhova E.D., Blinov D.V., Bundel’ A.Y., Kazakova E.V., Kirsanov A.A., Nikitin M.A., Perov V.L., Surkova G.V., Revokatova A.P., Shatunova M.V., Chumakov M.M.:

The COSMO-Ru System of Nonhydrostatic Mesoscale Short-Range Weather Forecasting of the Hydrometcenter of Russia: The Second Stage of Implementation and Development

Russian Meteorology and Hydrology. 2015. Vol. 40, No.6, pp. 400-410, DOI 10.3103/S1068373915060060

Kazakova E.V., Chumakov M.M., Rozinkina I.A.:

The System for Computing Snow Cover Parameters for Forming Initial Fields for Numerical Weather Prediction Based on the COSMO-Ru Model

Russian Meteorology and Hydrology. 2015. Vol. 40.No. 5, pp. 296-304, DOI 10.3103/S1068373915050027

Heinze, R., D. Mironov, and S. Raasch (2015):

Second-moment budgets in cloud topped boundary layers): A large-eddy simulation study.

J.Adv.Model.Earth Syst. 07, 510-536. doi: 10.1002/2014MS000376

Bollmeyer C, Keller JD, Ohlwein C, Wahl S, Crewell S, Friederichs P, Hense A, Keune J, Kneifel S, Pscheidt I, Redl S, Steinke S. 2015.

Towards a high-resolution regional reanalysis for the european CORDEX domain

Q. J. R. Meteorol. Soc. 141(686): 1-15, doi:10.1002/qj.2486.

Harnisch F, Keil C. 2015.

Initial conditions for convective-scale ensemble forecasting provided by ensemble data assimilation

Mon.Wea. Rev. 143: 1583-1600, doi:10.1175/MWR-D-14-00209.1.

Kazakova EV, Chumakov MM, Rozinkina IA. 2015.

The system for computing snow cover parameters for forming initial fields for numerical weather prediction based on the COSMO-Ru model.

Russian Meteorol. Hydrol. 40(5): 296--304, doi:10.3103/S1068373915050027.

Schomburg A, Schraff C, Potthast R. 2015.

A concept for the assimilation of satellite cloud information in an ensemble Kalman filter: Single-observation experiments

Q. J. R. Meteorol. Soc. 141: 893-908, doi:10.1002/qj.2407.

Marsigli, C., Montani A. and Paccagnella, T., 2014:

Provision of boundary conditions to a convection-permitting ensemble: comparison of two different approaches.

Nonlinear Processes in Geophysics, 21, 393–403.

Marsigli C., Montani A., Paccagnella T., 2014:

Perturbation of initial and boundary conditions for a limited-area ensemble: multi-model versus single-model approach.

Quarterly Journal of the Royal Meteorological Society, 140: 197–208.

Shrestha, P., M. Sulis, M. Masbou, S. Kollet and C. Simmer (2014):

A scale-consistent terrestrial systems modeling platform based on COSMO, CLM, and Parflow.

MWR, 142(9), 3466-3483 doi:10.1175/MWR-D-14-00029.1

Fuhrer, O., Osuna, C., Lapillonne, X., Gysi, T., Cumming, B., Bianco, M., ... & Schulthess, T.C.

Towards a performance portable, architecture agnostic implementation strategy for weather and climate models.

Supercomputing frontiers and innovations, 1(1), 45-62.

Lapillonne, X., & Fuhrer, O.:

Using compiler directives to port large scientific applications to GPUs: An example from atmospheric science.

Parallel Processing Letters, 24(01), 1450003.

Collaud Coen, M., Praz, C., Haefele, A., Ruffieux, D., Kaufmann, P., and Calpini, B.:

Determination and climatology of the planetary boundary layer height above the Swiss plateau by in situ and remote sensing measurements as well as by the COSMO-2 model

Atmos. Chem. Phys., 14, 13205-13221, doi: 10.5194/acp-14-13205-2014.

G.Surkova, D.Blinov, A.Kirsanov, A.Revokatova, G.Rivin:

Simulation of spread of air pollution plumes from forest fires with the use of COSMO-Ru7-ART chemical-transport model

Atmospheric and Oceanic Optics, 2014, Vol. 27, N 3, p. 268–274. DOI 10.1134/S1024856014030105

Schuster, D., S. Brdar, M. Baldauf, A. Dedner, R. Klöfkorn, and D. Kröner:

On discontinuous Galerkin approach for atmospheric flow in the mesoscale with and without moisture.

Meteorol. Z., 23(4), p. 449-464

Yano, J.-I., J.-F. Geleyn, M. Köhler, D. Mironov, J. Quaas, P. M. M. Soares, V. T. J. Phillips, R. S. Plant, A. Deluca, P. Marquet, L. Stulic, and Z. Fuchs (2014):

Basic concepts for convection parameterization in weather forecast and climate models): COST Action ES0905 final report.

Atmosphere 6, 88-147. doi: 10.3390/atmos6010088

Kostka PM, Weissmann M, Buras R, Mayer B, Stiller O. 2014.

Observation operator for visible and near-infrared satellite reflectances. J.

Atmps.Oceanic Technol. 31: 1216-1233, doi:10.1175/JTECH-D-13-00116.1.

Lange H, Craig GC. 2014.

The impact of data assimilation length scales on analysis and prediction of convective storms

Mon.Weather Rev. 142: 3781-3808, doi:10.1175/MWR-D-13-00304.1.

Milan M, Schüttemeyer D, Bick T, Simmer C. 2014.

A sequential ensemble prediction system at convection-permitting scales. Meteorol.

Atmps.Phys. 123: 17-31, doi:10.1007/s00703-013-0291-3.

Periáñez A, Reich H, Potthast R. 2014.

Optimal localization for ensemble Kalman filter systems.

J. Meteorol. Soc. Jpn. 92: 585-597, doi:10.2151/jmsj.2014-605.

Sommer M, Weissmann M. 2014.

Observation impact in a convective-scale localized ensemble transform Kalman filter

Q. J. R. Meteorol. Soc. 140: 2672-2679, doi:10.1002/qj.2343.

Zink, K.; A.Pauling, M. W. Rotach, H. Vogel, P.Kaufmann, B.Clot:

A new parameterization of pollen emission in numerical weather prediction models.

Geosci. Model Dev., 6, 1961-1975, doi: 10.5194/gmd-6-1961-2013.

Murav'ev A.V., Bundel' A.Y., Kiktev D.B., Blinov D.V., Smirnov A.V.:

Verification of mesoscale forecasts in the 2014 Olympic games region for the first test period.
Part I: Verification techniques and polygonal quality assessments of the COSMO model forecasts

Russian Meteorology and Hydrology. 2013. Vol. 38, No.11, pp. 723-734, DOI 10.3103/S1068373913110010

Murav'ev A.V., Bundel' A.Y., Kiktev D.B., Smirnov A.V.:

Verification of Mesoscale Forecasts in the 2014 Olympic Games Region.
Part II: Preliminary Results of Diagnostic Evaluation of Quality and Calibration of the Forecasts by the COSMO-Ru2 Model

Russian Meteorology and Hydrology. 2013. Vol. 38, No 12, pp. 797-807, DOI 10.3103/S1068373913120017

Kiktev D.B., Astakhova E.D., Blinov D.V., Zaripov R.B., Murav'ev A.V., Rivin G.S., Rozinkina I.A., Smirnov A.V., Tsyrul'nikov M.D.:

Development of Forecasting Technologies for Meteorological Support of the Sochi-2014 Winter Olympic Games

Russian Meteorology and Hydrology. 2013. Vol 38. No. 10. pp. 653-660, DOI 10.3103/S1068373913100014

Blinov D.V., Perov V.L., Peskov B.E., Rivin G.S.:

Extreme bora of February 7—8, 2012, in the area of Novorossiysk and its forecast with the COSMO-Ru model

Journal “Vestnik MSU”, ser. 5, geography, N 4, 2013, p. 36 -43 (in Russian).

Baldauf, M. and S. Brdar:

An analytic solution for linear gravity waves in a channel as a test for numerical models using the non-hydrostatic, compressible Euler equations.

Quart. J. Royal Met. Soc., 139, p. 1977-1989

Craig GC, Würsch M. 2013.

The impact of localization and observation averaging for convective-scale data assimilation in a simple stochastic model

Q. J. R. Meteorol. Soc., 139: 515-523, doi:10.1002/qj.1980.

Mironov, D., B. Ritter, J.-P. Schulz, M. Buchhold, M. Lange, and E. Machulskaya, 2012

Parameterisation of sea and lake ice in numerical weather prediction models of the German Weather Service (info).

Tellus A, 64, 17330.

Revokatov A. P., Surkova G.V., Kirsanov A.A., Rivin G.S.:

Forecast of the atmosphere pollution in the Moscow region using the COSMO-Ru-ART model

Journal "Vestnik MSU", ser. 5, geography, N 4, 2012, p. 25 -33 (in Russian).

Wojcik, D., K. Kurowski, B. Rosa, and M. Ziemianski:

A study on parallel performance of the EULAG F90/95 code.

Lecture Notes in Computer Science, 7204, p. 419-427

Brdar, S., M. Baldauf, A. Dedner, and R. Klöfkorn:

Comparison of dynamical cores for NWP models: comparison of COSMO and DUNE.

Theor. Comput. Fluid Dyn., 27, p. 453-472

Mironov, D. V. (2012):

Turbulence and land-surface parameterizations for mesoscale models.

Proc.Croatian-USA Workshop on Mesometeorology Ekopark Kras Resort near Zagreb, Croatia, 5 pp.

de Rooy, W. C., P. Bechtold, K. Fr\"ohlich, C. Hohenegger, H. Jonker, D. Mironov, A. P. Siebesma, J. Teixeira, and J.-I. Yano (2012):

Entrainment and detrainment in cumulus convection: an overview.

Quart.J.Roy.Meteor.Soc. 139, 1-19. doi: 10.1002/qj.1959

Mironov, D. V., and P. P. Sullivan (2012):

Mixing in the SBL over temperature-heterogeneous surfaces: LES findings and some parameterisation ideas.

Proc.ECMWF Workshop on Diurnal Cycles and the Stable Boundary Layer European Centre for Medium-Range Weather Forecasts, Reading, UK, 149-151.

Craig GC, Keil C, Leuenberger D. 2012.

Constraints on the impact of radar rainfall data assimilation on forecasts of cumulus convection

Q. J. R. Meteorol. Soc. 138: 340-352, doi:10.1002/qj.929

Hans-Stefan Bauer et al.:

Predictive skill of a subset of models participating in D-PHASE in the COPS region. (more)

Quarterly Journal of the Royal Meteorological Society, 137, 287-305, doi: 10.1002/qj.715

Montani A. et al.:

Seven years of activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS system: main achievements and open challenges.

Tellus A, in print, doi: 10.1111/j.1600-0870.2010.00499.x

Gebhardt, C., Theis, S.E., Paulat, M., Ben Bouallègue, Z.:

Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries

Atmos. Res. , doi: 10.1016/j.atmosres.2010.12.008

Rosa, B., Kurowski M.J., Ziemianski M.Z.:

Testing the Anelastic Nonhydrostatic Model EULAG as a Prospective Dynamical Core of a Numerical Weather Prediction Model.
Part I: Dry Benchmarks.

Acta Geophysica, 2011, Vol. 59, pp. 1236-1266, DOI 10.2478/s11600-011-0041-1

Kurowski M.J., Rosa , B., Ziemianski M.Z.:

Testing the Anelastic Nonhydrostatic Model EULAG as a Prospective Dynamical Core of a Numerical Weather Prediction Model.
Part II: Simulations of Supercell.

Acta Geophysica, 2011, Vol. 59, pp. 1267-1293, DOI 10.2478/s11600-011-0051-z

Ziemianski M.Z., Kurowski M.J., Piotrowski Z.P., Rosa, B., Fuhrer, O.:

Toward Very High Horizontal Resolution NWP over the Alps : Influence of Increasing Model Resolution on the Flow Pattern.

Acta Geophysica, 2011, Vol. 59, pp. 1205-1235, DOI 10.2478/s11600-011-0054-9

Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.

Operational convective-scale numerical weather prediction with the COSMO model: Description and sensitivities (info).

Mon. Weather Rev., 139, 3887–3905, 2011.

Petrik, R., M. Baldauf, H. Schlünzen, and A. Gassmann:

Validation of a mesoscale weather prediction model using subdomain budgets.

Tellus A, 63, p. 707-726

Kirillin, G., J. Hochschild, D. Mironov, A. Terzhevik, S. Golosov, and G. Nutzmann (2011):

FLake-Global: Online lake model with worldwide coverage.

Environ.Modell.Softw. 26, 683-684. doi: 10.1016/j.envsoft.2010.12.004

Teixeira, J., S. Cardoso, M. Bonazzola, J. Cole, A. Delgenio, C. Demont, C. Franklin, C. Hannay, C. Jakob, Y. Jiao, J. Karlsson, H. Kitagawa, M. Koehler, A. Kuwano-Yoshida, C. Ledrian, A. Lock, M. J. Miller, P. Marquet, J. Martins, C. R. Mechoso, E. V. Meijgaard, I. Meinke, P. M. A. Miranda, D. Mironov, R. Neggers, H. L. Pan, D. A. Randall, P. J. Rasch, B. Rockel, W. B. Rossow, B. Ritter, A. P. Siebesma, P. Soares, F. J. Turk, P. Vaillancourt, A. Von Eengeln and M. Zhao (2011):

Tropical and subtropical cloud transitions in weather and climate prediction models): the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI).

J.Climate 24, 5223-5256. doi: 10.1175/2011JCLI3672.1

Gorin VE, Tsyrulnikov MD. 2011.

Estimation of multivariate observation-error statistics for AMSU-A data

Mon.Weather Rev. 139: 3765-3780, doi:10.1175/2011MWR3554.1.

Michael Baldauf:

Linear stability analysis of Runge-Kutta based partial time-splitting schemes for the Euler equations

Monthly Weather Review, 138, 4475-4496

M. Pfeifer, W. Yen, M. Baldauf, G. Craig, S. Crewell, A. Seifert et al:

Validating precipitation forecasts using remote sensor synergy: A case study approach

Meteorologische Zeitschrift, 19/6, 601-617

Tanja Weusthoff et al.:

Assessing the Benefits of Convection-Permitting Models by Neighborhood Verification: Examples from MAP D-PHASE. (more)

Monthly Weather Review, 138, 3418-3433, doi: 10.1175/2010MWR3380.1

M. Turco and M. Milelli:

The forecaster's added value in QPF. (more)

Adv. Geosci., 25, 29-36, 2010

D. Cane and M. Milelli:

Can a Multimodel SuperEnsemble technique be used for precipitation forecasts? (more)

Adv. Geosci., 25, 17-22, 2010

M. Milelli, M. Turco, and E. Oberto:

Screen-level non-GTS data assimilation in a limited-area mesoscale model. (more)

Nat. Hazards Earth Syst. Sci., 10, 1129-1149, 2010

D. Cane and M. Milelli:

Multimodel SuperEnsemble technique for quantitative precipitation forecasts in Piemonte region (more)

Nat. Hazards Earth Syst. Sci., 10, 265-273, 2010

Szintai, B., P. Kaufmann, and M. W. Rotach:

Simulation of pollutant transport in complex terrain with a NWP-particle dispersion model combination.

Boundary-Layer Meteorology, 137, 373-396.

Vil'fand R.M., Rivin G.S., Rozinkina I.A.:

COSMO-Ru System of Nonhydrostatic Mesoscale Short-Range Weather Forecast of the Hydrometcenter of Russia: The First Stage of Realization and Development

Russian Meteorology and Hydrology. 2010. Vol. 35, No. 8, pp. 503-514, DOI 10.3103/S1068373910080017

Vil'fand R.M., Rivin G.S., Rozinkina I.A.:

Mesoscale Weather ShortRange Forecasting at the Hydrometcenter of Russia, on the Example of COSMO-Ru

Russian Meteorology and Hydrology. 2010, Vol. 35, No1, pp. 1-9, DOI 10.3103/S1068373910010012

Mironov, D., E. Heise, E. Kourzeneva, B. Ritter, N. Schneider, and A. Terzhevik, 2010

Implementation of the lake parameterisation scheme FLake into the numerical weather prediction model COSMO (info).

Boreal Env. Res., 15, 218–230

Mironov, D., L. Rontu, E. Kourzeneva, and A. Terzhevik (2010):

Towards improved representation of lakes in numerical weather prediction and climate models: Introduction to the special issue of Boreal Environment Research.

Boreal Env.Res. 15, 97-99.

Mironov, D. V., and P. P. Sullivan (2010):

Effect of horizontal surface temperature heterogeneity on turbulent mixing in the stably stratified atmospheric boundary layer.

Proc.19th Amer.Meteorol.Soc.Symp.on Boundary Layers and Turbulence Keystone, CO, USA, paper 6.3, 10 pp.

Mironov, D. V., and E. E. Fedorovich (2010):

On the limiting effect of the Earth's rotation on the depth of a stably stratified boundary layer.

Quart.J.Roy.Meteor.Soc. 136, 1473-1480.

Bonavita M, Torrisi L, Marcucci F. 2010.

Ensemble data assimilation with the CNMCA regional forecasting system

Q. J. R. Meteorol. Soc. 136: 132�~@~S145, doi:10.1002/qj.533.

Silke Dierer et al.:

Deficiencies in quantitative precipitation forecasts: sensitivity studies using the COSMO model (more).

Meteorologische Zeitschrift, 18, 631-645, doi: 10.1127/0941-2948/2009/0420

C. Knote, G. Bonafe and F. di Giuseppe:

Leaf Area Index Specification for Use in Mesoscale Weather Prediction Systems. (more)

Monthly Weather Review, 137 (2009), 10, 3535-3550

Szintai, B.; P. Kaufmann, M. W. Rotach:

Deriving turbulence characteristics from the COSMO numerical weather prediction model for dispersion applications.

Advances in Science and Research, 2009, 3, 79-84

Folini, D., P. Kaufmann, S. Ubl, and S. Henne:

Region of influence of 13 remote European measurement sites based on modeled carbon monoxide mixing ratios

J. Geophys. Res., 114, D08307, doi: 10.1029/2008JD011125.

Mironov, D. V. (2009):

Turbulence in the lower troposphere: second-order closure and mass-flux modelling frameworks. (info)

Interdisciplinary Aspects of Turbulence Lect.Notes Phys., 756 W. Hillebrandt and F. Kupka, Eds., Springer-Verlag, Berlin, Heidelberg, 161-221. doi: 10.1007/978-3-540-78961-1 5

Schulz, J.-P., 2008

Revision of the turbulent gust diagnostics in the COSMO model (pdf).

COSMO Newsletter No8, 17–22.

Schulz, J.-P., 2008

Introducing sub-grid scale orographic effects in the COSMO model (pdf).

COSMO Newsletter No9, 29–36.

Marsigli C., Montani A. and Paccagnella T., 2008:

A spatial verification method applied to the evaluation of high-resolution ensemble forecasts

Meteorological Applications, 15, 125-143.

Michael Baldauf:

Stability analysis for linear discretisations of the advection equation with Runge-Kutta time integration

J. Comput. Phys., 227, 6638-6659

M. Milelli, E. Oberto, and A. Parodi:

Sensitivity experiments of a severe rainfall event in north-western Italy 17 August 2006. (more)

Adv. Sci. Res., 2, 133-138, 2008

Gebhardt, C., Theis, S., Krahe, P., Renner, V.:

Experimental ensemble forecasts of precipitation based on a convection-resolving model

Atmospheric Science Letters, Vol. 9,pp 67-72, doi: 10.1002/asl.177

Folini, D., S. Ubl, and P. Kaufmann:

Lagrangian particle dispersion modeling for the high Alpine site Jungfraujoch.

J. Geophys. Res., 113, D18111, doi: 10.1029/2007JD009558.

Leuenberger D, Rossa A. 2007.

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm.

Meteorol. Atmps.Phys., online first, doi:10.1007/s00703-007-0260-9.

Bonavita M, Torrisi L, Marcucci F. 2008.

The ensemble Kalman filter in an operational regional NWP system: Preliminary results with real observations

Q. J. R. Meteorol. Soc. 134: 1733-1744, doi:10.1002/qj.313.

Milan M, Venema V, Schüttemeyer D, Simmer C. 2008.

Assimilation of radar and satellite data in mesoscale models: A physical initialization scheme.

Meteorol.Z. 17: 887-902, doi: 10.1127/0941-2948/2008/0340.

Rossa A, Leuenberger D. 2008.

Sensitivity of the LHN Scheme to Non-Rain Echoes.

Met. Applications, 15, 503-511, doi:10.1002/met.99.

Stephan K, Klink S, Schraff C. 2008.

Assimilation of radar-derived rain rates into the convective-scale model COSMO-DE at DWD

Q. J. R Meteorol. Soc. 134: 1315-1326, doi:10.1002/qj.269.

Rockel, B., Will, A., and Hense, A. 2008.

The regional climate model COSMO-CLM (CCLM) (info).

Meteorol. Z. 17, 347–348, 2008.

Seifert, A., and K. D. Beheng, 2006

A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description. (info).

Meteorol. Atmos. Phys., 92 (1), 45–66.

Verbunt, M., M. Zappa, J. Gurtz, and P. Kaufmann:

Verification of a coupled hydrometeorological modelling approach for Alpine tributaries in the Rhine basin.

J. Hydrol., 324, 224-238

Beyrich, F., J.-P. Leps, M. Mauder, J. Bange, T. Foken, S. Huneke, H. Lohse, A. Ludi, W. M. L. Meijninger, D. Mironov, U. Weisensee, and P. Zittel (2006):

Area-averaged surface fluxes over the LITFASS region based on eddy-covariance measurements.

Boundary-Layer Meteorol. 121, 33-65. doi: 10.1007/s10546-006-9052-x

Guerova G, Bettems JM, Brockmann E, Matzler C. 2006.

Assimilation of COST 716 near-real time GPS data in the nonhydrostatic limited area model used at MeteoSwiss.

Meteorol. Atmps.Phys. 91: 149-164, doi:10.1007/s00703-005-0110-6.

Marsigli C., Boccanera F., Montani A. and Paccagnella T., 2005:

The COSMO-LEPS ensemble system: validation of the methodology and verification.

Non-linear Processes in Geophysics, Vol. 12, 527-536

Tibaldi S., Paccagnella T., Marsigli C., Montani A. and Nerozzi F., 2005:

Short-to-medium-range limited-area ensemble prediction: the LEPS system.

Part of the book "Predictability of Weather and Climate", editors: Dr. T. N. Palmer and Dr. R. Hagedorn, edizione Cambridge University Press.

Marsigli C., Montani A., Nerozzi F., Paccagnella T., 2004:

Probabilistic high-resolution forecast of heavy precipitation over Central Europe.

Natural Hazard and Earth System Sciences, 4, 315-322.

Guerova G, Bettems JM, Brockmann E, Matzler C. 2004.

Assimilation of the GPS-derived integrated water vapour (IWV) in the MeteoSwiss numerical weather prediction model - a first experiment.

Phys. Chem. Earth. 29(2-3): 177-186, doi:10.1016/j.pce.2004.01.009.

Steppeler, J; Doms, G; Schattler, U; Bitzer, HW; Gassmann, A; Damrath, U; Gregoric, G 2003:

Meso-gamma scale forecasts using the nonhydrostatic model LM.

Meteorology and Atmospheric Physics, Volume 82, Issue: 1-4, Pages: 75-96. DOI: 10.1007/s00703-001-0592-9

H.-J. Herzog, G. Vogel and U. Schubert

LLM-a Nonhydrostatic Model Applied to High-Resolving Simulations of Turbulent Fluxes over Heterogeneous Terrain.

Theoretical and Applied Climatology, 73 (2002), in press.

M. Anadranistakis, K. Lagouvardos, V. Kotroni and K. Skouras

Combination of Kalman Filter and Empirical Method for the Correction of Near-Surface Temperature Forecasts: Application over Greece.

Geophysical Research Letters, 29 (2002), in press.

J. Steppeler, R. Hess, U. Schättler and L. Bonaventura

Review of Numerical Methods for Nonhydrostatic Weather Prediction Models.

Meteorology and Atmospheric Physics, 78 (2002), in press.

J. Steppeler, H.-W. Bitzer, M. Minotte, and L. Bonaventura

Nonhydrostatic Atmospheric Modeling using a z-Coordinate Representation.

Monthly Weather Review, 130 (2002), 8,  2143-2149.

M. Tomassini, G. Gendt, G. Dick, M. Ramatschi and C. Schraff

Monitoring of Integrated Water Vapour from ground-based GPS observations and their assimilation in a limited-area NWP model.

Physics and Chemistry of the Earth, 27 (2002), 4-5, 341-346, doi:10.1016/S1474-7065(02)00010-4.

B. Ritter, R. Schrodin, E. Heise, M. Lange and A. Mueller

Implementation and Testing of a Multi-Layer Soil Model in the NWP Models of DWD.

Research Activities in Atmospheric and Ocean Modelling, No. 33.

G. Doms, D. Majewski, A. Mueller and B. Ritter

A Prognostic Cloud Ice Scheme for NWP Models.

Research Activities in Atmospheric and Ocean Modelling, No. 33.

Almut Gassmann

A two-timelevel integration scheme for the nonhydrostatic Lokal-Modell (LM) of DWD.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 3.01-3.08.

Maria Tomassini and Christoph Schraff

Assimilation of Integrated Water Vapour from Ground-Based GPS Observations at DWD.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 1.63-1.64.

G. Doms, D. Majewski, A. Mueller and B. Ritter

First Validation of the Prognostic Cloud Ice Scheme in the Global Model GME.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 4.09-4.10.

Erdmann Heise and Reinhold Schrodin

A Multi-Layer Soil Model Including Freezing/Melting Processes.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 4.11-4.12.

Matthias Raschendorfer and Dmitrii Mironov

Operational Implementation of the New Turbulence Parameterization.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 4.23-4.24.

J. Steppeler and H.-W. Bitzer

A Z-Coordinate Version of the Nonhydrostatic Model LM in Three Space Dimensions.

Research Activities in Atmospheric and Oceanic Modelling, No32, WMO/TD-No.1105, pg 5.36-5.37.

Schrodin, R. and Heise, E. 2001.

The Multi-Layer Version of the DWD Soil Model TERRA-LM (pdf)

COSMO Tech. Rep., 2, 2001.

Raschendorfer, M.

The new turbulence parameterization of LM (pdf)

COSMO newsletter, 1, 89–97, 2001.

P. Braun, B. Maurer, G. Müller, P. Gross, G. Heinemann, Simmer

An integrated approach for the determination of regional evapotranspiration using mesoscale modelling, remote sensing and boundary layer measurements

Meteor. Atmosph. Phys. 76, 83-105, 2001

C. Reudenbach, G. Heinemann, E. Heuel, J. Bendix, M. Winiger

Investigation of summertime convective rainfall in Western Europe based on a synergy of remote sensing data and numerical models

Meteor. Atmosph. Phys. 76, 23-41, 2001

R. Hess

Assimilation of screen-level observations by variational soil moisture analysis.

Meteorology and Atmospheric Physics, 77 (2001), 1-4, 145-154. doi:10.1007/s007030170023.

K. Saito, J. Steppeler, T. Kato, H. Eito, N. Seino and A. Murata

Report on the 3rd International SRNWP Workshop on Nonhydrostatic Modelling.

Bulletin of the American Meteorological Society, 82 (2001), 10, 2245-2250.

T. Klein, G. Heinemann, P. Gross

Simulation of the katabatic flow near the Greenland ice margin using a high-resolution nonhydrostatic model.

Meteorologische Zeitschrift, 10 (2001), 4, 331-339

A. Gassmann

Filtering Orography in the Lokal-Modell of DWD

Research Activities in Atmospheric and Oceanic Modelling, No31, WMO/TD-No.1064, pg 5.11-5.12.

J. Steppeler and H.-W. Bitzer

A Version of the Nonhydrostatic Model LM in Z-coordinates

Research Activities in Atmospheric and Oceanic Modelling, No31, WMO/TD-No.1064, pg 5.38-5.39.

Luca Bonaventura

A Semi-Implicit, Semi-Lagrangian Scheme Using the Height Coordinate for a Nonhydrostatic and Fully Elastic Model of Atmospheric Flows

Journal of Computational Physics, Vol. 158, pp. 186-213, 2000

U. Damrath, G. Doms, D. Frühwald, E. Heise, B. Richter and J. Steppeler

Operational quantitative precipitation forecasting at the German Weather Service

Journal of Hydrology, 239, p. 260-285, 2000

U. Schättler, G. Doms and J. Steppeler

Requirements and problems in parallel model development at DWD

Scientific Programming, 8, pg 13-22, 2000

S. Thomas, C. Girard, G. Doms and U. Schättler

Semi-Implicit Scheme for the DWD Lokal-Modell

Meteorol. Atmos. Phys., 73, pg 105-125 2000

U. Damrath, G. Doms, T. Hanisch and U. Schättler

Pre-Operational Test of the Lokal-Modell LM at DWD

Research Activities in Atmospheric and Oceanic Modelling, No30, WMO/TD-No.987, pg 5.3-5.4.

M. Raschendorfer

The New Turbulence Parameterization in the Lokal-Modell of DWD

Research Activities in Atmospheric and Oceanic Modelling, No30, WMO/TD-No.987, pg. 4.30-4.31.

Haase G, Crewell S, Simmer C, Wergen W. 2000.

Assimilation of radar data in mesoscale models: Physical initialization and latent heat nudging.

Phys. Chem. Earth. Part B 25:1237-1242, doi:10.1016/S1464-1909(00)00186-6.

S. Thomas, G. Doms and U. Schättler

A Semi-implicit Scheme for the Nonhydrostatic Regional Model LM at DWD

Research Activities in Atmospheric and Oceanic Modelling, No.28, WMO/TD-No.942, pg 5.56-5.57.

C. Schraff and M. Buchhold

A Nudging Scheme for the Nonhydrostatic Regional Model LM at DWD

Research Activities in Atmospheric and Oceanic Modelling, No.28, WMO/TD-No.942, pg 1.33-1.35.

K. Saito, G. Doms, U. Schättler and J. Steppeler

3-D Mountain Waves by the Lokal-Modell of DWD and the MRI Mesoscale NonHydrostatic Model

Papers in Meteorology and Geophysics, vol. 49, pg 7-19, 1998

G. Doms, U. Schättler, J. Steppeler and L. Wicker

Development of the Nonhydrostatic Regional Model LM at DWD

Research Activities in Atmospheric and Oceanic Modelling, No27, WMO/TD-No.865, pg. 5.17-5.18

Schraff C. 1997.

Mesoscale data assimilation and prediction of low stratus in the Alpine region.

Meteorol. Atmps.Phys. 64: 21-50, doi:10.1007/BF01044128.

Ritter, B. and Geleyn, J. F.

A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations (info).

Mon. Weather Rev., 120, 303–325, 1992.

Tiedtke, M. 1989

A comprehensivemass flux scheme for cumulus parameterization in large-scale models (info).

Mon. Weather Rev., 117, 1779–1800, 1989.