Eigil Kaas

Climate Researcher at National Center for Climate Research at DMI, and Professor in Climate Dynamics at NBI

National Center for Climate Research,

Danish Meteorological Institute (DMI)

Niels Bohr Institute,

Univ. of Copenhagen

Danish Meteorological Institute, Lyngbyvej 100, DK-2100 Copenhagen, DENMARK


Niels Bohr Institute ,
Tagensvej 16,
DK-2200 Copenhagen,

Mobile phone:
+ 45 26 14 93 02


Private Address
Fiskergårdsvej 10,
DK-4000 Roskilde
Research interests
Teaching activities
PhD projects
Master degree projects
Recent reviewed publications

Research interests

My main fields of interests are climate dynamics/physics, meteorology and numerical methods used in atmospheric models for climate and numerical weather prediction (NWP). Recently I have also worked a bit on nowcasting, usage of crowd sourced data in NWP and application of AI methods in atmospheric models.

Teaching activities

Unfortunately I am not teaching any semester (block) courses right now, since my main duties are at the National Center for Climate Research at DMI.

Previously (since 2006) if have developed and taught the following courses:

  • Dynamical Meteorology (BSc). This course introduced the governing differential equations for atmospheric dynamics and the various types of waves in the atmosphere permitted by these equations. Furthermore, based on the Boussinesq and/or quasi-geostrophic approximations, the large scale dynamical structures and instabilities of the atmosphere were introduced.

  • General circulation of the atmosphere (MSc). This was a fundamental course in atmosphere and climate dynamics. Its aim was to analyse and understand the mechanisms responsible for the global circulation, and, thus, the general “machinery” of the atmosphere. The course also covered balances of energy and angular momentum, dynamically caused variability and meridional transports of, e.g., heat.

  • Dynamical models for climate and Numerical Weather Prediction (NWP) (MSc). This was a course on atmospheric dynamical modelling and data assimilation for use in climate research and numerical weather prediction (NWP). So, this was a fundamental theoretical course for climate modellers and NWP system developers.

  • Atmospheric Physics (Geofysik 1) (MSc). This was an undergraduate course introducing atmospheric physics and dynamics based on the popular book by Wallace and Hobbs.

  • Climate Models (MSc), Observations of the Past and the Present, and Projected Climate Change including Sea Level Rise

  • Geofysisk fluiddynamik (BSc)

  • Introduktion til geofysik (Geofysik1) (Bsc)

  • Klimadynamik (BSc) – developed in collaboration with Prof. Gary Shaffer

  • Klimafysik (BSc) – developed in collaboration with Prof. Kristine Hvidberg

  • Numerical methods in atmosphere and ocean models (MSc) – in collaboration with professor Peter Lynch at University College in Dublin.

  • Satellite geophysics (MSc) – in collaboration with Prof. Carl Christian Tscherning.

I have also been teacher on, and co-organiser of various PhD summer schools – please, see my CV.

Ongoing PhD projects (where I am main supervisor)

  • Wiebke Margitta Kolbe (planned 2025) is a PhD project in collaboration between the DTU space and National Center for Climate Research at DMI. The subject is “Extension of sea ice climate time series with historical satellite data”. The idea is to extend satellite based records for sea ice extend further back in time than done so far.

  • Kasper Skjold Tølløse (planned 2024) is an industrial PhD who works on improved forecasting of atmospheric pollutant transport with the DMI DERMA system. He also works on methods enabling better estimates of the location and strength of unknown releases of e.g. radioactive isotopes. The industrial collaborator is DMI.

PhD students/projects finalised 2009-2022

OBS: due to GDPR regulations I am not permitted to list current individual affiliations/occupations. I can mention, however, that my former PhD students have all got great jobs, such as researchers and vice-director at DMI, Post-docs+ at various universities and top research institutions (worldwide), research directors, academic positions at universities, and high level academic positions in the Danish Armed Forces :

  • Peter Valentin Ukkonen (2022) used machine learning techniques (AI/neural nets) to reduce the computational costs of radiative transfer parameteristion in NWP models – more specifically the IFS. The project was part of the ESCAPE-2 project in collaboration with DMI and ECMWF.

  • Emy Alerskans (2022) was an industrial PhD who developed new systems for ultra-local weather forecasts designed for farmers and other agricultural applications. The industrial collaborator was Fieldsense, and also DMI was involved.

  • Sissal Vágsheyg Erenbjerg (2021) studied the ocean flow through fjords at the Faroe Islands. The purpose of the project was to improve simulation/prediction of water flow/quality aiming at supporting research on lice attacks in salmon farms. In collaboration with Fiskaaling, Faroe Islands.

  • Ida Margrethe Ringgaard (2019) studied the interaction between varying Arctic sea ice and the global climate system with special emphasis on changes in the Europe and the Northern Hemisphere. Funded by the Ice2Ice project and in collaboration with CIC and DMI.

  • Kasper Hintz (2019) was an industrial PhD partly funded by the Danish Innovation Foundation. From the beginning the project was in collaboration with the private company Vaavud. However, due to financial issues DMI took over after about one year. The idea in this project was to use unconventional crowd sourced data – mainly wind and pressure – to enhance the skill in nowcasting, i.e., forecasts with a lead time of a few hours.

  • Martin Olesen (2019) uses the HIRHAM model to downscale past and present weather conditions over Greenland with special emphasis on the role of sea ice variations in the Nordic Seas. Funded by the Ice2Ice project and in collaboration with CIC and DMI.

  • Alexander Kurganskiy (2017) developed and tested a new module for simulation and forecasts of pollen concentration in the Enviro-HIRLAM model system. This project was a collaboration with DMI and the Russian State Hydrometeorological University, RSHU in St. Petersburg.

  • Brian Sørensen (finalised 2013). Brian work on, and developed, fundamental components of the ENVIRO-HIRLAM system. The main emphasis was on improving the dynamical coupling between pollutants and the dynamical model core. This project was part of CEEH (www.ceeh.dk).

  • Ayoe Buus Hansen (2013). Ayoe combined a locally mass conserving semi-Lagrangian transport scheme with the atmospheric chemical modules used at the National Environmental Research Institute. This project was part of CEEH (www.ceeh.dk).

  • Ivana Cvijanović. Ivana studied the climate dynamics related to abrupt climate change with main focus on potential atmospheric re-organisations.

  • Ulrik Smith Korsholm (in collaboration with DMI). Ulrik modelled the indirect effects of aerosol. Ulrik is co-developer of the ENVIRO-HIRLAM model at DMI.

  • Till Rasmussen. Till analysed and modelled the Sea Ice in the Nares Strait between Greenland and Canada (in collaboration with Nicolai Kliem, DMI).

Master thesis projects

OBS: due to GDPR regulations I am not permitted to list current individual affiliations/occupations. I can mention, however, that my former MSc students have got great jobs, such as high school teachers, researchers / forecasters / high level investigators at, e.g., DMI and The Danish Coastal Authority, and the UK-Met-office. Several also got jobs in private companies, such as Weather News, energy trading companies (Nordjyske Elhandel, Danske Comodities), Consulting Engineering (Rambøl, Niras, Cowi), Banks, Vision IT ApS, Swire Blue Ocean A/S (California), Gas Storage Denmark, Novo Nordisk, Wattsight A/S (Norway) etc. Several have also taken a PhD degree afterwards both abroad and with me – see above.

  • Alessandro Falcione (2020). Alessandro investigated the feasibility of assimilating crowdsourced surface pressure data from personal weather stations into the operational forecast model (Harmonie) at DMI. The project was run in close collaboration with Xiaohua Yang at DMI.

  • Wiebke Margitta Kolbe (2020). The project dealt with machine learning parameterisation of parts of the radiation code in the WRF-model (Weather and Research Forecasting model).

  • Kasper Tølløse (2020). Kasper used machine learning techniques for parameterisation of turbulent fluxes in the atmospheric boundary layer in an NWP model (WRF).

  • Luwei Shen (2019) used EP-flux analysis and other methods to map and understand the relationship between Northern Hemisphere atmospheric blocking and stratospheric conditions (e.g. sudden warmings). She used data from the EC-Earth model (delivered by DMI) and also reanalyses from ERA5. In collaboration with DMI (Bo Christiansen and Shuting Yang).

  • Patrick Bülow (2019) analysed the possible relationship between sudden drops – so called Forbush decreases – in galactic Cosmic Ray (GCR) flux, and the cloud cover on Earth. The idea in the project was to use Re-analysis data to separate that part of the cloud cover variations which can be ascribed to short term weather variations (noise) and to subtract that from the satellite based actual cloud cover. In this way a more clean (GCR-cloud) signal should be obtained. In collaboration with Jakob Svensmark (NBI).

  • Anesten Devasakayam (2018) worked on an explicit filter for stabilising non-hydrostatic models based on the fully compressible Euler equations with a new explicit time-splitting time scheme. This is an alternative to the use of (semi-)implicit discretisation. This was a follow up on the thesis by Emy Alerskans.

  • Anna Sofia Helena Karlsson (2018) studied the relative role of latent heat heat release in extra-tropical cyclogenesis. The main emphasis was on comparing conditions at present day with those in a warmer climate. Anna is working with the WRF model.

  • Anne Helene Koch Borrits (2018) worked with the DMI slippery road forecasting system. Anne developed and tested a processing and quality control system for thermal mapping data measurements taken along roads of the Danish road network. The project was carried out in collaboration with the Danish Road Directorate and DMI.

  • Andreas Nikolai Pedersen (apr 2018) investigated the impact of climate change on severe precipitation. Andreas performed case studies with severe convective precipitation using the WRF model. The idea is to change the initial conditions and the lateral boundary conditions to study the impact of increased temperature and related increased specific humidity on the amount of precipitation in each case.

  • Lisa Lea Jach (2017) worked on the coupling/exchange of energy and moisture between various types of land-surfaces and the atmosphere. Lisa worked with the WRF model in collaboration with university of Hohenheim, Germany.

  • Peter Valentin Ukkonen (2017) used information from a regional climate model to model extreme precipitation in a warmer climate, Peter used machine learning techniques for parameterization of deep convection.

  • Joshua Rahbek (2016) worked on physically based statistical downscaling of extreme precipitation events in a warmer climate with special focus on precipitation changes in the UK.

  • Kyle Matthew Honsinger (2016) analysed changes of large scale climate variability in a warmer climate as simulated with the EC-Earth climate model. The main result obtained was that a change in ENSO variability significantly impact and enhance the interannual climate variability over the North Pacific. In collaboration with Shuting Yang at DMI.

  • Emy Alerskans (2016) combined the use of a new explicit filter for stabilising non-hydrostatic models based on the fully compressible Euler equations with a new explicit time-splitting time scheme. This is an alternative to the use of (semi-)implicit discretisation.

  • Johanna Eggeling (2016) analysed relationships between temperature and the occurrence of extreme precipitation over the Brittish Isles. Current occupation: unknown.

  • Andreas Michael Lang (2016) worked on the impact of Sea ice thickness in the Arctic. Andreas modified the atmospheric component of the EC-EARTH global climate model so that it can take into account the influence of gradually reduced sea ice thickness. In collaboration with Shuting Yang at DMI.

  • Mathilde Thorn Ljungdal (2016) used termistor-string measurements from arctic drifters (buoys on drifting Arctic sea ice) to estimate the heat conductivity and actual heat flux through the ice. The results were used to validate corresponding time series of total surface heat flux in the ERA interrim re-analysis data set. Drifter data were made available by Leif Toudal at DMI.

  • Kasper Hintz (2015) assimilated (nudged) high resolution precipitation radar data information into the HIRLAM system at DMI aiming at improving short-term forecasts of heavy precipitation (“Nowcasting”). His special focus was on the importance of the length of the model time step which appeared to be quite important for resolving the most intensive convection. In collaboration with DMI.

  • Abdulai Ademola Kayode (2015) used GPS data collected at the Greenland ice sheet. “Demi” (his nickname) reprocessed the data using “Bernese” software using alternative parameters for ionospheric and tropospheric correction. The application was on the use of GPS to quantify surface movements of the Greenland Ice Sheet.

  • Zhenhua Sun (2013, 30 ECTS) used high temporal resolution atmospheric data to drive a simple hydrological model, which was set up for conditions in the city of Århus. The aim was to investigate the role of green infrastructures on the hydrology and pollution. Current occupation: unknown private enterprise in China.

  • Rune H. Gjermundbo (2013) used an atmospheric GCM coupled to a mixed layer ocean model to study mechanisms responsible for Arctic amplification with main emphasis on understanding the relative role of local (i.e. Arctic) versus remote (i.e. tropical) processes/mechanisms. External (but effectively the main) supervisor: Peter Lang Langen (DMI/DKC).

  • Kaija Jumppanen Andersen (2013) is using satellite altimetry to calculate geostrophic currents and changes therein in the North Atlantic over the last decades. Comparisons with estimated sea level atmospheric pressure (SLP) and wind stress are made and a simple model describing sea level as function of SLP is being set up. External supervisor: Ole Baltazar Andersen (DTU Space).

  • Danny Høgsholt (2013) applied a combined time-splitting using a forward-backward approach with a semi-Lagrangian scheme in order to solve the fully compressible Euler equations in simple 2-dimensional convective plume model.

  • Cecilie Drost Aakjær (2013) analysed the dynamics of Arctic Ocean freshwater storage in the EC-Earth coupled climate model. External supervisors: Steffen M. Olsen and Torben Schmith (DMI).

  • Bjarke Tobias Olsen (2013) studied mixing in models employing the Hybrid Eulerian – Lagrangian (HEL) method for solving continuity equations. The main emphasis was to identify an optimal degree of flow-dependent mixing in order to obtain realistic cascades of energy etc. to small scales.

  • Heidi Villadsen (2013) used the EC-Earth model to study the climatic impact of reduced surface albedo of snow and sea ice due to black carbon depositions. External supervisors: Jens Hesselbjerg Christensen (DMI) and Jørgen Brandt,Department of Environmental Science (AU).

  • Rasmus Anker Pedersen (2013) used an atmospheric GCM with different prescribed sea-ice concentrations to study the impact of sea ice reductions on the Arctic tropospheric temperature changes. External (but effectively the main) supervisor: Peter Lang Langen (DMI/DKC).

  • Philip Tarning-Andersen (2012) studied aerosol-cloud microphysics in a one dimensional atmospheric model, with emphasis on a simple parameterization of effective droplet radius in warm clouds (In collaboration with Ulrik Smith Korsholm, DMI).

  • Karis Anneke Kürstein Glibbery (2011) used different satellite data sets for outgoing long wave radiation (OLR) to verify the long wave feedbacks in the EC-Earth climate model running at DMI (In collaboration with Shuting Yang, DMI).

  • Matilde Marie Brandt Jensen (2011) studied and analysed Arctic sea ice thinning over the period 1979-2008 using a number of different remote sensing based data (In collaboration with Rasmus Tonboe, DMI).

  • Maria Elisabeth Wulff (2011). Maria used ice core data for recent years and observed precipitation at Greenland SYNOP stations to identify a correction data base for the precipitation simulated in the HIRHAM regional climate model. The correction is needed to obtain reasonable atmospheric data for driving an ice sheet model (not part of the study). (In collaboration with Gudfinna Adalsgeirdottir and others at the Danish Climate Centre, DMI).

  • Leif Skovbo (2009). Leif investigated the realism of certain verifiable feedbacks in IPCC climate models and used this to perform a model weighting for future climate scenarios.

  • Ayoe Buus Hansen (2009). Ayoe performed a two-dimensional intercomparison of semi-Lagrangian transport schemes and the ASD algorithm used in the atmospheric chemical modules at the National Environmental Research Institute. This project was part of CEEH (www.ceeh.dk).

  • Joakim Refslund Nielsen (2009). Joakim implemented and tested a new anti-diffusive monotonic filter in combination with a locally mass conserving semi-Lagrangian transport scheme in the HIRLAM model used at DMI.

  • Brian Sørensen (2009). Brian implemented and tested a new quasi-Lagrangian vertical coordinate in combination with a locally mass conserving semi-Lagrangian transport scheme in the HIRLAM model used at DMI.

  • Allan Christensen (2009). Allan implemented and tested a locally mass conserving semi-Lagrangian transport scheme in the HIRLAM model used at DMI.



Full CV , four page CV , two page CV , one page CV, publications.

“Recent” reviewed scientific publications

(pdf-copies can be delivered on request, also for accepted manuscripts):

Rasmussen, T. A. S, N. Kliem, E. Kaas (2010) Modelling the sea ice in the Nares Strait. Ocean Modelling, 35, No. 3 161-172.

Rasmussen, T. A. S, N. Kliem, E. Kaas (2011) The effect of climate change on the sea ice and the hydrography in the Nares Strait. Atmosphere-Ocean. doi:10.1080/07055900.2011.604404.

Cvijanovic, I, P. L. Langen, and E. Kaas (2011): Weakened atmospheric energy transport feedback in cold glacial climates. Clim. Past, 7, 1061-1073, doi:10.5194/cp-7-1061-2011.

A. B. Hansen, J. Brandt, J. H. Christensen, and E. Kaas (2011): Semi-Lagrangian methods in air pollution models, Geosci. Model Dev., 4, 511-541, doi:10.5194/gmd-4-511-2011.

Funder S., H. Goosse, H. Jepsen, E. Kaas, K. H. Kjær, N. J. Korsgaard, N. K. Larsen, H. Linderson, A. Lyså, P. Möller, J. Olsen, E. Willerslev (2011): A 10,000-Year Record of Arctic Ocean Sea-Ice Variability—View from the Beach, Science. 5 August 2011: 747-750. [DOI:10.1126/science.1202760].

Cvijanovic, I, P. L. Langen, E. Kaas, and Peter D. Ditlevsen (2013): Southward Intertropical Convergence Zone shifts and implications for an atmospheric bipolar seesaw. J. climate, http://dx.doi.org/10.1175/JCLI-D-12-00279.1

Sørensen, B., E. Kaas, U. S. Korsholm (2013): A mass conserving and multi-tracer efficient transport scheme in the online integrated Enviro-HIRLAM model. Geosci. Model Dev., 6,1029-1042, doi:10.5194/gmd-6-1029-2013, http://www.geosci-model-dev.net/6/1029/2013/gmd-6-1029-2013.pdf

Rathmann, N. M., S. Yang and E. Kaas (2013): Tropical cyclones in enhanced resolution CMIP5 experiments. Clim Dyn, DOI 10.1007/s00382-013-1818-5.

Krueger, O., F. Feser, L. Bärring, E.Kaas, T. Schmith, H. Tuomenvirta and H. von Storch (2013): Comment on “Trends and low frequency variability of extra-tropical cyclone activity in the ensemble of Twentieth Century Reanalysis” by Xiaolan L. Wang, Y. Feng, G. P. Compo, V. R. Swail, F. W. Zwiers, R. J. Allan, and P.D. Sardeshmukh, Climate Dynamics, published online, DOI 10.1007/s00382-013-1814-9

Brandt, J., J. D. Silver, J. H. Christensen, M. S. Andersen, J. H. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K. M. Hansen, G. B. Hedegaard, E. Kaas and L. M. Frohn (2013): Contribution from the ten major emission sectors in Europe and Denmark to the health-cost externalities of air pollution using the EVA model system – an integrated modelling approach. Atmos. Chem. Phys., 13, 7725-7746. doi:10.5194/acp-13-7725-2013.

Brandt, J, J. D. Silver, J. H. Christensen, M. S. Andersen, J. H. Bønløkke, T. Sigsgaard, C. Geels, A. Gross, A. B. Hansen, K. M. Hansen, G. B. Hedegaard, E. Kaas and L. M. Frohn (2013): Assessment of past, present and future health-cost externalities of air pollution in Europe and the contribution from international ship traffic using the EVA model system. Atmos. Chem. Phys., 13, 7747-7764, doi:10.5194/acp-13-7747-2013.

Kaas, E., B. Sørensen, C. C. Tscherning and M. Veicherts (2013): Multi-processing least squares collocation: Applications to gravity field analysis. Journal of Geodetic Science. Volume 3, Issue 3, Pages 219–223, DOI: 10.2478/jogs-2013-0025

Kaas, E., B. Sørensen, P. H. Lauritzen and A. B. Hansen (2013): A hybrid Eulerian Lagrangian numerical scheme for solving prognostic equations in fluid dynamics. Geosci. Model Dev. 6, 2023-2047, doi:10.5194/gmd-6-2023-2013

Baklanov, A., K. H. Schluenzen, P. Suppan, J. Baldasano, D. Brunner, S. Aksoyoglu, G. Carmichael, J. Douros, J. Flemming, R. Forkel, S. Galmarini, M. Gauss, G. Grell, M. Hirtl, S. Joffre, O. Jorba, E. Kaas, M. Kaasik, G. Kallos, X. Kong, U. Korsholm, A. Kurganskiy, J. Kushta, U. Lohmann, A. Mahura, A. Manders-Groot, A. Maurizi, N. Moussiopoulos, S. T. Rao, N. Savage, C. Seigneur, R. Sokhi, E. Solazzo, S. Solomos, B. Sørensen, G. Tsegas, E. Vignati, B. Vogel, and Y. Zhang, (2013): Online coupled regional meteorology-chemistry models in Europe: current status and prospects. Atmos. Chem. Phys. Atmos. Chem., 14, 317–398, doi:10.5194/acp-14-317-2014.

Lauritzen, P.H., P.A. Ullrich, C. Jablonowski, P.A. Bosler, D. Calhoun, A.J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A.B. Hansen, E. Kaas, J. Kent, J.F. Lamarque, M.J. Prather, D. Reinert, V.V. Shashkin, W.C. Skamarock, B. Sørensen, M.A. Taylor, and M.A. Tolstykh (2013): A standard test case suite for two-dimensional linear transport on the sphere: results from a collection of state-of-the-art schemes. Geosci. Model Dev., 7, 105–145, doi:10.5194/gmd-7-105-2014.

A. Acheampong, C. Fosu, L. K. Amekudzi, and E. Kaas (2015): Comparison of precipitable water over Ghana using GPS signals and reanalysis products. J. Geod. Sci.; Volume 5, Issue 1, ISSN (Online) 2081-9943, DOI: 10.1515/jogs-2015-0016, November 2015.

Lang, A., S. Yang, and E. Kaas (2017), Sea ice thickness and recent Arctic warming, Geophys. Res. Lett., 44, 409–418, doi:10.1002/2016GL071274.

Baklanov, A, U. S. Korsholm, R. Nuterman, A. Mahura, K. P. Nielsen, B. H. Sass, A. Rasmussen, A. Zakey, E. Kaas, A. Kurganskiy, B. Sørensen, and I González-Aparicio (2017): Enviro-HIRLAM online integrated meteorology–chemistry modelling system: strategy, methodology, developments and applications (v7.2). Geosci. Model Dev., DOI: 10.5194/gmd-10-2971-2017.

Olesen, M., J. H. Christensen, E. Kaas and F. Boberg (2018): On the robustness of high resolution regional climate projections for Greenland: A method for uncertainty distillation. Climate Research, https://doi.org/10.3354/cr01536.

Hintz, K. S, H. Vedel and E. Kaas (2019): Collecting and Processing of Barometric Data from Smartphones for Potential Use in NWP Data Assimilation. Meteorological Applications, https://doi.org/10.1002/met.1805

Hintz, K. S., K. O'Boyle, S. L. Dance, S. Al Ali, I. Ansper, D. Blaauboer, M. Clark, A. Cress, M. Dahoui, R. Darcy, J. Hyrkkanen, L. Isaksen, E. Kaas, M. Lavanant, G. Lebloa, E. Mallet, C. McNicholas, J. Onvlee-Hooimeijer, B. Sass, V. Siirand, H. Vedel, J. A. Waller, X. Yang, (2019): Collecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4-5 December 2018. Atmospheric Science Letters. https://doi.org/10.1002/asl.921

Hintz, K. S, H. Vedel, E. Kaas and N. W. Nielsen (2020): Estimation of wind speed and roughness length using smartphones: Method and quality assessment. Journal of Atmospheric and Oceanic Technology, https://doi.org/10.1175/JTECH-D-19-0037.1

Kurganskiy, A, C. A. Skjøth, A. Baklanov, M. Sofiev, A. Saarto, E. Severova, S. Smyshlyaev, and E. Kaas (2020): Incorporation of pollen data in source maps is vital for pollen dispersion models, Atmospheric Chemistry and Physics (ACP). 20, 2099–2121.

Ringgaard, I. M; S. Yang; E. Kaas; J. H. Christensen (2020): Barents-Kara sea ice and European winters in the coupled model EC-Earth. Climate Dynamics. 54, pages 3323–3338.

Jach, L ., K. Warrach-Sagi, J. Ingwersen, E. Kaas, V. Wulfmeyer(2020): Land Cover Impacts on Land-Atmosphere Coupling Strength in Climate Simulations with WRF over Europe. JGR – atmospheres, Volume 125, Issue 18, https://doi.org/10.1029/2019JD031989

Ukkonen, P., Pincus, R., Hogan, R. J., Nielsen, K. P., & Kaas, E. (2020). Accelerating radiation computations for dynamical models with targeted machine learning and code optimization. Journal of Advances in Modeling Earth Systems, 12, https://doi.org/10.1029/2020MS002226

Erenbjerg, S.V, Albretsen, Simonsen K., Sandvik, A. D., Kaas, E. (2020): A step towards high resolution modeling of the central Faroe shelf circulation by FarCoast800. In "Regional Studies in Marine Science. Volume 40, November 2020, 101475. https://doi.org/10.1016/j.rsma.2020.101475

Erenbjerg, S. V., Albretsen, J., Simonsen, K., Olsen, E., Kaas, E., & Hansen, B. (2021). A tidally driven estuary close to an amphidromy. Ocean Science, 17, 1639-1655. https://doi.org/10.5194/os-17-1639-2021

Alerskans, E. and Kaas, E. (2021). Local temperature forecasts based on statistical post-processing of numerical weather prediction data. Meteorological Applications, 28(4), https://doi.org/10.1002/met.2006

Husbjerg, L. S., Neubert, T., Chanrion, O., Dimitriadou, K., Li, D., Stendel, M., et al. (2022). Observations of blue corona discharges in thunderclouds. Geophysical Research Letters, 49, e2022GL099064. https://doi.org/10.1029/2022GL099064

Alerskans, E., Nyborg, J., Birk, M., & Kaas, E. (2022). A transformer neural network for predicting near-surface temperature. Meteorological Applications, 29( 5), e2098. https://doi.org/10.1002/met.2098

Nielsen, J.K., Kaas, E. (2023). The Impact of Public Perception of Timescales in the Climate System on Mitigation Policies. In: Mathematics Online First Collections. Springer, Cham. https://doi.org/10.1007/16618_2023_63

Kaas, E. (2023). Multiplicity of time scales in climate and the Earth system. In: Mathematics Online First Collections. Springer, Cham., In press.

UPDATED August 2023