To study the influence of three-dimensional cloud effects on the forecast of longwave radiation and air temperature during warm air advection onto a snow surface for the Moscow region, experiments were conducted with the ICON v.2025.04 model using various algorithms of cloud heterogeneity accounting. Additionally, experiments were conducted with the ecRAD radiation scheme in autonomous mode. The ICON model with the McICA algorithm reproduces positive NLR values, but underestimates them. The use of the SPARTACUS algorithm, which makes it possible to describe the three-dimensional effects of clouds, reduced the NLR RMSE by 4 W/m2. At the same time, in the ecRAD autonomous mode, the effects reached 15 W/m2, which corresponded to the measured NLR values within the measurement error. The study showed that the decrease in the effect of the SPARTACUS algorithm in the ICON model is associated with the influence of the algorithm on the cloud properties. Using the ecRAD autonomous mode, nonlinear NLR dependence on the cloud liquid water path and ice water path have been revealed. The temperature sensitivity to NLR changes was 2.7 °C per 100 W/m2 in model experiments with McICA and 4.9 °C per 100 W/m2 in experiments with SPARTACUS for night hours with positive NLR. Differences in the temperature response of the ICON model to changes in longwave radiation due to the replacement of the algorithms are also estimated.
longwave radiation, cloud-radiation interaction, three-dimensional effects, ecRAD, ICON, temperature sensitivity
1. Curry J., Rossow W.B., Randall D., Schramm J.L. Overview of Arctic cloud and radiation characteristics // J. Climate. 1996. V. 9. P. 1731–1764. DOI: 10.1175/1520-0442(1996)009%3C1731%3AOOACAR%3E2. 0.CO;2.
2. Hogan R.J., Ahlgrimm M., Balsamo G., Beljaars A.C.M., Berrisford P., Bozzo A., Di Giuseppe F., Forbes R.M., Haiden T., Lang S., Mayer M., Polichtchouk I., Sandu I., Vitart F., Wedi N. Radiation in Numerical Weather Prediction. ECMWF Technical Memorandum N 816. Reading: ECMWF, 2017. URL: https://www. ecmwf.int/sites/default/files/elibrary/2017/17771-radiation-numerical-weather-prediction.pdf (last access: 11.01.2026).
3. Arduini G., Keeley S., Day J.J., Sandu I., Zampieri L., Balsamo G. On the importance of representing snow over sea-ice for simulating the Arctic boundary layer // J. Adv. Model. Earth Syst. 2022. V. 14, N 7. DOI: 10.1029/2021MS002777.
4. Zängl G., Reinert D., Rípodas P., Baldauf M. The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core // Q. J. R. Meteorol. Soc. 2015. V. 141. P. 563–579. DOI: 10.1002/qj.2378.
5. Prill F., Reinert D., Rieger D., Zängl G. Working with the ICON Model. Germany: Deutscher Wetterdienst. 2025. DOI: 10.5676/dwd_pub/nwv/icon_tutorial2025.
6. Rivin G.S., Rozinkina I.A., Astakhova E.D., Blinov D.V., Bundel' A.YU., Kirsanov A.A., Shatunova M.I., Chubarova N.E., Alferov D.Yu., Varentsov M.I., Zakharchenko D.I., Kopeikin V.V., Nikitin M.N., Polyukhov A.A., Revokatova A.P., Tatarinovich E.V., Churyulin E.V. Sistema kratkosrochnogo chislennogo prognoza vysokoi detalizatsii COSMO-Ru, ee razvitie i prilojeniya // Gidrometeorologicheskie issledovaniya i prognozy. 2019. N 374. P. 37–53.
7. Mlawer E.J., Taubman S.J., Brown P.D., Iacono M.J., Clough S.A. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave // J. Geophys. Res.: Atmos. 1997. V. 102, N D14. P. 663–682. DOI: 10.1029/97JD00237.
8. Hogan R.J., Bozzo A.A. Flexible and Efficient Radiation Scheme for the ECMWF Model // J. Adv. Model. Earth Syst. 2018. V. 10, N 8. P. 1990–2008. DOI: 10.1029/2018MS001364.
9. Rieger D., Kohler M., Hogan R.J., Schafer S.A.K., Seifert A., de Lozar A., Zangl G. ecRad in ICON – details on the implementation and first results // Rep. ICON. 2019. N 4. DOI: 10.5676/DWD_pub/nwv/icon_004.
10. Tjernström M., Shupe M.D., Brooks I.M., Persson P.O.G., Prytherch J., Salisbury D.J., Sedlar J., Achtert P., Brooks B.J., Johnston P.E., Sotiropoulou G., Wolfe D. Warm-air advection, air mass transformation and fog causes rapid ice melt // Geophys. Res. Lett. 2015. V. 42, N 13. P. 5594–5602. DOI: 10.1002/2015GL064373.
11. Wendisch M., Brückner M., Crewell S., Ehrlich A., Notholt J., Lüpkes C., Macke A., Burrows J.P., Rinke A., Quaas J., Maturilli M., Schemann V., Shupe M.D., Akansu E.F., Barrientos-Velasco C., Bärfuss K., Blechschmidt A.-M., Block K., Bougoudis I., Bozem H., Böckmann C., Bracher A., Bresson H., Bretschneider L., Buschmann M., Chechin D.G., Chylik J., Dahlke S., Deneke H., Dethloff K., Donth T., Dorn W., Dupuy R., Ebell K., Egerer U., Engelmann R., Eppers O., Gerdes R., Gierens R., Gorodetskaya I.V., Gottschalk M., Griesche H., Gryanik V.M., Handorf D., Harm-Altstädter B., Hartmann J., Hartmann M., Heinold B., Herber A., Herrmann H., Heygster G., Höschel I., Hofmann Z., Hölemann J., Hünerbein A., Jafariserajehlou S., Jäkel E., Jacobi C., Janout M., Jansen F., Jourdan O., Jurányi Z., Kalesse-Los H., Kanzow T., Käthner R., Kliesch L.L., Klingebiel M., Knudsen E.M., Kovács T., Körtke W., Krampe D., Kretzschmar J., Kreyling D., Kulla B., Kunkel D., Lampert A., Lauer M., Lelli L., von Lerber A., Linke O., Löhnert U., Lonardi M., Losa S.N., Losch M., Maahn M., Mech M., Mei L., Mertes S., Metzner E., Mewes D., Michaelis J., Mioche G., Moser M., Nakoudi K., Neggers R., Neuber R., Nomokonova T., Oelker J., Papakonstantinou-Presvelou I., Pätzold F., Pefanis V., Pohl C., van Pinxteren M., Radovan A., Rhein M., Rex M., Richter A., Risse N., Ritter C., Rostosky P., Rozanov V.V., Donoso E. Ruiz, Saavedra Garfias P., Salzmann M., Schacht J., Schäfer M., Schneider J., Schnierstein N., Seifert P., Seo S., Siebert H., Soppa M.A., Spreen G., Stachlewska I.S., Stapf J., Stratmann F., Tegen I., Viceto C., Voigt C., Vountas M., Walbröl A., Walter M., Wehner B., Wex H., Willmes S., Zanatta M., Zeppenfeld S. Atmospheric and surface processes, and feedback mechanisms determining Arctic amplification: A review of first results and prospects of the (AC)3 project // Bull. Am. Meteorol. Soc. 2023. V. 104, N 1. P. 208–242. DOI: 10.1175/BAMS-D-21-0218.1.
12. Dahlke S., Rinke A., Shupe M.D., Cox C.J. The two Arctic wintertime boundary layer states: Disentangling the role of cloud and wind regimes in reanalysis and observations during MOSAiC // Atmos. Sci. Lett. 2025. V. 26, N 4. DOI: 10.1002/asl.1298.
13. Makhotina I.A., Makshtas A.P., Chechin D.G. Meteorological winter conditions in the Central Arctic according to the drifting stations “North Pole 35-40” // IOP Conf. Ser.: Earth Environ. Sci. 2019. V. 231. DOI: 10.1088/1755-1315/231/1/012031.
14. Makhotina I.A., Chechin D.G., Makshtas A.P. Radiatsionnyi effekt oblachnosti nad morskim l'dom v Arktike vo vremya polyarnoi nochi po dannym dreifuyushchikh stantsii «Severnyi Polyus»-37, 39, 40 // Fiz. atmosf. i okeana. 2021. V. 57, N 5. P. 514–525.
15. Stramler K., Del Genio A.D., Rossow W.B. Synoptically driven Arctic winter states // J. Clim. 2011. V. 24, N 6. P. 1747–1762. DOI: 10.1175/2010JCLI3817.1.
16. Piskunova D., Chubarova N., Shatunova M., Shuvalova J. Positive longwave net irradiance at ground: Evidence and reasons // IOP Conf. Ser.: Earth Environ. Sci. 2025. V. 1522, N 1. DOI: 10.1088/1755-1315/1522/1/012017.
17. Bresson H., Rinke A., Mech M., Reinert D., Schemann V., Ebell K., Maturilli M., Viceto C., Gorodetskaya I., Crewell S. Case study of a moisture intrusion over the Arctic with the ICOsahedral Non-hydrostatic (ICON) model: Resolution dependence of its representation // Atmos. Chem. Phys. 2022. V. 22, N 1. P. 173–196. DOI: 10.5194/acp-22-173-2022.
18. Kretzschmar J., Stapf J., Klocke D., Wendisch M., Quaas J. Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic // Atmos. Chem. Phys. 2020. V. 20. P. 13145–13165. DOI: 10.5194/acp-20-13145-2020.
19. Shuvalova J., Chubarova N., Shatunova M. Cloud characteristics and their effects on solar irradiance according to the ICON model, CLOUDNET and BSRN Observations // Atmosphere. 2023. V. 14, N 12. DOI: 10.3390/atmos14121769.
20. Fu Q., Yang P., Sun W.B. An accurate parametrization of the infrared radiative properties of cirrus clouds of climate models // J. Clim. 1998. V. 11, N 9. P. 2223–2237. DOI: 10.1175/1520-0442(1998)011<2223: AAPOTI>2.0.CO;2.
21. Edwards J.M., Slingo A. Studies with a flexible new radiation code: 1. Choosing a configuration for a large-scale model // Q. J. R. Meteorol. Soc. 1996. V. 122, N 531. P. 689–719. DOI: 10.1002/qj.49712253107.
22. Pincus R., Barker H., Morcrette J.-J. A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields // J. Geophys. Res. 2003. V. 108, N D13. DOI: 10.1029/2002JD003322.
23. Räisänen P., Barker H.W., Khairoutdinov M.F., Li J., Randall D.A. Stochastic generation of subgrid-scale cloudy columns for large-scale models // Q. J. R. Meteorol. Soc. 2004. V. 130. P. 2047–2067. DOI: 10.1256/qj.03.99.
24. Shonk J.K.P., Hogan R.J. Tripleclouds: An efficient method for representing horizontal cloud inhomogeneity in 1D radiation schemes by using three regions at each height // J. Clim. 2008. V. 21, N 11. P. 2352–2370. DOI: 10.1175/2007JCLI1940.1.
25. Hogan R.J., Schäfer S.A.K., Klinger C., Chiu J.C., Mayer B. Representing 3-D cloud radiation effects in two-stream schemes: 2. Matrix formulation and broadband evaluation // J. Geophys. Res.: Atmos. 2016. V. 121, N 14. P. 8583–8599. DOI: 10.1002/2016JD024875.
26. Schäfer S.A.K., Hogan R.J., Klinger C., Chiu J.-C., Mayer B. Representing 3D cloud-radiation effects in two-stream schemes: 1. Longwave considerations and effective cloud edge length // J. Geophys. Res. 2016. V. 121, N 14. P. 8567–8582. DOI: 10.1002/2016JD024876.
27. Räisänen P., Barker H.W., Cole J.N. The Monte Carlo independent column approximation’s conditional random noise: Impact on simulated climate // J. Clim. 2005. V. 18, N 22. P. 4715–4730. DOI: 10.1175/JCLI3556.1.
28. Hogan R.J., Illingworth A.J. Deriving cloud overlap statistics from radar // Q. J. R. Meteorol. Soc. 2000. V. 126, N 569. P. 2903–2909. DOI: 10.1002/qj.49712656914.
29. Open Data Server of the German Meteorological Service (DWD). URL: https://opendata.dwd.de/ (last access: 11.01.2026).
30. Maurer V., Früh B., Giorgetta M.A., Steger C., Brauch J., Schnur R., Zängl G. Domain nesting in ICON-A and its application to AMIP experiments with regional refinement // Rep. ICON. 2022. N 8. DOI: 10.5676/DWD_pub/nwv/icon_008.
31. Doms G., Forstner J., Heise E., Herzog H.-J., Mironov D., Raschendorfer M., Reinhardt T., Ritter B., Schrodin R., Schulz J.-P., Vogel G. A Description of the Nonhydrostatic Regional COSMO Model. Part II: Physical Parameterization. Germany: Deutsher Wetterdienst, 2021. DOI: 10.5676/DWD_pub/nwv/cosmo-doc_6.00_II.
32. Seifert A., Beheng K.D. A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 1: Model description // Meteorol. Atmos. Phys. 2006. V. 92, N 1. P. 45–66. DOI: 10.1007/s00703-005-0112-4.
33. Tiedtke M. A comprehensive mass flux scheme for cumulus parameterization in large-scale models // Mon. Weather Rev. 1989. V. 117, N 8. P. 1779–1800. DOI: 10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.
34. Bechtold P., Köhler M., Jung T., Doblas-Reyes F., Leutbecher M., Rodwell M.J., Vitart F., Balsamo G. Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales // Q. J. R. Meteorol. Soc. 2008. V. 134, N 634. P. 1337–1351. DOI: 10.1002/qj.289.
35. Raschendorfer M. The new turbulence parameterization of LM // COSMO News Lett. 2001. N 1. P. 89–97.
36. Chubarova N.E., Rozental' V.A., Zhdanova E.Yu., Polyukhov A.A. Novyi radiatsionnyi kompleks Meteorologicheskoi observatorii MGU standarta BSRN: metodicheskie aspekty i pervye rezul'taty izmerenii // Optika atmosf. i okeana. 2022. V. 35, N 8. P. 670–678. DOI: 10.15372/AOO20220811.
37. Piskunova D., Chubarova N., Poliukhov A., Zhdanova E. Radiative regime according to the new RAD-MSU (BSRN) complex in Moscow: The roles of aerosol, surface albedo, and sunshine duration // Atmosphere (Basel). 2024. V. 15, N 2. P. 1–19. DOI:-10.3390/atmos15020144.
38. McArthur L.J.B. World Climate Research Programme–Baseline Surface Radiation Network (BSRN): Operations Manual Version 2.1. WCRP-121. WMO/TD. N 1274. 2005. 176 p. URL: https://epic.awi.de/id/eprint/45991/1/McArthur.pdf (last access: 11.01.2026).
39. Radiatsiya v oblachnoi atmosfere / pod red. E.M. Feigel'son. L.: Gidrometeoizdat, 1981. 280 p.
40. Nezval' E.I., Chubarova N.E., Grebner Yu., Omura A. Vliyanie atmosfernykh parametrov na dlinnovolnovuyu niskhodyashchuyu radiatsiyu i osobennosti ee rezhima v Moskve // Fiz. atmosf. i okeana. 2012. V. 48, N 6. P. 682.
41. Piskunova D., Chubarova N., Poliukhov A., Zhdanova E. Radiative regime in Moscow (55.7 N, 37.5 E) according to the new RAD-MSU(BSRN) // IOP Conf. Ser.: Earth Environ. Sci. 2025. V. 1522, N 1. DOI: 10.1088/1755-1315/1522/1/012011.