Articles | Volume 13, issue 6
https://doi.org/10.5194/tc-13-1695-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-13-1695-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jun 2019
Research article |
| 26 Jun 2019
| 26 Jun 2019
Validation of the sea ice surface albedo scheme of the regional climate model HIRHAM–NAOSIM using aircraft measurements during the ACLOUD/PASCAL campaigns
Evelyn Jäkel
CORRESPONDING AUTHOR
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
Johannes Stapf
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
Manfred Wendisch
Leipzig Institute for Meteorology (LIM), University of Leipzig, Leipzig, Germany
Marcel Nicolaus
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Wolfgang Dorn
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
Annette Rinke
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
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Cited
21 citations as recorded by crossref.
- Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic J. Kretzschmar et al. 10.5194/acp-20-13145-2020
- Evaluation of downward and upward solar irradiances simulated by the Integrated Forecasting System of ECMWF using airborne observations above Arctic low-level clouds H. Müller et al. 10.5194/acp-24-4157-2024
- Measurements and Modeling of Optical-Equivalent Snow Grain Sizes under Arctic Low-Sun Conditions E. Jäkel et al. 10.3390/rs13234904
- Effects of variable ice–ocean surface properties and air mass transformation on the Arctic radiative energy budget M. Wendisch et al. 10.5194/acp-23-9647-2023
- What determines the Arctic solar radiation energy budget at the surface most strongly: Clouds, surface albedo, or the solar zenith angle? E. Jäkel et al. 10.1016/j.jemets.2025.100016
- Wintertime Airborne Measurements of Ice Nucleating Particles in the High Arctic: A Hint to a Marine, Biogenic Source for Ice Nucleating Particles M. Hartmann et al. 10.1029/2020GL087770
- Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions J. Stapf et al. 10.5194/acp-20-9895-2020
- Variability and properties of liquid-dominated clouds over the ice-free and sea-ice-covered Arctic Ocean M. Klingebiel et al. 10.5194/acp-23-15289-2023
- Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone S. Becker et al. 10.5194/amt-15-2939-2022
- Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC T. Sperzel et al. 10.1038/s41597-023-02492-6
- On the importance to consider the cloud dependence in parameterizing the albedo of snow on sea ice L. Foth et al. 10.5194/tc-18-4053-2024
- Broadband albedo of Arctic sea ice from MERIS optical data C. Pohl et al. 10.5194/tc-14-165-2020
- Evaluation of the Sea-Ice Simulation in the Upgraded Version of the Coupled Regional Atmosphere-Ocean- Sea Ice Model HIRHAM–NAOSIM 2.0 W. Dorn et al. 10.3390/atmos10080431
- Observations and modeling of areal surface albedo and surface types in the Arctic E. Jäkel et al. 10.5194/tc-18-1185-2024
- A sensor-agnostic albedo retrieval method for realistic sea ice surfaces: model and validation Y. Zhou et al. 10.5194/tc-17-1053-2023
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV A. Mullen et al. 10.3389/frsen.2021.767593
- Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt 10.3390/rs15205016
- MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC M. Mech et al. 10.1038/s41597-022-01900-7
- Overview of the MOSAiC expedition: Snow and sea ice M. Nicolaus et al. 10.1525/elementa.2021.000046
- Recent developments of artificial intelligence methods for sea ice concentration monitoring using high-resolution imaging datasets M. Stofa et al. 10.1016/j.ecoinf.2025.103132
21 citations as recorded by crossref.
- Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic J. Kretzschmar et al. 10.5194/acp-20-13145-2020
- Evaluation of downward and upward solar irradiances simulated by the Integrated Forecasting System of ECMWF using airborne observations above Arctic low-level clouds H. Müller et al. 10.5194/acp-24-4157-2024
- Measurements and Modeling of Optical-Equivalent Snow Grain Sizes under Arctic Low-Sun Conditions E. Jäkel et al. 10.3390/rs13234904
- Effects of variable ice–ocean surface properties and air mass transformation on the Arctic radiative energy budget M. Wendisch et al. 10.5194/acp-23-9647-2023
- What determines the Arctic solar radiation energy budget at the surface most strongly: Clouds, surface albedo, or the solar zenith angle? E. Jäkel et al. 10.1016/j.jemets.2025.100016
- Wintertime Airborne Measurements of Ice Nucleating Particles in the High Arctic: A Hint to a Marine, Biogenic Source for Ice Nucleating Particles M. Hartmann et al. 10.1029/2020GL087770
- Reassessment of shortwave surface cloud radiative forcing in the Arctic: consideration of surface-albedo–cloud interactions J. Stapf et al. 10.5194/acp-20-9895-2020
- Variability and properties of liquid-dominated clouds over the ice-free and sea-ice-covered Arctic Ocean M. Klingebiel et al. 10.5194/acp-23-15289-2023
- Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone S. Becker et al. 10.5194/amt-15-2939-2022
- Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC T. Sperzel et al. 10.1038/s41597-023-02492-6
- On the importance to consider the cloud dependence in parameterizing the albedo of snow on sea ice L. Foth et al. 10.5194/tc-18-4053-2024
- Broadband albedo of Arctic sea ice from MERIS optical data C. Pohl et al. 10.5194/tc-14-165-2020
- Evaluation of the Sea-Ice Simulation in the Upgraded Version of the Coupled Regional Atmosphere-Ocean- Sea Ice Model HIRHAM–NAOSIM 2.0 W. Dorn et al. 10.3390/atmos10080431
- Observations and modeling of areal surface albedo and surface types in the Arctic E. Jäkel et al. 10.5194/tc-18-1185-2024
- A sensor-agnostic albedo retrieval method for realistic sea ice surfaces: model and validation Y. Zhou et al. 10.5194/tc-17-1053-2023
- Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges W. Huang et al. 10.3390/rs16050842
- An Operational Methodology for Validating Satellite-Based Snow Albedo Measurements Using a UAV A. Mullen et al. 10.3389/frsen.2021.767593
- Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt 10.3390/rs15205016
- MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC M. Mech et al. 10.1038/s41597-022-01900-7
- Overview of the MOSAiC expedition: Snow and sea ice M. Nicolaus et al. 10.1525/elementa.2021.000046
- Recent developments of artificial intelligence methods for sea ice concentration monitoring using high-resolution imaging datasets M. Stofa et al. 10.1016/j.ecoinf.2025.103132
Latest update: 02 Jul 2025
Short summary
The sea ice surface albedo parameterization of a coupled regional climate model was validated against aircraft measurements performed in May–June 2017 north of Svalbard. The albedo parameterization was run offline from the model using the measured parameters surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes. An adjustment of the variables and additionally accounting for cloud cover reduced the root-mean-squared error.
The sea ice surface albedo parameterization of a coupled regional climate model was validated...
