Comment on egusphere-2023-349 DOI Creative Commons
Zhangcheng Pei, Sonya L. Fiddes, John French

et al.

Published: May 1, 2023

Abstract. As a long-standing problem in climate models, large positive shortwave radiation biases exist at the surface over Southern Ocean, impacting accurate simulation of sea temperature, atmospheric circulation, and precipitation. Underestimations low-level cloud fraction liquid water content are suggested to predominantly contribute these biases. Most model evaluations for focus on summer rely satellite products, which have their own limitations. In this work, we use surface-based observations Macquarie Island provide first long-term, seasonal evaluation both downwelling longwave Australian Community Climate Earth System Simulator Atmosphere-only Model Version 2 (ACCESS-AM2) Ocean. The capacity Clouds Earth’s Radiant Energy (CERES) product simulate is also investigated. We utilise novel lidar simulator, Automatic Lidar Ceilometer Framework (ALCF) all-sky camera investigate how influenced by properties. Overall, find an overestimation +9.5 ± 33.5 W m−2 fluxes underestimation -2.3 13.5 ACCESS-AM2 conditions, with more pronounced +25.0 48.0 occurring summer. CERES presents +8.0 18.0 -12.1 12.2 conditions. For radiative effect (CRE) biases, there +4.8 28.0 -7.9 20.9 CERES. An associated fraction. occurrence less clear suggest that modelled phase having impact Our results show require further development reduce not just but clear-sky

Language: Английский

High‐Resolution Thermal Imaging in the Antarctic Marginal Ice Zone: Skin Temperature Heterogeneity and Effects on Heat Fluxes DOI Creative Commons
Ippolita Tersigni, Alberto Alberello, Gabriele Messori

et al.

Earth and Space Science, Journal Year: 2023, Volume and Issue: 10(9)

Published: Sept. 1, 2023

Abstract Insufficient in situ observations from the Antarctic marginal ice zone (MIZ) limit our understanding and description of relevant mechanical thermodynamic processes that regulate seasonal sea cycle. Here we present high‐resolution thermal images ocean surface complementary measurements atmospheric variables were acquired underway during one austral winter spring expedition Atlantic Indian sectors Southern Ocean. Skin temperature data cover used to estimate partitioning heterogeneous calculate heat fluxes compare with ERA5 reanalyses. The MIZ was composed different but relatively regularly distributed types sharp gradients. surface‐weighted skin compared well reanalyses due a compensation errors between fraction floe temperature. These uncertainties determine dominant source inaccuracy for as computed observed variables. In spring, type distribution more irregular, alternation large open water fractions even 400 km edge. homogeneous did not produce substantial fluxes. discrepancies relative reanalysis are however larger than attributed biases variables, downward solar radiation being most critical.

Language: Английский

Citations

4
Assessing the cloud radiative bias at Macquarie Island in the ACCESS-AM2 model DOI Creative Commons
Zhangcheng Pei, Sonya L. Fiddes,

W. R. French

et al.

Atmospheric chemistry and physics, Journal Year: 2023, Volume and Issue: 23(23), P. 14691 - 14714

Published: Nov. 29, 2023

Abstract. As a long-standing problem in climate models, large positive shortwave radiation biases exist at the surface over Southern Ocean, impacting accurate simulation of sea temperature, atmospheric circulation, and precipitation. Underestimations low-level cloud fraction liquid water content are suggested to predominantly contribute these biases. Most model evaluations for focus on summer rely satellite products, which have their own limitations. In this work, we use surface-based observations Macquarie Island provide first long-term, seasonal evaluation both downwelling longwave Australian Community Climate Earth System Simulator Atmosphere-only Model version 2 (ACCESS-AM2) Ocean. The capacity Clouds Earth’s Radiant Energy (CERES) product simulate is also investigated. We utilize novel lidar simulator, Automatic Lidar Ceilometer Framework (ALCF), all-sky camera investigate how influenced by properties. Overall, find an overestimation +9.5±33.5 W m−2 fluxes underestimation -2.3±13.5 ACCESS-AM2 conditions, with more pronounced +25.0±48.0 occurring summer. CERES presents +8.0±18.0 -12.1±12.2 conditions. For radiative effect (CRE) biases, there +4.8±28.0 -7.9±20.9 CERES. An associated underestimated occurrence. suggest that modeled phase having impact Our results show require further development reduce not just but clear-sky

Language: Английский

Citations

4
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model DOI Creative Commons
Sonya L. Fiddes, Marc Mallet, Alain Protat

et al.

Geoscientific model development, Journal Year: 2024, Volume and Issue: 17(7), P. 2641 - 2662

Published: April 11, 2024

Abstract. The evaluation and quantification of Southern Ocean cloud–radiation interactions simulated by climate models are essential in understanding the sources magnitude radiative bias that persists for this region. To date, most methods focus on specific synoptic or cloud-type conditions do not consider entirety Ocean's cloud regimes at once. Furthermore, it is difficult to directly quantify complex non-linear role different properties have modulating effect. In study, we present a new method model evaluation, using machine learning can once identify complexities within system individual contributions. this, use an XGBoost (eXtreme Gradient Boosting) predict nudged version Australian Community Climate Earth System Simulator – Atmosphere-only model, property biases as predictive features. We find explain up 55 % from these alone. then apply SHAP (SHapley Additive exPlanations) feature importance analysis each plays predicting bias. liquid water path largest contributor over Ocean, though important regional dependencies exist. test usefulness evaluating perturbations clearly responses, including compensating errors.

Language: Английский

Citations

0
Unlocking potential: A case study on reducing shortwave radiation bias in the Southern Ocean through improved cloud phase retrievals based on machine learning DOI Open Access
Willi Schimmel, Carola Barrientos Velasco, Jonas Witthuhn

et al.

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: April 16, 2024

There are significant gaps in both experimental and theoretical understanding of mixed-phase clouds, their impacts on the hydrological cycle as well effects atmospheric radiation. Accurately identifying liquid water layers clouds is crucial for estimating cloud radiative effects. A proof-of-concept study utilizing a machine-learning-based liquid-layer detection method called VOODOO presented. This was applied alongside single-column transfer model to compare downwelling shortwave fluxes detected by standard Cloudnet processing chain ground-based pyranometer observations. Our findings reveal that creates more realistic content distributions significantly influences profiles heating rates. Moreover, our demonstrates substantial enhancement estimation compared conventional Cloudnet. Specifically, we observe remarkable reduction mean absolute error simulated radiation at surface 70\%, particularly homogeneous conditions. The percentage SW between observations 44\%, while VOODOO+Cloudnet reduces this 8\%. Overall, results underscore potential provide new insights into deep which were previously inaccessible using traditional lidar-based remote sensing techniques.

Language: Английский

Citations

0
Antarctic sea ice surface temperature bias in atmospheric reanalyses induced by the combined effects of sea ice and clouds DOI Creative Commons
Zhaohui Wang, Alexander Fraser, Phillip Reid

et al.

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Oct. 2, 2024

Language: Английский

Citations

0
Comment on egusphere-2023-349 DOI Creative Commons
Zhangcheng Pei, Sonya L. Fiddes, John French

et al.

Published: May 1, 2023

Abstract. As a long-standing problem in climate models, large positive shortwave radiation biases exist at the surface over Southern Ocean, impacting accurate simulation of sea temperature, atmospheric circulation, and precipitation. Underestimations low-level cloud fraction liquid water content are suggested to predominantly contribute these biases. Most model evaluations for focus on summer rely satellite products, which have their own limitations. In this work, we use surface-based observations Macquarie Island provide first long-term, seasonal evaluation both downwelling longwave Australian Community Climate Earth System Simulator Atmosphere-only Model Version 2 (ACCESS-AM2) Ocean. The capacity Clouds Earth’s Radiant Energy (CERES) product simulate is also investigated. We utilise novel lidar simulator, Automatic Lidar Ceilometer Framework (ALCF) all-sky camera investigate how influenced by properties. Overall, find an overestimation +9.5 ± 33.5 W m−2 fluxes underestimation -2.3 13.5 ACCESS-AM2 conditions, with more pronounced +25.0 48.0 occurring summer. CERES presents +8.0 18.0 -12.1 12.2 conditions. For radiative effect (CRE) biases, there +4.8 28.0 -7.9 20.9 CERES. An associated fraction. occurrence less clear suggest that modelled phase having impact Our results show require further development reduce not just but clear-sky

Language: Английский

Citations

0