Using satellite observations to evaluate model representation of Arctic mixed-phase clouds

Shaw, Jonah; McGraw, Zachary; Bruno, Olimpia; Storelvmo, Trude; Höfer, Stefan

doi:10.1002/essoar.10506728.1

Cited by 3 publications

(3 citation statements)

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“…The reduced NIMAX leads to lower ice number concentration, and hence increased size and increased fall speed and loss through sedimentation (Shaw et al, 2021) as well as affecting the balance of ice and supercooled liquid at high latitudes. In CAM6, this increases the supercooled liquid fraction when the NIMAX limiter is removed (Shaw et al, 2021). The CAM6 simulated supercooled liquid fraction is higher than observed in key regions (Gettelman et al, 2020).…”

Section: Ice Number Limitermentioning

confidence: 99%

Importance of Ice Nucleation and Precipitation on Climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)

Gettelman

Morrison

Eidhammer

et al. 2022

Preprint

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Abstract. Cloud microphysics is critical for weather and climate prediction. In this work, we document updates and corrections to the cloud microphysical scheme used in the Community Earth System Model (CESM) and other models. These updates include a new nomenclature for the scheme, and the ability to run the scheme on Graphics Processing Units (GPUs). The main science changes include removing an ice number limiter and associated changes to ice nucleation, adding vapor deposition onto snow, and introducing an implicit numerical treatment for sedimentation. We also detail the improvements in computational performance that can be achieved with GPU acceleration. We then show the impact of these scheme changes on (A) mean state climate, (B) cloud feedback response to warming and (C) aerosol forcing. We find that corrections are needed to the immersion freezing parameterization without a limit on ice number. We also find that the revised scheme produces less liquid and ice, but that this can be adjusted by changing the loss process for cloud liquid (autoconversion). Furthermore, there are few discernible effects of the PUMAS changes on cloud feedbacks, but some significant reductions in the magnitude of Aerosol Cloud Interactions (ACI). Small cloud feedback changes appear to be related to the implicit sedimentation scheme, with a number of factors affecting ACI.

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Section: Ice Number Limitermentioning

confidence: 99%

Importance of Ice Nucleation and Precipitation on Climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)

Gettelman

Morrison

Eidhammer

et al. 2022

Preprint

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“…1A). While lidar signals are usually thought to attenuate quickly in MPCs, the CALIOP lidar penetrates far enough into opaque clouds to retrieve information about two distinct MPC layers (Guzman et al, 2017;Shaw et al, 2022). Figure 1B shows that for opaque clouds, where the lidar signal is fully attenuated, the signal travels on average 1.67 ± 0.49 km (Fig.…”

Section: A Novel Approach To Constrain Mpcs In Climate Modelsmentioning

confidence: 93%

“…Additionally, observationally constraining MPC phase notably reduces the biases in top-of-the-atmosphere radiation when compared to CERES satellite observations over the current climate, which also enhances the robustness of our future climate projections. Our results -expanding the approach first tested for the Arctic in Shaw et al (2022) -provide a more sophisticated approach to constrain global mixed-phase cloud phase (Tan et al, 2016;Tan & Storelvmo, 2019;Cesana & Storelvmo, 2017). In our NorESM2 climate simulations the parameter choice for constraining cloud top and interior phase at the same time is notably different to only using an observational constraint on cloud interior phase.…”

Section: Introductionmentioning

confidence: 89%

Realistic representation of mixed-phase clouds increases future climate warming

Höfer

Hahn

Shaw

et al. 2023

Preprint

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Clouds are the main source of uncertainties when projecting climate change. Mixed-phase clouds (MPCs) that contain ice and supercooled-liquid particles are especially hard to constrain, and climate models neither agree on their phase nor their spatial extent. This is problematic, as models that underestimate contemporary supercooled-liquid in MPCs will underestimate future warming. Furthermore, it has recently been shown that supercooled-liquid water in MPCs is not homogeneously-mixed, neither vertically nor horizontally. However, while there have been attempts at observationally constraining MPCs to constrain uncertainties in future warming, all studies only use the phase of the interior of MPCs. Using novel satellite observations, and contrary to current knowledge, we show that MPCs are more liquid at the cloud top globally. We use these observations to constrain, for the first time, the cloud top phase in addition to the interior of MPCs in a global climate model, leading to +1C more 21st century warming in NorESM2 SSP5-8.5 climate projections. We anticipate that the difference between cloud top and interior phase in MPCs is an important new target metric for future climate model development, because similar MPC-related biases in future warming are likely present in many climate models.

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Reduction in the Arctic Surface Warm Bias in the NCAR CAM6 by Reducing Excessive Low-Level Clouds in the Arctic

et al. 2023

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High-latitude low clouds in the Northern winter have been known to be closely related to the Arctic surface air temperature by controlling downward longwave radiation, but Earth system models often fail to accurately simulate this relationship. In this study, we conducted a series of model experiments to examine the role of winter high-latitude low-level clouds in determining the Arctic surface temperature. Our findings show that low-level clouds play a significant role in regulating the Arctic surface temperature. We used the NCAR CAM6 model and compared the results of an unforced simulation run with those of an experiment using an empirical low-level cloud scheme to alleviate the typical overestimation of the low cloud fraction of state-of-the-art general circulation models at high latitudes. The unforced simulation exhibited excessive downward longwave radiation in the Arctic, resulting in a significant warm bias compared to reanalysis data. On the other hand, the experiment using a modified scheme more closely resembled the reanalysis data in terms of low-level cloud simulation. Overall, our study underscores the importance of accurately representing low-level clouds in high-latitude regions to reduce surface temperature bias in the model.

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Using satellite observations to evaluate model representation of Arctic mixed-phase clouds

Cited by 3 publications

References 0 publications

Importance of Ice Nucleation and Precipitation on Climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)

Importance of Ice Nucleation and Precipitation on Climate with the Parameterization of Unified Microphysics Across Scales version 1 (PUMASv1)

Realistic representation of mixed-phase clouds increases future climate warming

Reduction in the Arctic Surface Warm Bias in the NCAR CAM6 by Reducing Excessive Low-Level Clouds in the Arctic

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