A Review of the Factors Influencing Arctic Mixed‐Phase Clouds: Progress and Outlook

Tan, Ivy; Sotiropoulou, Georgia; Taylor, Patrick C.; Zamora, Lauren; Wendisch, Manfred

doi:10.1002/9781119700357.ch5

Cited by 3 publications

(1 citation statement)

References 294 publications

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“…Conversely, sea ice loss can result in increases in cloud fraction and cloud optical depth (Tan et al, 2023) via local aerosol production (Ridley et al, 2016), or decreases in lower tropospheric stability (P. C. Taylor et al, 2022). However, the disparate representations of these processes in models (Schmale et al, 2021;P.…”

Section: The Influence Of Sea Ice Anomaly On the Cloud Feedbackmentioning

confidence: 99%

Top of the Atmosphere Shortwave Arctic Cloud Feedbacks: A Comparison of Diagnostic Methods

Coulbury,

Tan

2024

Geophysical Research Letters

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The cloud feedback may result in amplification or damping of Arctic warming. Two common techniques used to diagnose the top‐of‐the‐atmosphere cloud feedback are the Adjusted Cloud Radiative Effect (AdjCRE) method and the Cloud Radiative Kernel (CRK) method. We apply both to CMIP5 and CMIP6 model data, finding that the AdjCRE calculated Arctic shortwave cloud feedback is twice as correlated with sea ice loss in CMIP5, and four times in CMIP6, as the CRK method. We find that the CRK method produces Arctic all‐sky residual percentages exceeding 20% in 15 of 18 models. We use the CRK method to decompose the feedback in CMIP5 and CMIP6 finding that its median value changed from negative to positive driven by a less‐negative cloud optical depth feedback. Despite its lack of closure, we conclude that the CRK method is better suited for Arctic SW feedbacks as it is less impacted by surface albedo changes.

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Section: The Influence Of Sea Ice Anomaly On the Cloud Feedbackmentioning

confidence: 99%

Top of the Atmosphere Shortwave Arctic Cloud Feedbacks: A Comparison of Diagnostic Methods

Coulbury,

Tan

2024

Geophysical Research Letters

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Influence of Parameterization Changes on Arctic Low Cloud Properties and Cloud Radiative Effects in Two Versions of the HadGEM3 Atmospheric Model: GA7.1 and GA6

Taylor,

Boeke,

Bodas‐Salcedo

2024

Earth and Space Science

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Arctic clouds play a key role in Arctic climate variability and change; however, contemporary climate models struggle to simulate cloud properties accurately. Model‐simulated cloud properties are determined by the physical parameterizations and their interactions within the model configuration. Quantifying effects of individual parameterization changes on model‐simulated clouds informs efforts to improve models and provides insights on climate system behavior. This study quantities the influence of parameterization scheme changes on Arctic low cloud properties within the Hadley Center Global Environmental Model 3 atmospheric model using a suite of experiments where individual parameterization packages are changed between the two configurations. The results indicate, surprisingly, that single parameterization changes explain most of the cloud property changes, whereas multiple parameterizations, including non‐cloud schemes, contribute to cloud radiative effect differences. Non‐cloud parameterizations are those not used to compute time step cloud properties. We employ a three‐term decomposition to quantify contributions from (a) regime independent, (b) regime dependent, and (c) the regime frequency of occurrence changes. Decomposition results indicate that cloud property changes vary by meteorological regime, each term contributes differently to each cloud property change, and non‐cloud parameterization changes make substantial contributions to the LW and SW cloud radiative effects by affecting clear‐sky fluxes. The analysis provides insights on the role of non‐cloud parameterizations for setting cloud radiative effects, a pathway for cloud‐atmosphere circulation interactions, raises questions on the importance of infrequently occurring regimes to climate simulations, and on useful observational approaches for improving models.

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First Observational Evidence That Dust‐Driven Cloud Phase Changes Cool the Surface Over Summertime Arctic Sea Ice

Zamora,

Kahn

2024

Geophysical Research Letters

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Cloud phase has important impacts on Arctic surface temperatures, and circumstantial evidence suggests that dust aerosols have strong regional impacts on Arctic cloud phase. We used 7 years of satellite observations and model and reanalysis products to control for co‐varying meteorology, and to assess how dust and other aerosols impact cloud phase and cloud radiative effects over the summertime sea ice. We focus on clouds at 3 km, where dust modeling is most accurate. There is strong indication that dust aerosols caused about 4.5% of clouds below −15°C to change phase, with smaller effects at higher temperatures. Sulfate has a smaller impact on cloud phase. Dust is associated with cloud‐mediated surface cooling of up to a 6.3 W m−2 below single‐layer clouds at ∼3 km in June. This is the first observational study to constrain likely dust‐related cloud radiative effects over the summertime Arctic sea ice.

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A Review of the Factors Influencing Arctic Mixed‐Phase Clouds: Progress and Outlook

Cited by 3 publications

References 294 publications

Top of the Atmosphere Shortwave Arctic Cloud Feedbacks: A Comparison of Diagnostic Methods

Top of the Atmosphere Shortwave Arctic Cloud Feedbacks: A Comparison of Diagnostic Methods

Influence of Parameterization Changes on Arctic Low Cloud Properties and Cloud Radiative Effects in Two Versions of the HadGEM3 Atmospheric Model: GA7.1 and GA6

First Observational Evidence That Dust‐Driven Cloud Phase Changes Cool the Surface Over Summertime Arctic Sea Ice

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