Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

Nam, Christine; Quaas, Johannes

doi:10.1002/grl.50945

Cited by 18 publications

(26 citation statements)

References 33 publications

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“…Yet, this feature does not hold true for S I except the case based on the 2B-GEOPROF data set with the −15 dBZ threshold. Our results also suggest that it is important to account for the influence of atmospheric stability due to the clear dependence of S POP on metrics like LTSS, though it is acknowledged that LTSS alone is an imperfect metric for isolating cloud regimes (e.g., Nam and Quaas, 2013). Different metrics associated with cloud regimes should be examined in the future to better understand the effect of cloud regimes on precipitation susceptibility.…”

Section: S X_y Under Different Stability Regimesmentioning

confidence: 80%

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

et al. 2018

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Abstract. Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol-cloud interactions and constraining aerosol indirect effects. However, large discrepancies exist in the previous satellite estimates of precipitation susceptibility. In this paper, multi-sensor aerosol and cloud products, including those from the CloudAerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) from June 2006 to April 2011 are analyzed to estimate precipitation frequency susceptibility S POP , precipitation intensity susceptibility S I , and precipitation rate susceptibility S R in warm marine clouds. We find that S POP strongly depends on atmospheric stability, with larger values under more stable environments. Our results show that precipitation susceptibility for drizzle (with a −15 dBZ rainfall threshold) is significantly different than that for rain (with a 0 dBZ rainfall threshold). Onset of drizzle is not as readily suppressed in warm clouds as rainfall while precipitation intensity susceptibility is generally smaller for rain than for drizzle. We find that S POP derived with respect to aerosol index (AI) is about one-third of S POP derived with respect to cloud droplet number concentration (CDNC). Overall, S POP demonstrates relatively robust features throughout independent liquid water path (LWP) products and diverse rain products. In contrast, the behaviors of S I and S R are subject to LWP or rain products used to derive them. Recommendations are further made for how to better use these metrics to quantify aerosolcloud-precipitation interactions in observations and models.

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Section: S X_y Under Different Stability Regimesmentioning

confidence: 80%

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

et al. 2018

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“…Medeiros and Stevens, 2009;Muhlbauer et al, 2014). These regimes can often be related to specific cloud types, but they are not necessarily a good constraint on the cloud properties if the regimes are not defined using the correct 5 parameters (Nam and Quaas, 2013;Leinonen et al, 2016). However, it is not required that these regimes map to the "Howard"…”

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confidence: 99%

Technical note: An automated cirrus classification

Gryspeerdt¹,

Quaas²,

Goren³

et al. 2017

Preprint

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Abstract. Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus clouds on the mechanism of formation, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus 5clouds by their formation mechanisms. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and in-situ. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that the regimes can provide extra information on the properties and origin of cirrus that could not be provided by the retrieved cloud properties or reanalysis data alone. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud 10 processes.

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“…We computed yearly mean values in six stratocumulus regions (see Fig. 4) and compared the differences in these six regions between simulations with present-day and preindustrial aerosol emissions and then took a weighted average (Nam and Quaas, 2013, used a similar approach to evaluate boundary layer clouds in satellite and model data). This raises the statistical significance of some model variables globally as the difference in the simulations in some stratocumulus regions can be larger than the internal variability.…”

Section: Methodology and Observational Datamentioning

confidence: 99%

Impact of the representation of marine stratocumulus clouds on the anthropogenic aerosol effect

et al. 2014

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Abstract. Stratocumulus clouds are important for climate as they reflect large amounts of solar radiation back into space. However they are difficult to simulate in global climate models because they form under a sharp inversion and are thin. A comparison of model simulations with the ECHAM6-HAM2 global aerosol climate model to observations, reanalysis and literature data revealed too strong turbulent mixing at the top of stratocumulus clouds and a lack of vertical resolution. Further reasons for cloud biases in stratocumulus regions are the too "active" shallow convection scheme, the cloud cover scheme and possibly too low subsidence rates.To address some of these issues and improve the representation of stratocumulus clouds, we made three distinct changes to ECHAM6-HAM2. With a "sharp" stability function in the turbulent mixing scheme we have observed, similar to previous studies, increases in stratocumulus cloud cover and liquid water path. With an increased vertical resolution in the lower troposphere in ECHAM6-HAM2 the stratocumulus clouds form higher up in the atmosphere and their vertical extent agrees better with reanalysis data. The recently implemented in-cloud aerosol processing in stratiform clouds is used to improve the aerosol representation in the model.Including the improvements also affects the anthropogenic aerosol effect. In-cloud aerosol processing in ECHAM6-HAM2 leads to a decrease in the anthropogenic aerosol effect in the global annual mean from −1.19 Wm −2 in the reference simulation to −1.08 Wm −2 , while using a "sharp" stability function leads to an increase to −1.34 Wm −2 . The results from the simulations with increased vertical resolution are diverse but increase the anthropogenic aerosol effect to −2.08 Wm −2 at 47 levels and −2.30 Wm −2 at 95 levels.

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Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

Cited by 18 publications

References 33 publications

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

Technical note: An automated cirrus classification

Impact of the representation of marine stratocumulus clouds on the anthropogenic aerosol effect

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