A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

Weverberg, Kwinten Van; Morcrette, C. J.; Boutle, Ian

doi:10.1175/mwr-d-20-0230.1

Cited by 8 publications

(14 citation statements)

References 48 publications

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“…It tends to underestimate the cloud cover that would be expected from the moist part, as it assumes the grid box mean RH is representative of uniform layer conditions. Recently, Weverberg et al (2021b) developed a cloud cover parameterisation ideally suited to these situations: the cloud fraction and water content are derived from a bimodal probability distribution function representing the sub-grid saturation variations, with a dry and a moist mode. The scheme improves several cloud properties in regional simulations compared with schemes assuming a unimodal PDF, such as implicitly assumed in the Sundqvist scheme (Weverberg et al, 2021a).…”

Section: Discussionmentioning

confidence: 99%

Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3

2021

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Abstract. In this study, we implement a vertical grid refinement scheme in the radiation routine of the global aerosol–climate model ECHAM-HAM, aiming to improve the representation of stratocumulus clouds and address the underestimation of their cloud cover. The scheme is based on a reconstruction of the temperature inversion as a physical constraint for the cloud top. On the refined grid, the boundary layer and the free troposphere are separated and the cloud's layer is made thinner. The cloud cover is recalculated either by conserving the cloud volume (SC-VOLUME) or by using the Sundqvist cloud cover routine on the new grid representation (SC-SUND). In global climate simulations, we find that the SC-VOLUME approach is inadequate, as there is a mismatch, in most cases, between the layer of the inversion and the layer of the stratocumulus cloud, which prevents its application and is itself likely caused by an overly low vertical resolution. Additionally, we find that the occurrence frequency of stratocumulus clouds is underestimated in ECHAM-HAM, limiting a priori the potential benefits of a scheme like SC-VOLUME targeting only cloud amount when present. With the SC-SUND approach, the possibility for new clouds to be formed on the refined grid results in a large increase in mean total cloud cover in stratocumulus regions. In both cases, however, the changes exerted in the radiation routine are too weak to produce a significant improvement in the simulated stratocumulus cloud cover. We investigate and discuss the reasons behind this. The grid refinement scheme could be used more effectively for this purpose if implemented directly in the model's cloud microphysics and cloud cover routines, but other possible ways forward are also discussed.

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Section: Discussionmentioning

confidence: 99%

Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3

2021

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“…This is the version of the PC2 scheme that is used in the RA2‐T configuration. A fourth configuration (“bimodal”) uses the diagnostic bimodal CF scheme (Van Weverberg et al ., 2021b). This scheme was developed to better link the subgrid thermodynamic variability with assumptions in the boundary‐layer scheme and to account for the impact of coexistence of two modes of variability within a grid box near entrainment zones.…”

Section: Model Set‐up and Observationsmentioning

confidence: 99%

“…The latter simply assumes that the CF is one as soon as some condensate is present. In addition, a new approach was tested, which combines the diagnostic bimodal scheme for liquid clouds, following Van Weverberg et al (2021b) with prognostic ice clouds, following Wilson et al (2008). This hybrid scheme aims at combining the strengths of PC2 at predicting precipitation and high clouds with the benefits of the bimodal scheme for low cloud cover.…”

Section: Introductionmentioning

confidence: 99%

“…(2008)), leading to more organized precipitation and better high‐level cloud cover. Low clouds in the midlatitudes, however, are much better captured by a diagnostic CF scheme, either by applying a bias correction on top of the Smith (1990) parametrization, or by using the recently developed bimodal CF scheme (Van Weverberg et al ., 2021b). So far, it has proven difficult to modify either the fully prognostic or fully diagnostic parametrizations to create a single configuration that performs well for both cloud and precipitation‐based metrics across the globe.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, a new approach was tested, which combines the diagnostic bimodal scheme for liquid clouds, following Van Weverberg et al . (2021b) with prognostic ice clouds, following Wilson et al . (2008).…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of cloud‐radiative effects to cloud fraction parametrizations in tropical, midlatitude, and arctic kilometre‐scale simulations

Weverberg

Morcrette

2022

Quart J Royal Meteoro Soc

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The regional atmosphere (RA) configuration of the Met Office Unified Model currently requires different cloud fraction parametrizations (CFPs) for tropical and midlatitude simulations. To explore the scope for unification of these two RA configurations, this article presents a detailed evaluation of simulations over tropical, midlatitude, and arctic domains, with two different diagnostic CFPs: a prognostic CFP, and no CFP at all. Furthermore, a novel, hybrid approach was used that treats liquid cloud diagnostically and ice cloud prognostically. Using observations from three US Department of Energy Atmospheric Radiation Measurement supersites, it is shown that none of these CFPs stands out as superior over all domains. Over the frequently overcast Arctic, the all-or-nothing approach best captures the cloud radiative properties. Conversely, CFPs are of benefit in regions with frequent partial cloudiness, such as the midlatitudes and the Tropics. However, their improved cloud radiative properties often hide an error compensation. All models underestimate overcast, low-base cloud with small water paths in convective environments. In addition, midlatitude overcast, low-base, optically thick clouds in the morning, possibly associated with overnight convection, are frequently too broken. Diagnostic schemes compensate for these errors by producing spurious, scattered afternoon cloud, which could be due to a correct cloud response to too eager convective initiation. Winter clouds over the midlatitudes are improved when liquid cloud is represented diagnostically with a bimodal saturation-departure probability density function, without error compensation. Although it is difficult to unify the RA across the globe around a single CFP scheme, the newly proposed hybrid scheme performs reasonably well for cloud cover across all regions. It also exhibits short-wave biases that are smaller than most other configurations and is less affected by excessive liquid water paths and compensating errors than fully diagnostic schemes are. Surface precipitation is fairly insensitive to the CFP in the simulations shown here.

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Utility of thermal remote sensing for evaluation of a high‐resolution weather model in a city

Hall,

Blunn,

Grimmond

et al. 2024

Quart J Royal Meteoro Soc

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Progress in high‐resolution numerical weather prediction (NWP) for urban areas will require new modelling approaches and extensive evaluation. Here, we exploit land surface temperature (LST) data from Landsat‐8 to assess 100 m resolution NWP for London (UK) on four cloud‐free days. The LST observations are directional radiometric temperatures with non‐negligible uncertainties. We consider the challenges of informative comparison between the Landsat LST and the NWP scheme's internal characterisation of the complete surface temperature. The LST spatial coverage allows large‐scale observation–model differences to be explored. In one case, obvious spatial artifacts in the NWP surface temperature are observed relative to the Landsat LST. These are found to be related to the NWP's initial method of downscaling of soil moisture using soil properties. Updated model runs have higher spatial correlation between model and Landsat LST. In cases where meteorological conditions favour the formation of horizontal convective rolls, warmer air temperatures associated with updraughts in the mixed layer extend inappropriately to the urban surface. This manifests as warm stripes in the model surface temperature that are not present in the Landsat LST. NWP–Landsat LST differences are larger in more built‐up areas on days nearer summer solstice. This is largely attributed to urban thermal anisotropy, as Landsat preferentially views warmer urban surfaces, whereas the model LST represents all surfaces. We evaluate two approaches to quantify this sampling effect, but further work is needed to fully constrain it and facilitate more informative model evaluation.

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A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

Cited by 8 publications

References 48 publications

Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3

Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3

Sensitivity of cloud‐radiative effects to cloud fraction parametrizations in tropical, midlatitude, and arctic kilometre‐scale simulations

Utility of thermal remote sensing for evaluation of a high‐resolution weather model in a city

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