PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description

Wilson, Damian R.; Bushell, Andrew C.; Kerr-Munslow, Amanda M.; Price, J. D.; Morcrette, C. J.

doi:10.1002/qj.333

Cited by 292 publications

(332 citation statements)

References 33 publications

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“…The two model versions used are based on the UK Met Office Unified Model (MetUM), whereby one version uses a new generation prognostic cloud scheme (Wilson et al, 2008a) while the other employs the current (or control) diagnostic scheme used routinely in the model (Smith, 1990). The results presented here complement the study of Wilson et al (2008b) who compared the same two representations of clouds using climate simulations.…”

Section: Introductionmentioning

confidence: 89%

“…The largescale cloud scheme used in the model is described by either the diagnostic scheme of Smith (1990) with modifications (Wilson et al, 2004) or a new prognostic cloud scheme (Wilson and Bushell, 2007;Wilson et al, 2008a); note that the ice condensate is prognostic in both schemes. The cloud fraction from the simulation using the diagnostic scheme is the sum of the cloud fraction from the largescale cloud scheme of Smith (1990) and a diagnostic convective cloud fraction described by Gregory (1999).…”

Section: Description Of the Access/metum Single Column Modelmentioning

confidence: 99%

“…Diagnostic cloud schemes such as the Smith (1990) scheme are relatively simple in their representation of cloud properties and exhibit strongly constrained relationships between cloud variables. These relationships restrict the variability of the cloud fields and can produce unrealistic cloud properties (Wilson et al, 2008a). The new PC2 cloud scheme (prognostic cloud, prognostic condensate) was designed to be more realistic by allowing a greater number of degrees of freedom in the cloud variables.…”

Section: Description Of the Access/metum Single Column Modelmentioning

confidence: 99%

“…The reason for this is the assumptions relating to which microphysical processes cause a change in the prognostic cloud fractions. In PC2 ice cloud fraction reduces due to the microphysical processes of sublimation, melting and evaporation, with the fall of ice increasing the cloud fraction when the cloud fraction of the layer above is greater than that in the present layer (Wilson et al, 2008a). The process of deposition is assumed to increase the ice water content (IWC) but not the cloud fraction.…”

Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

“…Using the same assumptions that are made in PC2 for the effect of sublimation on the cloud fraction (Wilson et al, 2008a), the effect of depositional growth on the ice cloud fraction can be formulated as…”

Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

See 4 more Smart Citations

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Franklin

Jakob

Protat

et al. 2011

Quart J Royal Meteoro Soc

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Single column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud-scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three-dimensional model simulations of tropical variability.

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Section: Introductionmentioning

confidence: 89%

Section: Description Of the Access/metum Single Column Modelmentioning

confidence: 99%

Section: Description Of the Access/metum Single Column Modelmentioning

confidence: 99%

Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

Section: Comparison Of Cloud Variability Between the Prognostic And Dmentioning

confidence: 99%

See 3 more Smart Citations

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Franklin

Jakob

Protat

et al. 2011

Quart J Royal Meteoro Soc

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Predictability of the quasi‐biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales

Scaife

Athanassiadou

Andrews

et al. 2014

Geophysical Research Letters

149

177

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The predictability of the quasi-biennial oscillation (QBO) is examined in initialized climate forecasts extending out to lead times of years. We use initialized retrospective predictions made with coupled ocean-atmosphere climate models that have an internally generated QBO. We demonstrate predictability of the QBO extending more than 3 years into the future, well beyond timescales normally associated with internal atmospheric processes. Correlation scores with observational analyses exceed 0.7 at a lead time of 12 months. We also examine the variation of predictability with season and QBO phase and find that skill is lowest in winter. An assessment of perfect predictability suggests that higher skill may be achievable through improved initialization and climate modeling of the QBO, although this may depend on the realism of gravity wave source parameterizations in the models. Finally, we show that skilful prediction of the QBO itself does not guarantee predictability of the extratropical winter teleconnection that is important for surface winter climate prediction.

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The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model

2014

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The representation of clouds over the Southern Ocean in contemporary climate models remains a major challenge. A major dynamical influence on the structure of clouds is the passage of extratropical cyclones. They exert significant dynamical influences on the clouds in the dynamically active frontal regions as well as in the dynamically suppressed regions ahead and behind the cyclones. A cyclone compositing methodology is applied to a reanalysis and vertical profiles of cloudiness from CloudSat/CALIPSO to quantify the relationship between clouds and dynamics in extratropical cyclones over the Southern Ocean. It is found that the range of cloud fraction, vertical motion, and relative humidity changes considerably with height. There is a strong quasi‐linear relationship between the three variables which changes with altitude. After establishing the observed relationships, the methodology is applied to the Australian Community Climate and Earth System Simulator to evaluate the model's ability to simulate the identified cloud‐dynamics relationships. While the model is able to qualitatively reproduce the overall cloud structure, the circulation around the cyclone is generally too weak. As a result, the model fails to represent the observed cloud to dynamics relationship. This wrong relationship in the model leads to a misrepresentation of the cloud field manifested as either an error in the cloud fraction or as simulating the “right” clouds for the “wrong” reason. The result underscores the importance of relationship‐oriented model evaluation techniques over simple right or wrong assessments.

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PC2: A prognostic cloud fraction and condensation scheme. I: Scheme description

Cited by 292 publications

References 33 publications

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

Predictability of the quasi‐biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales

The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model

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