Cloud optical depth feedbacks and climate modelling

Roeckner, Erich; Schlese, Ulrich; Biercamp, Joachim; Loewe, Peter

doi:10.1038/329138a0

Cited by 107 publications

(44 citation statements)

References 15 publications

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“…A few global models adopted prognostic cloud schemes (e.g., Smith 1990). Cloud feedback concepts of this period, such as the cloud water and ice content-temperature feedbacks explored in the simple RCE studies discussed previously were also explored in GCMs (e.g., Roeckner 1987;Le Treut and Li 1991;and others) yielding results similar to the earlier RCE studies. The need to include interactive cloud-radiation processes as opposed to fixed processes in GCMs began to be more fully appreciated by the modeling community.…”

Section: A Brief History Of Cloud Parameterizationmentioning

confidence: 86%

“…These simple models have generally fallen out of favor being replaced by more complex GCM climate models although many of the sensitivities derived from RCE models were broadly replicated in GCMs (Roeckner 1988;LeTreut and Li 1991;and others). More recently, however, the RCE paradigm has been revisited in a series of equilibrium experiments conducted using cloud-resolving models (CRMs).…”

Section: B Rce and Cloud-resolving Modelsmentioning

confidence: 99%

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Cloud Feedbacks in the Climate System: A Critical Review

2005

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This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earthatmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and ...

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Section: A Brief History Of Cloud Parameterizationmentioning

confidence: 86%

Section: B Rce and Cloud-resolving Modelsmentioning

confidence: 99%

Cloud Feedbacks in the Climate System: A Critical Review

2005

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“…Some studies with GCMs simulations showed that the changes in COT result in negative radiative feedbacks as climate warms (Roeckner et al, 1987;Mitchell et al, 1989) while others showed positive feedbacks (Tselioudis and Rossow, 1994;Chang and Coakley, 2006). Long records of space-borne measurements at global scale are actually needed in order to correctly map COT and better understand the radiative effects of clouds on climate changes, especially in response to anthropogenic activities and natural variations (Rossow and Schiffer, 1991).…”

Section: Introductionmentioning

confidence: 99%

A better understanding of cloud optical thickness derived from the passive sensors MODIS/AQUA and POLDER/PARASOL in the A-Train constellation

et al. 2012

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Abstract. Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and MODIS/AQUA in the ATrain constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are discussed.Comparisons of COT derived from POLDER and MODIS illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity.The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with MODIS values comparable to POLDER ones for liquid clouds and MODIS values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase is systematically larger.The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the cloudbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the sun-glint directions in case of broken cloud.

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“…Many researchers studied the effect of cloud microphysical feedback on climate change by means of radiative convective models (Charlock, 1982;Somerville and Remer,1984;Schlesinger and Roeckner, 1988;Stephens et al, 1990) and general circulation models (Roeckner et al, 1987;Cess et al, 1990;Slingo, 1990). In spite of these efforts, we…”

Section: Introductionmentioning

confidence: 99%

The Microphysical Feedback of Cirrus Cloud in Climate Change

Suzuki

Tanaka

Nakajima

1993

Journal of the Meteorological Society of Japan

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The feedback effects of cirrus clouds in climate change are investigated, taking account of the temperature dependence of both ice water content and size distribution. The sensitivity parameter which is defined as a sum of partial derivatives is calculated with an accurate radiation code applying the 4-stream discrete-ordinates method and the method of exponential-sum fitting for gaseous transmission (ESFT). Microphysical properties of cirrus clouds are parameterized in terms of the cloud temperature from the data of aircraft observations. The value of BH/BIWC]xB[IWC]/BT, i. e., a product of partial derivatives associated with ice water content feedback, is estimated to be 1.3-2.3 Wm-2C-1, meaning a positive feedback effect, and the value of BH/B[SD]xB[SD]/BT which is associated with size distribution feedback is estimated to be-0.1--1.8Wm-2C-1, meaning a negative feedback effect. The positive ice water content feedback is significantly cancelled by the negative size distribution feedback especially at cloud temperature in the vicinity of -45C. It is thus shown that the temperature dependence not only of ice water content but also of size distribution is important to estimate the microphysical feedback of cirrus cloud.

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Cloud optical depth feedbacks and climate modelling

Cited by 107 publications

References 15 publications

Cloud Feedbacks in the Climate System: A Critical Review

Cloud Feedbacks in the Climate System: A Critical Review

A better understanding of cloud optical thickness derived from the passive sensors MODIS/AQUA and POLDER/PARASOL in the A-Train constellation

The Microphysical Feedback of Cirrus Cloud in Climate Change

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