Towards an improved treatment of unresolved cloud-radiation interaction in weather and climate models
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The interaction between radiation and clouds represents a persistent source of uncertainty in numerical weather and climate prediction. Clouds are inherently complex meteorological phenomena, appearing in an immense variety of geometrical shapes and exhibiting highly variable degrees of heterogeneity. A physically consistent and computationally efficient coupling of three-dimensional cloud structures with the solar and thermal radiative field thereby remains one of the greatest challenges in the atmospheric science community. The present thesis aims to make progress towards an improved treatment of the unresolved cloud-radiation interchange for both regional and global modeling applications.
The first dissertation objective is to quantify the radiative bias in regional models for a realistically evolving shallow cumulus cloud field. The bias dependence on various input parameters of radiation schemes such as solar zenith angle, surface albedo, cloud cover and liquid water path is examined. Nighttime and daytime biases within the cloud-layer and at the surface are thoroughly investigated and evaluated against a high-resolution three-dimensional benchmark computation. The focus is laid on quantifying the regional-scale model bias arising from two chief shortcomings. First, the poor representation of unresolved cloudiness, which is normally approximated as a series of horizontally homogeneous partially cloudy layers. Second, the intrinsic constraint of one-dimensional radiation schemes, employing merely two streams for capturing the upward and downward radiative flux, but entirely neglecting the grid- and subgrid-scale horizontal photon flow. Since it is unclear which error source is dominant at the scale of regional modeling where these multiple issues intersect, the bias stemming from the latter drawback is simultaneously assessed. The principal findings highlight the importance of an improved cloud representation even at the regional scale.
The second dissertation objective is to advance the cloud-radiation interaction parameterization in coarse-resolution global models, focusing on the issues related to misrepresentation of cloud horizontal inhomogeneity. This subject is tackled with the state-of-the-art Tripleclouds radiative solver, the fundamental feature of which is the inclusion of the optically thicker and thinner cloud fraction. The research challenge is to optimally set the pair of cloud condensates characterizing the two cloudy regions and the corresponding geometrical split of layer cloudiness. A diverse cloud field data set was collected for the analysis, comprising case studies of cumulus, stratocumulus, cirrus and cumulonimbus. The primary goal is to test the validity of global cloud variability estimate along with various condensate distribution assumptions. More sophisticated parameterizations are subsequently explored, optimizing the treatment of overcast as well as extremely heterogeneous cloudiness. The radiative diagnostics including atmospheric heating rate and net surface flux are for the first time consistently studied using the Tripleclouds method. The performance of Tripleclouds mostly significantly surpasses the conventional calculation on horizontally homogeneous cloudiness. The effect of horizontal photon transport is further quantified. The overall conclusions are intrinsically different for each particular cloud type examined, encouraging endeavors to enhance the use of cloud regime dependent methodologies in next-generation atmospheric models.
The major technical effort undertaken within the scope of this work was the design of the classic two-stream radiation scheme supporting homogeneous partial cloudiness and its subsequent extension to incorporate the Tripleclouds concept. Both algorithms were implemented in the libRadtran radiative library, promoted to be utilized for further unraveling of key scientific mysteries related to cloud-radiation interplay.Keywords:
Albedo (alchemy)
Parametrization (atmospheric modeling)
Liquid water path
Cloud fraction
Solar zenith angle
Zenith
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Unified Model
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The representation of tropical cloud and its radiative effects in the Hadley Centre climate model are evaluated using a combination of Earth observation data and meteorological reanalyses. It is shown that useful information regarding the model’s physical parametrizations can be obtained by considering cloud radiative effects and cloud types in terms of ‘dynamical regimes’, defined in terms of sea surface temperature and large-scale vertical motion. In addition to comparisons with observed top-of-atmosphere radiation budget parameters and total cloud amount, information is obtained through direct comparisons of International Satellite Cloud Climatology Project (ISCCP) cloud types, defined according to cloud top pressure and optical depth, with corresponding model diagnostics. An analysis of the atmosphereonly model, HadAM3, demonstrates how errors in the albedo and outgoing long-wave radiation can be related to the simulation of particular cloud types in the different dynamical regimes. Inconsistencies between the simulations of the various cloud types and the top-of-atmosphere radiation budget are also highlighted. A version of the model including several new cloud-related parametrizations is then examined. A more consistent comparison with the observed radiation budget and cloud amounts is obtained, although deficiencies in the simulation still remain. A parametrization for the radiative effects of convective anvils and the impact of a new boundary layer mixing scheme are examined in more detail. Finally, it is shown how the climate model’s ability to simulate the observed interannual variability of cloud in the equatorial Pacific follows directly from the analysis according to dynamical regimes.
Parametrization (atmospheric modeling)
Cloud albedo
Albedo (alchemy)
Cloud forcing
Radiative flux
Cloud feedback
Cloud top
Cloud height
Cloud physics
Atmospheric models
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The overlap properties of ∼850 snapshots of convective cloud fields generated by a cloud‐resolving model are studied and compared with previously published results based on cloud radar observations. Total cloud cover is overestimated by the random overlap assumption but underestimated by the maximum overlap assumption and two standard implementations of the combined maximum/random overlap assumption. When the overlap of two layers is examined as a function of vertical separation distance, the value of the parameter α measuring the relative weight of maximum (α = 1) and random (α = 0) overlap decreases in such a way that only layers less than 1 km apart can be considered maximally overlapped, while layers more than 5 km apart are essentially randomly overlapped. The decrease of α with separation distance Δ z is best expressed by a power law, which may not, however, be suitable for parameterization purposes. The more physically appropriate exponential function has slightly smaller goodness of fit overall but still gives very good fits for Δ z between 0 and 5 km, which is the range of separation distances that would be of most importance in any overlap parameterization for radiative transfer purposes.
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While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown.
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Abstract A cloud parametrization scheme which allows for low, medium, high and convective clouds has been developed from GATE data for use in the Meteorological Office 11‐layer tropical model. The problems involved in using synoptic observations to derive methods of predicting clouds are discussed. Only limited success was obtained in relating observed cloud amounts to relative humidity and atmospheric temperature structure. The restrictions imposed on the cloud scheme by the model's resolution and by its inability to produce a perfect simulation are considered. In the light of these difficulties a simple approach was adopted based on the assumption that condensation on the smallest scales is part of a larger‐scale condensation regime related to the synoptic scale situation. The scheme has been designed to reproduce the main features of a cloud field by relating the large‐scale meteorological features associated with a cloud distribution to model variables. Low, medium and high cloud amounts are determined from a quadratic relationship with relative humidity. Low cloud has also been related to the temperature lapse rate in an attempt to model the persistent areas of sub‐tropical stratocumulus occurring under inversions. A relative humidity relationship is inappropriate for convective cloud which has, therefore, been related to the convective mass flux calculated in the convection scheme of the model. The scheme has been reasonably successful in predicting the cloudiness associated with the ITCZ and the NE. and SE. trades. The cloud fields showed a good degree of coherence from day to day and there were no signs of unrealistic feedbacks between radiation, cloud and dynamics.
Parametrization (atmospheric modeling)
Liquid water content
Cloud physics
Cloud top
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Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while the mostly dry mountain-breeze circulations force an additional component that results in semi-diurnal variations near the coast. A series of numerical tests, however, reveal sensitivity of the simulations to the choice of vertical grid, limiting the possibility of solid quantitative statements on the amplitudes and phases of the diurnal and semidiurnal components across the domain. According to our experiments, the Mellor-Yamada-Nakanishi-Niino (MYNN) boundary layer scheme and the WSM6 microphysics scheme is the combination of schemes that performs best. For that combination, mean cloud cover, liquid water path, and cloud depth are fairly wellsimulated, while mean cloud top height remains too low in comparison to observations. Both microphysics and boundary layer schemes contribute to the spread in liquid water path and cloud depth, although the microphysics contribution is slightly more prominent. Boundary layer schemes are the primary contributors to cloud top height, degree of adiabaticity, and cloud cover. Cloud top height is closely related to surface fluxes and boundary layer structure. Thus, our study infers that an appropriate tuning of cloud top height would likely improve the low-cloud representation in the model. Finally, we show that entrainment governs the degree of adiabaticity, while boundary layer decoupling is a control on cloud cover. In the intercomparison study using WRF single-column model experiments, most parameterizations show a poor agreement of the vertical boundary layer structure when compared with large-eddy simulation models. We also implement a new Total-Energy/Mass- Flux boundary layer scheme into the WRF model and evaluate its ability to simulate both stratocumulus and shallow cumulus clouds. Result comparisons against large-eddy simulation show that this advanced parameterization based on the new Eddy-Diffusivity/Mass-Flux approach provides a better performance than other boundary layer parameterizations.
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Plane-parallel radiative transfer modeling of clouds in GCMs is thought to be an inadequate representation of the effects of real cloudiness. A promising new approach for studying the effects of cloud horizontal inhomogeneity is stochastic radiative transfer, which computes the radiative effects of ensembles of cloud structures described by probability distributions. This approach is appropriate because cloud information is inherently statistical, and it is the mean radiative effect of complex 3D cloud structure that is desired. 2 refs., 1 fig.
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Uncertainty in cloud feedback is the leading cause of discrepancy in model predictions of climate change. The use of observed or model-simulated radiative fluxes to diagnose the effect of clouds on climate sensitivity requires an accurate understanding of the distinction between a change in cloud radiative forcing and a cloud feedback. This study compares simulations from different versions of the GFDL Atmospheric Model 2 (AM2) that have widely varying strengths of cloud feedback to illustrate the differences between the two and highlight the potential for changes in cloud radiative forcing to be misinterpreted.
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This dissertation describes various aspects of improvements made in the representation of
clouds in the global forecast model of the European Centre of Medium-Range Weather Fore-
casts (ECMWF). Cloud parametrization has long been identified as one of the most crucial
and uncertain aspects in General Circulation Models (GCMs) of the atmosphere, which are
used for both Numerical Weather Prediction and the simulation of climate. It is therefore
important to constantly monitor and improve the performance of cloud parametrizations in
those models.
The first part of the work describes the implementation of an existing cloud parametrization
into ECMWF's forecasting system with special attention to a new treatment of the prognos-
tic cloud variables in data assimilation. This is followed by an analysis of the performance
of the parametrization during a 15-year long data assimilation experiment carried out in the
context of the ECMWF reanalysis project. It is shown that despite an overall good perfor-
mance, several weaknesses in the simulation of clouds exist. Subtropical stratocumulus and
extratropical cloudiness are underestimated, while the cloud fraction in the trade cumulus
areas and in the Intertropical Convergence Zone is overestimated.
In the second part of the study detailed revisions of the parametrization of cloud generation
by convective and non-convective processes are described. A consistent new description of
cloud generation by convection is derived using the mass-
ux approach. Furthermore an
improved description of the generation of clouds by non-convective processes is introduced.
The superiority of the new formulation compared to the existing one is demonstrated and
links to other approaches to cloud parametrization are established.
The third part of the work studies the role of vertically varying cloud fraction for the descrip-
tion of microphysical processes. It is shown that the commonly used approach of representing
precipitation in GCMs by means of grid-averaged quantities leads to serious errors in the
parametrization of various physical processes such as the evaporation of precipitation, with
severe consequences for the model's hydrological cycle. A new parametrization of the eects
of vertically-varying cloud fraction based on a separation of cloudy and clear-sky precipita-
tion
uxes is developed and its performance assessed. It is shown that this parametrization
alleviates most of the identied problems and thereby more realistically describes the pre-
cipitation physics in the presence of cloud fraction variations.
The final part of the dissertation takes a critical look at the way the results of cloud
parametrizations are evaluated today. A number of studies using a variety of data sources
and modelling approaches are described and the need for a coordinated use of the various
existing validation techniques is highlighted. A strategy to achieve such coordination is
proposed.
This work provides contributions to virtually all facets of the development of cloud parame-
trizations. It combines theoretical aspects with the use of a variety of modelling approaches
and data sources for the assessment of the performance of the parametrization. All model
improvements described here are now part of the operational version of the ECMWF forecast
model.
Parametrization (atmospheric modeling)
Atmospheric Circulation
Extratropical cyclone
Atmospheric models
Cloud physics
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Citations (31)