ALBERT

Description: Thirty-three Landsat TM scenes of California stratocumulus cloud fields were acquired as part of the FIRE Marine Stratocumulus Intensive Field Observations in July 1987. They exhibit a wide variety of stratocumulus structures. Analysis has so far focused upon the July 7 scene, in which aircraft from NASA, NCAR, and the British Meteorological Office repeatedly gathered data across a stratocumulus-fair weather cumulus transition. The aircraft soundings validate the cloud base temperature threshold determined by spatial coherence analysis of the TM thermal band. Brightness variations in the stratocumulus region exhibit a -5/3 power-law decrease of the wavenumber spectra for scales larger than the cloud thickness, about 200 m, changing to a -3 power at smaller scales. Observations by an upward-looking three-channel microwave radiometer on San Nicolas Island also show the -5/3 power-law in total integrated liquid water, suggesting that the largest-scale TM brightness variations are primarily due to variations in the liquid water. The Kolmogorov 5/3 power suggests that for some purposes liquid water in turbulent stratocumulus clouds may be treated as a passive scalar, simply reflecting variations in vertical velocity. This may be tested using the velocities measured by the aircraft.

Description: There is a growing body of observational evidence on inhomogeneous cloud structure, most recently from the extensive measurements of the FIRE field program. Knowledge of cloud structure is important because it strongly influences the cloud radiative properties, one of the major factors in determining the global energy balance. Current atmospheric circulation models use plane-parallel radiation, so that the liquid water in each gridbox is assumed to be uniform, which gives an unrealistically large albedo. In reality cloud liquid water occupies only a subset of each gridbox, greatly reducing the mean albedo. If future climate models are to treat the hydrological cycle in a manner consistent with energy balance, a better treatment of cloud liquid is needed. FIRE concentrated upon two cloud types of special interest: cirrus and marine stratocumulus. Cirrus tend to be high and optically thin, thus reducing the effective radiative temperature without increasing the albedo significantly, leading to an enhanced greenhouse heating. In contrast, marine stratocumulus are low and optically thick, thus producing a large increase in reflected radiation with a small change in emitted radiation, giving a net cooling which could potentially mitigate the expected greenhouse warming. The FIRE measurements in California stratocumulus during June and July of 1987 show variations in cloud liquid water on all scales. Such variations are associated with inhomogeneous entrainment, in which entrained dry air, rather than mixing uniformly with cloudy air, remains intact in blobs of all sizes, which decay only slowly by invasion of cloudy air. Two important stratocumulus observations are described, followed by a simple fractal model which reproduces these properties, and finally, the model radiative properties are discussed.

Description: The fractal properties of clouds observed during the FIRE Marine Stratocumulus Intensive Field Observations (MS IFO) and their effects on the large scale radiative properties of the atmosphere are examined. This involves three states: (1) analysis of LANDSAT Thematic Mapper (TM) cloud data to determine the scaling properties associated with various cloud types; (2) simulation of fractal clouds with realistic scaling properties; and (3) computation of mean radiative properties of fractal clouds as a function of their scaling properties. Thirty-three LANDSAT scenes were acquired as part of the FIRE Marine Stratocumulus IFO in July 1987. They exhibit a wide variety of stratocumulus structures. Analysis has so far focused upon the July 7 scene, in which the NASA ER-2, the BMO C130 and the NCAR Electra repeatedly gathered data across a stratocumulus-fair weather cumulus transition.

Description: An increase in the planetary albedo of the earth-atmosphere system by only 10% can decrease the equilibrium surface temperature to that of the last ice age. Nevertheless, albedo biases of 10% or greater would be introduced into large regions of current climate models if clouds were given their observed liquid water amounts, because of the treatment of clouds as plane parallel. The focus on marine stratocumulus clouds is due to their important role in cloud radiative forcing and also that, of the wide variety of earth's cloud types, they are most nearly plane parallel, so that they have the least albedo bias. The fractal model employed here reproduces both the probability distribution and the wavenumber spectrum of the stratocumulus liquid water path, as observed during the First ISCCP Regional Experiment (FIRE). A single new fractal parameter 0 less than or equal to f less than or equal to 1, is introduced and determined empirically by the variance of the logarithm of the vertically integrated liquid water. The reduced reflectivity of fractal stratocumulus clouds is approximately given by the plane-parallel reflectivity evaluated at a reduced 'effective optical thickness,' which when f = 0.5 is tau(sub eff) approximately equal to 10. Study of the diurnal cycle of stratocumulus liquid water during FIRE leads to a key unexpected result: the plane-parallel albedo bias is largest when the cloud fraction reaches 100%, that is, when any bias associated with the cloud fraction vanishes. This is primarily due to the variability increase with cloud fraction. Thus, the within-cloud fractal structure of stratocumulus has a more significant impact on estimates of its mesoscale-average albedo than does the cloud fraction.

Description: Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data, with 80 and 30 m spatial resolution, respectively, have been employed to study the spatial structure of boundary-layer and intertropical convergence zone (ITCZ) clouds. The probability distributions of cloud areas and cloud perimeters are found to approximately follow a power-law, with a different power (i.e., fractal dimension) for each cloud type. They are better approximated by a double power-law behavior, indicating a change in the fractal dimension at a characteristic size which depends upon cloud type. The fractal dimension also changes with threshold. The more intense cloud areas are found to have a higher perimeter fractal dimension, perhaps indicative of the increased turbulence at cloud top. A detailed picture of the inhomogeneous spatial structure of various cloud types will contribute to a better understanding of basic cloud processes, and also has implications for the remote sensing of clouds, for their effects on remote sensing of other parameters, and for the parameterization of clouds in general circulation models, all of which rely upon plane-parallel radiative transfer algorithms.

Description: Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller-scale variability, where the radiative transfer is more three-dimensional, contributes less to the plane-parallel albedo bias than the larger scales, which are more variable. The lack of significant three-dimensional effects also relies on the assumption of a relatively simple geometry. Even with these assumptions, the independent pixel approximation is accurate only for fluxes averaged over large horizontal areas, many photon mean free paths in diameter, and not for local radiance values, which depend strongly on the interaction between neighboring cloud elements.

Description: Histograms of nearest neighbor spacings of fair weather cumulus at 15 locations over the world's oceans are presented based on the analysis of high resolution Landsat 3 Multispectral Scanner images for amounts of cloud cover ranging from 0.6 to 37.6 percent. These histograms are found to be essentially the same at all locations analyzed, similarly to previous findings on the size distributions and the fractal dimensions of the perimeters for this cloud type. The nearest neighbor spacings are linearly dependent on the effective cloud radii, with a proportionality factor ranging from five to twenty. The histograms peak at about 0.5 km. Nearest-neighbor spacings smaller than about a kilometer, associated with cumulus clouds with an effective radius less than a few hundred meters, have a distribution of cloud centers that is almost indepedent in the horizontal plane and show a tendency for the formation of clumps. Larger spacings of up to thirty kilometers occur and are associated with the larger clouds. These latter spacings are not independent.

Description: Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as UN population projections. This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations.