The Effect of Cumulus Cloud Field Anisotropy on Domain-Averaged Solar Fluxes and Atmospheric Heating Rates

Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce twenty three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-average transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction, i.e., the cloud fraction when the field is projected on a surface perpendicular to the direction of the incident solar beam

Long-Term Validation and Variability of the Shortwave and Longwave Radiation Data of the GEWEX Surface Radiation Budget (SRB) Project

In this investigation, we make systematic Surface Radiation Budget-Baseline Surface Radiation Network (SRB-BSRN), Surface Radiation Data Centre (SRB-WRDC) and Surface Radiation Budget-Global Energy Balance Archive (SRB-GEBA) comparisons for both shortwave and longwave daily and monthly mean radiation fluxes at the Earth's surface. We first have an overview of all the comparable pairs of data in scatter or scatter density plots. Then we show the time series of the SRB data at grids in which there are ground sites where longterm records of data are available for comparison. An overall very good agreement between the SRB data and ground observations is found. To see the variability of the SRB data during the 21.5 years, we computed the global mean and its linear trend. No appreciable trend is detected at the 5% level. The empirical orthogonal functions (EOF) of the SRB deseasonalized shortwave downward flux are computed over the Pacific region, and the first EOF coefficient is found to be correlated with the ENSO Index at a high value of coefficient of 0.7083

Coupling sky images with radiative transfer models: a new method to estimate cloud optical depth

A method for retrieving cloud optical depth (τc) using a UCSD developed ground-based sky imager (USI) is presented. The radiance red–blue ratio (RRBR) method is motivated from the analysis of simulated images of various τc produced by a radiative transfer model (RTM). From these images the basic parameters affecting the radiance and red–blue ratio (RBR) of a pixel are identified as the solar zenith angle (θ0), τc, solar pixel angle/scattering angle (ϑs), and pixel zenith angle/view angle (ϑz). The effects of these parameters are described and the functions for radiance, Iλτc, θ0, ϑs, ϑz, and RBRτc, θ0, ϑs, ϑz are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for τc, where RBR increases with τc up to about τc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Iλmeasϑs, ϑz, in addition to RBRmeasϑs, ϑz, to obtain a unique solution for τc. The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement (ARM) program site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min et al. (2003) method for overcast skies. τc values ranged from 0 to 80 with values over 80, being capped and registered as 80. A τc RMSE of 2.5 between the Min et al. (2003) method and the USI are observed. The MWR and USI  have an RMSE of 2.2, which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms

Online Educational Outcomes Could Exceed Those of the Traditional Classroom

An axiom of online education is that teachers should not mechanically translate existing courses into an online format. If so, how should new or ongoing courses be reshaped for the online environment and why? The answers come both from the opportunities offered by the structure of online education and from a body of research from cognitive psychology and cognitive science that provides insight into the way people actually learn. Freed from the time and space constraints inherent in face-to-face higher education settings as well as the deeply ingrained expectations of both teachers and students, online education provides a more flexible palette upon which evidence-based ideas about learning can be integrated into course structure and design. As a result, online education can potentially deliver learning experiences and outcomes that are superior to typical face-to-face classrooms. The ability to integrate experiences that stimulate real, long lasting learning represents one of online education’s greatest potential benefits

Evaluation of CERES and CloudSat Surface Radiative Fluxes Over Macquarie Island, the Southern Ocean

Abstract Many studies involving surface radiative fluxes rely on surface fluxes retrieved by the Clouds and the Earth's Radiant Energy System (CERES) project or derived from spaceborne cloud radar and lidar observations (CloudSat‐CALIPSO). In particular, most climate models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were found to have too little shortwave (SW) radiation being reflected back to space and excessive SW radiation reaching the surface over the Southern Ocean—an error with significant consequences for predicting both regional and global climate. There have been few evaluations of CERES or CloudSat retrievals over the Southern Ocean. In this article, CERES and CloudSat retrieved surface SW and longwave (LW) downwelling fluxes are evaluated using surface observations collected over the Southern Ocean during the Macquarie Island Cloud and Radiation Experiment (MICRE). Overall, biases (CERES—surface observations) in the CERES‐surface fluxes are found to be slightly larger over Macquarie Island than most other regions, approximately +10 W m−2 for the SW and −10 W m−2 for the LW in the annual mean, but with significant seasonal and diurnal variations. If the Macquarie observations are representative of the larger SO, these results imply that CMIP5 model errors in SW surface fluxes are (if anything) somewhat larger than previous evaluation studies suggest. The bias in LW surface flux shows a marked increase at night, which explains most of the total LW bias. The nighttime bias is due to poor representation of cloud base associated with low clouds

Shortwave absorptance in a tropical cloudy atmosphere: Reconciling calculations and observations

[1] The absorption of shortwave (SW) radiation by clouds is a topic surrounded by contradictory reports and controversy. Some studies have shown large discrepancies between observed SW absorption and absorption predicted by models, while others have found no significant difference. In this study, values of column SW absorptance obtained by combining collocated top-of-atmosphere (TOA) and surface observations at an island site in the tropical western Pacific are compared to radiative transfer model (RTM) output. To compensate for the field of view difference between satellite and surface instruments, the surface data are averaged over time. Scatterplots and statistical measures show that there is a significant discrepancy between models and observations with the RTMs apparently underestimating SW absorptance. The large variability of the absorptance computed from the observations, including negative values, suggests that the field of view mismatch between satellite and surface observations remains even after averaging of the surface data. This mismatch may contribute to the observation-model bias. In previous observational studies showing highly enhanced absorption compared to models, the slope of a linear fit to dαTOA/dT (the derivative of TOA albedo with respect to transmittance) was used to quantify cloud SW absorption, while nonlinearity of dα TOA/dT was interpreted as a sign of sampling issues. Here the models produce a steeper slope (about −0.9) than observations (−0.6 to −0.8), indicating that models predict too little cloud SW absorption. However, when the surface observations are averaged over a longer period, their slope grows steeper, and the root-mean-square difference between linear and quadratic fits to dα TOA/dT is reduced. This implies that insufficient averaging of surface data contributes to the observed SW absorption discrepancy. Reexamination of the observational data using the difference between cloud fraction estimated from satellite and surface measurements as an estimate of field of view mismatch supports this hypothesis. High measured absorptance values are shown to correspond to occasions of large field of view mismatch. When such data are excluded, the difference between the linear and quadratic fits is reduced, and the slope of the best fit line becomes steeper. We conclude that averaging surface data over 3 h or less is not always sufficient to eliminate sampling issues. However, the possibility that shortcomings of the RTMs contribute to the discrepancy in SW absorption values cannot be excluded

Influence of synoptic weather patterns on solar irradiance variability in northern Europe

Observations have revealed strong variability of shortwave (SW) irradiance at Earth’s surface on decadal time scales, referred to as global dimming and brightening. Previous studies have attributed the dimming and brightening to changes in clouds and atmospheric aerosols. This study assesses the influence of atmospheric circulation on clouds and SW irradiance to separate the influence of ‘‘natural’’ SW variability from direct and, to some extent, indirect aerosol effects. The focus is on SW irradiance in northern Europe in summer and spring because there is little high-latitude SW irradiance during winter. As a measure of large-scale circulation the Grosswetterlagen (GWL) dataset, a daily classi- fication of synoptic weather patterns, is used. Empirical models of normalized SW irradiance are constructed based on the GWL, relating the synoptic weather patterns to the local radiative climate. In summer, a temporary SW peak in the 1970s and subsequent dimming is linked to variations in the synoptic patterns over Scandinavia, possibly related to a northward shift in the North Atlantic storm track. In spring, a decrease of anticyclonic and increase of cyclonic weather patterns over northern Europe contributes to the dimming from the 1960s to 1990. At many sites, there is also a residual SWirradiance trend not explained by the GWL model: a weak nonsignificant residual dimming from the 1950s or 1960s to around 1990, followed by a statistically significant residual brightening. It is concluded that factors other than the large-scale circulation (e.g., decreasing aerosol emissions) also play an important role in northern Europe