The Vertical Structure of Cloud Radiative Forcing at the ACRF SGP Revealed by 8 Years of Continuous Measurements

Mace, G., University of Utah

Cloud Distributions/Characterizations

Cloud Modeling, Cloud Properties

Accepted to Journal of Climate, 2007.


Figure 1. Cloud occurrence, coverage, radiative forcing, and radiation effects over a composite annual cycle that is derived by averaging all observations collected during a particular month for all years. a) cloud occurrence in 100 mb vertical bins, b) cloud coverage, c) infrared cloud radiative forcing in 100 mb vertical bins, d) solar cloud radiative forcing, e) net cloud radiative forcing, f,g,h) solar (dotted), IR (solid), and net (dashed) cloud radiative effect for TOA (f), atmosphere (g), and surface (h). In parts c, d, e, the color gray is used for volumes where the uncertainty in the CRF is more than 20% of the absolute value of the time-averaged CRF in that bin.


Figure 1. Cloud occurrence, coverage, radiative forcing, and radiation effects over a composite annual cycle that is derived by averaging all observations collected during a particular month for all years. a) cloud occurrence in 100 mb vertical bins, b) cloud coverage, c) infrared cloud radiative forcing in 100 mb vertical bins, d) solar cloud radiative forcing, e) net cloud radiative forcing, f,g,h) solar (dotted), IR (solid), and net (dashed) cloud radiative effect for TOA (f), atmosphere (g), and surface (h). In parts c, d, e, the color gray is used for volumes where the uncertainty in the CRF is more than 20% of the absolute value of the time-averaged CRF in that bin.

A foundational goal of the ARM Program is to produce long-term measurements of cloud occurrence, cloud properties, and cloud radiative forcing that can be used to evaluate general circulation models. We address that foundational goal in this paper by using 8-years of continuous data collected at the ARM Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Specifically we examine the statistics of cloud occurrence and the radiative influences of clouds on the radiation budget of the surface, the vertically resolved atmospheric column, and the top of atmosphere (TOA). This is accomplished using a composite annual cycle constructed by averaging individual months, and through comparison of seasonal statistics.

The approach we take to bring the raw observational ARM data streams into a unified geophysical description of the atmospheric column as a function of time is fully described in previously published papers (Mace et al., 2006a and b). In this procedure, we begin with the individual calibrated instrument files, and then we derive a continuous representation of the thermodynamic profiles, clouds observed by radar and lidar. Cloud property retrievals are implemented and radiative properties are calculated. Finally the solar and infrared flux profiles of clear and cloudy radiation are computed. Validation has been provided through comparison with radiometric fluxes measured at the surface and at the TOA and through comparison with aircraft data and other validated products. We demonstrate that the approach has sufficient quantitative skill to analyze, monthly and longer time-scale cloud properties and radiative forcing.

Figures 1 and 2 summarize these research results. We find that the vertical profile of cloud occurrence is dominated by clouds in the upper troposphere and in the boundary layer at this midlatitude location. Upper tropospheric cloud layers dominate the heating of the troposphere, while lower level clouds provide a largely counterbalancing cooling influence. The combination of these two cloud types results in little net atmospheric cloud radiative effect (CRE); however, the displacement of the heating and cooling centers in the troposphere tend to stabilize temperature profiles in a time-averaged sense. The balance between heating and cooling in the atmosphere is due largely to deposition of thermal infrared flux. While solar absorption cannot be neglected where it occurs, it is largely offset by infrared emission. The exception is in the upper troposphere where solar heating tends to occur at higher altitudes rather than where the majority of the infrared cooling occurs in thicker clouds. Overall however, net solar cooling at the TOA due to reflection is realized largely at the surface, and the majority of the net radiative heating in the troposphere is due to IR absorption and emission. The vertical distribution of heating and cooling demonstrates a strong seasonal dependence with the heating center migrating toward higher altitudes as the summer troposphere deepens. However, remarkably, the seasonal cycle in IR heating of the troposphere is not evident in the annual cycle of TOA IR radiative effect and only weakly evident in the seasonal cycle of the radiative effect at the surface.

By comparing the time series of seasonal cloud cover and CRE, we find little interannual variability during the 8-year period. While there does appear to be some true anomalies in cloud cover (i.e., winter of 2003, summer of 2004) these periods do not result in large anomalies in cloud radiative effect suggesting that the distribution and properties of clouds, when they did occur, were not much different from the average. Autumn of 2001 is an example of a significant change in both cloud cover and radiative effect. During autumn of 2001, the coverage of upper tropospheric clouds increased and low level clouds decreased compared to other years. These changes had a significant influence on the net heating of the atmospheric column and especially on the vertical distribution of that heating.

We conclude that changes in the vertical distribution of clouds on seasonal and interannual time scales, while not having a significant influence on the column-integrated radiative effects that would be measured at the TOA, do significantly redistribute diabatic heating within the troposphere. This redistribution of radiant energy suggests that a true characterization of the feedback processes of clouds requires a solid understanding of the vertical distribution of that heating. Continuous ground-based data are uniquely suited to providing that information.

The ARM Program was initiated with a principal goal of documenting the occurrence and properties of clouds the effects that clouds have on the radiation budget of the atmosphere. The observational objectives of the ARM Program are coupled quite naturally with an objective to then use the information gleaned from the data to improve the representation of cloud processes and radiation in climate models. The study highlighted here demonstrates that the long-term data sets being created by the ARM Program are certainly capable of addressing the climatological variability of cloud occurrence, cloud properties, and the radiative influence of clouds on the surface, TOA, and atmospheric radiation budgets. The next logical step will be to evaluate the extent to which climate models are able to replicate the observational record created by ARM data.