A Surprising Problem with Thin Liquid Water Clouds

Turner, D. D., National Oceanic and Atmospheric Administration

Clouds with Low Optical [Water] Depths (CLOWD)

Radiative Processes

D.D. Turner, A.M. Vogelmann, R.T. Austin, J.C. Barnard, K. Cady-Pereira, J.C. Chiu, S.A. Clough, C. Flynn, M. M. Khaiyer, J. Liljegren, K. Johnson, B. Lin, C. Long, A. Marshak, S. Y. Matrosov, S.A. McFarlane, M. Miller, Q. Min, P. Minnis, W. O'Hirok, Z. Wang, and W. Wiscombe, 2006: Thin Liquid Water Clouds: Their Importance and Our Challenge. Bulletin of the American Meteorological Society (accepted).

For the "simplest" type of thin cloud (the uniform single-layered cloud [red] in the top image, measured using backscatter from a Raman lidar), the retrieved liquid-water paths (LWPs) for several approaches differ by up to 40 gm-2, which represents 50 to 100% differences (bottom panel). The results shown use different surface observations for their retrievals: microwave emission from the cloud, interpreted using the standard ARM retrieval method ("Microwave emission v1") and an improved microwave method that includes information about the surface meteorology ("Microwave emission v2"); emission of middle-infrared energy from the cloud ("Thermal emission"), and this emission used in combination with the transmission of near-infrared energy ("Thermal emis. & trans."), and, for comparison, a technique that uses visible and infrared energy measured by a satellite ("Satellite"). Other common retrieval approaches (not shown) have similar differences in LWP values, which present an unacceptably large uncertainty in the Earth's radiative energy budget.

From the tropics to the Arctic, 50% or more of liquid-water clouds are thin (optical depths below 10, which is thin enough to see the Sun through). The Earth's radiative energy balance is sensitive to small changes in the liquid-water paths of these clouds; a seemingly small change in cloud optical depth can easily cause changes in the local radiative energy balance that are larger than those due to greenhouse gas increases. Thus, particularly accurate observations are required to understand the impact of these clouds on the Earth's energy balance and their possible response in global warming scenarios. Because these liquid clouds are the simplest type of cloud to observe, they have generally been regarded as a solved problem. However, in a recent paper accepted by the Bulletin of the American Meteorological Society, scientists supported by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program revealed shockingly large differences among a vast range of state-of-the-art cloud retrieval methods.

Radiometers at the surface and on satellites provide observations that can be used to remotely retrieve cloud liquid-water amount and cloud drop size. These retrievals are essential for obtaining the type of long-term observations needed for cloud and climate studies, and retrieval methods have advanced considerably over the last two decades. To ascertain the accuracy of these retrievals, ARM scientists evaluated the results from 18 state-of-the-art methods representing essentially all techniques currently used. The key to conducting this study were the multiple sets of sophisticated observations available from the ARM Climate Research Facility located at the Southern Great Plains site in Oklahoma. The high-quality dataset from the SGP site uniquely enabled the cross-comparison of the different techniques.

The surprising result showed that scientists are further than expected from accurately retrieving these cloud properties. Even for the simplest, most homogeneous cloud observed, differences up to 100% were found among the different determinations of cloud liquid water amount and drop size. These differences occurred not only between state-of-the-art techniques of different types, but even between techniques sharing a common theoretical basis. Thus, irrespective of the observational technique used, the differences carry significant implications for the broad climate community's ability to observe and subsequently represent these clouds in climate models. This means that, despite considerable advances, much more work is necessary. Thus, the ARM Program created a crosscutting Working Group—Clouds with Low Optical [Water] Depths, or CLOWD—to accelerate progress on the outstanding issues related to the impact of thin clouds on climate.