Cloud Radiative Forcing at the ARM Climate Research Facility: Part 1. Technique, Validation, and Comparison to Satellite-Derived Diagnostic Quantities.
| Mace, Gerald | University of Utah |
| Benson, Sally | University of Utah |
| Sonntag, Karen | ARM Data Quality Office - University of Oklahoma |
| Kato, Seiji | Hampton University/NASA Langley Research Center |
| Min, Qilong | State University of New York at Albany |
| Minnis, Patrick | NASA Langley Research Center |
| Twohy, Cynthia | Oregon State University |
| Poellot, Michael | University of North Dakota |
| Dong, Xiquan | University of North Dakota |
| Zhang, Qiuqing | University of Alaska |
| Long, Chuck | Pacific Northwest National Laboratory |
It has been hypothesized that continuous ground-based remote sensing data from millimeter radars, lidars, and passive microwave radiometry combined with regular soundings of the atmospheric thermodynamic structure are sufficient to create a data set from which the effects of clouds on the clear sky radiation fluxes can be derived. We critically test that hypothesis in this paper. Using data collected at the Southern Great Plains Atmospheric Radiation Measurement (ARM) site sponsored by the U.S. Department of Energy, we explore an analysis methodology that results in the characterization of the physical state of the atmospheric profile at time resolutions as fine as five minutes and vertical resolutions of 90 m. The description includes thermodynamics and water vapor profile information derived by merging radiosonde soundings with ground-based data, and continues through specification of the cloud layer occurrence, and microphysical and radiative properties derived from retrieval algorithms and parameterizations. The description of the atmospheric physical state includes a calculation of the infrared and solar flux profiles. Validation of the methodology is provided by comparing the calculated fluxes with top of atmosphere (TOA) and surface flux measurements and by comparing the total column optical depths to independently derived estimates. We find over a 1-year period of comparison in overcast uniform skies, the calculations are strongly correlated to measurements with biases in the flux quantities at the surface and TOA of less than 10% and median fractional errors ranging from 20% to as low as 2%. In the optical depth comparison for uniform overcast skies during the year 2000 where the optical depth varies over 3 orders of magnitude we find a mean positive bias of 46% with a median bias of less than 10% and a 0.89 correlation coefficient. The slope of the linear regression line for this comparison is 0.86 with a normal deviation of 20% about this line. In addition to a case study where we examine the radiative feedback to the TOA, surface and atmosphere by a middle latitude synoptic-scale cyclone, we examine the cloud top pressure and optical depth retrievals of ISCCP and LBTM. Using data from the year 2000, we find that the satellite algorithms bias cloud tops into the middle troposphere and significantly underestimate optical depth in high optical depth events (greater than 100) by as much as a factor of 2.
This poster will be displayed at the ARM Science Team Meeting.