Ninth Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)


Using Integrated Surface Radiation Measurements to infer Cloud Properties

Charles N. Long, PNNL, Richland, WA; and J. C. Barnard, J. Calbo, and T. P. Ackerman

There are many surface radiation measurement sites such as those in the Baseline Surface Radiation Network (BSRN), which has recently been named as the official GCOS surface radiation monitoring network. Other networks similar to BSRN include the NOAA Surface Radiation (SURFRAD) Network, the Atmospheric Radiation Measurement (ARM) network, the Australian Bureau of Meteorology network, and the NOAA Climate Modeling Diagnostics Laboratory (CMDL) network, to name just a few. These sites all provide measurements of broadband downwelling shortwave (SW) and longwave (LW) irradiance, and standard surface meteorological parameters. Starting with the detection of daylight clear (i.e. cloudless) sky periods using a technique developed by Long and Ackerman (2000, JGR), we can continuously estimate the clear-sky downwelling SW, and determine the downwelling SW cloud effect. These data are then used to infer fractional sky cover amounts (Long et al, 1999, AMS 10th AtRad), and more recently, to derive cloud visible optical depths (Barnard and Long, 2004, JAM). Current work is geared toward similar retrievals using LW measurements, i.e. the detection of LW effective clear-sky periods, continuous estimation of clear-sky downwelling LW, and determination of LW cloud effect. Techniques are being developed to estimate effective LW sky cover (primarily consisting of the low and mid-level cloud amounts) from the broadband LW measurements (Durr and Philipona, 2004), and in conjunction with measurements from a narrow field-of-view Infrared Thermometer (Han and Ellingson, 1999; Takara and Ellingson, 2003). In both cases, estimates of cloud base effective radiating temperature, and cloud base height are inferred. All of the above cloud properties are being used in research to classify the type of clouds present (Calbo et al., 2001, JAM). Thus, it is possible to infer many basic properties of clouds from BSRN-type sites, which vastly increases our capabilities for satellite validation, model comparisons (Wild and Long, IRS 2004), and climate studies. We will present a brief description of these techniques, and corresponding examples.

extended abstract  Extended Abstract (1.1M)

wrf recording  Recorded presentation

Session 11, Atmospheric Observations
Thursday, 13 January 2005, 1:30 PM-5:00 PM

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