Showing papers by "David F. Young published in 2001"

The Influence of the 1998 El Niño upon Cloud-Radiative Forcing over the Pacific Warm Pool.

Abstract: Clouds cool the climate system by reflecting shortwave radiation and warm it by increasing the atmospheric greenhouse. Previous studies have shown that in tropical regions of deep convection there is a near cancellation between cloud-induced shortwave cooling and longwave warming. The present study investigates the possible influence of the 1998 El Nino upon this near cancellation for the tropical western Pacific's warm pool; this was accomplished by employing satellite radiometric measurements (Earth Radiation Budget Experiment, and Clouds and the Earth's Radiant Energy System). With the exclusion of the 1998 El Nino, this study also finds near cancellation between the shortwave and longwave cloud forcings and demonstrates that it refers to the average of different cloud types rather than being indicative of a single cloud type. The shortwave cooling slightly dominates the longwave warming, and there is considerable interannual variability in this modest dominance that appears attributable to interannual variability of tropopause temperature. For the strong 1998 El Nino, however, there is a substantially greater tendency toward net radiative cooling, and the physical mechanism for this appears to be a change in cloud vertical structure. For normal years, as well as for the weaker 1987 El Nino, high clouds dominate the radiation budget over the warm pool. In 1998, however, the measurements indicate the radiation budget is partially governed by middle-level clouds, thus explaining the net cooling over the warm pool during the 1998 El Nino as well as emphasizing differences between this event and the weaker 1987 El Nino.

Arctic Stratus Cloud Properties and Their Effect on the Surface Radiation Budget: Selected Cases from FIRE ACE

Abstract: To study Arctic stratus cloud properties and their effect on the surface radiation balance during the spring transition season, analyses are performed using data taken during three cloudy and two clear days in May 1998 as part of the First ISCCP Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). Radiative transfer models are used in conjunction with surface- and satellite-based measurements to retrieve the layer-averaged microphysical and shortwave radiative properties. The surface-retrieved cloud properties in Cases 1 and 2 agree well with the in situ and satellite retrievals. Discrepancies in Case 3 are due to spatial mismatches between the aircraft and the surface measurements in a highly variable cloud field. Also, the vertical structure in the cloud layer is not fully characterized by the aircraft measurements. Satellite data are critical for understanding some of the observed discrepancies. The satellite-derived particle sizes agree well with the coincident surface retrievals and with the aircraft data when they were collocated. Optical depths derived from visible-channel data over snow backgrounds were overestimated in all three cases, suggesting that methods currently used in satellite cloud climatologies derive optical depths that are too large. Use of a near-infrared channel with a solar infrared channel to simultaneously derive optical depth and particle size appears to alleviate this overestimation problem. Further study of the optical depth retrieval is needed. The surface-based radiometer data reveal that the Arctic stratus clouds produce a net warming of 20 W m(exp -2) in the surface layer during the transition season suggesting that these clouds may accelerate the spring time melting of the ice pack. This surface warming contrasts with the net cooling at the top of the atmosphere (TOA) during the same period. All analysis of the complete FIRE ACE data sets will be valuable for understanding the role of clouds during the entire melting and refreezing process that occurs annually in the Arctic.

Cloud Macro- and Microphysical Properties Derived from GOES Over the ARM SGP Domain

Abstract: Cloud macrophysical properties like fractional coverage and height Z(sub c) and microphysical parameters such as cloud liquid water path (LWP), effective droplet radius r(sub e), and cloud phase, are key factors affecting both the radiation budget and the hydrological cycle. Satellite data have been used to complement surface observations from Atmospheric Radiation Measurements (ARM) by providing additional spatial coverage and top-of-atmosphere boundary conditions of these key parameters. Since 1994, the Geostationary Operational Environmental Satellite (GOES) has been used for deriving at each half-hour over the ARM Southern Great Plains (SGP) domain: cloud amounts, altitudes, temperatures, and optical depths as well as broadband shortwave (SW) albedo and outgoing longwave radiation at the top of the atmosphere. A new operational algorithm has been implemented to increase the number of value-added products to include cloud particle phase and effective size (r(sub e) or effective ice diameter D(sub e)) as well as LWP and ice water path. Similar analyses have been performed on the data from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission satellite as part of the Clouds and Earth's Radiant Energy System project. This larger suite of cloud properties will enhance our knowledge of cloud processes and further constrain the mesoscale and single column models using ARM data as a validation/initialization resource. This paper presents the results of applying this new algorithm to GOES-8 data taken during 1998 and 2000. The global VIRS results are compared to the GOES SGP results to provide appropriate context and to test consistency.