A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations

Abstract

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave/imager (SSM/I) is described. The technique is comprised of a simple physical model that uses the 19.35‐ and 37‐GHz channels of the SSM/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This is accomplished through a comparison to independent ground‐based microwave radiometer measurements of liquid water on San Nicolas Island, over the North Sea, and on Kwajalein and Saipan Islands in the western Pacific. In areas of marine stratocumulus clouds off the coast of California a further comparison is made to liquid water inferred from advanced very high resolution radiometer (AVHRR) visible reflectance measurements. The results are also compared qualitatively with near‐coincident satellite imagery and with other existing microwave methods in selected regions. These comparisons indicate that the liquid water amounts derived from the simple scheme are consistent with the ground‐based measurements for nonprecipitating cloud systems in the subtropics and middle to high latitudes. The comparison in the tropics, however, was less conclusive. Nevertheless, the retrieval method appears to have general applicability over most areas of the global oceans. An observational measure of the minimum uncertainty in the retrievals is determined in a limited number of known cloud‐free areas, where the liquid water amounts are found to have a low variability of 0.016 kg m−2. A simple sensitivity and error analysis suggests that the liquid water estimates have a theoretical relative error typically ranging from about 25% to near 40% depending on the atmospheric/surface conditions and on the amount of liquid water present in the cloud. For the global oceans as a whole the average cloud liquid water is determined to be about 0.08 kg m−2. The major conclusion of this paper is that reasonably accurate amounts of cloud liquid water can be retrieved from SSM/I observations for nonprecipitating cloud systems, particularly in areas of persistent stratocumulus clouds, with less accurate retrievals in tropical regions.

Model intercomparison of indirect aerosol effects

“…We also show the inferred liquid water path from the SSMI satellite instrument (Weng and Grody, 1994;Greenwald et al, 1993) and from the MODIS satellite instrument (Platnick et al, 2003). We note that the liquid water path for the LMD-Z model was not available as a separate diagnostic, and hence we plot the Weng and Grody (1993) and by (b) Greenwald et al (1993) and (c) as inferred from the MODIS instrument for T>260 • (Platnick et al, 2003). Panel (d) shows the liquid plus ice path from MODIS, while panels (e) and (f) show the liquid water path from the CAM-Oslo and CCSR models in experiment 1a, respectively.…”

Uncertainty quantification and parameter tuning in the CAM5 Zhang‐McFarlane convection scheme and impact of improved convection on the global circulation and climate

“…Numbers denote rain rates at the 95th percentile. [Greenwald et al, 1993;Weng and Grody, 1994;Ferraro et al, 1996] and NVAP for the years 1988-1999 [Engelen and Stephens, 1999]. Both data are restricted to oceans.…”

Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5)

“…Global annual mean results from present-day simulations and observations. Shown are total cloud fraction (CLDTOT, %) and high cloud fraction (CLDHGH, %) compared to ISCCP data (Rossow and Schiffer, 1999), MODIS data (Platnick et al, 2003) and HIRS data (Wylie et al, 2005); shortwave cloud forcing (SWCF, W m −2 ), long-wave cloud forcing (LWCF, W m −2 ), whole-sky shortwave (FSNT, W m −2 ) and long-wave (FLNT, W m −2 ) net radiative fluxes at the top of the atmosphere, clear-sky shortwave (FSNTC, W m −2 ) and longwave (FLNTC, W m −2 ) radiative fluxes at the top of the atmosphere compared to ERBE data (Kiehl and Trenberth, 1997) and CERES data (Loeb et al 2009); liquid water path (LWP; g m −2 ) compared to SSM/I oceans data (Greenwald et al, 1993;Weng and Grody, 1994) and ISCCP data (Han et al, 1994); ice water path (IWP, g m −2 ) compared to CloudSat data (Li et al, 2012); column-integrated grid-mean cloud droplet number concentration (CDNUMC, 10 10 m −2 ) compared to MODIS data (Table 4 in Barahona et al, 2014); column-integrated grid-mean ice crystal number concentration (CDNUMI, 10 6 m −2 ), convective (PRECC, mm d −1 ) and large-scale (PRECL, mm d −1 ) and total precipitation rate (PRECT, mm d −1 ) compared to Global Precipitation Climatology Project data set (Adler et al, 2003 (Wielicki et al, 1996). Units are shown in the upper right corner.…”