In order to assess the irradiance estimate improvement, we use four sets of surface irradiance computations extracted from three different data products in this study. These four sets of modeled irradiances use nearly identical radiative transfer models. One data product is the CCCM (CALIPSO CloudSat CERES and MODIS, Edition B1 [Kato et al., 2010], hereafter CCCM_CC). CCCM contains cloud and aerosol vertical profiles derived from CALIOP (Version 3) and CPR (Revision 4), as well as cloud properties derived from MODIS radiances by a CERES cloud algorithm [Minnis et al., 2011; Trepte et al., 2010]. It also contains the vertical irradiance profile computed with cloud properties determined using a combination of CALIOP, CPR, and MODIS data. In addition, it contains the TOA and surface irradiances and irradiances at three atmospheric pressure levels (500, 200, and 70 hPa) computed with cloud properties derived from MODIS only (hereafter this irradiance set is referred as CCCM_MODISonly). The algorithm that uses only MODIS radiances is hereafter referred to as the B1 cloud algorithm. By comparing CCCM_CC and CCCM_MODISonly computed over the CALIOP and CPR ground track, we assess the improvement of instantaneous irradiances due to inclusion of the CALIOP- and CPR-derived cloud vertical profiles in the computations. The third set of modeled irradiances is from the CERES standard product Cloud and Radiative Swath (CRS, Terra edition 2G) [Charlock et al., 2006], which uses only MODIS-derived cloud [Minnis et al., 2011] properties (hereafter this irradiance set is referred as CRS). Because MODIS covers the entire globe daily, we can assess the error caused by the nadir view sampling by subsetting irradiances computed for nadir view CERES footprints and comparing them with irradiances computed for the full swath using CRS. The fourth set of modeled irradiances is from the CERES standard product AVG (Terra Edition 2C). AVG contains monthly mean gridded modeled TOA and surface irradiances. The monthly mean irradiance is computed from daily mean values that account for a diurnal cycle of cloud properties retrieved from geostationary satellites and temperature and humidity profiles from reanalysis [Young et al., 1998] (hereafter this irradiance set is referred as AVG). Therefore, we can assess the improvement of the global mean surface irradiance estimated with CALIOP- and CPR-derived cloud profiles with the use of these four sets.
 Modeled irradiances of CCCM used for this study are from January 2008 through December 2008, modeled irradiances of CRS are from January, April, July, and October 2008, and modeled irradiances of AVG are from January 2001 through December 2004. Note that the use of AVG data from a different year does not cause a significant problem, because we only use irradiances from AVG averaged annually and globally.
2.1. CALIPSO and CloudSat Merged Cloud Profiles and Irradiance Computations for CCCM_CC
 Because the method of integrating the CALIOP- and CPR-derived cloud masks is described in Kato et al. , only a brief description is provided here. Cloud vertical profiles from CALIOP and CPR are initially merged into 1 km horizontal resolution vertical cloud profiles (Figure 1). Starting with a CALIOP-derived cloud profile, we add cloud boundaries from CPR in the following cases: (i) when CPR detects a cloud boundary more than 480 m above or below cloud boundaries detected by CALIOP, the CPR-derived boundary is inserted; (ii) when the CALIOP signal is completely attenuated by clouds (attenuation level), and the CPR-derived cloud base is lower than the attenuation level, the CPR-derived cloud base is used; (iii) otherwise, the attenuation level is used as the cloud base. As a result of these processes, CALIOP provides approximately 85% of cloud top heights and 77% of cloud base heights for the merged cloud profiles.
 The resulting merged cloud profiles are then collocated with CERES footprints, which are approximately 20 km in size (Figure 1). To maintain the horizontal resolution used in the original CALIPSO and CloudSat products, 1 km horizontal atmospheric columns that contain the same cloud vertical profiles are grouped together (cloud group). The cloud-grouping process is described in detail by Kato et al. .
 Irradiance vertical profiles are computed for each cloud group by the use of a radiative transfer model (FLux model of CERES with k-distribution and correlated-k for Radiation (FLCKKR) [Fu and Liou, 1993; Fu et al., 1997; Kratz and Rose, 1999; Kato et al., 1999, 2005; Rose et al., 2006] with a two-stream approximation using the independent column approximation [Stephens et al., 1991]. The hierarchy of cloud optical property sources used in the irradiance computations and the details of the irradiance computations are explained in Appendix A. In brief, cloud properties derived from CALIOP, CPR, or MODIS are used in the computations. In retrieving cloud properties from MODIS radiances, the B1 cloud algorithm is forced to retrieve the uppermost cloud top effective height given by the collocated merged CALIOP and CPR cloud profile (hereafter, enhanced cloud algorithm, see Appendix A for detail) when a single-layer cloud is present in the pixel. As a consequence, the enhanced cloud algorithm uses a better cloud top effective temperature, which leads to a better estimate of the emission contribution in near-infrared (IR) channels. Note that when multilayer clouds are present (about 50% of cloudy cases [Kato et al., 2010]), the enhanced algorithm is the same as the B1 cloud algorithm. Therefore, the CALIOP- and CPR-derived cloud properties affect the clouds used in irradiance computations in two ways; first, by directly providing better cloud mask and profiles, and second, by improving cloud retrievals within the enhanced cloud algorithm.
 In the order of their use in the irradiance computations, the aerosol optical thickness sources are CALIOP, MYD04 [Remer et al., 2005], and the Model of Atmospheric Transport and Chemistry (MATCH [Collins et al., 2001]). The aerosol optical thickness is averaged over a CERES footprint. A CERES footprint could contain multiple vertical aerosol layers having different optical thicknesses, but there is no horizontal aerosol optical thickness variability within a given aerosol layer. CALIOP-derived aerosol optical thicknesses are averaged by excluding values with “the column optical depth aerosol” with an uncertainty of 99.99 (i.e., default value for cases when the CALIPSO extinction calculation failed). In addition, noise in the lidar signal can produce negative extinction values when aerosol loading is low and background noise is high. These negative values occasionally result in a small, negative column optical thickness. Although they are rare, large negative optical thickness (less than −0.1) can produce erroneous retrievals and are excluded in the averaging process. Aerosol optical properties, such as wavelength dependence of the aerosol optical thickness, asymmetry parameter, and single scattering albedo, are determined by assigning aerosol types based on Optical Properties of Aerosols and Clouds (OPAC) [Hess et al., 1998] and Tegen and Lacis . Aerosol types include small dust, large dust, sulfate, sea salt, soot, soluble particles, and insoluble particles. The aerosol type is chosen mostly based on MATCH, except for dust aerosols. When the CALIOP detects dust and polluted dust, large and small dust aerosol models, respectively, are used.
 Temperature and humidity profiles used in CCCM_CC, CCCM_MODISonly, and CRS irradiance computations are from the Goddard Earth Observing System (GEOS-5) Data Assimilation System reanalysis [Rienecker et al., 2008], while the profiles used in AVG irradiance computations are from GEOS-4 [Bloom et al., 2005]. The GEOS-4 and -5 temperature and relative humidity profiles have a temporal resolution of 6 h. Spatially, the profiles are regridded to 1° × 1° maps. Skin temperatures are from both GEOS-4 and GEOS-5 at a 3-hourly resolution, the native temporal resolution of GEOS-4 skin temperature, although the GEOS-5 product has a higher 1-hourly native resolution available. Gridded 6-hourly and 1° × 1° temperature and humidity profiles and the 3-hourly and 1° × 1° skin temperature are further linearly interpolated in space and time to the CERES footprint observation times and locations. Note that the effect on GEOS-5 and -4 temperature and humidity differences yields a global mean surface downward shortwave and longwave irradiances difference of −0.7 W m−2 and 1.2 W m−2, respectively. Because the longwave irradiance difference is smaller than the uncertainty discussed in section 4, we neglect the GEOS-5 and -4 differences in this study.
 CCCM_MODISonly irradiances are computed using cloud properties derived by the B1 cloud algorithm over the entire CERES footprint using MODIS radiances collocated with the CERES footprint. The B1 algorithm and irradiance computations are similar to those used for CRS, which are explained in section 2.2.
2.2. Irradiance Computations in CERES CRS and AVG Products
 The CRS product contains instantaneous modeled irradiances computed with MODIS-derived cloud properties. The CERES Ed2 cloud algorithm [Minnis et al., 2011], the precursor to the B1 algorithm, is used to derive cloud properties from MODIS 1 km resolution spectral radiances. A cloud within a 1 km MODIS pixel is assumed to be a horizontally uniform single-layer overcast cloud. Because the size of a CERES footprint is 20 km at nadir, there are more than 150 sets of retrieved cloud properties (retrieved from one out of two scan lines and one out of two pixels in a scan line, i.e., 25% of pixels within a footprint) within a CERES footprint. Cloud properties derived within a CERES footprint are averaged using the CERES instrument point spread function [Smith, 1994] as a weighting function. In averaging the cloud properties, two cloud top heights within a CERES footprint are retained and cloud properties of high and low clouds are averaged separately.
 AVG contains monthly gridded modeled irradiances computed with cloud properties derived from MODIS and 3-hourly geostationary satellites. Footprint-level cloud properties are gridded in 1° × 1° spatial grids and in 1-hourly temporal grids (hour boxes). Up to four cloud heights (cloud types) are retained for each hour box within a 1° × 1° grid box. Cloud properties for hour boxes other than those for the Aqua overpass time are derived from geostationary satellites. Both linear and logarithmic means of cloud optical thicknesses are computed for each cloud type. The distribution of cloud optical thickness expressed as a gamma distribution is estimated from the linear and logarithmic cloud optical thickness means [Barker 1996; Oreopoulos and Barker, 1999; Kato et al., 2005]. Once the distribution of cloud optical thickness is estimated for each cloud type, the gamma-weighted two-stream radiative transfer model is used to separately compute the shortwave irradiance vertical profile for four cloud types in AVG and two clouds types in CRS. A detailed description of the gamma-weighted two-stream radiative transfer model used for the irradiance computation is given by Kato et al. . The logarithmic mean optical thickness is used in the longwave irradiance computation with a modified two-stream approximation [Toon et al. 1989; Fu et al., 1997]. In addition, irradiance under a clear-sky condition is always computed for every grid box in AVG and for every footprint for CRS. The cloud base height, which largely influences the surface downward longwave irradiance in midlatitude and polar regions, is estimated by an empirical formula described by Minnis et al.  for CCCM_MODISonly, CRS, and AVG.
 Other inputs to the two-stream models are ozone amount [Yang et al., 2000] and ocean spectral surface albedo from Jin et al. , which are used for all four sets. Broadband land surface albedos are inferred from MODIS narrowband albedos [Moody et al., 2005] for CCCM_CC and CCCM_MODISonly and from the clear-sky TOA albedo derived from CERES measurements [Rutan et al., 2009] for CRS and AVG.