Global Cloud Detection for CERES Edition 4 Using Terra and Aqua MODIS Data

Abstract

The Clouds and Earth's Radiant Energy System (CERES) has been monitoring clouds and radiation since 2000 using algorithms developed before 2002 for CERES Edition 2 (Ed2) products. To improve cloud amount accuracy, CERES Edition 4 (Ed4) applies revised algorithms and input data to Terra and Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) radiances. The Ed4 cloud mask uses 5-7 additional channels, new models for clear-sky ocean and snow/ice-surface radiances, and revised Terra MODIS calibrations. Mean Ed4 daytime and nighttime cloud amounts exceed their Ed2 counterparts by 0.035 and 0.068. Excellent consistency between average Aqua and Terra cloud fraction is found over nonpolar regions. Differences over polar regions are likely due to unresolved calibration discrepancies. Relative to Ed2, Ed4 cloud amounts agree better with those from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). CALIPSO comparisons indicate that Ed4 cloud amounts are more than or as accurate as other available cloud mask systems. The Ed4 mask correctly identifies cloudy or clear areas 90%-96% of the time during daytime over nonpolar areas depending on the CALIPSO-MODIS averaging criteria. At night, the range is 88%-95%. Accuracy decreases over land. The polar day and night accuracy ranges are 90%-91% and 80%-81%, respectively. The mean Ed4 cloud fractions slightly exceed the average for seven other imager cloud masks. Remaining biases and uncertainties are mainly attributed to errors in Ed4 predicted clear-sky radiances. The resulting cloud fractions should help CERES produce a more accurate radiation budget and serve as part of a cloud property climate data record.

Evaluating the Magnitude of VIIRS Out-of-Band Response for Varying Earth Spectra

“…For example, Figure 4 highlights the significant OOB signal of the S-NPP VIIRS M1 (~0.42 µm) band, in this case based on the NG RSR characterization effort, and how that might respond to the Earth-reflected spectra of common inter-calibration targets like DCC, ATO, CTO, and the Lib-4 PICS. Figure 5 reveals scene-dependent γ behavior for the S-NPP VIIRS NG M5 (~0.67 µm) band, which is an important spectral channel for inter-calibration and parameterization efforts [6,7,49]. As seen in Tables 7-10, only the M9 (~1.38 µm) bands offer γ values in exceedance of 0.5% for both NOAA-20 and JPSS-2, the nature of which can be evaluated in Figure 6 for select scenes.…”

“…For Earth-monitoring efforts like CERES, satellite records must be combined seamlessly in order to avoid discontinuities in retrievals that arise from either radiometric scaling errors or varying algorithm assumptions. Therefore, it is important to particularly examine the average OOB contribution for the I1 (~0.64 µm) and M5 bands given the historic and continued proliferation of similar channels on Earth-observing imagers and their importance to inter-calibration and cloud parameterization efforts [6,7,49]. Scene-dependent γ significance should, it appears, generally not be a concern for the NOAA-20 and JPSS-2 VIIRS instruments in these bands (Tables 7-10).…”

“…Well-characterized spectral performance is critical to the reliable on-orbit operation of Earth-monitoring instruments, whether for routine measurements or for climate studies, and also lends confidence to radiometric calibration efforts and the products reliant on them [1,2]. The Clouds and the Earth's Radiant Energy System (CERES) project, for instance, relies on RSR-dependent calibration adjustments and atmospheric transmissivity calculations to produce accurate cloud products for consistent flux measurements [3][4][5][6][7]. As such, complete pre-launch evaluation of sensor geometric performance, including RSR co-registration and spatial response characterization, is a necessary requirement established to meet the goals of the remote sensing community [8][9][10][11][12][13].…”

The behavior of high-CAPE summer convection in large-domain large-eddy simulations with ICON

“…-SEVIRI CiPS (Cirrus Properties from SEVIRI, Strandgren et al, 2017a) -SEVIRI SatCORPS (The Satellite ClOud and Radiation Property retrieval System, Minnis et al, 2011, Trepte et al, 2019 -SEVIRI APICS (Algorithm for the Physical Investigation of Clouds with SEVIRI, Bugliaro et al, 2011) -SEVIRI CPP (Cloud Physical Properties from SEVIRI, Roebeling et al, 2006) -MODIS C6 (Moderate Resolution Imaging Spectroradiometer Collection 6 Cloud Products, Platnick et al, 2017) -SPARE-ICE (Synergistic Passive Atmospheric Retrieval Experiment-ICE, Holl et al, 2014) Four of them provide ice cloud properties with 15 min temporal resolution from the 12-channel SEVIRI imager aboard the geostationary MSG satellites (Schmetz et al, 2002), while two of them are from polar orbiting satellites (see next sections for details). The different methods and characteristics of the observational data sets are described in the following.…”

Evaluation of WRF-DART (ARW v.3.9.1.1 and DART manhattan release) multi-phase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment

“…The SatCORPS cloud products are retrieved using algorithms originally developed to analyse MODerate-resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua for the NASA Clouds and the Earth's Radiant Energy System (CERES) 25 project (Minnis et al, 2011;Trepte et al, 2018). These algorithms have been adapted to other imagers aboard geostationary (Minnis et al, 2008) and other low Earth-orbit satellites (Minnis et al, 2016).…”