Understanding the Drivers of Recent Top-of-atmosphere (TOA) Radiation Changes Observed by the Clouds and the Earth’s Energy System (CERES)
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Engineering topics
Publications and source records attributed to Norman G Loeb.
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From the A-train satellite mission, more than 11 years of Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat satellite measurements are available from 2007 to 2017. In this study, we examine cloud macrophysical changes from a passive sensor, Moderate Resolution Imaging Spectroradiometer (MODIS), and two active sensors, CALIPSO and CloudSat (CALCS). MODIS and CALCS capture common features of the cloud changes related to El Niño–Southern Oscillation (ENSO) events, i.e., increase of low clouds during La Niña and increase of mid and high clouds during El Niño over the eastern Pacific. However, optically thin cirrus clouds are well detected by CALCS while these are often missed by MODIS. As a result, MODIS shows much flatter distributions of cloud top heights. In addition, compared to MODIS, CALCS cloud volume anomalies are better correlated with relative humidity anomalies. The differences between MODIS and CALCS appear in low cloud variations. Particularly, fluctuations in MODIS low cloud anomalies are larger than CALCS, and MODIS low cloud anomalies are anticorrelated with mid/high cloud anomalies. This is because of the limitation in detecting underlying clouds by MODIS passive sensor. Also, the layer thickness of MODIS mid/high clouds is thinner than that from CALCS, less affecting cloud amounts at 0-3 km altitude.
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The uncertainty in regional surface energy flux derived by summing all energy flux components is known to be large. In addition, quantifying the regional energy flux uncertainty considering all flux component uncertainties is very difficult. However, this approach is needed to understand regional energy flux components and how these components change with time. The CERES surface radiation budget data product, Edition 4.1 EBAF combined with reanalysis products was used to assess regional surface energy budget over ocean in earlier studies. The CERES team revised the data product and released Edition 4.2 EBAF product in February 2023. Prominent differences from the earlier edition are: 1) no geostationary satellite derived cloud properties are used for surface irradiance computations and 2) MERRA-2 provides temperature and humidity profiles. Combined with surface turbulent fluxes from various products, this study uses the revised EBAF surface irradiances and addresses regional energy budget over ocean. In addition, the uncertainty in regional surface radiation and energy budgets is discussed.
Effects of cloud diurnal cycle on top-of-atmosphere (TOA) and surface regional monthly mean irradiances, climatological mean, and anomalies are analyzed using CERES derived TOA irradiances and surface irradiances computed with MODIS derived cloud properties. Cloud properties derived from Terra and Aqua MODIS are sufficient to capture cloud diurnal cycle to compute regional monthly mean surface irradiances. While missing cloud diurnal cycle leads to a biased TOA and surface regional irradiances for regions with a strong cloud diurnal cycle, monthly regional TOA and surface anomalies derived from one sun-synchronous orbit agrees well with those derived from two sun-synchronous orbits. Based on these results, the algorithm to produce Edition 4.2 CERES EBAF product is developed. Regional TOA and surface climatological means derived from one sun-synchronous orbit are adjusted to match corresponding climatological means derived from Terra+Aqua observations. This climatological adjustment approach is used to merge the Terra only period to the Terra+Aqua period and to extend the Terra and Aqua record by merging NOAA20 observations. Two additional differences of Edition 4.2 EBAF algorithm to compute surface irradiances compared to the earlier version are: 1) no geostationary satellite derived cloud properties are used and 2) temperature and humidity from MERRA-2 instead of GEOIS-5.4.1 are used. Once surface monthly regional mean irradiances are compared with surface observations, the agreement is equivalent to the agreement with the earlier version. However, because surface irradiances are not affected by geostationary satellite artifacts, regional surface irradiance anomaly time series is significantly improved, especially for longwave irradiances.
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