The algorithm to produce the Clouds and the Earth’s Radiant Energy System (CERES) Edition 4.0 (Ed4) Energy Balanced and Filled (EBAF)-surface data product is explained. The algorithm forces computed top-of-atmosphere (TOA) irradiances to match with Ed4 EBAF-TOA irradiances by adjusting surface, cloud, and atmospheric properties. Surface irradiances are subsequently adjusted using radiative kernels. The adjustment process is composed of two parts: bias correction and Lagrange multiplier. The bias in temperature and specific humidity between 200 and 500 hPa used for the irradiance computation is corrected based on observations by Atmospheric Infrared Sounder (AIRS). Similarly, the bias in the cloud fraction is corrected based on observations by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat. Remaining errors in surface, cloud, and atmospheric properties are corrected in the Lagrange multiplier process. Ed4 global annual mean (January 2005 through December 2014) surface net shortwave (SW) and longwave (LW) irradiances increase by 1.3 W m−2 and decrease by 0.2 W m−2, respectively, compared to EBAF Edition 2.8 (Ed2.8) counterparts (the previous version), resulting in an increase in net SW + LW surface irradiance of 1.1 W m−2. The uncertainty in surface irradiances over ocean, land, and polar regions at various spatial scales are estimated. The uncertainties in all-sky global annual mean upward and downward shortwave irradiance are 3 and 4 W m−2, respectively, and the uncertainties in upward and downward longwave irradiance are 3 and 6 W m−2, respectively. With an assumption of all errors being independent, the uncertainty in the global annual mean surface LW + SW net irradiance is 8 W m−2.

Points  Satellite and in situ observations independently show an approximate doubling of Earth's Energy Imbalance (EEI) from mid-2005 to mid-2019  Anthropogenic forcing, internal variability, and climate feedbacks all contribute to the positive trend in EEI  Marked decreases in clouds and sea-ice and increases in trace gases and water vapor combine to increase the rate of planetary heat uptake

This study examines changes in Earth's energy budget during and after the global warming "pause" (or "hiatus") using observations from the Clouds and the Earth's Radiant Energy System. We find a marked 0.83 ± 0.41 Wm −2 reduction in global mean reflected shortwave (SW) top-of-atmosphere (TOA) flux during the three years following the hiatus that results in an increase in net energy into the climate system. A partial radiative perturbation analysis reveals that decreases in low cloud cover are the primary driver of the decrease in SW TOA flux. The regional distribution of the SW TOA flux changes associated with the decreases in low cloud cover closely matches that of sea-surface temperature warming, which shows a pattern typical of the positive phase of the Pacific Decadal Oscillation. Large reductions in clear-sky SW TOA flux are also found over much of the Pacific and Atlantic Oceans in the northern hemisphere. These are associated with a reduction in aerosol optical depth consistent with stricter pollution controls in China and North America. A simple energy budget framework is used to show that TOA radiation (particularly in the SW) likely played a dominant role in driving the marked increase in temperature tendency during the post-hiatus period.Climate 2018, 6, 62 2 of 18 exhibits decreasing TOA net radiative flux [6]. Outgoing longwave (LW) radiation exhibits similar increases with warming in each RCP scenario, but reflected shortwave (SW) radiation decreases far more rapidly for RCP8.5 due to marked decreases in cloud cover and snow/sea-ice. In time, the climate system heats up sufficiently in all scenarios to arrive at a new equilibrium temperature and an energy balance at the TOA.At decadal timescales, when internal variations in the climate system dominate, the link between TOA radiation and surface temperature is more complex. Using pre-industrial control simulations of three generations of Met Office Hadley Centre coupled atmosphere-ocean climate models, Palmer et al. [7] show that while decadal trends in global mean sea-surface temperature (SST) tend to be positive (negative) when the decadal average net downward TOA flux is positive (negative), ≈30% of decades show opposite trends in SST and total energy, implying that it is not uncommon for a decade to show a decreasing trend in SST and a positive decadal average net TOA flux. The reason for the large scatter between decadal SST and total energy trends is re-distribution of heat within the ocean. In order to relate net TOA radiation and global mean surface temperature changes at decadal timescales, Xie et al. [4] decompose the climate feedback term into forced and natural variability components, with the latter term accounting for the lag between TOA radiation and surface temperature variations.Between approximately 1998 and 2013, the rate of increase in global mean surface temperature slowed down relative to that during the latter half of the 20th century [8][9][10]. This so-called "global warming hiatus" period coincided with the negative phase of...

A feature detection and extinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement Program’s (ARM) Raman lidar (RL) has been developed. Presented here is Part II of the FEX algorithm: the retrieval of cloud and aerosol extinction profiles. The directly retrieved extinction profiles using the Raman method are supplemented by other retrieval methods developed for elastic backscatter lidars. Portions of features where the extinction-to-backscatter ratios (i.e., lidar ratios) can be obtained are used to infer the lidar ratios for the regions where no such estimate can be made. When neither directly retrieved nor an inferred value can be determined, a climatological lidar ratio is used. This best-estimate approach results in the need to use climatological lidar ratios for less than about 5% of features, except for thin cirrus at the ARM tropical western Pacific Darwin site, where above 12 km, about 20% of clouds use a climatological lidar ratio. A classification of feature type is made, guided by the atmosphere’s thermodynamic state and the feature’s scattering properties: lidar ratio, backscatter, and depolarization. The contribution of multiple scattering is explicitly considered for each of the ARM RL channels. A comparison between aerosol optical depth from FEX and that from collocated sun photometers over multiple years at two ARM sites shows an agreement (in terms of bias error) of about −0.3% to −4.3% (relative to the sun photometer).

Independent research teams have constructed long-term tropical time series of the temperature of the middle troposphere (TMT) using satellite Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) measurements. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends beginning in 1979 disagree by more than a factor of 3. Previous studies suggest that the discrepancy in tropical TMT trends is caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections. This work introduces a new observationally based method for removing biases related to satellite diurnal drift. Over land, the derived diurnal correction is similar to a general circulation model (GCM) diurnal cycle. Over ocean, the diurnal corrections have a negligible effect on TMT trends, indicating that oceanic biases are small. It is demonstrated that this method is effective at removing biases between coorbiting satellites and biases between nodes of individual satellites. Using a homogenized TMT dataset, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from GCMs. It is shown that bias corrections for diurnal drift based on a GCM produce tropical trends very similar to those from the observationally based correction, with a trend difference smaller than 0.02 K decade−1. Differences between various TMT datasets are explored further. Large differences in tropical TMT trends between this work and that of the University of Alabama in Huntsville (UAH) are attributed to differences in the treatment of the NOAA-9 target factor and the diurnal cycle correction.