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Norman G. Loeb, Hailan Wang, Fred G. Rose, Seiji Kato, William L. Smith Jr, and Sunny Sun-Mack

Abstract

A diagnostic tool for determining surface and atmospheric contributions to interannual variations in top-of-atmosphere (TOA) reflected shortwave (SW) and net downward SW surface radiative fluxes is introduced. The method requires only upward and downward radiative fluxes at the TOA and surface as input and therefore can readily be applied to both satellite-derived and model-generated radiative fluxes. Observations from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.0 product show that 81% of the monthly variability in global mean reflected SW TOA flux anomalies is associated with atmospheric variations (mainly clouds), 6% is from surface variations, and 13% is from atmosphere–surface covariability. Over the Arctic Ocean, most of the variability in both reflected SW TOA flux and net downward SW surface flux anomalies is explained by variations in sea ice and cloud fraction alone (r 2 = 0.94). Compared to CERES, variability in two reanalyses—the ECMWF interim reanalysis (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)—show large differences in the regional distribution of variance for both the atmospheric and surface contributions to anomalies in net downward SW surface flux. For MERRA-2 the atmospheric contribution is 17% too large compared to CERES while ERA-Interim underestimates the variance by 15%. The difference is mainly due to how cloud variations are represented in the reanalyses. The overall surface contribution in both ERA-Interim and MERRA-2 is smaller than CERES EBAF by 15% for ERA-Interim and 58% for MERRA-2, highlighting limitations of the reanalyses in representing surface albedo variations and their influence on SW radiative fluxes.

Open access
Jake J. Gristey, J. Christine Chiu, Robert J. Gurney, Keith P. Shine, Stephan Havemann, Jean-Claude Thelen, and Peter G. Hill

Abstract

The spectrum of reflected solar radiation emerging at the top of the atmosphere is rich with Earth system information. To identify spectral signatures in the reflected solar radiation and directly relate them to the underlying physical properties controlling their structure, over 90 000 solar reflectance spectra are computed over West Africa in 2010 using a fast radiation code employing the spectral characteristics of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Cluster analysis applied to the computed spectra reveals spectral signatures related to distinct surface properties, and cloud regimes distinguished by their spectral shortwave cloud radiative effect (SWCRE). The cloud regimes exhibit a diverse variety of mean broadband SWCREs, and offer an alternative approach to define cloud type for SWCRE applications that does not require any prior assumptions. The direct link between spectral signatures and distinct physical properties extracted from clustering remains robust between spatial scales of 1, 20, and 240 km, and presents an excellent opportunity to understand the underlying properties controlling real spectral reflectance observations. Observed SCIAMACHY spectra are assigned to the calculated spectral clusters, showing that cloud regimes are most frequent during the active West African monsoon season of June–October in 2010, and all cloud regimes have a higher frequency of occurrence during the active monsoon season of 2003 compared with the inactive monsoon season of 2004. Overall, the distinct underlying physical properties controlling spectral signatures show great promise for monitoring evolution of the Earth system directly from solar spectral reflectance observations.

Open access
Kevin E. Trenberth, Yongxin Zhang, John T. Fasullo, and Lijing Cheng

Abstract

Ocean meridional heat transports (MHTs) are deduced as a residual using energy budgets to produce latitude versus time series for the globe, Indo-Pacific, and Atlantic. The top-of-atmosphere (TOA) radiation is combined with the vertically integrated atmospheric energy divergence from atmospheric reanalyses to produce the net surface energy fluxes everywhere. The latter is then combined with estimates of the vertically integrated ocean heat content (OHC) tendency to produce estimates of the ocean heat divergence. Because seasonal sea ice and land runoff effects are not fully considered, the mean annual cycle is incomplete, but those effects are small for interannual variability. However, there is a mismatch between 12-month inferred surface flux and the corresponding OHC changes globally, requiring adjustments to account for the Earth’s global energy imbalance. Estimates are greatly improved by building in the constraint that MHT must go to zero at the northern and southern extents of the ocean basin at all times, enabling biases between the TOA and OHC data to be reconciled. Zonal mean global, Indo-Pacific, and Atlantic basin ocean MHTs are computed and presented as 12-month running means and for the mean annual cycle for 2000–16. For the Indo-Pacific, the tropical and subtropical MHTs feature a strong relationship with El Niño–Southern Oscillation (ENSO), and in the Atlantic, MHT interannual variability is significantly affected by and likely influences the North Atlantic Oscillation (NAO). However, Atlantic and Pacific changes are linked, suggesting that the northern annular mode (as opposed to NAO) is predominant. There is also evidence of decadal variability or trends.

Open access