Satellite observations show a near-zero trend in the top-of-atmosphere global-mean net cloud radiative effect (CRE), suggesting that clouds did not further cool nor heat the planet over the last two decades. The causes of this observed trend are unknown and can range from effective radiative forcing (ERF) to cloud feedbacks, cloud masking, and internal variability. We find that the near-zero NetCRE trend is a result of a significant negative trend in the longwave (LW) CRE and a significant positive trend in the shortwave (SW) CRE, cooling and heating the climate system, respectively. We find that it is exceptionally unlikely (<1% probability) that internal variability can explain the observed LW and SW CRE trends. Instead, the majority of the observed LWCRE trend arises from cloud masking wherein increases in greenhouse gases reduce OLR in all-sky conditions less than in clear-sky conditions. In SWCRE, rapid cloud adjustments to greenhouse gases, aerosols, and natural forcing agents (ERF) explain a majority of the observed trend. Over the northeast Pacific, we show that ERF, hitherto an ignored factor, contributes as much as cloud feedbacks to the observed SWCRE trend. Large contributions from ERF and cloud masking to the global-mean LW and SW CRE trends are supplemented by negative LW and positive SW cloud feedback trends, which are detectable at 80%–95% confidence depending on the observational uncertainty assumed. The large global-mean LW and SW cloud feedbacks cancel, leaving a small net cloud feedback that is unconstrained in sign, implying that clouds could amplify or dampen global warming.
Global greenhouse gas forcing and feedbacks are the primary causes of climate change but have limited direct observations. Here we show that continuous, stable, global, hyperspectral infrared satellite measurements (2003–2021) display decreases in outgoing longwave radiation (OLR) in the CO2, CH4, and N2O absorption bands and increases in OLR in the window band and H2O absorption bands. By conducting global line-by-line radiative transfer simulations with 2003–2021 meteorological conditions, we show that increases in CO2, CH4, and N2O concentrations caused an instantaneous radiative forcing and stratospheric cooling adjustment that decreased OLR. The climate response, comprising surface and atmospheric feedbacks to radiative forcings and unforced variability, increased OLR. The spectral trends predicted by our climate change experiments using our general circulation model identify three bedrock principles of the physics of climate change in the satellite record: an increasing greenhouse effect, stratospheric cooling, and surface-tropospheric warming.
Schmidt, Gavin A., Timothy Andrews, Susanne E Bauer, Paul J Durack, Norman G Loeb, V Ramaswamy, Nathan P Arnold, Michael Bosilovich, Jason N S Cole, Larry W Horowitz, Gregory C Johnson, John M Lyman, Brian Medeiros, Takuro Michibata, Dirk Olonscheck, David J Paynter, Shiv Priyam Raghuraman, Michael Schulz, Daisuke Takasuka, Vijay Tallapragada, Patrick C Taylor, and Tilo Ziehn, July 2023: CERESMIP: A climate modeling protocol to investigate recent trends in the Earth's Energy Imbalance. Frontiers in Climate, 5, DOI:10.3389/fclim.2023.1202161. Abstract
The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.
The observed trend in Earth’s energy imbalance (TEEI), a measure of the acceleration of heat uptake by the planet, is a fundamental indicator of perturbations to climate. Satellite observations (2001–2020) reveal a significant positive globally-averaged TEEI of 0.38 ± 0.24 Wm−2decade−1, but the contributing drivers have yet to be understood. Using climate model simulations, we show that it is exceptionally unlikely (<1% probability) that this trend can be explained by internal variability. Instead, TEEI is achieved only upon accounting for the increase in anthropogenic radiative forcing and the associated climate response. TEEI is driven by a large decrease in reflected solar radiation and a small increase in emitted infrared radiation. This is because recent changes in forcing and feedbacks are additive in the solar spectrum, while being nearly offset by each other in the infrared. We conclude that the satellite record provides clear evidence of a human-influenced climate system.
The clear sky greenhouse effect (G) is defined as the trapping of infrared radiation by the atmosphere in the absence of clouds. The magnitude and variability of G is an important element in the understanding of Earth’s energy balance; yet the quantification of the governing factors of G is poor. The global mean G averaged over 2000 to 2016 is 130‐133 Wm−2 across datasets. We use satellite observations from CERES EBAF to calculate the monthly anomalies in the clear sky greenhouse effect (∆G). We quantify the contributions to ∆G due to changes in surface temperature, atmospheric temperature, and water vapor by performing partial radiation perturbation experiments using ERA‐Interim and GFDL AM4 climatological data. Water vapor in the middle troposphere and upper troposphere is found to contribute equally to the global mean and tropical mean ∆G. Holding relative humidity (RH) fixed in the radiative transfer calculations captures the temporal variability of global mean ∆G while variations in RH control the regional ∆G signal. The variations in RH are found to help generate the clear sky super greenhouse effect (SGE). 36% of Earth’s area exhibits SGE and this disproportionately contributes to 70% of the globally averaged magnitude of ∆G. In the global mean, G’s sensitivity to surface temperature is 3.1‐4.0 Wm−2K−1 and the clear sky longwave feedback parameter is 1.5‐2.0 Wm−2K−1. CERES observations lie at the more sensitive ends of these ranges and the spread arises from its cloud removal treatment, suggesting that it is difficult to constrain clear sky feedbacks
