In a warming climate, greenhouse gases modulate thermal cooling to space from the surface and atmosphere, which is a fundamental feedback process that affects climate sensitivity. Recent studies have found that when relative humidity (RH) is constant with global warming, Earth's clear-sky longwave feedback would be dominated by surface cooling to space. Using a millennium-length coupled general circulation model and accurate line-by-line radiative transfer calculations, here we show that the atmospheric cooling to space accounts for 12%–50% of the feedback parameter from poles to tropics. A simple yet comprehensive model is proposed here for explaining the atmospheric feedback process. It is found that when RH is held constant, the atmospheric feedback stabilizes the climate because (a) water vapor spectral lines are weakened by the collision-broadening effect between water vapor and radiatively inert background gases, and (b) thermal emissions from other greenhouse gases increases due to enhanced Planck emission which is proportional to the surface warming. Each mechanism is responsible for half of the atmospheric feedback. We further elucidate that in hotter climates, the atmospheric feedback is more stabilizing because of (a) greater tropospheric opacity, and (b) more dramatic changes in air temperature with respect to transmission, owing to the pseudo-adiabatic expansion of air with surface warming. The sum of surface and atmospheric feedback, the clear-sky longwave feedback is accurately predicted by the simple model from the climate base state. Our study provides a theoretical way for assessing Earth's clear-sky longwave feedback, with important implications for Earth-like planets.
Feng, Jing, David J Paynter, Chenggong Wang, and Raymond Menzel, September 2023: How atmospheric humidity drives the outgoing longwave radiation–surface temperature relationship and inter-model spread. Environmental Research Letters, 18(10), DOI:10.1088/1748-9326/acfb98. Abstract
The Earth's global radiation budget depends critically on the relationship between outgoing longwave radiation (OLR) and surface temperature (Ts). Using the fifth generation of European ReAnalysis dataset, we find that although OLR appears to be linearly dependent on Ts over a wide range, there are significant deviations from the linearity in the OLR–Ts relationship for regions warmer than 270 K Ts, which covers 89% of the surface of Earth. While the AMIP runs of CMIP6 models largely capture the overall OLR–Ts relationship, considerable discrepancies are found in clear-sky OLR at given Ts ranges. In this study, we investigate physical mechanisms that control the clear-sky OLR–Ts relationship seen in reanalysis and CMIP6 models by using accurate radiative transfer calculations. Our study identifies three key mechanisms to explain both the linearity and departure from linearity of the clear-sky OLR–Ts relationship. The first is a surface contribution, controlled by the thermal emission of the surface and the infrared opacity of the atmosphere, accounting for 60% of the observed clear-sky OLR–Ts linear slope. The second is changes in atmospheric emission induced by a foreign pressure effect on water vapor and other greenhouse gases, which accounts for 30% of the linear slope in a clear-sky condition. The third is changes in atmospheric emission induced by variations in relative humidity (RH), particularly in the mid-troposphere (250 to 750 hPa), which determines the non-linearity in the clear-sky OLR–Ts relationship and adds to the remaining 10% of the slope. The inter-model spread in mid-tropospheric RH explains a large fraction of the differences in clear-sky OLR across CMIP6 models at given surface temperatures. Furthermore, the three key mechanisms outlined here apply to the OLR–Ts relationship in all-sky conditions: clouds disguise the surface contribution but increase the atmospheric contribution, retaining a similar linear slope to the clear-sky condition while amplifying the non-linear curvature.
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.
Biogenic secondary organic aerosols (SOAs) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability in observed organic aerosol (OA) in the southeast US, combined with a global chemistry–climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40 % of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability in surface OA. We hypothesize that the rest of the OA decreasing trend is largely due to a reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability in OA in this region. Extending to a centennial scale, our model shows that global SOA production increases by 36 % despite BVOC reductions from the preindustrial period to the present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models.
Parameterizing incident solar radiation over complex topography regions in Earth system models (ESMs) remains a challenging task. In ESMs, downward solar radiative fluxes at the surface are typically computed using plane-parallel radiative transfer schemes, which do not explicitly account for the effects of a three-dimensional topography, such as shading and reflections. To improve the representation of these processes, we introduce and test a parameterization of radiation–topography interactions tailored to the Geophysical Fluid Dynamics Laboratory (GFDL) ESM land model. The approach presented here builds on an existing correction scheme for direct, diffuse, and reflected solar irradiance terms over three-dimensional terrain. Here we combine this correction with a novel hierarchical multivariate clustering algorithm that explicitly describes the spatially varying downward irradiance over mountainous terrain. Based on a high-resolution digital elevation model, this combined method first defines a set of sub-grid land units (“tiles”) by clustering together sites characterized by similar terrain–radiation interactions (e.g., areas with similar slope orientation, terrain, and sky view factors). Then, based on terrain parameters characteristic for each tile, correction terms are computed to account for the effects of local 3D topography on shortwave radiation over each land unit. We develop and test this procedure based on a set of Monte Carlo ray-tracing simulations approximating the true radiative transfer process over three-dimensional topography. Domains located in three distinct geographic regions (Alps, Andes, and Himalaya) are included in this study to allow for independent testing of the methodology over surfaces with differing topographic features. We find that accounting for the sub-grid spatial variability of solar irradiance originating from interactions with complex topography is important as these effects led to significant local differences with respect to the plane-parallel case, as well as with respect to grid-cell-scale average topographic corrections. We further quantify the importance of the topographic correction for a varying number of terrain clusters and for different radiation terms (direct, diffuse, and reflected radiative fluxes) in order to inform the application of this methodology in different ESMs with varying sub-grid tile structure. We find that even a limited number of sub-grid units such as 10 can lead to recovering more than 60 % of the spatial variability of solar irradiance over a mountainous area.
Hydrogen (H2) has been proposed as an alternative energy carrier to reduce the carbon footprint and associated radiative forcing of the current energy system. Here, we describe the representation of H2 in the GFDL-AM4.1 model including updated emission inventories and improved representation of H2 soil removal, the dominant sink of H2. The model best captures the overall distribution of surface H2, including regional contrasts between climate zones, when vd(H2) is modulated by soil moisture, temperature, and soil carbon content. We estimate that the soil removal of H2 increases with warming (2–4% per K), with large uncertainties stemming from different regional response of soil moisture and soil carbon. We estimate that H2 causes an indirect radiative forcing of 0.84 mW m−2/(Tg(H2)yr−1) or 0.13 mW m−2 ppbv−1, primarily due to increasing CH4 lifetime and stratospheric water vapor production.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
Pincus, Robert, Stefan A Buehler, Manfred Brath, Cyril Crevoisier, Omar Jamil, K Franklin Evans, James Manners, Raymond Menzel, Eli J Mlawer, David J Paynter, Rick L Pernak, and Yoann Tellier, December 2020: Benchmark calculations of radiative forcing by greenhouse gases. JGR Atmospheres, 125(23), DOI:10.1029/2020JD033483. Abstract
Changes in concentrations of greenhouse gases lead to changes in radiative fluxes throughout the atmosphere. The value of this change, the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line-by-line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. Clear-sky instantaneous forcing by greenhouse gases is computed using a set of 100 profiles, selected from a reanalysis of present-day conditions, that represent the global annual mean forcing from preindustrial times to the present day with sampling errors of less than 0.01 W m−2. Six contributing line-by-line models agree in their estimate of this forcing to within 0.025 W m−2 while even recently developed parameterizations have typical errors 4 or more times larger, suggesting both that the samples reveal true differences among line-by-line models and that parameterization error will be readily identifiable. Agreement among line-by-line models is better in the longwave than in the shortwave where differing treatments of the water vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are estimated from climate model simulations, and the adjustment due to stratospheric temperature changes estimated by assuming fixed dynamical heating. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest nonlinearity.
We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
