Evaluations of atmospheric downward longwave radiation from 44 coupled general circulation models of CMIP5

The WCRP Coupled Model Intercomparison Project (CMIP) simulations expect increasing downward longwave radiation (DLR, surface LW down) from a human-enhanced greenhouse effect during the 21st century in the range of 10 &#8211; 40 Wm-2. We announce a public challenge to these predictions based on a long known but rarely referred theoretical constraint. Following the logic of original radiative transfer equations of Schwarzschild (1906, Eq. 11), a relationship connects surface net radiation to the effective emission, independent of the optical depth. This relationship is reproduced by several textbooks on atmospheric radiation like Goody (1964, Eq. 2.115), Goody and Yung (1989, Eq. 2.146), Houghton (2002, Eq. 2.13), Pierrehumbert (2010, Eq. 4.44-4.45). In CERES notation: Surface [shortwave (SW) + longwave (LW)] net = OLR/2. A specific &#8220;gross&#8221; version is: Surface (SW net + LW down) = 2OLR. These are for the cloudless case. Their all-sky form includes longwave cloud radiative effect (LWCRE): Surface SW+LW net = (OLR &#8211; LWCRE)/2 and Surface (SW net + LW down) = 2OLR + LWCRE. Controlling these four equations on CERES EBAF Edition 4.1, 18 years of data, and on EBAF Ed4.1 Data Quality Summary Table 2-1 and Table 4-1, each of them is valid within 3 Wm-2. The all-sky versions are satisfied by the IPCC-AR5 (2013) global energy budget (Fig. 2.11) and a water cycle assessment (Stephens and L'Ecuyer 2015) within 2 Wm-2. We couldn't find any reference to these equalities in the literature on general circulation models or climate sensitivity. Applying known definitions, the equations can be solved for LWCRE, resulting in a set of small integers (Zagoni, EGU2019). All-sky fluxes: Surface SW net = 6; Surface LW net = &#8211;2; DLR = 13; OLR = 9. Clear-sky fluxes: Surface SW net = 8; Surface LW net = &#8211;3; DLR = 12; OLR = 10; Surface LW up (ULW) = 15 (both for all-sky and clear-sky); LWCRE (surface and TOA) = 1. From this solution it comes for all-sky: DLR = (13/9)OLR, ULW = (15/9)OLR, and for clear-sky ULW = (15/10)OLR. Since the physical principles and conditions behind these equations are solid and justified by observations, we expect them to remain valid in the forthcoming decades as well. CMIP6 models might represent regional distribution changes and cloud feedbacks correctly, in lack of global constraints they may lead to profoundly different outcomes in the long run. This is a testable difference. To check the robustness and stationarity of our equations, we challenge published CMIP5 predictions. We predict for the 21st century: all-sky DLR = (13/9)OLR &#177; 3.0 Wm-2; ULW = (15/9)OLR &#177; 3.0 Wm-2 and clear-sky ULW = (15/10)OLR &#177; 3.0 Wm-2. Initial status (CERES EBAF Edition 4.1 annual global means for 2018): all-sky OLR = 240.14, DLR = 344.82, ULW = 399.37, hence all-sky DLR = (13/9)OLR &#8211; 2.05 and ULW = (15/9)OLR &#8211; 0.86 (Wm-2); clear-sky ULW = 399.05, OLR = 265.80, hence ULW = (15/10)OLR + 0.35 Wm-2. Greenhouse effect: g(theory) = G/ULW = (ULW&#8211;OLR)/ULW = (15 &#8211; 9)/15 = 0.4, g(observed) = 0.399.

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The relevance of mid-Holocene Arctic warming to the future

Climate of the Past ◽

10.5194/cp-15-1375-2019 ◽

2019 ◽

Vol 15 (4) ◽

pp. 1375-1394 ◽

Cited By ~ 6

Author(s):

Masakazu Yoshimori ◽

Marina Suzuki

Keyword(s):

Surface Temperature ◽

General Circulation ◽

Temperature Response ◽

Longwave Radiation ◽

General Circulation Models ◽

Cross Model ◽

Arctic Warming ◽

Temperature Changes ◽

The Future ◽

Arctic Climate Change

Abstract. There remain substantial uncertainties in future projections of Arctic climate change. There is a potential to constrain these uncertainties using a combination of paleoclimate simulations and proxy data, but such a constraint must be accompanied by physical understanding on the connection between past and future simulations. Here, we examine the relevance of an Arctic warming mechanism in the mid-Holocene (MH) to the future with emphasis on process understanding. We conducted a surface energy balance analysis on 10 atmosphere and ocean general circulation models under the MH and future Representative Concentration Pathway (RCP) 4.5 scenario forcings. It is found that many of the dominant processes that amplify Arctic warming over the ocean from late autumn to early winter are common between the two periods, despite the difference in the source of the forcing (insolation vs. greenhouse gases). The positive albedo feedback in summer results in an increase in oceanic heat release in the colder season when the atmospheric stratification is strong, and an increased greenhouse effect from clouds helps amplify the warming during the season with small insolation. The seasonal progress was elucidated by the decomposition of the factors associated with sea surface temperature, ice concentration, and ice surface temperature changes. We also quantified the contribution of individual components to the inter-model variance in the surface temperature changes. The downward clear-sky longwave radiation is one of major contributors to the model spread throughout the year. Other controlling terms for the model spread vary with the season, but they are similar between the MH and the future in each season. This result suggests that the MH Arctic change may not be analogous to the future in some seasons when the temperature response differs, but it is still useful to constrain the model spread in the future Arctic projection. The cross-model correlation suggests that the feedbacks in preceding seasons should not be overlooked when determining constraints, particularly summer sea ice cover for the constraint of autumn–winter surface temperature response.

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Why is the AMOC Monostable in Coupled General Circulation Models?

Journal of Climate ◽

10.1175/jcli-d-13-00264.1 ◽

2014 ◽

Vol 27 (6) ◽

pp. 2427-2443 ◽

Cited By ~ 27

Author(s):

Wei Liu ◽

Zhengyu Liu ◽

Esther C. Brady

Keyword(s):

General Circulation ◽

General Circulation Models ◽

Meridional Overturning Circulation ◽

Surface Salinity ◽

Sensitivity Experiment ◽

Climate System Model ◽

Control Simulation ◽

Coupled General Circulation Models ◽

The Stability ◽

Flux Adjustment

Abstract This paper is concerned with the question: why do coupled general circulation models (CGCM) seem to be biased toward a monostable Atlantic meridional overturning circulation (AMOC)? In particular, the authors investigate whether the monostable behavior of the CGCMs is caused by a bias of model surface climatology. First observational literature is reviewed, and it is suggested that the AMOC is likely to be bistable in the real world in the past and present. Then the stability of the AMOC in the NCAR Community Climate System Model, version 3 (CCSM3) is studied by comparing the present-day control simulation (without flux adjustment) with a sensitivity experiment with flux adjustment. It is found that the monostable AMOC in the control simulation is altered to a bistable AMOC in the flux-adjustment experiment because a reduction of the surface salinity biases in the tropical and northern North Atlantic leads to a reduction of the bias of freshwater transport in the Atlantic. In particular, the tropical bias associated with the double ITCZ reduces salinity in the upper South Atlantic Ocean and, in turn, the AMOC freshwater export, which tends to overstabilize the AMOC and therefore biases the AMOC from bistable toward monostable state. This conclusion is consistent with a further analysis of the stability indicator of two groups of IPCC Fourth Assessment Report (AR4) CGCMs: one without and the other with flux adjustment. Because the tropical bias is a common feature among all CGCMs without flux adjustment, the authors propose that the surface climate bias, notably the tropical bias in the Atlantic, may contribute significantly to the monostability of AMOC behavior in current CGCMs.

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Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

Remote Sensing ◽

10.3390/rs13214464 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4464

Author(s):

Jiawen Xu ◽

Xiaotong Zhang ◽

Chunjie Feng ◽

Shuyue Yang ◽

Shikang Guan ◽

...

Keyword(s):

General Circulation ◽

Bayesian Model Averaging ◽

Mean Squared Error ◽

Radiant Energy ◽

Coupled Model ◽

Model Averaging ◽

Longwave Radiation ◽

Energy System ◽

General Circulation Models ◽

The Individual

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).

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Status and Improvements of Coupled General Circulation Models

Science ◽

10.1126/science.288.5473.1991 ◽

2000 ◽

Vol 288 (5473) ◽

pp. 1991-1997 ◽

Cited By ~ 37

Author(s):

H. Grassl

Keyword(s):

General Circulation ◽

General Circulation Models ◽

Coupled General Circulation Models

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The Double-ITCZ Syndrome in Coupled General Circulation Models: The Role of Large-Scale Vertical Circulation Regimes

Journal of Climate ◽

10.1175/2009jcli3002.1 ◽

2010 ◽

Vol 23 (5) ◽

pp. 1127-1145 ◽

Cited By ~ 95

Author(s):

A. Bellucci ◽

S. Gualdi ◽

A. Navarra

Keyword(s):

Surface Temperature ◽

Systematic Error ◽

General Circulation ◽

Large Scale ◽

Deep Convection ◽

General Circulation Models ◽

Intertropical Convergence Zone ◽

Convergence Zone ◽

Vertical Circulation ◽

Coupled General Circulation Models

Abstract The double–intertropical convergence zone (DI) systematic error, affecting state-of-the-art coupled general circulation models (CGCMs), is examined in the multimodel Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) ensemble of simulations of the twentieth-century climate. The aim of this study is to quantify the DI error on precipitation in the tropical Pacific, with a specific focus on the relationship between the DI error and the representation of large-scale vertical circulation regimes in climate models. The DI rainfall signal is analyzed using a regime-sorting approach for the vertical circulation regimes. Through the use of this compositing technique, precipitation events are regime sorted based on the large-scale vertical motions, as represented by the midtropospheric Lagrangian pressure tendency ω500 dynamical proxy. This methodology allows partition of the precipitation signal into deep and shallow convective components. Following the regime-sorting diagnosis, the total DI bias is split into an error affecting the magnitude of precipitation associated with individual convective events and an error affecting the frequency of occurrence of single convective regimes. It is shown that, despite the existing large intramodel differences, CGCMs can be ultimately grouped into a few homogenous clusters, each featuring a well-defined rainfall–vertical circulation relationship in the DI region. Three major behavioral clusters are identified within the AR4 models ensemble: two unimodal distributions, featuring maximum precipitation under subsidence and deep convection regimes, respectively, and one bimodal distribution, displaying both components. Extending this analysis to both coupled and uncoupled (atmosphere only) AR4 simulations reveals that the DI bias in CGCMs is mainly due to the overly frequent occurrence of deep convection regimes, whereas the error on rainfall magnitude associated with individual convective events is overall consistent with errors already present in the corresponding atmosphere stand-alone simulations. A critical parameter controlling the strength of the DI systematic error is identified in the model-dependent sea surface temperature (SST) threshold leading to the onset of deep convection (THR), combined with the average SST in the southeastern Pacific. The models featuring a THR that is systematically colder (warmer) than their mean surface temperature are more (less) prone to exhibit a spurious southern intertropical convergence zone.

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