scholarly journals The faint young Sun problem revisited with a 3-D climate–carbon model – Part 1

2014 ◽  
Vol 10 (2) ◽  
pp. 697-713 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot

Abstract. During the Archaean, the Sun's luminosity was 18 to 25% lower than the present day. One-dimensional radiative convective models (RCM) generally infer that high concentrations of greenhouse gases (CO2, CH4) are required to prevent the early Earth's surface temperature from dropping below the freezing point of liquid water and satisfying the faint young Sun paradox (FYSP, an Earth temperature at least as warm as today). Using a one-dimensional (1-D) model, it was proposed in 2010 that the association of a reduced albedo and less reflective clouds may have been responsible for the maintenance of a warm climate during the Archaean without requiring high concentrations of atmospheric CO2 (pCO2). More recently, 3-D climate simulations have been performed using atmospheric general circulation models (AGCM) and Earth system models of intermediate complexity (EMIC). These studies were able to solve the FYSP through a large range of carbon dioxide concentrations, from 0.6 bar with an EMIC to several millibars with AGCMs. To better understand this wide range in pCO2, we investigated the early Earth climate using an atmospheric GCM coupled to a slab ocean. Our simulations include the ice-albedo feedback and specific Archaean climatic factors such as a faster Earth rotation rate, high atmospheric concentrations of CO2 and/or CH4, a reduced continental surface, a saltier ocean, and different cloudiness. We estimated full glaciation thresholds for the early Archaean and quantified positive radiative forcing required to solve the FYSP. We also demonstrated why RCM and EMIC tend to overestimate greenhouse gas concentrations required to avoid full glaciations or solve the FYSP. Carbon cycle–climate interplays and conditions for sustaining pCO2 will be discussed in a companion paper.

2013 ◽  
Vol 9 (2) ◽  
pp. 1509-1534 ◽  
Author(s):  
G. Le Hir ◽  
Y. Teitler ◽  
F. Fluteau ◽  
Y. Donnadieu ◽  
P. Philippot

Abstract. Considering the weak luminosity of the early Sun, it is generally inferred that high concentrations of greenhouse gases (CO2, CH4) are required to prevent the early Earth's surface temperature to drop below the freezing point of liquid water. Conversely, a new controversial assumption based on banded iron formation mineralogy hypothesizes that the Archean atmosphere was potentially characterized by low concentrations of CO2. To solve the faint young Sun problem, it was suggested that a reduced albedo associated to less reflective clouds was able to prevent the Earth to jump into a snowball state. In this very active debate, we have investigated the early Earth climate using a general circulation model to test this scenario. Our simulations include the ice albedo feedback and specific Archean climatic factors such as a different cloudiness, a faster Earth's rotation rate, and a reduced continental surface. We demonstrate that when larger cloud droplets are accounted for, clouds warm high latitudes and inhibit sea-ice formation. This process limits the ice-albedo feedback efficiency and may prevent a global glaciation. Due to this particular mechanism, low pCO2 allow maintaining a mild climate during the early Archean. This conclusion will be challenged in the second part of this paper, where the carbon cycle is considered.


2000 ◽  
Vol 18 (5) ◽  
pp. 583-588 ◽  
Author(s):  
W. Soon ◽  
E. Posmentier ◽  
S. Baliunas

Abstract. We compare the equilibrium climate responses of a quasi-dynamical energy balance model to radiative forcing by equivalent changes in CO2, solar total irradiance (Stot) and solar UV (SUV). The response is largest in the SUV case, in which the imposed UV radiative forcing is preferentially absorbed in the layer above 250 mb, in contrast to the weak response from global-columnar radiative loading by increases in CO2 or Stot. The hypersensitive response of the climate system to solar UV forcing is caused by strongly coupled feedback involving vertical static stability, tropical thick cirrus ice clouds and stratospheric ozone. This mechanism offers a plausible explanation of the apparent hypersensitivity of climate to solar forcing, as suggested by analyses of recent climatic records. The model hypersensitivity strongly depends on climate parameters, especially cloud radiative properties, but is effective for arguably realistic values of these parameters. The proposed solar forcing mechanism should be further confirmed using other models (e.g., general circulation models) that may better capture radiative and dynamical couplings of the troposphere and stratosphere.Key words: Meteorology and atmospheric dynamics (climatology · general or miscellaneous) · Solar physics · astrophysics · and astronomy (ultraviolet emissions)


2011 ◽  
Vol 11 (3) ◽  
pp. 9057-9081
Author(s):  
T. Kurtén ◽  
L. Zhou ◽  
R. Makkonen ◽  
J. Merikanto ◽  
P. Räisänen ◽  
...  

Abstract. The release of vast quantities of methane into the atmosphere as a result of clathrate destabilization is a potential mechanism for rapid amplification of global warming. Previous studies have calculated the enhanced warming based mainly on the radiative effect of the methane itself, with smaller contributions from the associated carbon dioxide or ozone increases. Here, we study the effect of strongly elevated methane (CH4) levels on oxidant and aerosol particle concentrations using a combination of chemistry-transport and general circulation models. A 10-fold increase in methane concentrations is predicted to significantly decrease hydroxyl radical (OH) concentrations, while moderately increasing ozone (O3). These changes lead to a 70% increase in the atmospheric lifetime of methane, and an 18% decrease in global mean cloud droplet number concentrations (CDNC). The CDNC change causes a radiative forcing that is comparable in magnitude to the longwave radiative forcing ("enhanced greenhouse effect") of the added methane. Together, the indirect CH4-O3 and CH4-OH-aerosol forcings could more than double the warming effect of large methane increases. Our findings may help explain the anomalously large temperature changes associated with historic methane releases.


2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.


2007 ◽  
Vol 20 (11) ◽  
pp. 2602-2622 ◽  
Author(s):  
Ping Zhu ◽  
James J. Hack ◽  
Jeffrey T. Kiehl

Abstract In this study, it is shown that the NCAR and GFDL GCMs exhibit a marked difference in climate sensitivity of clouds and radiative fluxes in response to doubled CO2 and ±2-K SST perturbations. The GFDL model predicted a substantial decrease in cloud amount and an increase in cloud condensate in the warmer climate, but produced a much weaker change in net cloud radiative forcing (CRF) than the NCAR model. Using a multiple linear regression (MLR) method, the full-sky radiative flux change at the top of the atmosphere was successfully decomposed into individual components associated with the clear sky and different types of clouds. The authors specifically examined the cloud feedbacks due to the cloud amount and cloud condensate changes involving low, mid-, and high clouds between 60°S and 60°N. It was found that the NCAR and GFDL models predicted the same sign of individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate for all three types of clouds (low, mid, and high) despite the different cloud and radiation schemes used in the models. However, since the individual longwave and shortwave feedbacks resulting from the change in cloud amount and cloud condensate generally have the opposite signs, the net cloud feedback is a subtle residual of all. Strong cancellations between individual cloud feedbacks may result in a weak net cloud feedback. This result is consistent with the findings of the previous studies, which used different approaches to diagnose cloud feedbacks. This study indicates that the proposed MLR approach provides an easy way to efficiently expose the similarity and discrepancy of individual cloud feedback processes between GCMs, which are hidden in the total cloud feedback measured by CRF. Most importantly, this method has the potential to be applied to satellite measurements. Thus, it may serve as a reliable and efficient method to investigate cloud feedback mechanisms on short-term scales by comparing simulations with available observations, which may provide a useful way to identify the cause for the wide spread of cloud feedbacks in GCMs.


2013 ◽  
Vol 13 (16) ◽  
pp. 8335-8364 ◽  
Author(s):  
X.-Z. Liang ◽  
F. Zhang

Abstract. A cloud–aerosol–radiation (CAR) ensemble modeling system has been developed to incorporate the largest choices of alternate parameterizations for cloud properties (cover, water, radius, optics, geometry), aerosol properties (type, profile, optics), radiation transfers (solar, infrared), and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world's leading general circulation models (GCMs). CAR provides a unique framework to determine (via intercomparison across all schemes), reduce (via optimized ensemble simulations), and attribute specific key factors for (via physical process sensitivity analyses) the model discrepancies and uncertainties in representing greenhouse gas, aerosol, and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud–aerosol–radiation interactions. For demonstration purposes, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol, and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.


2018 ◽  
Vol 75 (7) ◽  
pp. 2217-2233 ◽  
Author(s):  
Guanglin Tang ◽  
Ping Yang ◽  
George W. Kattawar ◽  
Xianglei Huang ◽  
Eli J. Mlawer ◽  
...  

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).


2020 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Toshihiko Takemura

Abstract. Complex aerosol–cloud–precipitation interactions lead to large differences in estimates of aerosol impacts on climate among general circulation models (GCMs) and satellite retrievals. Typically, precipitating hydrometeors are treated diagnostically in most GCMs, and their radiative effects are ignored. Here, we quantify how the treatment of precipitation influences the simulated effective radiative forcing due to aerosol–cloud interactions (ERFaci) using a state-of-the-art GCM with a two-moment prognostic precipitation scheme that incorporates the radiative effect of precipitating particles, and investigate how microphysical process representations are related to macroscopic climate effects. Prognostic precipitation substantially weakens the magnitude of ERFaci (by approximately 75 %) compared with the traditional diagnostic scheme, and this is the result of the increased longwave (warming) and weakened shortwave (cooling) components of ERFaci. The former is attributed to additional adjustment processes induced by falling snow, and the latter stems largely from riming of snow by collection of cloud droplets. The significant reduction in ERFaci does not occur without prognostic snow, which contributes mainly by buffering the cloud response to aerosol perturbations through depleting cloud water via collection. Prognostic precipitation also alters the regional pattern of ERFaci, particularly over northern mid-latitudes where snow is abundant. The treatment of precipitation is thus a highly influential controlling factor of ERFaci, contributing more than other uncertain tunable processes related to aerosol–cloud–precipitation interactions. This change in ERFaci caused by the treatment of precipitation is large enough to explain the existing difference in ERFaci between GCMs and observations.


2012 ◽  
Vol 25 (17) ◽  
pp. 6036-6056 ◽  
Author(s):  
Minghong Zhang ◽  
Shuanglin Li ◽  
Jian Lu ◽  
Renguang Wu

Abstract This study examines the skills in simulating interannual variability of northwestern Pacific (NWP) summer climate in 12 atmospheric general circulation models (AGCMs) attending the Atmospheric Model Intercomparison Project phase 2 (AMIP II). The models show a wide range of skills, among those version 1 of the Hadley Centre Global Atmosphere Model (HadGAM1) showed the highest fidelity and thus may be a better choice for studying East Asian–NWP summer climate. To understand the possible causes for the difference among the models, five models {HadGAM1; ECHAM5; the Geophysical Fluid Dynamics Laboratory Atmosphere Model, version 2.1 (AM2.1); Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]; and the fourth-generation National Center for Atmospheric Research Community Atmosphere Model (CAM3)} that have various skill levels, ranging from the highest to the moderate to the minor, were selected for analyses. The simulated teleconnection of NWP summer climate with sea surface temperatures (SSTs) in the tropical Indian and Pacific Oceans was first compared. HadGAM1 reproduces suppressed (intensified) rainfall during El Niño (La Niña) events and captures well the remote connection with the tropical Indian Ocean, while the other models either underestimate [ECHAM5, AM2.1, MIROC3.2(hires)] or fail to reproduce (CAM3) these teleconnections. The Walker cell and diabatic heating were further compared to shed light on the underlying physical mechanisms for the difference. Consistent with the best performance in simulating interannual rainfall, HadGAM1 exhibits the highest-level skill in capturing the observed climatology of the Walker cell and diabatic heating. These results highlight the key roles of the model’s background climatology in the Walker cell and diabatic heating, thus providing important clues to improving the model’s ability.


2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo

Abstract A recent model intercomparison, the Global Land–Atmosphere Coupling Experiment (GLACE), showed that there is a wide range of land–atmosphere coupling strengths, or the degree that soil moisture affects the generation of precipitation, amongst current atmospheric general circulation models (AGCMs). Coupling strength in the Hadley Centre atmosphere model (HadAM3) is among the weakest of all AGCMs considered in GLACE. Reasons for the weak HadAM3 coupling strength are sought here. In particular, the impact of pervasive saturated soil conditions and low soil moisture variability on coupling strength is assessed. It is found that when the soil model is modified to reduce the occurrence of soil moisture saturation and to encourage soil moisture variability, the soil moisture–precipitation feedback remains weak, even though the relationship between soil moisture and evaporation is strengthened. Composites of the diurnal cycle, constructed relative to soil moisture, indicate that the model can simulate key differences in boundary layer development over wet versus dry soils. In particular, the influence of wet or dry soil on the diurnal cycles of Bowen ratio, boundary layer height, and total heat flux are largely consistent with the observed influence of soil moisture on these properties. However, despite what appears to be successful simulation of these key aspects of the indirect soil moisture–precipitation feedback, the model does not capture observed differences for wet and dry soils in the daily accumulation of boundary layer moist static energy, a crucial feature of the feedback mechanism.


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