Nearly all energy used for human purposes is dissipated as heat within Earth's land–atmosphere system. Thermal energy released from non‐renewable sources is therefore a climate forcing term. Averaged ...globally, this forcing is only +0.028 W m−2, but over the continental United States and western Europe, it is +0.39 and +0.68 W m−2, respectively. Here, present and future global inventories of anthropogenic heat flux (AHF) are developed, and parameterizations derived for seasonal and diurnal flux cycles. Equilibrium climate experiments show statistically‐significant continental‐scale surface warming (0.4–0.9°C) produced by one 2100 AHF scenario, but not by current or 2040 estimates. However, significant increases in annual‐mean temperature and planetary boundary layer (PBL) height occur over gridcells where present‐day AHF exceeds 3.0 W m−2. PBL expansion leads to a slight, but significant increase in atmospheric residence time of aerosols emitted from large‐AHF regions. Hence, AHF may influence regional climate projections and contemporary chemistry‐climate studies.
Because all climate models exhibit biases, their use for assessing future climate change requires implicitly assuming or explicitly postulating that the biases are stationary or vary predictably. ...This hypothesis, however, has not been, and cannot be, tested directly. This work shows that under very large climate change the bias patterns of key climate variables exhibit a striking degree of stationarity. Using only correlation with a model’s preindustrial bias pattern, a model’s 4xCO₂ bias pattern is objectively and correctly identified among a large model ensemble in almost all cases. This outcome would be exceedingly improbable if bias patterns were independent of climate state. A similar result is also found for bias patterns in two historical periods. This provides compelling and heretofore missing justification for using such models to quantify climate perturbation patterns and for selecting well-performing models for regional downscaling. Furthermore, it opens the way to extending bias corrections to perturbed states, substantially broadening the range of justified applications of climate models.
Organic aerosols (OA) play an important role in climate change. However, very few calculations of global OA radiative forcing include secondary organic aerosol (SOA) or the light‐absorbing part of OA ...(brown carbon). Here we use a global model to assess the radiative forcing associated with the change in primary organic aerosol (POA) and SOA between present‐day and preindustrial conditions in both the atmosphere and the land snow/sea ice. Anthropogenic emissions are shown to substantially influence the SOA formation rate, causing it to increase by 29 Tg/yr (93%) since preindustrial times. We examine the effects of varying the refractive indices, size distributions for POA and SOA, and brown carbon fraction in SOA. The increase of SOA exerts a direct forcing ranging from −0.12 to −0.31 W m−2 and a first indirect forcing in warm‐phase clouds ranging from −0.22 to −0.29 W m−2, with the range due to different assumed SOA size distributions and refractive indices. The increase of POA since preindustrial times causes a direct forcing varying from −0.06 to −0.11 W m−2, when strongly and weakly absorbing refractive indices for brown carbon are used. The change in the total OA exerts a direct forcing ranging from −0.14 to −0.40 W m−2. The atmospheric absorption from brown carbon ranges from +0.22 to +0.57 W m−2, which corresponds to 27%~70% of the black carbon (BC) absorption predicted in the model. The radiative forcing of OA deposited in land snow and sea ice ranges from +0.0011 to +0.0031 W m−2 or as large as 24% of the forcing caused by BC in snow and ice simulated by the model.
Key Points
A fully explicit SOA formation model is used to determine SOA radiative forcing
The direct radiative forcing by brown carbon in SOA is estimated
The radiative forcing of OA in snow/ice is estimated for the first time
The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM ...development community to create CLM4. The model is extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating – as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ~50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, atmospheric forcing height, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated.Taken together, these augmentations to CLM result in improved soil moisture dynamics, drier soils, and stronger soil moisture variability. The new model also exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is slightly degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.
Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated ...with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.
Recent attention has focused on the impact of black carbon (BC) on Arctic climate. Here, idealized equilibrium climate experiments are conducted to explore the dependence of Arctic temperature change ...on the altitude and season of local BC forcing. BC residing in the lowest atmospheric layer produces very strong Arctic warming per unit mass and forcing 2.8 ± 0.5 K (Wm − 2) − 1 because of low cloud and sea‐ice feedbacks that amplify both summer and winter warming. BC operating only within Arctic snow and sea‐ice also effectively warms the surface, but forcings at 400–750mbar and 210–250mbar cause weak surface warming and cooling, respectively, despite increasing atmospheric moist static energy. This is a consequence of stable atmospheric conditions in the Arctic limiting vertical mixing, and of higher‐altitude BC reducing surface insolation, increasing stability and summer low‐cloud cover, and decreasing poleward energy transport. The current simulated distribution of Arctic atmospheric BC slightly cools the surface, supporting an earlier study, while local atmospheric and cryosphere‐deposited BC warms the Arctic with a sensitivity of + 0.5 ± 0.4 K (Wm − 2) − 1. By season, April–May tropospheric BC induces the greatest mass‐normalized Arctic warming 0.18 K (Gg yr) − 1 because high insolation and surface albedo facilitate large specific forcing during this season. Forcing efficacy, however, increases with summer progression because of decreasing atmospheric stability, leading to a narrow range of mass‐normalized response with season. Although limited by exclusion of aerosol indirect effects, changes in ocean heat transport and forcing by co‐emitted species, these experiments show that Arctic climate response is sensitive to the vertical distribution and deposition efficiency of BC reaching the Arctic.
Key PointsSurface climate change from Arctic black carbon depends strongly on its altitudeNear‐surface BC causes strong warming because of cloud and sea‐ice feedbacksCurrent Arctic atmosphere + snow BC warms the surface while atmospheric BC may not
We apply our Snow, Ice, and Aerosol Radiative (SNICAR) model, coupled to a general circulation model with prognostic carbon aerosol transport, to improve understanding of climate forcing and response ...from black carbon (BC) in snow. Building on two previous studies, we account for interannually varying biomass burning BC emissions, snow aging, and aerosol scavenging by snow meltwater. We assess uncertainty in forcing estimates from these factors, as well as BC optical properties and snow cover fraction. BC emissions are the largest source of uncertainty, followed by snow aging. The rate of snow aging determines snowpack effective radius (re), which directly controls snow reflectance and the magnitude of albedo change caused by BC. For a reasonable re range, reflectance reduction from BC varies threefold. Inefficient meltwater scavenging keeps hydrophobic impurities near the surface during melt and enhances forcing. Applying biomass burning BC emission inventories for a strong (1998) and weak (2001) boreal fire year, we estimate global annual mean BC/snow surface radiative forcing from all sources (fossil fuel, biofuel, and biomass burning) of +0.054 (0.007–0.13) and +0.049 (0.007–0.12) W m−2, respectively. Snow forcing from only fossil fuel + biofuel sources is +0.043 W m−2 (forcing from only fossil fuels is +0.033 W m−2), suggesting that the anthropogenic contribution to total forcing is at least 80%. The 1998 global land and sea‐ice snowpack absorbed 0.60 and 0.23 W m−2, respectively, because of direct BC/snow forcing. The forcing is maximum coincidentally with snowmelt onset, triggering strong snow‐albedo feedback in local springtime. Consequently, the “efficacy” of BC/snow forcing is more than three times greater than forcing by CO2. The 1998 and 2001 land snowmelt rates north of 50°N are 28% and 19% greater in the month preceding maximum melt of control simulations without BC in snow. With climate feedbacks, global annual mean 2‐meter air temperature warms 0.15 and 0.10°C, when BC is included in snow, whereas annual arctic warming is 1.61 and 0.50°C. Stronger high‐latitude climate response in 1998 than 2001 is at least partially caused by boreal fires, which account for nearly all of the 35% biomass burning contribution to 1998 arctic forcing. Efficacy was anomalously large in this experiment, however, and more research is required to elucidate the role of boreal fires, which we suggest have maximum arctic BC/snow forcing potential during April–June. Model BC concentrations in snow agree reasonably well (r = 0.78) with a set of 23 observations from various locations, spanning nearly 4 orders of magnitude. We predict concentrations in excess of 1000 ng g−1 for snow in northeast China, enough to lower snow albedo by more than 0.13. The greatest instantaneous forcing is over the Tibetan Plateau, exceeding 20 W m−2 in some places during spring. These results indicate that snow darkening is an important component of carbon aerosol climate forcing.
The CCSM4 Land Simulation, 1850–2005 Lawrence, David M.; Oleson, Keith W.; Flanner, Mark G. ...
Journal of climate,
04/2012, Letnik:
25, Številka:
7
Journal Article
Recenzirano
Odprti dostop
This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to ...CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels.
Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia.
New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m−2for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.
Atmospheric iron affects the global carbon cycle by modulating ocean biogeochemistry through the deposition of soluble iron to the ocean. Iron emitted by anthropogenic (fossil fuel) combustion is a ...source of soluble iron that is currently considered less important than other soluble iron sources, such as mineral dust and biomass burning. Here we show that the atmospheric burden of anthropogenic combustion iron is 8 times greater than previous estimates by incorporating recent measurements of anthropogenic magnetite into a global aerosol model. This new estimation increases the total deposition flux of soluble iron to southern oceans (30-90 °S) by 52%, with a larger contribution of anthropogenic combustion iron than dust and biomass burning sources. The direct radiative forcing of anthropogenic magnetite is estimated to be 0.021 W m
globally and 0.22 W m
over East Asia. Our results demonstrate that anthropogenic combustion iron is a larger and more complex climate forcer than previously thought, and therefore plays a key role in the Earth system.
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