Uncertainty In Climate Forcing Research Articles

The decomposition of cloud–aerosol forcing in the UK Earth System Model (UKESM1)

Abstract. Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol–cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major cause of uncertainty in climate forcing; therefore, caution is needed in interpreting the results from coarse-resolution, highly parameterized global models. Here, we separate and quantify the components of the surface shortwave effective radiative forcing (ERF) due to aerosol in the atmosphere-only version of the UK Earth System Model (UKESM1) and evaluate the cloud properties and their radiative effects against observations. We focus on a northern region of the North Atlantic (NA) where stratocumulus clouds dominate (denoted the northern NA region) and a southern region where trade cumulus and broken stratocumulus dominate (southern NA region). Aerosol forcing was diagnosed using a pair of simulations in which the meteorology is approximately fixed via nudging to analysis; one simulation has pre-industrial (PI) and one has present-day (PD) aerosol emissions. This model does not include aerosol effects within the convective parameterization (but aerosol does affect the clouds associated with detrainment) and so it should be noted that the representation of aerosol forcing for convection is incomplete. Contributions to the surface ERF from changes in cloud fraction (fc), in-cloud liquid water path (LWPic) and droplet number concentration (Nd) were quantified. Over the northern NA region, increases in Nd and LWPic dominate the forcing. This is likely because the already-high fc there reduces the chances of further large increases in fc and allows cloud brightening to act over a larger region. Over the southern NA region, increases in fc dominate due to the suppression of rain by the additional aerosols. Aerosol-driven increases in macrophysical cloud properties (LWPic and fc) will rely on the response of the boundary layer parameterization, along with input from the cloud microphysics scheme, which are highly uncertain processes. Model grid boxes with low-altitude clouds present in both the PI and PD dominate the forcing in both regions. In the northern NA, the brightening of completely overcast low cloud scenes (100 % cloud cover, likely stratocumulus) contributes the most, whereas in the southern NA the creation of clouds with fc of around 20 % from clear skies in the PI was the largest single contributor, suggesting that trade cumulus clouds are created in response to increases in aerosol. The creation of near-overcast clouds was also important there. The correct spatial pattern, coverage and properties of clouds are important for determining the magnitude of aerosol forcing, so we also assess the realism of the modelled PD clouds against satellite observations. We find that the model reproduces the spatial pattern of all the observed cloud variables well but that there are biases. The shortwave top-of-the-atmosphere (SWTOA) flux is overestimated by 5.8 % in the northern NA region and 1.7 % in the southern NA, which we attribute mainly to positive biases in low-altitude fc. Nd is too low by −20.6 % in the northern NA and too high by 21.5 % in the southern NA but does not contribute greatly to the main SWTOA biases. Cloudy-sky liquid water path mainly shows biases north of Scandinavia that reach between 50 % and 100 % and dominate the SWTOA bias in that region. The large contribution to aerosol forcing in the UKESM1 model from highly uncertain macrophysical adjustments suggests that further targeted observations are needed to assess rain formation processes, how they depend on aerosols and the model response to precipitation in order to reduce uncertainty in climate projections.

Global peatland area and carbon dynamics from the Last Glacial Maximum to the present – a process-based model investigation

Abstract. Peatlands are an essential part of the terrestrial carbon cycle and the climate system. Understanding their history is key to understanding future and past land–atmosphere carbon fluxes. We performed transient simulations over the last 22 000 years with a dynamic global peat and vegetation model forced by Earth system model climate output, thereby complementing data-based reconstructions for peatlands. Our novel results demonstrate a highly dynamic evolution with concomitant gains and losses of active peatland areas. Modeled gross area changes exceed net changes several fold, while net peat area increases by 60 % over the deglaciation. Peatlands expand to higher northern latitudes in response to warmer and wetter conditions and retreating ice sheets, and they are partly lost in midlatitude regions. In the tropics, peatlands are partly lost due to the flooding of continental shelves and are regained through nonlinear responses to the combined changes in temperature, precipitation, and CO2. Large north–south shifts of tropical peatlands are driven by shifts in the position of the intertropical convergence zone associated with the abrupt climate events of the glacial termination. Time slice simulations for the Last Glacial Maximum (LGM) demonstrate large uncertainties in modeled peatland extent (global range from 1.5 to 3.4 Mkm2, million square kilometers) stemming from uncertainties in climate forcing. The net uptake of atmospheric CO2 by peatlands, modeled at 351 GtC since the LGM, considers decay from former peatlands. Carbon uptake would be misestimated, in particular during periods of rapid climate change and subsequent shifts in peatland distribution, when considering only changes in the area of currently active peatlands. Our study highlights the dynamic nature of peatland distribution and calls for an improved understanding of former peatlands to better constrain peat carbon sources and sinks.

Study of aerosol optical properties in the Middle East during 2013.

Aerosols affect the earth's atmospheric radiative fluxes via direct, semi-direct, and indirect mechanisms. Aerosols also are one of the main sources of uncertainty in climate models. In the Middle East, in addition to climate effects, various problems such as reduced visibility, human health hazards, and air pollution are caused by aerosols. Studying the optical and physical properties of aerosols on local and global scales helps reduce the uncertainties in climate forcing. In this study, aerosol optical properties, including Aerosol Optical Depth (AOD), Angstrom Exponent (AE), ASYmmetry parameter (ASY), Single Scattering Albedo (SSA), and phase function were analyzed. These properties were investigated over five sites in the Middle East during 2013 using the Aerosol Robotic NETwork (AERONET) data. The results revealed an inverse relationship between AOD and AE in all sites. A high AOD value and a low AE value were detected in spring and summer in all studied sites, suggestive of coarse mode dust particles. ASY initially decreased due to the dominance of absorbing type aerosols in the visible spectrum with the increase in wavelength. Afterwards, ASY increased with the increase in wavelength in the infrared region due to the dominance of the coarse mode particles. In most sites, SSA increased, particularly in spring and summer, with the increase in the wavelength because of the dominance of desert dust. In spring and summer, the phase function was high over all sites. High phase functions associated with small scattering angles were caused by the coarse mode particles.

A real-time Global Warming Index

We propose a simple real-time index of global human-induced warming and assess its robustness to uncertainties in climate forcing and short-term climate fluctuations. This index provides improved scientific context for temperature stabilisation targets and has the potential to decrease the volatility of climate policy. We quantify uncertainties arising from temperature observations, climate radiative forcings, internal variability and the model response. Our index and the associated rate of human-induced warming is compatible with a range of other more sophisticated methods to estimate the human contribution to observed global temperature change.

Are atmospheric updrafts a key to unlocking climate forcing and sensitivity?

Abstract. Both climate forcing and climate sensitivity persist as stubborn uncertainties limiting the extent to which climate models can provide actionable scientific scenarios for climate change. A key, explicit control on cloud–aerosol interactions, the largest uncertainty in climate forcing, is the vertical velocity of cloud-scale updrafts. Model-based studies of climate sensitivity indicate that convective entrainment, which is closely related to updraft speeds, is an important control on climate sensitivity. Updraft vertical velocities also drive many physical processes essential to numerical weather prediction.Vertical velocities and their role in atmospheric physical processes have been given very limited attention in models for climate and numerical weather prediction. The relevant physical scales range down to tens of meters and are thus frequently sub-grid and require parameterization. Many state-of-science convection parameterizations provide mass fluxes without specifying vertical velocities, and parameterizations that do provide vertical velocities have been subject to limited evaluation against what have until recently been scant observations. Atmospheric observations imply that the distribution of vertical velocities depends on the areas over which the vertical velocities are averaged. Distributions of vertical velocities in climate models may capture this behavior, but it has not been accounted for when parameterizing cloud and precipitation processes in current models.New observations of convective vertical velocities offer a potentially promising path toward developing process-level cloud models and parameterizations for climate and numerical weather prediction. Taking account of the scale dependence of resolved vertical velocities offers a path to matching cloud-scale physical processes and their driving dynamics more realistically, with a prospect of reduced uncertainty in both climate forcing and sensitivity.

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

AbstractOver the past decade, the number of studies that investigate aerosol–cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of basic physical mechanisms of aerosol–cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud–aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol–cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap—for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed.

Cloud climatology over the oceanic regions adjacent to the Indian Subcontinent: inter-comparison between passive and active sensors

Understanding the cloud vertical structure and its variation in space and time is important to reduce the uncertainty in climate forcing. Here, we present the cloud climatology over the oceanic regions (Arabian Sea, Bay of Bengal, and South Indian Ocean) adjacent to the Indian subcontinent using data from the Multiangle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), GCM-Oriented CALIPSO Cloud Product (GOCCP), and International Satellite Cloud Climatology Project (ISCCP). Fractional cloud cover (fc) shows stronger seasonal variations over the Arabian Sea (mean annual fc lies in the range 0.5–0.61) and Bay of Bengal (mean annual fc lies in the range 0.69–0.75) relative to the South Indian Ocean (mean annual fc lies in the range 0.64–0.71). Inter-comparison of statistics from passive (MISR, MODIS and ISCCP) and active (GOCCP) sensors reveals the challenges in interpreting satellite data for climate implications. While MISR detects more low clouds because of its stereo technique, MODIS and ISCCP detect more high clouds because of their radiometric techniques. Therefore, a combination of these two techniques in passive sensors may lead to more realistic understanding of the cloud vertical structure. GOCCP (active sensor) can detect multilayer cloud, but accuracy reduces if the high clouds are optically thick. A dominance of low and high clouds throughout the year is observed in these regions, where cumulus and cirrus dominate among low and high clouds, respectively.

From BASE-ASIA toward 7-SEAS: A satellite-surface perspective of boreal spring biomass-burning aerosols and clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research &Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010–13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in-situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosol–cloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

Numerical Simulations of Asian Dust-Aerosols and Regional Impact on Weather and Climate- Part I: Control Case-PRCM Simulation without Dust-Aerosols

Aerosol particles affect atmospheric radiation and cloud microphysics, and are considered a major uncertainty in climate forcing. At the same time, accurate simulation and prediction of meteorological conditions are necessary to simulate the distribution and chemical reaction of the aerosols. Distribution of pollutions can also be used to validate meteorological models. This paper consists of two parts: Part I: Numerical simulation of weather and soil conditions from the Purdue Regional Climate Model (PRCM); and Part II: Numerical modeling of online interaction between dust and weather/climate. Both parts were integrated continuously from April 08 to 24, 1998 without nudging or restarting. The detailed treatment of soil and the planetary boundary layer (PBL), using the semi-conserved ice-potential temperature and total water substance as prognostic variables, a local reference to calculate the pressure gradient, and the accurate advection scheme, allowed the PRCM to well reproduce the movements of the fronts/cyclones, downslope wind, upper/mid-level-jet, vertical mixing, and the low-level convergence over a complex terrain. They are crucial to the lift, dispersion, and transport of dusts over the Gobi Desert, the Taklimakan Desert, and the downstream regions. The dust model in Part II calculated the production, mixing, transport/removal, and radiative property of the dusts using the meteorology generated by the PRCM. The radiative effects of the dusts calculated from the dust model were then fed back to the PRCM. Because no nudging or restarting was applied during 17 continuous days of integration, the conservation laws of momentum, energy, and mass (including dry air, water substances and dusts) are valid. Hence, the PRCM provides data that are consistent for studying the movement of aerosols and the interactions among the aerosols, weather, and soil.

Potential aerosol indirect effects on atmospheric circulation and radiative forcing through deep convection

Aerosol indirect effects, i.e., the interactions of aerosols with clouds by serving as cloud condensation nuclei or ice nuclei constitute the largest uncertainty in climate forcing and projection. Previous IPCC reported negative aerosol indirect forcing, which does not account for aerosol‐convective cloud interactions because the complex processes involved are poorly understood and represented in climate models. Here we elucidated how aerosols change convective intensity, diabatic heating, and regional circulation under different environmental conditions. We found that aerosol indirect effect on deep convective cloud systems could lead to enhanced regional convergence and a strong top‐of‐atmosphere warming. Aerosol invigoration effect occurs mainly in warmed‐based convection with weak shear. This could result in a strong radiative warming in the atmosphere (up to +5.6 W m−2), a lofted latent heating, and a reduced diurnal temperature difference, all of which could potentially impact regional circulation and modify weather systems. The positive aerosol radiative forcing on deep clouds could offset the negative aerosol radiative forcing on low clouds to an unknown extent.

Reply to “Comments on ‘Why Hasn't Earth Warmed as Much as Expected?’”

In response to our article, Why Hasnt Earth Warmed as Much as Expected? (2010), Knutti and Plattner (2012) wrote a rebuttal. The term climate sensitivity is usually defined as the change in global mean surface temperature that is produced by a specified change in forcing, such as a change in solar heating or greenhouse gas concentrations. We had argued in the 2010 paper that although climate models can reproduce the global mean surface temperature history over the past century, the uncertainties in these models, due primarily to the uncertainty in climate forcing by airborne particles, mean that the models lack the confidence to actually constrain the climate sensitivity within useful limits for climate prediction. Knutti and Plattner are climate modelers, and they argued essentially that because the models could reproduce the surface temperature history, the issue we raised was moot. Our response amounts to straightening out this confusion; for the models to be constraining, they must be able to reproduce the surface temperature history with sufficient confidence, not just to match the measurements, but to exclude alternative histories. As before, we concluded that if we can actually make the aerosol measurements using currently available, state-of-the-art techniques, we can determine the aerosol climate forcing to the degree required to constrain that aspect of model climate sensitivity. A technical issue relating to the timescale over which a change in CO2 emissions would be equilibrated in the environmental energy balance was also discussed, again, a matter of differences in terminology.

The Shape of Things to Come: Why Is Climate Change So Predictable?

Abstract The framework of feedback analysis is used to explore the controls on the shape of the probability distribution of global mean surface temperature response to climate forcing. It is shown that ocean heat uptake, which delays and damps the temperature rise, can be represented as a transient negative feedback. This transient negative feedback causes the transient climate change to have a narrower probability distribution than that of the equilibrium climate response (the climate sensitivity). In this sense, climate change is much more predictable than climate sensitivity. The width of the distribution grows gradually over time, a consequence of which is that the larger the climate change being contemplated, the greater the uncertainty is about when that change will be realized. Another consequence of this slow growth is that further efforts to constrain climate sensitivity will be of very limited value for climate projections on societally relevant time scales. Finally, it is demonstrated that the effect on climate predictability of reducing uncertainty in the atmospheric feedbacks is greater than the effect of reducing uncertainty in ocean feedbacks by the same proportion. However, at least at the global scale, the total impact of uncertainty in climate feedbacks is dwarfed by the impact of uncertainty in climate forcing, which in turn is contingent on choices made about future anthropogenic emissions.

Global statistical analysis of MISR aerosol data: a massive data product from NASA's Terra satellite

AbstractIn climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have been put in place to collect global data. However, missing and noisy observations impose considerable difficulties for scientists researching the global distribution of aerosols, aerosol transportation, and comparisons between satellite observations and global‐climate‐model outputs. In this paper, we fit a Spatial Mixed Effects (SME) statistical model to predict the missing values, denoise the observed values, and quantify the spatial‐prediction uncertainties. The computations associated with the SME model are linear scalable to the number of data points, which makes it feasible to process massive global satellite data. We apply the methodology, which is called Fixed Rank Kriging (FRK), to the level‐3 Aerosol Optical Depth (AOD) dataset collected by NASA's Multi‐angle Imaging SpectroRadiometer (MISR) instrument flying on the Terra satellite. Overall, our results were superior to those from non‐statistical methods and, importantly, FRK has an uncertainty measure associated with it that can be used for comparisons over different regions or at different time points. Copyright © 2007 John Wiley & Sons, Ltd.