State dependence of CO2 forcing and its implications for climate sensitivity

When evaluating the effect of carbon dioxide (CO2) changes on Earth's climate, it is widely assumed that instantaneous radiative forcing from a doubling of a given CO2 concentration (IRF2×CO2) is constant and that variances in climate sensitivity arise from differences in radiative feedbacks or dependence of these feedbacks on the climatological base state. Here, we show that the IRF2×CO2 is not constant, but rather depends on the climatological base state, increasing by about 25% for every doubling of CO2, and has increased by about 10% since the preindustrial era primarily due to the cooling within the upper stratosphere, implying a proportionate increase in climate sensitivity. This base-state dependence also explains about half of the intermodel spread in IRF2×CO2, a problem that has persisted among climate models for nearly three decades.

Analysis of Correlation between Climate Change and Human Health Based on a Machine Learning Approach

Climate change increasingly affects every aspect of human life. Recent studies report a close correlation with human health and it is estimated that global death rates will increase by 73 per 100,000 by 2100 due to changes in temperature. In this context, the present work aims to study the correlation between climate change and human health, on a global scale, using artificial intelligence techniques. Starting from previous studies on a smaller scale, that represent climate change and which at the same time can be linked to human health, four factors were chosen. Four causes of mortality, strongly correlated with the environment and climatic variability, were subsequently selected. Various analyses were carried out, using neural networks and machine learning to find a correlation between mortality due to certain diseases and the leading causes of climate change. Our findings suggest that anthropogenic climate change is strongly correlated with human health; some diseases are mainly related to risk factors while others require a more significant number of variables to derive a correlation. In addition, a forecast of victims related to climate change was formulated. The predicted scenario confirms that a prevalently increasing trend in climate change factors corresponds to an increase in victims.

An Assessment of Earth's Climate Sensitivity Using Multiple Lines of Evidence

We assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of atmospheric CO2, characterized by an effective sensitivity S. This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density function (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6-3.9 K for our Baseline calculation and remains within 2.3-4.5 K under the robustness tests; corresponding 5-95% ranges are 2.3-4.7 K, bounded by 2.0-5.7 K (although such high-confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S, in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

Updated Global Warming Potentials and Radiative Efficiencies of Halocarbons and Other Weak Atmospheric Absorbers

Human activity has led to increased atmospheric concentrations of many gases, including halocarbons, and may lead to emissions of many more gases. Many of these gases are, on a per molecule basis, powerful greenhouse gases, although at present-day concentrations their climate effect is in the so-called weak limit (i.e., their effect scales linearly with concentration). We published a comprehensive review of the radiative efficiencies (RE) and global warming potentials (GWP) for around 200 such compounds in 2013 (Hodnebrog et al., 2013, https://doi.org/10.1002/rog.20013). Here we present updated RE and GWP values for compounds where experimental infrared absorption spectra are available. Updated numbers are based on a revised "Pinnock curve", which gives RE as a function of wave number, and now also accounts for stratospheric temperature adjustment (Shine & Myhre, 2020, https://doi.org/10.1029/2019MS001951). Further updates include the implementation of around 500 absorption spectra additional to those in the 2013 review and new atmospheric lifetimes from the literature (mainly from WMO (2019)). In total, values for 60 of the compounds previously assessed are based on additional absorption spectra, and 42 compounds have REs which differ by >10% from our previous assessment. New RE calculations are presented for more than 400 compounds in addition to the previously assessed compounds, and GWP calculations are presented for a total of around 250 compounds. Present-day radiative forcing due to halocarbons and other weak absorbers is 0.38 [0.33-0.43] W m-2, compared to 0.36 [0.32-0.40] W m-2 in IPCC AR5 (Myhre et al., 2013, https://doi.org/10.1017/CBO9781107415324.018), which is about 18% of the current CO2 forcing.

The global energy balance as represented in CMIP6 climate models

A plausible simulation of the global energy balance is a first-order requirement for a credible climate model. Here I investigate the representation of the global energy balance in 40 state-of-the-art global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). In the CMIP6 multi-model mean, the magnitudes of the energy balance components are often in better agreement with recent reference estimates compared to earlier model generations on a global mean basis. However, the inter-model spread in the representation of many of the components remains substantial, often on the order of 10-20 Wm^-2 globally, except for aspects of the shortwave clear-sky budgets, which are now more consistently simulated by the CMIP6 models. The substantial inter-model spread in the simulated global mean latent heat fluxes in the CMIP6 models, exceeding 20% (18 Wm^-2), further implies also large discrepancies in their representation of the global water balance. From a historic perspective of model development over the past decades, the largest adjustments in the magnitudes of the simulated present-day global mean energy balance components occurred in the shortwave atmospheric clear-sky absorption and the surface downward longwave radiation. Both components were gradually adjusted upwards over several model generations, on the order of 10 Wm^-2, to reach 73 and 344 Wm^-2, respectively in the CMIP6 multi-model means. Thereby, CMIP6 has become the first model generation that largely remediates long-standing model deficiencies related to an overestimation in surface downward shortwave and compensational underestimation in downward longwave radiation in its multi-model mean.

Cloud scattering impact on thermal radiative transfer and global longwave radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800-1250 cm^-1). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300-600 cm^-1) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ~3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important. The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%-4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m², and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m² and 1.8 W/m², respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6W/m², -1.1 W/m², and -2.5 W/m², respectively. The global scattering impact of 2.7 W/m² on the OLR is small when compared to the typical global OLR value of 240W/m², but it is significant when compared to cloud LW radiative forcing (30W/m²) and net cloud forcing (-14W/m²). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO₂.

Quantum Mechanical Modeling of the Vibrational Spectra of Minerals with a Focus on Clays

We present an overview of how to use quantum mechanical calculations to predict vibrational frequencies of molecules and materials such as clays and silicates. Other methods of estimating vibrational frequencies are mentioned, such as classical molecular dynamics simulations; references are given for additional information on these approaches. Herein, we discuss basic vibrational theory, calculating Raman and infrared intensities, steps for creating realistic models, and applications to spectroscopy, thermodynamics, and isotopic fractionation. There are a wide variety of programs and methods that can be employed to model vibrational spectra, but this work focuses on hybrid density functional theory (DFT) approaches. Many of the principles are the same when used in other programs and DFT methods, so a novice can benefit from simple examples that illustrate key points to consider when modeling vibrational spectra. Other methods and programs are listed to give the beginner a starting point for exploring and choosing which approach will be best for a given problem. The modeler should also be aware of the numerous analytical methods available for obtaining information on vibrations of atoms in molecules and materials. In addition to traditional infrared and Raman spectroscopy, sum-frequency generation (SFG) and inelastic neutron scattering (INS) are also excellent techniques for obtaining vibrational frequency information in certain circumstances.

Understanding Rapid Adjustments to Diverse Forcing Agents

Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.

Large regional shortwave forcing by anthropogenic methane informed by Jovian observations

Recently, it was recognized that widely used calculations of methane radiative forcing systematically underestimated its global value by 15% by omitting its shortwave effects. We show that shortwave forcing by methane can be accurately calculated despite considerable uncertainty and large gaps in its shortwave spectroscopy. We demonstrate that the forcing is insensitive, even when confronted with much more complete methane absorption spectra extending to violet light wavelengths derived from observations of methane-rich Jovian planets. We undertake the first spatially resolved global calculations of this forcing and find that it is dependent on bright surface features and clouds. Localized annual mean forcing from preindustrial to present-day methane increases approaches +0.25 W/m², 10 times the global annualized shortwave forcing and 43% of the total direct CH₄ forcing. Shortwave forcing by anthropogenic methane is sufficiently large and accurate to warrant its inclusion in historical analyses, projections, and mitigation strategies for climate change.

The cloud-free global energy balance and inferred cloud radiative effects: an assessment based on direct observations and climate models

In recent studies we quantified the global mean Earth energy balance based on direct observations from surface and space. Here we infer complementary reference estimates for its components specifically under cloud-free conditions. While the clear-sky fluxes at the top of atmosphere (TOA) are accurately known from satellite measurements, the corresponding fluxes at the Earth's surface are not equally well established, as they cannot be directly measured from space. This is also evident in 38 global climate models from CMIP5, which are shown to greatly vary in their clear-sky surface radiation budgets. To better constrain the latter, we established new clear-sky reference climatologies of surface downward shortwave and longwave radiative fluxes from worldwide distributed Baseline Surface Radiation Network sites. 33 out of the 38 CMIP5 models overestimate the clear-sky downward shortwave reference climatologies, whereas both substantial overestimations and underestimations are found in the longwave counterparts in some of the models. From the bias structure of the CMIP5 models we infer best estimates for the global mean surface downward clear-sky shortwave and longwave radiation, at 247 and 314 Wm^-2, respectively. With a global mean surface albedo of 13.5% and net shortwave clear-sky flux of 287 Wm^-2 at the TOA this results in a global mean clear-sky surface and atmospheric shortwave absorption of 214 and 73 Wm^-2, respectively. From the newly-established diagrams of the global energy balance under clear-sky and all-sky conditions, we quantify the cloud radiative effects not only at the TOA, but also within the atmosphere and at the surface.

The ethnobotanical domain of the Swat Valley, Pakistan

BACKGROUND

This study contributes to the current ethnomedicinal knowledge of the Swat Valley, Pakistan. District Swat possesses remarkable biodiversity owing to its varied topographical and climatic conditions, prompting a distinct human-plant association. Our hypothesis is that the presence of such a great biodiversity has shaped into a formal ethnobotanical culture in the area transmitted through generations. We suspect that the versatility of some plant species has greater influence on the culture. Therefore, the prime objective of the study is to understand this unique human-plant relationship in the valley and to create scientific roots for the selection and practice of herbs in the ethnobotanical domain of the district.

METHODS

Primary data were collected using questionnaires and face-to-face interviews with the locals. The data collected were used for calculating some important indices, i.e. relative frequency of citation (RFC), participant agreement ratio (PAR), frequency of citation (FC), Smith's Salience Index (SI), Relative Importance Index (RII), Cultural Value Index (CVI) and a newly proposed, Ali's Conservation Priority Index (CPI). Index scores were used as key identifier of the ethnobotanically important plants of the area.

RESULTS

Residents of the Swat Valley have listed plant uses in 15 use categories. Around 9% of the respondents have a common consensus on the selection and use of plants for the treatment of evil eye with similar results for body cuts (8.2%) followed by psychological/neural ailments (8.0%). Respondents agree that Berberis lyceum Royle. dominates in all five indices. Skimmia laureola Franch. also constitutes one of the central plants of the ethnobotanical domain, ranking second in the SI, fifth in the RII, seventh in CVI, and third in the Cultural Importance Index. It holds the thirty-fifth position in the CPI. Over 80% of the population treat different diseases with herbal remedies. In the common ethnobotanical domain of the area, plants like Mentha longifolia L., Berberis lyceum, and Skimmia laureola are very important and have high salience and importance values, thus suggesting these plants are versatile for their uses in the study area.

CONCLUSION

In conclusion, only some plant species are prioritised for their use in the ethnobotanical domain of the community. Medicinal and aromatic plant (MAP) usage is widespread in the Swat Valley. The ethnobotanical knowledge could be used as a tool to understand the adaptability of a specific taxon in the area and the possible conservation risk to their existence.

Response to Comment on "Long-term climate forcing by atmospheric oxygen concentrations"

Goldblatt argues that a decrease in pressure broadening of absorption lines in an atmosphere with low oxygen leads to an increase in outgoing longwave radiation and atmospheric cooling. We demonstrate that cloud and water vapor feedbacks in a global climate model compensate for these decreases and lead to atmospheric warming.

Comment on "Long-term climate forcing by atmospheric oxygen concentrations"

Poulsen et al (Reports, 12 June 2015, p. 1238) argued that lower atmospheric oxygen levels during the Phanerozoic would have given a warmer climate. However, radiative and atmospheric structure changes under lower pressure both cause cooling, making their result unusual in that a hierarchy of models gives opposing results. Scrutiny of how radiative and cloud processes were represented, and a mechanistic explanation of the results, are required.

An observational radiative constraint on hydrologic cycle intensification

Intensification of the hydrologic cycle is a key dimension of climate change, with substantial impacts on human and natural systems. A basic measure of hydrologic cycle intensification is the increase in global-mean precipitation per unit surface warming, which varies by a factor of three in current-generation climate models (about 1-3 per cent per kelvin). Part of the uncertainty may originate from atmosphere-radiation interactions. As the climate warms, increases in shortwave absorption from atmospheric moistening will suppress the precipitation increase. This occurs through a reduction of the latent heating increase required to maintain a balanced atmospheric energy budget. Using an ensemble of climate models, here we show that such models tend to underestimate the sensitivity of solar absorption to variations in atmospheric water vapour, leading to an underestimation in the shortwave absorption increase and an overestimation in the precipitation increase. This sensitivity also varies considerably among models due to differences in radiative transfer parameterizations, explaining a substantial portion of model spread in the precipitation response. Consequently, attaining accurate shortwave absorption responses through improvements to the radiative transfer schemes could reduce the spread in the predicted global precipitation increase per degree warming for the end of the twenty-first century by about 35 per cent, and reduce the estimated ensemble-mean increase in this quantity by almost 40 per cent.

Radiative flux and forcing parameterization error in aerosol-free clear skies

Radiation parameterizations in GCMs are more accurate than their predecessorsErrors in estimates of 4 ×CO₂ forcing are large, especially for solar radiationErrors depend on atmospheric state, so global mean error is unknown.

Observational determination of surface radiative forcing by CO2 from 2000 to 2010

The climatic impact of CO2 and other greenhouse gases is usually quantified in terms of radiative forcing, calculated as the difference between estimates of the Earth's radiation field from pre-industrial and present-day concentrations of these gases. Radiative transfer models calculate that the increase in CO2 since 1750 corresponds to a global annual-mean radiative forcing at the tropopause of 1.82 ± 0.19 W m(-2) (ref. 2). However, despite widespread scientific discussion and modelling of the climate impacts of well-mixed greenhouse gases, there is little direct observational evidence of the radiative impact of increasing atmospheric CO2. Here we present observationally based evidence of clear-sky CO2 surface radiative forcing that is directly attributable to the increase, between 2000 and 2010, of 22 parts per million atmospheric CO2. The time series of this forcing at the two locations-the Southern Great Plains and the North Slope of Alaska-are derived from Atmospheric Emitted Radiance Interferometer spectra together with ancillary measurements and thoroughly corroborated radiative transfer calculations. The time series both show statistically significant trends of 0.2 W m(-2) per decade (with respective uncertainties of ±0.06 W m(-2) per decade and ±0.07 W m(-2) per decade) and have seasonal ranges of 0.1-0.2 W m(-2). This is approximately ten per cent of the trend in downwelling longwave radiation. These results confirm theoretical predictions of the atmospheric greenhouse effect due to anthropogenic emissions, and provide empirical evidence of how rising CO2 levels, mediated by temporal variations due to photosynthesis and respiration, are affecting the surface energy balance.

Shortwave and longwave radiative contributions to global warming under increasing CO2

In response to increasing concentrations of atmospheric CO2, high-end general circulation models (GCMs) simulate an accumulation of energy at the top of the atmosphere not through a reduction in outgoing longwave radiation (OLR)—as one might expect from greenhouse gas forcing—but through an enhancement of net absorbed solar radiation (ASR). A simple linear radiative feedback framework is used to explain this counterintuitive behavior. It is found that the timescale over which OLR returns to its initial value after a CO2 perturbation depends sensitively on the magnitude of shortwave (SW) feedbacks. If SW feedbacks are sufficiently positive, OLR recovers within merely several decades, and any subsequent global energy accumulation is because of enhanced ASR only. In the GCM mean, this OLR recovery timescale is only 20 y because of robust SW water vapor and surface albedo feedbacks. However, a large spread in the net SW feedback across models (because of clouds) produces a range of OLR responses; in those few models with a weak SW feedback, OLR takes centuries to recover, and energy accumulation is dominated by reduced OLR. Observational constraints of radiative feedbacks—from satellite radiation and surface temperature data—suggest an OLR recovery timescale of decades or less, consistent with the majority of GCMs. Altogether, these results suggest that, although greenhouse gas forcing predominantly acts to reduce OLR, the resulting global warming is likely caused by enhanced ASR.

The runaway greenhouse: implications for future climate change, geoengineering and planetary atmospheres

The ultimate climate emergency is a 'runaway greenhouse': a hot and water-vapour-rich atmosphere limits the emission of thermal radiation to space, causing runaway warming. Warming ceases only after the surface reaches approximately 1400 K and emits radiation in the near-infrared, where water is not a good greenhouse gas. This would evaporate the entire ocean and exterminate all planetary life. Venus experienced a runaway greenhouse in the past, and we expect that the Earth will in around 2 billion years as solar luminosity increases. But could we bring on such a catastrophe prematurely, by our current climate-altering activities? Here, we review what is known about the runaway greenhouse to answer this question, describing the various limits on outgoing radiation and how climate will evolve between these. The good news is that almost all lines of evidence lead us to believe that is unlikely to be possible, even in principle, to trigger full a runaway greenhouse by addition of non-condensible greenhouse gases such as carbon dioxide to the atmosphere. However, our understanding of the dynamics, thermodynamics, radiative transfer and cloud physics of hot and steamy atmospheres is weak. We cannot therefore completely rule out the possibility that human actions might cause a transition, if not to full runaway, then at least to a much warmer climate state than the present one. High climate sensitivity might provide a warning. If we, or more likely our remote descendants, are threatened with a runaway greenhouse, then geoengineering to reflect sunlight might be life's only hope. Injecting reflective aerosols into the stratosphere would be too short-lived, and even sunshades in space might require excessive maintenance. In the distant future, modifying Earth's orbit might provide a sustainable solution. The runaway greenhouse also remains relevant in planetary sciences and astrobiology: as extrasolar planets smaller and nearer to their stars are detected, some will be in a runaway greenhouse state.

Are there pre-Quaternary geological analogues for a future greenhouse warming?

Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race's current grand climate experiment. This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean-atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene-Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO(2) forcing--whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate--or the sensitivity of the climate system itself to CO(2) was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO(2)) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO(2) concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO(2) thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.