Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

Sensitivity of North American grassland birds to weather and climate variability

Grassland birds in North America have declined sharply over the last 60 years, driven by the widespread loss and degradation of grassland habitats. Climate change is occurring more rapidly in grasslands relative to some other ecosystems, and exposure to extreme and novel climate conditions may affect grassland bird ecology and demographics. To determine the potential effects of weather and climate variability on grassland birds, we conducted a systematic review of relationships between temperature and precipitation and demographic responses in grassland bird species of North America. Based on 124 independent studies, we used a vote-counting approach to quantify the frequency and direction of significant effects of weather and climate variability on grassland birds. Grassland birds tended to experience positive and negative effects of higher temperatures and altered precipitation. Moderate, sustained increases in mean temperature and precipitation benefitted some species, but extreme heat, drought, and heavy rainfall often reduced abundance and nest success. These patterns varied among climate regions, temporal scales of temperature and precipitation (<1 or ≥1 month), and taxa. The sensitivity of grassland bird populations to extreme weather and altered climate variability will likely be mediated by regional climates, interaction with other stressors, life-history strategies of various species, and species' tolerances for novel climate conditions.

Spring temperature drives phenotypic selection on plasticity of flowering time

In seasonal environments, a high responsiveness of development to increasing temperatures in spring can infer benefits in terms of a longer growing season, but also costs in terms of an increased risk of facing unfavourable weather conditions. Still, we know little about how climatic conditions influence the optimal plastic response. Using 22 years of field observations for the perennial forest herb Lathyrus vernus, we assessed phenotypic selection on among-individual variation in reaction norms of flowering time to spring temperature, and examined if among-year variation in selection on plasticity was associated with spring temperature conditions. We found significant among-individual variation in mean flowering time and flowering time plasticity, and that plants that flowered earlier also had a more plastic flowering time. Selection favoured individuals with an earlier mean flowering time and a lower thermal plasticity of flowering time. Less plastic individuals were more strongly favoured in colder springs, indicating that spring temperature influenced optimal flowering time plasticity. Our results show how selection on plasticity can be linked to climatic conditions, and illustrate how we can understand and predict evolutionary responses of organisms to changing environmental conditions.

Tree species growth response to climate warming varies by forest canopy position in boreal and temperate forests

Reports of forest sensitivity to climate change are based largely on the study of overstory trees, which contribute significantly to forest growth and wood supply. However, juveniles in the understory are also critical to predict future forest dynamics and demographics, but their sensitivity to climate remains less known. In this study, we applied boosted regression tree analysis to compare the sensitivity of understory and overstory trees for the 10 most common tree species in eastern North America using growth information from an unprecedented network of nearly 1.5 million tree records from 20,174 widely distributed, permanent sample plots across Canada and the United States. Fitted models were then used to project the near-term (2041-2070) growth for each canopy and tree species. We observed an overall positive effect of warming on tree growth for both canopies and most species, leading to an average of 7.8%-12.2% projected growth gains with climate change under RCP 4.5 and 8.5. The magnitude of these gains peaked in colder, northern areas for both canopies, while growth declines are projected for overstory trees in warmer, southern regions. Relative to overstory trees, understory tree growth was less positively affected by warming in northern regions, while displaying more positive responses in southern areas, likely driven by the buffering effect of the canopy from warming and climate extremes. Observed differences in climatic sensitivity between canopy positions underscore the importance of accounting for differential growth responses to climate between forest strata in future studies to improve ecological forecasts. Furthermore, latitudinal variation in the differential sensitivity of forest strata to climate reported here may help refine our comprehension of species range shift and changes in suitable habitat under climate change.

Timing and magnitude of drought impacts on carbon uptake across a grassland biome

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remain unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km² temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C₄ -dominated shortgrass steppe and the C₃ -dominated northern mixed prairies. Across over 700,000 pixel-year combinations covering more than 600,000 km² , we studied how the driest years between 2003-2020 altered the daily and bi-weekly dynamics of grassland carbon (C) uptake. Reductions to C uptake intensified into the early summer during drought and peaked in mid- and late June in both ecoregions. Stimulation of spring C uptake during drought was small and insufficient to compensate for losses during summer. Thus, total grassland C uptake was consistently reduced by drought across both ecoregions; however, reductions were twice as large across the more southern and warmer shortgrass steppe. Across the biome, increased summer vapor pressure deficit (VPD) was strongly linked to peak reductions in vegetation greenness during drought. Rising VPD will likely exacerbate reductions in C uptake during drought across the western US Great Plains, with these reductions greatest during the warmest months and in the warmest locations. High spatiotemporal resolution analyses of grassland response to drought over large areas provide both generalizable insights and new opportunities for basic and applied ecosystem science in these water-limited ecoregions amid climate change.

Summer drought exposure, stand structure, and soil properties jointly control the growth of European beech along a steep precipitation gradient in northern Germany

Increasing exposure to climate warming-related drought and heat threatens forest vitality in many regions on earth, with the trees' vulnerability likely depending on local climatic aridity, recent climate trends, edaphic conditions, and the drought acclimatization and adaptation of populations. Studies exploring tree species' vulnerability to climate change often have a local focus or model the species' entire distribution range, which hampers the separation of climatic and edaphic drivers of drought and heat vulnerability. We compared recent radial growth trends and the sensitivity of growth to drought and heat in central populations of a widespread and naturally dominant tree species in Europe, European beech (Fagus sylvatica), at 30 forest sites across a steep precipitation gradient (500-850 mm year^-1 ) of short length to assess the species' adaptive potential. Size-standardized basal area increment remained more constant during the period of accelerated warming since the early 1980s in populations with >360 mm growing season precipitation (April-September), while growth trends were negative at sites with <360 mm. Climatic drought in June appeared as the most influential climatic factor affecting radial growth, with a stronger effect at drier sites. A decadal decrease in the climatic water balance of the summer was identified as the most important factor leading to growth decline, which is amplified by higher stem densities. Inter-annual growth variability has increased since the early 1980s, and variability is generally higher at drier and sandier sites. Similarly, within-population growth synchrony is higher at sandier sites and has increased with a decrease in the June climatic water balance. Our results caution against predicting the drought vulnerability of trees solely from climate projections, as soil properties emerged as an important modulating factor. We conclude that beech is facing recent growth decline at drier sites in the centre of its distribution range, driven by climate change-related climate aridification.

Spatial patterns of climate change across the Paleocene-Eocene Thermal Maximum

The Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) is one of our best geological analogs for understanding climate dynamics in a "greenhouse" world. However, proxy data representing the event are only available from select marine and terrestrial sedimentary sequences that are unevenly distributed across Earth's surface, limiting our view of the spatial patterns of climate change. Here, we use paleoclimate data assimilation (DA) to combine climate model and proxy information and create a spatially complete reconstruction of the PETM and the climate state that precedes it ("PETM-DA"). Our data-constrained results support strong polar amplification, which in the absence of an extensive cryosphere, is related to temperature feedbacks and loss of seasonal snow on land. The response of the hydrological cycle to PETM warming consists of a narrowing of the Intertropical Convergence Zone, off-equatorial drying, and an intensification of seasonal monsoons and winter storm tracks. Many of these features are also seen in simulations of future climate change under increasing anthropogenic emissions. Since the PETM-DA yields a spatially complete estimate of surface air temperature, it yields a rigorous estimate of global mean temperature change (5.6 ^∘C; 5.4 ^∘C to 5.9 ^∘C, 95% CI) that can be used to calculate equilibrium climate sensitivity (ECS). We find that PETM ECS was 6.5 ^∘C (5.7 ^∘C to 7.4 ^∘C, 95% CI), which is much higher than the present-day range. This supports the view that climate sensitivity increases substantially when greenhouse gas concentrations are high.

The Antarctic ozone hole and the pattern effect on climate sensitivity

We provide a perspective on recent scientific literature that argues the reduction in climate sensitivity identified with relative cooling in the eastern tropical Pacific Ocean could be caused by the onset of the Antarctic ozone hole starting in about 1980. If this is true, the pattern effect could persist as long as the ozone hole, nearly 60 y. This would continue the reduction in warming associated with the pattern effect on climate sensitivity. In addition, increased probability of La Niña events would imply an increased chance of drought in the American Southwest and other impacts of cooling in the eastern tropical Pacific.

Since about 1980, the tropical Pacific has been anomalously cold, while the broader tropics have warmed. This has caused anomalous weather in midlatitudes as well as a reduction in the apparent sensitivity of the climate associated with enhanced low-cloud abundance over the cooler waters of the eastern tropical Pacific. Recent modeling work has shown that cooler temperatures over the Southern Ocean around Antarctica can lead to cooler temperatures over the eastern tropical Pacific. Here we suggest that surface wind anomalies associated with the Antarctic ozone hole can cause cooler temperatures over the Southern Ocean that extend into the tropics. We use the short-term variability of the Southern Annular Mode of zonal wind variability to show an association between surface zonal wind variations over the Southern Ocean, cooling over the Southern Ocean, and cooling in the eastern tropical Pacific. This suggests that the cooling of the eastern tropical Pacific may be associated with the onset of the Antarctic ozone hole.

Re-assessment of the climatic controls on the carbon and water fluxes of a boreal aspen forest over 1996-2016: Changing sensitivity to long-term climatic conditions

Recent evidence suggests that the relationships between climate and boreal tree growth are generally non-stationary; however, it remains uncertain whether the relationships between climate and carbon (C) fluxes of boreal forests are stationary or have changed over recent decades. In this study, we used continuous eddy-covariance and microclimate data over 21 years (1996-2016) from a 100-year-old trembling aspen stand in central Saskatchewan, Canada to assess the relationships between climate and ecosystem C and water fluxes. Over the study period, the most striking climatic event was a severe, 3-year drought (2001-2003). Gross ecosystem production (GEP) showed larger interannual variability than ecosystem respiration (R_e ) over 1996-2016, but R_e was the dominant component contributing to the interannual variation in net ecosystem production (NEP) during post-drought years. The interannual variations in evapotranspiration (ET) and C fluxes were primarily driven by temperature and secondarily by water availability. Two-factor linear models combining precipitation and temperature performed well in explaining the interannual variation in C and water fluxes (R²  > .5). The temperature sensitivities of all three C fluxes (NEP, GEP and R_e ) declined over the study period (p < .05), and, as a result, the phenological controls on annual NEP weakened. The decreasing temperature sensitivity of the C fluxes may reflect changes in forest structure, related to the over-maturity of the aspen stand at 100 years of age, and exacerbated by high tree mortality following the severe 2001-2003 drought. These results may provide an early warning signal of driver shift or even an abrupt status shift of aspen forest dynamics. They may also imply a universal weakening in the relationship between temperature and GEP as forests become over-mature, associated with the structural and compositional changes that accompany forest ageing.

Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.

Joint effects of climate, tree size, and year on annual tree growth derived from tree-ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

Climate Effects on Subsoil Carbon Loss Mediated by Soil Chemistry

Subsoils store at least 50% of soil organic carbon (SOC) globally, but climate change may accelerate subsoil SOC (SOC_sub) decomposition and amplify SOC-climate feedbacks. The climate sensitivity of SOC_sub decomposition varies across systems, but we lack the mechanistic links needed to predict system-specific SOC_sub vulnerability as a function of measurable properties at larger scales. Here, we show that soil chemical properties exert significant control over SOC_sub decomposition under elevated temperature and moisture in subsoils collected across terrestrial National Ecological Observatory Network sites. Compared to a suite of soil and site-level variables, a divalent base cation-to-reactive metal gradient, linked to dominant mechanisms of SOC_sub mineral protection, was the best predictor of the climate sensitivity of SOC decomposition. The response was "U"-shaped, showing higher sensitivity to temperature and moisture when either extractable base cations or reactive metals were highest. However, SOC_sub in base cation-dominated subsoils was more sensitive to moisture than temperature, with the opposite relationship demonstrated in reactive metal-dominated subsoils. These observations highlight the importance of system-specific mechanisms of mineral stabilization in the prediction of SOC_sub vulnerability to climate drivers. Our observations also form the basis for a spatially explicit, scalable, and mechanistically grounded tool for improved prediction of SOC_sub response to climate change.

Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands

Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this 'temporal sensitivity' varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure. We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA. Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts. The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.

Forest riparian buffers reduce timber harvesting effects on stream temperature, but additional climate adaptation strategies are likely needed under future conditions

Stream water temperature imposes metabolic constraints on the health of cold-water fish like salmonids. Timber harvesting can reduce stream shading leading to higher water temperatures, while also altering stream hydrology. In the Pacific Northwest, riparian buffer requirements are designed to mitigate these impacts; however, anticipated future changes in air temperature and precipitation could reduce the efficacy of these practices in protecting aquatic ecosystems. Using a combined modeling approach (Soil and Water Assessment Tool (SWAT), Shade, and QUAL2K), this study examines the effectiveness of riparian buffers in reducing impacts of timber harvest on stream water temperature in Lookout Creek, Oregon across a range of potential future climates. Simulations assess changes in riparian management alone, climate alone, and combined effects. Results suggest that maximum stream water temperatures during thermal stress events are projected to increase by 3.3-7.4 °C due to hydroclimatic change alone by the end of this century. Riparian management is effective in reducing stream temperature increases from timber harvesting alone but cannot fully counteract the additional effects of a warming climate. Overall, our findings suggest that the protection of sensitive aquatic species will likely require additional adaptation strategies, such as the protection or provisioning of cool water refugia, to enhance survival during maximum thermal stress events.

Observational evidence that cloud feedback amplifies global warming

Global warming drives changes in Earth's cloud cover, which, in turn, may amplify or dampen climate change. This "cloud feedback" is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)-the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m^-2⋅K^-1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.

Modeling vegetation greenness and its climate sensitivity with deep-learning technology

Climate sensitivity of vegetation has long been explored using statistical or process-based models. However, great uncertainties still remain due to the methodologies' deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate-vegetation models based on long short-term memory (LSTM) network, which is a powerful deep-learning algorithm for long-time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep-learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.

Topsoil organic matter build-up in glacier forelands around the world

Since the last glacial maximum, soil formation related to ice-cover shrinkage has been one major sink of carbon accumulating as soil organic matter (SOM), a phenomenon accelerated by the ongoing global warming. In recently deglacierized forelands, processes of SOM accumulation, including those that control carbon and nitrogen sequestration rates and biogeochemical stability of newly sequestered carbon, remain poorly understood. Here, we investigate the build-up of SOM during the initial stages (up to 410 years) of topsoil development in 10 glacier forelands distributed on four continents. We test whether the net accumulation of SOM on glacier forelands (i) depends on the time since deglacierization and local climatic conditions (temperature and precipitation); (ii) is accompanied by a decrease in its stability and (iii) is mostly due to an increasing contribution of organic matter from plant origin. We measured total SOM concentration (carbon, nitrogen), its relative hydrogen/oxygen enrichment, stable isotopic (¹³ C, ¹⁵ N) and carbon functional groups (C-H, C=O, C=C) compositions, and its distribution in carbon pools of different thermal stability. We show that SOM content increases with time and is faster on forelands experiencing warmer climates. The build-up of SOM pools shows consistent trends across the studied soil chronosequences. During the first decades of soil development, the low amount of SOM is dominated by a thermally stable carbon pool with a small and highly thermolabile pool. The stability of SOM decreases with soil age at all sites, indicating that SOM storage is dominated by the accumulation of labile SOM during the first centuries of soil development, and suggesting plant carbon inputs to soil (SOM depleted in nitrogen, enriched in hydrogen and in aromatic carbon). Our findings highlight the potential vulnerability of SOM stocks from proglacial areas to decomposition and suggest that their durability largely depends on the relative contribution of carbon inputs from plants.

[Simulation and uncertainty analysis of natural regeneration for pine-oak forests.]

The complexity and uncertainty of forest regeneration is crucial for predicting forest ecosystem dynamics. A natural regeneration model of pine-oak forests in Qinling Mountains was constructed with competition, climate and topography factors using Bayesian statistics and global sensitivity analysis (GSA). The alternative models were based on Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models. According to the uncertainty of model parameter transfer, the analysis results were quantified, and the dominant factors of small probability events affecting forest regeneration were explained. The results showed that the ZINB model was the best one in the simulation of Pinus tabuliformis and Quercus aliena var. acuteserrata. Stand basal area, light interception, slope location and minimum temperature during growing season were the most critical factors affecting natural regeneration of P. tabuliformis, while stand basal area, cosine of aspect interacted with the natural logarithm of elevation, annual mean temperature, and precipitation of the warmest quarter were the most critical factors for Q. aliena var. acuteserrata. The contributions of various factors to the predictive uncertainty were: competition factor (25%) < climate factor (29%) < topography factor (46%) for the simulation of P. tabuliformis regeneration, and climate factor (12%) < competition factor (24%) < topography factor (64%) for the simulation of Q. aliena var. acuteserrata regeneration. The natural regeneration quantity of P. tabuliformis was positively correlated with mean annual temperature and minimum precipitation during growing season, and negatively correlated with the mean temperature in the driest quarter. The natural regeneration quantity of Q. aliena var. acuteserrata was positively correlated with mean annual temperature, minimum precipitation during growing season, precipitation of the warmest quarter, and negatively correlated with mean temperature of the driest quarter. The ZINB model based on Bayesian methods could effectively quantify the major factors driving forest regeneration and interpret the uncertainty propagated from parameters, which was useful for predicting forest regeneration.

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.

Intraspecific responses to climate reveal nonintuitive warming impacts on a widespread thermophilic conifer

Many ecologically important forest trees from dry areas have been insufficiently investigated for their ability to adapt to the challenges posed by climate change, which hampers the implementation of mitigation policies. We analyzed 14 common-garden experiments across the Mediterranean which studied the widespread thermophilic conifer Pinus halepensis and involved 157 populations categorized into five ecotypes. Ecotype-specific tree height responses to climate were applied to projected climate change (2071-2100 ad), to project potential growth patterns both locally and across the species' range. We found contrasting ecotypic sensitivities to annual precipitation but comparatively uniform responses to mean temperature, while evidence of local adaptation for tree height was limited to mesic ecotypes. We projected intriguing patterns of response range-wide, implying either height inhibition or stimulation of up to 75%, and deduced that the ecotype currently experiencing more favorable (wetter) conditions will show the largest inhibition. Extensive height reductions can be expected for coastal areas of France, Greece, Spain and northern Africa. Our findings underline the fact that intraspecific variations in sensitivity to precipitation must be considered when projecting tree height responses of dry forests to future climate. The ecotype-specific projected performances call for management activities to ensure forest resilience in the Mediterranean through, for example, tailored deployment strategies.

Microbial Community Structure in Arctic Lake Sediments Reflect Variations in Holocene Climate Conditions

The reconstruction of past climate variability using physical and geochemical parameters from lake sedimentary records is a well-established and widely used approach. These geological records are also known to contain large and active microbial communities, believed to be responsive to their surroundings at the time of deposition, and proceed to interact intimately with their physical and chemical environment for millennia after deposition. However, less is known about the potential legacy of past climate conditions on the contemporary microbial community structure. We analysed two Holocene-length (past 10 ka BP) sediment cores from the glacier-fed Ymer Lake, located in a highly climate-sensitive region on south-eastern Greenland. By combining physical proxies, solid as well as fluid geochemistry, and microbial population profiling in a comprehensive statistical framework, we show that the microbial community structure clusters according to established lithological units, and thus captures past environmental conditions and climatic transitions. Further, comparative analyses of the two sedimentary records indicates that the manifestation of regional climate depends on local settings such as water column depth, which ultimately constrains microbial variability in the deposited sediments. The strong coupling between physical and geochemical shifts in the lake and microbial variation highlights the potential of molecular microbiological data to strengthen and refine existing sedimentological classifications of past environmental conditions and transitions. Furthermore, this coupling implies that microbially controlled transformation and partitioning of geochemical species (e.g., manganese and sulphate) in Ymer lake today is still affected by climatic conditions that prevailed thousands of years back in time.

Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution

A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree-ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space-for-time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas-fir (Pseudotsuga menziesii), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed-effects model to capture ring-width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas-fir's range; narrower rings and stronger climate sensitivity occurred across the semi-arid interior. Ring-width response to spatial versus temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas-fir's distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed-effects modeling for reviving a conceptual cornerstone of dendroecology, Cook's 1987 aggregate growth model, and the great potential to use tree-ring networks and results as a calibration target for next-generation vegetation models.

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

The climatic drivers of primary Picea forest growth along the Carpathian arc are changing under rising temperatures

Climatic constraints on tree growth mediate an important link between terrestrial and atmospheric carbon pools. Tree rings provide valuable information on climate-driven growth patterns, but existing data tend to be biased toward older trees on climatically extreme sites. Understanding climate change responses of biogeographic regions requires data that integrate spatial variability in growing conditions and forest structure. We analyzed both temporal (c. 1901-2010) and spatial variation in radial growth patterns in 9,876 trees from fragments of primary Picea abies forests spanning the latitudinal and altitudinal extent of the Carpathian arc. Growth was positively correlated with summer temperatures and spring moisture availability throughout the entire region. However, important seasonal variation in climate responses occurred along geospatial gradients. At northern sites, winter precipitation and October temperatures of the year preceding ring formation were positively correlated with ring width. In contrast, trees at the southern extent of the Carpathians responded negatively to warm and dry conditions in autumn of the year preceding ring formation. An assessment of regional synchronization in radial growth variability showed temporal fluctuations throughout the 20th century linked to the onset of moisture limitation in southern landscapes. Since the beginning of the study period, differences between high and low elevations in the temperature sensitivity of tree growth generally declined, while moisture sensitivity increased at lower elevations. Growth trend analyses demonstrated changes in absolute tree growth rates linked to climatic change, with basal area increments in northern landscapes and lower altitudes responding positively to recent warming. Tree growth has predominantly increased with rising temperatures in the Carpathians, accompanied by early indicators that portions of the mountain range are transitioning from temperature to moisture limitation. Continued warming will alleviate large-scale temperature constraints on tree growth, giving increasing weight to local drivers that are more challenging to predict.

Growing season moisture drives interannual variation in woody productivity of a temperate deciduous forest

The climate sensitivity of forest ecosystem woody productivity (ANPP_stem ) influences carbon cycle responses to climate change. For the first time, we combined long-term annual growth and forest census data of a diverse temperate broadleaf deciduous forest, seeking to resolve whether ANPP_stem is primarily moisture- or energy-limited and whether climate sensitivity has changed in recent decades characterised by more mesic conditions and elevated CO₂ . We analysed tree-ring chronologies across 109 yr of monthly climatic variation (1901-2009) for 14 species representing 97% of ANPP_stem in a 25.6 ha plot in northern Virginia, USA. Radial growth of most species and ecosystem-level ANPP_stem responded positively to cool, moist growing season conditions, but the same conditions in the previous May-July were associated with reduced growth. In recent decades (1980-2009), responses were more variable and, on average, weaker. Our results indicated that woody productivity is primarily limited by current growing season moisture, as opposed to temperature or sunlight, but additional complexity in climate sensitivity may reflect the use of stored carbohydrate reserves. Overall, while such forests currently display limited moisture sensitivity, their woody productivity is likely to decline under projected hotter and potentially drier growing season conditions.

Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2

A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI-ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low-level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO2 over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO2 forcing, which nonetheless can be represented by a simple two-layer model.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long-term data assimilation

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback.

On the Interplay Between Convective Aggregation, Surface Temperature Gradients, and Climate Sensitivity

This study explores the extent to which convective aggregation interacts with sea surface temperature (SST) and affects climate sensitivity. For this purpose, radiative-convective equilibrium simulations are run with a general circulation model coupled to an ocean mixed layer, and several types of perturbations are imposed to the ocean-atmosphere system. Convective aggregation turns out to be much more sensitive to temperature in coupled experiments than in prescribed SST experiments. But changes in convective aggregation induced by a doubling of the CO2 concentration are always smaller than changes associated with the transition from a non-aggregated to an aggregated state. If aggregation changes were acting alone, they would exert a strong negative feedback on global mean surface temperature. However, in a coupled framework, aggregation changes interact with the SST and generate SST gradients that strengthen the positive low-cloud feedback associated with changes in SST pattern. This overcompensates the negative feedback due to aggregation changes and leads to a larger equilibrium climate sensitivity than in the absence of SST gradients. Although this effect might be model specific, interactions between convective aggregation and the spatial distribution of SST appear crucial to assess the impact of convective aggregation on climate sensitivity.

History of El Niño impacts on the global carbon cycle 1957-2017: a quantification from atmospheric CO2 data

Interannual variations in the large-scale net ecosystem exchange (NEE) of CO₂ between the terrestrial biosphere and the atmosphere were estimated for 1957-2017 from sustained measurements of atmospheric CO₂ mixing ratios. As the observations are sparse in the early decades, available records were combined into a 'quasi-homogeneous' dataset based on similarity in their signals, to minimize spurious variations from beginning or ending data records. During El Niño events, CO₂ is anomalously released from the tropical band, and a few months later also in the northern extratropical band. This behaviour can approximately be represented by a linear relationship of the NEE anomalies and local air temperature anomalies, with sensitivity coefficients depending on geographical location and season. The apparent climate sensitivity of global total NEE against variations in pan-tropically averaged annual air temperature slowly changed over time during the 1957-2017 period, first increasing (though less strongly than in previous studies) but then decreasing again. However, only part of this change can be attributed to actual changes in local physiological or ecosystem processes, the rest probably arising from shifts in the geographical area of dominating temperature variations.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Divergent response of seasonally dry tropical vegetation to climatic variations in dry and wet seasons

Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO₂ growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index (NDVI), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant (p < 0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature (γ^int ) and to precipitation (δ^int ). γ^int is ~1% °C^-1 more negative and δ^int is ~8% 100 mm^-1 more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in γ^int can be explained by background moisture and temperature conditions. Positive γ^int occurred in wet season where mean temperature is lower than 27°C and precipitation is at least 60 mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity (GPP) estimates (empirical modeling by machine-learning algorithm applied to flux tower measurements, and nine process-based carbon cycle models) were examined for the GPP-climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of γ^int , while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis-climate relationship and thus the projection for impacts of climate change on tropical carbon cycle.

The impact of Earth system feedbacks on carbon budgets and climate response

A number of studies have examined the size of the allowable global cumulative carbon budget compatible with limiting twenty-first century global average temperature rise to below 2°C and below 1.5°C relative to pre-industrial levels. These estimates of cumulative emissions have a number of uncertainties including those associated with the climate sensitivity and the global carbon cycle. Although the IPCC fifth assessment report contained information on a range of Earth system feedbacks, such as carbon released by thawing of permafrost or methane production by wetlands as a result of climate change, the impact of many of these Earth system processes on the allowable carbon budgets remains to be quantified. Here, we make initial estimates to show that the combined impact from typically unrepresented Earth system processes may be important for the achievability of limiting warming to 1.5°C or 2°C above pre-industrial levels. The size of the effects range up to around a 350 GtCO₂ budget reduction for a 1.5°C warming limit and around a 500 GtCO₂ reduction for achieving a warming limit of 2°C. Median estimates for the extra Earth system forcing lead to around 100 GtCO₂ and 150 GtCO₂, respectively, for the two warming limits. Our estimates are equivalent to several years of anthropogenic carbon dioxide emissions at present rates. In addition to the likely reduction of the allowable global carbon budgets, the extra feedbacks also bring forward the date at which a given warming threshold is likely to be exceeded for a particular emission pathway.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Comparing Climate Sensitivity, Past and Present

Climate sensitivity represents the global mean temperature change caused by changes in the radiative balance of climate; it is studied for both present/future (actuo) and past (paleo) climate variations, with the former based on instrumental records and/or various types of model simulations. Paleo-estimates are often considered informative for assessments of actuo-climate change caused by anthropogenic greenhouse forcing, but this utility remains debated because of concerns about the impacts of uncertainties, assumptions, and incomplete knowledge about controlling mechanisms in the dynamic climate system, with its multiple interacting feedbacks and their potential dependence on the climate background state. This is exacerbated by the need to assess actuo- and paleoclimate sensitivity over different timescales, with different drivers, and with different (data and/or model) limitations. Here, we visualize these impacts with idealized representations that graphically illustrate the nature of time-dependent actuo- and paleoclimate sensitivity estimates, evaluating the strengths, weaknesses, agreements, and differences of the two approaches. We also highlight priorities for future research to improve the use of paleo-estimates in evaluations of current climate change.

Egg size investment in superb fairy-wrens: helper effects are modulated by climate

Natural populations might exhibit resilience to changing climatic conditions if they already show adaptive flexibility in their reproductive strategies. In cooperative breeders, theory predicts that mothers with helpers should provide less care when environmental conditions are favourable, but maintain high investment when conditions are challenging. Here, we test for evidence of climate-mediated flexibility in maternal investment in the cooperatively breeding superb fairy-wren Malurus cyaneus We focus on egg size because in this species egg size influences offspring size, and females reduce egg investment when there are helpers at the nest. We report that females lay larger eggs during dry, hot conditions. However, the effect of temperature is modulated by the presence of helpers: the average egg size of females with helpers is reduced during cooler conditions but increased during hot conditions relative to females without helpers. This appears to reflect plasticity in egg investment rather than among female differences. Analysis of maternal survival suggests that helped females are better able to withstand the costs of breeding in hot conditions than females without helpers. Our study suggests that females can use multiple, independent cues to modulate egg investment flexibly in a variable environment.

Tree-ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change

Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming-induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree-ring width dataset accessed from the International Tree-Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty-first-century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.

Increasing temperature cuts back crop yields in Hungary over the last 90 years

The transformation of climatic regime has an undeniable impact on plant production, but we rarely have long enough date series to examine the unfolding of such effects. The clarification of the relationship between crop plants and climate has a near-immediate importance due to the impending human-made global change. This study investigated the relationship between temperature, precipitation, drought intensity and the yields of four major cereals in Hungary between 1921 and 2010. The analysis of 30-year segments indicated a monotonously increasing negative impact of temperature on crop yields. A 1°C temperature increase reduced the yield of the four main cereals by 9.6%-14.8% in 1981-2010, which revealed the vulnerability of Eastern European crop farming to recent climate change. Climate accounted for 17%-39% of yield variability over the past 90 years, but this figure reached 33%-67% between 1981 and 2010. Our analysis supports the claim that the mid-20th century green revolution improved yields "at the mercy of the weather": during this period, the impact of increasing fertilization and mechanisation coincided with climatic conditions that were more favourable than today. Crop yields in Eastern Europe have been stagnating or decreasing since the mid-1980s. Although usually attributed to the large socio-economic changes sweeping the region, our analysis indicates that a warming climate is at least partially responsible for this trend. Such a robust impact of increasing temperatures on crop yields also constitutes an obvious warning for this core grain-growing region of the world.

Relationship of tropospheric stability to climate sensitivity and Earth's observed radiation budget

Climate feedbacks generally become smaller in magnitude over time under CO₂ forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO₂ Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.

stems in tundra shrubs

Shrub densification has been widely reported across the circumpolar arctic and subarctic biomes in recent years. Long-term analyses based on dendrochronological techniques applied to shrubs have linked this phenomenon to climate change. However, the multi-stemmed structure of shrubs makes them difficult to sample and therefore leads to non-uniform sampling protocols among shrub ecologists, who will favor either root collars or stems to conduct dendrochronological analyses. Through a comparative study of the use of root collars and stems of Betula glandulosa, a common North American shrub species, we evaluated the relative sensitivity of each plant part to climate variables and assessed whether this sensitivity is consistent across three different types of environments in northwestern Québec, Canada (terrace, hilltop and snowbed). We found that root collars had greater sensitivity to climate than stems and that these differences were maintained across the three types of environments. Growth at the root collar was best explained by spring precipitation and summer temperature, whereas stem growth showed weak and inconsistent responses to climate variables. Moreover, sensitivity to climate was not consistent among plant parts, as individuals having climate-sensitive root collars did not tend to have climate-sensitive stems. These differences in sensitivity of shrub parts to climate highlight the complexity of resource allocation in multi-stemmed plants. Whereas stem initiation and growth are driven by microenvironmental variables such as light availability and competition, root collars integrate the growth of all plant parts instead, rendering them less affected by mechanisms such as competition and more responsive to signals of global change. Although further investigations are required to determine the degree to which these findings are generalizable across the tundra biome, our results indicate that consistency and caution in the choice of plant parts are a key consideration for the success of future dendroclimatological studies on shrubs.

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO₂ at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO₂ in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO₂ in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO₂ drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO₂ sensitivity. Fire in model simulations reduced model sensitivity to climate and CO₂ , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO₂ in individual models.

Nonlinear climate sensitivity and its implications for future greenhouse warming

Global mean surface temperatures are rising in response to anthropogenic greenhouse gas emissions. The magnitude of this warming at equilibrium for a given radiative forcing-referred to as specific equilibrium climate sensitivity (S)-is still subject to uncertainties. We estimate global mean temperature variations and S using a 784,000-year-long field reconstruction of sea surface temperatures and a transient paleoclimate model simulation. Our results reveal that S is strongly dependent on the climate background state, with significantly larger values attained during warm phases. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, we find that the range of paleo-based estimates of Earth's future warming by 2100 CE overlaps with the upper range of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Furthermore, we find that within the 21st century, global mean temperatures will very likely exceed maximum levels reconstructed for the last 784,000 years. On the basis of temperature data from eight glacial cycles, our results provide an independent validation of the magnitude of current CMIP5 warming projections.

Thermodynamic control of anvil cloud amount

General circulation models show that as the surface temperature increases, the convective anvil clouds shrink. By analyzing radiative-convective equilibrium simulations, we show that this behavior is rooted in basic energetic and thermodynamic properties of the atmosphere: As the climate warms, the clouds rise and remain at nearly the same temperature, but find themselves in a more stable atmosphere; this enhanced stability reduces the convective outflow in the upper troposphere and decreases the anvil cloud fraction. By warming the troposphere and increasing the upper-tropospheric stability, the clustering of deep convection also reduces the convective outflow and the anvil cloud fraction. When clouds are radiatively active, this robust coupling between temperature, high clouds, and circulation exerts a positive feedback on convective aggregation and favors the maintenance of strongly aggregated atmospheric states at high temperatures. This stability iris mechanism likely contributes to the narrowing of rainy areas as the climate warms. Whether or not it influences climate sensitivity requires further investigation.

Monitoring intra-annual dynamics of wood formation with microcores and dendrometers in Picea abies at two different altitudes

Seasonal analyses of cambial cell production and day-by-day stem radial increment can help to elucidate how climate modulates wood formation in conifers. Intra-annual dynamics of wood formation were determined with microcores and dendrometers and related to climatic signals in Norway spruce (Picea abies (L.) Karst.). The seasonal dynamics of these processes were observed at two sites of different altitude, Savignano (650 m a.s.l.) and Lavazè (1800 m a.s.l.) in the Italian Alps. Seasonal dynamics of cambial activity were found to be site specific, indicating that the phenology of cambial cell production is highly variable and plastic with altitude. There was a site-specific trend in the number of cells in the wall thickening phase, with the maximum cell production in early July (DOY 186) at Savignano and in mid-July (DOY 200) at Lavazè. The formation of mature cells showed similar trends at the two sites, although different numbers of cells and timing of cell differentiation were visible in the model shapes; at the end of ring formation in 2010, the number of cells was four times higher at Savignano (106.5 cells) than at Lavazè (26.5 cells). At low altitudes, microcores and dendrometers described the radial growth patterns comparably, though the dendrometer function underlined the higher upper asymptote of maximum growth in comparison with the cell production function. In contrast, at high altitude, these functions exhibited different trends. The best model was obtained by fitting functions of the Gompertz model to the experimental data. By combining radial growth and cambial activity indices we defined a model system able to synchronize these processes. Processes of adaptation of the pattern of xylogenesis occurred, enabling P. abies to occupy sites with contrasting climatic conditions. The use of daily climatic variables in combination with plant functional traits obtained by sensors and/or destructive sampling could provide a suitable tool to better investigate the effect of disturbances on response strategies in trees and, consequently, contribute to improving our prediction of tree growth and species resilience based on climate scenarios.

Estimating option values of solar radiation management assuming that climate sensitivity is uncertain

Although solar radiation management (SRM) might play a role as an emergency geoengineering measure, its potential risks remain uncertain, and hence there are ethical and governance issues in the face of SRM's actual deployment. By using an integrated assessment model, we first present one possible methodology for evaluating the value arising from retaining an SRM option given the uncertainty of climate sensitivity, and also examine sensitivities of the option value to SRM's side effects (damages). Reflecting the governance challenges on immediate SRM deployment, we assume scenarios in which SRM could only be deployed with a limited degree of cooling (0.5 °C) only after 2050, when climate sensitivity uncertainty is assumed to be resolved and only when the sensitivity is found to be high (T2x = 4 °C). We conduct a cost-effectiveness analysis with constraining temperature rise as the objective. The SRM option value is originated from its rapid cooling capability that would alleviate the mitigation requirement under climate sensitivity uncertainty and thereby reduce mitigation costs. According to our estimates, the option value during 1990-2049 for a +2.4 °C target (the lowest temperature target level for which there were feasible solutions in this model study) relative to preindustrial levels were in the range between $2.5 and $5.9 trillion, taking into account the maximum level of side effects shown in the existing literature. The result indicates that lower limits of the option values for temperature targets below +2.4 °C would be greater than $2.5 trillion.

Climate sensitivity uncertainty: when is good news bad?

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity--how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the 'likely' range has been 1.5-4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2-4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the 'best estimate'. We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: when might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal well-being? The lowered bottom value also implies higher uncertainty about the temperature increase, definitely bad news. Under reasonable assumptions, both the lowering of the lower bound and the removal of the 'best estimate' may well be bad news.

Better predictions, better allocations: scientific advances and adaptation to climate change

Climate science initially aspired to improve understanding of what the future would bring, and thereby produce appropriate public policies and effective international climate agreements. If that hope is dashed, as now seems probable, effective policies for adapting to climate change become critical. Climate science assumes new responsibilities by helping to foster more appropriate adaptation measures, which might include shifting modes or locales of production. This theoretical article focuses on two broader tools: consumption smoothing in response to the risk of future losses, and physical adaptation measures to reduce potential damages. It shows that informative signals on the effects of climate change facilitate better decisions on the use of each tool, thereby increasing social welfare.

Insights into low-latitude cloud feedbacks from high-resolution models

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

Feedbacks, climate sensitivity and the limits of linear models

The term 'feedback' is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify and quantify parts of the complex Earth system. We combine new model results with a historical and educational perspective to organize existing ideas around feedbacks and linear models. Our results suggest that the state- and forcing-dependency of feedbacks are probably not appreciated enough, and not considered appropriately in many studies. A non-constant feedback parameter likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system.

The inconstancy of the transient climate response parameter under increasing CO2

In the Coupled Model Intercomparison Project Phase 5 (CMIP5), the model-mean increase in global mean surface air temperature T under the 1pctCO2 scenario (atmospheric CO(2) increasing at 1% yr(-1)) during the second doubling of CO(2) is 40% larger than the transient climate response (TCR), i.e. the increase in T during the first doubling. We identify four possible contributory effects. First, the surface climate system loses heat less readily into the ocean beneath as the latter warms. The model spread in the thermal coupling between the upper and deep ocean largely explains the model spread in ocean heat uptake efficiency. Second, CO(2) radiative forcing may rise more rapidly than logarithmically with CO(2) concentration. Third, the climate feedback parameter may decline as the CO(2) concentration rises. With CMIP5 data, we cannot distinguish the second and third possibilities. Fourth, the climate feedback parameter declines as time passes or T rises; in 1pctCO2, this effect is less important than the others. We find that T projected for the end of the twenty-first century correlates more highly with T at the time of quadrupled CO(2) in 1pctCO2 than with the TCR, and we suggest that the TCR may be underestimated from observed climate change.

Effects of explicit atmospheric convection at high CO2

The effect of clouds on climate remains the largest uncertainty in climate change predictions, due to the inability of global climate models (GCMs) to resolve essential small-scale cloud and convection processes. We compare preindustrial and quadrupled CO2 simulations between a conventional GCM in which convection is parameterized and a "superparameterized" model in which convection is explicitly simulated with a cloud-permitting model in each grid cell. We find that the global responses of the two models to increased CO2 are broadly similar: both simulate ice-free Arctic summers, wintertime Arctic convection, and enhanced Madden-Julian oscillation (MJO) activity. Superparameterization produces significant differences at both CO2 levels, including greater Arctic cloud cover, further reduced sea ice area at high CO2, and a stronger increase with CO2 of the MJO.

Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation

Physiological thermal-tolerance limits of terrestrial ectotherms often exceed local air temperatures, implying a high degree of thermal safety (an excess of warm or cold thermal tolerance). However, air temperatures can be very different from the equilibrium body temperature of an individual ectotherm. Here, we compile thermal-tolerance limits of ectotherms across a wide range of latitudes and elevations and compare these thermal limits both to air and to operative body temperatures (theoretically equilibrated body temperatures) of small ectothermic animals during the warmest and coldest times of the year. We show that extreme operative body temperatures in exposed habitats match or exceed the physiological thermal limits of most ectotherms. Therefore, contrary to previous findings using air temperatures, most ectotherms do not have a physiological thermal-safety margin. They must therefore rely on behavior to avoid overheating during the warmest times, especially in the lowland tropics. Likewise, species living at temperate latitudes and in alpine habitats must retreat to avoid lethal cold exposure. Behavioral plasticity of habitat use and the energetic consequences of thermal retreats are therefore critical aspects of species' vulnerability to climate warming and extreme events.

Climate sensitivity, sea level and atmospheric carbon dioxide

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1(°)C for a 4 W m(-2) CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4(°)C for a 4 W m(-2) CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.