An explanation for the difference between twentieth and twenty-first century land–sea warming ratio in climate models

A land–sea surface warming ratio (or φ) that exceeds unity is a robust feature of both observed and modelled climate change. Interestingly, though climate models have differing values for φ, it remains almost time-invariant for a wide range of twenty-first century climate transient warming scenarios, while varying in simulations of the twentieth century. Here, we present an explanation for time-invariant land–sea warming ratio that applies if three conditions on radiative forcing are met: first, spatial variations in the climate forcing must be sufficiently small that the lower free troposphere warms evenly over land and ocean; second, the temperature response must not be large enough to change the global circulation to zeroth order; third, the temperature response must not be large enough to modify the boundary layer amplification mechanisms that contribute to making φ exceed unity. Projected temperature changes over this century are too small to breach the latter two conditions. Hence, the mechanism appears to show why both twenty-first century and time-invariant CO₂ forcing lead to similar values of φ in climate models despite the presence of transient ocean heat uptake, whereas twentieth century forcing—which has a significant spatially confined anthropogenic tropospheric aerosol component that breaches the first condition—leads to modelled values of φ that vary widely amongst models and in time. Our results suggest an explanation for the behaviour of φ when climate is forced by other regionally confined forcing scenarios such as geo-engineered changes to oceanic clouds. Our results show how land–sea contrasts in surface and boundary layer characteristics act in tandem to produce the land–sea surface warming contrast.     

Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming

Although current global warming may have a large anthropogenic component, its quantification relies primarily on complex General Circulation Models (GCM’s) assumptions and codes; it is desirable to complement this with empirically based methodologies. Previous attempts to use the recent climate record have concentrated on “fingerprinting” or otherwise comparing the record with GCM outputs. By using CO₂ radiative forcings as a linear surrogate for all anthropogenic effects we estimate the total anthropogenic warming and (effective) climate sensitivity finding: ΔT _anth  = 0.87 ± 0.11 K, $\uplambda_{{2{\text{x}}{\text{CO}}_{2} ,{\text{eff}}}} = 3.08 \pm 0.58\,{\text{K}}$ . These are close the IPPC AR5 values ΔT _anth  = 0.85 ± 0.20 K and $\uplambda_{{2{\text{x}}{\text{CO}}_{2} }} = 1.5\!-\!4.5\,{\text{K}}$ (equilibrium) climate sensitivity and are independent of GCM models, radiative transfer calculations and emission histories. We statistically formulate the hypothesis of warming through natural variability by using centennial scale probabilities of natural fluctuations estimated using scaling, fluctuation analysis on multiproxy data. We take into account two nonclassical statistical features—long range statistical dependencies and “fat tailed” probability distributions (both of which greatly amplify the probability of extremes). Even in the most unfavourable cases, we may reject the natural variability hypothesis at confidence levels >99 %.     

Uncertainty in the 2°C warming threshold related to climate sensitivity and climate feedback

Climate sensitivity is an important index that measures the relationship between the increase in greenhouse gases and the magnitude of global warming. Uncertainties in climate change projection and climate modeling are mostly related to the climate sensitivity. The climate sensitivities of coupled climate models determine the magnitudes of the projected global warming. In this paper, the authors thoroughly review the literature on climate sensitivity, and discuss issues related to climate feedback processes and the methods used in estimating the equilibrium climate sensitivity and transient climate response (TCR), including the TCR to cumulative CO₂ emissions. After presenting a summary of the sources that affect the uncertainty of climate sensitivity, the impact of climate sensitivity on climate change projection is discussed by addressing the uncertainties in 2°C warming. Challenges that call for further investigation in the research community, in particular the Chinese community, are discussed.     

Climate change hotspots in the CMIP5 global climate model ensemble

We use a statistical metric of multi-dimensional climate change to quantify the emergence of global climate change hotspots in the CMIP5 climate model ensemble. Our hotspot metric extends previous work through the inclusion of extreme seasonal temperature and precipitation, which exert critical influence on climate change impacts. The results identify areas of the Amazon, the Sahel and tropical West Africa, Indonesia, and the Tibetan Plateau as persistent regional climate change hotspots throughout the 21st century of the RCP8.5 and RCP4.5 forcing pathways. In addition, areas of southern Africa, the Mediterranean, the Arctic, and Central America/western North America also emerge as prominent regional climate change hotspots in response to intermediate and high levels of forcing. Comparisons of different periods of the two forcing pathways suggest that the pattern of aggregate change is fairly robust to the level of global warming below approximately 2 °C of global warming (relative to the late-20th-century baseline), but not at the higher levels of global warming that occur in the late-21st-century period of the RCP8.5 pathway, with areas of southern Africa, the Mediterranean, and the Arctic exhibiting particular intensification of relative aggregate climate change in response to high levels of forcing. Although specific impacts will clearly be shaped by the interaction of climate change with human and biological vulnerabilities, our identification of climate change hotspots can help to inform mitigation and adaptation decisions by quantifying the rate, magnitude and causes of the aggregate climate response in different parts of the world.     

Synoptic drivers of 400 years of summer temperature and precipitation variability on Mt. Olympus,Greece

The Mediterranean region has been identified as a global warming hotspot, where future climate impacts are expected to have significant consequences on societal and ecosystem well-being. To put ongoing trends of summer climate into the context of past natural variability, we reconstructed climate from maximum latewood density (MXD) measurements of Pinus heldreichii (1521–2010) and latewood width (LWW) of Pinus nigra (1617–2010) on Mt. Olympus, Greece. Previous research in the northeastern Mediterranean has primarily focused on inter-annual variability, omitting any low-frequency trends. The present study utilizes methods capable of retaining climatically driven long-term behavior of tree growth. The LWW chronology corresponds closely to early summer moisture variability (May–July, r = 0.65, p < 0.001, 1950–2010), whereas the MXD-chronology relates mainly to late summer warmth (July–September, r = 0.64, p < 0.001; 1899–2010). The chronologies show opposing patterns of decadal variability over the twentieth century (r = ?0.68, p < 0.001) and confirm the importance of the summer North Atlantic Oscillation (sNAO) for summer climate in the northeastern Mediterranean, with positive sNAO phases inducing cold anomalies and enhanced cloudiness and precipitation. The combined reconstructions document the late twentieth—early twenty-first century warming and drying trend, but indicate generally drier early summer and cooler late summer conditions in the period ~1700–1900 CE. Our findings suggest a potential decoupling between twentieth century atmospheric circulation patterns and pre-industrial climate variability. Furthermore, the range of natural climate variability stretches beyond summer moisture availability observed in recent decades and thus lends credibility to the significant drying trends projected for this region in current Earth System Model simulations.     

Non-uniform interhemispheric temperature trends over the past 550 years

The warming trend over the last century in the northern hemisphere (NH) was interrupted by cooling from ad 1940 to 1975, a period during which the southern hemisphere experienced pronounced warming. The cause of these departures from steady warming at multidecadal timescales are unclear; the prevailing explanation is that they are driven by non-uniformity in external forcings but recent models suggest internal climate drivers may play a key role. Paleoclimate datasets can help provide a long-term perspective. Here we use tree-rings to reconstruct New Zealand mean annual temperature over the last 550 years and demonstrate that this has frequently cycled out-of-phase with NH mean annual temperature at a periodicity of around 30–60 years. Hence, observed multidecadal fluctuations around the recent warming trend have precedents in the past, strongly implicating natural climate variation as their cause. We consider the implications of these changes in understanding and modelling future climate change.     

Potential spread of recently naturalised plants in New Zealand under climate change

Climate change and biological invasions are major causes of biodiversity loss and may also have synergistic effects, such as range shifts of invaders due to changing climate. Bioclimatic models provide an important tool to assess how the threat of invasive species may change with altered temperature and precipitation regimes. In this study, potential distributions of three recently naturalised plant species in New Zealand are modelled (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla), using four different general circulation models (CCCMA-CGCM3, CSIRO-Mk3.0, GFDL-CM2.0 and UKMO-HADCM3) with two emission scenarios (A2 and B1) each. Based on a maximum entropy approach, models were trained on global data using a small set of uncorrelated predictors. The models were projected to the country of interest, using climate models that had been statistically downscaled to New Zealand, in order to obtain high resolution predictions. This study provides evidence of the potential range expansion of these species, with potentially suitable habitat increasing by as much as 169 % (A. cunninghamiana; with up to 115,805 km² of suitable habitat), 133 % (P. guajava; 164,450 km²) and 208 % (S. actinophylla; 31,257 km²) by the end of the century compared to the currently suitable habitat. The results show that while predictions vary depending on the chosen climate scenario, there is remarkable consistency amongst most climate models within the same emission scenario, with overlaps in areas of predicted presence ranging between 81 % and 99.5 % (excluding CSIRO-Mk3.0). By having a better understanding of how climate change will affect distribution of invasive plants, appropriate management measures can be taken.     

The effects of increased stream temperatures on juvenile steelhead growth in the Yakima River Basin based on projected climate change scenarios

Stakeholders within the Yakima River Basin expressed concern over impacts of climate change on mid-Columbia River steelhead (Oncorhynchus mykiss), listed under the Endangered Species Act. We used a bioenergetics model to assess the impacts of changing stream temperatures—resulting from different climate change scenarios—on growth of juvenile steelhead in the Yakima River Basin. We used diet and fish size data from fieldwork in a bioenergetics model and integrated baseline and projected stream temperatures from down-scaled air temperature climate modeling into our analysis. The stream temperature models predicted that daily mean temperatures of salmonid-rearing streams in the basin could increase by 1–2 °C and our bioenergetics simulations indicated that such increases could enhance the growth of steelhead in the spring, but reduce it during the summer. However, differences in growth rates of fish living under different climate change scenarios were minor, ranging from about 1–5 %. Because our analysis focused mostly on the growth responses of steelhead to changes in stream temperatures, further work is needed to fully understand the potential impacts of climate change. Studies should include evaluating changing stream flows on fish activity and energy budgets, responses of aquatic insects to climate change, and integration of bioenergetics, population dynamics, and habitat responses to climate change.     

Climate change affecting temperature and aridity zones: a case study in Eastern Inner Mongolia, China from 1960–2008

Recent climate change is substantially affecting the spatial pattern of geographical zones, and the temporal and spatial inconsistency of climatic warming and drying patterns contributes to the complexity of the shifting of temperature and aridity zones. Eastern Inner Mongolia, China, located in the interface region of different biomes and ecogeographic zones, has experienced dramatic drying and warming over the past several decades. In this study, the annual accumulated temperature above 10 °C (AAT10) and the aridity index, two key indicators in geographical regionalization, are used to assess warming and drying processes and track the movements of temperature and aridity zones from 1960 to 2008. The results show a significant warming at the regional level from 1960 to 2008 with an AAT10 increase rate of 7.89 °C·d/year (p?<?0.001) in Eastern Inner Mongolia, while the drying trend was not significant during this period. Spatial heterogeneity of warming and drying distributions was also evident. Analysis of warming and drying via piecewise regression revealed two separate, specific trends between the first 31 years (1960–1990) and the subsequent 18 years (1991–2008). Generally, mild warming and very slight wetting occurred prior to 1990, while after 1991 both warming and drying were significant and enhanced. Continuous warming drove a northward shift of temperature zones from the 1960s to 2000s, while aridity zones displayed enhanced temporal and spatial variability. Climate change effects on temperature and aridity zones imply that the patterns of cropping systems, macro-ecosystems, and human land use modes are potentially undergoing migration and modification due to climate change.     

Linear response functions to project contributions to future sea level

We propose linear response functions to separately estimate the sea-level contributions of thermal expansion and solid ice discharge from Greenland and Antarctica. The response function formalism introduces a time-dependence which allows for future rates of sea-level rise to be influenced by past climate variations. We find that this time-dependence is of the same functional type, R(t) ～ t ^α, for each of the three subsystems considered here. The validity of the approach is assessed by comparing the sea-level estimates obtained via the response functions to projections from comprehensive models. The pure vertical diffusion case in one dimension, corresponding to α =  ?0.5, is a valid approximation for thermal expansion within the ocean up to the middle of the twenty first century for all Representative Concentration Pathways. The approximation is significantly improved for α =  ? 0.7. For the solid ice discharge from Greenland we find an optimal value of α =  ?0.7. Different from earlier studies we conclude that solid ice discharge from Greenland due to dynamic thinning is bounded by 0.42 m sea-level equivalent. Ice discharge induced by surface warming on Antarctica is best captured by a positive value of α = 0.1 which reflects the fact that ice loss increases with the cumulative amount of heat available for softening the ice in our model.     

District specific,in silico evaluation of rice ideotypes improved for resistance/tolerance traits to biotic and abiotic stressors under climate change scenarios

Using crop models as supporting tools for analyzing the interaction between genotype and environment represents an opportunity to identify priorities within breeding programs. This study represents the first attempt to use simulation models to define rice ideotypes improved for their resistance to biotic stressors (i.e., diseases); moreover, it extends approaches for evaluating the impact of changes in traits for tolerance to abiotic constraints (temperature shocks inducing sterility). The analysis—targeting the improvement of 34 varieties in six Italian rice districts—was focused on the impact of blast disease, and of pre-flowering cold- and heat-induced spikelet sterility. In silico ideotypes were tested at 5-km spatial resolution under current conditions and climate change scenarios centered on 2020, 2050, and 2085, derived according to the projections of two general circulation models–Hadley and NCAR–for two IPCC emission scenarios–A1B and B1. The study was performed using a dedicated simulation platform, i.e., ISIde, explicitly developed for ideotyping studies. The ideotypes improved for blast resistance obtained clear yield increases for all the combinations GCM?×?emission scenario?×?time horizon, i.e., 12.1 % average yield increase under current climate, although slightly decreasing for time windows approaching the end of the century and with a marked spatial heterogeneity in responses across districts. Concerning abiotic stressors, increasing tolerance to cold-induced sterility would lead to a substantial yield increase (+9.8 %) only for Indica-type varieties under current climate, whereas no increases are expected under future conditions and, in general, for Japonica-type varieties. Given the process-based logic behind the models used—supporting coherence of model responses under future scenarios—this study provides useful information for rice breeding programs to be realized in the medium-long term.     

Conceptual understanding of climate change with a globally resolved energy balance model

The future climate change projections are essentially based on coupled general circulation model (CGCM) simulations, which give a distinct global warming pattern with arctic winter amplification, an equilibrium land-sea warming contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the Intergovernmental Panel on Climate Change (IPCC) predictions, the conceptual understanding of these predicted structures of climate change and the causes of their uncertainties is very difficult to reach if only based on these highly complex CGCM simulations. In the study presented here we will introduce a very simple, globally resolved energy balance (GREB) model, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the strongly simplified energy balance models and the fully coupled 4-dimensional complex CGCMs. It provides a fast tool for the conceptual understanding and development of hypotheses for climate change studies, which shall build a basis or starting point for more detailed studies of observations and CGCM simulations. It is based on the surface energy balance by very simple representations of solar and thermal radiation, the atmospheric hydrological cycle, sensible turbulent heat flux, transport by the mean atmospheric circulation and heat exchange with the deeper ocean. Despite some limitations in the representations of the basic processes, the models climate sensitivity and the spatial structure of the warming pattern are within the uncertainties of the IPCC models simulations. It is capable of simulating aspects of the arctic winter amplification, the equilibrium land-sea warming contrast and the inter-hemispheric warming gradient with good agreement to the IPCC models in amplitude and structure. The results give some insight into the understanding of the land-sea contrast and the polar amplification. The GREB model suggests that the regional inhomogeneous distribution of atmospheric water vapor and the non-linear sensitivity of the downward thermal radiation to changes in the atmospheric water vapor concentration partly cause the land-sea contrast and may also contribute to the polar amplification. The combination of these characteristics causes, in general, dry and cold regions to warm more than other regions.     

Potential impact of vegetation feedback on European heat waves in a 2 x CO 2 climate

Inclusion of the effects of vegetation feedback in a global climate change simulation suggests that the vegetation–climate feedback works to alleviate partially the summer surface warming and the associated heat waves over Europe induced by the increase in atmospheric CO₂ concentrations. The projected warming of 4°C over most of Europe with static vegetation has been reduced by 1°C as the dynamic vegetation feedback effects are included.. Examination of the simulated surface energy fluxes suggests that additional greening in the presence of vegetation feedback effects enhances evapotranspiration and precipitation, thereby limiting the warming, particularly in the daily maximum temperature. The greening also tends to reduce the frequency and duration of heat waves. Results in this study strongly suggest that the inclusion of vegetation feedback within climate models is a crucial factor for improving the projection of warm season temperatures and heat waves over Europe.     

Changes in mixed layer depth under climate change projections in two CGCMs

Two coupled general circulation models, i.e., the Meteorological Research Institute (MRI) and Geophysical Fluid Dynamics Laboratory (GFDL) models, were chosen to examine changes in mixed layer depth (MLD) in the equatorial tropical Pacific and its relationship with ENSO under climate change projections. The control experiment used pre-industrial greenhouse gas concentrations whereas the 2 × CO₂ experiment used doubled CO₂ levels. In the control experiment, the MLD simulated in the MRI model was shallower than that in the GFDL model. This resulted in the tropical Pacific’s mean sea surface temperature (SST) increasing at different rates under global warming in the two models. The deeper the mean MLD simulated in the control simulation, the lesser the warming rate of the mean SST simulated in the 2 × CO₂ experiment. This demonstrates that the MLD is a key parameter for regulating the response of tropical mean SST to global warming. In particular, in the MRI model, increased stratification associated with global warming amplified wind-driven advection within the mixed layer, leading to greater ENSO variability. On the other hand, in the GFDL model, wind-driven currents were weak, which resulted in mixed-layer dynamics being less sensitive to global warming. The relationship between MLD and ENSO was also examined. Results indicated that the non-linearity between the MLD and ENSO is enhanced from the control run to the 2 × CO₂ run in the MRI model, in contrast, the linear relationship between the MLD index and ENSO is unchanged despite an increase in CO₂ concentrations in the GFDL model.     

On the persistent spread in snow-albedo feedback

Snow-albedo feedback (SAF) is examined in 25 climate change simulations participating in the Coupled Model Intercomparison Project version 5 (CMIP5). SAF behavior is compared to the feedback’s behavior in the previous (CMIP3) generation of global models. SAF strength exhibits a fivefold spread across CMIP5 models, ranging from 0.03 to 0.16 W m^?2 K^?1 (ensemble-mean = 0.08 W m^?2 K^?1). This accounts for much of the spread in 21st century warming of Northern Hemisphere land masses, and is very similar to the spread found in CMIP3 models. As with the CMIP3 models, there is a high degree of correspondence between the magnitudes of seasonal cycle and climate change versions of the feedback. Here we also show that their geographical footprint is similar. The ensemble-mean SAF strength is close to an observed estimate of the real climate’s seasonal cycle feedback strength. SAF strength is strongly correlated with the climatological surface albedo when the ground is covered by snow. The inter-model variation in this quantity is surprisingly large, ranging from 0.39 to 0.75. Models with large surface albedo when these regions are snow-covered will also have a large surface albedo contrast between snow-covered and snow-free regions, and therefore a correspondingly large SAF. Widely-varying treatments of vegetation masking of snow-covered surfaces are probably responsible for the spread in surface albedo where snow occurs, and the persistent spread in SAF in global climate models.     

How well are daily intense rainfall events captured by current climate models over Africa?

The ability of state-of-the-art climate models to capture the mean spatial and temporal characteristics of daily intense rainfall events over Africa is evaluated by analyzing regional climate model (RCM) simulations at 90- and 30-km along with output from four atmospheric general circulation models (AGCMs) and coupled atmosphere–ocean general circulation models (AOGCMs) of the Climate Model Intercomparison Project 5. Daily intense rainfall events are extracted at grid point scale using a 95th percentile threshold approach applied to all rainy days (i.e., daily rainfall ≥1 mm day^?1) over the 1998–2008 period for which two satellite-derived precipitation products are available. Both RCM simulations provide similar results. They accurately capture the spatial and temporal characteristics of intense events, while they tend to overestimate their number and underestimate their intensity. The skill of AGCMs and AOGCMs is generally similar over the African continent and similar to previous global climate model generations. The majority of the AGCMs and AOGCMs greatly overestimate the frequency of intense events, particularly in the tropics, generally fail at simulating the observed intensity, and systematically overestimate their spatial coverage. The RCM performs at least as well as the most accurate global climate model, demonstrating a clear added value to general circulation model simulations and the usefulness of regional modeling for investigating the physics leading to intense events and their change under global warming.     

Carbon and water flux responses to physiology by environment interactions: a sensitivity analysis of variation in climate on photosynthetic and stomatal parameters

Sensitivity of carbon uptake and water use estimates to changes in physiology was determined with a coupled photosynthesis and stomatal conductance (g _s) model, linked to canopy microclimate with a spatially explicit scheme (MAESTRA). The sensitivity analyses were conducted over the range of intraspecific physiology parameter variation observed for Acer rubrum L. and temperate hardwood C₃ (C₃) vegetation across the following climate conditions: carbon dioxide concentration 200–700 ppm, photosynthetically active radiation 50–2,000 μmol m^?2 s^?1, air temperature 5–40 °C, relative humidity 5–95 %, and wind speed at the top of the canopy 1–10 m s^?1. Five key physiological inputs [quantum yield of electron transport (α), minimum stomatal conductance (g ₀), stomatal sensitivity to the marginal water cost of carbon gain (g ₁), maximum rate of electron transport (J _max), and maximum carboxylation rate of Rubisco (V _cmax)] changed carbon and water flux estimates ≥15 % in response to climate gradients; variation in α, J _max, and V _cmax input resulted in up to ~50 and 82 % intraspecific and C₃ photosynthesis estimate output differences respectively. Transpiration estimates were affected up to ~46 and 147 % by differences in intraspecific and C₃ g ₁ and g ₀ values—two parameters previously overlooked in modeling land–atmosphere carbon and water exchange. We show that a variable environment, within a canopy or along a climate gradient, changes the spatial parameter effects of g ₀, g ₁, α, J _max, and V _cmax in photosynthesis-g _s models. Since variation in physiology parameter input effects are dependent on climate, this approach can be used to assess the geographical importance of key physiology model inputs when estimating large scale carbon and water exchange.     

A more accurate scheme for calculating Earth’s skin temperature

The theoretical framework of the vertical discretization of a ground column for calculating Earth’s skin temperature is presented. The suggested discretization is derived from the evenly heat-content discretization with the optimal effective thickness for layer-temperature simulation. For the same level number, the suggested discretization is more accurate in skin temperature as well as surface ground heat flux simulations than those used in some state-of-the-art models. A proposed scheme (“op(3,2,0)”) can reduce the normalized root–mean–square error (or RMSE/STD ratio) of the calculated surface ground heat flux of a cropland site significantly to 2% (or 0.9 W m^?2), from 11% (or 5 W m^?2) by a 5-layer scheme used in ECMWF, from 19% (or 8 W m^?2) by a 5-layer scheme used in ECHAM, and from 74% (or 32 W m^?2) by a single-layer scheme used in the UCLA GCM. Better accuracy can be achieved by including more layers to the vertical discretization. Similar improvements are expected for other locations with different land types since the numerical error is inherited into the models for all the land types. The proposed scheme can be easily implemented into state-of-the-art climate models for the temperature simulation of snow, ice and soil.     

Deep-ocean heat uptake and equilibrium climate response

We integrate the coupled climate model ECHAM5/MPIOM to equilibrium under atmospheric CO₂ quadrupling. The equilibrium global-mean surface-temperature change is 10.8 K. The surface equilibrates within about 1,200 years, the deep ocean within 5,000 years. The impact of the deep ocean on the equilibrium surface-temperature response is illustrated by the difference between ECHAM5/MPIOM and ECHAM5 coupled with slab ocean model (ECHAM5/SOM). The equilibrium global-mean surface temperature response is 11.1 K in ECHAM5/SOM and is thus 0.3 K higher than in ECHAM5/MPIOM. ECHAM5/MPIOM shows less warming over the northern-hemisphere mid and high latitudes, but larger warming over the tropical ocean and especially over the southern-hemisphere high latitudes. ECHAM5/MPIOM shows similar polar amplification in both the Arctic and the Antarctic, in contrast to ECHAM5/SOM, which shows stronger polar amplification in the northern hemisphere. The southern polar warming in ECHAM5/MPIOM is greatly delayed by Antarctic deep-ocean warming due to convective and isopycnal mixing. The equilibrium ocean temperature warming under CO₂ quadrupling is around 8.0 K and is near-uniform with depth. The global-mean steric sea-level rise is 5.8 m in equilibrium; of this, 2.3 m are due to the deep-ocean warming after the surface temperature has almost equilibrated. This result suggests that the surface temperature change is a poor predictor for steric sea-level change in the long term. The effective climate response method described in Gregory et al. (2004) is evaluated with our simulation, which shows that their method to estimate the equilibrium climate response is accurate to within 10 %.     

Future climate in the Pacific Northwest

Climate models used in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) on the whole reproduce the observed seasonal cycle and twentieth century warming trend of 0.8°C (1.5°F) in the Pacific Northwest, and point to much greater warming for the next century. These models project increases in annual temperature of, on average, 1.1°C (2.0°F) by the 2020s, 1.8°C (3.2°F) by the 2040s, and 3.0°C (5.3°F) by the 2080s, compared with the average from 1970 to 1999, averaged across all climate models. Rates of warming range from 0.1°C to 0.6°C (0.2°F to 1.0°F) per decade. Projected changes in annual precipitation, averaged over all models, are small (+1% to +2%), but some models project an enhanced seasonal cycle with changes toward wetter autumns and winters and drier summers. Changes in nearshore sea surface temperatures, though smaller than on land, are likely to substantially exceed interannual variability, but coastal upwelling changes little. Rates of twenty-first century sea level rise will depend on poorly known factors like ice sheet instability in Greenland and Antarctica, and could be as low as twentieth century values (20 cm, 8^″) or as large as 1.3 m (50^″).