How stable are 20th century calibration models? A high-resolution summer temperature reconstruction for the eastern Swiss Alps back to A.D. 1580 derived from proglacial varved sediments

We found a significant positive correlation between local summer air temperature (May-September) and the annual sediment mass accumulation rate (MAR) in Lake Silvaplana (46°N, 9°E, 1800 m a.s.l.) during the twentieth century (r = 0.69, p < 0.001 for decadal smoothed series). Sediment trap data (2001-2005) confirm this relation with exceptionally high particle yields during the hottest summer of the last 140 years in 2003. On this base we developed a decadal-scale summer temperature reconstruction back to AD 1580. Surprisingly, the comparison of our reconstruction with two other independent regional summer temperature reconstructions (based on tree-rings and documentary data) revealed a significant negative correlation for the pre-1900 data (ie, late ‘Little Ice Age’). This demonstrates that the correlation between MAR and summer temperature is not stable in time and the actualistic principle does not apply in this case. We suggest that different climatic regimes (modern/‘Little Ice Age’) lead to changing state conditions in the catchment and thus to considerably different sediment transport mechanisms. Therefore, we calibrated our MAR data with gridded early instrumental temperature series from AD 1760-1880 (r = -0.48, p < 0.01 for decadal smoothed series) to properly reconstruct the late LIA climatic conditions. We found exceptionally low temperatures between AD 1580 and 1610 (0.75°C below twentieth-century mean) and during the late Maunder Minimum from AD 1680 to 1710 (0.5°C below twentieth-century mean). In general, summer temperatures did not experience major negative departures from the twentieth-century mean during the late ‘Little Ice Age’. This compares well with the two existing independent regional reconstructions suggesting that the LIA in the Alps was mainly a phenomenon of the cold season.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Circulation dynamics and its influence on European and Mediterranean January-April climate over the past half millennium: results and insights from instrumental data, documentary evidence and coupled climate models

We use long instrumental temperature series together with available field reconstructions of sea-level pressure (SLP) and three-dimensional climate model simulations to analyze relations between temperature anomalies and atmospheric circulation patterns over much of Europe and the Mediterranean for the late winter/early spring (January–April, JFMA) season. A Canonical Correlation Analysis (CCA) investigates interannual to interdecadal covariability between a new gridded SLP field reconstruction and seven long instrumental temperature series covering the past 250 years. We then present and discuss prominent atmospheric circulation patterns related to anomalous warm and cold JFMA conditions within different European areas spanning the period 1760–2007. Next, using a data assimilation technique, we link gridded SLP data with a climate model (EC-Bilt-Clio) for a better dynamical understanding of the relationship between large scale circulation and European climate. We thus present an alternative approach to reconstruct climate for the pre-instrumental period based on the assimilated model simulations. Furthermore, we present an independent method to extend the dynamic circulation analysis for anomalously cold European JFMA conditions back to the sixteenth century. To this end, we use documentary records that are spatially representative for the long instrumental records and derive, through modern analogs, large-scale SLP, surface temperature and precipitation fields. The skill of the analog method is tested in the virtual world of two three-dimensional climate simulations (ECHO-G and HadCM3). This endeavor offers new possibilities to both constrain climate model into a reconstruction mode (through the assimilation approach) and to better asses documentary data in a quantitative way.

The chironomid-temperature relationship: expression in nature and palaeoenvironmental implications

Fossils of chironomid larvae (non-biting midges) preserved in lake sediments are well-established palaeotemperature indicators which, with the aid of numerical chironomid-based inference models (transfer functions), can provide quantitative estimates of past temperature change. This approach to temperature reconstruction relies on the strong relationship between air and lake surface water temperature and the distribution of individual chironomid taxa (species, species groups, genera) that has been observed in different climate regions (arctic, subarctic, temperate and tropical) in both the Northern and Southern hemisphere. A major complicating factor for the use of chironomids for palaeoclimate reconstruction which increases the uncertainty associated with chironomid-based temperature estimates is that the exact nature of the mechanism responsible for the strong relationship between temperature and chironomid assemblages in lakes remains uncertain. While a number of authors have provided state of the art overviews of fossil chironomid palaeoecology and the use of chironomids for temperature reconstruction, few have focused on examining the ecological basis for this approach. Here, we review the nature of the relationship between chironomids and temperature based on the available ecological evidence. After discussing many of the surveys describing the distribution of chironomid taxa in lake surface sediments in relation to temperature, we also examine evidence from laboratory and field studies exploring the effects of temperature on chironomid physiology, life cycles and behaviour. We show that, even though a direct influence of water temperature on chironomid development, growth and survival is well described, chironomid palaeoclimatology is presently faced with the paradoxical situation that the relationship between chironomid distribution and temperature seems strongest in relatively deep, thermally stratified lakes in temperate and subarctic regions in which the benthic chironomid fauna lives largely decoupled from the direct influence of air and surface water temperature. This finding suggests that indirect effects of temperature on physical and chemical characteristics of lakes play an important role in determining the distribution of lake-living chironomid larvae. However, we also demonstrate that no single indirect mechanism has been identified that can explain the strong relationship between chironomid distribution and temperature in all regions and datasets presently available. This observation contrasts with the previously published hypothesis that climatic effects on lake nutrient status and productivity may be largely responsible for the apparent correlation between chironomid assemblage distribution and temperature. We conclude our review by summarizing the implications of our findings for chironomid-based palaeoclimatology and by pointing towards further avenues of research necessary to improve our mechanistic understanding of the chironomid-temperature relationship.

Ocean acidification limits temperature-induced poleward expansion of coral habitats around Japan

Using results from four coupled global carbon cycle-climate models combined with in situ observations, we estimate the effects of future global warming and ocean acidification on potential habitats for tropical/subtropical and temperate coral communities in the seas around Japan. The suitability of coral habitats is classified on the basis of the currently observed regional ranges for temperature and saturation states with regard to aragonite (Ωarag). We find that, under the "business as usual" SRES A2 scenario, coral habitats are projected to expand northward by several hundred kilometers by the end of this century. At the same time, coral habitats are projected to become sandwiched between regions where the frequency of coral bleaching will increase, and regions where Ωarag will become too low to support sufficiently high calcification rates. As a result, the habitat suitable for tropical/subtropical corals around Japan may be reduced by half by the 2020s to 2030s, and is projected to disappear by the 2030s to 2040s. The habitat suitable for the temperate coral communities is also projected to decrease, although at a less pronounced rate, due to the higher tolerance of temperate corals for low Ωarag. Our study has two important caveats: first, it does not consider the potential adaptation of the coral communities, which would permit them to colonize habitats that are outside their current range. Second, it also does not consider whether or not coral communities can migrate quickly enough to actually occupy newly emerging habitats. As such, our results serve as a baseline for the assessment of the future evolution of coral habitats, but the consideration of important biological and ecological factors and feedbacks will be required to make more accurate projections.

Comparing oxygen transfer performance between three membrane oxygenators: effect of temperature changes during cardiopulmonary bypass

Recently, a new oxygenator (Dideco 903 [D903], Dideco, Mirandola, Italy) has been introduced to the perfusion community, and we set about testing its oxygen transfer performance and then comparing it to two other models. This evaluation was based on the comparison between oxygen transfer slope, gas phase arterial oxygen gradients, degree of blood shunting, maximum oxygen transfer, and diffusing capacity calculated for each membrane. Sixty patients were randomized into three groups of oxygenators (Dideco 703 [D703], Dideco; D903; and Quadrox, Jostra Medizintechnik AG, Hirrlingen, Germany) including 40/20 M/F of 68.6 +/- 11.3 years old, with a body weight of 71.5 +/- 12.1 kg, a body surface area (BSA) of 1.84 +/- 0.3 m(2), and a theoretical blood flow rate (index 2.4 times BSA) of 4.4 +/- 0.7 L/min. The maximum oxygen transfer (VO(2)) values were 313 mL O(2)/min (D703), 579 mL O(2)/min (D903), and 400 mL O(2)/min (Quadrox), with the D903 being the most superior (P < 0.05). Oxygen (O(2)) gradients were 320 mm Hg (D703), 235 mm Hg (D903), and 247 mm Hg (Quadrox), meaning D903 and Quadrox are more efficient versus the D703 (P < 0.05). Shunt fraction (Qs/Qt) and diffusing capacity (DmO(2)) were comparable (P = ns). Diffusing capacity values indexed to BSA (DmO(2)/m(2)) were 0.15 mL O(2)/min/mm Hg/m(2) (D703), 0.2 mL O(2)/min/mm Hg/m(2) (D903), and 0.18 mL O(2)/min/mm Hg/m(2) (Quadrox) with D903 outperforming D703 (P < 0.0005). During hypothermia (32.0 +/- 0.3 degrees C), there was a lower absolute and relative VO(2 )for all three oxygenators (P = ns). The O(2) gradients, DmO(2) and DmO(2)/m(2), were significantly lower for all oxygenators (P < 0.01). Also, Qs/Qt significantly rose for all oxygenators (P < 0.01). The oxygen transfer curve is characteristic to each oxygenator type and represents a tool to quantify oxygenator performance. Using this parameter, we demonstrated significant differences among commercially available oxygenators. However, all three oxygenators are considered to meet the oxygen needs of the patients.

Arctic patterned-ground ecosystems: A synthesis of field studies and models along a North American Arctic Transect

Arctic landscapes have visually striking patterns of small polygons, circles, and hummocks. The linkages between the geophysical and biological components of these systems and their responses to climate changes are not well understood. The "Biocomplexity of Patterned Ground Ecosystems" project examined patterned-ground features (PGFs) in all five Arctic bioclimate subzones along an 1800-km trans-Arctic temperature gradient in northern Alaska and northwestern Canada. This paper provides an overview of the transect to illustrate the trends in climate, PGFs, vegetation, n-factors, soils, active-layer depth, and frost heave along the climate gradient. We emphasize the thermal effects of the vegetation and snow on the heat and water fluxes within patterned-ground systems. Four new modeling approaches build on the theme that vegetation controls microscale soil temperature differences between the centers and margins of the PGFs, and these in turn drive the movement of water, affect the formation of aggradation ice, promote differential soil heave, and regulate a host of system propel-ties that affect the ability of plants to colonize the centers of these features. We conclude with an examination of the possible effects of a climate wan-ning on patterned-ground ecosystems.

Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

Simulating the temperature and precipitation signal in an Alpine ice core

Accumulation and delta O-18 data from Alpine ice cores provide information on past temperature and precipitation. However, their correlation with seasonal or annual mean temperature and precipitation at nearby sites is often low. This is partly due to the irregular sampling of the atmosphere by the ice core (i.e. ice cores almost only record precipitation events and not dry periods) and the possible incongruity between annual layers and calendar years. Using daily meteorological data from a nearby station and reanalyses, we replicate the ice core from the Grenzgletscher (Switzerland, 4200m a.s.l.) on a sample-by-sample basis by calculating precipitation-weighted temperature (PWT) over short intervals. Over the last 15 yr of the ice core record, accumulation and delta O-18 variations can be well reproduced on a sub-seasonal scale. This allows a wiggle-matching approach for defining quasi-annual layers, resulting in high correlations between measured quasi-annual delta O-18 and PWT. Further back in time, the agreement deteriorates. Nevertheless, we find significant correlations over the entire length of the record (1938-1993) of ice core delta O-18 with PWT, but not with annual mean temperature. This is due to the low correlations between PWT and annual mean temperature, a characteristic which in ERA-Interim reanalysis is also found for many other continental mid-to-high-latitude regions. The fact that meteorologically very different years can lead to similar combinations of PWT and accumulation poses limitations to the use of delta O-18 from Alpine ice cores for temperature reconstructions. Rather than for reconstructing annual mean temperature, delta O-18 from Alpine ice cores should be used to reconstruct PWT over quasi-annual periods. This variable is reproducible in reanalysis or climate model data and could thus be assimilated into conventional climate models.

A chrysophyte stomatocyst-based reconstruction of cold-season air temperature from Alpine Lake Silvaplana (AD 1500–2003); methods and concepts for quantitative inferences

Relatively little is known about past cold-season temperature variability in high-Alpine regions because of a lack of natural cold-season temperature proxies as well as under-representation of high-altitude sites in meteorological, early-instrumental and documentary data sources. Recent studies have shown that chrysophyte stomatocysts, or simply cysts (sub-fossil algal remains of Chrysophyceae and Synurophyceae), are among the very few natural proxies that can be used to reconstruct cold-season temperatures. This study presents a quantitative, high-resolution (5-year), cold-season (Oct–May) temperature reconstruction based on sub-fossil chrysophyte stomatocysts in the annually laminated (varved) sediments of high-Alpine Lake Silvaplana, SE Switzerland (1,789 m a.s.l.), since AD 1500. We first explore the method used to translate an ecologically meaningful variable based on a biological proxy into a simple climate variable. A transfer function was applied to reconstruct the ‘date of spring mixing’ from cyst assemblages. Next, statistical regression models were tested to convert the reconstructed ‘dates of spring mixing’ into cold-season surface air temperatures with associated errors. The strengths and weaknesses of this approach are thoroughly tested. One much-debated, basic assumption for reconstructions (‘stationarity’), which states that only the environmental variable of interest has influenced cyst assemblages and the influence of confounding variables is negligible over time, is addressed in detail. Our inferences show that past cold-season air-temperature fluctuations were substantial and larger than those of other temperature reconstructions for Europe and the Alpine region. Interestingly, in this study, recent cold-season temperatures only just exceed those of previous, multi-decadal warm phases since AD 1500. These findings highlight the importance of local studies to assess natural climate variability at high altitudes.

Investigating the consistency between proxy-based reconstructions and climate models using data assimilation: a mid-Holocene case study

The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.

LakeMIP Kivu: evaluating the representation of a large, deep tropical lake by a set of one-dimensional lake models

The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.

Last interglacial temperature evolution — a model inter-comparison

There is a growing number of proxy-based reconstructions detailing the climatic changes that occurred during the last interglacial period (LIG). This period is of special interest, because large parts of the globe were characterized by a warmer-than-present-day climate, making this period an interesting test bed for climate models in light of projected global warming. However, mainly because synchronizing the different palaeoclimatic records is difficult, there is no consensus on a global picture of LIG temperature changes. Here we present the first model inter-comparison of transient simulations covering the LIG period. By comparing the different simulations, we aim at investigating the common signal in the LIG temperature evolution, investigating the main driving forces behind it and at listing the climate feedbacks which cause the most apparent inter-model differences. The model inter-comparison shows a robust Northern Hemisphere July temperature evolution characterized by a maximum between 130–125 ka BP with temperatures 0.3 to 5.3 K above present day. A Southern Hemisphere July temperature maximum, −1.3 to 2.5 K at around 128 ka BP, is only found when changes in the greenhouse gas concentrations are included. The robustness of simulated January temperatures is large in the Southern Hemisphere and the mid-latitudes of the Northern Hemisphere. For these regions maximum January temperature anomalies of respectively −1 to 1.2 K and −0.8 to 2.1 K are simulated for the period after 121 ka BP. In both hemispheres these temperature maxima are in line with the maximum in local summer insolation. In a number of specific regions, a common temperature evolution is not found amongst the models. We show that this is related to feedbacks within the climate system which largely determine the simulated LIG temperature evolution in these regions. Firstly, in the Arctic region, changes in the summer sea-ice cover control the evolution of LIG winter temperatures. Secondly, for the Atlantic region, the Southern Ocean and the North Pacific, possible changes in the characteristics of the Atlantic meridional overturning circulation are crucial. Thirdly, the presence of remnant continental ice from the preceding glacial has shown to be important when determining the timing of maximum LIG warmth in the Northern Hemisphere. Finally, the results reveal that changes in the monsoon regime exert a strong control on the evolution of LIG temperatures over parts of Africa and India. By listing these inter-model differences, we provide a starting point for future proxy-data studies and the sensitivity experiments needed to constrain the climate simulations and to further enhance our understanding of the temperature evolution of the LIG period.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.