Global Climate Model Predictions Research Articles

Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site

Abstract. Complex distributions of aerosol properties evolve in space and time as a function of emissions, new particle formation, coagulation, condensational growth, chemical transformation, phase changes, turbulent mixing and transport, removal processes, and ambient meteorological conditions. The ability of chemical transport models to represent the multi-scale processes affecting the life cycle of aerosols depends on their spatial resolution since aerosol properties are assumed to be constant within a grid cell. Subgrid-scale-dependent processes that affect aerosol populations could have a significant impact on the formation of particles, their growth to cloud condensation nuclei (CCN) sizes, aerosol–cloud interactions, dry deposition and rainout and hence their burdens, lifetimes, and radiative forcing. To address this issue, we characterize subgrid-scale variability in terms of measured aerosol number, size, composition, hygroscopicity, and CCN concentrations made by repeated aircraft flight paths over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystem (HI-SCALE) campaign. Subgrid variability is quantified in terms of both normalized frequency distributions and percentage difference percentiles using grid spacings of 3, 9, 27, and 81 km that represent those typically used by cloud-system-resolving models as well as the current and next-generation climate models. Even though the SGP site is a rural location, surprisingly large horizontal gradients in aerosol properties were frequently observed. For example, 90 % of the 3, 9, and 27 km cell mean organic matter concentrations differed from the 81 km cell around the SGP site by as much as ∼ 46 %, large spatial variability in aerosol number concentrations and size distributions were found during new particle formation events, and consequently 90 % of the 3, 9, and 27 km cell mean CCN number concentrations differed from the 81 km cell mean by as much as ∼ 38 %. The spatial variability varied seasonally for some aerosol properties, with some having larger spatial variability during the spring and others having larger variability during the late summer. While measurements at a single surface site cannot reflect the surrounding variability of aerosol properties at a given time, aircraft measurements that are averaged within an 81 km cell were found to be similar to many, but not all, aerosol properties measured at the ground SGP site. This analysis suggests that it is reasonable to directly compare most ground SGP site aerosol measurements with coarse global climate model predictions. In addition, the variability quantified by the aircraft can be used as an uncertainty range when comparing the surface point measurements with model predictions that use coarse grid spacings.

Toward Regional Marine Ecological Forecasting Using Global Climate Model Predictions From Subseasonal to Decadal Timescales: Bottlenecks and Recommendations

This perspective paper discusses how the research community can promote enhancement of marine ecosystem forecasts using physical ocean conditions predicted by global climate models (GCMs). We review the major climate prediction projects and outline new research opportunities to achieve skillful marine biological forecasts. Physical ocean conditions are operationally predicted for subseasonal to seasonal timescales, and multi-year predictions have been enhanced recently. However, forecasting applications are currently limited by the availability of oceanic data; most subseasonal-to-seasonal prediction projects make only sea-surface temperature (SST) publicly available, though other variables useful for biological forecasts are also calculated in GCMs. To resolve the bottleneck of data availability, we recommend that climate prediction centers increase the range of ocean data available to the public, perhaps starting with an expanded suite of 2-dimensional variables, whose storage requirements are much smaller than 3-dimensional variables. Allowing forecast output to be downloaded for a selected region, rather than the whole globe, would also facilitate uptake. We highlight new research opportunities in both physical forecasting (e.g., new approaches to dynamical and statistical downscaling) and biological forecasting (e.g., conducting biological reforecasting experiments) and offer lessons learned to help guide their development. In order to accelerate this research area, we also suggest establishing case studies (i.e., particular climate and biological events as prediction targets) to improve coordination. Advancing our capacity for marine biological forecasting is crucial for the success of the UN Decade of Ocean Science, for which one of seven desired outcomes is “A Predicted Ocean”.

Aerosol characteristics at the Southern Great Plains site during the HI-SCALE campaign

Abstract. Large uncertainties exist in global climate model predictions of radiative forcing due to insufficient understanding and simplified numerical representation of cloud formation and cloud–aerosol interactions. The Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in north-central Oklahoma to provide a better understanding of land–atmosphere interactions, aerosol and cloud properties, and the influence of aerosol and land–atmosphere interactions on cloud formation. The HI-SCALE campaign consisted of two intensive observational periods (IOPs) (April–May and August–September, 2016), during which coincident measurements were conducted both on the G-1 aircraft platform and at the SGP ground site. In this study we focus on the observations at the SGP ground site. An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton-transfer-reaction mass spectrometer (PTR-MS) were deployed, characterizing chemistry of non-refractory aerosol and trace gases, respectively. Contributions from various aerosol sources, including biogenic and biomass burning emissions, were retrieved using factor analysis of the AMS data. In general, the organic aerosols at the SGP site was highly oxidized, with oxygenated organic aerosol (OOA) identified as the dominant factor for both the spring and summer IOP though more aged in spring. Cases of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) and biomass burning events were further investigated to understand additional sources of organic aerosol. Unlike other regions largely impacted by IEPOX chemistry, the IEPOX SOA at SGP was more highly oxygenated, likely due to the relatively weak local emissions of isoprene. Biogenic emissions appear to largely control the formation of organic aerosol (OA) during the HI-SCALE campaign. Potential HOM (highly oxygenated molecule) chemistry likely contributes to the highly oxygenated feature of aerosols at the SGP site, with impacts on new particle formation and global climate.

Compounding food and income insecurity in Yemen: Challenges from climate change

This paper provides a model-based assessment of local and global climate change impacts for the case of Yemen, focusing on agricultural production, household incomes and food security. Global climate change is mainly transmitted through rising world food prices. Our simulation results suggest that climate change induced price increases for food will raise agricultural GDP while decreasing real household incomes and food security. Rural non-farm households are hit hardest as they tend to be net food consumers with high food budget shares, but farm households also experience real income losses given that many of them are net buyers of food. The impacts of local climate change are less clear given the ambiguous predictions of global climate models (GCMs) with respect to future rainfall patterns in Yemen. Local climate change impacts manifest itself in long term yield changes, which differ between two alternative climate scenarios considered. Under the MIR scenario, agricultural GDP is somewhat higher than with perfect mitigation and rural incomes rise due to higher yields and lower prices for sorghum and millet. Under the CSI scenario, positive and negative yield changes cancel each other out. As a result, agricultural GDP and household incomes hardly change compared to perfect mitigation.

Analysis of Permafrost Thermal Dynamics and Response to Climate Change in the CMIP5 Earth System Models

AbstractThe authors analyze global climate model predictions of soil temperature [from the Coupled Model Intercomparison Project phase 5 (CMIP5) database] to assess the models’ representation of current-climate soil thermal dynamics and their predictions of permafrost thaw during the twenty-first century. The authors compare the models’ predictions with observations of active layer thickness, air temperature, and soil temperature and with theoretically expected relationships between active layer thickness and air temperature annual mean- and seasonal-cycle amplitude. Models show a wide range of current permafrost areas, active layer statistics (cumulative distributions, correlations with mean annual air temperature, and amplitude of seasonal air temperature cycle), and ability to accurately model the coupling between soil and air temperatures at high latitudes. Many of the between-model differences can be traced to differences in the coupling between either near-surface air and shallow soil temperatures or shallow and deeper (1 m) soil temperatures, which in turn reflect differences in snow physics and soil hydrology. The models are compared with observational datasets to benchmark several aspects of the permafrost-relevant physics of the models. The CMIP5 models following multiple representative concentration pathways (RCP) show a wide range of predictions for permafrost loss: 2%–66% for RCP2.6, 15%–87% for RCP4.5, and 30%–99% for RCP8.5. Normalizing the amount of permafrost loss by the amount of high-latitude warming in the RCP4.5 scenario, the models predict an absolute loss of 1.6 ± 0.7 million km2 permafrost per 1°C high-latitude warming, or a fractional loss of 6%–29% °C−1.

Values and Uncertainties in the Predictions of Global Climate Models

Over the last several years, there has been an explosion of interest and attention devoted to the problem of Uncertainty Quantification (UQ) in climate science-that is, to giving quantitative estimates of the degree of uncertainty associated with the predictions of global and regional climate models. The technical challenges associated with this project are formidable, and so the statistical community has understandably devoted itself primarily to overcoming them. But even as these technical challenges are being met, a number of persistent conceptual difficulties remain. So why is UQ so important in climate science? UQ, I would like to argue, is first and foremost a tool for communicating knowledge from experts to policy makers in a way that is meant to be free from the influence of social and ethical values. But the standard ways of using probabilities to separate ethical and social values from scientific practice cannot be applied in a great deal of climate modeling, because the roles of values in creating the models cannot be discerned after the fact-the models are too complex and the result of too much distributed epistemic labor. I argue, therefore, that typical approaches for handling ethical/social values in science do not work well here.

Potential use of a regional climate model in seasonal tropical cyclone activity predictions in the western North Pacific

This study investigates the potential use of a regional climate model in forecasting seasonal tropical cyclone (TC) activity. A modified version of Regional Climate Model Version 3 (RegCM3) is used to examine the ability of the model to simulate TC genesis and landfalling TC tracks for the active TC season in the western North Pacific. In the model, a TC is identified as a vortex satisfying several conditions, including local maximum relative vorticity at 850 hPa with a value ≥450 × 10−6 s−1, and the temperature at 300 hPa being 1°C higher than the average temperature within 15° latitude radius from the TC center. Tracks are traced by following these found vortices. Six-month ensemble (8 members each) simulations are performed for each year from 1982 to 2001 so that the climatology of the model can be compared to the Joint Typhoon Warning Center (JTWC) observed best-track dataset. The 20-year ensemble experiments show that the RegCM3 can be used to simulate vortices with a wind structure and temperature profile similar to those of real TCs. The model also reproduces tracks very similar to those observed with features like genesis in the tropics, recurvature at higher latitudes and landfall/decay. The similarity of the 500-hPa geopotential height patterns between RegCM3 and the European Centre for Medium-Range Weather Forecasts 40 Year Re-analysis (ERA-40) shows that the model can simulate the subtropical high to a large extent. The simulated climatological monthly spatial distributions as well as the interannual variability of TC occurrence are also similar to the JTWC data. These results imply the possibility of producing seasonal forecasts of tropical cyclones using real-time global climate model predictions as boundary conditions for the RegCM3.

Variation in the distribution of ocean shrimp (Pandalus jordani) recruits: links with coastal upwelling and climate change

In this analysis, an atypical northward shift in the distribution of age-1 ocean shrimp (Pandalus jordani) recruits off Oregon in 2000 and 2002–2004 was linked to anomolously strong coastal upwelling winds off southern Oregon (42°N latitude) in April–July of the year of larval release (t−1). This is the first clear evidence that strong upwelling winds can depress local recruitment of ocean shrimp. Regression analysis confirmed a long-term negative correlation between loge of ocean shrimp recruitment and April sea level height (SLH) at Crescent City, California, in the year of larval release, for both northern and southern Oregon waters. The regional pattern of ocean shrimp catches and seasonal upwelling winds showed that, although the timing of the spring transition as reflected in April SLH drives ocean shrimp recruitment success off Oregon generally, the strength and consistency of spring upwelling limits the distribution of large concentrations of ocean shrimp at the southern end of the northern California/Oregon/Washington area. A northward shift in 1999 and 2001–03 in the northern edge of this ‘zone of maximum upwelling’ is the likely cause of the weak southern Oregon recruitment and resulting atypical distribution of ocean shrimp observed off Oregon in 2000 and 2002–04, with a return to a more typical catch distribution as spring upwelling moderated in subsequent years. It is noted that a northward shift in the conditions that produce strong and steady spring upwelling winds is consistent with many predictions of global climate models under conditions of global warming.

Sea Ice in Canada’s Arctic: Implications for Cruise Tourism

Although cruise travel to the Canadian Arctic has grown steadily since 1984, some commentators have suggested that growth in this sector of the tourism industry might accelerate, given the warming effects of climate change that are making formerly remote Canadian Arctic communities more accessible to cruise vessels. Using sea-ice charts from the Canadian Ice Service, we argue that Global Climate Model predictions of an ice-free Arctic as early as 2050–70 may lead to a false sense of optimism regarding the potential exploitation of all Canadian Arctic waters for tourism purposes. This is because climate warming is altering the character and distribution of sea ice, increasing the likelihood of hull-penetrating, high-latitude, multi-year ice that could cause major pitfalls for future navigation in some places in Arctic Canada. These changes may have negative implications for cruise tourism in the Canadian Arctic, and, in particular, for tourist transits through the Northwest Passage and High Arctic regions.

Greenland Ice Sheet Surface Air Temperature Variability: 1840–2007*

Abstract Meteorological station records and regional climate model output are combined to develop a continuous 168-yr (1840–2007) spatial reconstruction of monthly, seasonal, and annual mean Greenland ice sheet near-surface air temperatures. Independent observations are used to assess and compensate for systematic errors in the model output. Uncertainty is quantified using residual nonsystematic error. Spatial and temporal temperature variability is investigated on seasonal and annual time scales. It is found that volcanic cooling episodes are concentrated in winter and along the western ice sheet slope. Interdecadal warming trends coincide with an absence of major volcanic eruptions. Year 2003 was the only year of 1840–2007 with a warm anomaly that exceeds three standard deviations from the 1951–80 base period. The annual whole ice sheet 1919–32 warming trend is 33% greater in magnitude than the 1994–2007 warming. The recent warming was, however, stronger along western Greenland in autumn and southern Greenland in winter. Spring trends marked the 1920s warming onset, while autumn leads the 1994–2007 warming. In contrast to the 1920s warming, the 1994–2007 warming has not surpassed the Northern Hemisphere anomaly. An additional 1.0°–1.5°C of annual mean warming would be needed for Greenland to be in phase with the Northern Hemispheric pattern. Thus, it is expected that the ice sheet melt rates and mass deficit will continue to grow in the early twenty-first century as Greenland’s climate catches up with the Northern Hemisphere warming trend and the Arctic climate warms according to global climate model predictions.

Modeling compensated root water and nutrient uptake

Plant root water and nutrient uptake is one of the most important processes in subsurface unsaturated flow and transport modeling, as root uptake controls actual plant evapotranspiration, water recharge and nutrient leaching to the groundwater, and exerts a major influence on predictions of global climate models. In general, unsaturated models describe root uptake relatively simple. For example, root water uptake is mostly uncompensated and nutrient uptake is simulated assuming that all uptake is passive, through the water uptake pathway only. We present a new compensated root water and nutrient uptake model, implemented in HYDRUS. The so-called root adaptability factor represents a threshold value above which reduced root water or nutrient uptake in water- or nutrient-stressed parts of the root zone is fully compensated for by increased uptake in other soil regions that are less stressed. Using a critical value of the water stress index, water uptake compensation is proportional to the water stress response function. Total root nutrient uptake is determined from the total of active and passive nutrient uptake. The partitioning between passive and active uptake is controlled by the a priori defined concentration value c max. Passive nutrient uptake is simulated by multiplying root water uptake with the dissolved nutrient concentration, for soil solution concentration values below c max. Passive nutrient uptake is thus zero when c max is equal to zero. As the active nutrient uptake is obtained from the difference between plant nutrient demand and passive nutrient uptake (using Michaelis–Menten kinetics), the presented model thus implies that reduced passive nutrient uptake is compensated for by active nutrient uptake. In addition, the proposed root uptake model includes compensation for active nutrient uptake, in a similar way as used for root water uptake. The proposed root water and nutrient uptake model is demonstrated by several hypothetical examples, for plants supplied by water due to capillary rise from groundwater and surface drip irrigation.

Modelling adaptive management strategies for coping with the impacts of climate variability and change on riverine algal blooms

AbstractThe impact of climate change on hydrology and water resources is one of the most critical issues facing the world in the next few decades. In particular, there is a need to quantify the risks associated with maintaining the security of resource quantity and quality, and to assess the effectiveness of potential management strategies. In this paper, we assess the impacts of climate variability and change on one aspect of river health. A simple model of Anabaena algal bloom occurrence at a weir pool in the lower Murrumbidgee River, Australia, has been coupled to a catchment model that is used to simulate streamflow, irrigation demand and diversions, dam water storage and releases, and decision‐making by both irrigators and managers. Long‐term climate data are obtained from a statistical downscaling algorithm, which, when applied to global climate model predictions can provide climate data suitable for driving the coupled model under a variety of climatic scenarios. The coupled model is then used to assess the impact of climate variability and projected climate change on the frequency, duration and magnitude of Anabaena blooms. The impact of two management strategies for bloom control are also assessed and it is shown that even a single, quite simple, resource‐neutral, adaptive management strategy has the potential to substantially reduce the occurrence and impact of algal blooms and to more than compensate for the deleterious impacts of climate change. This result supports the notion that planning for the future can lead to positive outcomes in the present.

Adjustment of CLIGEN parameters to generate precipitation change scenarios in southeastern Australia

Global climate model predictions are often downscaled with stochastic weather generators to produce suitable climate change scenarios for impact analysis. Proportional adjustment to generated daily precipitation and direct adjustment to parameter values for weather generators have been used for assessing the impact of climate change on runoff and soil loss. Little is known of how these parameter values should be realistically adjusted, the amount of adjustment, and whether the adjustments are correlated among different parameters. Rainfall in southeastern Australia has significantly increased since the late 1940s. Rainfall records in Sydney show a similar trend. Long term daily and 6-min intensity data from Sydney have made it possible to examine how CLIGEN parameter values have changed in relation to the underlying significant increase in rainfall. This study shows that for Sydney, most of the increase in rainfall is a result of the increase in wet day precipitation. The increase in the standard deviation of wet-day precipitation is greater than that in the mean, implying a greater rainfall variability during wetter periods. The wet-following-wet transition probability, and maximum 30-min rainfall intensity are all positively and significantly correlated with the change in wet-day precipitation. The change in peak intensity is about half the change in rainfall. No significant relationship can be established between the changes in mean monthly rainfall and those in the skewness coefficient for wet day precipitation and wet following dry transition probability for the site. Simultaneous adjustment of all these parameters is needed for generation of precipitation change scenarios for the region. Using simple proportional adjustment to generated precipitation sequences would lead to maximum impacts on runoff and soil loss predicted with WEPP, while attributing precipitation change equally to the change in wet day precipitation and the number of wet days would under-estimate the magnitude of the impacts considerably for the site.

Modelling the impact of superimposed ice on the mass balance of an Arctic glacier under scenarios of future climate change

AbstractA surface-energy/mass-balance model with an explicit calculation of meltwater refreezing and superimposed ice formation is applied to midre Lovénbreen, Spitsbergen, Svalbard. The model is run with meteorological measurements to represent the present climate, and run with scenarios taken from global climate model predictions based on the IS92a emissions scenario to represent future climates. Model results indicate that superimposed ice accounts for on average 37% of the total net accumulation under present conditions. The model is found to be highly sensitive to changes in the mean annual air temperature and much less sensitive to changes in the total annual precipitation. A 0.5˚C decade–1 temperature increase is predicted to cause an average mass-balance change of –0.43 ma–1, while a 2% decade–1 increase in precipitation will result in only a +0.02 ma–1 change in mass balance. An increase in temperature results in a significant decrease in the size of the accumulation area at midre Lovénbreen and hence a similar decrease in the net volume of superimposed ice. The model predicts, however, that the relative importance of superimposed ice will increase to account for >50% of the total accumulation by 2050. The results show that the refreezing of meltwater and in particular the formation of superimposed ice make an important positive contribution to the mass balance of midre Lovénbreen under present conditions and will play a vital future role in slowing down the response of glacier mass balance to climate change.

Stable Isotopes as Validation Tools for Global Climate Model Predictions of the Impact of Amazonian Deforestation

Abstract This paper examines changes in isotopic abundances for 18O and deuterium in precipitation over the Amazon basin based on data in the Global Network on Isotopes in Precipitation (GNIP) database from the International Atomic Energy Agency (IAEA)/WMO. The analysis is conducted in the context of recent changes (and anticipated future changes) to the land surface hydrology as a result of tropical deforestation. Statistically significant temporal changes (1965–90) in selected stable isotopic signatures in the Amazon have been compared with global climate model (GCM) predictions revealing notable differences. For example, the wet season deuterium excess differences between Belem and Manaus, Brazil, are consistent with recent GCM simulations only if there has been a relative increase in evaporation from nonfractionating water sources over this period. No significant change in dry season isotopic characteristics is found despite earlier predictions that land-use change signals would be found. Results of G...

The correlation between 18O/ 16O ratios of meteoric water and surface temperature: its use in investigating terrestrial climate change over geologic time

Correlations between mean annual temperature (MAT) and the weighted average oxygen isotope composition of yearly precipitation (δ 18O pt) are well-known, but the utility of modern relations to make reliable estimates of temperature change over geological time is uncertain. This question has been addressed by using seasonal subsets of the global data base of temperature and isotopic measurements to represent two different climate modes. A comparison of middle- to high-latitude δ 18O pt/temperature relations for each climate mode reveals (1) a significant offset between them, and (2) a difference in the strength of their correlations. The offset in relations is due to differences in temperature and water vapor budget in the tropics, and can lead to serious underestimates of temperature change. Differences in the strength of correlations arise from the influence of climate mode-specific, non-temperature factors on δ 18O pt. The overall result is that no single relation can be used in all cases to make unambiguous temperature estimates using a temporal record of δ 18O pt values. One way to overcome these problems is to reconstruct δ 18O pt/temperature relations for the time periods being investigated. If an appropriate proxy for δ 18O pt is available, it may also be possible to estimate temperature without relying on δ 18O pt/temperature relations. A promising alternative to these options is to use records of δ 18O pt to test predictions of global climate models, an approach that may allow a reliable and more complete reconstruction to be made of climate change over geologic time.

PIXE investigation of aerosol composition over the Zambian Copperbelt

Atmospheric sulphate aerosol concentrations are of interest in climate change studies because of their negative climate forcing potential. Quantification of their forcing strength requires the compilation of global sulphur emission inventories to determine the magnitude of regional sources. We report on measurements of the ambient aerosol concentrations in proximity to a copper refinery in the central African Copperbelt, along the border of Zambia and the Democratic Republic of the Congo. This region is historically regarded as one of the largest African sources of sulphate aerosols. Sulphate is produced by oxidation in the atmosphere of SO2 emitted during the pyrometallurgical processing of Cu–Co sulphide ores. Since the last quantification of sulphur emissions (late 1960s), there has been large-scale reduction in copper production and more frequent use of the leaching technique with negligible sulphur emissions.Samples were collected over four weeks, November–December 1996, at Kitwe, Zambia. A low volume two-stage time-resolving aerosol sampler (streaker) was used. Coarse and fine mode aerosols were separated at >2.5 and >10 μmad. Hourly elemental concentrations were determined by 3.2 MeV PIXE, and routinely yielded Si, S, K, Ca, Ti, Mn, Fe, Cu and Zn, above detection limits. Si, K, Ca and Fe (major crustal components) dominated the coarse elemental mass. In the fine stage, S and Si accounted for up to 80% of the measured mass, and S alone up to 60%. Time series analysis allowed the division of sulphur and crustal elements (Si, K, Ca, Fe) between (i) background concentrations representative of synoptic scale air masses; and (ii) contributions from local sources, i.e., copper smelter and re-suspended soil dust. Short duration episodes of S concentrations, up to 26 μg/m3, were found simultaneously with enhanced Cu, Fe and Zn. Contributions from individual pyrometallurgic processes and the cobalt slag dump could be distinguished from the elemental signatures. Periods of diminished sulphur concentrations were also identified, indicating a well-mixed regional air mass. These results will contribute towards validating global climate model predictions of aerosol forcing over central Africa.

Feedbacks between climate and boreal forests during the Holocene epoch

PREVIOUS studies1–5 have demonstrated that the predictions of global climate models are highly sensitive to large changes in vegetation cover, such as the complete removal of tropical or boreal forests. Although these studies have illustrated the potential effects of massive deforestation on the climate system, vegetation changes of this scale are very unlikely to occur. Investigating past environments may better illustrate the possible interactions between climate and vegetation cover. For example, palaeobotanical evidence indicates that 6,000 years ago boreal forests extended north of the modern treeline6, apparently in response to high-latitude warming resulting from variations in the Earth's orbit7,8. The expanded boreal forests, which took the place of tundra, must also have affected climate by significantly reducing the surface albedo5. Here we use a global climate model to examine the relative effects of orbitally-induced insolation variations and of the northward extension of boreal forests on the mid-Holocene climate. Orbital variations alone warm the high latitudes by 2 °C or more in summer, autumn and winter. The subsequent northward extension of boreal forests gives rise to an additional warming of approximately 4 °C in spring and about 1 °C in the other seasons. This suggests that large positive feedbacks between climate and boreal forests may have taken place in the recent geological past.