1. Introduction
Paleo-proxy records based on pollen assemblages are commonly used to indicate local climate conditions of the past based on the environmental constraints of the pollen producing plants. Given a sufficient network of plant cover information, a picture of climate emerges. This view is necessarily one-sided, with the assumption being that climate determines plant cover. The observed plant cover itself, while in energy balance with local climate, may be forcing climate both locally and remotely through ecoclimate teleconnections (i.e., by changing large-scale thermal and energy gradients and hence atmospheric circulation). As the paleo-proxy records do not provide complete coverage in the spatial domain, we do not have a full picture of climate globally at any time in the past. We suggest that the influence of vegetation on atmospheric circulation patterns can be used to paint a broader view of global climate conditions. Here we show that the remote and local forcing of atmospheric circulation by vegetation leads to different dynamical circulation patterns with consequences for precipitation across the globe. Additionally, by considering ecoclimate teleconnections, knowledge of vegetation cover in one region in the past can lead to additional, testable hypothesis about climate in other parts of the globe.
a. The “Green Sahara” problem
As an example for how vegetation cover can be used to understand climate patterns beyond the region they cover, we will consider here what is called the Green Sahara problem. Paleo-proxy records indicate that North African climate was more humid during the mid-Holocene, approximately 6000 years ago, compared to today (McIntosh and McIntosh 1981; Ritchie et al. 1985; Petit-Maire and Guo 1996). Evidence for wetter conditions across what is now the Sahara desert includes higher paleolake levels (Street and Grove 1979; Street-Perrott and Perrott 1993) and, of particular interest to this study, pollen records indicate that the Sahara desert supported vegetation during the mid-Holocene (Hoelzmann et al. 1998; Joussaume et al. 1999) with Sahel-like vegetation as far north as at least 23°N (Jolly et al. 1998b).
There are two broad categories of mechanisms that have been invoked to explain how the Sahara was capable of maintaining sufficient precipitation for vegetation in the mid-Holocene. First, the orbital forcing in the mid-Holocene was such that Earth was slightly closer to the sun in the Northern Hemisphere summer and farther in the winter compared to the present day (Berger 1978). This leads to an increase in the seasonality of temperature in the Northern Hemisphere with warmer summers and cooler winters as well as a farther northward push of the Hadley circulation during boreal summer (Kutzbach 1981; Braconnot et al. 2007a).
Second, the Charney hypothesis (Charney et al. 1975; Charney 1975) suggests that the contrast in surface albedo between a bright desert and a dark ocean surface maintains an east–west circulation cycle with updraft over the ocean and enhanced downwelling of dry air over the desert. If the Sahara were instead vegetated, the surface would be darker, thus reducing the land–ocean albedo contrast and subsequently the zonal circulation. If the Sahara were somehow vegetated, it might maintain its own precipitation by decreasing the downwelling of dry air relative to the desert state. While Charney was not referring directly to the mid-Holocene green Sahara, his general hypothesis (i.e., local surface albedo controls circulation and precipitation) is central to many arguments describing how what is currently the Sahara desert at one time supported green vegetation.
As we have noted, over the Sahara and present-day Saudi Arabia, green vegetation was more widespread in the mid-Holocene relative to today (e.g., Hoelzmann et al. 1998). In addition to a greener Sahara, vegetation distributions inferred from pollen records show that deciduous forests were widespread in the midlatitudes, especially in Europe (Prentice et al. 1998). Relative to the present day, the distribution of grasslands in Eurasia was reduced, with deciduous forest in its place during the mid-Holocene (Tarasov et al. 1998). In this study we perform a series of experiments to test the climate impact of these two pattern changes in vegetation cover implied by proxy record–based estimates from the mid-Holocene.
A significant body of literature primarily based on modeling techniques has attempted to incorporate and evaluate the effects of orbital forcing, local vegetation changes, and changes in ocean surface temperatures to explain the difference in vegetation distribution between the mid-Holocene and today in the Sahara/Sahel region of Africa (e.g., Joussaume et al. 1995; Kutzbach et al. 1996; Claussen and Gayler 1997; Brovkin et al. 1998; Claussen et al. 1999; Braconnot et al. 2000; Bonfils et al. 2001; Levis et al. 2004; Otto-Bliesner et al. 2006). Studies have also focused on this region during the present day, finding that local vegetation enhances rainfall variability through feedbacks from both evapotranspiration and surface albedo (Zeng et al. 1999).
A northward shift of the intertropical convergence zone (ITCZ) is observed in model experiments of the mid-Holocene due simply to the change in orbital forcing (e.g., Kutzbach 1981). Orbital forcing is insufficient to produce precipitation comparable to estimates from proxy records in many studies; however, simulation of precipitation in the mid-Holocene over North Africa is improved by the inclusion of either interactively coupled vegetation or offline forcing from vegetation (e.g., Claussen et al. 1999). Most importantly, previous work has shown that local decreases in surface albedo properties (e.g., Claussen and Gayler 1997; Bonfils et al. 2001; Levis et al. 2004) are required to reduce the high surface albedo–driven downwelling identified by Charney.
The experiments from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2) and phase 5 of the Coupled Model Intercomparison Project (CMIP5) (Braconnot et al. 2007a,b; Harrison et al. 2013) show some shift in the ITCZ with changes in orbital forcing and, in some cases, dynamic representation of vegetation distributions predicted from climate. However, all of the models from both archives, including models with both static and dynamic vegetation, underestimate the relatively increased precipitation in Afro-Asian monsoon precipitation in the mid-Holocene (Harrison et al. 2013).
In this study we investigate a new mechanism for elevated levels of precipitation over North Africa in the mid-Holocene. We propose that an expansion of Eurasian forest relative to today would cause a northward shift in the Hadley circulation and alter precipitation patterns in the tropics and subtropics. This mechanism has been identified in the present day by Swann et al. (2012); however, during the mid-Holocene, this mechanism can act in combination with both orbital forcing and local changes in vegetation to increase precipitation over North Africa.
b. Remote forcing of precipitation over Africa
It has long been observed that the location of tropical precipitation is highly correlated with sea surface temperatures in the tropics (e.g., Bjerknes 1969; Manabe et al. 1974; Cornejo-Garrido and Stone 1977; Liebmann and Hartmann 1982; Gill and Rasmussen 1983). At low latitudes, nearby ocean surface temperature is thus a big driver of local precipitation. There is, however, emerging evidence in the literature for a midlatitude control on the tropical Hadley circulation (e.g., Chiang and Bitz 2005; Broccoli et al. 2006; Frierson and Hwang 2012; Chiang and Friedman 2012; Hwang et al. 2013), specifically with regards to shifting the latitudinal position of the ITCZ.
Several examples of different types of forcing in the midlatitudes have been shown to influence the Hadley circulation and shift the ITCZ. Theoretical work with an interactive ocean indicates that this tropical response is driven by increased cross-equatorial atmospheric energy transport requirements, requiring an altered Hadley circulation (Kang et al. 2008, 2009). Consistent with this, analysis of nine future climate simulations with slab oceans found that all models shift their ITCZ toward the hemisphere with an increase in energy sources (Frierson and Hwang 2012). The relationship between interhemispheric energy difference and the location of the ITCZ has been shown in coupled models as well (e.g., Broccoli et al. 2006). This mechanism has been invoked to explain a southward ITCZ shift during the Last Glacial Maximum (Chiang and Bitz 2005), the circulation response to anthropogenic aerosol forcing of the Northern Hemisphere in recent decades (Rotstayn et al. 2000; Yoshimori and Broccoli 2008; Hwang et al. 2013), and increases in midlatitude forest cover (Swann et al. 2012). It has also been postulated that this mechanism could be responsible for an abrupt climate change observed at 14.6 kya (1 kya = 103 yr ago; Broecker and Putnam 2013).
Numerous studies have investigated the link between vegetation cover and local climate across the globe (i.e., Kleidon et al. 2000; Bala et al. 2007; Bathiany et al. 2010). Several studies have also investigated the influence that vegetation might have on “remote” locations through changes in atmospheric circulation (e.g., Notaro and Liu 2007; Chen et al. 2012; Ma et al. 2013) and links have been found between changes in tropical forest cover and large-scale climate patterns (Kabat et al. 2004; Avissar and Werth 2005). As mentioned above, there is an extensive literature on the influence of local vegetation on the climate of the mid-Holocene over Africa (e.g., Claussen 2009). Reale and Dirmeyer (2000) also find a displacement of precipitation over Africa related to land use change in the Mediterranean region during the Roman classical period, a few thousand years following the time period of this study.
Swann et al. (2012) was the first to demonstrate a link between midlatitude forest cover and the location of the ITCZ. In their experiments, an increase in midlatitude forest cover in the Northern Hemisphere causes more solar energy to be absorbed at the surface because of the relatively lower albedo of forest versus grass. The expanded forest cover caused the Northern Hemisphere to warm as insufficient soil moisture limited the ability of the surface to shed energy through latent heat flux, instead balancing the surface energy budget through an increase in sensible heat flux and subsequent increase in surface temperature. Later studies using a different climate model have also shown links between future expected vegetation distributions and the location of the ITCZ and the South Asian monsoon (Falloon et al. 2012; McCarthy et al. 2012). We propose here that the influence of midlatitude forests found in Swann et al. (2012) holds in the mid-Holocene as well, and that the expansion of forests in Eurasia is able to enhance a shift in the ITCZ and cross-equatorial energy transport in addition to any changes induced by orbital forcing.
2. Methods
To investigate the role of vegetation changes over Eurasia and the Sahara, we use the National Center for Atmospheric Research (NCAR) Community Atmosphere and Land Models with a carbon cycle and slab ocean (CAM3.5-CLM3.5-CASA′) (Gent et al. 2010; Oleson et al. 2008; Chen et al. 2010). All simulations were also tested with an earlier version of the atmospheric model (CAM3.0-CLM3.5-CASA′) with qualitatively similar results. CAM3.5 uses an updated convective scheme compared with CAM3.0 as described in Chen et al. (2010).
Vegetation in the model interacts with climate through changing stomatal conductance, leaf area, and biomass and hence surface albedo, transpiration, and roughness. The leaf and stem area of vegetation is interactive with climate while the fraction of each grid cell assigned to each plant functional type is fixed for a given simulation. The interactive leaf area of plants in this model can feed back on climate and changes in productivity are explicitly calculated. The slab ocean model has interactive sea surface temperatures as other studies have shown that thermodynamic interaction between the ocean and atmosphere is necessary for allowing shifts in large-scale circulation and precipitation. The slab ocean model also has thermodynamic sea ice.
The version of the model used in this study has been evaluated against observations by Gent et al. (2010) and is found to have improvements over previous versions, particularly in ENSO behavior and monsoon dynamics (Chen et al. 2010). A closely related land model to that used for this study has been extensively tested against observations as part of the Carbon-Land Model Intercomparison Project (Randerson et al. 2009), which created observational benchmarks against which to compare the performance of land surface–carbon cycle models. CAM-CASA′ performs reasonably against observations with the most obvious deficiencies being too little carbon uptake during the growing season in northern biomes and net primary productivity (NPP) estimates that are overall slightly too high. The hydraulic aspects of the land model have additionally been tested against FLUXNET data (Stöckli et al. 2008).
Using this model setup we performed two control simulations and three experiments. In the first experiment, all the midlatitude area in Eurasia (15°W–165°E) between 30° and 60°N currently occupied by either C3 grasses or agriculture is converted to broadleaf deciduous forests [Eurasian vegetation (EV); see also Fig. 1b]. This particular conversion in Eurasia (from grass and crops to forest) is used to simulate the previously forested regions of Eurasia currently occupied by grasslands and agricultural regions. In the second experiment, bare ground over the Sahara desert and Saudi Arabia is converted to grassland [Sahara vegetation (SV); see also Fig. 1a], similar to projections of mid-Holocene vegetation cover (Hoelzmann et al. 1998). In the third experiment these two vegetation changes are imposed simultaneously [Sahara and Eurasia vegetation (SEV)]. In all experiments, the remaining vegetation is left unmodified, as are glaciers and lakes. These experiments are performed for the orbital conditions of the mid-Holocene (MH). The two control runs use present day vegetation cover and represent the orbital conditions of the mid-Holocene (CMH), and the present-day orbital conditions [preindustrial (CPI)]. CO2 levels are held fixed at preindustrial CO2 levels of 280 ppm. A list of control simulations and experiments can be found in Table 1.
Changes to vegetation cover: Patterns of vegetation change imposed in model experiments. (a) Map of new grasses added over the Sahara and Saudi Arabia for SV experiment in percent of grid cell converted. New grasses were added in a pattern similar to Hoelzmann et al. (1998). (b) Map of new deciduous forests added over Eurasia for EV experiment in percent of grid cell converted. New forests were added on agricultural lands and C3 grassland in Europe and Asia between 30° and 60°N. The patterns of vegetation change from (a) and (b) are combined for a third experiment (SEV).
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Summary of simulations. Experiments and control runs shown in this paper are summarized here with the abbreviation, a short description, the vegetation cover imposed, orbital conditions, and CO2 concentrations used in each simulation. The vegetation patterns imposed are shown in Figs. 1a and 1b. Present-day orbital conditions are set to the year 1950, and mid-Holocene orbital conditions are set to 6000 yr before present.
The base value of optical properties for each plant type is specified in the model, but realized surface albedo values in any simulation are interactively calculated as a function of dynamic leaf area, stem area, leaf angle, plant type, snow cover, the moisture content and soil type of bare ground, and other land cover types (lakes and ice). As a general order of magnitude, the albedo of a flat leaf in visible light is 0.1 for broadleaf deciduous trees and 0.11 for both C3 and C4 grasses. Bare soil albedo varies between 0.08 and 0.36 depending on the soil color class and the soil moisture relative to saturation.
The model simulations are integrated for 60 yr, and the results presented are averages of the last 50 yr. The spinup time of 10 years is sufficient to bring climate variables (temperature, precipitation, sea ice cover, snow cover, soil moisture, etc.) into equilibrium. CO2 is held fixed at 280 ppm for the entire 60 yr in all simulations. The spatial resolution of the model uses T42 spectral truncation, which corresponds to approximately 2.8° by 2.8° grid cells, and there are 10 soil layers.
Resulting climate fields are then analyzed by comparing experiments with controls and experiments with one another. Anomalies are calculated as the difference between an experiment (SV, EV, or SEV) and present-day vegetation (CPI or CMH). We focus in particular on two comparisons. The first is between the combined experiment [Saharan grass, Eurasian forests, and orbital forcing (SEVMH)] and the preindustrial control (CPI) where a change in variable ϕ is represented by Δϕ = ϕSEVMH − ϕCPI. The second isolates only the additional added effect of expanded Eurasian forests during the mid-Holocene where we compare SEVMH with SVMH so that Δϕ = ϕSEVMH − ϕSVMH. Statistical significance for Δϕ is determined using a Student’s t test and significance is reported as p values, where a p value of 0.05 indicates that we reject the null hypothesis that the anomaly is zero with 95% confidence. In general we use a significance threshold of 95% but report actual p values and indicate higher significance where possible. We estimate a lagged autocorrelation of 2 years or less for all variables and have used a conservative estimate of 25 degrees of freedom for each 50-yr period.
a. Impact of orbital forcing, Saharan grasslands, and Eurasian forests
An expansion of forests in Eurasia and grasslands in the Sahara during the mid-Holocene relative to today has several remote impacts beyond the region with directly modified vegetation. These include impacts to temperature and precipitation patterns, changes in plant productivity, and changes in atmospheric dynamics and energy transport. We first present results showing changes in climate patterns, and second discuss changes in energy transport and dynamics, which, in some cases, are the proximate cause for changes in climate patterns.
1) Temperature and precipitation
Compared with preindustrial climate, temperatures during the mid-Holocene were generally colder in lower latitudes and higher near the poles (Fig. 2a). This is expected from the orbital forcing differences between approximately 6000 years ago and the present day that led to an increase in the seasonality of temperature in the Northern Hemisphere with warmer summers and cooler winters (Kutzbach 1981; Braconnot et al. 2007a). The combined experiment (SEVMH) shows some aspects of the same low-latitude cooling pattern driven mostly by orbital forcing (Figs. 2a,b), but Eurasian forests have the additional effect of increasing temperatures over the Northern Hemisphere continents (Fig. 2c). Forests were added only to Eurasia in the SEVMH experiment; however, temperatures over North America are also increased (Fig. 2c). The spatial pattern of annual mean temperature change driven by vegetation cover change is consistent across seasons for SEVMH relative to the mid-Holocene control, with pronounced cooling over new grasslands in the Sahara and warming over Northern Hemisphere continental regions (Fig. 3).
Changes to temperature: Change in annually averaged temperature (K) for (a) the mid-Holocene control compared with the preindustrial control (CMH–CPI) showing the effect of orbital forcing; (b) the SEVMH simulation compared with preindustrial control (SEVMH–CPI) showing the combined effect of orbital forcing, grassland in the Sahara, and expanded forests in Europe; and (c) the SEVMH experiment compared with the SVMH experiment (SEVMH–SVMH) showing the isolated additive effect of expanded European forests. A zonal average is shown to the right of each map. Values that do not pass a significance test at 95% confidence have been omitted.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Changes to temperature for SEVMH–CMH: Change in temperature (K) for each of four seasons for the SEVMH simulation compared with the mid-Holocene control (SEVMH–CMH) showing the combined effect of grassland in the Sahara and expanded forests in Europe during the mid-Holocene. The four seasons are (a) DJF, (b) MAM, (c) JJA, and (d) SON. Values that do not pass a significance test at 95% confidence have been omitted.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Precipitation patterns change in the mid-Holocene are due to orbital forcing but are further enhanced by changes in vegetation distributions (Fig. 4). Large changes in precipitation are prominent in tropical regions associated with a northward shift of the ITCZ. The increased seasonality in temperature in the Northern Hemisphere during the mid-Holocene led to summers that were warmer than the present day. For the combined experiment (SEVMH), these warm summers lead to a shift in the precipitation weighted location of the ITCZ (Lintner et al. 2004) of 0.6° northward in August (SEVMH–CPI, p value = 0.04). The shift in the ITCZ can also be seen visually as drying bands to the south of wetting bands (Fig. 4). The shift in ITCZ location is consistent with changes in atmospheric dynamics and energy transport as discussed in section 3 below.
As in Fig. 2, but for changes to precipitation (mm day−1).
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
The spatial pattern of precipitation change driven by vegetation cover change is relatively consistent across seasons for SEVMH relative to the mid-Holocene control (Fig. 5) with a few notable variations. The shift in the ITCZ over the Atlantic migrates north and south with the sun, with the most pronounced drying over northern South America in June–August (JJA; Fig. 5c), and drying in the south of Brazil in March–May (MAM) and September–November (SON; Figs. 5b,d). This is consistent with times when the ITCZ is shifted northward due to the addition of vegetation causing drying. Over the Sahara, wetter conditions are seen in three of four seasons, with local winter showing no significant change [December–February (DJF); Fig. 5a].
As in Fig. 3, but for changes to precipitation (mm day−1) for SEVMH–CMH. Note that the scale on the color bar is different from that in Fig. 4.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
The additional contribution of midlatitude Eurasian forests to precipitation patterns is subtle, but most notably shows a modest, yet statistically significant, increase in precipitation over North Africa (Fig. 4c) and coincident increase in plant productivity (see Fig. 8d). The precipitation increases over North Africa by an average of 26.3% (8 mm yr−1) in the domain 15°–30°N and 0°–30°E (box shown in Fig. 6c) due to the addition of Eurasian forests compared to the Saharan grass only experiment (SEVMH–SVMH; Fig. 7). This suggests that additional Eurasian forest cover relative to today enhances precipitation over the green Sahara, acting in an additive manner beyond other forcing. Precipitation decreases in the storm track off of Asia in the mid-Holocene are also diminished by forests in Eurasia, resulting in little change near the coast compared to the preindustrial (Fig. 4c). Precipitation changes little over the local areas where forests were added in Eurasia.
Changes to precipitation over Africa: Change in annually averaged precipitation (mm day−1) for the (a) the mid-Holocene control compared with the preindustrial control (CMH–CPI) showing the effect of orbital forcing, (b) the SEVMH simulation compared with preindustrial control (SEVMH–CPI) showing the combined effect of orbital forcing, grassland in the Sahara, and expanded forests in Europe, and (c) the SEVMH experiment compared with the SVMH experiment (SEVMH–SVMH) showing the isolated additive effect of expanded European forests. The box drawn in (c) corresponds to the domain 15°–30°N, 0°–30°E and represents the averaging region used in Fig. 7. Values that do not pass a significance test at 95% confidence have been omitted.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Changes to precipitation over Africa: Change in precipitation (mm day−1) averaged over the domain 15°–30°N, 0°–30°E is shown for the annual mean and four seasons; DJF, MAM, JJA, and SON. Each time average is shown for CMH–CPI showing the effect of orbital forcing (red), EVMH–CPI showing the effect of expanded forest cover in Eurasia (green), SVMH–CPI showing the effect of local grassland in the Sahara (brown), SEVMH–CPI showing the combined effect of orbital forcing, grassland in the Sahara, and expanded forests in Europe (blue), and SEVMH–SVMH showing the isolated additive effect of expanded European forests (cyan). The averaging domain is represented by the box in Fig. 6c.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
In the mid-Holocene, proxy records for plant available moisture and estimates of precipitation minus evaporation (P − E) from lake level data indicate that it was generally wetter over much of Africa (e.g., Street-Perrott and Perrott 1993; Hoelzmann et al. 1998; Joussaume et al. 1999). This magnitude of precipitation increase in our model simulations (SEVMH or SVMH) when averaged across the basin is lower than predictions of the excess precipitation needed to maintain steppe vegetation observed to inhabit the region in the mid-Holocene (Jolly et al. 1998a,b; Joussaume et al. 1999), although local increases are sufficiently large (Fig. 6b). As noted above, the additional influence of forests in Eurasia is to further increase precipitation over Africa beyond the change driven by orbital forcing and local grass in the Sahara (Fig. 6c).
2) Plant productivity and teleconnections
The net carbon uptake by plants, or NPP, is lower in the mid-Holocene relative to present day outside of areas where plant cover was purposefully added (Fig. 8). The reduced NPP is driven by a combination of decreases in temperature in the spring and fall seasons, decreases in growing season length, and decreases in regional precipitation patterns with associated changes in soil moisture.
Changes to NPP: Change in net primary production (gC m−2 yr−1) for (a) CMH–CPI isolating the effects of orbital forcing, (b) EVMH–CMH isolating the effects of expanded forests in Eurasia, (c) SVMH–CMH isolating the effects of grass in the Sahara, and (d) SEVMH–SVMH isolating the additive effect of expanded Eurasian forests. Areas where more than 10% of each grid cell was modified as in Fig. 1 are outlined in magenta, although note that this pattern of vegetation change is fully implemented only in (d). Note that (b) has modifications to land cover only in Eurasia and (c) only in Africa and Saudi Arabia. Values that do not pass a significance test at 95% confidence have been omitted.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Productivity increases in the areas where vegetation has been directly added in each experiment including increases in NPP over Eurasia (EVMH; Figs. 8b and 1b) and the Sahara (SVMH; Figs. 8c and 1a). No change in productivity is observed over the Sahara in in either CMH or EVMH as there are no plants designated over the Sahara desert in the present-day vegetation map. We might expect to find that the combined experiment with both grass in the Sahara and forests in Eurasia (SEVMH) to be a near-linear combination of its component experiments, particularly in locations where vegetation was modified, yet we find that Eurasian forests have the additional effect of making the grasslands in the Sahara even more productive—consistent with the increase in precipitation over North Africa (Figs. 6c and 8d). That is to say that there is an additional feedback from Eurasian forests that enhances precipitation over the Sahara, and this feedback operates through shifts in atmospheric dynamics as discussed below.
We find decreases in productivity in eastern North America in response to adding forests in Eurasia (Fig. 8b). The teleconnection to North America is also activated by adding grass in the Sahara (Fig. 8c), but the additional effect of all forcing together shows that Eurasian forests further exacerbate the decrease in NPP (Fig. 8d). Proxy records including lake levels, aeolian deposits, and estimates of precipitation minus evaporation and aridity all show drying across North America at this time (Viau and Gajewski 2001; Forman et al. 2001; Harrison and Prentice 2003) consistent with both the effects of orbital forcing alone and the enhanced decrease in productivity associated with ecoclimate teleconnections from forest cover in Eurasia or grass in the Sahara.
Expanding forests in Eurasia also decreases productivity over the cerrado regions of Brazil (Fig. 8b), while adding grass in the Sahara causes decreases in NPP primarily in southern Brazil (Fig. 8c). Estimates of precipitation in the mid-Holocene over the Amazon are sparse. Proxy observations suggest drier conditions over the southern flank of the Amazon in South America (Prado et al. 2013), with wetter conditions over the Andes (Liu et al. 2004). Charcoal records show a more mixed signal over South America (Power et al. 2008). Ecosystem reconstructions from pollen data suggest a shift to vegetation cover consistent with drier conditions relative to today (Mayle and Power 2008) and the results from our simulations. This decrease in NPP is enhanced in our simulations, particularly over western Brazil, by expanding forest cover in Eurasia (Fig. 8d). Orbitally driven changes in productivity over Brazil are small (Fig. 8a).
3) Atmospheric circulation and dynamics
An expansion of forest in Eurasia and grassland in the Sahara result in a major northward shift in the location of precipitation in the tropics during the mid-Holocene (Fig. 4b). We hypothesize that an increase in energy absorbed by a darker vegetated surface creates an energy imbalance between the two hemispheres, leading to a northward shift in the Hadley circulation and decreased northward flux of energy across the equator to restore energy balance (Fig. 9; see also Chiang and Friedman 2012). A change in energy flux by the atmosphere across the equator then indicates that the shift in circulation has occurred. The anomalous energy flux could occur in the ocean as well, but heat flux by the ocean is held fixed in these simulations.
Forest expansion shifts the Hadley circulation: The diagrams describe the hypothesized mechanism by which the ecoclimate teleconnection acts in this study. (b) The forest expansion case has an increase of midlatitude forests relative to (a) the control vegetation, with trees replacing areas occupied by grass in the present day. The relatively darker expanded forest absorbs additional solar energy (Eabsorbed) leading to an imbalance in energy between the two hemispheres. To restore energy balance the Hadley circulation (represented by blue and red circulation boxes) moves northward in order to increase the cross equatorial transport of energy from north to south (Eflux). The ITCZ (represented by vertical blue dashed lines) follows the location of convergence of air from both hemispheres and is therefore drawn northward with the expansion of tree cover in midlatitudes in (b). This mechanism is presented in Swann et al. (2012) for the present day and proposed by this study to act in the mid-Holocene in response to changes in vegetation patterns between the two time periods.
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Orbital forcing alone leads to an anomalous northward energy flux across the equator in the annual mean. Adding vegetation in the Northern Hemisphere, either in Eurasia alone or the Sahara alone, leads to statistically insignificant changes in cross-equatorial energy flux. However, increasing forest cover in Eurasia combined with grass cover in the Sahara perturbs the annual mean energy balance enough to shift the Hadley circulation southward (Fig. 9). Changes in vegetation cover increase the solar energy absorbed by the surface as the albedo decreases both directly with the addition of vegetation, and indirectly through the relative loss of sea ice at high northern latitudes due to relative increases in temperature. The surface albedo change results in an average of 4.5 W m−2 decrease in net top-of-atmosphere energy flux north of 30°N for the SEVMH experiment (2.4% change from CPI, p value < 0.001). This energy imbalance, with a deficit in the Southern Hemisphere, then requires a northward shift in the Hadley circulation and a corresponding shift in the ITCZ, which is manifested in the change in precipitation patterns (Fig. 4b). Orbital forcing alone does not lead to an annual mean shift in cross equatorial energy flux; however, the addition of forests in Eurasia on top of other forcing (SEVMH) does significantly increase the southward cross equatorial energy flux. The combination of all forcing together (SEVMH) decreases the northward cross equatorial energy flux by more than twice as much as EVMH, reducing the northward flux from 1.8 PW in CPI by approximately 0.054 PW—a change of 3% (Fig. 10, Table 2). In other words, the effect of Eurasian afforestation combined with Saharan grasslands on cross-equatorial energy flux is larger than the linear combination as the combined effect includes feedbacks.
Anomalous northward atmospheric energy transport: Zonally averaged latitudinal profile of the annually averaged anomalous northward energy transport by the atmosphere comparing each experiment against present day vegetation and orbital conditions (CPI). The red dashed line represents the effects of orbital forcing (CMH–CPI), the green dash-dotted line represents the effects of adding grasslands in the Sahara and orbital forcing (SVMH–CPI), the brown line with crosses represents the effects of expanding forests in Eurasia and orbital forcing (EVMH–CPI), and the thick blue line represents the combined effect of both vegetation changes and orbital forcing (SEVMH–CPI).
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
Changes to atmospheric energy transport: Change in annually averaged northward energy flux by the atmosphere at each latitude is shown in each row for an experiment compared against the preindustrial control (CPI). The last row (SEVMH–SVMH) shows the additive effect of expanding forests in Eurasia. Columns show the total change in energy flux (EFlux) in petawatts, the change represented in percent of the preindustrial control flux at the equator, and the p value of significance. Significance at the 99% confidence level or above is indicated by boldface values.
We next quantify the factors that are driving changes in the interhemispheric energy difference. Much of the additional accumulated energy in the Northern Hemisphere in our experiments is coming from a decrease in surface albedo. Calculations using a global radiative kernel allow us to separate the contribution to the top-of-atmosphere net radiative balance between the hemispheres from clouds, water vapor, temperature, and albedo. We find that adding Saharan grasslands leads to less than 0.5 W m−2 energy difference between the hemispheres (SVMH–CMH), primarily from noncloud feedbacks (94.5%) such as surface albedo and enhanced longwave forcing from water vapor (Fig. 11). Expanding Eurasian forests more than doubles the interhemispheric energy difference to 1.1 W m−2 (SEVMH–CMH) with the additional feedback coming about one-third (33.2%) from cloud feedbacks and two-thirds (66.8%) from noncloud feedbacks (Fig. 11). The larger interhemispheric energy difference in the combined experiment is consistent with SEVMH having the largest change in differential energy absorption between the hemispheres (from a decrease in surface albedo due to forest and grassland expansion) and as well as the largest change in both cross-equatorial energy flux and precipitation shift (Figs. 4b and 10). The latitudinal profile of energy flux (Fig. 11) shows that grass in the Sahara leads to a locally increased energy flux from noncloud processes, while Eurasian forests increase the energy flux at local latitudes primarily through cloud processes.
Changes to top-of-atmosphere net energy fluxes: The change in top of atmosphere net radiative flux of energy is shown as a function of latitude for the total flux (thick solid line), contributions from clouds (thin solid line), and contributions from noncloud factors (dashed line) including albedo, longwave and shortwave forcing from water vapor, and changes in temperature. These fluxes are shown for the combined effect of Eurasian forests and Saharan grass (blue lines, SEVMH–CMH) and the additive effect of Eurasian forests in the combined experiment (magenta lines, SEVMH–SVMH). Colored overbars show the latitudes at which grass was added to the Sahara in SEVMH and SVMH (green) and forests were added to Eurasia in SEVMH (brown).
Citation: Journal of Climate 27, 13; 10.1175/JCLI-D-13-00690.1
b. Summary
The research presented here illustrates the concept of ecoclimate teleconnections using the Green Sahara as an example. We discuss how distant vegetation changes can influence both the local climate in a given location, and our plant-derived proxy record of that local climate. We have shown three main consequences of increases in Eurasian forest area during the mid-Holocene relative to today. First, the addition of forest cover in Eurasia and grasses in the Sahara leads to a decrease in surface albedo and consequent increase in energy absorbed into the Northern Hemisphere. This additional energy leads to an imbalance between the hemispheres that persists throughout the year. Second, this energy imbalance leads to a northward shift in the Hadley circulation in order to transport more energy across the equator and a consequent shift in the location of the ITCZ (Fig. 9). This northward shift in the ITCZ gives an added boost to precipitation over North Africa on top of increases from local grass in the Sahara. Third, the shift of the Hadley circulation leads to teleconnections and an impact on plant productivity in eastern North America and central and southern Brazil.
Our underlying explanatory framework is consistent with the emerging hypothesis of ITCZ shifts from altering atmospheric cross-equatorial energy transports (Chiang and Friedman 2012). The results presented here show the response of a single climate model and the dependence of these results on the model itself cannot be ruled out; however, this gross behavior is robust across a number of modeling studies. Quantitatively, however, the strength of the teleconnection may differ from model to model. The response of the carbon cycle and plant productivity through ecoclimate teleconnections has not yet been tested across models in experiments similar to those presented here and represents a new finding of this study.
We propose that an additional forcing, from the remote effects of Eurasian forest cover changes, could help shift the ITCZ northward over Africa and increase precipitation in the Sahara during the mid-Holocene. Given that the change in precipitation from Eurasian forests occurs globally, this new hypothesis is testable by additional information about climate from proxy records around the globe. The work presented here suggests that the interpretation of paleo-proxy records based on plant cover should consider ecoclimate teleconnections—the fact that local vegetation reflects both local climate conditions and may imply global circulation patterns. By considering these ecoclimate teleconnections, knowledge of vegetation cover in one region in the past can lead to additional, testable hypothesis about climate in other parts of the globe.
Acknowledgments
We would like to acknowledge the help of Gordon Bonan and Samuel Levis for assisting us with model setup. Dargan Frierson provided comments and Brian Rose provided helpful discussions. We acknowledge National Science Foundation Awards ATM-0628678 and AGS-1143329 to the University of California, Berkeley, and National Science Foundation Award AGS-1321745 to the University of Washington. This work was partially conducted while A.L.S.S. was a Giorgio Ruffolo Fellow in the Sustainability Science Program at Harvard University, for which support from Italy’s Ministry for Environment, Land and Sea is gratefully acknowledged. Some of the computing resources used in this work were provided by the Climate Simulation Laboratory at NCAR’s Computational and Information Systems Laboratory (CISL), sponsored by the National Science Foundation and other agencies.
REFERENCES
Avissar, R., and D. Werth, 2005: Global hydroclimatological teleconnections resulting from tropical deforestation. J. Hydrometeor., 6, 134–145, doi:10.1175/JHM406.1.
Bala, G., K. Caldeira, M. Wickett, T. Phillips, D. Lobell, C. Delire, and A. Mirin, 2007: Combined climate and carbon-cycle effects of large-scale deforestation. Proc. Natl. Acad. Sci. USA, 104, 6550–6555, doi:10.1073/pnas.0608998104.
Bathiany, S., M. Claussen, V. Brovkin, T. Raddatz, and V. Gayler, 2010: Combined biogeophysical and biogeochemical effects of large-scale forest cover changes in the MPI earth system model. Biogeosciences, 7, 1383–1399, doi:10.5194/bg-7-1383-2010.
Berger, A., 1978: Long-term variations of caloric insolation resulting from the earth’s orbital elements. Quat. Res., 9, 139–167, doi:10.1016/0033-5894(78)90064-9.
Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163–172, doi:10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2.
Bonfils, C., N. de Noblet-Ducoudré, P. Braconnot, and S. Joussaume, 2001: Hot desert albedo and climate change: Mid-Holocene monsoon in North Africa. J. Climate, 14, 3724–3737, doi:10.1175/1520-0442(2001)014<3724:HDAACC>2.0.CO;2.
Braconnot, P., S. Joussaume, and K. Taylor, 2000: Paleoclimate Modeling Intercomparison Project (PMIP). Proceedings of the Third PMIP Workshop, WCRP-111, WMO/TD-1007, 9–24.
Braconnot, P., and Coauthors, 2007a: Results of PMIP2 coupled simulations of the mid-Holocene and Last Glacial Maximum—Part 1: Experiments and large-scale features. Climate Past, 3, 261–277, doi:10.5194/cp-3-261-2007.
Braconnot, P., and Coauthors, 2007b: Results of PMIP2 coupled simulations of the mid-Holocene and Last Glacial Maximum—Part 2: Feedbacks with emphasis on the location of the ITCZ and mid- and high latitudes heat budget. Climate Past, 3, 279–296, doi:10.5194/cp-3-279-2007.
Broccoli, A., K. Dahl, and R. Stouffer, 2006: Response of the ITCZ to Northern Hemisphere cooling. Geophys. Res. Lett.,33, L01702, doi:10.1029/2005GL024546.
Broecker, W. S., and A. E. Putnam, 2013: Hydrologic impacts of past shifts of Earth’s thermal equator offer insight into those to be produced by fossil fuel CO2. Proc. Natl. Acad. Sci. USA,110, 16 710–16 715, doi:10.1073/pnas.1301855110.
Brovkin, V., M. Claussen, V. Petoukhov, and A. Ganopolski, 1998: On the stability of the atmosphere-vegetation system in the Sahara/Sahel region. J. Geophys. Res., 103 (D24), 31 613–31 624, doi:10.1029/1998JD200006.
Charney, J. G., 1975: Dynamics of deserts and drought in Sahel. Quart. J. Roy. Meteor. Soc., 101, 193–202, doi:10.1002/qj.49710142802.
Charney, J. G., P. H. Stone, and W. J. Quirk, 1975: Drought in Sahara: A biogeophysical feedback mechanism. Science, 187, 434–435, doi:10.1126/science.187.4175.434.
Chen, G.-S., M. Notaro, Z. Liu, and Y. Liu, 2012: Simulated local and remote biophysical effects of afforestation over the southeast United States in boreal summer. J. Climate, 25, 4511–4522, doi:10.1175/JCLI-D-11-00317.1.
Chen, H., T. Zhou, R. Neale, X. Wu, and G. Zhang, 2010: Performance of the new NCAR CAM3.5 in East Asian summer monsoon simulations: Sensitivity to modifications of the convection scheme. J. Climate, 23, 3657–3675, doi:10.1175/2010JCLI3022.1.
Chiang, J. C. H., and C. Bitz, 2005: Influence of high latitude ice cover on the marine intertropical convergence zone. Climate Dyn., 25, 477–496, doi:10.1007/s00382-005-0040-5.
Chiang, J. C. H., and A. Friedman, 2012: Extratropical cooling, interhemispheric thermal gradients, and tropical climate change. Annu. Rev. Earth Planet. Sci., 40, 383–412, doi:10.1146/annurev-earth-042711-105545.
Claussen, M., 2009: Late Quaternary vegetation-climate feedbacks. Climate Past, 5, 203–216, doi:10.5194/cp-5-203-2009.
Claussen, M., and V. Gayler, 1997: The greening of the Sahara during the mid-Holocene: Results of an interactive atmosphere-biome model. Global Ecol. Biogeogr. Lett., 6, 369–377, doi:10.2307/2997337.
Claussen, M., C. Kubatzki, V. Brovkin, A. Ganopolski, P. Hoelzmann, and H. Pachur, 1999: Simulation of an abrupt change in Saharan vegetation in the mid-Holocene. Geophys. Res. Lett., 26, 2037–2040, doi:10.1029/1999GL900494.
Cornejo-Garrido, A., and P. Stone, 1977: On the heat balance of the Walker circulation. J. Atmos. Sci., 34, 1155–1162, doi:10.1175/1520-0469(1977)034<1155:OTHBOT>2.0.CO;2.
Falloon, P. D., R. Dankers, R. A. Betts, C. D. Jones, B. B. B. Booth, and F. H. Lambert, 2012: Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system model. Biogeosciences, 9, 4739–4756, doi:10.5194/bg-9-4739-2012.
Forman, S. L., R. Oglesby, and R. S. Webb, 2001: Temporal and spatial patterns of Holocene dune activity on the Great Plains of North America: Megadroughts and climate links. Global Planet. Change, 29, 1–29, doi:10.1016/S0921-8181(00)00092-8.
Frierson, D., and Y. Hwang, 2012: Extratropical influence on ITCZ shifts in slab ocean simulations of global warming. J. Climate, 25, 720–733, doi:10.1175/JCLI-D-11-00116.1.
Gent, P. R., S. G. Yeager, R. B. Neale, S. Levis, and D. A. Bailey, 2010: Improvements in a half degree atmosphere/land version of the CCSM. Climate Dyn., 34, 819–833, doi:10.1007/s00382-009-0614-8.
Gill, A. E., and E. M. Rasmussen, 1983: The 1982–83 climate anomaly in the equatorial Pacific. Nature, 306, 229–234, doi:10.1038/306229a0.
Harrison, S., and C. Prentice, 2003: Climate and CO2 controls on global vegetation distribution at the last glacial maximum: Analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations. Global Change Biol., 9, 983–1004, doi:10.1046/j.1365-2486.2003.00640.x.
Harrison, S., and Coauthors, 2013: Climate model benchmarking with glacial and mid-Holocene climates. Climate Dyn., doi:10.1007/s00382-013-1922-6, in press.
Hartmann, D. L., 1994: Global Physical Climatology. Academic Press, 411 pp.
Hoelzmann, P., D. Jolly, S. Harrison, F. Laarif, R. Bonnefille, and H. Pachur, 1998: Mid-Holocene land-surface conditions in northern Africa and the Arabian Peninsula: A data set for the analysis of biogeophysical feedbacks in the climate system. Global Biogeochem. Cycles, 12, 35–51, doi:10.1029/97GB02733.
Hwang, Y.-T., D. M. W. Frierson, and S. M. Kang, 2013: Anthropogenic sulfate aerosol and the southward shift of tropical precipitation in the late 20th century. Geophys. Res. Lett., 40, 2845–2850, doi:10.1002/grl.50502.
Jolly, D., S. Harrison, B. Damnati, and R. Bonnefille, 1998a: Simulated climate and biomes of Africa during the late quaternary: Comparison with pollen and lake status data. Quat. Sci. Rev., 17, 629–657, doi:10.1016/S0277-3791(98)00015-8.
Jolly, D., and Coauthors, 1998b: Biome reconstruction from pollen and plant macrofossil data for Africa and the Arabian Peninsula at 0 and 6000 years. J. Biogeogr., 25, 1007–1027, doi:10.1046/j.1365-2699.1998.00238.x.
Joussaume, S., K. Taylor, and C. Saclay, 1995: Status of the Paleoclimate Modeling Intercomparison Project. Proc. First International AMIP Scientific Conf., Monterey, CA, WMO, 425–430.
Joussaume, S., and Coauthors, 1999: Monsoon changes for 6000 years ago: Results of 18 simulations from the Paleoclimate Modeling Intercomparison Project (PMIP). Geophys. Res. Lett., 26, 859–862, doi:10.1029/1999GL900126.
Kabat, P., and Coauthors, Eds., 2004: Vegetation, Water, Humans and the Climate. Springer, 566 pp.
Kang, S. M., I. M. Held, D. M. W. Frierson, and M. Zhao, 2008: The response of the ITCZ to extratropical thermal forcing: Idealized slab-ocean experiments with a GCM. J. Climate, 21, 3521–3532, doi:10.1175/2007JCLI2146.1.
Kang, S. M., D. M. W. Frierson, and I. M. Held, 2009: The tropical response to extratropical thermal forcing in an idealized GCM: The importance of radiative feedbacks and convective parameterization. J. Atmos. Sci., 66, 2812–2827, doi:10.1175/2009JAS2924.1.
Kleidon, A., K. Fraedrich, and M. Heimann, 2000: A green planet versus a desert world: Estimating the maximum effect of vegetation on the land surface climate. Climatic Change, 44, 471–493, doi:10.1023/A:1005559518889.
Kutzbach, J., 1981: Monsoon climate of the early Holocene—Climate experiment with the Earth’s orbital parameters for 9000 years ago. Science, 214, 59–61, doi:10.1126/science.214.4516.59.
Kutzbach, J., G. Bonan, J. Foley, and S. Harrison, 1996: Vegetation and soil feedbacks on the response of the African monsoon to orbital forcing in the early to middle Holocene. Nature, 384, 623–626, doi:10.1038/384623a0.
Levis, S., G. B. Bonan, and C. Bonfils, 2004: Soil feedback drives the mid-Holocene North African monsoon northward in fully coupled CCSM2 simulations with a dynamic vegetation model. Climate Dyn., 23, 791–802, doi:10.1007/s00382-004-0477-y.
Liebmann, B., and D. Hartmann, 1982: Interannual variations of outgoing IR associated with tropical circulation changes during 1974–78. J. Atmos. Sci., 39, 1153–1162.
Lintner, B., A. Gilliland, and I. Fung, 2004: Mechanisms of convection-induced modulation of passive tracer interhemispheric transport interannual variability. J. Geophys. Res., 109, D13102, doi:10.1029/2003JD004306.
Liu, Z., S. Harrison, J. Kutzbach, and B. Otto-Bliesner, 2004: Global monsoons in the mid-Holocene and oceanic feedback. Climate Dyn., 22, 157–182, doi:10.1007/s00382-003-0372-y.
Ma, D., M. Notaro, Z. Liu, G. Chen, and Y. Liu, 2013: Simulated impacts of afforestation in East China monsoon region as modulated by ocean variability. Climate Dyn., 41, 2439–2450, doi:10.1007/s00382-012-1592-9.
Manabe, S., D. Hahn, and J. Holloway, 1974: The seasonal variation of the tropical circulation as simulated by a global model of the atmosphere. J. Atmos. Sci., 31, 43–83, doi:10.1175/1520-0469(1974)031<0043:TSVOTT>2.0.CO;2.
Mayle, F. E., and M. J. Power, 2008: Impact of a drier Early-Mid-Holocene climate upon Amazonian forests. Philos. Trans. Roy. Soc. London, 363B, 1829–1838, doi:10.1098/rstb.2007.0019.
McCarthy, M. P., J. Sanjay, B. B. B. Booth, K. Krishna Kumar, and R. A. Betts, 2012: The influence of vegetation on the ITCZ and South Asian monsoon in HadCM3. Earth Syst. Dyn., 3, 87–96, doi:10.5194/esd-3-87-2012.
McIntosh, S., and R. McIntosh, 1981: West African prehistory: Archaeological studies in recent decades have illuminated the prehistory of this vast region, revealing unexpected complexity in its development from 10,000 BC to AD 1000. Amer. Sci., 69,602–613.
Notaro, M., and Z. Liu, 2007: Potential impact of the Eurasian boreal forest on North Pacific climate variability. J. Climate, 20, 981–992, doi:10.1175/JCLI4052.1.
Oleson, K. W., and Coauthors, 2008: Improvements to the Community Land Model and their impact on the hydrological cycle. J. Geophys. Res.,113, G01021, doi:10.1029/2007JG000563.
Otto-Bliesner, B. L., E. C. Brady, G. Clauzet, R. Tomas, S. Levis, and Z. Kothavala, 2006: Last glacial maximum and Holocene climate in CCSM3. J. Climate, 19, 2526–2544, doi:10.1175/JCLI3748.1.
Petit-Maire, N., and Z. Guo, 1996: Mise en évidence de variations climatiques holocènes rapides, en phase dans les déserts actuels de Chine et du Nord de l’Afrique. C. R. Acad. Sci.,322, 847–851.
Power, M. J., and Coauthors, 2008: Changes in fire regimes since the Last Glacial Maximum: An assessment based on a global synthesis and analysis of charcoal data. Climate Dyn., 30, 887–907, doi:10.1007/s00382-007-0334-x.
Prado, L., I. Wainer, C. Chiessi, M.-P. Ledru, and B. Turcq, 2013: A mid-Holocene climate reconstruction for eastern South America. Climate Past, 9, 2117–2133, doi:10.5194/cp-9-2117-2013.
Prentice, I. C., S. Harrison, D. Jolly, and J. Guiot, 1998: The climate and biomes of Europe at 6000 yr BP: Comparison of model simulations and pollen-based reconstructions. Quat. Sci. Rev., 17, 659–668, doi:10.1016/S0277-3791(98)00016-X.
Randerson, J. T., and Coauthors, 2009: Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models. Global Change Biol., 15, 2462–2484, doi:10.1111/j.1365-2486.2009.01912.x.
Reale, O., and P. Dirmeyer, 2000: Modeling the effects of vegetation on Mediterranean climate during the Roman classical period. Part I: Climate history and model sensitivity. Global Planet. Change,25, 163–184, doi:10.1016/S0921-8181(00)00002-3.
Ritchie, J., C. Eyles, and C. Haynes, 1985: Sediment and pollen evidence for an early to mid-Holocene humid period in the eastern Sahara. Nature, 314, 352–355, doi:10.1038/314352a0.
Rotstayn, L., B. Ryan, and J. Penner, 2000: Precipitation changes in a GCM resulting from the indirect effects of anthropogenic aerosols. Geophys. Res. Lett., 27, 3045–3048, doi:10.1029/2000GL011737.
Shell, K. M., J. T. Kiehl, and C. A. Shields, 2008: Using the radiative kernel technique to calculate climate feedbacks in NCAR’s Community Atmospheric Model. J. Climate, 21, 2269–2282, doi:10.1175/2007JCLI2044.1.
Soden, B. J., I. M. Held, R. Colman, K. M. Shell, J. T. Kiehl, and C. A. Shields, 2008: Quantifying climate feedbacks using radiative kernels. J. Climate, 21, 3504–3520, doi:10.1175/2007JCLI2110.1.
Stöckli, R., and Coauthors, 2008: Use of FLUXNET in the Community Land Model development. J. Geophys. Res.,113, G01025, doi:10.1029/2007JG000562.
Street, F., and A. Grove, 1979: Global maps of lake-level fluctuations since 30,000 yr BP. Quat. Res., 12, 83–118, doi:10.1016/0033-5894(79)90092-9.
Street-Perrott, F., and R. Perrott, 1993: Holocene vegetation, lake levels and climate of Africa. Global Climates since the Last Glacial Maximum, University of Minnesota Press, 318–356.
Swann, A. L. S., I. Y. Fung, and J. C. H. Chiang, 2012: Mid-latitude afforestation shifts general circulation and tropical precipitation. Proc. Natl. Acad. Sci. USA, 109, 712–716, doi:10.1073/pnas.1116706108.
Tarasov, P., and Coauthors, 1998: Present-day and mid-Holocene biomes reconstructed from pollen and plant macrofossil data from the former Soviet Union and Mongolia. J. Biogeogr., 25, 1029–1053, doi:10.1046/j.1365-2699.1998.00236.x.
Viau, A., and K. Gajewski, 2001: Holocene variations in the global hydrological cycle quantified by objective gridding of lake level databases. J. Geophys. Res.,106 (D23), 31 703–31 716, doi:10.1029/2000JD000237.
Yoshimori, M., and A. J. Broccoli, 2008: Equilibrium response of an atmosphere-mixed layer ocean model to different radiative forcing agents: Global and zonal mean response. J. Climate, 21, 4399–4423, doi:10.1175/2008JCLI2172.1.
Zeng, N., J. D. Neelin, K.-M. Lau, and C. J. Tucker, 1999: Enhancement of interdecadal climate variability in the Sahel by vegetation interaction. Science, 286, 1537–1540, doi:10.1126/science.286.5444.1537.