North African Humid Periods over the past 800000 years – Timing, Amplitude and Forcing

doi:10.21203/rs.3.rs-2375224/v1

Download PDF

Article

North African Humid Periods over the past 800000 years – Timing, Amplitude and Forcing

https://doi.org/10.21203/rs.3.rs-2375224/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 08 Sep, 2023

Read the published version in Nature Communications →

Version 1

posted

You are reading this latest preprint version

The Sahara region has experienced periodic wet periods over the Quaternary and beyond. These North African Humid Periods (NAHPs) are astronomically paced by precession which controls the position of the African monsoon system. However, most IPCC-class climate models cannot generate enough precipitation to reconcile the magnitude of these events and so the driving mechanisms remain poorly constrained. Here, we present an 800kyr climate dataset produced using a recently developed version of the HadCM3B coupled climate model that simulates 20 NAHPs over the past 800kyr which have good agreement with the timing and amplitude of NAHPs identified in proxy data. Our results confirm that precession determines their pacing, but we identify that their amplitude is strongly linked to eccentricity via its control over ice sheet extent. During glacials, cooling due to enhanced ice-sheet albedo suppresses the amplitude of the NAHPs during periods of precession minima. Our results highlight the importance of both precession and eccentricity, and the role of high latitude processes in determining the timing and amplitude of the NAHPs. This may have implications for the out of Africa dispersal of plants and animals throughout the Quaternary.

Earth and environmental sciences/Climate sciences/Palaeoclimate

Earth and environmental sciences/Climate sciences/Climate change/Climate and Earth system modelling

Earth and environmental sciences/Climate sciences/Atmospheric science/Atmospheric dynamics

Earth and environmental sciences/Climate sciences/Cryospheric science

Earth and environmental sciences/Ecology/Animal migration

There is widespread palaeoclimatological evidence indicating that the Sahara has experienced wetter periods in the past, with proliferation of vegetation, rivers and lakes into what is now desert^1–16. Currently 230 of these North African humid periods (NAHPs) have been identified in proxy records over the past 8 myr⁸. They were ultimately driven by the precession cycle, with periods of increased boreal summer insolation intensifying the African monsoon system^6,17−21. Internal biogeophysical feedbacks then amplify the external orbital forcing and further enhance precipitation^15,22−25. Although precession is evident in numerous monsoon proxies^12,13,20, some records show gaps at intervals of precession minima termed “skipped beats”¹². These coincide with glacial periods, suggesting that the monsoon response could be modulated by eccentricity and/or obliquity. The glacial boundary conditions, namely CO₂ and the extent and shape of the ice sheets may also influence the African monsoon response to insolation change^26,27. Problematically, most climate models fail to reproduce the precipitation change seen in the Holocene NAHP^28–30. Furthermore studies investigating the role of glacial boundary conditions are not conclusive, with some indicating that the NAHPs are sensitive to ice sheet extent^9,15,18, whereas other conclude that they have little impact^6,19,31. Therefore, our ability to understand the mechanisms of the NAHPs remains poorly constrained.

Here, we address these outstanding research questions using a recently developed version of a coupled general circulation model (HadCM3BB-v1.0, see methods) that enables us to simulate the dynamics and spatial footprint of NAHP events over the past 800kyr. This allows us to clarify the forcings and mechanisms that drive the NAHPs and the skipped beats. Our results show that the NAHPs are paced by precession due to its influence on the West African Monsoon (WAM) and regional jet streams. Glacial CO₂ concentrations do not significantly impact NAHP timing or amplitude. In contrast, we show that extensive ice sheets during glacials suppress NAHPs, this drives the skipped beats and elucidates a high latitude control on the NAHPs. Eccentricity therefore indirectly forces the NAHPs via its control over northern hemisphere glaciation.

Climate models largely fail to reproduce the intensification of NAHP precipitation implied by observations^{28–30,32−35}. This disparity between models and observations has persisted for decades across numerous climate models, and has been linked to misrepresentation of vegetation, ocean and dust feedbacks^24,25,36,37. How these could be reconfigured in models remains unclear^38,39. Instead, recent work has modified convection and land surface parameterisations^40,41. This palaeo-conditioning was shown to markedly improve the simulation of the Holocene NAHP⁴⁰, however it has not been tested beyond this time period.

Here we utilise the HadCM3B coupled climate model⁴² and incorporate the updated atmospheric parameters and vegetation parameterisations identified in Hopcroft, et al. ⁴¹ in order to palaeo-condition the model and constrain NAHP timing and mechanisms over the past 800kyr (methods). The model is herein termed HadCM3BB-v1.0. We performed 219 snapshot simulations with results splined to a continuous timeseries on a 100 year timestep (methods). Although there are limitations to the snapshot approach (supplementary information), it has been shown to accurately simulate millennial palaeoclimate variability⁴³. Moreover, it has advantages over accelerated approaches because it is not distorting the underlying physics. Model validation (supplementary information) confirms that our methodology and HadCM3BB-v1.0 accurately reproduces present day and long-term patterns in global climate. Furthermore, HadCM3BB-v1.0 more accurately simulates mid-Holocene precipitation in the Sahara and other regions, not only relative to HadCM3B, but also against the majority of CMIP6 models²⁹ (Extended Fig. 1).

The timeseries for Saharan precipitation (15N:30°N, -15:35°E; Fig. 1j) indicates 20 NAHPs (Fig. 1i) over the past 800kyr, defined as where precipitation exceeds one standard deviation above the mean (317 mm/yr). In all cases, the timing of the 20 NAHPs correspond to precession minima (Fig. 1a), with 17 possible precession minima periods where the model simulates a ‘skipped beat’, although precipitation still increases during these periods compared to precession maxima (Fig. 1j, Extended Fig. 4). NAHP timing correlates well with those inferred from Mediterranean Sapropels^7,44 and proxy reconstructions of North African humidity², Gulf of Aden leaf-wax isotopes¹³, and west Saharan dust records¹ (Fig. 1d-h).

The average NAHP Saharan precipitation is 410mm/yr (Fig. 1j). This varies spatially (Fig. 2a, Extended Fig. 2), with west Saharan (15:30°N, -15:15°E) average NAHP precipitation of 552mm/yr and maximum amplitude of 763mm/yr (NAHP 6). In contrast there is only marginal increase in North-east Africa and the Arabian Peninsula (Fig. 2a). Precipitation increase occurs contemporaneously in the Western and Eastern Sahara (Extended Fig. 2). The annual increase is dominated by anomalies in the summer months, with a small increase in winter precipitation in the Iberian Peninsula and Western Mediterranean, albeit not to the extent identified in other modelling studies (Extended Fig. 3)^6,18. Proxy evidence for the Holocene NAHP indicates an increase ranging from ~ 400mm/yr (15–30°N, -10:30°E)⁴⁵ to 640mm/yr in the Western Sahara (15-33N, -15:0E)¹⁴. This compares to a modelled 494mm/yr and 584mm/yr for the same regions for 6-11kyr BP.

During the NAHPs, HadCM3BB-v1.0 simulates the proliferation of forest to 18°N, and C4 grasses and shrubs across the central and western Sahara (Fig. 3a). When utilising a specific North African vegetation classification⁸ (Fig. 3b), vegetation thresholds for sparse savannah grassland are estimated to be as little as 100mm/yr, which is also the current lower boundary for Sahelian vegetation⁴⁶. With this classification (Fig. 3b) the modelled NAHP precipitation sustains woodland to approximately 16°N, wooded grassland and grassland across the central and western Sahara, and southward migration of Mediterranean vegetation. Note that during the 17 skipped beats, precipitation increase is still significant enough to support the proliferation of grassland across the Western Sahara (Extended Fig. 4). This may influence proxy records and may be why some West Saharan dust and leaf-wax records indicate almost equally enhanced vegetation and precipitation at each precession minima^1,10,12.

The modelled NAHP amplitude in the North-eastern Sahara (Egypt and N.E. Libya) and the Arabian Peninsula is likely too small (Fig. 2a), with widespread evidence indicating regional river networks and lakes during the NAHPs^47–53. In N.E. Africa, precipitation in the Tibesti mountains (360 mm/yr) and the upper Nile sources (Ethiopia, South Sudan, and southern Sudan) may have been enough to support vegetation growth downstream. However, the Arabian Peninsula poses a more marked conundrum. Modelled precipitation is limited to the south-west (580mm/yr), which deteriorates to < 100mm/yr within the interior. This may be linked to an inaccurate response of the East African or Indian Monsoon systems to insolation change, or to the response of tropical plumes which affect Northern Arabia and may have been important during the NAHPs^54–57. Additionally, Mediterranean storm tracks, which are a key winter regional moisture source^50,58, may be poorly resolved in the model. High-resolution or regional modelling which better resolves these processes^59–61 may reconcile these biases and is a focus of future work.

Our results confirm that precession is the dominant pacemaker of the NAHPs, as verified by wavelet analysis (Fig. 4d). The greater precipitation anomaly in the western Sahara indicates that the WAM is important in driving the modelled NAHPs. Periods of precession-driven increased summer boreal insolation shifts the position of maximum precipitation and the Intertropical Convergence Zone (ITCZ) northward (Fig. 1l, Fig. 2a), and increases the strength of the WAM as indicated by the monsoon index (Fig. 1k).

The WAM is a complex system comprised of several key components (Fig. 2b)^62–64. The summer monsoon, indicated by westerly (positive) zonal wind, extends to 18°N during precession maxima (Fig. 2b). Its northward penetration is dependent on the position of the anticyclonic Saharan Heat Low⁶⁵, atmospheric uplift here is not strong enough to cause precipitation. The rain belt is comprised of upward motion involving deep convection throughout the troposphere. The Sahara is located below the descending branch of the Hadley Cell which forms the sub-tropical westerly jet, this subsidence inhibits convective rainfall. The African and Tropical Easterly Jets form in the middle and top of the troposphere, with the former sustained by dry-northerly and moist-southerly convection^62,66,67. The region between, and to the south in HadCM3BB-v1.0, of the African and Tropical Easterly Jets is characterised by strong uplift which favours precipitation⁶⁸ (Fig. 2b).

Observations indicate that the relationship between the African and Tropical Easterly Jets determines Sahelian rainfall, with a more northerly weaker African Easterly Jet and/or stronger Tropical Easterly Jet associated with increased precipitation and vice versa^67,68. Our results show that this same pattern is apparent during the NAHPs (Fig. 2b), in addition to an enhanced WAM that extends further north. Furthermore, there is northward displacement, strengthening and warming of the sub-tropical westerly jet (Fig. 2b), with a positive mid-tropospheric geopotential height anomaly and increase in relative humidity (Fig. 2c). As a result, the descending air that characterises the sub-tropical westerly jet at precession maxima changes to ascending air during the NAHPs, indicating formation of a jet ridge over the Northern Sahara (Fig. 2b). It is the combined WAM, African/Tropical Easterly Jets, and the sub-tropical westerly jet response which results in increased precipitation during the NAHPs. This initiates vegetation change and enhances biogeophysical feedbacks including evapotranspiration which is dominant in the subtropics and tropics in HadCM3B⁶⁹. This further enhances precipitation.

In addition to precession, a significant eccentricity signal and a weaker intermittent obliquity signal is evident in the wavelet analysis of modelled Saharan precipitation (Fig. 4d). Eccentricity may be present due to modulation of the precession cycle. However, the signal may also highlight the influence of the glacial boundary conditions which fluctuate on these orbital timescales⁷⁰. These forcings may influence the response of the monsoon system to precession and may consequently cause the skipped beats. Past modelling studies that have investigated greenhouse gas and ice sheet forcing on the NAHPs have proved inconclusive. Some show that ice sheets and greenhouse gases had little impact on precession-controlled Saharan precipitation^6,19,31. In contrast, others^9,15,18 showed that glacial ice sheets suppress NAHP formation and that ice sheet retreat is required for initiating an NAHP, implying an ice-sheet determined orbital signal in Saharan precipitation. However these studies used either a lower resolution EMIC^{9,15,18,19,31}, did not simulate a NAHP with significant magnitude⁶, or covered a relatively short temporal timescale^6,9,15,18.

We performed additional sensitivity experiments to evaluate the role of greenhouse gas and ice sheet forcing (Fig. 4a; methods). When incorporating only orbital variations (Orb_Only; Fig. 4a,b), Saharan precipitation is determined primarily by precession with a weaker obliquity signal (Fig. 4b). The absence of an eccentricity signal indicates firstly that precession enhanced precipitation is not directly modulated by eccentricity (i.e. the magnitude of precession minima precipitation is not directly correlated with precession forcing), and secondly that the eccentricity signal is a response to the glacial boundary conditions. The addition of greenhouse gas forcing (Orb_GHG; Fig. 4a, 4c) has only a small impact on the amplitude and variability of Saharan precipitation. It is therefore the addition of the ice sheets (NAHP_All, Figs. 1j, 4a, 4d) that produces the strong eccentricity signal in Saharan precipitation and generates the ‘skipped beats’ in the NAHPs. During glacial periods, extensive ice sheets suppress precession-induced precipitation change in the Sahara. Ice sheet volume is determined by eccentricity (Extended Fig. 5)⁷⁰ and therefore eccentricity indirectly forces the NAHPs via its influence on the ice sheets.

O'Mara, et al. ¹⁰ concluded that obliquity was a dominant control on NAHPs between MIS 10 and 13. Our modelled results indicate that obliquity does have a significant influence on Saharan precipitation during MIS 10–12 (Fig. 3f). However, its longer-term influence over the past 800kyr is secondary to precession and eccentricity. We also do not see a relationship between AMOC strength and NAHP amplitude as identified in Menviel, et al. ⁹. Furthermore, the important influence of ice sheets on NAHP amplitude, and uncertainties regarding their extent, growth and decay phases⁷¹, may explain the few inconsistences between the modelled NAHPs and the observations as labelled in Fig. 1i.

Now that we have shown the key role of the ice sheets in controlling NAHP amplitude, we need to identify how they suppress the NAHPs. Studies that have investigated the influence of ice sheets on monsoon evolution^72–74 identify both a thermodynamic and topographic impact. The former reflects albedo change, which alters absorbed insolation and consequently atmospheric and oceanic temperatures. For example sea surface temperatures have long been implicated in the extent of Sahelian precipitation due to their control on the land-sea thermal contrast and WAM strength^75–78. The topographic impact reflects ice sheet elevation, which influences synoptic scale wind patterns.

During glacial precession minima the ice sheets cool the atmosphere, weaken the WAM and cause the sub-tropical westerly jet to descend which inhibits precipitation (Extended Fig. 6), similar to periods of precession maxima (Fig. 2b). Using the atmosphere-only version of our model (HadAM3BB-v1.0; methods), we identify that this response is primarily due to the thermodynamic impact of the ice sheet. This is dominated by the atmospheric response to albedo change, with a smaller contribution from sea surface temperature changes (Extended Fig. 7; supplementary information). During glacials, the increase in albedo and resultant colder atmosphere acts to weaken the WAM, and results in a more southerly, weaker, colder and descending sub-tropical westerly jet, indicative of a jet trough which inhibits convective precipitation (Extended Fig. 6). This is similar to the precession maxima mechanism. The glacial SSTs reduce precipitation by weakening the WAM and shifting the position of the African/Tropical Easterly Jets (Extended Fig. 6; supplementary information). It is therefore a combination of the sea surface temperature and atmospheric response to albedo change that is the primary mechanism by which ice sheets suppress NAHPs during precession minima.

In summary, the ability of the HadCM3BB-v1.0 model to accurately simulate the timing and amplitude of the NAHPs in Western Africa confirms that palaeo-conditioning a model can improve palaeo-hydrographic modelling in this region throughout the late Quaternary. The NAHPs were predominantly paced by precession and, in the west, by its influence on the WAM and sub-tropical westerly jet. Our results show that during glacials, expansive ice sheets suppressed NAHP formation predominantly due to the impact of glacial albedo change, thus highlighting the role of high latitude processes in determining the timing and amplitude of the NAHPs. The ability to model NAHPs is important for understanding climate dynamics past and future, and enables the opportunity to study in much more detail the role of the Sahara as a factor controlling the dispersal of plants and animals, including humans, and the consequent movement of genetic and cultural information within and out of Africa.

HadCM3B Model

The Hadley Centre Coupled Model 3 Bristol (HadCM3B) is a coupled climate model that consists of a 3d dynamical atmospheric component with a resolution of 2.5°x3.75°, 19 vertical levels, and a 30 minute timestep⁷⁹, and an ocean model with a resolution of 1.25°x1.25°, 20 vertical levels and a 1 hour timestep⁸⁰. Levels have a finer resolution towards the Earth surface. The model is a variant of HadCM3 that has been developed at the University of Bristol, and is described in detailed in Valdes, et al. ⁴². Despite its relative old age, the model has been shown to accurately simulate the climate system and remains competitive with more modern climate models. A key advantage of the model is its computationally efficient, which permits long simulations and large ensemble studies. We also utilise the atmosphere only version of the model; HadAM3B⁴². This incorporates the same atmospheric component as HadCM3B but with prescribed sea-surface temperatures (SSTs).

The model incorporates the Met Office Surface Exchange Scheme (MOSES) version 2.1⁸¹ which simulates water and energy fluxes and physiological processes such as photosynthesis, transpiration and respiration which is determined by stomatal conductance and consequently CO2 concentration. The fractional coverage of nine surface types are incorporated by MOSES 2.1 and simulated by the dynamic global vegetation model (DGVM) TRIFFID. Of the nine surface types, five are plant functional types (PFTs); deciduous and needleleaf trees, C3 and C4 grasses, shrubs, with the residual assigned to bare soil. Vegetation evolves throughout a model simulation depending on temperature, moisture, CO₂ and competition with other PFTs. HadCM3B does not include an interactive carbon/methane cycle or ice model, so these boundary conditions have been imposed as discussed below.

Palaeoconditioning

The update to the atmospheric and vegetation parameters follows the work of Hopcroft, et al. ⁴¹⁴⁰. The most important change was to modify the vertical profile of convective entrainment and detrainment, decreasing the entrainment rate near the surface and increasing the entrainment rate higher up in the atmosphere globally. This resulted in greater mixing between convective plumes and the environment in the upper troposphere relative to the lower troposphere increasing the precipitation response from African Easterly Wave events. Hopcroft, et al. ⁴¹ showed that this permitted the model to more accurately simulate mid-Holocene greening of the Sahara. At the same time, it did not adversely influence present day climate simulations. The moisture stress function of vegetation was also altered to be linear in soil moisture potential rather than soil moisture, and then optimised to reproduce vegetation cover-climate relationships for the present day and the mid-Holocene⁴⁰. Together these updates allow a dynamic simulation of the Holocene greening of the Sahara that shows many similarities with the reconstructions of this time period⁸², including a more gradual and later desertification in the East and South of the Sahara and a centennial-scale transition over North Western Sahara.

The palaeo-condition model has not been tested for periods beyond the mid-Holocene. Here, we incorporate the changes described above into HadCM3B, the updated model configuration is termed HadCM3BB-v1.0.

Boundary Conditions

The simulations have been forced with well constrained orbital parameters⁸³ and greenhouse gas concentrations (CO₂, N₂O and CH₄) taken from the Vostok Ice core^84,85.

The extent and elevation of the Antarctic, Greenland, North American and Fennoscandian ice sheets has been imposed utilising the reconstruction of de Boer, et al. ⁸⁶. This provides ice extent and thickness which are used within the model to calculate continental elevation (depending on ice thickness and isostatic rebound), bathymetry, ice-sheet extent, and consequently the land-sea mask. There remain uncertainties regarding Ice sheet reconstruction beyond the LGM, in part due to poor preservation following the last deglaciation. Although the ice area might be approximated based on sea-level data, uncertainties remain associated with ice sheet structure during growth and decay phases. As stated in the text, this may cause uncertainty regarding the suppression of some the NAHP events and be the reason for inconsistencies between the model and observations.

Snapshot Experiments

The boundary conditions have been incorporated into 219 snapshot experiments covering 0kyr BP (corresponding to the year 1950 albeit with pre-industrial GHG concentrations) to 800kyr BP. These are set at 1kyr intervals for 0-24kyr BP and 4kyr intervals to for 24-800kyr BP. Each simulation has been run for 500 years with analysis conducted on the final 50 years of each simulation unless stated otherwise. This spin-up permits the atmosphere and surface ocean to reach a state of near equilibrium. This approach allows the simulations to be run simultaneously and is therefore very efficient.

The snapshot climatologies were then splined to a 100-yr timeseries for all variables used in the study, including the land sea mask and ice fraction (subsequently rounded to 0 or 100% coverage in any grid cell). Splining has been done using the ftcurv function of the NCAR command language (NCL)⁸⁷ which utilises spline under tension. This is the same methodology outlined in Armstrong, et al. ⁴³. The timeseries data was then bilinearly interpolated to 1° resolution for surface variables. There has been no bias correction applied to the data in this study.

Boundary Condition Sensitivity Experiments

In order to identify the contributing role of three forcing factors on the NAHPs; orbital variations, GHGs and ice sheets, we performed two additional sets of snapshot experiments (2x 219 simulations) using HadCM3BB-v1.0. The original set of snapshot simulations incorporate all three forcings (as discussed above) and is termed NAHP_All. In order to identify just the orbital forcing, the simulations were re-run with varying orbital parameters, but with constant pre-industrial GHGs (CO₂ − 280ppm, CH₄ – 760ppbv, and N₂O – 270ppbv) and ice sheet extent and elevation, this is termed Orb_Only. The third set of snapshot simulations incorporates both orbital and GHG forcing, with constant pre-industrial ice sheets, termed Orb_GHG.

The snapshot climatologies were similarly splined to a 100-yr timeseries and bilinearly interpolated to 1° resolution for surface variables.

Topographic Vs. Thermodynamic Ice-sheet Sensitivity Experiments

In order to resolve the topographic vs thermodynamic contribution of the ice sheets to the suppression of the NAHPs during precession minima, we have used the atmosphere-only version of the model (HadAM3B⁴²) and incorporated the updates described above (HadAM3BB-v1.0). We have run the model controlling for SSTs, ice sheet elevation, and ice sheet albedo.

Due to computational limitations, we have not rerun the whole suite of snapshot simulations. Instead, we have performed a set of singular snapshot experiments corresponding to where the impact of the ice sheet is shown to have a significant suppressing effect on the amplitude of precession minima induced Saharan precipitation. We identify the eighth precession minima, corresponding to 176Kyr BP, as where ice sheet extent suppresses precipitation the greatest amount, from ~ 510mm/yr for Orb_Only/Orb_GHG to 205mm/yr for NAHP_All (Fig. 4a). As the 176kyr BP precipitation is equivalent for both Orb_Only and Orb_GHG, and because we only want to compare the impact of the ice sheet (rather than any possible impact of GHGs), we utilise input from the Orb_GHG experiment. We assume that our findings for this time period are consistent for all the suppressed NAHPs during glacials.

The first experiment is the control HadAM3BB-v1.0 simulation (termed ‘Control’). This incorporates the boundary conditions and SST input from the 176kyr NAHP_All snapshot experiment. The climatology is therefore very similar to the 176kyr BP HadCM3BB-v1.0 NAHP_All experiment (supplementary information). In order to isolate the thermodynamic impact of SSTs, we have run HadAM3BB-v1.0 with 176kyr boundary conditions, but with SSTs prescribed from the 176kyr Orb_GHG snapshot simulation, termed ‘glacial_noSST’. This simulation therefore has glacial forcings except for SSTs. To identify the thermodynamic impact of ice sheet albedo, we have run HadAM3BB-v1.0 with 176kyr boundary conditions including SSTs, but with ice sheet albedo from the 176kyr Orb_GHG experiment (this is equivalent to PI ice sheet albedo). This is termed ‘glacial_noAlb’. This simulation therefore has glacial forcings except for non-glacial (PI) surface albedo. SSTs are fixed throughout the simulation so the albedo change will only impact the atmosphere. Note however that this is not a clean comparison because the height of the ice sheet will cause it to snow, so there will be a contribution from albedo in some locations. To identify the topographic impact of the ice sheet, we have run HadAM3BB-v1.0 with 176kyr boundary conditions, but with ice sheet topography from the 176kyr Orb_GHG experiment (this is equivalent to PI ice sheet topography). This is termed ‘glacial_noTopo’. This simulation has glacial forcings except for non-glacial (PI) topography. Each simulation was run for 200 years and analysis conducted on the final 30 years. An analysis of these simulations is provided in the Supplementary.

Data Availability

A total of 661 model simulations were performed for this study. The raw model output and an overview of all the simulations is available at

https://www.paleo.bristol.ac.uk/ummodel/scripts/papers/Armstrong_et_al_2022.html

Code Availability

All scripts used to analyse the data and produce the Figures have been written using the NCAR command language (NCL, Version 6.4.0) and are available on request

Crocker, A. J. et al. Astronomically controlled aridity in the Sahara since at least 11 million years ago. Nature Geoscience 15, 671-+, doi:10.1038/s41561-022-00990-7 (2022).
Grant, K. M. et al. A 3 million year index for North African humidity/aridity and the implication of potential pan-African Humid periods. Quaternary Science Reviews 171, 100–118, doi:10.1016/j.quascirev.2017.07.005 (2017).
Hely, C., Lezine, A. M. & Contributors, A. P. D. Holocene changes in African vegetation: tradeoff between climate and water availability. Climate of the Past 10, 681–686, doi:10.5194/cp-10-681-2014 (2014).
Hoffmann, D. L. et al. Timing and causes of North African wet phases during the last glacial period and implications for modern human migration. Scientific Reports 6, 36367, doi:10.1038/srep36367 (2016).
Jennings, R. P. et al. The greening of Arabia: Multiple opportunities for human occupation of the Arabian Peninsula during the Late Pleistocene inferred from an ensemble of climate model simulations. Quaternary International 382, 181–199, doi:10.1016/j.quaint.2015.01.006 (2015).
Kutzbach, J. E. et al. African climate response to orbital and glacial forcing in 140,000-y simulation with implications for early modern human environments. Proceedings of the National Academy of Sciences of the United States of America 117, 2255–2264, doi:10.1073/pnas.1917673117 (2020).
Larrasoaña, J. C. A review of West African monsoon penetration during Green Sahara periods; implications for human evolution and dispersals over the last three million years. Oxford Open Climate Change 1, doi:10.1093/oxfclm/kgab011 (2021).
Larrasoaña, J. C., Roberts, A. P. & Rohling, E. J. Dynamics of Green Sahara Periods and Their Role in Hominin Evolution. PLoS ONE 8, e76514, doi:10.1371/journal.pone.0076514 (2013).
Menviel, L. et al. Drivers of the evolution and amplitude of African Humid Periods. Communications Earth & Environment 2, doi:10.1038/s43247-021-00309-1 (2021).
O'Mara, N. A. et al. Pleistocene drivers of Northwest African hydroclimate and vegetation. Nature Communications 13, doi:10.1038/s41467-022-31120-x (2022).
Pausata, F. S. R. et al. The Greening of the Sahara: Past Changes and Future Implications. One Earth 2, 235–250, doi:10.1016/j.oneear.2020.03.002 (2020).
Skonieczny, C. et al. Monsoon-driven Saharan dust variability over the past 240,000 years. Sci Adv 5, doi:10.1126/sciadv.aav1887 (2019).
Tierney, J. E., deMenocal, P. B. & Zander, P. D. A climatic context for the out-of-Africa migration. Geology 45, 1023–1026, doi:10.1130/g39457.1 (2017).
Tierney, J. E., Pausata, F. S. R. & deMenocal, P. B. Rainfall regimes of the Green Sahara. Sci Adv 3, e1601503-e1601503, doi:10.1126/sciadv.1601503 (2017).
Timm, O., Kohler, P., Timmermann, A. & Menviel, L. Mechanisms for the Onset of the African Humid Period and Sahara Greening 14.5–11 ka BP. Journal of Climate 23, 2612–2633, doi:10.1175/2010jcli3217.1 (2010).
Claussen, M., Dallmeyer, A. & Bader, J. in Oxford Research Encyclopedia of Climate Science (Oxford University Press, 2017).
Timmermann, A., Lorenz, S. J., An, S.-I., Clement, A. & Xie, S.-P. The effect of orbital forcing on the mean climate and variability of the tropical Pacific. 20, 4147–4159 (2007).
Blanchet, C. L. et al. Drivers of river reactivation in North Africa during the last glacial cycle. Nature Geoscience 14, 97–103, doi:10.1038/s41561-020-00671-3 (2021).
Duque-Villegas, M., Claussen, M., Brovkin, V. & Kleinen, T. Effects of orbital forcing, greenhouse gases and ice sheets on Saharan greening in past and future multi-millennia. Climate of the Past 18, 1897–1914, doi:10.5194/cp-18-1897-2022 (2022).
Ziegler, M., Tuenter, E. & Lourens, L. J. The precession phase of the boreal summer monsoon as viewed from the eastern Mediterranean (ODP Site 968). Quaternary Science Reviews 29, 1481–1490, doi:10.1016/j.quascirev.2010.03.011 (2010).
DeMenocal, P. B. & Tierney, J. E. Green Sahara: African humid periods paced by Earth’s orbital changes. Nature Education Knowledge 3, 12 (2012).
Levis, S., Bonan, G. B. & Bonfils, C. Vol. 23 791–802 (2004).
Brovkin, V., Claussen, M., Petoukhov, V. & Ganopolski, A. On the stability of the atmosphere-vegetation system in the Sahara/Sahel region. Journal of Geophysical Research: Atmospheres 103, 31613–31624, doi:10.1029/1998jd200006 (1998).
Kutzbach, J., Bonan, G., Foley, J. & Harrison, S. P. 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 (1996).
Chandan, D. & Peltier, W. R. African Humid Period Precipitation Sustained by Robust Vegetation, Soil, and Lake Feedbacks. Geophysical Research Letters 47, doi:10.1029/2020gl088728 (2020).
Claussen, M., Brovkin, V., Ganopolski, A., Kubatzki, C. & Petoukhov, V. Climate Change in Northern Africa: The Past is Not the Future. Climatic Change 57, 99–118, doi:10.1023/a:1022115604225 (2003).
Marzin, C., Braconnot, P. & Kageyama, M. Relative impacts of insolation changes, meltwater fluxes and ice sheets on African and Asian monsoons during the Holocene. Climate Dynamics 41, 2267–2286, doi:10.1007/s00382-013-1948-9 (2013).
Harrison, S. P. et al. Evaluation of CMIP5 palaeo-simulations to improve climate projections. Nature Climate Change 5, 735–743, doi:10.1038/nclimate2649 (2015).
Brierley, C. M. et al. Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations. Climate of the Past 16, 1847–1872, doi:10.5194/cp-16-1847-2020 (2020).
Harrison, S. P. et al. Climate model benchmarking with glacial and mid-Holocene climates. Climate Dynamics 43, 671–688, doi:10.1007/s00382-013-1922-6 (2014).
Weber, S. L. & Tuenter, E. The impact of varying ice sheets and greenhouse gases on the intensity and timing of boreal summer monsoons. Quaternary Science Reviews 30, 469–479, doi:10.1016/j.quascirev.2010.12.009 (2011).
Braconnot, P. et al. Evaluation of climate models using palaeoclimatic data. Nature Climate Change 2, 417–424, doi:10.1038/nclimate1456 (2012).
Otto-Bliesner, B. L. et al. Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)-Paleoclimate Modeling Intercomparison Project (PMIP4). Climate of the Past 17, 63–94, doi:10.5194/cp-17-63-2021 (2021).
Biasutti, M. et al. Global energetics and local physics as drivers of past, present and future monsoons. Nature Geoscience 11, 392-+, doi:10.1038/s41561-018-0137-1 (2018).
Perez-Sanz, A., Li, G., Gonzalez-Samperiz, P. & Harrison, S. P. Evaluation of modern and mid-Holocene seasonal precipitation of the Mediterranean and northern Africa in the CMIP5 simulations. Climate of the Past 10, 551–568, doi:10.5194/cp-10-551-2014 (2014).
Braconnot, P., Joussaume, S., Marti, O. & de Noblet, N. Synergistic feedbacks from ocean and vegetation on the African monsoon response to mid-Holocene insolation. Geophysical Research Letters 26, 2481–2484, doi:10.1029/1999gl006047 (1999).
Pausata, F. S. R., Messori, G. & Zhang, Q. Impacts of dust reduction on the northward expansion of the African monsoon during the Green Sahara period. Earth and Planetary Science Letters 434, 298–307, doi:10.1016/j.epsl.2015.11.049 (2016).
Chen, W. Z. et al. Feedbacks of soil properties on vegetation during the Green Sahara period. Quaternary Science Reviews 240, doi:10.1016/j.quascirev.2020.106389 (2020).
Hopcroft, P. O., Valdes, P. J., Harper, A. B. & Beerling, D. J. Multi vegetation model evaluation of the Green Sahara climate regime. Geophysical Research Letters 44, 6804–6813, doi:10.1002/2017gl073740 (2017).
Hopcroft, P. O. & Valdes, P. J. Paleoclimate-conditioning reveals a North Africa land–atmosphere tipping point. Proceedings of the National Academy of Sciences 118, e2108783118, doi:10.1073/pnas.2108783118 (2021).
Hopcroft, P. O., Valdes, P. J. & Ingram, W. Using the Mid-Holocene “Greening” of the Sahara to Narrow Acceptable Ranges on Climate Model Parameters. Geophysical Research Letters 48, doi:10.1029/2020gl092043 (2021).
Valdes, P. J. et al. The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0. Geoscientific Model Development 10, 3715–3743, doi:10.5194/gmd-10-3715-2017 (2017).
Armstrong, E., Hopcroft, P. O. & Valdes, P. J. A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years. Scientific Data 6, doi:10.1038/s41597-019-0277-1 (2019).
Emeis, K. C., Sakamoto, T., Wehausen, R. & Brumsack, H. J. The sapropel record of the eastern Mediterranean Sea - results of Ocean Drilling Program Leg 160. Palaeogeography Palaeoclimatology Palaeoecology 158, 371–395, doi:10.1016/s0031-0182(00)00059-6 (2000).
Bartlein, P. J. et al. Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis. Climate Dynamics 37, 775–802, doi:10.1007/s00382-010-0904-1 (2011).
Nicholson, S. E. in Oxford Research Encyclopedia of Climate Science (Oxford University Press, 2018).
Osborne, A. H. et al. A humid corridor across the Sahara for the migration of early modern humans out of Africa 120,000 years ago. Proceedings of the National Academy of Sciences of the United States of America 105, 16444–16447, doi:10.1073/pnas.0804472105 (2008).
Neugebauer, I. et al. The unexpectedly short Holocene Humid Period in Northern Arabia. Communications Earth & Environment 3, doi:10.1038/s43247-022-00368-y (2022).
Petraglia, M. D., Groucutt, H. S., Guagnin, M., Breeze, P. S. & Boivin, N. Human responses to climate and ecosystem change in ancient Arabia. Proceedings of the National Academy of Sciences of the United States of America 117, 8263–8270, doi:10.1073/pnas.1920211117 (2020).
Breeze, P. S. et al. Palaeohydrological corridors for hominin dispersals in the Middle East similar to 250 – 70,000 years ago. Quaternary Science Reviews 144, 155–185, doi:10.1016/j.quascirev.2016.05.012 (2016).
Crassard, R. et al. Middle Palaeolithic and Neolithic Occupations around Mundafan Palaeolake, Saudi Arabia: Implications for Climate Change and Human Dispersals. Plos One 8, doi:10.1371/journal.pone.0069665 (2013).
Drake, N. A. et al. Sedimentary and geomorphic evidence of Saharan megalakes: A synthesis. Quaternary Science Reviews 276, doi:10.1016/j.quascirev.2021.107318 (2022).
Drake, N. A., Blench, R. M., Armitage, S. J., Bristow, C. S. & White, K. H. Ancient watercourses and biogeography of the Sahara explain the peopling of the desert. Proceedings of the National Academy of Sciences 108, 458–462, doi:10.1073/pnas.1012231108 (2011).
Rubin, S., Ziv, B. & Paldor, N. Tropical plumes over eastern North Africa as a source of rain in the middle east. Monthly Weather Review 135, 4135–4148, doi:10.1175/2007mwr1919.1 (2007).
Skinner, C. B. & Poulsen, C. J. The role of fall season tropical plumes in enhancing Saharan rainfall during the African Humid Period. Geophysical Research Letters 43, 349–358, doi:10.1002/2015gl066318 (2016).
Tubi, A., Dayan, U. & Lensky, I. M. Moisture transport by tropical plumes over the Middle East: a 30-year climatology. Quarterly Journal of the Royal Meteorological Society 143, 3165–3176, doi:10.1002/qj.3170 (2017).
Waldmann, N., Torfstein, A. & Stein, M. Northward intrusions of low- and mid-latitude storms across the Saharo-Arabian belt during past interglacials. Geology 38, 567–570, doi:10.1130/g30654.1 (2010).
Kutzbach, J. E., Chen, G., Cheng, H., Edwards, R. L. & Liu, Z. Potential role of winter rainfall in explaining increased moisture in the Mediterranean and Middle East during periods of maximum orbitally-forced insolation seasonality. Climate Dynamics 42, 1079–1095, doi:10.1007/s00382-013-1692-1 (2014).
Flaounas, E. et al. Assessment of an ensemble of ocean-atmosphere coupled and uncoupled regional climate models to reproduce the climatology of Mediterranean cyclones. Climate Dynamics 51, 1023–1040, doi:10.1007/s00382-016-3398-7 (2018).
Gaertner, M. et al. Simulation of medicanes over the Mediterranean Sea in a regional climate model ensemble: impact of ocean-atmosphere coupling and increased resolution. Climate Dynamics 51, 1041–1057, doi:10.1007/s00382-016-3456-1 (2018).
Jung, T., Gulev, S. K., Rudeva, I. & Soloviov, V. Sensitivity of extratropical cyclone characteristics to horizontal resolution in the ECMWF model. Quarterly Journal of the Royal Meteorological Society 132, 1839–1857, doi:10.1256/qj.05.212 (2006).
Niang, C. et al. Transport pathways across the West African Monsoon as revealed by Lagrangian Coherent Structures. Scientific Reports 10, doi:10.1038/s41598-020-69159-9 (2020).
Moron, V., Philippon, N. & Fontaine, B. Simulation of West African monsoon circulation in four atmospheric general circulation models forced by prescribed sea surface temperature. Journal of Geophysical Research-Atmospheres 109, doi:10.1029/2004jd004760 (2004).
Sultan, B. & Janicot, S. The West African monsoon dynamics. Part II: The "preonset'' and "onset'' of the summer monsoon. Journal of Climate 16, 3407–3427, doi:10.1175/1520-0442(2003)016<3407:Twamdp>2.0.Co;2 (2003).
Lavaysse, C., Flamant, C., Evan, A., Janicot, S. & Gaetani, M. Recent climatological trend of the Saharan heat low and its impact on the West African climate. Climate Dynamics 47, 3479–3498, doi:10.1007/s00382-015-2847-z (2016).
Thorncroft, C. D. & Blackburn, M. Maintenance of the African easterly jet. Quarterly Journal of the Royal Meteorological Society 125, 763–786, doi:10.1256/smsqj.55501 (1999).
Cook, K. H. Generation of the African easterly jet and its role in determining West African precipitation. Journal of Climate 12, 1165–1184, doi:10.1175/1520-0442(1999)012<1165:Gotaej>2.0.Co;2 (1999).
Nicholson, S. E. A revised picture of the structure of the "monsoon" and land ITCZ over West Africa. Climate Dynamics 32, 1155–1171, doi:10.1007/s00382-008-0514-3 (2009).
Armstrong, E., Valdes, P., House, J. & Singarayer, J. The Role of CO2 and Dynamic Vegetation on the Impact of Temperate Land-Use Change in the HadCM3 Coupled Climate Model. Earth Interactions 20, 1–20, doi:10.1175/ei-d-15-0036.1 (2016).
Ruddiman, W. F. Orbital insolation, ice volume, and greenhouse gases. Quaternary Science Reviews 22, 1597–1629, doi:10.1016/s0277-3791(03)00087-8 (2003).
Justino, F., Timmermann, A., Merkel, U. & Peltier, W. R. Vol. 19 3–14 (2006).
Cheng, H. et al. Ice Age Terminations. Science 326, 248–252, doi:10.1126/science.1177840 (2009).
Gao, Y., Liu, Z. & Lu, Z. Dynamic Effect of Last Glacial Maximum Ice Sheet Topography on the East Asian Summer Monsoon. Journal of Climate 33, 6929–6944, doi:10.1175/jcli-d-19-0562.1 (2020).
Wen, X. Y., Liu, Z. Y., Wang, S. W., Cheng, J. & Zhu, J. Correlation and anti-correlation of the East Asian summer and winter monsoons during the last 21,000 years. Nature Communications 7, doi:10.1038/ncomms11999 (2016).
Dixon, R. D., Peyrillé, P. & Guichard, F. Sahelian Precipitation Change Induced by SST Increase: The Contrasting Roles of Regional and Larger-Scale Drivers. Geophysical Research Letters 46, 11378–11387, doi:10.1029/2019gl084872 (2019).
Folland, C. K., Palmer, T. N. & Parker, D. E. SAHEL RAINFALL AND WORLDWIDE SEA TEMPERATURES, 1901-85. Nature 320, 602–607, doi:10.1038/320602a0 (1986).
Giannini, A., Biasutti, M. & Verstraete, M. M. Vol. 64 119–128 (2008).
Zhang, R. & Delworth, T. L. Vol. 33 L17712 (2006).
Pope, V. D., Gallani, M. L., Rowntree, P. R. & Stratton, R. A. The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3. Climate Dynamics 16, 123–146, doi:10.1007/s003820050009 (2000).
Gordon, C. et al. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dynamics 16, 147–168, doi:10.1007/s003820050010 (2000).
Essery, R., Best, M. & Cox, P. M. Moses 2.2 technical doumentation. Hadley Centre technical note 30, 1–30 (2001).
Hoperoft, P. O. & Valdes, P. J. Green Sahara tipping points in transient climate model simulations of the Holocene. Environmental Research Letters 17, doi:10.1088/1748-9326/ac7c2b (2022).
Berger, A., Loutre, M. F. & Gallee, H. Sensitivity of the LLN climate model to the astronomical and CO2 forcings over the last 200 ky. Climate Dynamics 14, 615–629, doi:10.1007/s003820050245 (1998).
Loulergue, L. et al. Orbital and millennial-scale features of atmospheric CH4 over the past 800,000 years. Nature 453, 383–386, doi:10.1038/nature06950 (2008).
Spahni, R. et al. Atmospheric methane and nitrous oxide of the late Pleistocene from Antarctic ice cores. Science 310, 1317–1321, doi:10.1126/science.1120132 (2005).
de Boer, B., Lourens, L. J. & van de Wal, R. S. W. Persistent 400,000-year variability of Antarctic ice volume and the carbon cycle is revealed throughout the Plio-Pleistocene. Nature Communications 5, doi:10.1038/ncomms3999 (2014).
The NCAR Command Language (Version 6.6.2) [Software]. (UCAR/NCAR/CISL/TDD, Boulder, Colorado., 2019).

Acknowledgements

This work was carried out using the computational facilities of the Advanced Computing Research Centre, University of Bristol—http://www.bris.ac.uk/acrc (Bluecrystal). E.A. and M.T. acknowledge funding from Kone Foundation (grant number 202006876). P.O.H. is supported by a University of Birmingham fellowship. Thank you to Frederik Schenk for discussion on the topic area.

Author Information

Authors & Affiliations

Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland

Edward Armstrong& Miikka Tallavaara

Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

Peter O. Hopcroft

School of Geographical Sciences, University of Bristol, Bristol, UK

Paul Valdes

Cabot Institute, University of Bristol, Bristol, UK

Paul Valdes

Contributions

E.A. conducted the analysis, production of the figures and composed the original manuscript. M.T. contributed to the analysis and provided the observation datasets for comparison. P.O.H. and P.V. developed and published the palaeo-conditioning for the model. P.V. compiled and carried out the climate model simulations and the design of experimental set-up. All authors commented and reviewed the manuscript.

Corresponding author

Correspondence to Edward Armstrong

Ethics declarations

The authors declare no competing interests.

There is NO Competing Interest.

SupplementaryFinalDraft.docx

Download PDF

Journal Publication

published 08 Sep, 2023

Read the published version in Nature Communications →

Version 1

posted

You are reading this latest preprint version

North African Humid Periods over the past 800000 years – Timing, Amplitude and Forcing

Status:

Journal Publication

Version 1

Abstract

Figures

Introduction

Simulating The Nahps

Timing, Amplitude And Spatial Pattern Of The Nahps

Precession Driven Mechanism Of The Nahps

Nahp Forcing – Orbits, Greenhouse Gases And The Ice Sheets

Methods

HadCM3B Model

Palaeoconditioning

Boundary Conditions

Snapshot Experiments

Boundary Condition Sensitivity Experiments

Topographic Vs. Thermodynamic Ice-sheet Sensitivity Experiments

Data Availability

Code Availability

References

Declarations

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1