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Seasonality in long-term climate change

La saisonnalité en paléoclimatologie
Matthieu Carré et Rachid Cheddadi
p. 173-177


La saisonnalité du climat est un élément essentiel dans le fonctionnement du système Terre. Les changements climatiques globaux à long-terme sont en grande partie induits, à travers des processus et rétroactions d’échelle saisonnière, par des changements de la distribution saisonnière du flux d’énergie solaire reçue par la surface terrestre. Pourtant, pour diverses raisons, la plupart des études paléoclimatiques se concentrent sur la reconstruction des moyennes annuelles des variables climatiques, alors que le climat se définit avant tout par le cycle annuel de ces variables. Ceci génère une documentation incomplète et parfois biaisée de la variabilité climatique naturelle. Nous passons ici brièvement en revue les éléments qui montrent l’importance de la saisonnalité climatique dans l’étude des changements climatiques à long terme, les techniques existantes pour reconstruire la saisonnalité climatique ainsi que les difficultés et défis associés. Nous souhaitons montrer ici que le prochain saut qualitatif dans notre niveau de compréhension de la variabilité climatique naturelle passe par une documentation des changements passés de la saisonnalité.

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We thank Thierry Corrège for a constructive review and for providing the coral picture.

1 - Introduction

1Climate is not properly defined by annual means, but rather by the annual cycle of the variables composing it. While this goes without saying for climatologists who study the current climate from daily instrumental observations, it is often overlooked by paleo-climatologists who study long-term changes. Yet, the natural processes leading to large scale climate shifts act mostly at the seasonal time scale. The inception and termination of glacial periods during the Quaternary, in particular, were due to changes in the seasonal flux of solar energy received by the Earth’s surface, as proposed by the Milankovitch theory (Milankovitch, 1930) later confirmed by the timing of quaternary glacial cycles recorded in the ocean (Hays et al., 1976). In addition, climate seasonality is one of the key environmental parameters that determine ecosystems composition and dynamics, and agriculture strategies. We present here a brief overview of the issues and challenges related to climate seasonality in the study of long-term climate change.

2 - The role of seasonal scale processes

2Most of the Earth’s climate undergoes a significant contrast between summer and winter. Seasons are characterized by opposite mass or energy transfers that add up in an annual budget at the end of the annual cycle. The climate is in equilibrium when annual budgets are null in average. The mean climate state starts drifting if the annual budget resulting from seasonality is shifted under the influence of an external forcing. As a simple illustrative example, the volume of continental ice sheets, an important component of global climate feedbacks, decreases during deglaciation periods because the winter snow accumulation does not compensate for the summer melting (Denton & Hughes, 1983). As a second example, aridification occurs when rainfall does not compensate for water loss (by evaporation and runoff) in the annual soil moisture balance. Climate thus shifts to a new equilibrium state involving lower average moisture, rainfall and evaporative flux. Today, the seasonal distribution of precipitation is being affected by anthropogenic climate change (Feng et al., 2013). Even in cases where the overall annual amount of precipitation is unchanged, an increasing duration of the dry season implies an increasing annual evaporation, a more negative hydrological annual budget, and results in an aridification trend. The phenomenon may be amplified through vegetation feedbacks since a shorter growing season for ecosystems will affect the type of vegetation and the seasonal cycle of evapotranspiration.

3So far, priority was given in paleoclimatology to the observation of large scale changes of the mean conditions, which is an essential first step. The discovery of millennial climate variability is fairly recent (Hays et al., 1976) and the first tracers developed were mostly not adapted to document seasonal variability. Today, and although there is significant room for improvement, the variability of mean conditions in the late Quaternary is reasonably well constrained for a number of variables (surface temperature, sea level, ice sheet extent, vegetation…). Some key variables, such as rainfall, are much less constrained, and vast regions such as Africa, are still clearly under-documented. Nonetheless, the density of data, especially in the northern mid-to high latitudes, now allows for large scale data synthesis (Pages 2k, 2013), field reconstructions (Evans et al., 2002; Mann et al., 2009), and data-model comparisons (Masson et al., 1999; Braconnot et al., 2012).

4Paleoclimate data syntheses sometimes reveal substantial disagreement among proxies. A different response to seasonality changes is one of the most frequent hypotheses to explain those discrepancies. For instance, high lake levels during glacial time around the Mediterranean (Harrison & Digerfeldt, 1993) may be interpreted as evidence for increased humidity, while contemporary pollen records indicated drier conditions (Allen et al., 1999). These observations were shown to be compatible with an increased seasonality in precipitation: moister winters and drier summers (Prentice et al., 1992). Significant differences also exists between sea surface reconstructions based on Mg/Ca ratios in foraminifers, and alkenon UK’37, that are likely related to different seasonal patterns of productivity of foraminifers and coccoliths (Leduc et al., 2010; Schneider et al., 2010). Global temperature reconstructions of the past millennium heavily rely on dendrochronological records which are strongly biased toward summer temperature (Mann et al., 2009; Pages 2k, 2013). These examples show that our understanding of the long term variability in mean annual temperature or precipitation is limited by the lack of information about their seasonal distribution.

5Changes in seasonality affect the annual budget, which, through an accumulative process over decades to millennia, leads to large transformations of the mean global conditions. These changes can be accelerated through feedback processes that also have a large seasonal component: the Earth surface albedo for instance, is a highly seasonal variable, changing through the year with sea ice extent, continental snow cover, vegetation, and clouds. It is now widely accepted that glacial-interglacial cycles are a response to changes in the seasonal distribution of the solar energy on the Earth’s surface (Berger, 1978; Ruddiman, 2003). Tropical monsoon systems have also been shown to respond to seasonal insolation forcing (Wang et al., 2001; Cruz et al., 2005). These massive changes result from seasonal scale processes that are almost exclusively explored using climate model experiments. Observations of past changes in climate seasonality are thus required to validate climate simulations, to improve the accuracy of reconstructions of mean annual conditions from low resolution proxy records, and to improve our understanding of how external forcing influence the Earth system.

3 – Reconstructing past climate seasonality

6The main obstacle to reconstructing past climate seasonality is essentially methodological. We identify here two broad approaches of proxy reconstruction: the first one is a direct approach based on fast accumulating paleoclimate archives from which high resolution monthly resolved geochemical records are measured (fig. 1). These archives include fossil corals (Beck et al., 1992; Felis et al., 2004; Corrège et al., 2004; Sun et al., 2005; Lazareth et al., 2013), mollusk shells (Shackleton, 1973; Driscoll et al., 2014; Carré et al., 2014), sclerosponge (Rosenheim et al, 2004), fish otoliths (Patterson et al., 1998), fossil teeth (Sharp & Cerling, 1998; Balasse et al., 2002), tree-rings (Evans & Shrag, 2004), speleothems (Ridley et al., 2015), and ice cores (Morgan & van Ommen, 1997). The pre-requisite to obtain seasonal variability is to have a continuous albeit not necessarily constant growth throughout the year. In temperate climates, tree rings only record spring and summer, the season of growth, and are therefore not suitable to document changes in the seasonal contrast. While tropical trees may not form annual rings, their continuous growth makes them potential archives of seasonal moisture variations through carbon and oxygen stable isotopes. Similarly, mollusk shells in high latitudes tend to stop calcifying in winter and often only record the warm season (Rhoads & Lutz, 1980). On the contrary, tropical accretionary organisms, corals or mollusks, generally record the full annual cycle (Aharon, 1991; Beck et al., 1992; Azzoug et al., 2012; Carré et al., 2013). Some fast growing speleothems, generally found in tropical regions, allow for monthly scale continuous records provided that the water residence time does not exceed a month (Johnson et al., 2006; Ridley et al., 2015).

7An important constraint in the use of these high resolution archives is their need for species- or site-specific calibration studies. And there is of course the time and cost issue: studying a time period with a monthly resolution requires at least 10 times as much time and money than an annually resolved study. Many would find such an investment either too risky or less productive in terms of scientific output. The high intrinsic scientific value of such scarce information has to be, however, reminded as a compensation for this risk. An interesting compromise can be met by studying low frequency variability first and focusing in a second step on the seasonality of critical periods.

8Climate seasonality may be defined differently depending on the climate variable. The temperature annual cycle is generally close to sinusoidal and therefore well defined by annual minima and maxima. Precipitation seasonality, in contrast, is correctly defined by the distribution of rainfall through the year, which requires an internal chronology with a monthly or lower resolution. To our knowledge, only mollusk shells provide such precise internal chronology through daily or tidal growth lines (Clark, 1968; Goodwin et al., 2001). Combining high resolution isotopic records and tidal growth lines analyses in shells of the tropical bivalve S. senilis, Azzoug et al. (2012) proposed the first proxy technique allowing the direct quantitative estimation of the duration of rainy and dry seasons. Tropical corals offer a unique and powerful opportunity to reconstruct both temperature and precipitation seasonality since Sr/Ca ratios and δ18O values measured in corals can be combined to calculate sea surface temperature and water δ18O which is directly influenced by rainfall (Corrège, 2006).

9The second approach is indirect and based on the assumption that seasonality is a determining factor of faunal and floral assemblages. Using modern observations of climate organism distributions, statistical transfer functions can be developed to reconstruct past climate variables, including annual means and seasonal values, from different types of fossil assemblages. Imbrie & Kipp (1971) described the calibration technique for marine proxies based on assemblages in marine core tops. It was applied to foraminifers (Mix et al., 1986), and radiolarian assemblages (Pisias et al., 1997) for the reconstruction of sea surface temperature annual means and seasonal ranges, but despite promising results, reconstructions of past seasonal ranges were not broadly pursued.

10On continents, fossil pollen grains preserved in sediments provide a wealth of climate information. Unlike the archives discussed above, pollen records may have a low temporal resolution and are much less constrained in their chronological frame that is often based on a reduced set of dated samples. However, any shift in the climate seasonality affects the ecosystems both in the species composition and in the relative proportion of species occurrence, and de facto their related pollen assemblages. Monthly means of climate variables (temperature and rainfall) may be quantified using statistical transfer functions (Cheddadi & Khater, 2016). Several techniques have been developed, including statistical analogy between the past ecosystems and the modern ones (Guiot, 1990), and the combination of the climatic requirements of plant taxa (Chevalier et al., 2014). Although very powerful, these statistical methods also have limitations. They require large databases of pollen assemblages in the first case or of modern plant distributions in the second, and rely on several assumptions that require caution. The modern climate-vegetation relationship used for reconstructions may be biased by the influence of human activities on ecosystems, by the changing concentration of atmospheric CO2 (Jolly & Haxeltine, 1997), or because the climatic niche of the studied ecosystem is truncated for geographic reasons. This type of indirect approach may be applied to a variety of fossil remains, provided their distribution is primarily driven by climate.

Fig. 1: Illustrative examples of archives of climate seasonality

Fig. 1: Illustrative examples of archives of climate seasonality

A) Coral X-ray picture showing annual banding and two micro-sampling tracks in a coral core. Photo credit: T. Correge. (B) Monthly scale reconstruction of sea surface temperature (black) and water oxygen isotopic composition (blue) from Sr/Ca ratios and coral δ18O measured in a Diploastrea coral from Vanuatu and dated in the Younger Dryas period (Correge et al., 2004). (C) Cross section of a Mesodesma donacium bivalve shell from Peru. Photo credit: M. Carré. (D) δ18O record of a M. donacium shell converted to sea surface temperature and plotted on a monthly time scale reconstructed from growth lines (Carré et al., 2014). (E) Picture of pollen grains. Photo credit: R. Cheddadi. (F) Reconstruction of changes in winter (DJF, blue) and summer (JAS, orange) rainfall during the past 16,000 years in Lebanon from fossil pollen assemblages (Cheddadi & Khater, 2016).

4 - Perspectives

11We argue here that getting to the next level of understanding of natural climate variability requires a larger effort into the reconstruction of past climate seasonality. Quantitative reconstruction techniques specifically dedicated to climate seasonality need to be further explored and improved. There is an immense room for methodological development in the indirect approach based on organism assemblages and statistical transfer functions, especially in the ocean. The performance of these techniques relies on vast databases of modern observations and sophisticated statistical analyses to untangle the complex influences that determine the accuracy of each climate proxy. Finally, a reevaluation of the main scientific focus and methodological habits of the scientific community seems necessary, at least for some regions. The variability of precipitation seasonality in the tropics is a largely unexplored field that requires a significant effort. In Europe, North America and the north Atlantic, the most documented regions on Earth, new reconstructions of the mean annual temperature in the late Quaternary only marginally improve the existing set of observation and do not significantly improve our understanding that is reaching a plateau. In contrast, reconstructions of past seasonal contrasts are clearly lacking. New observations of past climate seasonality would open new questions, and new roads toward a more detailed level of understanding.

Fig. 1: Illustrative examples of archives of climate seasonality.

(A) Coral X-ray picture showing annual banding and two micro-sampling tracks in a coral core. Photo credit: T. Corrège. (B) Monthly scale reconstruction of sea surface temperature (black) and water oxygen isotopic composition (blue) from Sr/Ca ratios and coral 18O measured in a Diploastrea coral from Vanuatu and dated in the Younger Dryas period (Corrège et al., 2004). (C) Cross section of a Mesodesma donacium bivalve shell from Peru. Photo credit: M. Carré. (D) 18O record of a M. donacium shell converted to sea surface temperature and plotted on a monthly time scale reconstructed from growth lines (Carré et al., 2014). (E) Picture of pollen grains. Photo credit: R. Cheddadi. (F) Reconstruction of changes in winter (DJF, blue) and summer (JAS, orange) rainfall during the past 16,000 years in Lebanon from fossil pollen assemblages (Cheddadi & Khater, 2016).

Fig. 1: Illustrations d’archives et d’enregistrements de la saisonnalité climatiques. (A) Radiographie d’un corail montrant des bandes annuelles et deux séries de micro-échantillonnage. Crédit photo : T. Corrège. (B) Reconstruction des variations mensuelles des températures de surface de la mer (noir) et du rapport isotopique de l’oxygène dans l’eau de mer (bleu) d’après les rapports Sr/Ca et les valeurs de 18O mesurés dans un corail Diploastrea des Vanuatu daté du Younger Dryas (Corrège et al., 2004). (C) Section d’une coquille du bivlave Mesodesma donacium du Pérou. Crédit photo : M. Carré. (D) Enregistrement de 18O d’une coquille de M. donacium converti en température de surface de la mer sur un axe temporel mensuel reconstruit d’après les lignes de croissance de la coquille (Carré et al., 2014). (E) Photo de grains de pollen. Crédit photo : R. Cheddadi. (F) Reconstruction quantifiée des précipitations d’hiver (DJF, bleu) et d’été (JAS, orange) au Liban au cours des 16 000 dernières années d’après des assemblages polliniques fossiles (Cheddadi & Khater, 2016).

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Table des illustrations

Titre Fig. 1: Illustrative examples of archives of climate seasonality
Légende A) Coral X-ray picture showing annual banding and two micro-sampling tracks in a coral core. Photo credit: T. Correge. (B) Monthly scale reconstruction of sea surface temperature (black) and water oxygen isotopic composition (blue) from Sr/Ca ratios and coral δ18O measured in a Diploastrea coral from Vanuatu and dated in the Younger Dryas period (Correge et al., 2004). (C) Cross section of a Mesodesma donacium bivalve shell from Peru. Photo credit: M. Carré. (D) δ18O record of a M. donacium shell converted to sea surface temperature and plotted on a monthly time scale reconstructed from growth lines (Carré et al., 2014). (E) Picture of pollen grains. Photo credit: R. Cheddadi. (F) Reconstruction of changes in winter (DJF, blue) and summer (JAS, orange) rainfall during the past 16,000 years in Lebanon from fossil pollen assemblages (Cheddadi & Khater, 2016).
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Matthieu Carré et Rachid Cheddadi, « Seasonality in long-term climate change », Quaternaire, vol. 28/2 | 2017, 173-177.

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Matthieu Carré

CNRS-IRD-UM, Institut des Sciences de l’Evolution de Montpellier, FR-34090 MONTPELLIER. Courriel :; CNRS-UPMC-IRD-MNHN, LOCEAN laboratory, PARIS.

Rachid Cheddadi

CNRS-IRD-UM, Institut des Sciences de l’Evolution de Montpellier, FR-34090 MONTPELLIER. Courriel :

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