Abstract Several palaeoclimate proxy records have been interpreted as representing the direct effects of Tibetan uplift on climate, and particularly the intensity of the Asian summer monsoon. However, there are other possible causes for the transitions and changes which have been observed, such as varying greenhouse gas concentrations, nodes or extremes in orbital forcing, and changing continental configurations. In this study we model the direct effects of Tibetan uplift on sea surface temperatures (SSTs), vegetation, and river discharge. We investigate whether these climatic effects of topographic uplift are likely to be detectable in proxy records, and also whether the proxies could be used to distinguish between different paradigms for the history of plateau uplift. We find that the SSTs in the western Pacific, South China Sea and Indian Ocean are generally insensitive to Tibetan uplift; however, vegetation in the region of the plateau itself, and river discharge from the Yangtze, Pearl, and in particular the Ganges/Brahmaputra, could provide a good test of our understanding of Tibetan uplift history.

Abstract: Climate plays a significant role in determining the styles of depositional processes at different latitudes, which in turn influence the locations of hydrocarbon systems. Results of climate modeling may therefore provide important information for predicting the presence or absence of suitable hydrocarbon plays. To determine whether the models provide realistic results, the critical step is to validate the model results against proxy data where they are available. Paleoclimate proxy data are most often derived from more accessible low- to midlatitude regions and are biased towards warm climate states. However, general circulation models (GCMs) have traditionally been biased to colder temperatures, in particular at high-latitudes, struggling to maintain the high-latitude regions warm enough to sustain forests that were present during greenhouse periods, such as the mid-Cretaceous (~130–89 Ma), without exaggerated warming of the equatorial regions. To improve this approach, the HadCM3L coupled atmosphere–ocean GCM, a state-of-the-art model for the long simulations required to reach an equilibrium climate, was run for each stage of the Cretaceous using new paleogeographic base maps. Here, we compare the results for the Aptian (118.5 Ma) and Albian (105.8 Ma) with paleoclimate proxy data from the high northern latitudes in order to determine if the model produces viable results for this region. Paleoclimate analysis of fossil wood from conifer forests from Svalbard of Aptian–Albian age suggests that they grew in moist cool upland areas adjacent to warmer temperate lowland regions, probably with rivers and/or swamps present. Studies of conifers from the Canadian Arctic islands indicate that they grew under slightly cooler conditions than on Svalbard, similar to northern Canada today. The HadCM3L GCM results for Svalbard show that the dominant biome was evergreen taiga/montane forest with lowland temperate vegetation present during the Albian Stage, possibly with an element of deciduous taiga/montane forest in the Aptian (both cold boreal forests with short hot summers according to the Köppen–Geiger classification). The modeled mean annual temperature was ~−3.7° C at the sample sites, with summer temperatures rising to a mean of ~18° C during the Albian. Mean annual precipitation was ~571 mm. In the Canadian Arctic, the model results indicate that the biomes were more mixed than on Svalbard. The Aptian biome was dominantly deciduous taiga/montane forest with temperate vegetation in low-lying areas. The Albian landscape was dominated by evergreen taiga/montane forest, with some elements of deciduous taiga. Both stages were classified as cold boreal forest with short hot summers under the Köppen-Geiger classification scheme. Mean annual temperature was modeled to be ~−6.5° C at the sample sites, with summer temperatures reaching a mean of ~13° C, and mean annual precipitation was ~406 mm. These results suggest that the HadCM3L GCM, coupled with updated paleogeographic maps, can produce a good match to the climate proxy data in these difficult-to-model high-latitude areas.