The success of distribution models projected onto altered climate states of different time periods is dependent on the accuracy of the modeled climate. Climate models have been steadily improving, especially as concern about climate change has grown, as such models offer a means to predict potential changes (Stocker et al., 2013). For example, global climate models are now routinely coupled with complex oceanography models and vegetation models (and typically referred to as coupled atmosphere–ocean general circulation models – AOGCMs), and are thereby becoming increasingly integrated across the primary drivers of climate. Despite this, uncertainty remains in the climate modeling simulations. Different AOGCMs that BDA-366 perform equally well for the present-day routinely produce differing responses when projecting away from present (Collins et?al., 2013, Flato et?al., 2013 and Gavin et?al., 2014). There are over 20 different general circulation models endocytosis are being used to simulate paleoclimates in a comparative manner through the Paleoclimate Modeling Intercomparison Project (PMIP, Braconnot et al., 2011) which is now in its third stage of development (PMIP3; https://pmip3.lsce.ipsl.fr/). The focus of PMIP3 has been on a limited range of time periods, primarily on the mid-Holocene (6 ka) and the Last Glacial Maximum (21 ka), but also some simulations for the Last Interglacial (early Eemian, mid-Eemian and glacial inception) and the abrupt cooling event at 8.2 ka. With the growing climate modeling capacity, coordinated efforts between modeling groups and validation against current and past climates, we can expect that the climate predictions of past and future are set to be continuously improving.
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