Abstract
Abstract. Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.
Highlights
General circulation model (GCM) simulations of the Earth’s climate are sophisticated tools that reproduce many physical processes of the climate system, helping to understand and characterize the dynamics of the climate system both at global and regional scales, as well as from decadal to millennial timescales (Flato et al, 2013)
The distribution of Long-term Surface Temperature (LoST) temperatures at grid cells containing Borehole temperature profile (BTP) measurements reproduces the shape of the distribution of raw T0 temperatures (Fig. 2a), indicating that the gradient plus inverse distance squared (GIDS) interpolation does not substantially modify the shape of the original distribution of temperatures retrieved from BTP measurements
Estimates of long-term surface temperatures from Climate Research Unit (CRU) data reflect such a temperature increase, hindering the direct comparison between both datasets. Despite this difference in the climatology of both databases, the long-term surface temperature from the LoST dataset reproduces the expected spatial pattern of temperatures for North America (Fig. 2c, d), which is in agreement with long-term surface temperatures estimated from BTP measurements and with long-term surface temperatures from CRU data
Summary
General circulation model (GCM) simulations of the Earth’s climate are sophisticated tools that reproduce many physical processes of the climate system, helping to understand and characterize the dynamics of the climate system both at global and regional scales, as well as from decadal to millennial timescales (Flato et al, 2013). Despite the large number of different GCMs developed and maintained by modeling groups around the world, future projections of climate change still present a large degree of uncertainty (Knutti and Sedlácek, 2012), mainly due to the different climate sensitivity achieved by each model. The equilibrium climate sensitivity (ECS) is typically defined as the change in equilibrium temperature given a doubling of the atmospheric CO2 concentration (Gregory et al, 2002), and it is considered to be one of the most important metrics to understand the longterm evolution of the climate system. The large uncertainty in ECS estimates is present in state-of-the-art GCMs (Andrews et al, 2012; Flato et al, 2013; Forster et al, 2013; Knutti et al, 2017), mainly as a result of approximating the description of several climate phenomena, tuning practices and the spread in control climate states. Each GCM approximates and resolves the differential equations governing the evolution of the climate system
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