An ensemble of AMIP simulations with prescribed land surface temperatures

Abstract

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature, and soil temperature and moisture) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free land experiments are used to perform a set of “AMIP prescribed land” (PL) simulations, which are evaluated against their free land counterparts. The PL simulations agree well with the free land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP prescribed land experiments.

Separating the Influences of Land Warming, the Direct CO2 Effect, the Plant Physiological Effect, and SST Warming on Regional Precipitation Changes

“…These free‐running experiments were used as the basis for new “prescribed land” (PL) experiments (Ackerley et al, ). Surface properties (surface temperature, deep soil temperature, and soil moisture) were saved every 3 hr from the free‐running experiments then interpolated to hourly values.…”

“…An atmosphere-only configuration of ACCESS (Australian Community Climate and Earth System Simulator) 1.0 (Ackerley & Dommenget, 2016;Bi et al, 2013) was used, with a horizontal resolution of 3.75 • longitude by 2.5 • latitude and 38 vertical levels. The design and validation of the AGCM experiments used in this analysis are described in detail in Ackerley et al (2018).…”

“…The instantaneous radiative forcing is the forcing that would occur in a climate model (in this case under a quadrupling of CO 2 ) if CO 2 concentrations were increased but the atmosphere did not adjust (i.e., no changes in atmospheric temperature, clouds, or WV). Although this diagnostic was not available for ACCESS1.0, it was calculated for HadGEM2-A, a climate model with an extremely similar formulation to ACCESS1.0 (see Ackerley et al, 2018), and HadGEM2-A is used as a proxy for ACCESS1.0 for this diagnostic. Instantaneous radiative forcing is also shown in supporting information for four other GCMs for which it was available: CanAM4, IPSL-CM5-LR, MIROC3, and MIROC5.…”

“…Nonlinear (NL) residuals are the residual between precipitation change in the full PL experiments and the sum of individual components, for example, amip4K-NLresidual = (amip4KPL − amipPL) − (amip4K-SSTonly − amipPL) − (amip4K-Landonly − amipPL). Ackerley et al (2018) showed that the use of the PL framework only introduces small errors into the mean climate compared to standard AGCM experiments and that these small biases are fairly stationary under CO 2 forcing. Errors introduced by the use of the PL framework are shown in Figure 2 and Tables 2 and 3…”

“…Input surface temperature, soil moisture, and deep soil temperatures are also available from the NCI upon request (also refer to Ackerley, 2017). The relevant doi (and other metadata) for each of the individual experiments can be found in the supporting information attached to Ackerley et al (2018). Use of these data in any publications requires both a citation of Ackerley et al (2018) and an appropriate acknowledgement to the data resource page (see Ackerley, 2017, for more details on acknowledging the data set).…”