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We explore the relative roles of Earth’s axial tilt (‘tilt effect’) and orbital eccentricity (‘distance effect’) on the seasonal cycle of tropical sea surface temperature (SST), decomposing the two contributions using simulations of an Earth System model varying eccentricity and longitude of perihelion.  This dataset archives model output produced in this investigation using the Community Earth System Model version 2, and MATLAB code for analyzing the data. 

Abstract The seasonality of Earth’s climate is driven by two factors: the tilt of the Earth’s rotation axis relative to the plane of its orbit (hereafter thetilt effect), and the variation in the Earth–Sun distance due to the Earth’s elliptical orbit around the Sun (hereafter thedistance effect). The seasonal insolation change between aphelion and perihelion is only ~ 7% of the annual mean and it is thus assumed that the distance effect is not relevant for the seasons. A recent modeling study by the authors and collaborators demonstrated however that the distance effect is not small for the Pacific cold tongue: it drives an annual cycle there that is dynamically distinct and ~ 1/3 of the amplitude from the known annual cycle arising from the tilt effect. The simulations also suggest that the influence of distance effect is significant and pervasive across several other regional climates, in both the tropics and extratropics. Preliminary work suggests that the distance effect works its influence through the thermal contrast between the mostly ocean hemisphere centered on the Pacific Ocean (the ‘Marine hemisphere’) and the hemisphere opposite to it centered over Africa (the ‘Continental hemisphere’), analogous to how the tilt effect drives a contrast between the northern and southern hemispheres. We argue that the distance effect should be fully considered as an annual cycle forcing in its own right in studies of Earth’s modern seasonal cycle. Separately considering the tilt and distance effects on the Earth’s seasonal cycle provides new insights into the workings of our climate system, and of direct relevance to paleoclimate where there are outstanding questions for long-term climate changes that are related to eccentricity variations. 

The modern configuration of the South East Asian Islands (SEAI) evolved over the last fifteen million years, as a result of subduction, arc magmatism, and arc-continent collisions, contributing to both increased land area and high topography.  The presence of the additional land area has been postulated to enhance convective rainfall, facilitating both increased silicate weathering and the development of the modern-day Walker circulation.  Using an Earth System Model in conjunction with a climate-silicate weathering model, we argue instead for a significant role of SEAI topography for both effects.  This dataset archives model output used in this investigation, including simulations using the Community Earth System Model version 1.2, and the climate-silicate weathering model GEOCLIM. All data are in Netcdf format, and were generated either by the Community Earth System Model 1.2 (Hurrell et al. 2013) or the climate-silicate weathering model GEOCLIM (Park et al. 2020).  Model output is organized into 4 tar files: 1) B1850C5.tar Contains model output for the fully coupled CESM1.2 runs, for 2D fields and for 3D pressure vertical velocity (W) between 10S-10N.  Monthly mean data for years 41-110 of the simulations.   Naming convention is No SEAI topography: B1850C5_noSEAItopo_y41-110.nc and B1850C5_noSEAItopo_W_y41-110.nc 50% SEAI topography: B1850C5_0.5SEAItopo_y41-110.nc and B1850C5_0.5SEAItopo_W_y41-110.nc 100% SEAI topography: B1850C5_y41-110.nc and B1850C5_W_y41-110.nc 150% SEAO topogaphy: B1850C5_1.5SEAItopo_y41-110.nc and B1850C5_1.5SEAItopo_W_y41-110.nc 2) E1850C5.tar Contains model output for the slab ocean CESM1.2 runs, for 2D fields and for 3D pressure vertical velocity (W) between 10S-10N.  Monthly mean data for years 21-50 of the simulations.  Naming convention is No SEAI topography: E1850C5_noSEAItopo_y21-50.nc and E1850C5_noSEAItopo_W_y21-50.nc 50% SEAI topography: E1850C5_0.5SEAItopo_y21-50.nc and E1850C5_0.5SEAItopo_W_y21-50.nc 100% SEAI topography: E1850C5_y21-50.nc and E1850C5_W_y21-50.nc 150% SEAO topogaphy:  E1850C5_1.5SEAItopo_y21-50.nc and E1850C5_1.5SEAItopo_W_y21-50.nc 3) GEOCLIM.tar Contains model output from the climate-silicate weathering model GEOCLIM.  Data is provided for all 573 parameter combinations.  All values are climatological annual means. All files contain these variables: GMST: global mean surface temperature (in K) atm_CO2_level: atmospheric pCO2 (in ppm) degassing: globally-integrated CO2 flux (in mol/yr) The files ending with 1xCO2.nc also contain these spatial fields: lithology fraction: fraction of land covered by a lithology class erosion: Regolith erosion rate (m/yr) weathering: Ca-Mg weathering rate (mol/m^2/yr) E1850C5_1xCO2.nc - GEOCLIM output using the Modern SEAI simulation as input, and for CO2 fixed to 286.7ppm.  E1850C5_noSEAI_1xCO2.nc - GEOCLIM output using the no SEAI simulation as input, and for CO2 fixed to 286.7ppm.  E1850C5_noSEAItopo_1xCO2.nc - GEOCLIM output using the flat SEAI simulation as input, and for CO2 fixed to 286.7ppm.  E1850C5_noSEAI_equil.nc - GEOCLIM output using the no SEAI simulation as input, and CO2 adjusted so that system is in carbon flux equilibrium.   E1850C5_noSEAItopo_flatSEAIslope_equil.nc - GEOCLIM output using the flat SEAI simulation as input, and CO2 adjusted so that system is in carbon flux equilibrium.   4) Surface.tar Contains land fraction and surface geopotential fields for the modern SEAI (Landfrac.nc) and no SEAI (Landfrac_noSEAI.nc) simulations References Hurrell, J.W., Holland, M.M., Gent, P.R., Ghan, S., Kay, J.E., Kushner, P.J., Lamarque, J.F., Large, W.G., Lawrence, D., Lindsay, K. and Lipscomb, W.H., 2013. The community earth system model: a framework for collaborative research. Bulletin of the American Meteorological Society, 94(9), pp.1339-1360. Park, Y., Maffre, P., Goddéris, Y., Macdonald, F.A., Anttila, E.S. and Swanson-Hysell, N.L., 2020. Emergence of the Southeast Asian islands as a driver for Neogene cooling. Proceedings of the National Academy of Sciences, 117(41), pp.25319-25326. 

This dataset stores the data of the article The effect of Pliocene regional climate changes on silicate weathering: a potential amplifier of Pliocene-Pleistocene cooling P. Maffre, J. Chiang & N. Swanson-Hysell, Climate of the Past). This study uses a climate model (GCM) to reproduce an estimate of Pliocene Sea Surface Temperature (SST). The main GCM outputs of this modeling (with a slab ocean model) are stored in "GCM_outputs_for_GEOCLIM/", as well as the climatologies from ERA5 reanalysis. The other GCM outputs that were used in intermediary steps (coupled ocean-atmosphere, and fixed SST simulations) are stored in "other_GCM_outputs/". The forcing files (Q-flux) and other boundary conditions to run the "main" GCM simulations can be found in "other_GCM_outputs/Q-flux_derivation/", as well as the scripts used to generate them. Secondly, the mentioned study uses the GCM outputs in "GCM_outputs_for_GEOCLIM/" as inputs for the silicate weathering model GEOCLIM-DynSoil-Steady-State (https://github.com/piermafrost/GEOCLIM-dynsoil-steady-state/tree/PEN), to investigate weathering and equilibrium CO2 changes due to Pliocene SST conditions. The results of these simulations are stored in "GEOCLIM-DynSoil-Steady-State_outputs/". The purpose of this dataset is to provide the raw outputs used to draw the conclusions of Maffre et al. (2023), and to allow the experiments to be reproduced, by providing the scripts to generate the boundary conditions. 

Abstract The geography of the Southeast Asian Islands (SEAI) has changed over the last 15 million years, as a result of tectonic processes contributing to both increased land area and high topography. The presence of the additional land area has been postulated to enhance convective rainfall, facilitating both increased silicate weathering and the development of the modern‐day Walker circulation. Using an Earth System Model in conjunction with a climate‐silicate weathering model, we argue instead for a significant role of SEAItopographyfor both effects. SEAI topography increases orographic rainfall over land, through intercepting moist Asian‐Australian monsoon winds and enhancing land‐sea breezes. Large‐scale atmospheric uplift over the SEAI region increases by ∼14% as a consequence of increased rainfall over the SEAI and enhancement through dynamical ocean‐atmosphere feedback. The atmospheric zonal overturning circulation over the Indo‐Pacific increases modestly arising from dynamical ocean‐atmosphere feedback, more strongly over the tropical Indian Ocean. On the other hand, the effect of the SEAI topography on global silicate weathering is substantial, resulting in a ∼109 ppm reduction in equilibriumpCO₂and decrease in global mean temperature by ∼1.7ºC. The chemical weathering increase comes from both enhanced physical erosion rates and increased rainfall due to the presence of SEAI topography. The lowering ofpCO₂by SEAI topography also enhances the Indo‐Pacific atmospheric zonal overturning circulation. Our results support a significant role for the progressive emergence of SEAI topography in global cooling over the last several million years.