Biomes simulated by BIOME4 using CESM2 lig127k, midHolocene, and piControl climate data on a global 0.5-degree grid

This data set consists of simulated biomes for the last interglacial (127 ka), middle Holocene (6 ka), and preindustrial (1850 CE) time periods displayed in Figure 14 of Otto-Bliesner et al. (2020). Biomes were simulated with BIOME4 (ver. 4.2, https://pmip2.lsce.ipsl.fr/synth/biome4.shtml; Kaplan et...

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Bibliographic Details
Main Authors: Brady, Esther C., Shafer, Sarah L., Bartlein, Patrick J., Otto-Bliesner, Bette L.
Format: Dataset
Language:unknown
Published: U.S. Geological Survey 2020
Subjects:
Online Access:https://dx.doi.org/10.5066/p9d9s4ey
https://www.sciencebase.gov/catalog/item/5fad7ca9d34eb413d5df46c8
Description
Summary:This data set consists of simulated biomes for the last interglacial (127 ka), middle Holocene (6 ka), and preindustrial (1850 CE) time periods displayed in Figure 14 of Otto-Bliesner et al. (2020). Biomes were simulated with BIOME4 (ver. 4.2, https://pmip2.lsce.ipsl.fr/synth/biome4.shtml; Kaplan et al., 2003), an equilibrium vegetation model, using CESM2 (ver. 2.1.0) simulated climate data produced under PMIP4/CMIP6 (Paleoclimate Modelling Intercomparison Project phase 4 / Coupled Model Intercomparison Project phase 6) lig127k, midHolocene, and piControl experiments (Otto-Bliesner et al., 2017, 2020). To create input climate data for BIOME4, we used CESM2 reference-height temperature (tas), total precipitation rate (pr), and vertically integrated total cloud (clt), with tas converted from K to ?C, pr converted to monthly total precipitation (mm) from precipitation rate (kg/m2/s), and clt converted from decimal fraction to %. The climate data were regridded to a 0.5-degree global grid using bilinear interpolation and bias-corrected by calculating long-term mean differences (lig127k minus piControl, midHolocene minus piControl, piControl minus historical 1961-1990 CE 30-year mean) and applying the differences to CRU CL 2.0 (1961-1990 CE 30-year mean) climate data (New et al., 2002), also on a 0.5-degree grid. The lig127k and midHolocene data were calendar adjusted using PaleoCalAdjust (v1.0; Bartlein and Shafer, 2019). Cloud data were converted to sunshine (%) using the approach of Doorenbos and Pruitt (1977). The overall approach follows closely that described in more detail by Harrison et al. (2014). Other BIOME4 input data included orbital eccentricity (ecc) and obliquity (obliq) values for each time period (Bartlein and Shafer, 2019). Atmospheric CO2 concentration was 275.0 ppm for 127 ka, 264.4 ppm for 6 ka, and 284.7 ppm for 1850 CE (Otto-Bliesner et al., 2020). The data included in this data release were developed for climate change research and may not be suitable for other applications. The data are provided in self-documenting netCDF (network Common Data Form) files (Unidata, 2011). References Bartlein, P.J., and Shafer, S.L., 2019, Paleo calendar-effect adjustments in time-slice and transient climate-model simulations (PaleoCalAdjust v1.0): impact and strategies for data analysis: Geoscientific Model Development, 12, 3889-3913, https://doi.org/10.5194/gmd-12-3889-2019. Doorenbos, J., and Pruitt, W.O., 1977, Guidelines for predicting crop water requirements: FAO Irrigation and Drainage Paper 24. Rome, Italy: FAO, 145 pp., http://www.fao.org/3/a-f2430e.pdf. Harrison, S.P., 2017, BIOME 6000 DB classified plotfile version 1: University of Reading, UK. Dataset, http://dx.doi.org/10.17864/1947.99. Harrison, S.P., Bartlein, P.J., Brewer, S., Prentice, I.C., Boyd, M., Hessler, I., Holmgren, K., Izumi, K., Willis, K., 2014, Climate model benchmarking with glacial and mid-Holocene climates: Climate Dynamics, 43, 671-688, https://doi.org/10.1007/s00382-013-1922-6. Kaplan, J.O., Bigelow, N.H., Prentice, I.C., Harrison, S.P., Bartlein, P.J., Christensen, T.R., Cramer, W., Matveyeva, N.V., McGuire, A.D., Murray, D.F., Razzhivin, V.Y., Smith, B., Walker, D.A., Anderson, P.M., Andreev, A.A., Brubaker, L.B., Edwards, M.E., and Lozhkin, A.V., 2003, Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections: Journal of Geophysical Research--Atmospheres, 108(D19), 8171, https://doi.org/10.1029/2002JD002559. New, M., Lister, D., Hulme, M., and Makin, I., 2002, A high-resolution data set of surface climate over global land areas: Climate Research, 21, 1-25, https://doi.org/10.3354/cr021001. Otto-Bliesner, B.L., Braconnot, P., Harrison, S.P., Lunt, D.J., Abe-Ouchi, A., Albani, S., Bartlein, P.J., Capron, E., Carlson, A.E., Dutton, A., Fischer, H., Goelzer, H., Govin, A., Haywood, A., Joos, F., LeGrande, A.N., Lipscomb, W.H., Lohmann, G., Mahowald, N., Nehrbass-Ahles, C., Pausata, F.S.R., Peterschmitt, J.-Y., Phipps, S.J., Renssen, H., and Zhang, Q., 2017, The PMIP4 contribution to CMIP6 -- Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations: Geoscientific Model Development, 10, 3979-4003, https://doi.org/10.5194/gmd-10-3979-2017. Otto-Bliesner, B.L., Brady, E.C., Tomas, R.A., Albani, S., Bartlein, P.J., Mahowald, N.M., Shafer, S.L., Kluzek, E., Lawrence, P.J., Leguy, G., Rothstein, M., and Sommers, A.N., 2020, A comparison of the CMIP6 midHolocene and lig127k simulations in CESM2: Paleoceanography and Paleoclimatology 35, e2020PA003957, https://doi.org/10.1029/2020PA003957. Unidata, 2011, Network Common Data Form (netCDF) version 4.1.3 [software]: UCAR/Unidata, Boulder, Colorado, https://doi.org/10.5065/D6H70CW6.