NOAA PSL Climate Data Repository - FACTS Climate Experiment Documentation

FACTS Climate Experiment Documentation

Experiment Forcings
Time Coverage & Ensemble Size
Variables
Model Descriptions

Climate Experiment Forcings

The table below shows the forcings used in the climate experiments that are being made available through the FACTS website.

Experiment Identifiers		Forcings¹
Experiment Name²	File Name ID³	Sea Surface Temperature (SST)	Sea Ice	Greenhouse Gases (GHG)	Ozone
AMIP with Observed Radiative Forcing	amip_obs_rf	Obs	Obs	Obs	Obs
AMIP with 1880s Radiative Forcing	amip_1880s_rf	Obs Detrended to 1880	Present Climatology	Past Climatology	Past Climatology
AMIP with Natural History Forcing	amip_nat_hist	CMIP5-est1⁵	CMIP5-est1⁵	Past Climatology	Past Climatology
AMIP with Climatological Radiative Forcing	amip_clim_rf	Obs	Obs	Present Climatology	Present Climatology
AMIP with Observed Radiative Forcing, Climatological Sea Ice and Polar SST	amip_clim_polar	Obs/Present Climatology	Present Climatology	Obs	Obs
Leading Pattern of Global SST Variabilty⁴ with Observed Radiative Forcing	eof1_sst	1st EOF⁴	Obs	Obs	Obs
First 2 Leading Patterns of Global SST Variability⁴ with Observed Radiative Forcing	eof1+eof2_sst	1st & 2nd EOF⁴	Obs	Obs	Obs
Large Ensemble	LENS	Coupled model	Coupled model	Obs/RCP8.5	Obs

¹ Obs - Observed conditions, Present Climatology (varies by forcing, but generally some average conditions between 1981-2010), Past Climatology (1881-1910 climatology, or a specific pre-industrial date). See experiment descriptions for complete details.
² Text for "experiment" global attribute in files
³ Experiment identifier in file and directory names
⁴ Leading Patterns are the first and second Empirical Orthogonal Functions (EOF) of Global monthly SST variability 1979-2011 (EOF1, EOF2)
⁵ Method described in: A benchmark estimate of the effect of anthropogenic emissions on the ocean surface.
⁶ CESM Large Ensemble Project

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Climate Experiment Time Coverage & Ensemble Size

The table below shows the ensemble size & time coverage for the climate experiments that are being made available through the FACTS website.

Experiment Identifiers		Time Coverage Number of Ensemble Members
Experiment Name	File Name ID	ECHAM5	CAM4	ESRL-GFSv2	GEOS-5	AM3	ESRL-CAM5.1	LBNL-CAM5.1
AMIP with Observed Radiative Forcing	amip_obs_rf	Jan 1979- Feb 2019 50	Jan 1979- May 2015 20	Jan 1979- Feb 2018 50	Jan 1871- Aug 2014 12	Jan 1870- Feb 2014 12	Jan 1900- Feb 2019 40	Jan 1959- Sep 2014 50
AMIP with 1880s Radiative Forcing	amip_1880s_rf	Jan 1979- Feb 2019 50	Jan 1979- Dec 2012 20				Jan 1979- Feb 2019 40
AMIP with Natural History Forcing	amip_nat_hist							Jan 1959- Oct 2014 50
AMIP with Climatological Radiative Forcing	amip_clim_rf	Jan 1979- Dec 2012 10
AMIP with Observed Radiative Forcing, Climatological Sea Ice and Polar SST	amip_clim_polar	Jan 1979- Feb 2018 30	Jan 1979- May 2015 20	Jan 1979- Jun 2015 30			Jan 1979- Apr 2017 20
Leading Pattern of Global SST Variabilty⁴ with Observed Radiative Forcing	eof1_sst	Jan 1979- Apr 2017 30	Jan 1979- May 2015 20	Jan 1979- Jun 2015 50
First 2 Leading Patterns of Global SST Variabilty⁴ with Observed Radiative Forcing	eof1+eof2_sst	Jan 1979- Apr 2017 30

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Climate Experiment Variables

The table below shows a list of monthly variables generally being made available through the FACTS website. Each experiment may have only some of the variables available. The netCDF files use the CMIP5 variable names and units where possible and include variable attributes to show the original model variable name and units.

	CMIP5 Variables Names and Units			Model Variables Names
Variable Description (long_name attribute)	Variable Name	Units	CF Standard name	ECHAM5	CAM4/CAM5.1	ESRL-GFSv2	AM3	GEOS-5
Surface Upward Latent Heat Flux	hfls	W m-2	surface_upward_latent_heat_flux	ahfl	LHFLX	lhtfl		lhfx
Surface Upward Sensible Heat Flux	hfss	W m-2	surface_upward_sensible_heat_flux	ahfs	SHFLX	shtfl		shfx
Geopotential Height	zg	m	geopotential_height	geopoth	Z3	hgt		h
Precipitation	pr	kg m-2 s-1	precipitation_flux	precip	PRECT	precip	precip	pr
Surface Runoff	mrro	kg m-2 s-1	runoff_flux	runoff	QRUNOFF
Total Soil Moisture Content	mrso	m	soil_moisture_content	ws	MRSO
Sea Level Pressure	psl	Pa	air_pressure_at_sea_level	slp	PSL	prmsl		slp
Snow Water Equivalent	snw	kg m-2	surface_snow_amount	sn	SNOWHLND
Air Temperature	ta	K	air_temperature	st	T	tmp		t
Daily Maximum Near-Surface Air Temperature	tasmax	K	air_temperature	t2max	TREFMXAV
Daily Minimum Near-Surface Air Temperature	tasmin	K	air_temperature	t2min	TREFMNAV
Near-Surface Air Temperature	tas	K	air_temperature	temp2	TREFHT	t2m	t_ref	t2m
Surface Temperature	ts	K	surface_temperature	tsurf	TS
Eastward Wind	ua	m s-1	eastward_wind	u	U	ugrd		u
Northward Wind	va	m s-1	northward_wind	v	V	vgrd		v

Coordinate Variables

	CMIP5 Variables and Units			Model Variables
Variable Description (long_name attribute)	Variable Name	Units	CF Standard name	ECHAM5	CAM4/CAM5.1	ESRL-GFSv2	AM3	GEOS-5
time	time	days since ?	time	time	time	time	time	time
latitude	lat	degrees_north	latitude	lat	lat	lat	grid_yt	lat
longitude	lon	degrees_east	longitude	lon	lon	lon	grid_xt	lon
pressure	plev	Pa	air_pressure	lev	level	lev		lev

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Descriptions of the models available in FACTS

AM3

Model:

AM3

Source:

Geophysical Fluid Dynamics Laboratory (GFDL)

Horizontal Resolution:

~1.9^ox1.9^o (192x92)

Vertical Resolution:

48 layers

References:

Donner, Leo J., Bruce Wyman, Richard S Hemler, Larry W Horowitz, Yi Ming, Ming Zhao, J-C Golaz, Paul Ginoux, Shian-Jiann Lin, M Daniel Schwarzkopf, John Austin, G Alaka, W F Cooke, Thomas L Delworth, Stuart Freidenreich, C Tony Gordon, Stephen M Griffies, Isaac M Held, William J Hurlin, Stephen A Klein, Thomas R Knutson, Amy R Langenhorst, H C Lee, Y Lin, B I Magi, Sergey Malyshev, P C D Milly, Vaishali Naik, Mary Jo Nath, R Pincus, Jeff J Ploshay, V Ramaswamy, Charles J Seman, Elena Shevliakova, Joseph J Sirutis, William F Stern, Ronald J Stouffer, R John Wilson, Michael Winton, Andrew T Wittenberg, and Fanrong Zeng, July 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL Global Coupled Model CM3. Journal of Climate, 24(13), doi:10.1175/2011JCLI3955.1.

Bretherton, Christopher S., James R McCaa, Herve Grenier, 2004: A New Parameterization for Shallow Cumulus Convection and Its Application to Marine Subtropical Cloud-Topped Boundary Layers. Part I: Description and 1D Results. Monthly Weather Review, 132, 864-882.

Donner, Leo J., Charles J Seman, Richard S Hemler, and Song-Miao Fan, 2001: A Cumulus Parameterization Including Mass Fluxes, Convective Vertical Velocities, and Mesoscale Effects: Thermodynamic and Hydrological Aspects in a General Circulation model. Journal of Climate, 14(16), 3444-3463.

Golaz, J-C, M Salzmann, Leo J Donner, Larry W Horowitz, Yi Ming, and Ming Zhao, July 2011: Sensitivity of the Aerosol Indirect Effect to Subgrid Variability in the Cloud Parameterization of the GFDL Atmosphere General Circulation Model AM3. Journal of Climate, 24(13), DOI:10.1175/2010JCLI3945.1.

Ming, Yi, V Ramaswamy, Leo J Donner, and V T J Phillips, 2006: A new parameterization of cloud droplet activation applicable to general circulation models. Journal of the Atmospheric Sciences, 63(4), DOI:10.1175/JAS3686.1.

Wilcox, E M., and Leo J Donner, 2007: The Frequency of Extreme Rain Events in Satellite Rain-Rate Estimates and an Atmospheric General Circulation Model. Journal of Climate, 20(1), DOI:10.1175/JCLI3987.1

CAM4

Model:

CCSM4.0 CAM

Source:

National Center for Atmospheric Research (NCAR)

Horizontal Resolution:

~1.0^oX1.0^o (288x192)

Vertical Resolution:

25 layers

References:

Neale, R. B., et al., (2010a), Description of the NCAR Community Atmosphere Model (CAM 4.0), NCAR Tech. Note NCAR/TN-XXX+STR, 206 pp., Natl. Cent. for Atmos. Res, Boulder, Colo.

CAM5.1

Model:

CAM-5.1.1 (CESM-1.0)

Source:

National Center for Atmospheric Research (NCAR)

Horizontal Resolution:

~1.0^oX1.0^o (288x192)

Vertical Resolution:

25 layers

References:

Neale, R. B., et al., (2012), Description of the NCAR Community Atmosphere Model (CAM 5.0), NCAR Tech. Note NCAR/TN-486+STR, 289 pp., Natl. Cent. for Atmos. Res, Boulder, Colo.

CanESM2

Model:

CanESM2

Source:

Canadian Centre for Climate Modelling and Analysis

Horizontal Resolution:

~2.8^oX2.8^o (128x64)

Vertical Resolution:

35 layers

Model Description:

Second generation Canadian Earth System Model

Large Ensemble Experiment References and Licensing

The Canadian Earth System Model Large Ensembles

CESM1-CAM5

Model:

CESM1.0-CAM5

Source:

National Center for Atmospheric Research (NCAR)

Horizontal Resolution:

~1.0^oX1.0^o (288x192)

Vertical Resolution:

25 layers

References:

Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G., Arblaster, J., Bates, S., Danabasoglu, G., Edwards, J., Holland, M. Kushner, P., Lamarque, J.-F., Lawrence, D., Lindsay, K., Middleton, A., Munoz, E., Neale, R., Oleson, K., Polvani, L., and M. Vertenstein (2015), The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability, Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-13-00255.1, 96, 1333-1349.

ECHAM5

Model:

ECHAM5.4

Source:

Max Planck Institute for Meteorology (MPI)

Horizontal Resolution:

0.75^ox0.75^o (480x240)

Vertical Resolution:

31 layers

References:

Roeckner, E., G. Bäuml, L. Bonaventura, R. Brokopf, M. Esch, M. Giorgetta, S. Hagemann, I. Kirchner, L. Kornblueh, E. Manzini, A. Rhodin, U. Schlese, U. Schulzweida, and A. Tompkins, 2003: The atmospheric general circulation model ECHAM5. Part I: Model description. Max Planck Institute for Meteorology Rep. 349, 127 pp.

ESRL-CAM5HR

Model:

ESRL-CAM5HR

Source:

National Center for Atmospheric Research (NCAR)

Horizontal Resolution:

~0.5^oX0.5^o (576x384)

Vertical Resolution:

26 layers

References:

ESRL-GFSv2

Model:

GFSv2 run at ESRL

Source:

NOAA/NWS Environmental Modeling Center (EMC)

Horizontal Resolution:

1.0^ox1.0^o (360x181)

Vertical Resolution:

64 layers

References:

Suranjana Saha, Shrinivas Moorthi, Xingren Wu, Jiande Wang, Sudhir Nadiga, Patrick Tripp, David Behringer, Yu-Tai Hou, Hui-ya Chuang, Mark Iredell, Michael Ek, Jesse Meng, Rongqian Yang, Malaquías Peña Mendez, Huug van den Dool, Qin Zhang, Wanqiu Wang, Mingyue Chen, and Emily Becker, 2014: The NCEP Climate Forecast System Version 2. J. Climate, 27, 2185–2208. doi: http://dx.doi.org/10.1175/JCLI-D-12-00823.1

GEOS-5

Model:

GEOS-5

Source:

NASA Goddard Space Flight Center (GSFC)

Horizontal Resolution:

1.25^ox1^o (288x181)

Vertical Resolution:

72 layers

References:

Molod, A., L. Takacs, M. Suarez, J. Bacmeister, I. Somg, and A. Eichmann, 2012: The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna. Tech. rep., NASA Technical Report Series on Global Modeling and Data Assimilation, NASA TM2012-104606, Vol. 28, 117 pp.

Siegfried D. Schubert, Hailan Wang, Randal D. Koster, Max J. Suarez, and Pavel Ya. Groisman, 2014: Northern Eurasian Heat Waves and Droughts. J. Climate, 27, 3169–3207.

GFDL-CM3

Model:

GFDL-CM3

Source:

Geophysical Fluid Dynamics Laboratory (GFDL)

Horizontal Resolution:

2.5^ox2.0^o (144x90)

Vertical Resolution:

48 layers

References:

Griffies, S. M., and Coauthors, 2011: GFDL’s CM3 coupled climate model: Characteristics of the ocean and sea ice simulations. J. Climate, 24, 3520–3544, doi: 10.1175/2011JCLI3964.1

Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component of the GFDL global coupled model CM3. J. Climate, 24, 3484–3519, doi: 10.1175/2011JCLI3955.1

Golaz, J.-C., M. Salzmann, L. J. Donner, L. W. Horowitz, Y. Ming, and M. Zhao, 2011: Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL atmosphere general circulation model AM3. J. Climate, 24, 3145–3160, doi: 10.1175/2010JCLI3945.1

Sun, Lantao, Michael Alexander, and Clara Deser, 2018: Evolution of the global coupled climate response to Arctic sea ice loss during 1990-2090 and its contribution to climate change, J. Climate, 31, 7823-7843, doi: 10.1175/JCLI-D-18-0134.1

(click on a model name to show the details of that model)

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