DOI: 10.5061/dryad.stqjq2c8j
title: Climate model experiments of regional-scale tree die-off replaced by C3 grass (all monthly data fields): Part 1

description: Climate change is triggering regional-scale alterations in vegetation
 including land cover change such as forest die-off. At sufficient
 magnitudes, land cover change from forest die-off in one region can change
 not only local climate but also vegetation including agriculture elsewhere
 via changes in larger-scale climate patterns, termed an “ecoclimate
 teleconnection”. Ecoclimate teleconnections can therefore have impacts on
 vegetative growth in distant regions, but the degrees to which the impact
 decays with distance or directionally diffuses relative to the initial
 perturbation are general properties that have not been evaluated. We used
 the Community Earth system model to study this, examining the implications
 of tree die-off in 14 major US forested regions. For each case, we
 evaluated the ecological impact across North America as a function of
 distance and direction from the location of regional tree die-off. We
 found that the effects on gross primary productivity generally decayed
 linearly with distance, with notable exceptions. Distance from the region
 of tree die-off alone explained up to ~30% of the variance in many
 regions. We also found that the gross primary productivity impact was not
 uniform across directions and that including an additional term to account
 for direction to regional land cover change from tree die-off was
 statistically significant for nearly all regions and explained up to ~40%
 of the variance in many regions, comparable in magnitude to the influence
 of El Nino on gross primary productivity in the Western US. Our results
 provide insights into the generality of distance decay and directional
 diffusion of ecoclimate teleconnections and suggest that it may be hard to
 identify expected impacts of tree die-off without case-specific
 simulations. Such patterns of distance decay, directional diffusion, and
 their exceptions are relevant for cross-regional policy that links forests
 and other agriculture (e.g. US Department of Agriculture). The data in
 this specific dataset (part 1) represents all variables from the
 simulations where trees were replaced by C3 grass at monthly averaged time
 resolution as well as the timeseries of the specific variables plotted in
 the accompanying  Feng et al. publication in ERL.
description: These data are climate model output from experiments described
 further in the relate manuscrip by Feng et al. Briefly, we conducted simulations using National Center for
 Atmospheric Research (NCAR) Community Earth System Model version 1.3
 (CESM, https://www.cesm.ucar.edu/models). The CESM model couples Community Atmosphere Model version 5 (CAM5) (Neale <em>et al</em> 2012) to the Community Land Model (CLM4.5) (Oleson <em>et al</em> 2013), the CICE4 sea ice model (Hunke <em>et al</em> 2010), and implements a slab ocean with prescribed heat transport derived from a fully-coupled ocean-atmosphere simulation (Neale <em>et al</em> 2012). Further details about the parameterization of the component models can be found in the papers above, as well as in the technical documentation (Oleson <em>et al</em> 2013). Year 2000 land use conditions based on satellite observations (Lawrence and Chase 2007) were used in the model setup, and the atmospheric CO<sub>2</sub> concentration was set to be constant at 400 ppm as our simulations are intended to represent approximately present-day “equilibrium” conditions in a stable climate as discussed further below. The land model component calculates surface fluxes of energy, water, and momentum which are passed to the atmospheric model. Carbon fluxes are also calculated diagnostically, and leaf area dynamically responds to photosynthesis rates through allocation of fixed carbon to leaves. This allows both surface albedo and evapotranspiration rates to vary with climate as a function of atmospheric conditions, stomatal conductance per leaf area, and leaf area. Model simulations were conducted at the spatial resolution of 1.9◦ latitude by 2.5◦ longitude for 100 years. Climate and terrestrial variables (e.g. global surface temperature, leaf area index) reach equilibrium after approximately 40 years of model spin up. The spin up period is discarded, and we then analyze time series for the remaining 60 years. This 60-year period can be considered “equilibrium” conditions, where variations over time represent samples over the expected internal variability of the climate system rather than a time series into the future. The CESM simulations were implemented on the NCAR Cheyenne supercomputing cluster (Computational and Information Systems Laboratory, 2017), sponsored by the National Science Foundation. We conducted 15 simulations: a control with no tree die-off and 14 experimental simulations, each corresponding to the scenario of tree die-off in one of 14 most forested ecoregions in the United States (i.e. NE, MA, SE, GL, PP, AP, OZ, NR, SR, DS, GB, PN, PS, and TA Domains of the US National Ecological Observatory Network (NEON) as in Swann et al. 2018). In each experiment, all forested area in an ecoregion was replaced with C3 grass. Present-day tree abundance was based on satellite observations (Lawrence and Chase 2007). Thus the magnitude of tree die-off varies between experiments as a function of the present-day forest cover.  <strong>References</strong> Hunke E C, Lipscomb W H, Turner A K, Jeffery N and Elliott S 2010 <em>Cice: the los alamos sea ice model documentation and software user’s manual version 4.1 la-cc-06-012 T-3 Fluid Dynamics Group,</em> Los Alamos National Laboratory 675 500 Lawrence P J and Chase T N. Representing a new MODIS consistent land surface in the community land model (CLM 3.0). <em>J. Geophys. Res.: Biogeosciences,</em> 112(G1). Neale R B, Chen C-C, Gettelman A, Lauritzen P H, Park S, Williamson D L, Conley A J, Garcia R, Kinnison D, Lamarque J-F and Others 2012 Description of the NCAR community atmosphere model (CAM 5.0) <em>NCAR Tech. Note NCAR/TN-486+STR 289</em> Oleson K, Lawrence D M, Bonan G B and Drewniak B 2013 Technical description of version 4.5 of the Community Land Model (CLM)(No. NCAR/TN-503+ STR) <em>UCAR: Boulder, CO, USA</em> Swann A L S, Laguë M M, Garcia E S, Field J P, Breshears D D, Moore D J P, Saleska S R, Stark S C, Villegas J C, Law D J and Minor D M 2018 Continental-scale consequences of tree die-offs in North America: identifying where forest loss matters most <em>Environ. Res. Lett.</em> 13 055014
description: # Climate model experiments of regional-scale tree die-off replaced by C3
 grass (all monthly data fields): Part 1
 [https://doi.org/10.5061/dryad.stqjq2c8j](https://doi.org/10.5061/dryad.stqjq2c8j) This dataset presents climate model output for 14 experiments and 1 control run simulated using the Community Earth System Model at monthly mean resolution. In each experiment, tree cover is modified for an ecoregion of the US described by NEON domains ([https://www.neonscience.org/field-sites/about-field-sites](https://www.neonscience.org/field-sites/about-field-sites)). See further description of the experiments and model information in the accompanying paper. This dataset is ***part 1*** of a collection of four datasets related to the same study: Part 1: Contains all variables from simulations where trees were replaced with C3 grass, at a monthly averaged time resolution. It also includes time series for the specific variables plotted in the accompanying Feng et al. publication in Environmental Research Letters (ERL) [[https://doi.org/10.5061/dryad.stqjq2c8j](https://urldefense.com/v3/__https://doi.org/10.5061/dryad.stqjq2c8j__;!!K-Hz7m0Vt54!i7nYlnE0GWoD-8XfyK6avWBoTt0vp31R7NQgXopp8HyuY-G31AoFz_Aqu8pgLWEx_mVa_SltTOmy$)]. Part 2: Contains selected variables from simulations where trees were replaced with C3 grass, at a daily time resolution [[https://doi.org/10.5061/dryad.z8w9ghxqr](https://urldefense.com/v3/__https://doi.org/10.5061/dryad.z8w9ghxqr__;!!K-Hz7m0Vt54!i7nYlnE0GWoD-8XfyK6avWBoTt0vp31R7NQgXopp8HyuY-G31AoFz_Aqu8pgLWEx_mVa_Rt6xHxG$)]. Part 3: Contains all variables from simulations where trees were replaced with shrubs, at a monthly averaged time resolution [[https://doi.org/10.5061/dryad.5hqbzkhh0](https://urldefense.com/v3/__https://doi.org/10.5061/dryad.5hqbzkhh0__;!!K-Hz7m0Vt54!i7nYlnE0GWoD-8XfyK6avWBoTt0vp31R7NQgXopp8HyuY-G31AoFz_Aqu8pgLWEx_mVa_edlwt__$)]. Part 4: Contains selected variables from simulations where trees were replaced with shrubs, at a daily time resolution [[https://doi.org/10.5061/dryad.ttdz08m8f](https://urldefense.com/v3/__https://doi.org/10.5061/dryad.ttdz08m8f__;!!K-Hz7m0Vt54!i7nYlnE0GWoD-8XfyK6avWBoTt0vp31R7NQgXopp8HyuY-G31AoFz_Aqu8pgLWEx_mVa_fUEi49U$)]. ## Description of the data and file structure Data is presented in NetCDF files, which contain metadata information that describes variable names, units, and grid information. The data are global and additionally have a time dimension. Files are provided that contain time series of six individual variables presented in our manuscript for each of our 14 experiments and a control run. We additionally include the climatology (average year) of all saved variables (most of which are not presented in our manuscript), which are presented in two files for each experiment, one for variables from the land grid and one for variables from the atmosphere grid. The full list of variables can be seen in the metadata of the netCDF files. Experiment files are named by the NEON domain number, as well as the plant functional type number of the plant type that replaced trees in a given domain. Relationship between NEON domain numbers to the names used in our paper (names and numbers are also listed on maps provided by NEON): | NEON Domain | Abbreviation | Domain Number | | ----------------- | ------------ | ------------- | | Northeast | NE | 1 | | Mid Atlantic | MA | 2 | | Southeast | SE | 3 | | Great Lakes | GL | 5 | | Prairie Peninsula | PP | 6 | | Appalachians | AP | 7 | | Ozarks | OZ | 8 | | Northern Plains | NP | 9 | | Central Plains | CP | 10 | | Southern Plains | SP | 11 | | Northern Rockies | NR | 12 | | Southern Rockies | SR | 13 | | Desert Southwest | DS | 14 | | Great Basin | GB | 15 | | Pacific Northwest | PN | 16 | | Pacific Southwest | PS | 17 | | Tundra | TU | 18 | | Taiga | TA | 19 | For example, for surface temperature (TSA), the first number (15) refers to the "Great Basin" domain, and the second number (14) refers to the plant type to which trees were converted C3 grass (this is the same for all experiments in this dataset). `cnh_neon_15_to_14.clm2.h0.ts.allyears.TSA.nc` ### Time series for variables plotted directly in the accompanying paper We present time series files for six variables that are analyzed in our manuscript. Additional metadata about the variables including units are contained in the metadata of the netCDF files. | Variable Abbreviation | Variable Name | | --------------------- | -------------------------- | | GPP | Gross Primary Productivity | | QVEGT | Vegetation Transpiration | | RAIN | Precipitation over Land | | TSA | Surface Temperature | | Z3 | Geopotential Height | | CLDLOW | Low Cloud Cover Fraction | ### Average Climatology of All variables In addition to time series data, we provide average climatology files labeled with "year_avg" in the file name which have the average over the time series for each month. These files include all variables that were saved from the model simulations even if they were not analyzed in the attached manuscript. There are two files for each of the 14 experiments and the control run, one containing output from the atmospheric model ("cam") and one containing output from the land model ("clm2"). example file name for experiment 15: `cnh_neon_15_to_14.cam.h0.40-100_year_avg.nc ` `cnh_neon_15_to_14.clm2.h0.40-100_year_avg.nc` ### Tarball of Monthly resolution time series of All variables We also provide tarballs that contain the monthly time resolution timeseries for all land and atmosphere variables. The tarballs are grouped by experiment and either land or atmosphere variables. You can find the following variables inside the tarballs. ### Land Variables | **Variable Abbreviation** | **Variable Name** | | :------------------------ | :------------------------------------------------------------------------------------------------------------- | | AR | autotrophic respiration (MR + GR) | | BTRAN | transpiration beta factor | | CPOOL | temporary photosynthate C pool | | EFLX\_LH\_TOT | total latent heat flux \[+ to atm] | | ELAI | exposed one-sided leaf area index | | ER | total ecosystem respiration, autotrophic + heterotrophic | | ESAI | exposed one-sided stem area index | | FAREA\_BURNED | fractional area burned | | FCEV | canopy evaporation | | FCTR | canopy transpiration | | FGEV | ground evaporation | | FGR | heat flux into soil/snow including snow melt and lake / snow light transmission | | FIRE | emitted infrared (longwave) radiation | | FLDS | atmospheric longwave radiation | | FPSN | photosynthesis | | FROOTC | fine root C | | FSA | absorbed solar radiation | | FSDS | atmospheric incident solar radiation | | FSH | sensible heat | | FSM | snow melt heat flux | | FSNO | fraction of ground covered by snow | | FSR | reflected solar radiation | | FUELC | fuel load | | GPP | gross primary production | | H2OSNO | snow depth (liquid water) | | H2OSOI | volumetric soil water (vegetated landunits only) | | HR | total heterotrophic respiration | | HTOP | canopy top | | LAISHA | shaded projected leaf area index | | LAISUN | sunlit projected leaf area index | | LEAF\_MR | leaf maintenance respiration | | LEAFC | leaf C | | LEAFN | leaf N | | LITTERC | litter C | | LIVECROOTC | live coarse root C | | LIVESTEMC | live stem C | | MR | maintenance respiration | | NBP | net biome production, includes fire, landuse, and harvest flux, positive for sink | | NEE | net ecosystem exchange of carbon, includes fire, landuse, harvest, and hrv\_xsmrpool flux, positive for source | | NPP | net primary production | | PBOT | atmospheric pressure | | PCT\_LANDUNIT | % of each landunit on grid cell | | PCT\_NAT\_PFT | % of each PFT on the natural vegetation (i.e., soil) landunit | | PSNSHA | shaded leaf photosynthesis | | QBOT | atmospheric specific humidity | | QFLOOD | runoff from river flooding | | QRUNOFF | total liquid runoff (does not include QSNWCPICE) | | QSNOMELT | snow melt | | QSOIL | Ground evaporation (soil/snow evaporation + soil/snow sublimation - dew) | | QVEGE | canopy evaporation | | QVEGT | canopy transpiration | | RAIN | atmospheric rain | | RH2M | 2m relative humidity | | SEEDC | pool for seeding new PFTs | | SNOW | atmospheric snow | | SNOW\_DEPTH | snow height of snow covered area | | SNOWDP | gridcell mean snow height | | SOILC | soil C | | SOILPSI | soil water potential in each soil layer | | SOILWATER\_10CM | soil liquid water + ice in top 10cm of soil (veg landunits only) | | THBOT | atmospheric air potential temperature | | TLAI | total projected leaf area index | | TOTCOLC | total column carbon, incl veg and cpool | | TOTECOSYSC | total ecosystem carbon, incl veg but excl cpool | | TOTECOSYSN | total ecosystem N | | TOTPFTC | total pft-level carbon, including cpool | | TOTSOMC | total soil organic matter carbon | | TOTVEGC | total vegetation carbon, excluding cpool | | TREFMNAV | daily minimum of average 2-m temperature | | TREFMXAV | daily maximum of average 2-m temperature | | TSA | 2m air temperature | | TSAI | total projected stem area index | | TSOI | soil temperature (vegetated landunits only) | | TV | vegetation temperature | | TWS | total water storage | | U10 | 10-m wind | | WIND | atmospheric wind velocity magnitude | | WOODC | wood C | | ZBOT | atmospheric reference height | #### Atmosphere Variables | Variable Abbreviation | Variable Name | | :-------------------- | :-------------------------------------------------- | | CLDHGH | Vertically-integrated high cloud | | CLDLOW | Vertically-integrated low cloud | | CLDMED | Vertically-integrated mid-level cloud | | CLDTOT | Vertically-integrated total cloud | | CLOUD | Cloud fraction | | EMISCLD | cloud emissivity | | FLDS | Downwelling longwave flux at surface | | FLNS | Net longwave flux at surface | | FLNSC | Clearsky net longwave flux at surface | | FLNT | Net longwave flux at top of model | | FLNTC | Clearsky net longwave flux at top of model | | FLUT | Upwelling longwave flux at top of model | | FLUTC | Clearsky upwelling longwave flux at top of model | | FSDS | Downwelling solar flux at surface | | FSDSC | Clearsky downwelling solar flux at surface | | FSNS | Net solar flux at surface | | FSNSC | Clearsky net solar flux at surface | | FSNT | Net solar flux at top of model | | FSNTC | Clearsky net solar flux at top of model | | FSNTOA | Net solar flux at top of atmosphere | | FSNTOAC | Clearsky net solar flux at top of atmosphere | | FSUTOA | Upwelling solar flux at top of atmosphere | | H2O2\_SRF | H2O2 in bottom layer | | ICEFRAC | Fraction of sfc area covered by sea-ice | | LANDFRAC | Fraction of sfc area covered by land | | LHFLX | Surface latent heat flux | | LWCF | Longwave cloud forcing | | OCNFRAC | Fraction of sfc area covered by ocean | | PBLH | PBL height | | PRECC | Convective precipitation rate (liq + ice) | | PRECL | Large-scale (stable) precipitation rate (liq + ice) | | PRECSC | Convective snow rate (water equivalent) | | PS | Surface pressure | | QFLX | Surface water flux | | QREFHT | Reference height humidity | | RELHUM | Relative humidity | | SHFLX | Surface sensible heat flux | | SNOWHICE | Snow depth over ice | | SNOWHLND | Water equivalent snow depth | | SOLIN | Solar insolation | | SST | sea surface temperature | | SWCF | Shortwave cloud forcing | | T | Temperature | | TMQ | Total (vertically integrated) precipitable water | | TREFHT | Reference height temperature | | TS | Surface temperature (radiative) | | TSMN | Minimum surface temperature over output period | | TSMX | Maximum surface temperature over output period | | U10 | 10m wind speed | | Z3 | Geopotential Height (above sea level) | ## Sharing/Access information This data is covered by a CC0 waiver. ## Code/Software This data is the direct output from [CESM](https://www.cesm.ucar.edu/models/cesm2) with time points concatenated into a single file for each variable, or presented as climatological averages with all variables in a single file. ## Version Changes 01-Apr-2025: Added tarballs containing the monthly mean time series for many more output variables.