DOI: 10.5061/dryad.h44j0zpw1
title: Community Land Model synthetic meteorology simulation model output

description: Terrestrial processes such as photosynthesis and the movement of water
 through soils can influence climate from local to global scales by
 controlling land-to-atmosphere fluxes of water, energy, and carbon.
 Terrestrial processes are also influenced by climate, as demonstrated by
 the large body of research exploring how the terrestrial water and carbon
 cycles respond to climate change. Biogeophysical land-atmosphere feedbacks
 can therefore potentially modulate changes in land surface water and
 carbon fluxes. However, the influence of land-atmosphere feedbacks on
 terrestrial processes has been underexplored. Most previous
 studies evaluate the biogeophysical impact of land surface changes either
 in a land only context (i.e., not accounting for land-atmosphere feedbacks
 at all) or in a fully coupled context (i.e., quantifying the net change in
 land fluxes without the ability to attribute how much of the response is
 from feedbacks). While some coupled studies invoke land-atmosphere
 feedbacks as important drivers of the net coupled land surface changes, it
 is rare for coupled modeling studies to unambiguously disentangle the
 extent to which (or mechanisms through which) land-atmosphere feedbacks
 contribute to the net coupled land response. In isolation, neither coupled
 nor land-only simulations alone are able to directly disentangle the
 influence of land-atmosphere feedbacks on the overall coupled change in
 land water and carbon fluxes. We ran idealized model experiments in the
 Community Land Model version 5 (CLM5) that can be used to disentangle the
 atmosphere-to-land branch of the overall land-atmosphere feedback.
description: We ran idealized simulations in the Community Land Model version
 5 (CLM5) to isolate how different atmospheric drivers influence
 terrestrial processes. In each idealized simulation (as described in table
 below), we modified a different atmospheric driver in the atmospheric
 forcing data. This method allows us to quantify the terrestrial response
 to mean state climate changes, but does not assess the terrestrial
 response to shorter timescale atmospheric variability. In this data
 repository we include simulations from the reference case and the
 "Increase temp", "Decrease temp", and "Increase
 humidity" idealized simulations.  Our synthetic
 meteorology simulations were based on the land-only preindustrial control
 from a perturbed parameter ensemble in CLM5 (https://doi.org/10.5061/dryad.0k6djhb73). In this control simulation, CLM5 was run with default parameters under preindustrial conditions where the atmospheric state was prescribed at 3-hourly resolution to match the atmosphere simulated by the Community Atmosphere Model version 6 in a preindustrial coupled equilibrium simulation in the Community Earth System Model version 2 (CESM2). The idealized simulations in this repository branched from year 119 of that preindustrial control simulation and were run for 20 years. Simulation Variable Name Variable description Perturbation Increase temp a2x3h_Sa_tbot Temperature at the lowest model level +1 K Decrease temp a2x3h_Sa_tbot Temperature at the lowest model level -1 K Increase precip a2x3h_Faxa_rainl Large-scale precipitation rate 10% a2x3h_Faxa_rainc   Convective precipitation rate 10% a2x3h_Faxa_snowl   Large scale snow rate 10% a2x3h_Faxa_snowc   Convective snow rate 10% Decrease precip a2x3h_Faxa_rainl  Large-scale precipitation rate -10% a2x3h_Faxa_rainc  Convective precipitation rate -10% a2x3h_Faxa_snowl  Large scale snow rate -10% a2x3h_Faxa_snowc  Convective snow rate -10% Increase SWdown a2x1hi_Faxa_swndr Direct near-infrared incident solar radiation 10% a2x1hi_Faxa_swvdr Direct visible incident solar radiation 10% a2x1hi_Faxa_swndf Diffuse near-infrared incident solar radiation 10% a2x1hi_Faxa_swvdf Diffuse visible incident solar radiation 10% Increase LWdown    a2x3h_Faxa_lwdn Downward longwave heat flux 10% Increase humidity  a2x3h_Sa_shum  Specific humidity at the lowest model level  10%
description: # Synthetic Meteorology Model Simulations
 [https://doi.org/10.5061/dryad.h44j0zpw1](https://doi.org/10.5061/dryad.h44j0zpw1) ## **Data structure** This dataset is organized into four zipped folders: `OFFL0000_PI_SOM_decreaseTemp1K_derecho.tar.gz` (the "Decrease temp" simulation),  `OFFL0000_PI_SOM_increaseTemp1deg_derecho.tar.gz` (the "Increase temp" simulation), `OFFL0000_PI_SOM_increaseHumidity10pct_derecho.tar.gz` (the "Increase humidity" simulation), and `OFFL0000_PI_SOM_referenceCase_02.tar.gz` (the reference case). Each folder contains monthly model output in single variable timeseries for the following variables: * FPSN: Photosynthesis (umol m^-2 s^-1) * GPP: Gross primary production (gC/m^2/s) * PBOT: atmospheric pressure at surface (Pa) * TBOT: atmospheric air temperature (K) * TLAI: total projected leaf area index (m^2/m^2) * TSAI: total projected stem area index (m^2/m^2) Metadata are included in the netcdf files. These can be opened with HDFView