DOI: 10.5061/dryad.stqjq2c6g
title: CONUS VPD and soil moisture thresholds for suboptimal vegetation function

description: The dataset contains minimum and maximum vapor pressure deficit (VPD) and
 soil moisture parameters that define the range of suboptimal vegetation
 function (i.e., between uninhibited photosynthesis and complete
 shutdown). The ranges were estimated using the Dynamic Canopy
 Biophysical Properties model (DCBP; Lowman & Barros 2018), which
 consists of a phenology forecasting model based on the growing season
 index (GSI), which provides a unitless measure of the potential phenologic
 state of vegetation based on the concurrent meteorological conditions
 (Jolly et al. 2005).
description: The Dynamic Canopy Biophysical Properties model (DCBP) was used to determine the range for suboptimal vegetation function for VPD and soil moisture (Lowman & Barros 2018). This model combines phenologic forecasting with data assimilation to estimate the environmental conditions under which photosynthesis operates. Maximum VPD, VPDmax, and minimum soil moisture, SMmin, denote when plants shut down photosynthetic activity due to water stress in the atmosphere and soil, respectively. The DCBP consists of a phenology forecasting model based on the growing season index (GSI), which provides a unitless measure of the potential phenologic state of vegetation based on the concurrent meteorological conditions (Jolly et al. 2005). In the DCBP, the meteorological conditions that affect plant growth and senescence include minimum daily temperature, daylength, VPD, and soil water potential (Lowman & Barros 2018). The GSI is used to determine a growth vector which takes into account the potential and current phenologic state. This growth vector is then used to estimate how FPAR and LAI will change in the next time step (Lowman & Barros 2018; Stockli et al. 2008). An inverse modeling framework is used to estimate the parameters that define the GSI and provide the thresholds for VPD and soil water potential within the DCBP. Specifically, minimum and maximum VPD and soil water potential are determined using an Ensemble Kalman Filter (EnKF) that jointly estimates the GSI parameters and the phenologic states of FPAR and LAI (Lowman & Barros 2018; Stockli et al. 2008; Moradkhani et al. 2005). MODIS FPAR and LAI data are assimilated at an 8-day interval (the native temporal resolution of the satellite product) to constrain and reduce error in the GSI parameter estimates. The GSI parameters that define the range of suboptimal vegetation function are produced on a pixel-by-pixel basis at the 0.125° resolution of the NLDAS-2 spatial grid (Xia et al. 2012). The specific parameters that are used in this study to indicate vegetation stress related to flash drought are maximum VPD and minimum soil water potential. Minimum soil water potential is converted to a minimum soil moisture threshold on a pixel-by-pixel basis using the Clapp and Hornberger equation (Dingman 2015; Campbell 1974). Works Cited: Campbell, G.S., 1974. A Simple Method for Determining Unsaturated Conductivity from Moisture Retention Data. Soil Science 117, 311–314. Dingman, S.L., 2015. Physical Hydrology: Third Edition. Waveland Press. Lowman, L.E.L., Barros, A.P., 2018. Predicting canopy biophysical properties and sensitivity of plant carbon uptake to water limitations with a coupled eco-hydrological framework. Ecological Modelling 372, 33–52. https://doi.org/10.1016/j.ecolmodel.2018.01.011 Moradkhani, H., Sorooshian, S., Gupta, H.V., Houser, P.R., 2005. Dual state–parameter estimation of hydrological models using ensemble Kalman filter. Advances in Water Resources 28, 135–147. https://doi.org/10.1016/j.advwatres.2004.09.002 Stöckli, R., Rutishauser, T., Dragoni, D., O’Keefe, J., Thornton, P.E., Jolly, M., Lu, L., Denning, A.S., 2008. Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research: Biogeosciences 113. https://doi.org/10.1029/2008JG000781
description: The DCBP parameters that determine the thresholds for VPD and
 soil moisture are stored in netCDF files. Each file is stored as a matrix
 on the NLDAS CONUS grid at 0.125° spatial
 resolution and represents the average of 2000 ensemble members. There are
 four separate files in total: 
 vpd_max_avg.nc: Maximum VPD threshold
 vpd_min_avg.nc: Minimum VPD threshold
 sm_max_avg.nc: Maximum soil moisture threshold
 sm_min_avg.nc: Minimum soil moisture threshold
description: # CONUS VPD and soil moisture thresholds for suboptimal vegetation
 function
 [https://doi.org/10.5061/dryad.stqjq2c6g](https://doi.org/10.5061/dryad.stqjq2c6g) ## Description of the data and file structure The DCBP parameters that determine the thresholds for VPD and soil moisture are stored in netCDF files. Each file is stored as a matrix on the NLDAS CONUS grid at 0.125° spatial resolution and represents the average of 2000 ensemble members. There are four separate files in total: 1. vpd\_max\_avg.nc: Maximum VPD threshold 2. vpd\_min\_avg.nc: Minimum VPD threshold 3. sm\_max\_avg.nc: Maximum soil moisture threshold 4. sm\_min\_avg.nc: Minimum soil moisture threshold The units for VPD are kPa and the units for soil moisture are m3/m3. Missing data are stored as NaN and occur where pixels are labeled as water in the NLDAS-2 Land/Sea Mask. ## Sharing/Access information Data was derived from the following sources: * Mitchell, K.E., Lohmann, D., Houser, P.R., Wood, E.F., Schaake, J.C., Robock, A., Cosgrove, B.A., Sheffield, J., Duan, Q., Luo, L. and Higgins, R.W., 2004. The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. *Journal of Geophysical Research: Atmospheres*, *109*(D7). * Myneni, R., Y. Knyazikhin, and T. Park, 2015. MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 global 500 m SIN grid V006. NASA EOSDIS Land Processes DAAC, accessed 21 July 2021, [https://lpdaac.usgs.gov/products/mod15a2hv006/](https://lpdaac.usgs.gov/products/mod15a2hv006/). * Tobin, K.J., Crow, W.T., Dong, J. and Bennett, M.E., 2019. Validation of a new root-zone soil moisture product: Soil MERGE. *IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing*, *12*(9), pp.3351-3365. * Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., Meng, J. and Livneh, B., 2012. Continental‐scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS‐2): 1. Intercomparison and application of model products. *Journal of Geophysical Research: Atmospheres*, *117*(D3). ## Code/Software N/A