DATA

Global Actual Evapotranspiration

- 0.5 deg gridded global, monthly evapotranspiration ascii files 1986-1995

- 1.0 deg gridded global, monthly evapotranspiration ascii files 1984-2006

- Cite: Fisher, J.B., Tu, K., Baldocchi, D.D., 2008.  Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites.  Remote Sensing of Environment 112: 901-919.

- 36 km gridded global, monthly evapotranspiration netcdf files 2002-2017

- Cite: Fisher, J.B., Tu, K., Baldocchi, D.D., 2008.  Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites.  Remote Sensing of Environment 112: 901-919.

- Cite: Purdy, A.J., Fisher, J.B., Goulden, M.L., Colliander, A., Halverson, G., Tu, K., Famiglietti, J.S., 2018. SMAP soil moisture improves global evapotranspiration. Remote Sensing of Environment 219: 1-14.

- 9 km gridded (EASE grid) global, monthly evapotranspiration netcdf files 2015-2017 (PT-JPL enhanced with SMAP soil moisture; higher accuracy): email me (2.5 GB)

- 36 km gridded (EASE grid) global, monthly evapotranspiration netcdf files 2015-2017 (PT-JPL enhanced with SMAP soil moisture; higher accuracy)

- Cite: Purdy, A.J., Fisher, J.B., Goulden, M.L., Colliander, A., Halverson, G., Tu, K., Famiglietti, J.S., 2018. SMAP soil moisture improves global evapotranspiration. Remote Sensing of Environment 219: 1-14.

Global Potential Evapotranspiration

- 0.5 deg gridded global, monthly potential evapotranspiration ascii files 1986-1995 – Priestley Taylor

- 0.5 deg gridded global, monthly potential evapotranspiration ascii files 1986-1995 – Penman-Monteith

- 0.5 deg gridded global, monthly potential evapotranspiration ascii files 1986-1995 – Thornthwaite

- Cite: Fisher, J.B., Whittaker, R., Malhi, Y., 2011. ET Come Home: Potential evapotranspiration in geographical ecology. Global Ecology and Biogeography 20: 1-18.

Global Terrestrial Vegetation Nutrient Limitation

- 0.5 deg gridded global nutrient limitation in terrestrial vegetation contemporary

- Cite: Fisher, J.B., Badgley, G., Blyth, E., 2012. Global nutrient limitation in terrestrial vegetation. Global Biogeochemical Cycles 26, GB3007, doi:10.1029/2011GB004252.

Global Canopy Height

 - 1 km gridded global vegetation canopy height for trees > 5 m from ICESat/GLAS (also see: http://lidarradar.jpl.nasa.gov/)

 - Cite: Simard, M., Pinto, N., Fisher, J.B., Baccini, A., 2011. Mapping forest canopy height globally with spaceborne LiDAR. Journal of Geophysical Research–Biogeosciences 116: G04021, doi:10.1029/2011JG001708.

Remotely Sensed Mycorrhizal Association for 4 Regions in the US

- 30 m gridded mycorrhizal association from Landsat

- Cite: Fisher, J.B., Sweeney, S., Brzostek, E.R., Evans, T.P., Johnson, D.J., Myers, J.A., Bourg, N.A., Wolf, A.T., Howe, R.W., Phillips, R.P., 2016. Tree–mycorrhizal associations detected remotely from canopy spectral properties. Global Change Biology 22(7): 2596-2607.

Global Near Surface Meteorology (air temperature, water vapor pressure)

- 5 km daily gridded netcdf MODIS tiles 2001-2014: email me (82 GB total; 1 day sample for Aug 1, 2014: 15 MB)

- Cite: Famiglietti, C.A., Fisher, J.B., Halverson, G., Borbas, E.E., 2018. Global validation of MODIS near-surface air and dew point temperatures. Geophysical Research Letters 45: doi.org/10.1029/2018GL077813.

Sap Flow

- Quercus douglasii (Blue Oak trees) – Tonzi Ranch, 30-minutes, 2005 (6.3MB, Excel)

- Pinus ponderosa (Ponderosa Pine trees) – Blodgett Forest, 30-minutes, 2005 (7.7MB, Excel)

- Arctostaphylos manzanita and Ceanothus cordulatus (Manzanita and Ceanothus shrubs) – Blodgett forest, 30-minutes, 2005 (7.7MB, Excel)

- Note: data provided are raw thermocouple temperatures that can be cleaned, gap-filled, and converted to sap velocity/flow according to the user.

- Cite: Fisher, J.B., Baldocchi, D.D., Misson, L., Dawson, T., Goldstein, A.H., 2007.  What the towers don’t see at night: Nocturnal sap flow in trees and shrubs at two AmeriFlux sites in California.  Tree Physiology 27(4): 597-610.

MODELS

Evapotranspiration (PT-JPL)

- PT-JPL: MATLAB for spatial arrays (e.g., remote sensing)

- PT-JPL: Python

- PT-JPL: Excel for point values (e.g., flux tower)

- Cite: Fisher, J.B., Tu, K., Baldocchi, D.D., 2008.  Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites.  Remote Sensing of Environment 112: 901-919.

Plant Nitrogen Uptake (FUN: Fixation & Uptake of Nitrogen)

- FUN: Matlab

- FUN: Fortran

- FUN: Excel

- Cite: Fisher, J.B., Sitch, S., Malhi, Y., Fisher, R.A., Huntingford, C., Tan, S.-Y., 2010. Carbon cost of plant nitrogen acquisition: A mechanistic, globally applicable model of plant nitrogen uptake, retranslocation, and fixation. Global Biogeochemical Cycles 24: GB1014, doi:10.1029/2009GB003621.