MONSOON PROJECT SURVEY DATA OUTPUTS: Majadas de Tietar Tree-Grass Savanna Ecosystem 05/05/2021-20/05/2021 Here we make available high resolution (0.82 cm) energy and water flux maps from unmanned aerial system (UAS) data collected using a Micasense Altum in May 2021. We use the Two Source Energy Balance Model (via pyTSEB) and include model inputs and outputs. We use the Priestley Taylor (TSEB hereafter) and Dual Time Difference (DTD hereafter) methods in pyTSEB, the details of which can be found here pyTSEB https://pytseb.readthedocs.io/en/latest/index.html. The data collection method largely follows https://www.mdpi.com/2072-4292/13/7/1286, however a new paper detailing these surveys in Majadas is under review (as of November 2021). This upload includes the following gridded datasets: Model inputs Zipfiles are named according to their collection date (DDMMYYYY.7z). Within each zipfile are the datasets corresponding to different flight times UTC +2 (hhmm_DDMMYY). Within each survey folder are rasters with descriptive filenames using the following format: Product type_Resolution_survey area_date_flight time.tif The following prefixes denote the Product types: CHM_... = Canopy Height Model (m) GFrac2_... = Green Fraction (0-1) MSpec_... = Raw multispectral dataset from Altum (Blue, Green, Red, NIR, Rededge, LWIR) TEmpK_... = Radiometric Surface Temperature (empirical calibration, K) TRawK_... = Radiometric Surface Temperature (no calibration, K) LST2_... = Radiometric Surface Temperature (calibrated using methods outlined here https://www.mdpi.com/2072-4292/12/7/1075, K) Grass_... = grass vegetation mask Tree_... = tree vegetation mask We also supply the config files used to generate TSEB and DTD. To run these you will need to edit the filepaths according to your own system. Model Outputs Majadas_TSEB_EMP_outputs.7z = Two Source Energy Balance (pyTSEB) model outputs (using the Priestley-Taylor method), using radiometric temperature datasets calibrated empirically. Majadas_DTD_EMP_outputs.7z = TSEB Dual Time Difference model outputs (from pyTSEB) using radiometric temperature datasets calibrated empirically. DTD_ET.7z = Evapotranspiration rasters (calculated using DTD latent heat data) in g m-2 s-1 File names are descriptive: Model type_radiometric temperature method_vegetation type_survey area_date_flighttime.tif Model type = DTD or TSEB Radiometric temperature method = always empirical calibration here vegetation type = grass, tree, or merge (which is both tree and grass) Survey area = N (north, or Nitrogen fertiliser treatment), C (central, or Control fertiliser treatment), S (south, or Nitrogen and Phosphorus fertiliser treatment) date = in DDMMYY format flight time = takeoff time for the drone (hhmm) (UTC+2) To find the exact local time of survey times, please see the table in flight_data3.csv

Deutscher Akademischer Austauschdienst Grant Number 57429870