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Penman-Monteith-Leuning Evapotranspiration in GEE
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README.md

Penman-Monteith-Leuning Evapotranspiration In Google Earth Engine

Modeling framework

Penman-Monteith-Leuning model (abbreviated as PML_V1) was proposed by Leuning et al. (2008), and further improved by Zhang et al., (2010, 2016). In PML, evaporation is divided into: transpiration from vegetation (Ec), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei).

PML_V2 was developed by Gan et al., (2018) and Zhang et al., (2019), which coupled ET and gross primary products via canopy conductance theory. They are both in the resolution of 500 m and 8-day, and range from -60°S to 90°N.

Figure 1. Flowchart of global forcing data processing and PML_V2 modeling processes.

Variable Description Unit
Tmax daily maximum temperature °C
Tmin daily minimum temperature °C
Tavg daily mean temperature °C
Pa atmosphere pressure kPa
U wind speed at 10-m height m/s
q specific humidity kg/kg
Prcp precipitation mm/d
Rln inward longwave solar radiation W/m2
Rs inward shortwave solar radiation W/m2
Pi the difference of Prcp and Ei mm/d
Es_eq equilibrium evaporation mm/d
ET_water evaporation from water body, snow and ice mm/d
qc quality control variable for albedo and surface emissivity. -

Data product

Table 1. PML_V1 and PML_V2 bands information (PML_V1 have no GPP band, other bands are some).
Note: Only PMLV1 is available currently.

BandName Units Scale Description
GPP gC m-2 d-1 0.01 Gross primary product
Ec mm d-1 0.01 Vegetation transpiration
Es mm d-1 0.01 Soil evaporation
Ei mm d-1 0.01 Interception from vegetation canopy
ET_water mm d-1 0.01 Water body, snow and ice evaporation. Penman
evapotranspiration is regarded as actual evaporation for them.
qc - - Interpolation information for Albedo and Emissivity.
Bitmask for qc:
Bits 0-2: Emissivity interpolation information
0: good value, no interpolation
1: linear interpolation
2: history 8-day average interpolation
3: history monthly average interpolation
Bits 3-5: Albedo interpolation information
Same as Emissivity.

1.1 Access data

Click the following links to get the access. The corresponding links are:

1.2 Data download

PML products are standard ee.ImageCollection object in GEE. You can clip regional data by polygon shapefile from ee.ImageCollection.

  1. For small regions, you can transform ee.ImageCollection into multiple bands ee.Image. In this way, you can download all the dataset in a time:
  2. For large regions, you have to download trough ee.ImageCollection.

Clip and export the regional data you need by the polygon shapefile you uploaded. This is a little example.

Updates

  • 2019-08-02: extend the time period to 2018

References:

[1]. Zhang, Y., Kong, D., Gan, R., Chiew, F.H.S., McVicar, T.R., Zhang, Q., and Yang, Y.. (2019) Coupled estimation of 500m and 8-day resolution global evapotranspiration and gross primary production in 2002-2017. Remote Sens. Environ. 222, 165-182, https://doi:10.1016/j.rse.2018.12.031

[2]. Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing*, 155(May), 13–24. https://doi.org/10.1016/j.isprsjprs.2019.06.014

[3]. Zhang, Y., Peña-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y.Y., Miralles, D.G., Pan, M., 2016. Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci. Rep. 6, 19124. https://doi.org/10.1038/srep19124

[4]. Zhang, Y., Leuning, R., Hutley, L.B., Beringer, J., McHugh, I., Walker, J.P., Using long-term water balances to parameterize surface conductances and calculate evaporation at 0.05°spatial resolution. Water Resour. Res. 46. https://doi.org/10.1029/2009WR008716

[5]. Leuning, R., Zhang, Y.Q., Rajaud, A., Cleugh, H., Tu, K., 2008. A simple surface conductance model to estimate regional evaporation using MODIS leaf area index and the Penman- Monteith equation. Water Resour. Res. 44. https://doi.org/10.1029/2007WR006562

[6]. Gan, R., Zhang, Y., Shi, H., Yang, Y., Eamus, D., Cheng, L., Chiew, F.H.S., Yu, Q., 2018. Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems. Ecohydrology. e1974. https://doi.org/10.1002/eco.1974

[7]. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031

Acknowledgements

Keep in mind that this repository is released under a GPL2 license, which permits commercial use but requires that the source code (of derivatives) is always open even if hosted as a web service.

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