Effects of in-situ and reanalysis climate data on estimation of cropland gross primary production using the Vegetation Photosynthesis Model

Cui Jin, Xiangming Xiao, Pradeep Wagle, Timothy Griffis, Jinwei Dong, Chaoyang Wu, Yuanwei Qin, David R. Cook

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Satellite-based Production Efficiency Models (PEMs) often require meteorological reanalysis data such as the North America Regional Reanalysis (NARR) by the National Centers for Environmental Prediction (NCEP) as model inputs to simulate Gross Primary Production (GPP) at regional and global scales. This study first evaluated the accuracies of air temperature (TNARR) and downward shortwave radiation (RNARR) of the NARR by comparing with in-situ meteorological measurements at 37 AmeriFlux non-crop eddy flux sites, then used one PEM - the Vegetation Photosynthesis Model (VPM) to simulate 8-day mean GPP (GPPVPM) at seven AmeriFlux crop sites, and investigated the uncertainties in GPPVPM from climate inputs as compared with eddy covariance-based GPP (GPPEC). Results showed that TNARR agreed well with in-situ measurements; RNARR, however, was positively biased. An empirical linear correction was applied to RNARR, and significantly reduced the relative error of RNARR by ~25% for crop site-years. Overall, GPPVPM calculated from the in-situ (GPPVPM(EC)), original (GPPVPM(NARR)) and adjusted NARR (GPPVPM(adjNARR)) climate data tracked the seasonality of GPPEC well, albeit with different degrees of biases. GPPVPM(EC) showed a good match with GPPEC for maize (Zea mays L.), but was slightly underestimated for soybean (Glycine max L.). Replacing the in-situ climate data with the NARR resulted in a significant overestimation of GPPVPM(NARR) (18.4/29.6% for irrigated/rainfed maize and 12.7/12.5% for irrigated/rainfed soybean). GPPVPM(adjNARR) showed a good agreement with GPPVPM(EC) for both crops due to the reduction in the bias of RNARR. The results imply that the bias of RNARR introduced significant uncertainties into the PEM-based GPP estimates, suggesting that more accurate surface radiation datasets are needed to estimate primary production of terrestrial ecosystems at regional and global scales.

Original languageEnglish (US)
Pages (from-to)240-250
Number of pages11
JournalAgricultural and Forest Meteorology
Volume213
DOIs
StatePublished - Nov 1 2015

Bibliographical note

Funding Information:
This study was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture , under award number 2013-69002-23146 , and a research grant from the National Science Foundation EPSCoR program (Project No. IIA-1301789 ). We would like to thank Drs. Andrew E. Suyker, John Baker, Tilden Meyers, Roser Matamala for providing eddy flux data.

Keywords

  • AmeriFlux
  • Downward shortwave radiation
  • MODIS
  • NARR
  • Vegetation Photosynthesis Model (VPM)
  • Vegetation indices

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