A modified Vegetation Photosynthesis and Respiration Model (VPRM) for the eastern USA and Canada, evaluated with comparison to atmospheric observations and other biospheric models

2021 ◽  
Author(s):  
Sharon Gourdji ◽  
Anna Karion ◽  
Israel Lopez-Coto ◽  
Subhomoy Ghosh ◽  
Kim Lynn Mueller ◽  
...  
Keyword(s):  
Respiration Model ◽  
Eastern Usa ◽  
Atmospheric Observations ◽  
Photosynthesis And Respiration

scholarly journals The Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM): a parsimonious, satellite data-driven model of high-latitude CO<sub>2</sub> exchange

2015 ◽  
Vol 8 (2) ◽  
pp. 979-1027 ◽  
Author(s):  
K. A. Luus ◽  
J. C. Lin
Keyword(s):  
Eddy Covariance ◽  
North American ◽  
High Latitude ◽  
Growing Season ◽  
Growing Season Length ◽  
The North ◽  
Air Temperatures ◽  
High Latitude Region ◽  
Respiration Model ◽  
Photosynthesis And Respiration

Abstract. We introduce the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), a remote-sensing based approach for generating accurate, high resolution (≥1 km2, three-hourly) estimates of net ecosystem CO2 exchange (NEE). PolarVPRM simulates NEE using polar-specific vegetation classes, and by representing high-latitude influences on NEE. We present a description, validation, and error analysis (first-order Taylor expansion) of PolarVPRM, followed by an examination of per-pixel trends (2001–2012) in model output for the North American terrestrial region north of 55° N. PolarVPRM was validated against eddy covariance observations from nine North American sites, of which three were used in model calibration. PolarVPRM performed well over all sites. Model intercomparisons indicated that PolarVPRM showed slightly better agreement with eddy covariance observations relative to existing models. Trend analysis (2001–2012) indicated that warming air temperatures and drought stress in forests increased growing season rates of respiration, and decreased rates of net carbon uptake by vegetation when air temperatures exceeded optimal temperatures for photosynthesis. Concurrent increases in growing season length at Arctic tundra sites allowed increases in photosynthetic uptake over time by tundra vegetation. PolarVPRM estimated that the North American high-latitude region changed from a carbon source (2001–2004) to sink (2005–2010) to source (2011–2012) in response to changing environmental conditions.

Optimization and validation of the vegetation photosynthesis and respiration model in a temperate broad-leaved Korean pine forest

2017 ◽  
Vol 37 (20) ◽  
Author(s):  
张嘉荣 ZHANG Jiarong ◽  
王咏薇 WANG Yongwei ◽  
张弥 ZHANG Mi ◽  
刁一伟 DIAO Yiwei ◽  
刘诚 LIU Cheng
Keyword(s):  
Pine Forest ◽  
Korean Pine ◽  
Respiration Model ◽  
Korean Pine Forest ◽  
Photosynthesis And Respiration

scholarly journals Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM)

2013 ◽  
Vol 10 (10) ◽  
pp. 6485-6508 ◽  
Author(s):  
B. Badawy ◽  
C. Rödenbeck ◽  
M. Reichstein ◽  
N. Carvalhais ◽  
M. Heimann
Keyword(s):  
Interannual Variability ◽  
Ecosystem Respiration ◽  
Spatial Scales ◽  
Gross Primary Production ◽  
Technical Note ◽  
Atmospheric Co2 ◽  
Limiting Factor ◽  
Respiration Model ◽  
Photosynthesis And Respiration ◽  
Process Based Models

Abstract. We present a Simple Diagnostic Photosynthesis and Respiration Model (SDPRM) that has been developed based on pre-existing formulations. The photosynthesis model is based on the light use efficiency logic for calculating the gross primary production (GPP), while the ecosystem respiration (Reco) is a modified version of an Arrhenius-type equation. SDPRM is driven by satellite-derived fAPAR (fraction of Absorbed Photosynthetically Active Radiation) and climate data from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR). The model estimates 3-hourly values of GPP for seven major biomes and daily Reco. The motivation is to provide a priori fields of surface CO2 fluxes with fine temporal and spatial scales for atmospheric CO2 inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO2 inversion or simulated from process-based models. In this Technical Note, different analyses were carried out to test the sensitivity of the estimated fluxes of GPP and CO2 to their driving forces. The spatial patterns of the climatic controls (temperature, precipitation, water) on the interannual variability of GPP are consistent with previous studies, even though SDPRM has a very simple structure and few adjustable parameters and hence it is much easier to modify in an inversion than more sophisticated process-based models. In SDPRM, temperature is a limiting factor for the interannual variability of Reco over cold boreal forest, while precipitation is the main limiting factor of Reco over the tropics and the southern hemisphere, consistent with previous regional studies.

scholarly journals Assessing biotic contributions to CO<sub>2</sub> fluxes in northern China using the Vegetation, Photosynthesis and Respiration Model (VPRM-CHINA) and observations from 2005 to 2009

2018 ◽  
Vol 15 (21) ◽  
pp. 6713-6729 ◽  
Author(s):  
Archana Dayalu ◽  
J. William Munger ◽  
Steven C. Wofsy ◽  
Yuxuan Wang ◽  
Thomas Nehrkorn ◽  
...  
Keyword(s):  
Growing Season ◽  
Northern China ◽  
Time Of Day ◽  
Measured Signal ◽  
Co2 Uptake ◽  
Top Down ◽  
Spatiotemporal Resolution ◽  
Study Region ◽  
Respiration Model ◽  
Photosynthesis And Respiration

Abstract. Accurately quantifying the spatiotemporal distribution of the biological component of CO2 surface–atmosphere exchange is necessary to improve top-down constraints on China's anthropogenic CO2 emissions. We provide hourly fluxes of CO2 as net ecosystem exchange (NEE; µmol CO2 m−2 s−1) on a 0.25∘×0.25∘ grid by adapting the Vegetation, Photosynthesis, and Respiration Model (VPRM) to the eastern half of China for the time period from 2005 to 2009; the minimal empirical parameterization of the VPRM-CHINA makes it well suited for inverse modeling approaches. This study diverges from previous VPRM applications in that it is applied at a large scale to China's ecosystems for the first time, incorporating a novel processing framework not previously applied to existing VPRM versions. In addition, the VPRM-CHINA model prescribes methods for addressing dual-cropping regions that have two separate growing-season modes applied to the same model grid cell. We evaluate the VPRM-CHINA performance during the growing season and compare to other biospheric models. We calibrate the VPRM-CHINA with ChinaFlux and FluxNet data and scale up regionally using Weather Research and Forecasting (WRF) Model v3.6.1 meteorology and MODIS surface reflectances. When combined with an anthropogenic emissions model in a Lagrangian particle transport framework, we compare the ability of VPRM-CHINA relative to an ensemble mean of global hourly flux models (NASA CMS – Carbon Monitoring System) to reproduce observations made at a site in northern China. The measurements are heavily influenced by the northern China administrative region. Modeled hourly time series using vegetation fluxes prescribed by VPRM-CHINA exhibit low bias relative to measurements during the May–September growing season. Compared to NASA CMS subset over the study region, VPRM-CHINA agrees significantly better with measurements. NASA CMS consistently underestimates regional uptake in the growing season. We find that during the peak growing season, when the heavily cropped North China Plain significantly influences measurements, VPRM-CHINA models a CO2 uptake signal comparable in magnitude to the modeled anthropogenic signal. In addition to demonstrating efficacy as a low-bias prior for top-down CO2 inventory optimization studies using ground-based measurements, high spatiotemporal resolution models such as the VPRM are critical for interpreting retrievals from global CO2 remote-sensing platforms such as OCO-2 and OCO-3 (planned). Depending on the satellite time of day and season of crossover, efforts to interpret the relative contribution of the vegetation and anthropogenic components to the measured signal are critical in key emitting regions such as northern China – where the magnitude of the vegetation CO2 signal is shown to be equivalent to the anthropogenic signal.

scholarly journals The Polar Vegetation Photosynthesis and Respiration Model: a parsimonious, satellite-data-driven model of high-latitude CO<sub>2</sub> exchange

2015 ◽  
Vol 8 (8) ◽  
pp. 2655-2674 ◽  
Author(s):  
K. A. Luus ◽  
J. C. Lin
Keyword(s):  
Eddy Covariance ◽  
North American ◽  
High Latitude ◽  
Growing Season ◽  
Growing Season Length ◽  
The North ◽  
Air Temperatures ◽  
High Latitude Region ◽  
Respiration Model ◽  
Photosynthesis And Respiration

Abstract. We introduce the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), a remote-sensing-based approach for generating accurate, high-resolution (≥ 1 km2, 3 hourly) estimates of net ecosystem CO2 exchange (NEE). PolarVPRM simulates NEE using polar-specific vegetation classes, and by representing high-latitude influences on NEE, such as the influence of soil temperature on subnivean respiration. We present a description, validation and error analysis (first-order Taylor expansion) of PolarVPRM, followed by an examination of per-pixel trends (2001–2012) in model output for the North American terrestrial region north of 55° N. PolarVPRM was validated against eddy covariance (EC) observations from nine North American sites, of which three were used in model calibration. Comparisons of EC NEE to NEE from three models indicated that PolarVPRM displayed similar or better statistical agreement with eddy covariance observations than existing models showed. Trend analysis (2001–2012) indicated that warming air temperatures and drought stress in forests increased growing season rates of respiration, and decreased rates of net carbon uptake by vegetation when air temperatures exceeded optimal temperatures for photosynthesis. Concurrent increases in growing season length at Arctic tundra sites allowed for increases in photosynthetic uptake over time by tundra vegetation. PolarVPRM estimated that the North American high-latitude region changed from a carbon source (2001–2004) to a carbon sink (2005–2010) to again a source (2011–2012) in response to changing environmental conditions.

A MODIS-based ecosystem respiration model and its application in optimizing vegetation photosynthesis and respiration model: A case study of two terrestrial ecosystems in Northern China

2020 ◽  
Author(s):  
Yong Hao ◽  
Haimei Jiang ◽  
Haotian Ye
Keyword(s):  
Ecosystem Respiration ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Grassland Ecosystem ◽  
Linear Temperature ◽  
Growing Seasons ◽  
Respiration Model ◽  
Photosynthesis And Respiration ◽  
Semi Arid ◽  
Cropland Ecosystem

&lt;p&gt;Turbulent flux data observed in surface layer during growing seasons at Xilinhaote National Climatic Observatory and Jinzhou Agroecosystem Observatory and remote sensing data were analyzed to acquire main environmental factors and biological factors which drive the ecosystem respiration (R&lt;sub&gt;eco&lt;/sub&gt;). Then the key driven factors of R&lt;sub&gt;eco&lt;/sub&gt;&amp;#160;were selected to optimize a semi-empirical ecosystem respiration model. Based on the new ecosystem respiration model, respiration part of Vegetation Photosynthesis and Respiration Model&amp;#160;(VPRM) was optimized and its simulation effect of net ecosystem exchange (NEE) was validated in a semi-arid grassland ecosystem and a maize cropland ecosystem.&lt;/p&gt;&lt;p&gt;Compared to the linear temperature model, the nocturnal R&lt;sub&gt;eco&lt;/sub&gt;&amp;#160;simulated by the new ecosystem respiration model&amp;#160;agreed remarkably better with the observed R&lt;sub&gt;eco&lt;/sub&gt;&amp;#160;(at Xilinhaote site, R&lt;sup&gt;2&lt;/sup&gt;&amp;#160;increased from 0.08 to 0.61 in 2010-2012; at Jinzhou site, R&lt;sup&gt;2&lt;/sup&gt;&amp;#160;increased from 0.13 to 0.55 in 2010).&amp;#160;And the new ecosystem respiration model showed similar performance in predicting nocturnal R&lt;sub&gt;eco&lt;/sub&gt;&amp;#160;(at Xilinhaote site, R&lt;sup&gt;2&lt;/sup&gt;&amp;#160;increased from 0.32 to 0.57 in 2013; at Jinzhou site, R&lt;sup&gt;2&lt;/sup&gt;&amp;#160;increased from 0.33 to 0.61 in 2011).&lt;/p&gt;&lt;p&gt;This study also indicates that optimization of the respiration part of VPRM can improve the simulation effect of NEE during nighttime of the growing seasons in a semi-arid grassland ecosystem and a maize cropland ecosystem, R&lt;sup&gt;2&lt;/sup&gt;&amp;#160;between the modeled NEE and the observed NEE increased from 0.30 to 0.57 in the semi-arid grassland ecosystem and&lt;sup&gt;&amp;#160;&lt;/sup&gt;increased from 0.03 to 0.48 in the maize cropland ecosystem. However, in the whole time of the growing seasons, little difference was found between the modelled NEE by the original VPRM model and that by our modified VPRM model, probably for the reason that daytime NEE is mainly dominated by vegetation photosynthesis.&lt;/p&gt;

scholarly journals A satellite-based biosphere parameterization for net ecosystem CO2exchange: Vegetation Photosynthesis and Respiration Model (VPRM)

2008 ◽  
Vol 22 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Pathmathevan Mahadevan ◽  
Steven C. Wofsy ◽  
Daniel M. Matross ◽  
Xiangming Xiao ◽  
Allison L. Dunn ◽  
...  
Keyword(s):  
Respiration Model ◽  
Photosynthesis And Respiration
Sign in / Sign up

Export Citation Format

Share Document