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

Abstract

Abstract. We introduce the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM), a remote-sensingbased approach for generating accurate, high-resolution ( ≥ 1 km 2 , 3 hourly) estimates of net ecosystem CO 2 exchange (NEE). PolarVPRM simulates NEE using polarspecific 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)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(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)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(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)(2002)(2003)(2004) to a carbon sink (2005)(2006)(2007)(2008)(2009)(2010) to again a source (2011)(2012) in response to changing environmental conditions.

Investigating Alaskan methane and carbon dioxide fluxes using measurements from the CARVE tower

“…CO 2 enhancements at the CARVE tower site are replicated remarkably well by the WRF-STILT model when convolved with PolarVPRM biogenic CO 2 fluxes (Luus and Lin, 2015), with a few noted exceptions. The high correlation between modeled and observed CO 2 gives confidence in the STILT footprints and the WRF meteorological model that was used to generate them.…”

“…The CO 2 measurements at the CRV tower were interpreted with the assistance of biospheric CO 2 flux estimates generated by the PolarVPRM (Luus and Lin, 2015). PolarVPRM captures the strong diurnal and seasonal variability of CO 2 fluxes parsimoniously, according to empirical associations between environmental conditions and eddy covariance measurements of CO 2 , and regionally across Alaska (3-hourly, 1/6 × 1/4 • latitude × longitude), using data products from the North American Regional Reanalysis (NARR) (Mesinger et al, 2006) and the Moderate Resolution Imaging Spectroradiometer (MODIS).…”

“…Henderson et al (2015) provide details of the model configuration and validation of the meteorological simulations. We assess CO 2 fluxes from the land surface of Alaska by convolving surface fluxes from the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM) (Luus and Lin, 2015) with the footprints and comparing the resulting modeled CO 2 enhancements with tower observations. To infer CH 4 fluxes, we have convolved the footprints with a constant (in space and time) flux model and an elevation-based flux model and scaled the results to monthly mean observed enhancements to estimate monthly average fluxes over a wide region, using similar methods as Chang et al (2014).…”

Spring photosynthetic onset and net CO2 uptake in Alaska triggered by landscape thawing

“…Previous work using chamber data shows higher GPP in 2013 than in 2014 at ATQ(Davidson et al, 2016), consistent with higher TDD (720 days). These findings indicate higher GPP in 2005, which supports a calibration bias at ATQ and argues for an updated calibration of PVPRM using the longer record of data at existing eddy covariance towers(Luus & Lin, 2015) and inclusion of new tundra and boreal towers (http://ameriflux.lb l.gov/data/).…”

The influence of daily meteorology on boreal fire emissions and regional trace gas variability

“…For CO 2 we also estimated and removed the influence of net ecosystem exchange (NEE) associated with gross primary production and ecosystem respiration fluxes. CO 2 anomalies originating from NEE were estimated by coupling the Polar Vegetation Photosynthesis Respiration Model (PVPRM) [Luus and Lin, 2015] fluxes with PWRF-STILT [Henderson et al, 2015] simulations at the CRV tower. PVPRM provided 3-hourly estimates of net ecosystem exchange from high-latitude ecosystems for regions north of 55°N.…”