Terrestrial CO2 Fluxes, Concentrations, Sources and Budget in Northeast China: Observational and Modeling Studies

CO2&#160;fluxes and concentrations are not well understood in Northeast China, where dominant land surface types are mixed forest and cropland. &#160;Here, we analyzed the CO2&#160;fluxes and concentrations using Eddy Covariance&#160;(EC)&#160;measurements, satellite observations, and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF-VPRM). &#160;We also used WRF-VPRM outputs to examine CO2&#160;transport/dispersion, and to quantify the biogenic&#160;and anthropogenic contributions to atmospheric&#160;CO2&#160;concentrations. &#160;Finally, we investigated the uncertainties&#160;of simulating&#160;CO2&#160;fluxes&#160;related to&#160;four VPRM parameters (including&#160;maximum light use efficiency,&#160;photosynthetically active radiation half-saturation value, and two&#160;respiration parameters) using offline ensemble simulations with&#160;randomly selected&#160;parameter values.&#160;&#160;The results indicated that&#160;mixed forests&#160;acted as a larger CO2&#160;source&#160;and sink than rice paddies&#160;on average in 2016 due to a longer growth period and stronger ecosystem respiration, although the minimum EC-measured daily mean net ecosystem exchange (NEE) was smaller at rice paddy&#160;(-10 &#956;mol m-2&#160;s-1) than at mixed forest&#160;(-6.5 &#956;mol m-2&#160;s-1) during the growing season (May through September). &#160;The monthly&#160;fluctuation of column-averaged CO2&#160;concentrations (XCO2) exceeded 10 ppm&#160;in Northeast China during 2016. &#160;Biogenic contribution&#160;(large&#160;negative&#160;in summer&#160;and insignificant in other months)&#160;offset about 70% of anthropogenic contribution of XCO2&#160;in this region. &#160;WRF-VPRM modeling successfully captured seasonal&#160;and episodic variations of NEE and CO2&#160;concentrations, however, the NEE in mixed forest was overestimated during daytime, mainly due to the uncertainties of VPRM parameters,&#160;especially maximum light use efficiency.

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Simulating Spatiotemporal Dynamics of Sichuan Grassland Net Primary Productivity Using the CASA Model and In Situ Observations

The Scientific World JOURNAL ◽

10.1155/2014/956963 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 6

Author(s):

Chuanjiang Tang ◽

Xinyu Fu ◽

Dong Jiang ◽

Jingying Fu ◽

Xinyue Zhang ◽

...

Keyword(s):

Primary Productivity ◽

Net Primary Productivity ◽

Alpine Meadow ◽

Growth Period ◽

Temporal Variations ◽

Light Use Efficiency ◽

Important Indicator ◽

Casa Model ◽

Use Efficiency

Net primary productivity (NPP) is an important indicator for grassland resource management and sustainable development. In this paper, the NPP of Sichuan grasslands was estimated by the Carnegie-Ames-Stanford Approach (CASA) model. The results were validated with in situ data. The overall precision reached 70%; alpine meadow had the highest precision at greater than 75%, among the three types of grasslands validated. The spatial and temporal variations of Sichuan grasslands were analyzed. The absorbed photosynthetic active radiation (APAR), light use efficiency (ε), and NPP of Sichuan grasslands peaked in August, which was a vigorous growth period during 2011. High values of APAR existed in the southwest regions in altitudes from 2000 m to 4000 m. Light use efficiency (ε) varied in the different types of grasslands. The Sichuan grassland NPP was mainly distributed in the region of 3000–5000 m altitude. The NPP of alpine meadow accounted for 50% of the total NPP of Sichuan grasslands.

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Evaluating terrestrial CO2 flux diagnoses and uncertainties from a simple land surface model and its residuals

Biogeosciences ◽

10.5194/bg-11-217-2014 ◽

2014 ◽

Vol 11 (2) ◽

pp. 217-235 ◽

Cited By ~ 16

Author(s):

T. W. Hilton ◽

K. J. Davis ◽

K. Keller

Keyword(s):

Carbon Dioxide ◽

Parameter Estimation ◽

North American ◽

Land Surface ◽

Atmospheric Carbon Dioxide ◽

Ecosystem Respiration ◽

Land Surface Model ◽

Net Ecosystem Exchange ◽

Surface Model ◽

Considerable Uncertainty

Abstract. Global terrestrial atmosphere–ecosystem carbon dioxide fluxes are well constrained by the concentration and isotopic composition of atmospheric carbon dioxide. In contrast, considerable uncertainty persists surrounding regional contributions to the net global flux as well as the impacts of atmospheric and biological processes that drive the net flux. These uncertainties severely limit our ability to make confident predictions of future terrestrial biological carbon fluxes. Here we use a simple light-use efficiency land surface model (the Vegetation Photosynthesis Respiration Model, VPRM) driven by remotely sensed temperature, moisture, and phenology to diagnose North American gross ecosystem exchange (GEE), ecosystem respiration, and net ecosystem exchange (NEE) for the period 2001 to 2006. We optimize VPRM parameters to eddy covariance (EC) NEE observations from 65 North American FluxNet sites. We use a separate set of 27 cross-validation FluxNet sites to evaluate a range of spatial and temporal resolutions for parameter estimation. With these results we demonstrate that different spatial and temporal groupings of EC sites for parameter estimation achieve similar sum of squared residuals values through radically different spatial patterns of NEE. We also derive a regression model to estimate observed VPRM errors as a function of VPRM NEE, temperature, and precipitation. Because this estimate is based on model-observation residuals it is comprehensive of all the error sources present in modeled fluxes. We find that 1 km interannual variability in VPRM NEE is of similar magnitude to estimated 1 km VPRM NEE errors.

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Light absorption by leaf chlorophyll and maximum light use efficiency

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2006.874796 ◽

2006 ◽

Vol 44 (7) ◽

pp. 1933-1935 ◽

Cited By ~ 28

Author(s):

Xiangming Xiao

Keyword(s):

Light Absorption ◽

Light Use Efficiency ◽

Maximum Light ◽

Leaf Chlorophyll ◽

Use Efficiency

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Deriving Maximum Light Use Efficiency From Crop Growth Model and Satellite Data to Improve Crop Biomass Estimation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2016.2605303 ◽

2017 ◽

Vol 10 (1) ◽

pp. 104-117 ◽

Cited By ~ 17

Author(s):

Taifeng Dong ◽

Jiangui Liu ◽

Budong Qian ◽

Qi Jing ◽

Holly Croft ◽

...

Keyword(s):

Growth Model ◽

Satellite Data ◽

Crop Growth ◽

Biomass Estimation ◽

Light Use Efficiency ◽

Crop Growth Model ◽

Maximum Light ◽

Use Efficiency ◽

Crop Biomass

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Global cropland monthly Gross Primary Production in the year 2000

Biogeosciences Discussions ◽

10.5194/bgd-11-3465-2014 ◽

2014 ◽

Vol 11 (2) ◽

pp. 3465-3488

Author(s):

T. Chen ◽

G. R. van der Werf ◽

N. Gobron ◽

E. J. Moors ◽

A. J. Dolman

Keyword(s):

Primary Production ◽

Survey Data ◽

Land Surface ◽

Gross Primary Production ◽

Co2 Exchange ◽

Light Use Efficiency ◽

Natural Ecosystems ◽

Use Efficiency ◽

Crop Types ◽

Year 2000

Abstract. Croplands cover about 12% of the ice-free terrestrial land surface. Compared with natural ecosystems, croplands have distinct characteristics due to anthropogenic influences. Their global gross primary production (GPP) is not well constrained and estimates vary between 8.2 and 14.2 Pg C yr−1. We quantified global cropland GPP using a light use efficiency (LUE) model, employing satellite observations and survey data of crop types and distribution. A novel step in our analysis was to assign a maximum light use efficiency estimate (&varepsilon;&ast;GPP) to each of the 26 different crop types, instead of taking a uniform value as done in the past. These &varepsilon;&ast;GPP values were calculated based on flux tower CO2 exchange measurements and a literature survey of field studies, and ranged from 1.20 g CMJ−1 to 2.96 g CMJ−1. Global cropland GPP was estimated to be 11.05 Pg C yr−1 in the year 2000. Maize contributed most to this (1.55 Pg C yr−1), and the continent of Asia contributed most with 38.9% of global cropland GPP. In the continental United States, annual cropland GPP (1.28 Pg C yr−1) was close to values reported previously (1.24 Pg C yr−1) constrained by harvest records, but our estimates of &varepsilon;&ast;GPP values were much higher. Our results are sensitive to satellite information and survey data on crop type and extent, but provide a consistent and data-driven approach to generate a look-up table of &varepsilon;&ast;GPP for the 26 crop types for potential use in other vegetation models.

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Impact of cloudiness on net ecosystem exchange of carbon dioxide in different types of forest ecosystems in China

Biogeosciences Discussions ◽

10.5194/bgd-6-8215-2009 ◽

2009 ◽

Vol 6 (4) ◽

pp. 8215-8245 ◽

Cited By ~ 1

Author(s):

M. Zhang ◽

G.-R. Yu ◽

L.-M. Zhang ◽

X.-M. Sun ◽

X.-F. Wen ◽

...

Keyword(s):

Carbon Dioxide ◽

Forest Ecosystem ◽

Temperate Forest ◽

Forest Ecosystems ◽

Ecosystem Respiration ◽

Mixed Forest ◽

Net Ecosystem Exchange ◽

Diffuse Radiation ◽

Carbon Uptake ◽

Sky Conditions

Abstract. Clouds can significantly affect carbon uptake of forest ecosystems by affecting incoming solar radiation on the ground, temperature and other environmental factors. In this study, we analyzed the effects of cloudiness on the net ecosystem exchange of carbon dioxide (NEE) of a temperate broad-leaved Korean pine mixed forest at Changbaishan (CBS) and a subtropical evergreen broad-leaved forest at Dinghushan (DHS) of ChinaFLUX, based on the flux data obtained during June–August from 2003 to 2006. The results showed that the response of the NEE of forest ecosystem to photosynthetically active radiation (PAR) was different under clear sky and cloudy sky conditions, and this difference was not consistent between CBS and DHS. Compared with clear skies, light-saturated maximum photosynthetic rate (Pec,max) of CBS during mid-growing season (from June to August) was respectively enhanced by 34%, 25%, 4% and 11% on cloudy skies in 2003, 2004, 2005 and 2006; however, Pec,max of DHS was higher under clear skies than under cloudy skies from 2004 to 2006. NEE of forests at CBS reached its maximum when the clearness index (kt) was between 0.4 and 0.6, and the NEE decreased obviously when kt exceeded 0.6. Compare with CBS, although NEE of forest at DHS tended to the maximum when kt varied between 0.4 and 0.6, the NEE did not decrease noticeably when kt exceeded 0.6. The results indicated that cloudy sky conditions were more beneficial to carbon uptake for the temperate forest ecosystem rather than for the subtropical forest ecosystem. This is due to the fact that the non-saturating light conditions and increase of diffuse radiation were more beneficial to photosynthesis, and the reduced temperature was more conducive to decreasing the ecosystem respiration in temperate forest ecosystems under cloudy sky conditions. This phenomenon is important to evaluate carbon uptake of temperate forests under climate change conditions.

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