A Simple KISS Model to Examine the Relationship Between Atmospheric CO2 Concentration, and Ocean & Land Surface Temperatures, Taking into Consideration Solar and Volcanic Activity, As Well As Fossil Fuel Use

2011 ◽  
pp. 353-382
Author(s):  
James P. Wallace ◽  
Anthony Finizza ◽  
Joseph D'Aleo
Keyword(s):  
Volcanic Activity ◽  
Land Surface ◽  
Fossil Fuel ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Fuel Use ◽  
Atmospheric Co2 Concentration ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
The Relationship

scholarly journals CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity

2020 ◽  
Vol 12 (9) ◽  
pp. 1377 ◽  
Author(s):  
Ruonan Qiu ◽  
Ge Han ◽  
Xin Ma ◽  
Zongyao Sha ◽  
Tianqi Shi ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Linear Model ◽  
Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Gross Primary Productivity ◽  
Atmospheric Co2 ◽  
Atmospheric Co2 Concentration ◽  
Non Linear ◽  
The Relationship

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to regridding of global fossil fuel CO<sub>2</sub> emissions

2014 ◽  
Vol 7 (6) ◽  
pp. 2867-2874 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady
Keyword(s):  
Co2 Emissions ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Grid Cells ◽  
Atmospheric Co2 Concentration ◽  
Dynamical Consistency

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO2 emissions (FFCO2) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell−1 yr−1 (−3.39 kgC m−2 yr−1) to +30.0 TgC grid cell−1 yr−1 (+2.6 kgC m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to regridding of global fossil fuel CO<sub>2</sub> emissions

2014 ◽  
Vol 7 (3) ◽  
pp. 3575-3593
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
Y. Liu ◽  
S. Asefi-Najafabady
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Co2 Concentration ◽  
Point Sources ◽  
Atmospheric Co2 ◽  
Atmospheric Co2 Concentration ◽  
Dynamical Consistency ◽  
Oceanic Carbon

Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Finite grid resolution can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. We test these mismatches by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are: (1) a commonly-used method that allocates emissions to gridcells with no attempt to ensure dynamical consistency with atmospheric transport; (2) an improved method that reallocates emissions to gridcells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 Tg C gridcell−1 yr−1 (−3.39 kg C m−2 yr−1) to +30.0 Tg C gridcell−1 yr−1 (+2.6 kg C m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

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