scholarly journals Spatio-temporal variability of marine primary and export production in three global coupled climate carbon cycle models

2007 ◽  
Vol 4 (3) ◽  
pp. 1877-1921 ◽  
Author(s):  
B. Schneider ◽  
L. Bopp ◽  
M. Gehlen ◽  
J. Segschneider ◽  
T. L. Frölicher ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temporal Variability ◽  
Satellite Observations ◽  
Future Climate Change ◽  
Nutrient Concentrations ◽  
Ocean Colour ◽  
Coupled Models ◽  
Low Latitude ◽  
Export Production ◽  
The Impact

Abstract. This study compares spatial and temporal variability in net primary productivity (PP) and particulate organic carbon (POC) export production (EP) from three different coupled climate carbon cycle models (IPSL, MPIM, NCAR) with observation-based estimates derived from satellite measurements of ocean colour and inverse modelling. Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006)\\nocite{Behrenfeld06} with stronger stratification (higher SSTs) leading to negative PP anomalies and vice versa. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for global PP anomalies. Two of the models also reproduce the inverse relationship between stratification (SST) and PP, especially in the equatorial Pacific. With the help of the model results we are able to explain the chain of cause and effect leading from stratification (SST) through nutrient concentrations to PP and finally to EP. There are significant uncertainties in observational PP and especially EP. Our finding of a good agreement between independent estimates from coupled models and satellite observations provides increased confidence that such models can be used as a first basis to estimate the impact of future climate change on marine productivity and carbon export.

scholarly journals Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models

2008 ◽  
Vol 5 (2) ◽  
pp. 597-614 ◽  
Author(s):  
B. Schneider ◽  
L. Bopp ◽  
M. Gehlen ◽  
J. Segschneider ◽  
T. L. Frölicher ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temporal Variability ◽  
Future Climate Change ◽  
Spatial And Temporal Variability ◽  
Ocean Colour ◽  
Coupled Models ◽  
Low Latitude ◽  
Tropical Ocean ◽  
Export Production ◽  
Ocean Carbon

Abstract. Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.

scholarly journals The role of satellite observations in understanding the impact of El Niño on the carbon cycle: current capabilities and future opportunities

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170407 ◽  
Author(s):  
Paul I. Palmer
Keyword(s):  
Carbon Cycle ◽  
Satellite Data ◽  
El Niño ◽  
El Nino ◽  
Carbon Dynamics ◽  
Climate Variation ◽  
Satellite Observations ◽  
Future Research ◽  
The Impact

The 2015/2016 El Niño was the first major climate variation when there were a range of satellite observations that simultaneously observed land, ocean and atmospheric properties associated with the carbon cycle. These data are beginning to provide new insights into the varied responses of land ecosystems to El Niño, but we are far from fully exploiting the information embodied by these data. Here, we briefly review the atmospheric and terrestrial satellite data that are available to study the carbon cycle. We also outline recommendations for future research, particularly the closer integration of satellite data with forest biometric datasets that provide detailed information about carbon dynamics on a range of timescales. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

scholarly journals The impact of spatiotemporal variability in atmospheric CO<sub>2</sub> concentration on global terrestrial carbon fluxes

2018 ◽  
Author(s):  
Eunjee Lee ◽  
Fan-Wei Zeng ◽  
Randal D. Koster ◽  
Brad Weir ◽  
Lesley E. Ott ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temporal Variability ◽  
Gross Primary Production ◽  
Carbon Fluxes ◽  
Atmospheric Co2 ◽  
Spatiotemporal Variability ◽  
Terrestrial Carbon ◽  
Diurnal Variability ◽  
Co2 Concentrations ◽  
The Impact

Abstract. Land carbon fluxes, e.g., gross primary production (GPP) and net biome production (NBP), are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. The Coupled Model Intercomparison Project Phase 6 (CMIP6) has recently proposed increased spatial and temporal resolutions for the surface CO2 concentrations used to calculate GPP, and yet a comprehensive evaluation of the consequences of this increased resolution for carbon cycle dynamics is missing. Here, using global offline simulations with a terrestrial biosphere model, the sensitivity of terrestrial carbon cycle fluxes to multiple facets of the spatiotemporal variability of atmospheric CO2 is quantified. Globally, the spatial variability of CO2 is found to increase the mean global GPP by 0.2 PgC year−1, as more vegetated land areas benefit from higher CO2 concentrations induced by the inter-hemisphere gradient. The temporal variability of CO2, however, compensates for this increase, acting to reduce overall global GPP; in particular, consideration of the diurnal variability of atmospheric CO2 reduces multi-year mean global annual GPP by 0.5 PgC year−1 and net land carbon uptake by 0.1 PgC year−1. The relative contribution of the different facets of CO2 variability to GPP are found to vary regionally and seasonally, with the seasonal variation in atmospheric CO2, for example, having a notable impact on GPP in boreal regions during fall. Overall, in terms of estimating global GPP, the magnitudes of the sensitivities found here are minor, indicating that the common practice of applying spatially-uniform and annually increasing CO2 (without higher frequency temporal variability) in offline studies is a reasonable approach – the small errors induced by ignoring CO2 variability are undoubtedly swamped by other uncertainties in the offline calculations. Still, for certain regional- and seasonal-scale GPP estimations, the proper treatment of spatiotemporal CO2 variability appears important.

scholarly journals Projected 21st century decrease in marine productivity: a multi-model analysis

2009 ◽  
Vol 6 (4) ◽  
pp. 7933-7981 ◽  
Author(s):  
M. Steinacher ◽  
F. Joos ◽  
T. L. Frölicher ◽  
L. Bopp ◽  
P. Cadule ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Particulate Organic Carbon ◽  
21St Century ◽  
Mixed Layer Depth ◽  
The Arctic ◽  
Nutrient Concentrations ◽  
Export Production ◽  
Model Average ◽  
Marine Productivity

Abstract. Changes in marine net primary productivity and export of particulate organic carbon are projected over the 21st century with three global coupled carbon cycle-climate models. These include representations of marine ecosystems and the carbon cycle of different structure and complexity. All three models show a decrease in global mean marine productivity and export production between 7 and 20% by 2100 relative to preindustrial conditions, for the SRES A2 emission scenario. Two different regimes for productivity changes are consistently identified in all three models. The first chain of mechanisms is dominant in the low- and mid-latitude ocean and in the North Atlantic: reduced input of macro-nutrients into the euphotic zone related to enhanced stratification, reduced mixed layer depth, and slowed circulation causes a decrease in macro-nutrient concentrations and in productivity and export of particulate organic carbon. The second regime is projected for parts of the Southern Ocean: an alleviation of light and/or temperature limitation leads to an increase in primary and export production as productivity is fueled by a sustained nutrient input. A region of disagreement among the models is the Arctic, where two models project an increase in productivity while one model projects a decrease. Projected changes in seasonal and interannual variability are modest in most regions. Regional model skill metrics are proposed to generate multi-model mean fields that show an improved skill in representing observations compared to a simple multi-model average. Model results are compared to recent productivity projections with three different algorithms, usually applied to infer primary production from satellite observations.

scholarly journals Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Matthias Forkel ◽  
Markus Drüke ◽  
Martin Thurner ◽  
Wouter Dorigo ◽  
Sibyll Schaphoff ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Vegetation Dynamics ◽  
Climate Impacts ◽  
Forest Carbon ◽  
Satellite Observations ◽  
Future Climate Change ◽  
Carbon Turnover ◽  
Bioclimatic Variables ◽  
Optimized Model ◽  
Global Vegetation

AbstractThe response of land ecosystems to future climate change is among the largest unknowns in the global climate-carbon cycle feedback. This uncertainty originates from how dynamic global vegetation models (DGVMs) simulate climate impacts on changes in vegetation distribution, productivity, biomass allocation, and carbon turnover. The present-day availability of a multitude of satellite observations can potentially help to constrain DGVM simulations within model-data integration frameworks. Here, we use satellite-derived datasets of the fraction of absorbed photosynthetic active radiation (FAPAR), sun-induced fluorescence (SIF), above-ground biomass of trees (AGB), land cover, and burned area to constrain parameters for phenology, productivity, and vegetation dynamics in the LPJmL4 DGVM. Both the prior and the optimized model accurately reproduce present-day estimates of the land carbon cycle and of temporal dynamics in FAPAR, SIF and gross primary production. However, the optimized model reproduces better the observed spatial patterns of biomass, tree cover, and regional forest carbon turnover. Using a machine learning approach, we found that remaining errors in simulated forest carbon turnover can be explained with bioclimatic variables. This demonstrates the need to improve model formulations for climate effects on vegetation turnover and mortality despite the apparent successful constraint of simulated vegetation dynamics with multiple satellite observations.

scholarly journals Climate–Carbon Cycle Feedback Analysis: Results from the C4MIP Model Intercomparison

2006 ◽  
Vol 19 (14) ◽  
pp. 3337-3353 ◽  
Author(s):  
P. Friedlingstein ◽  
P. Cox ◽  
R. Betts ◽  
L. Bopp ◽  
W. von Bloh ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Net Primary Productivity ◽  
Future Climate ◽  
Climate Feedback ◽  
Future Climate Change ◽  
Ocean Carbon Cycle ◽  
Intergovernmental Panel ◽  
Ocean Carbon ◽  
The Impact

Abstract Eleven coupled climate–carbon cycle models used a common protocol to study the coupling between climate change and the carbon cycle. The models were forced by historical emissions and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 anthropogenic emissions of CO2 for the 1850–2100 time period. For each model, two simulations were performed in order to isolate the impact of climate change on the land and ocean carbon cycle, and therefore the climate feedback on the atmospheric CO2 concentration growth rate. There was unanimous agreement among the models that future climate change will reduce the efficiency of the earth system to absorb the anthropogenic carbon perturbation. A larger fraction of anthropogenic CO2 will stay airborne if climate change is accounted for. By the end of the twenty-first century, this additional CO2 varied between 20 and 200 ppm for the two extreme models, the majority of the models lying between 50 and 100 ppm. The higher CO2 levels led to an additional climate warming ranging between 0.1° and 1.5°C. All models simulated a negative sensitivity for both the land and the ocean carbon cycle to future climate. However, there was still a large uncertainty on the magnitude of these sensitivities. Eight models attributed most of the changes to the land, while three attributed it to the ocean. Also, a majority of the models located the reduction of land carbon uptake in the Tropics. However, the attribution of the land sensitivity to changes in net primary productivity versus changes in respiration is still subject to debate; no consensus emerged among the models.

scholarly journals The impact of spatiotemporal variability in atmospheric CO<sub>2</sub> concentration on global terrestrial carbon fluxes

2018 ◽  
Vol 15 (18) ◽  
pp. 5635-5652 ◽  
Author(s):  
Eunjee Lee ◽  
Fan-Wei Zeng ◽  
Randal D. Koster ◽  
Brad Weir ◽  
Lesley E. Ott ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Temporal Variability ◽  
Gross Primary Production ◽  
Carbon Fluxes ◽  
Atmospheric Co2 ◽  
Spatiotemporal Variability ◽  
Terrestrial Carbon ◽  
Diurnal Variability ◽  
Co2 Concentrations ◽  
The Impact

Abstract. Land carbon fluxes, e.g., gross primary production (GPP) and net biome production (NBP), are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. The Coupled Model Intercomparison Project Phase 6 (CMIP6) has recently proposed increased spatial and temporal resolutions for the surface CO2 concentrations used to calculate GPP, and yet a comprehensive evaluation of the consequences of this increased resolution for carbon cycle dynamics is missing. Here, using global offline simulations with a terrestrial biosphere model, the sensitivity of terrestrial carbon cycle fluxes to multiple facets of the spatiotemporal variability in atmospheric CO2 is quantified. Globally, the spatial variability in CO2 is found to increase the mean global GPP by a maximum of 0.05 Pg C year−1, as more vegetated land areas benefit from higher CO2 concentrations induced by the inter-hemispheric gradient. The temporal variability in CO2, however, compensates for this increase, acting to reduce overall global GPP; in particular, consideration of the diurnal variability in atmospheric CO2 reduces multi-year mean global annual GPP by 0.5 Pg C year−1 and net land carbon uptake by 0.1 Pg C year−1. The relative contributions of the different facets of CO2 variability to GPP are found to vary regionally and seasonally, with the seasonal variation in atmospheric CO2, for example, having a notable impact on GPP in boreal regions during fall. Overall, in terms of estimating global GPP, the magnitudes of the sensitivities found here are minor, indicating that the common practice of applying spatially uniform and annually increasing CO2 (without higher-frequency temporal variability) in offline studies is a reasonable approach – the small errors induced by ignoring CO2 variability are undoubtedly swamped by other uncertainties in the offline calculations. Still, for certain regional- and seasonal-scale GPP estimations, the proper treatment of spatiotemporal CO2 variability appears important.

scholarly journals Strong sensitivity of Southern Ocean carbon uptake and nutrient cycling to wind stirring

2013 ◽  
Vol 10 (9) ◽  
pp. 15033-15076 ◽  
Author(s):  
K. B. Rodgers ◽  
O. Aumont ◽  
S. E. Mikaloff Fletcher ◽  
Y. Plancherel ◽  
L. Bopp ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Southern Ocean ◽  
Ad Hoc ◽  
Global Ocean ◽  
Nutrient Concentrations ◽  
Carbon Uptake ◽  
Carbon Cycle Model ◽  
Ocean Biogeochemistry ◽  
Ocean Carbon ◽  
The Impact

Abstract. Here we test the hypothesis that winds have an important role in determining the rate of exchange of CO2 between the atmosphere and ocean through wind stirring over the Southern Ocean. This is tested with a sensitivity study using an ad hoc parameterization of wind stirring in an ocean carbon cycle model. The objective is to identify the way in which perturbations to the vertical density structure of the planetary boundary in the ocean impacts the carbon cycle and ocean biogeochemistry. Wind stirring leads to reduced uptake of CO2 by the Southern Ocean over the period 2000–2006, with differences of order 0.9 Pg C yr−1 over the region south of 45° S. Wind stirring impacts not only the mean carbon uptake, but also the phasing of the seasonal cycle of carbon and other species associated with ocean biogeochemistry. Enhanced wind stirring delays the seasonal onset of stratification, and this has large impacts on both entrainment and the biological pump. It is also found that there is a strong sensitivity of nutrient concentrations exported in Subantarctic Mode Water (SAMW) to wind stirring. This finds expression not only locally over the Southern Ocean, but also over larger scales through the impact on advected nutrients. In summary, the large sensitivity identified with the ad hoc wind stirring parameterization offers support for the importance of wind stirring for global ocean biogeochemistry, through its impact over the Southern Ocean.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Potential Impacts of Future Climate Change Scenarios on Ground Subsidence

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 219 ◽  
Author(s):  
Antonio-Juan Collados-Lara ◽  
David Pulido-Velazquez ◽  
Rosa María Mateos ◽  
Pablo Ezquerro
Keyword(s):  
Climate Change ◽  
Land Subsidence ◽  
Ground Subsidence ◽  
Lower Percentage ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Fine Grained ◽  
Fine Grained Material ◽  
The Impact

In this work, we developed a new method to assess the impact of climate change (CC) scenarios on land subsidence related to groundwater level depletion in detrital aquifers. The main goal of this work was to propose a parsimonious approach that could be applied for any case study. We also evaluated the methodology in a case study, the Vega de Granada aquifer (southern Spain). Historical subsidence rates were estimated using remote sensing techniques (differential interferometric synthetic aperture radar, DInSAR). Local CC scenarios were generated by applying a bias correction approach. An equifeasible ensemble of the generated projections from different climatic models was also proposed. A simple water balance approach was applied to assess CC impacts on lumped global drawdowns due to future potential rainfall recharge and pumping. CC impacts were propagated to drawdowns within piezometers by applying the global delta change observed with the lumped assessment. Regression models were employed to estimate the impacts of these drawdowns in terms of land subsidence, as well as to analyze the influence of the fine-grained material in the aquifer. The results showed that a more linear behavior was observed for the cases with lower percentage of fine-grained material. The mean increase of the maximum subsidence rates in the considered wells for the future horizon (2016–2045) and the Representative Concentration Pathway (RCP) scenario 8.5 was 54%. The main advantage of the proposed method is its applicability in cases with limited information. It is also appropriate for the study of wide areas to identify potential hot spots where more exhaustive analyses should be performed. The method will allow sustainable adaptation strategies in vulnerable areas during drought-critical periods to be assessed.

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