scholarly journals Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

2014 ◽  
Vol 11 (13) ◽  
pp. 3547-3602 ◽  
Author(s):  
P. Ciais ◽  
A. J. Dolman ◽  
A. Bombelli ◽  
R. Duren ◽  
A. Peregon ◽  
...  

Abstract. A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

2013 ◽  
Vol 10 (7) ◽  
pp. 11447-11581 ◽  
Author(s):  
P. Ciais ◽  
A. J. Dolman ◽  
A. Bombelli ◽  
R. Duren ◽  
A. Peregon ◽  
...  

Abstract. A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The goal of this study is to identify the current state of carbon observations and needs for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion (by several orders of magnitude) of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over remote areas such as the southern oceans, tropical forests and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in-situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases inter-operable, and on the calibration of each component of the system to agreed-upon international scales.


2019 ◽  
Author(s):  
André Ehrlich ◽  
Manfred Wendisch ◽  
Christof Lüpkes ◽  
Matthias Buschmann ◽  
Heiko Bozem ◽  
...  

Abstract. The Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) campaign was carried out North-West of Svalbard (Norway) between 23 May–26 June 2017. The objective of ACLOUD was to study Arctic boundary layer and mid-level clouds and their role in Arctic Amplification. Two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. Both aircraft were equipped with identical instrumentation for measurements of basic meteorological parameters, as well as for turbulent and and radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 operated in situ instruments to characterize cloud and aerosol particles as well as trace gases. A detailed overview of the specifications, data processing, and data quality is provided here. It is shown, that the scientific analysis of the ACLOUD data benefits from the coordinated operation of both aircraft. By combining the cloud remote sensing techniques operated on Polar 5, the synergy of multiinstrument cloud retrieval is illustrated. The remote sensing methods are validated using truly collocated in situ and remote sensing observations. The data of identical instruments operated on both aircraft are merged to extend the spatial coverage of mean atmospheric quantities and turbulent and radiative flux measurement. Therefore, the data set of the ACLOUD campaign provides comprehensive in situ and remote sensing observations characterizing the cloudy Arctic atmosphere. All processed, 1 calibrated, and validated data are published in the world data center PANGAEA as instrument-separated data subsets (Ehrlich et al., 2019b, https://doi.org/10.1594/PANGAEA.902603).


2019 ◽  
Vol 11 (4) ◽  
pp. 1853-1881 ◽  
Author(s):  
André Ehrlich ◽  
Manfred Wendisch ◽  
Christof Lüpkes ◽  
Matthias Buschmann ◽  
Heiko Bozem ◽  
...  

Abstract. The Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign was carried out north-west of Svalbard (Norway) between 23 May and 6 June 2017. The objective of ACLOUD was to study Arctic boundary layer and mid-level clouds and their role in Arctic amplification. Two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. Both aircraft were equipped with identical instrumentation for measurements of basic meteorological parameters, as well as for turbulent and radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 operated in situ instruments to characterize cloud and aerosol particles as well as trace gases. A detailed overview of the specifications, data processing, and data quality is provided here. It is shown that the scientific analysis of the ACLOUD data benefits from the coordinated operation of both aircraft. By combining the cloud remote sensing techniques operated on Polar 5, the synergy of multi-instrument cloud retrieval is illustrated. The remote sensing methods were validated using truly collocated in situ and remote sensing observations. The data of identical instruments operated on both aircraft were merged to extend the spatial coverage of mean atmospheric quantities and turbulent and radiative flux measurement. Therefore, the data set of the ACLOUD campaign provides comprehensive in situ and remote sensing observations characterizing the cloudy Arctic atmosphere. All processed, calibrated, and validated data are published in the World Data Center PANGAEA as instrument-separated data subsets (Ehrlich et al., 2019b, https://doi.org/10.1594/PANGAEA.902603).


2016 ◽  
Vol 113 (28) ◽  
pp. 7733-7738 ◽  
Author(s):  
Nicholas C. Parazoo ◽  
Roisin Commane ◽  
Steven C. Wofsy ◽  
Charles D. Koven ◽  
Colm Sweeney ◽  
...  

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.


Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.


2005 ◽  
Vol 18 (21) ◽  
pp. 4531-4544 ◽  
Author(s):  
G. Bala ◽  
K. Caldeira ◽  
A. Mirin ◽  
M. Wickett ◽  
C. Delire

Abstract A coupled climate and carbon (CO2) cycle model is used to investigate the global climate and carbon cycle changes out to the year 2300 that would occur if CO2 emissions from all the currently estimated fossil fuel resources were released to the atmosphere. By the year 2300, the global climate warms by about 8 K and atmospheric CO2 reaches 1423 ppmv. The warming is higher than anticipated because the sensitivity to radiative forcing increases as the simulation progresses. In this simulation, the rate of emissions peaks at over 30 Pg C yr−1 early in the twenty-second century. Even at the year 2300, nearly 50% of cumulative emissions remain in the atmosphere. Both soils and living biomass are net carbon sinks throughout the simulation. Despite having relatively low climate sensitivity and strong carbon uptake by the land biosphere, these model projections suggest severe long-term consequences for global climate if all the fossil fuel carbon is ultimately released into the atmosphere.


2015 ◽  
Vol 49 (2) ◽  
pp. 112-121
Author(s):  
Stephen R. Piotrowicz ◽  
David M. Legler

AbstractThe Global Ocean Observing System (GOOS) is the international observation system that ensures long-term sustained ocean observations. The ocean equivalent of the atmospheric observing system supporting weather forecasting, GOOS, was originally developed to provide data for weather and climate applications. Today, GOOS data are used for all aspects of ocean management as well as weather and climate research and forecasting. National Oceanic and Atmospheric Administration (NOAA), through the Climate Observation Division of the Office of Oceanic and Atmospheric Research/Climate Program Office, is a major supporter of the climate component of GOOS. This paper describes the eight elements of GOOS, and the Arctic Observing Network, to which the Climate Observation Division is a major contributor. In addition, the paper addresses the evolution of the observing system as rapidly evolving new capabilities in sensors, platforms, and telecommunications allow observations at unprecedented temporal and spatial scales with the accuracy and precision required to address questions of climate variability and change.


2019 ◽  
Vol 11 (19) ◽  
pp. 2257
Author(s):  
Ji-Yeon Baek ◽  
Young-Heon Jo ◽  
Wonkook Kim ◽  
Jong-Seok Lee ◽  
Dawoon Jung ◽  
...  

In this study, a low-altitude remote sensing (LARS) observation system was employed to observe a rapidly changing coastal environment-owed to the regular opening of the sluice gate of the Saemangeum seawall-off the west coast of South Korea. The LARS system uses an unmanned aerial vehicle (UAV), a multispectral camera, a global navigation satellite system (GNSS), and an inertial measurement unit (IMU) module to acquire geometry information. The UAV system can observe the coastal sea surface in two dimensions with high temporal (1 s−1) and spatial (20 cm) resolutions, which can compensate for the coarse spatial resolution of in-situ measurements and the low temporal resolution of satellite observations. Sky radiance, sea surface radiance, and irradiance were obtained using a multispectral camera attached to the LARS system, and the remote sensing reflectance (Rrs) was accordingly calculated. In addition, the hyperspectral radiometer and in-situ chlorophyll-a concentration (CHL) measurements were obtained from a research vessel to validate the Rrs observed using the multispectral camera. Multi-linear regression (MLR) was then applied to derive the relationship between Rrs of each wavelength observed using the multispectral sensor on the UAV and the in-situ CHL. As a result of applying MLR, the correlation and root mean square error (RMSE) between the remotely sensed and in-situ CHLs were 0.94 and ~0.8 μg L−1, respectively; these results show a higher correlation coefficient and lower RMSE than those of other, previous studies. The newly derived algorithm for the CHL estimation enables us to survey 2D CHL images at high temporal and spatial resolutions in extremely turbid coastal oceans.


2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.


2020 ◽  
Vol 12 (17) ◽  
pp. 2774
Author(s):  
Marta Konik ◽  
Piotr Kowalczuk ◽  
Monika Zabłocka ◽  
Anna Makarewicz ◽  
Justyna Meler ◽  
...  

The Nordic Seas and the Fram Strait regions are a melting pot of a number of water masses characterized by distinct optical water properties. The warm Atlantic Waters transported from the south and the Arctic Waters from the north, combined with the melt waters contributing to the Polar Waters, mediate the dynamic changes of the year-to-year large-scale circulation patterns in the area, which often form complex frontal zones. In the last decade, moreover, a significant shift in phytoplankton phenology in the area has been observed, with a certain northward expansion of temperate phytoplankton communities into the Arctic Ocean which could lead to a deterioration in the performance of remote sensing algorithms. In this research, we exploited the capability of the satellite sensors to monitor those inter-annual changes at basin scales. We propose locally adjusted algorithms for retrieving chlorophyll a concentrations Chla, absorption by particles ap at 443 and 670 nm, and total absorption atot at 443 and 670 nm developed on the basis of intensive field work conducted in 2013–2015. Measured in situ hyper spectral remote sensing reflectance has been used to reconstruct the MODIS and OLCI spectral channels for which the proposed algorithms have been adapted. We obtained MNB ≤ 0.5% for ap(670) and ≤3% for atot(670) and Chla. RMS was ≤30% for most of the retrieved optical water properties except ap(443) and Chla. The mean monthly mosaics of ap(443) computed on the basis of the proposed algorithm were used for reconstructing the spatial and temporal changes of the phytoplankton biomass in 2013–2015. The results corresponded very well with in situ measurements.


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