. Satellite retrievals of the column-averaged dry air
mole fractions of CO 2 (XCO 2 ) could help to improve carbon flux estimation
due to their good spatial coverage. In this study, in order to assimilate the
GOSAT (Greenhouse Gases Observing
Satellite) XCO 2 retrievals, the Global Carbon Assimilation System (GCAS) is
upgraded with new assimilation algorithms, procedures, a localization
scheme, and a higher assimilation parameter resolution. This upgraded system is
referred to as GCASv2. Based on this new system, the global terrestrial ecosystem
(BIO) and ocean (OCN) carbon fluxes from 1 May 2009 to 31 December 2015 are
constrained using the GOSAT ACOS (Atmospheric CO 2 Observations from Space) XCO 2 retrievals (Version 7.3). The
posterior carbon fluxes from 2010 to 2015 are independently evaluated using
CO 2 observations from 52 surface flask sites. The results show that the
posterior carbon fluxes could significantly improve the modeling of
atmospheric CO 2 concentrations, with global mean bias decreases from a
prior value of 1.6  ±  1.8 ppm to − 0.5  ±  1.8 ppm. The uncertainty
reduction (UR) of the global BIO flux is 17 %, and the highest monthly
regional UR could reach 51 %. Globally, the mean annual BIO and OCN carbon
sinks and their interannual variations inferred in this study are very close
to the estimates of CarbonTracker 2017 (CT2017) during the study period, and the inferred mean
atmospheric CO 2 growth rate and its interannual changes are also very
close to the observations. Regionally, over the northern lands, the
strongest carbon sinks are seen in temperate North America, followed by Europe,
boreal Asia, and temperate Asia; in the tropics, there are strong sinks in
tropical South America and tropical Asia, but a very weak sink in Africa.
This pattern is significantly different from the estimates of CT2017, but
the estimated carbon sinks for each continent and some key regions like
boreal Asia and the Amazon are comparable or within the range of previous bottom-up
estimates. The inversion also changes the interannual variations in carbon
fluxes in most TransCom land regions, which have a better relationship with
the changes in severe drought area (SDA) or leaf area index (LAI), or are more consistent with
previous estimates for the impact of drought. These results suggest that the
GCASv2 system works well with the GOSAT XCO 2 retrievals and shows good
performance with respect to estimating the surface carbon fluxes; meanwhile, our results
also indicate that the GOSAT XCO 2 retrievals could help to better
understand the interannual variations in regional carbon fluxes.

/pdf/regional-co-2-fluxes-from-2010-to-2015-inferred-from-gosat-4palu4tyv4.pdf

Regional CO 2 fluxes from 2010 to 2015 inferred from GOSAT XCO 2 retrievals using a new version of the Global Carbon Assimilation System

Constraining global terrestrial gross primary productivity in a global carbon assimilation system with OCO-2 chlorophyll fluorescence data

. Optimized biogenic carbon fluxes for Europe were estimated from high-resolution regional-scale inversions, utilizing atmospheric CO2 measurements at 16 stations for the year 2007. Additional sensitivity tests with different data-driven error structures were performed. As the atmospheric network is rather sparse and consequently contains large spatial gaps, we use a priori biospheric fluxes to further constrain the inversions. The biospheric fluxes were simulated by the Vegetation Photosynthesis and Respiration Model (VPRM) at a resolution of 0.1° and optimized against eddy covariance data. Overall we estimate an a priori uncertainty of 0.54 GtC yr−1 related to the poor spatial representation between the biospheric model and the ecosystem sites. The sink estimated from the atmospheric inversions for the area of Europe (as represented in the model domain) ranges between 0.23 and 0.38 GtC yr−1 (0.39 and 0.71 GtC yr−1 up-scaled to geographical Europe). This is within the range of posterior flux uncertainty estimates of previous studies using ground-based observations.

/pdf/atmospheric-co-2-inversions-on-the-mesoscale-using-data-2jju3gw6b2.pdf

Atmospheric CO 2 inversions on the mesoscale using data-driven prior uncertainties: quantification of the European terrestrial CO 2 fluxes

/pdf/satellite-remote-sensing-for-global-stocktaking-methods-1mierk5b.pdf

Satellite remote sensing for global stocktaking： Methods， progress and perspectives

Abstract. Understanding carbon sources and sinks across the Earth's
surface is fundamental in climate science and policy; thus, these topics
have been extensively studied but have yet to be fully resolved and are
associated with massive debate regarding the sign and magnitude of the
carbon budget from global to regional scales. Developing new models and
estimates based on state-of-the-art algorithms and data constraints can
provide valuable knowledge and contribute to a final ensemble model in which various optimal carbon budget estimates are integrated, such as the annual global carbon budget paper. Here, we develop a new atmospheric inversion system based on the 4D local ensemble transform Kalman filter (4D-LETKF) coupled with the GEOS-Chem global transport model to infer surface-to-atmosphere net carbon fluxes from Orbiting Carbon Observatory-2 (OCO-2) V10r XCO2 retrievals. The 4D-LETKF algorithm is adapted to an OCO-2-based global carbon inversion system for the first time in this work. On average, the mean annual terrestrial and oceanic fluxes between 2015 and 2020 are estimated as − 2.02 and − 2.34 GtC yr−1, respectively, compensating for 21 % and 24 %, respectively, of global fossil carbon dioxide (CO2) emissions (9.80 GtC yr−1). Our inversion results agree with the CO2 atmospheric growth rates reported by the National Oceanic and Atmospheric Administration (NOAA) and reduce the modeled CO2 concentration biases relative to the prior fluxes against surface and aircraft measurements. Our inversion-based carbon fluxes are broadly consistent with those provided by other global atmospheric inversion models, although discrepancies still occur in the land–ocean flux partitioning schemes and seasonal flux amplitudes over boreal and tropical regions, possibly due to the sparse observational constraints of the OCO-2 satellite and the divergent prior fluxes used in different inversion models. Four sensitivity experiments are performed herein to vary the prior fluxes and uncertainties in our inversion system, suggesting that regions that lack OCO-2 coverage are sensitive to the priors, especially over the tropics and high latitudes. In the further development of our inversion system, we will optimize the data-assimilation configuration to fully utilize current observations and increase the spatial and seasonal representativeness of the prior fluxes over regions that lack observations.


/pdf/global-and-regional-carbon-budget-for-2015-2020-inferred-3dq8jwq8.pdf

Global and regional carbon budget for 2015–2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem

. A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO2 concentration in state vectors, using the ensemble Kalman filter (EnKF) with 1-week assimilation windows, using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results show that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

/pdf/a-global-carbon-assimilation-system-using-a-modified-sc33558uhg.pdf

A global carbon assimilation system using a modified ensemble Kalman filter

We present the China Ocean ReAnalysis version 2 (CORA2) in this paper. We compare CORA2 with its predecessor, CORA1, and with other ocean reanalysis products created between 2004 and 2019 [GLORYS12v1 (Global Ocean reanalysis and Simulation), HYCOM (HYbrid Coordinate Ocean Model), GREP (Global ocean Reanalysis Ensemble Product), SODA3 (Simple Ocean Data Assimilation, version 3), and ECCO4 (Estimating the Circulation and Climate of the Ocean, version 4)], to demonstrate its improvements and reliability. In addition to providing tide and sea ice signals, the accuracy and eddy kinetic energy (EKE) of CORA2 are also improved owing to an enhanced resolution of 9 km and updated data assimilation scheme compared with CORA1. Error analysis shows that the root-mean-square error (RMSE) of CORA2 sea-surface temperature (SST) remains around 0.3°C, which is comparable to that of GREP and smaller than those of the other products studied. The subsurface temperature (salinity) RMSE of CORA2, at 0.87°C (0.15 psu), is comparable to that of SODA3, smaller than that of ECCO4, and larger than those of GLORYS12v1, HYCOM, and GREP. CORA2 and GLORYS12v1 can better represent sub-monthly-scale variations in subsurface temperature and salinity than the other products. Although the correlation coefficient of sea-level anomaly (SLA) in CORA2 does not exceed 0.8 in the whole region, as those of GREP and GLORYS12v1 do, it is more effective than ECCO4 and SODA3 in the Indian Ocean and Pacific Ocean. CORA2 can reproduce the variations in steric sea level and ocean heat content (OHC) on the multiple timescales as the other products. The linear trend of the steric sea level of CORA2 is closer to that of GREP than that of the other products, and the long-term warming trends of global OHC in the high-resolution CORA2 and GLORYS12v1 are greater than those in the low-resolution EN4 and GREP. Although CORA2 shows overall poorer performance in the Atlantic Ocean, it still achieves good results from 2009 onward. We plan to further improve CORA2 by assimilating the best available observation data using the incremental analysis update (IAU) procedure and improving the SLA assimilation method.

/pdf/global-ocean-reanalysis-cora2-and-its-inter-comparison-with-312sujdy.pdf

Global ocean reanalysis CORA2 and its inter comparison with a set of other reanalysis products

With global warming, extreme high temperatures become more frequent and are an important factor affecting aircrafts’ takeoff performance. Using Community Earth System Model version 1 (CESM1) and Boeing Performance Software (BPS), the influence of increasing temperature on aircrafts’ maximum takeoff weight (MTOW) and takeoff distance is evaluated quantitatively in this study. The results show that the distribution of summer daily maximum temperature shifts obviously to higher temperature at all the chosen airports and the variation in temperature is larger at four airports (Jinan, Shanghai, Lhasa, and Urumqi) during 2071−2080 under the RCP8.5 scenario than that in the historical run (1991−2000). The warming air leads to the MTOW reducing and takeoff distance increasing. Taking the Boeing 737–800 aircraft as an illustration, the number of weight-restriction days increases significantly across the airports, which can influence airlines’ economic benefit and flight operations in the future. It is also found that the takeoff distance does not change linearly with temperature, but shows a stronger increase with higher temperature. The takeoff distance increases about 6.2% on average during 2071−2080 compared to 1991−2000 for the low-altitude airports, calling for an additional 113−222 m takeoff distance in future summers.

/pdf/decreased-aircraft-takeoff-performance-under-global-warming-43zssc7a.pdf

Decreased Aircraft Takeoff Performance under Global Warming

: The impact on the Gulf Stream and Kuroshio from Arctic sea ice loss is investigated using the Community Climate System Model version 4 (CCSM4) model for their important roles during climate change. Results show that the Gulf Stream (Kuroshio) weakens (strengthens) in response to Arctic sea ice loss via ocean (atmosphere) adjustments. More precisely, the Kuroshio acceleration is mainly due to the anomalous wind stress over the North Pacific, while the ocean gyre adjustments in the Atlantic are responsible for the weakened Gulf Stream. As positive buoyancy fluxes induced by Arctic sea ice loss triggers a slowdown of the Atlantic Meridional Overturning Circulation (AMOC), the Gulf Stream decelerates evidently, which current speed decreases about 5-8 cm/s in the upper ocean. Resulted from less advection and horizontal diffusion in the temperature budget, less poleward warm water leads to a narrow sea surface cooling sandwiched between strong warm-21 ing in the subpolar and subtropical Atlantic. Furthermore, colder surface decreases the upward heat 22 flux (mainly latent heat flux) along the Gulf Stream Extension (GE) path, which leads to a warming 23 hole in the atmosphere.

Contrary Responses of the Gulf Stream and the Kuroshio to Arctic Sea Ice Loss

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

B. Dan

Author Tools

Chat about Author

Papers

A global carbon assimilation system using a modified ensemble Kalman filter

Global ocean reanalysis CORA2 and its inter comparison with a set of other reanalysis products

Decreased Aircraft Takeoff Performance under Global Warming

Contrary Responses of the Gulf Stream and the Kuroshio to Arctic Sea Ice Loss