CO2 flux variation and its contribution area in the debris-covered area of Koxkar Glacier, Mt. Tianshan in China

AbstractA physically based energy-balance model with improved parameterization of solar radiation for a sloped ice surface has been developed to estimate the backwasting rate of an ice cliff in a debris-covered area. The model has been tested against observations between 5 August and 5 September 2008 on 38 ice cliffs in the debris-covered area of Koxkar glacier, Tuomuer mountain, China. We calculated that the energy-balance model gave a good estimate of the backwasting rates, with errors in the range ±1.96 cm d−1 and root-mean-square errors of 0.99 cm d−1. Errors arising from setting of surface albedo and turbulent flux parameterization were limited. We found that shortwave radiation is the most important heat source for ice-cliff ablation, contributing about 76% of the total heat available for ice melt, while the sensible heat flux provides nearly 24% of the total heat for ice-cliff wastage. The latent heat flux and net longwave radiation are comparatively small according to the model calculation. The mean backwasting rate of ice cliffs in the debris-covered area of Koxkar glacier is estimated at 7.64 m a−1 when the winter ablation is neglected. With this annual backwasting rate and given a mean slope angle of 46.4°, the backwasting of ice cliffs produces about 1.60 × 106 m3 of meltwater, accounting for about 7.3% of the total melt runoff from the debris-covered area.

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Climate pathways behind phytoplankton-induced atmospheric warming

10.5194/bg-2021-118 ◽

2021 ◽

Author(s):

Rémy Asselot ◽

Frank Lunkeit ◽

Philip B. Holden ◽

Inga Hense

Keyword(s):

Heat Exchange ◽

Light Absorption ◽

Co2 Flux ◽

Co2 Concentration ◽

Atmospheric Temperature ◽

Co2 Exchange ◽

Co2 Solubility ◽

Covered Area ◽

Atmospheric Warming ◽

The Impact

Abstract. We investigate in which ways marine biologically-mediated heating increases the surface atmospheric temperature. While the effects of phytoplankton light absorption on the ocean have gained attention over the past years, the impact of this biogeophysical mechanism on the atmosphere is still unclear. Phytoplankton light absorption warms the surface of the ocean with consequences for the air-sea heat exchange and CO2 flux. We focus on the ocean-atmosphere interface and study the importance of air-sea heat exchange versus air-sea CO2 flux. To shed light on the role of phytoplankton light absorption on the surface atmospheric temperature, we performed different simulations with the EcoGENIE Earth system model. We configure the model without a seasonal cycle and, if not stated otherwise, the atmospheric CO2 concentration is allowed to evolve freely. The climate pathways examined are: heat exchange, dissolved CO2, solubility of CO2, and sea-ice covered area. Overall we show that the air-sea CO2 exchange has a larger effect on the biologically-induced atmospheric warming than the air-sea heat flux. Moreover, we notice that the freely evolving solubility of CO2 has a cooling effect on the surface atmospheric temperature.

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Flexographic ink-coating interactions: effects of latex variations in coating layers

TAPPI Journal ◽

10.32964/tj15.4.253 ◽

2016 ◽

Vol 15 (4) ◽

pp. 253-262 ◽

Cited By ~ 1

Author(s):

ERIK BOHLIN ◽

CAISA JOHANNSON ◽

MAGNUS LESTELIUS

Keyword(s):

Contact Angles ◽

High Ratio ◽

Print Quality ◽

Particle Sizes ◽

Mixed Composition ◽

Coating Surface ◽

Covered Area ◽

Surface Optical ◽

Flexographic Printing ◽

Coating Formulation

The effect of coating structure variations on flexographic print quality was studied using pilot-coated paperboard samples with different latex content and latex particle sizes. Two latexes, with particle sizes of 120 nm and 160 nm, were added at either 12 parts per hundred (pph) or 18 pph to the coating formulation. The samples were printed with full tone areas at print forces of 25 N and 50 N in a laboratory flexographic printing press using a waterbased ink. A high ratio of uncovered areas (UCAs) could be detected for the samples that contained 18 pph latex printed at a print force of 25 N. UCAs decreased with increased print force and with decreased amounts of latex in the coating formulation. The fraction of latex covered area on the coating surface was estimated to be 0.35–0.40 for the 12 pph, and 0.70–0.75 for the 18 pph samples. The ink penetration depth into the coating layer could be linked to the fraction of latex-free areas on the coating surface. Optical cross section microscopy indicated that a higher printing force did not increase the depth of penetrated ink to any greater extent. Higher printing force did increase contact between plate and substrate, leading to an improved distribution of the ink. This, in turn, increased print density and decreased UCAs. On closer inspection, the UCAs could be categorized as being induced by steep topographic changes. When appearing at other locations, they were more likely to be caused by poor wetting of the surface. To understand the wetting behavior of the coating surface, observed contact angles were compared with calculated contact angles on surfaces of mixed composition.

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Effect of recent observations on Asian CO2 flux estimates by transport model inversions

Tellus B ◽

10.3402/tellusb.v55i2.16734 ◽

2003 ◽

Vol 55 (2) ◽

pp. 522-529 ◽

Cited By ~ 9

Author(s):

Shamil Maksyutov ◽

Toshinobu Machida ◽

Hitoshi Mukai ◽

Prabir K. Patra ◽

Takakiyo Nakazawa ◽

...

Keyword(s):

Transport Model ◽

Co2 Flux

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Improving Runoff Simulations using Satellite-observed Time-series of Snow Covered Area

Hydrology Research ◽

10.2166/nh.2003.0008 ◽

2003 ◽

Vol 34 (4) ◽

pp. 281-294 ◽

Cited By ~ 11

Author(s):

R.V. Engeset ◽

H-C. Udnæs ◽

T. Guneriussen ◽

H. Koren ◽

E. Malnes ◽

...

Keyword(s):

Time Series ◽

Radar Sensors ◽

Noaa Avhrr ◽

Runoff Forecasting ◽

Snow Covered Area ◽

Covered Area ◽

Satellite Sensors ◽

Major Floods ◽

Using Data ◽

Southern Norway

Snowmelt can be a significant contributor to major floods, and hence updated snow information is very important to flood forecasting services. This study assesses whether operational runoff simulations could be improved by applying satellite-derived snow covered area (SCA) from both optical and radar sensors. Currently the HBV model is used for runoff forecasting in Norway, and satellite-observed SCA is used qualitatively but not directly in the model. Three catchments in southern Norway are studied using data from 1995 to 2002. The results show that satellite-observed SCA can be used to detect when the models do not simulate the snow reservoir correctly. Detecting errors early in the snowmelt season will help the forecasting services to update and correct the models before possible damaging floods. The method requires model calibration against SCA as well as runoff. Time-series from the satellite sensors NOAA AVHRR and ERS SAR are used. Of these, AVHRR shows good correlation with the simulated SCA, and SAR less so. Comparison of simultaneous data from AVHRR, SAR and Landsat ETM+ for May 2000 shows good inter-correlation. Of a total satellite-observed area of 1,088 km2, AVHRR observed a SCA of 823 km2 and SAR 720 km2, as compared to 889 km2 using ETM+.

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Solar-Flux Variation in Helium Lines According to SDO/EVE Data in the 24th Cycle and the Forecast for Different Levels of Solar Activity. Lyman Decrements of Hydrogen and Helium Lines

Geomagnetism and Aeronomy ◽

10.1134/s0016793220070099 ◽

2020 ◽

Vol 60 (7) ◽

pp. 966-973

Author(s):

E. A. Bruevich ◽

T. V. Kazachevskaya ◽

G. V. Yakunina

Keyword(s):

Solar Activity ◽

Solar Flux ◽

Flux Variation ◽

24Th Cycle ◽

Different Levels

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Variation in Soil Properties Regulate Greenhouse Gas Fluxes and Global Warming Potential in Three Land Use Types on Tropical Peat

Atmosphere ◽

10.3390/atmos9120465 ◽

2018 ◽

Vol 9 (12) ◽

pp. 465 ◽

Cited By ~ 7

Author(s):

Kiwamu Ishikura ◽

Untung Darung ◽

Takashi Inoue ◽

Ryusuke Hatano

Keyword(s):

Global Warming ◽

Soil Moisture ◽

Groundwater Level ◽

Global Warming Potential ◽

C:N Ratio ◽

Co2 Flux ◽

Nitrate Content ◽

N2o Flux ◽

Ch4 Flux ◽

In The Beginning

This study investigated spatial factors controlling CO2, CH4, and N2O fluxes and compared global warming potential (GWP) among undrained forest (UDF), drained forest (DF), and drained burned land (DBL) on tropical peatland in Central Kalimantan, Indonesia. Sampling was performed once within two weeks in the beginning of dry season. CO2 flux was significantly promoted by lowering soil moisture and pH. The result suggests that oxidative peat decomposition was enhanced in drier position, and the decomposition acidify the peat soils. CH4 flux was significantly promoted by a rise in groundwater level, suggesting that methanogenesis was enhanced under anaerobic condition. N2O flux was promoted by increasing soil nitrate content in DF, suggesting that denitrification was promoted by substrate availability. On the other hand, N2O flux was promoted by lower soil C:N ratio and higher soil pH in DBL and UDF. CO2 flux was the highest in DF (241 mg C m−2 h−1) and was the lowest in DBL (94 mg C m−2 h−1), whereas CH4 flux was the highest in DBL (0.91 mg C m−2 h−1) and was the lowest in DF (0.01 mg C m−2 h−1), respectively. N2O flux was not significantly different among land uses. CO2 flux relatively contributed to 91–100% of GWP. In conclusion, it is necessary to decrease CO2 flux to mitigate GWP through a rise in groundwater level and soil moisture in the region.

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CO<sub>2</sub> flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression

Biogeosciences ◽

10.5194/bg-4-1005-2007 ◽

2007 ◽

Vol 4 (6) ◽

pp. 1005-1025 ◽

Cited By ~ 190

Author(s):

L. Kutzbach ◽

J. Schneider ◽

T. Sachs ◽

M. Giebels ◽

H. Nykänen ◽

...

Keyword(s):

Linear Regression ◽

Nonlinear Regression ◽

Co2 Flux ◽

Exponential Model ◽

Co2 Uptake ◽

Co2 Fluxes ◽

Closed Chamber ◽

Exponential Regression ◽

Closure Time ◽

Over Time

Abstract. Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

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CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals

Remote Sensing ◽

10.3390/rs13152996 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2996

Author(s):

Qinwei Zhang ◽

Mingqi Li ◽

Maohua Wang ◽

Arthur Paul Mizzi ◽

Yongjian Huang ◽

...

Keyword(s):

United States ◽

Spatial Resolution ◽

High Spatial Resolution ◽

Co2 Flux ◽

Total Carbon ◽

Mean Bias Error ◽

Bias Error ◽

Parallel Experiment ◽

Concentration Measurements ◽

Global Stocktake

High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.

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