Reconstructing and modelling 71 years of forest growth in a Canadian boreal landscape: a test of the CBM-CFS3 carbon accounting model

2010 ◽  
Vol 40 (1) ◽  
pp. 109-118 ◽  
Author(s):  
P. Y. Bernier ◽  
L. Guindon ◽  
W. A. Kurz ◽  
G. Stinson
Keyword(s):  
Yield Curve ◽  
Forest Growth ◽  
Carbon Accounting ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Forest Sector ◽  
Eastern Canada ◽  
Data Set ◽  
Carbon Budget Model ◽  
Accounting Model

We carried out a verification exercise of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) carbon accounting model through the use of a reconstructed data set of forest growth and disturbances spanning a 71 year period (1928–1998) and encompassing a 62 km2 landscape of boreal forest in eastern Canada. Overall, results show that yield curve simulations using CBM-CFS3 underestimate realized net biomass accrual by 10% in undisturbed stands. The bias in disturbed stands may be slightly larger. Errors linked to the estimation of the initial 1928 merchantable volume and biomass through the operational forest photointerpretation and inventory procedure may be the largest single cause of the bias. The local application of regionally parameterized yield curves may also be at fault. It is unlikely that long-term trends in climate or atmospheric composition may have generated such bias. Analyses of changes in specific carbon pools and comparisons made with results from a similar exercise carried out in a Pacific coastal forest show a small relative impact on total carbon from forest management activities in the absence of natural disturbances.

scholarly journals First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2012 ◽  
Vol 5 (1) ◽  
pp. 1355-1379
Author(s):  
F. Forster ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
D. W. T. Griffith ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
Calibration Factor ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar FTIR measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR time series shows a phase shift in XCH4 seasonality, i.e. a significant time-dependent bias leading to a standard deviation (stdv) of the difference time series (NIR-MIR) of 8.4 ppb. After eliminating differences in a prioris by using ACTM-simulated profiles as a common prior, the seasonalities of the (corrected) MIR and NIR time series agree within the noise (stdv = 5.2 ppb for the difference time series). The difference time series (NIR-MIR) do not show a significant trend. Therefore it is possible to use a simple scaling factor for the intercalibration without a time-dependent linear or seasonal component. Using the Garmisch and Wollongong data together, we obtain an overall calibration factor MIR/NIR = 0.9926(18). The individual calibration factors per station are 0.9940(14) for Garmisch and 0.9893(40) for Wollongong. They agree within their error bars with the overall calibration factor which can therefore be used for both stations. Our results suggest that after applying the proposed intercalibration concept to all stations performing both NIR and MIR measurements, it should be possible to obtain one refined overall intercalibration factor for the two networks. This would allow to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Validation of SCIAMACHY HDO/H<sub>2</sub>O measurements using the TCCON and NDACC-MUSICA networks

2015 ◽  
Vol 8 (4) ◽  
pp. 1799-1818 ◽  
Author(s):  
R. A. Scheepmaker ◽  
C. Frankenberg ◽  
N. M. Deutscher ◽  
M. Schneider ◽  
S. Barthlott ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Hydrological Cycle ◽  
Source Region ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
The Tibetan Plateau ◽  
Wet Season ◽  
Data Set ◽  
The Mean ◽  
The Impact

Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.

scholarly journals Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON

2016 ◽  
Vol 9 (2) ◽  
pp. 683-709 ◽  
Author(s):  
Susan Kulawik ◽  
Debra Wunch ◽  
Christopher O'Dell ◽  
Christian Frankenberg ◽  
Maximilian Reuter ◽  
...  
Keyword(s):  
Mole Fraction ◽  
Seasonal Cycle ◽  
Atmospheric Co2 ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Cycle Phase ◽  
Data Set ◽  
Single Observation ◽  
Cycle Amplitude ◽  
The Impact

Abstract. Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (XCO2) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 ppm vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to error2 = a2 + b2/n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of  ∼  0.3 ppm, with biases larger than the TCCON-predicted bias uncertainty of 0.4 ppm at many stations. We find that GOSAT and CT2013b underpredict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53° N, MACC overpredicts between 26 and 37° N, and CT2013b underpredicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in JJA; there is correlation between 0.2 and 0.8 in the NH, with models showing 10–50 % the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45–67° N for GOSAT and CT2013b.

scholarly journals First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2013 ◽  
Vol 6 (2) ◽  
pp. 397-418 ◽  
Author(s):  
R. Sussmann ◽  
A. Ostler ◽  
F. Forster ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
A Priori ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the first intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR XCH4 time series for Garmisch shows a quasi-periodic seasonal bias leading to a standard deviation (stdv) of the difference time series (NIR–MIR) of 7.2 ppb. After reducing time-dependent a priori impact by using realistic site- and time-dependent ACTM-simulated profiles as a common prior, the seasonal bias is reduced (stdv = 5.2 ppb). A linear fit to the MIR/NIR scatter plot of monthly means based on same-day coincidences does not show a y-intercept that is statistically different from zero, and the MIR/NIR intercalibration factor is found to be close to ideal within 2-σ uncertainty, i.e. 0.9996(8). The difference time series (NIR–MIR) do not show a significant trend. The same basic findings hold for Wollongong. In particular an overall MIR/NIR intercalibration factor close to the ideal 1 is found within 2-σ uncertainty. At Wollongong the seasonal cycle of methane is less pronounced and corresponding smoothing errors are not as significant, enabling standard MIR and NIR retrievals to be used directly, without correction to a common a priori. Our results suggest that it is possible to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Identifying the sources driving observed PM<sub>2.5</sub> temporal variability over Halifax, Nova Scotia, during BORTAS-B

2013 ◽  
Vol 13 (14) ◽  
pp. 7199-7213 ◽  
Author(s):  
M. D. Gibson ◽  
J. R. Pierce ◽  
D. Waugh ◽  
J. S. Kuchta ◽  
L. Chisholm ◽  
...  
Keyword(s):  
Nova Scotia ◽  
Atmospheric Chemistry ◽  
Forest Fires ◽  
Atmospheric Composition ◽  
Back Trajectory ◽  
Valuable Insight ◽  
Eastern Canada ◽  
Data Set ◽  
Average Mass ◽  
The Impact

Abstract. The source attribution of observed variability of total PM2.5 concentrations over Halifax, Nova Scotia, was investigated between 11 July and 26 August 2011 using measurements of PM2.5 mass and PM2.5 chemical composition (black carbon, organic matter, anions, cations and 33 elements). This was part of the BORTAS-B (quantifying the impact of BOReal forest fires on Tropospheric oxidants using Aircraft and Satellites) experiment, which investigated the atmospheric chemistry and transport of seasonal boreal wildfire emissions over eastern Canada in 2011. The US EPA Positive Matrix Factorization (PMF) receptor model was used to determine the average mass (percentage) source contribution over the 45 days, which was estimated to be as follows: long-range transport (LRT) pollution: 1.75 μg m−3 (47%); LRT pollution marine mixture: 1.0 μg m−3 (27.9%); vehicles: 0.49 μg m−3 (13.2%); fugitive dust: 0.23 μg m−3 (6.3%); ship emissions: 0.13 μg m−3 (3.4%); and refinery: 0.081 μg m−3 (2.2%). The PMF model describes 87% of the observed variability in total PM2.5 mass (bias = 0.17 and RSME = 1.5 μg m−3). The factor identifications are based on chemical markers, and they are supported by air mass back trajectory analysis and local wind direction. Biomass burning plumes, found by other surface and aircraft measurements, were not significant enough to be identified in this analysis. This paper presents the results of the PMF receptor modelling, providing valuable insight into the local and upwind sources impacting surface PM2.5 in Halifax and a vital comparative data set for the other collocated ground-based observations of atmospheric composition made during BORTAS-B.

scholarly journals Technical note: Sensitivity of instrumental line shape monitoring for the ground-based high-resolution FTIR spectrometer with respect to different optical attenuators

2017 ◽  
Vol 10 (3) ◽  
pp. 989-997 ◽  
Author(s):  
Youwen Sun ◽  
Mathias Palm ◽  
Christine Weinzierl ◽  
Christof Petri ◽  
Justus Notholt ◽  
...  
Keyword(s):  
High Resolution ◽  
Line Shape ◽  
Radiant Energy ◽  
Technical Note ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Incident Intensity ◽  
Instrumental Line ◽  
Ftir Spectrometer ◽  
Potential Strategy

Abstract. The TCCON (Total Carbon Column Observing Network) and most NDACC (Network for Detection of Atmospheric Composition Change) sites assume an ideal ILS (instrumental line shape) for analysis of the spectra. In order to adapt the radiant energy received by the detector, an attenuator or different sizes of field stop can be inserted in the light path. These processes may alter the alignment of a high-resolution FTIR (Fourier transform infrared) spectrometer, and may result in bias due to ILS drift. In this paper, we first investigated the sensitivity of the ILS monitoring with respect to application of different kinds of attenuators for ground-based high-resolution FTIR spectrometers within the TCCON and NDACC networks. Both lamp and sun cell measurements were conducted after the insertion of five different attenuators in front of and behind the interferometer. The ILS characteristics derived from lamp and sun spectra are in good agreement. ILSs deduced from all lamp cell measurements were compared. As a result, the disturbances to the ILS of a high-resolution FTIR spectrometer with respect to the insertion of different attenuators at different positions were quantified. A potential strategy to adapt the incident intensity of a detector was finally deduced.

scholarly journals Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

2015 ◽  
Vol 8 (2) ◽  
pp. 1787-1832 ◽  
Author(s):  
J. Heymann ◽  
M. Reuter ◽  
M. Hilker ◽  
M. Buchwitz ◽  
O. Schneising ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Detailed Comparison ◽  
Mean Difference ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Data Set ◽  
Time Period ◽  
Comparison Results ◽  
The Future

Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY onboard ENVISAT (March 2002–April 2012) and TANSO-FTS onboard GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System (IFS). We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r = 0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT-TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (±2 h, 10° × 10° around TCCON sites), i.e., the observed air masses are not exactly identical, but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.

Increasing revenue and attendance in Canadian Baptist churches

2015 ◽  
Vol 42 (12) ◽  
pp. 1071-1089
Author(s):  
Alan Chan ◽  
Bruce G. Fawcett ◽  
Shu-Kam Lee
Keyword(s):  
Church Health ◽  
Eastern Canada ◽  
Data Set ◽  
Content Type ◽  
Factors Affecting ◽  
Scarce Resources ◽  
Baptist Churches ◽  
And Performance ◽  
The Impact ◽  
Simulation Exercises

Purpose – Church giving and attendance are two important indicators of church health and performance. In the literature, they are usually understood to be simultaneously determined. The purpose of this paper is to estimate if there a sustainable church congregation size using Wintrobe’s (1998) dictatorship model. The authors want to examine the impact of youth and adult ministry as well. Design/methodology/approach – Using the data collected from among Canadian Baptist churches in Eastern Canada, this study investigates the factors affecting the level of the two indicators by the panel-instrumental variable technique. Applying Wintrobe’s (1998) political economy model on dictatorship, the equilibrium level of worship attendance and giving is predicted. Findings – Through various simulation exercises, the actual church congregation sizes is approximately 50 percent of the predicted value, implying inefficiency and misallocation of church resources. The paper concludes with insights on effective ways church leaders can allocate scarce resources to promote growth within churches. Originality/value – The authors are the only researchers getting the permission from the Atlantic Canada Baptist Convention to use their mega data set on church giving and congregation sizes as per the authors’ knowledge. The authors are also applying a theoretical model on dictatorship to religious/not for profits organizations.

scholarly journals Interactive effects of ambient ozone and climate measured on growth of mature loblolly pine trees

1996 ◽  
Vol 26 (4) ◽  
pp. 670-681 ◽  
Author(s):  
S.B. McLaughlin ◽  
D.J. Downing
Keyword(s):  
Soil Moisture ◽  
Loblolly Pine ◽  
Moisture Stress ◽  
Growth Patterns ◽  
Forest Growth ◽  
Interactive Effects ◽  
Forest Trees ◽  
Short Term ◽  
Data Set ◽  
Ambient Ozone

Seasonal growth patterns of mature loblolly pine (Pinustaeda L.) trees over the interval 1988–1993 have been analyzed to evaluate the effects of ambient ozone on growth of large forest trees. Patterns of stem expansion and contraction of 34 trees were examined using serial measurements with sensitive dendrometer band systems. Study sites, located in eastern Tennessee, varied significantly in soil moisture, soil fertility, and stand density. Levels of ozone, rainfall, and temperature varied widely over the 6-year study interval. Regression analysis identified statistically significant influences of ozone on stem growth patterns, with responses differing widely among trees and across years. Ozone interacted with both soil moisture stress and high temperatures, explaining 63% of the high frequency, climatic variance in stem expansion identified by stepwise regression of the 5-year data set. Observed responses to ozone were rapid, typically occurring within 1–3 days of exposure to ozone at ≥40 ppb and were significantly amplified by low soil moisture and high air temperatures. Both short-term responses, apparently tied to ozone-induced increases in whole-tree water stress, and longer term cumulative responses were identified. These data indicate that relatively low levels of ambient ozone can significantly reduce growth of mature forest trees and that interactions between ambient ozone and climate are likely to be important modifiers of future forest growth and function. Additional studies of mechanisms of short-term response and interspecies comparisons are clearly needed.

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