scholarly journals Optimal estimation of the surface fluxes of methyl chloride using a 3-D global chemical transport model

2009 ◽  
Vol 9 (6) ◽  
pp. 27693-27744 ◽  
Author(s):  
X. Xiao ◽  
R. G. Prinn ◽  
P. J. Fraser ◽  
P. G. Simmonds ◽  
R. F. Weiss ◽  
...  
Keyword(s):  
Salt Marshes ◽  
Transport Model ◽  
Heat Waves ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Methyl Chloride ◽  
Surface Fluxes ◽  
Tropical Plants ◽  
Source And Sink

Abstract. Methyl chloride (CH3Cl) is a chlorine-containing trace gas in the atmosphere contributing significantly to stratospheric ozone depletion. Large uncertainties in estimates of its source and sink magnitudes and temporal and spatial variations currently exist. GEIA inventories and other bottom-up emission estimates are used to construct a priori maps of the surface fluxes of CH3Cl. The Model of Atmospheric Transport and Chemistry (MATCH), driven by NCEP interannually varying meteorological data, is then used to simulate CH3Cl mole fractions and quantify the time series of sensitivities of the mole fractions at each measurement site to the surface fluxes of various regional and global sources and sinks. We then implement the Kalman filter (with the unit pulse response method) to estimate the surface fluxes on regional/global scales with monthly resolution from January 2000 to December 2004. High frequency observations from the AGAGE, SOGE, NIES, and NOAA/ESRL HATS in situ networks and low frequency observations from the NOAA/ESRL HATS flask network are used to constrain the source and sink magnitudes. The inversion results indicate global total emissions around 4100±470 Gg yr−1 with very large emissions of 2200±390 Gg yr−1 from tropical plants, which turn out to be the largest single source in the CH3Cl budget. Relative to their a priori annual estimates, the inversion increases global annual fungal and tropical emissions, and reduces the global oceanic source. The inversion implies greater seasonal and interannual oscillations of the natural sources and sink of CH3Cl compared to the a priori. The inversion also reflects the strong effects of the 2002/2003 globally widespread heat waves and droughts on global emissions from tropical plants, biomass burning and salt marshes, and on the soil sink.

scholarly journals Optimal estimation of the surface fluxes of methyl chloride using a 3-D global chemical transport model

2010 ◽  
Vol 10 (12) ◽  
pp. 5515-5533 ◽  
Author(s):  
X. Xiao ◽  
R. G. Prinn ◽  
P. J. Fraser ◽  
P. G. Simmonds ◽  
R. F. Weiss ◽  
...  
Keyword(s):  
Salt Marshes ◽  
Transport Model ◽  
Heat Waves ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Methyl Chloride ◽  
Surface Fluxes ◽  
Tropical Plants ◽  
Source And Sink

Abstract. Methyl chloride (CH3Cl) is a chlorine-containing trace gas in the atmosphere contributing significantly to stratospheric ozone depletion. Large uncertainties in estimates of its source and sink magnitudes and temporal and spatial variations currently exist. GEIA inventories and other bottom-up emission estimates are used to construct a priori maps of the surface fluxes of CH3Cl. The Model of Atmospheric Transport and Chemistry (MATCH), driven by NCEP interannually varying meteorological data, is then used to simulate CH3Cl mole fractions and quantify the time series of sensitivities of the mole fractions at each measurement site to the surface fluxes of various regional and global sources and sinks. We then implement the Kalman filter (with the unit pulse response method) to estimate the surface fluxes on regional/global scales with monthly resolution from January 2000 to December 2004. High frequency observations from the AGAGE, SOGE, NIES, and NOAA/ESRL HATS in situ networks and low frequency observations from the NOAA/ESRL HATS flask network are used to constrain the source and sink magnitudes. The inversion results indicate global total emissions around 4100 ± 470 Gg yr−1 with very large emissions of 2200 ± 390 Gg yr−1 from tropical plants, which turn out to be the largest single source in the CH3Cl budget. Relative to their a priori annual estimates, the inversion increases global annual fungal and tropical emissions, and reduces the global oceanic source. The inversion implies greater seasonal and interannual oscillations of the natural sources and sink of CH3Cl compared to the a priori. The inversion also reflects the strong effects of the 2002/2003 globally widespread heat waves and droughts on global emissions from tropical plants, biomass burning and salt marshes, and on the soil sink.

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (19) ◽  
pp. 7313-7323 ◽  
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

scholarly journals Trends and inter-annual variability of methane emissions derived from 1979-1993 global CTM simulations

2003 ◽  
Vol 3 (1) ◽  
pp. 73-88 ◽  
Author(s):  
F. Dentener ◽  
M. van Weele ◽  
M. Krol ◽  
S. Houweling ◽  
P. van Velthoven
Keyword(s):  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Methane Emissions ◽  
Anthropogenic Emission ◽  
Top Down ◽  
Bottom Up ◽  
Annual Variability ◽  
The Difference ◽  
Ozone Precursor

Abstract. The trend and interannual variability of methane sources are derived from multi-annual simulations of tropospheric photochemistry using a 3-D global chemistry-transport model. Our semi-inverse analysis uses the fifteen years (1979--1993) re-analysis of ECMWF meteorological data and annually varying emissions including photo-chemistry, in conjunction with observed CH4 concentration distributions and trends derived from the NOAA-CMDL surface stations. Dividing the world in four zonal regions (45--90 N, 0--45 N, 0--45 S, 45--90 S) we find good agreement in each region between (top-down) calculated emission trends from model simulations and (bottom-up) estimated anthropogenic emission trends based on the EDGAR global anthropogenic emission database, which amounts for the period 1979--1993 2.7 Tg CH4 yr-1. Also the top-down determined total global methane emission compares well with the total of the bottom-up estimates. We use the difference between the bottom-up and top-down determined emission trends to calculate residual emissions. These residual emissions represent the inter-annual variability of the methane emissions. Simulations have been performed in which the year-to-year meteorology, the emissions of ozone precursor gases, and the stratospheric ozone column distribution are either varied, or kept constant. In studies of methane trends it is most important to include the trends and variability of the oxidant fields. The analyses reveals that the variability of the emissions is of the order of 8Tg CH4 yr-1, and likely related to wetland emissions and/or biomass burning.

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (3) ◽  
pp. 11783-11810
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Co2 Flux ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a forward model such as a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. Model transport error is an important source of observational error. We investigate the potential of using CO satellite observations as additional constraints in a joint CO2–CO inversion to improve CO2 flux estimates, by exploiting the CTM transport error correlations between CO2 and CO. We estimate the error correlation globally and for different seasons by a paired-model method (comparing CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h CTM forecasts of CO2 and CO columns for the same forecast time). We find strong positive and negative error correlations (r2>0.5) between CO2 and CO columns over much of the world throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. Results from a testbed inverse modeling application show that CO2–CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2–CO inversion vs. a CO2–only inversion.

scholarly journals Stratospheric ozone intrusion events and their impacts on tropospheric ozone

2017 ◽  
Author(s):  
Jesse W. Greenslade ◽  
Simon P. Alexander ◽  
Robyn Schofield ◽  
Jenny A. Fisher ◽  
Andrew K. Klekociuk
Keyword(s):  
Southern Ocean ◽  
Southern Hemisphere ◽  
Tropospheric Ozone ◽  
Bandpass Filter ◽  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Chemical Transport Model ◽  
Macquarie Island ◽  
Modelling Studies

Abstract. Stratosphere-to-troposphere transport (STT) provides an important natural source of ozone to the upper troposphere, but the characteristics of STT events in the southern hemisphere extratropics and their contribution to the regional tropospheric ozone budget remain poorly constrained. Here, we develop a quantitative method to identify STT events from ozonesonde profiles. Using this method we estimate the seasonality and quantify the ozone transported across the tropopause over Davis (69° S), Macquarie Island (54° S), and Melbourne (38° S). STT seasonality is determined by two distinct methods: a Fourier bandpass filter of the vertical ozone profile, and an analysis of the Brunt-Viäsälä frequency. Using a bandpass filter on 7–9 years of ozone profiles from each site provides clear detection of STT events, with maximum occurrences during summer and minimum during winter above all three sites. The majority of tropospheric ozone enhancements from STT events occur within 2.5 km, 3 km of the tropopause at Davis, and Macquarie Island. Events are more spread out at Melbourne, occurring frequently up to 7.5 km from the tropopause. The mean fraction of total tropospheric ozone attributed to STT during STT events is 2–4 % at each site; however, during individual events over 10 % of tropospheric ozone may be directly transported from the stratosphere. The cause of STTs is determined to be largely due to synoptic low pressure frontal systems, determined using coincident ERA-Interim reanalysis meteorological data. Ozone enhancements can also be caused by biomass burning plumes transported from Africa and South America, these are apparent during austral winter and spring, and are determined using satellite measurements of CO. To provide regional context for the ozonesonde observations, we use the GEOS-Chem chemical transport model, which is too coarsely resolved to distinguish STT events but is able to accurately simulate the seasonal cycle of tropospheric ozone columns over the three southern hemisphere sites. Combining the ozonesonde-derived STT event characteristics with the simulated tropospheric ozone columns from GEOS-Chem, we conservatively estimate that the annual tropospheric ozone flux over the Southern Ocean due to STT events is ~ 3.2 ×1016 molecules cm−2 yr−1. This value is significantly lower than expected from previous global estimates due to the conservative nature of several components of our calculation, in particular the contribution of STT to total tropospheric ozone during an event (STT impact). Using an assumed STT impact of 35 % based on prior modelling studies rather than our observational estimate of 2–4 % increases the estimated Southern Ocean flux by an order of magnitude. Despite lingering uncertainties in scaling ozonesonde measurements to regional values, ozonesonde datasets provide a useful tool for STT detection, and the analysis methods described in this paper could be applied to many existing long-term records.

scholarly journals Stratospheric ozone intrusion events and their impacts on tropospheric ozone in the Southern Hemisphere

2017 ◽  
Vol 17 (17) ◽  
pp. 10269-10290 ◽  
Author(s):  
Jesse W. Greenslade ◽  
Simon P. Alexander ◽  
Robyn Schofield ◽  
Jenny A. Fisher ◽  
Andrew K. Klekociuk
Keyword(s):  
Southern Hemisphere ◽  
Tropospheric Ozone ◽  
Bandpass Filter ◽  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Austral Summer ◽  
Chemical Transport Model ◽  
Macquarie Island ◽  
Ozone Profile

Abstract. Stratosphere-to-troposphere transport (STT) provides an important natural source of ozone to the upper troposphere, but the characteristics of STT events in the Southern Hemisphere extratropics and their contribution to the regional tropospheric ozone budget remain poorly constrained. Here, we develop a quantitative method to identify STT events from ozonesonde profiles. Using this method we estimate the seasonality of STT events and quantify the ozone transported across the tropopause over Davis (69° S, 2006–2013), Macquarie Island (54° S, 2004–2013), and Melbourne (38° S, 2004–2013). STT seasonality is determined by two distinct methods: a Fourier bandpass filter of the vertical ozone profile and an analysis of the Brunt–Väisälä frequency. Using a bandpass filter on 7–9 years of ozone profiles from each site provides clear detection of STT events, with maximum occurrences during summer and minimum during winter for all three sites. The majority of tropospheric ozone enhancements owing to STT events occur within 2.5 and 3 km of the tropopause at Davis and Macquarie Island respectively. Events are more spread out at Melbourne, occurring frequently up to 6 km from the tropopause. The mean fraction of total tropospheric ozone attributed to STT during STT events is  ∼ 1. 0–3. 5 % at each site; however, during individual events, over 10 % of tropospheric ozone may be directly transported from the stratosphere. The cause of STTs is determined to be largely due to synoptic low-pressure frontal systems, determined using coincident ERA-Interim reanalysis meteorological data. Ozone enhancements can also be caused by biomass burning plumes transported from Africa and South America, which are apparent during austral winter and spring and are determined using satellite measurements of CO. To provide regional context for the ozonesonde observations, we use the GEOS-Chem chemical transport model, which is too coarsely resolved to distinguish STT events but is able to accurately simulate the seasonal cycle of tropospheric ozone columns over the three southern hemispheric sites. Combining the ozonesonde-derived STT event characteristics with the simulated tropospheric ozone columns from GEOS-Chem, we estimate STT ozone flux near the three sites and see austral summer dominated yearly amounts of between 5. 7 and 8. 7 × 1017 molecules cm−2 a−1.

scholarly journals Trends and inter-annual variability of methane emissions derived from 1979-1993 global CTM simulations

2002 ◽  
Vol 2 (2) ◽  
pp. 249-287 ◽  
Author(s):  
F. Dentener ◽  
M. van Weele ◽  
M. Krol ◽  
S. Houweling ◽  
P. van Velthoven
Keyword(s):  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Regional Scale ◽  
Methane Emissions ◽  
Anthropogenic Emission ◽  
Top Down ◽  
Bottom Up ◽  
Annual Variability ◽  
The Difference

Abstract. The trend and interannual variability of methane sources are derived from multi-annual simulations of tropospheric photochemistry using a 3D global chemistry-transport model. Our semi-inverse analysis uses the fifteen years (1979 -1993) re-analysis of ECMWF meteorological data and annually varying including photo-chemistry, in conjunction with observed CH4 concentration distributions and trends derived from the NOAA-CMDL surface stations. Dividing the world in four zonal regions, (45-90 N, 0-45 N, 0-45 S; 45-90 S) we find good agreement in each region between (top-down) calculated emission trends from model simulations and (bottom-up) estimated anthropogenic emission trends based on the EDGAR global anthropogenic emission database, which amounts for the period 1979 -1993 2.7 Tg CH4 yr -1. Also the top-down determined total global methane emission compares well with the total of the bottom-up estimates. We use the difference between the bottom-up and top-down determined emission trends to calculate residual emissions. These residual emissions represent the inter-annual variability of the methane emissions. Simulations have been performed in which the year-to-year meteorology, the emissions of ozone precursor gases, and the stratospheric ozone column distribution are either varied, or kept constant. The analyses reveals that the variability of the emissions is of the order of 8 Tg CH4 yr -1, and most likely related to mid- and low-latitude wetland emissions and/or biomass burning. Indeed, a weak correlation is found between the residual emissions and regional scale temperatures.

scholarly journals Atmospheric three-dimensional inverse modeling of regional industrial emissions and global oceanic uptake of carbon tetrachloride

2010 ◽  
Vol 10 (21) ◽  
pp. 10421-10434 ◽  
Author(s):  
X. Xiao ◽  
R. G. Prinn ◽  
P. J. Fraser ◽  
R. F. Weiss ◽  
P. G. Simmonds ◽  
...  
Keyword(s):  
Carbon Tetrachloride ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
A Priori ◽  
Three Dimensional ◽  
Low Frequency ◽  
Montreal Protocol ◽  
Interannual Variations ◽  
Chemical Transport Model ◽  
Industrial Emissions

Abstract. Carbon tetrachloride (CCl4) has substantial stratospheric ozone depletion potential and its consumption is controlled under the Montreal Protocol and its amendments. We implement a Kalman filter using atmospheric CCl4 measurements and a 3-dimensional chemical transport model to estimate the interannual regional industrial emissions and seasonal global oceanic uptake of CCl4 for the period of 1996–2004. The Model of Atmospheric Transport and Chemistry (MATCH), driven by offline National Center for Environmental Prediction (NCEP) reanalysis meteorological fields, is used to simulate CCl4 mole fractions and calculate their sensitivities to regional sources and sinks using a finite difference approach. High frequency observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) and low frequency flask observations are together used to constrain the source and sink magnitudes, estimated as factors that multiply the a priori fluxes. Although industry data imply that the global industrial emissions were substantially declining with large interannual variations, the optimized results show only small interannual variations and a small decreasing trend. The global surface CCl4 mole fractions were declining in this period because the CCl4 oceanic and stratospheric sinks exceeded the industrial emissions. Compared to the a priori values, the inversion results indicate substantial increases in industrial emissions originating from the South Asian/Indian and Southeast Asian regions, and significant decreases in emissions from the European and North American regions.

scholarly journals What can tracer observations in the continental boundary layer tell us about surface-atmosphere fluxes?

2005 ◽  
Vol 5 (5) ◽  
pp. 9249-9290 ◽  
Author(s):  
C. Gerbig ◽  
J. C. Lin ◽  
J. W. Munger ◽  
S. C. Wofsy
Keyword(s):  
Transport Model ◽  
Near Field ◽  
A Priori ◽  
Horizontal Resolution ◽  
Significant Loss ◽  
Surface Fluxes ◽  
Environmental Drivers ◽  
Functional Responses ◽  
Spatially Resolved ◽  
Pseudo Data

Abstract. We analyze the potential for inferring spatially resolved surface fluxes from atmospheric tracer observations within the mixed layer, such as from monitoring towers, using a receptor oriented transport model (Stochastic Time-Inverted Lagrangian Transport model – STILT) coupled to a simple biosphere in which CO2 fluxes are represented as functional responses to environmental drivers (radiation and temperature). Transport and biospheric fluxes are coupled on a dynamic grid using a polar projection with high horizontal resolution (~20 km) in near field, and low resolution far away (as coarse as 2000 km), reducing the number of surface pixels without significant loss of information. To test the system, and to evaluate the errors associated with the retrieval of fluxes from atmospheric observations, a pseudo data experiment was performed. A large number of realizations of measurements (pseudo data) and a priori fluxes were generated, and for each case spatially resolved fluxes were retrieved. Results indicate strong potential for high resolution retrievals based on a network of tall towers, subject to the requirement of correctly specifying the a priori uncertainty covariance, especially the off diagonal elements that control spatial correlations. False assumptions about the degree to which the uncertainties in the a priori fluxes are spatially correlated may lead to a strong underestimation of uncertainties in the retrieved fluxes, or, equivalently, to biased retrievals. The framework presented here, however, allows a conservative choice of the off diagonal elements that avoids biasing the retrievals.

scholarly journals On the Predictability of Land Surface Fluxes from Meteorological Variables

2017 ◽  
Author(s):  
Ned Haughton ◽  
Gab Abramowitz ◽  
Andy J. Pitman
Keyword(s):  
Land Surface ◽  
Meteorological Data ◽  
A Priori ◽  
Predictive Performance ◽  
Empirical Models ◽  
Surface Fluxes ◽  
Meteorological Variables ◽  
Meteorological Forcing ◽  
Wide Range ◽  
Surface Models

Abstract. Previous research has shown that Land Surface Models (LSMs) are performing poorly when compared with rela- tively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appears to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that is used by LSMs for predicting land surface fluxes, by interrogating Fluxnet data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce, and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We re-analyse previously published LSM simulations, and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

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