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This study explores the role of snowpack in polar boundary layer chemistry, especially as a direct source of reactive bromine (BrOX=BrO+Br) and nitrogen (NOX=NO+NO2) in the Arctic springtime. Surface snow samples were collected daily from a Canadian high Arctic location at Eureka, Nunavut (80°N, 86°W) from the end of February to the end of March in 2018 and 2019. The snow was sampled at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ~600 m above sea level (asl). At the inland sites, surface snow salinity has a double-peak distribution with the first and lowest peak at 0.001-0.002 practical salinity unit (psu), which corresponds to the precipitation effect, and the second peak at 0.01-0.04 psu, which is likely related to the salt accumulation effect (due to loss of water vapour by sublimation). Snow salinity on sea ice has a triple-peak distribution; its first and second peaks overlap with the inland peaks, and the third peak at 0.2-0.4 psu is likely due to the sea water effect (due to upward migration of brine on sea ice). At all sites, snow sodium and chloride concentrations increase by almost 10-fold from the top 0.2 cm to ~1.5 cm in depth. Surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Moreover, surface snow bromide at sea level has an increasing trend over the measurement time period, with mean slopes of 0.024 in the 0-0.2 cm layer and 0.016 μM d-1 in the 0.2-0.5 cm layer. Surface snow nitrate at sea level also shows a significant increasing trend, with mean slopes of 0.27, 0.20, and 0.07 μM d-1 in the top 0.2 cm, 0.2-0.5 cm, and 0.5-1.5 cm layers, respectively. Using these trends, an integrated net deposition flux of bromide of 1.01×107 molecules cm-2 s-1 and an integrated net deposition flux of nitrate of 2.6×108 molecules cm-2 s-1 were derived. In addition, nitrate and bromide in the morning samples are significantly higher than the afternoon samples, indicating a strong photochemistry effect. However, the mean bromide loss rate (0.027-0.040 μM) is smaller than the nitrate loss rate (0.23-0.362 μM) by an order of magnitude, implying the reactive bromine emission flux from snowpack is significantly smaller than the reactive nitrogen emission flux, which is consistent with the large difference between their derived net deposition fluxes. After considering the photochemical loss effect, the corrected bromide deposition flux at sea level is 2.73×107 molecules cm-2 s-1; for nitrate, the corrected deposition flux is 5.98×108 molecules cm-2 s-1. In addition, the surface snow nitrate and bromide at inland sites were found to be significantly correlated (R=0.48-0.76), and the [NO3-]/[Br-] ratio of 4-7 indicates a possible acceleration effect of reactive bromine in atmospheric NOX-to-nitrate conversion. This is the first time such an effect has been seen in snow chemistry data obtained with a sampling frequency as short as one day. [ABSTRACT FROM AUTHOR]

Both measurements and modelling of air pollution in the Arctic are difficult. Yet with the Arctic warming at nearly four times the global average rate, and changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. This study examines the simulations of atmospheric concentrations of methane, carbon monoxide and ozone in the Arctic by 11 models. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). Mixing ratios of trace gases are modelled at three-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1 and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0-7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased ow in the tropospheric column, on average by -9.6% for CH4, -21% for CO and -18% for O3. Results for CH4 are relatively consistent across the four years, whereas CO has a maximum negative bias in the spring and minimum in the summer, and O3 has a maximum difference centred around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15% of the model-location comparisons. [ABSTRACT FROM AUTHOR]

Ozone depletion over the polar regions is monitored each year by satellite and ground-based instruments. In this study, the vortex-averaged ozone loss over the last three decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from Système d'Analyse par Observation Zénithale (SAOZ) ground-based instruments and Multi-Sensor Reanalysis (MSR2). The passive tracer method allows us to determine the evolution of the daily rate of column ozone destruction, and the magnitude of the cumulative loss the end of the winter. Three metrics are used to estimate the linear trend since 2000 and to assess the current situation of ozone recovery over both polar regions: 1) The maximum ozone loss at the end of the winter; 2) the onset day of ozone loss at specific threshold and 3) the ozone loss residuals computed from the differences between annual ozone loss and ozone loss values regressed with respect to sunlit volume of polar stratospheric clouds (VPSC). This latter metric is based on linear and parabolic regressions for ozone loss in the Northern and Southern Hemispheres, respectively. In the Antarctic, metrics 1, and yield trends of -2.3 and -1.8% dec-1 for the 2000-2021 period, significant at 1 and 2 standard error, respectively. For metric 2, various thresholds were considered, all of them showing a time delay for when they are reached. The trends are significant at the 2 level and vary from 3.5 to 4.2 day dec-1 between the various thresholds. In the Arctic, metric 1 exhibits large interannual variability and no significant trend is detected; this result is highly influenced by the record ozone losses in 2011 and 2020. Metric 2 is not applied in the Northern Hemisphere due to the difficulty of finding a threshold value in a consistent number of winters. Metric 3 shows a negative trend in Arctic ozone loss residuals of -1.7 ±1% dec-1, significant at level. This is therefore the first quantitative detection of ozone recovery in the Arctic springtime lower stratosphere. [ABSTRACT FROM AUTHOR]

Megacities can experience high levels of fine particulate matter (PM2.5) pollution linked to ammonia (NH3) mainly emitted from agricultural activities. Here, we investigate such pollution in the cities of Paris, Mexico and Toronto, each of which have distinct emission sources, agricultural regulations, and topography. Ten years of measurements from the Infrared Atmospheric Sounding Interferometer (IASI) are used to assess the spatio-temporal NH3 variability over and around the three cities. In Europe and North America, we determine that temperature is associated with the increase in NH3 atmospheric concentrations with coefficient of determination (r2) of 0.8 over agricultural areas. The variety of the NH3 sources (industry and agricultural) and the weaker temperature seasonal cycle in southern North America induce a lower correlation factor (r2 = 0.5). The three regions are subject to long range transport of NH3, as shown using HYSPLIT cluster back-trajectories. The highest NH3 concentrations measured at the city scales are associated with air masses coming from the surrounding and north-northeast regions of Paris, the south-southwest areas of Toronto, and the southeast/southwest zones of Mexico City. Using NH3 and PM2.5 measurements derived from IASI and surface observations from 2008 to 2017, annually frequent pollution events are identified in the 3 cities. Wind roses reveal statistical patterns during these pollution events with dominant northeast-southwest directions in Paris and Mexico cities, and the transboundary transport of pollutants from the United-States in Toronto. To check how well chemistry transport models perform during pollution events, we evaluate simulations made using the GEOS-Chem model for March 2011. In these simulations we find that NH3 concentrations are overall underestimated, though day-to-day variability is well represented. PM2.5 is generally underestimated over Paris and Mexico, but overestimated over Toronto. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulphuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of groundbased solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources. Most of the NH3 measured at the urban station is from local sources, while the NH3 observed at the remote site is most likely transported from the city and surrounding areas. The evolution of the boundary layer and the temperature play a significant role in the recorded seasonal and diurnal patterns of NH3. Although the vertical columns of NH3 are much larger at the urban station, the observed annual cycles are similar for both stations, with the largest values in the warm months, such as April and May. The IASI measurements underestimate the FTIR NH3 total columns by an average of 32.2 ± 27.5 % but exhibit similar temporal variability. The NH3 spatial distribution from IASI shows the largest columns in the northeast part of the city. In general, NH3 total columns over Mexico City exhibited an average annual increase of 92 ± 3.9 x 1013 molecules/cm² yr (urban) and 8.4 ± 1.4 x 1013 molecules/cm² yr (remote) was observed in Mexico City at both FTIR stations and a decadal increase of 62 % with IASI data. [ABSTRACT FROM AUTHOR]

Within the framework of the International Arctic Systems for Observing the Atmosphere (IASOA), we report a modelling-based study on surface ozone across the Arctic. We use surface ozone from six sites: Summit (Greenland), Pallas (Finland), Barrow (USA), Alert (Canada), Tiksi (Russia), and Villum Research Station (VRS) at Station Nord (North Greenland, Danish Realm), and ozonesonde data from three Canadian sites: Resolute, Eureka, and Alert. Two global chemistry models: a global chemistry transport model (p-TOMCAT) and a global chemistry climate model (UKCA), are used for model-data comparisons. Remotely sensed data of BrO from the GOME-2 satellite instrument and ground-based Multi-axis Differential Optical Absorption Spectroscopy (MAX-DOAS) at Eureka, Canada are used for model validation. The observed climatology data show that spring surface ozone at coastal sites is heavily depleted, making ozone seasonality at Arctic coastal sites distinctly different from that at inland sites. Model simulations show that surface ozone can be greatly reduced by bromine chemistry. In April, bromine chemistry can cause a net ozone loss (monthly mean) of 10–20 ppbv, with almost half attributable to open-ocean-sourced bromine and the rest to sea-ice-sourced bromine. However, the open-ocean-sourced bromine, via sea spray bromide depletion, cannot by itself produce ozone depletion events (ODEs) (defined as ozone volume mixing ratios VMRs < 10 ppbv). In contrast, sea-ice-sourced bromine, via sea salt aerosol (SSA) production from blowing snow, can produce ODEs even without bromine from sea spray, highlighting the importance of sea ice surface in polar boundary layer chemistry. Model bromine is sensitive to model configuration, e.g., under the same bromine loading, the total inorganic bromine (BrY) in the Arctic spring boundary layer in the p-TOMCAT base run (i.e., with all bromine emissions) can be 2 times larger than that in the UKCA base run. Despite the model differences, both model base runs can successfully reproduce large bromine explosion events (BEEs) in polar spring. Model-integrated tropospheric column BrO generally matches GOME-2 tropospheric columns within ~50 % (in the UKCA base run) and factors of 2–3 (in the p-TOMCAT base run). The success of the models in reproducing both ODEs and BEEs in the Arctic indicates that the relevant parameterizations implemented in the models work reasonably well, which supports the proposed mechanism of SSA and bromine production from blowing snow on sea ice. Given that sea ice is a large source of SSA and halogens, changes in sea ice type and extent in a warming climate will influence Arctic boundary layer chemistry, including the oxidation of atmospheric elemental mercury. [ABSTRACT FROM AUTHOR]

We analyzed seasonality and interannual variability of tropospheric HCN column amounts in densely populated eastern China for the first time. The results were derived from solar absorption spectra recorded with ground-based high spectral resolution Fourier transform infrared (FTIR) spectrometer at Hefei (117°10' E, 31°54' N) between 2015 and 2018. The tropospheric HCN columns over Hefei, China showed significant seasonal variations with three monthly mean peaks throughout the year. The magnitude of the tropospheric HCN column peak in May > September > December. The tropospheric HCN column reached a maximum of (9.8 ± 0.78) x 1015 molecules/cm² in May and a minimum of (7.16 ± 0.75) x 1015 molecules/cm² in November. In most cases, the tropospheric HCN columns at Hefei (32° N) are higher than the FTIR observations at Ny Alesund (79° N), Kiruna (68° N), Bremen (53° N), Jungfraujoch (47° N), Toronto (44° N), Rikubetsu (43° N), Izana (28° N), Mauna Loa (20° N), La Reunion Maido (21° S), Lauder (45° S), and Arrival Heights (78° S) that are affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Enhancements of the tropospheric HCN columns were observed between September 2015 and July 2016 compared to the counterpart measurements in other years. The magnitude of the enhancement ranges from 5 to 46 % with an average of 22 %. Enhancement of tropospheric HCN (ΔHCN) is correlated with the coincident enhancement of tropospheric CO (ΔCO), indicating that enhancements of tropospheric CO and HCN were due to the same sources. The GEOS-Chem tagged CO simulation, the global fire maps and the PSCFs (Potential Source Contribution Function) calculated using back trajectories revealed that the seasonal maxima in May is largely due to the influence of biomass burning in South Eastern Asia (SEAS) (41 ± 13.1 %), Europe and Boreal Asia (EUBA) (21 ± 9.3 %) and Africa (AF) (22 ± 4.7 %). The seasonal maxima in September is largely due to the influence of biomass burnings in EUBA (38 ± 11.3 %), AF (26 ± 6.7 %), SEAS (14 ± 3.3 %), and Northern America (NA) (13.8 ± 8.4 %). For the seasonal maxima in December, dominant contributions are from AF (36 ± 7.1 %), EUBA (21 ± 5.2 %), and NA (18.7 ± 5.2 %). The tropospheric HCN enhancement between September 2015 and July 2016 at Hefei (32° N) were attributed to an elevated influence of biomass burnings in SEAS, EUBA, and Oceania (OCE) in this period. Particularly, an elevated fire number in OCE in the second half of 2015 dominated the tropospheric HCN enhancement in September-December 2015. An elevated fire number in SEAS in the first half of 2016 dominated the tropospheric HCN enhancement in January-July 2016. [ABSTRACT FROM AUTHOR]

We present a multi-year time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier transform infrared (FTIR) spectrometers at ten sites affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Alesund, Thule, Kiruna, Poker Flat, and St. Petersburg, and four are mid-latitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the inter-annual trends and seasonal variabilities of the CO time series are accounted for, allowing ambient concentrations to be determined. Enhancements above ambient levels were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution, while complementary measurements of aerosol optical depth from nearby AERONET sites confirm the presence of wildfire smoke. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFAS) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003-2018. The influence of the various wildfire sources is found to differ between sites while North American and Asian boreal wildfires fires were found to be the greatest contributors to episodic CO enhancements in the summertime at all sites. [ABSTRACT FROM AUTHOR]

We examined biases in the global GEOS-Chem chemical transport model for the period of February-May 2010 using weak constraint (WC) four-dimensional variational (4D-Var) data assimilation and dry-air mole fractions of CH4 (XCH4) from the Greenhouse gases Observing SATellite (GOSAT). The ability of the observations and the WC 4D-Var method to mitigate model errors in CH4 concentrations was first investigated in a set of observing system simulation experiments (OSSEs). We then assimilated the GOSAT XCH4 retrievals and found that they were capable of differentiating the vertical distribution of model errors and of removing a significant portion of biases in the modelled CH4 state. In the WC 4D-Var assimilation, corrections were added to the modeled CH4 state at each model time step to account for model errors and improve the model fit to the assimilated observations. Compared to the conventional strong constraint (SC) 4D-Var assimilation, the WC method was able to significantly improve the model fit to independent observations. Examination of the WC state corrections suggested that a significant source of the model errors was associated with discrepancies in the model CH4 in the stratosphere. The WC state corrections also suggested that the model vertical transport in the troposphere at mid- and high-latitudes is too weak. The problem was traced back to biases in the uplift of CH4 over the source regions in eastern China and North America. In the tropics, the WC assimilation pointed to the possibility of biased CH4 outflow from the African continent to the Atlantic in the mid-troposphere. The WC assimilation in this region would greatly benefit from glint observations over the ocean to provide additional constraints on the vertical structure of the model errors in the tropics. We also compared the WC assimilation at the 4° × 5° and 2° × 2.5° horizontal resolutions and found that the WC corrections to mitigate the model errors were significantly larger at 4° × 5° than at 2° × 2.5° resolution, indicating the presence of resolution-dependent model errors. Our results illustrate the potential utility of the WC 4D-Var approach for characterizing model errors. However, a major limitation of this approach is the need to better characterize the specified model error covariance in the assimilation scheme. [ABSTRACT FROM AUTHOR]

Interannual variations in temperature and precipitation impact the carbon balance of terrestrial ecosystems, leaving an imprint in atmospheric CO2. Quantifying the impact of climate anomalies on the net ecosystem exchange (NEE) of terrestrial ecosystems can provide a constraint to evaluate terrestrial biosphere models against, and may provide an emergent constraint on the response of terrestrial ecosystems to climate change. We investigate the spatial scales over which interannual variability in NEE can be constrained using atmospheric CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT). NEE anomalies are calculated by performing a series of inversion analyses using the GEOS-Chem model to assimilate GOSAT observations. Monthly NEE anomalies are compared to proxies, variables which are associated with anomalies in the terrestrial carbon cycle, and to upscaled NEE estimates from FLUXCOM. Strong agreement is found in the timing of anomalies in the GOSAT flux inversions with soil temperature and FLUXCOM. Strong correlations are obtained (P<0.05, R>RNINO3.4) in the tropics on continental and larger scales, and in the northern extratropics on sub-continental scales during the summer (R2≥0.49). These results, in addition to a series of observing system simulation experiments that were conducted, provide evidence that GOSAT flux inversions can isolate anomalies in NEE on continental and larger scales. However, in both the tropics and northern extratropics, the agreement between the inversions and the proxies/FLUXCOM is sensitive to the flux inversion configuration. Our results suggest that regional scales are likely the minimum scales that can be resolved in the tropics using GOSAT observations, but obtaining robust NEE anomaly estimates on these scales may be difficult. [ABSTRACT FROM AUTHOR]

The occurrence of frequent aerosol nucleation and growth events in the Arctic during summertime may impact the region’s climate through increasing the number of cloud condensation nuclei in the Arctic atmosphere. Measurements of aerosol size distributions and aerosol composition were taken during the summers of 2015 and 2016 at Eureka and Alert on Ellesmere Island in Nunavut, Canada. The corresponding results provide a better understanding of the frequency and spatial extent of these nucleation and growth events as well as of the composition and sources of aerosol mass during particle growth. These events are observed beginning in June with the melting of the sea ice rather than with polar sunrise, which strongly suggests emissions from marine sources are the primary cause of the events. Frequent particle nucleation followed by growth occurs throughout the summer. Correlated particle growths events at the two sites, separated by 480 km, indicate conditions existing over such large scales play a key role in determining the timing and the characteristics of the events. In addition, aerosol mass spectrometry measurements are used to analyze the size-resolved chemical composition of aerosols during two selected growth events. It is found that particles with diameters smaller than 100 nm are predominately organic with only a small sulphate contribution. The oxidation of the organic fraction also changes with particle size with larger particles containing a greater fraction of organic acids relative to other non-acid oxygenates (e.g. alcohols or aldehydes). It is also observed that the relative amount of m / z 44 in the measured mass spectra increases during the growth events suggesting increases in organic acid concentrations in the particle phase. The nucleation and growth events at Eureka are observed most often when the temperature inversion between the sea and the measurement site (at 610 m a.s.l.) is non-existent or weak allowing presumably fresh marine emissions to be mixed upward to the observatory altitude. While the nature of the gaseous precursors responsible for the growth events are poorly understood, oxidation of dimethyl sulphide alone to produce particle phase sulphate or methanesulphonic acid is not consistent with the measured aerosol composition, suggesting the importance of condensation of other gas phase organic compounds for particle growth. [ABSTRACT FROM AUTHOR]

Ground-based, satellite, and reanalysis datasets were used to identify two similar cyclone-induced surface ozone depletion events at Eureka, Canada (80.1°â€‰N, 86.4°â€‰W), in March 2007 and April 2011. These two events were coincident with observations of HDO depletion, indicating that condensation and sublimation occurred during the transport of the ozone-depleted airmasses. Ice clouds (vapour and crystals) and aerosols were detected by lidar and radar when the ozone- and HDO-depleted airmasses arrived over Eureka. For the 2007 event, an ice cloud layer was coincident with an aloft ozone depletion layer at 870 m altitude on 2-3 March, indicating this ice cloud layer contained bromine-enriched blowing snow particles. Over the following three days, a shallow surface ozone depletion event (ODE) was observed at Eureka after the precipitation of bromine-enriched particles onto the local snow pack. A chemistry climate model (UKCA) and a chemical transport model (pTOMCAT) were used to simulate the surface ozone depletion events. Incorporating the latest surface snow salinity data obtained for the Weddell Sea into the models resulted in improved agreement between the modelled and measured BrO concentrations above Eureka. MERRA-2 global reanalysis data and the FLEXPART particle dispersion model were used to study the link between the ozone and HDO depletion. In general, the modelled ozone and BrO showed good agreement with the ground-based observations, however the modelled BrO and ozone in the near surface layer are quite sensitive to the snow salinity. HDO depletion observed during these two blowing-snow ODEs was found to be weaker than pure Rayleigh fractionation. This work provides evidence of a blowing-snow sublimation process, which is a key step in producing bromine-enriched sea-salt aerosol. [ABSTRACT FROM AUTHOR]

Changes of atmospheric methane (CH4) since 2005 have been evaluated using Fourier Transform Infrared (FTIR) solar observations performed at ten ground-based sites, all members of the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns that amounts to 0.31 ± 0.03% year-1 (2-sigma level of uncertainty) for the 2005-2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem Chemical Transport Model tagged simulation that accounts for the contribution of each emission source and one sink in the total methane, simulated over the 2005-2012 time period and based on emissions inventories and transport. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane of 0.35 ± 0.03% year-1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04% year-1, averaged over ten stations). Analysis of the GEOS-Chem tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the inter-annual variability of methane. However, anthropogenic emissions such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Based on the GEOS-Chem tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained. [ABSTRACT FROM AUTHOR]

A new model for greenhouse gas transport has been developed based on Environment and Climate Change Canada's operational weather and environmental prediction models. When provided with realistic posterior fluxes for CO2, the CO2 simulations compare well to NOAA's CarbonTracker fields, and to near surface continuous measurements, columns from the Total Carbon Column Observing Network (TCCON), and NOAA aircraft profiles. This coupled meteorological and tracer transport model is used to study the atmospheric modulation of CO2 transport. The predictability of CO2 due to initial state sensitivity is shorter than that for the temperature field but is consistent with the predictability of the wind fields. However, when broken down into spatial scales, CO2 has predictability at the very largest scales due to long time scale memory in surface CO2 fluxes as well as in land and ocean surface forcing of meteorological fields. The predictability due to the land and ocean surface is most evident in boreal summer when biospheric uptake produces large spatial gradients in the CO2 field. Predictability errors provide an upper limit for errors arising solely from the use of uncertain meteorological analyses. When considering meteorological analysis errors, CO2 can be defined only on large scales. Thus, there is a spatial scale below which information cannot be obtained simply due to the fact that meteorological analyses are imperfect. Compared to the spatial scales resolvable in the context of imperfect atmospheric analyses, the differences between two sets of posterior fluxes are resolvable only for very large scales. Similarly, the impact of convective tracer transport exceeds that due to atmospheric analysis errors for only the largest spatial scales. [ABSTRACT FROM AUTHOR]

A new model for greenhouse gas transport has been developed based on Environment and Climate Change Canada's operational weather and environmental prediction models. When provided with realistic posterior fluxes for CO2, the CO2 simulations compare well to NOAA's CarbonTracker fields, and to near surface continuous measurements, columns from the Total Carbon Column Observing Network (TCCON), and NOAA aircraft profiles. This coupled meteorological and tracer transport model is used to study the atmospheric modulation of CO2 transport. The predictability of CO2 due to initial state sensitivity is shorter than that for the temperature field but is consistent with the predictability of the wind fields. However, when broken down into spatial scales, CO2 has predictability at the very largest scales due to long time scale memory in surface CO2 fluxes as well as in land and ocean surface forcing of meteorological fields. The predictability due to the land and ocean surface is most evident in boreal summer when biospheric uptake produces large spatial gradients in the CO2 field. Predictability errors provide an upper limit for errors arising solely from the use of uncertain meteorological analyses. When considering meteorological analysis errors, CO2 can be defined only on large scales. Thus, there is a spatial scale below which information cannot be obtained simply due to the fact that meteorological analyses are imperfect. Compared to the spatial scales resolvable in the context of imperfect atmospheric analyses, the differences between two sets of posterior fluxes are resolvable only for very large scales. Similarly, the impact of convective tracer transport exceeds that due to atmospheric analysis errors for only the largest spatial scales. [ABSTRACT FROM AUTHOR]