The entire GLOBALVIEW-CO2 web content is presented here. Click here to download the PDF version.

GLOBALVIEW-CO2 is a product of the Cooperative Atmospheric Data Integration Project. While the project is coordinated and maintained by the Carbon Cycle Greenhouse Gases Group of the National Oceanic and Atmospheric Administration, Earth System Research Laboratory (NOAA ESRL), it is a cooperative effort among the many organizations and institutions making high-quality atmospheric CO2 measurements.

What's New in 2011?

GLOBALVIEW-CO2 is an attempt to address issues of temporal discontinuity and data sparseness in atmospheric observations and is a tool intended for use in carbon cycle modeling. The impetus for the work done by the many cooperating organizations and institutions is to make high-precision atmospheric measurements of trace gas species that will facilitate a better understanding of the processes controlling their abundance. These and other measurements have been widely used to constrain atmospheric models that derive plausible source/sink scenarios. Serious obstacles to this approach are the paucity of sampling sites and the lack of temporal continuity among observations from different locations. Consequently, there is the potential for models to misinterpret these spatial and temporal gaps resulting in derived source/sink scenarios that are unduly influenced by the sampling distribution.

GLOBALVIEW-CO2 is derived from atmospheric measurements but contains no actual data. Observations used to derive the data product have been selected for baseline conditions. Baseline selection is site-specific. In most instances, selection is done by the PIs before submission to GLOBALVIEW and based on their knowledge of local conditions. Users are encouraged to review the literature for further details on baseline selection strategies. To facilitate use with carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. Be aware that information contained in the actual data may be lost in this process. Users are encouraged to review the actual data in the literature, in data archives (CDIAC, WDCGG), or by contacting the participating laboratories.

GLOBALVIEW-CO2 is derived using the data extension and data integration techniques described by Masarie and Tans, [1995]. These techniques were developed using CO2 measurements from the NOAA ESRL cooperative air sampling network. Carbon dioxide measurement records from other laboratories have been extended and integrated with the NOAA ESRL measurements into GLOBALVIEW-CO2 with careful attention to both methodology and standard scales.

We thank our colleagues at the following laboratories for their participation in and contribution to GLOBALVIEW-CO2. Each laboratory has been assigned a Lab ID Number that is used to associate GLOBALVIEW records with the contributing lab.

GLOBALVIEW-CO2, 2011

1. Release Date: 16 September 2011
2. Data additions
   Discrete surface measurements:

   • CIB Centro de Investigacion de la Baja Atmosfera, Spain (ESRL in collaboration with Centro de Investigacion de la Baja Atmosfera, Univ. of Valladolid (CIBA))
   • DRP Drake Passage (ESRL in collaboration with the National Science Foundation (NSF))
   • MEX Mex High Altitude Global Climate Observation Center, Mexico (ESRL in collaboration with Sistema Internacional de Monitoreo Ambiental (SIMA))
   • OXK Ochsenkopf, Germany (ESRL in collaboration with Max Planck Institute for Biogeochemistry (MPI-BGC))

   Continuous surface or short-tower measurements:

   • ESP045 Estevan Point, British Columbia, Canada (EC)
3. Site Classification Change
   Discrete data from Estevan Point are no longer included in constructing the marine boundary layer (MBL) reference matrix. Quasi-continuous measurements from the site show a small diurnal cycle. Discrete samples are not always collected at a time when air is predominantly marine in origin.

   All EC quasi-continuous measurement records are now designated as continuous surface sites (_06C0) instead of continuous tower sites (_06C3). The "tower" designation is reserved for records where GLOBALVIEW results from multiple levels on the tower are presented (e.g., hun, lef, wkt).

There are 9 types of files included in a GLOBALVIEW data product. To learn more about a GLOBALVIEW file type, click on one of the images below or read on.

In order to use GLOBALVIEW-CO2 as it was intended, users should read and understand the documentation provided here. It is also highly recommended that users consult the relevant published literature; a partial list is provided in References.

GLOBALVIEW-CO2 is derived from measurements but contains no actual data. To facilitate use with carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. Be aware that information contained in the actual data may be lost in this process. Users are encouraged to review the actual data in the literature, in data archives (CDIAC, WDCGG), or by contacting the participating laboratories.

Smoothed, interpolated, and extrapolated values in the extended records are determined with varying degrees of confidence. We strongly encourage users to consider the relative weights assigned to these values when using this product.

GLOBALVIEW-CO2 is subject to change as members of the Cooperative Atmospheric Data Integration Project reserve the right to adjust individual measurement records based on recalibrations of standard gases and instruments.

The GLOBALVIEW-CO2 data product continues to evolve. Extended records and statistical summaries may change as techniques are refined and new data are added.

GLOBALVIEW-CO2 is freely available. Anyone using GLOBALVIEW-CO2 is agreeing to acknowledge its authors. The list of cooper ating scientists and their organizations and institutions is large and would be cumbersome to include as a reference, thus GLOBALVIEW-CO2 and its contributors should be referenced as [GLOBALVIEW-CO2, 2011], and in a list of references as

which complies with the recommended reference styles of both the American Geophysical Union and the American Meteorological Society.

GLOBALVIEW is coordinated and maintained by NOAA ESRL Carbon Cycle. Questions may be directed to Ken Masarie (Project Manager).

Data Preparation

GLOBALVIEW uses discrete and quasi-continuous measurements from fixed surface and tower sites and moving ship and aircraft sites. Discrete samples are collected in situ at weekly to monthly intervals and returned to the collaborating measurement laboratory for analysis. Quasi-continuous samples are measured in situ using systems located at the sampling location.

Each measurement record used to derive GLOBALVIEW-CO2 has been carefully edited and selected by the organization or institution contributing the observations. Observations used to derive the data product have been selected for baseline conditions to exclude samples influenced by local source and sinks . Baseline selection is site-specific. In most instances, selection is done by the PIs before submission to GLOBALVIEW and based on their knowledge of local conditions. The measurement records are accumulated at NOAA ESRL along with documentation and references. Wherever possible, NOAA ESRL attempts to reproduce the selected data set based on descriptions in the literature. Users are encouraged to review the literature for further details on baseline selection strategies.

Quasi-continuous data used to derive GLOBALVIEW have been preprocessed to produce a single value per day. Often this averaging process is performed by the collaborating laboratories using well-established methods that have been published in the literature. In some instances, the averaging is done at ESRL and in cooperation with the contributing laboratories. Table 1 summarizes the different averaging strategies. Users are encouraged to review the literature and contact the measurement labs directly for details about and access to the actual observations.

Data Integration

Comparison Experiments

A primary challenge for the GLOBALVIEW project and for the atmospheric trace gas measurement community is to ensure that measurements made using independent techniques can be integrated into larger cooperative data sets without introducing significant biases. This is a difficult challenge (see Data Integration). Several strategies exist to make this assessment including ongoing comparisons of 1) measurements of air from the same high-pressure cylinders; 2) measurements from glass flasks filled from the same high-pressure cylinders; 3) measurements from low-pressure cylinders decanted from high-pressure cylinders; 4) measurements of air from the same ambient samples; and 5) measurements from the same location (co-located) using different methodologies. Ongoing direct comparison of co-located atmospheric measurements is one of the more effective strategies [See, for example, Masarie et al., 2001]. Where ongoing comparison experiments of atmospheric measurements do not exist, we must rely on other less direct methods. In all instances, selected measurements are compared to other measurement records that are nearby in latitude as an additional assessment of potential calibration or sampling problems. The first step in assessing measurement comparability between independent records is to ensure data are reported on a consistent standard scale.

Standard Scale

The majority of laboratories contributing to the GLOBALVIEW-CO2 data product are members of the World Meteorological Organization (WMO) Global Atmosphere Watch (GAW) network. Data from the GAW network are reported relative to the WMO CO2 Mole Fraction Scale, which is maintained and propagated by the Central CO2 Laboratory (CCL). GAW laboratories are required to maintain direct traceability of their internal calibration scale to the CCL. A few laboratories contributing to the data product are not part of the WMO GAW program and thus provide data referenced to some other scale. This section describes ongoing efforts to assess the comparability of calibration scales and atmospheric observations.

1. The WMO CO2 Mole Fraction Scale

   The WMO Scale is based on regular determinations of the mole fraction of CO2 in dry air from a set of 15 primary standards using a high precision manometric system with NIST-traceable measurements to temperature, pressure and volume [Tans et al., 2003; Zhao et al., 1997]. Uncertainty of the WMO Scale is estimated to be ~0.06 µmol mol-1 (one sigma). Reproducibility of the determinations is about 0.03 µmol mol-1 (one sigma), based on repeated manometric analyses [Zhao and Tans, 2006]. The scale as defined by the primary standards (projected 30 year average lifetime) is subsequently propagated to a set of 9 secondary (transfer) standards (3-4 year average lifetime) using relative nondispersive infrared (NDIR) measurement techniques. NDIR measurement reproducibilityp is ~0.01 µmol mol-1. Propagation of the WMO Scale from the Primary cylinders to working standards, via intermediate Secondary standards maintained by the CCL, has a reproducibility of ~0.02 µmol mol-1 (one sigma). Cylinders are calibrated for other laboratories against the transfer standards using the NDIR methodology. The use of a calibration hierarchy enables the CCL to occasionally re-assign, when justification for such a change is strong, the value of a primary or secondary standard and propagate the change, in a straightforward manner, to all dependent calibrations.

   Recent History

   In 1995, the WMO designated NOAA ESRL as the Central CO2 Laboratory (CCL) responsible for the maintenance of the absolute WMO Mole Fraction Scale for carbon dioxide. Before that time, the scale had been maintained by the Scripps Institution of Oceanography (SIO).

   In 1990, ESRL prepared 15 CO2-in-air reference gas mixtures in large aluminum high pressure cylinders for use as primary standards, ranging in CO2 mole fraction from approximately 250 to 520 µmol mol-1. These cylinders were calibrated four times at SIO by the NDIR method from mid-1991 to 1999. In 1996, ESRL began making absolute manometric determinations of its 15 "primary" standards. Between 1996 and 2001, values assigned to the 15 primaries were based on both SIO NDIR measurements and ESRL manometric determinations. Starting in 2002, the values assigned to the primaries have been based on manometric determinations by ESRL alone.

   Revisions to calibrations provided before 2005 by the CCL have been made. This is mainly due to revisions of the calibrations performed by Scripps between 1991 and 1999. Until 1996 the assigned values of the primary standards were based entirely on the infrared calibrations by Scripps. The average of all assigned values to the primaries increased by 0.16 µmol mol-1 from 1993 to 2002. Since then the average of all assigned values of the primaries has decreased by 0.01 µmol mol-1.

   The CO2 Mole Fraction Scale is defined by a polynomial curve fit to the Primary Standards. This is done to smooth out the uncertainty of assigned values to individual Primary Standards caused by the imprecision of the absolute calibrations, which is 0.03 ppm (see above). In September 2005, the WMO scale was revised, and a quadratic curve fit was used. After another set of calibrations of the Primaries in 2006-2007, the individual Primaries were revised by only minor amounts, up to 0.01 ppm. However, in defining the revised scale for 2007, we chose to use a cubic polynomial for the curve fit, which led to mole fraction-dependent differences between WMO-X2007 and WMO-X2005 between -0.03 and 0.03 ppm in the range of ambient air. All laboratories who have had cylinders calibrated by the CO2 CCL should have received revised calibration assignments based on the new scale. If you would like to receive revised values based on the new scale please contact Duane Kitzis (NOAA/ESRL).

2. Traceability to the WMO Scale

   Not all data contributed to the Cooperative Atmospheric Data Integration Project for CO2 are directly traceable to the WMO Mole Fraction Scale. A few laboratories have never had their standard gases calibrated by the CCL and report CO2 measurements relative to some other scale (see Table 2). Measurements from these laboratories are not directly traceable to the WMO Mole Fraction Scale. Several other laboratories have, at one time, had their standards calibrated by the CCL but have not maintained a routine recalibration schedule. Because the mole fraction of CO2 contained in high-pressure cylinders can potentially change with time due to CO2 adsorption or production within the cylinder or regulator, or through other effects, a laboratory's internal scale may potentially change with time relative to the WMO scale, which itself is anchored through absolute manometric determinations. Without routine recalibration by the CCL to reestablish direct traceability to the WMO-X2007 scale, laboratories contribute CO2 data that are no longer directly traceable to the WMO scale. Please note that recent calibration with the CCL does not necessarily imply measurements are on the most current WMO Mole Fraction Scale.

   Table 2. Traceability to the WMO scale based on calibration by the CCL.

   LABORATORY [lab #]	RECENT CAL. DATES1	# of CYLINDERS3	REPORTED SCALE
   ESRL [01]	2010 05 / 2009 12	20 (recal) / 20 (recal)	WMO
   CSIRO [02]	2003 11 / 2002 12	10 (recal) / 11 (cal)	WMO4
   NCAR [03]	2011 04 / 2006 04	6 (recal) / 6 (cal)	WMO4
   SIO [04]	--	--	Scripps 08A
   EC [06]	2009 06 / 2008 09	2 (cal) / 8 (recal)	WMO
   LSCE [11]	2008 01 / 2007 07	1 (cal) / 7 (recal)	WMO4
   NIWA [15]	2010 04 / 2008 10	2 (cal) / 2 (cal)	WMO
   IMS [17]	1998 10	5 (cal)	WMO4
   JMA [19]	2011 01/ 2008 10	14 (cal) / 14 (recal)	WMO
   NIES [20]	2006 09 / 2002 12	5 (recal) / 2 (cal)	NIES09
   UBA/UHEI-IUP [23]	2007 12 / 2006 04	6 (cal) / 6 (recal)	WMO4
   SNU [24]	2004 09 / 2003 06	4 (cal) / 5 (cal)	2008A SIO
   AEMET [27]	2008 09 / 2006 03	2 (cal) / 8 (cal)	WMO
   ENEA [28]	2008 12 / 2008 02	4 (recal) / 4 (cal)	WMO
   PNRA/DNA [29]	2001 07 / 2000 12	3 (cal) / 3 (cal)	WMO4
   FMI [30]	2007 05 / 2007 02	2 (cal) / 6 (cal)	WMO
   CAMS [33]	2009 04 / 2008 10	6 (cal) / 6 (cal)	WMO
   HMS [35]	2010 10 / 2007 11	3 (cal) / 6 (cal)	WMO
   SAWS [36]	2009 04 / 2007 05	2 (cal) / 2 (recal)	WMO
   MPI-BGC [45]	2009 04 / 2009 02	1 (cal) / 2 (cal)	WMO

   1Only the two most recent calibration events are shown.
   2Calibration made at ESRL relative to the ESRL secondary standards.
   3Initial (cal)ibration and subsequent (recal)ibration by the CCL (NOAA) are specified.
   4Traceability to the WMO Mole Fraction Scale has lapsed. A recalibration schedule of every 3 years is thought to be the minimum frequency for maintaining traceability to the WMO scale.
   5Insufficient number of cylinders calibrated to properly link laboratory internal scale to WMO Mole Fraction Scale. The minimum number of standards required to establish traceability to the WMO Mole Fraction Scale is three.
   6Internal scale is indirectly linked to WMO Mole Fraction Scale.

3. Comparisons of Standard Scales

   In an attempt to assess differences in standard scales among organizations making CO2 measurements, laboratories contributing to GLOBALVIEW-CO2 have participated in recent interlaboratory intercomparison or round robin (RR) experiments endorsed by the WMO and IAEA. Based on preliminary results from the 2002-2006 intercomparison of standard gases, the majority of participating laboratories agreed to within 0.1 µmol mol-1 [see Table 3]. The preliminary results were kindly provided by Dr. Lingxi Zhou (CAMS) [Zhou et al., in preparation]. Final results were not available at the time of this update. Results from previous RR experiments are also available [Peterson et al., 1999].

   Table 3. 2002-2006 Round Robin Results [per comm. Lingxi Zhou, 2008-08-20]: Differences from NOAA ESRL (Lab minus ESRL).

   LABORATORY [lab #]	MEASUREMENT DATE	DIFFERENCE from NOAA (µmol mol-1)
   Nominal Tank Concentration		355	365	385
   CSIRO [02]	2005 10	-0.01	-0.03	-0.08
   NCAR [03]	2006 06	0.07	-0.04	-0.04
   SIO [04]	2005 06	0.10	0.02	0.02
   EC [06]	2005 05	0.06	-0.05	-0.06
   MRI [10]	2003 07	-0.16	-0.16	-0.08
   LSCE [11]	2002 12	0.10	0.03	0.05
   NIWA [15]	2005 05	-0.08	-0.08	-0.09
   IMS [17]	2002 10	0.08	0.02	-0.03
   JMA [19]	2004 01	0.13	0.00	-0.02
   NIES [20]	2003 04	-0.10	-0.15	-0.14
   UBA/UHEI-IUP [23]	2002 10	-0.01	-0.06	-0.06
   SNU1 [24]	--	--	--	--
   AEMET1 [27]	--	--	--	--
   ENEA [28]	2002 11	0.05	-0.15	-0.26
   PNRA/DNA1 [28]	--	--	--	--
   FMI [30]	2003 01	-0.02	-0.04	-0.14
   CAMS [33]	2004 08	-0.03	-0.20	0.02
   HMS [35]	2003 02	0.06	-0.21	-0.06
   SAWS [36]	2005 12	-0.02	-0.09	-0.18
   MPI-BGC [45]	2003 12	0.04	0.02	-0.02

   1Did not participate in the 2002-2006 RR experiment.

   Based on available comparison information, we estimate that data used to derive GLOBALVIEW-CO2 are comparable to within 0.2 µmol mol-1. At present, the Cooperative Atmospheric Data Integration Project for Carbon Dioxide has made no standard scale adjustments to any of the measurement records integrated into GLOBALVIEW-CO2. Records that appear to be affected by a serious scale discrepancy have been omitted at this time.

Table 1 below provides general information on sampling locations for measurement records used to derive GLOBALVIEW-CO2. A summary of this list is available as a text file (gv_table.co2).

The descriptive information includes

• Identification code and location. Note that in some instances the identification code includes additional information (see File Names).
• Organization collecting the air sample or making the measurements.
• Sampling strategy and platform.
• Contributing laboratory and average sample frequency of available data. The average is based on the most recent 3 years of available data.
• Position of the sampling site where latitude is in degrees (000 is at the equator, north of the equator is positive (+), and south of the equator negative (-)), longitude is in degrees (east of Meridian of Greenwich is positive (+), and west of Meridian of Greenwich is negative (-)), and altitude is in meters above sea level (masl).
• Time period of available measurements.

GLOBALVIEW-CO2, 2011

1. Release Date: 16 September 2011
2. Data additions
   Discrete surface measurements:

   • CIB Centro de Investigacion de la Baja Atmosfera, Spain (ESRL in collaboration with Centro de Investigacion de la Baja Atmosfera, Univ. of Valladolid (CIBA))
   • DRP Drake Passage (ESRL in collaboration with the National Science Foundation (NSF))
   • MEX Mex High Altitude Global Climate Observation Center, Mexico (ESRL in collaboration with Sistema Internacional de Monitoreo Ambiental (SIMA))
   • OXK Ochsenkopf, Germany (ESRL in collaboration with Max Planck Institute for Biogeochemistry (MPI-BGC))

   Continuous surface or short-tower measurements:

   • ESP045 Estevan Point, British Columbia, Canada (EC)
3. Site Classification Change
   Discrete data from Estevan Point are no longer included in constructing the marine boundary layer (MBL) reference matrix. Quasi-continuous measurements from the site show a small diurnal cycle. Discrete samples are not always collected at a time when air is predominantly marine in origin.

   All EC quasi-continuous measurement records are now designated as continuous surface sites (_06C0) instead of continuous tower sites (_06C3). The "tower" designation is reserved for records where GLOBALVIEW results from multiple levels on the tower are presented (e.g., hun, lef, wkt).

GLOBALVIEW-CO2, 2010

1. Release Date: 26 November 2010
2. Web Site
   In response to user-feedback, we have re-organized the GLOBALVIEW web site to improve readability and access. We have added a Documentation Section, which presents the GLOBALVIEW-CO2 web content in a single web page. For convenience, we also provide the documentation as a PDF file.
3. Data additions
   Discrete surface measurements:

   • ABP Arembepe, Bahia, Brazil (Instituto de Pesquisas Energécas e Nucleares, Il Centro de Quíca e Meio Ambiente, Divisao de Quimica Ambiental (IPEN-CQMA))
   • ABP Arembepe, Bahia, Brazil (ESRL in collaboration with Instituto de Pesquisas Energécas e Nucleares, Il Centro de Quíca e Meio Ambiente, Divisao de Quimica Ambiental (IPEN-CQMA))
   Discrete measurements from aircraft:

   • CMA Cape May, New Jersey, United States (ESRL)
   • ETL East Trout Lake, Saskatchewan, Canada (ESRL)
   • SCA Charleston, South Carolina, United States (ESRL)
   • SGP Southern Great Plains, Oklahoma, United States (ESRL)
   Continuous surface or short-tower measurements:

   • STR Sutro, San Francisco, California, United States (ESRL)
     Please Note: Data have been filtered using a statistical method to remove local influences. This methodology is preliminary pending further analysis.
   Continuous measurements from a tall tower:

   • SCT Augusta Tower, Beech Island, South Carolina, United States (ESRL)
   • WBI030 West Branch, Iowa, United States (ESRL in collaboration with University of Iowa). Data from the 30 magl intake height.
4. Tower Measurement Programs (Important Changes)
   • In May 2009, sampling at the 11, 76 and 244 magl intake heights at the Park Falls, Wisconsin (LEF) tower was discontinued. Measurements at the 30, 122 and 396 m heights continue. The extended records for each level span the period of available measurements. We present two sets of statistical summaries. One set spans the period 2004-2008 when all 6 levels were in use (LEF<ht>-6lvls_01C3_<qualifier>.co2); a second set spans the period 2004-2009 when the 30, 122 and 396 m levels were available (LEF<ht>_01C3_<qualifier>.co2).
   • The Moody, Texas (WKT) quasi-continuous tower record used in this release includes measurements for the period 2007 through 2009 for the 30, 122 and 457 magl levels. Data prior to 2007 require further evaluation due to known problems.
   • In June 2009, the sampling intake height at the Lac Labiche, Alberta, Canada site (LLB) operated by EC was changed from 10 to 45 magl.
   • In March 2009, the sampling intake height at the Egbert, Ontario, Canada site (EGB) operated by EC was changed from 3 to 25 magl.
5. Presentation of Tower Measurements
   • To improve the usefulness of the diurnal statistical summaries, results are now presented in site Local Time (LST). See Content Description for details.
   • We now provide a statistical summary of differences between nighttime and daytime averages at each intake height. For each day and at each level, we compute differences between a 4-hour nighttime average [0-4 LST] and an afternoon-hours daytime average [see Data Comparability, Table 1 for details]. We aggregate the daily differences by month and present a multi-year monthly summary. See Content Description for details.
   • For tower sites with multiple intake heights, we provide a statistical summary of the daytime and nighttime vertical gradients. The daytime vertical gradient is computed as follows. For each day, we compute an afternoon-hours daytime average [see Data Comparability, Table 1 for details] for each level. We difference the day average at each level with the day average at the highest level. If a day value is missing for any intake height, the gradient is not determined for that day. We aggregate the daily daytime vertical gradients by month and present a multi-year monthly summary. The nighttime vertical gradient is computed in the same way but using hours 0-4 LST. See Content Description for details.
6. Header Content
   The header content within each product file (except for the reference MBL matrix) has been changed. We have added "Time Period", which describes the date range represented within the file. This addition increases the number of lines in the header to 19. All header lines now begin with the '#' character.
7. Site Code Change
   The 3-letter site identification code for Fraserdale, Ontario, Canada (FRD) operated by EC was changed to FSD to be consistent with the WMO GAWSIS.
   The 3-letter site identification code for Sable Island, Nova Scotia, Canada (SBL) operated by EC was changed to WSA to be consistent with the WMO GAWSIS.

GLOBALVIEW-CO2, 2009b

1. Revision Date: 29 October 2009
   This revision corrects errors in the computation of daily averages from the 6 quasi-continuous surface and tower records added in the 15 October 2009 release (see notes below).

   • The 3-hour averaging window used to compute daily values from the quasi-continuous data at the BAO, WBI and WGC tall towers was not consistent with the window used for other ESRL tall tower records. This revision uses daily values computed using the same 3-hour window (13-15 LST) for all ESRL tower sites.
   • The 3-hour averaging window used to compute daily values from the quasi-continuous data at the ETL105 and LLB010 towers was not consistent with the window used for other EC tower records. This revision uses daily values computed using the same 3-hour window (15-17 LST) for all EC tower sites.
   • Daily values for EGB (Egbert, Ontario, Canada) were computed using all valid hourly values. This revision uses daily values computed using valid afternoon hours (15-17 LST) only.

   These corrections only impact GLOBALVIEW files for the recently added quasi-continuous surface and tower sites (EGB, ETL105, LLB010, BAO, WBI and WGC) described in the 15 October 2009 release notes below. Table 1 (Sampling Locations) summarizes how daily values are computed.

1. Release Date: 15 October 2009
2. Data additions
   Discrete surface measurements:

   • BHD Baring Head, New Zealand (ESRL in collaboration with National Institute of Water and Atmospheric Research (NIWA))
   • LMP Lampedusa, Italy (ESRL in collaboration with National Agency for New Technology, Energy, and Environment (ENEA))
   Continuous surface or short-tower measurements:

   • EGB Egbert, Ontario, Canada (EC)
   • ETL105 East Trout Lake, Saskatchewan, Canada (EC)
   • LLB010 Lac La Biche, Alberta, Canada (EC)
   Continuous measurements from a tall tower:

   • BAO Boulder Atmospheric Observatory, Colorado, United States (ESRL)
   • WBI West Branch, Iowa, United States (ESRL in collaboration with University of Iowa)
   • WGC Walnut Grove, California, United States (ESRL in collaboration with DOE Environmental Energy Technologies Division at Lawrence Berkeley National Laboratory)
3. Sampling Strategy
   We have introduced the sampling strategy "P" to make a distinction between single flasks (D) and flask packages. See File Names for details.

GLOBALVIEW-CO2, 2008

1. Release Date: 27 August 2008
2. Data additions
   Discrete surface measurements:

   • HPB Hohenpeissenberg, Germany (ESRL)
   • SGP374 Southern Great Plains, Oklahoma, United States (ESRL)
   Continuous surface measurements:

   • HDPDTA Hidden Peak, Colorado, United States (NCAR) (Daytime Averages, 1200-1800 LST)
   • HDPNTA Hidden Peak, Colorado, United States (NCAR) (Nighttime Averages, 0000-0400 LST)
   • NWRDTA Niwot Ridge, Colorado, United States (NCAR) (Daytime Averages, 1200-1800 LST)
   • NWRNTA Niwot Ridge, Colorado, United States (NCAR) (Nighttime Averages, 0000-0400 LST)
   • SPLDTA Storm Peak, Colorado, United States (NCAR) (Daytime Averages using 1200-1800 LST)
   • SPLNTA Storm Peak, Colorado, United States (NCAR) (Nighttime Averages using 0000-0400 LST)
3. Site Code Change
   In January 2007, the ESRL aircraft site at Rowley, Iowa, United States (RIA) was moved to West Branch, Iowa (WBI). Data from RIA are now merged with data from WBI.
4. Lab Change
   • Collaborating laboratory 06, formerly called "Meteorological Service of Canada" (MSC), is now called "Environment Canada" (EC).
   • Collaborating laboratory 27, formerly called "Instituto Nacional de Meteorologia" (INM), is now called "Meteorological State Agency of Spain" (AEMET).

GLOBALVIEW-CO2, 2007

1. Release Date: 20 August 2007
2. Data additions
   Discrete surface measurements:

   • CYA Casey, Antarctica, Australia (CSIRO)
   • PTA Point Arena, California, United States (ESRL)
   Discrete measurements from aircraft:

   • BNE Beaver Crossing, Nebraska, United States (ESRL)
   • DND Dahlen, North Dakota, United States (ESRL)
   • HIL Homer, Illinois, United States (ESRL)
   • LEF Park Falls, Wisconsin, United States (ESRL)
   • RIA Rowley, Iowa, United States (ESRL)
   • THD Trinidad Head, California, United States (ESRL)
   Continuous measurements from a tall tower:

   • AMT Argyle, Maine, United States (ESRL)
3. Sampling at Izana Observatory (IZO)
   Please note that daily averages from Izana Observatory contributed by the Observatorio Atmosferico de Izana, Instituto Nacional de Meteorologia (INM), Spain are computed using only nighttime hours, i.e., 20-23 (previous day) and 00-07 (reported day) to assure free troposphere background conditions at this high altitude mountain site. Prior to 2002, NOAA discrete samples were typically collected between 20 and 23 hours. Since June 2002, the collection time of NOAA samples has changed to afternoon hours (15-16). NOAA samples collected in the afternoon are not directly comparable to the INM daily averages computed using only nighttime hours.
4. Site Code Change
   The Old Black Spruce, Saskatchewan, Canada site (OBS) operated by MSC was renamed Candle Lake, Saskatchewan, Canada (CDL).
5. Aircraft Sampling in the Western Pacific (WPO)
   The long-term aircraft sampling program over the Western Pacific is now managed by the Center for Global Environmental Research National Institute for Environmental Studies (NIES) in collaboration with the Meteorological Research Institute (MRI), Japan. Please note that the standard gas scale used to report 1993-2005 data is different from the scale used to report the 2006 data due to the change in the central analytical laboratory from MRI to NIES. The difference of the CO2 standard gas scale is estimated to be about -0.14 ppm (MRI minus NIES) around 380 ppm CO2 level and +0.10 ppm around 340 ppm. A consistent data set will be made available after a more careful evaluation of the standard gas scale between the two laboratories.
6. Data deletions from GLOBALVIEW-CO2
   The ESRL discrete measurements from Park Falls, Wisconsin (LEF) and Grifton, North Carolina (ITN) are no longer included in the GLOBALVIEW product. These sites are instead represented by the ESRL tall tower quasi-continuous measurements, which provide a more representative record of observed high-frequency variability and daily patterns.

GLOBALVIEW-CO2, 2006

1. Release Date: 31 August 2006
2. Data additions
   Discrete surface measurements:

   • BKT Bukit Kototagang, Indonesia (ESRL)
   • MKN Mt. Kenya, Kenya (ESRL)
   • PAL Pallas, Finland (ESRL)

   Discrete measurements from aircraft:

   • TGC Sinton, Texas, United States (ESRL)
   • NHA Worcester, Massachusetts, United States (ESRL)
3. Lab Name Change
   As of October 1, 2005, the Climate Monitoring and Diagnostics Laboratory (CMDL) has merged into the Earth System Research Laboratory (ESRL) as part of its Global Monitoring Division (GMD).

GLOBALVIEW-CO2, 2005

1. Release Date: 15 August 2006
2. Data additions
   Discrete measurements from aircraft:

   • ESP Estevan Point, British Columbia, Canada (ESRL)
   • HFM Harvard Forest, Massachusetts, United States (ESRL)
   • ZOT Zotino, Siberia, Russia (MPI-BGC)

   Continuous surface measurements:

   • SBL Sable Island, Canada (MSC)

   Continuous measurements from a short tower:

   • OBS023 Saskatchewan, Canada (MSC)
3. Lab Identification Number Change
   The Lab ID number for NOAA ESRL has been changed from 00 to 01.
4. Site Classification Change
   The Fraserdale, Ontario, Canada (FRD) site has been re-classified within GLOBALVIEW as a tower site. It is now referred to as FRD040 indicating the sample intake height is 40m above the surface.
5. Modifications to the Preparation and Use of Tower Data
   Preparation of semi-continuous measurements from sites designated as tower platforms has been modified in an effort to standardize the treatment of data from towers sampling at one or many levels.
   
   Tower data are now averaged with daily resolution using afternoon hours only. In earlier releases of this data product, daily averages were computed using all hours (e.g., 24-hour average).
   
   The residual distribution used to prepare the statistical summary of average diurnal cycles is now determined at each level by subtracting the afternoon-hour average mixing ratio for each day from every observation for that day. In earlier releases of this product, the residual distribution was determined at each level by subtracting the 24-hour average mixing ratio for each day from every observation for that day; for tall tower measurements, the 24-hour average was determined from measurements at the highest level.

GLOBALVIEW-CO2, 2004

1. Release Date: 15 August 2004
2. Data additions
   Discrete surface measurements:

   • PDM Pic Du Midi, France (LSCE)

GLOBALVIEW-CO2, 2003

1. Release Date: 15 August 2003
2. Data additions
   Discrete surface measurements:

   • BGU Begur, Spain (LSCE)
   • SUM Summit, Greenland (ESRL)

   Continuous surface measurements:

   • FRDRBC Fraserdale, Ontario, Canada (Restricted Baseline Condition, MSC)
   • PALCBC Pallas, Finland (Continental Baseline Condition, FMI)
   • PALMBC Pallas, Finland (Marine Baseline Condition, FMI)

   Continuous measurements from a tall tower:

   • WKT Moody, Texas, United States (ESRL)

GLOBALVIEW-CO2, 2002

1. Release Date: 15 August 2002
2. Data additions
   Discrete surface measurements:

   • BGU Begur, Spain (LSCE)
   • SUM Summit, Greenland (ESRL)
3. Change to the release policy
   Participants of the Cooperative Atmospheric Data Integration Project-CO2 agreed to change the current release policy of the GLOBALVIEW-CO2 data product. A single ?complete? version of the data product will now be freely available to everyone [Toru et al., In Preparation].
4. Site Code Change
   The Kosan, Republic of Korea (KSN) site was renamed Gosan, Republic of Korea (GSN).
5. Summary of Sample Collection Times
   This update includes a summary of sample collection times for discrete measurement records (See SUMMARY - SAMPLE COLLECTION TIMES for details).
6. Data additions
   Discrete surface measurements:

   • ALT Alert, Nunavut, Canada (SIO)
   • CBA Cold Bay, Alaska, United States (SIO)
   • CGO Cape Grim, Tasmania, Australia (SIO)
   • KUM Cape Kumukahi, Hawaii, United States (SIO)
   • LJO La Jolla, California, United States (SIO)
   • PSA Palmer Station, Antarctica, United States (SIO)
   • SBL Sable Island, Nova Scotia, Canada (MSC)
   • SMO American Samoa (SIO)
   • SPO South Pole, Antarctica, United States (SIO)
   • TRM Tromelin Island, France (LSCE)

   Discrete measurements from aircraft:

   • WPO Western Pacific Ocean (MRI)
   • RTA Rarotonga, Rarotonga (ESRL)

GLOBALVIEW-CO2, 2001

1. Release Date: 15 August 2001
2. Data additions
   Continuous surface measurements:

   • COI Cape Ochi-ishi, Japan (NIES)
   • HAT Hateruma Island, Japan (NIES)
   • CPT Cape Point, South Africa (SAWS)

   Discrete surface measurements:

   • KZD Sary Taukum, Kazakstan (ESRL)
   • KZM Plateau Assy, Kazakstan (ESRL)
   • TDF Tierra Del Fuego, Argentina (ESRL)

   Discrete measurements from aircraft:

   • HAA Molokai Island, Hawaii, United States (ESRL)
   • PFA Poker Flat, Alaska, United States (ESRL)

GLOBALVIEW-CO2, 2000

1. Release Date: 15 August 2000
2. Modifications to the Data Extension procedure

   The data extension approach used to prepare the GLOBALVIEW product extends measurement time series by filling periods of missing data for a specific site with values based on knowledge gained from measurements at the site itself and from measurements from marine boundary layer (MBL) sites at comparable latitude. This "latitude reference" method has been improved upon over that described in Masarie and Tans, [1995] (hereafter MT95).

   In GLOBALVIEW-CO2, 1999 we improved the technique used to construct reference MBL time series to reduce their sensitivity to changes in the distribution of sites and to minimize discontinuities in these reference curves resulting from periods of sporadic or interrupted sampling with existing MBL records. In GLOBALVIEW-CO2, 2000, we have made a minor change to the construction of the difference climatology to minimize discontinuities between smooth values and interpolated and extrapolated values.

   Summary of the difference climatology described by MT95

   Data were prepared by fitting a function, f(t) [Equation 1 in MT95 consisting of harmonics and a polynomial] to each measurement record. The residuals from this fit are smoothed to capture interannual variations in the seasonal cycle. These variations are added to f(t) to produce a smooth curve, SSTA(t) [Equation 2, MT95], which is our best fit representation of the data The reference MBL time series, MBLSTA(t), is constructed for the latitude of each sampling location using the methods described by MT95 and modified according to A.1999.2 (see below). The difference distribution, ΔSTA,REF(t)=SSTA(t)-MBLSTA(t), highlights features that distinguish the individual record from the reference. A difference climatology was then described by fitting a function, δSTA,REF(t) [Equation 9, MT95] to ΔSTA,REF(t). This difference climatology describes the average difference between the smooth curve, SSTA(t), and the reference MBLSTA(t). To account for interannual variability in the difference distribution, ΔSTA,REF(t), we digitally filter the residuals, ΔSTA,REF(t)-δSTA,REF(t) using a low-pass filter with FWHM of 40 days. The smoothed residuals are then combined with the difference climatology according to Equation 10, MT95 to produce a smoothed difference climatology, SSTA,REF(t).
   
   Data extension relies on the assumption that the difference climatology described by δSTA,REF(t) is valid for periods when there are no actual measurements. Limitations of the assumption are discussed in Sections 4 and 5 of MT95. Finally, the extended record is constructed using SSTA(t) where measurements exist and by combining MBLSTA(t) and the difference climatology where measurements do not exist. Specifically, interpolated values are constructed by combining the MBL reference, MBLSTA(t), with the smoothed difference climatology, SSTA,REF(t). Extrapolated values are constructed by combining the MBL reference, MBLSTA(t), with the difference climatology, δSTA,REF(t).

   Modifications to the use of the difference climatology

   The difference climatology, δSTA,REF(t), is computed from the difference distribution, ΔSTA,REF(t), as described by MT95 and summarized above. The method described by MT95 to construct extrapolated values, however, had a tendency to introduce discontinuities at the transition between smoothed values, S(t), and extrapolated values (Figure 1b). These discontinuities arise when extrapolated values based on average behavior join values derived from observations, which do not reflect average behavior. The largest discontinuities occur when the seasonal pattern of actual data at a transition deviates significantly from the long-term average seasonal cycle (Figure 1a). To minimize discontinuities at the boundary between extrapolated values and smooth values, we smooth the transitions between the difference climatology, δSTA,REF(t), and the difference distribution, ΔSTA,REF(t). This is accomplished by defining a relaxation period (RELAX=8 weeks) whereby we force the difference climatology to "relax" linearly from its value RELAX weeks away to the first value from the difference distribution following a gap or to the last value from a difference distribution before a gap in the actual data begins.
   
   Extrapolated values are required to "fill" external gaps in the observations that occur when a data record begins or ends within the data extension synchronization period. For example, since the ESRL [lab# 01] flask sampling effort on container ships in the Pacific Ocean (POC) began in 1987 and the synchronization period for GLOBALVIEW-CO2, 2000 is 1979 through 1999, there exists an external gap at the beginning of the POC extended record. The transition between δPOCN30,REF(ti) and ΔPOCN30,REF(ti) where ti is the weekly time step corresponding to the first actual observation in the POCN30 record is smoothed using the following strategy. Values from δPOCN30,REF(t) are used (as in MT95) for time steps before ti-RELAX. Between the time steps ti-RELAX and ti, we use values from linear interpolation between δPOCN30,REF(ti-RELAX) and ΔPOCN30,REF(ti). Figure 1c illustrates this technique.
   
   The method to construct interpolated values (described by MT95) did not introduce discontinuities at transitions. By using the smoothed difference climatology, SSTA,REF(t), continuity was imposed at the transition between SSTA,REF(t) and ΔSTA,REF(t) by the curve fitting methods as described by Thoning et al. [1989]. A more defensible approach for the extension of data records is to use only the difference climatology, δSTA,REF(t), which describes the average difference between all actual observations and the MBL reference. Thus, we now apply the smoothing strategy described above to the construction of interpolated values.

   
   

   Figure 1. (a) Portion of the POCN30 difference climatology (squares) derived using the method described by MT95. (b) POCN30 extended record derived from (a). (c) Portion of POCN30 difference climatology derived using the modified method described in the text. (d) POCN30 extended record derived from (b) showing minimal discontinuity at the transition between extrapolated values (squares) and smoothed values (circles).

   
   Interpolated values are required to "fill" internal gaps in a data record that occur when an interruption in the observations exceeds 8 weeks (as described in MT95). There are two cases to consider, which again, can be best illustrated using the ESRL POCN30 record. First, there are internal gaps in the POCN30 record that exceed 8 weeks but are less than 2 * RELAX weeks (e.g., 1987). In these cases, we linear interpolate between ΔPOCN30,REF(ti) and ΔPOCN30,REF(tii) where ti corresponds to the weekly time step before the gap in the record begins and tii is the weekly time step when the observations restart. Second, there are internal gaps exceeding 2 * RELAX weeks in length (e.g., 1988). In these cases, we linear interpolate between ΔPOCN30,REF(ti) and δPOCN30,REF(ti+RELAX) and δPOCN30,REF(tii-RELAX) and ΔPOCN30,REF(tii). Between δPOCN30,REF(ti+RELAX) and δPOCN30,REF(tii-RELAX), we use the values δPOCN30,REF(ti+RELAX : tii-RELAX). Figure 1c illustrates each of these cases.
   
   Discontinuities in extended records caused by jumps at transitions between the difference climatology and the difference distribution are artifacts of the data extension method and do not reflect instantaneous sources and sinks of carbon. It is reasonable then to minimize these discontinuities since models "inverting" GLOBALVIEW-CO2 will be required to interpret these jumps. To smooth these discontinuities, we assume that the transition to the actual difference distribution will be gradual and not instantaneous. Because we cannot justify using one model over another, we have chosen linear interpolation.
   
   By smoothing the transition between the difference climatology and the difference distribution at external and internal gaps, we have minimized discontinuities caused by the non-average behavior of actual observations (Figure 1d). This improvement is apparent in the extended records included in this data product. These modifications, however, still cannot overcome certain discontinuities in the extended records caused by limitations in the observational network itself (see Release Notes for GLOBALVIEW-CO2, 1999).

GLOBALVIEW-CO2, 1999

1. Release Date: 15 August 1999
2. Modifications to the Data Extension procedure The data extension approach used to prepare the GLOBALVIEW product extends measurement time series by filling periods of missing data for a specific site with values based on knowledge gained from measurements at the site itself and from measurements from marine boundary layer (MBL) sites at comparable latitude. This "latitude reference" method has been improved upon over that described in Masarie and Tans, [1995] (hereafter MT95). Specifically, the technique used to construct reference MBL time series has been modified to reduce their sensitivity to changes in the distribution of sites and to minimize discontinuities in these reference curves resulting from periods of sporadic or interrupted sampling within existing MBL records.

   Summary of latitude reference method described by MT95

   Data were prepared by fitting a function, f(t) [Equation 1 in MT95 consisting of harmonics and a polynomial] to each measurement record. The residuals from this fit are smoothed to capture interannual variations in the seasonal cycle. These variations are added to f(t) to produce a smooth curve, S(t) [Equation 2, MT95], which is our best fit representation of the data The residuals are also smoothed to capture variations in the long-term trend only and these are added to the polynomial terms of f(t) to give the deseasonalized long-term trend, T(t) [Equation 3, MT95]. A detrended seasonal cycle is computed as S(t)-T(t), and the average seasonal cycle, H(t), is represented by the harmonic components of f(t) [see Equation 1].
   
   A single measurement record extended using the latitude reference method (as described in Section 4.2, MT95) utilized the record itself as well as information gleaned from additional measurements available from the observational network. Fundamental to this approach is the difference climatology that characterizes the uniqueness of a site record relative to a MBL reference calculated at the site's latitude. Differences between the smooth curve, SSTA(t), and the MBL reference, MBLSTA(t) are calculated (Equation 8, MT95). This distribution, ΔSTA,REF(t), highlights features in the site record that are not represented by the MBL reference. A curve [Equation 9, MT95] is then fitted to this distribution to characterize the average offset and average seasonal cycle of ΔSTA,REF(t) and represents the difference climatology for the site. We then assume the difference climatology is valid for periods where there are no measurements; limitations of this assumption are discussed in Sections 4 and 5 of MT95. Finally, the extended record is constructed using SSTA(t) where measurements exist and by combining MBLSTA(t) and the difference climatology where measurements do not exist.

   Modifications to the derivation of the MBL reference

   Reference MBL time series continue to be constructed using observations from active MBL sampling sites during the synchronization period (fixed span of time into which measurement records will be extended, e.g., 1979-1998). The method described in MT95, however, had a tendency to introduce discontinuities into the derived reference time series that were due to changes in the distribution of MBL measurements. For example, during construction of reference MBL time series, each MBL measurement record contributed its smooth values, S(t), everywhere measurements existed; no values from the site were contributed if an interruption in the observations exceeded 8 weeks. Further, the smooth curve was not defined before sampling at a location begins or after it ends. Thus, during construction of reference MBL time series, values from the smooth curves from MBL sites would abruptly appear, disappear, and reappear depending on the continuity and distribution of actual MBL measurements. This was particularly a problem in the equatorial and southern tropical regions where sampling is already sparse. In these regions, site additions, deletions, or gaps in the few existing MBL records had considerable impact on the reference MBL time series and added noise to existing variability due to changes in carbon exchange and atmospheric circulation.
   
   Modifications to the latitude reference procedure minimize the affects of a changing observational network on the derived reference MBL time series. This is accomplished in two ways. First, instead of using the smooth curve, S(t), from MBL measurement records as described by MT95, we use the long-term trend, T(t), the detrended seasonal cycle, S(t)-T(t), and the average seasonal cycle, H(t) derived from each MBL measurement record. Because the trend curve is, by definition, less sensitive than the smooth curve to short-term interruptions, we utilize interpolated values from the trend curve during problematic sampling periods. The seasonal component of the measurement record is represented by the detrended seasonal cycle where there are measurements and by the average seasonal cycle where there are short-term interruptions in the record. By using average seasonal cycle patterns, interruptions or periods of infrequent sampling in a MBL record where the seasonal cycle may be poorly defined or entirely missing have minimal impact on the derived MBL reference. Second, instead of using weights (which depend on sampling density and measurement variability) with annual resolution as described, we now use a single weight at each site that is determined using the entire measurement record. This eliminates variability in the MBL reference that arises when assigned weights may change abruptly from one year to the next, again, due to changes in the observational network. Considered together, these modifications to the latitude reference procedure ensure that once measurements at a MBL location commence, they contribute uninterrupted to the construction of the reference MBL time series until sampling is discontinued. This point is clarified in the description that follows.
   
   First, weekly latitudinal distributions (mixing ratio versus latitude) of values extracted from the long-term trends, T(t), at MBL sites are compiled. A weighted curve as described by Tans et al. [1989] is then fitted to each weekly distribution to approximate the meridional distribution of trends. At each time step, values are extracted from the curve at intervals of 0.05 sine of latitude from 90°S to 90°N producing a matrix (T(t,l)) of trends as a function of time and latitude.
   
   Second, using the same MBL sites, weekly latitudinal distributions of values extracted from the detrended seasonal cycle where measurements exist and from the average seasonal cycle where there are interruptions in the data record are compiled. A weighted curve is then fitted to each weekly distribution to approximate the meridional distribution of seasonal cycle patterns. At each time step, values are extracted from the curve at intervals of 0.05 sine latitude from 90°S to 90°N producing a matrix [S(t,l)-T(t,l); H(t,l)] of detrended seasonal cycle patterns as a function of time and latitude.
   
   Third, we construct the MBL matrix REF(t,l) = T(t,l) + {S(t,l)-T(t,l); H(t,l)}. This matrix contains derived model fits to the latitude distribution of long-term trends and detrended average or actual seasonal cycles from all MBL sites at each time step and latitude interval.
   
   Finally, a reference MBL time series can be extracted from the MBL matrix at any latitude using linear interpolation. For example, as described in Section 4.2 of MT95, a reference MBL time series is constructed at Cape Grim (CGO), REFCGO(t), by extracting, at each time step, a mixing ratio from the MBL matrix at the sine (latitude) of CGO. The MBL reference at CGO is most influenced by CGO itself (because it is designated as a MBL site) during the period of measurements, by MBL sites nearby in latitude to CGO, and to a lesser extent by all other MBL values used in the curve fits. The MBL reference at CGO is included in the CGO extension file. Reference MBL time series are included in data extension files for all MBL and non-MBL sampling locations. The reference MBL matrix is also included in this GLOBALVIEW product (See REFERENCE MARINE BOUNDARY LAYER MATRIX for details).
   
   The reference MBL time series constructed using this technique are considerably smoother and more stable than those generated using the original technique. This new technique, however, still cannot overcome certain limitations in the observational network itself. For example, in late-1990, the NOAA sampling at AMS (38°S) was terminated. NOAA sample collection began at CRZ (46°S) in early-1991 as a replacement to the AMS location. The 4-month gap in MBL measurements in this latitude region, however, results in a discontinuous period of low CO2 values in the reference MBL time series at CGO (41°S) that is bracketed in latitude by CRZ to the south and AMS to the north. This discontinuity in the MBL reference at the latitude of CGO is substantially attenuated in GLOBALVIEW-CO2 where continuous measurements at AMS [1980-1997] contributed by the LSCE laboratory in France provide the continuity that was lacking in the NOAA sampling network.