Global Monitoring Division

The GLOBALVIEW data products are designed to enhance the spatial and temporal distribution of atmospheric observations of CO2, CH4 and other related greenhouse gases. GLOBALVIEW products are specifically intended as tools for use in carbon cycle modeling studies.

A GLOBALVIEW data product is derived from measurements but contains no actual data. The product includes synchronized smoothed time series derived from continuous and discrete land-surface, ship, aircraft, and tower observations; weight files; summaries of seasonal patterns, diurnal patterns (where relevant), sampling time-of-day (where available), and atmospheric variability; the derived marine boundary layer (MBL) reference matrix used in the data extension process; and extensive documentation.

GLOBALVIEW products are 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 and methane measurement records from other laboratories have been extended and integrated with the NOAA ESRL measurements into GLOBALVIEW-CO2 and GLOBALVIEW-CH4 with careful attention to both methodology and standard scales.

The impetus for the work done by the many cooperating organizations and institutions is to make 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 is an attempt to address these issues of temporal discontinuity and data sparseness and is a tool intended for use in carbon cycle modeling.