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Abstract Synoptic-scale weather patterns affect local meteorological variables, such as vapor pressure deficit (VPD), temperature, and insolation, that are known to influence evapotranspiration (ET) and net CO₂flux (FC). However, little research exists that links synoptic-scale patterns to ET and FC. In this study, we seek to understand how synoptic-scale patterns influence ET and FC for the temperate mixed-hardwood forest at Hubbard Brook Experimental Forest (HBEF) in New Hampshire, United States. We use self-organizing maps to identify the most common synoptic pattern types impacting HBEF during the 2016–21 growing seasons and determine how ET and FC vary with these synoptic pattern types. Our analysis reveals that high ET and most negative FC days occur for the weather pattern phases starting after the departure of a low pressure system and through the approach of a high pressure system. ET and the magnitude of FC remain high if the latitude of the high is south of HBEF but moderate (especially for ET) if the high is to the north and causes east winds to advect a humid maritime air mass over the region. ET is lowest when HBEF is located between high pressure to the east and low pressure to the west, which causes humid southerly flow to decrease VPD and insolation. Meanwhile, FC magnitude may remain high when this pattern occurs in June–July when photosynthetic capacity is at its highest. Our results suggest that future changes in the frequency of passing low pressure systems and pathways of high pressure systems could impact the fluxes of water and CO₂from this forest. Significance StatementFor decades, we have understood that local meteorological variables, such as insolation, temperature, and relative humidity, have a strong influence on a forest ecosystem’s use of water and carbon dioxide, two important greenhouse gases. We also understand that large-scale weather patterns and their interactions with forests shape these local meteorological conditions. This research advances knowledge of the relationship between various large-scale weather patterns and their impacts on forest’s use of water and carbon dioxide via local meteorological variables for a mixed-hardwood forest in the Northeastern United States. Connecting these results to the frequency of these various large-scale weather pattern types projected by global climate models will help us predict how forest ecosystems will influence water vapor and carbon dioxide concentrations and thus impact global climate.