Gross Primary Productivity (GPP) is the largest flux in the global carbon cycle and satellite-based GPP estimates have long been used to study the trends and inter-annual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar-orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites - R series (GOES-R) to test the ability of sub-daily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We optimized parameters for three models to estimate GPP. A light response curve (LRC) achieved the lowest test mean absolute error for winter (1.82 µmol CO2 m-2 s-1), spring (2.51 µmol CO2 m-2 s-1), summer (1.45 µmol CO2 m-2 s-1), and fall (1.25 µmol CO2 m-2 s-1). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation towards the morning hours during the dry summers. The LRC and the light-use efficiency model were in agreement with these patterns of increasing shift of GPP towards the morning hours during the summer months. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

Agriculture is a significant source of carbon dioxide (CO2) and methane (CH4) and is the dominant source of anthropogenic nitrous oxide (N2O) emissions. Changes in agricultural land management practices that reduce overall greenhouse gas (GHG) emissions have been suggested to help mitigate climate change, but a better understanding of the timing, magnitude, and drivers of GHG fluxes is needed. Alfalfa agroecosystems may be significant sources of N2O given their ability to increase N inputs through symbiotic N2 fixation and frequent irrigation events that create conditions for hot moments of N2O production. However, few studies have explored long-term N2O emissions and their associated drivers in alfalfa ecosystems. We collected over 108,000 CO2, CH4 and N2O soil flux measurements over four years using cavity ring-down spectroscopy from a conventional flood-irrigated alfalfa field in California, USA. This ecosystem was a consistent source of N2O (annual mean: 624.4 ± 27.8 mg N2O m-2 yr-1, range: 263.6. ± 5.6 to 901.9 ± 74.5 mg N2O m-2 yr-1) and a small net sink of CH4 (annual mean: -53.5 ± 2.5 mg CH4 m-2 yr-1, range: -78.2 ± 8.8 to -31.6 ± 2.5 mg CH4 m-2 yr-1). Soil CO2 fluxes averaged 4925.9 ± 13.5 g CO2 m-2 yr-1 and were greater than other alfalfa ecosystem estimates, likely driven by elevated temperatures and plant productivity throughout the growing season. Hot moments of N2O emissions represented only 0.2% to 1.1% of annual measurements but were 31.6% to 56.8% of the annual flux. We found that both the magnitude and the contribution of N2O hot moments to annual emissions decreased over time. Normalized difference vegetation index (NDVI), soil temperature, moisture, and O2 were all significantly correlated with soil CO2, N2O, and CH4 fluxes, although associations varied across both soil depth and timescales. Our results suggest that flood-irrigated alfalfa is a significant source of agricultural N2O emissions, and that plant productivity and soil moisture effects on O2 availability may modulate the net GHG budget of alfalfa agroecosystems.