Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE), and their relationship with environmental drivers, are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010–2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems are dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

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.

A common viewpoint across the Earth science community is that global soil moisture estimates from satellite L-band (1.4 GHz) measurements represent moisture only in the shallow soil layers (0-5 cm) and are of limited value for studying global terrestrial ecosystems because plants use water from deeper rootzones. Here, we argue that such a viewpoint is flawed for two reasons. First, microwave soil emission theory and statistical considerations of vertically correlated soil moisture information together indicate that L-band measurements are typically representative of soil moisture within at least the top 15-25 cm, or 3-5 times deeper than commonly thought. Second, in reviewing isotopic tracer field studies of plant water uptake, we find a global prevalence of vegetation that primarily draws moisture from these upper soil layers. This is especially true for grasslands and croplands covering more than a third of global vegetated surfaces. While shrub and tree species tend to draw deeper soil moisture, these plants often still preferentially or seasonally draw water from the upper soil layers. Therefore, L-band satellite soil moisture estimates are more relevant to global vegetation water uptake than commonly appreciated, and we encourage their application across terrestrial hydrosphere and biosphere studies.