Abstract. The carbon cycle in Arctic-boreal regions (ABR) is an important component of the planetary carbon balance, with growing concerns about the consequences of ABR warming on the global climate system. The greatest uncertainty in annual carbon dioxide (CO2) budgets exists during the non-growing season, primarily due to challenges with data availability and limited spatial coverage in measurements. The goal of this study was to determine the main environmental controls of non-growing season CO2 fluxes in ABR over a latitudinal gradient (45° N to 69° N) featuring four different ecosystem types: closed-crown coniferous boreal forest, open-crown coniferous boreal forest, erect-shrub tundra, and prostrate-shrub tundra. CO2 fluxes calculated using a snowpack diffusion gradient method (n = 560) ranged from 0 to 1.05 gC m2 day-1. To assess the dominant environmental controls governing CO2 fluxes, a Random Forest machine learning approach was used. We identified that soil temperature as the main control of non-growing season CO2 fluxes with 68 % of relative model importance, except when soil liquid water occurred during zero degree Celsius curtain conditions (Tsoil ≈ 0 °C and liquid water coexists with ice in soil pores). Under zero-curtain conditions, liquid water content became the main control of CO2 fluxes with 87 % of relative model importance. We observed exponential regressions between CO2 fluxes and soil temperature (RMSE = 0.024 gC m-2 day-1) in frozen soils, as well as liquid water content (RMSE = 0.137 gC m-2 day-1) in zero-curtain conditions. This study is showing the role of several variables on the spatio-temporal variability of CO2 fluxes in ABR during the non-growing season and highlight that the complex vegetation-snow-soil interactions in northern environments must be considered when studying what drives the spatial variability of soil carbon emission during the non-growing season.

Abstract. The carbon cycle in Arctic-boreal regions (ABR) is an important component of the planetary carbon balance, with growing concerns about the consequences of ABR warming on the global climate system. The greatest uncertainty in annual carbon dioxide (CO2) budgets exists during the non-growing season, primarily due to challenges with data availability and limited spatial coverage in measurements. The goal of this study was to determine the main environmental controls of non-growing season CO2 fluxes in ABR over a latitudinal gradient (45° N to 69° N) featuring four different ecosystem types: closed-crown coniferous boreal forest, open-crown coniferous boreal forest, erect-shrub tundra, and prostrate-shrub tundra. CO2 fluxes calculated using a snowpack diffusion gradient method (n = 560) ranged from 0 to 1.05 gC m2 day-1. To assess the dominant environmental controls governing CO2 fluxes, a Random Forest machine learning approach was used. We identified that soil temperature as the main control of non-growing season CO2 fluxes with 68 % of relative model importance, except when soil liquid water occurred during zero degree Celsius curtain conditions (Tsoil ≈ 0 °C and liquid water coexists with ice in soil pores). Under zero-curtain conditions, liquid water content became the main control of CO2 fluxes with 87 % of relative model importance. We observed exponential regressions between CO2 fluxes and soil temperature (RMSE = 0.024 gC m-2 day-1) in frozen soils, as well as liquid water content (RMSE = 0.137 gC m-2 day-1) in zero-curtain conditions. This study is showing the role of several variables on the spatio-temporal variability of CO2 fluxes in ABR during the non-growing season and highlight that the complex vegetation-snow-soil interactions in northern environments must be considered when studying what drives the spatial variability of soil carbon emission during the non-growing season.

Abstract. The carbon cycle in Arctic–boreal regions (ABRs) is an important component of the planetary carbon balance, with growing concerns about the consequences of ABR warming for the global climate system. The greatest uncertainty in annual carbon dioxide (CO2) budgets exists during winter, primarily due to challenges with data availability and limited spatial coverage in measurements. The goal of this study was to determine the main environmental controls of winter CO2 fluxes in ABRs over a latitudinal gradient (45∘ to 69∘ N) featuring four different ecosystem types: closed-crown coniferous boreal forest, open-crown coniferous boreal forest, erect-shrub tundra, and prostrate-shrub tundra. CO2 fluxes calculated using a snowpack diffusion gradient method (n=560) ranged from 0 to 1.05 g C m2 d−1. To assess the dominant environmental controls governing CO2 fluxes, a random forest machine learning approach was used. We identified soil temperature as the main control of winter CO2 fluxes with 68 % of relative model importance, except when soil liquid water occurred during 0 ∘C curtain conditions (i.e., Tsoil≈0 ∘C and liquid water coexist with ice in soil pores). Under zero-curtain conditions, liquid water content became the main control of CO2 fluxes with 87 % of relative model importance. We observed exponential regressions between CO2 fluxes and soil temperature in fully frozen soils (RMSE=0.024 gCm-2d-1; 70.3 % of mean FCO2) and soils around the freezing point (RMSE=0.286 gCm-2d-1; 112.4 % of mean FCO2). FCO2 increases more rapidly with Tsoil around the freezing point than at Tsoil<5 ∘C. In zero-curtain conditions, the strongest regression was found with soil liquid water content (RMSE=0.137 gCm-2d-1; 49.1 % of mean FCO2). This study shows the role of several variables in the spatio-temporal variability in CO2 fluxes in ABRs during winter and highlights that the complex vegetation–snow–soil interactions in northern environments must be considered when studying what drives the spatial variability in soil carbon emissions during winter.

Abstract. Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation, based on theoretical and empirical evidence. Because the total amount of water in vegetation varies with relative water content (as well as with biomass), this correlation further suggests a possible relationship between VOD and plant water potential, a quantity that drives plant hydraulic behavior. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in central Massachusetts, United States. We measured stem xylem and leaf water potentials of trees within the stand and retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and measured soil moisture. VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 05:00 eastern daylight time (UTC−4). VOD was also positively correlated with both the measured dielectric constant and water potentials of stem xylem over the growing season. The presence of moisture on the leaves did not affect the observed relationship between VOD and stem water potential. We used our observed VOD–water-potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.

Abstract. Vegetation optical depth (VOD) retrieved from microwave radiometry correlates with the total amount of water in vegetation, based on theoretical and empirical evidence. Because the total amount of water in vegetation varies with relative water content (as well as with biomass), this correlation further suggests a possible relationship between VOD and plant water potential, a quantity that drives plant hydraulic behavior. Previous studies have found evidence for that relationship on the scale of satellite pixels tens of kilometers across, but these comparisons suffer from significant scaling error. Here we used small-scale remote sensing to test the link between remotely sensed VOD and plant water potential. We placed an L-band radiometer on a tower above the canopy looking down at red oak forest stand during the 2019 growing season in central Massachusetts, United States. We measured stem xylem and leaf water potentials of trees within the stand and retrieved VOD with a single-channel algorithm based on continuous radiometer measurements and measured soil moisture. VOD exhibited a diurnal cycle similar to that of leaf and stem water potential, with a peak at approximately 05:00 eastern daylight time (UTC−4). VOD was also positively correlated with both the measured dielectric constant and water potentials of stem xylem over the growing season. The presence of moisture on the leaves did not affect the observed relationship between VOD and stem water potential. We used our observed VOD–water-potential relationship to estimate stand-level values for a radiative transfer parameter and a plant hydraulic parameter, which compared well with the published literature. Our findings support the use of VOD for plant hydraulic studies in temperate forests.

Abstract. Soil microwave permittivity is a crucial parameter in passive microwave retrieval algorithms but remains a challenging variable to measure. To validate and improve satellite microwave data products, precise and reliable estimations of the relative permittivity (εr=ε/ε0=ε′-jε′′; unitless) of soils are required, particularly for frozen soils. In this study, permittivity measurements were acquired using two different instruments: the newly designed open-ended coaxial probe (OECP) and the conventional Stevens HydraProbe. Both instruments were used to characterize the permittivity of soil samples undergoing several freeze–thaw cycles in a laboratory environment. The measurements were compared to soil permittivity models. The OECP measured frozen (εfrozen′=[3.5; 6.0], εfrozen′′=[0.46; 1.2]) and thawed (εthawed′=[6.5; 22.8], εthawed′′=[1.43; 5.7]) soil microwave permittivity. We also demonstrate that cheaper and widespread soil permittivity probes operating at lower frequencies (i.e., Stevens HydraProbe) can be used to estimate microwave permittivity given proper calibration relative to an L-band (1–2 GHz) probe. This study also highlighted the need to improve dielectric soil models, particularly during freeze–thaw transitions. There are still important discrepancies between in situ and modeled estimates and no current model accounts for the hysteresis effect shown between freezing and thawing processes, which could have a significant impact on freeze–thaw detection from satellites.

Abstract The extent, timing and duration of seasonal freeze/thaw (FT) state exerts dominant control on boreal forest carbon, water and energy cycle processes. Recent and on-going L-Band (≈1.4 GHz) spaceborne missions have the potential to provide enhanced information on FT state over large geographic regions with rapid revisit time. However, the low spatial resolution of these spaceborne observations (≈45 km) makes it difficult to isolate the primary contributions (soil, vegetation, snow) to the FT signal in boreal forest. To better quantify these controls, two L-Band radiometers were deployed (September 2016 to July 2017) at a black spruce (Picea mariana) dominated boreal forest site; one unit above and one unit on the ground surface below the canopy to disentangle the microwave contributions of overstory canopy, and the ground surface on the FT brightness temperature (TB) signal. Bi-weekly multi-angular measurements from both units were combined in order to estimate effective scattering albedo (ω) and the microwave vegetative optical depth (τ), using the τ-ω microwave vegetation radiative transfer model. Soil moisture probes were inserted in the trunk of two black spruce and one larch (Larix laricina) trunks located in the footprint of the above-canopy radiometer to measure tree trunk relative dielectric constant (RDCtree). Results showed a strong relationship between RDCtree and tree skin temperature (Ttree) under freezing temperature conditions, which led to a gradual decrease of τ in winter. During the spring thawing period in April and May, τ remained relatively stable. In contrast, it increased substantially in June, most likely in relation to the growing season onset. Overall, τ was related to the seasonal RDCtree cycle (r = 0.76). Regarding ω, a value of 0.086 (±0.029) was obtained, but no dependency on Ttree or RDCtree was observed. Despite the observed impact of FT on vegetation L-Band signals, results from continuous TB observations spanning from 14 September 2016 to 25 May 2017, indicated that the main contribution to the observed L-Band TB freeze-up signal in the fall originated from the ground surface. The above-canopy unit showed some sensitivity to overstory canopy FT, yet the sensitivity was lower compared to the signal induced by the ground FT. In April and May, L-Band radiometer FT retrieval agreed closely to the melt onset detection using RDCtree but it was likely related to the coincident presence of liquid water in the snow. Our findings have important applications to L-Band spaceborne FT algorithm development and validation across the boreal forest. More specifically, our findings allow better quantification of the potential effect of frozen ground on various biogeophysical and biogeochemical processes in boreal forests.

Abstract. Decoupling the integrated microwave signal originating from soil and vegetation remains a challenge for all microwave remote sensing applications. To improve satellite and airborne microwave data products in forest environments, a precise and reliable estimation of the relative permittivity (ε=ε′-iε′′) of trees is required. We developed an open-ended coaxial probe suitable for in situ permittivity measurements of tree trunks at L-band frequencies (1–2 GHz). The probe is characterized by uncertainty ratios under 3.3 % for a broad range of relative permittivities (unitless), [2–40] for ε′ and [0.1–20] for ε′′. We quantified the complex number describing the permittivity of seven different tree species in both frozen and thawed states: black spruce, larch, red spruce, balsam fir, red pine, aspen and black cherry. Permittivity variability is substantial and can range up to 300 % for certain species. Our results show that the permittivity of wood is linked to the freeze–thaw state of vegetation and that even short winter thaw events can lead to an increase in vegetation permittivity. The open-ended coaxial probe proved to be precise enough to capture the diurnal cycle of water storage inside the trunk for the length of the growing season.

Abstract A field campaign was conducted October 30th to November 13th, 2015 with the intention of capturing diurnal soil freeze/thaw state at multiple scales using ground measurements and remote sensing measurements. On four of the five sampling days, we observed a significant difference between morning (frozen scenario) and afternoon (thawed scenario) ground-based measurements of the soil relative permittivity. These results were supported by an in situ soil moisture and temperature network (installed at the scale of a spaceborne passive microwave pixel) which indicated surface soil temperatures fell below 0 °C for the same four sampling dates. Ground-based radiometers appeared to be highly sensitive to F/T conditions of the very surface of the soil and indicated normalized polarization index (NPR) values that were below the defined freezing values during the morning sampling period on all sampling dates. The Scanning L-band Active Passive (SLAP) instrumentation, flown over the study region, showed very good agreement with the ground-based radiometers, with freezing states observed on all four days that the airborne observations covered the fields with ground-based radiometers. The Soil Moisture Active Passive (SMAP) satellite had morning overpasses on three of the sampling days, and indicated frozen conditions on two of those days. It was found that >60% of the in situ network had to indicate surface temperatures below 0 °C before SMAP indicated freezing conditions. This was also true of the SLAP radiometer measurements. The SMAP, SLAP and ground-based radiometer measurements all indicated freezing conditions when soil temperature sensors installed at 5 cm depth were not frozen.