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Viable nature-based climate solutions (NbCS) are needed to achieve climate goals expressed in international agreements like the Paris Accord. Many NbCS pathways have strong scientific foundations and can deliver meaningful climate benefits but effective mitigation is undermined by pathways with less scientific certainty. Here we couple an extensive literature review with an expert elicitation on 43 pathways and find that at present the most used pathways, such as tropical forest conservation, have a solid scientific basis for mitigation. However, the experts suggested that some pathways, many with carbon credit eligibility and market activity, remain uncertain in terms of their climate mitigation efficacy. Sources of uncertainty include incomplete GHG measurement and accounting. We recommend focusing on resolving those uncertainties before broadly scaling implementation of those pathways in quantitative emission or sequestration mitigation plans. If appropriate, those pathways should be supported for their cobenefits, such as biodiversity and food security.

How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO₂(F_c) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that whileSHin the ASL decreases linearly with height regardless of soil moisture conditions,LHandF_cdecrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the “true” surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimatedLH. The non‐closure does not imply thatF_cis always underestimated;F_ccan be overestimated over dry soils despite the non‐closure issue.

The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio (r_v) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity (w) variance (), andr_vvariance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

Single point eddy covariance measurements of the Earth’s surface energy budget frequently identify an imbalance between available energy and turbulent heat fluxes. While this imbalance lacks a definitive explanation, it is nevertheless a persistent finding from single-site measurements; one with implications for atmospheric and ecosystem models. This has led to a push for intensive field campaigns with temporally and spatially distributed sensors to help identify the causes of energy balance non-closure. Here we present results from the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19)—an observational experiment designed to investigate how the Earth’s surface energy budget responds to scales of surface spatial heterogeneity over a forest ecosystem in northern Wisconsin. The campaign was conducted from June–October 2019, measuring eddy covariance (EC) surface energy fluxes using an array of 20 towers and a low-flying aircraft. Across the domain, energy balance residuals were found to be highest during the afternoon, coinciding with the period of surface heterogeneity-driven mesoscale motions. The magnitude of the residual varied across different sites in relation to the vegetation characteristics of each site. Both vegetation height and height variability showed positive relationships with the residual magnitude. During the seasonal transition from latent heat-dominated summer to sensible heat-dominated fall the magnitude of the energy balance residual steadily decreased, but the energy balance ratio remained constant at 0.8. This was due to the different components of the energy balance equation shifting proportionally, suggesting a common cause of non-closure across the two seasons. Additionally, we tested the effectiveness of measuring energy balance using spatial EC. Spatial EC, whereby the covariance is calculated based on deviations from spatial means, has been proposed as a potential way to reduce energy balance residuals by incorporating contributions from mesoscale motions better than single-site, temporal EC. Here we tested several variations of spatial EC with the CHEESEHEAD19 dataset but found little to no improvement to energy balance closure, which we attribute in part to the challenging measurement requirements of spatial EC.

Abstract. Long-term tall-tower eddy-covariance (EC) measurements have been recently established in three European pilot cities as part of the ICOS-Cities project. We conducted a comparison of EC software to ensure a reliable generation of interoperable flux estimates, which is the prerequisite for avoiding methodological biases and improving the comparability of the results. We analyzed datasets covering 5 months collected from EC tall-tower installations located in urbanized areas of Munich, Zurich, and Paris. Fluxes of sensible heat, latent heat, and CO2 were calculated using three software packages (i.e., TK3, EddyPro, and eddy4R) to assess the uncertainty of flux estimations attributed to differences in implemented postprocessing schemes. A very good agreement on the mean values and standard deviations was found across all three sites, which can probably be attributed to a uniform instrumentation, data acquisition, and preprocessing. The overall comparison of final flux time series products showed a good but not yet perfect agreement among the three software packages. TK3 and EddyPro both calculated fluxes with low-frequency spectral correction, resulting in better agreement than between TK3 and the eddy4R workflow with disabled low-frequency spectral treatment. These observed flux discrepancies indicate the crucial role of treating low-frequency spectral loss in flux estimation for tall-tower EC systems.