Reddy: An Open-Source Toolbox for Analyzing Eddy-Covariance Measurements in Heterogeneous Environments - Laura Mack; Norbert Pirk (Boundary-Layer Meteorology, 2026)
Land–atmosphere exchange is mediated by turbulent fluxes that can be quantified with eddy-covariance (EC) measurements. EC has been widely used to measure ecosystem-scale vertical exchange between atmosphere and vegetation, and to test and refine atmospheric turbulence theories, thereby improving the representation of turbulent fluxes in land surface models. Traditionally, research has focused on idealized, homogeneous and flat surfaces, but recent work increasingly targets turbulent exchange in complex, heterogeneous environments under non-ideal conditions, where challenges include advective fluxes, mesoscale circulations between contrasting surface types, and non-stationary nighttime turbulence. Here, we introduce the open-source R package Reddy, which integrates multiple EC analysis methods into a single modular framework. Reddy enables users to tailor post-processing choices to site-specific conditions by integrating turbulence diagnostics and flux calculations in an iterative re-evaluation spiral, where processing choices are adapted step-by-step. The package supports station management and facilitates detailed scientific analyses, and is accompanied by an extensive documentation and hands-on EC processing tutorials. We demonstrate Reddy using measurements from three Norwegian sites: (1) a morning transition following a strongly stably stratified night at an alpine tundra valley, (2) spectral and ogive analysis before and after ice-cover transition at a boreal lake, and (3) fitting flux–variance relations at a permafrost-affected palsa peatland. Comparison with EddyPro shows close agreement for carbon dioxide fluxes derived from closed-path systems, but increased scatter for near-zero methane fluxes derived from open-path systems. Reddy extends existing EC software and helps bridging micrometeorology and ecology in heterogeneous, real-world environments.

Probabilistic modelling of atmosphere–surface coupling with a copula Bayesian network - Laura Mack; Marvin Kähnert; Norbert Pirk (Environmental Modelling & Software, 2026)

Transfer Efficiency and Organization in Turbulent Transport over Alpine Tundra - Laura Mack; Terje Koren Berntsen; Nikki Vercauteren; Norbert Pirk (Boundary-Layer Meteorology, 2024)
The exchange of momentum, heat and trace gases between atmosphere and surface is mainly controlled by turbulent fluxes. Turbulent mixing is usually parametrized using Monin–Obukhov similarity theory (MOST), which was derived for steady turbulence over homogeneous and flat surfaces, but is nevertheless routinely applied to unsteady turbulence over non-homogeneous surfaces. We study four years of eddy-covariance measurements at a highly heterogeneous alpine valley site in Finse, Norway, to gain insights into the validity of MOST, the turbulent transport mechanisms and the contributing coherent structures. The site exhibits a bimodal topography-following flux footprint, with the two dominant wind sectors characterized by organized and strongly negative momentum flux, but different anisotropy and contributions of submeso-scale motions, leading to a failure of eddy-diffusivity closures and different transfer efficiencies for different scalars. The quadrant analysis of the momentum flux reveals that under stable conditions sweeps transport more momentum than the more frequently occurring ejections, while the opposite is observed under unstable stratification. From quadrant analysis, we derive the ratio of the amount of disorganized to organized structures, that we refer to as organization ratio (OR). We find an invertible relation between transfer efficiency and corresponding organization ratio with an algebraic sigmoid function. The organization ratio further explains the scatter around scaling functions used in MOST and thus indicates that coherent structures modify MOST. Our results highlight the critical role of coherent structures in turbulent transport in heterogeneous tundra environments and may help to find new parametrizations for numerical weather prediction or climate models.

Climate–ecosystem modelling made easy: The Land Sites Platform - Lasse T. Keetz; Eva Lieungh; Kaveh Karimi‐Asli; Sonya R. Geange; Emiliano Gelati; Hui Tang; Yeliz A. Yilmaz; Kjetil S. Aas; Inge H. J. Althuizen; Anders Bryn; Stefanie Falk; Rosie Fisher; et al. (Global Change Biology, 2023)
Dynamic Global Vegetation Models (DGVMs) provide a state‐of‐the‐art process‐based approach to study the complex interplay between vegetation and its physical environment. For example, they help to predict how terrestrial plants interact with climate, soils, disturbance and competition for resources. We argue that there is untapped potential for the use of DGVMs in ecological and ecophysiological research. One fundamental barrier to realize this potential is that many researchers with relevant expertize (ecology, plant physiology, soil science, etc.) lack access to the technical resources or awareness of the research potential of DGVMs. Here we present the Land Sites Platform (LSP): new software that facilitates single‐site simulations with the Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled with the Community Land Model. The LSP includes a Graphical User Interface and an Application Programming Interface, which improve the user experience and lower the technical thresholds for installing these model architectures and setting up model experiments. The software is distributed via version‐controlled containers; researchers and students can run simulations directly on their personal computers or servers, with relatively low hardware requirements, and on different operating systems. Version 1.0 of the LSP supports site‐level simulations. We provide input data for 20 established geo‐ecological observation sites in Norway and workflows to add generic sites from public global datasets. The LSP makes standard model experiments with default data easily achievable (e.g., for educational or introductory purposes) while retaining flexibility for more advanced scientific uses. We further provide tools to visualize the model input and output, including simple examples to relate predictions to local observations. The LSP improves access to land surface and DGVM modelling as a building block of community cyberinfrastructure that may inspire new avenues for mechanistic ecosystem research across disciplines.

A Methodology for Providing Surface-Cover-Corrected Net Radiation at Heterogeneous Eddy-Covariance Sites - Eirik Næsset Ramtvedt; Norbert Pirk (Boundary-Layer Meteorology, 2022)
A one-point measurement of net radiation is typically not representative of radiative energy available for the turbulent exchange of latent and sensible heat at eddy-covariance sites with heterogeneous surface cover. We propose a methodology for providing surface-cover-corrected net radiation matching the footprint of turbulent fluxes at a heterogenous eddy-covariance site. This is demonstrated at a complex sub-alpine site in southern central Norway over a week. The methodology is assessed by comparing the energy balance closure calculated with the regular one-point net radiation measurement at the flux tower against the surface-cover-corrected net radiation. The assessment indicates a decrease in the energy imbalance by 8% when assessed with the energy balance ratio, but no improvement is revealed when assessed with regression methods. However, only a small dataset serves as basis for this demonstration, and the findings therefore cannot necessarily be generalized. Further testing and application of the methodology is required to understand the full effect of surface-cover-correcting mismatching footprints of turbulent fluxes and net radiation at heterogeneous eddy-covariance sites.

Toward a statistical description of methane emissions from arctic wetlands - Norbert Pirk; Mikhail Mastepanov; Efrén López-Blanco; Louise H. Christensen; Hanne H. Christiansen; Birger Ulf Hansen; Magnus Lund; Frans-Jan W. Parmentier; Kirstine Skov; Torben R. Christensen (Ambio, 2017)