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We examine the physical and biological responses of forest canopies to step changes in light caused by passing low cumulus clouds that intermittently block the direct solar beam. Using data obtained at a tropical rainforest and at a midlatitude deciduous forest, we estimate the course of sensible heat flux, net ecosystem exchange, evapotranspiration, and water-use efficiency in response to the rapid changes in the incident radiative flux. To describe these fluxes during the interval over which the effects of stomatal time delays can be most influential, eddy fluxes are estimated over minute or shorter intervals by invoking a conditional-sampling procedure based on forming a Reynolds-average ensemble. The most important differences between the two forests’ physical responses are in the thermal balances and heat-flux time response constants. During the initial period after the light transition the only mean variables that show appreciable changes are the blackbody and air temperatures, the other scalars being little affected. We find that a distinct transient thermal internal boundary layer appears ≈ 20 m thick above the temperate deciduous forest and ≈ 45 m thick above the tropical rainforest. At each forest, the effective thickness of the inferred thermal outer-canopy ‘big leaf’ is about 1 mm. Twenty minutes after the abrupt change in incident light, ensemble eddy-flux estimates approach those found using conventional time averaging, confirming the validity of the ensemble approach. Previously unrecognized transient maxima in net ecosystem exchange and evapotranspiration are evident 5–10 min following the shadow-to-light transition, longer than the average light interval between shadows observed on partly-cloudy days in each case. Short-term variations in sensible heat flux, net ecosystem exchange, and evapotranspiration approximate an exponential adjustment, implying that first-order time-dependent single-leaf models are adequate to describe whole-canopy processes in these cases, providing an experimental method for determining whole-canopy bulk stomatal time constants. During the sunlit interval (direct and diffuse radiative fluxes combined) net ecosystem exchange is enhanced, while under cloud shadow (only diffuse radiative flux) water-use efficiency increases. This light and shadow alternation provides a mechanism describing the observed enhanced net ecosystem exchange and water-use efficiency under certain types of partly-cloudy sky. We apply empirical flux-response curves to an idealized case of radiative flux varying in a regular on–off light and shadow pattern. For this case, an analytical solution for mean net ecosystem exchange flux as a function of diffuse-radiation fraction yields results that strongly resemble previous findings based on conventional time-averaged fluxes. Our analysis and modelling indicates that a well-known correlation between diffuse radiative flux and enhanced net ecosystem exchange and water-use efficiency on cloudy days is in many cases not causal, but rather to be a consequence of time averaging over light-and-shadow intervals. By linking processes associated with photosynthesis in fluctuating light at the leaf scale to the canopy scale, our efforts facilitate the scaling-up of leaf responses to the ecosystem scale.

An improved ray tracing air mass model to calculate the air mass numbers for the entire zenith angle range is developed. The improved model uses the approach when the trajectory element of light in the atmosphere is approximated by an arc of a circle. This way the angles at the beginning and at the end of the trajectory element can be counted simultaneously. This approach gives the second-order approximation for the real light trajectory with more accurate results than the results of the approaches of Link and Neuzil (Tables of Light Trajectories in the Terrestrial Atmosphere, Hermann, 1969) and the Kasten and Young models [Appl. Opt. 28, 4735 (1989)]. The developed model allows us to avoid the calculation problems of the Link and Neuzil and Kasten models when the zenith angle is close to or equal to 90°. As a result, we deliver the new air mass number table for the entire zenith angle range and provide the comparison of the developed model results with the results of the Link and Neuzil and the Kasten models.

Soil respiration (SR) is a main component of the carbon cycle in terrestrial ecosystems, and being strongly affected by changes in the environment, it is a good indicator of the ecosystem’s ability to cope with climate change. This research aims to find better empirical SR models using 25-year-long SR monitoring in two forest ecosystems formed on sandy Entic Podzol and loamy Haplic Luvisol. The following parameters were considered in the examined models: the mean monthly soil or air temperatures (T_soil or T_air), the amount of precipitation during the current (P) and the previous (PP) months, and the storage of soil organic carbon (SOC). The weighted non-linear regression was used for model parameter estimations for the normal, wet, and dry years. To improve the model resolutions by magnitude, we controlled the slope and intercept of the linear model comparison between the measured and modeled data through the change in R₀—SR at zero soil temperature. The mean bias error (MBE), root-mean-square error (RMSE), and determination coefficient (R²) were used for the estimation of the goodness of model performances. For the sandy Entic Podzol, it is more appropriate to use the models dependent on SOC (TPPC). While for the loamy Haplic Luvisol, the Raich–Hashimoto model (TPPrh) with the quadratic T_soil or T_air dependency shows the better results. An application of T_soil for the model parameterization gives better results than T_air: the TPPC model was able to adequately describe the cold-period SR (T_soil ≤ 2 °C); the TPPrh model was able to avoid overestimations of the warm-period SR (T_soil > 2 °C). The TPPC model parameterized with T_soil can be used for the quality control of the cold-period SR measurements. Therefore, we showed the importance of accounting for SOC and the water-holding ability when the optimal SR model is chosen for the analysis.

Validation and operational improvements to the existing SUNY satellite-to-solar irradiance model through incorporation of four of the geostationary satellite infrared (IR) channels are presented herein. The SUNY model is the gridded data set used by NREL in the National Solar Radiation Database (NSRDB) and is available commercially through the Clean Power Research software, SolarAnywhere ^® Data. This improved model addresses the present model's limitations when representing the irradiance conditions in circumstances of snow cover, high ground reflectance and persistent cloud cover. Improvements in the satellite-to-solar irradiance model have been realized using the IR channels to detect snow conditions and modulate the model background to more accurately reflect irradiance conditions.