Comparison of different stomatal conductance algorithms for ozone flux modelling

A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An

Scale issues in soil moisture modelling: problems and prospects

Soil moisture storage is an important component of the hydrological cycle and plays a key role in land-surface-atmosphere interaction. The soil-moisture storage equation in this study considers precipitation as an input and soil moisture as a residual term for runoff and evapotranspiration. A number of models have been developed to estimate soil moisture storage and the components of the soil-moisture storage equation. A detailed discussion of the impli cation of the scale of application of these models reports that it is not possible to extrapolate processes and their estimates from the small to the large scale. It is also noted that physically based models for small-scale applications are sufficiently detailed to reproduce land-surface- atmosphere interactions. On the other hand, models for large-scale applications oversimplify the processes. Recently developed physically based models for large-scale applications can only be applied to limited uses because of data restrictions and the problems associated with land surface characterization. It is reported that remote sensing can play an important role in over coming the problems related to the unavailability of data and the land surface characterization of large-scale applications of these physically based models when estimating soil moisture storage.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Late Winter Biogeochemical Conditions Under Sea Ice in the Canadian High Arctic

With the Arctic summer sea-ice extent in decline, questions are arising as to how changes in sea-ice dynamics might affect biogeochemical cycling and phenomena such as carbon dioxide (CO2) uptake and ocean acidification. Recent field research in these areas has concentrated on biogeochemical and CO2 measurements during spring, summer or autumn, but there are few data for the winter or winter–spring transition, particularly in the High Arctic. Here, we present carbon and nutrient data within and under sea ice measured during the Catlin Arctic Survey, over 40 days in March and April 2010, off Ellef Ringnes Island (78° 43.11′ N, 104° 47.44′ W) in the Canadian High Arctic. Results show relatively low surface water (1–10 m) nitrate (<1.3 µM) and total inorganic carbon concentrations (mean±SD=2015±5.83 µmol kg−1), total alkalinity (mean±SD=2134±11.09 µmol kg−1) and under-ice pCO2sw (mean±SD=286±17 µatm). These surprisingly low wintertime carbon and nutrient conditions suggest that the outer Canadian Arctic Archipelago region is nitrate-limited on account of sluggish mixing among the multi-year ice regions of the High Arctic, which could temper the potential of widespread under-ice and open-water phytoplankton blooms later in the season