Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 3 of 3 for “"LPJ"”.

  1. Process-based simulation of the terrestrial biosphere : an evaluation of present-day and future terrestrial carbon balance estimates and their uncertainty

    … Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from …

    potsdam-diss Repository record for Process-based simulation of the terrestrial biosphere : an evaluation of present-day and future terrestrial carbon balance estimates and their uncertainty (opens in a new tab)

  2. Statistical and process-based models for understanding species distributions in changing environments

    … the limited success of an established PBM (LPJ-GUESS) applied to the same problem. Examination of process representation and parameterization in the PBM identifies implemented processes to adjust (competition between species, disturbance) and missing processes that are crucial in boreal …

    potsdam-diss Repository record for Statistical and process-based models for understanding species distributions in changing environments (opens in a new tab)

  3. Spatial and temporal dynamics of the terrestrial carbon cycle : assimilation of two decades of optical satellite data into a process-based global vegetation model

    … process-based dynamic global vegetation model LPJ and a 21-year time series of global AVHRR-fPAR data (fPAR – fraction of photosynthetically active radiation). Assimilation of the satellite data into the model allows improved simulations of carbon fluxes on global as well as on regional scales. …

    potsdam-diss Repository record for Spatial and temporal dynamics of the terrestrial carbon cycle : assimilation of two decades of optical satellite data into a process-based global vegetation model (opens in a new tab)