ORCID Profile
0000-0002-6510-4914
Current Organisation
Japan Agency for Marine-Earth Science and Technology
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Publisher: Copernicus GmbH
Date: 15-01-2016
Abstract: Abstract. Here, the authors describe the construction of a forcing data set for land surface models (including both physical and biogeochemical models LSMs) with eight meteorological variables for the 35-year period from 1979 to 2013. The data set is intended for use in a model intercomparison study, called GTMIP, which is a part of the Japanese-funded Arctic Climate Change Research Project. In order to prepare a set of site-fitted forcing data for LSMs with realistic yet continuous entries (i.e. without missing data), four observational sites across the pan-Arctic region (Fairbanks, Tiksi, Yakutsk, and Kevo) were selected to construct a blended data set using both global reanalysis and observational data. Marked improvements were found in the diurnal cycles of surface air temperature and humidity, wind speed, and precipitation. The data sets and participation in GTMIP are open to the scientific community (doi:10.17592/001.2015093001).
Publisher: Copernicus GmbH
Date: 10-02-2020
Publisher: American Geophysical Union (AGU)
Date: 03-2022
DOI: 10.1029/2021JG006421
Abstract: Spring leaf phenology and its response to climate change have crucial effects on surface albedo, carbon balance, and the water cycle of terrestrial ecosystems. Based on long‐term (period 1963 – 2014) in situ observations of budburst date and leaf unfolding date of more than 300 deciduous woody species from 32 sites across the temperate zone in China, we conducted model‐data comparison of spatial and temporal variations for spring leaf phenology calculated using the phenology modules that were embed into 10 existing terrestrial ecosystem models. Our results suggested that ORganizing Carbon and Hydrology in Dynamic EcosystEms and Spatially Explicit In idual‐Based performed the best in reproducing the spatial patterns of spring leaf phenology, but tended to underestimate the temporal variations in responding to temperature warming, showing low interannual variability (IAV) and temperature sensitivity ( S T ). In contrast, the performances of Vegetation Integrated SImulator for Trace Gases were the best in modeling IAV and S T . BIOME3, Lund‐Potsdam‐Jena model, Joint UK Land Environment Simulator, BioGeochemical Cycles, Community Land Model, Integrated Biosphere Simulator, and Commonwealth Scientific and Industrial Research Organisation Atmosphere Biosphere Land Exchange Model failed to reproduce both the spatial and temporal patterns. Using temperature series (1960 – 2100) form Coupled Model Intercomparison Project Number 6 scenarios to force the 10 phenology modules, our results highlighted large uncertainties in predicting spring leaf phenology changes with the warming climate, and more work is required to deal with the deficiencies of phenology model parameters and algorithms.
Publisher: Copernicus GmbH
Date: 10-02-2020
DOI: 10.5194/BG-2019-491
Abstract: Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent-historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools to make global assessments. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global forest biomass turnover times vary from 12.2 to 23.5 years between models. TBM differences in phenological processes, which control allocation to and turnover rate of leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Twelve model-based hypotheses are identified, along with recommendations for pragmatic steps to test them using existing and novel observations, which would help to reduce both spatial and temporal uncertainty in turnover time. Efforts to resolve uncertainty in turnover time will need to address both mortality and establishment components of forest demography, as well as key drivers of demography such as allocation of carbon to woody versus non-woody biomass growth.
Publisher: Copernicus GmbH
Date: 05-08-2020
Abstract: Abstract. The length of time that carbon remains in forest biomass is one of the largest uncertainties in the global carbon cycle, with both recent historical baselines and future responses to environmental change poorly constrained by available observations. In the absence of large-scale observations, models used for global assessments tend to fall back on simplified assumptions of the turnover rates of biomass and soil carbon pools. In this study, the biomass carbon turnover times calculated by an ensemble of contemporary terrestrial biosphere models (TBMs) are analysed to assess their current capability to accurately estimate biomass carbon turnover times in forests and how these times are anticipated to change in the future. Modelled baseline 1985–2014 global average forest biomass turnover times vary from 12.2 to 23.5 years between TBMs. TBM differences in phenological processes, which control allocation to, and turnover rate of, leaves and fine roots, are as important as tree mortality with regard to explaining the variation in total turnover among TBMs. The different governing mechanisms exhibited by each TBM result in a wide range of plausible turnover time projections for the end of the century. Based on these simulations, it is not possible to draw robust conclusions regarding likely future changes in turnover time, and thus biomass change, for different regions. Both spatial and temporal uncertainty in turnover time are strongly linked to model assumptions concerning plant functional type distributions and their controls. Thirteen model-based hypotheses of controls on turnover time are identified, along with recommendations for pragmatic steps to test them using existing and novel observations. Efforts to resolve uncertainty in turnover time, and thus its impacts on the future evolution of biomass carbon stocks across the world's forests, will need to address both mortality and establishment components of forest demography, as well as allocation of carbon to woody versus non-woody biomass growth.
Location: No location found
No related grants have been discovered for Hisashi Sato.