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  • 2020-2024  (2)
  • Physics  (2)
  • UA 4548  (2)
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  • 2020-2024  (2)
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  • Physics  (2)
RVK
  • UA 4548  (2)
  • 1
    Online Resource
    Online Resource
    American Meteorological Society ; 2022
    In:  Journal of Climate Vol. 35, No. 23 ( 2022-12-01), p. 7833-7852
    In: Journal of Climate, American Meteorological Society, Vol. 35, No. 23 ( 2022-12-01), p. 7833-7852
    Abstract: Afforestation can impact surface temperature through local and nonlocal biophysical effects. However, the local and nonlocal effects of afforestation in China have rarely been explicitly investigated. In this study, we separate the local and nonlocal effects of idealized afforestation in China based on a checkerboard method and the regional Weather Research and Forecasting (WRF) Model. Two checkerboard pattern–like afforestation simulations (AFF1/4 and AFF3/4) with regularly spaced afforested and unaltered grid cells are performed; afforestation is implemented in one out of every four grid cells in AFF1/4 and in three out of every four grid cells in AFF3/4. The mechanisms for the local and nonlocal effects are examined through the decomposition of the surface energy balance. The results show that the local effects dominate surface temperature responses to afforestation in China, with a cooling effect of approximately −1.00°C for AFF1/4 and AFF3/4. In contrast, the nonlocal effects warm the land surface by 0.14°C for AFF1/4 and 0.41°C for AFF3/4. The local cooling effects mainly result from 1) enhanced sensible and latent heat fluxes and 2) decreases in downward shortwave radiation due to increased low cloud cover fractions. The nonlocal warming effects mainly result from atmospheric feedbacks, including 1) increases in downward shortwave radiation due to decreased low cloud cover fractions and 2) increases in downward longwave radiation due to increased middle and high cloud cover fractions. This study highlights that, despite the unexpected nonlocal warming effect, afforestation in China still has great potential in mitigating climate warming through biophysical processes.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    American Meteorological Society ; 2022
    In:  Journal of Climate Vol. 35, No. 11 ( 2022-06-01), p. 3293-3311
    In: Journal of Climate, American Meteorological Society, Vol. 35, No. 11 ( 2022-06-01), p. 3293-3311
    Abstract: Deforestation can impact precipitation through biophysical processes and such effects are commonly examined by models. However, previous studies mostly conduct deforestation experiments with a single model and the simulated precipitation responses to deforestation diverge across studies. In this study, 11 Earth system models are used to robustly examine the biophysical impacts of deforestation on precipitation, precipitation extremes, and the seasonal pattern of the rainy season through a comparison of a control simulation and an idealized global deforestation simulation with clearings of 20 million km 2 of forests. The multimodel mean suggests decreased precipitation, reduced frequency and intensity of heavy precipitation, and shortened duration of rainy seasons over deforested areas. The deforestation effects can even propagate to some regions that are remote from deforested areas (e.g., the tropical and subtropical oceans and the Arctic Ocean). Nevertheless, the 11 models do not fully agree on the precipitation changes almost everywhere. In general, the models exhibit higher consistency over the deforested areas and a few regions outside the deforested areas (e.g., the subtropical oceans) but lower consistency over other regions. Such intermodel spread mostly results from divergent responses of evapotranspiration and atmospheric moisture convergence to deforestation across the models. One of the models that has multiple simulation members also reveals considerable spread of the precipitation responses to deforestation across the members due to internal model variability. This study highlights the necessity of robustly examining precipitation responses to deforestation based on multiple models and each model with multiple simulation members.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    RVK:
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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