81 research outputs found
Controls on winter ecosystem respiration in temperate and boreal ecosystems
Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal patterns of winter ecosystem respiration (Reco) of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data from 57 ecosystem sites ranging from ~35° N to ~70° N. Deciduous forests were characterized by the highest winter Reco rates (0.90 ± 0.39 g C m-2 d-1), when winter is defined as the period during which daily air temperature remains below 0 °C. By contrast, arctic wetlands had the lowest winter Reco rates (0.02 ± 0.02 g C m-2 d-1). Mixed forests, evergreen needle-leaved forests, grasslands, croplands and boreal wetlands were characterized by intermediate winter Reco rates (g C m-2 d-1) of 0.70(±0.33), 0.60(±0.38), 0.62(±0.43), 0.49(±0.22) and 0.27(±0.08), respectively. Our cross site analysis showed that winter air (Tair) and soil (Tsoil) temperature played a dominating role in determining the spatial patterns of winter Reco in both forest and managed ecosystems (grasslands and croplands). Besides temperature, the seasonal amplitude of the leaf area index (LAI), inferred from satellite observation, or growing season gross primary productivity, which we use here as a proxy for the amount of recent carbon available for Reco in the subsequent winter, played a marginal role in winter CO2 emissions from forest ecosystems. We found that winter Reco sensitivity to temperature variation across space (QS) was higher than the one over time (interannual, QT). This can be expected because QS not only accounts for climate gradients across sites but also for (positively correlated) the spatial variability of substrate quantity. Thus, if the models estimate future warming impacts on Reco based on QS rather than QT, this could overestimate the impact of temperature change
Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data
Soil moisture is a key variable of land surface hydrology, and its correct
representation in land surface models is crucial for local to global climate
predictions. The errors may come from the model itself (structure and
parameterization) but also from the meteorological forcing used. In order to
separate the two source of errors, four atmospheric forcing datasets, GSWP3
(Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological
Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental
Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim
reanalysis data), were used to drive simulations in China by the land surface
model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms:
aMeliorated Interactions between Carbon and Temperature). Simulated soil
moisture was compared with in situ and satellite datasets at different
spatial and temporal scales in order to (1)Â estimate the ability of
ORCHIDEE-MICT to represent soil moisture dynamics in China; (2)Â demonstrate
the most suitable forcing dataset for further hydrological studies in Yangtze
and Yellow River basins; and (3)Â understand the discrepancies of simulated
soil moisture among simulations. Results showed that ORCHIDEE-MICT can
simulate reasonable soil moisture dynamics in China, but the quality varies
with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows
the best performance according to the root mean square error (RMSE) and
correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI
are good choices for further hydrological studies in the two catchments. The
mismatch between simulated and observed soil moisture is mainly explained by
the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT
should be revised for further simulations in China. Underestimated soil
moisture in the North China Plain demonstrates possible significant impacts
of human activities like irrigation on soil moisture variation, which was not
considered in our simulations. Finally, the discrepancies of meteorological
variables and simulated soil moisture among the four simulations are
analyzed. The result shows that the discrepancy of soil moisture is mainly
explained by differences in precipitation frequency and air humidity rather
than differences in precipitation amount.</p
Controls on winter ecosystem respiration in temperate and boreal ecosystems
Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability
to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal patterns of winter ecosystem respiration (Reco) of northern ecosystems are poorly understood. For this reason, we analyzed eddy covariance flux data from 57
ecosystem sites ranging from 35 N to 70 N. Deciduous forests were characterized by the highest winter Reco rates (0.90±0.39 gCmâ2 dâ1), when winter is defined as the period during which daily air temperature remains below 0 °C. By contrast, arctic wetlands had the lowest winter Reco rates (0.02±0.02 gCmâ2 dâ1). Mixed forests, evergreen
needle-leaved forests, grasslands, croplands and boreal wetlands were characterized by intermediate winter Reco rates (g Cmâ2 dâ1) of 0.70(±0.33), 0.60(±0.38), 0.62(±0.43),
0.49(±0.22) and 0.27(±0.08), respectively. Our cross site analysis showed that winter air (Tair) and soil (Tsoil) temperature
played a dominating role in determining the spatial patterns of winter Reco in both forest and managed ecosystems (grasslands and croplands). Besides temperature, the seasonal amplitude of the leaf area index (LAI), inferred from satellite observation, or growing season gross primary productivity,
which we use here as a proxy for the amount of recent carbon available for Reco in the subsequent winter, played a marginal role in winter CO2 emissions from forest ecosystems. We found that winter Reco sensitivity to temperature variation across space (QS) was higher than the one over time (interannual, QT ). This can be expected because QS not only accounts for climate gradients across sites but also for (positively correlated) the spatial variability of substrate quantity. Thus, if the models estimate future warming impacts on Reco based on QS rather than QT , this could overestimate
the impact of temperature changes
Dynamic SVAT model calibration process based on thermal infrared brightness temperature data.
Analytical parameterization of canopy directional emissivity and directional radiance in the thermal infrared. Application on the retrieval of soil and foliage temperatures using two directional measurements
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