[1] We analyze simulated sea ice changes in eight different earth system models that have conduct... more [1] We analyze simulated sea ice changes in eight different earth system models that have conducted experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP). The simulated response of balancing abrupt quadrupling of CO2 (abrupt4xCO2) with reduced shortwave radiation successfully moderates annually averaged Arctic temperature rise to about 1 °C, with modest changes in seasonal sea ice cycle compared with the pre-industrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns, but much less in winter and spring seasons. However there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. In summer and autumn, the models consistently simulate less sea ice relative to pre-industrial simulations in the Beaufort, Chukchi, East Siberian and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Se...
ABSTRACT [1] We analyze simulated sea ice changes in eight different earth system models that hav... more ABSTRACT [1] We analyze simulated sea ice changes in eight different earth system models that have conducted experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP). The simulated response of balancing abrupt quadrupling of CO2 (abrupt4xCO2) with reduced shortwave radiation successfully moderates annually averaged Arctic temperature rise to about 1 °C, with modest changes in seasonal sea ice cycle compared with the pre-industrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns, but much less in winter and spring seasons. However there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. In summer and autumn, the models consistently simulate less sea ice relative to pre-industrial simulations in the Beaufort, Chukchi, East Siberian and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Sea ice extent increases in the Greenland Sea, particularly in winter and spring, and is to some extent associated with changed sea ice drift. Decreased sea ice cover in winter and spring in the Barents Sea is associated with increased cyclonic activity entering this area under G1. In comparison, the abrupt4xCO2 experiment shows almost total sea ice loss in September and strong correlation with regional temperatures in all seasons consistent with open ocean conditions. The tropospheric circulation displays a Pacific North America (PNA) pattern-like anomaly with negative phase in G1-piControl and positive phase under abrupt4xCO2-piControl.
2010 4th International Conference on Bioinformatics and Biomedical Engineering, 2010
Abstract We evaluate the ability of the regional chemistry/aerosol climate model REMOTE to simula... more Abstract We evaluate the ability of the regional chemistry/aerosol climate model REMOTE to simulate Asian dust transport over China in response to changing Asian monsoon conditions. Applied to years of different monsoon strength, model results are compared to ...
ABSTRACT As an important indicator of cropping intensity, Cropping Index (CI) is defined as the n... more ABSTRACT As an important indicator of cropping intensity, Cropping Index (CI) is defined as the number of peaks in the Vegetation Index (VI) time-series curve in a year. The existing CI mapping algorithms (e.g., the cross-fitting and the second order difference algorithm) are vulnerable to noise contained in the VI time series and need a priori knowledge and some extra constraints which could not be directly derived from the VI time-series data. In this paper, a shape-matching method is developed which can map CI directly from the preprocessed VI time-series data without the de-noising processes. This shape-matching method utilizes a decision-making process to find out the true peaks in the VI time-series curve based on a rank order mathematical morphology algorithm. The processing procedure involves five steps: (a) determination of the temporal moving window size, (b) detection of local maximum/minimum points, (c) exclusion of false maximum/minimum points, (d) determination of the threshold for the minimum growth amplitude, and (e) mapping of CI. This shape-matching method only needs two input parameters, the temporal moving window size and the threshold for the minimum growth amplitude, which can be both directly derived from the VI time-series data with some selected test pixels. Moreover, the response of the shape-matching method is relatively insensitive to the exact values of its design parameters, making it more flexible and effective in adapting to other regions. This new method is applied to map the CIs in Jiangsu Province, China, in 2010, based on the Enhanced Vegetation Index (EVI) time-series data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) product. The overall CI mapping accuracy for the shape-matching method is 80 percent, which is much higher than the CI mapping accuracy of 60 percent for the second order difference algorithm. This shape-matching method can be further applied to other regions with a grid-search for its optimal parameters using some test pixels.
Journal of Geophysical Research D: Atmospheres, 2013
ABSTRACT [1] Numerical model simulations provide a useful platform for investigating the interact... more ABSTRACT [1] Numerical model simulations provide a useful platform for investigating the interactions between the atmospheric dust cycle and environmental change in Asia. However, model validation is still limited by the scarcity of ground observations of past terrestrial dust deposition fluxes. Here we apply a regional atmosphere-chemistry/aerosol climate model to simulate Asian dust emissions, transport, and deposition over East Asia during the years 1996–1998 and compare the present-day deposition fluxes and dominant dust sources obtained from the numerical simulations to those measured in a high-resolution Holocene palaeodust peat record on the eastern Qinghai-Tibetan Plateau. The model was found to produce reasonable dust emission fluxes from the Chinese dust sources, with average annual emissions of 179 Mt y−1, and successfully reproduced both the dominant dust sources and average deposition fluxes to the peat core, with modeled and observed fluxes of 6.1 g m−2 y−1. Sensitivity tests show that modeled dust fluxes are sensitive to the parameterization of erodible surfaces, and future development of the regional model to simulate dust emissions in Asia should include an improved scheme for the soil surface properties. The results presented here suggest that the regional model holds the potential to study past and present dust cycles in Asia but evidence the need for both further refinement of the model's dust parameterizations in this region and more high-resolution terrestrial validation data sets such as peat archives. This study demonstrates how present-day simulations, for which reanalysis data is available as boundary conditions, are useful tools to explore the relationship between the dust cycle and environmental change during the Holocene.
[1] We analyze simulated sea ice changes in eight different earth system models that have conduct... more [1] We analyze simulated sea ice changes in eight different earth system models that have conducted experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP). The simulated response of balancing abrupt quadrupling of CO2 (abrupt4xCO2) with reduced shortwave radiation successfully moderates annually averaged Arctic temperature rise to about 1 °C, with modest changes in seasonal sea ice cycle compared with the pre-industrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns, but much less in winter and spring seasons. However there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. In summer and autumn, the models consistently simulate less sea ice relative to pre-industrial simulations in the Beaufort, Chukchi, East Siberian and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Se...
ABSTRACT [1] We analyze simulated sea ice changes in eight different earth system models that hav... more ABSTRACT [1] We analyze simulated sea ice changes in eight different earth system models that have conducted experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP). The simulated response of balancing abrupt quadrupling of CO2 (abrupt4xCO2) with reduced shortwave radiation successfully moderates annually averaged Arctic temperature rise to about 1 °C, with modest changes in seasonal sea ice cycle compared with the pre-industrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns, but much less in winter and spring seasons. However there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. In summer and autumn, the models consistently simulate less sea ice relative to pre-industrial simulations in the Beaufort, Chukchi, East Siberian and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Sea ice extent increases in the Greenland Sea, particularly in winter and spring, and is to some extent associated with changed sea ice drift. Decreased sea ice cover in winter and spring in the Barents Sea is associated with increased cyclonic activity entering this area under G1. In comparison, the abrupt4xCO2 experiment shows almost total sea ice loss in September and strong correlation with regional temperatures in all seasons consistent with open ocean conditions. The tropospheric circulation displays a Pacific North America (PNA) pattern-like anomaly with negative phase in G1-piControl and positive phase under abrupt4xCO2-piControl.
2010 4th International Conference on Bioinformatics and Biomedical Engineering, 2010
Abstract We evaluate the ability of the regional chemistry/aerosol climate model REMOTE to simula... more Abstract We evaluate the ability of the regional chemistry/aerosol climate model REMOTE to simulate Asian dust transport over China in response to changing Asian monsoon conditions. Applied to years of different monsoon strength, model results are compared to ...
ABSTRACT As an important indicator of cropping intensity, Cropping Index (CI) is defined as the n... more ABSTRACT As an important indicator of cropping intensity, Cropping Index (CI) is defined as the number of peaks in the Vegetation Index (VI) time-series curve in a year. The existing CI mapping algorithms (e.g., the cross-fitting and the second order difference algorithm) are vulnerable to noise contained in the VI time series and need a priori knowledge and some extra constraints which could not be directly derived from the VI time-series data. In this paper, a shape-matching method is developed which can map CI directly from the preprocessed VI time-series data without the de-noising processes. This shape-matching method utilizes a decision-making process to find out the true peaks in the VI time-series curve based on a rank order mathematical morphology algorithm. The processing procedure involves five steps: (a) determination of the temporal moving window size, (b) detection of local maximum/minimum points, (c) exclusion of false maximum/minimum points, (d) determination of the threshold for the minimum growth amplitude, and (e) mapping of CI. This shape-matching method only needs two input parameters, the temporal moving window size and the threshold for the minimum growth amplitude, which can be both directly derived from the VI time-series data with some selected test pixels. Moreover, the response of the shape-matching method is relatively insensitive to the exact values of its design parameters, making it more flexible and effective in adapting to other regions. This new method is applied to map the CIs in Jiangsu Province, China, in 2010, based on the Enhanced Vegetation Index (EVI) time-series data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) product. The overall CI mapping accuracy for the shape-matching method is 80 percent, which is much higher than the CI mapping accuracy of 60 percent for the second order difference algorithm. This shape-matching method can be further applied to other regions with a grid-search for its optimal parameters using some test pixels.
Journal of Geophysical Research D: Atmospheres, 2013
ABSTRACT [1] Numerical model simulations provide a useful platform for investigating the interact... more ABSTRACT [1] Numerical model simulations provide a useful platform for investigating the interactions between the atmospheric dust cycle and environmental change in Asia. However, model validation is still limited by the scarcity of ground observations of past terrestrial dust deposition fluxes. Here we apply a regional atmosphere-chemistry/aerosol climate model to simulate Asian dust emissions, transport, and deposition over East Asia during the years 1996–1998 and compare the present-day deposition fluxes and dominant dust sources obtained from the numerical simulations to those measured in a high-resolution Holocene palaeodust peat record on the eastern Qinghai-Tibetan Plateau. The model was found to produce reasonable dust emission fluxes from the Chinese dust sources, with average annual emissions of 179 Mt y−1, and successfully reproduced both the dominant dust sources and average deposition fluxes to the peat core, with modeled and observed fluxes of 6.1 g m−2 y−1. Sensitivity tests show that modeled dust fluxes are sensitive to the parameterization of erodible surfaces, and future development of the regional model to simulate dust emissions in Asia should include an improved scheme for the soil surface properties. The results presented here suggest that the regional model holds the potential to study past and present dust cycles in Asia but evidence the need for both further refinement of the model's dust parameterizations in this region and more high-resolution terrestrial validation data sets such as peat archives. This study demonstrates how present-day simulations, for which reanalysis data is available as boundary conditions, are useful tools to explore the relationship between the dust cycle and environmental change during the Holocene.
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