The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used...The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used in various studies. However, the nearly one-year gap between GRACE and GRACE-FO has affected our ability to obtain continuous time-variable gravity data. In this study, we use the Singular Spectrum Analysis (SSA) method to fill the nearly one-year gap between the GRACE and GRACE-FO missions, as well as the gaps within the GRACE mission itself, to generate a continuous and complete mascon product from April 2002 to December 2022. These products are evaluated at the basin scale in Greenland, Antarctica, and ten river basins worldwide, as well as across oceans. The results show that our filled data can effectively recover seasonal and interannual signals and exhibit good consistency with previous reconstructions. The products provided in this study will benefit GRACE applications related to oceans, glaciers, and terrestrial water storage.展开更多
The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. ...The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.展开更多
Background: Tropical forests play a fundamental role in the provision of diverse ecosystem services, such as biodiversity,climate and air quality regulation, freshwater provision, carbon cycling, agricultural support ...Background: Tropical forests play a fundamental role in the provision of diverse ecosystem services, such as biodiversity,climate and air quality regulation, freshwater provision, carbon cycling, agricultural support and culture. To understand the role of forests in the carbon balance, aboveground biomass(AGB) estimates are needed. Given the importance of Brazilian tropical forests, there is an urgent need to improve AGB estimates to support the Brazilian commitments under the United Nations Framework Convention on Climate Change(UNFCCC). Many AGB maps and datasets exist, varying in availability, scale and coverage. Thus, stakeholders, policy makers and scientists must decide which AGB product, dataset or combination of data to use for their particular goals. In this study, we assessed the gaps in the spatial AGB data across the Brazilian Amazon forests not only to orient the decision makers about the data that are currently available but also to provide a guide for future initiatives.Results: We obtained a map of the gaps in the forest AGB spatial data for the Brazilian Amazon using statistics and differences between AGB maps and a spatial multicriteria evaluation that considered the current AGB datasets. The AGB spatial data gap map represents areas with good coverage of AGB data and, consequently, the main gaps or priority areas where further biomass assessments should focus, including the northeast of Amazon State, Amapá and northeast of Pará. Additional y, by quantifying the variability in both the AGB maps and field data on multiple environmental factors,we provide valuable elements for understanding the current AGB data as a function of climate, soil, vegetation and geomorphology.Conclusions: The map of AGB data gaps could become a useful tool for policy makers and different stakeholders working on National Communications, Reducing Emissions from Deforestation and Degradation(REDD+), or carbon emissions modeling to prioritize places to implement further AGB assessments. Only 0.2% of the Amazon biome forest is sampled, and extensive effort is necessary to improve what we know about the tropical forest.展开更多
Taking the relevant data of 27 provinces in China during 2013 and 2017 as samples,this paper firstly measured the agricultural total factor productivity( TFP) using Malmquist index method. Then,it built the panel data...Taking the relevant data of 27 provinces in China during 2013 and 2017 as samples,this paper firstly measured the agricultural total factor productivity( TFP) using Malmquist index method. Then,it built the panel data model,and empirically tested the impacts of agricultural TFP on the income gap between urban and rural residents. The results show that the improvement in agricultural TFP can promote the narrowing of the income gap between urban and rural residents,and the factors such as urbanization level and industrial structure also have significant impacts on the income gap between urban and rural residents. On the basis of these,it came up with recommendations,including increasing agricultural human capital investment and establishing agricultural production research institutions.展开更多
基金the National Natural Science Foundation of China(E3ER0402A2,E421040401)the University of Chinese Academy of Sciences Research Start-up Grant(110400M003)the Fundamental Research Funds for the Central Universities(E2ET0411X2).
文摘The primary mission of the Gravity Recovery and Climate Experiment (GRACE) satellite and its successor,GRACE Follow-On (GRACE-FO), is to provide time-variable gravity fields, and its observations have been widely used in various studies. However, the nearly one-year gap between GRACE and GRACE-FO has affected our ability to obtain continuous time-variable gravity data. In this study, we use the Singular Spectrum Analysis (SSA) method to fill the nearly one-year gap between the GRACE and GRACE-FO missions, as well as the gaps within the GRACE mission itself, to generate a continuous and complete mascon product from April 2002 to December 2022. These products are evaluated at the basin scale in Greenland, Antarctica, and ten river basins worldwide, as well as across oceans. The results show that our filled data can effectively recover seasonal and interannual signals and exhibit good consistency with previous reconstructions. The products provided in this study will benefit GRACE applications related to oceans, glaciers, and terrestrial water storage.
文摘The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.
基金part of the Sao Paulo Research Foundation (FAPESP) Grant No.2013/20616–6 and 2018/18493–7the project LiDAR Remote Sensing of Brazilian Amazon Forests:Analysis of Forest Biomass,Forest Degradation,and Secondary Regrowth funded by the USAID Prime Award Number AID-OAA-A-11-00012。
文摘Background: Tropical forests play a fundamental role in the provision of diverse ecosystem services, such as biodiversity,climate and air quality regulation, freshwater provision, carbon cycling, agricultural support and culture. To understand the role of forests in the carbon balance, aboveground biomass(AGB) estimates are needed. Given the importance of Brazilian tropical forests, there is an urgent need to improve AGB estimates to support the Brazilian commitments under the United Nations Framework Convention on Climate Change(UNFCCC). Many AGB maps and datasets exist, varying in availability, scale and coverage. Thus, stakeholders, policy makers and scientists must decide which AGB product, dataset or combination of data to use for their particular goals. In this study, we assessed the gaps in the spatial AGB data across the Brazilian Amazon forests not only to orient the decision makers about the data that are currently available but also to provide a guide for future initiatives.Results: We obtained a map of the gaps in the forest AGB spatial data for the Brazilian Amazon using statistics and differences between AGB maps and a spatial multicriteria evaluation that considered the current AGB datasets. The AGB spatial data gap map represents areas with good coverage of AGB data and, consequently, the main gaps or priority areas where further biomass assessments should focus, including the northeast of Amazon State, Amapá and northeast of Pará. Additional y, by quantifying the variability in both the AGB maps and field data on multiple environmental factors,we provide valuable elements for understanding the current AGB data as a function of climate, soil, vegetation and geomorphology.Conclusions: The map of AGB data gaps could become a useful tool for policy makers and different stakeholders working on National Communications, Reducing Emissions from Deforestation and Degradation(REDD+), or carbon emissions modeling to prioritize places to implement further AGB assessments. Only 0.2% of the Amazon biome forest is sampled, and extensive effort is necessary to improve what we know about the tropical forest.
文摘Taking the relevant data of 27 provinces in China during 2013 and 2017 as samples,this paper firstly measured the agricultural total factor productivity( TFP) using Malmquist index method. Then,it built the panel data model,and empirically tested the impacts of agricultural TFP on the income gap between urban and rural residents. The results show that the improvement in agricultural TFP can promote the narrowing of the income gap between urban and rural residents,and the factors such as urbanization level and industrial structure also have significant impacts on the income gap between urban and rural residents. On the basis of these,it came up with recommendations,including increasing agricultural human capital investment and establishing agricultural production research institutions.
