Using the three-layer variable infiltration capacity （VIC-3L） hydrological model and the successive interpolation approach （SIA） of climate factors, the authors studied the effect of different land cover types on ...Using the three-layer variable infiltration capacity （VIC-3L） hydrological model and the successive interpolation approach （SIA） of climate factors, the authors studied the effect of different land cover types on the surface hydrological cycle. Daily climate data from 1992 to 2001 and remotely-sensed leaf area index （LAI） are used in the model. The model is applied to the Baohe River basin, a subbasin of the Yangtze River basin, China, with an area of 2500 km^2. The vegetation cover types in the Baohe River basin consist mostly of the mixed forest type （-85%）. Comparison of the modeled results with the observed discharge data suggests that： （1） Daily discharges over the period of 1992-2001 simulated with inputs of remotely-sensed land cover data and LAI data can generally produce observed discharge variations, and the modeled annual total discharge agrees with observations with a mean difference of 1.4%. The use of remote sensing images also makes the modeled spatial distributions of evapotranspiration physically meaningful. （2） The relative computing error （RCE） of the annual average discharge is -24.8% when the homogeneous broadleaf deciduous forestry cover is assumed for the watershed. The error is 21.8% when a homogeneous cropland cover is assumed and -14.32% when an REDC （Resource and Environment Database of China） land cover map is used. The error is reduced to 1.4% when a remotely-sensed land cover at 1000-m resolution is used.展开更多
The role of tropical forests in the global carbon budget remains controversial,as carbon emissions from deforestation are highly uncertain.This high uncertainty arises from the use of either fixed forest carbon stock ...The role of tropical forests in the global carbon budget remains controversial,as carbon emissions from deforestation are highly uncertain.This high uncertainty arises from the use of either fixed forest carbon stock density or maps generated from satellite-based optical reflectance with limited sensitivity to biomass to generate accurate estimates of emissions from deforestation.New space missions aiming to accurately map the carbon stock density rely on direct measurements of the spatial structures of forests using lidar and radar.We found that lost forests are special cases,and their spatial structures can be directly measured by combining archived data acquired before and after deforestation by space missions principally aimed at measuring topography.Thus,using biomass mapping,we obtained new estimates of carbon loss from deforestation ahead of forthcoming space missions.Here,using a high-resolution map of forest loss and the synergy of radar and lidar to estimate the aboveground biomass density of forests,we found that deforestation in the 2000s in Latin America,one of the severely deforested regions,mainly occurred in forests with a significantly lower carbon stock density than typical mature forests.展开更多
Comparison and validation of canopy reflectance(CR)models are two important steps to ensure their reliability.Pure forest plantations are an ideal type of forest for validating CR models because of their simple backgr...Comparison and validation of canopy reflectance(CR)models are two important steps to ensure their reliability.Pure forest plantations are an ideal type of forest for validating CR models because of their simple background and the low variance in the crown structures which are usually assumed to be identical in most CR models.A Geometric Optical Model for Forest Plantations(GOFP)was compared using dataset in two radiation transfer model intercomparison exercise(RAMI)stands and validated using in situ dataset of detailed optical and structural data of two forest plantations in the Saihanba Forestry Center,China.The results show that(1)the tree distributions in stands described by the hypergeometric model in GOFP show good consistencies with the dataset in the two RAMI stands and measurements from the two Saihanba forest stands;and(2)the CRs simulated with GOFP are also compared well in the two RAMI stands and validated with measurements collected with unmanned aerial vehicles in the two Saihanba stands.GOFP shows a better consistency with the CR measurements than those from CR models for natual forestsbecause the tree distribution in forest plantations is described more reasonably in GOFP.展开更多
Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among studies.Using 3 microwave(L-and X-band vegetation ...Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among studies.Using 3 microwave(L-and X-band vegetation optical depth[VOD])and 3 optical(normalized difference vegetation index,leaf area index,and tree cover)remote-sensing vegetation products,this study compared the estimated live woody aboveground biomass carbon(AGC)dynamics over China between 2013 and 2019.Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps(mean correlation value R=0.84),followed by L-VOD(R=0.83),which outperform the other VODs.An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019.The performance of the AGC estimation model was good(root mean square error=0.05 Pg C and R^(2)=0.90 with a mean relative uncertainty of 9.8% at pixel scale[0.25°]).Results of the AGC estimation model showed that carbon uptake by the forests in China was about+0.17 Pg C year^(-1) from 2013 to 2019.At the regional level,provinces in southwest China including Guizhou(+22.35 Tg C year^(-1)),Sichuan(+14.49 Tg C year^(-1)),and Hunan(+11.42 Tg C year^(-1))provinces had the highest carbon sink rates during 2013 to 2019.Most of the carbon-sink regions have been afforested recently,implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.展开更多
In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation of the net carbon flux. An optimization scheme is proposed to estimate two key pa...In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation of the net carbon flux. An optimization scheme is proposed to estimate two key parameters （V2max and Q10） by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate V25max and Q10 of the boreal ecosystem productivity simulator （BEPS） to improve its NEP simulation in the boreal North American region. Then, in situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations from BEPS with initial and optimized parameters. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results implicate that it is possible to optimize ecosystem model parameters by different sensitivities of V25max and Q10 during growing and non-growing seasons through atmospheric inversion or data assimilation techniques.展开更多
Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time...Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate（net primary productivity,NPP） modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.展开更多
The widely performed Bayesian synthesis inversion method(BSIM)utilizes prior carbon flux and atmospheric carbon dioxide observations to optimize the unknown flux.The prior flux is usually computed from ecological mode...The widely performed Bayesian synthesis inversion method(BSIM)utilizes prior carbon flux and atmospheric carbon dioxide observations to optimize the unknown flux.The prior flux is usually computed from ecological models with large biases.The BSIM is useful in solving the problem of insufficient data,but it will increase the inaccuracies in the estimates caused by the biased prior flux.In this study,we propose a dual optimization method(DOM)to introduce a set of scaling factors as new state variables to correct for the prior flux according to information on plant functional types.The DOM estimates the scaling factors and carbon flux simultaneously by minimizing the cost function.The statistical properties of the DOM,which compare favorably with the BSIM,are provided in this article.We tested the DOM through simulation experiments which represent a true ecosystem.The results,according to the root mean squared error,show that the DOM has a higher accuracy than the BSIM in flux estimates.展开更多
The Earth’s three poles,the North Pole,South Pole,and Third Pole(i.e.,the Tibetan Plateau and its surroundings),hold the largest amount of fresh water on Earth as glaciers,sea ice,and snow.They are sensitive to clima...The Earth’s three poles,the North Pole,South Pole,and Third Pole(i.e.,the Tibetan Plateau and its surroundings),hold the largest amount of fresh water on Earth as glaciers,sea ice,and snow.They are sensitive to climate change.However,the linkages between climate variations of the three poles,particularly between the South Pole and Third Pole,remain largely unknown.The temperatures at 200 hPa over the three poles are the highest in the summer and are less affected by surface conditions,which could reflect large-scale dynamic linkages.Temperatures at 200 hPa peak the three poles during their respective hemispheric summer and exhibit in-phase variations on interdecadal timescales(10–100 years).The 200 hPa temperatures over the North Pole and South Pole were significantly correlated with the Brewer-Dobson circulation(BDC),which transports stratospheric ozone poleward,heating the air at 200 hPa.Tropopause warming over the Third Pole was found to enhance the poleward BDC,particularly to the South Pole,linking the Third Pole’s climate to the other two poles.Additionally,the Interdecadal Pacific Oscillation(IPO)also exhibits links with the 200 hPa temperatures of the three poles.展开更多
文摘Using the three-layer variable infiltration capacity （VIC-3L） hydrological model and the successive interpolation approach （SIA） of climate factors, the authors studied the effect of different land cover types on the surface hydrological cycle. Daily climate data from 1992 to 2001 and remotely-sensed leaf area index （LAI） are used in the model. The model is applied to the Baohe River basin, a subbasin of the Yangtze River basin, China, with an area of 2500 km^2. The vegetation cover types in the Baohe River basin consist mostly of the mixed forest type （-85%）. Comparison of the modeled results with the observed discharge data suggests that： （1） Daily discharges over the period of 1992-2001 simulated with inputs of remotely-sensed land cover data and LAI data can generally produce observed discharge variations, and the modeled annual total discharge agrees with observations with a mean difference of 1.4%. The use of remote sensing images also makes the modeled spatial distributions of evapotranspiration physically meaningful. （2） The relative computing error （RCE） of the annual average discharge is -24.8% when the homogeneous broadleaf deciduous forestry cover is assumed for the watershed. The error is 21.8% when a homogeneous cropland cover is assumed and -14.32% when an REDC （Resource and Environment Database of China） land cover map is used. The error is reduced to 1.4% when a remotely-sensed land cover at 1000-m resolution is used.
基金National Natural Science Foundation of China(42022009)National Key Research and Development Program of China(2017YFA0603002)+2 种基金National Natural Science Foundation of China(41471311)as well as by partial support from the National Key Research and Development Program of China(2020YFE0200800)National Natural Science Foundation of China(42090013).
文摘The role of tropical forests in the global carbon budget remains controversial,as carbon emissions from deforestation are highly uncertain.This high uncertainty arises from the use of either fixed forest carbon stock density or maps generated from satellite-based optical reflectance with limited sensitivity to biomass to generate accurate estimates of emissions from deforestation.New space missions aiming to accurately map the carbon stock density rely on direct measurements of the spatial structures of forests using lidar and radar.We found that lost forests are special cases,and their spatial structures can be directly measured by combining archived data acquired before and after deforestation by space missions principally aimed at measuring topography.Thus,using biomass mapping,we obtained new estimates of carbon loss from deforestation ahead of forthcoming space missions.Here,using a high-resolution map of forest loss and the synergy of radar and lidar to estimate the aboveground biomass density of forests,we found that deforestation in the 2000s in Latin America,one of the severely deforested regions,mainly occurred in forests with a significantly lower carbon stock density than typical mature forests.
基金funded by the National Natural Science Foundation of China(grant no.41701383,42071392,and 41801234)Anhui Provincial Natural Science Foundation(grant no.1808085QD105)+1 种基金the Fundamental Research Funds for the Central Universities of China(grant no.PA2020GDSK0083)the Fund of Key Laboratory of Information Perception and Systems forPublic Security of MIIT(Nanjing University of Science and Technology)(grant no.202003).
文摘Comparison and validation of canopy reflectance(CR)models are two important steps to ensure their reliability.Pure forest plantations are an ideal type of forest for validating CR models because of their simple background and the low variance in the crown structures which are usually assumed to be identical in most CR models.A Geometric Optical Model for Forest Plantations(GOFP)was compared using dataset in two radiation transfer model intercomparison exercise(RAMI)stands and validated using in situ dataset of detailed optical and structural data of two forest plantations in the Saihanba Forestry Center,China.The results show that(1)the tree distributions in stands described by the hypergeometric model in GOFP show good consistencies with the dataset in the two RAMI stands and measurements from the two Saihanba forest stands;and(2)the CRs simulated with GOFP are also compared well in the two RAMI stands and validated with measurements collected with unmanned aerial vehicles in the two Saihanba stands.GOFP shows a better consistency with the CR measurements than those from CR models for natual forestsbecause the tree distribution in forest plantations is described more reasonably in GOFP.
基金supported by the National Science Fund for Distinguished Young Scholars(41825020)the National Natural Science Foundation of China(42171339)+1 种基金the Postdoctoral Start-Up Project of Southwest University(SWU020016)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA05050200).
文摘Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among studies.Using 3 microwave(L-and X-band vegetation optical depth[VOD])and 3 optical(normalized difference vegetation index,leaf area index,and tree cover)remote-sensing vegetation products,this study compared the estimated live woody aboveground biomass carbon(AGC)dynamics over China between 2013 and 2019.Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps(mean correlation value R=0.84),followed by L-VOD(R=0.83),which outperform the other VODs.An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019.The performance of the AGC estimation model was good(root mean square error=0.05 Pg C and R^(2)=0.90 with a mean relative uncertainty of 9.8% at pixel scale[0.25°]).Results of the AGC estimation model showed that carbon uptake by the forests in China was about+0.17 Pg C year^(-1) from 2013 to 2019.At the regional level,provinces in southwest China including Guizhou(+22.35 Tg C year^(-1)),Sichuan(+14.49 Tg C year^(-1)),and Hunan(+11.42 Tg C year^(-1))provinces had the highest carbon sink rates during 2013 to 2019.Most of the carbon-sink regions have been afforested recently,implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.
基金supported by the National Basic Research Program of China(2010CB950703)the National Natural Science Foundation of China(41571338)
文摘In this study, we explore the feasibility of optimizing ecosystem photosynthetic and respiratory parameters from the seasonal variation of the net carbon flux. An optimization scheme is proposed to estimate two key parameters （V2max and Q10） by exploiting the seasonal variation in the net ecosystem carbon flux retrieved by an atmospheric inversion system. This scheme is implemented to estimate V25max and Q10 of the boreal ecosystem productivity simulator （BEPS） to improve its NEP simulation in the boreal North American region. Then, in situ NEE observations at six eddy covariance sites are used to evaluate the NEE simulations from BEPS with initial and optimized parameters. The results show that the performance of the optimized BEPS is superior to that of the BEPS with the default parameter values. These results implicate that it is possible to optimize ecosystem model parameters by different sensitivities of V25max and Q10 during growing and non-growing seasons through atmospheric inversion or data assimilation techniques.
文摘Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate（net primary productivity,NPP） modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.
基金supported by the Key Global Change Program of the Chinese Ministry of Science and Technology(2010 CB950703)
文摘The widely performed Bayesian synthesis inversion method(BSIM)utilizes prior carbon flux and atmospheric carbon dioxide observations to optimize the unknown flux.The prior flux is usually computed from ecological models with large biases.The BSIM is useful in solving the problem of insufficient data,but it will increase the inaccuracies in the estimates caused by the biased prior flux.In this study,we propose a dual optimization method(DOM)to introduce a set of scaling factors as new state variables to correct for the prior flux according to information on plant functional types.The DOM estimates the scaling factors and carbon flux simultaneously by minimizing the cost function.The statistical properties of the DOM,which compare favorably with the BSIM,are provided in this article.We tested the DOM through simulation experiments which represent a true ecosystem.The results,according to the root mean squared error,show that the DOM has a higher accuracy than the BSIM in flux estimates.
基金supported by the National Natural Science Foundation of China(Grant Nos.41822101,41888101,41971022&41772180)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant Nos.XDB26020000 and XDA20060401)+2 种基金the State Administration of Foreign Experts Affairs of China(Grant No.GS20190157002)fellowship for the National Youth Talent Support Program of China(Ten Thousand People Plan)Youth Talent Program of Fujian Province,and the Innovation Team Project(Grant No.IRTL1705)。
文摘The Earth’s three poles,the North Pole,South Pole,and Third Pole(i.e.,the Tibetan Plateau and its surroundings),hold the largest amount of fresh water on Earth as glaciers,sea ice,and snow.They are sensitive to climate change.However,the linkages between climate variations of the three poles,particularly between the South Pole and Third Pole,remain largely unknown.The temperatures at 200 hPa over the three poles are the highest in the summer and are less affected by surface conditions,which could reflect large-scale dynamic linkages.Temperatures at 200 hPa peak the three poles during their respective hemispheric summer and exhibit in-phase variations on interdecadal timescales(10–100 years).The 200 hPa temperatures over the North Pole and South Pole were significantly correlated with the Brewer-Dobson circulation(BDC),which transports stratospheric ozone poleward,heating the air at 200 hPa.Tropopause warming over the Third Pole was found to enhance the poleward BDC,particularly to the South Pole,linking the Third Pole’s climate to the other two poles.Additionally,the Interdecadal Pacific Oscillation(IPO)also exhibits links with the 200 hPa temperatures of the three poles.
