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| 1 | Simulating Net Carbon Budget of Forest Ecosystems and Its Response to Climate Change in Northeastern China Using Improved FORCCHN显示文摘As dominant biomes,forests play an important and indispensable role in adjusting the global carbon balance under climate change.Therefore,there are scientific and political implications in investigating the carbon budget of forest ecosystems and its response to climate change.Here we synthesized the most recent research progresses on the carbon cycle in terrestrial ecosystems,and applied an individual-based forest ecosystem carbon budget model for China(FORCCHN) to simulate the dynamics of the carbon fluxes of forest ecosystems in the northeastern China.The FORCCHN model was further improved and applied through adding variables and modules of precipitation(rainfall and snowfall) interception by tree crown,understory plants and litter.The results showed that the optimized FORCCHN model had a good performance in simulating the carbon budget of forest ecosystems in the northeastern China.From 1981 to 2002,the forests played a positive role in absorbing carbon dioxide.However,the capability of forest carbon sequestration had been gradually declining during the the same period.As for the average spatial distri-bution of net carbon budget,a majority of the regions were carbon sinks.Several scattered areas in the Heilongjiang Province and the Liaoning Province were identified as carbon sources.The net carbon budget was apparently more sensitive to an increase of air temperature than change of precipitation. | ZHAO Junfang YAN Xiaodong JIA Gensuo | 2012 | Chinese Geographical Science2012，22，1： | 6 |
| 2 | Satellite-Based Estimation of Daily Average Net Radiation under Clear-Sky Conditions显示文摘Daily average net radiation(DANR) is an important variable for estimating evapotranspiration from satellite data at regional scales, and is used for atmospheric and hydrologic modeling, as well as ecosystem management. A scheme is proposed to estimate the DANR over large heterogeneous areas under clear-sky conditions using only remotely sensed data.The method was designed to overcome the dependence of DANR estimates on ground data, and to map spatially consistent and reasonably distributed DANR, by using various land and atmospheric data products retrieved from MODIS(Moderate Resolution Imaging Spectroradiometer) data. An improved sinusoidal model was used to retrieve the diurnal variations of downward shortwave radiation using a single instantaneous value from satellites. The downward shortwave component of DANR was directly obtained from this instantaneous value, and the upward shortwave component was estimated using satellite-derived albedo products. Four observations of air temperature from MOD07 L2 and MYD07 L2 data products were used to derive the downward longwave component of DANR, while the upward longwave component was estimated using the land surface temperature(LST) and the surface emissivity from MOD11 L2. Compared to in situ observations at the cropland and grassland sites located in Tongyu, northern China, the root mean square error(RMSE) of DANR estimated for both sites under clear-sky conditions was 37 W m-2and 40 W m-2, respectively. The errors in estimation of DANR were comparable to those from previous satellite-based methods. Our estimates can be used for studying the surface radiation balance and evapotranspiration. | HOU Jiangtao JIA Gensuo ZHAO Tianbao WANG Hesong TANG Bohui | 2014 | Advances in Atmospheric Sciences2014，31，3： | 5 |
| 3 | The role of big Earth data in understanding climate change显示文摘Climate-related changes have already been observed at various spatial and temporal scales,along with frequent extreme climate events and emerging issues in great complexity.Meanwhile,the impacts of climate change are expected to become increasingly more severe for more people and places as the amount of warming increases.However,great challenges and uncertainties exist in understanding climate change and its complex impacts,largely due to the limited availability and compatibility of large-scale data. | Gensuo Jia | 2020 | Big Earth Data2020，4，2： | 2 |
| 4 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 5 | Assessing spatial patterns of forest fuel using AVIRIS data显示文摘 | JIA Gensuo BURKE I C ALEXANDER F | 2006 | Remote Sensing of Environment2006，102，： | 1 |
| 6 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 7 | Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model显示文摘Urban heat island(UHI),driving by urbanization,plays an important role in urban sustainability under climate change.However,the quantification of UHI’s response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods.This study proposed a framework to quantify the response of surface UHI(SUHI)to urban expansion using the annual temperate cycle model.We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat.We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism.Spatially,the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas.Temporally,the increase in SUHI under urban expansion was more significant in daytime compare to nighttime.We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas.Additionally,urban greening led to the decrease in summer daytime SHUI in central urban areas.These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion,providing a scientific basis for prediction and mitigation of UHI. | Huidong Li Yuyu Zhou Gensuo Jia Kaiguang Zhao Jinwei Dong | 2022 | Geoscience Frontiers2022，13，1： | 1 |
| 8 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 9 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 10 | Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data 显示文摘 | Zhang Anzhi Jia Gensuo | 2013 | Remote Sensing of Environment2013，134，： | 1 |
| 11 | Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data显示文摘 | Anzhi Zhang Gensuo Jia | 2013 | Remote Sensing of Environment2013，，： | 1 |
| 12 | Visibility trends in the Yangtze River Delta of China during 1981--2005显示文摘 | Gao Lina Jia Gensuo Zhang Renjian | 1981 | Journal of Air and Waste Management Association1981，，： | 1 |
| 13 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 14 | Circumpolar Arctic Tundra Vegetation Change Is Linked to Sea Ice Decline显示文摘 | Bhatt+ Donald A. Walker # Martha K. Raynolds # Josefino C. Comiso @ Howard E. Epstein & Gensuo Jia Uma S. Walker Donald A Raynolds Martha K Comiso Josefino C Epstein Howard E Jia Gensuo Gens ++ Jorge E. Pinzon ## Compton J. Tucker ## Craig E. Tweedi | 2010 | Earth Interactions2010，，8： | 1 |
| 15 | A global terrestrial ecosystem respiration dataset(2001-2010)estimated with MODIS land surface temperature and vegetation indices显示文摘This paper describes how a validated semi-empirical,but physiologically based,remote sensing model-Ensemble_all-was upscaled using MODIS land surface temperature data(MOD11C2),enhanced vegetation indices(MOD13C1)and land-cover data(MCD12C1)to produce a global terrestrial ecosystem respiration data set(Reco)for January 2001-December 2010.The temporal resolution of this data set is 1 month,the spatial resolution is 0.05°,and the range is from 55°S to 65°N and 180°W to 180°E(crop and natural vegetation mosaic is not included).After crossvalidating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model,a LPJ_S1 process model and a machine learning method model,we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world.This data set can be found at http://gffzze4f4599d7a764a8fhufk6ckqwk6bu6b6w.ffgz.tsg.suse.edu.cn/10.11922/sciencedb.934. | Jinlong Ai Shuyuan Xiao Hui Feng Huan Wang Gensuo Jia Yonghong Hu | 2020 | Big Earth Data2020，4，2： | 1 |
| 16 | Understanding the spring phenology of Arctic tundra using multiple satellite data products and ground observations显示文摘The Arctic is highly sensitive to climate change,and the rise in its near-surface air temperatures has been almost twice the global average.The increased growth of the Arctic tundra and its changing seasonality have been observed,largely in response to the impacts of climate change.In this study,we investigated the temporal and spatial variations of the start of the growing season(SOS)using various remote sensing indices,including Normalized Difference Vegetation Index,Normalized Difference Water Index,and Normalized Difference Snow Index from 2000 to 2018 in Arctic tundra regions.The SOS was derived at 29 sites from ground observations,including CO2 flux data,phenological images,and field records that were used to validate the SOS from remote sensing indices.Our results revealed that the SOS was delayed by approximately 3.86 days per degree of latitude along the northward latitudinal gradient.From 2000 to 2018,the start of the growing season and the interannual variability differed greatly among tundra types.Although the overall trends were not significant from 2000 to 2018,the start of the growing season in different plant communities was consistently delayed after 2016.High Arctic vegetation,including(1)low wetland complexes(5–10 cm)dominated by sedges,grasses,and mosses,and(2)slightly higher prostrate and hemi-prostrate shrubs(<15 cm),experienced a delayed start of the growing season.The start of the growing season of Low Arctic vegetation,comprising(1)wetland complexes(10–40 cm)dominated by sedges,grasses,mosses,and dwarf shrubs,(2)moist tundra(20–50 cm)dominated by tussock cottongrass and dwarf shrubs,and(3)transition zones containing tundra and taiga,displayed no obvious trend. | Jiangshan ZHENG Xiyan XU Gensuo JIA Wenjin WU | 2020 | Science China Earth Sciences2020，63，10： | 1 |
| 17 | Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions显示文摘 | Larry D. Hinzman Neil D. Bettez W. Robert Bolton F. Stuart Chapin Mark B. Dyurgerov Chris L. Fastie Brad Griffith Robert D. Hollister Allen Hope Henry P. Huntington Anne M. Jensen Gensuo J. Jia Torre Jorgenson Douglas L. Kane David R. Klein Gary Kofinas A | 2005 | Climatic Change2005，，3： | 1 |
| 18 | Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems显示文摘 | Douglas A Stow Allen Hope David McGuire David Verbyla John Gamon Fred Huemmrich Stan Houston Charles Racine Matthew Sturm Kenneth Tape Larry Hinzman Kenji Yoshikawa Craig Tweedie Brian Noyle Cherie Silapaswan David Douglas Brad Griffith Gensuo Jia Howard | 2003 | Remote Sensing of Environment2003，，3： | 1 |
| 19 | Strong heatwaves with widespread urban-related hotspots over Africa in 2019显示文摘2019年是近几十年来最热的年份之一,包括非洲在内的全球许多地区都受到大范围的热浪侵袭.然而,非洲作为脆弱的发展中地区,我们对其近年热浪事件的了解非常有限.本研究中,我们结合了不同的气候数据集,卫星观测资料和人口数据,研究了2019年非洲地区主要热浪事件发生的时空特征和热点分布区.总体而言,2019年是非洲地区自1981年以来热浪强度最强,持续时间最久的年份之一.在主要城市和人口所在的非洲西海岸,东北部,南部和赤道地区是热浪发生的热点区.位于赤道以北的非洲地区,暴露于极端(第99个百分位)热浪的城市人口比例从1981-2010年基准期的4%(500万人)上升至2019年的36%(4300万人).位于赤道以南地区,暴露于极端热浪的城市人口则从基准期的15%(1700万人)上升至57%(5300万人).2019年的热浪时空特征和热点分布与大气环流的季节变化异常和海温的暖异常有关.如果不及时采取适应措施以尽量减少人口对热浪事件影响的敏感性,热浪对非洲人口稠密地区构成的风险可能会迅速增加. | Eghosa Igun Xiyan Xu Yonghong Hu Gensuo Jia | 2022 | Atmospheric and Oceanic Science Letters2022，15，5： | 0 |
| 20 | Delayed Antarctic melt season reduces albedo feedback显示文摘Antarctica’s response to climate change varies greatly both spatially and temporally.Surface melting impacts mass balance and also lowers surface albedo.We use a 43-year record(from 1978 to 2020)of Antarctic snow melt seasons from space-borne microwave radiometers with a machine-learning algorithm to show that both the onset and the end of the melt season are being delayed.Granger-causality analysis shows that melt end is delayed due to increased heat flux from the ocean to the atmosphere at minimum sea-ice extent from warming oceans.Melt onset is Granger-caused primarily by the turbulent heat flux from ocean to atmosphere that is in turn driven by sea-ice variability.Delayed snowmelt season leads to a net decrease in the absorption of solar irradiance,as a delayed summer means that higher albedo occurs after the period of maximum solar radiation,which changes Antarctica’s radiation balance more than sea-ice cover. | Lei Liang Huadong Guo Shuang Liang Xichen Li John C.Moore Xinwu Li Xiao Cheng Wenjin Wu Yan Liu Annette Rinke Gensuo Jia Feifei Pan Chen Gong | 2023 | National Science Review2023，10，9： | 0 |
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