通量及其不确定性对农业区高塔CO2浓度模拟的影响

doi:10.3969/j.issn.1000-6362.2017.08.001

摘要/Abstract

摘要：

利用WRF-STILT模型模拟玉米种植区生长季（6-9月）小时CO2浓度，并基于美国最大农业种植区‘玉米带’100m高塔CO2浓度观测数据，对WRF-STILT模型的模拟能力及CO2通量的不确定性对模拟结果的影响进行分析。结果表明：（1）WRF-STILT能够模拟高塔观测的CO2浓度日变化特征，模拟值与观测值的均方根误差为13.70molmol-1，模拟结果偏高7.26molmol-1。（2）EDGAR和Carbon Tracker两种典型化石燃料的CO2通量，其区域平均值相差＜6%，但两者对CO2浓度增加值的模拟结果相差约10%；（3）CO2通量空间分辨率的差异会导致模拟结果产生偏差，使用区域边长为1o的EDGAR化石燃料CO2通量模拟的浓度贡献值仅为0.1o的0.4倍，且空间分辨率越低，模拟误差越大；（4）白天和夜晚Carbon Tracker模拟的植被生态系统净交换数据是高塔涡度相关方法观测结果的2.26和1.56倍，下垫面分类的误差以及相应的通量模拟误差使模拟的CO2浓度贡献出现12molmol-1的差异，这是模拟结果偏高7.26molmol-1的潜在误差来源。研究认为，WRF-STILT模型和高空间及时间分辨率的CO2通量能够较好模拟出农业区生长季的CO2强日变化特征，CO2通量的误差是模拟结果误差的主要来源，研究结果表明该方法具有评估和优化通量的巨大潜力。

关键词: WRF-STILT模型, 涡度相关, 化石燃料, 通量不确定性

Abstract:

Based on the CO2 concentration observations in U.S. corn belt, which was measured at 100m height of a tall tower, hourly CO2 concentration was simulated for the growing season (June–September, 2008) with the WRF-STILT model. And the effect of flux uncertainty on modeled CO2 concentration was also analyzed. The results showed as: (1) WRF-STILT model can simulate the observed strong diurnal variation in growing season, with RMSE be 13.70molmol-1, and it was overestimated by 7.26molmol-1, the shape and area of intense footprint zonesare different for different months (September＞August＞June＞July) .(2) The difference of regional average anthropogenic CO2 flux for EDGAR and Carbon Tracker was within 6%, when both of them were at the same spatial resolution, the simulated CO2 enhancement difference was close to 10%. (3) Spatial resolution can lead to large bias in the modeled CO2 enhancement, when using 1o emissions, the simulated CO2 enhancement was only 0.4 times of the results using 0.1o emissions, and with the decreases of spatial resolution, the modeled bias increases. (4) Daytime and nighttime NEE of Carbon Tracker is 2.26 and 1.56 times that of tall tower NEE observations, and the misrepresentatives of underlying land use categories can lead to about 12molmol-1 bias in the modeled results, which may be the potential reason of bias high for 7.26molmol-1. Our study concludes that when combing WRF-STILT model with high quality CO2 flux, the strong diurnal variation of CO2 concentration can be well simulated, and the uncertainty of CO2 flux is the main reason for modeled CO2 concentration bias, it also indicates the potential of evaluating and retrieving prior CO2 flux.

Key words: WRF-STILT model, Eddy covariance, Fossil emissions, Flux uncertainty

胡诚，张弥，肖薇，王咏薇，王伟，Tim Griffis，刘寿东，李旭辉. 通量及其不确定性对农业区高塔CO2浓度模拟的影响[J]. 中国农业气象, 2017, 38(08): 469-480.

HU Cheng, ZHANG Mi, XIAO Wei, WANG Yong-wei,WANG Wei, TIM Griffis,LIU Shou-dong, LI Xu-hui. Effect of Flux and its Uncertainty on Tall Tower CO2 Concentration Simulation in the Agricultural Domain[J]. Chinese Journal of Agrometeorology, 2017, 38(08): 469-480.

参考文献

[1]于贵瑞,王秋凤,朱先进.区域尺度陆地生态系统碳收支评估方法及其不确定性[J].地理科学进展,2011,30(1):103-113. Yu G R,Wang Q F,Zhu X J.Method and uncertainties in evaluating the carbon budgets of regional terrestrial ecosystems[J].Progress in Geography,2011,30(1):103-113.(in Chinese) [2]Maki T,Ikegami M,Fujita T,et al.New technique to analyse global distributions of CO2,concentrations and fluxes from non-processed observational data[J].Tellus Series B-chemical & Physical Meteorology, 2010, 62(5):797-809. [3]Saeki T,Maksyutov S,Sasakawa M,et al.Carbon flux estimation for Siberia by inverse modeling constrained by aircraft and tower CO2,measurements[J].Journal of Geophysical Research Atmospheres, 2013,118(2):1100-1122. [4]Houghton R A.Balancing the global carbon budget[J].Earth and Planetary Sciences,2007,35(35):313-347. [5]Quéré C L,Raupach M R,Canadell J G,et al.Trends in the sources and sinks of carbon dioxide[J].Nature Geoscience, 2009,2(12):831-836. [6]于成龙,刘丹.小兴安岭天然阔叶混交林生长季CO2通量特征分析[J].中国农业气象,2011,32(4):525-529. Yu C L,Liu D.Analysis on CO2 flux during growth season of natural broadleaved mixed forest in Xiaoxinganling Mountains[J].Chinese Journal of Agrometeorology,2011, 32(4):525-529.(in Chinese) [7]李永秀,杨再强,张富存,等. 光合作用模型在长江下游冬麦区的适用性研究[J].中国农业气象,2011,32(4):588-592. Li Y X,Yang Z Q,Zhang F C,et al.Applicability of different photosynthesis models for winter wheat in the lower Yangtze river[J].Chinese Journal of Agrometeorology,2011,32(4): 588-592.(in Chinese) [8]Chen M,Griffis T J,Baker J,et al.Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes[J].Journal of Geophysical Research- Biogeosciences,2015,120(2):310-325. [9]Peters W,Jacobson A R,Sweeney C,et al.An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker[J].Proceedings of the National Academy of Sciences of the United States of America,2007,104(48): 18925-18930. [10]Zhao C,Andrews A E,Bianco L,et al.Atmospheric inverse estimates of methane emissions from Central California[J]. Journal of Geophysical Research Atmospheres, 2009, 114(D16):4723-4734. [11]Chen Z,Griffis T J,Millet D B,et al.Partitioning N2O Emissions within the US Corn Belt using an Inverse Modeling Approach[J].Global Biogeochemical Cycles, 2016,30:1192-1205. [12]Su Y K,Millet D B,Hu L,et al.Constraints on carbon monoxide emissions based on tall tower measurements in the U.S. upper midwest[J].Environmental Science & Technology, 2013,47(15):8316-24. [13]Lin J C,Gerbig C,Wofsy S C,et al.A near-field tool for simulating the upstream influence of atmospheric observations:the Stochastic Time-Inverted Lagrangian Transport (STILT) model[J].Journal of Geophysical Research Atmospheres,2003,108(4493):1211-1222. [14]Gerbig C,Lin J C,Wofsy S C,et al.Toward constraining regional-scale fluxes of CO2,with atmospheric observations over a continent:analysis of COBRA data using a receptor-oriented framework[J].Journal of Geophysical Research Atmospheres,2003,108(D24):4757-ACH6. [15]Alexandratos N,Bruinsma A J.World agriculture towards 2030/2050: the 2012 revision[M].Rome:Food and Agriculture Organization of the United Nations,2008. [16]潘根兴,赵其国.我国农田土壤碳库演变研究:全球变化和国家粮食安全[J].地球科学进展,2005,20(4):384-393. Pan G X,Zhao Q G.Study on evolution of organic carbon stock in agricultural soils of China:facing the challenge of global change and food security[J].Advances in Earth Science,2005, 20(4):384-393.(in Chinese) [17]陈纪波,胡慧,陈克垚,等.基于非线性PLSR模型的气候变化对粮食产量的影响分析[J].中国农业气象,2016,37(6): 674-681. Chen J B,Hu H,Chen K Y,et al.Effects of climate change on the grain yield based on nonlinear PLSR model[J].Chinese Journal of Agrometeorology,2016,37(6):674-681.(in Chinese) [18]Kaminski T,Rayner P J,Heimann M,et al.On aggregation errors in atmospheric transport inversions[J].Journal of Geophysical Research Atmospheres,2001,106(D5):4703- 4715. [19]Turner A J,Jacob D J.Balancing aggregation and smoothing errors in inverse models[J].Atmospheric Chemistry & Physics,2015,15(1):1001-1026. [20]Wang E,Little B B,Williams J R,et al.Simulation of hail effects on crop yield losses for corn-belt states in USA[J].Transactions of the CSAE,2012,258(21):10012- 10016. [21]高韵秋,刘寿东,胡凝,等.南京夏季城市冠层大气CO2浓度时空分布规律的观测[J].环境科学,2015(7):2367-2373. Gao Y Q,Liu S D,Hu N,et al.Direct observation on the temporal and spatial patterns of the CO2 concentration in the atmospheric of Nanjing urban canyon in summer[J]. Environmental Science,2015(7):2367-2373.(in Chinese) [22]Griffis T J,Baker J M,Sargent S D,et al.Influence of C4 vegetation on 13CO2 discrimination and isoforcing in the upper Midwest,United States[J].Global Biogeochemical Cycles,2010,24(4):16. [23]Nehrkorn T,Eluszkiewicz J,Wofsy S C,et al.Coupled weather research and forecasting-stochastic time-inverted lagrangian transport (WRF–STILT) model[J].Meteorology & Atmospheric Physics,2010,107(1):564. [24]Ahmadov R,Gerbig C,Kretschmer R,et al.Comparing high resolution WRF-VPRM simulations and two global CO2 transport models with coastal tower measurements of CO2[J]. Biogeosciences,2009,6(5):807-817. [25]Mallia D V,Lin J C,Urbanski S,et al.Impacts of upwind wildfire emissions on CO,CO2,and PM2.5, concentrations in Salt Lake City,Utah[J].Journal of Geophysical Research Atmospheres,2015, 120(1):147-166. [26]Gerbig C,Lin J C,Wofsy S C,et al.Towards constraining regional scale fluxes of CO2 with atmospheric observations over a continent 1:observed spatial variability from airborne platforms[J].Journal of Geophysical Research Atmospheres, 2003,108(D24):ACH 5-1. [27]Pillai D,Gerbig C,Kretschmer R,et al.Comparing lagrangian and eulerian models for CO2 transport – a step towards Bayesian inverse modeling using WRF/STILT-VPRM[J]. Atmospheric Chemistry & Physics,2012,12(1):1267-1298. [28]European Commission,Joint Research Centre/Netherlands Environmental Assessment Agency. Emission Database for Global Atmospheric Research (EDGAR),release version 4.0[M].2009. [29]Gurney K R,Mendoza D L,Zhou Y,et al.The vulcan project:high resolution fossil fuel combustion CO2 emissions fluxes for the United States[J].Environmental Science & Technology,2009,43(14):5535-5541. [30]Boden T A,Marland G,Andres R J.Global,regional,and national fossil-fuel CO2 emissions[J].Carbon Dioxide Information Analysis Center,Oak Ridge National Laboratory, U.S.Department of Energy,Oak Ridge, Tenn.,U.S. A.,2013. [31]Oda T,Maksyutov S.A very high-resolution (1km×1km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights[J].Atmospheric Chemistry & Physics,2010,10(7): 16307-16344. [32]Mu M,Randerson J T,Van d W G R,et al.Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide[J]. Journal of Geophysical Research Atmospheres, 2011, 116(D24):191-200. [33]Giglio L,Randerson J T,Werf G R V D.Analysis of daily, monthly,and annual burned area using the fourth-generation global fire emissions database (GFED4)[J].Journal of Geophysical Research Biogeosciences,2013,118(1):317-328. [34]Wiedinmyer C,Akagi S K,Yokelson R J,et al.The Fire INventory from NCAR (FINN):a high resolution global model to estimate the emissions from open burning[J]. Geoscientific Model Development Discussions,2010, 3(4): 625-641. [35]Potter C S,Randerson J T,Field C B,et al.Terrestrial ecosystem production:a process model based on global satellite and surface data[J].Global Biogeochemical Cycles,1993,7(4):811-841. [36]Zhang X,Lee X,Griffis T J,et al.Estimating regional greenhouse gas fluxes: an uncertainty analysis of planetary boundary layer techniques and bottom-up inventories[J]. Atmospheric Chemistry & Physics,2014,14(19): 10705- 10719. [37]Davis K J,Bakwin P S,Yi C,et al.The annual cycles of CO2,and H2O exchange over a northern mixed forest as observed from a very tall tower[J].Global Change Biology, 2003,9(9):1278-1293. [38]刁一伟,黄建平,刘诚,等.长江三角洲地区净生态系统二氧化碳通量及浓度的数值模拟[J].大气科学,2015,39(5): 849-860. Diao Y W,Huang J P,Liu C,et al.A modeling study of CO2 flux and concentrations over the Yangtze River Delta using the WRF-GHG model[J].Chinese Journal of Atmospheric Sciences,2015, 39(5):849-860.(in Chinese) [39]麦博儒,安兴琴,邓雪娇,等.珠江三角洲近地层CO2通量模拟分析与评估验证[J].中国环境科学,2014,34(8): 1960-1971. Mai B R,An X Q,Deng X J,et al.Simulation analysis and verification of surface CO2 flux over Pearl River Delta,China[J].China Enviromental Science,2014,34(8): 1960-1971.(in Chinese) [40]Miller J B,Lehman S J,Montzka S A,et al.Linking emissions of fossil fuel CO2,and other anthropogenic trace gases using atmospheric 14CO2[J].Journal of Geophysical Research Atmospheres,2012,117(D8):8302. [41]Nassar R,Napier-Linton L,Gurney K R,et al.Improving the temporal and spatial distribution of CO2 emissions from global fossil fuel emission data sets[J].Journal of Geophysical Research Atmospheres,2013,118(2):917-933.