基于多源陆面通量数据相融合的新资料及其在中国夏季风影响过渡区的应用

李宏宇; 张强; 王春玲; 马贵东; 井元元; 岳平; 张良

doi:10.3878/j.issn.1006-9895.2005.19192

基于多源陆面通量数据相融合的新资料及其在中国夏季风影响过渡区的应用

doi: 10.3878/j.issn.1006-9895.2005.19192

李宏宇^{1, 2, 3,},
张强³,
王春玲⁴,
马贵东^{1, 2},
井元元^{1, 2},
岳平³,
张良³

1.
河北省气象与生态环境重点实验室，石家庄 050021
2.
河北省气候中心，石家庄 050021
3.
中国气象局兰州干旱气象研究所/甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点开放实验室，兰州 730020
4.
北京市气象服务中心，北京 100089

基金项目: 国家自然科学基金项目41705075、41630426、41975016、41875020，中国气象局气候变化专项CCSF201940，河北省湿地生态与保护重点实验室（筹）开放基金项目hklk201901

详细信息

作者简介:
李宏宇，男，1987年出生，博士、副高级工程师，主要从事陆面过程研究。E-mail: aridlhy@qq.com

中图分类号: P468
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出版历程
- 收稿日期: 2019-07-26
- 网络出版日期: 2020-05-26
- 刊出日期: 2020-11-20

New Dataset Based on Multi-Source Land Surface Flux Data and Its Application in the East Asian Summer Monsoon Boundary Area

Hongyu LI^{1, 2, 3
,},
Qiang ZHANG³,
Chunling WANG⁴,
Guidong MA^{1, 2},
Yuanyuan JING^{1, 2},
Ping YUE³,
Liang ZHANG³

1.
Key Laboratory of Meteorological and Ecological Environment of Hebei Province, Shijiazhuang 050021
2.
Climate Center of Hebei Province, Shijiazhuang 050021
3.
Gansu Key Laboratory of Arid Climatic Change and Reducing Disaster/Key Open Laboratory of Arid Climatic Change and Disaster Reduction of Gansu Province/Institute of Arid Meteorology, China Meteorological Administration, Lanzhou 730020
4.
Beijing Meteorological Service Center, Beijing 100089

Funds: National Natural Science Foundation of China (Grants 41705075, 41630426, 41975016, 41875020), Climate Change Special Fund from China Meteorological Administration (Grant CCSF201940), Open Foundation of Hebei Key Laboratory of Wetland Ecology and Conservation (Grant hklk201901)

摘要

摘要: 夏季风影响过渡区是陆面能量交换与区域气候相互作用显著的热点区域。然而，目前缺乏适用于该区域的高精度长期通量数据集，这限制了陆面水热交换与气候相互作用的研究。如何融合目前已有的多源通量资料进行重构建以及应用显得十分必要。本研究综合包括中国北方协同观测试验和中国通量网的多种下垫面通量观测以及多种格点资料，试图重构中国夏季风影响过渡区的陆面能量通量数据集。在筛选具有优良下垫面代表性站点并考察模拟和观测散点分布规律的基础上，利用多元回归模型构建了一套适用于夏季风影响过渡区并且受观测资料约束的月平均感热、潜热和净辐射数据集。交叉验证结果表明构建的数据集相对于几种原始格点数据集精度有一定提高，最大程度上消除了原始格点资料的系统偏差。进一步分析表明在地表能量平衡分量中，陆面湍流通量对夏季风的响应更为显著，并且夏季风影响过渡区陆面湍流热通量对夏季风持续时间呈现对数分布的年际变化规律；当夏季风处于低持续影响状态时陆面湍流热通量年际变化更为显著，偏弱的夏季风系统可能导致陆面过程对气候变化更强的影响。本文基于多源通量数据融合构建的新数据集可以为气候变化研究提供数据支撑，同时增加了对陆面过程与季风系统相互作用的认识。
- 东亚夏季风 /
- 影响过渡区 /
- 陆面通量 /
- 数据集 /
- 夏季风持续时间
Abstract: The EASM (East Asian summer monsoon) boundary area is active with intense interaction between the land surface process and the regional climate. However, the lack of high-quality long-term flux datasets for this region limits the study of the interaction among the land surface water, heat exchange, and climate. It is necessary to reconstruct a new dataset based on the currently available multiple flux data and then apply it in climate research. In this study, the datasets of land surface energy fluxes in the EASM boundary area in China were reconstructed by integrating the field observations conducted over northern China and several gridded datasets. Based on the selection of sites with good underlying representative surface and the investigation of the scattering distribution of simulations and observations, a set of monthly average sensible heat, latent heat, and net radiation datasets was generated using a multiple regression model. The cross-validation results showed that the accuracy of the constructed dataset was improved compared with several original gridded datasets, and the systematic deviation of the original lattice data was maximally eliminated. Further analysis suggests that among the surface energy balance components, the response of land surface turbulent flux to summer monsoon was more significant, and the interannual variation of the land surface turbulent heat flux with the summer monsoon duration in the EASM boundary area showed logarithmic distribution. The turbulent heat fluxes presented more significant interannual variations, as the summer monsoon was in a low persistent state. A weaker summer monsoon system may lead to a stronger impact of land surface processes on climate change. The new dataset based on multi-source flux data fusion can support climate change research and further clarify the interaction between land surface processes and monsoon climate.
- EASM (East Asian summer monsoon) /
- Boundary area /
- Land surface flux /
- Dataset /
- Summer monsoon duration

HTML全文

图 1 夏季风影响过渡区内所选观测站点的地理分布。红线代表夏季风活动的南北边缘，蓝色实框、蓝色空三角形和红色实圆点分别代表草原站、农田站和裸地/荒漠站

Figure 1. Geographical distribution of observation sites in EASM (East Asian summer monsoon) boundary area. Red lines represent the north and south edge of summer monsoon. Blue solid frames, blue hollow triangles, and red solid dots represent grassland, cropland, and bare land/desert sites, respectively

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图 2 陆面通量数据构建步骤的框图

Figure 2. Flowchart of the procedure of land surface fluxes data construction

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图 3 以站点为圆心、不同距离为半径的圆形区域内观测站点所属下垫面类型所占比例：（a）裸地/戈壁；（b）草原；（c）农田；（d）森林。Spt和Zhy分别代表沙坡头和张掖站，Yuz、Nma、Aro、Tyu、Xil和Dsu分别代表榆中、奈曼、阿柔、通榆、锡林格勒和东苏站，Pli、Jzh、Qya、Miy、Chw、Yke和Dxi分别代表平凉、锦州、庆阳、密云、长武、盈科和定西站，Dyk代表大野口站

Figure 3. Percentage of land cover types at measurement sites within the circular area with different radii for (a) bare land/desert, (b) grassland, (c) cropland, and (d) forest. Spt and Zhy represent Shapotou and Zhangye sites, respectively; Yuz, Nma, Aro, Tyu, Xil, and Dsu represent Yuzhong, Naiman, Arou, Tongyu, Xilingele, and Dongsu sites, respectively; Pli, Jzh, Qya, Miy, Chw, Yke, and Dxi represent Pingliang, Jinzhou, Qingyang, Miyun, Changwu, Yingke, and Dingxi sites, respectively; Dyk represents Dayekou site

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图 4 草地（蓝色圆圈）、农田（绿色方框）、裸地/荒漠（红色实心圆点）三种下垫面类型净辐射通量（左）、感热通量（中）、潜热通量（右）的模拟值与观测值的散点分布

Figure 4. The scatter distributions of net radiation fluxes (NRF, left), sensible heat fluxes (SHF, middle), latent heat fluxes (LHF, right) from simulation (Sim) and observations (Obs) for grassland (blue circles), farmland (green squares), and bare land/desert (solid red points)

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图 5 新构建的（a）净辐射通量、（b）感热通量和（c）潜热通量数据集与观测值的散点图，RMSE、R、N分别表示格点资料的均方根误差、格点资料与观测资料的线性相关系数、样本数

Figure 5. Scatter plots of newly constructed (a) net radiation fluxes (R_n), (b) sensible heat fluxes (H_S), and (c) latent heat fluxes (H_L) datasets and observations, RMSE, R, N represent the root mean square error of grid datasets, linear correlation coefficients between grid data and observation, sample number, respectively

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图 6 不同格点资料（a）净辐射通量、（b）感热通量和（c）潜热通量均方差的相关偏差项、标准差偏差项和平均值偏差项贡献分布

Figure 6. The distributions of contributions from correlation deviation term, standard deviation term, and mean bias term of the mean square error (MSE) in (a) net radiation fluxes, (b) sensible heat fluxes, and (c) latent heat fluxes for different grid datasets

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图 7 不同格点资料的（a）净辐射通量、（b）感热通量和（c）潜热通量在多个插值网格下的均方根误差分布

Figure 7. RMSE distributions of (a) net radiation fluxes, (b) sensible heat fluxes, and (c) latent heat fluxes at multiple grid scales for different grid datasets

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图 8 夏季风影响过渡区（a、b）净辐射通量、（c、d）感热通量和（e、f）潜热通量的夏季气候平均（左，单位：W m⁻²）和年际变率（右，单位：W m⁻²）空间分布

Figure 8. Spatial distributions of summer climate mean (left, units: W m⁻²) and interannual variability (right, units: W m⁻²) of (a, b) net radiation fluxes, (c, d) sensible heat fluxes, and (e, f) latent heat fluxes in the EASM boundary area

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图 9 夏季风影响过渡区（a）西部和（b）东部区域湍流热通量（左侧纵坐标）、夏季风持续时间指数（右侧纵坐标）年际变化以及（c）西部和（d）东部湍流热通量和夏季风持续时间指数的散点分布

Figure 9. Interannual variations of turbulent heat fluxes (left y-axis) and duration index of summer monsoon (right y-axis) in (a) west and (b) east regions of the EASM boundary area. Scatter distributions between turbulent heat fluxes and duration index of summer monsoon for (c) west and (d) east regions of the EASM boundary area

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表 1 使用资料简介

Table 1. Introduction of data used in the study

数据类型	名称	机构名称	空间分辨率	时间分辨率	时间长度
再分析资料	NCEP/DOE	NCEP/DOE	T62 (200 km)	6 h	1979年1月至今
	JRA-25	JMA	T106 (110 km)	3 h	1979年1月至2014年2月
	ERA-Int	ECMWF	1.5°×1.5°	6 h	1979年1月至今
	MERRA	NASA	0.5°×0.67°	1 h	1979年1月至今
离线陆面模式数据集	GLDAS2-NOAH	NASA	1°×1°	3 h	1979年1月至2010年12月
陆面观测	中国北方陆面过程观测	中国科学院大气物理研究所/ 地理科学与资源所	16个站点	30 min	详见表2

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表 2 所选观测站点基本情况

Table 2. Basic information on selected observation sites

站点名称	纬度	经度	下垫面类型	观测时段
沙坡头	37.45°N	104.95°S	荒漠	2008年7～9月；2009年7～9月
张掖	38.86°N	100.41°S	裸地	2008年7～9月；2009年7～9月
长武	35.2°N	107.67°S	农田	2008年7～9月；2009年7～9月
定西	35.56°N	104.59°S	旱作农田	2008年7～9月；2009年7～9月
锦州	41.15°N	121.2°S	农田（玉米）	2008年7～9月；2009年7～9月
密云	40.63°N	117.32°S	农田/果林	2008年7～9月；2009年7～9月
平凉	35.53°N	106.94°S	农田	2009年7月至2010年12月
庆阳	35.66°N	107.84°S	农田（小麦）	2009年5月至2010年12月
盈科	38.86°N	100.58°S	绿洲农田（玉米）	2008年7～9月；2009年7～9月
大野口	38.53°N	100.25°S	常绿针叶林	2008年7～9月；2009年7～9月
阿柔	38.04°N	100.46°S	亚高山草甸	2008年7～9月；2009年7～9月
东苏	44.09°N	113.57°S	荒漠化草原	2008年7～9月；2009年7～9月
奈曼	42.93°N	120.7°S	荒漠化草原	2008年7～9月；2009年7～9月
通榆	44.88°N	122.88°S	退化草原	2003年1月至2008年12月
榆中	35.95°N	104.13°S	草原	2007年1月至2010年12月
锡林格勒	44.13°N	116.32°S	草原	2004年1月至2008年12月

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表 3 5种格点资料的误差统计情况

Table 3. Errors statistics of five gridded data

资料名称	净辐射通量R_n			感热通量H_S			潜热通量H_L
资料名称	RMSE/W m⁻²	Bias/W m⁻²	R	RMSE/W m⁻²	Bias/W m⁻²	R	RMSE/W m⁻²	Bias/W m⁻²	R
NCEP/DOE	34.06	12.46	0.90	32.93	9.23	0.69	20.76	11.45	0.79
JRA-25	23.76	3.08	0.92	18.77	4.48	0.76	14.67	2.21	0.85
ERA-Int	20.40	−0.78	0.93	12.66	4.98	0.83	15.16	3.40	0.86
MERRA	24.45	10.55	0.92	22.21	14.85	0.77	15.47	3.50	0.86
GLDAS2-NOAH	27.97	19.94	0.93	32.92	26.31	0.63	17.22	1.04	0.80
注：RMSE、Bias、R分别表示格点资料的均方根误差、系统误差以及格点资料与观测资料的线性相关系数。

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表 4 三种陆面通量多元回归模型的截距和回归系数

Table 4. Interception and regression coefficients of three multiple regression models for land surface fluxes

陆面通量	截距/ W m⁻²	回归系数
陆面通量	截距/ W m⁻²	NCEP/ DOE	JRA-25	ERA-Int	MERRA	GLDAS2- NOAH
R_n	−8.1894	−0.4522	0.2826	0.6218	0.2019	0.3943
H_S	5.1904	−0.1113	0.0596	0.594	0.1396	0.0093
H_L	2.854	−0.1512	0.2401	0.2057	0.3972	0.191

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表 5 构建数据集与原始格点数据交叉验证的均方根误差（RMSE_CV）

Table 5. Root mean square error of cross-validation (RMSE-CV) between constructed and original gridded datasets

数据集	交叉验证的均方根误差
数据集	R_n/W m⁻²	H_S/W m⁻²	H_L/W m⁻²
构建数据集	22.1	9.4	13.8
NCEP/DOE	34.1	32.9	20.8
JRA-25	23.8	18.8	14.7
ERA-Int	20.4	12.7	15.2
MERRA	24.5	22.2	15.5
GLDAS2-NOAH	28.0	32.9	17.2
注：黑色字体数字表示一列中最小的两个数。

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