Assimilation Experiment of LIS Based on AMSR-E Soil Moisture Products

Yang Xiaofeng; Lu Qifeng; Yang Zhongdong

Vol.24, NO.4, 2013

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2013 > 24(4): 435-445

Yang Xiaofeng, Lu Qifeng, Yang Zhongdong. Assimilation experiment of LIS based on AMSR-E soil moisture products. J Appl Meteor Sci, 2013, 24(4): 435-445.

Citation:

Yang Xiaofeng, Lu Qifeng, Yang Zhongdong. Assimilation experiment of LIS based on AMSR-E soil moisture products. J Appl Meteor Sci, 2013, 24(4): 435-445.

Yang Xiaofeng, Lu Qifeng, Yang Zhongdong. Assimilation experiment of LIS based on AMSR-E soil moisture products. J Appl Meteor Sci, 2013, 24(4): 435-445.

Citation:

Yang Xiaofeng, Lu Qifeng, Yang Zhongdong. Assimilation experiment of LIS based on AMSR-E soil moisture products. J Appl Meteor Sci, 2013, 24(4): 435-445.

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Assimilation Experiment of LIS Based on AMSR-E Soil Moisture Products

National Satellite Meteorological Center, Beijing 100081

Received Date: 2012-07-03
Rev Recd Date: 2013-04-19
Publish Date: 2013-08-31

Abstract

Abstract

Soil moisture is an important part of the soil, playing an important role in energy and mass exchange between land and atmosphere. It is an important environment factor and the process parameter of hydrology, meteorology and other researches. In order to accurately depict and understand the interaction between land and atmosphere, precise and high resolution soil moisture contour information is needed. But whether using the objective measurement or numerical prediction of land surface process simulation, soil moisture contour line with spatial-temporal continuum and good precision can't be obtained. In order to eliminate the error, data assimilation method (EnKF) is used to process passive microwave inversion products (AMSR-E) and land surface model (NOAH) outputs, and then shallow soil moisture information is transmitted to deeper soil layers by land assimilation system (LIS). These methods are used to calculate soil moisture with high precise, high resolution and low error. Through these methods, 4-layer (10 cm, 30 cm, 60 cm, 100 cm) soil moisture data with spatial resolution of 0.25° by 0.25° for the year of 2003 are obtained.Agro-meteorological-station soil moisture data and ecological-station data are used to verify the 4-layer soil moisture results. The simulation accuracy of the land surface model is improved when data assimilation method is used, the simulation accuracy in different layers is different, and the accuracy in the grassland ecosystem is higher than that in crop and forest ecosystems. The spatial characteristics of assimilation results match with real values, which is high in the southeast and low in the northwest. Assimilation soil moisture data has more detailed information in horizontal scales compared to station data and has more detailed information in vertical scales compared to the passive microwave inversion products.The accuracy of the assimilation process depends on the passive microwave inversion products (AMSR-E). However, AMSR-E has stopped running and inversion errors of passive microwave inversion products will be accumulated in data assimilation run. In order to solve these problems, passive microwave inversion products of FY-3B can be used experimentally. Besides, assimilation experiment can be started by directly assimilate radiation brightness temperature of microwave channels. Simulation accuracy of soil moisture can be further improved through these processes. Effect of assimilation experiment is different in different vegetation, which mainly depends on capabilities of land surface model. Therefore, improving the land surface model is also an effective means to improve soil moisture simulation accuracy.
- LIS;
- soil moisture;
- EnKF;
- AMSR-E;
- assimilation experiment

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References(33)

Figures and Tables

Fig. 1 Distribution of agro-meteorological stations and ecological stations used for testing

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Fig. 2 Time series of agro-meteorological-station observations and Experiment 1, Experiment 2 average results in 10 cm, 30 cm, 60 cm

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Fig. 3 Soil moisture distribution of Experiment 2 output, AMSR-E and agro-meteorological-station observations on 1 July 2003

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Fig. 4 Soil moisture comparison of agro-meteorological-station observations, outputs of Experiment 1 and Experiment 2 at Station A, B and C

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Fig. 5 Soil moisture comparison of observations, outputs of Experiment 1 and Experiment 2 in 10 cm, 30 cm, 60 cm, 100 cm layers at Xishuangbanna Station

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Fig. 6 Soil moisture comparison of observations, outputs of Experiment 1 and Experiment 2 in 10 cm, 30 cm, 60 cm layers at Haibei Station

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Fig. 7 Soil moisture comparison of observations, outputs of Experiment 1 and Experiment 2 in 10 cm, 30 cm, 60 cm, 100 cm layers at Fengqiu Station

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Table 1 Three-layer results of Experiment 1, Experiment 2 and agro-meteorological-station observations (unit:%)

土壤深度	观测	试验1	试验2	差值		均方根误差
土壤深度	观测	试验1	试验2	试验1与观测	试验2与观测	试验1与观测	试验2与观测
10 cm	19.70	16.56	17.68	3.14	2.02	9.29	8.70
30 cm	25.42	17.59	21.27	7.83	4.15	12.52	10.80
60 cm	25.18	21.24	27.65	7.59	-2.47	11.17	10.96
注：以上数值均为土壤水分体积含水量平均值。

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Table 2 10-cm soil moisture observations and outputs of Experiment 1, Experiment 2 in different vegetation conditions (unit:%)

统计量	森林生态系统		草地生态系统		作物生态系统
统计量	长白山站	西双版纳站	海北站	内蒙古站	桃园站	封丘站
试验1偏差	6.97	3.07	5.02	3.22	3.36	3.12
试验2偏差	5.27	2.23	0.71	1.90	2.49	0.59
试验1均方根误差	8.65	4.09	5.66	4.32	4.10	3.89
试验2均方根误差	7.62	3.76	2.53	3.53	4.26	1.79
注：以上数值均为土壤水分体积含水量平均值。

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