面向资料同化的FY-4A 卫星GIIRS探测仪偏差特征分析和偏差订正

刘娟娟; 徐兰; 成巍; 王斌; 巩欣亚; 邓中仁; 李亚云; 狄迪

doi:10.3878/j.issn.1006-9895.2111.21034

面向资料同化的FY-4A 卫星GIIRS探测仪偏差特征分析和偏差订正

doi: 10.3878/j.issn.1006-9895.2111.21034

刘娟娟^{1, 2,},
徐兰^{1, 2},
成巍³,
王斌^{1, 2},
巩欣亚^{4, 7},
邓中仁⁶,
李亚云³,
狄迪^5, ,

1.
中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室, 北京 100029
2.
中国科学院大学, 北京100049
3.
北京应用气象研究所, 北京100029
4.
国家卫星气象中心, 北京 100081
5.
南京信息工程大学大气物理学院, 南京 210044
6.
南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室, 南京 210044
7.
许健民气象卫星创新中心, 北京 100081

基金项目: 国家重点研发计划重大自然灾害监测预警与防范项目2017YFC1501803，国家自然科学基金项目41905098

详细信息

作者简介:
刘娟娟，女，1980年出生，博士，副研究员，主要从事资料同化和集合预报研究。E-mail: ljjxgg@mail.iap.ac.cn

通讯作者:
狄迪，E-mail: didi@nuist.edu.cn

中图分类号: P414.4
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- 文章访问数: 295
- HTML全文浏览量: 61
- PDF下载量: 89
- 被引次数: 0
出版历程
- 收稿日期: 2021-02-22
- 录用日期: 2021-11-29
- 网络出版日期: 2021-11-30
- 刊出日期: 2022-03-16

Bias Characteristics and Bias Correction of GIIRS Sounder onboard FY-4A Satellite for Data Assimilation

Juanjuan LIU^{1, 2
,},
Lan XU^{1, 2},
Wei CHENG³,
Bin WANG^{1, 2},
Xinya GONG^{4, 7},
Zhongren DENG⁶,
Yayun LI³,
Di DI^{5
, ,}

1.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
2.
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049
3.
Beijing Institute of Applied Meteorology, Beijing 100029
4.
National Satellite Meteorological Center, Beijing 100081
5.
School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044
6.
Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044
7.
FengYun Meteorological Satellite Innovation Center (FY-MSIC), Beijing 100081

Funds: National Key R&D Program of China (Grant 2017YFC1501803), National Natural Science Foundation of China (Grant 41905098)

摘要

摘要: 干涉式大气垂直探测仪（Geostationary Interferometric Infrared Sounder，简称GIIRS）是国际上第一部对地静止卫星平台上的高光谱红外大气垂直探测仪，能为对流尺度区域模式预报提供所需的高时空和高光谱分辨率的大气状态信息。本文利用高分辨率区域模式WRF及其同化系统WRFDA对GIIRS观测的偏差（观测亮温减去模拟亮温，记为O−B）分布特征进行了全景分析，结果表明：长波通道O−B偏差和标准差普遍小于中波通道，且都存在一段受污染的通道。O−B偏差的日变化和偏差与卫星天顶角的关系相对较弱，而所有筛选通道的偏差都与亮温值及卫星的扫描阵列位置有关，偏差的水平分布主要表现出“阵列偏差”的特征。2020年重新定标后，GIIRS观测数据质量比2019年有明显提高。在此基础上进一步进行了偏差订正试验，试验发现选取扫描阵列作为偏差订正的主要因子，都能有效地改进2019年和2020年筛选出的GIIRS通道的偏差，订正后O−B和O−A的系统性误差（偏差）都变小。该研究结果可为全球/区域模式中同化GIIRS长波及中波通道的辐射资料提供参考。
- 风云四号A星(FY-4A) /
- 干涉式大气垂直探测仪(GIIRS) /
- 偏差订正 /
- 卫星资料同化
Abstract: The geostationary interferometric infrared sounder (GIIRS) is the first hyperspectral infrared (IR) sounder onboard the geostationary meteorological satellite—FengYun-4A satellite. The GIIRS can provide atmospheric state information with a high temporal, spatial, and spectral resolution that could enhance the prediction of convective-scale regional models. This paper presents a panoramic analysis of the bias characteristics of the GIIRS with the high-resolution regional model WRF and its assimilation system WRFDA. Results reveal that the bias (observations minus simulations, or O−B) and standard deviation of long-wave infrared (LWIR) channels are generally smaller than those of middle-wave infrared (MWIR) channels, and both have some contaminated channels. The diurnal variation of biases is relatively unremarkable, and the O−B bias has a weak relationship with the satellite zenith angle. However, the biases in all selected channels are related to the value of brightness temperature observations and the scanning position of the satellite. In addition, the spatial distribution characteristics of the bias are relevant to the bias characteristics impacted by the scanning position. After re-calibration of the GIIRS in 2020, the quality of the GIIRS observation data is significantly improved compared with that in 2019. Based on this, further bias correction tests are carried out using correction factors relevant to the scanning position. Results reveal that both the systematic errors (bias) of O−B and O−A have been significantly reduced, implying the effectiveness of the bias correction scheme. This study provides implications for GIIRS radiance assimilation in global/regional models.
- FY-4A satellite /
- GIIRS (Geostationary Interferometric Infrared Sounder) /
- Bias correction /
- Satellite data assimilation

HTML全文

图 1 2019年6月1日00:00（协调世界时，下同）（a）多通道扫描成像辐射计（AGRI）云掩膜产品（CLM）和（b）干涉式大气红外高光谱探测仪（GIIRS）云检测的晴空视场分布。图红色和蓝色的圆点（即CLM=100% clear）代表该视场（Fields of View，简称FOV）云检测结果为完全晴空

Figure 1. Clear sky spatial distribution of (a) AGRI (Advanced Geosynchronous Radiation Imager) cloud mask products and (b) cloud detection results of the GIIRS (Geostationary Interferometric Infrared Sounder) at 0000 UTC on 1 June 2019. Red and blue dots in (a) and (b) represent the fields of view (FOV) with cloud mask products of 100% clear

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图 2 （a）2019年6月3日00:00与（b）2020年8月3日00:00使用异常数据标示码（pclk）标识剔除异常值后通道6的观测亮温分布（单位：K）。缺少的FOV代表pclk标识剔除的异常FOV

Figure 2. Spatial distribution of the observed brightness temperature (units: K) of channel 6 after excluding the outliers using pclk marking at (a) 0000 UTC on 3 June 2019 and (b) 0000 UTC on 3 August 2020. The missing FOV represents the excluded outliers by pclk

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图 3 （a）2019年6月和（b）2020年8月GIIRS通道O−B（观测亮温减去模拟亮温）的偏差（红色）和标准差（蓝色）的一个月统计结果，单位：K。粉色阴影为CO₂吸收波段；灰色阴影为窗区和O₃吸收波段；绿色阴影为H₂O吸收波段；黄色阴影为CO₂和N₂O吸收波段，红色辅助线代表偏差为0 K

Figure 3. Statistical results of the bias (units: K, red lines) and standard deviation (STD, units: K, blue lines) between the observed and simulated brightness temperature (O−B) in all channels in (a) June 2019 and (b) August 2020. The pink shade denotes the CO₂ band; the gray shade denotes the window and the O₃ band; the green shade denotes the H₂O band; the yellow shade denotes the CO₂ and N₂O bands; the red auxiliary line denotes the O−B bias at 0 K

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图 4 2020年8月剔除观测异常后部分（a）长波通道及（b）中波通道O−B的偏差（红色）和标准差（蓝色）的一个月统计结果，单位: K。红色辅助线代表偏差为0 K

Figure 4. Statistical results of the bias (units: K, red lines) and standard deviation (STD, units: K, blue lines) between the observed and simulated brightness temperature (O−B) in August 2020 (a) in part of LWIR (long-wave infrared) channels with the elimination of the anomaly observation, (b) in part of MWIR (middle-wave infrared) channels with the elimination of the anomaly observation, units: K. The red auxiliary line denotes the O−B bias at 0 K

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图 5 （a）GIIRS通道的模拟亮温分布（单位：K）及挑选出的（b）长波通道的Jacobian（dT_b dT⁻¹, 单位：K K⁻¹）和（c）中波通道的Jacobian（dT_b dlnq⁻¹, 单位：K [ln(g kg⁻¹)]⁻¹）的垂直分布。（a）中黑色实线代表所有通道的模拟亮温分布，蓝色圆点代表挑选出的通道的模拟亮温分布，阴影部分含义与图3一致；（b）中加粗了通道6和121的Jacobian分布；（c）中加粗了通道942和1286的Jacobian分布

Figure 5. (a) Simulated bright temperature distribution of the GIIRS, units: K, and the vertical distribution of the Jacobian in selected (b) LWIR (dT_b dT⁻¹, units: K K⁻¹) and (c) MWIR (dT_b dlnq⁻¹, units: K [ln(g kg⁻¹)]⁻¹ channels. The black lines represent the simulated brightness temperature in all channels, blue dots represent the simulated brightness temperature in selected channels, the colorful shade in Fig 5a have the same meaning as in Fig. 3; the Jacobian of channels 6 and 121 is bold in Fig 5b; the Jacobian of channels 942 and 1286 is bold in Fig 5c

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图 6 2020年8月各通道O−B偏差（单位：K，红色）及标准差（单位：K，蓝色）的一个月时间序列：（a）通道6；（b）通道121；（c）通道942；（d）通道1286

Figure 6. Time series of the bias (units: K, red lines) and standard deviation (STD, units: K, blue lines) between the observed and simulated brightness temperature (O−B) in August 2020 in channels (a) 6, (b) 121, (c) 942, and (d) 1286

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图 7 2020年8月00:00、06:00、12:00和18:00各通道O−B的偏差（单位：K，红色）及标准差（单位：K，蓝色）的一个月统计结果：（a）通道6；（b）通道121；（c）通道942；（d）通道1286

Figure 7. Statistical results of the bias (units: K, red bars) and standard deviation (STD, units: K, blue bars) between the observed and simulated brightness temperature (O−B) of 0000 UTC, 0600 UTC, 1200 UTC, and 1800 UTC in August 2020 in channels (a) 6, (b) 121, (c) 942, and (d) 1286

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图 8 GIIRS观测区域扫描阵列探元分布（框中数值代表探元编号）

Figure 8. Positions and north–south pixel numbers of the GIIRS FOV in a single field-of-regard(the value in the boxes represents the number of detectors)

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图 9 2020年8月通道（a、b）6、（c、d）121、（e、f）942和（g、h）1286 O−B偏差（左列；单位：K）和标准差（右列；单位：K）与阵列的关系（Col 1～4代表从西到东的4列扫描阵列）

Figure 9. Dependence of the bias (units: K; left column) and standard deviation (STD, units: K; right column) between the observed and simulated brightness temperature (O−B) in August 2020 in channels (a, b) 6, (c, d) 121, (e, f) 942, and (g, h) 1286. Cols 1–4 represent the 4 scanning positions from west to east

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图 10 2020年8月通道（a、b）6、（c、d）121、（e、f）942和（g、h）1286 O−B偏差（左列，单位：K）和标准差（右列，单位：K）的空间分布

Figure 10. Spatial distribution characteristics of the bias (left column; units: K) and standard deviation (right column; units: K) between the observed and simulated brightness temperature (O−B) in August 2020 in channels (a, b) 6, (c, d) 121, (e, f) 942, and (g, h) 1286

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图 11 2020年8月通道（a）6、（b）121、（c）942和（d）1286 O−B偏差（单位：K）和观测亮温值（单位：K）的关系（Cor代表相关系数，阴影代表观测数量）

Figure 11. Dependence of the bias (units: K) between the observed and simulated brightness temperature (O−B) in August 2020 in channels (a) 6, (b) 121, (c) 942, and (d) 1286 on the value of observed brightness temperature (OBS, units: K). Cor represents the correlation coefficient; observation counts are shaded

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图 12 2020年8月通道（a）6、（b）121、（c）942和（d）1286 O−B偏差（单位：K）和卫星天顶角的关系（Cor代表相关系数，阴影代表观测数量）

Figure 12. Dependence of the bias (units: K) between the observed and simulated brightness temperature (O−B) in August 2020 in channels (a) 6, (b) 121, (c) 942, and (d) 1286 on the satellite zenith angle (units: °). Cor represents the correlation coefficient; observation counts are shaded

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图 13 2019年6月（左列）和2020年8月（右列）挑选出的通道观测分别与（a、b）背景场、（c、d）分析场的模拟偏差，单位：K。红色和蓝色分别代表进行VarBC偏差订正和未进行VarBC偏差订正的结果

Figure 13. Bias in June 2019 (a) between the observed and simulated background brightness temperature (O−B, units: K) and (c) between the observed and analysis brightness temperature (O−A, units: K). Bias in August 2020 (b) between the observed and simulated background brightness temperature (O−B, units: K) and (d) between the observed and analysis brightness temperature (O−A, units: K) in all selected channels (Red lines represent the results with VarBC; blue lines represent the results without VarBC)

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表 1 选定的292条GIIRS通道

Table 1. 292 selected GIIRS channels

GIIRS通道
CO₂吸收波段		窗区和O₃吸收波段					H₂O吸收波段			CO₂和 N₂O吸收波段
2	4	151	154	159	163	166	935	937	939	1304	1310
6	8	168	170	172	174	176	942	951	953	1315	1317
10	12	178	180	182	184	186	955	957	959	1321	1325
14	16	188	190	192	194	196	961	965	989	1346	1348
18	20	198	200	202	204	206	1008	1010	1014	1353	1356
22	24	208	210	212	214	216	1016	1020	1023	1369	1382
26	28	218	220	222	224	226	1025	1028	1045	1389	1393
32	35	228	230	232	234	236	1047	1049	1053	1400	1402
67	69	238	240	242	244	246	1056	1058	1066	1406	1409
71	73	248	250	252	254	256	1072	1075	1081	1411	1415
75	77	258	260	262	264	266	1084	1086	1096	1420	1423
79	81	268	270	272	275	277	1103	1105	1107	1433	1436
83	85	279	281	287	294	296	1125	1129	1142	1444	1447
87	89	298	300	302	304	306	1144	1162	1165	1451	1457
91	93	308	310	312	314	316	1169	1177	1180	1467	1469
95	97	318	320	322	324	326	1182	1187	1189	1470	1472
99	101	328	331	333	335	337	1200	1202	1211	1474	1483
103	105	339	341	343	345	347	1213	1232	1236	1485	1494
107	109	349	351	353	357	361	1240	1247	1250	1508	1510
111	113	364	367	369	371	373	1262	1264	1266	1543	1549
115	117	375	377	379	381	383	1276	1278	1282
119	121	385	387	389	398	403	1286	1288	1294
123	125	406	410	413	416	419
127	129	421	435	439	474	476
131	133	478	480	482	484	486
135	137	488	490	492	550	587
139	141
143	145
148

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