风云三号D星气温观测气候变化应用稳定性评估

doi:10.12006/j.issn.1673-1719.2025.083

摘要/Abstract

摘要：

为推进风云三号气象卫星气温观测在气候变化研究中的应用，依照全球气候观测系统（GCOS）基本气候变量观测要求，以NOAA卫星均一化气温为参照，定量评估了风云三号D星微波温度计-II型（FY-3D MWTS-II）业务观测全球高空气温资料稳定性，结论如下：对流层中层通道4海洋上空、对流层上层通道6和平流层下层通道9观测稳定性达到气候变化应用要求；通道4陆地上空气温和平流层中上层10~13通道气温存在由轨道漂移引发的日变化误差，对流层上层通道7和平流层下层通道8气温存在定标误差漂移，气候变化应用前需要均一化处理。稳定性评估可为气候变化研究筛选高信度卫星观测资料，为构建风云卫星均一化气温气候数据集奠定科学基础，进而显著提高风云卫星气温观测气候应用水平。

关键词: 风云三号D星, 气温, 稳定性, 评估, 气候变化

Abstract:

Since the launch of China’s Fengyun-3 meteorological satellite in 2008, its microwave radiometer temperature observation data has been widely used in numerical weather forecasting and disaster monitoring, but its application in the climate change research remains notably insufficient. In particular, its stability has not been quantitatively evaluated, which is crucial for climate change studies. To fill this gap, in accordance with the basic climate variable observation requirements defined by the Global Climate Observing Systems (GCOS), the stability for Fengyun-3D/MWTS-II operational temperature observations has been quantitatively evaluated through anomaly and difference trend analysis, taking the homogenized temperature climate dataset from NOAA satellites as a reference. During the evaluation, the effects of diurnal sampling errors (i.e., diurnal drift) caused by orbital drift on temperature observations in different global regions (ocean and land) and across different channels were considered. The following conclusions were drawn: (1) For the mid-tropospheric channel 4 over the ocean, upper tropospheric channel 6, and lower stratospheric channel 9, the effects of diurnal drift are minimal, and their stability meets the requirements for climate change research. The temperature trend of channel 4 over land is largely influenced by diurnal drift errors. (2) The upper tropospheric channel 7 and lower stratospheric channel 8 exhibit small diurnal drift effects but have significant calibration drift errors. (3) The temperatures from the stratospheric mid-to-upper layers (channels 10-13) are all affected by diurnal drift errors, making it difficult to determine if there is a calibration drift error. Therefore, diurnal drift errors need to be corrected before stability evaluation. The stability evaluation aids in the selection of high-confidence satellite observations for climate change research, provides key evidence for correcting diurnal drift and calibration drift errors, and lays a scientific foundation for constructing a homogenized temperature climate dataset from Fengyun satellites. This study will advance the application of Fengyun-3D observations in climate change research.

Key words: Fengyun-3D, Atmospheric temperature, Stability, Evaluation, Climate change

郭艳君, 邹成智. 风云三号D星气温观测气候变化应用稳定性评估[J]. 气候变化研究进展, 2025, 21(6): 733-741.

GUO Yan-Jun, ZOU Cheng-Zhi. Evaluation of temporal stability in atmospheric temperature observations from FengYun-3D satellite for climate change research[J]. Climate Change Research, 2025, 21(6): 733-741.

图/表 5

表1 FY-3D和NOAA卫星微波气温探测通道参数对比和气候变化应用稳定性需求

Table 1 Comparison of microwave temperature sounding channels between FY-3D and NOAA, and the temporal stability requirements for climate change

图1 FY-3D 和 FY-3E抬升轨道月均过赤道时刻（LECT）及FY-3D LECT与2019年1月LECT逐月差值

Fig. 1 Monthly mean Ascending Local Equator Crossing Time (LECT) for the FY-3D and FY-3E satellites from 2019 to 2024, along with the FY-3D LECT differences relative to its January 2019

图2 2019—2024年NOAA (a)和FY-3D (b) 9个通道全球、海洋和陆地气温变化趋势对比及两者差值变化趋势(c) 注：直方图代表趋势，误差线代表与序列长度和变率相关的不确定性，信度超过95%，(c)图黑色虚线代表满足稳定性指标阈值。

Fig. 2 Trends of mean-layer temperature anomalies during 2019-2024 for the 9 channels analyzed in this study, averaged over the globe, ocean, and land for NOAA (a), FY-3D (b), and their differences (c). (The bars represent trends with error bars superimposed on them. The trend uncertainty represents 95% confidence intervals with autocorrelation adjustments, which account for time length limitations and temporal variability. The black dashed lines in (c) represent the stability thresholds for the 9 channels)

图3 2019—2024年FY-3D和NOAA 9个通道月平均全球海洋(a)和陆地(b)气温距平和差值序列注：图例中的数字代表通道，例如(a1)图中FY-3D_4代表FY-3D通道4气温距平，NOAA_6代表NOAA通道6气温距平，Diff_4-6代表FY-3D通道4与NOAA通道6的气温距平差值；距平为月平均气温与2019—2023年平均气温的差值；图里数字标注自左至右分别为变化趋势、标准差和相关系数，其中蓝色为NOAA值，红色为FY-3D值，黑色为两者之差或相关值。

Fig. 3 Monthly temperature anomaly time series from 2019 to 2024 for FY-3D and NOAA, and their differences, averaged over the ocean (a) and land (b). (Anomalies are calculated as departures from the 2019-2024 base period. The labels in each panel from left to right represent linear trend and uncertainty, standard deviation, and correlation coefficient, respectively. Blue represents NOAA, red represents FY-3D, and black represents their difference or correlation)

图4 2019—2024年FY-3D通道4与NOAA通道6气温均方根误差空间分布

Fig. 4 Spatial distribution of temperature RMSE between FY-3D channel 4 and NOAA channel 6 during 2019-2024

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