A Long-term Atmospheric Temperature Dataset Derived from NOAA Microwave Sounding Unit with Cross-calibration

Zou Chengzhi; Gao Mei

Vol.19, NO.5, 2008

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Article Navigation > Journal of Applied Meteorological Science > 2008 > 19(5): 582-587

Zou Chengzhi, Gao Mei. A long-term atmospheric temperature dataset derived from NOAA microwave sounding unit with cross-calibration. J Appl Meteor Sci, 2008, 19(5): 582-587.

Citation:

Zou Chengzhi, Gao Mei. A long-term atmospheric temperature dataset derived from NOAA microwave sounding unit with cross-calibration. J Appl Meteor Sci, 2008, 19(5): 582-587.

Zou Chengzhi, Gao Mei. A long-term atmospheric temperature dataset derived from NOAA microwave sounding unit with cross-calibration. J Appl Meteor Sci, 2008, 19(5): 582-587.

Citation:

Zou Chengzhi, Gao Mei. A long-term atmospheric temperature dataset derived from NOAA microwave sounding unit with cross-calibration. J Appl Meteor Sci, 2008, 19(5): 582-587.

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A Long-term Atmospheric Temperature Dataset Derived from NOAA Microwave Sounding Unit with Cross-calibration

Zou Chengzhi¹,
Gao Mei²

1.
Center for Satellite Applications and Research, NESDIS/NOAA, Camp Springs, Maryland 20746, USA
2.
Chinese Academy of Meteorological Sciences, Beijing 100081

Received Date: 2008-05-04
Rev Recd Date: 2008-07-30
Publish Date: 2008-10-31

Abstract

Abstract

The Microwave Sounding Unit(MSU)on board the National Oceanic and Atmospheric Administration(NOAA)polar-orbiting satellites measures the atmospheric temperature from the surface to the lower stratosphere under all weather conditions, excluding precipitation. These instruments are extensively used to determine the atmospheric temperature trend. However, calibration errors are a major source of uncertainties in the trend determination. Recently, NOAA/National Environmental Satellite, Data and Information Services has developed a non-linear sequential calibration method using simultaneous nadir overpass(SNO)to reduce calibration errors and then a long term MSU deep layer atmospheric temperature dataset is generated based on the new calibration. The dataset is introduced, which includes global 5-day averaged deep-layer temperatures for the mid-troposphere, tropopause, and lower-stratosphere with grid resolution of 2.5° latitude by 2.5° longitude. Also, the methodologies for the dataset generation are described, which including cross-calibration, incident angle correction, grid data generation, and bias correction in gridded data. The 20-year climate trends during 1987—2006 for the three layers are obtained from the dataset. Finally, the website for acquiring the dataset is provided.
- NOAA;
- satellite;
- MSU;
- microwave sounding;
- atmospheric temperature;
- calibration

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References(14)

Figures and Tables

图 1 定标原理

Fig. 1 Schematic viewing the calibration principle of the Microwave Sounding Unit

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图 2 用NOAA 11和NOAA 12的SNO亮温比较线性定标和非线性SNO定标效果

(a)线性定标的离散亮温比较,(b)非线性SNO定标的离散亮温比较, (c)对应(a)的两颗卫星亮温差与温度的比较,(d)对应(b)的两颗卫星亮温差与温度的比较(T_l代表线性定标所产生的亮温, T_b代表非线性定标所产生的亮温; N11和N12分别代表NOAA 11和NOAA 12)

Fig. 2 Demonstration of the SNO non-linear calibration effect with scatter plots of the SNO brightness temperatures between NOAA-11 and NOAA-12

(a)T_l scatter plot between NOAA-11 and NOAA-12 with linear calibration,(b)T_b scatter plot between NOAA-11 and NOAA-12 with SNO non-linear calibration,(c)T_l differences between NOAA-12 and NOAA-11 versus NOAA-11 T_l,(d)T_b differences between NOAA-12 and NOAA-11 versus NOAA-11 T_b (T_l represents brightness temperature obtained from linear calibration and T_b is the brightness temperature obtained from the SNO nonlinear calibration; N11 and N12 represent NOAA-11 and NOAA-12, respectively)

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图 3 不同卫星之间的亮温差时间序列

Fig. 3 Brightness temperature difference time series of 5-day and global ocean averages between different satellites

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图 4 合成后的20年海洋平均亮温异常时间序列

Fig. 4 20-year anomaly time series of the composite brightness temperatures

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