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The Gain-Related Calibration of HY-2B Scatterometer Using Natural Targets | IEEE Journals & Magazine | IEEE Xplore

The Gain-Related Calibration of HY-2B Scatterometer Using Natural Targets


Abstract:

The HY-2 series scatterometers (HSCAT) are now providing global Ku-band radar observations. In order to build two-decade normalized radar cross section ( $\sigma ^{\circ ...Show More

Abstract:

The HY-2 series scatterometers (HSCAT) are now providing global Ku-band radar observations. In order to build two-decade normalized radar cross section ( \sigma ^{\circ } ) datasets with high quality and high stability, increased attention should first be paid to the instrument variations caused by space environments. The HY-2B scatterometer (HSCAT-B) has operated to yield a two-year dataset in orbit. The monitoring of long-term ocean calibration results and telemetric temperatures indicate that beam radiometric imbalances and long-term instability exist in \sigma ^{\circ } due to the gain variations related to temperature changes. Such variations will result in estimated \sigma ^{\circ } biases with a peak-to-peak of approximately 0.5 dB. Gain-related calibration models depicting the functions of temperatures were developed using ocean calibration results. The beam radiometric imbalances were corrected using linear gain compensation models of antenna temperatures. The long-term instability was corrected using a linear dependence on microwave front-end and antenna temperatures. Following gain-related calibration, the beam imbalances and long-term instability of the HSCAT-B \sigma ^{\circ } were eliminated. The seasonal responses over the Amazon rainforest were also found to correspond to the QuikSCAT \sigma ^{\circ } measurements, with amplitudes of approximately 0.15 dB for the morning passes and approximately 0.1 dB for the evening passes. The corrected \sigma ^{\circ } will be more suitable for the generation of climate data records. In addition, with the exception of the prelaunch thermal vacuum test, the external calibrations using natural targets are considered to be alternative approaches to gain-related calibrations due to the temperature variations of radar electronics.
Article Sequence Number: 5212911
Date of Publication: 05 October 2021

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I. Introduction

The HY-2 satellite series scatterometers (HSCAT) are Ku-band spaceborne radars which were designed to continuously measure the normalized radar cross section () over the earth’s surface. At the present time, HSCAT-B is on board the HY-2B satellite, which was launched in October 2018, and HSCAT-C is on board the HY-2C satellite, which was launched in September 2020. The high-precision HSCAT-B and HSCAT-C will contribute to the Ocean Surface Vector Wind Virtual Constellation (OSVW-VC) developed by Committee on Earth Observation Satellite (CEOS), together with the other scatterometers. In climate monitoring, the stability of observation requirement for near-surface wind speed defined by World Meteorological Organization is 0.05 m/s per decade, which corresponds to 0.05 dB. A high-precision single scatterometer will be the basis of the highest quality OSVW-VC and will have major value for global climate change research. Based on the state-of-the-art calibration and validation technique, the long-term stability of is expected to be within 0.1 dB [23]. In order to achieve this goal, post-launch calibrations and monitoring of the HSCAT-B are essential for ensuring continuous and consistent in-orbit dataset, due to the fact that gain variations over time may occur as the results of space environment variations, aging of the microwave components, antenna deformations, and so on. During the calibration and validation procedures, natural extended-area targets, such as the Amazon rainforest, open-ocean, and sea ice target, have been used for the launched scatterometers [1]–[23].

Select All
1.
M. W. Spencer et al., "NASA Scatterometer calibration philosophy and approach", Proc. SPIE, vol. 1935, pp. 63-73, Aug. 1993.
2.
W.-Y. Tsai et al., "Postlaunch sensor verification and calibration of the NASA Scatterometer", IEEE Trans. Geosci. Remote Sens., vol. 37, no. 3, pp. 1517-1542, May 1999.
3.
C. Wu et al., "Design and calibration of SeaWinds scatterometer", IEEE Trans. Aerosp. Electron. Syst., vol. 39, no. 1, pp. 94-108, Jan. 2003.
4.
T. Misra et al., " Oceansat-II scatterometer: Sensor performance evaluation σ 0 analyses and estimation of biases ", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 6, pp. 3310-3315, Jun. 2014.
5.
A. Stoffelen, "A simple method for calibration of a scatterometer over the ocean", J. Atmos. Ocean. Technol., vol. 16, no. 2, pp. 275-282, Feb. 1999.
6.
M. H. Freilich and H. Qi, "Scatterometer beam balancing using open-ocean backscatter measurements", J. Atmos. Ocean. Technol., vol. 16, no. 2, pp. 283-297, 1999.
7.
J. Verspeek, "Scatterometer calibration tool development", 2006.
8.
A. Elyouncha and X. Neyt, "C-band satellite scatterometer intercalibration", IEEE Trans. Geosci. Remote Sens., vol. 51, no. 3, pp. 1478-1491, Mar. 2013.
9.
A. Elyouncha et al., "Inter-calibration of Metop-A and Metop-B scatterometers using ocean measurements", Proc. SPIE, vol. 747, pp. 6-13, Oct. 2013.
10.
B. Mu and Q. Song, "In-orbit radiometric calibration of the HY-2A microwave scatterometer through open ocean measurements", J. Remote Sens., vol. 18, no. 5, pp. 1072-1078, Mar. 2014.
11.
I. J. Birrer, E. M. Bracalente, G. J. Dome, J. Sweet and G. Berthold, "σ° signature of the Amazon rain forest obtained from the seasat scatterometer", IEEE Trans. Geosci. Remote Sens., vol. GE-20, no. 1, pp. 11-17, Jan. 1982.
12.
D. G. Long and G. B. Skouson, "Calibration of spaceborne scatterometers using tropical rain forests", IEEE Trans. Geosci. Remote Sens., vol. 34, no. 2, pp. 413-424, Mar. 1996.
13.
J. Zec, D. G. Long and W. L. Jones, "NSCAT normalized radar backscattering coefficient biases using homogenous land targets", J. Geophys. Res. Oceans, vol. 104, no. C5, pp. 11557-11568, May 1999.
14.
J. Zec, W. L. Jones and D. G. Long, "SeaWinds beam and slice balance using data over Amazonian rainforest", Proc. IGARSS, pp. 2215-2217, 2000.
15.
L. B. Kunz and D. G. Long, "Calibrating SeaWinds and QuikSCAT scatterometers using natural land targets", IEEE Geosci. Remote Sens. Lett., vol. 2, no. 2, pp. 182-186, Apr. 2005.
16.
R. Kumar, S. A. Bhowmick, K. N. Babu, R. Nigam and A. Sarkar, "Relative calibration using natural terrestrial targets: A preparation towards Oceansat-2 scatterometer", IEEE Trans. Geosci. Remote Sens., vol. 49, no. 6, pp. 2268-2273, Jun. 2011.
17.
J. C. Barrus, "Intercalibration of QuikSCAT and OSCAT land backscatter", 2013.
18.
S. Jaruwatanadilok and B. W. Stiles, "Trends and variation in Ku-band backscatter of natural targets on land observed in QuikSCAT data", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp. 4383-4390, Jul. 2014.
19.
S. A. Bhowmick, R. Kumar and A. S. K. Kumar, "Cross calibration of the OceanSAT-2 scatterometer with QuikSCAT scatterometer using natural terrestrial targets", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 6, pp. 3393-3398, Jun. 2014.
20.
N. M. Madsen and D. G. Long, "Calibration and validation of the RapidScat scatterometer using tropical rainforests", IEEE Trans. Geosci. Remote Sens., vol. 54, no. 5, pp. 2846-2854, May 2016.
21.
J. Zec, W. L. Jones, R. Alsabah and A. Al-Sabbagh, "RapidScat cross-calibration using the double difference technique", Remote Sens., vol. 9, no. 11, pp. 1160-1173, 2017.
22.
Y. Zhang, B. Mu, M. Lin and Q. Song, "An evaluation of the Chinese HY-2B Satellite’s microwave scatterometer instrument", IEEE Trans. Geosci. Remote Sens., vol. 59, no. 6, pp. 4513-4521, Jun. 2021.
23.
A. Verhoef, J. Vogelzang, J. Verspeek and A. Stoffelen, "Long-term scatterometer wind climate data records", IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 10, no. 5, pp. 2186-2194, May 2017.
24.
C. A. Mears, D. K. Smith and F. J. Wentz, "Comparison of special sensor microwave imager and buoy-measured wind speeds from 1987 to 1997", J. Geophys. Res. Oceans, vol. 106, no. C6, pp. 11719-11729, Jun. 2001.
25.
H. Hersbach et al., ERA5 hourly data on single levels from 1979 to present, U.K, Dec. 2020.

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