TY - GEN
T1 - Evaluating Reflectivity Quality of the New Airship-Borne Weather Radar Using the S-Band Ground-Based Weather Radar in China
AU - Han, Shuo
AU - Dong, Xichao
AU - Chen, Xin Peng
AU - Liu, Fang
AU - Zhu, Lin
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper analyzes the reliability of the reflectivity data from the Ku-band airship-borne weather radar (AR) based on the observations of four precipitation processes using the AR and China's S-band new generation weather radar (CINRAD/SA) between 2022 and 2023. When observing relatively uniform precipitation, the standard deviation of the reflectivity data from the AR is consistently more than 80% lower than the theoretical 1dB. This indicates that the reflectivity data from the AR exhibits minimal fluctuations and satisfies the design requirements of the radar. Furthermore, when observing convective precipitation, the echo structures observed by the AR are generally consistent with those observed by CINRAD/SA. However, the AR has a higher range resolution, enabling it to capture more detailed precipitation structures. Lastly, the average deviation between the reflectivity data from the AR and the matching data from CINRAD/SA is less than 1dB, indicating good linear consistency. This suggests that the reflectivity data from the AR is reliable.
AB - This paper analyzes the reliability of the reflectivity data from the Ku-band airship-borne weather radar (AR) based on the observations of four precipitation processes using the AR and China's S-band new generation weather radar (CINRAD/SA) between 2022 and 2023. When observing relatively uniform precipitation, the standard deviation of the reflectivity data from the AR is consistently more than 80% lower than the theoretical 1dB. This indicates that the reflectivity data from the AR exhibits minimal fluctuations and satisfies the design requirements of the radar. Furthermore, when observing convective precipitation, the echo structures observed by the AR are generally consistent with those observed by CINRAD/SA. However, the AR has a higher range resolution, enabling it to capture more detailed precipitation structures. Lastly, the average deviation between the reflectivity data from the AR and the matching data from CINRAD/SA is less than 1dB, indicating good linear consistency. This suggests that the reflectivity data from the AR is reliable.
KW - Data quality
KW - Quantitative comparative analysis
KW - Standard deviation analysis
KW - Weather radar
UR - http://www.scopus.com/inward/record.url?scp=85178364072&partnerID=8YFLogxK
U2 - 10.1109/IGARSS52108.2023.10281824
DO - 10.1109/IGARSS52108.2023.10281824
M3 - Conference contribution
AN - SCOPUS:85178364072
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3811
EP - 3814
BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Y2 - 16 July 2023 through 21 July 2023
ER -