Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

Joint Authors

Zhang, Qin
Ye, Junhua
Zhang, Shuangcheng
Han, Fei

Source

Journal of Sensors

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-12-24

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Civil Engineering

Abstract EN

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV.

In general, these methods can be divided into two categories, ground-based or space-based.

In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde.

Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO.

Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde.

Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area.

FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized.

So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area.

Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation.

NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water.

We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV.

In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

American Psychological Association (APA)

Zhang, Qin& Ye, Junhua& Zhang, Shuangcheng& Han, Fei. 2018. Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data. Journal of Sensors،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1201087

Modern Language Association (MLA)

Zhang, Qin…[et al.]. Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data. Journal of Sensors No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1201087

American Medical Association (AMA)

Zhang, Qin& Ye, Junhua& Zhang, Shuangcheng& Han, Fei. Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1201087

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1201087