Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations

Asgarimehr, Milad; Hoseini, Mostafa; Semmling, Maximilian; Ramatschi, Markus; Camps, Adriano; Nahavandchi, Hossein; Haas, Rüdiger; Wickert, Jens

doi:10.1109/tgrs.2021.3062492

Cited by 19 publications

(7 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and as the wind speed increases, the mss increments are marginal with respect to the mss in rain-free conditions, and therefore the change in the DDM peak is negligible. These large variations of the DDM peak are in agreement with the experimental results presented in [25] and [26].…”

Section: G Impact Of Rainsupporting

confidence: 92%

Sensitivity of Delay Doppler Map in Spaceborne GNSS-R to Geophysical Variables of the Ocean

Camps

Park

2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

Global Navigation Satellite Systems reflectometry (GNSS-R) is a particular case of a multistatic radar in which the signals transmitted by navigation satellites are the signals of opportunity. These signals can be processed as a radar scatterometer, as a radar altimeter, or as an unfocused synthetic aperture radar. GNSS-R has shown its potential to infer numerous geophysical variables: over land soil moisture, vegetation height, detection of freeze-thaw state, etc., map sea ice extent and type …, and over the ocean wind speed and direction, significant wave height, altimetric measurements or even more recently NASA has released a marine plastics litter product, and some also claim that sea surface salinity (SSS) can be inferred. In addition, retrieval algorithms neglect some of the variations of the delay Doppler map (DDM) that are linked to the observation geometry, i.e., look angle with respect to the speed vectors of the transmitter and receiver. All these different effects impact the DDM peak value and its shape, and may affect the retrieval of geophysical parameters, and ultimately the data interpretation. In this study, the following factors impacting the DDM peak value are studied: the observation geometry, the sea surface temperature, and SSS, the 10 m height wind speed (U 10 ) and direction (WD), the presence of foam, the sea development state, the presence of swell, currents, rain, and the presence of oil slicks perturbing the sea surface roughness. This illustrates the complexity of the challenges presented when trying to retrieve some of these variables, the required corrections, and their accuracy.

show abstract

Section: G Impact Of Rainsupporting

confidence: 92%

Sensitivity of Delay Doppler Map in Spaceborne GNSS-R to Geophysical Variables of the Ocean

Camps

Park

2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Minfeng Song, Xiufeng He, Dongzhen Jia, Ruya Xiao, Xiaolei Wang, Zhetao Zhang are with the School of Earth Sciences and Engineering, Hohai gradually developed during recent decades since the first usage as a new remote sensing concept was proposed in [1] [2]. Numerous studies based on the spaceborne measurements demonstrated the potential of GNSS-R to sense the Earth's surface [3], including sea surface height [4] [5] [6], wind speed [7] [8], soil moisture [9][10], sea ice [11] [12], and potentially precipitation over calm oceans [13] [14]. Compared to spaceborne scenarios, the ground-based GNSS interferometry reflectometry (GNSS-IR) technique based on interference data represented by SNR records is an even lower cost and higher temporal and spatial resolution Earth monitoring approach.…”

mentioning

confidence: 99%

Sea Surface States Detection in Polar Regions Using Measurements of Ground-Based GNSS Interferometric Reflectometry

Song

Jia

et al. 2022

IEEE Trans. Geosci. Remote Sensing

Self Cite

View full text Add to dashboard Cite

This paperanalyzes the interferometric measurements of ground-based Global Navigation Satellite Systems (GNSS) stations and proposes a novel method for sea surface states detection. The novel technique benefits from a costeffective data collection from a large number of global GNSS stations. In this study, we extend a traditional GNSS interferometry reflectometry (GNSS-IR) model so that it can be applied to a multilayer surface by considering the surface roughness, total reflectivity, and penetration loss in multilayer situations. Based on this model, the wavelet analysis is used to perform parameterization on the interferometric observations represented by the Signal to Noise Ratio (SNR). An integration factor and power curve are also proposed to characterize the surface state transition. One-year data from an Arctic geodetic GNSS station in the north of Canada are collected for analysis to validate the proposed approach with comparisons to the existing methods based on the amplitude and damping factors. The results show that the new method demonstrates good usability and sensitivity to detect surface state transitions, eg. icing, snowfall, and snow melting. However, the amplitude and damping factorbased methods derived from the single-layer model are only able to detect the pure ice surface and cannot respond to thick snow conditions. Finally, the high-resolution spaceborne images confirm the reliability of this method, exhibiting a great potential for long-term coastal sea surface detection based on the global geodetic GNSS stations and later being expected to be applied to sense cryosphere surface states.

show abstract

“…In addition, rainfall, as a common natural phenomenon at the sea surface, not only desalinates the salinity of seawater, but also causes changes in the roughness of the sea surface [41]. Although CYGNSS observables can provide some response to rainfall-induced roughness changes, this response is limited.…”

Section: Discussionmentioning

confidence: 99%

Correction of the SMAP Sea Surface Brightness Temperature and Retrieval of Sea Surface Salinity Incorporating CYGNSS Observables

Li,

Guo,

Zhang

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

The correction of sea surface brightness temperature is crucial for improving the accuracy of sea surface salinity (SSS) retrieval by L-band microwave radiometer. However, the traditional method of correcting brightness temperature using only wind speed and significant wave height (SWH) is inadequate, as sea surface roughness is affected by multiple factors. The Global Navigation Satellite System Reflectometer (GNSS-R) observables, which directly respond to sea surface roughness, have been preliminarily validated in groundbased experiments for their potential to correct sea surface brightness temperature. Compared to ground-based GNSS-R, spaceborne GNSS-R has a wider coverage and can better support the brightness temperature correction of spaceborne L-band microwave radiometers. This paper has preliminarily verified the correlation between Cyclone GNSS (CYGNSS) observables and brightness temperature variations, and found that the incidence angle of the observable needs to be taken into account when retrieving SSS jointly with Soil Moisture Active and Passive (SMAP) and CYGNSS. A multilayer perceptron (MLP) model was established to assess the SSS retrieval performance of SMAP combined with different parameters. The results show that the retrieval performance based on the MLP model is better than that based on the geophysical model function (GMF) model. Compared to joint wind speed and SWH, joint CYGNSS observables performs better in retrieving SSS. The root mean square error (RMSE) of retrieval salinity decreased from 0.58 to 0.46 psu, and the correlation coefficient (R) increased from 0.83 to 0.90. This provides reference for future joint retrieval of SSS using Lband microwave radiometers and spaceborne GNSS-R.

show abstract

Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations

Cited by 19 publications

References 36 publications

Sensitivity of Delay Doppler Map in Spaceborne GNSS-R to Geophysical Variables of the Ocean

Sensitivity of Delay Doppler Map in Spaceborne GNSS-R to Geophysical Variables of the Ocean

Sea Surface States Detection in Polar Regions Using Measurements of Ground-Based GNSS Interferometric Reflectometry

Correction of the SMAP Sea Surface Brightness Temperature and Retrieval of Sea Surface Salinity Incorporating CYGNSS Observables

Contact Info

Product

Resources

About