An Analytic Solution to Precipitation Attenuation Expression with Spaceborne Synthetic Aperture Radar Based on Volterra Integral Equation

Luo, Ting; Xie, Yuee; Wang, Rui; Yu, Xueying

doi:10.3390/rs14020357

Cited by 4 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Changes in reflectivity structure are not only a direct result of the change in scattering properties by representing mixed‐phase particles, but also from the change in squall line structure and evolution. The reflectivity parameterization described here does not account for attenuation (e.g., Luo et al., 2022). Although this study only examined a single case, the changes to reflectivity structure and the bright band with predicted liquid fraction are consistent with expected behavior, and likely to be general.…”

Section: Discussionmentioning

confidence: 99%

Combining Triple‐Moment Ice With Prognostic Liquid Fraction in the P3 Microphysics Scheme: Impacts on a Simulated Squall Line

Cholette

Milbrandt

Morrison

et al. 2023

J Adv Model Earth Syst

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Combining Triple‐Moment Ice With Prognostic Liquid Fraction in the P3 Microphysics Scheme: Impacts on a Simulated Squall Line

Cholette

Milbrandt

Morrison

et al. 2023

J Adv Model Earth Syst

View full text Add to dashboard Cite

show abstract

“…The MOS inversion method performs statistical calculations on simulated NRCS data, yielding the mean vector m cSAR and the covariance matrix C cSAR . The typical parameter vector derived from the actual equivalent NRCS data acquired by SAR is denoted as x mSAR [39]. Comparing simulation and observation, we calculate the likelihood distance as follows:…”

Section: Retrieval Of Precipitation Distributionmentioning

confidence: 99%

Evaluating the Effects of Raindrop Motion on the Accuracy of the Precipitation Inversion Algorithm by X-SAR

Yu,

Xie,

Wang

2024

Atmosphere

Self Cite

View full text Add to dashboard Cite

Precipitation has a profound impact on both human life and the natural environment. X-band synthetic aperture radar (X-SAR) utilizes high-resolution microwave remote-sensing technology, providing opportunities for global precipitation measurements. The current precipitation inversion algorithms from X-SAR measurements assume that precipitation particles remain relatively stationary with the ground. However, the motion of raindrops could potentially reduce the accuracy of these algorithms. In this study, we first established a functional relationship between raindrop motion and SAR echoes based on the standard deviation of the raindrop Doppler velocity spectrum. Secondly, an exploratory algorithm was proposed to retrieve rainfall distribution under the raindrop motion error model (RMM) and quantitatively calculate the precipitation inversion error caused by raindrop motion. In comparison to conditions where the atmosphere is stationary, when the standard deviation of the Doppler velocity spectrum of raindrops is 1.1 m/s, the relative error of the retrieved surface rain rate increases from 2.1% to 35.8%. Numerical simulations show that SAR echoes are sensitive to changes in the standard deviation of the Doppler velocity spectrum, and the impact of raindrop motion on the accuracy of X-SAR precipitation measurements cannot be neglected.

show abstract

An Algorithm for Retrieving the 2-D Distribution of Moderate Rain by X-SAR

Xie

Wang

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

Synthetic aperture radar (SAR) can detect ground information with high precision, which provides another opportunity for the retrieval of rain. Rainfall intensities in East Asia are mainly moderate. The current retrieval algorithms have high accuracy in rainstorms, but they overestimate the rainfall intensity greatly in moderate rain. Therefore, it is very important to reduce the retrieval error of SAR in moderate rain. After analyzing the scattering model of precipitation, this paper proposes an algorithm for retrieving 2-D moderate rain distribution (MRA). Since the 2-D distribution of rain is related to the vertical and horizontal distributions, MRA combines the empirical regression equation with the directional model of rain rates at different levels to retrieve the vertical distribution of precipitation. Compared with the model-oriented statistical (MOS) algorithm, MRA reduces the root mean square error when retrieving the surface rain rate from 2.6 to 0.1. In addition, based on the high-precision rain parameters retrieved by MRA, the horizontal distribution is retrieved through the likelihood distance. This horizontal distribution retrieval method not only has less amount of calculation but also avoids the difficulties of mathematical analysis.

show abstract

An Analytic Solution to Precipitation Attenuation Expression with Spaceborne Synthetic Aperture Radar Based on Volterra Integral Equation

Cited by 4 publications

References 23 publications

Combining Triple‐Moment Ice With Prognostic Liquid Fraction in the P3 Microphysics Scheme: Impacts on a Simulated Squall Line

Combining Triple‐Moment Ice With Prognostic Liquid Fraction in the P3 Microphysics Scheme: Impacts on a Simulated Squall Line

Evaluating the Effects of Raindrop Motion on the Accuracy of the Precipitation Inversion Algorithm by X-SAR

An Algorithm for Retrieving the 2-D Distribution of Moderate Rain by X-SAR

Contact Info

Product

Resources

About