Evaluation of Surface Clutter for Future Geostationary Spaceborne Weather Radar

Li, Xuehua; He, Jinhai; Wang, Chuanzhi; Tang, Shunxian; Hou, Xiaoyu

doi:10.3390/atmos8010014

Cited by 7 publications

(13 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The simulated results are consistent with Takahashi (2017) and Li et al (2017), suggesting that both…”

Section: Homogeneous Casesupporting

confidence: 73%

“…However, the impact of the surface clutter and the oblique measurement would depend on the shape and position of the precipitation system. This study extends Li et al (2017) for a realistic case. By considering the importance to societal and scientific benefit, we chose a typhoon as a test case in this study.…”

Section: Introductionsupporting

confidence: 54%

“…They showed that the direct measurement of winds from the geostationary orbit would be possible for a hurricane case. Li et al (2017) evaluated the impact of surface clutter for the same radar assuming a uniform rain layer. They showed that most of rain echoes at off-nadir scanning angles will not be contaminated by the surface clutter, when rain intensity is greater than 10 mm h -1 .…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simulating precipitation radar observations from a geostationary satellite

Okazaki¹,

Honda²,

Kotsuki³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Spaceborne precipitation radars, such as the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) Core Observatory, have been important platforms to provide a direct measurement of three-dimensional precipitation structure globally. Building upon the success of TRMM and GPM Core Observatory, the Japan Aerospace Exploration Agency (JAXA) is currently surveying the feasibility of a potential satellite mission equipped with a precipitation radar on a geostationary orbit. The quasi-continuous observation realized by the geostationary satellite radar would offer a new insight into meteorology and would advance numerical weather prediction (NWP) through their effective use by data assimilation. Although the radar would be beneficial, the radar on the geostationary orbit measures precipitation obliquely at off-nadir points. Besides, the observing resolution will be several times larger than those onboard TRMM and GPM Core Observatory due to the limited antenna size that we could deliver. The tilted sampling volume and the coarse resolution would result in more contaminations from the surface clutters. To investigate the impact of these limitations and to explore the potential usefulness of the geostationary satellite radar, this study simulates the observation data for a typhoon case using an NWP model and a radar simulator. The results demonstrate that it would be possible to obtain three-dimensional precipitation data. However, the quality of the observation depends on the beam width, the beam sampling span, and the position of precipitation systems. With a wide beam width and a coarse beam span, the radar cannot observe weak precipitation at low altitudes due to the surface clutters. The limitation can be mitigated by oversampling (i.e., a wide beam width and a fine sampling span). With a narrow beam width and a fine beam sampling span, the surface clutter interference is confined to the surface level. When the precipitation system is located far from the nadir, the precipitation signal is obtained only for strong precipitation.

show abstract

“…The simulated results are consistent with Takahashi (2017) and Li et al (2017), suggesting that both…”

Section: Homogeneous Casesupporting

confidence: 73%

Section: Introductionsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulating precipitation radar observations from a geostationary satellite

Okazaki¹,

Honda²,

Kotsuki³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Therefore, the antenna gain corresponding to the precipitation particles is different in different positions in a GSDWR beam element, so that the echo power is also different and must, therefore, be antenna weighted [25]. The weighting function expression is shown in Equation (15).…”

Section: Analysis Of the Simulation Resultsmentioning

confidence: 99%

“…Although the Geostationary Spaceborne Doppler Weather Radar (GSDWR) is still a conceptual radar [1,13,14], it has been studied in the United States and China and some of the related parameters of the radar system are shown in Table 1. The GSDWR is designed to work in geostationary orbit at an altitude of 36,000 km, with a maximum scan angle of 4 • , and a spiral scanned antenna beam [15]. The scan model is shown in Figure 1a.…”

Section: Gsdwr Introductionmentioning

confidence: 99%

A Velocity Dealiasing Algorithm on Frequency Diversity Pulse-Pair for Future Geostationary Spaceborne Doppler Weather Radar

Wang

Qin

et al. 2018

Atmosphere

Self Cite

View full text Add to dashboard Cite

Velocity ambiguity is one of the main challenges in accurately measuring velocity for the future Geostationary Spaceborne Doppler Weather Radar (GSDWR) due to its short wavelength. The aim of this work was to provide a novel velocity dealiasing method for frequency diversity for the future implementation of GSDWR. Two different carrier frequencies were transmitted on the adjacent pulse-pair and the order of the pulse-pair was exchanged during the transmission of the next pulse-pair. The Doppler phase shift between these two adjacent pulses was estimated based on the technique of the frequency diversity pulse-pair (FDPP), and Doppler velocity was estimated on the sum of the Doppler phase within the adjacent pulse repetition time (PRT). From the theoretical result, the maximum unambiguous velocity estimated by FDPP is only decided by the interval time of the two adjacent pulses and radar wavelength. An echo signal model on frequency diversity was established to simulate echo signals of the GSDWR to verify the extension of the maximum unambiguous velocity and the accuracy of the velocity estimation for FDPP used on GSDWR. The study demonstrates that the FDPP algorithm can extend the maximum unambiguous velocity greater than the Stagger PRT method and the unambiguous range and velocity are no longer limited by the chosen value of pulse repetition frequency (PRF). In the Ka band, the maximum unambiguous velocity can be extended to 105 m/s when the interval time is 10 µs and most velocity estimation biases are less than 0.5 m/s.

show abstract

Oversampling Reflectivity Observations From a Geostationary Precipitation Radar Satellite: Impact on Typhoon Forecasts Within a Perfect Model OSSE Framework

Taylor

Okazaki

Honda

et al. 2021

J Adv Model Earth Syst

View full text Add to dashboard Cite

For the past two decades, precipitation radars (PR) onboard low-orbiting satellites such as Tropical Rainfall Measuring Mission (TRMM) have provided invaluable insight into global precipitation variability and led to advancements in numerical weather prediction through data assimilation. Building upon this success, planning has begun on the next generation of satellite-based PR instruments, with the consideration for a future geostationary-based PR (GPR), bringing the advantage of higher observation frequency over previous and current PR satellites. Following the successful demonstration by a recent study to test the feasibility of a GPR to obtain three-dimensional precipitation data, this study takes the first step to investigate the potential usefulness of GPR observations for numerical weather prediction by performing a perfect model observing system simulation experiment (OSSE) for a West Pacific tropical cyclone (TC). Data assimilation experiments are performed assimilating reflectivity observations obtained for a range of beam sampling spans, following a previous finding that oversampling improves observation quality. Results showed observations obtained with finer sampling spans of 5 km and 10 km were able to better capture key tropical cyclone features in analyses, including the eye, heavy rainfall associated with the eyewall, and outer convective rainbands. Results also showed that through increased moistening and upward velocity within the inner storm environment, assimilation of observations drove an intensification of the secondary circulation and deepening of the storm, leading to an improvement in TC intensity error. Intensity forecasts were found improved for assimilation of observations obtained with increasingly finer beam sampling span, suggesting an important benefit of oversampling. Plain Language SummaryIn a recent study, the feasibility of a future precipitation radar based onboard a geostationary satellite (GPR) that could obtain three-dimensional precipitation measurements was successfully tested. In this study, we take the first step to investigate whether reflectivity observations can be used to improve analyses and forecasts of global weather systems. We perform data assimilation experiments that use simulated GPR observations for a West Pacific tropical cyclone, with observations obtained with varying radar beam sampling spans to generate observation oversampling, following a previous finding that this improves observation quality. Results found that key convective features of the tropical cyclone (TC), including the eye, eyewall structure, and outer rainbands, were all better captured in simulations assimilating observations obtained with finer beam sampling spans, with 5 km sampling providing best results. Observations were also found to have a positive impact on TC intensity in both model analyses and forecasts, with forecast errors for minimum sea level pressure improved at all lead times up to 18 h. TC intensity forecasts were also improved with increasingly finer beam span, sugge...

show abstract

Evaluation of Surface Clutter for Future Geostationary Spaceborne Weather Radar

Cited by 7 publications

References 15 publications

Simulating precipitation radar observations from a geostationary satellite

Simulating precipitation radar observations from a geostationary satellite

A Velocity Dealiasing Algorithm on Frequency Diversity Pulse-Pair for Future Geostationary Spaceborne Doppler Weather Radar

Oversampling Reflectivity Observations From a Geostationary Precipitation Radar Satellite: Impact on Typhoon Forecasts Within a Perfect Model OSSE Framework

Contact Info

Product

Resources

About