Parallax Correction in the Analysis of Multiple Satellite Data Sets

Wang, Chunpeng; Huang, Xianglei

doi:10.1109/lgrs.2013.2283573

Cited by 12 publications

(5 citation statements)

References 15 publications

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“…Thinning can also potentially limit impacts of dry biases when assimilating clear-air radiance observations (e.g., Jones et al 2020;Zhu et al 2023). We also apply a parallax correction (Wang and Huang 2014;Jones et al 2020;Johnson et al 2022) to account for potential location errors for cloudy observations caused by the viewing angle of the satellite. Unlike Johnson et al (2022), we do not apply bias correction or any adaptive observation error methods for the channel-10 all-sky radiances.…”

Section: B Observation and Preprocessing Methodsmentioning

confidence: 99%

Assimilation of GOES-16 ABI All-Sky Radiance Observations in RRFS Using EnVar: Methodology, System Development, and Impacts for a Severe Convective Event

Degelia

Wang

et al. 2023

Monthly Weather Review

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The Advanced Baseline Imager (ABI) aboard the GOES-16 and GOES-17 satellites provides high-resolution observations of cloud structures that could be highly beneficial for convective-scale DA. However, only clear-air radiance observations are typically assimilated at operational centers due to a variety of problems associated with cloudy radiance data. As such, many questions remain about how to best assimilate all-sky radiance data, especially when using hybrid DA systems such as EnVar wherein a nonlinear observation operator can lead to cost function gradient imbalance and slow minimization. Here, we develop new methods for assimilating all-sky radiance observations in EnVar using the novel Rapid Refresh Forecasting System (RRFS) that utilizes the Finite-Volume Cubed-Sphere (FV3) model. We first modify the EnVar solver by directly including brightness temperature (Tb) as a state variable. This modification improves the balance of the cost function gradient and speeds up minimization. Including Tb as a state variable also improves the model fit to observations and increases forecast skill compared to utilizing a standard state vector configuration. We also evaluate the impact of assimilating ABI all-sky radiances in RRFS for a severe convective event in the central Great Plains. Assimilating the radiance observations results in better spin-up of a tornadic supercell. These data also aid in suppressing spurious convection by reducing the snow hydrometeor content near the tropopause and weakening spurious anvil clouds. The all-sky radiance observations pair well with reflectivity observations that remove primarily liquid hydrometeors (i.e., rain) closer to the surface. Additionally, the benefits of assimilating the ABI observations continue into the forecast period, especially for localized convective events.

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Section: B Observation and Preprocessing Methodsmentioning

confidence: 99%

Assimilation of GOES-16 ABI All-Sky Radiance Observations in RRFS Using EnVar: Methodology, System Development, and Impacts for a Severe Convective Event

Degelia

Wang

et al. 2023

Monthly Weather Review

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“…Once latitude and longitude coordinates were extracted and calculated, brightness temperatures were converted from the radiances, following procedures explained in Schmit et al (2012). After obtaining latitudes, longitudes, and brightness temperatures, latitude and longitude parallax shifts were computed using the theory discussed in C. Wang and X. Huang (2014) and Bieliński (2020), allowing for accurate latitude and longitude when adjusting the GOES ABI data. Users should remember that the ACHA data file available when this paper was written has a different spatial resolution than the Level 1B radiance data file.…”

Section: Methods For Correcting For Parallax In Goes Abi Datamentioning

confidence: 99%

“…Infrared radiation sensed by the satellite instrument is emitted (or, in the case of visible or nearinfrared radiation, reflected) from the earth's surface or near-surface features and travels to the satellite. C. Wang and X. Huang (2014) describe a general solution to the parallax correction issue concerning the collocation of measurements of the same object from different satellites that use different viewing geometries. Their paper highlights the importance of accurate collocation to avoid introducing incorrect information in the data fusion of multiple sensors on different satellite platforms.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

JOM

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A parallax shift is a displacement in the apparent navigated position of a feature that arises because of its perspective from the viewing platform and is also a function of the feature height. For Geostationary Operational Environmental Satellite (GOES) imagery, this shift is especially apparent away from the satellite subpoint. Users should understand the degree of this shift when combining GOES Advanced Baseline Imager (ABI) imagery with other data, such as radar and lightning. However, it can be challenging, especially at spatial resolutions around the cloud/storm scale. This article explores parallax displacement for both uniform and computed cloud-top heights. Parallax shift will be shown using two case studies. The first case is from 7 September 2021, in which northern Illinois hailstorms are examined using ground-based Level II NEXRAD radar data, GOES-16 ABI imagery, and Geostationary Lightning Mapper data. The second case, on 9 April 2021, examines an eruption of the La Soufrière volcano on St. Vincent from the differing perspectives of GOES-16 and -17. The discussion of these cases will show how parallax is an apparent displacement that will vary depending on what satellites are used for observation, where the phenomenon is with respect to the satellite, and the height of the phenomenon being analyzed. Newer satellite instruments with finer spatial resolutions and improved georeferencing will maximize data usability at more extreme angles and require users to account for the accompanying enhanced parallax shift. Even at lesser angles, parallax displacement is an important consideration for many meteorological and other applications.

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“…Previous studies have shown that careful consideration of observation and model bias, observation error variance and covariance, and quality control is necessary to effectively assimilate all-sky IR radiances (Chandramouli et al, 2022;Johnson et al, 2022;Otkin et al, 2018). Parallax correction is implemented during quality control to account for viewing angle issues in cloudy observations, following C. Wang and Huang (2014), Jones et al (2020), Johnson et al (2022), andDegelia et al (2023). The optimal bias correction method remains an open question and may vary across different microphysics schemes.…”

Section: Assimilated Abi Observationsmentioning

confidence: 99%

Impact of Microphysics Parameterization Schemes on the Assimilation of GOES‐16 ABI All‐Sky Infrared Radiances for a Bow Echo Analysis and Prediction

Kim,

Wang,

Johnson

2024

JGR Atmospheres

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This study aims to investigate how assimilating GOES‐16 ABI infrared brightness temperature (BT) with different microphysics schemes affects the convection‐allowing analysis and prediction of the 3 May 2020 bow echo case. The Gridpoint Statistical Interpolation‐based Ensemble Kalman Filter (GSI‐EnKF) system and Weather Research and Forecasting (WRF) model are utilized to conduct data assimilation (DA) experiments using Thompson, WDM6, NSSL, and Morrison microphysics schemes. Correlation structures between BT and model state variables indicate that assimilating infrared BT can adjust bowing MCS dynamics via latent cooling and the rear inflow jet. Such corrections during DA cycling enhance the rear inflow jet and bow echo size, primarily for microphysics schemes featuring faster hydrometeor fall velocity and stronger latent cooling. The improved analyses lead to better forecasts of the bow echo's shape, size, timing of the bowing process, and wind speeds. Substituting a larger microphysics‐dependent effective radius for a constant default value increases prior BT, the magnitude of BT innovations, and accumulated impact on the rear inflow jet, especially for the WDM6 and Morrison schemes. In the subsequent forecasts, incorporating microphysics‐dependent effective radius further improves the experiment using the Morrison scheme but degrades it when using the WDM6 scheme.

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Parallax Correction in the Analysis of Multiple Satellite Data Sets

Cited by 12 publications

References 15 publications

Assimilation of GOES-16 ABI All-Sky Radiance Observations in RRFS Using EnVar: Methodology, System Development, and Impacts for a Severe Convective Event

Assimilation of GOES-16 ABI All-Sky Radiance Observations in RRFS Using EnVar: Methodology, System Development, and Impacts for a Severe Convective Event

Untitled

Impact of Microphysics Parameterization Schemes on the Assimilation of GOES‐16 ABI All‐Sky Infrared Radiances for a Bow Echo Analysis and Prediction

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