Lagrangian Coherent Structures and Vortex Formation in High Spatiotemporal‐Resolution Satellite Winds of an Atmospheric Kármán Vortex Street

Abstract Recent advances in geostationary imaging have enabled the derivation of high spatiotemporal‐resolution cloud‐motion winds for the study of mesoscale unsteady flows. Due to the general absence of ground truth, the quality assessment of satellite winds is challenging. In the current limited practice, straightforward plausibility checks on the smoothness of the retrieved wind field or tests on aggregated trends such as the mean velocity components are applied for quality control. In this study, we demonstrate additional diagnostic tools based on feature extraction from the retrieved velocity field. Lagrangian Coherent Structures (LCS), such as vortices and transport barriers, guide and constrain the emergence of cloud patterns. Evaluating the alignment of the extracted LCS with the observed cloud patterns can potentially serve as a test of the retrieved wind field to adequately explain the time‐dependent dynamics. We discuss the suitability and expressiveness of direct, geometry‐based, texture‐based, and feature‐based flow visualization methods for the quality assessment of high spatiotemporal‐resolution winds through the real‐world example of an atmospheric Kármán vortex street and its laboratory archetype, the 2D cylinder flow

2018 Atmospheric Motion Vector (AMV): intercomparison study

Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’.The “Space Science and Engineering Center” (SSEC) of the “University ofWisconsin-Madison” (UW) was funded to do this research by the “European Organization for the Exploitation of Meteorological Satellites (EUMETSAT)”, through the “Satellite Application Facility on Support to Nowcasting and Very short range forecasting (NWCSAF)” “Visiting Scientist Activity (VSA)” program

Development of Enhanced Vortex-Scale Atmospheric Motion Vectors for Hurricane Applications

Atmospheric motion vectors (AMVs) derived from geostationary meteorological satellites have long stood as an important observational contributor to analyses of global-scale tropospheric wind patterns. This paradigm is evolving as numerical weather prediction (NWP) models and associated data assimilation systems are at the point of trying to better resolve finer scales. Understanding the physical processes that govern convectively-driven weather systems is usually hindered by a lack of observations on the scales necessary to adequately describe these events. Fortunately, satellite sensors and associated scanning strategies have improved and are now able to resolve convective-scale flow fields. Coupled with the increased availability of computing capacity and more sophisticated algorithms to track cloud motions, we are now poised to investigate the development and application of AMVs to convective-scale weather events. Our study explores this frontier using new-generation GOES-R Series imagery with a focus on hurricane applications. A proposed procedure for processing enhanced AMV datasets derived from multispectral geostationary satellite imagery for hurricane-scale analyses is described. We focus on the use of the recently available GOES-16 mesoscale domain sector rapid-scan (1-min) imagery, and emerging methods to optimally extract wind estimates (atmospheric motion vectors (AMVs)) from close-in-time sequences. It is shown that AMV datasets can be generated on spatiotemporal scales not only useful for global applications, but for mesoscale applications such as hurricanes as well

Lagrangian Coherent Structures and Vortex Formation in High Spatiotemporal‐Resolution Satellite Winds of an Atmospheric Kármán Vortex Street

Recent advances in geostationary imaging have enabled the derivation of high spatiotemporal‐resolution cloud‐motion winds for the study of mesoscale unsteady flows. Due to the general absence of ground truth, the quality assessment of satellite winds is challenging. In the current limited practice, straightforward plausibility checks on the smoothness of the retrieved wind field or tests on aggregated trends such as the mean velocity components are applied for quality control. In this study, we demonstrate additional diagnostic tools based on feature extraction from the retrieved velocity field. Lagrangian Coherent Structures (LCS), such as vortices and transport barriers, guide and constrain the emergence of cloud patterns. Evaluating the alignment of the extracted LCS with the observed cloud patterns can potentially serve as a test of the retrieved wind field to adequately explain the time‐dependent dynamics. We discuss the suitability and expressiveness of direct, geometry‐based, texture‐based, and feature‐based flow visualization methods for the quality assessment of high spatiotemporal‐resolution winds through the real‐world example of an atmospheric Kármán vortex street and its laboratory archetype, the 2D cylinder flow.Key Points: Recently developed high‐cadence geostationary satellite winds enable the Lagrangian analysis of unsteady island wake flows. Good correspondence between Lagrangian Coherent Structures and observed cloud patterns indirectly confirms the fidelity of fluid dynamics. Discussion of benefits and pitfalls of common flow visualization techniques for the analysis of fluid dynamics.Swiss National Science FoundationBundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659https://doi.org/10.5281/zenodo.3534276https://www.avl.class.noaa.gov/https://github.com/tobguent/vislcs-guadalup

A Demonstration of Three-Satellite Stereo Winds

Stereo tracking of clouds from multiple satellites permits the simultaneous retrieval of an atmospheric motion vector (“wind”) and its height in the atmosphere. The direct measurement of height is a major advantage of stereo methods over observations made from a single satellite where the height must be inferred from infrared brightness temperatures. A pair of operational geostationary satellites over the Americas provides stereo coverage where their two fields of view intersect. Stereo coverage can be extended to nearly a full hemisphere with a third satellite. We demonstrate this configuration with the operational GOES-R constellation of GOES-16 (east) and GOES-17 (west) augmented by GOES-18 in its central test slot and use the 500-m resolution Advanced Baseline Imager Band 2. We examine the consistency of the pairwise products created from GOES-18 and -16 versus GOES-18 and -17 and create a fused triple-GOES product that spans nearly the full hemisphere seen from GOES-18. We also examine the retrieval of ground points observed under clear skies and compare their retrievals to zero speed and known terrain heights. The results are compatible with a wind accuracy about 0.1 m/s with height assignment uncertainty of 175 m

A Demonstration of Three-Satellite Stereo Winds

Stereo tracking of clouds from multiple satellites permits the simultaneous retrieval of an atmospheric motion vector (“wind”) and its height in the atmosphere. The direct measurement of height is a major advantage of stereo methods over observations made from a single satellite where the height must be inferred from infrared brightness temperatures. A pair of operational geostationary satellites over the Americas provides stereo coverage where their two fields of view intersect. Stereo coverage can be extended to nearly a full hemisphere with a third satellite. We demonstrate this configuration with the operational GOES-R constellation of GOES-16 (east) and GOES-17 (west) augmented by GOES-18 in its central test slot and use the 500-m resolution Advanced Baseline Imager Band 2. We examine the consistency of the pairwise products created from GOES-18 and -16 versus GOES-18 and -17 and create a fused triple-GOES product that spans nearly the full hemisphere seen from GOES-18. We also examine the retrieval of ground points observed under clear skies and compare their retrievals to zero speed and known terrain heights. The results are compatible with a wind accuracy about 0.1 m/s with height assignment uncertainty of 175 m

Evolution of an Atmospheric Kármán Vortex Street From High‐Resolution Satellite Winds: Guadalupe Island Case Study

Vortex streets formed in the stratocumulus‐capped wake of mountainous islands are the atmospheric analogues of the classic Kármán vortex street observed in laboratory flows past bluff bodies. The quantitative analysis of these mesoscale unsteady atmospheric flows has been hampered by the lack of satellite wind retrievals of sufficiently high spatial and temporal resolution. Taking advantage of the cutting‐edge Advanced Baseline Imager, we derived kilometer‐scale cloud‐motion winds at 5‐min frequency for a vortex street in the lee of Guadalupe Island imaged by Geostationary Operational Environmental Satellite‐16. Combined with Moderate Resolution Imaging Spectroradiometer data, the geostationary imagery also provided accurate stereo cloud‐top heights. The time series of geostationary winds, supplemented with snapshots of ocean surface winds from the Advanced Scatterometer, allowed us to capture the wake oscillations and measure vortex shedding dynamics. The retrievals revealed a markedly asymmetric vortex decay, with cyclonic eddies having larger peak vorticities than anticyclonic eddies at the same downstream location. Drawing on the vast knowledge accumulated about laboratory bluff body flows, we argue that the asymmetric island wake arises from the combined effects of Earth's rotation and Guadalupe's nonaxisymmetric shape resembling an inclined flat plate at low angle of attack. However, numerical simulations will need to establish whether or not the selective destabilization of the shallow atmospheric anticyclonic eddies is caused by the same mechanisms that destabilize the deep columnar anticyclones of laboratory flows, such as three‐dimensional vertical perturbations due to centrifugal or elliptical instabilities