Targeted Observations of Tropical Cyclone Movement Based on the Adjoint-Derived Sensitivity Steering Vector

Wu, Chun‐Chieh; Chen, Jan‐Huey; Lin, Po‐Hsiung; Chou, Kun-Hsuan

doi:10.1175/jas3974.1

Cited by 117 publications

(99 citation statements)

References 17 publications

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“…Traditionally, there are two types of mathematical techniques: the one is based on sensitivity analysis, such as adjoint sensitivity (Bergot 1999), singular vectors (SVs; Palmer et al 1998), and the adjoint-derived sensitivity steering vector (ADSSV; Wu et al 2007), etc. ; and the other is related with data assimilation methods, such as the ensemble transform technique (Bishop and Toth 1999); the ensemble transform Kalman filter (ETKF; Bishop et al 2001), the ensemble Kalman filter (EnKF; Liu and Kalnay 2008); the piece-by-piece data assimilation targeting method (PBPDA; Huang and Meng 2014), etc.…”

Section: The Target Observationmentioning

confidence: 99%

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

Duan

Tian

2018

Clim Dyn

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This paper investigates the optimal observational array for improving the initialization of El Niño-Southern Oscillation predictions by exploring the sensitive areas for target observations of two types of El Niño predictions. The sensitive areas are identified by calculating the optimally growing errors (OGEs) of the Zebiak-Cane model, as corrected by the optimal forcing vector that is determined by assimilating the observed sea surface temperature anomalies (SSTAs). It is found that although the OGEs have similar structures for different start months of predictions, the regions covered by much large errors for the SSTA component tend to locate at different zonal positions and depends on the start months. Furthermore, these regions are also in difference between two types of El Niño events. The regions covered by large errors of OGEs represent the sensitive areas for target observations. Considering the dependence of the sensitive areas on related El Niño types and the start months of predictions, the present study propose a quantitative frequency method to determine the sensitive areas for target observations associated with two types of El Niño predictions, which is expected to be applicable for both types of El Niño predictions with different start months. As a result, the sensitive areas that describe the array of target observations are presented with a reversal triangle-like shape locating in the eastern Pacific, specifically the area of 120°W-85°W, 0°S-11°S, and an extension to the west along the equator and then gathering at the 180° longitude and the western boundary. "Hindcast" experiments demonstrated that such observational array is very useful in distinguishing two types of El Niño and superior to the TAO/TRITON array. It is therefore suggested that the observational array provided in the present study is towards the optimal one and the original TAO/TRITON array should be further optimized when applied to predictions of the diversities of El Niño events.

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Section: The Target Observationmentioning

confidence: 99%

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

Duan

Tian

2018

Clim Dyn

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“…Until recently, many studies used adaptive observation strategies to identify sensitive regions for adaptively observing extratropical or tropical cyclones (e.g. Reynolds, 2005, 2006;Kim and Jung, 2006;Majumdar et al, 2006;Wu et al, 2007;Kim et al, 2008aKim et al, , 2011Kim and Jung, 2009a, b;Jung et al, 2010;Park et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Statistical adjoint sensitivity distributions of meteorological forecast errors of Asian dust transport events in Korea

Kim¹,

Kay²,

Yang³

et al. 2013

Tellus B: Chemical and Physical Meteorology

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A B S T R A C TThe sensitivities of meteorological forecast errors associated with Asian dust transport events to changes in the initial state were evaluated for 46 occurrences that affected the Korean Peninsula from 2005 to 2010. Adjoint-based sensitivities were used to determine these sensitivities. Sensitive regions were located primarily over two regions upstream from the Korean Peninsula: the northern source region, including areas of Mongolia and northern China, and the Tibetan Plateau. Depending on transport trajectories, month, and year, the sensitive regions were located over either the northern source regions or the Tibetan Plateau. That is, the Asian dust forecast in Korea was found to be sensitive to the meteorological fields over the northern source regions, but also those over the Tibetan Plateau even though the latter is not a dust source region or an upstream area according to the transport trajectories. Employing additional observations at existing instrumentation sites or developing new observational sites in both sensitive regions could be beneficial in reducing the atmospheric circulation forecast errors in East Asia, thus improving the accuracy of transport forecasts of Asian dust events affecting the Korean Peninsula.

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“…Adaptive (or targeted) observations have been applied to TCs to increase the accuracy of TC forecasts by decreasing the initial condition uncertainties Reynolds 2005, 2006;Jung 2006, 2009a, b;Kim et al 2011a;Jung et al 2012;Majumdar et al 2006;Wu et al 2007Wu et al , 2009aLang et al 2012). The observational regions detected by adaptive observation strategies are called sensitive regions because the observations in those regions may have a large influence on enhancing weather forecasts (Kim et al 2004a).…”

Section: Introductionmentioning

confidence: 99%

Statistical distributions of singular vectors for tropical cyclones affecting Korea over a 10-year period

Park

Kim

Lee

et al. 2013

Meteorol Atmos Phys

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To investigate the statistical sensitivity distributions of tropical cyclone (TC) forecasts over the Korean Peninsula, total energy (TE) singular vectors (SVs) were calculated and evaluated over a 10-year period. TESVs were calculated using the fifth-generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) and its tangent linear and adjoint models with a Lanczos algorithm over a 48-h period. Chosen cases were 21 TCs that affected the Korean Peninsula among 230 TCs that were generated in the western North Pacific from 2001 to 2010. Sensitive regions indicated by TESVs were mainly located near mid-latitude troughs and TC centers but varied depending on TC track and environmental conditions such as subtropical high and mid-latitude trough. The cases were classified into three groups by clustering TC tracks based on the finite mixture model. The two groups that passed through the western and southern sea of the Korean Peninsula had maximally sensitive regions in the mid-latitude trough and largely sensitive regions around the TC center, while the other group that passed straight through the eastern sea of the Korean Peninsula had maximally sensitive regions near the northeastern region of the TC center. Vertically, the former two clustered groups had the westerly tilted TESVs and potential vorticity structures under the mid-latitude troughs at the initial time, indicating the TCs were in a baroclinic environment. Conversely, the straight-moving TCs were not in a baroclinic environment. Based on the results in the present study, the TCs moving toward a fixed verification region over the Korean Peninsula have different sensitivity regions and structures according to their moving tracks and characteristic environmental conditions, which may provide guidance for targeted observations of TCs affecting the Korean Peninsula.

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Targeted Observations of Tropical Cyclone Movement Based on the Adjoint-Derived Sensitivity Steering Vector

Cited by 117 publications

References 17 publications

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño

Statistical adjoint sensitivity distributions of meteorological forecast errors of Asian dust transport events in Korea

Statistical distributions of singular vectors for tropical cyclones affecting Korea over a 10-year period

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