Study on Adjoint-Based Targeted Observation of Mesoscale Low on Meiyu Front

2009 ◽  
pp. 253-268
Author(s):  
Peiming Dong ◽  
Ke Zhong ◽  
Sixiong Zhao
Keyword(s):  
Meiyu Front ◽  
Targeted Observation ◽  
Mesoscale Low

Characteristics of Convections of Medium Depth to South of the Meiyu Front Analyzed by Using Numerical Simulation

SOLA ◽  
2006 ◽  
Vol 2 ◽  
pp. 160-163 ◽  
Author(s):  
Cheng-Zhong Zhang ◽  
Hiroshi Uyeda ◽  
Hiroyuki Yamada ◽  
Biao Geng
Keyword(s):  
Numerical Simulation ◽  
Meiyu Front

Physical Mechanism of Formation of the Bimodal Structure in the Meiyu Front System

2005 ◽  
Vol 22 (12) ◽  
pp. 3218-3220
Author(s):  
Cui Xiao-Peng ◽  
Gao Shou-Ting ◽  
Zong Zhi-Ping ◽  
Liu Wen-Ming ◽  
Li Xiao-Fan
Keyword(s):  
Physical Mechanism ◽  
Mechanism Of Formation ◽  
Bimodal Structure ◽  
Meiyu Front

A meso-α-scale study of meiyu front heavy rain—Part II : The dynamical analysis of rain-band disturbance

1987 ◽  
Vol 4 (4) ◽  
pp. 485-495 ◽  
Author(s):  
Yang Guoxiang ◽  
Lu Hancheng ◽  
He Qiqiang
Keyword(s):  
Heavy Rain ◽  
Dynamical Analysis ◽  
Meiyu Front ◽  
Rain Band

scholarly journals Ensemble-Based Targeted Observation Method Applied to Radar Radial Velocity Observations on Idealized Supercell Low-Level Rotation Forecasts: A Proof of Concept

2020 ◽  
Vol 148 (3) ◽  
pp. 877-890 ◽  
Author(s):  
Christopher A. Kerr ◽  
Xuguang Wang
Keyword(s):  
Decision Making ◽  
Radial Velocity ◽  
Variance Reduction ◽  
Sampling Error ◽  
Error Variance ◽  
Low Level ◽  
Optimal Ensemble ◽  
Targeted Observation ◽  
Background Forecast ◽  
Full Volume

Abstract The potential future installation of a multifunction phased-array radar (MPAR) network will provide capabilities of case-specific adaptive scanning. Knowing the impacts adaptive scanning may have on short-term forecasts will influence scanning strategy decision-making in hopes to produce the most optimal ensemble forecast while also benefiting human severe weather warning decision-making. An ensemble-based targeted observation algorithm is applied to an observing system simulation experiment (OSSE) where the impacts of synthetic idealized supercell radial velocity observations are estimated before the observations are “collected” and assimilated. The forecast metric of interest is the low-level rotation forecast metric (0–1-km updraft helicity), a surrogate for tornado prediction. It is found that the ensemble-based targeted observation approach can reasonably estimate the true error variance reduction when an effective method that treats sampling error is applied, the period of model forecast is associated with less degrees of nonlinearity, and the observation information content relative to the background forecast is larger. In some scenarios, a subset of a full-volume scan assimilation produces better forecasts than all observations within the full volume. Assimilating the full-volume scan increases the number of potential spurious correlations arising between the forecast metric and radial velocity observation induced state perturbations, which may degrade the forecast metric accuracy.

Targeted observation analysis of the tides and currents in a Coastal Marine Proving Ground

2020 ◽  
Vol 70 (10) ◽  
pp. 1303-1313
Author(s):  
Jiali Zhang ◽  
Anmin Zhang ◽  
Xuefeng Zhang ◽  
Liang Zhang ◽  
Dong Li ◽  
...  
Keyword(s):  
Coastal Marine ◽  
Targeted Observation

Using a mesoscale ensemble to predict forecast error and perform targeted observation

2014 ◽  
Vol 33 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Jun Du ◽  
Rucong Yu ◽  
Chunguang Cui ◽  
Jun Li
Keyword(s):  
Forecast Error ◽  
Targeted Observation

Targeted observations based on identified sensitive areas by CNOP to improve the thermal structures prediction in the summer Yellow Sea: preparatory work for the campaign in the field

2020 ◽  
Author(s):  
Jingyi Liu ◽  
Wuhong Guo ◽  
Baolong Cui ◽  
Kun Liu ◽  
Huiqin Hu
Keyword(s):  
Yellow Sea ◽  
The Yellow Sea ◽  
Sensitive Area ◽  
Optimal Perturbation ◽  
Field Campaign ◽  
Sensitive Areas ◽  
Initial Errors ◽  
Thermal Structures ◽  
Targeted Observation ◽  
Preparatory Work

<p>Targeted observation is an appealing procedure to improve oceanic model predictions by taking additional assimilation of collected measurements. However, studies on targeted observation in the oceanic field have been largely based on modeling efforts, and there is a need for field validating observations. Here, we report the preparatory work of a field campaign, which is designed based on the identified sensitive area by the Conditional Nonlinear Optimal Perturbation (CNOP) approach, to improve the short-range summer thermal structures prediction in the Yellow Sea (YS). We firstly simulated the hindcasting (2016-2018) temperature structures in the summertime, and found that the locations of the sensitive areas are generally consistent in space for each hindcast year. Then, we introduced the technique of multiple-assimilation and the definition of time-varying sensitive area, and designed observing strategies for the YS summer campaign. Observing System Simulation Experiments (OSSEs) were conducted prior to address the plan on field campaign in the Yellow Sea in August 2019. Results show that, reducing the initial errors in the sensitive area can lead to more improvement on thermal structures prediction than that in other area.</p>

Factors Influencing Ensemble Sensitivity–Based Targeted Observing Predictions at Convection-Allowing Resolutions

2020 ◽  
Vol 148 (11) ◽  
pp. 4497-4517
Author(s):  
Aaron J. Hill ◽  
Christopher C. Weiss ◽  
Brian C. Ancell
Keyword(s):  
Random Perturbation ◽  
Ensemble Prediction ◽  
Ensemble Prediction System ◽  
Small Random Perturbation ◽  
Numerical Noise ◽  
Targeted Observations ◽  
Targeted Observation ◽  
Ensemble Systems ◽  
Short Time ◽  
Impact Predictions

AbstractEnsemble sensitivity analysis (ESA) is applied to select types of observations, in various locations and in advance of forecast convection, to systematically evaluate the effectiveness of ESA-based observation targeting for 10 convection forecasts. To facilitate the analysis, observing system simulation experiments and perfect models are utilized to generate synthetic targeted observations of temperature and pressure for future assimilation with an ensemble prediction system. Various observation assimilation experiments are carried out to assess the impacts of nonlinearity, covariance localization, and numerical noise on ESA-based observation-impact predictions. It is discovered that localization applied during data assimilation restricts targeted-observation increments onto the forecast responses of composite reflectivity and 3-hourly accumulated precipitation, making impact predictions poor. In addition, numerical noise introduced by nonlinear perturbation evolution tends to reduce the correlations between observed and predicted impacts; small, random-perturbation experiments often yielded similar impacts on forecasts as targeted observations. Nonlinearity also manifests in the observation impacts when comparing targeted observations with nontargeted, randomly chosen observations; random observations have seemingly the same impact on forecasts as targeted observations. The results, under idealized conditions and simplified ensemble configurations, demonstrate that ESA-based targeting for nonlinear convection forecasts may be most applicable at short time scales. Important implications for ESA-based targeting methods employed with real-time ensemble systems are also discussed.

scholarly journals Validation and Interpretation of Adjoint-Derived Sensitivity Steering Vector as Targeted Observation Guidance

2011 ◽  
Vol 139 (5) ◽  
pp. 1608-1625 ◽  
Author(s):  
Shin-Gan Chen ◽  
Chun-Chieh Wu ◽  
Jan-Huey Chen ◽  
Kun-Hsuan Chou
Keyword(s):  
Initial Conditions ◽  
Deep Layer ◽  
Lower Troposphere ◽  
Subtropical High ◽  
Integration Time ◽  
Steering Vector ◽  
Steering Flow ◽  
Targeted Observation ◽  
Low Sensitivity ◽  
The Impact

The adjoint-derived sensitivity steering vector (ADSSV) has been proposed and applied as a guidance for targeted observation in the field programs for improving tropical cyclone predictability, such as The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). The ADSSV identifies sensitive areas at the observing time to the steering flow at the verifying time through adjoint calculation. In addition, the ability of the ADSSV to represent signals of influence from synoptic systems such as the midlatitude trough and the subtropical high prior to the recurvature of Typhoon Shanshan (2006) has also been demonstrated. In this study, the impact of initial perturbations associated with the high or low ADSSV sensitivity on model simulations is investigated by systematically perturbing initial vorticity fields in the case of Shanshan. Results show that experiments with the perturbed initial conditions located in the high ADSSV area (i.e., the midlatitude trough and the subtropical high) lead to more track deflection relative to the unperturbed control run than experiments with perturbations in the low sensitivity area. The evolutions of the deep-layer-mean steering flow and the direction of the ADSSV are compared to provide conceptual interpretation and validation on the physical meaning of the ADSSV. Concerning the results associated with the perturbed regions in high sensitivity regions, the variation of the steering flow within the verifying area due to the initial perturbations is generally consistent with that of the direction of the ADSSV. In addition, the bifurcation between the ADSSV and the steering change becomes larger with the increased integration time. However, the result for the perturbed region in the low-sensitivity region indicates that the steering change does not have good agreement with the ADSSV. The large initial perturbations to the low-sensitivity region may interact with the trough to the north due to the nonlinearity, which may not be accounted for in the ADSSV. Furthermore, the effect of perturbations specifically within the sensitive vertical layers is investigated to validate the vertical structure of the ADSSV. The structure of kinetic energy shows that the perturbation associated with the trough (subtropical high) specifically in the mid-to-upper (mid-to-lower) troposphere evolves similarly to that in the deep-layer troposphere, leading to comparable track changes. A sensitivity test in which perturbations are locally introduced in a higher-sensitivity area is conducted to examine the different impact as compared to that perturbed with the broader synoptic feature.

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