Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF

Intensity Forecast

<p>The present study uses the nonlinear singular vector (NFSV) approach to identify the optimally-growing tendency perturbations of the Weather Research and Forecasting (WRF) model for tropical cyclone (TC) intensity forecasts. For nine selected TC cases, the NFSV-tendency perturbations of the WRF model, including components of potential temperature and/or moisture, are calculated when TC intensities are forecasted with a 24-hour lead time, and their respective potential temperature components are demonstrated to have more impact on the TC intensity forecasts. The perturbations coherently show barotropic structure around the central location of the TCs at the 24-hour lead time, and their dominant energies concentrate in the middle layers of the atmosphere. Moreover, such structures do not depend on TC intensities and subsequent development of the TC. The NFSV-tendency perturbations may indicate that the model uncertainty that is represented by tendency perturbations but associated with the inner-core of TCs, makes larger contributions to the TC intensity forecast uncertainty. Further analysis shows that the TC intensity forecast skill could be greatly improved as preferentially superimposing an appropriate tendency perturbation associated with the sensitivity of NFSVs to correct the model, even if using a WRF with coarse resolution.</p><div> <div>&#160;</div> </div>

Impact of environmental moisture on tropical cyclone intensification

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-16111-2015 ◽

2015 ◽

Vol 15 (11) ◽

pp. 16111-16139 ◽

Cited By ~ 1

Author(s):

L. Wu ◽

H. Su ◽

R. G. Fovell ◽

T. J. Dunkerton ◽

Z. Wang ◽

...

Keyword(s):

Boundary Layer ◽

Tropical Cyclone ◽

Inner Core ◽

Wrf Model ◽

Convective Activity ◽

Dry Air ◽

Moving Storm ◽

Lagrangian Boundary ◽

Moisture Increase

Abstract. The impacts of environmental moisture on the intensification of a tropical cyclone (TC) are investigated in the Weather Research and Forecasting (WRF) model, with a focus on the azimuthal asymmetry of the moisture impacts. A series of sensitivity experiments with varying moisture perturbations in the environment are conducted and the Marsupial Paradigm framework is employed to understand the different moisture impacts. We find that modification of environmental moisture has insignificant impacts on the storm in this case unless it leads to convective activity in the environment, which deforms the quasi-Lagrangian boundary of the storm. By facilitating convection and precipitation outside the storm, enhanced environmental moisture ahead of the northwestward-moving storm induces a dry air intrusion to the inner core and limits TC intensification. However, increased moisture in the rear quadrants favors intensification by providing more moisture to the inner core and promoting storm symmetry, with primary contributions coming from moisture increase in the boundary layer. The different impacts of environmental moisture on TC intensification are governed by the relative locations of moisture perturbations and their interactions with the storm Lagrangian structure.

Impact of environmental moisture on tropical cyclone intensification

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-14041-2015 ◽

2015 ◽

Vol 15 (24) ◽

pp. 14041-14053 ◽

Cited By ~ 7

Author(s):

L. Wu ◽

H. Su ◽

R. G. Fovell ◽

T. J. Dunkerton ◽

Z. Wang ◽

...

Keyword(s):

Tropical Cyclone ◽

Moisture Transport ◽

Inner Core ◽

Wrf Model ◽

Convective Activity ◽

Dry Air ◽

Moving Storm ◽

Lagrangian Boundary ◽

Moisture Increase

Abstract. The impacts of environmental moisture on the intensification of a tropical cyclone (TC) are investigated in the Weather Research and Forecasting (WRF) model, with a focus on the azimuthal asymmetry of the moisture impacts relative to the storm path. A series of sensitivity experiments with varying moisture perturbations in the environment are conducted and the Marsupial Paradigm framework is employed to understand the different moisture impacts. We find that modification of environmental moisture has insignificant impacts on the storm in this case unless it leads to convective activity that deforms the quasi-Lagrangian boundary of the storm and changes the moisture transport into the storm. By facilitating convection and precipitation outside the storm, enhanced environmental moisture ahead of the northwestward-moving storm induces a dry air intrusion to the inner core and limits TC intensification. In contrast, increased moisture in the rear quadrants favors intensification by providing more moisture to the inner core and promoting storm symmetry, with primary contributions coming from moisture increase in the boundary layer. The different impacts of environmental moisture on TC intensification are governed by the relative locations of moisture perturbations and their interactions with the storm Lagrangian structure.

Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development

10.1175/mwr-d-15-0363.1 ◽

2016 ◽

Vol 144 (6) ◽

pp. 2395-2420 ◽

Cited By ~ 5

Author(s):

J.-W. Bao ◽

S. A. Michelson ◽

E. D. Grell

Keyword(s):

Tropical Cyclone ◽

Wrf Model ◽

Cloud Microphysics ◽

Rapid Intensification ◽

Latent Heating ◽

Vertical Distributions ◽

Double Moment ◽

Microphysical Processes ◽

Definition Of

Abstract Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes.

Role of eyewall and rainband eddy forcing in tropical cyclone intensification

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-14289-2019 ◽

2019 ◽

Vol 19 (22) ◽

pp. 14289-14310 ◽

Cited By ~ 3

Author(s):

Ping Zhu ◽

Bryce Tyner ◽

Jun A. Zhang ◽

Eric Aligo ◽

Sundararaman Gopalakrishnan ◽

...

Keyword(s):

Tropical Cyclone ◽

Turbulent Mixing ◽

Inner Core ◽

Rapid Changes ◽

Flow Feature ◽

Secondary Circulations ◽

Vertical Turbulent Mixing ◽

Operational Models

Abstract. While turbulence is commonly regarded as a flow feature pertaining to the planetary boundary layer (PBL), intense turbulent mixing generated by cloud processes also exists above the PBL in the eyewall and rainbands of a tropical cyclone (TC). The in-cloud turbulence above the PBL is intimately involved in the development of convective elements in the eyewall and rainbands and consists of a part of asymmetric eddy forcing for the evolution of the primary and secondary circulations of a TC. In this study, we show that the Hurricane Weather Research and Forecasting (HWRF) model, one of the operational models used for TC prediction, is unable to generate appropriate sub-grid-scale (SGS) eddy forcing above the PBL due to a lack of consideration of intense turbulent mixing generated by the eyewall and rainband clouds. Incorporating an in-cloud turbulent-mixing parameterization in the vertical turbulent-mixing scheme notably improves the HWRF model's skills in predicting rapid changes in intensity for several past major hurricanes. While the analyses show that the SGS eddy forcing above the PBL is only about one-fifth of the model-resolved eddy forcing, the simulated TC vortex inner-core structure, secondary overturning circulation, and the model-resolved eddy forcing exhibit a substantial dependence on the parameterized SGS eddy processes. The results highlight the importance of eyewall and rainband SGS eddy forcing to numerical prediction of TC intensification, including rapid intensification at the current resolution of operational models.

Initial Condition Sensitivity of Western Pacific Extratropical Transitions Determined Using Ensemble-Based Sensitivity Analysis

10.1175/2009mwr2879.1 ◽

2009 ◽

Vol 137 (10) ◽

pp. 3388-3406 ◽

Cited By ~ 51

Author(s):

Ryan D. Torn ◽

Gregory J. Hakim

Keyword(s):

Sensitivity Analysis ◽

Tropical Cyclone ◽

Initial Conditions ◽

Forecast Error ◽

Wrf Model ◽

Forecast Errors ◽

Initial Condition ◽

Ensemble Forecasts ◽

The Relationship

Abstract An ensemble Kalman filter based on the Weather Research and Forecasting (WRF) model is used to generate ensemble analyses and forecasts for the extratropical transition (ET) events associated with Typhoons Tokage (2004) and Nabi (2005). Ensemble sensitivity analysis is then used to evaluate the relationship between forecast errors and initial condition errors at the onset of transition, and to objectively determine the observations having the largest impact on forecasts of these storms. Observations from rawinsondes, surface stations, aircraft, cloud winds, and cyclone best-track position are assimilated every 6 h for a period before, during, and after transition. Ensemble forecasts initialized at the onset of transition exhibit skill similar to the operational Global Forecast System (GFS) forecast and to a WRF forecast initialized from the GFS analysis. WRF ensemble forecasts of Tokage (Nabi) are characterized by relatively large (small) ensemble variance and greater (smaller) sensitivity to the initial conditions. In both cases, the 48-h forecast of cyclone minimum SLP and the RMS forecast error in SLP are most sensitive to the tropical cyclone position and to midlatitude troughs that interact with the tropical cyclone during ET. Diagnostic perturbations added to the initial conditions based on ensemble sensitivity reduce the error in the storm minimum SLP forecast by 50%. Observation impact calculations indicate that assimilating approximately 40 observations in regions of greatest initial condition sensitivity produces a large, statistically significant impact on the 48-h cyclone minimum SLP forecast. For the Tokage forecast, assimilating the single highest impact observation, an upper-tropospheric zonal wind observation from a Mongolian rawinsonde, yields 48-h forecast perturbations in excess of 10 hPa and 60 m in SLP and 500-hPa height, respectively.

The Efficacy of the WRF-ARW Model in the Genesis and Intensity Forecast of Tropical Cyclone Fani over the Bay of Bengal

Journal of Engineering Science ◽

10.3329/jes.v12i3.57482 ◽

2022 ◽

Vol 12 (3) ◽

pp. 85-100

Author(s):

Md Shakil Hossain ◽

Md Abdus Samad ◽

SM Arif Hossen ◽

SM Quamrul Hassan ◽

MAK Malliak

Keyword(s):

Tropical Cyclone ◽

Bay Of Bengal ◽

Lead Time ◽

Wrf Model ◽

Horizontal Resolution ◽

Outcome Analysis ◽

Time Model ◽

Cyclonic Storm ◽

Arw Model ◽

Global Data Assimilation System

An attempt has been carried out to assess the efficacy of the Weather Research and Forecasting (WRF) model in predicting the genesis and intensification events of Very Severe Cyclonic Storm (VSCS) Fani (26 April – 04 May 2019) over the Bay of Bengal (BoB). WRF model has been conducted on a single domain of 10 km horizontal resolution using the Global Data Assimilation System (GDAS) FNL (final) data (0.250 × 0.250). According to the model simulated outcome analysis, the model is capable of predicting the Minimum Sea Level Pressure (MSLP) and Maximum Sustainable Wind Speed (MSWS) pattern reasonably well, despite some deviations. The model has forecasted the Lowest Central Pressure (LCP) of 919 hPa and the MSWS of 70 ms-1 based on 0000 UTC of 26 April. Except for the model run based on 0000 UTC of 26 April, the simulated values of LCP are relatively higher than the observations. According to the statistical analysis, MSLP and MSWS at 850 hPa level demonstrate a significantly greater influence on Tropical Cyclone (TC) formation and intensification process than any other parameters. The model can predict the intensity features well enough, despite some uncertainty regarding the proper lead time of the model run. Reduced lead time model run, particularly 24 to 48 hr, can be chosen to forecast the genesis and intensification events of TC with minimum uncertainty. Journal of Engineering Science 12(3), 2021, 85-100

Probabilistic Prediction of Tropical Cyclone Intensity with an Analog Ensemble

10.1175/mwr-d-17-0314.1 ◽

2018 ◽

Vol 146 (6) ◽

pp. 1723-1744 ◽

Cited By ~ 10

Author(s):

Stefano Alessandrini ◽

Luca Delle Monache ◽

Christopher M. Rozoff ◽

William E. Lewis

Keyword(s):

Tropical Cyclone ◽

Inner Core ◽

Absolute Error ◽

Eastern Pacific ◽

Training Dataset ◽

Ensemble Prediction ◽

Lead Times ◽

Probabilistic Prediction ◽

Cyclone Intensity

An analog ensemble (AnEn) technique is applied to the prediction of tropical cyclone (TC) intensity (i.e., maximum 1-min averaged 10-m wind speed). The AnEn is an inexpensive, naturally calibrated ensemble prediction of TC intensity derived from a training dataset of deterministic Hurricane Weather Research and Forecasting (HWRF; 2015 version) Model forecasts. In this implementation of the AnEn, a set of analog forecasts is generated by searching an HWRF archive for forecasts sharing key features with the current HWRF forecast. The forecast training period spans 2011–15. The similarity of a current forecast with past forecasts is estimated using predictors derived from the HWRF reforecasts that capture thermodynamic and kinematic properties of a TC’s environment and its inner core. Additionally, the value of adding a multimodel intensity consensus forecast as an AnEn predictor is examined. Once analogs are identified, the verifying intensity observations corresponding to each analog HWRF forecast are used to produce the AnEn intensity prediction. In this work, the AnEn is developed for both the eastern Pacific and Atlantic Ocean basins. The AnEn’s performance with respect to mean absolute error (MAE) is compared with the raw HWRF output, the official National Hurricane Center (NHC) forecast, and other top-performing NHC models. Also, probabilistic intensity forecasts are compared with a quantile mapping model based on the HWRF’s intensity forecast. In terms of MAE, the AnEn outperforms HWRF in the eastern Pacific at all lead times examined and up to 24-h lead time in the Atlantic. Also, unlike traditional dynamical ensembles, the AnEn produces an excellent spread–skill relationship.

Analyzing Simulated Convective Bursts in Two Atlantic Hurricanes. Part I: Burst Formation and Development

10.1175/mwr-d-16-0267.1 ◽

2017 ◽

Vol 145 (8) ◽

pp. 3073-3094 ◽

Cited By ~ 19

Author(s):

Andrew T. Hazelton ◽

Robert F. Rogers ◽

Robert E. Hart

Keyword(s):

Radial Flow ◽

Inner Core ◽

Wrf Model ◽

Tropical Meteorology ◽

Core Region ◽

Convective Bursts ◽

Atlantic Hurricanes ◽

Radial Outflow

Understanding the structure and evolution of the tropical cyclone (TC) inner core remains an elusive challenge in tropical meteorology, especially the role of transient asymmetric features such as localized strong updrafts known as convective bursts (CBs). This study investigates the formation of CBs and their role in TC structure and evolution using high-resolution simulations of two Atlantic hurricanes (Dean in 2007 and Bill in 2009) with the Weather Research and Forecasting (WRF) Model. Several different aspects of the dynamics and thermodynamics of the TC inner-core region are investigated with respect to their influence on TC convective burst development. Composites with CBs show stronger radial inflow in the lowest 2 km, and stronger radial outflow from the eye to the eyewall around z = 2–4 km, than composites without CBs. Asymmetric vorticity associated with eyewall mesovortices appears to be a major factor in some of the radial flow anomalies that lead to CB development. The anomalous outflow from these mesovortices, along with outflow from supergradient parcels above the boundary layer, favors low-level convergence and also appears to mix high- θ e air from the eye into the eyewall. Analyses of individual CBs and parcel trajectories show that parcels are pulled into the eye and briefly mix with the eye air. The parcels then rapidly move outward into the eyewall, and quickly ascend in CBs, in some cases with vertical velocities of over 20 m s−1. These results support the importance of horizontal asymmetries in forcing extreme asymmetric vertical velocity in tropical cyclones.

Mesoscale Horizontal Kinetic Energy Spectra of a Tropical Cyclone

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-17-0391.1 ◽

2018 ◽

Vol 75 (10) ◽

pp. 3579-3596 ◽

Cited By ~ 2

Author(s):

Yuan Wang ◽

Lifeng Zhang ◽

Jun Peng ◽

Saisai Liu

Keyword(s):

Tropical Cyclone ◽

Kinetic Energy ◽

Gravity Waves ◽

Lower Stratosphere ◽

Wrf Model ◽

Physical Processes ◽

Upper Troposphere ◽

Mature Period ◽

Vertically Propagating

A high-resolution cloud-permitting simulation with the Weather Research and Forecasting (WRF) Model is performed to investigate the mesoscale horizontal kinetic energy (HKE) spectra of a tropical cyclone (TC). The spectrum displays an arc-like shape in the troposphere and a quasi-linear shape in the lower stratosphere for wavelengths below 500 km during the mature period of the TC, while they both develop a quasi −5/3 slope. The total HKE spectrum is dominated by its rotational component in the troposphere but by its divergent component in the lower stratosphere. Further spectral HKE budget diagnosis reveals a generally downscale cascade of HKE, although a local upscale cascade gradually forms in the lower stratosphere. However, the mesoscale energy spectrum is not only governed by the energy cascade, but is evidently influenced also by other physical processes, among which the buoyancy effect converts available potential energy (APE) to HKE in the mid- and upper troposphere and converts HKE to APE in the lower stratosphere, the vertically propagating inertia–gravity waves transport the HKE from the upper troposphere to lower and higher layers, and the vertical transportation of convection always transports HKE upward.

Two Overlooked Biases of the Advanced Research WRF (ARW) Model in Geopotential Height and Temperature

10.1175/mwr-d-12-00045.1 ◽

2012 ◽

Vol 140 (12) ◽

pp. 3907-3918 ◽

Cited By ~ 10

Author(s):

Tae-Kwon Wee ◽

Ying-Hwa Kuo ◽

Dong-Kyou Lee ◽

Zhiquan Liu ◽

Wei Wang ◽

...

Keyword(s):

Potential Temperature ◽

Wrf Model ◽

Initial Condition ◽

Forecast Bias ◽

Hydrostatic Equation ◽

Arw Model ◽

Occultation Data ◽

Bias Corrections

Abstract The authors have discovered two sizeable biases in the Weather Research and Forecasting (WRF) model: a negative bias in geopotential and a warm bias in temperature, appearing both in the initial condition and the forecast. The biases increase with height and thus manifest themselves at the upper part of the model domain. Both biases stem from a common root, which is that vertical structures of specific volume and potential temperature are convex functions. The geopotential bias is caused by the particular discrete hydrostatic equation used in WRF and is proportional to the square of the thickness of model layers. For the vertical levels used in this study, the bias far exceeds the gross 1-day forecast bias combining all other sources. The bias is fixed by revising the discrete hydrostatic equation. WRF interpolates potential temperature from the grids of an external dataset to the WRF grids in generating the initial condition. Associated with the Exner function, this leads to the marked bias in temperature. By interpolating temperature to the WRF grids and then computing potential temperature, the bias is removed. The bias corrections developed in this study are expected to reduce the disparity between the forecast and observations, and eventually to improve the quality of analysis and forecast in the subsequent data assimilation. The bias corrections might be especially beneficial to assimilating height-based observations (e.g., radio occultation data).