scholarly journals Adjoint-Derived Impact of Assimilated Observations on Tropical Cyclone Intensity Forecasts of Hurricane Joaquin (2015) and Hurricane Matthew (2016)

2020 ◽  
Vol 37 (8) ◽  
pp. 1333-1352
Author(s):  
Brett T. Hoover ◽  
Chris S. Velden
Keyword(s):  
Tropical Cyclone ◽  
Initial Conditions ◽  
Lower Troposphere ◽  
Extended Period ◽  
Precipitable Water ◽  
Cyclone Intensity ◽  
Model Background ◽  
Tropical Cyclone Intensity Forecasts ◽  
Observation Impact ◽  
The Impact

AbstractThe adjoint-derived observation impact method is used as a diagnostic to derive the impact of assimilated observations on a metric representing the forecast intensity of a tropical cyclone (TC). Storm-centered composites of observation impact and the model background state are computed across 6-hourly analysis/forecast cycles to compute the composite observation impact throughout the life cycle of Hurricane Joaquin (2015) to evaluate the impact of in situ wind and temperature observations in the upper and lower troposphere, as well as the impact of brightness temperature and precipitable water observations, on intensity forecasts with forecast lengths from 12 to 48 h. The compositing across analysis/forecast cycles allows for the exploration of consistent relationships between the synoptic-scale state of the initial conditions and the impact of observations that are interpreted as flow-dependent interactions between model background bias and correction by assimilated observations on the TC intensity forecast. The track of Hurricane Matthew (2016), with an extended period of time near the coasts of Florida, Georgia, and the Carolinas, allows for a comparison of the impact of aircraft reconnaissance observations with the impact of nearby overland rawinsonde observations available within the same radius of the TC.

scholarly journals Evaluation of Atmosphere and Ocean Initial Condition Uncertainty and Stochastic Exchange Coefficients on Ensemble Tropical Cyclone Intensity Forecasts

2016 ◽  
Vol 144 (9) ◽  
pp. 3487-3506 ◽  
Author(s):  
Ryan D. Torn
Keyword(s):  
Standard Deviation ◽  
Tropical Cyclone ◽  
Initial Conditions ◽  
Continuous Growth ◽  
Cyclone Intensity ◽  
Uncertainty Sources ◽  
Tropical Cyclone Intensity Forecasts ◽  
Hurricane Wrf ◽  
Stochastic Representations ◽  
The Impact

Tropical cyclone (TC) intensity forecasts are impacted by errors in atmosphere and ocean initial conditions and the model formulation, which motivates using an ensemble approach. This study evaluates the impact of uncertainty in atmospheric and oceanic initial conditions, as well as stochastic representations of the drag Cd and enthalphy Ck exchange coefficients on ensemble Advanced Hurricane WRF (AHW) TC intensity forecasts of multiple Atlantic TCs from 2008 to 2011. Each ensemble experiment is characterized by different combinations of either deterministic or ensemble atmospheric and/or oceanic initial conditions, as well as fixed or stochastic representations of Cd or Ck. Among those experiments with a single uncertainty source, atmospheric uncertainty produces the largest standard deviation in TC intensity. While ocean uncertainty leads to continuous growth in ensemble standard deviation, the ensemble standard deviation in the experiments with Cd and Ck uncertainty levels off by 48 h. Combining atmospheric and oceanic uncertainty leads to larger intensity standard deviation than atmosphere or ocean uncertainty alone and preferentially adds variability outside of the TC core. By contrast, combining Cd or Ck uncertainty with any other source leads to negligible increases in standard deviation, which is mainly due to the lack of spatial correlation in the exchange coefficient perturbations. All of the ensemble experiments are deficient in ensemble standard deviation; however, the experiments with combinations of uncertainty sources generally have an ensemble standard deviation closer to the ensemble-mean errors.

scholarly journals The Impact of Targeted Dropwindsonde Observations on Tropical Cyclone Intensity Forecasts of Four Weak Systems during PREDICT

2014 ◽  
Vol 142 (8) ◽  
pp. 2860-2878 ◽  
Author(s):  
Ryan D. Torn
Keyword(s):  
Tropical Cyclone ◽  
Meridional Wind ◽  
Horizontal Wind ◽  
Small Subset ◽  
Tropical Cyclone Intensity ◽  
Ensemble Forecasts ◽  
Cyclone Intensity ◽  
Intensity Forecast ◽  
Tropical Cyclone Intensity Forecasts ◽  
The Impact

Abstract The value of assimilating targeted dropwindsonde observations meant to improve tropical cyclone intensity forecasts is evaluated using data collected during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field project and a cycling ensemble Kalman filter. For each of the four initialization times studied, four different sets of Weather Research and Forecasting Model (WRF) ensemble forecasts are produced: one without any dropwindsonde data, one with all dropwindsonde data assimilated, one where a small subset of “targeted” dropwindsondes are identified using the ensemble-based sensitivity method, and a set of randomly selected dropwindsondes. For all four cases, the assimilation of dropwindsondes leads to an improved intensity forecast, with the targeted dropwindsonde experiment recovering at least 80% of the difference between the experiment where all dropwindsondes and no dropwindsondes are assimilated. By contrast, assimilating randomly selected dropwindsondes leads to a smaller impact in three of the four cases. In general, zonal and meridional wind observations at or below 700 hPa have the largest impact on the forecast due to the large sensitivity of the intensity forecast to the horizontal wind components at these levels and relatively large ensemble standard deviation relative to the assumed observation errors.

scholarly journals The Impact of Variational Assimilation of SSM/I and QuikSCAT Satellite Observations on the Numerical Simulation of Indian Ocean Tropical Cyclones

2008 ◽  
Vol 23 (3) ◽  
pp. 460-476 ◽  
Author(s):  
Randhir Singh ◽  
P. K. Pal ◽  
C. M. Kishtawal ◽  
P. C. Joshi
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Lower Troposphere ◽  
Heat Fluxes ◽  
Cyclone Intensity ◽  
Wind Speeds ◽  
The Impact ◽  
Quikscat Winds

Abstract In this study, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with three-dimensional variational data assimilation (3DVAR) is utilized to investigate the influence of Special Sensor Microwave Imager (SSM/I) and Quick Scatterometer (QuikSCAT) observations on the prediction of an Indian Ocean tropical cyclone. The 3DVAR sensitivity runs were conducted separately with QuikSCAT wind vectors, SSM/I wind speeds, and total precipitable water (TPW) to investigate their individual impact on cyclone intensity and track. The Orissa supercyclone over the Bay of Bengal during October 1999 was used for simulation and assimilation experiments. Assimilation of the QuikSCAT wind vector improves the initial position of the cyclone’s center with a position error of 33 km, which was 163 km in the background analysis. Incorporation of QuikSCAT winds was found to increase the air–sea heat fluxes over the cyclonic region, which resulted in the improved simulated intensity when compared with the simulation made without QuikSCAT winds in the initial conditions. The cyclone track improved significantly with assimilation of QuikSCAT wind vectors. The track improvement resulted from relocation of the initial cyclonic vortex after assimilation of QuikSCAT wind vectors. Like QuikSCAT, assimilation of SSM/I wind speeds strengthened the cyclonic circulation in the initial conditions. This increase in the low-level wind speeds enhanced the air–sea exchange processes and improved the simulated intensity of the cyclone. The lack of information about the wind direction from SSM/I prevented it from making much of an impact on track prediction. As compared to the first guess, assimilation of the SSM/I TPW shows a moistening of the lower troposphere over most of the Bay of Bengal except over the central region of the cyclone, where the assimilation of SSM/I TPW reduces the lower-tropospheric moisture. This decrease of moisture in the TPW assimilation experiment resulted in a weak cyclone intensity.

scholarly journals A Novel Multiscale Intensity Metric for Evaluation of Tropical Cyclone Intensity Forecasts

2014 ◽  
Vol 71 (4) ◽  
pp. 1292-1304 ◽  
Author(s):  
Tomislava Vukicevic ◽  
Eric Uhlhorn ◽  
Paul Reasor ◽  
Bradley Klotz
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Microwave Radiometer ◽  
Maximum Speed ◽  
Forecast Errors ◽  
Cyclone Intensity ◽  
Maximum Wind ◽  
Tropical Cyclone Intensity Forecasts ◽  
The Difference ◽  
The Impact

Abstract In this study, a new multiscale intensity (MSI) metric for evaluating tropical cyclone (TC) intensity forecasts is presented. The metric consists of the resolvable and observable, low-wavenumber intensity represented by the sum of amplitudes of azimuthal wavenumbers 0 and 1 for wind speed within the TC vortex at the radius of maximum wind and a stochastic residual, all determined at 10-m elevation. The residual wind speed is defined as the difference between an estimate of maximum speed and the low-wavenumber intensity. The MSI metric is compared to the standard metric that includes only the maximum speed. Using stepped-frequency microwave radiometer wind speed observations from TC aircraft reconnaissance to estimate the low-wavenumber intensity and the National Hurricane Center’s best-track (BT) intensity for the maximum wind speed estimate, it is shown that the residual intensity is well represented as a stochastic quantity with small mean, standard deviation, and absolute norm values that are within the expected uncertainty of the BT estimates. The result strongly suggests that the practical predictability of TC intensity is determined by the observable and resolvable low-wavenumber intensity within the vortex. Verification of a set of high-resolution numerical forecasts using the MSI metric demonstrates that this metric provides more informative and more realistic estimates of the intensity forecast errors. It is also shown that the maximum speed metric allows for error compensation between the low-wavenumber and residual intensities, which could lead to forecast skill overestimation and inaccurate assessment of the impact of forecast system change on the skill.

scholarly journals Impact of Satellite Observations on the Tropical Cyclone Track Forecasts of the Navy Operational Global Atmospheric Prediction System

2009 ◽  
Vol 137 (1) ◽  
pp. 41-50 ◽  
Author(s):  
James S. Goerss
Keyword(s):  
Tropical Cyclone ◽  
Precipitable Water ◽  
Satellite Observation ◽  
Satellite Observations ◽  
Prediction System ◽  
Wind Speeds ◽  
The North ◽  
Percent Improvement ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Abstract The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.

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.

scholarly journals Experimental Tropical Cyclone Forecasts Using a Variable-Resolution Global Model

2015 ◽  
Vol 143 (10) ◽  
pp. 4012-4037 ◽  
Author(s):  
Colin M. Zarzycki ◽  
Christiane Jablonowski
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Hurricane Sandy ◽  
Track Forecast ◽  
Time Step ◽  
Variable Resolution ◽  
The Impact

Abstract Tropical cyclone (TC) forecasts at 14-km horizontal resolution (0.125°) are completed using variable-resolution (V-R) grids within the Community Atmosphere Model (CAM). Forecasts are integrated twice daily from 1 August to 31 October for both 2012 and 2013, with a high-resolution nest centered over the North Atlantic and eastern Pacific Ocean basins. Using the CAM version 5 (CAM5) physical parameterization package, regional refinement is shown to significantly increase TC track forecast skill relative to unrefined grids (55 km, 0.5°). For typical TC forecast integration periods (approximately 1 week), V-R forecasts are able to nearly identically reproduce the flow field of a globally uniform high-resolution forecast. Simulated intensity is generally too strong for forecasts beyond 72 h. This intensity bias is robust regardless of whether the forecast is forced with observed or climatological sea surface temperatures and is not significantly mitigated in a suite of sensitivity simulations aimed at investigating the impact of model time step and CAM’s deep convection parameterization. Replacing components of the default physics with Cloud Layers Unified by Binormals (CLUBB) produces a statistically significant improvement in forecast intensity at longer lead times, although significant structural differences in forecasted TCs exist. CAM forecasts the recurvature of Hurricane Sandy into the northeastern United States 60 h earlier than the Global Forecast System (GFS) model using identical initial conditions, demonstrating the sensitivity of TC forecasts to model configuration. Computational costs associated with V-R simulations are dramatically decreased relative to globally uniform high-resolution simulations, demonstrating that variable-resolution techniques are a promising tool for future numerical weather prediction applications.

scholarly journals The Impact of Dropwindsonde Data from the THORPEX Pacific Area Regional Campaign and the NOAA Hurricane Field Program on Tropical Cyclone Forecasts in the Global Forecast System

2011 ◽  
Vol 139 (9) ◽  
pp. 2689-2703 ◽  
Author(s):  
Sim D. Aberson
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Initial Conditions ◽  
Unexpected Result ◽  
Cyclone Track ◽  
East Pacific ◽  
Global Impacts ◽  
The Impact ◽  
Pacific Area ◽  
Taiwan Region

Four aircraft released dropwindsondes in and around tropical cyclones in the west Pacific during The Observing System Research and Predictability Experiment (THORPEX) Pacific Area Regional Campaign (T-PARC) in 2008 and the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR); multiple aircraft concurrently participated in similar missions in the Atlantic. Previous studies have treated each region separately and have focused on the tropical cyclones whose environments were sampled. The large number of missions and tropical cyclones in both regions, and additional tropical cyclones in the east Pacific and Indian Oceans, allows for the global impact of these observations on tropical cyclone track forecasts to be studied. The study shows that there are unintended global consequences to local changes in initial conditions, in this case due to the assimilation of dropwindsonde data in tropical cyclone environments. These global impacts are mainly due to the spectral nature of the model system. These differences should be small and slightly positive, since improved local initial conditions should lead to small global forecast improvements. However, the impacts on tropical cyclones far removed from the data are shown to be as large and positive as those on the tropical cyclones specifically targeted for improved track forecasts. Causes of this unexpected result are hypothesized, potentially providing operational forecasters tools to identify when large remote impacts from surveillance missions might occur.

scholarly journals The Role of Inner-Core Moisture in Tropical Cyclone Predictability and Practical Forecast Skill

2017 ◽  
Vol 74 (7) ◽  
pp. 2315-2324 ◽  
Author(s):  
Kerry Emanuel ◽  
Fuqing Zhang
Keyword(s):  
Tropical Cyclone ◽  
Wind Field ◽  
Inner Core ◽  
Forecast Skill ◽  
Initial Condition ◽  
Tropical Cyclone Intensity ◽  
Cyclone Intensity ◽  
Storm Intensity ◽  
Tropical Cyclone Intensity Forecasts

Abstract Errors in tropical cyclone intensity forecasts are dominated by initial-condition errors out to at least a few days. Initialization errors are usually thought of in terms of position and intensity, but here it is shown that growth of intensity error is at least as sensitive to the specification of inner-core moisture as to that of the wind field. Implications of this finding for tropical cyclone observational strategies and for overall predictability of storm intensity are discussed.

Sign in / Sign up

Export Citation Format

Share Document