Search Results

You are looking at 71 - 76 of 76 items for

  • Author or Editor: Chun-Chieh Wu x
  • Refine by Access: All Content x
Clear All Modify Search
Martin Weissmann
,
Florian Harnisch
,
Chun-Chieh Wu
,
Po-Hsiung Lin
,
Yoichiro Ohta
,
Koji Yamashita
,
Yeon-Hee Kim
,
Eun-Hee Jeon
,
Tetsuo Nakazawa
, and
Sim Aberson

Abstract

A unique dataset of targeted dropsonde observations was collected during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in the autumn of 2008. The campaign was supplemented by an enhancement of the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. For the first time, up to four different aircraft were available for typhoon observations and over 1500 additional soundings were collected.

This study investigates the influence of assimilating additional observations during the two major typhoon events of T-PARC on the typhoon track forecast by the global models of the European Centre for Medium-Range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the National Centers for Environmental Prediction (NCEP), and the limited-area Weather Research and Forecasting (WRF) model. Additionally, the influence of T-PARC observations on ECMWF midlatitude forecasts is investigated.

All models show an improving tendency of typhoon track forecasts, but the degree of improvement varied from about 20% to 40% in NCEP and WRF to a comparably low influence in ECMWF and JMA. This is likely related to lower track forecast errors without dropsondes in the latter two models, presumably caused by a more extensive use of satellite data and four-dimensional variational data assimilation (4D-Var) of ECMWF and JMA compared to three-dimensional variational data assimilation (3D-Var) of NCEP and WRF. The different behavior of the models emphasizes that the benefit gained strongly depends on the quality of the first-guess field and the assimilation system.

Full access
Kun-Hsuan Chou
,
Chun-Chieh Wu
,
Po-Hsiung Lin
,
Sim D. Aberson
,
Martin Weissmann
,
Florian Harnisch
, and
Tetsuo Nakazawa

Abstract

The typhoon surveillance program Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) has been conducted since 2003 to obtain dropwindsonde observations around tropical cyclones near Taiwan. In addition, an international field project The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in which dropwindsonde observations were obtained by both surveillance and reconnaissance flights was conducted in summer 2008 in the same region. In this study, the impact of the dropwindsonde data on track forecasts is investigated for DOTSTAR (2003–09) and T-PARC (2008) experiments. Two operational global models from NCEP and ECMWF are used to evaluate the impact of dropwindsonde data. In addition, the impact on the two-model mean is assessed.

The impact of dropwindsonde data on track forecasts is different in the NCEP and ECMWF model systems. Using the NCEP system, the assimilation of dropwindsonde data leads to improvements in 1- to 5-day track forecasts in about 60% of the cases. The differences between track forecasts with and without the dropwindsonde data are generally larger for cases in which the data improved the forecasts than in cases in which the forecasts were degraded. Overall, the mean 1- to 5-day track forecast error is reduced by about 10%–20% for both DOTSTAR and T-PARC cases in the NCEP system. In the ECMWF system, the impact is not as beneficial as in the NCEP system, likely because of more extensive use of satellite data and more complex data assimilation used in the former, leading to better performance even without dropwindsonde data. The stronger impacts of the dropwindsonde data are revealed for the 3- to 5-day forecast in the two-model mean of the NCEP and ECMWF systems than for each individual model.

Full access
Chun-Chieh Wu
,
Kun-Hsuan Chou
,
Po-Hsiung Lin
,
Sim D. Aberson
,
Melinda S. Peng
, and
Tetsuo Nakazawa

Abstract

Starting from 2003, a new typhoon surveillance program, Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR), was launched. During 2004, 10 missions for eight typhoons were conducted successfully with 155 dropwindsondes deployed. In this study, the impact of these dropwindsonde data on tropical cyclone track forecasts has been evaluated with five models (four operational and one research models). All models, except the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model, show the positive impact that the dropwindsonde data have on tropical cyclone track forecasts. During the first 72 h, the mean track error reductions in the National Centers for Environmental Prediction’s (NCEP) Global Forecast System (GFS), the Navy Operational Global Atmospheric Prediction System (NOGAPS) of the Fleet Numerical Meteorology and Oceanography Center (FNMOC), and the Japanese Meteorological Agency (JMA) Global Spectral Model (GSM) are 14%, 14%, and 19%, respectively. The track error reduction in the Weather Research and Forecasting (WRF) model, in which the initial conditions are directly interpolated from the operational GFS forecast, is 16%. However, the mean track improvement in the GFDL model is a statistically insignificant 3%. The 72-h-average track error reduction from the ensemble mean of the above three global models is 22%, which is consistent with the track forecast improvement in Atlantic tropical cyclones from surveillance missions. In all, despite the fact that the impact of the dropwindsonde data is not statistically significant due to the limited number of DOTSTAR cases in 2004, the overall added value of the dropwindsonde data in improving typhoon track forecasts over the western North Pacific is encouraging. Further progress in the targeted observations of the dropwindsonde surveillances and satellite data, and in the modeling and data assimilation system, is expected to lead to even greater improvement in tropical cyclone track forecasts.

Full access
Eric A. Hendricks
,
Yi Jin
,
Jonathan R. Moskaitis
,
James D. Doyle
,
Melinda S. Peng
,
Chun-Chieh Wu
, and
Hung-Chi Kuo

Abstract

High-impact Typhoon Morakot (2009) was investigated using a multiply nested regional tropical cyclone prediction model. In the numerical simulations, the horizontal grid spacing, cumulus parameterizations, and microphysical parameterizations were varied, and the sensitivity of the track, intensity, and quantitative precipitation forecasts (QPFs) was examined. With regard to horizontal grid spacing, it is found that convective-permitting (5 km) resolution is necessary for a reasonably accurate QPF, while little benefit is gained through the use of a fourth domain at 1.67-km horizontal resolution. Significant sensitivity of the track forecast was found to the cumulus parameterization, which impacted the model QPFs. In particular, the simplified Arakawa–Schubert parameterization tended to erroneously regenerate the remnants of Tropical Storm Goni to the southwest of Morakot, affecting the large-scale steering flow and the track of Morakot. Strong sensitivity of the QPFs to the microphysical parameterization was found, with the track and intensity showing little sensitivity. It is also found that Morakot’s accumulated precipitation was reasonably predictable, with the control simulation producing an equitable threat score of 0.56 for the 3-day accumulated precipitation using a threshold of 500 mm. This high predictability of precipitation is due in part to more predictable large-scale and topographic forcing.

Full access
Chun-Chieh Wu
,
Jan-Huey Chen
,
Sharanya J. Majumdar
,
Melinda S. Peng
,
Carolyn A. Reynolds
,
Sim D. Aberson
,
Roberto Buizza
,
Munehiko Yamaguchi
,
Shin-Gan Chen
,
Tetsuo Nakazawa
, and
Kun-Hsuan Chou

Abstract

This study compares six different guidance products for targeted observations over the northwest Pacific Ocean for 84 cases of 2-day forecasts in 2006 and highlights the unique dynamical features affecting the tropical cyclone (TC) tracks in this basin. The six products include three types of guidance based on total-energy singular vectors (TESVs) from different global models, the ensemble transform Kalman filter (ETKF) based on a multimodel ensemble, the deep-layer mean (DLM) wind variance, and the adjoint-derived sensitivity steering vector (ADSSV). The similarities among the six products are evaluated using two objective statistical techniques to show the diversity of the sensitivity regions in large, synoptic-scale domains and in smaller domains local to the TC. It is shown that the three TESVs are relatively similar to one another in both the large and the small domains while the comparisons of the DLM wind variance with other methods show rather low similarities. The ETKF and the ADSSV usually show high similarity because their optimal sensitivity usually lies close to the TC. The ADSSV, relative to the ETKF, reveals more similar sensitivity patterns to those associated with TESVs. Three special cases are also selected to highlight the similarities and differences among the six guidance products and to interpret the dynamical systems affecting the TC motion in the northwestern Pacific. Among the three storms studied, Typhoon Chanchu was associated with the subtropical high, Typhoon Shanshan was associated with the midlatitude trough, and Typhoon Durian was associated with the subtropical jet. The adjoint methods are found to be more capable of capturing the signal of the dynamic system that may affect the TC movement or evolution than are the ensemble methods.

Full access
Stephen A. Cohn
,
Terry Hock
,
Philippe Cocquerez
,
Junhong Wang
,
Florence Rabier
,
David Parsons
,
Patrick Harr
,
Chun-Chieh Wu
,
Philippe Drobinski
,
Fatima Karbou
,
Stéphanie Vénel
,
André Vargas
,
Nadia Fourrié
,
Nathalie Saint-Ramond
,
Vincent Guidard
,
Alexis Doerenbecher
,
Huang-Hsiung Hsu
,
Po-Hsiung Lin
,
Ming-Dah Chou
,
Jean-Luc Redelsperger
,
Charlie Martin
,
Jack Fox
,
Nick Potts
,
Kathryn Young
, and
Hal Cole

Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.

Full access