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This paper presents an observational and numerical study of Typhoon Mindulle (2004) as it affected Taiwan. Mindulle made landfall on the east coast of Taiwan at 1500 UTC 1 July 2004, and after 13 h, it exited Taiwan from the north coast. Severe rainfall (with a maximum amount of 787 mm) occurred over central-southwestern Taiwan on 2 July 2004. During the landfall of Mindulle's main circulation, a secondary low formed over the Taiwan Strait. However, the secondary low, after it developed significantly (vorticity exceeded 5 ϫ 10 Ϫ4 s Ϫ1 over a 30-km radius), did not replace the original center as was observed in many other storms. Instead, it moved inland and dissipated after the original center redeveloped near the north coast of Taiwan. In this study, the evolution of the secondary low, the redevelopment of the primary center, and the processes leading to the severe rainfall were examined. Results showed that the processes leading to the formation and the development of the secondary low were similar to those described in previous studies. These processes include the leeside subsidence warming, the horizontal transport of vorticity around the northern tip of the Central Mountain Range (CMR), and the overmountain upper-level vorticity remnant. However, because of the northward track, Mindulle preserved some strong vorticity on the eastern slope of the CMR. This strong vorticity remnant was steered northward over the ocean offshore from the north coast where the redevelopment of the primary center occurred. This "quasi-continuous track" of Mindulle has not been documented in previous studies. The vortex interaction between the redeveloped primary center and the secondary low resulted in the northeastward movement of the secondary low, which then dissipated after making landfall. Analyses also showed that even though heavy rainfall would occur over the mountain area when only the southwesterly flow prevailed, as on 3 July 2004, Typhoon Mindulle and the secondary low provided extra convergence that resulted in the west-east-oriented convective bands. These convective bands and the orographic lifting of the circulation associated with the secondary low resulted in the heavy rainfall over the central-western plains area.

To better understand the change in California's climate over the past century, the long-term variability and extreme events of precipitation as well as minimum, mean, and maximum temperatures during the rainy season (from November to March) are investigated using observations. Their relationships to 28 rainy season average climate indices with and without time lags are also studied. The precipitation variability is found to be highly correlated with the tropical/Northern Hemisphere pattern (TNH) index at zero time lag with the highest correlation in Northern California and the Sierra and the correlation decreasing southward. This is an important finding because there have been no conclusive studies on the dominant climate modes that modulate precipitation variability in Northern California. It is found that the TNH modulates California precipitation variability through the development of a positive (negative) height anomaly and its associated low-level moisture fluxes over the northeast Pacific Ocean during the positive (negative) TNH phase. Temperature fields, especially minimum temperature, are found to be primarily modulated by the east Pacific/North Pacific pattern, Pacific decadal oscillation, North Pacific pattern, and Pacific-North American pattern at zero time lag via changes in the lower-tropospheric temperature advections. Regression analysis suggests a combination of important climate indices would improve predictability for precipitation and minimum temperature statewide and subregionally compared to the use of a single climate index. While California's precipitation currently is primarily projected by ENSO, this study suggests that using the combination of the TNH and ENSO indices results in better predictability than using ENSO indices only.

This paper presents an evaluation study of a real-time fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) mesoscale ensemble prediction system in the Taiwan area during the 2003 mei-yu season. The ensemble system consists of 16 members that used the same nested domains of 45-and 15-km resolutions, but different model settings of the initial conditions (ICs), the cumulus parameterization scheme (CPS), and the microphysics scheme (MS). Verification of geopotential height, temperature, relative humidity, and winds in the 15-km grid shows that the members using the Kain-Fritsch CPS performed better than those using the Grell CPS, and those using the Central Weather Bureau (CWB) Nonhydrostatic Forecast System (NFS) ICs fared better than those using the CWB Global Forecast System (GFS) ICs. The members applying the mixed-phase MS generally exhibited the smallest errors among the four MSs. Precipitation verification shows that the members using the Grell CPS, in general, had higher equitable threat scores (ETSs) than those using the Kain-Fritsch CPS, that the members with the GFS ICs performed better than with the NFS ICs, and that the mixed-phase and Goddard MSs gave relatively high ETSs in the rainfall simulation. The bias scores show that, overall, all 16 members underforecasted rainfall. Comparisons of the ensemble means show that, on average, an ensemble mean, no matter how many members it contains, can produce better forecasts than an individual member. Among the three possible elements (IC, CPS, and MS) that can be varied to compose an ensemble, the ensemble that contains members with all three elements varying performed the best, while that with two elements varying was second best, and that with only one varying was the worst. Furthermore, the first choice for composing an ensemble is to use perturbed ICs, followed by the perturbed CPS, and then the perturbed MS.

[1] The impact of retrieved total precipitable water (TPW) from Moderate Resolution Imaging Spectrometer (MODIS) infrared (IR), MODIS near-infrared (NIR), and the combined Atmospheric Infrared Sounder (AIRS)-IR and Advanced Microwave Sounding Unit-Microwave channels on simulations of Hurricane Emily was assessed and compared using the Weather Research and Forecasting model and its three-dimensional variation data assimilation (3D-Var) system. After assimilating MODIS IR TPW, the model clearly better reproduced storm tracking, intensity, and the 10 m wind field, while the improvement was limited or nil when assimilating either MODIS NIR TPW or AIRS TPW. After the data assimilation of MODIS IR TPW, a positive moisture increment was present to the east of the simulated storm in 3D-Var analysis (i.e., initial conditions). The positive TPW increment enhanced a convective cloud, which was also observed by satellites. The convective cloud effectively modulated the height and wind fields, resulting in a weakening of the vertical wind shear (VWS) over the region. The weak VWS band was then advected to the north of the storm, preventing the storm from attaching to the strong VWS zone located between 20°N and 30°N. There was no such positive moisture increment, convective cloud, or weak VWS band occurring to the east of the simulated storm in the other data assimilation experiments. This explains why the simulated storm intensified with assimilation of MODIS IR TPW but not for the other experiments.