Figure 9. Comparison of Lim and Chang's (1981) barotropic equatorial beta-plane cold surge theory (panels A and B) and observed NOGAPS 850 hPa wind analysis (panels C and D), each for two time periods separated by three days. Because the narrow width of the South China Sea confined the width of the intense surge belt to about one half of that in the terrain-free equatorial beta-plane solution, a comparison of the theory and the actual development may be made by scaling the east—west dimension of the upper panels to one half of the original size (L = 15° longitude instead of 30° ), or treating the highlighted rectangular area in panels A and B as being comparable to the domain of the NOGAPS plots. The location of the high center in panel B was also shifted eastward by 0.4 L to account for the reduced zonal scale, the typical eastward movement of the East Asian surface high center, and the geographical restriction of the surge belt by the South China Sea. See text for details. [Diagram adapted from Lim and Chang (1980) and Chang et al. (2003) by permission of American Meteorological Society and American Geophysical Union, respectively.]

of Typhoon Vamei is shown in Fig. 9, where the top panels (A and B) display the theoretical solutions three days apart in a pressure-induced surge, and the bottom panels (C and D) display the NOGAPS 850 hPa wind analysis for 19 December and 22 December 2007, respectively.

Panel A shows the theoretical solution of a case of an equatorward surge that is initiated by a high-pressure anomaly centered at 30°N, with no mean flow. The pattern resembles the typical cold surge event that follows the southeastward movement of an East Asian surface high center with the development of a northeast-southwest tilt. This tilt is due to the dispersive properties of equatorial beta-plane Rossby waves in which the lower meridional modes have larger amplitudes closer to the equator, and therefore propagate westward more quickly. As the northeasterly wind strengthens south of the high center, it streams southward, and after crossing the equator, it turns eastward between the equator and 15° S. Panel B shows the solution three days later, in which the northeast-southwest tilt becomes even more pronounced. To the southeast of the northeasterly surge streak, southwesterly cross-equatorial winds produce a wave (area d) as they swing back south to merge with the equatorial easterlies. The area between the surge streak and area d is a northeast-southwest-oriented counterclockwise circulation belt over the equator. The flow pattern (west of the equatorial easterlies) is mainly the manifestation of a dispersive Rossby wave group. The lower panels show the NOGAPS 850 hPa wind analysis at the beginning of the actual cold surge (panel C; 0000 UTC 19 December), and three days later (panel D; 0000 UTC 22 December). Because of the narrow width of the South China Sea, the width of the intense surge belt is confined to about 750 km, which is approximately one half of that in the equatorial beta-plane solution in panel B which is not subject to any terrain restriction. Thus, a comparison of the theory and the actual development may be made by scaling the east-west dimension of the upper panels to one half of the original size (L = 15° longitude instead of 30°), or treating the highlighted rectangular area in panels A and B as being comparable to the domain of the NOGAPS plots. The location of the high center in panel B was also shifted eastward by 0.4 L to account for the slower propagation due to the reduced zonal scale and two factors in real cold air outbreak events: the eastward movement of the East Asian surface high center due to the westerly mean flow, and the fixed location of the surge belt that is restricted geographically by the South China Sea.

4. Concluding Remarks: Key Question Posed by Typhoon Vamei

Since the observation of Typhoon Vamei, a number of modeling studies have successfully simulated this case of equatorial formation (e.g. Chambers and Li, 2007; Juneng et al., 2007; Koh, 2006). This is not surprising, since the interaction between the winter monsoon circulation and the complex terrain and the moisture from the warm ocean surface provided the vorticity and latent heat sources for development. However, the strong cold surge and Borneo vortex that led to the development of Typhoon Vamei are both regularly observed, major systems of the Asian winter monsoon in the South China Sea, and abundant low-level warm and moist air is present every winter. So the most interesting question is more than just how or why Typhoon Vamei could form so close to the equator, but rather, why more typhoon formation was not observed in the equatorial South China Sea.

Chang et al. (2003) postulated that the answer lies in the narrow extent of the equatorial South China Sea. Prior to Typhoon Vamei's formation, a strong cold surge persisted for nearly one week over the narrowing South China Sea, providing a source for background cyclonic vorticity as the surge wind crossed the equator. The anomalous strength and persistence of this surge was related to the anomalously strong meridional gradient of sea-level pressure in the equatorial South China Sea during December 2001 (Bureau of Meteorology Northern Territory Region, 2002). The narrowing of the South China Sea at the equator plays two counteracting roles that combine to make the occurrence of the typhoon formation possible but rare. On the one hand, the channeling and strengthening of the cross-equatorial surge winds helps to produce the background cyclonic vorticity at the equator. On the other hand, the open water region of approximately 5° longitude is just sufficient to accommodate the diameter of a small tropical cyclone. However, it is too small for most synoptic-sized disturbances to remain over the water for more than a day or so. In the unusual case of Typhoon Vamei, the durations of the intense cold surge and the Borneo circulation remaining over water were both significantly longer than normal, which allowed the interaction to continue for nearly a week until the storm was formed.

In an analysis of the NCEP/NCAR reanalysis during the boreal winters of

1951/52-2001/02, Chang et al. (2003) found that a total of 61 strong surge events lasting one week or more in the southern South China Sea occurred. The total number of days under these persistent surges is 582. Assuming that the vortex needs at least a 3-day overlap with the surge to develop, the sustained cyclogenesis due to a strong background relative vorticity is estimated to be present at the equator on about 10% of the boreal winter days. If the minimum persistent surge duration required is reduced from 7 days to 5, the available time of the spinning top effect is increased to 14%. During the 51 boreal winters, the frequency of a pre-existing Borneo vortex staying over the equatorial water continuously for 4 days or more is 6, or a probability of 12% in a given year. Whether a pre-existing disturbance develops into a tropical cyclone depends on background vertical shears of wind and vor-ticity, upper level divergence, and a variety of environmental factors (Anthes, 1982; McBride, 1995). In the more favored tropical cyclone basins of the western Pacific and North Atlantic, the percentage of pre-existing synoptic disturbances developing into tropical cyclones during their respective tropical cyclone seasons ranges between 10% and 30%. Thus, of all the conditions that led to the formation of Vamei, Chang et al. (2003) estimated the probability of an equatorial development from similar conditions to be about once in a century or longer. This estimate appears consistent with the history of observations. However, it is not known whether other near-equatorial developments have occurred but were not observed during the presatellite era.


Interesting discussions were provided by H. Lim and S. L. Woon (Singapore); S. H. Ooi and Y. F. Hwang (Malaysia); C.-H. Liu and H.-C. Kuo (Taiwan); and R. Edson and M. Lander (Guam). This work was supported by ONR contract

N0001402WR20302, NSF Grant ATM0101135 and the National Science Council/National Taiwan University.

[Received 15 August 2007; Revised 19 January 2008; Accepted 22 January 2008.]


Anthes, R. A., 1982: Tropical Cyclones: Their Evolution, Structure and Effects, American Meteorological Society Boston, 208 pp.

Chan, J., and C. Li, 2004: The East Asia winter monsoon. In East Asian Monsoon. C.-P. Chang (ed.), World Scientific Series on Earth System Science in Asia, Vol. 2, pp. 54-106.

Chambers, C. R. S., and T. Li, 2007: Simulation of a near-equatorial typhoon Vamei (2001). Meteorol. Atmos. Phys., 97, 67-80.

Chang, C.-P., J. E. Millard, and G. T. J. Chen, 1983: Gravitational character of cold surges during Winter MONEX. Mon. Wea. Rev., 111, 293-307.

Chang, C.-P., C.-H. Liu, and H.-C. Kuo, 2003: Typhoon Vamei: an equatorial tropical cyclone formation. Geophys. Res. Lett., 30, 1151-1154.

Chang, C.-P., P. A. Harr, J. McBride, and H. H. Hsu, 2004: Maritime Continent monsoon: annual cycle and boreal winter variability. East Asian Monsoon, C.-P. Chang (ed.), World Scientific Series on Earth System Science in Asia, Vol. 2, pp. 107-150.

Chang, C.-P., P. A. Harr, and H. J. Chen, 2005: Synoptic disturbances over the equatorial South China Sea and western Maritime Continent during boreal winter. Mon. Wea. Rev., 133, 489-503.

DeMaria, M., and J. D. Pickle, 1988: A simplified system of equations for simulations of tropical cyclones. J. Atmos. Sci. 45, 1542-1554.

Fortner, L. E., 1958: Typhoon Sarah, 1956. Bull. Amer. Meteor. Soc., 39, 633-639.

Gray, W. M., 1968: Global view of tropical disturbances and storms. Mon. Wea. Rev., 96, 669-700.

Holland, G. J., 1984: On the climatology and structure of tropical cyclones in the Australian Southwest Pacific Region. Aus. Meteor. Mag., 32, 17-31.

Johnson, R. H., and R. A. Houze, Jr., 1987: Precipitating clouds systems of the Asian monsoon. In Monsoon Meteorology, C.-P. Chang and T. N.

Krishnamurti (eds.), Oxford University Press, pp. 298-353.

Juneng, L., F. T. Tangang, C. J. Reason, S. Moten, and W. A. W. Hassan, 2007: Simulation of tropical cyclone Vamei (2001) using the PSU/ NCARMM5 model. Meteorol. Atmos. Phys., 97, 273-290.

Koh, T.-Y., 2006: Numerical weather prediction research in Singapore and case study of tropical cyclone vamei. In Winter MONEX: A Quarter Century and Beyond (WMO Asian Monsoon Workshop, 4-7 April 2006, Kuala Lumpur, Malaysia).

Lau, W. K.-M., and C.-P. Chang, 1987: Planetary scale aspects of winter monsoon and teleconnections. In Monsoon Meteorology, C.-P. Chang and T. N. Krishnamurti (eds.), Oxford University Press, pp. 161-202. Lim, H., and C.-P. Chang, 1981: A theory for mid-latitude forcing of tropical motions during winter monsoon. J. Atmos. Sci., 38, 2377-2392. McBride, J. L., 1995: Tropical cyclone formation. In Global Perspective on Tropical Cyclones, R. L. Elsberry (ed.), Tech. Docu. 693, World Meteorological Organization, pp. 63-105.

Assimilation of Satellite Ocean Surface Winds at NCEP and Their Impact on Atmospheric Analyses and Weather Forecasting

Tsann-Wang Yu

NOAA Center for Atmospheric Sciences, Howard University, Washington, D.C., USA

[email protected] edu

The improvement in the forecasting skills of short range numerical weather prediction is attributable to two major advances since the inception of operational numerical weather prediction in the late 1950's: the advent of satellite remote sensing since the 1970's, which has vastly increased the number of observations in the operational database, and the improvement in the treatment of model physics, numerics and spatial resolution of the global forecast models, and their associated atmospheric data analysis and data assimilation systems, which are capable of effectively using the vast amounts of satellite data observations for NWP operations. The evolution of the operational global data assimilation systems at NCEP is briefly described, followed by a review of various satellites during the last two decades that have been designed to provide global coverage of ocean surface winds. These include SEASAT, NSCAT, ERS-1/2, SSM/I and the most current operational satellite, QuikSCAT. On board these satellites, data characteristics of two microwave instruments for measuring the ocean surface winds from both an active scatterometer and a passive radiometer are discussed. The procedures for effectively using these satellite ocean surface wind data in the global data assimilation experiments, and that for assessing the impact of any particular data set, are described. Results of preimplementation impact investigations on the use of these satellite surface winds are discussed, and based on the results of these investigations, these data are implemented in NCEP's NWP operations. It is fair to state that from the gross statistics based on many cases of forecasts, the impact of satellite ocean surface winds on the short range NWP forecasts is mostly positive and significant, albeit small because the data are of a single level nature and are available only over the ocean surface. A case study is presented which shows that the use of satellite scatterometer ocean surface winds has a significantly large positive impact on the storm intensity and circulation over the southwestern Pacific Ocean.

1. Introduction

The forecasting skills of short range numerical weather prediction (NWP) have been steadily improving since the beginning of the NWP operations in the late 1950's. These improvements are undoubtedly attributable to improvements in model physics and numerics, increase in spatial resolutions, and advances in the fields of satellite remote sensing, atmospheric analysis and data assimilation. At operational NWP

centers such as the National Center for Environmental Prediction (NCEP) and the European Center for Medium Range Weather Forecasts, (ECMWF), the numbers of conventional and satellite data used in a synoptic cycle analysis are typically more than 2 million, of which the majority (more than 90%) are from satellite observations. Figures 1 and 2 respectively show 500 mb geopotential height anomaly correlations for NCEP (Lord, 2004) and ECMWF

CDAS/Reanl vs GFS NH/SH 500Hpa day 5 Anomaly Correlation (20-80 N/S)

1960 1970 1980 1990 2000

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