Timeline (years) showing the changing sources of raw data and other important events related to the CMA TC database since 1949. AWS is the autoweather system, and JMA is the Japan Meteorological Agency.
The basic contents of the CMA TC database, as well as the main procedures and analysis rules, have changed little since they were designed and fixed during the reanalysis project. However, the input data used in analysis, and the technical details of the analytical procedures, have changed several times, especially since the start of the postseason analysis era. An overview of these related issues may be useful to those using the database. In this paper, we summarize the basic features of, and changes to, the CMA TC database since its creation. The contents of both datasets, which hold the best-track data and TC-induced wind and precipitation data, are summarized in section 2. An overview of the input data and technical details is provided in section 3. Finally, concluding remarks are presented in section 4.
China Weather
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As mentioned above, the CMA TC database includes two parts: the best-track dataset and its supplementary data, and the TC-induced wind and precipitation observation dataset for the land area of China. Both datasets cover seasons from 1949 to the present, and are updated annually.
The basic-track information is similar to that in the datasets of the other agencies, and includes location, MSW, and minimum sea level pressure (MSLP). However, the CMA is unique in using MSW obtained from a 2-min mean. The technical aspects regarding the 2-min mean MSW will be discussed in section 3b. The CMA best-track dataset also focuses on specific phenomena, such as extratropical cyclone stages, subcenters, the outer-range severe winds of TCs over the SCS, and coastal severe winds associated with TCs landfalling in China. In addition, specialized landfalling TC data and satellite imagery analysis data are included as supplements to the best-track data. In the following sections, we introduce this special content of the CMA best-track dataset.
In addition to the ordinary MSW data used as a parameter of TC intensity, there is a special wind speed parameter m in the CMA best-track data. This parameter (m) is related to two forms of special phenomena: outer-range severe winds associated with some TCs over the SCS and the coastal severe winds associated with some landfalling TCs. Both phenomena have been associated with TCs and related disasters (e.g., casualties and damage to fishing boats), especially during the early years.
Some TCs that make landfall in China may generate a severe wind zone along the coastline, with winds even stronger than their MSWs (Chen and Ding 1979). Such phenomena usually occur when a TC interacts with a warm depression over the landmass. In these cases, the additional parameter m denotes the maximum coastal severe wind, which is farther away from the TC center than the MSW. Figure 3b shows the intensity evolution of a typical landfalling case with a coastal severe wind: Typhoon Gilda (1952). Unlike the evolution of outer-range severe winds, the MSW and coastal severe wind weakened step by step as Gilda (1952) moved inland, and hence farther from the coastline. This is a typical feature of landfalling TCs accompanied by a severe coastal wind.
As these two forms of severe wind phenomena are represented in the same format in the dataset, a convenient method of distinguishing between them is to check the location of the TC; that is, outer-range severe winds are restricted to TCs over the SCS, while coastal severe winds only occur when the TC moves over the land area of China.
As a supplement to the best-track dataset, the CMA TC database also includes specialized data for TCs that made landfall in China from the 1949 season to the present. A sample of the landfalling TC data is shown in Table 2. The data include the TC ID, landfall event, location, date and time, and TC intensity at the time of landfall in China. The TC ID is the same as that in the best-track dataset. The landfall times indicate how many times a TC made landfall in China, including on the Zhoushan Archipelago (in the East China Sea), the large islands of Hainan (in the SCS), and Taiwan. For instance, the severe TS Otto (1998), marked with CMA ID 9802, made landfall in China twice: first in Taiwan and then in Fujian Province (Table 2). Landfall intensity is determined using three measures: the Beaufort scale (BS) for wind strength, MSW, and MSLP. It should be noted that both the BS and MSLP data are available back to the 1949 season, and the MSW data are available back to the 1973 season.
Some principles are predefined for analysis of the draft best-track data. In general, the best-track data are smoothed to reduce unrealistically abrupt changes in either track or intensity over the 6-, 12-, 18-, and 24-h periods. Keeping this in mind, different principles are applied when analyzing TCs over land or ocean, due to differences within the input data. In particular, over the ocean area, the best track is usually determined primarily according to either in situ observations or satellite images, while over the land area, the locations and intensities are analyzed based on station observations. The in situ observations include aircraft reconnaissance over the open ocean, radar over the coastal and land area, and from stations and radiosonde over land. The basic meteorological elements used in the analysis include temperature, wind, pressure, precipitation, etc. It is worth mentioning that an analysis of the evolution of the rainfall pattern accompanying a TC is helpful for fixing its position over land (see the example in section 3c).
For TCs over the land area of China, both the MSLP and MSW are recorded according to the observations. For TCs over the ocean, during the aircraft reconnaissance period before 1987 (Fig. 4), the reconnaissance data, among all available in situ observations, were preferred for intensity estimation, while other available in situ observations, such as ship reports and island observations, served as cross references and alternative sources of information. After aircraft reconnaissance was canceled, satellite imagery became the preferred choice for TCs over the open ocean, where other in situ observations were unavailable. Real-time TC warning advice is also preferred when other observations are unavailable. It should also be noted that while the wind averaging time of the MSW in the CMA best-track dataset is usually 2 min, the aircraft reconnaissance wind was observed at 1-min intervals and was not converted to a 2-min basis. This is reasonable, since the conversion factor of the two different sustained wind speeds is about 1.0 over the open ocean (Harper et al. 2010).
Note that Fig. 8 incorporates both observation-based data (i.e., aircraft reconnaissance and weather station observations) and estimated data (e.g., satellite image analysis). With respect to the WPR, the two sources of data are not equally reliable. Also, the WPR may obey different rules for the tropical and extratropical cyclone stages.
The analysis of TC-induced wind and precipitation over the land area of China is another important issue for the CMA TC database. Approximately 2100 candidate stations have been included in the database since 2007 (Fig. 5), as compared with approximately 1600 stations in the 1980s and 1990s, and even fewer during the early 1950s (see section 3a). The change in the number of stations was mainly due to the development of the observation network in China (Ying and Wan 2011). Based on these station observations, the wind and precipitation patterns associated with TCs are determined from either synoptic charts or satellite imagery. The wind and precipitation generated by the TCs can then be determined (refer to the right side of Fig. 7).
It is well known that the interaction of TCs with other synoptic systems is quite complex over the land area of China (e.g., Chen and Ding 1979; Lei and Chen 2001). Several rules have been defined to facilitate the distinction between wind and precipitation generated by TCs and that associated with other systems. However, subjective analysis is still necessary to deal with the unique state of individual cases, which cannot be addressed according to predefined rules.
Above all, either severe wind or precipitation induced by interactions between TCs and other systems should be included in the database. This is a crucial rule and was created to ensure that more comprehensive TC data were included. Specific rules have also been established to define which interactions between a TC and various synoptic systems should be considered TC-associated. These rules are as follows.
When a TC interacts with the southwestern vortex (Kuo et al. 1986; Lu 1986; Wang and Orlanski 1987), the precipitation within the vortex circulation should be excluded from TC-associated precipitation, since the vortex itself is a rain-bearing system.
As the raw data sources and analysis procedures changed temporally and spatially, the reliability of the data also changed, especially in the best-track dataset. For instance, the annual TC number may not be reliable prior to the satellite era, as some TCs over the open ocean could have remained undetected. Although satellite images were not used in the reanalysis stage covering seasons from 1949 to 1971, other sources of data, such as the real-time TC warning advice issued by various agencies and the JTWC annual reports, were used to determine the candidate TC cases for reanalysis. Therefore, the annual TC number, as with the other agencies, may be reliable during the entire satellite era, including seasons before 1987. 152ee80cbc
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