tokens: been identified by IE methodology, where the IE is less than 1.5%. c ( N IE /Total) × 100%. The same study explained in the above paragraph was performed with two other identifiers of MCs (see Huttunen et al. 2005 , their Table 2, and Wu et al. 2003 , /WIND list). In Table 3 , the results are shown in the last two columns. The low successfulness (55.5%) with Huttunen et al. ( 2005 ) has an explanation. The IE methodology was unsuccessful in four events: one event was identified as a cloud candidate (cl) with a time extension of eight hours; two events were classified as MCs, however, on that date ICMEs were not reported; and the last MC was also identified by Wu et al. ( 2003 , /WIND list, event 42 (September 21) with poor quality (3) and with a time extension of seven hours. 4.1.5. False Alarm Cases Furthermore, we saw false alarm cases. False alarm cases are grouped into three categories: (1) non-MC ICMEs according to the catalog of Richardson Cane ( 2010 , Table 3) (20 of these cases were identified); (2) stream interaction regions (SIRs) according to the catalog of Jian et al. ( 2006 , p. 367–371), where 36 SIRs were identified; (3) other cases (non-MC ICMEs and non-SIRs). In Table 4 , the previous categories are shown. In the first category, 15% of false alarms are reported. This is important and can save time, e.g., when a specialist wants to identify new MCs in a large data period. These three cases could be MC-ICME; however, they are not studied in this work. Table 4 Summary of Events That Are Not MCs Reported in 1999 and False Alarm Cases in the IE Analysis Notes. a Number of false alarm cases, i.e., where . b Percent of false alarm cases /Total) × 100%). c Adapted from Richardson Cane ( 2010 , Table 3), from 33 ICMEs: 13 were MCs-ICMEs and 20 were non-MC ICMEs. d Jian et al. ( 2006 , p. 367–371). In the second category, there is only one false positive case. In summary, the IE methodology is not useful to identify SIRs. Finally, five cases are in the third category. These cases are interesting because disturbances in the IMF can be observed. In addition, we are left with two open questions. What really are these events? Why do they have low IE values, similar to an MC? We think that these cases could be flux ropes. However, further study should be done to investigate the above cases. In summary, the IE methodology identified 9 from 13 MCs, and nine false alarm cases are emitted. In a year (1999), a total of 788 windows of 2500 values exist, which means that the percent of false alarms was 1.14%, which is a good result. However, we prefer to propose it as a preliminary result because one year is considered poor statistics to accept the result as a robust identifier of MCs. Despite the difficulties, we can conclude that the IE methodology is useful for studying MCs, and in the next section, the IE methodology is used to identify two MCs. 4.2. Results: Part II After tests on efficiency, the methodology is applied to study some SW
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