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Many investigators have used satellite data to derive rainfall intensity and to compare them with rain gauge data. However, there has always been a problem: what is the optimal time period for the two different types of data? A set of well-controlled data collected by ground-based dual-frequency microwave radiometers at the National Central University (24. 9ЊN, 121.1ЊE) in Taiwan between January of 1996 and December of 1997 was used to find the answer. The results show that a 1-h interval would be the optimal time period and that hourly data will provide a better accuracy than other options (5, 10, or 30 min or 2 h). Two algorithms, the differential and the brightness temperature, were established to estimate rainfall intensity using ground-based dual-frequency microwave brightness temperature and rain gauge data. The results show that the root-mean-square error and the correlation coefficient are 0.63 mm h Ϫ1 and 0.88, respectively, for the differential method, and 0.91 mm h Ϫ1 and 0.71 for the brightness temperature method. The analysis also shows that because the atmospheric background and environmental influence in the continuous observations are identical, the changes in brightness temperature are only caused from the changes in liquid water content in the air. That probably made the differential method a better choice for rainfall intensity estimation than the brightness temperature method. Moreover, ground-based radiometers measure downwelling radiation from bottom up, and little ice-particle scattering or horizontal inhomogeneity is involved. The results can be compared with retrievals from satellite microwave radiometers for a better understanding of the physics of microwave emission and scattering due to raindrops or ice particles.

Typhoon Nari struck Taiwan on 16 September 2001, taking 92 lives. Analysis reveals that the storm's heavy rains were due to warmer ocean temperatures, Nari's unique track and slow‐moving speed, and the terrain of Taiwan. Analysis further suggests that the heavy rains in Nari contained many small raindrops. The typhoon rains overwhelmed existing flood protection capacities downstream of the Chi‐Lung River in a part of Taipei that has no regulatory reservoirs, resulting in major flooding. Preliminary findings underscore several key issues for future study, the goal of which will be to improve quantitative precipitation estimation/prediction, hydrologic modeling, and flood prediction.

This study presents dust event spatiotemporal distribution and regional trends, and the impact of surface wind and precipitation on dust occurrences in Mongolia. We used data collected between 2000 and 2013 from 113 meteorological stations in natural forest steppe, steppe, Gobi Desert, and mountain zones. We analyzed the relationship between dusty days, derived using the sum of days with dust storms and/ or drifting dust, and days with strong winds (at a threshold wind speed of a constant 6.5 m s -1 , hereafter, strong wind days) and precipitation by comparing the dusty days in dust-frequent years, dust-less years, and dust-mean years. Dusty days in dust-frequent years were associated with strong wind days when the precipitation is about 10 mm and dust occurrences were suppressed by large amounts of precipitation (approximately 22 mm) in dust-less years over the southeastern part of the Gobi Desert in May. We propose a potential dust index (PDI) based on the correlations among dusty days, strong winds and precipitation. The PDI performed as predicted in most areas of the country in the spring season.