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May 1995. ; Also issued as Peter Clark Clement's thesis (M.S.) -- Colorado State University, 1995. ; Includes bibliographical references. ; Accurate precipitation measurement is desired over large areal extents in fine temporal and spatial resolution for a myriad of scientific disciplines and practical applications. Hydrological sciences and federal and local government agencies would benefit from improved precipitation measurements. The question is can radars satisfy this desire for better precipitation measurements. The WSR-88D radar network will provide nearly complete radar coverage of the contiguous United States and has the ability to operationally measure large areal extents in fine temporal and spatial resolutions. Precipitation products derived from the WSR-88D networks are becoming readily more accessible and steadily gaining in popularity and use, often without any reference to accuracy. This study is a comparison of precipitation from the CSU-CHILL multiparameter research radar, National Weather Service's WSR-88D located outside Denver, CO (KFTG), and networks of tipping bucket gages. Comparisons are made to reveal spatial coverage of precipitation, time distribution of precipitation, and quantify amounts of precipitation derived from the two radars and gage networks from three convective precipitation events in northeastern Colorado. This study finds the multiparameter variable, specific differential phase derived precipitation (R(KDP)) compared well with gage precipitation for rainfall accumulations greater than 1 cm. On 20 June 1994 for 12 gages with four-hour accumulated precipitation greater than 1 cm, the R(KDP) to gage precipitation ratio was 0.89. On 21 June 1994 for 3 gages with one-hour accumulated precipitation greater than 1 cm, the R(KDP) to gage ratio was 1.37. For precipitation accumulations less than 1 cm, R(KDP) greatly overestimated gage precipitation which is consistent with previous findings. On 20 June at one gage site (FOR) with a known 30- minute period of mixed phase ...

Changes in classified precipitation in Iran and its relationship with global mean surface temperature (GMST) have not been comprehensively investigated. Therefore, this study analyzed changes in precipitation of different intensities over Iran for the 1987–2017 period. Results show that the total annual precipitation (PRCPTOT) and the number of wet days (RR) have significantly decreased over Iran. Also, the mean precipitation intensity (SDII) has increased somewhat. There is a non-uniform change for three intensity categories of precipitation. The amounts (frequency) of light, moderate, and heavy precipitation have significantly decreased at 47% (57.9%), 18.7% (15.8%), and 3.94% (7.9%) of stations respectively. Therefore, the decrease in the amount and frequency of light and moderate precipitation is more severe than heavy precipitation and the proportion of heavy precipitation to the total annual precipitation has increased somewhat during 1987-2017. Overall, the result shows that the intensity of decreasing trends of amount and frequency of precipitation has increased from the south (east) to the north (west) of Iran. Also, SDII has increased from the south (east) to the north (west) of Iran. The sensitivity value was obtained by calculating the ratio of linear trends of precipitation indices and GMST. The regional median sensitivity and percentage change in PRCPTOT, RR, and SDII per 1-kelvin increase in GMST are -6.1%, -11.2%, and 12.9% respectively. Considering that Iran is located in the arid subtropical region, a significant decrease in the amount and frequency of precipitation may have destructive effects on water resources.

This paper presents a classification of the atmospheric circulations producing extreme precipitation events in Bulgaria. Heavy precipitation data set from the National Institute of Meteorology and Hydrology, Bulgaria, atmospheric fields of geopotential height at 1000 hPa, at 500 hPa and temperature at 850 hPa of the ECMWF operational analysis are used to determine the atmospheric patterns (AP). Other atmospheric fields such as geopotential height at 850 hPa, at 700 hPa and relative humidity at 700 hPa are also depicted to analyze the AP. Two statistical methods are used to obtain the AP. Principal Component Analysis (PCA) was applied to reduce the number of variables. Then, Cluster Analysis (CA) was performed and four main AP were obtained. For two AP, heavy precipitation is associated with a low-level cyclone. They can occur in all seasons. For the cold season (October to March), the trajectories of the cyclones are represented. Another pattern, which occurs mainly in the warm season (April to September), depicts an upperlevel cyclonic disturbance associated with heavy precipitation. The last AP represents a weak cyclonic circulation. Finally, a more detailed nine-cluster classification has been also obtained by adding some regional and seasonal features of the heavy precipitation events. ; This research was supported by the Ministry of Environment of the Government of the Kingdom of Spain.