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Qian Cao, Thomas H. Painter, William Ryan Currier, Jessica D. Lundquist, and Dennis P. Lettenmaier

development of techniques that merge the two data sources, for example, mean field bias ( Berndt et al. 2014 ; Nikolopoulos et al. 2015 ), probability density function matching ( Nikolopoulos et al. 2015 ; Hasan et al. 2016 ), and geostatistical approaches including kriging, cokriging, and kriging with external drift (KED; Velasco-Forero et al. 2009 ; Berndt et al. 2014 ; Rabiei and Haberlandt 2015 ). Despite the fact that integration of radar and gauge data exploits both of their strengths, its

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Zeinab Takbiri, Ardeshir Ebtehaj, Efi Foufoula-Georgiou, Pierre-Emmanuel Kirstetter, and F. Joseph Turk

) developed a statistical approach that partitions high-frequency brightness temperatures (≥89 GHz) into two distinct warm and cold weather regimes by thresholding the brightness temperature at 53 GHz. Another class of empirical approaches relies on Bayesian techniques. These techniques use a database or a lookup table that relates brightness temperatures of snowing clouds to the radar snowfall observations along with the atmospheric temperature profile. As an example, Liu and Seo (2013) used matched

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Yagmur Derin, Emmanouil Anagnostou, Marios Anagnostou, and John Kalogiros

methods to validate satellite constellation measurements with surface rainfall measured by dense rain gauge and disdrometer networks at various sites. One such campaign was OLYMPEX, which was conducted in the Pacific Northwest. The goal of OLYMPEX was to validate rain and snow measurements in midlatitude frontal systems as they moved from ocean to coast to mountains and determine how remotely sensed measurements of precipitation by GPM could be applied to a range of hydrological, weather forecasting

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