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Copyright of Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales is the property of Academia Colombiana de Ciencias Exactas, Fisicas y Naturales and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Given that there is an increasing demand and use of numerical models to forecast precipitation events, it is essential to advance in the use of different verification methods to measure the quality of the forecasts with the evaluation of errors and biases. The method for object-based diagnostic evaluation (MODE) is a spatial verification method that identifies regions of interest, like precipitation, in the same way that a human would do. This method defines objects in the forecast and observation fields based on user-defined parameters. MODE was used to evaluate the performance of 4-km hourly precipitation forecasts from the Weather and Research Forecasting Model (WRF) over southern South America against the Global Precipitation Measurement (GPM) derived product IMERG Final Run version (IMERG-F). For a one month period, tests were performed to select the values for threshold and the radius of convolution parameters adequate for 3 and 24 hour accumulated precipitation. The whole verification period considered was 2017-2018 and furthermore, traditional verification statistics (eg, Probability of Detection, False Alarm Ratio) were used. Additionally, 24-hour accumulated precipitation forecasts from WRF were compared with those from the Global Forecast System (GFS). This study proved that traditional verification methods allow objectively to know the quality of precipitation forecasts. Conversely, object verification rather than making a pointwise evaluation of hits and misses, identifies precipitation patterns and compares attributes describing position, size and intensity of matched forecasted and observed objects. Regarding the analyzed models, although WRF and GFS present many surprises and false alarms, hit events present low errors associated with location and intensity of precipitation. [ABSTRACT FROM AUTHOR]

Copyright of Agro Productividad is the property of Colegio de Postgraduados and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tecnología y Ciencias del Agua is the property of Instituto Mexicano de Tecnologia del Agua (IMTA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Semata: Ciencias Sociais e Humanidades is the property of Universidad de Santiago de Compostela, Servicio de Publicaciones and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)