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Probabilistic quantitative precipitation forecasts (PQPF) based on the medium range forecast (MRF) ensemble are currently in operational use below their full potential quality (i.e., accuracy and reliability). This unfulfilled potential is due to the MRF ensemble being adversely affected by systematic errors which arise from an imperfect model and less than ideal ensemble initial perturbations. This thesis sought to construct a calibration to account for these systematic errors and thus produce higher quality PQPF. Systematic errors were explored with the use of the verification rank histogram, which tracks the performance of the ensemble. The information in these histograms was then used in interpreting MRF ensemble forecasts to produce calibrated PQPF. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.