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Russ S. Schumacher, Aaron J. Hill, Mark Klein, James A. Nelson, Michael J. Erickson, Sarah M. Trojniak, and Gregory R. Herman


Excessive rainfall is difficult to forecast, and there is a need for tools to aid Weather Prediction Center (WPC) forecasters when generating Excessive Rainfall Outlooks (EROs), which are issued for the contiguous United States at lead times of 1–3 days. To address this need, a probabilistic forecast system for excessive rainfall, known as the Colorado State University-Machine Learning Probabilities (CSU-MLP) system, was developed based on ensemble reforecasts, precipitation observations, and machine learning algorithms, specifically random forests. The CSU-MLP forecasts were designed to emulate the EROs, with the goal being a tool that forecasters can use as a “first guess” in the ERO forecast process. Resulting from close collaboration between CSU and WPC and evaluation at the Flash Flood and Intense Rainfall experiment, iterative improvements were made to the forecast system and it was transitioned into operational use at WPC. Quantitative evaluation shows that the CSU-MLP forecasts are skillful and reliable, and they are now being used as a part of the WPC forecast process. This project represents an example of a successful research-to-operations transition, and highlights the potential for machine learning and other post-processing techniques to improve operational predictions.

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Hylke E. Beck, Eric F. Wood, Ming Pan, Colby K. Fisher, Diego G. Miralles, Albert I. J. M. van Dijk, Tim R. McVicar, and Robert F. Adler

km at the equator), supporting global-scale land-surface modeling at hyperresolution ( Wood et al. 2011 ; Bierkens et al. 2015 ). Other P datasets with a high spatial resolution (≤0.1°) include Climate Hazards Group Infrared Precipitation with Stations (CHIRPS; 0.05°; Funk et al. 2015b ), CPC morphing technique (CMORPH; 0.07°; Joyce et al. 2004 ), Global Satellite Mapping of Precipitation (GSMaP; 0.1°; Ushio et al. 2009 ; Mega et al. 2014 ), Integrated Multisatellite Retrievals for Global

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Robert F. Myers

The current state of development of the various subsystems of the vertical sounding system is discussed briefly with a forecast of available improvements in measurement techniques expected within the next few years. The possible areas for long-term improvement are explored and some of the consequences considered. A set of design goals is postulated.

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Eugene P. Auciello

The First Northeast Regional Operational Workshop, focusing on hydrometeorology in the northeastern United States, was held 21–23 September 1999 in Albany, New York. Sessions in local and mesoscale modeling, lake-effect snow, hydrology, heavy precipitation forecasting and events, operational techniques, and northeast severe convection were presented. A summary of workshop presentations is provided.

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Manuel E. López

Various special methods of analyzing raobs in the tropics for forecasting purposes are tested and a combination of the best features found is recommended; this technique consists in plotting the 24-hour change of contours of the isobaric surfaces on a time or space cross-section. Some of the difficulties and limitations of such methods are pointed out.

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Thomas W. Bettge, David P. Baumhefner, and Robert M. Chervin

Readily available forecasts of winter season temperature anomalies for the continental United States are analyzed and compared to the observed anomalies for each of the past five winter seasons. Forecast skill is evaluated by different verification methodologies, and it is shown that a judgment of skill can be dependent on the particular verification technique employed. Verification in terms of principal components is shown to be a useful diagnostic aid, in that it allows for the recognition of naturally occurring temperature anomaly patterns in the atmosphere. Other general issues concerning the current state of seasonal climate forecasting also are discussed as they relate to the question of verification strategies.

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Eugene P. Auciello and Ronald L. Lavoie

The modernization of the National Weather Service (NWS) will provide new datasets along with advanced technological capabilities that will enhance our understanding of meteorological and hydrological processes. Improved local warning and forecast techniques should flow from this new understanding. The knowledge transfer to improved services can be greatly accelerated by local partnerships with universities and others in the scientific community. Hence, a key objective of the modernization and associated restructuring of the NWS is to stimulate collaborative research activities among weather forecast offices, river forecast centers, universities, and others in the scientific community. This article describes steps the NWS is taking to improve opportunities for collaboration.

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John M. Porter, L. L. Means, J. E. Hovde, and W. B. Chappell

The aim of this study was to discover synoptic conditions which favored squall-line formation in the north-central United States. The squall lines over approximately a three-year period were classified into three types and studied using charts from the surface to 200 mb. Although the various parameters were not reduced to a strictly objective technique, a check list of significant parameters was prepared for the use and guidance of forecasters. It is believed that this check sheet will help the forecaster in forecasting squall-line development in the north-central United States.

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T.N. Palmer, C. Brankovic, F. Molteni, S. Tibaldi, L. Ferranti, A. Hollingsworth, U. Cubasch, and E. Klinker

Results from a 3 1/2-yr experimental program of extended-range integrations of the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather prediction model are summarized. The topics discussed include

Our results are broadly consistent with those from other major centers evaluating the feasibility of dynamical extended-range prediction. We believe that operational extended-range forecasting using the ECMWF model may be viable to day 20—and possibly beyond—following further research on techniques for Monte Carlo forecasting, and when model systematic error in the tropics has been reduced significantly.

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Jere L. Gilles and Corinne Valdivia

Forecasts play an important role in planting decisions for Andean peasant producers. Predictions of the upcoming cropping season determine when, where, and what farmers will plant. This research looks at the sources of forecast information used by farmers in three indigenous communities in the Bolivian and Peruvian Altiplano by examining networks used to access weather forecasts. The Altiplano is impacted by the ENSO phenomenon and by frequent droughts and frosts so weather- and climate-related risks are the greatest threats to food security. While both Peru and Bolivia have forecasting systems that widely broadcast forecasts via mass media, farmers do not take them into account when they make production decisions. Instead, they rely on traditional forecasting techniques even though confidence in these indicators is declining. Even though traditional forecast indicators are understood by most producers, few make their own forecasts. Instead they depend upon a few local experts who appear to have little connection to scientific forecasts or agricultural extension agencies. The implications of these findings for improving forecast use are then discussed.

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