The National Oceanic and Atmospheric Administration’s Climate Prediction Center (CPC) provides access to a suite of real-time monthly climate forecasts that compose the North American Multi-Model Ensemble (NMME) in an attempt to meet the increasing demands for monthly to seasonal climate prediction. While the North American and global map-based forecasts provided by CPC are informative on a broad or continental scale, operational and decision-making institutions need products with a much more specific regional focus. To address this need, we developed a Region-Specific Seasonal Climate Forecast (RSCF–NMME) tool by combining NMME forecasts with regional climatological data. The RSCF–NMME automatically downloads and archives data and is displayed via a dynamic web-based graphical user interface. The tool has been applied to the Great Lakes region and utilized as part of operational water-level forecasting procedures by the U.S. Army Corps of Engineers, Detroit District (USACE-Detroit). Evaluation of the tool, compared with seasonal climate forecasts released by CPC, shows that the tool can provide additional useful information to users and overcomes some of the limitations of the CPC forecasts. The RSCF–NMME delivers details about a specific region’s climate, verification observations, and the ability to view different model forecasts. With its successful implementation within an operational environment, the tool has proven beneficial and thus set a precedent for expansion to other regions where there is a demand for region-specific seasonal climate forecasts.
Previous research has shown that the temperature and precipitation variability in the Upper Colorado River basin (UCRB) is correlated with large-scale climate variability [i.e., El Niño-Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO)]. But this correlation is not very strong, suggesting the need to look beyond the statistics. Looking at monthly contributions across the basin, results show that February is least sensitive to variability, and a wet October could be a good predictor for a wet season. A case study of a wet and a dry year (with similar ENSO/PDO conditions) shows that the occurrence of a few large accumulating events is what drives the seasonal variability, and these large events can happen under a variety of synoptic conditions. Looking at several physical factors that can impact the amount of accumulation in any given event, it is found that large accumulating events (.10 mm in one day) are associated with westerly winds at all levels, higher wind speeds at all levels, and greater amounts of total precipitable water. The most important difference between a large accumulating and small accumulating event is the presence of a strong (.4 m s 21 ) low-level westerly wind. Because much more emphasis should be given to this more local feature, as opposed to large-scale variability, an accurate seasonal forecast for the basin is not producible at this time.
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