Utilizing Climatologies to Aid in the Issuance of the Weather Prediction Center's Excessive Rainfall Outlook

The Weather Prediction Center has been issuing the Excessive Rainfall Outlook (ERO) in its present form since 2009 as an aid to local Weather Forecast Offices in the prediction of upcoming heavy rainfall that has the potential to cause flash flooding. Over the years, many developers and forecasters have contributed to the refining of the ERO and have worked to improve its accuracy. We now propose a new forecasting aid to act as a guide for the forecasters as they prepare their ERO for the day using the climatology of past EROs and their corresponding observations. The ERO Analog Tool first finds similar EROs to the one that the forecaster is preparing (referred to as the “current ERO”). Similar EROs include those that were issued for the same geographical area and time of year. For the ERO Analog tool, the geographical location of a past ERO is determined by the location of its centroid, which must fall within a 5 degree latitude/longitude box of the current ERO. The past ERO must also have been issued in the same month of its respective year as the current ERO or in the preceding or following month. Next, the shape of the similar EROs and their corresponding observations are objectively assessed using the Model Evaluation Tools (MET) Method for Object-based Diagnostic Evaluation (MODE) tool. The visualization of these climatologically similar past EROs then allows forecasters to identify local biases and forecaster tendencies by examining the past EROs and their matching observational object shapes with respect to the current ERO’s location. We note that not all days’ conditions are conducive to use of this tool. In cases with rare setups or isolated events (for example a landfalling hurricane), the climatology presented in the ERO Analog Tool may not be the best guide in deciding the bounds for the current ERO. Forecasters will be evaluating the benefits of using this prototype tool this upcoming convective season.