New England record rain event of 29–31 March 2010

A significant East Coast Storm affected New England on 29-30 March 2010. The storm brought heavy rainfall and record flooding to portions of southeastern New England. Providence, RI set a daily rainfall record of 134mm (5.32 inches) on 30 March 2010 and had a two-day total rainfall of 221.5mm (8.79 inches) setting a new two-day rainfall record. Many sites in southern New England set daily and monthly rainfall records. The heavy rain was relatively well predicted by the National Centers for Environmental Predictions Ensemble forecast systems. The forecasts of this event depicted a pattern conducive for heavy rainfall. It will be shown that standardized anomalies aided in identifying the potential impact of this event. Initially, the NCEP models and ensemble forecast systems predicted a surge of high precipitable water with strong southerly winds. As the event unfolded, a second surge of rainfall was predicted with strong easterly winds as a surface cyclone developed and moved up the coast. This created a unique situation where a Maddox synoptic heavy rain pattern evolved into a frontal type event. The two periods of heavy rainfall produced the record two-day totals and contributed to the flood problems. It will be shown that the precipitable water and wind anomalies were critical in defining the pattern and gauging the potential impact of this storm. In addition to the pattern and associated anomalies, the models and ensemble forecast systems indicated a potential for heavy rainfall. Based on the anomalies of key fields; such as precipitable water, low-level v-winds, and u-winds; associated with heavy rainfall the potential for a significant event was potentially indicated. The pattern and anomalies reinforced the probabilities of heavy rainfall indicated by the ensemble forecast systems. Both forecast and analyzed anomalies associated with this historic storm will be presented. These data will show how the synoptic-scale anomalies were well correlated with the heavy rainfall. The anomalies facilitate putting this event into a historical perspective relative to previous events. This case demonstrates the utility of using anomalies to increase forecaster confidence and situational awareness. It will shown how improved anomaly based situational awareness combined with probabilistic ensemble quantitative precipitation forecasts facilitate and improve decision support activities for future significant events such as this.