Hurricanes and flood-related events cause more direct economic damage than any other type of natural disaster. In the United States, that damage totals more than USD 1 trillion in damages since 1980. On average, direct flood losses have risen from USD 4 billion annually in the 1980s to roughly USD 17 billion annually from 2010 to 2018. Despite flooding’s tremendous economic impact on US properties and communities, current estimates of expected damages are lacking due to the fact that flood risk in many parts of the US is unidentified, underestimated, or available models associated with high quality assessment tools are proprietary. This study introduces an economic-focused Environmental Impact Assessment (EIA) approach that builds upon an our existing understanding of prior assessment methods by taking advantage of a newly available, climate adjusted, parcel-level flood risk assessment model (First Street Foundation, 2020a and 2020b) in order to quantify property level economic impacts today, and into the climate adjusted future, using the Intergovernmental Panel on Climate Change’s (IPCC) Representative Concentration Pathways (RCPs) and NASA’s Global Climate Model ensemble (CMIP5). This approach represents a first of its kind—a publicly available high precision flood risk assessment tool at the property level developed completely with open data sources and open methods. The economic impact assessment presented here has been carried out using residential buildings in New Jersey as a testbed; however, the environmental assessment tool on which it is based is a national scale property level flood assessment model at a 3m resolution. As evidence of the reliability of the EIA tool, the 2020 estimated economic impact (USD 5481 annual expectation) was compared to actual average per claim-year NFIP payouts from flooding and found an average of USD 5540 over the life of the program (difference of less than USD 100). Additionally, the tool finds a 41.4% increase in average economic flood damage through the year 2050 when environmental change is included in the model.

Abstract. Continental–global-scale flood hazard models simulate design floods, i.e. theoretical flood events of a given probability. Since they output phenomena unobservable in reality, large-scale models are typically compared to more localised engineering models to evidence their accuracy. However, both types of model may share the same biases and so not validly illustrate their predictive skill. Here, we adapt an existing continental-scale design flood framework of the contiguous US to simulate historical flood events. A total of 35 discrete events are modelled and compared to observations of flood extent, water level, and inundated buildings. Model performance was highly variable, depending on the flood event chosen and validation data used. While all events were accurately replicated in terms of flood extent, some modelled water levels deviated substantially from those measured in the field. Despite this, the model generally replicated the observed flood events in the context of terrain data vertical accuracy, extreme discharge measurement uncertainties, and observational field data errors. This analysis highlights the continually improving fidelity of large-scale flood hazard models, yet also evidences the need for considerable advances in the accuracy of routinely collected field and high-river flow data in order to interrogate flood inundation models more comprehensively.

The North American Great Lakes influence surface weather downwind, distinctly in winter when southward migrating cold air passes over relatively warm lakes. Study of the synoptic atmospheric patterns favorable for lake effects has focused on lake-effect snowfall, the most impactful effect of the lakes. Although the patterns are conducive to lake effects, they might not actually yield discernible modification of downwind surface weather. This study uses historical daily data (1964-1965 through 2017-2018) of weather types to detect cool season (November-April) modification of cold, dry air upwind of the Great Lakes to cool, moist air downwind of the eastern (Erie, Ontario) and western (Michigan, Superior) lakes. A spatial arrangement of weather types across the region is shown to identify individual days characterized by a lake effect. The frequency of lake effects increased through the first one third of the record, but it has since decreased, most profoundly since a change point in the late 1990s and more prominently for the eastern lakes. At stations immediately downwind of the lakes, the result is a changed cool season hydroclimate, with fifty-four-year declines in lake-effect precipitation amount and frequency and in the percentages of seasonal precipitation amount and frequency attributed to lake effects.

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An air mass approach was used to identify episodes of cool season cold-air damming (CAD) within the central Appalachian Mountains region of the eastern United States. Daily air mass type data were used to identify days on which moist polar (MP) air was regionally evident east of the mountains, while non-MP air was in place at nearby stations west of the mountains. Over a 35-year study period, 219 CAD days were identified (>6 per year) with the annual frequency exhibiting no trend but suggesting that El Niño (La Niña) coincides with a greater (lesser) frequency of CAD days in winter (December-February). Synoptic atmospheric composites reveal west-to-east migration of a parent anticyclone to a classic position along the border of the northeastern United States and southeastern Canada. This coincides with a pattern of amplifying and slowly eastward-moving 500 hPa height anomalies characterized by positive (negative) values over eastern (western) North America that are signalled a few days in advance by the index representing the Pacific-North American teleconnection pattern. Confinement of the CAD below the 850 hPa level is evident in the synoptic wind field, while the composite vertical profile of the atmosphere within the CAD environment further depicts the shallow nature of the surface-based cool, moist air. Northeasterly winds at the surface veer to southeasterly within a few hundred metres above the surface, and then southwesterly at less than one km above the surface, at the 850 hPa level. The air mass approach to CAD identification appears to successfully identify regional occurrences of synoptically forced CAD, although it likely does not detect local and/or diabatically forced CAD.