As the most severe drought over the Northeastern United States (NEUS) in the past century, the 1960s drought had pronounced socioeconomic impacts. Although it was followed by a persisting wet period, the conditions leading to the 1960s extreme drought could return in the future, along with its challenges to water management. To project the potential consequences of such a future drought, pseudo-global warming simulations using the Weather Research and Forecasting Model are performed to simulate the dynamical conditions of the historical 1960s drought, but with modified thermodynamic conditions under the shared socioeconomic pathway SSP585 scenario in the early (2021-2027), middle (2041-2047) and late (2091-2097) 21st century. Our analysis focuses on essential hydroclimatic variables including temperature, precipitation, evapotranspiration, soil moisture, snowpack and surface runoff. In contrast to the historical 1960s drought, similar dynamical conditions will generally produce more precipitation, increased soil moisture and evapotranspiration, and reduced snowpack. However, we also find that although wet months get much wetter, dry months may become drier, meaning that wetting trends are most significant in wet months but are essentially negligible for extremely dry months with negative monthly mean net precipitation. For these months, the trend towards wetting conditions provides little relief from the effects of extreme dry months. These conditions may even aggravate water shortages due to an increasingly rapid transition from wet to dry conditions. Other challenges emerge for residents and stakeholders in this region, including more extreme hot days, record-low snow pack, frozen ground degradation and subsequent decreases in surface runoff.

Climate models are frequently-used tools for adaptation planning in light of future uncertainty. However, not all climate models are equally trustworthy, and so model biases must be assessed to select models suitable for producing credible projections. Drought is a well-known and high-impact form of extreme weather, and knowledge of its frequency, intensity, and duration key for regional water management plans. Droughts are also difficult to assess in climate datasets, due to the long duration per event, relative to the length of a typical simulation. Therefore, there is a growing need for a standardized suite of metrics addressing how well models capture this phenomenon. In this study, we present a widely applicable set of metrics for evaluating agreement between climate datasets and observations in the context of drought. Two notable advances are made in our evaluation system: First, statistical hypothesis testing is employed for normalization of individual scores against the threshold for statistical significance. And second, within each evaluation region and dataset, principal feature analysis is used to select the most descriptive metrics among 11 metrics that capture essential features of drought. Our metrics package is applied to three characteristically distinct regions in the conterminous US and across several commonly employed climate datasets (CMIP5/6, LOCA and CORDEX). As a result, insights emerge into the underlying drivers of model bias in global climate models, regional climate models, and statistically downscaled models.

Abstract. Intensified extreme precipitation and resulting flooding are among the most impactful consequences of climate change, especially over the northeastern US (NEUS). To project and understand the impacts of climate change (or related climate perturbations) on extreme weather events as they may occur in the future, the Pseudo-Global Warming (PGW) method has been employed with great success. However, it has never been ascertained to what degree the conclusions from PGW studies are sensitive to the design of the PGW experiment. Consequently, three key questions related to the application of the PGW method remain unanswered: At what spatial scale should climate perturbations be applied? Among the different meteorological variables available, which should be perturbed? And will PGW projections vary significantly under different experiment designs? To begin to address these questions, we examine the sensitivity and robustness of conclusions drawn from the PGW method over NEUS by conducting multiple PGW experiments. The results show that the projections of precipitation and other essential variables are consistent at the regional mean scale, with a relative difference of much less than 10\\%; however, different experimental designs nonetheless cause significant displacements among storm events. Several previously assumed advantages of modifying temperature at the regional mean scale do not appear to hold, such as the preservation of geostrophic balance. Also, we find the regional mean perturbation produces a positive precipitation bias due to overestimated warming over the ocean. Overall, PGW experiments with perturbations from temperature or the combination of temperature and wind at the gridpoint scale are both recommended, depending on the research target. The first approach can isolate the spatially-dependent thermodynamic impact, and the latter incorporates both the thermodynamic and dynamic impacts.

Since the infamous extreme drought of the 1960s, the climate of the Northeastern United States (NEUS) has generally trended towards warmer and wetter conditions. Nonetheless, there is mounting evidence that short-term droughts will continue to pose a significant risk for this region. To better explore the processes governing events such as these, climate models have adopted more complex representations of the fully coupled atmosphere-land-ocean-sea ice system; however, large uncertainties in future projections still persist, with internal variability necessitating large ensembles to understand trends in both rare and high-impact extreme events such as rapidly developing droughts (a term here that includes flash droughts developing on monthly scales). In this study, 7 large ensemble (LE) models are employed to answer the outstanding question – how is the frequency and character of drought in the NEUS changing under a warming climate? We find most LE models indicate the NEUS will experience a long-term wetting trend with more “extremely wet” months, but also more frequent short-term extreme droughts. These changes are associated with increasing precipitation, atmospheric water demand, and climate variability. We also conclude that discrepant trends in precipitation and evapotranspiration variability will lead to increasing anti-correlation of these variables, which is relevant to the intensification of rapidly developing drought – particularly in the spring season. These changes are associated with an increase in evapotranspiration from plants, brought by an earlier emergence of the growing season and denser vegetation.

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