Characterizing changes in precipitation patterns over time is critical for hydrologically-dependent fields like water resource management and agriculture. Here, we explore observed trends in interannual precipitation variability using a suite of metrics that describe changes in precipitation over time. We analyze daily in-situ Global Historical Climatology Network precipitation data from 1970 to present over seventeen internally consistent sub-national United States domains using a regional Mann-Kendall trend test. We find robustly increasing trends in annual mean precipitation and wet day frequency for most of the central and eastern U.S., but decreasing trends in the western U.S. Importantly, we identify widespread significant trends in interannual precipitation variability, with increasing variability in the southeast, decreasing variability in the far west, and mixed signals in the Rocky Mountains and north-central U.S. Our results provide important context for water resource managers and a new observational standard for climate model performance assessments.

AbstractWater levels in the Laurentian Great Lakes have fluctuated dramatically over recent decades. Since 2015, each of the lakes has reached a record high, often following a recent record or near-record low. These exceptional swings have motivated examinations of changes in lake level variability, particularly given the known climate change-driven intensification of the hydrologic cycle. Recent studies have presented evidence of rising lake level variability and changing water balance components (i.e., overlake precipitation, overlake evaporation, and basin runoff), however a full characterization of trends in variability is needed. Here, we build on previous analyses by quantitatively answering the question: are trends in hydrologic interannual variability over the Great Lakes over recent decades – both lake levels and individual hydrologic components – statistically robust, or simply the result of random chance? Using two non-parametric trend tests, we find that interannual variability of lake levels is significantly increasing in Lakes Superior, Michigan-Huron, and Erie, while decreasing in well-regulated Lake Ontario. We also find robust increasing variability in overlake precipitation, overlake evaporation, and basin runoff for the vast majority of lakes. These results suggest that critical work must follow to both attribute causes of detected trends and to determine if trends will continue increasing in the future with continued anthropogenic climate change. 1. IntroductionRecent extraordinary shifts in Great Lakes water levels have prompted questions about potential changes in year-over-year lake level variability. Changes in the variability of Great Lake levels, namely, how quickly lake levels fluctuate between higher and lower water levels, can have dramatic environmental and societal impacts. Examples include shifts in shoreline erosion patterns (Gronewold and Stow, 2014; Davidson-Arnott, 2016), shipping costs (Millerd, 2010; Lindeberg and Albercook, 2000; Wang et al., 2012), tourism and recreation (Wall, 1998; Hartmann, 1990), and risks to critical infrastructure like water resource management (de Loe and Kreutzwiser, 2000), hydropower (Meyer et al., 2017), and toxic waste facilities (Environmental Law and Policy Center, 2022). Researchers and the public alike have thus been captivated by the rapid transition of Great Lake levels between record low and high lake levels and the resultant impacts (e.g., Gronewold et al., 2021; Egan, 2021). This interest is further motivated by the observed and projected intensification of the hydrologic cycle due to anthropogenic climate change (IPCC, 2021; Seager, 2014). Within this context, Gronewold et al. (2021) presented evidence of rising lake level variability and described the situation caused by this hydrologic cycle intensification as a “continental-scale hydrological tug-of-war” between changing water balance components.Lake levels of large lakes are dominated by three net basin supply (NBS) components: overlake precipitation, overlake evaporation, and basin runoff, where the collective balance of these three components largely determine Great Lakes levels (Δlake storage = poverlake + rbasin - eoverlake) (Gronewold et al., 2021). Note that we define runoff here as the amount of water entering the lake from all incoming river systems in a respective Great Lakes basin, excepting flow from any upstream lakes. These components are all expected to change with the amplification of anthropogenic climate change and trends in these components have already been well observed. For instance, Javed et al. (2019) find increasing evaporation, spatially mixed results on precipitation, and no change in runoff, over Lakes Michigan and Huron. Harp and Horton (2022) characterize an increase in wet day precipitation intensity of ~5% over the U.S.-portion of the Great Lakes basin from 1951 to the present. Looking forward, Mailhot et al. (2019) found increases in net basin supply components with an intensifying annual cycle, but claimed “no long-term changes can be confidently estimated for lake levels.” Kayastha et al. (2022) used a regionally downscaled model to project future Great Lake levels and found a rise in both water levels and net basin supply components, particularly overlake precipitation and runoff. The climate change-driven increase in Great Lake levels was similarly projected by Van De Weghe et al. (2022). These findings differ with earlier work by Hayhoe et al. (2010) which projected falling Great Lakes levels based on increasing evaporation rates with increasing regional temperatures. Examining individual hydrologic components, Wang et al. (2018) project a 16% increase in lake evaporation by the end of the 21st century in a high greenhouse gas emissions scenario (RCP8.5). However, despite examination of trends of lake levels, little attention has been given to statistically characterizing observed trends in variability for either Great Lakes levels or their net basin supply components. Here, we address this knowledge gap by providing a statistically rigorous assessment of changes in interannual variability over the past five decades.

The characterization of changes over the full distribution of precipitation intensities remains an overlooked and underexplored subject, despite their critical importance to hazard assessments and water resource management. Here, we aggregate daily in situ Global Historical Climatology Network precipitation observations within seventeen internally consistent domains in the United States for two time periods (1951-1980 and 1991-2020). We find statistically significant changes in wet day precipitation distributions in all domains – changes primarily driven by a shift from lower to higher wet day intensities. Patterns of robust change are geographically consistent, with increases in the mean (4.5-5.7%) and standard deviation (4.4-8.7%) of wet day intensity in the eastern U.S., but mixed signals in the western U.S. Beyond their critical importance to the aforementioned impact assessments, these observational results can also inform climate model performance evaluations.