Precipitation in the Great Lakes region has a distinct seasonal cycle that peaks in early summer, followed by a decline in August and a secondary peak in September. This seasonality is often not captured by models, which necessitates understanding of the driving mechanisms to ascertain the model biases. This study analyzes the atmospheric moisture budget using reanalysis datasets to assess the role of regional evapotranspiration and moisture influx from remote origins in defining the precipitation seasonality, and to understand how the Great Lakes modulate spatial patterns and magnitudes of these components. Specifically, the land-water thermal contrast yields large seasonal variations in the evaporative fluxes and creates distinctive localized spatial patterns of moisture flux divergence. We find considerable month-to-month variations in both evapotranspiration and the net moisture transport through the boundaries, where they play a cooperative (contrasting) role in amplifying (dampening) the moisture content available for precipitation and total precipitable water. Our seasonal analysis suggests that the misrepresentation of the budget quantities in models, for example in simulation of moisture transport processes and parameterization schemes, can result in an anomalous precipitation behavior and, in some cases, violation of the atmospheric moisture mass balance, resulting in large residual magnitudes. We also identify conspicuous differences in the representation of moisture budget components in the various reanalyses which can alter their representation of the regional hydroclimates.

Lakes are an integral part of the geosphere, but they are challenging to represent in Earth system models which either exclude lakes or prescribe properties without simulating lake dynamics. In ECMWF Interim reanalysis (ERA-Interim), lakes are represented by prescribing lake surface water temperatures (LSWT) from external data sources, while the newer generation ERA5 introduces the FLake parameterization scheme to the modelling system with different LSWT assimilation data sources. This study assesses the performance of these two reanalyses over three regions with the largest lakes in the world (Laurentian Great Lakes, African Great Lakes, and Lake Baikal) to understand the effects of their simulation differences on hydrometeorological variables. We find that differences in lake representation alter the associated hydrological and atmospheric processes and can affect regional hydroclimatic assessments. There are prominent differences in LSWT between the two datasets which influence the simulation of lake-effect snowstorms in the Laurentian winters and lake-land breeze circulation patterns in the African region. Generally, ERA5 has warmer LSWT in all three regions for most months (by 2-12 K) and its evaporation rates are up to twice the magnitudes in ERA-Interim. In the Laurentian lakes, ERA5 has strong biases in LSWT and evaporation magnitudes. Over Lake Baikal and the African Great Lakes, ERA5 LSWT magnitudes are closer to satellite-based datasets, albeit with warm bias (1-4 K), while ERA-Interim underestimates the magnitudes. ERA5 also simulates intense precipitation hotspots in lake proximity that are not visible in ERA-Interim and other observation-based datasets. Despite these limitations, ERA5 improves the simulation of lake-land circulation patterns across the African Great Lakes.

The Indus River basin is highly vulnerable to water scarcity due to increasing population, unsustainable management practices, and climate change. Yet the regional hydroclimate and precipitation dynamics remain poorly understood. Using running trend and spectral analysis with multiple gauge-based, remote sensing, and reanalysis precipitation datasets, this study analyzes precipitation temporal variability, its subregional variations, and the main seasonal drivers, particularly the South Asian monsoon. The results uncover remarkable alternation of long-term positive and negative interdecadal precipitation trends in the basin over the past half century. These trends have led to substantial changes in water input over the region at the time scales comparable to climate assessment periods (30 years), and therefore this high intrinsic variability must be accounted for in climate change adaptation studies. This study also reconstructs onset and withdrawal dates of the South Asian monsoon that exhibit interdecadal variability, but their dominant modes differ from that of annual precipitation. The findings hypothesize that higher-frequency variability in El Niño–Southern Oscillation is likely to have a pronounced impact on monsoon onset and duration in the studied region.

This study evaluates the historical climatology and future changes of the atmospheric water cycle for the Laurentian Great Lakes region using 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. While the models have unique seasonal characteristics in the historical (1981 – 2010) simulations, common patterns emerge by the mid-century SSP2-4.5 scenario (2041 – 2070), including a prevalent shift in the precipitation seasonal cycle with summer drying and wetter winter-spring months, and a ubiquitous increase in the magnitudes of convective precipitation, evapotranspiration, and moisture inflow into the region. The seasonal cycle of moisture flux convergence is amplified (i.e., the magnitude of winter convergence and summer divergence increases), which is the primary driver of future total precipitation changes. Precipitation recycling ratio is also projected to decline in summer and increase in winter by the mid-century, signifying a larger contribution of the regional moisture (via evapotranspiration) to total precipitation in the colder months. Many models (6/15) do not include representation of the Great Lakes, while others (4/15) have major inconsistencies in how the lakes are simulated both in terms of spatial representation and treatment of lake processes. In models with some lake presence, contribution of lake grid cells to the regional evapotranspiration magnitude can be more than 50% in winter. In future, winter months have a larger increase in evaporation over water surfaces than the surrounding land, which corroborates past findings of sensitivity of deep lakes to climate warming and highlights the importance of lake representation in these models for reliable regional hydroclimatic assessments.

Despite the fact that the Great Lakes contain roughly 20% of the world's surface freshwater, there is a relatively limited body of recent work in peer reviewed literature that addresses recent trends in lake levels. This work is largely coming from a handful of authors who are most well-versed in the complexities of monitoring and modeling in a basin that spans an international border and contains vast areas of surface water connected by both natural and managed connecting channel flows. At the same time, the recent dramatic changes from record low water levels in the early 2010's to record high water levels across the Great Lakes in 2019 and 2020 have brought significant attention to the hydroclimatic conditions in the basin, underscoring the need to bring new approaches and diverse perspectives (including from outside the basin) to address hydroclimate research challenges in the Great Lakes. Significant effort has led to advancements in data and model coordination among U.S. and Canadian federal agencies throughout the decades, and at the same time research from the broader community has led to higher resolution gridded data products. In this paper, we aim to present the current state of data and models for use in hydrological simulation with the objective of providing a guide to navigating the waters of Great Lakes hydroclimate data. We focus on data for use in modeling water levels, but we expect the information to be more broadly applicable to other hydroclimate research. We approach this by including perspectives from both the Great Lakes water management community and the broader earth science community.