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The Laurentian Great Lakes significantly influence the climate of the Midwest and Northeast United States, due to their vast thermal inertia, moisture source potential, and unique heat and moisture flux dynamics. This study presents a newly developed coupled lake-ice-atmosphere (CLIAv1) modeling system for the Great Lakes by coupling the National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) regional climate model (RCM) with the three-dimensional (3D) Finite Volume Community Ocean Model (FVCOM) and investigates the impact of coupled dynamics on simulating the Great Lakes' winter climate. By integrating 3D lake hydrodynamics, CLIAv1 addresses the limitations of traditional one-dimensional (1D) lake and demonstrates superior performance in reproducing observed LSTs, ice cover distribution, and the vertical thermal structure of the Great Lakes compared to the NU-WRF model coupled with the default 1D Lake Ice Snow and Sediment Simulator (LISSS). CLIAv1 also enhances simulation of over-lake atmospheric conditions, including air temperature, wind speed, and sensible and latent heat fluxes, underscoring the importance of resolving complex lake dynamics for reliable climate projections. More importantly, this study addresses the crucial question about what are the key processes influencing lake thermal structure and ice cover that are missed by 1D lake models but effectively captured by 3D lake models. Through process-oriented numerical experiments, we identify key 3D hydrodynamic processes – ice transport, heat advection, and shear production in turbulence – that explain the superiority of 3D lake models over 1D lake models, particularly in cold season performance and lake-atmosphere interactions. Properly resolving these processes using 3D hydrodynamic model is crucial for successfully simulating the lake-ice-atmosphere coupled Great Lakes winter system. This research underscores the necessity of incorporating 3D hydrodynamic models in RCMs to improve our predictive understanding of the Great Lakes' response to climate change. The findings advocate for a shift towards high-resolution, physics-based modeling approaches to ensure accurate future climate and limnological projections for large freshwater systems. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is altering ecological and human systems globally, including in United States (US) national parks, which conserve unique biodiversity and resources. Yet, the magnitude and spatial patterns of climate change across all the parks have been unknown. Here, in the first spatial analysis of historical and projected temperature and precipitation across all 417 US national parks, we show that climate change exposes the national park area more than the US as a whole. This occurs because extensive parts of the national park area are in the Arctic, at high elevations, or in the arid southwestern US. Between 1895 and 2010, mean annual temperature of the national park area increased 1.0 °C ± 0.2 °C century-1 (mean ± standard error), double the US rate. Temperature has increased most in Alaska and its extensive national parks. Annual precipitation of the national park area declined significantly on 12% of national park area, compared to 3% of the US. Higher temperatures due to climate change have coincided with low precipitation in the southwestern US, intensifying droughts in the region. Physical and ecological changes have been detected and attributed mainly to anthropogenic climate change in areas of significant temperature increases in US national parks. From 2000 to 2100, under the highest emissions scenario (representative concentration pathway [RCP] 8.5), park temperatures would increase 3 °C-9 °C, with climate velocities outpacing dispersal capabilities of many plant and animal species. Even under the scenario of reduced emissions (RCP2.6), temperature increases could exceed 2 °C for 58% of national park area, compared to 22% of the US. Nevertheless, greenhouse gas emissions reductions could reduce projected temperature increases in national parks by one-half to two-thirds.

The overall performance of the simulated seasonal precipitation response to local terrestrial forcings, namely vegetation abundance and soil moisture, in the Sahel among the Coupled Model Intercomparison Project Phase Five (CMIP5) Earth System Models (ESMs) is systematically investigated and compared with its observational counterpart using a multivariate statistical method. The observed seasonal precipitation response is evaluated against a large ensemble of observational, reanalysis, and satellite data sets to provide quantification of uncertainties. The behaviour of models with and without a Dynamic Global Vegetation Model (DGVM) component is also explored, along with the mechanisms responsible for terrestrial feedback on rainfall. In general, the CMIP5 models can reasonably capture the seasonal evolution of Sahel precipitation and soil moisture, albeit with wet biases during the pre‐monsoon period and dry biases during the peak monsoon period. The non‐DGVM ESMs simulate comparable leaf area indices (LAIs) with observations, while DGVM‐enabled ESMs simulate too much year‐round LAI. The variance of precipitation that is attributed to oceanic forcings in CMIP5 is comparable with observations; however, the variance of precipitation that is attributed to terrestrial forcings is smaller in CMIP5 models than observed, especially for non‐DGVM ESMs. CMIP5 models, especially those without DGVMs, undervalue precipitation's observed response strength to soil moisture anomalies. In both observations and CMIP5 models, none of the atmospheric variables show significant responses to direct vegetation forcing, except for the response in transpiration. Although vegetation has minimal direct effect on the atmospheric state, it can affect the atmosphere by modifying soil moisture and transpiration rate indirectly, which helps explain the more realistic simulation of rainfall in DGVM‐enabled ESMs than non‐DGVM ESMs. Coupling of an ESM to a DGVM is critical in generating reasonable land–atmosphere feedback and examining future ecological and climatic changes over the Sahel. [ABSTRACT FROM AUTHOR]