There are large uncertainties in our future projections of climate change at the regional scale, with spatial variabilities not resolved adequately by coarse-grained Earth System Models (ESMs). In this study, we use pseudo global warming simulations driven by end of the century upper end RCP (Representative Concentration Pathway) 8.5 projections from 11 state-of-the-art ESMs to examine changes in summer heat stress extremes using physiologically relevant heat stress metrics (heat index and wet bulb globe temperature) over the Great Lakes Region (GLR). These simulations, generated from a cloud-resolving model, are at a fine spatiotemporal resolution to detect heterogeneities relevant for human heat exposure. These downscaled climate projections are combined with gridded future population estimates to isolate population versus warming contributions to population-adjusted heat stress in this region. Our results show that a significant portion of summer will be dominated by critical outdoor heat stress levels within GLR for this scenario. Additionally, regions with higher heat stress generally have disproportionately higher population densities. Humidity change generates positive feedback on future heat stress, generally amplifying heat stress (by 24.2% to 79.5%) compared to changing air temperature alone, with the degree of control of humidity depending on the heat stress metric used. The uncertainty of the results for future heat stress are quantified based on multiple ESMs and heat stress metrics used in this study. Overall, our study shows the importance of dynamically resolving heat stress at population-relevant scales to get more accurate estimates of future heat risk in the region.

This study develops a surrogate-based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near-surface air temperature (T2m). Average physics uncertainties are determined to be 1.5°C for LST and T2m over land, and 1.9°C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations are the dominant sources of uncertainty for both LST and T2m, and there is a substantial atmosphere-lake physics interaction component. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model’s surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model. Last, we show that the deduced physics uncertainty of T2m is statistically smaller than a regional warming perturbation exceeding 0.5°C.

To understand the future summer precipitation changes over the Great Lakes Region (GLR), we perform an ensemble of regional climate simulations through the Pseudo-Global Warming (PGW) approach. We found that different types of convective precipitation respond to the PGW signal differently. Isolated deep convection (IDC), which is usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), which are usually concentrated upstream of the GLR, shows a shift to the downstream region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to be increased in almost the entire studied domain, providing a potential environment more (less) favorable for stronger (weaker) convection systems. Meanwhile, changes in lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, underscoring the significance of these thermodynamic factors in controlling precipitation over the domain. Results show that decreased LCL and LCF over places where convective precipitation is increased, is mainly contributed by the atmospheric moisture increase. In response to the prescribed warming perturbation, MCSs show more frequent occurrences downstream, while localized IDCs show more intense rain rate, longer duration, and larger rainfall area.

Radiative skin temperature is often used to examine heat exposure in multi-city studies and for informing urban heat management efforts since urban air temperature is rarely measured at the appropriate scales. Cities also have lower relative humidity, which is not traditionally accounted for in large-scale observational urban heat risk assessments. Here using crowdsourced measurements from over 40,000 weather stations in ≈600 urban clusters in Europe, we show the moderating effect of this urbanization-induced humidity reduction on heat stress during the 2019 heatwave. We demonstrate that daytime differences in heat index between urban clusters and their surroundings are weak and associations of this urban-rural difference with background climate, generally examined from the skin temperature perspective, is diminished due to moisture feedback. We also examine the spatial variability of skin temperature, air temperature, and heat indices within these clusters, relevant for detecting hotspots and potential disparities in heat exposure, and find that skin temperature is a poor proxy for the intra-urban distribution of heat stress. Finally, urban vegetation shows much weaker (~1/6th as strong) associations with heat stress than with skin temperature, which has broad implications for optimizing urban heat mitigation strategies. Our results are valid for both operational metrics of heat stress (such as apparent temperature and Humidex) and for various empirical heat indices from epidemiological studies. This study provide large-scale empirical evidence that skin temperature, used due to the lack of better alternatives, is weakly suitable for informing heat mitigation strategies within and across cities, necessitating more urban meteorological observations.

In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. The testbed is applied to two models: the regionally-refined Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) at horizontal resolutions ranging from 6.5 to 1.625 km and the Weather Research and Forecasting (WRF) model with 4 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions, initialization time, and model configurations, with initial conditions from the Rapid Refresh (RAP) producing the best simulation. Significant improvement is identified in the SCREAM simulations as horizontal grid spacing is refined. While a propagation delay of approximately 2 hours is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF hardly produces surface wind over 25 m/s, and the derecho wind gust in WRF is 42-46% lower than in SCREAM. Moreover, WRF has a lower bias in simulating cold clouds but overestimates the precipitation intensity. Both models well reproduce the observed outgoing longwave radiation spatial patterns (Pearson correlation > 0.88) while they simulate larger areas of composite radar reflectivity > 40 dBZ by up to 4 times and underestimate the precipitating area by ~ 70\% in WRF and 47\% in SCREAM compared to observations.

This study investigates the impacts of wildfire aerosols (primary organic carbon, black carbon and sulfate) on the Northern hemispheric boreal winter climate. We found that wildfire aerosols emitted from equatorial Africa result in two mid-high latitude Rossby wave trains. One is from subtropical Atlantic propagating northward across Europe to Siberia, and the other one propagates eastward from Mid-East across Asia to Northwest Pacific. The maximum positive height anomaly locates in Europe, concurrent with a greater-than-2K surface warming. These Rossby wave trains are excited by the atmospheric heating in equatorial Africa and propagate into extratropics with the help of the westerly jet. Through the heat budget analysis, the source of the Rossby wave is primarily due to the solar absorption of black carbon in Africa. The present study emphasize that aerosols especial the absorbing aerosols would have profound thermo-dynamic effects on remote regions and need more attentions.