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Many climate models exhibit a dry and warm bias over the central United States during the summer months, including the Energy Exascale Earth System Model (E3SM) and its Multiscale Modeling Framework (MMF) configuration. Understanding the causes of this bias is important to shine a light on this common model error and reduce the uncertainty in future projections. In this study, we use E3SMv2 and E3SM-MMF to assess how parameterized and resolved convection affect temperature and precipitation biases over the Southern Great Plains site of the Atmospheric Radiation Measurement program. Both configurations overestimate near-surface temperature and underestimate precipitation at the ARM SGP site. The bias is associated with a lack of low-level clouds during days without precipitation and too much incoming solar radiation causing the surface to warm. Low-level cloud fraction in E3SM-MMF during the nonprecipitating days is lower in comparison to E3SMv2 and observation, consistent with the larger warm bias. We also find that the underestimated precipitation can be characterized as "too frequent, too weak" in E3SMv2 and "too rare, too intense" in E3SM-MMF. These deficiencies conspire to sustain the warm and dry bias over the central United States. [ABSTRACT FROM AUTHOR]

Climate simulations with more accurate process-level representation at finer resolutions (<100 km) are a pressing need in order to provide more detailed actionable information to policy makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building and running high-resolution (HR, here 0.25 ∘ average grid spacing at the Equator) models (HRMs). A more affordable path to HRMs is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low resolution (LR, 1 ∘). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces the precipitation metrics of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behavior of physical parameterizations, especially for variables influencing sub-grid-scale physical processes. RRMs can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a test bed and as such represents an efficient and more robust physics test bed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective test bed for HRM development. [ABSTRACT FROM AUTHOR]

Climate simulation with more accurate process-level representation at finer resolutions is a pressing need in order to provide actionable information to policy-makers regarding extreme events in a changing climate. Computational limitation is a major obstacle for building, and running high-resolution (HR, here 0.25° average grid spacing at the equator) models (HRM). A more affordable path to HRM is to use a global regionally refined model (RRM), which only simulates a portion of the globe at HR while the remaining is at low-resolution (LR, 1°). In this study, we compare the Energy Exascale Earth System Model (E3SM) atmosphere model version 1 (EAMv1) RRM with the HR mesh over the contiguous United States (CONUS) to its corresponding globally uniform LR and HR configurations, as well as to observations and reanalysis data. The RRM has a significantly reduced computational cost (roughly proportional to the HR mesh size) relative to the globally uniform HRM. Over the CONUS, we evaluate the simulation of important dynamical and physical quantities as well as various precipitation measures. Differences between the RRM and HRM over the HR region are predominantly small, demonstrating that the RRM reproduces both well- and poorly simulated behaviours of the HRM over the CONUS. Further analysis based on RRM simulations with the LR vs. HR model parameters reveals that RRM performance is greatly influenced by the different parameter choices used in the LR and HR EAMv1. This is a result of the poor scale-aware behaviour of physical parameterizations, especially for variables influencing sub-grid scale physical processes. RRM can serve as a useful framework to test physics schemes across a range of scales, leading to improved consistency in future E3SM versions. Applying nudging-to-observations techniques within the RRM framework also demonstrates significant advantages over a free-running configuration for use as a testbed, and as such represents an efficient and more robust physics testbed capability. Our results provide additional confirmatory evidence that the RRM is an efficient and effective approach for HRM development and hydrologic research. [ABSTRACT FROM AUTHOR]

Examines the effects of elective cesarean delivery policy on the cases of brachial palsy and cesarean delivery rate in fetal macrosomia in the United States. Percentage of infants with macrosomia infection; Number of infants delivered with cesarean procedures; Account on the percentage of infants with brachial plexus injury.

No Abstract available. [ABSTRACT FROM AUTHOR]