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In this study, we calibrate a regional climate model's (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM's ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement: This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model's reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately. [ABSTRACT FROM AUTHOR]

Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological datasets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded datasets over the conterminous United States. Compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5–2.5 day increase in mean wet spell length, 30% low bias in 20-yr return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation dataset is developed that omits the time adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new dataset is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. These changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate change applications across the CONUS. [ABSTRACT FROM AUTHOR]

Introduction: Naval Surface Forces provide care in austere environments with unique facility, personnel, and material limitations that can put the patient at risk without proper consideration of these circumstances. Tailored shipboard education currently exists but is greatly dependent on the time, preferences, expertise, and ability of a single teaching officer, allowing for significant variability in the level of training.Materials and Methods: One hundred and twenty-two individuals were trained in 19 topics presented over 12 months through the Naval Surface Forces Pacific Command Medical Readiness Division to all surface providers on Naval Base San Diego. Participants completed pre- and post-course assessments for each training session based on the objectives of the lesson, as well as reassessments and subjective course critiques every 3 months.Results: Fifteen of 19 courses showed more than 20% improvement, with a range of improvement from 21 to 67%, and an average of 30% (95% confidence interval: 26.1-33.8, p < 0.001). Short-term follow-up showed higher-than-baseline scores at 6-, 9-, and 12-month follow-up; these were significantly higher than nonattendees (p = 0.003, 0.05, 0.004, respectively). Students who reported being either very confident or very confident and comfortable with teaching the content increased from 40.6% before the course to 60.8% after the course. Pre- (p = 0.02) and post- (p = 0.01) course level of confidence was directly correlated to students' assessment of the courses' applicability, with increasing level of confidence correlating to a perceived increase in applicability of the material.Conclusion: This study demonstrates improvement in Naval surface provider knowledge and attitudes in a variety of subject areas after implementation of a novel curriculum tailored specifically to address the unique considerations for practice at sea. Material was beneficial to all trainees despite significant differences in training background. Confidence gained as a result of the course was directly correlated to perceived relevance of the material, but not to educational background. Future work could investigate the use of curriculum in deployed providers and incorporation into current training of the OPNAVINST 6400.1c, Appendix A. [ABSTRACT FROM AUTHOR]