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The Hurricane Weather Research and Forecasting Model (HWRF) was the flagship hurricane model at NOAA's National Centers for Environmental Prediction for 16 years and a state-of-the-art tool for tropical cyclone (TC) intensity prediction at the National Weather Service and across the globe. HWRF was a joint development between NOAA research and operations, specifically the Environmental Modeling Center and the Atlantic Oceanographic and Meteorological Laboratory. Significant support also came from the National Hurricane Center, Developmental Testbed Center, University Corporation for Atmospheric Research, universities, cooperative institutes, and the TC community. In the North Atlantic basin, where most improvement efforts focused, HWRF intensity forecast errors decreased by 45%-50% at many lead times between 2007 and 2022. These large improvements resulted from increases in horizontal and vertical resolution, as well as advances in model physics and data assimilation. HWRF intensity forecasts performed particularly well over the Gulf of Mexico in recent years, providing useful guidance for a large number of impactful landfalling hurricanes. Such advances were made possible not only by significant gains in computing but also through substantial investment from the Hurricane Forecast Improvement Program. SIGNIFICANCE STATEMENT: HWRF is considered one of the most important and successful ocean-coupled, regional numerical weather prediction models. This work documents HWRF forecast performance for TCs in the North Atlantic since its operational inception (2007-22). Track, intensity, and storm size (wind radii) forecasts all showed significant error reductions and skill improvements, including 45%-50% lower intensity errors. HWRF intensity forecasts showed marked improvement for rapid intensification events, especially in the Gulf of Mexico, where numerous impactful TCs made landfall throughout HWRF's lifetime. HWRF's impressive performance led to its expanded use as guidance for official TC forecasts and as a research tool across the TC community. These successes paved the way for NOAA's next-generation hurricane model, the Hurricane Analysis and Forecast System. KEYWORDS: Extreme events; Hurricanes/ typhoons; Tropical cyclones; Short-range prediction; Model evaluation/ performance; Numerical weather prediction/ forecasting, 1. Introduction (the rise of dynamical hurricane models at NOAA) Tropical cyclone (TC) forecast errors have markedly decreased over the past two decades, largely due to improved numerical weather prediction [...]

Gender conflict, which is emerging as a serious concern in Korean society, is also a subject of discourse in the field of education. A vast majority of university students are affected by economic downturn and are required to compete in an uncertain situation. This study proposes an educational model from the perspective of understanding the younger generation, which is struggling in uncertain situations, rather than treating gender conflict merely as hatred between individual women and men. This paper also proposes an educational environment wherein students feel encouraged to deal with gender conflicts by understanding their liminal spaces and crossing borders for gender equity.

The COVID-19 pandemic has had a huge impact on every facet of life around the world. For many, the world has become a place of doubt and uncertainty as people struggle to cope with the changes coming in the wake of COVID-19 and seek to determine how best to respond. With ecological, economic, and ideological crises occurring alongside COVID-19, this study proposes religious education that emphasizes the value of life, promotes equality, and fosters global interconnectedness. This religious education provides an open, equal, and interconnected environment where learners can understand, discuss, and confront global problems for the common future.

Coupling a three-dimensional ocean circulation model to an atmospheric model can significantly improve forecasting of tropical cyclones (TCs). This is particularly true of forecasts for TC intensity (maximum sustained surface wind and minimum central pressure), but also for structure (e.g., surface wind-field sizes). This study seeks to explore the physical mechanisms by which a dynamic ocean influences TC evolution, using an operational TC model. The authors evaluated impacts of ocean-coupling on TC intensity and structure forecasts from NOAA's Hurricane Analysis and Forecast System v1.0 B (HFSB), which became operational at the NOAA National Weather Service in 2023. The study compared existing HFSB coupled simulations with simulations using an identical model configuration in which the dynamic ocean coupling was replaced by a simple diurnally varying sea surface temperature model. The authors analyzed TCs of interest from the 2020-2022 Atlantic hurricane seasons, selecting forecast cycles with small coupled track-forecast errors for detailed analysis. The results show the link between the dynamic, coupled ocean response to TCs and coincident TC structural changes directly related to changing intensity and surface wind-field size. These results show the importance of coupling in forecasting slower-moving TCs and those with larger surface wind fields. However, there are unexpected instances where coupling impacts the nearTC atmospheric environment (e.g., mid-level moisture intrusion), ultimately affecting intensity forecasts. These results suggest that, even for more rapidly moving and smaller TCs, the influence of the ocean response to the wind field in the near-TC atmospheric environment is important for TC forecasting. The authors also examined cases where coupling degrades forecast performance. Statistical comparisons of coupled versus uncoupled HFSB further show an interesting tendency: high biases in peak surface winds for the uncoupled forecasts contrast with corresponding low biases, contrary to expectations, in coupled forecasts; the coupled forecasts also show a significant negative bias in the radii of 34 kt winds relative to National Hurricane Center best track estimates. By contrast, coupled forecasts show very small bias in minimum central pressure compared with a strong negative bias in uncoupled. Possible explanations for these discrepancies are discussed. The ultimate goal of this work will be to enable better evaluation and forecast improvement of TC models in future work. [ABSTRACT FROM AUTHOR]

The first operational version of the coupled Hurricane Analysis and Forecast System (HAFSv1) launched in 2023 consists of the HYbrid Coordinate Ocean Model (HYCOM) and finite-volume cubed-sphere (FV3) dynamic atmosphere model. This system is a product of efforts involving improvements and updates over a 4-year period (2019-2022) through extensive collaborations between the Environmental Modeling Center at the US National Centers for Environmental Prediction (NCEP) and NOAA Atlantic Oceanography and Meteorology Laboratory. To provide two sets of numerical guidance, the initial operational capability of HAFSv1 was configured to two systems -HFSA and HFSB. In this study, we present in-depth analysis of the forecast skills of the upper ocean that was co-evolved by the HFSA and HFSB. We chose hurricane Laura (2020) as an example to demonstrate the interactions between the storm and oceanic mesoscale features. Comparisons performed with the available in situ observations from gliders as well as Argos and National Data Buoy Center moorings show that the HYCOM simulations have better agreement for weak winds than high winds (greater than Category 2). The skill metrics indicate that the model sea-surface temperature (SST) and mixed layer depth (MLD) have a relatively low correlation. The SST, MLD, mixed layer temperature (MLT), and ocean heat content (OHC) are negatively biased. For high winds, SST and MLT are more negative, while MLD is closer to the observations with improvements of about 8%-19%. The OHC discrepancy is proportional to predicted wind intensity. Contrarily, the mixed layer salinity (MLS) uncertainties are smaller and positive for higher winds, probably owing to the higher MLD. The less-negative bias of MLD for high winds implies that the wind-force mixing is less effective owing to the higher MLD and high buoyancy stability (approx. 1.5-1.7 times) than the observations. The heat budget analysis suggests that the maximum heat loss by hurricane Laura was 0(< 3°C per day). The main contributor here is advection, followed by entrainment, which act against or with each other depending on the storm quadrant. We also found relatively large unaccountable heat residuals for the in-storm period, and the residuals notably led the heat tendency, meaning that further improvements of the subscale simulations are warranted. In summary, HYCOM simulations showed no systematic differences forced by either HFSA or HFSB. [ABSTRACT FROM AUTHOR]

There is much interest in the use of mesenchymal stem cells/marrow stromal cells (MSC) to treat neurodegenerative disorders, in particular those that are fatal and difficult to treat, such as Huntington's disease. MSC present a promising tool for cell therapy and are currently being tested in FDA-approved phase I-III clinical trials for many disorders. In preclinical studies of neurodegenerative disorders, MSC have demonstrated efficacy, when used as delivery vehicles for neural growth factors. A number of investigators have examined the potential benefits of innate MSC-secreted trophic support and augmented growth factors to support injured neurons. These include overexpression of brain-derived neurotrophic factor and glial-derived neurotrophic factor, using genetically engineered MSC as a vehicle to deliver the cytokines directly into the microenvironment. Proposed regenerative approaches to neurological diseases using MSC include cell therapies in which cells are delivered via intracerebral or intrathecal injection. Upon transplantation, MSC in the brain promote endogenous neuronal growth, encourage synaptic connection from damaged neurons, decrease apoptosis, reduce levels of free radicals, and regulate inflammation. These abilities are primarily modulated through paracrine actions. Clinical trials for MSC injection into the central nervous system to treat amyotrophic lateral sclerosis, traumatic brain injury, and stroke are currently ongoing. The current data in support of applying MSC-based cellular therapies to the treatment of Huntington's disease is discussed.