A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By resolving the transient dynamics of convective storms in the tropics, global storm-resolving models remove the need to parameterize tropical deep convection, providing a fundamentally more sound representation of the climate system and a more natural link to commensurately high-resolution data from satellite-borne sensors. The models and some basic characteristics of their output are described in more detail, as is the availability and planned use of this output for future scientific study. Tropically and zonally averaged energy budgets, precipitable water distributions, and precipitation from the model ensemble are evaluated, as is their representation of tropical cyclones and the predictability of column water vapor, the latter being important for tropical weather.

Abstract. Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the NavierStokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmosphere Model version 4.1 (AM4.1), which builds on developments at GFDL over 2013-2018 for coupled carbon-chemistry-climate simulation as part of the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's AM4.0 development effort, which focused on physical and aerosol interactions and which is used as the atmospheric component of CM4.0, AM4.1 focuses on comprehensiveness of Earth system interactions. Key features of this model include doubled horizontal resolution of the atmosphere (~200 to~100 km) with revised dynamics and physics from GFDL's previous-generation AM3 atmospheric chemistry-climate model. AM4.1 features improved representation of atmospheric chemical composition, including aerosol and aerosol precursor emissions, key land-atmosphere interactions, comprehensive land-atmosphere-ocean cycling of dust and iron, and interactive ocean-atmosphere cycling of reactive nitrogen. AM4.1 provides vast improvements in fidelity over AM3, captures most of AM4.0's baseline simulations characteristics, and notably improves on AM4.0 in the representation of aerosols over the Southern Ocean, India, and China-even with its interactive chemistry representation-and in its manifestation of sudden stratospheric warmings in the coldest months. Distributions of reactive nitrogen and sulfur species, carbon monoxide, and ozone are all substantially improved over AM3. Fidelity concerns include degradation of upper atmosphere equatorial winds and of aerosols in some regions. Plain Language Summary GFDL has developed a coupled chemistry-climate Atmospheric Model (AM4.1) as part of its fourth-generation coupled model development activities. AM4.1 includes comprehensive atmospheric chemistry for representing ozone and aerosols and has been developed for use in chemistry and air quality applications, including advanced land-atmosphere-ocean coupling. With fidelity near to that of AM4.0, AM4.1 features vastly improved representation of climate mean patterns and variability from previous GFDL atmospheric chemistry-climate models.

We present the System for High-resolution prediction on Earth-to-Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short-to-medium-range and subseasonal-to-seasonal prediction, global-to-regional convective-scale hurricane and contiguous U.S. precipitation forecasts, and global cloud-resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3-based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13-km SHiELD demonstrates steadily improved large-scale prediction skill and precipitation prediction skill. SHiELD and the coarser-resolution S-SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden-Julian Oscillation. The global-to-regional nested configurations T-SHiELD (tropical Atlantic) and C-SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium-range prediction of convective storms. Plain Language Summary At many weather forecasting centers where computer weather models are run, different models are run for different applications. However, each separate model multiplies the effort needed to maintain and upgrade each model and makes it difficult to move improvements between models. We present a new "unified" weather modeling system, System for High-resolution prediction on Earth-to-Local Domains, able to be configured for a variety of applications. This system uses a powerful computer code, FV3, to compute the fluid motion of the atmosphere at any scale and also able to zoom in on areas of interest to better "see" severe storms or intense hurricanes. We show how we started from a quickly assembled model for testing FV3 and then gradually improved the representation of different atmospheric processes and expanded into new uses for the system, including short-range severe thunderstorm prediction, hurricane forecasting, and forecasts out to as long as 6 weeks. We address some of the challenges that we faced and discuss prospects for future model improvements. Since many of the parts of System for High-resolution prediction on Earth-to-Local Domains are used by models being developed by the National Weather Service for use by weather forecasters, the advances described here can be rapidly introduced into those models, eventually improving official forecasts. 1. Unified Modeling at GFDL As computing power increases, global atmosphere models are now capable of regul...

NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology.

It is increasingly recognized that vitamin D deficiency is associated with increased risks of metabolic disorders among overweight children. A recent study showed that vitamin D deficiency exacerbated inflammation in nonalcoholic fatty liver disease through activating toll-like receptor 4 in a high-fat diet (HFD) rat model. The present study aimed to further investigate the effects of vitamin D deficiency on HFD-induced insulin resistance and hepatic lipid accumulation. Male ICR mice (35 d old) were randomly assigned into 4 groups as follows. In control diet and vitamin D deficiency diet (VDD) groups, mice were fed with purified diets. In HFD and VDD+HFD groups, mice were fed with HFD. In VDD and VDD+HFD groups, vitamin D in feed was depleted. Feeding mice with vitamin D deficiency diet did not induce obesity, insulin resistance, and hepatic lipid accumulation. By contrary, vitamin D deficiency markedly alleviated HFD-induced overweight, hyperinsulinemia, and hepatic lipid accumulation. Moreover, vitamin D deficiency significantly attenuated HFD-induced up-regulation of hepatic peroxisome proliferator-activated receptor γ, which promoted hepatic lipid uptake and lipid droplet formation, and its target gene cluster of differentiation 36. In addition, vitamin D deficiency up-regulated carnitine palmitoyltrans 2, the key enzyme for fatty acid β-oxidation, and uncoupling protein 3, which separated oxidative phosphorylation from ATP production, in adipose tissue. These data suggest that vitamin D deficiency is not a direct risk factor for obesity, insulin resistance, and hepatic lipid accumulation. Vitamin D deficiency alleviates HFD-induced overweight, hyperinsulinemia, and hepatic lipid accumulation through promoting fatty acid β-oxidation and elevating energy expenditure in adipose tissue.

Accurate and stable numerical discretization of the equations for the nonhydrostatic atmosphere is required, for example, to resolve interactions between clouds and aerosols in the atmosphere. Here the authors present a modification of the hydrostatic control-volume approach for solving the nonhydrostatic Euler equations with a Lagrangian vertical coordinate. A scheme with low numerical diffusion is achieved by introducing a low Mach number approximate Riemann solver (LMARS) for atmospheric flows. LMARS is a flexible way to ensure stability for finite-volume numerical schemes in both Eulerian and vertical Lagrangian configurations. This new approach is validated on test cases using a 2D (x–z) configuration.

[1] Daily relative humidity anomaly records of 73 stations over China have been analyzed by the method of Detrended Fluctuation Analysis (DFA for short). It is obvious that the relative humidity fluctuations take different statistical behavior from other meteorological quantities and it is found their average scaling exponent is higher than that of the temperature fluctuations. When the scaling exponents obtained from the DFA is plotted versus the standard deviation of the relative humidity fluctuations, no obvious correlation or patch behavior can be found over different areas and climate regions. So the product of the scaling exponent and the standard deviation of the same record is proposed to form a new climate region classifying index.Citation: Chen, X., G. Lin, and Z. Fu (2007), Long-range correlations in daily relative humidity fluctuations: A new index to characterize the climate regions over China, Geophys. Res. Lett., 34, L07804,