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Atmospheric resolved-scale air flow (dynamics) and sub-grid parameterizations (physics) are two essential components of a weather or climate model. These two independent components are coupled and advanced using the same time step, either parallel or sequentially split. However, traditionally dynamics and physics are engineered in isolation and developed independently in models. As a result, many parts of the physics run at a physically-inappropriate time frequency or with heat transfers that are inconsistent with the dynamics, leading to errors. In addition, physical parameterizations should contain dynamical and non-dynamical processes. We believe there are compelling reasons that dynamical processes, if resolved, should be taken care of by the dynamical core.Our study proposes a novel integrated dynamics-physics coupling framework (Zhou and Harris, 2022) within the GFDL (Geophysical Fluid Dynamics Laboratory) weather-to-seasonal prediction system SHiELD (System for High-resolution prediction on Earth-to-Local Domains; Harris et al., 2020) that promises to resolve the above issues. We will present our integrated coupling framework and the development of integrated physical parameterization for this framework in detail. The performance of forecast experiments using the modeling system SHiELD with this integrated coupling framework will be highlighted, focusing on large-scale circulation, cloud and precipitation, hurricane, and convective-storm predictions.

A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting their initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables.

The Tropical cyclone (TC) forecast skill of the eight global medium-range forecast models which are participating in the DIMOSIC (DIfferent Models, Same Initial Conditions) project is investigated in this study. Each model was used to generate 10-day forecasts from the same initial conditions provided by the European Centre for Medium-Range Weather Forecasts. There are a total of 123 initial dates spanning in one year from June 2018 to June 2019 with a 3-day interval. The TC track and intensity forecasts are evaluated against the best track dataset. TC-related precipitation and tropical cyclogenesis forecasts are also compared to explore the differences and similarities of TC forecasts across the models. This comparison of TC forecasts allows model developers in different centers to benchmark their model against other models, with the impact of the initial condition quality removed. The verifications reveal that most models show slow-moving and right-of-track biases in their TC track forecasts. Also, a common dry bias in TC-related precipitation indicates a general deficiency in TC intensity and convection in the models which should be related to insufficient model resolution. These findings provide important references for future model developments.

We investigate the sensitivity of hurricane intensity and structure to the horizontal tracer advection in the Geophysical Fluid Dynamics Laboratory (GFDL) Finite-Volume Cubed-Sphere Dynamical Core (FV3). We compare two schemes, a monotonic scheme and a less diffusive positive-definite scheme. The positive-definite scheme leads to significant improvement in the intensity prediction relative to the monotonic scheme in a suite of 5-day forecasts that mostly consist of rapidly intensifying hurricanes. Notable storm structural differences are present: the radius of maximum wind (RMW) is smaller and eyewall convection occurs farther inside the RMW when the positive-definite scheme is used. Moreover, we find that the horizontal tracer advection scheme affects the eyewall convection location by affecting the moisture distribution in the inner-core region. This study highlights the importance of dynamical core algorithms in hurricane intensity prediction.

Verification methods for convection-allowing models (CAMs) should consider the finescale spatial and temporal detail provided by CAMs, and including both neighborhood and object-based methods can account for displaced features that may still provide useful information. This work explores both contingency table–based verification techniques and object-based verification techniques as they relate to forecasts of severe convection. Two key fields in severe weather forecasting are investigated: updraft helicity (UH) and simulated composite reflectivity. UH is used to generate severe weather probabilities called surrogate severe fields, which have two tunable parameters: the UH threshold and the smoothing level. Probabilities computed using the UH threshold and smoothing level that give the best area under the receiver operating curve result in very high probabilities, while optimizing the parameters based on the Brier score reliability component results in much lower probabilities. Subjective ratings from participants in the 2018 NOAA Hazardous Weather Testbed Spring Forecasting Experiment (SFE) provide a complementary evaluation source. This work compares the verification methodologies in the context of three CAMs using the Finite-Volume Cubed-Sphere Dynamical Core (FV3), which will be the foundation of the U.S. Unified Forecast System (UFS). Three agencies ran FV3-based CAMs during the five-week 2018 SFE. These FV3-based CAMs are verified alongside a current operational CAM, the High-Resolution Rapid Refresh version 3 (HRRRv3). The HRRR is planned to eventually use the FV3 dynamical core as part of the UFS; as such evaluations relative to current HRRR configurations are imperative to maintaining high forecast quality and informing future implementation decisions.

Motivated by the use of the GFDL microphysics scheme in the Finite-Volume Cubed-Sphere Dynamical Core Global Forecast System (FV3GFS), the all-sky radiance assimilation framework has been expanded to include precipitating hydrometeors. Adding precipitating hydrometeors allows the assimilation of precipitation-affected radiance in addition to cloudy radiance. In this upgraded all-sky framework, the five hydrometeors, including cloud liquid water, cloud ice, rain, snow, and graupel, are the new control variables, replacing the original cloud water control variable. The Community Radiative Transfer Model (CRTM) was interfaced with the newly added precipitating hydrometeors. Subgrid cloud variability was considered by using the average cloud overlap scheme. Multiple scattering radiative transfer was activated in the upgraded framework. Radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A) and the Advanced Technology Microwave Sounder (ATMS) over ocean were assimilated in all-sky approach. This new constructed all-sky framework shows neutral to positive impact on overall forecast skill. Improvement was found in 500-hPa geopotential height forecast in both Northern and Southern Hemispheres. Temperature forecast was also improved at 850 hPa in the Southern Hemisphere and the tropics.

Tropical ice clouds play an important role in the energy balance of the tropical atmosphere, yet their modeling has been a challenge and feedback from high clouds in climate models is very uncertain. The new generation of Global Storm Resolving Models (GSRM) is capable of resolving convective and mesoscale motions globally, and therefore promises to greatly advance our understanding of tropical clouds. This new generation of model also creates new opportunities for comparison with measurements since their horizontal resolution is comparable to that of active sensor measurements. Here we show the value of metrics evaluating cloud fraction, ice mixing ratio and longwave cloud radiative heating to validate tropical ice clouds simulated by Global Storm Resolving Models using A-Train ice cloud retrieval products. For this purpose, we use the X-SHiELD experimental Cloud Resolving Model, developed at NOAA/GFDL, and observations based on the 2C-ICE and DARDAR products, with the addition of the 2B-FLXHR-LIDAR radiative transfer algorithm for the validation of broadband fluxes. We show that, by aggregating model output and measurements in ice water path – pressure space, biases in the ice distribution can be revealed, whereby the position of the anvils is too low in the model. Such biases point to deficiencies in the microphysics of cloud ice, are likely shared by other models using similar microphysics packages, and have important consequences on thermal emission properties.

A new global model using the GFDL nonhydrostatic Finite-Volume Cubed-Sphere Dynamical Core (FV3) coupled to physical parameterizations from the National Centers for Environmental Prediction’s Global Forecast System (NCEP/GFS) was built at GFDL, named fvGFS. The modern dynamical core, FV3, has been selected for the National Oceanic and Atmospheric Administration’s Next Generation Global Prediction System (NGGPS) due to its accuracy, adaptability, and computational efficiency, which brings a great opportunity for the unification of weather and climate prediction systems. The performance of tropical cyclone (TC) forecasts in the 13-km fvGFS is evaluated globally based on 363 daily cases of 10-day forecasts in 2015. Track and intensity errors of TCs in fvGFS are compared to those in the operational GFS. The fvGFS outperforms the GFS in TC intensity prediction for all basins. For TC track prediction, the fvGFS forecasts are substantially better over the northern Atlantic basin and the northern Pacific Ocean than the GFS forecasts. An updated version of the fvGFS with the GFDL 6-category cloud microphysics scheme is also investigated based on the same 363 cases. With this upgraded microphysics scheme, fvGFS shows much improvement in TC intensity prediction over the operational GFS. Besides track and intensity forecasts, the performance of TC genesis forecast is also compared between the fvGFS and operational GFS. In addition to evaluating the hit/false alarm ratios, a novel method is developed to investigate the lengths of TC genesis lead times in the forecasts. Both versions of fvGFS show higher hit ratios, lower false alarm ratios, and longer genesis lead times than those of the GFS model in most of the TC basins.

The outputs of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic, Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project (CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total, there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden-Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.

Cloud dominates influence factors of atmospheric radiation, while aerosol-cloud interactions are of vital importance in its spatiotemporal distribution. In this study, a two-moment (mass and number) cloud microphysics scheme, which significantly improved the treatment of the coupled processes of aerosols and clouds, was incorporated into version 1.1 of the IAP/LASG global Finite-volume Atmospheric Model (FAMIL1.1). For illustrative purposes, the characteristics of the energy balance and cloud radiative forcing (CRF) in an AMIP-type simulation with prescribed aerosols were compared with those in observational/reanalysis data. Even within the constraints of the prescribed aerosol mass, the model simulated global mean energy balance at the top of the atmosphere (TOA) and at the Earth’s surface, as well as their seasonal variation, are in good agreement with the observational data. The maximum deviation terms lie in the surface downwelling longwave radiation and surface latent heat flux, which are 3.5 W m-2 (1%) and 3 W m-2 (3.5%), individually. The spatial correlations of the annual TOA net radiation flux and the net CRF between simulation and observation were around 0.97 and 0.90, respectively. A major weakness is that FAMIL1.1 predicts more liquid water content and less ice water content over most oceans. Detailed comparisons are presented for a number of regions, with a focus on the Asian monsoon region (AMR). The results indicate that FAMIL1.1 well reproduces the summer-winter contrast for both the geographical distribution of the longwave CRF and shortwave CRF over the AMR. Finally, the model bias and possible solutions, as well as further works to develop FAMIL1.1 are discussed.

We present a new global‐to‐regional model, cfvGFS, able to explicitly (without parameterization) represent convection over part of the Earth. This model couples the Geophysical Fluid Dynamics Laboratory Finite‐Volume Cubed‐Sphere Dynamical Core (FV3) to the Global Forecast System physics and initial conditions, augmented with a six‐category microphysics and a modified planetary boundary layer scheme. We examine the characteristics of cfvGFS on a 3‐km continental U. S. domain nested within a 13‐km global model. The nested cfvGFS still has good hemispheric skill comparable to or better than the operational Global Forecast System, while supercell thunderstorms, squall lines, and derechos are explicitly represented over the refined region. In particular, cfvGFS has excellent representations of fine‐scale updraft helicity fields, an important proxy for severe weather forecasting. Precipitation biases are found to be smaller than in uniform‐resolution global models and competitive with operational regional models; the 3‐km domain also improves upon the global models in 2‐m temperature and humidity skill. We discuss further development of cfvGFS and the prospects for a unified global‐to‐regional prediction system.

Tropical anvil clouds are an important player in Earth's climate and climate sensitivity, but simulations of anvil clouds are uncertain. Here we pinpoint one source of uncertainty by demonstrating ...

Recent progress in computing and model development has initiated the era of global storm-resolving modeling and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results show that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency to accurately simulate TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models are able to open a new chapter in TC prediction, but they need to be improved to unleash their full potential.

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.

Persistent open ridges and blocking highs (maxima) of 500-hPa geopotential height (Z500; PMZ) adjacent in space and time are identified and tracked as one event with a Lagrangian objective approach to derive their climatological statistics with some dynamical reasoning. A PMZ starts with a core that contains a local eddy maximum of Z500 and its neighboring grid points whose eddy values decrease radially to about 20 geopotential meters (GPMs) smaller than the maximum. It connects two consecutive cores that share at least one grid point and are within 10° of longitude of each other using an intensity-weighted location. The PMZ ends at the core without a successor. On each day, the PMZ impacts an area of grid points contiguous to the core and with eddy values decreasing radially to 100 GPMs. The PMZs identified and tracked consist of persistent ridges, omega blockings and blocked anticyclones either connected or as individual events. For example, the PMZ during 2–13 August 2003 corresponds to persistent open ridges that caused the extreme heatwave in Western Europe. Climatological statistics based on the PMZs longer than 3 days generally agree with those of blockings. In the Northern Hemisphere, more PMZs occur in DJF season than in JJA and their duration both exhibit a log-linear distribution. Because more omega-shape blocking highs and open ridges are counted, the PMZs occur more frequently over Northeast Pacific than over Atlantic-Europe during cool seasons. Similar results are obtained using the 200-hPa geopotential height (in place of Z500), indicating the quasi-barotropic nature of the PMZ.

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.

Annual incident solar radiation at the top of atmosphere should be independent of longitudes. However, in many Coupled Model Intercomparison Project phase 5 (CMIP5) models, we find that the incident radiation exhibited zonal oscillations, with up to 30 W/m2 of spurious variations. This feature can affect the interpretation of regional climate and diurnal variation of CMIP5 results. This oscillation is also found in the Community Earth System Model. We show that this feature is caused by temporal sampling errors in the calculation of the solar zenith angle. The sampling error can cause zonal oscillations of surface clear-sky net shortwave radiation of about 3 W/m2 when an hourly radiation time step is used and 24 W/m2 when a 3 h radiation time step is used.

This paper documents version 1 of the Finite-volume Atmospheric Model of the IAP/LASG (FAMIL1), which has a flexible horizontal resolution up to a quarter of 1°. The model, currently running on the “Tianhe 1A” supercomputer, is the atmospheric component of the third-generation Flexible Global Ocean-Atmosphere-Land climate System model (FGOALS3) which will participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition to describing the dynamical core and physical parameterizations of FAMIL1, this paper describes the simulated characteristics of energy and water balances and compares them with observational/reanalysis data. The comparisons indicate that the model simulates well the seasonal and geographical distributions of radiative fluxes at the top of the atmosphere and at the surface, as well as the surface latent and sensible heat fluxes. A major weakness in the energy balance is identified in the regions where extensive and persistent marine stratocumulus is present. Analysis of the global water balance also indicates realistic seasonal and geographical distributions with the global annual mean of evaporation minus precipitation being approximately 10−5 mm d−1. We also examine the connections between the global energy and water balance and discuss the possible link between the two within the context of the findings from the reanalysis data. Finally, the model biases as well as possible solutions are discussed.

The Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2) was used to simulate realistic climates and to study anthropogenic influences on climate change. Specifically, the FGOALS-s2 was integrated with Coupled Model Intercomparison Project Phase 5 (CMIP5) to conduct coordinated experiments that will provide valuable scientific information to climate research communities. The performances of FGOALS-s2 were assessed in simulating major climate phenomena, and documented both the strengths and weaknesses of the model. The results indicate that FGOALS-s2 successfully overcomes climate drift, and realistically models global and regional climate characteristics, including SST, precipitation, and atmospheric circulation. In particular, the model accurately captures annual and semi-annual SST cycles in the equatorial Pacific Ocean, and the main characteristic features of the Asian summer monsoon, which include a low-level southwestern jet and five monsoon rainfall centers. The simulated climate variability was further examined in terms of teleconnections, leading modes of global SST (namely, ENSO), Pacific Decadal Oscillations (PDO), and changes in 19th–20th century climate. The analysis demonstrates that FGOALS-s2 realistically simulates extra-tropical teleconnection patterns of large-scale climate, and irregular ENSO periods. The model gives fairly reasonable reconstructions of spatial patterns of PDO and global monsoon changes in the 20th century. However, because the indirect effects of aerosols are not included in the model, the simulated global temperature change during the period 1850–2005 is greater than the observed warming, by 0.6°C. Some other shortcomings of the model are also noted.

Data analysis based on station observations reveals that many meteorological variables averaged over the Tibetan Plateau (TP) are closely correlated, and their trends during the past decades are well correlated with the rainfall trend of the Asian summer monsoon. However, such correlation does not necessarily imply causality. Further diagnosis confirms the existence of a weakening trend in TP thermal forcing, characterized by weakened surface sensible heat flux in spring and summer during the past decades. This weakening trend is associated with decreasing summer precipitation over northern South Asia and North China and increasing precipitation over northwestern China, South China, and Korea. An atmospheric general circulation model, the HadAM3, is employed to elucidate the causality between the weakening TP forcing and the change in the Asian summer monsoon rainfall. Results demonstrate that a weakening in surface sensible heating over the TP results in reduced summer precipitation in the plateau region and a reduction in the associated latent heat release in summer. These changes in turn result in the weakening of the near-surface cyclonic circulation surrounding the plateau and the subtropical anticyclone over the subtropical western North Pacific, similar to the results obtained from the idealized TP experiment in Part I of this study. The southerly that normally dominates East Asia, ranging from the South China Sea to North China, weakens, resulting in a weaker equilibrated Sverdrup balance between positive vorticity generation and latent heat release. Consequently, the convergence of water vapor transport is confined to South China, forming a unique anomaly pattern in monsoon rainfall, the so-called “south wet and north dry.” Because the weakening trend in TP thermal forcing is associated with global warming, the present results provide an effective means for assessing projections of regional climate over Asia in the context of global warming.

This chapter describes the framework of the global climate system model known as FGOALS-s2. FGOALS-s2 consists of the following components: SAMIL2 (atmosphere), LICOM2 (ocean), CSIM5 (sea ice), and CLM3 (land). These components are coupled together with the flux coupler from NCAR. FGOALS-s2 has been used to conduct the experiments for analysis studies in support of the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC AR5) and phase 5 of the Coupled Model Intercomparison Project (CMIP5). Here, the 500-year preindustrial control run was adopted to briefly investigate the stability of FGOALS-s2.

This chapter describes the model speed and model in/out (I/O) efficiency of the high-resolution atmospheric general circulation model the Finite-volume Atmospheric Model of IAP/LASG (FAMIL), investigated at the National Supercomputer Center in Tianjin, China, on its Tianhe-1A supercomputer platform. A series of three-model-day simulations were conducted with the standard Aqua-Planet Experiment (APE) project, designed within FAMIL, to obtain time stamps for the calculation of model speed, simulation cost, and model I/O efficiency. The results of the simulation demonstrate that FAMIL has remarkable scalability below 3,456 and 6,144 cores; the lowest simulation costs were found to be 1,536 and 3,456 cores for 12.5 and 6.25 km resolutions, respectively. Furthermore, FAMIL has excellent I/O scalability and efficiencies of more than 80 and 99 % on 6 and 1,536 I/Os, respectively.