Model Grid Spacing Research Articles

A Numerical Study of the Impact of Topography on the July 2021 Extreme Rainfall Event in Zhengzhou, China

AbstractAn unprecedented extreme rainfall event occurred in Zhengzhou, Henan Province, China, in July 2021. To understand the impact of local topography on this extreme rainfall event, the Weather Research and Forecasting model is configured with 27 and 9 km model grid spacings (MGS), along with United States Geological Survey (USGS) topography data at 8.3 and 0.9 km resolutions, called MGS27_USGS8.3, MGS9_USGS8.3, and MGS9_USGS0.9. Results show that the 9 km MGS, permitting activities with coarse γ scales (∼20 km), successfully reproduces the generation of mesoscale cyclones. However, the finer topography enables a more accurate representation of orographic blocking and lifting effects, thereby adjusting the position of the mesoscale cyclone. It can depict the location of adiabatic processes, local circulation, and vertical pressure gradient forces more accurately, thereby adjusting the position of topography‐induced vertical motions. The turbulence diagnostics show that the topography‐induced lifting motion enhances clouds that block longwave radiation, leading to local environment warming, which in turn enhances turbulence and further amplifies the updrafts, ultimately improving the spatial distribution and temporal variation of precipitation. This study provides insights for an in‐depth understanding of the mechanisms of topography on extreme rainfall.

Improving a WRF-Based High-Impact Weather Forecast System for a Northern California Power Utility

We describe enhancements to an operational forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to forecast conditions in Northern and Central California for critical decision-making such as proactively de-energizing selected circuits within the power grid. WRF forecasts are routinely produced on a 2 km grid, and the results are used as input to wildfire fuel moisture, fire probability, wildfire spread, and outage probability models. This forecast system produces skillful real-time forecasts while achieving an optimal blend of model resolution and ensemble size appropriate for today’s computational resources afforded to utilities. Numerous experiments were performed with different model settings, grid spacing, and ensemble configuration to develop an operational forecast system optimized for skill and cost. Dry biases were reduced by leveraging a new irrigation scheme, while wind skill was improved through a novel approach involving the selection of Global Ensemble Forecast System (GEFS) members used to drive WRF. We hope that findings in this study can help other utilities (especially those with similar weather impacts) improve their own forecast system.

The impact of mesh size, turbulence parameterization, and land‐surface‐exchange scheme on simulations of the mountain boundary layer in the hectometric range

AbstractThe horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range. We perform limited‐area simulations with the Icosahedral Nonhydrostatic (ICON) model across horizontal grid spacings (1 km, 500 m, 250 m, 125 m) in the Inn Valley, Austria, and evaluate the model with observations from the Cross‐Valley Flow in the Inn Valley Investigated by Dual‐Doppler LIDAR Measurements (CROSSINN) measurement campaign. This allows us to investigate whether increasing the horizontal resolution automatically improves the representation of the flow structure, surface exchange, and common meteorological variables. Increasing the horizontal resolution results in an improved simulation of the thermally induced circulation. However, the model still faces challenges with scale interactions and the evening transition of the up‐valley flow. Differences between two turbulence schemes (1D turbulence kinetic energy (TKE) and 3D Smagorinsky) emerge due to their different surface transfer formulations, yielding a delayed evening transition in the 3D Smagorinsky scheme. Generally speaking, the correct simulation of the mountain boundary layer depends mostly on the representation of model topography and surface exchange, and the choice of turbulence parameterization is secondary.

The impact of aerosols and model grid spacing on a supercell storm from Swabian MOSES 2021

AbstractThe supercell storm that occurred in southwestern Germany on June 23, 2021, had an exceptionally long lifetime of 7.5 hr, travelled a distance of nearly 190 km, and produced large amounts of hail. During that summer, the Swabian MOSES field campaign was held in that area, and several hydro‐meteorological measurements are available, as the storm passed directly over the main observation site. We present hindcasts of this event with the Icosahedral Non‐hydrostatic model using two horizontal grid spacings (i.e., 2 km, 1 km) with a single‐moment and an advanced double‐moment microphysics scheme. Numerical results show that all 2 km model realizations do not simulate convective precipitation at the correct location and time. For the 1 km grid spacing, changes in aerosol concentration resulted in large changes in convective precipitation. Only the 1 km run assuming a low cloud condensation nuclei (CCNs) concentration is able to realistically capture the storm, whereas no supercell is simulated in the more polluted scenarios. Observed aerosol particle concentrations indicate that CCNs values were the lowest of the month, which suggests that the low aerosol concentration is a reasonable assumption. The thermodynamic structure of the pre‐convective environment, as well as other observations, showed the best agreement to this model run as well, indicating that the good representation of the supercell was obtained for the right reason. The automatic tracking of individual clouds revealed that more convective cells with longer lifetimes are simulated at finer resolution. We also find a negative aerosol–precipitation effect that is not only due to a reduced collision–coalescence process, but also to weaker cold‐rain processes. These findings demonstrate the benefits of using an aerosol‐aware double‐moment microphysics scheme for convective‐scale predictability and that the use of different CCNs concentrations can determine whether a supercell is successfully simulated or not.

Impact of model grid spacing on the feedback between shortwave three-dimensional radiative transfer and an isolated nonprecipitating cumulus

Impact of model grid spacing on the feedback between shortwave three-dimensional radiative transfer and an isolated nonprecipitating cumulus

Assessment of Five Wind-Farm Parameterizations in the Weather Research and Forecasting Model: A Case Study of Wind Farms in the North Sea

Abstract To simulate the large-scale impacts of wind farms, wind turbines are parameterized within mesoscale models in which grid sizes are typically much larger than turbine scales. Five wind-farm parameterizations were implemented in the Weather Research and Forecasting (WRF) Model v4.3.3 to simulate multiple operational wind farms in the North Sea, which were verified against a satellite image, airborne measurements, and the FINO-1 meteorological mast data on 14 October 2017. The parameterization by Volker et al. underestimated the turbulence and wind speed deficit compared to measurements and to the parameterization of Fitch et al., which is the default in WRF. The Abkar and Porté-Agel parameterization gave close predictions of wind speed to that of Fitch et al. with a lower magnitude of predicted turbulence, although the parameterization was sensitive to a tunable constant. The parameterization by Pan and Archer resulted in turbine-induced thrust and turbulence that were slightly less than that of Fitch et al., but resulted in a substantial drop in power generation due to the magnification of wind speed differences in the power calculation. The parameterization by Redfern et al. was not substantially different from Fitch et al. in the absence of conditions such as strong wind veer. The simulations indicated the need for a turbine-induced turbulence source within a wind-farm parameterization for improved prediction of near-surface wind speed, near-surface temperature, and turbulence. The induced turbulence was responsible for enhancing turbulent momentum flux near the surface, causing a local speed-up of near-surface wind speed inside a wind farm. Our findings highlighted that wakes from large offshore wind farms could extend 100 km downwind, reducing downwind power production as in the case of the 400-MW Bard Offshore 1 wind farm whose power output was reduced by the wakes of the 402-MW Veja Mate wind farm for this case study. Significance Statement Because wind farms are smaller than the common grid spacing of numerical weather prediction models, the impacts of wind farms on the weather have to be indirectly incorporated through parameterizations. Several approaches to parameterization are available and the most appropriate scheme is not always clear. The absence of a turbulence source in a parameterization leads to substantial inaccuracies in predicting near-surface wind speed and turbulence over a wind farm. The impact of large clusters of offshore wind turbines in the wind field can exceed 100 km downwind, resulting in a substantial loss of power for downwind turbines. The prediction of this power loss can be sensitive to the chosen parameterization, contributing to uncertainty in wind-farm economic planning.

Comparing Loon Superpressure Balloon Observations of Gravity Waves in the Tropics With Global Storm‐Resolving Models

AbstractSuperpressure balloons, which drift approximately on isopycnal surfaces, get displaced by gravity waves and are thus capable of detecting gravity wave signatures. The project Loon provides superpressure balloon data in the upper troposphere and lower stratosphere from 2011 to 2021. We compare Loon data from the 6 years of best data coverage with output of global storm‐resolving models from the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains winter initiative in the tropics. We study the variance of the vertical velocity and, for the models, the gravity wave momentum flux as function of distance to closest convection. The models show large differences in the variance of the vertical wind velocity, which is crucial for calculating vertical gravity wave momentum fluxes. We find large differences between the models with respect to simulated convection, lateral propagation, and the wave background away from sources. We then sample balloons as models by optimizing the match of vertical wind distributions using a temporal low pass filter. The average distance the balloons travel during the optimum low pass filtering time turns out to correspond approximately to four times the model grid spacing. The functional dependence of the vertical velocity variance on distance to closest convection is similar between the models and the observations sampled as models. The robustness of this result across all models suggests that storm‐resolving models provide a useful resource for machine learning some characteristics of convectively generated gravity waves.

Demonstrating the Potential Impacts of Assimilating FY-4A Visible Radiances on Forecasts of Cloud and Precipitation with a Localized Particle Filter

Abstract The Advanced Geostationary Radiation Imager (AGRI) on board the Fengyun-4A (FY-4A) satellite provides visible radiances that contain critical information on clouds and precipitation. In this study, the impact of assimilating FY-4A/AGRI all-sky visible radiances on the simulation of a convective system was evaluated with an observing system simulation experiment (OSSE) using a localized particle filter (PF). The localized PF was implemented into the Data Assimilation Research Testbed (DART) coupled with the Weather Research and Forecasting (WRF) Model. The results of a 2-day data assimilation (DA) experiment generated encouraging outcome at a synoptic scale. Assimilating FY-4A/AGRI visible radiances with the localized PF significantly improved the analysis and forecast of cloud water path (CWP), cloud coverage, rain rate, and rainfall areas. In addition, some positive impacts were produced on the temperature and water vapor mixing ratio in the vicinity of cloudy regions. Sensitivity studies indicated that the best results were achieved by the localized PF configured with a localization distance that is equivalent to the model grid spacing (20 km) and with an adequately short cycling interval (30 min). However, the localized PF could not improve cloud vertical structures and cloud phases due to a lack of related information in the visible radiances. Moreover, the localized PF was compared with the ensemble adjustment Kalman filter (EAKF) and it was indicated that the localized PF outperformed EAKF even when the number of ensemble members was doubled for the latter, indicating a great potential of the localized PF in assimilating visible radiances.

On the Changes in Convection-Allowing WRF Forecasts of MCS Evolution due to Decreases in Model Horizontal and Vertical Grid Spacing. Part II: Impacts on QPFs

Abstract Several past studies have demonstrated improvement in forecasting convective precipitation by decreasing model grid spacing to the point of explicitly resolving deep convection. Real-case convective modeling studies have attempted to identify what model grid spacing feasibly provides the most optimal forecast given computational constraints. While Part I of this manuscript investigated changes in MCS cold pool characteristics with varied vertical and horizontal grid spacing, Part II explores changes in skill for MCS spatial placement, forward speed, and QPFs among runs with decreased horizontal and vertical grid spacing by employing the same WRF-ARW runs as in Part I. QPF forecast skill significantly improved for later portions of the MCS life cycle when decreasing horizontal grid spacing from 3 to 1 km with the part double-moment Thompson microphysics scheme. Some improvements were present in QPFs with higher precipitation amounts in the early stages of MCSs simulated with the single-moment WSM6 microphysics scheme. However, significant improvements were not common with MCS placement or QPF of the entire precipitation swath with either the Thompson or WSM6 schemes, suggesting that the benefit to MCS QPFs with decreased horizontal grid spacings is limited. Furthermore, increasing vertical resolution from 50 to 100 levels worsened WSM6 scheme QPF skill in some cases, suggesting that choices of or improvement in model physics may be equally or more positively impactful to NWP forecasts than grid spacing changes.

Impact of Advection Schemes on Tracer Interrelationships in Large-Eddy Simulations of Deep Convection

Abstract This study investigates the preservation of tracer interrelationships during advection in large-eddy simulations of an idealized deep convective cloud, which is particularly relevant to chemistry, aerosol, and cloud microphysics models. Employing the Cloud Model 1, advection is represented using third-, fifth-, and seventh-order weighted essentially non-oscillatory schemes. As a simplified analogy for cloud hydrometeors and aerosols, several inert passive tracers following linear and nonlinear relationships are initialized after the cloud reaches ∼6-km depth. Numerical mixing in the simulated turbulent convective clouds leads to significant deviations from the initial nonlinear relationships between tracers. In these simulations, a considerable fraction of the grid points where the tracers’ nonlinear relationships are altered from advection are classified as unrealistic (e.g., ∼13% for the environmental tracers on average), including errors from range-preserving unmixing and overshooting. Errors in the sum of three tracers are also relatively large, ranging between ∼1% and 16% for 5% of the grid points in and near the cloud. The magnitude of unrealistic mixing and errors in the sum of three tracers generally increase with the order of accuracy of the advection scheme. These results are consistent across model grid spacings ranging from 50 to 200 m, and across three different flow realizations for each combination of grid spacing and advection scheme tested. Tests employing a previously proposed scalar normalization procedure show substantially reduced errors in the sum of three tracers with a relatively small negative impact on other tracer relationships. This analysis, therefore, suggests efficacy of the normalization procedure when applied to turbulent three-dimensional cloud simulations. Significance Statement In nature, transporting several quantities through bulk motions of a fluid does not affect preexisting relationships between them. However, this is not always accomplished in numerical models of the atmosphere, because of intrinsic limitations in the transport algorithms employed. We aim to investigate how these errors behave in 3D realistic simulations of a cumulus cloud, where the turbulent flow constitutes a particular challenge. We show that relationships between quantities are significantly and frequently perturbed during bulk transport in the model. Moreover, our results suggest that increasing complexity of the bulk-transport algorithms (in a way that is conventionally employed for improving the representation of individual quantities) tends to worsen the representation of relationships between two or three quantities.

Seasonal heavy precipitation sensitivity to moisture corrections in the western Mediterranean across resolutions

The controlling role of atmospheric water vapour for heavy precipitation leading to extreme events has been widely demonstrated, along with the existing gap of adequate moisture observations and the frequent biases present in model simulations concerning this fundamental variable. In this study, we profit from a state-of-the-art dense network of GPS measurements over Europe retrieving a homogenized GPS-derived Zenith Total Delay (GPS-ZTD) data set up to 10 min of temporal resolution, to assess the seasonal sensitivity of convection-related processes and heavy precipitation modelling to atmospheric humidity corrections. For this purpose, we perform nudging experiments with the COSMO-CLM model at two spatial resolutions, 7 km (parameterized convection) and 2.8 km (explicitly resolved convection) covering the autumn period of 2012, when the Special Observation Period (SOP) 1 of the Hydrological Cycle in the Mediterranean Experiment (HyMeX) program took place in the Western Mediterranean, which is our area of interest.The benefits and disadvantages of GPS-ZTD nudging and resulting moisture corrections are disentangled. The impact on high-resolution parameterized versus convection-permitting simulations is compared. A process-understanding methodology and a local-to-regional approach are used. Our results show a beneficial impact on the seasonal scale at both model grid spacings improving the representation of the chain of processes leading to heavy precipitation, contrary to the non-systematic improvement at the event and sub-event scales. The correction of atmospheric moisture entails a reduction of about 10% in the total column water vapour and corrections on single locations up to 10 mm counteracting the model wet bias across scales. The location, structure, and amount of total precipitation are positively affected. Particularly, the combination of high-resolution atmospheric humidity observations and fine convection-permitting simulations shows great potential for correction of the precipitation daily cycle, key for accurate precipitation modelling. The difference in the density of local and upstream observational networks and the lack of information on the vertical stratification of moisture are identified weaknesses, which could be determinants in obtaining more accurate corrections on seasonal to sub-seasonal scales after assimilation strategies.

Relating Vertical Velocity and Cloud/Precipitation Properties: A Numerical Cloud Ensemble Modeling Study of Tropical Convection

AbstractFundamental relationships exist between cloud and precipitation development and their dynamic processes. Latent heat released by cloud/precipitation formation affects cloud vertical motions, which in turn affect convective cloud development. Here, a cloud‐resolving model is used to relate cloud properties and latent heating with cloud drafts using 15‐day simulations for an oceanic and continental environment. The results show condensation, deposition, and freezing occur mainly in moderate (3–5 m s−1) to strong (>10 m s−1) updrafts, evaporation and sublimation mainly in weak (1–2 m s−1) to moderate downdrafts, and melting in moderate updrafts and downdrafts. Active updrafts cover only a small percentage of the model domain but contribute significantly to the latent heat release and are associated with large proportions of the hydrometeors. Active updrafts with vertical velocities exceeding 1 and 2 m s−1 account for more than 75% and 50%, respectively, of the condensation, deposition, and freezing in both the oceanic and continental cases. However, active downdrafts with vertical velocity magnitudes exceeding |1 m s−1| account for less than 40% and 25%, respectively, of the evaporation and sublimation. More evaporation and sublimation than condensation and deposition occur in the inactive cloud regions. Sensitivity tests are also conducted to assess the impact of model grid spacing (1,000 m vs. 250 m) and microphysical schemes (3 ice classes vs. 4 ice classes) on latent heat release and hydrometeor amount. The results show that model resolution had more impact than the microphysics on the simulated cloud properties in both cases.

Augmenting the Double-Gaussian Representation of Atmospheric Turbulence and Convection via a Coupled Stochastic Multi-Plume Mass-Flux Scheme

Abstract Modern general circulation models continue to require parameterizations of subgrid transport due to planetary boundary layer (PBL) turbulence and convection. Some schemes that unify these processes rely on assumed joint probability distributions of vertical velocity and moist conserved thermodynamic variables to predict the subgrid-scale contribution to the mean state of the atmosphere. The multivariate double-Gaussian mixture has been proposed as an appropriate model for PBL turbulence and shallow convection, but it is unable to reproduce important features of shallow cumulus convection. In this study, a novel unified PBL turbulence–convection–cloud macrophysics scheme is presented based on the eddy-diffusivity/mass-flux framework. The new scheme augments the double-Gaussian representation of subgrid variability with multiple stochastic mass-flux plumes at minimal added computational cost. Improved results for steady-state maritime and transient continental shallow convection from a single-column model implementation of the new scheme are shown with respect to reference large-eddy simulations. Improvements are seen in the cloud layer due to mass-flux plumes occupying the extreme moist, low liquid-water potential temperature tail of the joint temperature–moisture distribution. Significance Statement Computer models of the atmosphere used to predict future climate are unable to directly represent air motion at small spatial scales because it would take too long to run the model over the entire planet. Instead, models typically use coarse model grid spacing and a simplified statistical representation of the physical processes that cause small-scale motions. This paper improves a particular simplified representation by adding a mechanism to represent statistically rare events of strong small-scale air motion that coherently transport air from near the surface to higher in the atmosphere. This increased transport also improves the representation of clouds, a particularly difficult phenomenon to simulate in models.

Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean–atmosphere models

High-frequency precipitation variance is calculated in 12 different free-running (non-data-assimilative) coupled high resolution atmosphere–ocean model simulations, an assimilative coupled atmosphere–ocean weather forecast model, and an assimilative reanalysis. The results are compared with results from satellite estimates of precipitation and rain gauge observations. An analysis of irregular sub-daily fluctuations, which was applied by Covey et al. (Geophys Res Lett 45:12514–12522, 2018. https://doi.org/10.1029/2018GL078926) to satellite products and low-resolution climate models, is applied here to rain gauges and higher-resolution models. In contrast to lower-resolution climate simulations, which Covey et al. (2018) found to be lacking with respect to variance in irregular sub-daily fluctuations, the highest-resolution simulations examined here display an irregular sub-daily fluctuation variance that lies closer to that found in satellite products. Most of the simulations used here cannot be analyzed via the Covey et al. (2018) technique, because they do not output precipitation at sub-daily intervals. Thus the remainder of the paper focuses on frequency power spectral density of precipitation and on cumulative distribution functions over time scales (2–100 days) that are still relatively “high-frequency” in the context of climate modeling. Refined atmospheric or oceanic model grid spacing is generally found to increase high-frequency precipitation variance in simulations, approaching the values derived from observations. Mesoscale-eddy-rich ocean simulations significantly increase precipitation variance only when the atmosphere grid spacing is sufficiently fine (< 0.5°). Despite the improvements noted above, all of the simulations examined here suffer from the “drizzle effect”, in which precipitation is not temporally intermittent to the extent found in observations.

Response of Moist Convection to the Spectral Feature of the Surface Flux Field at Model Resolution Across the Gray Zone

AbstractThe Weather Research and Forecasting model is run at the effective resolution Δf across the gray zone, or the “terra incognita”, at which Δf ∼ l, where l is the scale of energy‐containing turbulent eddies. We examine the developments of afternoon moist convection over different multiscale features of the surface flux field as a function of the model grid spacing Δ that varies from 100 m to 1 km. Numerical experiments demonstrate that the model performs better under heterogeneous than homogeneous surface conditions in the gray zone in terms of the spatial distribution of moist convection. This improved performance is due to the explicit resolvability of the mesoscale temperature and humidity perturbations, which are critical for the growth of deep moist convection over the heterogeneous surface condition. However, under both heterogeneous and homogeneous surface conditions, the timing and intensity of moist convection vary with the model resolution. Compared with that in the large eddy simulation at Δ = 100 m, the earlier onset of moist convection at coarser resolutions appears to be related to the overestimated total buoyancy fluxes and total kinetic energy near the surface. That is, the more intense vertical mixing near the surface might induce a warmer surface layer, which yields individual cell updrafts strong enough to penetrate the capping inversion. In addition, misrepresentation of the diluting effects of entrainment on the penetrating updrafts in coarser‐resolution simulations could be responsible for the rapid development of deep convection instead of a gradual transition from shallow to deep moist convection.

Sensitivity of large eddy simulations of tropical cyclone to sub-grid scale mixing parameterization

The surface wind structure and vertical turbulent transport processes in the eyewall of hurricane Isabel (2003) are investigated using six large-eddy simulations (LESs) with different horizontal grid spacing and three-dimensional (3D) sub-grid scale (SGS) turbulent mixing models and a convection permitting simulation that uses a coarser grid spacing and one-dimensional vertical turbulent mixing scheme. The mean radius-height distribution of storm tangential wind and radial flow, vertical velocity structure, and turbulent kinetic energy and momentum fluxes in the boundary layer generated by LESs are consistent with those derived from historical dropsonde composites, Doppler radar, and aircraft measurements. Unlike the convection permitting simulation that produces storm wind fields lacking small-scale disturbances, all LESs are able to produce sub-kilometer and kilometer scale eddy circulations in the eyewall. The inter-LES differences generally reduce with the decrease of model grid spacing. At 100-m horizontal grid spacing, the vertical momentum fluxes induced by the model-resolved eddies and the associated eddy exchange coefficients in the eyewall simulated by the LESs with different 3D SGS mixing schemes are fairly consistent. Although with uncertainties, the decomposition in terms of eddy scales suggests that sub-kilometer eddies are mainly responsible for the vertical turbulent transport within the boundary layer (~1 km depth following the conventional definition) whereas eddies greater than 1 km become the dominant contributors to the vertical momentum transport above the boundary layer in the eyewall. The strong dependence of vertical turbulent transport on eddy scales suggests that the vertical turbulent mixing parameterization in mesoscale simulations of tropical cyclones is ultimately a scale-sensitive problem.

Are the Different Eddy Metrics Quantifying the Winter North Pacific Storm Track Consistent With Each Other?

AbstractHistorical simulations from twenty‐nine Coupled Model Intercomparison Project Phase 6 (CMIP6) models are used to investigate the consistency among different eddy metrics characterizing the winter North Pacific storm track (WNPST). All CMIP6 models can reproduce the basic climatological characteristics of the WNPST. Results show that, out of the metrics studies, only the upper‐tropospheric filtered meridional wind variance () is significantly correlated with the model grid spacing. The climatological amplitudes of different eddy metrics are consistent with each other, except for the consistency between the upper‐tropospheric and lower‐tropospheric meridional eddy heat flux and that between the middle‐tropospheric eddy kinetic energy and filtered sea level pressure variance (). The strength trends of different eddy metrics are consistent with each other except for upper‐tropospheric and . The meridional migration trends are consistent among different eddy metrics excluding . Given that the sensitivity to horizontal resolution, climatological amplitude, strength trend and meridional migration trend of different Eulerian eddy metrics may exhibit inconsistency, the use of multiple eddy metrics to increase the reliability of the results is suggested.

The Climatology and the Midwinter Suppression of the Cold Season North Pacific Storm Track in CMIP6 Models

AbstractThe reproducibility of climatology and the midwinter suppression of cold season North Pacific storm track (NPST) in historical runs of 18 CMIP6 models is evaluated against the NCEP reanalysis data. The results show that the position of the climatological peak area of 850 hPa meridional eddy heat flux (v′t′850) is well captured by these models. The spatial patterns of climatological v′t′850 are basically consistent with the NCEP reanalysis. Generally, NorESM2-LM and CESM2-WACCM present a relatively strong capability to reproduce the climatological amplitude of v′t′850 with lower RMSE than the other models. Compared with CMIP5 models, the inter-model spread of v′t′850 climatology among the CMIP6 models is smaller, and their multi-model ensemble is closer to the NCEP reanalysis. The geographical distribution in more than half of the selected models is further south and east. For the subseasonal variability of v′t′850, nearly half of the models exhibit a double-peak structure. In contrast, the apparent midwinter suppression in the NPST represented by the 250 hPa filtered meridional wind variance (v′v′250) is reproduced by all the selected models.In addition, the present study investigates the possible reasons for simulation biases regarding climatological NPST amplitude. It is found that a higher model horizontal resolution significantly intensifies the climatological v′v′250. There is a significant in-phase relationship between climatological v′t′250 and the intensity of the East Asian winter monsoon (EAWM). However, the climatological v′t′850 is not sensitive to the model grid spacing. Additionally, the climatological low-tropospheric atmospheric baroclinicity is uncorrelated with climatological v′v′250. The stronger climatological baroclinic energy conversion is associated with the stronger climatological v′t′850.

Sensitivity of convective precipitation to model grid spacing and land‐surface resolution in ICON

AbstractThe impact of model grid spacing and land‐surface resolution (LSR) on convective precipitation are investigated for areas with different orographic complexities. ICOsahedral Nonhydrostatic (ICON) model simulations were performed for six days having weak large‐scale forcing using six model grid spacings (in metres): Numerical Weather Prediction (NWP) (, ) and Large‐Eddy Simulation (LES) physics simulations (, , , and ) in a nested set‐up. Concerning LSR, we focused on simulations with LSRs of 1,250 and 5,000 m, keeping the model grid spacing at 156 m. The onset of precipitation in is earlier by 0.5–2 hr, while LSR modifications show a similar onset compared with . The relative percentage difference (RPD) of areal mean daily precipitation across LES physics simulations decreases consistently with model grid spacing for most of the cases. The RPD of precipitation in is considerably higher (75th percentile: ≈155%) than that of the LSR runs at resolutions of both 1,250 and 5,000 m, with 75th percentiles of ≈7% and ≈22%, respectively. To investigate the processes causing the differences in precipitation characteristics, like onset time and amount, the heat and moisture budgets of and were compared. The results show that, at the initial stage of cloud formation, a higher number of smaller clouds are formed in compared with . The small clouds in are subject to considerable evaporative cooling at their edges and shell regions, due to entrainment processes. As a result, these clouds often dissolve before they can grow deep. Later on, cloud aggregation in also enables precipitation. The delayed onset of precipitation and reduced areas of aggregated clouds having low precipitation rates are the main reasons for less precipitation in than in .

Sensitivities of slantwise convection dynamics to model grid spacing under an idealized framework

AbstractAlthough the release of conditional symmetric instability (CSI) by slantwise convection is recognized as an important baroclinic process, the basic dynamics of these circulations and their representation in numerical models remain inadequately understood. To address this issue, a series of 2D idealized experiments of pure slantwise convection are performed in an initially statically stable environment using the non‐hydrostatic Weather Research and Forecasting model, with the horizontal grid lengths varying between 1 and 40 km. The results show that the larger‐scale feedbacks of the slantwise convection converge numerically when a cross‐band grid length (∆y) of 5 km is reached. The differences between the non‐converged and converged results tie closely to the release of a shallow layer of conditional instability that inevitably accompanies the early development of the slantwise circulation due to differential advection of saturation equivalent potential temperature (). The resolved small‐scale upright convection embedded within the slantwise band can energize the horizontal acceleration of the slantwise band at mid‐to‐upper levels by transporting low geostrophic momentum upward that results in localized inertial instability. The convective cell also enhances the large‐scale CSI neutralization by advecting high downward with strong downdraughts that orient more vertically than coarser‐gridded runs. Moreover, ∆y ≤ 5 km also better resolves the horizontal pressure gradients for cross‐band motions. This work suggests that global/climate numerical weather prediction models may not adequately resolve important characteristics of slantwise convection. As most cumulus schemes target only upright convection, the inclusion of parametrized slantwise convection may improve their performance.