Horizontal Grid Research Articles

High Resolution Dynamical Downscaling of Air Temperature and Precipitation using WRF-ARW Model Over Iraq

The ability of the Weather Research and Forecasting (WRF-ARW) model to simulate precipitation variability throughout the Middle East, especially Iraq, is evaluated in this study. The Weather Research and Forecasting model (WRF v 4.2.1) was used. Using a two-way nesting technique and Mercator projection, the WRF model was set up with two nested grids with high regional resolution at 30 km (WRF30km) and 10 km (WRF10km) horizontal grid spacing. From the surface to 50 hPa, both domains have 41 vertical levels. The outer domain covers the Middle East region and the smaller one covers the Iraq region. The ARW supports horizontal nesting, allowing higher resolution over a region of interest, by introducing additional grids, which is available only for horizontal refinement. The nested grids are rectangular and are aligned with the parent (coarser) grid within which they are nested. To predict many atmospheric parameters WRF-ARW model was used based on the initial conditions taken from National Centre for Atmospheric Research (NCAR) records for the period from 23 to 25 of march 2019. The study area is essentially an area bounded by longitudes 35°-55° and latitudes 29°-38° typically including the area of Iraq. The WRF-ARW model was set up on a Linux platform with a 10 km grid size in the zonal and meridional directions. The aim of this study is to evaluate the two WRF tools dynamical downscaling and nesting) at high resolution (30 and 10 km), for simulating rainfall and temperature over Iraq.

Nonlinear Internal Tides in a Realistically Forced Global Ocean Simulation

AbstractThe decay of the low‐mode internal tide due to the superharmonic energy cascade is investigated in a realistically forced global Hybrid Coordinate Ocean Model simulation with 1/25° (4 km) horizontal grid spacing. Time‐mean and depth‐integrated supertidal kinetic energy is found to be largest near low‐latitude internal tide generation sites, such as the Bay of Bengal, Amazon Shelf, and Mascarene Ridge. The supertidal kinetic energy can make up to 50% of the total internal tide kinetic energy several hundred kilometers from the generation sites. As opposed to the tidal flux divergence, the supertidal flux divergence does not correlate with the barotropic to baroclinic energy conversion. Instead, the time‐mean and depth‐integrated supertidal flux divergence correlates with the nonlinear kinetic energy transfers from (sub)tidal to supertidal frequency bands as estimated with a novel coarse‐graining approach. The regular spaced banding patterns of the surface‐intensified nonlinear energy transfers are attributed to semidiurnal mode 1 and mode 2 internal waves that interfere constructively at the surface. This causes patches where both surface tidal kinetic energy and nonlinear energy transfers are elevated. The simulated internal tide off the Amazon Shelf steepens significantly near these patches, generating solitary‐like waves in good agreement with Synthetic Aperture Radar imagery. Globally, we find that regions of high supertidal energy flux also show a high correlation with observed instances of internal solitary waves.

Water isotopic characterisation of the cloud–circulation coupling in the North Atlantic trades – Part 1: A process-oriented evaluation of COSMOiso simulations with EUREC4A observations

Abstract. Naturally available, stable, and heavy water molecules such as HDO and H218O have a lower saturation vapour pressure than the most abundant light water molecule H216O; therefore, these heavy water molecules preferentially condense and rain out during cloud formation. Stable water isotope observations thus have the potential to provide information on cloud processes in the trade-wind region, in particular when combined with high-resolution model simulations. In order to evaluate this potential, nested COSMOiso (isotope-enabled Consortium for Small Scale Modelling; Steppeler et al., 2003; Pfahl et al., 2012) simulations with explicit convection and horizontal grid spacings of 10, 5, and 1 km were carried out in this study over the tropical Atlantic for the time period of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate; Stevens et al., 2021) field experiment. The comparison to airborne in situ and remote sensing observations shows that the three simulations are able to distinguish between different mesoscale cloud organisation patterns as well as between periods with comparatively high and low rain rates. Cloud fraction and liquid water content show a better agreement with aircraft observations with higher spatial resolution, because they show strong spatial variations on the scale of a few kilometres. A low-level cold-dry bias, including too depleted vapour in the subcloud and cloud layer and too enriched vapour in the free troposphere, is found in all three simulations. Furthermore, the simulated secondary isotope variable d-excess in vapour is overestimated compared to observations. Special attention is given to the cloud base level, which is the formation altitude of shallow cumulus clouds. The temporal variability of the simulated isotope variables at cloud base agrees reasonably well with observations, with correlations of the flight-to-flight data as high as 0.7 for δ2H and d-excess. A close examination of isotopic characteristics under precipitating clouds, non-precipitating clouds, clear-sky and dry-warm patches at the altitude of cloud base shows that these different environments are represented faithfully in the model with similar frequencies of occurrence, isotope signals, and specific-humidity anomalies as found in the observations. Furthermore, it is shown that the δ2H of cloud base vapour at the hourly timescale is mainly controlled by mesoscale transport and not by local microphysical processes, while the d-excess is mainly controlled by large-scale drivers. Overall, this evaluation of COSMOiso, including the isotopic characterisation of different cloud base environments, suggests that the simulations can be used for investigating the role of atmospheric circulations on different scales for controlling the formation of shallow cumulus clouds in the trade-wind region, as will be done in part 2 of this study.

A station‐based evaluation of near‐surface south foehn evolution in COSMO‐1

AbstractThis study investigates the skill of the Consortium for Small‐scale Modeling (COSMO) model (v5.7) at 1.1 km horizontal grid size in simulating the near‐surface foehn properties and evolution for five south foehn events and a five‐year‐long climatology. A significant near‐surface cold bias is found during foehn, with an average bias of K in the Rhine Valley in the five foehn cases and K in the major northern foehn valleys in the five‐year foehn climatology. The cold bias tends to be larger in the stronger and moister deep foehn events. Sensitivity experiments are carried out to examine the possible causes of the cold bias, including changes to the parameterization of the land–atmosphere interaction, 1D turbulence parameterization, and horizontal grid spacing. Most sensitivity experiments have only a very minor impact on the cold bias, except for the model run with a horizontal grid spacing of 550 m. The 550‐m COSMO run shows a reduced cold bias during foehn hours and also an improvement in the simulated foehn duration and northward foehn extent. By inspecting the vertical dimension, we found that the near‐surface cold bias downstream might partly originate upstream. A further contribution to the downstream cold bias is likely due to insufficient vertical mixing in the foehn flow. The latter is possibly enhanced in the 550‐m model run, leading to a less stably stratified atmosphere in the lower few hundred meters of the atmosphere and a reduction of the reported model cold bias.

Modeling Lightning Activity in the Third Pole Region: Performance of a km-Scale ICON-CLM Simulation

The Third Pole region, especially the Himalayas, is a lightning hotspot. Predicting lightning activity in this region is difficult due to the complex monsoon and westerly circulations, as well as the complex orography. Km-scale simulations can explicitly, without parameterization, tackle deep convective phenomena. A year-long (October 2019–September 2020) ICON-CLM simulation was performed with a km-scale horizontal grid spacing of 3.3 km to assess the region’s lightning activity and evaluate the model ICON-CLM. The simulated lightning potential index (LPI) was compared against the lightning proxy CAPE × PREC (CP) derived from ICON-CLM and reanalysis ERA5. In addition, the LPI was evaluated against the TRMM lightning climatology and observed flashes from the International Space Station Lightning Imaging Sensor (ISS-LIS). The LPI reproduced the major spatial, seasonal, and diurnal features of lightning activity as represented in the TRMM climatology. In contrast, the CP from both ICON-CLM and ERA5 performed less well regarding the location of events and the diurnal features. Taking the mean values of the LPI and CP of all the grids within 90 km × 90 km around the ISS-LIS detected lightning event, we found that over 80% of lightning events were recorded using the ICON-CLM simulation. Analysis of individual cases showed that the LPI predicted localization of lightning events better, but flash counts were slightly lower than the CP. Therefore, the combined use of ICON-CLM’s simulated LPI and CP can be a valuable predictor for lightning events over the Third Pole region.

Exploring hail and lightning diagnostics over the Alpine-Adriatic region in a km-scale climate model

Abstract. The north and south of the Alps, as well as the eastern shores of the Adriatic Sea, are hot spots of severe convective storms, including hail and lightning associated with deep convection. With advancements in computing power, it has become feasible to simulate deep convection explicitly in climate models by decreasing the horizontal grid spacing to less than 4 km. These kilometer-scale models improve the representation of orography and reduce uncertainties associated with the use of deep convection parameterizations. In this study, we perform km-scale simulations for eight observed cases of severe convective storms (seven with and one without observed hail) over the Alpine-Adriatic region. The simulations are performed with the climate version of the regional model Consortium for Small-scale Modeling (COSMO) that runs on graphics processing units (GPUs) at a horizontal grid spacing of 2.2 km. To analyze hail and lightning we have explored the hail growth model (HAILCAST) and lightning potential index (LPI) diagnostics integrated with the COSMO-crCLIM model. Comparison with available high-resolution observations reveals good performance of the model in simulating total precipitation, hail, and lightning. By performing a detailed analysis of three of the case studies, we identified the importance of significant meteorological factors for heavy thunderstorms that were reproduced by the model. Among these are the moist unstable boundary layer and dry mid-level air, the topographic barrier, as well as an approaching upper-level trough and cold front. Although COSMO HAILCAST tends to underestimate the hail size on the ground, the results indicate that both HAILCAST and LPI are promising candidates for future climate research.

Explicitly Resolved Cloud Feedbacks in the Radiative‐Convective Equilibrium Model Intercomparison Project

AbstractRadiative‐convective equilibrium (RCE) is particularly well suited for studying tropical deep‐convection, a regime of clouds that contributes some of the highest uncertainties to the estimates of total cloud feedback. In order to perform a comprehensive calculation and decomposition of cloud feedbacks in cloud‐permitting models, previously primarily done in global climate models, the configuration of a satellite simulator for use with offline data was successfully implemented. The resultant total cloud feedback is slightly positive, primarily driven by the longwave effects of increases in cloud altitude. The high‐cloud altitude feedback is robustly positive and has a central value and uncertainty well‐matched with prior estimates. Reductions in high cloud amount drive a tropical anvil cloud area feedback that is on average negative, consistent with prior estimates. However, a subset of models with finer horizontal grid spacing indicate that a positive tropical anvil cloud area feedback cannot be ruled out. Even though RCE is only applicable to tropical deep‐convective clouds, the RCE total cloud feedback is within the range of prior comprehensive estimates of the global total cloud feedback. This emphasizes that the tropics heavily influence the behavior of global cloud feedbacks and that RCE can be exploited to learn more about how processes related to deep convection control cloud feedbacks.

Enhancing Air Quality Forecasts Across the Contiguous United States (CONUS) During Wildfires Using Analog-Based Post-Processing Methods

With our growing understanding of the risks of air pollution to human health, air quality forecasting has become a very important tool to enable decision-makers to take preventive and corrective measures for current and future policies. In addition, accurate predictions of air quality can help predict and mitigate the impacts of wildfires on human health, which have an increased risk due to anthropogenic climate change. However, errors in air quality forecasts limit their value in decision-making processes. Thus, increasing the accuracy of air quality forecasts is of significant importance. In this study, we have utilized the Community Multiscale Air Quality (CMAQ) modeling system with a 12 km horizontal grid resolution to generate daily 48-h fine particulate matter (PM2.5) forecasts for the Contiguous United States (CONUS) domain for June 1st through September 29th (major wildfire season) during 2015–2021. We conduct CMAQ offline simulations using meteorological inputs generated by the NOAA’s Unified Forecast System (UFS) numerical weather prediction model. We analyze the performance of the CMAQ PM2.5 and UFS meteorological forecasts over seven years of simulations for Environmental Protection Agency (EPA)-defined ten regions using the Air Quality System (AQS) ambient air pollution data from over a thousand monitoring sites across the CONUS. We have found that on average, the CMAQ model performs better in the eastern CONUS with the lowest Root Mean Square Error (RMSE) (10–30 μg/m3) while in the west, where wildfires are prevalent, the model has the highest RMSE of up to 120 μg/m3. To address these substantial model errors, we advance the field by applying Analog Ensemble (AnEn), a state-of-the-art statistical-dynamical method, to enhance PM2.5 forecast accuracy, with a particular focus on wildfire events, when producing an accurate forecast is highly challenging. We further refine this approach by incorporating a Carbon Monoxide-FIRE (CO-FIRE) tracer to precisely monitor fire smoke. In parallel to our objective and for the first time, we introduce two novel predictors, i.e., a CO−FIRE tracer in the model, and the maximum observed PM2.5 concentrations from the previous day (PM2.5−preday−max), and evaluate their potential significance in improving forecast accuracy, which aligns with the primary goal of our study. Despite the challenges of using AnEn for wildfires, we demonstrate that it has the potential to improve the CMAQ model forecast over the CONUS. We find that AnEn decreases the model RMSE by up to 25%, including additional 7% and 15% reduction by CO−FIRE and PM2.5−preday−max predictors, respectively, at different forecast lead times. In addition, the correlation between AnEn forecasts and observations is 20%–40% higher than that between CMAQ and observations. The Mean Bias Error (MBE) for AnEn forecasts is consistent and approximately −0.5 μg/m3 whereas CMAQ MBE varies between −1 and +1 μg/m3 between 0–48 forecast hours. AnEn significantly improves the PM2.5 forecast results during its highest episodes. During the initial days of wildfires, AnEn performs similarly to CMAQ. However, it soon catches up and decreases the error significantly.

Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system

Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite consists of active and passive sensors whose observations will be acted on by an array of retrieval algorithms. EarthCARE's retrieval algorithms have undergone pre-launch verifications within a virtual observing system that consists of 3D atmosphere–surface data produced by the Global Environmental Multiscale (GEM) numerical weather prediction (NWP) model, as well as instrument simulators that when applied to NWP data yield synthetic observations for EarthCARE's four sensors. Retrieval algorithms operate on the synthetic observations, and their estimates go into radiative transfer models that produce top-of-atmosphere solar and thermal broadband radiative quantities, which are compared to synthetic broadband measurements, thus mimicking EarthCARE's radiative closure assessment. Three high-resolution test frames were simulated; each measures ∼6200 km along-track by 200 km across-track. Horizontal grid spacing is 250 m, and there are 57 atmospheric layers up to 10 mbar. The frames span wide ranges of conditions and extend over (i) Greenland to the Caribbean, crossing a cold front off Nova Scotia; (ii) Nunavut to Baja California, crossing over Colorado's Rocky Mountains; and (iii) the central equatorial Pacific Ocean, which includes a mesoscale convective system. This report discusses how the test frames were produced and presents their key geophysical features. All data are publicly available and, owing to their high-resolution, could be used to simulate observations for other measurement systems.

Statistical Analysis of Spatiotemporal Variations of Air‐Sea CO2 Fluxes in the Kuroshio Region

AbstractSpatiotemporal variations in air‐sea CO2 fluxes in the Kuroshio region were evaluated using measurements made by voluntary cargo ships and research vessels. The data were re‐gridded to produce a 1° × 1° horizontal grid and 0.1‐year timesteps. Spatial clustering showed that the area north of approximately 30°N was the strongest atmospheric CO2 sink. The spatial differences were largest in winter and insignificant in summer. The oceanic CO2 uptake in the Kuroshio region increased from 2000 to 2019. Changes in the wind speed and total alkalinity affected the decadal increase in CO2 absorption. The spatial distributions of the air‐sea CO2 fluxes were affected by the Kuroshio large meander (KLM). This effect was likely caused by the change in seawater fCO2 via the change in the Kuroshio Extension Path during the KLM period. The Fourier regression technique used in the data analysis was expected to facilitate analyses of the carbonate system in coastal waters, where comprehensive on‐site measurements and satellite analyses are difficult.

Sensitivity of simulated wind power under diverse spatial scales and multiple terrains using the weather research and forecasting model

During the process of grid refinement and downscaling in the Weather Research and Forecasting (WRF) model, the horizontal grid resolution inevitably enters the realm of uncertainty known as the Terra Incognita. Within this region, conventional mesoscale Planetary Boundary Layer schemes fail to achieve the desired optimized outcomes following grid refinement. This study conducted a series of sensitivity analyses to explore the performance of the WRF model in simulating wind speed and direction at different spatial scales under various conditions. By comparing 10 min mean values for flat and complex terrains and then evaluating the performance of the model using statistical scoring. The results indicate that for wind resource assessment, the mesoscale boundary exceeds the height of the atmospheric boundary layer during the simulation period. For flat terrains, nesting is not recommended. Instead, nesting into Terra Incognita and microscale is preferred for complex terrains. The model demonstrates overall accuracy in wind direction estimation but tends to underestimate wind speed. Notably, the accuracy of simulations at 70 m above ground is higher than that at 10 m. The assessment of wind speed and direction exhibits distinct patterns across various wind speed ranges, wind direction, and atmospheric stabilities.

Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling

Abstract. Modeling ice sheet instabilities is a numerical challenge of potentially high real-world relevance. Yet, differentiating between the impacts of model physics, numerical implementation choices, and numerical errors is not straightforward. Here, we use an idealized North American geometry and climate representation (similarly to the HEINO (Heinrich Event INtercOmparison) experiments – Calov et al., 2010) to examine the process and numerical sensitivity of ice stream surge cycling in ice flow models. Through sensitivity tests, we identify some numerical requirements for a more robust model configuration for such contexts. To partly address model-specific dependencies, we use both the Glacial Systems Model (GSM) and the Parallel Ice Sheet Model (PISM). We show that modeled surge characteristics are resolution dependent, though they converge (decreased differences between resolutions) at finer horizontal grid resolutions. Discrepancies between fine and coarse horizontal grid resolutions can be reduced by incorporating sliding at sub-freezing temperatures. The inclusion of basal hydrology increases the ice volume lost during surges, whereas the dampening of basal-temperature changes due to a bed thermal model leads to a decrease.

Emulating lateral gravity wave propagation in a global chemistry–climate model (EMAC v2.55.2) through horizontal flux redistribution

Abstract. The columnar approach of gravity wave (GW) parameterisations in weather and climate models has been identified as a potential reason for dynamical biases in middle-atmospheric dynamics. For example, GW momentum flux (GWMF) discrepancies between models and observations at 60∘ S arising through the lack of horizontal orographic GW propagation are suspected to cause deficiencies in representing the Antarctic polar vortex. However, due to the decomposition of the model domains onto different computing tasks for parallelisation, communication between horizontal grid boxes is computationally extremely expensive, making horizontal propagation of GWs unfeasible for global chemistry–climate simulations. To overcome this issue, we present a simplified solution to approximate horizontal GW propagation through redistribution of the GWMF at one single altitude by means of tailor-made redistribution maps. To generate the global redistribution maps averaged for each grid box, we use a parameterisation describing orography as a set of mountain ridges with specified location, orientation and height combined with a ray-tracing model describing lateral propagation of so-generated mountain waves. In the global chemistry–climate model (CCM) EMAC (ECHAM MESSy Atmospheric Chemistry), these maps then allow us to redistribute the GW momentum flux horizontally at one level, obtaining an affordable overhead of computing resources. The results of our simulations show GWMF and drag patterns that are horizontally more spread out than with the purely columnar approach; GWs are now also present above the ocean and regions without mountains. In this paper, we provide a detailed description of how the redistribution maps are computed and how the GWMF redistribution is implemented in the CCM. Moreover, an analysis shows why 15 km is the ideal altitude for the redistribution. First results with the redistributed orographic GWMF provide clear evidence that the redistributed GW drag in the Southern Hemisphere has the potential to modify and improve Antarctic polar vortex dynamics, thereby paving the way for enhanced credibility of CCM simulations and projections of polar stratospheric ozone.

Tropical Transition of Tropical Storm Kirogi (2012) over the Western North Pacific: Synoptic Analysis and Mesoscale Simulation

Abstract Tropical transition (TT) is a cyclogenesis process in which a baroclinic disturbance is transformed into a tropical cyclone. Many studies have analyzed TT events over the North Atlantic. This study assesses TT processes from a possible subtropical cyclone to Tropical Storm Kirogi at a relatively high latitude over the western North Pacific in an environment of enhanced baroclinicity in August 2012. Analyses based on satellite observations, the JRA-55 reanalysis, and a simulation with 2.5-km horizontal grid spacing demonstrate three stages during the TT: the baroclinic, intermediate, and convective stages. Over the baroclinic stage, Kirogi had an asymmetric comma-shaped cloud pattern with convection in the northern and eastern parts of the cyclone. This convection is attributed to quasigeostrophic forcing and frontogenesis associated with advection of warm and moist air. Vorticity locally generated by this convection was advected to the cyclone center by cyclone-relative northerly flow. Kirogi also had a shallow warm-core structure due to the interaction with an upper-level cold trough extending from the midlatitudes. In the intermediate stage, the warm and moist air in the lower troposphere and the cold trough in the upper troposphere wrapped around Kirogi. In the convective stage, Kirogi attained characteristics of a typical tropical cyclone with convection concentrated near the cyclone center and a deep warm-core structure. These results demonstrate that baroclinic processes can directly trigger formation of a tropical storm at relatively high latitudes over the western North Pacific in a similar manner to that over the North Atlantic. Significance Statement Tropical cyclogenesis is an important process for early identification of tropical cyclone hazards. Tropical transition is a tropical cyclogenesis process that is triggered by a subtropical or extratropical disturbance. It is unique to relatively high latitudes and has social importance particularly for midlatitude countries. There have been fewer studies on tropical transition over the western North Pacific than over the North Atlantic. This study demonstrates the dynamics of a distinct tropical transition event that led to the formation of Tropical Storm Kirogi (2012) at a relatively high latitude over the western North Pacific.

The Downward Transport of Strong Wind by Convective Rolls in a Mediterranean Windstorm

Abstract The devastating winds in extratropical cyclones can be assigned to different mesoscale flows. How these strong winds are transported to the surface is discussed for the Mediterranean windstorm Adrian (Vaia), which caused extensive damage in Corsica in October 2018. A mesoscale analysis based on a kilometer-scale simulation with the Meso-NH model shows that the strongest winds come from a cold conveyor belt (CCB). The focus then shifts to a large-eddy simulation (LES) for which the strongest winds over the sea are located in a convective boundary layer. Convection is organized into coherent turbulent structures in the form of convective rolls. It is their downward branches that contribute most to the nonlocal transport of strong winds from the CCB to the surface layer. On landing, the convective rolls break up because of the complex topography of Corsica. Sensitivity experiments to horizontal grid spacing show similar organization of boundary layer rolls across the resolution. A comparative analysis of the kinetic energy spectra suggests that a grid spacing of 200 m is sufficient to represent the vertical transport of strong winds through convective rolls. Contrary to LES, convective rolls are not resolved in the kilometer-scale simulation and surface winds are overestimated due to excessive momentum transport. These results highlight the importance of convective rolls for the generation of surface wind gusts and the need to better represent them in boundary layer parameterizations.

Diagnosing Factors Leading to an Incorrect Supercell Thunderstorm Forecast

Abstract On 28 April 2019, hourly forecasts from the operational High-Resolution Rapid Refresh (HRRR) model consistently predicted an isolated supercell storm late in the day near Dodge City, Kansas, that subsequently was not observed. Two convection-allowing model (CAM) ensemble runs are created to explore the reasons for this forecast error and implications for severe weather forecasting. The 40-member CAM ensembles are run using the HRRR configuration of the WRF-ARW Model at 3-km horizontal grid spacing. The Gridpoint Statistical Interpolation (GSI)-based ensemble Kalman filter is used to assimilate observations every 15 min from 1500 to 1900 UTC, with resulting ensemble forecasts run out to 0000 UTC. One ensemble only assimilates conventional observations, and its forecasts strongly resemble the operational HRRR with all ensemble members predicting a supercell storm near Dodge City. In the second ensemble, conventional observations plus observations of WSR-88D radar clear-air radial velocities, WSR-88D diagnosed convective boundary layer height, and GOES-16 all-sky infrared brightness temperatures are assimilated to improve forecasts of the preconvective environment, and its forecasts have half of the members predicting supercells. Results further show that the magnitude of the low-level meridional water vapor flux in the moist tongue largely separates members with and without supercells, with water vapor flux differences of 12% leading to these different outcomes. Additional experiments that assimilate only radar or satellite observations show that both are important to predictions of the meridional water vapor flux. This analysis suggests that mesoscale environmental uncertainty remains a challenge that is difficult to overcome. Significance Statement Forecasts from operational numerical models are the foundation of weather forecasting. There are times when these models make forecasts that do not come true, such as 28 April 2019 when successive forecasts from the operational High-Resolution Rapid Refresh (HRRR) model predicted a supercell storm late in the day near Dodge City, Kansas, that subsequently was not observed. Reasons for this forecast error are explored using numerical experiments. Results suggest that relatively small changes to the prestorm environment led to large differences in the evolution of storms on this day. This result emphasizes the challenges to operational severe weather forecasting and the continued need for improved use of all available observations to better define the atmospheric state given to forecast models.

Microphysics affect the sensitivities of rainfall to different horizontal-resolution simulations: Evidence from a case study of the Weather Research and Forecasting model runs

The Weather Research and Forecasting (WRF) model was used to examine the sensitivities of Typhoon Fitow (2013) to the variations in horizontal mesh spacing ranging from 9 km to 1 km and to different microphysics schemes. The minimum sea level pressure decreased by 5 hPa and the maximum wind speeds increased by 20 m s−1 near the typhoon center as the horizontal grid spacing decreased from 9 km, 3 km, and 1 km in both Purdue-Lin and National Severe Storms Laboratory (NSSL) microphysics. The strengthening of the tropical cyclone may have been due to similar physical processes in the Purdue-Lin and NSSL simulations. Fine-resolution simulations produced localized and intense rainfall, in correspondence to localized and intense upward motions. Moreover, as the horizontal mesh spacing reduced from 9 km to 1 km, the distributions of the upward and downward motions broadened and the radar reflectivity bins with contour frequencies >10% increased. The simulated rainfall in the NSSL with a horizontal grid spacing below 3 km and in Purdue-Lin with a 1 km grid spacing reproduced spatial and temporal distributions similar to the actual observations. This suggested that the elaborate microphysics may compensate for the lack of horizontal resolution, to some extent. The precipitation budget analysis further suggested that the diminishment of rainfall was attributed to the reduced net condensation and hydrometeor convergence respectively in the Purdue-Lin and NSSL scheme as the mesh spacing reduced, which was further attributable to the decreased condensation or deposition.

Soil moisture precipitation feedbacks in the Eastern European Alpine region in convection-permitting climate simulations.

A novel convection permitting modelling framework that combines a pseudo-global warming approach with continuously forced deep soil moisture from prescribed perturbation storylines is applied in the Eastern European Alpine region and parts of the Pannonian Basin to investigate soil moisture precipitation (SMP) feedbacks on summertime precipitation and the feedbacks' role under changed climate conditions. A set of 1-year convection-permitting (3 km horizontal grid spacing) soil moisture sensitivity simulations with the regional climate model of the Consortium for Small-Scale Modelling in Climate Mode are conducted. In order to account for global warming, end-of-the-century climate change effects from four global climate models, projecting the greenhouse gas concentration scenario RCP 8.5, are imprinted. The simulations reveal that (1) the locations of precipitation events are highly sensitive to soil moisture modifications while intensities and the internal structure of precipitation events are nearly unaffected and (2) high precipitation intensities are more likely in combinations with positive temporal but distinctive (either strong positive or strong negative) spatial SMP coupling. Low precipitation intensities are in favour of combinations of negative temporal and positive spatial coupling. The analyses suggest that soil moisture at a given time acts as a guiding field for the location of the next precipitation event. Interestingly, this behaviour is independent of climate change, although the coupling strength's increase is 1.5-1.7 times larger than expected from linear climate change scaling when climate becomes 50% dryer. Finally, it is found that (1) local deviations in the climate change signal of summertime precipitation in the range of up to ±40% are caused by uncertainty in deep soil moisture in the range of ±10% and (2) these local deviations in the climate change signal are dominated by soil moisture uncertainty in future climate conditions.

Analysis of the Features of Water Circulation in the Northern Part of the Black Sea for Different Seasons on the Basis of the Results of Numerical Modeling with the Assimilation of the Data of Hydrological Surveys in 2016

The analysis of the dynamic and energy characteristics of water circulation in the northern part of the Black Sea was performed on the basis of the assimilation in the numerical model of the data of three hydrological surveys in 2016, carried out on expeditions of 87, 89 and 91 cruises of the R/V Professor Vodyanitsky (summer, autumn and autumn-winter seasons). Numerical experiments were implemented on a horizontal grid (~1.6 km × ~1.6 km) with 27 vertical horizons and an atmospheric effect close to the real one was used. A procedure of assimilation of the observational data was based on the Kalman filter, taking into account the heterogeneity and nonisotropy of the errors of the estimates of the temperature and salinity fields. The integral energy terms in the kinetic and potential energy budget equations for three seasons were estimated. In the summer season, there was a slight weakening of the RC and the main mechanism for the formation of anticyclonic eddies near Sevastopol and near the southeastern shores of Crimea was baroclinic instability of the current (as evidenced by the increase in the slope of isopycnical surfaces and negative values of the work of the buoyancy force). An anticyclonic eddy near Yalta with a radius of about 25 km was generated due to the development of shear instability of the current. In the autumn season, the RC jet was pressed to the shore and there was a decrease in the number of eddies in comparison to the summer season. The formation of anticyclonic eddies with a radius of about 35–40 km in the western part of the region was caused by barotropic instability of the current, the formation of eddies along the Crimean coast – by baroclinic instability. In the autumn-winter season, the RC had a pronounced jet character and there was an increase in the processes of baroclinic instability with the generation of eddies of different scales between the coast and the RC, as well as in the area, located between 31.5 and 33° E, with the weakening of the wind effect. During all seasons, small-scale anticyclonic and cyclonic eddies could be generated along the western and eastern coast of Crimea in the upper layer when current flowed around the coastline and inhomogeneities of the bottom topography under the action of weak winds.

Unravelling the mechanism of summer monsoon rainfall modes over the west coast of India using model simulations

AbstractA transition from a predominantly offshore to an onshore rainfall phase over the west coast of India was simulated using three one‐way nested domains with 12, 4, and 1.33 km horizontal grid spacing in the Weather Research and Forecasting model. The mechanism of offshore–onshore rainfall oscillation and the orographic effects of the Western Ghats are studied. A convective parametrization scheme was employed only in the 12 km domain. A trough extending offshore from the west coast facilitates offshore rainfall. This trough is absent during the onshore phase, and rainfall occurs over the coast mainly via orographic uplift by the Western Ghats. The model overestimates rainfall over the Western Ghats at all resolutions as it consistently underestimates the boundary‐layer stratification along the coast. Weaker stratification weakens the blocking effect of the Western Ghats, resulting in anomalous deep convection and rainfall over its windward slopes. The 4 and 1.33 km domains simulate the offshore‐to‐onshore transition of rainfall but fail to capture a sufficient contrast in rainfall between land and sea compared with observations. The 12 km domain produces light rainfall, anchored along the coast, throughout the simulation period and, hence, gravely underestimates the offshore rainfall. The offshore rainfall persisted in the 4 and 1.33 km domains in a sensitivity experiment in which the Western Ghats were flattened. This suggests that orographic effects do not significantly influence offshore rainfall. In another experiment, the convective parametrization scheme in the 12 km domain was turned off. This experiment simulated the offshore and onshore rainfall phases correctly to some extent but the rainfall intensity was unrealistically high. Thus, a model with a horizontal grid spacing of , in which convection evolves explicitly, is desired for simulating the west‐coast rainfall variations. However, improvements in the representation of boundary‐layer processes are needed to capture the land–sea contrast.