Variable-resolution Model Research Articles

Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3

Abstract. A historic rainstorm occurred over Henan, China, in July 2021 (“7.20” extreme precipitation event), resulting in significant human casualties and socioeconomic losses. A global variable-resolution model (MPAS-Atmosphere v7.3) was employed to simulate this extreme precipitation event. A series of simulations have been done at both quasi-uniform (60 and 15 km) and variable-resolution (60–15 and 60–3 km) meshes from hydrostatic to nonhydrostatic scale with two parameterization scheme suites. For the 48 h peak precipitation duration (20–22 July), the 60–3 km variable-resolution simulation coupled with the scale-aware convection-permitting parameterization scheme suite stands out predominantly among other simulation experiments as it reproduces this extreme precipitation event most accurately. At 15 km resolution, the 60–15 km variable-resolution simulation achieves comparable forecasting skills to the 15 km quasi-uniform simulation but at a much reduced computing cost. In addition, we found that the default mesoscale suite generally outperforms the convection-permitting suite at 15 km resolution as simulations coupled with the convection-permitting suite missed the third peak of this extreme precipitation event, while the mesoscale suite did not. Furthermore, it is found that the large-scale circulation plays a critical role in the peak precipitation simulations at 15 km resolution, via influencing the simulated low-level wind. During the second peak precipitation period, simulations with the convection-permitting parameterization scheme suite at 15 km resolution generate a prominent low-level easterly wind component bias, which is largely attributed to the excessively evaporative cooling in the lower troposphere. This study further reveals that at 15 km resolution the diabatic heating from the grid-scale precipitation accounts more for the low-level wind bias than the convective-scale precipitation. Given that two different cloud microphysics schemes, namely Thompson and WSM6 schemes, are used in the convection-permitting and default mesoscale parameterization scheme suites, respectively, these microphysics schemes are found to be the primary contributor to the low-level wind simulation bias.

Assessment of dynamical downscaling performance over cordex east Asia using MPAS-A global variable resolution model: climatology, seasonal cycle, and extreme events

Assessment of dynamical downscaling performance over cordex east Asia using MPAS-A global variable resolution model: climatology, seasonal cycle, and extreme events

Comparison of Met Office regional model soil moisture with COSMOS‐UK field‐scale in situ observations

AbstractThe UK Met Office state‐of‐the‐art, deterministic, convection‐permitting, coupled land‐atmosphere, regional weather forecasting system, known as the UKV or UK Variable resolution model (Tang et al. Meteorological Applications, 2013; 20:417–426), has been operational since 2015. Science updates are regularly made to the UKV land surface data assimilation scheme when those updates improve predictions of screen temperature and humidity, since these quantities have a direct impact on atmospheric states and weather forecasts. Less attention has been paid to whether UKV soil moisture analyses are close to independent, in‐situ soil moisture observations, partly because it is difficult to make meaningful comparisons between 1.5 km2 gridded model outputs and traditional point sensor measurements. Soil moisture is recognized to be important when hydrological forecasts for runoff and rivers are required. This is because soil moisture controls the extent to which rainfall can infiltrate the soil, and the amount of surface runoff affects the timing of peak river flows (Ward & Robinson, Principles of Hydrology. McGraw‐Hill Publishing Company; 2000; Singh et al. Water Resources Research, 2021, 57, e2020WR028827). Gómez et al. (Remote Sensing, 2020; 12:3691) report benefits to river flow forecasts when using soil moisture data assimilation in the UKV system instead of a daily downscaled product from the Met Office global model. The Met Office measures soil temperature and soil moisture at Cardington (Osborne & Weedon, Journal of Hydrometeorology, 2021, 22:279–295); there is no other UK Met Office site at which soil moisture is measured. In this study, we use field‐scale (~200 m radius) soil moisture measurements from the UK Centre for Ecology and Hydrology's (UKCEH's) COSMOS‐UK network to provide independent verification and analysis of UKV soil moisture during summer 2018, an unusually dry period in the United Kingdom. We find that the match to COSMOS‐UK soil moisture observations is generally good, and that changes made to the land data assimilation approach during a recent operational upgrade had a generally beneficial impact on UKV soil moisture analyses under very dry conditions.

Technical descriptions of the experimental dynamical downscaling simulations over North America by the CAM–MPAS variable-resolution model

Abstract. Comprehensive assessment of climate datasets is important for communicating model projections and associated uncertainties to stakeholders. Uncertainties can arise not only from assumptions and biases within the model but also from external factors such as computational constraint and data processing. To understand sources of uncertainties in global variable-resolution (VR) dynamical downscaling, we produced a regional climate dataset using the Model for Prediction Across Scales (MPAS; dynamical core version 4.0) coupled to the Community Atmosphere Model (CAM; version 5.4), which we refer to as CAM–MPAS hereafter. This document provides technical details of the model configuration, simulations, computational requirements, post-processing, and data archive of the experimental CAM–MPAS downscaling data. The CAM–MPAS model is configured with VR meshes featuring higher resolutions over North America as well as quasi-uniform-resolution meshes across the globe. The dataset includes multiple uniform- (240 and 120 km) and variable-resolution (50–200, 25–100, and 12–46 km) simulations for both the present-day (1990–2010) and future (2080–2100) periods, closely following the protocol of the North American Coordinated Regional Climate Downscaling Experiment. A deviation from the protocol is the pseudo-warming experiment for the future period, using the ocean boundary conditions produced by adding the sea surface temperature and sea-ice changes from the low-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-LR) in the Coupled Model Intercomparison Project Phase 5 to the present-day ocean state from a reanalysis product. Some unique aspects of global VR models are evaluated to provide background knowledge to data users and to explore good practices for modelers who use VR models for regional downscaling. In the coarse-resolution domain, strong resolution sensitivity of the hydrological cycles exists over the tropics but does not appear to affect the midlatitude circulations in the Northern Hemisphere, including the downscaling target of North America. The pseudo-warming experiment leads to similar responses of large-scale circulations to the imposed radiative and boundary forcings in the CAM–MPAS and MPI-ESM-LR models, but their climatological states in the historical period differ over various regions, including North America. Such differences are carried to the future period, suggesting the importance of the base state climatology. Within the refined domain, precipitation statistics improve with higher resolutions, and such statistical inference is verified to be negligibly influenced by horizontal remapping during post-processing. Limited (≈50 % slower) throughput of the current code is found on a recent many-core/wide-vector high-performance computing system, which limits the lengths of the 12–46 km simulations and indirectly affects sampling uncertainty. Our experience shows that global and technical aspects of the VR downscaling framework require further investigations to reduce uncertainties for regional climate projection.

Strong surface winds in Storm Eunice. Part 1: storm overview and indications of sting jet activity from observations and model data

Strong surface winds in Storm <i>Eunice</i>. Part 1: storm overview and indications of sting jet activity from observations and model data

Dynamic and thermodynamic processes related to precipitation diurnal cycle simulated by GRIST

Most state-of-the-art general circulation models cannot well simulate the diurnal cycle of precipitation, especially the nocturnal rainfall peak over land. This study assesses the diurnal cycle of precipitation simulated using the Global-to-Regional Integrated forecast SysTem (GRIST) in its numerical weather prediction (NWP) configuration at resolutions typical of current global climate models. In the refinement region, the variable-resolution model well distinguishes the distinct features of diurnal cycle. No apparent artificial features are observed in the transition zone of the variable-resolution mesh. The model also exhibits a similar diurnal cycle pattern to the observation in the coarse-resolution region. We further investigate the model behaviors of dynamics–physics interaction by analyzing hourly dynamical and thermodynamical diagnostics. Composite analysis based on rainfall peak time is applied to examine the model capability in distinguishing different precipitation processes of daytime and nighttime peaks. Over East Asia, the model well reproduces both the nocturnal-to-early-morning and the afternoon rainfall peaks. The model simulates the dominant contribution of large-scale upward moisture advection to the formation of stratiform-like rainfall peaks, and produces daytime surface-heating induced rainfall. Refinement of the resolution substantially increases the composited nighttime precipitation intensity but has little impact on the composite percentage. The model captures the realistic dynamical and thermodynamical conditions for the occurrence of nocturnal rainfall. These results demonstrate that the variable-resolution model is able to reproduce the diurnal cycle of climatological summer rainfall through realistic precipitation processes.

Improved-Efficacy EM-Driven Optimization of Antenna Structures Using Adaptive Design Specifications and Variable-Resolution Models

Optimization-driven parameter tuning is an essential step in the design of antenna systems. Although in many cases, it is still conducted through parametric studies, rigorous numerical methods become a necessity if truly optimum designs are sought for, and the problem intricacies (number of variables, multiple goals, and constraints) make the interactive approaches insufficient. The two practical considerations of electromagnetic (EM)-driven optimization are reliability and computational cost. Repetitive EM simulations may incur unmanageable expenses, whereas the lack of a decent starting point or objective function multimodality may prevent the numerical procedures (especially the local ones) from identifying satisfactory designs. In pursuit of reliability improvements, a design specification adjustment procedure has been recently proposed that improves the immunity of local search procedures to poor starting points, where the objective function is modified by relocating the design goals (e.g., center frequencies) closer to the actual operating parameters of the antenna at the current design, to make them attainable through local search. The goals are then gradually adjusted and converged to the original targets toward the end of the optimization process. In this article, we introduce an algorithm for reliable and low-cost antenna tuning that capitalizes on the specification management scheme while embedding it in variable-resolution optimization framework. In our approach, the EM model fidelity is adaptively adjusted based on the misalignment between the actual and target operating conditions, as well as the convergence status of the algorithm. By initiating the search process from the lowest fidelity model (gradually dialed up to the highest fidelity one), considerable computational savings of almost 60% can be achieved, with respect to the single-fidelity procedure. The speedup is possible without compromising reliability of the optimization process, as demonstrated using three examples of microstrip antennas, designed under different and challenging scenarios.

Impact Analysis of Variable Resolution of MPAS on Intrinsic Predictability Using Bred Vectors

Variable resolution configuration is a defining feature of the NCAR MPAS (Model for Prediction Across Scales) model, which allows us to smoothly vary the horizontal resolution for taking a closer look at an area of interest. In this study, we aimed to analyze the impact of variable resolution on intrinsic predictability using bred vectors. Thus, the breeding cycles of the MPAS model with and without variable resolution configuration were implemented and tested with two different rescaling intervals of 6 h and 1 day. Rescaling within our breeding cycles were centered by the nature run, thus we could deal with the intrinsic predictability limited only by the initial error growth. We confirmed reasonable estimates of fast-growing errors by bred vectors at two different scales of convective and synoptic systems. We then found that the variable resolution configuration gave consistent improvement of intrinsic predictability not only over the high-resolution area but also outside. A quantitative analysis showed that an improvement with the variable resolution could be found in general for most vertical levels for both rescaling interval experiments. Additionally, we present the computational cost and experience of performing the variable resolution model which would help users in their decisions on this setting.

Impacts of Topographic Complexity on Modeling Moisture Transport and Precipitation over the Tibetan Plateau in Summer

The non-hydrostatic global variable resolution model (MPAS-atmosphere) is used to conduct the simulations for the South Asian Summer monsoon season (June, July, and August) in 2015 with a refinement over the Tibetan Plateau (TP) at the convection-permitting scale (4 km). Two experiments with different topographical datasets, complex (4-km) and smooth (60-km) topography, are designed to investigate the impacts of topographical complexity on moisture transport and precipitation. Compared with the observations and reanalysis data, the simulation can successfully capture the general features of key meteorological fields over the TP despite slightly underestimating the inflow through the southern TP. The results indicate that the complex topography can decrease the inward and outward moisture transport, ultimately increasing the total net moisture transport into the TP by ∼11%. The impacts of complex topography on precipitation are negligible over the TP, but the spatial distributions of precipitation over the Himalayas are significantly modulated. With the inclusion of complex topography, the sharper southern slopes of the Himalayas shift the lifted airflow and hence precipitation northward compared to the smooth topography. In addition, more small-scale valleys are resolved by the inclusion of complex topography, which serve as channels for moisture transport across the Himalayas, further favoring a northward shift of precipitation. Overall, the difference between the two experiments with different topography datasets is mainly attributed to their differing representation of the degree of the southern slopes of the Himalayas and the extent to which the valleys are resolved.

Response of Temperature-Related Rice Disaster to Different Warming Levels Under an RCP8.5 Emission Scenario in a Major Rice Production Region of China

Rice is the basic food for about 50% of the global population, and feeds two-thirds of the Chinese population. Under the influence of global change, extreme weather, and climate events increase in frequency, duration, and intensity, which affect food production substantially. In the medium-to-long term in the future, the impacts of climate change on food availability are likely to grow. In this work, we first define the rice damage indices and then use surface observation and regional climate downscaling results from the variable resolution model LMDZ4 driven by the six Coupled Model Intercomparison Project phase 5 (CMIP5) global climate models (GCMs) to describe the temporal-spatial characteristics and the future changes of the temperature-related rice damages in Northeast China and Central and East China, the major commercial rice production regions in China. Compared with the observation, LMDZ4 demonstrates its ability to reproduce the regional characteristics of both heat and chilling rice damages. Based on the future regional projections under the RCP8.5 pathway, future changes of rice damage under four temperature-rising categories of 1.5, 2, 3, and 4°C are estimated. In the two rice production regions, the future extent of heat-related damage for Northeast China is mostly limited to the western area, and the occurrence of heat damage generally increases with global warming levels, particularly when it is higher than 2°C. For Central and East China, the heat-related rice damage increases in both coverage and intensity. The region is also likely to have a faster increasing rate of heat damage than in Northeast China. When global warming reaches 3 and 4°C, the median heat-related damage spreads over almost the whole region of Central and East China. Moreover, the probability of regional-scale heavy level heat damage would be over 50% by the end of twenty-first century. On the other hand, the disastrous impact of a cold event affecting rice yield is reduced in both coverage and duration although the model projections over Northeast China show larger intermodel variability and uncertainty.

Evaluation of a Prototype Broadband Water-Vapour Profiling Differential Absorption Lidar at Cardington, UK

For a one-month period in summer 2020, a prototype Vaisala broadband differential absorption lidar (BB-DIAL) was deployed at a Met Office research site. It was compared with in-situ observations of humidity (93 radiosonde ascents and 27 of uncrewed aerial vehicle flights) and the Met Office 1.5 km resolution numerical weather prediction (NWP) model: UK Variable resolution model (UKV). The BB-DIAL was able to collect data up to the cloud base, in all-weather situations including rain, when it was possible to reach 3 km. The average maximum height was 1300 m, with 75% of the data reaching 1000 m and 35% extending to 1500 m. Compared with radiosondes, the standard deviation for the water vapour is between 5% and 10%. The comparison with the UKV is very encouraging, with a correlation of 0.90. The error against the radiosonde is smaller than against the UKV, which is encouraging for assimilation the BB-DIAL data in UKV. Some data quality issues, such as an increase in error and variable bias in the region of overlap between the far field and close field, spurious oscillations and an unrealistic dry layer above fog are identified. Despite these issues, the overall results from this assessment are promising in terms of potential benefit, instrument reliability and capturing significant humidity changes in the boundary layer.

On the Momentum Flux of Vertically-Propagating Orographic Gravity Waves Excited in Nonhydrostatic Flow over Three-dimensional Orography

AbstractThis work studies nonhydrostatic effects (NHE) on the momentum flux of orographic gravity waves (OGWs) forced by isolated three-dimensional orography. Based on linear wave theory, an asymptotic expression for low horizonal Froude number ( where (U, V) is the mean horizontal wind, γ and a are the orography anisotropy and half-width and N is the buoyancy frequency) is derived for the gravity wave momentum flux (GWMF) of vertically-propagating waves. According to this asymptotic solution, which is quite accurate for any value of Fr, NHE can be divided into two terms (NHE1 and NHE2). The first term contains the high-frequency parts of the wave spectrum that are often mistaken as hydrostatic waves, and only depends on Fr. The second term arises from the difference between the dispersion relationships of hydrostatic and nonhydrostatic OGWs. Having an additional dependency on the horizontal wind direction and orography anisotropy, this term can change the GWMF direction. Examination of NHE for OGWs forced by both circular and elliptical orography reveals that the GWMF is reduced as Fr increases, at a faster rate than for two-dimensional OGWs forced by a ridge. At low Fr, the GWMF reduction is mostly attributed to the NHE2 term, whereas the NHE1 term starts to dominate above about Fr = 0.4. The behavior of NHE is mainly determined by Fr, while horizontal wind direction and orography anisotropy play a minor role. Implications of the asymptotic GWMF expression for the parameterization of nonhydrostatic OGWs in high-resolution and/or variable-resolution models are discussed.

Configuration and evaluation of a global unstructured mesh atmospheric model (GRIST-A20.9) based on the variable-resolution approach

Abstract. Targeting a long-term effort towards a variable-resolution (VR) global weather and climate model, this study systematically configures and evaluates an unstructured mesh atmospheric model based on the multiresolution approach. The model performance is examined from dry dynamics to simple physics and full physics scenarios. In the dry baroclinic wave test, the VR model reproduces comparable fine-scale structures in the refined regions as a fine-resolution quasi-uniform (QU) mesh model. The mesh transition zone does not adversely affect the wave pattern. Regional kinetic energy spectra show that the fine-scale resolving ability improves as the fine resolution increases. Compared to a QU counterpart that has equivalent degrees of freedom, the VR model tends to increase the global errors, but the errors can be reduced when the resolution of the coarse region is increased. The performance over the coarse region is generally close to that of a low-resolution QU counterpart. Two multi-region refinement approaches, the hierarchical and polycentric refinement modes, further validate the model performance under the multiresolution refinement. Activating hyperdiffusion for horizontal velocity is helpful with respect to VR modeling. An idealized tropical cyclone test is further used to examine its ability to resolve fine-scale structures. In the simple physics environment, the VR model can have the tropical cyclone stably pass the transition zone in various configurations. A series of sensitivity tests examines the model performance in a hierarchical refinement mode. The simulations exhibit consistency even when the VR mesh is slightly perturbed by one of the three parameters that control the density function. The tropical cyclone, starting from the second refinement region and passing through the inner transition zone, gets intensified and covers a smaller area in the refined regions. Such variations are consistent with the behavior that one may observe when uniformly refining the QU mesh. In the full physics environment with a highly variable mesh that reaches sub-10 km resolution, the VR model also produces a reasonable evolution for the tropical cyclone. The explicit diffusion shows its usefulness in terms of suppressing some unrealistic isolated-scale structures that are far away from the initial vortex and does not adversely affect the physically important object. The fine-scale structure is determined mainly by the fine-resolution area, although the systems may have larger differences before they move into the fine-resolution area. Altogether, this work demonstrates that the multiresolution configuration is a reliable and economic alternative to high-resolution global modeling. The adverse impact due to mesh transition and the coarse region can be controlled well.

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the United States

AbstractA process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the United States. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation features at 12-, 25-, and 50-km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency, and intensity are found to be consistently underestimated in the central United States, particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while the MCS precipitation area is too large and its intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during the daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

Toward Convective-Scale Prediction within the Next Generation Global Prediction System

AbstractThe 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.

Influences of Large-Scale Flow Variations on the Track Evolution of Typhoons Morakot (2009) and Megi (2010): Simulations with a Global Variable-Resolution Model

AbstractInfluences of large-scale flow variations on the track evolution of two typhoons, moderate Morakot (2009) and superintense Megi (2010), are investigated using the global variable-resolution model MPAS with a higher-resolution region of 15 km for the simulated typhoons. For Morakot, the associated track and extreme rainfall over southern Taiwan captured by MPAS compared well with the regional WRF simulations. To isolate the influences of various large-scale flows, three modes are filtered out from global reanalysis: the synoptic-scale mode, quasi-biweekly oscillation (QBW) mode, and the Madden–Julian oscillation (MJO) mode. In the absence of QBW or MJO, the simulated Morakot moves westward across Taiwan without the observed north turn after landfall. When the intensity of the MJO mode is increased by 50% in the experiment (MJO+50%), a much earlier northward turn is induced. The simulated Morakot under the observed MJO lies in between MJO+50% and MJO−50% results. The MJO variations also show similar impacts on the track evolution of Typhoon Megi.The wavenumber-1 decompositions of vorticity budget terms are shown to highlight important contributions to the vorticity tendency and typhoon translation with and without the MJO. The northward turn of both typhoons in the presence of the MJO is mainly in response to positive horizontal vorticity advection to the north of the typhoon center. However, vorticity tilting is relatively more important for Morakot due to its slantwise structure. Furthermore, positive vorticity stretching and vertical advection are significant in the vicinity of southern Taiwan due to the effects of the Central Mountain Range and tend to retard the departing Morakot.

Mountain Waves in High Resolution Forecast Models: Automated Diagnostics of Wave Severity and Impact on Surface Winds

An automated method producing a diagnostic of the severity of lee waves and their impacts on surface winds as represented in output from a high resolution linear numerical model (3D velocities over mountains (3DVOM)) covering several areas of the U.K. is discussed. Lee waves involving turbulent rotor activity or downslope windstorms represent a hazard to aviation and ground transport, and summary information of this kind is highly valuable as an efficient ‘heads-up’ for forecasters, for automated products or to feed into impact models. Automated diagnosis of lee wave surface effects presents a particular challenge due to the complexity of turbulent zones in the lee of irregular terrain. The method proposed quantifies modelled wind perturbations relative to those that would occur in the absence of lee waves for a given background wind, and diagnoses using it are found to be quite consistent between cases and for different ranges of U.K. hills. A recent upgrade of the operational U.K. limited area model, the U.K. Variable Resolution Model (UKV) used for general forecasting at the Met Office means that it now resolves lee waves, and its performance is here demonstrated using comparisons with aircraft- and surface-based observations and the linear model. In the future, automated diagnostics may be adapted to use its output to routinely produce contiguous mesoscale maps of lee wave activity and surface impacts over the whole U.K.

A Technique for Verification of Convection-Permitting NWP Model Deterministic Forecasts of Lightning Activity

Abstract This manuscript introduces a new technique for evaluating lightning forecasts from convection-permitting models. In recent years, numerical weather prediction models at the convection-permitting scales (horizontal grid resolutions of 1–5 km) have been able to produce realistic-looking forecasts of lightning activity when compared with observations. However, it is challenging to assess what value these forecasts add above standard large-scale indices. Examining this problem, it is found that existing skill scores and neighborhood verification methods are unable to cope with both the double-penalty effect and the model’s variable frequency bias. A displacement distance and a quasi-symmetric distance score are introduced based on the distance between the model and the observations, the latter showing any improvement the forecast has over a completely “hedged” forecast. This can be combined with a domain-improved contingency table and comparisons between modeled and observed lightning flashes to evaluate the forecast performance in three important dimensions: coverage, distance, and intensity. The verification metric is illustrated with a single case, which shows that the convective-scale U.K. variable resolution model (UKV) delivers improved forecasts compared with the large-scale indices in both coverage and distance. Additionally, a month-long analysis is performed, which reveals that the coverage of lightning is in good agreement with the observations; lightning is displaced by the model by a distance on the order of 50–75 km, but the model overpredicts the lightning intensity by at least a factor of 6 after observational detection efficiencies have been considered.

Biases and improvements in three dynamical downscaling climate simulations over China

A dynamical downscaling is performed to improve the regional climate simulation in China. It consists of using a variable resolution model LMDZ4 nested into three global climate models (GCMs): BCC-csm1-1-m, FGOALS-g2 and IPSL-CM5A-MR, respectively. The regional climate from different simulations is assessed in terms of surface air temperature and rainfalls through a comparison to observations (both station data and gridded data). The comparison includes climatic trends during the last 40 years, statistical distribution of sub-regional climate, and the seasonal cycle. For surface air temperature, a significant part of the improvement provided by LMDZ4 is related to the effect of surface elevation which is more realistic in high-resolution simulations; the rest is related to changes in regional or local atmospheric general circulation. All GCMs and the downscaling model LMDZ4 are, more or less, able to describe the spatial distribution of surface air temperature and precipitation in China. LMDZ4 does show its superiority, compared to GCMs, in depicting a good regional terrain including the Tibetan Plateau, the Sichuan Basin and the Qilian Mountains.

Moist Process Biases in Simulations of the Madden–Julian Oscillation Episodes Observed during the AMIE/DYNAMO Field Campaign

Abstract Two Madden–Julian oscillation (MJO) episodes observed during the 2011 Atmospheric Radiation Measurement Program MJO Investigation Experiment (AMIE)/DYNAMO field campaign are simulated using a regional model with various cumulus parameterizations, a regional cloud-permitting model, and a global variable-resolution model with a high-resolution region centered over the tropical Indian Ocean. Model biases in relationships relevant to existing instability theories of MJO are examined and their relative contributions to the overall model errors are quantified using a linear statistical model. The model simulations capture the observed approximately log-linear relationship between moisture saturation fraction and precipitation, but precipitation associated with the given saturation fraction is overestimated especially at low saturation fraction values. This bias is a major contributor to the excessive precipitation during the suppressed phase of MJO. After accounting for this bias using a linear statistical model, the spatial and temporal structures of the model-simulated MJO episodes are much improved, and what remains of the biases is strongly correlated with biases in saturation fraction. The excess precipitation bias during the suppressed phase of the MJO episodes is accompanied by excessive column-integrated radiative forcing and surface evaporation. A large portion of the bias in evaporation is related to biases in wind speed, which are correlated with those of precipitation. These findings suggest that the precipitation bias sustains itself at least partly by cloud radiative feedbacks and convection–surface wind interactions.