Convection-permitting Model Research Articles

A Bibliometric Analysis of Convection-Permitting Model Research

Convection-permitting models (CPMs) are receiving growing scientific interest for their capability to accurately simulate extreme weather events at a kilometer-scale spatial resolution, offering valuable information for local climate change adaptation. This study employs both qualitative and quantitative bibliometric analysis techniques to examine research trends in CPM, utilizing data from 3,508 articles published between 2000 and 2023. The annual number of publications exhibits a linear increase, rising from fewer than 50 in 2000 to over 250 after 2020, with the majority of research originating from the US, China, the UK, and Germany. The most productive institutes include the National Oceanic Atmospheric Administration (NOAA) and the National Center for Atmospheric Research (NCAR) in the US, each contributing over 10% of total publications. Title and abstract terms in publications related to keywords such as ”scenario”, ”climate simulation”, etc., dominate publications from 2018 to 2023, coinciding with advances in computing power. Notably, terms associated with CPM physical processes received the highest citations from 2000 to 2023, underscoring the importance of such these research topics. Given the computational expense of running CPMs and the increasing demand for future predictions using CPMs, novel methods for generating long-term simulations are imperative.

Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations

Extreme rainfall events trigger natural hazards, including floods and debris flows, posing serious threats to society and the economy. Accurately quantifying extreme rainfall return levels in ungauged locations is crucial for improving flood protection infrastructure and mitigating water-related risks. This paper quantifies the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. We assess the performance of CPM-informed estimates of extreme return level against a traditional interpolation techniques. We find that kriging methods with external drift outperform inverse distance weighting for both traditional and CPM-informed approaches. We then assess the effectiveness of the two methods under different scenarios of station density. At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 h. The performance becomes comparable between 6 and 24 h. For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, with average reductions in fractional standard error of 24 %, 13 %, and 8 % for return periods of 2, 10 and 50 years, respectively for a rain gauge density of 1/800 km², and 16 %, 8 %, and 3 % for density of 1/400 km². Information from CPM simulations can thus be useful for estimating sub-daily extreme rainfall events in ungauged sites, particularly in data-scarce areas in which the density of rain gauges is low.

The crucial representation of deep convection for the cyclogenesis of Medicane Ianos

Abstract. This paper presents a model intercomparison study to improve the prediction and understanding of Mediterranean cyclone dynamics. It is based on a collective effort with five mesoscale models to look for a robust response among 10 numerical frameworks used in the community involved in the networking activity of the EU COST Action “MedCyclones”. The obtained multi-model, multi-physics ensemble is applied to the high-impact Medicane Ianos of September 2020 with a focus on the cyclogenesis phase, which was poorly forecast by numerical weather prediction systems. Models systematically perform better when initialised from operational IFS analysis data compared to the widely used ERA5 reanalysis. Reducing horizontal grid spacing from 10 km with parameterised convection to convection-permitting 2 km further improves the cyclone track and intensity. This highlights the critical role of deep convection during the early development stage. Higher resolution enhances convective activity, which improves the phasing of the cyclone with an upper-level jet and its subsequent intensification and evolution. This upscale impact of convection matches a conceptual model of upscale error growth in the midlatitudes, while it emphasises the crucial interplay between convective and baroclinic processes during medicane cyclogenesis. The 10 numerical frameworks show robust agreement but also reveal model specifics that should be taken into consideration, such as the need for a parameterisation of deep convection even at 2 km horizontal grid spacing in some models. While they require generalisation to other cases of Mediterranean cyclones, the results provide guidance for the next generation of global convection-permitting models in weather and climate.

Characteristics of Precipitation and Mesoscale Convective Systems Over the Peruvian Central Andes in Multi 5‐Year Convection‐Permitting Simulations

AbstractUsing the Weather Research and Forecasting model with two planetary boundary layer schemes, ACM2 and MYNN, convection‐permitting model (CPM) regional climate simulations were conducted for a 6‐year period, including a one‐year spin‐up period, at a 15‐km grid spacing covering entire South America and a nested convection‐permitting 3‐km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4‐km simulation covering South America produced by National Center for Atmospheric Research (NCAR), three gridded precipitation products, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and mesoscale convective systems (MCSs) in the Peruvian central Andes region. Results show that all km‐scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3‐km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4‐km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low‐level jet and terrain‐induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests model improvements and better model configurations for future regional climate projections.

Responses of summer mesoscale convective systems to irrigation over the North China Plain based on convection-permitting model simulations

Extensive irrigation activities in the North China Plain (NCP) significantly influence regional weather and climate. However, previous studies focusing on the NCP were primarily based on coarse-resolution models, which are unable to explicitly resolve convection systems, causing large uncertainty in precipitation simulations. In this study, a convection-permitting model coupled with a dynamic irrigation scheme is utilized to investigate the impacts of irrigation on summertime mesoscale convective systems (MCSs) over the NCP. Sensitivity experiments with irrigation off and on are conducted for 5 summers and an MCS identification and tracking algorithm is applied to both satellite observations and model simulations. We find that incorporating irrigation in the model increases MCS precipitation, which agrees more with observations. The probability distributions of MCS lifetime, area, propagation speed, and intensity are all better simulated with irrigation. Irrigation increases the occurrence frequency of MCSs throughout the entire day. The nighttime increase is partly because of more frequent local initiation of MCS developed from isolated deep convection, while the daytime increase is mainly attributed to the changes in MCSs initiating elsewhere and then propagating to the NCP. On average, irrigation induces additional moisture that is more thermodynamically favorable for precipitation, but this effect is partially offset by the weakened ascending air motion primarily caused by irrigation surface cooling. Compared to weak MCS precipitation events, strong MCS precipitation events experience greater enhancement in precipitation intensity when including irrigation because the offset effect from the change in large-scale ascending air motion is insignificant. In addition, irrigation makes the variation of MCS precipitation intensity more correlated with the variation in ascending motion but less correlated with that in atmospheric moisture. Our results suggest the pronounced impacts of irrigation on MCSs over the NCP which should be included in numerical models to improve regional precipitation simulation and prediction.

Tropical Cyclone Boundary Layer Asymmetries in a Tilt-Following Perspective

Abstract Previous observations and modeling studies showed that tropical cyclones (TCs) in a sheared environment develop an asymmetric boundary layer (BL). While the relationship between the BL asymmetries and environmental shear has been demonstrated, the exact cause of these BL asymmetries and the phase relationship between them are less well understood. In this study, we examine the dynamical processes leading to the asymmetric structure of the TC BL in a sheared environment using idealized, convection-permitting model simulations. Our results show that the emergence of the BL asymmetries is closely linked to the TC vortex tilt and rainband processes. Specifically, stratiform diabatic processes in the downtilt-left region result in midlevel descending inflow, which brings midtropospheric, low-θE air toward the BL and forms a surface cold pool in the downtilt-left quadrant. This descending inflow also advects high absolute angular momentum inward, redistributing the vertical vorticity and causing a storm-scale tangential wind acceleration within the downtilt-left quadrant. As the BL low-θE air advances inward, it becomes supergradient and decelerates radially, forming BL outflow in the uptilt-left quadrant. The outflow advects positive relative vorticity uptilt, forming an elliptic BL vorticity and circulation structure. As the tilted TC vortex and the accompanying rainband precess cyclonically over time, the above sequence of events and the resultant BL asymmetries also precess cyclonically, maintaining a quasi-stationary configuration relative to the vortex tilt. These results suggest that the primary organizing factor of the boundary layer asymmetries is the tilted vortex structure and not strictly the environmental shear direction.

Global convection-permitting model improves subseasonal forecast of plum rain around Japan

Abstract In 2020 early summer, a historically severe rainy season struck East Asia, causing extensive damage to life and property. Subseasonal forecast of this event challenges the limits of rainy season predictability. Employing the integrated Atmospheric Model Across Scales (iAMAS) and the Sunway supercomputer, we conducted ensemble one-month forecasts at global 3 km, variable 4-60 km, and global 60 km resolutions. The global convection-permitting forecast accurately captures the rainband, while other forecasts exhibited northward and weaker shifts due to the northward shifts of the atmospheric rivers (ARs) over Japan, attributed to intensified Western North Pacific Subtropical High (WNPSH). Further, the double-ITCZ-like tropical rainfall pattern in Western Pacific (D-ITCZ-WP) in global convection-permitting forecast contributes to a more accurate WNPSH and rainband. In contrast, other forecasts show a single-ITCZ-like pattern in Western Pacific (S-ITCZ-WP), leading to a northward-shifted WNPSH and rainband, advocating the importance of accurately representing tropical convections, as they can significantly affect mid-/high-latitude weather and climate.

Rainfall Sensitivity to Microphysics and Planetary Boundary Layer Parameterizations in Convection-Permitting Simulations over Northwestern South America

Convection-permitting modeling allows us to understand mechanisms that influence rainfall in specific regions. However, microphysics parameterization (MP) and planetary boundary layer (PBL) schemes remain an important source of uncertainty, affecting rainfall intensity, occurrence, duration, and propagation. Here, we study the sensitivity of rainfall to three MP [Weather Research and Forecasting (WRF) Single-Moment 6-class (WSM6), Thompson, and Morrison] and two PBL [the Yonsei University (YSU) and Mellor–Yamada Nakanishi Niino (MYNN)] schemes with a convection-permitting resolution (4 km) over northwestern South America (NWSA). Simulations were performed by using the WRF model and the results were evaluated against soundings, rain gauges, and satellite data, considering the spatio-temporal variability of rainfall over diverse regions prone to deep convection in NWSA. MP and PBL schemes largely influenced simulated rainfall, with better results for the less computationally expensive WSM6 MP and YSU PBL schemes. Regarding rain gauges and satellite estimates, simulations with Morrison MP overestimated rainfall, especially westward of the Andes, whereas the MYNN PBL underestimated precipitation in the Amazon–Savannas flatlands. We found that the uncertainty in the rainfall representation is highly dependent on the region, with a higher influence of MP in the Colombian Pacific and PBL in the Amazon–Savannas flatlands. When analyzing rainfall-related processes, the selection of both MP and PBL parameterizations exerted a large influence on the simulated lower tropospheric moisture flux and moisture convergence. PBL schemes significantly influenced the downward shortwave radiation, with MYNN simulating a greater amount of low clouds, which decreased the radiation income. Furthermore, latent heat fluxes were greater for YSU, favoring moist convection and rainfall. MP schemes had a marked impact on vertical velocity. Specifically, Morrison MP showed stronger convection and higher precipitation rates, which is associated with a greater latent heat release due to solid-phase hydrometeor formation. This study provides insights into assessing physical parameterizations in numerical models and suggests key processes for rainfall representation in NWSA.

Realistic Precipitation Diurnal Cycle in Global Convection‐Permitting Models by Resolving Mesoscale Convective Systems

AbstractAccurately representing the precipitation diurnal cycle has long been a challenge for global climate models (GCMs). Here we evaluate the precipitation diurnal cycle in the DYAMOND global convection‐permitting models (CPMs) and CMIP6 HighResMIP models. Comparison of the high‐ (25–50 km) and low‐resolution (100–250 km) models with parameterized convection in HighResMIP shows that simply increasing model resolution does not noticeably improve the precipitation diurnal cycle. In contrast, CPMs can better capture the observed amplitude and timing of precipitation diurnal cycle. However, the simulated spatial variation of timing in CPMs is smaller than observed, leading to an exaggeration of the spatially averaged diurnal amplitude. The better‐simulated precipitation diurnal cycle in the CPMs is tied to mesoscale convective systems (MCSs), which contribute about half of the total precipitation. The observed life cycle of MCSs, including initiation and mature stages, is well captured in the CPMs, leading to a more realistic precipitation diurnal cycle.

Western Europe’s extreme July 2019 heatwave in a warmer world

Summertime heatwaves are extreme events with a large societal impact. Intensity, duration and spatial extent, all heatwave properties are projected to increase in a warming world, implying that summers that qualified as extreme in the past will become increasingly normal. In this paper we quantify how the changes play out for the July 2019 European heatwave that shattered temperature records throughout Western Europe. We combine a storyline approach with ensemble Pseudo Global Warming (PGW) and high-resolution dynamical downscaling. The downscaling is done with a regional climate model (RACMO2, 12 km resolution) and a convection-permitting model (HCLIM-AROME, 2.5 km resolution). Under PGW the maximum temperature during the heatwave rises 1.5 to 2.5 times faster than the global mean, implying that even at moderate warming levels the heatwave impact changes are tangible. Moreover, there is no sign that the increase in the maximum temperature levels off at higher warming levels, implying that at +4K above present-day temperatures could reach 50 ∘C. During heatwaves cities become islands of heat where daily maxima and night-time minima are up to 5 ∘C higher than in rural areas as we show in ultra-high resolution HCLIM-AROME simulations at 150 m resolution.

A Method to Assess and Explain Changes in Sub‐Daily Precipitation Return Levels From Convection‐Permitting Simulations

AbstractReliable projections of extreme future precipitation are fundamental for risk management and adaptation strategies. Convection‐permitting models (CPMs) explicitly resolve large convective systems and represent sub‐daily extremes more realistically than coarser resolution models, but present short records due to the high computational costs. Here, we evaluate the potential of a non‐asymptotic approach, the Simplified Metastatistical Extreme Value (SMEV) to provide information on the future change of extreme sub‐daily return levels based on CPM simulations. We focus on a complex‐orography area in the North Eastern Italy and use three 10‐year time periods COSMO‐crCLIM simulations (2.2 km resolution) under RCP8.5 scenario. When compared to a block r‐maxima approach currently used in similar applications, the proposed approach shows reduced uncertainty in rare return level estimates (about 5%–10% smaller confidence interval) and can improve the quantification of future changes from CPM simulations. We evaluate these changes and their statistical significance in return levels for 1–24 hr durations. The changes show an interesting spatial organization associated with orography, with significant positive changes located at high elevations. These positive changes tend to increase with increasing return period and decreasing duration. Because SMEV can separate the roles of event intensity and occurrence, it allows for physical interpretations of these changes. We suggest that non‐asymptotic approaches permit the quantification of change in rare extremes within available CPM runs.

Improving land surface feedbacks to the atmosphere in convection-permitting climate simulations for Europe

We investigated positive temperature (warm) and negative precipitation (dry) biases in convection-permitting model (CPM) simulations for Europe (2.2 km grid spacing) that were considerably larger than in equivalent regional climate model (RCM) simulations (12 km grid spacing). We found that improvements in dry biases could be made by (1) using a more complex runoff scheme which takes into account topography and groundwater, (2) delaying the onset of water stress in vegetation to enhance transpiration, (3) changing the microphysics scheme to CASIM (Cloud AeroSol Interacting Microphysics) which also decreases heavy rainfall and increases light rainfall. Increasing soil moisture to the critical point can remove dry precipitation biases in southern Europe but not in northern areas, indicating that soil moisture limitation is a key contributor to precipitation biases in the south only. Instead, in the north, changing the cloud scheme of the model has more impact on precipitation biases. We found that the more intense and intermittent nature of rainfall in the CPM, which is more realistic leads to different canopy interception compared to the RCM. This can impact canopy evaporation, evapotranspiration and feed back on precipitation. Increasing rainfall storage in the canopy only leads to small improvements in warm biases, since it still fills rapidly with intense CPM rainfall, suggesting the need for an additional moisture store via improved groundwater modelling or surface pooling. Overall, this work highlights the challenge of correctly capturing land surface feedbacks in CPMs, which play an important role in future climate projections in some regions.

Enhancing Extreme Precipitation Predictions With Dynamical Downscaling: A Convection‐Permitting Modeling Study in Texas and Oklahoma

AbstractPrecipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times.

Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model

Abstract. A fundamental issue associated with the dynamical downscaling technique using limited-area models is related to the presence of a “spatial spin-up” belt close to the lateral boundaries where small-scale features are only partially developed. Here, we introduce a method to identify the distance from the border that is affected by the spatial spin-up (i.e., the spatial spin-up distance) of the precipitation field in convection-permitting model (CPM) simulations. Using a domain over eastern North America, this new method is applied to several simulations that differ on the nesting approach (single or double nesting) and the 3-D variables used to drive the CPM simulation. Our findings highlight three key points. Firstly, when using a single nesting approach, the spin-up distance from lateral boundaries can extend up to 300 km (around 120 CPM grid points), varying across seasons, boundaries and driving variables. Secondly, the greatest spin-up distances occur in winter at the western and southern boundaries, likely due to strong atmospheric inflow during these seasons. Thirdly, employing a double nesting approach with a comprehensive set of microphysical variables to drive CPM simulations offers clear advantages. The computational gains from reducing spatial spin-up outweigh the costs associated with the more demanding intermediate simulation of the double nesting. These results have practical implications for optimizing CPM simulation configurations, encompassing domain selection and driving strategies.

Assessment of snow simulation using Noah-MP land surface model forced by various precipitation sources in the Central Tianshan Mountains, Central Asia

Accurate mountainous snow estimation is paramount for hydrological processes and water resources estimation in arid regions. Using Land surface models (LSMs) is a practical numerical approach for snow estimation in a complex orography region such as the Tianshan Mountains. However, the bias of precipitation forcing is a major source of uncertainty for snow simulation over scarce-data regions. This study evaluated the performance of 4 km snow simulations using the Noah-MP LSM driven by eight precipitation sources. They are retrieved from non-model products and climate model simulations during the 2018-2019 cold season in the Central Tianshan Mountains (CTS) region. Multi-source validation datasets (in-situ observation, field snow pits, and remote sensing products) have been used for evaluation and uncertainty estimation. The results showed that the difference in precipitation amount significantly affected the snowpack simulation performance. Compared with non-model products (Global Land Data Assimilation System (GLDAS), Global Precipitation Measurement (GPM), and Gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP)), the cold season precipitation from climate model simulations exhibited a better performance overall in the high-elevation regions (elevation > 1000 m) evaluated by in-situ observations. In addition, the 4 km convection-permitting modeling (CPM) precipitation (WRF-Morrison and WRF-WSM6) showed higher accuracy (RMSE: 23.48 mm/season and 18.94 mm/season, respectively) than gray-zone resolution simulations and ERA5-land driven runs in the high-elevation regions. The snow depth simulation driven by WRF-Morrison precipitation had the second smallest RMSE (4.67 cm/day) and lowest bias (-0.74 cm/day) value in the high-elevation regions compared with in-situ observation. Meanwhile, CPM precipitation-driven runs exhibited the smallest RMSE value based on the assessment of snow field pits. In addition, the CPM-driven simulation achieved the closest match to the elevation-based distribution of snow cover days in regions with elevation over 1000 m and duration over 60 days compared to the MODIS product. The findings of this study highlight that CPM with proper parameterization configurations has added values in producing realistic topographic precipitation for snow modeling using LSMs over data-scarcity mountainous areas.

Future Change in Urban Flooding Using New Convection‐Permitting Climate Projections

AbstractRainfall intensity in the United Kingdom is projected to increase under climate change with significant implications for rainfall‐driven (combined pluvial and fluvial) flooding. In the UK, the current recommended best practice for estimating changes in pluvial flood hazard under climate change involves applying a simple percentage uplift to spatially uniform catchment rainfall, despite the known importance of the spatial and temporal characteristics of rainfall in the generation of pluvial floods. The UKCP Local Convective Permitting Model (CPM) has for the first time provided the capacity to assess changes in flood hazard using hourly, 2.2 km CPM precipitation data that varies in space and time. Here, we use an event set of ∼13,500 precipitation events across the three UKCP Local epochs (1981–2000, 2021–2040, and 2061–2080) to simulate rainfall‐driven flooding using the LISFLOOD‐FP hydrodynamic model at 20 m resolution over a 750 km2 area of Bristol and Bath, UK. We find that both the event set and uplift approaches indicate an increase in flood hazard under near‐term (2021–2040) and future (2061–2080) climate change. However, the event set produces markedly higher estimates of flood hazard when compared to the uplift approach, ranging from 19% to 49% higher depending on the return period. This suggests including the full spatiotemporal rainfall variability and its future change in rainfall‐driven flood modeling is critical for future flood risk assessment.

Advancing South American Water and Climate Science through Multidecadal Convection-Permitting Modeling

Advancing South American Water and Climate Science through Multidecadal Convection-Permitting Modeling

Assessment of physical schemes for WRF model in convection-permitting mode over southern Iberian Peninsula

Convection-permitting models (CPMs) enable the representation of meteorological variables at horizontal high-resolution spatial scales (≤ 4 km), where convection plays a significant role. In this regard, physical schemes need to be evaluated considering factors in the studied region such as orography and climate variability. This study investigates the sensitivity of the Weather Research and Forecasting (WRF) model as CPM to the use of different physics schemes on Andalusia, a complex orography region in the southern part of the Iberian Peninsula (IP). To do that, a set of 1-year WRF simulations was completed based on two “one-way” nested domains: the parent domain (d01) spanning the entire IP with 5 km spatial resolution and the nested domain (d02) for the region of Andalusia at 1 km of spatial resolution. 12 physic schemes were examined from combinations of microphysics (MP) schemes including THOMPSON, WRF single moment 6-class (WSM6), and WRF single moment 7-class (WSM7), and different options for the convection in d01, the Grell 3D (G3), Grell-Freitas (GF), Kain-Fritsch (KF), and deactivated cumulus parameterization (OFF). The simulated precipitation and 2-m temperature for the year 2018, characterized to be a very wet year, were compared with observational datasets from different sources to determine the optimal WRF configuration, including point-to-point and station-point comparisons at different time aggregations (from annual to hourly). In general, greater differences were shown when comparing the results of convection schemes in d01. Simulations completed with GF or OFF presented better performance compared to the reference datasets. Concerning the MP, although THOMPSON showed a better fit in high mountain areas, it generally presents a worse agreement with the reference datasets. In terms of temperature, the results were very similar and, therefore, the selection of the “best” configuration was based mainly on the precipitation results with the WSM7-GF scheme being suitable for Andalusia region.

Convection-permitting simulations reveal expanded rainfall extremes of tropical cyclones affecting South Korea due to anthropogenic warming

AbstractUnderstanding how global warming affects tropical cyclone (TC) intensity and precipitation for target regions is essential to preparing for associated damages but detailed processes remain uncertain. This study provides the first quantification of anthropogenic influences on TC characteristics affecting South Korea using convection-permitting model (CPM) simulations (3 km resolution). For the observed four recent TCs that strongly affected South Korea, CPM simulations were performed under current (ALL) and counterfactual conditions without human influences (NAT). The observed sea surface temperature and lateral boundary conditions were used for ALL while changes attributable to human influences (estimated using CMIP6 multimodel simulations) were removed from observed boundary conditions for NAT runs. ALL experiments captured the observed TC intensity and precipitation reasonably. After removing human influences, TC intensity and precipitation were reduced in NAT experiments. Importantly, areas with extreme precipitation (i.e., having precipitation larger than 150 mm) were found to expand by 16–37% in ALL compared to NAT, which was induced by an enhanced upward motion near the TC core and an increase of background water vapor in line with warming. Further, the role of increased moisture was found to become important as TC moves to mid-latitudes. This study provides valuable insights into how greenhouse warming can intensify TC-induced extreme precipitation over East Asia.

Assessment of simulations of a polar low with the Canadian Regional Climate Model.

Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.