Abstract
The vertical structure of three polar lows is described using profiling radar, lidar, and passive remote sensors deployed at a coastal site in northern Norway. The data were collected as ...part of the Cold‐air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). These data are examined in the context of satellite imagery, operational weather radar reflectivity imagery, and output from the AROME Arctic model. A comparison to satellite images shows that AROME‐Arctic captured the polar lows well. All three polar lows form in marine cold‐air outbreaks and are surrounded by open‐cellular convection typical of such outbreaks. Two of the lows form in a forward shear environment and one under reverse shear. Initially, the three polar lows are comma shaped; two of them transition to be more spiraliform at their mature stage and have mostly cloud‐free warm cores. The warm cores are the result of a warm‐seclusion process. All three lows have stratiform precipitation bands, marked by little cloud liquid water, and rather high surface precipitation rate. The vertical drafts and turbulence in these stratiform clouds are generally weak. All three lows also have convective clouds, which have stronger vertical drafts, stronger turbulence, and pockets of high liquid water content.
This paper studies the potential of ground-based microwave radiometers (MWR) for providing accurate temperature retrievals by combining convective scale numerical models and brightness temperatures ...(BTs). A one-dimensional variational (1D-Var) retrieval technique has been tested to optimally combine MWR and 3-h forecasts from the French convective scale model AROME. A microwave profiler HATPRO (Humidity and Temperature PROfiler) was operated during 6 months at the meteorological station of Bordeaux (Météo France). MWR BTs were monitored against simulations from the Atmospheric Radiative Transfer Simulator 2 radiative transfer model. An overall good agreement was found between observations and simulations for opaque V-band channels but large errors were observed for channels the most affected by liquid water and water vapour emissions (51.26 and 52.28 GHz). 1D-Var temperature retrievals are performed in clear-sky and cloudy conditions using a screening procedure based on cloud base height retrieval from ceilometer observations, infrared radiometer temperature and liquid water path derived from the MWR observations. The 1D-Var retrievals were found to improve the AROME forecasts up to 2 km with a maximum gain of approximately 50 % in root-mean-square-errors (RMSE) below 500 m. They were also found to outperform neural network retrievals. A static bias correction was proposed to account for systematic instrumental errors. This correction was found to have a negligible impact on the 1D-Var retrievals. The use of low elevation angles improves the retrievals up to 12 % in RMSE in cloudy-sky in the first layers. The present implementation achieved a RMSE with respect to radiosondes within 1 K in clear-sky and 1.3 K in cloudy-sky conditions for temperature.
•Potential of convective-scale data assimilation (DA) over a small model domain.•Comparing the performance of two convection-permitting models (CPMs), the WRF and HARMONIE-AROME in both downscaling ...and data assimilation runs.•Impact of assimilating conventional observations over areas influenced by complex terrain.•Improving quantitative precipitation forecasts (QPFs) by applying cyclic 3D-Var data assimilation method.•The ability of the 3D-Var cyclic data assimilation to improve short-range forecasts over the west of Iran and neighboring areas.
The impact of applying three-dimensional variational data assimilation (3D-Var DA) on convective-scale forecasts is investigated by using two mesoscale models, the Weather Research and Forecasting model (WRF-ARW) and the Hirlam and Aladin Research Model On Non-hydrostatic-forecast Inside Europe (HARMONIE-AROME). One month (1 to 30 December 2013) of numerical experiments were conducted with these two models at 2.5 km horizontal resolution, in order to partly resolve convective phenomena, on the same domain over a mountainous area in Iran and neighboring areas. Furthermore, in order to estimate the domain specific background error statistics (BES) in convective scales, two months (1 November to 30 December 2017) of numerical experiments were carried out with both models by downscaling operational ECMWF forecasts. For setting the numerical experiments in an operational scenario, ECMWF operational forecast data were used as initial and lateral boundary conditions (ICs/LBCs). In order to examine the impact of data assimilation, the 3D-Var method in cycling mode was adopted and the forecasts were verified every 6 hours up to 36 hours for selected meteorological variables. In addition, 24 h accumulated precipitation forecasts were verified separately. Generally, the WRF and HARMONIE-AROME exhibit similar verification statistics for the selected forecast variables. The impact of DA on the numerical forecast shows some evidence of improvement in both models, and this effect decreases severely at longer lead times. Results from verifying the 24 h convective-scale precipitation forecasts from both models with and without DA suggest the superiority of the WRF model in forecasting more accurately the occurred precipitation over the simulation domain, even for the downscaling run.
Limited‐area ensemble predictions can be sensitive to the specification of lateral boundary conditions, which are often built by subsampling larger ensembles. Using the operational PEARP and ...AROME‐EPS ensembles, we compare several subsampling methods, including random selection, representative members, and a new selection method. The tests show that the algorithms used for the clustering and the member selection have a significant impact on the resulting ensembles. Clustering‐based methods are shown to outperform random subsampling, mostly (but not only) because they change the ensemble spread. Cluster sizes can be highly variable, which can complicate ensemble interpretation. We present a subsampling algorithm that has little impact on performance scores, but better preserves ensemble spread and produces nearly equally likely members by limiting cluster size variability.
Limited‐area ensemble predictions can be sensitive to the specification of lateral boundary conditions, which are often built by subsampling larger ensembles. Using the operational PEARP and AROME‐EPS ensembles, we compare several subsampling methods, including random selection, representative members, and a new selection method.
Kraków, Poland, is a city with poor air quality, located in the large Wisła (Vistula) valley, and affected by a foehn wind from the Tatra Mountains. We analyzed 14 long episodes of the foehn from the ...periods Sep 2017 - Apr 2018 and Sep 2018 - Apr 2019. Data used included measurements of PM
10
(i.e. particulate matter with an aerodynamic diameter up to 10 µm) concentrations) concentrations, air temperature and relative humidity, wind speed and direction from ground stations and mast measurements up to 100 m a.g.l., along with model analysis results. A non-operational configuration of the AROME CMC (the Application of Research to Operations at Mesoscale canonical model configuration) 1 km x 1 km was applied. A conceptual model concerning the impact of a foehn on urban air pollution was developed. The occurrence of a particular effect of a foehn on the PM
10
spatial-temporal pattern depends on its mode of transfer through the city: a. a foehn flows above the valley where a strong cold air pool and a return flow can be found; b. a foehn enters the valley from the eastern, wider part or from the valley top and destroys the cold air pool; c. gravity waves generated by a foehn are strong enough to enter the western narrower part of the valley and cause large spatial differences in turbulence parameters within the city. The first transfer mode worsens air pollution dispersion conditions throughout the city and leads to large increases in PM
10
levels (from below 50 to 150-200 µg⋅m
−3
), the second mode improves dispersion and leads to large decreases in PM
10
levels (from 150-200 to below 50 µg⋅m
−3
) throughout the city, and the third generates large spatial differences in PM
10
levels (50-70 µg⋅m
−3
) within the city. There is no single effect of a foehn on air pollution dispersion conditions.
Urban areas are currently vulnerable to the effects of extreme weather events. Climate change is expected to increase the frequency of such events, including heatwaves (HWs), on which we are ...focusing. Our aim is to quantify how the exposure to HWs will evolve with climate change and its impact on populations. We take advantage of the CNRM-AROME convection-permitting scale (2.5-km) simulations coupled with the urban canopy model TEB, to capture urban effects (in particular urban heat island, UHI) and their interactions with regional processes. The climate simulations cover an extended area of France for historical (1986–2005) and future (2080–2099) periods using the RCP8.5 emission scenario. An HW indicator is applied to assess the respective exposure of urban and associated rural areas. CNRM-AROME projects a strong shift in the minimum and maximum temperature distribution to warmer values in the future, especially in rural areas. Related to the stronger rural temperature increase, the model projects a diurnal and nocturnal UHI reduction. Nevertheless, HW maximum intensity, duration and frequency are projected to increase in both urban and rural areas with climatic and geographical disparities. The analysis is ready to be applied for a multi-model approach within the framework of CORDEX FPS URB-RCC.
•The CPRCM AROME simulates the past HWs in a realistic way, both in terms of frequency and duration.•Climate change could exacerbate local climatic and geographical disparities.•UHIs under HW conditions are expected to decrease by the end of the century in the 14 cities of metropolitan France.•Urban and rural areas could be affected by an increase in the HW duration, intensity and frequency.
The Mediterranean Sea is an important source of heat and moisture for heavy precipitation events (HPEs). Moreover, the ocean mixed layer (OML) evolves rapidly under such intense events. Whereas ...short‐term numerical weather prediction systems generally use low‐resolution non‐evolving sea surface temperature (SST), the development of high‐resolution high‐frequency coupled system allows us to fully take into account the fine‐scale interactions between the low‐level atmosphere and the OML which occur during HPEs.
The aim of this study is to investigate the impact of fine‐scale air–sea interactions and coupled processes involved during the HPEs which occurred during 12–15 October 2012 (IOP13) and 26–28 October 2012 (IOP16a/b) of the HyMeX first field campaign. For that purpose, the high‐resolution coupled system AROME‐NEMO WMED was developed. This system is based on the 2.5 km‐resolution non‐hydrostatic convection‐permitting atmospheric model AROME‐WMED and the 1/36°‐resolution NEMO‐WMED36 ocean model. The coupling frequency is 1 h. To distinguish the effects due to the change in the initial SST field from that due to the interactive 3D ocean, the coupled run is compared to two AROME‐WMED atmosphere‐only experiments with no SST evolution during the 48 h forecast cycles—one using the AROME‐WMED SST analysis, the second using the SST field of the coupled experiment each day at 0000 UTC. The results of the three experiments re‐assert that the SST initial condition strongly influences the HPE forecast, in terms of intensity and location. With water budget analyses, the significant impact of the ocean interactive evolution on the surface evaporation water supply for HPEs is also highlighted. In cases of strong and intense air–sea exchanges, as in the mistral event of IOP16b, the coupling reproduces the intense and rapid surface cooling and demonstrates the importance of representing the ocean turbulent mixing with entrainment at the OML base.
The AROME‐NEMO WMED coupled model was developed to investigate the role of air–sea coupling on two heavy rainfall events. For each case‐study, the coupled run is compared to two atmosphere‐only AROME‐WMED experiments with no SST evolution. The large impact of the initial SST field on the precipitation forecast is re‐asserted, and the significant effect of the interactive 3D ocean coupling (with surface cooling notably due to entrainment) on the evaporation water supply for HPE is highlighted.
Performance of meso-scale numerical weather prediction model HARMONIE-AROME was assessed for a summer-time heatwave in a high-latitude coastal city of Turku in SW Finland. Representativeness of the ...model's ECOCLIMAP-SG based physiographic land cover specification with a resolution of 750 m was assessed against the 20 m resolution CORINE Land Cover (CLC) dataset. Moreover, the modelled 2 m air temperatures were compared with temperature observations recorded at 74 sites of the local climate observation network. Correlation analysis between the model's physiographic data (PGD) and CLC shows a statistically significant (p ≤ 0.01) match between the datasets in 76% of the land cover types, indicating mainly a good representativeness of the HARMONIE-AROME's land cover parameterization in the study area. The cases of mismatch are mostly related to the differences in ECOCLIMAP-SG and CLC classification principles and/or resolution, and thus can not be considered to indicate poor representativeness of the ECOCLIMAP-SG classification in the area. The HARMONIE-AROME modelled temperatures were on average slightly higher than the observed temperatures, and the difference was largest for daily minimum temperatures. Heterogeneity of land cover and topography inside a 750 m grid cell was related to larger difference between the modelled and observed temperature.
•The T modelled by HARMONIE-AROME was accurate; only 0.8 °C warmer than the observed T.•The largest site-specific differences were 2.1 °C / 0.4 °C (same/opposite direction).•Diurnally, the difference between the modelled and observed T was largest at night.•ECOCLIMAP-SG reflects well the land cover (CLC) in the study area.•The best correspondence between ECOCLIMAP-SG and CLC was on natural uninhabited areas.
The characterisation of the aerodynamic roughness length (z0) and the displacement height (d) is critical when modelling the wind field using the log vertical profile. It is known that the values of ...these parameters depend on land coverage and weather conditions. Thus, many authors have studied their relationship, providing typical values for each land cover. In this paper, we have performed a comprehensive literature review to collect the intervals of z0 and d values for each land coverage. Using these intervals, we estimate their values using an optimisation technique that improves the results of a downscaling wind model. The downscaling model is a 3D adaptive, mass-consistent finite element model (Wind3D) that takes values from the HARMONIE-AROME or ECMWF mesoscale numerical weather prediction models. The optimisation is carried out by a memetic algorithm that combines the Differential Evolution method, a rebirth operator and the L-BFGS-B algorithm. The fitness function to be minimised is the root mean square error (RMSE) against observed wind data. This fast procedure allows updating the aerodynamic parameters for any weather condition. Numerical experiments have been carried out to show the performance of the methodology.
•The proposed methodology improves the results from a wind downscaling model.•A comprehensive literature review of aerodynamic parameters is presented.•An aerodynamic parameter weighted mean suitable for non-homogeneous terrain is used.•The aerodynamic parameters are optimized using a memetic algorithm.•The methodology has been validated against measured data in Gran Canaria (Spain).
A realistic representation of mixed-phase clouds in weather and climate models is essential to accurately simulate the model's radiative balance and water cycle. In addition, it is important for ...providing downstream applications with physically realistic model data for computation of, for instance, atmospheric icing on societal infrastructure and aircraft. An important quantity for forecasts of atmospheric icing is to model accurately supercooled liquid water (SLW). In this study, we implement elements from the Thompson cloud microphysics scheme into the numerical weather prediction model HARMONIE-AROME, with the aim to improve its ability to predict SLW. We conduct an idealised process-level evaluation of microphysical processes, and analyse the water phase budget of clouds and precipitation to compare the modified and original schemes, and also identify the processes with the most impact to form SLW. Two idealised cases representing orographic lift and freezing drizzle, both known to generate significant amounts of SLW, are setup in a 1 D column version of HARMONIE-AROME. The experiments show that the amount of SLW is largely sensitive to the ice initiation processes, snow and graupel collection of cloud water, and the rain size distribution. There is a doubling of the cloud water maximum mixing ratio, in addition to a prolonged existence of SLW, with the modified scheme compared with the original scheme. The spatial and temporal extent of cloud ice and snow are reduced, due to stricter conditions for ice nucleation. The findings are important as the HARMONIE-AROME models is used for operational forecasting in many countries in northern Europe having a colder climate, as well as for climate assessments over the Arctic region.
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