The capability of a regional (AROME‐Arctic) and a global (ECMWF HRES) weather‐prediction model are compared for simulating a well‐observed polar low (PL). This PL developed on 3–4 March 2008 and was ...measured by dropsondes released from three flights during the IPY‐THORPEX campaign. Validation against these measurements reveals that both models simulate the PL reasonably well. AROME‐Arctic appears to represent the cloud structures and the high local variability more realistically. The high local variability causes standard error statistics to be similar for AROME‐Arctic and ECMWF HRES. A spatial verification technique reveals that AROME‐Arctic has improved skills at small scales for extreme values. However, the error growth of the forecast, especially in the location of the PL, is faster in AROME‐Arctic than in ECMWF HRES. This is likely associated with larger convection‐induced perturbations in the former than the latter model. Additionally, the PL development is analysed. This PL has two stages, an initial baroclinic and a convective mature stage. Sensible heat flux and condensational heat release both contribute to strengthen the initial baroclinic environment. In the mature stage, latent heat release appears to maintain the system. At least two conditions must be met for this stage to develop: (a) the sensible heat flux sufficiently destabilises the local environment around the PL, and (b) sufficient moisture is available for condensational heat release. More than half of the condensed moisture within the system originates from the surroundings. The propagation of the PL is “pulled” towards the area of strongest condensational heating. Finally, the sensitivity of the PL to the sea‐surface temperature is analysed. The maximum near‐surface wind speed connected to the system increases by 1–2 m·s−1 per K of surface warming and a second centre develops in cases of highly increased temperature.
The capability of the weather‐prediction model AROME‐Arctic for simulating a well‐observed polar low is investigated. The development of this polar low is thoroughly studied by sensitivity experiments. It is found that the system has two phases, an initial baroclinic and a mature convective phase, and that the development is very sensitive to the sea‐surface temperature.
The impact of Arctic conventional and satellite observations on regional short‐range weather forecasts is assessed using observing‐system experiments, in which observations are removed (denied) when ...creating the initial conditions of the forecasts. The experiments are conducted with the AROME‐Arctic regional mesoscale numerical weather prediction system, using as lateral boundary conditions (LBCs) observing‐system experiments performed at the European Centre for Medium‐Range Forecasts (ECMWF) with the global forecasting system. This allows the assessment of the relative impacts of observations on forecast skill through regional data assimilation (DA), through LBCs, and the total impact due to the denial of observations in both the regional and global forecasting systems. The study is conducted during the first and second Special Observing Periods of the Year Of Polar Prediction. The total impact on the upper‐air forecasts is dominated by the impact of observations through their assimilation in the LBCs, while for the winter period the impact on surface fields is dominated by the regional DA. The latter is significant up to 36 hr, while the former impact can last throughout the verified forecast range (48 hr). The use of observations in the LBCs has both significantly positive and significantly negative impacts. In terms of total impact on forecast skill, conventional observations, followed by infrared radiances, have the largest impact on all upper‐air parameters, except for humidity. For upper‐air humidity forecasts, the microwave radiances have the largest impact. In terms of observation impact through regional DA, conventional observations play the largest role for upper‐air temperature and geopotential, microwave for upper‐air humidity, and atmospheric motion vectors and Infrared Atmospheric Sounding Interferometer (IASI) for wind forecast. Regional DA of conventional observations also contributes the most to improvements of surface fields, except for 10‐m winds, for which the microwave temperature‐sensitive radiances are the most important.
The relative impact of Arctic observations is assessed through data denial in an observing‐system experiment (OSE) with the AROME‐Arctic regional mesoscale model and accounting for the global OSE as lateral boundary conditions (LBCs). The relative impacts of observations through regional data assimilation (DA, purple), through LBCs where the observations are used only in the LBCs (green), and the total impact, which corresponds to the denial of the observations in both regional and global models (light blue), are computed.
Temperature and humidity retrievals from an international network of ground‐based microwave radiometers (MWRs) have been collected to assess the potential of their assimilation into a ...convective‐scale numerical weather prediction (NWP) system. Thirteen stations over a domain encompassing the western Mediterranean basin were considered for a time period of 41 days in autumn, when heavy precipitation events most often plague this area.
Prior to their assimilation, MWR data were compared to very‐short‐term forecasts. Observation‐minus‐background statistics revealed some biases, but standard deviations were comparable to that obtained with radiosondes. The MWR data were then assimilated in a three‐dimensional variational data assimilation system through the use of a rapid update cycle. A first set of four different experiments were designed to assess the impact of the assimilation of temperature and humidity profiles, both separately and jointly. This assessment was done through the use of a comprehensive dataset of upper‐air and surface observations collected in the framework of the HyMeX programme.
The results showed that the impact was generally very limited on all verified parameters, except for precipitation. The impact was found to be generally beneficial in terms of most verification metrics for about 18 h, especially for larger accumulations. Two additional data‐denial experiments showed that even more positive impact could be obtained when MWR data were assimilated without other redundant observations. The conclusion of the study points to possible ways of enhancing the impact of the assimilation of MWR data in convective‐scale NWP systems.
This paper presents a validation of the AROME-SIMRA model, which is a nested computational fluid dynamics model that simulates both mesoscale and microscale phenomena. To validate the model, we ...analyzed 47 h of mean flow data collected by 13 three-dimensional sonic anemometers. These anemometers were mounted on tall masts located near the shoreline of Sulafjord, with heights ranging from 12m to 95m above the ground. Due to the difficulty measuring wind along the bridge span, analyzing flow conditions for the construction of a bridge that spans a vast fjord is a difficult process. Therefore, the primary objective of this study is to validate a nested macroscale–microscale model. This model will be utilized to analyze flow conditions across the span of the proposed bridge crossing in Sulafjord. The study explores the deviation between the measured and the simulated mean turbulence flow characteristics. Only records with the mean wind of 12ms−1 and above at SulaNW met-mast are considered due to their relevance in buffeting response, which led to the identification of a limited number of sectors representative of strong wind conditions. Mean wind speed comparisons show a minimum correlation of 0.6 and a maximum of 0.9 for all the anemometers analyzed. For wind directions, a low correlation between observation and numerical simulation is obtained at SulaSW met-mast located southwest of Sulafjord. A high Angle of Attack is obtained for both simulation and measurements. However, the correlation is dependent on the mast location, wind direction, and anemometer height. Along the bridge span, the flow is largely horizontal for the northwestern flow.
•Mesoscale atmospheric flow.•Microscale turbulence.•Nested Meso-microscale application to bridge design.•Finite element and a-posteriori error estimation.
During Intensive Observation Period 13 (15 to 16 October 2012) of the first Special Observing Period of the Hydrological cycle in the Mediterranean Experiment (HyMeX), Southern Italy (SI) was ...affected by two consecutive heavy precipitation events (HPEs). Both HPEs were associated with multi‐cell V‐shaped retrograde regeneration mesoscale convective systems (MCSs). The life cycle of two MCSs in connection with their dynamic and thermodynamic environments were analysed using a combination of ground‐based, airborne and spaceborne observations and numerical simulations. Rain gauges revealed that heavy precipitation occurred in two phases: the first one from 1300 to 1700 UTC (35 mm h−1) was caused by a V‐shaped system initiating over the Tyrrhenian Sea in the early morning of 15 October. Convection was triggered by the low‐level convergence between the southwesterlies ahead of an upper‐level trough positioned over southeastern France and very moist southerlies from the Strait of Sicily. The convection was favoured by high convective available potential energy (1500 J kg−1) resulting from warm and moist conditions at low levels associated with high sea surface temperatures in the Strait of Sicily. In addition, humidity at mid‐level was enriched by the presence of an elevated moisture plume from tropical Africa, favouring the efficiency of the convection to produce more precipitation. The second phase of heavy precipitation (2300 UTC on 15 October to 0200 UTC on 16 October, 34 mm h−1) was caused by a MCS initiating over Algeria around 1300 UTC, which subsequently travelled over the Strait of Sicily toward Sicily and SI. Convection was maintained by the combination of large low‐level moisture contents and a marked convergence ahead of the cold front. Unlike other MCSs forming in the same region earlier on that day, this huge V‐shaped system did affect SI because the strong upper‐level flow progressively backed from southwesterly to south southwesterly.
Water vapour measurements from a ground‐based Raman lidar and an airborne differential absorption lidar, complemented by high‐resolution numerical simulations from two mesoscale models (AROME‐WMED ...and Meso‐NH), are considered to investigate three transition events from Mistral/Tramontane to southerly marine flow taking place in the Montpellier region (southern France) in the time frame September–October 2012, during the Hydrological Cycle in the Mediterranean Experiment Special Observation Period 1. Low‐level wind reversals associated with these transitions are found to have a strong impact on water vapour transport, leading to a large variability of the water vapour vertical and horizontal distributions. Water vapour mixing ratio within the boundary layer is found to vary from typical values in the range 4–8 g kg−1 during the Mistral/Tramontane flows to values in the range 8–15 g kg−1 during the southerly marine flows. The increase/decrease in water vapour mixing ratio within the boundary layer may be abrupt and marked during these transition periods, with values increasing/decreasing by a factor of 2–4 within 1 h. The high spatial and temporal resolutions of the lidar data allow monitoring the time evolution of the water vapour field during these transitions from predominantly northerly Mistral/Tramontane flow to a predominantly southerly flow, permitting identification of the quite sharp separation between these flows, which is also satisfactorily well captured by the mesoscale models. Water vapour measurements from the ground‐based lidar are complemented by particle backscatter measurements from the same system, which reveal the significant variability in the aerosol and cloud fields associated with these transition events.
Abstract
Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation of precipitation extremes. In this ...article, the CPRCM CNRM-AROME developed at the Centre National de Recherches Météorologiques (CNRM) since a few years is described and evaluated using a 2.5-km 19-year long hindcast simulation over a large northwestern European domain using different observations through an added-value analysis in which a comparison with its driving 12-km RCM CNRM-ALADIN is performed. The evaluation is challenging due to the lack of high-quality observations at both high temporal and spatial resolutions. Thus, a high spatio-temporal observed gridded precipitation dataset was built from the collection of seven national datasets that helped the identification of added value in CNRM-AROME. The evaluation is based on a series of standard climatic features that include long-term means and mean annual cycles of precipitation and near-surface temperature where CNRM-AROME shows little improvements compared to CNRM-ALADIN. Additional indicators such as the summer diurnal cycle and indices of extreme precipitation show, on the contrary, a more realistic behaviour of the CNRM-AROME model. Moreover, the analysis of snow cover shows a clear added-value in the CNRM-AROME simulation, principally due to the improved description of the orography with the CPRCM high resolution. Additional analyses include the evaluation of incoming shortwave radiation, and cloud cover using satellite estimates. Overall, despite some systematic biases, the evaluation indicates that CNRM-AROME is a suitable CPRCM that is superior in many aspects to the RCM CNRM-ALADIN.
Abstract Meteorological processes over islands with complex orography could be better simulated by Convection Permitting Regional Climate Models (CP-RCMs) thanks to an improved representation of the ...orography, land–sea contrasts, the combination of coastal and orographic effects, and explicit deep convection. This paper evaluates the ability of the CP-RCM CNRM-AROME (2.5-km horizontal resolution) to simulate relevant meteorological characteristics of the Mediterranean island of Corsica for the 2000–2018 period. These hindcast simulations are compared to their driving Regional Climate Model (RCM) CNRM-ALADIN (12.5-km horizontal resolution and parameterised convection), weather stations for precipitation and wind and gridded precipitation datasets. The main benefits are found in the representation of (i) precipitation extremes resulting mainly from mesoscale convective systems affected by steep mountains during autumn and (ii) the formation of convection through thermally induced diurnal circulations and their interaction with the orography during summer. Simulations of hourly precipitation extremes, the diurnal cycle of precipitation, the distribution of precipitation intensities, the duration of precipitation events, and sea breezes are all improved in the 2.5-km simulations with respect to the RCM, confirming an added value. However, existing differences between model simulations and observations are difficult to explain as the main biases are related to the availability and quality of observations, particularly at high elevations. Overall, better results from the 2.5-km resolution, increase our confidence in CP-RCMs to investigate future climate projections for Corsica and islands with complex terrain.
The 1981–2010 monthly precipitation climatologies for Norway at 1 km resolution are presented. They are computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model ...with the in situ observations. Specifically, the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis onto 2.5 km resolution, is considered together with 2009 rain‐gauges located within the model domain. The precipitation climatologies are defined by superimposing the grid of 1981–2010 monthly normals from the numerical model and the kriging interpolation of station residuals. The combined approach aims at improving the quality of gridded climatologies and at providing reliable precipitation gradients also over those remote Norwegian regions not covered by observations, especially over the northernmost mountainous areas. The integration of rain‐gauge data greatly reduces the original HCLIM‐AROME biases. The HCLIM+RK errors obtained from the leave‐one‐out station validation turn out to be lower than those provided by two considered interpolation schemes based on observations only: a multi‐linear local regression kriging (MLRK) and a local weighted linear regression (LWLR). As average over all months, the mean absolute (percentage) error is 10.0 mm (11%) for HCLIM+RK, and 11.4 (12%) and 11.6 mm (12%) for MLRK and LWLR, respectively. In addition, by comparing the results at both station and grid cell level, the accuracy of MLRK and LWLR is more sensitive to the spatial variability of station distribution over the domain and their interpolated fields are more affected by discontinuities and outliers, especially over those areas not covered by the rain‐gauge network. The obtained HCLIM+RK climatologies clearly depict the main west‐to‐east gradient occurring from the orographic precipitation regime of the coast to the more continental climate of the inland and it allows to point out the features of the climatic subzones of Norway.
The paper presents the 1981–2010 monthly precipitation climatologies over Norway at 1‐km grid spacing. The climatologies are computed by an interpolation scheme (HCLIM+RK) combining the in situ observations with the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis. The comparison with methods using observations only proved that HCLIM+RK improves the accuracy of Norwegian climatologies and provides reliable precipitation patterns also over the remote areas not covered by rain‐gauges.
Tropical cyclones (TCs) can develop as a result of the tropical transition (TT) process, which occurs when an extratropical cyclone (EC) begins to exhibit tropical characteristics, forming a TC. In ...this study, four TT processes that lead to a hurricane structure Delta (2005), Ophelia (2017), Leslie (2018), and Theta (2020) are evaluated using two high-resolution numerical models (WRF and HARMONIE-AROME). Both tracks and intensities of the cyclones are assessed by comparing the simulated minimum sea level pressure and maximum wind speed to an observational dataset. Moreover, a spatial verification is performed by comparing the MSG-SEVIRI brightness temperature (BT) and accumulated precipitation (IMERG) to the corresponding simulations accomplished by both models. Analyzing the track results, the WRF model, on average, outstands HARMONIE-AROME. However, it is the HARMONIE-AROME model that performs better than WRF when reproducing the intensity of these cyclones. Concerning the BT spatial validation, HARMONIE-AROME slightly outperformed WRF when reproducing the cyclone's structure but failed when simulating the BT amplitude. Besides, both models achieved a nearly perfect cyclone location. In terms of accumulated precipitation results, the HARMONIE-AROME model overestimates the larger structures while underestimating the smaller ones, whereas the WRF model underestimates the bigger structures, being poorly located by both models. Although it is difficult to establish which numerical model performs better, the overall results show an outstanding of the HARMONIE-AROME model over the WRF model when simulating TT processes.
•Performance of HARMONIE-AROME and WRF-ARW in four Tropical Transitions.•Track and intensity cyclone and spatial verification are evaluated.•HURDAT, MSG-SEVIRI and GPM-IMERG are used as observations.•Object-based method used to evaluate Brightness Temperature and accumulated precipitation.
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