Papers are invited on:
• Initialization, and meteorological and land surface boundary conditions.
• Numerical and grid spacing aspects
• Studies concerning data assimilation.
• Development of physical parameterization schemes.
• Model evaluation and validation against a broad range of available observations.
• Future WRF development.
• Tailored WRF versions, e.g. polar WRF, WRF-LES, WRF-Chem, H-WRF, the WRF single-column model
• WRF applications in weather forecasting, air quality studies, wind energy engineering.
• Regional climate studies
• Mesoscale meteorological phenomena studied with WRF.
• Analogous studies using Model for Prediction Across Scales (MPAS)
Measurements of both the wind turbine inflow and its wake from a floating wind turbine are here analyzed to understand the role of the vertical wind shear and the veer on both inflow and wake characteristics. The inflow measurements correspond to those from a nacelle-mounted Doppler wind lidar that retrieved radial velocities up to three rotor diameters in front of the turbine, measuring thus within a large portion of the atmosphere. The wake measurements correspond to those from a scanning lidar that measured up to ten rotor diameters in both plan position indicator and range height indicator modes, thus covering spatially a good portion of the wake. For a significant number of periods, both inflow and wake measurements reveal the presence of a clear low-level jet (LLJ) with noses close to turbine hub height (about 100 m). The presence of LLJs complicates inflow modeling as, depending on the inflow model and measurement coverage, negative wind shears might appear.
We therefore study the ability of the Weather Research and Forecasting (WRF) model in simulating similar inflow conditions as those observed under the above LLJ episodes. Since turbulence and the presence of the turbine itself are highly important, we use the ability of the WRF model to perform large-eddy simulations (LES) for these conditions and we model the turbine by using a generalized actuator disk (GAD). The WRF-LES simulations reveal the turbulence and atmospheric stability conditions that are required to replicate the inflow conditions that lead to these shallow LLJs. Further, after similar LLJ conditions (as those measured) are achieved with the WRF-LES simulations, a similar turbine as the real floating turbine is implemented in the simulation via the GAD. Here, we then analyzed the differences and similarities between the wake measurements and the wake simulations and their characteristics.
How to cite: Peña, A. and Angelou, N.: A WRF-LES study of turbine inflow and wake characterization, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-254, https://doi.org/10.5194/ems2024-254, 2024.
A modeling study of a real case has been conducted to assess the performance of the large-eddy simulation version of the Weather Research and Forecasting Model (WRF-LES) in the Vallée d'Aure region, situated on the northern side of the Pyrenees.
This study aims to evaluate the model's ability to accurately simulate thermally-driven flows (TDF) and the vertical thermal and dynamic structure of the planetary boundary layer (PBL). This is essential because the characteristics of TDFs at mountain environments are influenced by factors such as the strength of the temperature gradient near the surface, interaction with winds of varying spatiotemporal scales, such as synoptic winds, and the vertical structure of the pre-existing PBL.
The accurate simulation of turbulence in the PBL at sub-kilometer horizontal scales is a complex issue, but it offers advantages under stable conditions and over heterogeneous surfaces when local properties are required or when resolving small-scale surface features is desirable, as is the case of the valley here considered. To evaluate the performance of methods currently available in the WRF-LES model, different sensitivity experiments are conducted with different PBL treatments.
To validate these simulations, data from the MOSAI1 field campaign, conducted in collaboration with the LATMOS-i2 and WINDABL3 projects, have been used. Throughout this campaign, meteorological radiosoundings were performed, and three meteorological stations were strategically installed in the valley, incorporating surface turbulence measurements.
(1) MOSAI project (Model and Observation for Surface-Atmosphere Interactions, https://mosai.aeris-data.fr/).
(2) LATMOS-i project (Land-ATMOSphere interactions in a changing environment: How do they impact on atmospheric-boundary-layer processes at the meso, sub-meso and local scales in mountainous and coastal areas?) (PID2020-115321RB-I00, funded by MCIN/AEI/ 10.13039/501100011033).
(3) WINDABL project (PR2022-055). Project to impulse the career of young researchers funded by the University of Cádiz (Spain) (Plan Propio).
How to cite: Carbone, J., Ortiz-Corral, P., Román-Cascón, C., and Yagüe, C.: Assessment of WRF-LES Model Performance in Simulating Valley Breezes and Vertical Structure of the Planetary Boundary Layer in the Pyrenees., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-431, https://doi.org/10.5194/ems2024-431, 2024.
Mountain areas are particularly sensitive to global warming as they usually present a complex distribution of climates and ecosystems and feedbacks tend to amplify the effects of climate change. Additionally, the large spatial variability of temperature gradients and heterogeneity in the occurrence, amount and distribution of precipitation and snow cover in mountainous areas are especially relevant for water resources and stresses the need for high altitude observations and high-resolution modelling over complex terrain. However, harsh meteorological conditions and the complex orography associated with this environment that, as part of the Mediterranean domain, has been underscored as a climate change hot-spot, hinder the obtention of a good coverage of high-altitude observations and pose challenges for regional climate models.
CIMAs is a joint effort aiming at improving our understanding of climate variability over mountain regions in Iberia. A pilot area has been selected over the Sierra de Guadarrama (Spanish Central range, about 50 km from Madrid) aiming at studying climate variability through very high (1 km) resolution simulations, exploring models’ ability to capture relevant processes at that scale. A set of observational sites ranging from high altitudes to low levels at both sides of the mountain range has been used.
ERA Interim, ERA5 and different WRF nested simulations, spanning the last three decades and reaching 1 km resolution, have been compared to a dense network of in situ observations. Results show a clear improvement with increasing resolution for temperature, but some altitude-related biases for precipitation. In this sense, some sensitivity tests to changing convection parameterisations and to convection permitting configurations have been assessed.
How to cite: Greciano-Zamorano, E., González Rouco, J. F., Vegas Cañas, C., García Pereira, F., Navarro Montesinos, J., García Bustamante, E., Rodríguez Camino, E., and Rodríguez Guisado, E.: Climate Initiative for Iberian Mountain Areas (CIMAs): improving our understanding of climate variability over mountain areas using high resolution modelling., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1138, https://doi.org/10.5194/ems2024-1138, 2024.
In recent years, using convection-permitting scales in regional climate simulations has become more and more frequent. These scales allow the models to include previously parameterized atmospheric processes, which improve the accuracy of a model in simulating precipitation. Data assimilation techniques can also improve the simulation of precipitation and temperature. However, the number of simulations combining these two options is scarce because of the high computational costs. Hence, it is important to evaluate the effect of data assimilation schemes on such convection-permitting simulations and to determine their added values.
In this study, we use the Weather Research and Forecasting model (WRF; version 3.8.1) to dynamically downscale the ERA5 reanalysis over Western Europe for period 2010–2020. We use one year of spin-up to allow the correct initialization of both soil and atmosphere. The spatial resolution of the simulation is set to 3 km and the temporal resolution to 1 hour. 51 vertical levels are employed, up to 20 hPa. Two model configurations are tested: with and without data assimilation (the Da and NoDA experiments, respectively). The former uses the 3DVAR data assimilation (WRFDA), which is run every six hours (00, 06, 12 and 18 UTC – analysis times). Observations are provided by the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations), but only the observations inside a 120-minute window around analysis times are assimilated. Additionally, the DA experiment employs monthly-varying background error covariance matrices. Both experiments share the same parameterization options (e.g., Noah-MP land surface model) and use the daily-varying SST field from the NOAA OI SST v2 dataset instead of SST from ERA5.
The results show that both experiments generate monthly precipitation patterns over Europe which are similar to those from observational datasets such as IMERG and CHIRPS, or the reanalysis ERA5. However, in general, and particularly during summer months, DA generates larger amounts of precipitation than NoDA. These amounts are in line with those from CHIRPS. In terms of temperature, the DA experiment shows warmer temperatures than NoDA over central Europe during winter and colder temperatures over most of the domain in the remaining months. The temperatures of DA are again more in line with those from observational data sets such as CRU or EOBS. The datasets employed in the verification were not assimilated in WRFDA, and independent from each other.
These results highlight the fact that increasing the spatial resolution to reach convection-permitting scales has a positive impact on the simulation, allowing the generation of reliable precipitation and temperature fields. The use of 3DVAR data assimilation can additionally improve the performance of the regional model due to its effect on the positive feedbacks between soil moisture, air temperature, water vapour content and precipitation.
How to cite: Gonzalez-Roji, S. J. and Raible, C. C.: Improved precipitation and temperature over Western Europe due to convection-permitting scales and 3DVAR data assimilation, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-359, https://doi.org/10.5194/ems2024-359, 2024.
July 2019 in Catalonia, northeastern Spain, was an anomalously warm month marked by an irregular precipitation pattern, both spatially and temporally. Throughout this period, some discrepancies between WRF operational forecasts and observations were detected, which might stem from the lack of the sea surface temperature (SST) updating in the WRF model configuration. To study the SST-updating effects on WRF v4.5, two simulations were performed using ERA5 as initial and boundary conditions, the first one without updating SST and the second one updating it. Specifically, the study focused on two distinct periods of July 2019: days 8-10, characterized by storms over the Pyrenees (hereafter STORM), and days 24-26, characterized by a heatwave (hereafter HEATW). The objectives of this study are 1) to assess the SST updating impacts on WRF model, particularly on the surface layer and planetary boundary layer (PBL) parametrizations, and 2) to explore the differential behavior of the WRF model between storm and heatwave conditions.
Results show that changes in SST modifies surface layer parameterization through surface fluxes, with the latent heat flux being more sensitive than the sensible heat flux. These fluxes impacted the stability regimes through the modification of the Monin-Obukhov length and the stability functions. During STORM period the atmosphere tends towards neutrality when updating SST, hence is dominated by wind shear turbulence, whereas on HEATW period the SST updating leads to very unstable conditions, dominated by buoyancy.
Regarding the PBL parameterization, the SST updating leads to an increase of the PBL height during STORM and a decrease during HEATW, with a greater absolute variation observed during the latter period. Averaged potential temperature vertical profiles at 00 UTC reveal greater variability during storm conditions, especially at higher levels (500-1000 m), whereas during heatwave situations, the surface mixing layer is discernible up to ~80 m, corresponding to the maximum mixing height. Furthermore, during HEATW the averaged potential temperature profile revealed the maximum differences between the updated and non-updated simulations at the surface, with differences decreasing with height. Conversely, during STORM, the higher differences between profiles were located a few tens of meters above the surface.
These findings show the significance of SST updating in operational forecasting during July 2019. Specifically, during the period of storm, the SST updating presents a greater impact on meteorological variables, particularly on air potential temperature, compared to the period of heatwave. These results are specific to July 2019 over the northwestern Mediterranean Sea, and further investigation is needed to assess their applicability in different time periods with similar meteorological conditions. Despite that, the study helps to a better understanding of the sensitivity of the WRF model to SST changes and the need of a proper SST representation.
How to cite: Busquets, E., Udina, M., and Bech, J.: Exploring the sea surface temperature updating in WRF model over northwestern Mediterranean Sea, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-181, https://doi.org/10.5194/ems2024-181, 2024.
Cities experience the urban heat island effect (UHI), i.e. cities are warmer than the countryside. Climate change and rapid urbanization means UHI effects are projected to become more frequent, and better UHI modelling and warning strategies against adverse human thermal comfort are thus needed. Urban temperatures vary locally due to the presence of buildings, trees, water bodies that affect the absorbed solar radiation, the wind speed and evapotranspiration. Urban weather models typically use so called urban canopy models to estimate the energy and radiation balance of facets like roofs, walls and roads, and calculate temperatures and wind speeds in streets canyons. For successful modelling, these models need high-resolution urban morphology information as surface boundary conditions, like building height, street width, tree positions, building material and radiation properties of roofs, roads and building walls. Recent model development focused on mapping buildings and trees following the so called NUDAPT approach to quantify intra-urban UHI patterns, but spatial information about radiation properties of roofs, roads and building walls has not been mapped nor incorporated in urban canopy models.
In the Urban-M4 project we aim to collect high-resolution radiation information of walls and roads, from widely available data sources such as street view imagery, public databases and airborne observations. These gridded data will feed into hectometric WRF model simulations for Amsterdam and Enschede (The Netherlands) for hot summer days. Here we present a framework for the project as well as the experimental setup for our WRF simulations and some initial results from sensitivity experiments gauging the effect of changing radiation information on urban heat in Amsterdam.
How to cite: Kalverla, P., Donnelly, C., Steeneveld, G.-J., and Timmermans, W.: Exploring the use of urban imagery for representation of urban fabric in the SLUCM, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-991, https://doi.org/10.5194/ems2024-991, 2024.
Nowcasting is a crucial tool in every meteorological office: it provides steadily updated forecasting guidance and is essential in cases of extreme weather when forecasters need to know the evolution of the situation in great detail and issue early warnings if necessary.
It is well known that forecasting products based on radar echo extrapolation have the best skill for the first one or two hours. Beyond this range, numerical weather prediction (NWP) models are needed to obtain reliable precipitation forecasts. The Meteorological Service of Catalonia (SMC), like many other operational centres around the globe, blends extrapolation techniques with NWP to produce seamless forecasts (Casellas et al., 2022).
The NWP component of the nowcasting system at the SMC is based on the WRF model. To build a time-lagged ensemble, several simulations run every 3 hours that assimilate radar and conventional data with the WRF-3DVAR and 3DEnVAR methods and the vLAPS system (Jiang et al., 2015).
However, WRFDA also incorporates the 4DVAR technique, which takes into account the time tendency of the observations and uses an NWP model as a dynamical constraint, thus linking microphysics with the dynamical and thermodynamical fields (Sun and Wang, 2013). Several studies conclude that this initialisation method yields better results when compared to 3DVAR for precipitation forecasts (Mazzarella et al., 2021), especially at longer lead times.
The main challenge for using 4DVAR for operational purposes is its computational cost. Fortunately, the high frequency of SMC’s composite radar data, available every 6 minutes, allows us to use small assimilation windows and, at the same time, keep a large number of observations that can be assimilated at their appropriate time.
In this work, we introduce our strategy to obtain timely analysis so that the WRFDA-4DVAR method can be used to initialise some members in our nowcasting system in an operational framework. In addition, the performance of the forecasts compared to those initialised with WRF-3DVAR and 3DEnVAR are shown.
References
Casellas, E., Atencia, A., Mercader, J., Moré, J., Rigo, T., Sairouni, A., & Segalà, S. (2022): Blending of precipitation probability forecasts: weather radar advection and NWP models. 11th European Conference on Radar in Meteorology and Hydrology, Locarno (Switzerland), 29 August-2 September 2022.
Mazzarella, V., Ferretti, R., Picciotti, E., and Marzano, F. S.: Investigating 3D and 4D variational rapid-update-cycling assimilation of weather radar reflectivity for a heavy rain event in central Italy, Nat. Hazards Earth Syst. Sci., 21, 2849–2865, https://doi.org/10.5194/nhess-21-2849-2021, 2021.
Sun, J., and H. Wang, 2013: Radar Data Assimilation with WRF 4D-Var. Part II: Comparison with 3D-Var for a Squall Line over the U.S. Great Plains. Mon. Wea. Rev., 141, 2245–2264, https://doi.org/10.1175/MWR-D-12-00169.1.
How to cite: Mercader Carbó, J., Bravo Blanco, M., and Moré Pratdesaba, J.: WRFDA-4DVAR radar data assimilation for operational very short-range precipitation forecasts in Catalonia: Initialisation strategies and preliminary results, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-269, https://doi.org/10.5194/ems2024-269, 2024.
The All-Sky Radiance (ASR) data from geostationary satellites are important for improving initial conditions in numerical modeling through data assimilation, as it provides dense spatio-temporal atmospheric information over a wide area. Accurately applying the error information inherent in observations is essential for enhancing its effectiveness of satellite data assimilation. In this study, we calculated an observation error model for the ten infrared radiation channels of the Advanced Meteorological Imager (AMI) on the GEO-KOMPSAT-2A (GK-2A) for the summer season using the standard deviation of the brightness temperature observation minus background (O-B) as a function of the cloud impact parameter (Ca). The normalized brightness temperature of O-B probability density function is scaled such that it more closely approximates a normal distribution. For data assimilation experiments, we used the Community Radiative Transfer Model (CRTM) as the satellite observation operator and applied the 3-dimensional variational data assimilation method of the Weather Research and Forecasting Model Data Assimilation. When applying the adjusted observation error model for summer precipitation cases in the Korean peninsula, both the analysis and forecast fields improved compared to a prescribed constant error value. The best rainfall forecast performance was observed in the linear model, which followed the normal distribution better than the high-order regression observation error model. This is thought to be due to the observation error in the linear model saturates more gradually, allowing for consideration of a wider variability of Ca, i.e., a more detailed spatial distribution of cloud impact. Meanwhile, the assimilation results of Clear-Sky Radiance (CSR), excluding cloud area information, were compared to analyze the additional effects of cloud-precipitation area information during ASR assimilation. Further, we plan to assimilate both the water vapor channel ASR and the surface-sensitive channel CSR to improve the cloud detection algorithm, quality control, and refine surface parameter estimates for enhanced predictability.
Key words: GK-2A infrared channels, data assimilation, observation error, precipitation forecast
※ This research was supported by the National Research Foundation of Korea (No. 2022R1A2C1012361) funded by the Ministry of Science and Technology, and also was funded by the Korea Meteorological Administration Research and Development Program under Grant RS-2023-00237740. Additional support was provided by the BK21 FOUR project funded by the Ministry of Education.
How to cite: Min, K.-H. and Jo, S.-Y.: Analysis of Predictability Improvement due to the Enhancement of Observation Error for the GK-2A Infrared Channels in Data Assimilation, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-981, https://doi.org/10.5194/ems2024-981, 2024.
Spain is a country located in Southwestern Europe highly vulnerable to different extreme weather-related events such as heatwaves, droughts, and wildfires, causing detrimental effects on the environment, economy, and society. Under projected scenarios, the assessment of the exposure and vulnerability to these phenomena, and particularly to the most impactful events, is a priority to improve management and adaptation measures. Following the framework of the European project titled “Extreme meteorological and hydrological risk in Spain: impact assessment, future scenarios and tools to improve resilience and adaptation to climate change (EXMERISK)”, we aimed to conduct a high-resolution analysis identifying specific types of heatwaves linked to a higher number of deaths in Spain and estimating their probability of occurrence in future periods simulated under the SSP585 scenario (2036-2065, mid-century, and 2071-2100, end-century). Daily non-external, circulatory, and respiratory mortality for all population in Spain and separated by sex groups were provided by the Spanish National Institute, between 1985 to 2014. We used Weather Research and Forecasting (WRF) forced with ERA5 reanalysis and the outputs of the Community Earth System Model V2 (CESM2) to obtain dynamic simulations of climatic variables. Heatwaves were defined following the Spanish Meteorological Agency criteria (AEMET), in which for at least three consecutive days daily maximum temperature exceeded the 95th percentile between July-August and affecting at least 10% of the area under study. We determined specific characteristics of heatwaves linked to a higher number of deaths in Spain and estimated the probability of occurrence of future heatwaves of durations and magnitudes equal or higher than those associated with them. This study has relevant implications in the public health field, to better understand the expected occurrence of heatwaves which may be more impactful in terms of death and develop further measures to reduce the health burden and vulnerability associated with climate change.
How to cite: Salvador, C., Fernández-Alvarez, J. C., Gimeno-Sotelo, L., Alvarez-Socorro, G., Gimeno, L., and Nieto, R.: Exploring the probability of occurrence of the present-climate deadliest heatwaves in Spain in the mid- and end-century, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-906, https://doi.org/10.5194/ems2024-906, 2024.
In meteorological models, land use and soil texture play a key role in determining surface variables, as they intervene in the exchange of energy, moisture and momentum between the land and the air. In recent years, new data have been made public at higher resolutions, whether they are based on satellite, surveys or machine learning.
In this work we want to study the impact of using updated datasets of land use and soil textures in the WRF model (v4.3) with the Noah-MP surface parameterization, which operationally runs at Meteorological Service of Catalonia (SMC).
For the land use, we combine two sources, the Europe CORINE land cover (2018) at 100m resolution, and, with 1m resolution, one from the cartographic and geological institute of Catalonia (ICGC), an organization carrying out actions related to the awareness, survey and information about the soil and subsoil.
For soil texture, we use SOILGRIDS, a system for global digital soil mapping that makes use of global soil profile information and covariate data to model the spatial distribution of soil properties, which includes some additional variables such as silt, density and gravel. These let us analyze the impact of three different pedotransfer functions: Saxton & Rawls (2006), Wösten(1999), Weynants (2009) that transform the variables given by the soil texture to the ones needed by the model.
The results of the different initializations are verified against our surface station network for the spring 2023 to quantify their impact. Our results compared to the operational version show an improvement on wind and temperature, with a wider thermal range.
Bibliography
Jiménez-Esteve B, et al: “Land use and topography influence in a complex terrain area: a high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model.” Atmos Res, 202, (2018):49–62
Pedruzzi R. et al: “Update of land use/land cover and soil texture for Brazil: Impact on WRF modeling results over São Paulo”, Atmospheric Environment, 268, (2022)
Poggio, L., et al: “SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty”, SOIL, 7,(2021), 217–240
Saxton K.E. et al: “Estimating generalized soil-water characteristics from texture”, Soil Sci. Soc. Am. J., 50 (1986), pp. 1031-1036
Weynants M. et al: “Revisiting Vereecken pedotransfer functions: introducing a closed-form hydraulic model”, Vadose Zone J., 8 (2009), pp. 86-95
Wösten J.H.M. et al: “Development and use of a database of hydraulic properties of European soils”, Geoderma, 90 (1999), pp. 169-185
How to cite: Bravo, M., Mercader, J., and Moré, J.: Land use and soil texture effects on WRFv4.3 , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-459, https://doi.org/10.5194/ems2024-459, 2024.
The coastal regions of Antarctica are subject to frequent passages of low-pressure systems and transient pressure ridges. This synoptic-scale setup favors abrupt weather changes and occurrence of dangerous outdoor conditions such as snowstorms, extremely low wind-chill values due to low air temperature and strong winds, or intense solar radiation potentially leading to snow blindness. In this coastal zone most Antarctic research stations are located, and numerous scientific and logistical field activities are conducted. Under these circumstances, operational weather forecasts are of utmost importance. In this contribution, a WRF-based high-resolution weather prediction system is presented and evaluated. This experimental system was run to support the 2023 and 2024 summer expeditions to the J. G. Mendel Station on James Ross Island, Antarctic Peninsula. Initial and boundary conditions were provided by the GFS model, model topography by the Reference Elevation Model for Antarctica. The model configuration included the 3DTKE boundary layer scheme suitable for sub-kilometer resolutions, Thompson microphysics, RRTMG longwave and shortwave radiation schemes and the NoahMP land surface model. The model was run once a day in 500-m horizontal resolution (132-h lead time) and 1.5-km horizontal resolution (96-h lead time, more recent initial conditions). Forecasted time series of air temperature, wind speed and direction, precipitation amount, snow height, global radiation and sea-level pressure for multiple field locations were sent to the Mendel Station via a satellite internet service. The WRF model forecasts were validated with in-situ observations at the coastal Mendel Station (10 m a.s.l.) and the top of Davies Dome glacier (514 m a.s.l.). Furthermore, the model accuracy was compared with the output of publicly available Antarctic Mesoscale Prediction System (AMPS). Compared to AMPS, the WRF model in 500-m resolution massively improved air temperature prediction at Mendel Station, reducing mean bias from -4.2 °C to -0.8 °C in 2023. In late 2023, multiple AMPS physical parameterizations were updated, possibly contributing to reduced bias of -2.9 °C in the 2024 season. However, the WRF model still performed significantly better with bias of ‑0.5 °C. On Davies Dome, the WRF model performed slightly better in 2023 (by 0.4°C) while in 2024 the models performed similarly well. Regarding wind speed, both the WRF model and AMPS provided comparable results with mean bias 1.5 - 1.9 m·s‑1 at Mendel Station (more favourable for WRF) and 0.1 - 0.7 m·s‑1 on Davies Dome (more favourable for AMPS). Prediction of two significant snowfall events in 2023 was done with a very good accuracy.
How to cite: Matějka, M. and Láska, K.: Operational weather forecasting in Antarctica with the WRF model in sub-kilometer resolution, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-566, https://doi.org/10.5194/ems2024-566, 2024.
In the early afternoon hours of April 17, 2024, a severe thunderstorm hit northern Greece and more precisely the administrative area of Central Macedonia. The storm developed extreme characteristics, unexpected for an early spring storm. Its maximum height reached almost 11 kilometers and the maximum reflectivity was about 62dBZ. Seeding operations for the prevention of hail were performed in the context of the National Hail Suppression Program (NHSP) of Hellenic Agricultural Insurance Organization (ELGA). Even after the operations, hail was recorded in some of the hail pads along the storm’s 50 kilometers path.
Radar data from the C-band weather radar located at Filyro (30 kilometers east - southeast of the storm) are used to present the storm’s evolution while the synoptic environment of the onset and the following development of the storm is examined. The unusual high temperatures (+10°C above the climatic mean) in the days that preceded the storm seem to have played an important role in its final intensity.
The non-hydrostatic Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF-ARW 4.3.3) is used to perform multiple simulations to explore the model’s sensitivity to different parametrizations for this -out of its season- extreme storm. Three model domains with grid-spacings of 15km, 5km and 1.67km were used with the finer ones covering Greece and Northern Greece respectively. The parameterization used for operational forecast in the NHSP (inherently lighter due to limited computational power) proved good enough, giving almost the exact position and intensity but lagging for about a couple of hours in the time of the storm. The temporal evolution of the storm was better captured using more complex parameterizations.
How to cite: Tegoulias, I.: Summertime characteristics of a thunderstorm in April? Environmental causes and numerical investigation of a severe thunderstorm in Northern Greece using the WRF model, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-575, https://doi.org/10.5194/ems2024-575, 2024.
The region of Central Macedonia in northern Greece has a vital role in the financial life of the country because of its tourism and agricultural production. A primary objective of the Agroray project, which is a collaboration of Raymetrics S.A. and the Laboratory of Meteorology and Climatology of the Aristotle University of Thessaloniki, is the development of an operational high-resolution numerical weather prediction system that focuses on Pieria and its surrounding areas. This system provides timely and valid forecasts and allow the farmers to optimize their activities and protect their production from intense or high-impact weather events. It is based on the non-hydrostatic Weather Research and Forecasting (WRF) model with the Advanced Research dynamic solver. Three model domains, using telescoping nesting, cover: i) Europe, the Mediterranean Sea and northern Africa, ii) a large part of Greece and iii) central Macedonia, part of Thessaly and western Macedonia (central and northern Greece), at horizontal grid-spacings of 9 km, 3 km and 1 km, respectively. In the framework of the Agroray project, the meteorological forecasts become available to the farmers and the public (https://meteoray.com/en/). Kalman filtering is applied to the numerical forecasts at locations with station observations in order to reduce their systematic errors. The aim of this research is to present the meteorological model setup and its operational use, as well as to validate its performance during selected intense weather events (related to frost or intense precipitation) that affected the area of interest. The statistical scores were computed against station measurements and weather radar-estimated precipitation, using point statistics and a neighborhood-based technique, to investigate the impact of different model characteristics and surface input data on the model performance.
Acknowledgments: This research was carried out as part of the Agroray project, entitled “Development of a forecasting system and geographical indicators for the agriculture” (project code: KMP6-0078047) under the framework of the action “Investment Plans of Innovation” of the Operational Program “Central Macedonia 2014–2020”, which is co-funded by the European Regional Development Fund and Greece.
How to cite: Pytharoulis, I., Kartsios, S., Spyrou, C., Tegoulias, I., Bampzelis, D., and Zanis, P.: A WRF-based operational high-resolution numerical weather prediction system in northern Greece, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-592, https://doi.org/10.5194/ems2024-592, 2024.
The precipitation changes over mainland Southeast Asia (SEA) are important to water resources in many countries in this region. The diurnal cycle of precipitation is a crucial aspect of the local climate. The sub-daily convective activities and precipitation variability are strongly modulated by the surrounding complex topography However, the intricate interplay between topographical features and local atmospheric processes, and how they shape the spatial distribution of diurnal precipitation variability across SEA, remains unclear. This study investigates diurnal precipitation patterns and associated physical processes, particularly focusing on modeling the diurnal cycles in this region using convection-permitting models (CPMs). To investigate the effect of model resolution on diurnal precipitation and associated processes, we conducted two high-resolution simulations using the Weather Research and Forecasting (WRF) model driven by ERA5 at spatial resolutions of 9 and 3 km, focusing on summertime (June-August) during 2002-2005. We compared the output from the two WRF experiments to ERA5 and observation-based datasets, including in situ observations (GHCN-D), and gridded observations (APHRODITE, IMERG). The diurnal patterns in space were clustered into 5 distinct groups based on K-means classification. Compared with the ERA5 reanalysis, the two high-resolution WRF simulations show a reduced wet bias relative to IMERGE and better captured intense precipitation events found in the in situ measurements, while the precipitation in ERA5 is more similar to APHRODITE. Furthermore, the results show that the WRF simulations outperform ERA5 in capturing the spatial patterns of precipitation intensities and peak time, especially in mountainous and coastline regions, using IMERG as the reference. These differences can be explained by differences in convective available potential energy (CAPE) between the WRF simulations and ERA5, as well as near-surface winds. Between the two WRF simulations, the 3-km WRF simulation displays weaker precipitation intensities compared to the 9-km WRF simulations, which better match the hourly IMERG data, while the 9-km WRF simulations perform better in peak time of diurnal precipitation. Assessing the benefits of higher-resolution modeling is challenging because the benefits vary between variables and regions. In conclusion, the work highlights the importance of applying CPMs to capture diurnal cycles of precipitation, local convective activities (CAPE), and near-surface winds over complex topography.
How to cite: Lai, H.-W. and Ou, T.: Investigating the Diurnal Cycle of Summer Precipitation over Mainland Southeast Asia: Insights from Dynamic downscaling Simulations, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-25, https://doi.org/10.5194/ems2024-25, 2024.
