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.

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 95^th 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.