2024

1. [Bello-Millán et al. 2024] Abstract A tornadic supercell near the village of Campillos (Malaga province) occurred on 26 August 2019 with several associated damages. In this study, we analyze the sensitivity of the Weather Research and Forecasting (WRF) model to initial and boundary conditions and microphysics parameterizations when reproducing this particular event. A total of 20 cases were simulated with four initial and boundary conditions (ERA5, GDAS/FNL, GFS, HRES-IFS) and five microphysics parameterizations (WDM6, Goddard, Morrison, Thompson, WSM6). Forecasts are quantitatively compared with 10-min observations at 153 weather stations for the following variables: temperature at 2 m (T2), relative humidity at 2 m (RH2), wind speed at 10 m (U10) and accumulated precipitation in 3 h (PCP3h). Similarly, the spatial verification method MODE (Method for Object-Based Diagnostic Evaluation) has been used to evaluate the reproduction of convective storms by high-resolution numerical simulations. Our results indicate that microphysics plays a key role in this event, being more relevant than initial and boundary conditions. In particular, Goddard configuration combined with ERA5 or IFS initial and boundary conditions has shown the best overall performance. Simulation based on Goddard and ERA5 captured features to diagnose the development of severe convection. Therefore, WRF model, with the correct parameter sets, was able to reproduce the environmental conditions for supercell formation. The spatial resolution used in the simulations was appropriate to explicitly generate a supercellular storm, although it was not sufficiently high to resolve the formation of tornadoes. Nevertheless, the model showed signs of an environment favourable to tornadogenesis.
   WRF, microphysics, tornadic supercell

2. [Ridal et al. 2024] Abstract. A regional reanalysis has been produced for a domain covering entire Europe from 1984 to 2021. The reanalysis is produced as part of the Copernicus Climate Change Service. The Service provides the high-resolution deterministic Copernicus European Regional Reanalysis (CERRA), run at a horizontal resolution of 5.5 km, a 10-member ensemble run at 11-km resolution as well as an offline surface analysis, CERRA-Land. CERRA-EDA uses an ensemble data assimilation (EDA) technique to perturb the initial condition of the different members. Apart from the horizontal resolution the CERRA and CERRA-EDA setups are the same; for example, the same data assimilation scheme, same physics parameterization as well as the same vertical levels. These new systems are built from HARMONIE cy40 version, including some back-phased physics from a newer model version (cy42). Conventional observations, satellite-based radiances, atmospheric motion vector winds and bending angle from radio occultation observations are used. In addition, ground-based zenith total delay (ZTD) from global navigational satellite systems (GNSS) and local surface observations, rescued from historical archives at the local National Meteorological Services, are used. Another new feature is the construction of the background error statistics for the data assimilation. Information from the ensemble run, CERRA-EDA, is used in the derivation of the background error statistics for the high-resolution CERRA runs. These background error statistics are updated every second day. By doing so, daily environment variation is taken into account as well as all variations over the 37 years of production. The reanalyses and reforecasts from CERRA show an added value compared to the global ERA5 for almost all variables at the surface level. This becomes particularly clear when selecting smaller areas with complex terrain where the high resolution is beneficial. In the free atmosphere it is primarily the analyses and short forecasts, 3–6 hours, that give an added value.
   Cerra

3. [Schumacher et al. 2024] Abstract In the 2022 summer, western–central Europe and several other regions in the northern extratropics experienced substantial soil moisture deficits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change using observation-driven soil moisture estimates and climate models. We find that in western–central Europe, a June–August root zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate but would have occurred only about once per century during preindustrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to simulate soil moisture with land surface models driven by meteorological data. Nevertheless, observation-based products indicate long-term declining summer soil moisture for both regions, and this tendency is likely fueled by regional warming, while no clear trends emerge for precipitation. Finally, our climate model analysis suggests that under 2 ∘C global warming, 2022-like soil drought conditions would become twice as likely for western–central Europe compared to today and would take place nearly every year across the northern extratropics.
   Drought 2022

4. [Solano-Farias et al. 2024] Abstract Convection-permitting models (CPMs) enable the representation of meteorological variables at horizontal high- resolution spatial scales (≤ 4 km), where convection plays a significant role. In this regard, physical schemes need to be evaluated considering factors in the studied region such as orography and climate variability. This study investigates the sensitivity of the Weather Research and Forecasting (WRF) model as CPM to the use of different physics schemes on Andalusia, a complex orography region in the southern part of the Iberian Peninsula (IP). To do that, a set of 1-year WRF simulations was completed based on two “one-way” nested domains: the parent domain (d01) spanning the entire IP with 5 km spatial resolution and the nested domain (d02) for the region of Andalusia at 1 km of spatial resolution. 12 physic schemes were examined from combinations of microphysics (MP) schemes including THOMPSON, WRF single moment 6-class (WSM6), and WRF single moment 7-class (WSM7), and different options for the convection in d01, the Grell 3D (G3), Grell-Freitas (GF), Kain-Fritsch (KF), and deactivated cumulus parameterization (OFF). The simulated precipitation and 2-m tem- perature for the year 2018, characterized to be a very wet year, were compared with observational datasets from different sources to determine the optimal WRF configuration, including point-to-point and station-point com- parisons at different time aggregations (from annual to hourly). In general, greater differences were shown when comparing the results of convection schemes in d01. Simulations completed with GF or OFF presented better performance compared to the reference datasets. Concerning the MP, although THOMPSON showed a better fit in high mountain areas, it generally presents a worse agreement with the reference datasets. In terms of tem- perature, the results were very similar and, therefore, the selection of the “best” configuration was based mainly on the precipitation results with the WSM7-GF scheme being suitable for Andalusia region.
   WRF CPS, precipitation, Andalucia

5. [de Vrese et al. 2024] Abstract Rising temperatures entail important changes in the soil hydrologic processes of the northern permafrost zone. Using the ICON‐Earth System Model, we show that a large‐scale thaw of essentially impervious frozen soil layers may cause a positive feedback by which permafrost degradation amplifies the causative warming. The thawing of the ground increases its hydraulic connectivity and raises drainage rates which facilitates a drying of the landscapes. This limits evapotranspiration and the formation of low‐altitude clouds during the snow‐free season. A decrease in summertime cloudiness, in turn, increases the shortwave radiation reaching the surface, hence, temperatures and advances the permafrost degradation. Our simulations further suggest that the consequences of a permafrost cloud feedback may not be limited to the regional scale. For a near‐complete loss of the high‐latitude permafrost, they show significant temperature impacts on all continents and northern‐hemisphere ocean basins that raise the global mean temperature by 0.25 K.
   ICON ESM, cloud feedback

6. [van Westen et al. 2024] Abstract: One of the most prominent climate tipping elements is the Atlantic meridional overturning circulation (AMOC), which can potentially collapse because of the input of fresh water in the North Atlantic. Although AMOC collapses have been induced in complex global climate models by strong freshwater forcing, the processes of an AMOC tipping event have so far not been investigated. Here, we show results of the first tipping event in the Community Earth System Model, including the large climate impacts of the collapse. Using these results, we develop a physics-based and observable early warning signal of AMOC tipping: the minimum of the AMOC-induced freshwater transport at the southern boundary of the Atlantic. Reanalysis products indicate that the present-day AMOC is on route to tipping. The early warning signal is a useful alternative to classical statistical ones, which, when applied to our simulated tipping event, turn out to be sensitive to the analyzed time interval before tipping.
   AMOC tipping and precursors.

7. [Wu et al. 2024] ABSTRACT: Atmospheric winds are crucial to the transport of heat, moisture, momentum, and chemical species, facili- tating Earth’s climate system interactions. Existing weather and climate studies rely heavily on the wind fields from reanal- ysis datasets. In this study, we analyze the uncertainty of instantaneous atmospheric winds in three reanalysis (ERA5, MERRA-2, and CFSv2) datasets. We show that the mean wind vector differences (WVDs) between the reanalysis datasets are about 3–6 m s21 in the troposphere. The mean absolute wind direction differences can be more than 508. Large WVDs greater than 5 m s21 are found for 30%–50% of the time when the observed precipitation rate is larger than 0.1 mm h21 over the eastern Pacific Ocean, Indian Ocean, Atlantic Ocean, and some mountain areas. The mean WVDs exhibit sea- sonal variations but no significant diurnal variations. The uncertainty of vertical wind shear has a correlation of 0.59 with the uncertainty of winds at 300 hPa. The magnitudes of vorticity and horizontal divergence uncertainties are on the order of 1 3 1025 s21, which is comparable to the mean values of vorticity and horizontal divergence. In comparison with some limited observations from field campaigns, the reanalysis datasets exhibit a mean WVD ranging from 2 to 4.5 m s21. Among the three reanalysis datasets, ERA5 shows the closest agreement with the observations while MERRA-2 has the largest discrepancy. The substantial uncertainty and errors of the reanalysis wind products highlight the critical need for new satellite missions dedicated to 3D wind measurements.
   Wind; Model comparison; Reanalysis data