This study presents a comprehensive assessment of a very high-resolution reanalysis dataset developed for the entire Italian territory and the broader Alpine domain, spanning the 30-year period from 1990 to 2020. The dataset was produced via dynamical downscaling of the ERA5 reanalysis using the convection-permitting non-hydrostatic model MOLOCH, implemented at a spatial resolution of 1.8 km. This fine-scale resolution enables a more accurate representation of local-scale atmospheric processes, particularly in areas with complex terrain.

Validation was conducted against multiple high-resolution observational datasets, including GRIPHO, ARCIS, and the ISAC-CNR precipitation and temperature datasets. Additionally, comparisons were made with other state-of-the-art downscaled reanalysis products such as ERA5-LAND, CERRA-LAND, and MERIDA-HRES. Results confirm the dataset’s high reliability in reproducing key meteorological variables like near-surface temperature and precipitation, as well as its superior ability to capture higher-order statistical features such as event intensity, frequency, and extreme values.

The dataset’s utility is further demonstrated through a variety of multi-disciplinary applications. In hydrology, it allows for detailed drought monitoring and water balance assessments. In meteorology, it supports investigations into orographic effects and high-impact weather events. In the context of climate science, the dataset provides robust input for trend and variability analysis at local and regional scales.

This work highlights the critical role of very high-resolution reanalysis data in supporting both scientific research and decision-making processes. The dataset lays the groundwork for future applications in disaster risk reduction, infrastructure planning, and climate adaptation.

The financial support from Next Generation EU, Mission 4, Component C2 – INVESTIMENTO 1.1, CUP B53D23006850006, project “INTERROGATION” is gratefully acknowledged.

How to cite: Stocchi, P., Mohsin, T., Cavalleri, F., Davolio, S., Brunetti, M., Camici, S., and Mastrangelo, D.: MORE: High-Resolution MOLOCH-downscaled ERA5 REanalysis – Validation and Applications in Weather, Climate, and Hydrology, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-445, https://doi.org/10.5194/ems2025-445, 2025.

Reanalysis data sets are becoming increasingly popular for a broad spectrum of applications such as climate adaptation and mitigation, renewable energy, agriculture or hydrology, including the assessment of meteorological hazards and extremes. Recently, the high relevance of reanalysis data sets has been increased further due to their value as a basis for training AI-based NWP model emulators. Most of these applications require much finer grid spacing compared to ERA5 (31 km), ERA6 (14 km), or even ICON-DREAM (dual resolution reanalysis for emulators, applications, and monitoring, 13 and 6.5 km). Therefore, regional reanalysis is designed and produced for limited geographical regions, allowing for the provision of high-quality and high-resolution data sets.

 This presentation is a companion work with colleagues from the research and development department of DWD, who introduce the new concept for regional reanalysis and the adaptation to their new regional reanalysis product ICON-FORCE. We aim to present the sparse-input version of ICON-FORCE, named ICON-FORCE-c, which is designed for the needs of DWD's Climate and Environment business area. For this product, we will use only two types of observation data, which are 1) conventional observations and as a future update 2) SEVIRI radiometer satellite data.

ICON-FORCE-c will be produced using the operational 2 km ICON-LAM numerical weather prediction (NWP) model framework. Its operational data assimilation cycle comprises the KENDA LETKF-based data assimilation scheme at hourly intervals, complemented by a snow analysis every 6 hours, and T2M, SST and soil moisture analysis every 24 hours (at 00 UTC). The background error covariances are provided by a 20 member ensemble at the same 2.1 km resolution of the deterministic run. The boundary conditions come from the ICON-DREAM European nest domain.

As the concept summary, we introduce two versions of ICON-FORCE, 1) the full-input and 2) the sparse-input regional reanalyses. While full-input reanalyses aim to provide the best description of the Earth system, with the modern regional observational network, the sparse input reanalyses aims to provide the best possible climate state for the area, thus focusing on climate trends and its consistency. We demonstrate how changes in the observational system, which includes the introduction of new observations within a reanalysis, have the potential to cause artifical trends. 

In this work, we present in more detail the sparse-input regional reanalysis, whose period extent will be determined by the availability of the ICON-DREAM boundary data. We present first evaluation results comparing the performance of ICON-FORCE-c to the full-input version as well as ICON-DREAM.

How to cite: Kelbch, A., Valmassoi, A., Külheim, F., Borsche, M., and Spangehl, T.: Concept of the 2 km ICON-LAM reanalysis based on conventional observations for climate applications at Central Europe, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-477, https://doi.org/10.5194/ems2025-477, 2025.

This study presents a global reanalysis of land surface variables from 1981 to 2022 at a 0.25° x 0,25° spatial resolution, conducted using the ISBA land surface model within the SURFEX v9 modeling platform. Two experiments were performed: (1) an open-loop (OL) simulation with the ISBA land surface model and (2) a data assimilation analysis (ANA) experiment incorporating Leaf Area Index (LAI) observations in ISBA using the LDAS-Monde system. The simulations were forced offline with ERA5 reanalysis atmopsheric variables. The assimilated LAI dataset consists of THEIA AVHRR-derived observations from 1981 to 2018, and of Copernicus Land Monitoring Service (CLMS) GEOV2 from 2019 to 2022.

The study analyzes the impact of LAI assimilation on surface variables, with a particular focus on soil temperature anomalies at deep layers. By comparing the OL and ANA runs, we assess how improved vegetation representation influences soil thermal dynamics and energy exchanges over multiple decades.

To validate the impact of LAI assimilation, an evaluation is conducted over France, where in situ temperature observations at 1m depth are available from more than 70 automatic weather stations. This comparison provides insight into how LAI assimilation affects subsurface thermal conditions and helps quantify its added value in the reanalysis. Additionally, on a global scale, we assess the impact of LAI assimilation on Gross Primary Production (GPP), highlighting the improvements observed after integrating LAI observations into the model.

This long-term global reanalysis, spanning over 40 years, provides a unique dataset for studying historical land surface dynamics and their interactions with climate variability. Having both OL and ANA simulations is crucial, as the OL experiment serves as a benchmark for understanding long-term trends driven by atmospheric forcing alone, while the ANA experiment allows us to quantify the impact of observational constraints on land surface processes. This dual approach is essential for improving our confidence in land surface modeling, enabling better representation of vegetation-atmosphere interactions, and providing a solid foundation for future climate studies, hydrological assessments, and ecosystem monitoring.

How to cite: Rojas Muñoz, O. J., Calvet, J.-C., and Bonan, B.: Assessing the impact of LAI data assimilation in a multidecadal global reanalysis, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-37, https://doi.org/10.5194/ems2025-37, 2025.

Climate change is currently one of the main threats our planet is facing. Observations are playing a pivotal role in underpinning the science to understand the climate system and monitor its changes including extreme events, which have adverse effects on human lives. Information generated from measurements by Earth observation satellites contribute significantly to the development of this understanding and to the continuous monitoring of ongoing climate change and its impacts. However, the meaningful use of data from these satellites requires them to be long-term, spatially and temporally homogeneous, and uncertainty characterised. The process of preparing satellite data for climate studies is tedious and only recently being recognised as fundamental first step in preparing records of Essential Climate Variables (ECV) from these data.

During the last decade EUMETSAT has generated several fundamental climate data records (FCDR) consisting of measurements from instruments operating from microwave to visible frequencies. These measurements are not only from EUMETSAT’s own satellite but also from satellites operated by other agencies such as NOAA and CMA. Scientific advances for the data generation have been made through several EU research projects such as ERA-CLIM, FIDUCEO and GAIA-CLIM. FIDUCEO project was pivotal for developing a framework for characterising uncertainties of Earth Observation data. The principles developed in the project have been adapted and or extended by EUMETSAT by including other sensors and by consolidating longer time series.

This presentation outlines the basic principles of FCDR generation illustrated through a few examples. Basic steps of the FCDR generation is comprised of quality control of the raw data, recalibration of the raw data to produce physical quantities, such as radiances or reflectance, generate quality indicators, and create the outputs in user-friendly formats, e.g., NetCDF4. Furthermore, uncertainty characterisation and harmonisation of a suit of instruments are performed. We illustrate these principles by two examples, one on the creation of harmonised time series of microwave humidity sounder data and the other on the creation of FCDRs from geostationary satellite infrared and visible measurements. 

These FCDRs are then used to create data records of ECVs for example by the EUMETSAT Satellite Application Facilities (SAFs). EUMETSAT data records support international research activities in the World Climate Research Programme (WCRP) and national and international climate services such as the Copernicus Climate Change Service. Illustration of the use of FCDRs to improve the quality of CDRs will be presented.

How to cite: John, V. O.: Uncertainty characterised Fundamental Climate Data Records for the use in renalyses, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-535, https://doi.org/10.5194/ems2025-535, 2025.

The ARRA re-analysis is based on the AROME numerical weather prediction (NWP) system at 1.3 km over France. ARRA will cover the period 1961-2020 and will catch up the real time in 2026. ARRA, because of its high horizontal resolution, uses as the lateral boundary conditions the UERRA re-analysis produced at 11km for the period 1961-1984 and the European Copernicus CERRA reanalysis, produced at 5.5 km resolution after 1984.

With this new re-analysis at the kilometer scale with a non-hydrostic model, small-scale phenomena such as convection, orographic wind and extreme precipitation should be significantly improved compared to the ERA5 global re-analysis or the European Copernicus re-analysis (CERRA).

The ARRA reanalysis has a 3-hour cycle for the surface analysis (air temperature and humidity at 2 meters, snow and soil moisture) associated with the Incremental Analysis Update (IAU) technique for the upper atmosphere using UERRA or CERRA analysis. An other component, called ARRA-Land and produced at the same resolution, will focus on surface variables, snow and soil moisture. ARRA-Land is an offline simulation of the SURFEX modeling platform with more advanced surface physics than in ARRA and is driven by the ARRA atmospheric forcing fields and by an analysis of 24-hour cumulative precipitation (MESCAN (Soci et al. 2016)).

After a brief description of the system configuration and production status, a preliminary comparison with ERA5 and CERRA will be presented, focusing on several cases of extreme precipitation over France such as Nimes (1988), Vaison-La-Romaine (1992), … and in the Alps such as 22-25 September 1993 in Switzerland. The added value of the 24hour-precipitation analysis for the selected cases will be discussed in the perspective of the ARRA-Land product.

ARRA re-analysis data will probably be used for training purposes in the perspective of an AI based version of AROME.

How to cite: Bazile, E., Le Moigne, P., Van Hyfte, S., Selly, Y., Verrelle, A., Willemet, J.-M., Blanc, P., Monteiro, D., and Rousset, F.: Preliminary evaluation of the ARRA re-analysis over France : focus on extreme precipitation, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-648, https://doi.org/10.5194/ems2025-648, 2025.

Reanalyses are commonly employed for the analysis of climatological trends due to their emphasis on temporal consistency. The ERA5 reanalysis family, comprising the deterministic ERA5-HRES and the ensemble-based ERA5-EDA, has proven to be a valuable resource for trend extraction. In this study, long-term trends (1941–2000) in total annual precipitation are examined across three regions: the Alps, Italy, and Fennoscandia.

It is recognized that variations in the observational systems used for data assimilation impact water cycle components like precipitation. This fact raises the question of to what extent temporal variations in ERA5 precipitation amounts are solely a result of climate variations and the influence of changes in the observational system impacting simulation accuracy. Addressing this issue, this work compares ERA5-HRES and ERA5-EDA with three additional ECMWF reanalyses, CERA-20C, ERA-20C, and ERA-20CM, using homogenized, trend-focused observational datasets: LAPrec1901 (for the Alps), UniMi/ISAC-CNR (for Italy), and NGCD (for Fennoscandia).

The results show that isolating the climatological signal in ERA5 from the effects of observational system changes presents a significant challenge. Distinct trend behavior is identified in ERA5 data for the period 1940–1970, especially over the Alps and, to a lesser extent, Italy and Norway, diverging from observed trends. An increasing, though non-linear, trend in the deviation from observational datasets is observed prior to 1970, with widespread differences over large mountain areas. In contrast, more localized increasing trends are detected after 1970.

These findings emphasize the necessity of accounting for the influence of evolving data assimilation systems when interpreting precipitation trends from reanalyses. Enhancing future reanalysis interpretability could benefit from adopting a model-only integration for the same period, as implemented in ERA-20C and ERA-20CM, to help disentangle climate-driven signals from those introduced by the assimilation process.

This assessment underlines the critical need for careful evaluation of long-term precipitation trends in reanalyses and supports the continued development of auxiliary configurations to improve the robustness of climate trend analyses.

How to cite: Cavalleri, F., Lussana, C., Manara, V., Brunetti, M., and Maugeri, M.: A Temporal Consistency Analysis of Long-Term Precipitation Trends in ERA5 and other ECMWF reanalyses over the Alps, Italy, and Fennoscandia, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-230, https://doi.org/10.5194/ems2025-230, 2025.

This study investigates the mean meridional wind patterns and their long-term trends within the Northern Hadley Cell (NHC) from 1980 to 2022, using reanalysis datasets and radiosonde observations. The Hadley circulation, a key component of Earth’s atmospheric circulation, is vital in redistributing heat and momentum between the equator and mid-latitudes. Understanding changes in its strength and structure is essential for interpreting current climate dynamics and improving projections of future climate change.

Our analysis reveals a consistent discrepancy between reanalyses and radiosonde measurements in representing the vertical structure of the NHC. Specifically, reanalyses tend to underestimate the mean poleward flow in the upper troposphere compared to radiosonde data while accurately capturing equatorward flow in the lower troposphere. Despite climate model projections generally indicating a weakening trend of the NHC under global warming, our examination of radiosonde data shows no statistically significant long-term trend. This absence of a clear signal in observational data introduces additional uncertainty into future projections of the Hadley circulation's response to climate change.

In contrast, reanalysis datasets, including ERA5, suggest a strengthening of the NHC over recent decades, mainly driven by an intensification of the upper-tropospheric poleward branch. To assess the reliability of this trend in reanalyses, we analysed the analysis increments from ERA5, which represent the corrections applied during data assimilation. Our findings indicate that the observed strengthening trend is not an artefact introduced by the data assimilation process. Instead, the analysis increments tend to nudge the first-guess model state, which underestimates the NHC strength, toward stronger meridional circulation, aligning more closely with assimilated observations.

These results highlight the importance of using multiple data sources when assessing long-term atmospheric trends and caution against relying solely on either reanalyses or climate model projections. The divergence between observational and reanalysis-based trends underscores ongoing uncertainties in the behaviour of large-scale circulation systems under climate change and calls for further investigation into the causes of these discrepancies.

How to cite: Pikovnik, M. and Zaplotnik, Ž.: The Changes of the Northern Hadley Cell Strength in Reanalyses and Radiosonde Observations, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-78, https://doi.org/10.5194/ems2025-78, 2025.

The tropics are expanding poleward as a result of anthropogenic climate change, this in turn has great implications on the temperature and precipitation patterns in the subtropical regions. Previous studies have found varying widening trends, most of which have been derived using reanalysis and climate model data including complex error characteristics due to their inherent choices. These discrepancies in the widening trends underline the interest for studies using alternative datasets with reduced uncertainty.

Here, we explore the potential of GNSS radio occultation (RO) data for the analysis of the tropical width, as an independent observational source of information. RO data has many advantages characteristics such as high accuracy, global availability and long-term consistency. Another valuable attribute is the high vertical resolution in the upper troposphere. These specific advantages make it highly interesting for the study of tropical atmospheric phenomena. The RO processing provides a high-quality temperature record over the period September 2002 to December 2020, with dense horizontal coverage since 2006.

To evaluate the skill of RO data to accurately capture the expansion of the tropics, we look at four different metrics which are commonly analyzed in studies of the tropical width: the tropopause break, the eddy driven jet and the subtropical jet. To calculate these metrics temperature and wind data is necessary. Synoptic-scale climatic winds from RO geopotential height records are being derived in the Wegener Center research group. These monthly wind records include as a novelty higher-order solutions of the wind-field equations. The metric results are compared to three state-of-the-art reanalysis datasets (i.e., ERA5, MERRA-2, and JRA-3Q). In this process, zonal patterns and the regional structure of the tropospheric features are investigated to further test the utility of RO in respect to its spatial robustness. Moreover, we aim to provide a perspective on the needed record length to calculate trends for these metrics.

Comparison to reanalyses shows good agreement between the different datasets for zonal average monthly mean values over the available RO record period. As for the analysis of the longitudinally resolved metrics, results from reanalyses and RO align well with some exceptions over the northern hemisphere. While the RO record 2006 to 2020 is yet too short for trend studies on tropical widening, we find overall encouraging results that suggest RO to be an alternative observation-based dataset to modern reanalysis. RO data will be valuable for future trend studies of tropical features, especially due to its long-term consistency and high accuracy.

How to cite: Reiter, A., Danzer, J., and Steiner, A.: Exploring the potential of GNSS radio occultation for the analysis of tropical width metrics, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-360, https://doi.org/10.5194/ems2025-360, 2025.