Frequency analysis of rainfall intensities or rainfall depths (precipitation totals) is usually performed by estimating respective design values occurring on average once per a given number of years (return period N). Estimates of design rainfall depths R_N (design precipitation totals) with a given frequency F = 1 / N for different rainfall durations D can be fitted with a depth-duration-frequency (DDF) curve defined by a suitable mathematical function. For a given return period, the DDF curve depicts the increase of the design precipitation total when increasing the duration (length of the considered time window). Thus, each DDF curve is monotonically increasing, while its slope gradually decreases with increasing rainfall duration.

For a limited range of rainfall durations (e.g., from 0.5 to 3 hours), design precipitation totals can be fitted by a single power function. However, this statistical model becomes less reliable or even useless when employing either shorter or longer durations, because the DDF curve gets a much more complex shape then. We also provide a possible explanation of such complex shapes of DDF curves as a result of different meteorological conditions producing high precipitation totals of different durations. Two tipping points of the DDF curve can be due to the transition from the scale of single convective cells to the scale of whole multicellular storms, as well as from the scale of multicellular storms to the synoptic scale. Thus, differences of shapes of DDF curves between lowlands and highlands can be explained by changes of representation of convective and stratiform rains among precipitation maxima of different duration.

How to cite: Müller, M., Crhová, L., and Kašpar, M.: Complex shapes of rainfall depth-duration-frequency curves, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1030, https://doi.org/10.5194/ems2024-1030, 2024.

In August 2023, the extreme weather event “Hans” moved into Scandinavia from the southeast, bringing large amounts of rainfall. It led to large-scale floods, a number of landslides and forced evacuations across large parts of southeastern Norway, and ended up costing more than 150 million Euros.

In Norway, water poses the largest physical climate risk, and adaptation to prepare for such events is crucial. Successful adaptation relies on accurate design values for any location, area (such as a catchment), as well as for a future climate.

We will show results from a project focusing on all the aforementioned aspects. Specifically, we will present 

• a user-friendly web tool offering design values for short-duration rainfall at any location in Norway, based on a spatial model with observations and gridded covariates as input (Dyrrdal et al., 2015),
• a framework for updating recommended climate change allowances based on user needs, to account for a changing climate in long-term planning and infrastructure design, and 
• estimated Areal Reduction Factors (ARFs), which convert point estimates of extreme precipitation to estimates of extreme precipitation over a spatial domain, often used in flood risk estimation (Lutz et al., 2024). This analysis considers regional and seasonal dependence in ARFs for extremes of different durations based on gridded data products and provides preliminary recommendations for updated ARFs in Norway

References:

Brox Nilsen, I., Bratlie, R., Dyrrdal, A.V., Engeland, K., Hisdal, H., Lawrence, D., and Øye Leine, A.-L., 2023: Brukerbehov for justerte anbefalinger om klimapåslag (“User needs associated with adjusted recommendations of climate change allowance”; in Norwegian”), VANN, 03/2023

Dyrrdal, A.V., Lenkoski, A.,Thorarinsdottir, T.L., and Stordal, F., 2015: Bayesian hierarchical modeling of extreme hourly precipitation in Norway. Environmetrics, 26(2), 89-106, https://doi.org/10.1002/env.2301

Lutz, J., Roksvåg, T., Dyrrdal, A.V., Lussana, C., Thorarinsdottir, T., 2024: Areal reduction factors from gridded data products, Journal of Hydrology, in print. Available at https://doi.org/10.1016/j.jhydrol.2024.131177

How to cite: Dyrrdal, A. V., Lutz, J., Roksvåg, T., Lussana, C., Thorarinsdottir, T., Grinde, L., and Nilsen, I. B.: Design precipitation - new results for Norway, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-915, https://doi.org/10.5194/ems2024-915, 2024.

Many countries currently develop or improve their national strategies against natural hazards, especially against those related to weather phenomena. This is particularly important because of possible future changes in extreme weather statistics. Regarding precipitation, the increase of its intensity is generally expected in a number of regions due to the warming climate. However, major river floods are caused by extreme precipitation events affecting large areas. Therefore, it is necessary to study possible changes also in other characteristics of precipitation events, namely, the spatial extent and distribution of precipitation, and the duration of the events including a possible shift in the season of their occurrence.

The presentation focuses on the assessment of possible changes in heavy rain characteristics in Czechia within the activities of the national project PERUN. We use outputs from the Aladin-CLIMATE/CZ model and follow up on the already published analysis of extremes for the past period 1961-2020, in which we used measurements at rain gauge stations. We employ three types of model runs providing one- to five-day precipitation totals with the horizontal resolution of 2.3 km: (i) model re-analysis covering the period 1990-2019 and serving to the validation of the model in terms of its ability to simulate past extremes, (ii) historical (control) run covering the period 1981-2014, and (iii) climatological run covering the period 2015-2099 and considering two scenarios SSP5-8.5 and SSP2-4.5. Changes in heavy rain characteristics are evaluated by the comparison of outputs from the climatological and historical run. Due to the multiplication of impacts of heavy rains when occurring in larger area, we proposed an areal approach of their evaluation. We apply the weather extremity index (WEI), a universal indicator which is a function of the affected area and the average return period of precipitation totals considering the rainfall duration when the WEI is the highest. This enables to detect the events with the heaviest rains and their characteristics in the period of interest.

First results indicate higher frequency of extreme rainfall events occurring also in the cold half year which have circulation causes generally different from the summer ones. This opens the door for the next research devoted to the study of circulation anomalies which induce the events.

How to cite: Kašpar, M., Müller, M., and Zacharov, P.: Possible future changes in extreme rainfall events in Czechia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1028, https://doi.org/10.5194/ems2024-1028, 2024.

Since its founding in 1989, the Global Precipitation Climatology Centre (GPCC) has been producing global precipitation analyses based on land surface in-situ measurements. This year the GPCC marks its 35th anniversary. During these years the precipitation database has been continuously expanded and includes a high station density and large temporal coverage. Due to the semi-automatic quality control routinely performed on the incoming station data, the GPCC database has a very high quality. Today, the GPCC holds data from more than 126,000 stations, about three quarters of them having long time series.

The core of the analyses is formed by data from the global meteorological and hydrological services, which provided their records to the GPCC, as well as national meteorological and hydrological services from all over the world.  In addition, the GPCC receives SYNOP and CLIMAT reports via the WMO-GTS. These form a supplement for the high quality precipitation analyses and the basis for the near real-time evaluations.

Quality control activities include cross-referencing stations from different sources, flagging of data errors, and correcting temporally or spatially offset data. This data then forms the basis for the following interpolation and product generation.

In near real time, the 'First Guess Monthly', 'First Guess Daily', 'Monitoring Product', ‘Provisional Daily Precipitation Analysis’ and the 'GPCC Drought Index' are generated. These are based on WMO-GTS data and monthly data generated by the CPC (NOAA).

With a 2-3 year update cycle, the high quality data products are generated with intensive quality control and built on the entire GPCC data base. These non-real time products consist of the 'Full Data Monthly', 'Full Data Daily', 'Climatology', and 'HOMPRA-Europe' and are now available in the 2022 version.

All gridded datasets presented in this paper are freely available in netcdf format on the GPCC website https://gpcc.dwd.de and referenced by a digital object identifier (DOI). The site also provides an overview of all datasets, as well as a detailed description and further references for each dataset.

How to cite: Rustemeier, E., Ziese, M., Schirmeister, Z., Finger, P., Heller, A., Schulze, R., Zepperitz, M., Fränkling, S., and Breidenbach, J. N.: Overview of the gridded daily and monthly precipitation data sets provided by the Global Precipitation Climatology Centre (GPCC), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-952, https://doi.org/10.5194/ems2024-952, 2024.

The goal of this research was to assess the aridity of the Iberian Peninsula (IP) and its susceptibility to precipitation extreme events (PEEs) throughout a long historical period of 1950–2022 and a shorter historical period of 1981–2022, by calculating two aridity indices, eight extreme precipitation indices, and two recently-developed extreme precipitation susceptibility indices (EPSIs), namely a composite index and a principal component analysis-based index. The calculations were based on ERA5-Land reanalysis data, previously bias-corrected with observational data from the Iberia01 dataset as a baseline in a 1971–2015 overlapping period, using a quantile-mapping approach. By performing a trend analysis with the Mann-Kendall non-parametric test for the two study periods, annual and seasonal drying trends over southwestern, central and northeastern regions were detected, as well as an annual wetting trend over the southeast. The assessment of PEEs’ contribution to total precipitation presented higher values, of around 24% to 28%, over eastern IP, and showed that it is increasing in several coastal regions during winter, as well as in north-central regions during summer and annually. The most susceptible regions to extreme precipitation events (high to very high susceptibility) are found on the mountains’ Atlantic-facing (western IP mountains) or Mediterranean-facing (eastern IP mountains) side and correspond to approximately 50% of the IP territory. The IP’s inner regions present low to moderate susceptibility. The results achieved agree with previous studies’ results, and give a highly detailed illustration of the PEEs’ susceptibility map of the IP and the recent past trends of all IP regions, which is a novelty comparatively to past studies. These data have a variety of applications, e.g., to improve assessment and mitigation of urban flood risks, mitigate water scarcity in the agro-food industry, or prevent crop destruction during extreme precipitation events.

Acknowledgments: Research funded through National Funds by FCT – Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020 and LA/P/0126/2020 (https://doi.org/10.54499/UIDB/04033/2020). The corresponding author thanks FCT and MIT Portugal Program for their support through the grant PRT/BD/154652/2023.

How to cite: Claro, A., Fonseca, A., Fraga, H., and Santos, J.: Extreme precipitation and aridity in Iberian Peninsula: a new high-resolution susceptibility analysis over 1950–2022, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-139, https://doi.org/10.5194/ems2024-139, 2024.

Sub-estimation of weather radar quantitative precipitation estimates (QPE) is often attributed to the classical mechanism of precipitation evaporation below the cloud layer. The aim of this study is to investigate the potential impact of evaporation on radar reflectivity profiles using data from co-located automatic weather stations (AWS), which furnish ground-level measurements of air temperature, pressure, and relative humidity.  The study is based on a six-year observational dataset from an area characterized by intense agricultural activity and divided into two sub-areas: an irrigated area and a rainfed area, separated by an artificial channel. The research is carried out over The Land Surface Interactions with the Atmosphere over the Iberian Semi-arid Environment (LIAISE) domain, in the eastern Ebro valley in Catalonia (NE Spain) using C-band weather radar observations and AWS data from the Meteorological Service of Catalonia.

Although the analysis revealed clear differences in average ground-level temperature and humidity between the irrigated and non-irrigated areas in dry days during the warm season, no clear differences were found on average precipitation frequency, intensity, amount and convective fraction between the two sub-areas.  A more detailed study, specifically focusing on reflectivity profiles occurring during the first 30 minutes of rain following a 24-hour dry period, was conducted to examine cases prone to rainfall evaporation. The results indicated that after a 30-minute period of the rainfall onset, ground-level AWS temperature and relative humidity of both irrigated and rainfed areas -which were different before rainfall- tended to converge indicating that during rainfall ground level conditions are quickly homogenized. Finally, for this 30 first minutes and specific conditions, radar reflectivity observations at 1 km height did exhibit a statistically significant correlation with ground-level relative humidity for convective cases, irrespective of the sub area (irrigated or rainfed) considered. These results contribute to enhance our understanding of possible evaporation effects on weather radar QPE and may serve as a basis for the future development of an evaporation correction method. This study was supported by projects RTI2018-098693-B-C32 and PID2021-124253OB-I00.

How to cite: Polls, F., Peinó, E., Udina, M., and Bech, J.: Investigating ground-level relative humidity and radar reflectivity using C-band weather radar observations in two contiguous irrigated and rainfed areas, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-453, https://doi.org/10.5194/ems2024-453, 2024.

Assessing global precipitation trends with some degree of certainty under climate change is a challenge for the scientific community. Therefore, accurate and reliable observations of this variable are required on a global scale that extend to climatological time scales. For this purpose, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is currently the only active sensor able to provide, at global scale, three-dimensional measurements of the structure and characteristics of precipitation. In this study, the performance of the variable's precipitation intensity, radar reflectivity factor (Z_Ku and Z_Ka) and Drop Size Distribution (DSD) parameters (weighted mean diameter, D_m; intercept parameter, N_w) of the GPM DPR are evaluated. For this purpose, information from seven disdrometers (OTT Parsivels^{1, 2}) located in different topographic areas of the northeast of the Iberian Peninsula is used as reference. Comparison of the DSD parameters show an overestimation of D_m approximately 0.1 mm at low and moderate precipitation rates (0.1-4 mm/h) and of 0.4 mm at precipitation rates higher than 4 mm/h by the dual-frequency DPR algorithm regarding the disdrometer. In contrast, the performance of N_w is underestimated by the DPR, with a maximum value close to 6 dB at moderate precipitation rates (4-8 mm/h). The lowest errors were observed regarding radar reflectivity factor and D_m, while the agreement was poorer considering the N_w and rainfall index.  This lack of accuracy of the GPM DPR rainfall index measurement in Catalonia could be due to the use of predefined constants in the relationships between the rainfall rate and the D_m on which its algorithm is based. This suggests an in-depth investigation of the retrieval algorithms adopted to improve their performance, which requires more disdrometer data to increase precipitation sampling opportunities.

How to cite: Peinó, E., Bech, J., Polls, F., Udina, M., Petracca, M., Adirosi, E., Gonzalez, S., and Boudevillain, B.: Validation of GPM DPR rainfall and Drop Size Distribution through disdrometers in the Northeastern Iberian Peninsula, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-503, https://doi.org/10.5194/ems2024-503, 2024.

Rainfall microphysics is a critical component for numerous applications including remote sensing and quantitative precipitation estimations, meteorological and hydrological modeling, soil erosion, and telecommunication signal propagation in the atmosphere. This study delves into the effects of wind on rainfall microphysics by utilizing high-resolution commercially available and in-house developed meteorological instruments. Specifically, here we present our findings on the effects of wind on the evolution of raindrop size distribution (DSD) and the governing microphysical processes (i.e. raindrop fall and collisions). This is an observation-based study utilizing high-resolution field measurements. The effect of wind on DSD observations was uncovered using a large dataset available from a multi-institutional field campaign that was conducted in central Oklahoma. The fall and collisions of raindrops were investigated using a large dataset collected at our outdoor rainfall laboratory located on the West campus of the University of Texas at San Antonio, Texas, USA during a 3-year-long field campaign. The dataset includes observations from a unique optical-type disdrometer, called High-speed Optical Disdrometer (HOD), that we developed. HOD’s innovative technology enables capturing high-resolution sequential images of the same hydrometeor multiple times as it passes through the measurement volume to provide high-accuracy measurements of hydrometeor characteristics and visual observations of the processes, including first-time field observations of raindrop collisions.  We will provide an overview of the DSD evolution through the air column and discuss the underlying physical processes in light of the wind effects. This material is based upon work supported by the National Science Foundation under Grants No. AGS-1741250.

How to cite: Testik, F. Y.: Wind Influence on Rainfall Microphysics through High-resolution Observations, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-128, https://doi.org/10.5194/ems2024-128, 2024.

With a current population of over 12 million (Eurostat 2021), the Ile-de-France region is particularly vulnerable to climate change, air-quality and water scarcity. Socio-economic development is leading to a degradation of the urban environment as a result of all human activities and the artificialization of land. Mitigating these adverse effects requires the implementation of specific adaptation policies to make the region more resilient to extreme events (such as heat waves, floods, droughts, pollution episods), but also to better manage water resources. To achieve this, we need to better characterize and understand the dynamics of precipitation in this region.

The presence of urban areas modifies the interactions between the surface and the atmosphere through the modifications of energy and water budgets inducing the urban heat island effect, an increased surface roughness, and anthropogenic aerosols emissions.  Several studies investigated the impact of these urban areas on precipitation with various conclusions due to lots of disparity (methods, datasets, cities' characteristics, climate) between the studies (e.g Lalonde et al., 2023; Liu and Niyogi, 2019).  By using a unique methodology and a radar product covering the whole Continental USA at 4km resolution or the whole Europe at 2km resolution over tens of years, Lalonde et al. (2024) still highlighted a large diversity of urban impacts between cities, concluding on the necessity of specific analysis for each city.

In this study, we use the recently available long-term 1 km/hourly radar product COMEPHORE (Tabary et al., 2012) which provide precipitation rates over France since 1997 to characterize the spatial variability of precipitation over Ile de France with a special focus on the impact of urban area. We complement this dataset with vertical profiles of reflectivity and vertical velocities provided by one radar located in a southwest suburb of Paris (most of the time upwind from Paris city center) and another one located in the city center to detect potential differences in microphysical properties of precipitation between urban and upwind environments.

In the next step, we aim to assess the role of aerosols and urban form in this variability.  

How to cite: Zouzoua, P. M., Bastin, S., Viltard, N., Lalonde, M., David, G., Barthes, L., and Pauwels, N.: Characterization and Understanding of the spatial variability of precipitation over Paris area observed by radars in the last 25 years. , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-848, https://doi.org/10.5194/ems2024-848, 2024.

   On 20^th July 2021, an extreme rainfall event occurred at Zhengzhou city in China with maximum hourly rainfall of 201.9 mm and 24h accumulated rainfall of 624.1 mm at Zhengzhou weather station. From 8:00 (BJT) 17^th to 8:00 (BJT) 23^rd, the maximum accumulated rainfall reaches 1122.6 mm at the Hebi Science and Technology Innovation Center Weather Station.

In this study, multi-source observations including dense surface observations, Doppler weather radar network, radio sounding, and wind profiler were used to analyze the evolution of the rainfall process. Quality control and data analysis methods were implemented to check and merge the individual observations.

The dense observations provide an opportunity to analyze the distributions of the rainfall, the vortex, convergence zone, vertical wind share, and the interaction between the winds and mountains. Surface observations and radar retrieved winds provide a three dimensional wind field with horizontal resolution of a few kilometers and vertical resolution of five hundred meters. More details were shown by the data. For example, the vortex is not obvious in surface observations in 19^th and 20^th , while radar retrieved winds shown a vortex structure in higher levels. The mountains enhanced the convergence of lower level winds which are important for forming the convective storms.

 The nudging and the 4Dvar methods were tested to assimilate the dense observations. Based on the experiments, high resolution reanalysis data were produced using the dense observations and WRF model. More details about the heavy rainfall case will be shown in this study based on hourly observations and the reanalysis data.

How to cite: Liang, X.: Application of Multi-source Observations in a Heavy Rainfall Case Analysis, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-622, https://doi.org/10.5194/ems2024-622, 2024.

Extreme hydro-meteorological events are increasingly prevalent in southern Europe, particularly in the European Alps, posing significant threats to ecological and socio-economic systems. The accurate detection and analysis of these events require a nuanced definition of what constitutes "extreme." While statistical approaches typically define extremes based on the tails of probability distributions, it is essential to recognize that the severity of these events may not always align with statistical extremes. Impact-related thresholds can vary spatially and temporally, making a single absolute threshold inadequate for capturing extremes across different locations, time periods, and seasons.

In this study, we focus on identifying and characterizing extreme hydro-meteorological events in a transboundary Alpine region between Austria and Italy from 2003 to 2021. We employ various definitions of extreme events that consider spatiotemporal aspects and utilize multiple datasets. Daily accumulated precipitation serves as the primary parameter due to its widespread availability across datasets and its role as a triggering factor for various hazards like landslides, debris flows, and floods.

We employ three statistical methods to detect extreme events: regional-scale identification of highest daily precipitation amounts, local-scale detection of high-intensity daily precipitation values, and identification of exceptional daily precipitation records relative to average conditions for specific periods of the year. These methods are applied to four gridded precipitation datasets, including observation and reanalysis products, each with different technical specifications.

Subsequently, we compare the identified events from each method-dataset combination with existing records of gravitational mass movements and fluvial floods in the Austrian-Italian border region to assess their ability to detect actual impacts. Findings suggest that a majority of detected precipitation extremes (e.g., 74% for regional scale identification with reanalysis data) correlate with observed impacts. However, different method-dataset combinations exhibit varying strengths and weaknesses, reflecting the characteristics of the dataset and/or statistical method employed. Some combinations show lower performance in detecting impactful events due to conflicts between dataset resolution and statistical method requirements.

How to cite: Enigl, K., Crespi, A., Lehner, S., Haslinger, K., and Pittore, M.: Identification of past extreme precipitation events and their connection to recorded impacts: a multi-data and multi-method assessment over the Central-Eastern Alps., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-675, https://doi.org/10.5194/ems2024-675, 2024.