High-resolution measurements and analyses of precipitation are crucial, especially in urban areas with high vulnerabilities, in order to describe the hydrological response and improve water risk management. Thus, this session also addresses contributions on the application of high-resolution precipitation data in hydrological impact and design studies.
Summarizing, one or more of the following topics shall be addressed:
Precipitation measurement techniques
• High-resolution precipitation observations from different platforms (e.g., gauges, disdrometers, radars, satellites, microwave links) and their combination
• Precipitation reference data sets (e.g., GPCC, OPERA)
• Drought monitoring and impact
• Statistical analysis of extreme precipitation (events)
• Statistical analysis of changes/trends in precipitation totals (monthly, seasonal, annual)
• Multi-scale analysis, including sub-kilometer scale statistical precipitation description and downscaling methods
• Definition and application of indices to characterize extreme precipitation events
• Climate change studies on extreme precipitation (events)
• Urban hydrology and hydrological impact as well as design studies
• New concepts of adaptation to climate change with respect to extreme precipitation in urban areas
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 RN (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 (ZKu and ZKa) and Drop Size Distribution (DSD) parameters (weighted mean diameter, Dm; intercept parameter, Nw) of the GPM DPR are evaluated. For this purpose, information from seven disdrometers (OTT Parsivels1, 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 Dm 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 Nw 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 Dm, while the agreement was poorer considering the Nw 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 Dm 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.
Measurements are essential to provide information on the actual state of the atmosphere in order to improve our understanding of atmospheric processes and their role in water cycle and the climate system. In this paper we focus on measurements from optical disdrometers which seek to improve our understanding of complexity of precipitations processes at surface.
In this work we focus on the use of the basque disdrometer network a novel and evolving network with operational purpose. Deployed by the Basque Government, this network currently comprises more than 10 Parsivel OTT-2 disdrometers positioned across various locations in the Basque Country. Optical disdrometers function by gauging the degree of light obstruction caused by particles traversing a laser beam. When raindrops intercept the beam, a sensor detects a reduction in light intensity, which is then converted into an electric signal by a photodiode. This reduction in intensity corresponds to the size of the raindrops impeding the beam. Moreover, by analyzing the duration of this reduced intensity, the descending velocity can be estimated. Consequently, such instrumentation provides us with both raw information, such as raindrop size and velocity distribution, and derived data, including rain intensity, hydrometeor classification, reflectivity, visibility, etc., recorded every minute.
In this paper, we present a study focused on analyzing the key characteristics of precipitation episodes in the Basque Country. This analysis involves incorporating information derived from various aggregated indicators, which are based on selected event statistics such as maximum, minimum, mean, median, mode, percentiles, and others. These statistics are applied to various event variables, including duration, number of particles, rain intensity, total rainfall, raindrop size distribution, and more.
To accomplish the analysis, we prepare a comprehensive dataset spanning three years (2021-23) of precipitation episodes derived from minute-by-minute raw data recorded by the disdrometer network. The event raw data undergoes proper filtering and processing before being aggregated into precipitation episodes. These episodes are subsequently grouped based on shared characteristics or factors that facilitate analysis, such as predominant precipitation type, total precipitation amount, maximum intensity or season, among other categories. The ultimate goal is to identify patterns and common characteristics.
How to cite: Gaztelumendi, S., Egaña, J., and Aranda, J. A.: On the use of disdrometer data for characterization of precipitation episodes in the Basque Country, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-454, https://doi.org/10.5194/ems2024-454, 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 20th 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) 17th to 8:00 (BJT) 23rd, 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 19th and 20th , 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.
In this study, we examined the influence of low-level moisture on rainfall behavior in the southern Korean Peninsula using remote sensing of the mobile vehicle platform. An intensive dataset, with high temporal resolution rawinsonde soundings and global navigation satellite system (GNSS) observations in target area, was used. We analyzed the low-level thermodynamic structure in terms of the relationship between precipitable water vapor (PWV) and heavy rainfall. Results demonstrated that an increase in precipitation on the leeward side of the mountainous region coincided with the prevailing winds on the southeasterly flank of the windward site. The probability of heavy rainfall increased in the highest PWV bin (> 60 mm). Interestingly, the vertical structures of the horizontal wind speed indicate a low-level jet (LLJ) with a maximum of ~40 m s-1, ~3–4 km where low-level moisture tends to be concentrated. In addition, the vertical variability of the horizontal wind speed in the highest PWV bins corresponds to considerable changes in upslope flows for all precipitation bins, indicating that the LLJ along with strong low-level moisture of ~3–4 km is an important indicator of rain occurrence in the downstream mountains. The observational evidence base obtained from mobile vehicle platform equipped with GNSS and rawinsonde sensor can provide some insights to improve the predictability of heavy rainfall in the southern Korean Peninsula. In future, combined analysis using numerical modeling, radar observations, satellites (e.g., SSM/I, GK-2A) and other upper-air observations (e.g., wind profiler and Doppler wind lidar) will be conducted.
How to cite: Kim, Y.-J. and Lim, B.: Observing the influence of low-level moisture on rainfall behavior using vehicle-based remote sensing, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-219, https://doi.org/10.5194/ems2024-219, 2024.
Small, fast responding catchments are prone to flooding induced by local convective precipitation events. In such cases, the availability of high-quality information as basis for target-oriented warnings and effective protective measures in potentially affected regions is essential. More precisely, they rely on high-quality precipitation data, reliable weather and flood forecasting and last but not least information and education of persons in charge for prevention of hazards.
Within the project HoWa-PRO funded by the German Federal Ministry of Education and Research (BMBF) a new hydro-meteorological processing chain has been established to improve flood forecasting and warnings for small catchments. The system has been automated and a routine mode consisting of three main parts has been established:
- To produce high-quality Quantitative Precipitation Estimates (QPE) the Deutscher Wetterdienst (DWD) performs an operational gauge-adjustment of radar-based precipitation estimates. Within HoWa-PRO, the additional merging of precipitation data derived from numerous Commercial Microwave Links (CML) with high temporal resolution and low latency promises an improvement of capturing local extreme precipitation events leading to a multi-sensor QPE product optimized for convective weather.
- The QPE products together with forecasts from DWD’s seamless prediction system SINFONY-INTENSE – a combination of nowcasting and numerical weather prediction run in a Rapid Update Cycle (RUC) – serve as input for a hydrologic ensemble prediction system designed for small catchments resulting in discharge time series including uncertainty information.
- To meet the requirements of communicating the uncertainty information of the ensemble forecasts to key clients in disaster and risk management, an information platform (howapro.de) with tailored visual information on flood early warnings for small catchments constitute the last part of the processing chain. In addition, a serious game has been designed for educational purposes.
This contribution gives an overview of the whole processing chain and presents case studies and first verification results.
How to cite: Winterrath, T., Wenzel, M., Chwala, C., Graf, M., Grundmann, J., Wagner, M., Elghorab, M., Philipp, A., Sallwey, J., Stefanova, A., and Müller, M.: Using opportunistic sensors in a new hydro-meteorological precipitation and flood forecasting system for small catchments, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-460, https://doi.org/10.5194/ems2024-460, 2024.
The global community is increasingly alarmed by the impact of climate change, particularly in relation to the increased occurrence of droughts and the subsequent depletion of water resources in coming years. However, specific future projections using high-resolution climate simulations that focus on the water resources and frequency and intensity of hydrological droughts in Japan is currently lacking. This study investigated the impact of climate change on water availability and dry spells in Japan using large ensemble regional climate projections derived from the database for Policy Decision making for Future climate change (d4PDF). Self-organizing maps were applied to atmospheric circulation fields to study the linkages between water availability and weather patterns (WPs) during summer in the present and future climate simulations. The climate projections exhibited a reduced water availability defined by precipitation and evapotranspiration in the majority of Japan, consistent with increases in both frequency and duration of dry spells. The impacts of climate change on water availability vary by WP, with a significant increase in dry conditions under WPs with intensified climatological Pacific high over eastern Japan. Our results suggest that future changes in water availability can be attributed to changes in WP-related precipitation/evapotranspiration under warming conditions and in WP frequency in relation to the Pacific high, recognized as thermodynamic and dynamic effects of climate change, respectively. The decompositions of climate change impacts by WP analogs revealed that thermodynamic and dynamic effects account for approximately 80 and 20% of water availability changes, respectively. In addition, the effects of climate change on hydrological drought in central Japan were examined using hydrological model simulations that were based on climate projections derived from an ensemble of high-resolution downscaling at a 5-km scale. The results indicated a decrease in the streamflow during summer as the climate change progressed, corresponding to an increase in drought years. In addition, the 1%ile values of streamflow decreased by 40 (15) % in the +4-K (+2-K) warming climate simulations. Moreover, there was a considerable increase in the number of consecutive hydrological drought days, reaching an unprecedented level. The yielded results are useful in the consideration of adaptive solutions that will ensure the sustainable use of water resources that balances economic and environmental demands.
How to cite: Ohba, M., Arai, R., Sato, T., Imamura, M., and Toyoda, Y.: Projected climate change impacts on water availability and hydrological droughts in Japan, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-5, https://doi.org/10.5194/ems2024-5, 2024.
When studying precipitation in mid-latitudes, it is appropriate to focus on the basic types: convective and stratiform. Stratiform precipitation is inherently more crucial for agriculture, and a decrease in its amounts, coupled with higher temperatures, can lead to a greater soil moisture deficit. Conversely, more frequent and intense convective and stratiform precipitation may result in floods and landslides, thus posing additional hazards and causing damages.
In this study, we analyze the characteristics of convective and stratiform precipitation (e.g. annual cycle, proportion of convective and stratiform precipitation, trends, and extremes) in the Czech Republic using data from the regional climate model ALADIN-CLIMATE/CZ, operated by the Czech Hydrometeorological Institute. The model has been upgraded to achieve a convection-permitting resolution of 2.3 km, along with the implementation of a non-hydrostatic, fully elastic dynamical core. As the outputs from this model will be utilized to enhance the accuracy of climate change scenarios for the Czech Republic region, it is necessary to evaluate the simulation accuracy of convective and stratiform precipitation.
We analyze two datasets of convective and stratiform precipitation from the ALADIN-CLIMATE/CZ model. Firstly, we examine direct model-simulated convective and stratiform precipitation. Secondly, we analyze convective and stratiform precipitation separated from the model's output using a physically based algorithm. While the algorithm is applicable over complex terrain, it exhibits better efficiency over land with smooth topography. Therefore, we believe it is suitable for the Czech Republic region. The characteristics of convective and stratiform precipitation derived from both datasets are compared to each other, as well as to observations from SYNOP stations and radar data
How to cite: Rulfová, Z. and Beranová, R.: Convective and stratiform precipitation in ALADIN-CLIMATE/CZ, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-159, https://doi.org/10.5194/ems2024-159, 2024.
The effect of climate change on extreme precipitation and its impacts are investigated for the city of Berlin. The study is based on regional climate scenario simulations with a convection permitting horizontal resolution of 3 km conducted with CCLM (COSMO model in CLimate Mode).
The regional model was forced with a CMIP5 global model simulation (MIROC5). Precipitation output is available at an hourly temporal resolution. We show results from simulations with historical greenhouse gas concentrations (1971-2000) and compare them to results with RCP8.5 greenhouse gas forcing.
The relationship between duration, intensity and probability of the simulated precipitation is evaluated with a duration dependent general extreme value approach. The results are presented in the form of intensity-duration-frequency (IDF) curves. The curves for the historical period fit well to the corresponding product of the German weather service based on station observations (KOSTRA). The comparison of the IDF curves between the historical and the scenario periods reveals that extreme precipitation will strongly increase in a warmer climate for all analysed accumulation times between 1 hour and 5 days. Hourly events that occurred on average every 100 years in the historical period, for example, are found to be 45% more intense in Berlin during the period 2031-2060 at RCP8.5 conditions. For events with a very low probability (return periods above 50 years) this increase is ,however, not steady in time.
If no adaptation measures are taken, the projected increase in extreme precipitation can also be expected to have an impact on the intensity and
probability of urban flooding. Risk maps for pluvial flooding are usually based on statistical precipitation events estimated from past observation, also known as design rainfall. Often the 100-year return value for an hourly accumulation time is used. To demonstrate how the anticipated changes in extreme precipitation reflect on the potential future flood risk for Berlin, risk maps for the future climate scenario are produced using the design rainfall from the climate scenario simulations as input for hydro-numerical simulations. The hydro-dynamical simulations are performed with the robust 2-D shallow water model hms++ coupled to the canal-system model of the Berlin water company (BWB). In addition to the maps, changes in flood depth for selected hot-spots and increases in sewer overflow volumes are presented.
How to cite: Nissen, K., Tügel, F., Fauer, F., Rust, H., Hinkelmann, R., and Ulbrich, U.: Extreme precipitation and flooding in Berlin under climate change conditions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-348, https://doi.org/10.5194/ems2024-348, 2024.
As heavy rainfall events (HPEs) become more frequent and intense with ongoing climate change, accurate and comprehensive analyses of their patterns, including the generation of depth‑duration‑frequency (DDF) curves, are crucial for enhancing our understanding of rainfall dynamics, assessing associated risk, and implementing effective mitigation strategies. DDF curves are essential for designing water management systems and facilities, such as dams, dikes, spillways, flood retention basins, and urban drainage systems. For Germany, this data is provided by KOSTRA‑DWD (Koordinierte Starkniederschlagsregionalisierung und -auswertung des Deutschen Wetterdienstes), a product developed since the 1980s at the Department of Hydrometeorology of the Deutscher Wetterdienst.
In recent years, KOSTRA‑DWD has been thoroughly revised, considering state‑of‑the‑art (geo)statistical methods and additional rainfall data. The latest version, KOSTRA‑DWD‑2020, is based on the annual maximum series (AMS) obtained from 1900 rain‑gauge stations. AMS have been calculated for 22 durations from 5 min to 7 days. Subsequently, the generalised extreme value distribution (GEV; Fréchet distribution with shape parameter fixed to 0.1) has been fitted to AMS of a particular duration. Considering the interconnectedness of HPEs of different durations, the concept of Koutsoyiannis et al. (1998) has been implemented to smooth heavy rainfall statistics over all durations. Ultimately, regionalisation of GEV parameters using kriging with external drift, along with estimation of DDF curves for 9 return periods ranging from 1 to 100 years, has been conducted.
However, preliminary comparisons between DDF maps from KOSTRA‑DWD‑2020 and those generated from radar data have revealed some discrepancies. Firstly, radar data yields quantitatively lower levels of DDF estimates than KOSTRA‑DWD‑2020, mainly due to the shorter time series of only 20 years. We hypothesise that in numerous grid points of radar data there may not be a sufficient number of HPEs observed within this relatively short time period, resulting in lower levels of DDF curves. Another reason may be the smoothing of HPEs in the 1 km² grid cells of radar data compared to point measurements from rain‑gauge stations. Secondly, the spatial patterns of DDF estimates at short durations (e.g. 60 min and less) are more heterogeneous in radar data than in KOSTRA‑DWD‑2020. Above all, HPEs identified from radar data do not seem to be as strongly linked to the orography as demonstrated in KOSTRA-DWD-2020.
This preliminary study compares DDF estimates obtained from both data sources and outlines the first steps towards developing a hybrid methodology called KOSTRA‑DWD‑Hybrid, which seeks to combine long‑term rain‑gauge measurements with high‑resolution radar data. By combining these two data sources, we aim to harness the strengths of each and overcome their respective limitations, enhancing the accuracy and comprehensiveness of heavy rainfall statistics.
Koutsoyiannis et al., 1998, A mathematical framework for studying rainfall intensity‑duration‑frequency relationships. J. Hydrol. (206), 118-135, https://doi.org/10.1016/S0022-1694(98)00097-3
How to cite: Palarz, A., Junghänel, T., Ostermöller, J., Deutschländer, T., and Lengfeld, K.: Towards a new multi‑sensor heavy rainfall statistic for Germany (KOSTRA‑DWD‑Hybrid): combining long‑term rain gauge measurements with high‑resolution radar data, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-676, https://doi.org/10.5194/ems2024-676, 2024.
Design precipitation intensity is an essential variable used in water management practice. In particular, it is essential for the hydrological modeling of proposed measures in ungauged catchments. However, point design precipitation totals cannot be used in larger catchments as they do not include information on the areal variability of precipitation. Therefore, in practice, point design precipitation totals are reduced to catchment areas using empirically derived Area Reduction Factors that are subject to a number of uncertainties. To reduce these uncertainties, we present here an evaluation of areal design precipitation derived from radar data using the Czech Republic as an example.
The input dataset is radar reflectivity data at an altitude of 2 km (pseudo-CAPPI 2km) for 20 years between 2002 and 2021 with a temporal resolution of 10 minutes and a spatial resolution of 1 km. These data are then adjusted with daily precipitation totals from stations. From the adjusted precipitation intensities, precipitation totals are determined for durations from 30 minutes to 3 days. From these rainfall totals, their areal averages are calculated for individual catchments at four hierarchical levels. From these, the L-moment method is used to derive Generalized Extreme Value (GEV) distribution parameters, which are used to determine design areal precipitation totals in the considered catchments for all considered durations.
Naturally, as the catchment area increases, the areal design precipitation decreases. The average 1-hour design precipitation total with a return period of 20 years is 36 mm for the smallest catchments, whereas the design precipitation is approximately half of that for a catchment of 1000 km2. However, for longer periods of rainfall accumulation, the decrease is not as pronounced. Therefore, on larger catchments, larger ratios of the design totals are achieved between longer and shorter accumulation times. In terms of the spatial distribution of design areal precipitation totals, the design 1-hour totals are very randomly distributed, with an obvious dependence on the catchment size. On the contrary, in the case of the design 24-hour totals, the influence of georelief is a major factor, with the highest totals being strongly concentrated in the mountains and their foothills.
We have shown that the adjusted radar data are suitable for estimating design area precipitation over the catchment, although the longer return periods are particularly subject to the uncertainty caused by the short data series. The demonstrated influence of georelief on longer accumulation times then points to the inappropriateness of the approach of deriving design areal precipitation using reduction coefficients empirically derived from point values for large areas. Radar data, allowing direct calculation of design areal precipitation totals for a specific catchment, seem to be more appropriate.
How to cite: Hulec, F., Kašpar, M., and Müller, M.: Design areal precipitation in Czech catchments – radar data usage instead of station data reduction, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1027, https://doi.org/10.5194/ems2024-1027, 2024.
Characteristics of short-term rainfalls, especially their intensity and design values, are very important for the technical (e.g., sewage system) and hydrological practice. However, measurement and data processing of these characteristics are rather complicated. The still frequently used design values of short-term rainfalls in Czechia come from studies that are more than 60 years old.
Therefore, the new design values of rainfall totals are in preparation within the project “Prediction, Evaluation and Research for Understanding National sensitivity and impacts of drought and climate change for Czechia” (PERUN). The intensity-duration-frequency (IDF) curves for the 5min – 3day rainfall totals will be prepared for selected measurement stations of the Czech Hydrometeorological Institute. More than 170 stations with sufficient length (mainly more than 25 years) of joined digitalized pluviographs records and the automatic rain gauge measurement series from 1951–2022 were processed. The 5-year to 100-year design values were estimated using the region-of-influence (ROI) method. Afterwards, the final IDF curves (theoretical function) should be fitted with the estimated design values. However, the classical approach of fitting three-parametric intensity curve is suitable only for a part of the IDF curve (i.e. short-term rainfalls). Thus, a new approach, i.e., use of a polynomial function, was suggested as suitable representation of the whole curve including long-term (approx. 6-hour – 3-days) rainfalls.
In our contribution, we focus on comparison of the classical approach to fitting IDF curves (i.e., use of three-parametric intensity curve) and newly suggested approach (i.e., use of polynomial function). We focus on the part of the curve for short-term rainfall (durations of 5-360min) where classical intensity curve is generally used.
How to cite: Crhová, L., Müller, M., and Kašpar, M.: Comparison of two approaches to fitting new IDF curves in Czechia, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-758, https://doi.org/10.5194/ems2024-758, 2024.
Understanding the patterns of extreme precipitation is crucial for effective water resource management, infrastructure design, and flood risk assessment. This study offers a comprehensive analysis of the maximum annual 5-day precipitation totals (Rx5d) in Slovakia using regional frequency analysis (RFA) to elucidate the probabilistic behavior of these events, essential for informed decision-making amid changing climate patterns. The main objectives were to identify homogeneous regions based on Rx5D, estimate regional frequency distributions, calculate maximum Rx5D for return periods of 5, 10, 20, 50, 100, and 200 years, and map these estimates for Slovakia. The cluster analysis, employing index-flood procedure and Ward's method, identified 14 reasonably homogeneous clusters. Homogeneity and discordancy tests further refined these clusters. The regional frequency distribution for each Rx5D region was determined using L-moment ratio diagrams, measure and Anderson-Darling tests, resulting in the selection of Gumbel (GUM), Generalized Pareto (GPA), and Generalized Logistic (GLO) as the best-fit distributions for different regions. Our results indicate that, design Rx5D values expected once every 100 years in lowland regions could occur as frequently as once every 25 years in mountainous areas. The most extreme design Rx5D values exceeding 200 mm were observed in the high-elevation mountainous regions, underscoring the heightened risk of extreme precipitation events in these areas. The study suggests that cluster analysis coupled with L-moments-based regional frequency analysis can effectively derive design rainfall estimates for Slovakia. The developed regional frequency curves are invaluable for estimating return periods of extreme 5-day precipitation events at any location within the study area, proving indispensable for effective flood risk management, infrastructure design, and climate adaptation planning.
How to cite: Markovič, L., Faško, P., and Bochníček, O.: Regional frequency analysis for maximum 5-day precipitation totals using L-moments approach in Slovakia., EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-295, https://doi.org/10.5194/ems2024-295, 2024.
