This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann‐Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature,withthemedianintensityofextremeprecipitationchanginginproportionwithchangesinglobal mean temperature at a rate of between 5.9% and 7.7%K 21 , depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 138S and 118N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Global increasing trends in annual maximum daily precipitation

Climate models project that heavy precipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6–7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that subdaily (e.g., hourly) precipitation extremes may increase at about twice this rate. Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parametrize convective precipitation (i.e., thunderstorms and rain showers). Here we employ a convection-resolving model using a horizontal grid spacing of 2.2 km across an extended region covering the Alps and its larger-scale surrounding from northern Italy to northern Germany. Consistent with previous results, projections using a Representative Concentration Pathways version 8.5 greenhouse gas scenario reveal a significant decrease of mean summer precipitation. However, unlike previous studies, we find that both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation. Differences to previous studies might be due to the model or region considered, but we also show that it is inconsistent to extrapolate from present-day precipitation scaling into the future.

Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster?

Hydrology plays a central role in applied as well as fundamental environmental sciences, but it is well known to suffer from an overwhelming diversity of models, in particular to simulate streamflow Based on Switzerland's example, we discuss here in detail how such diversity did arise even at the scale of such a small country The case study's relevance stems from the fact that Switzerland shows a relatively high density of academic and research institutes active in the field of hydrology, which led to an evolution of hydrological models that stands exemplarily for the diversification that arose at a larger scale Our analysis summarizes the main driving forces behind this evolution, discusses drawbacks and advantages of model diversity and depicts possible future evolutions Although convenience seems to be the main driver so far, we see potential change in the future with the advent of facilitated collaboration through open sourcing and code sharing platforms We anticipate that this review, in particular, helps researchers from other fields to understand better why hydrologists have so many different models

https://eartharxiv.org/repository/object/2046/download/4586/

Why do we have so many different hydrological models? A review based on the case of Switzerland

In comparison to a local-scale flood risk analysis, modeling flood losses and risks at the river basin scale is challenging. Particularly in mountainous watersheds, extreme precipitation can be distributed spatially and temporally with remarkable variability. Depending on the topography of the river basin and the topological characteristics of the river network, certain rainfall patterns can lead to a synchronization of the flood peaks between tributaries and the main river. Thus, these complex interactions can lead to high variability in flood losses. In addition, flood inundation modeling at the river basin scale is computationally resource-intensive and the simulation of multiple scenarios is not always feasible. In this study, we present an approach for reducing complexity in flood-risk modeling at the river basin scale. We developed a surrogate model for flood loss analysis in the river basin by decomposing the river system into a number of subsystems. A relationship between flood magnitude and flood losses is computed for each floodplain in the river basin by means of a flood inundation and flood loss model at sub-meter resolution. This surrogate model for flood-loss estimation can be coupled with a hydrological-hydraulic model cascade, allowing to compute a high number of flood scenarios for the whole river system. The application of this model to a complex mountain river basin showed that the surrogate model approach leads to a reliable and computationally fast analysis of flood losses in a set of probable maximum precipitation scenarios. Hence, this approach offers new possibilities for stress test analyses and Monte-Carlo simulations in the analysis of system behavior under different system loads.

Extending coupled hydrological-hydraulic model chains with a surrogate model for the estimation of flood losses

Extreme flood estimates for dam safety are routinely obtained from hydrologic simulations driven by selected design storms. The temporal structure of such design storms can be obtained from Rainfall Mass Curves (RMCs), which are adimensionalized curves of the cumulative precipitation depth as a function of event duration. This paper assesses for the first time the spatialand temporal variability of observed RMCs for Switzerland, an Alpine region with complex topography. The relevance of the detected RMC variability for extreme flood estimation is illustrated based on an application to a high elevation catchment, the Mattmark dam catchment in the Swiss Alps. The obtained results underline that quantile RCMs represent a simple yet powerful tool to construct design storms for dam safety verification and that regional, seasonal and event-duration effects on RMCs are small enough to justify the use of a unique set of Swiss-wide quantile RMCs. The presented analysis could be refined in the future by explicitly accounting for orographic, convective or frontal precipitation events.

/pdf/swiss-rainfall-mass-curves-and-their-influence-on-extreme-4miu94o13q.pdf

Swiss Rainfall Mass Curves and their Influence on Extreme Flood Simulation

Les barrages alpins en Suisse doivent etre dimensionnes pour resister a des crues extremes avec un temps de retour d’au moins 10.000 ans. La methode PMP-PMF a ete appliquee pour estimer des pluies et des crues extremes avec un temps de retour aussi eleve. Les PMP ont ete calculees avec un modele atmospherique et un modele de pluie pour plusieurs durees avec une resolution horizontale de 2 km. Ces modeles permettent de reproduire de maniere satisfaisante ces PMP pour l’ensemble du pays lorsqu’on les compare avec les precipitations extremes estimees pour un temps de retour de 500 ans a partir de methodes statistiques. Les PMP calculees par les modeles sont toutefois trop elevees sur plusieurs sommets alpins et trop basses au Sud des Alpes. Malgre ces approximations, elles peuvent etre utilisees pour calculer avec un modele hydrologique approprie des crues de securite avec un temps de retour d’au moins 10.000 ans pour les bassins versants en Suisse ayant une surface inferieure a 230 km2.

https://serval.unil.ch/resource/serval:BIB_869665BFB0E9.P001/REF.pdf

Détermination des précipitations et des crues extrêmes en Suisse à l’aide de la méthode PMP-PMF

Relevance of the correlation between precipitation and the 0 °C isothermal altitude for extreme flood estimation

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Détermination des précipitations et des crues extrêmes en Suisse à l’aide de la méthode PMP-PMF

Relevance of the correlation between precipitation and the 0 °C isothermal altitude for extreme flood estimation