Rainfall-triggered slope instabilities under a changing climate: comparative study using historical and projected precipitation extremes

This study aims to quantitatively assess the impact of extreme precipitation events under current and future climate scenarios on landslides. Rainfall-triggered landslides are analyzed primarily using extreme precipitation estimates, derived using the so-called stationary assumption (i.e., statistics of extreme events will not vary significantly over a long period of time). However, extreme precipitation patterns have shown to vary substantially due to climate change, leading to unprecedented changes in the statistics of extremes. In this study, a nonstationary approach, applied to climate model simulations, is adopted to project the upper bound of future precipitation extremes. Future precipitation estimates are obtained from the coupled model intercomparison project phase 5 (CMIP5) simulations. Baseline (historical) and projected (future) precipitation extremes are obtained for a study area near Seattle, Washington. The precipitation patterns are integrated into a series of fully coupled two-dimensional stress – unsaturated flow finite element simulations. The responses of the baseline and projected models at a 7 day rainfall duration obtained for a 50 year recurrence interval are compared in terms of the local strength reduction factor, displacements, matric suctions, and suction stresses. The results indicate that the usage of historical rainfall data can lead to underestimations in the hydromechanical behavior of natural slopes where locally increased transient seepage rates occur from the upper bound of future extreme precipitation estimates.

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ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

Journal of Climate ◽

10.1175/2007jcli1705.1 ◽

2008 ◽

Vol 21 (1) ◽

pp. 22-39 ◽

Cited By ~ 48

Author(s):

Siegfried D. Schubert ◽

Yehui Chang ◽

Max J. Suarez ◽

Philip J. Pegion

Keyword(s):

United States ◽

West Coast ◽

Extreme Precipitation ◽

East Coast ◽

Daily Precipitation ◽

Precipitation Variability ◽

The West ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

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Spatiotemporal Changes in Extreme Precipitation and Its Dependence on Topography over the Poyang Lake Basin, China

Advances in Meteorology ◽

10.1155/2019/1253932 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

Xianghu Li ◽

Qi Hu

Keyword(s):

Water Resources ◽

Extreme Precipitation ◽

Poyang Lake ◽

Precipitation Extremes ◽

Lake Basin ◽

Extreme Precipitation Events ◽

Poyang Lake Basin ◽

Spatiotemporal Changes ◽

Increasing Trends ◽

Precipitation Events

Spatiotemporal changes in extreme precipitation at local scales in the context of climate warming are overwhelmingly important for prevention and mitigation of water-related disasters and also provide critical information for effective water resources management. In this study, the variability and trends of extreme precipitation in both time and space in the Poyang Lake basin over the period of 1960–2012 are analyzed. Also, changes in precipitation extremes with topography are investigated, and possible causes are briefly discussed. The results show that extreme precipitation over the Poyang Lake basin is intensified during the last 50 years, especially the increasing trends are more significant before the end of the 1990s. Moreover, high contribution rates of extreme precipitation to the total rainfall (40–60%) indicated that extreme precipitation plays an important role to the total water resources in this area. The precipitation extremes also exhibited a significant spatial dependence in the basin. The northeastern and eastern areas are exposed to high risk of flood disaster with the higher frequency of extreme precipitation events. In addition, the distribution of precipitation extremes had a clear dependence on elevation, and the topography is an important factor affecting the variability of extreme precipitation over the Poyang Lake basin.

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Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0097.1 ◽

2016 ◽

Vol 17 (2) ◽

pp. 693-711 ◽

Cited By ~ 16

Author(s):

Hamed Ashouri ◽

Soroosh Sorooshian ◽

Kuo-Lin Hsu ◽

Michael G. Bosilovich ◽

Jaechoul Lee ◽

...

Keyword(s):

United States ◽

Extreme Precipitation ◽

Gulf Coast ◽

The United States ◽

Value Theory ◽

Extreme Value ◽

Precipitation Extremes ◽

Precipitation Product ◽

Extreme Precipitation Events ◽

Precipitation Events

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

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Spatial and Temporal Analysis of Precipitation Extremities of Eastern Nepal in the Last Two Decades (1997–2016)

10.5194/egusphere-egu2020-2784 ◽

2020 ◽

Author(s):

Sunil Subba ◽

Yaoming Ma ◽

Weiqiang Ma

Keyword(s):

Climate Change ◽

Extreme Events ◽

Extreme Precipitation ◽

Tropical Rainfall Measuring Mission ◽

Heavy Precipitation ◽

Temporal Analysis ◽

Extreme Precipitation Events ◽

Slope Estimator ◽

The Impact ◽

Precipitation Events

In recent days there have been discussions regarding the impact of climate change and its vagaries of the weather, particularly concerning extreme events. Nepal, being a mountainous country, is more susceptible to precipitation extreme events and related hazards, which hinder the socioeconomic development of the nation. In this regard, this study aimed to address this phenomenon for one of the most naturally and socioeconomically important regions of Nepal, namely, Eastern Nepal. The data were collected for the period of 1997 to 2016. The interdecadal comparison for two periods (1997&#8211;2006 and 2007&#8211;2016) was maintained for the calculation of extreme precipitation indices as per recommended by Expert Team on Climate Change Detection and Indices. Linear trends were calculated by using Mann&#8208;Kendall and Sen's Slope estimator. The average annual precipitation was found to be decreasing at an alarming rate of &#8722;20 mm/year in the last two decades' tenure. In case of extreme precipitation events, consecutive dry days, one of the frequency indices, showed a solo increase in its trend (mostly significant). Meanwhile, all the intensity indices of extreme precipitation showed decreasing trends (mostly insignificant). Thus, it can be concluded that Eastern Nepal has witnessed some significant drier days in the last two decades, as the events of heavy, very heavy, extremely heavy precipitation events, and annual wet day precipitation (PRCPTOT) were found to be decreasing. The same phenomena were also seen in the Tropical Rainfall Measuring Mission 3B42 V7 satellite precipitation product for whole Nepal.

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A climatology of sub-seasonal temporal clustering of extreme precipitation in Switzerland and its links to extreme discharge

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-2949-2021 ◽

2021 ◽

Vol 21 (10) ◽

pp. 2949-2972

Author(s):

Alexandre Tuel ◽

Olivia Martius

Keyword(s):

Extreme Precipitation ◽

River Discharge ◽

Precipitation Extremes ◽

Spatiotemporal Pattern ◽

High Discharge ◽

Temporal Clustering ◽

Extreme Precipitation Events ◽

Southern Side ◽

Northern Side ◽

The Alps

Abstract. The successive occurrence of extreme precipitation events on sub-seasonal timescales can lead to large precipitation accumulations and extreme river discharge. In this study, we analyze the sub-seasonal clustering of precipitation extremes in Switzerland and its link to the occurrence and duration of extreme river discharge. We take a statistical approach based on Ripley's K function to characterize the significance of the clustering for each season separately. Temporal clustering of precipitation extremes exhibits a distinct spatiotemporal pattern. It occurs primarily on the northern side of the Alps in winter and on their southern side in fall. Cluster periods notably account for 10 %–16 % of seasonal precipitation in these two regions. The occurrence of a cluster of precipitation extremes generally increases the likelihood and duration of high-discharge events compared to non-clustered precipitation extremes, particularly at low elevations. It is less true in winter, when the magnitude of precipitation extremes is generally lower and much of the precipitation falls as snow. In fall, however, temporal clusters associated with large precipitation accumulations over the southern Alps are found to be almost systematically followed by extreme discharge.

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On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe

10.5194/hess-2021-625 ◽

2021 ◽

Author(s):

Alexandre Tuel ◽

Bettina Schaefli ◽

Jakob Zscheischler ◽

Olivia Martius

Keyword(s):

Extreme Precipitation ◽

Temporal Structure ◽

Extreme Precipitation Event ◽

Precipitation Event ◽

Discharge Data ◽

High Discharge ◽

Temporal Clustering ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract. River discharge is impacted by the sub-seasonal (weekly to monthly) temporal structure of precipitation. One example is the successive occurrence of extreme precipitation events over sub-seasonal timescales, referred to as temporal clustering. Its potential effects on discharge have received little attention. Here, we address this question by analysing discharge observations following extreme precipitation events either clustered in time or occurring in isolation. We rely on two sets of precipitation and discharge data, one centered on Switzerland and the other over Europe. We identify "clustered" extreme precipitation events based on the previous occurrence of another extreme precipitation within a given time window. We find that clustered events are generally followed by a more prolonged discharge response with a larger amplitude. The probability of exceeding the 95th discharge percentile in the five days following an extreme precipitation event is in particular up to twice as high for situations where another extreme precipitation event occurred in the preceding week compared to isolated extreme precipitation events. The influence of temporal clustering decreases as the clustering window increases; beyond 6–8 weeks the difference with non-clustered events is negligible. Catchment area, streamflow regime and precipitation magnitude also modulate the response. The impact of clustering is generally smaller in snow-dominated and large catchments. Additionally, particularly persistent periods of high discharge tend to occur in conjunction with temporal clusters of precipitation extremes.

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Sensitivity of Heavy Precipitation Forecasts to Small Modifications of Large-Scale Weather Patterns for the Elbe River

Journal of Hydrometeorology ◽

10.1175/2010jhm1186.1 ◽

2010 ◽

Vol 11 (3) ◽

pp. 770-780 ◽

Cited By ~ 10

Author(s):

Ingo Schlüter ◽

Gerd Schädler

Keyword(s):

Extreme Precipitation ◽

Large Scale ◽

Spatiotemporal Variability ◽

Small Scale ◽

Synoptic Situation ◽

Flood Events ◽

Weather Patterns ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract Extreme flood events are caused by long-lasting and/or intensive precipitation. The detailed knowledge of the distribution, intensity, and spatiotemporal variability of precipitation is, therefore, a prerequisite for hydrological flood modeling and flood risk management. For hydrological modeling, temporal and spatial high-resolution precipitation data can be provided by meteorological models. This study deals with the question of how small changes in the synoptic situation affect the characteristics of extreme forecasts. For that purpose, two historic extreme precipitation events were hindcasted using the Consortium for Small Scale Modeling (COSMO) model of the German Weather Service (DWD) with different grid resolutions (28, 7, and 2.8 km), where the domains with finer resolutions were nested into the ones with coarser resolution. The results show that the model is capable of simulating such extreme precipitation events in a satisfactory way. To assess the impact of small changes in the synoptic situations on extreme precipitation events, the large-scale atmospheric fields were shifted to north, south, east, and west with respect to the orography by about 28 and 56 km, respectively, in one series of runs while in another series, the relative humidity and temperature were increased to modify the amount of precipitable water. Both series were performed for the Elbe flood events in August 2002 and January 2003, corresponding to two very different synoptic situations. The results show that the modeled precipitation can be quite sensitive to small changes of the synoptic situation with changes in the order of 20% for the maximum daily precipitation and that the types of synoptic situations play an important role. While van Bebber weather conditions, of Mediterranean origin, were quite sensitive to modifications, more homogeneous weather patterns were less sensitive.

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Monsoonal Precipitation Over Peninsular Malaysia in the CMIP6 Highresmip Experiments: The Role of Model Resolution

10.21203/rs.3.rs-741632/v1 ◽

2021 ◽

Author(s):

Ju Liang ◽

Mou Leong Tan ◽

Matthew Hawcroft ◽

Jennifer L. Catto ◽

Kevin I. Hodges ◽

...

Keyword(s):

Extreme Precipitation ◽

Monsoon Season ◽

Southwest Monsoon ◽

Peninsular Malaysia ◽

Vertical Resolution ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Different Seasons ◽

Model Ensembles ◽

The Impact

Abstract This study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

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Evaluating the extreme precipitation events using a mesoscale atmosphere model and satellite based precipitation product

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-1-6979-2013 ◽

2013 ◽

Vol 1 (6) ◽

pp. 6979-7014

Author(s):

I. Yucel ◽

A. Onen

Keyword(s):

Data Assimilation ◽

Extreme Precipitation ◽

Heavy Rainfall ◽

Wrf Model ◽

Hydrologic Model ◽

Rainfall Events ◽

Extreme Precipitation Events ◽

Precipitation Estimates ◽

Heavy Rainfall Events ◽

Precipitation Events

Abstract. Quantitative precipitation estimates are obtained with more uncertainty under the influence of changing climate variability and complex topography from numerical weather prediction (NWP) models. On the other hand, hydrologic model simulations depend heavily on the availability of reliable precipitation estimates. Difficulties in estimating precipitation impose an important limitation on the possibility and reliability of hydrologic forecasting and early warning systems. This study examines the performance of the Weather Research and Forecasting (WRF) model and the Multi Precipitation Estimates (MPE) algorithm in producing the temporal and spatial characteristics of the number of extreme precipitation events observed in the West Black Sea Region of Turkey. Precipitations derived from WRF model with and without three-dimensional variational (3-DVAR) data assimilation scheme and MPE algorithm at high spatial resolution (4 km) are compared with gauge precipitation. WRF-derived precipitation showed capabilities in capturing the timing of precipitation extremes and in some extent the spatial distribution and magnitude of the heavy rainfall events wheras MPE showed relatively weak skills in these aspects. WRF skills in estimating such precipitation characteristics are enhanced with the application of 3-DVAR scheme. Direct impact of data assimilation on WRF precipitation reached to 12% and at some points there exists quantitative match for heavy rainfall events, which are critical for hydrological forecast.

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Global scaling of observed sub-daily precipitation extremes to dewpoint temperature

10.5194/egusphere-egu2020-10643 ◽

2020 ◽

Author(s):

Haider Ali ◽

Hayley Fowler ◽

Geert Lenderink ◽

Elizabeth Lewis

Keyword(s):

Air Temperature ◽

Extreme Precipitation ◽

Daily Precipitation ◽

The United States ◽

Precipitation Extremes ◽

Precipitation Data ◽

Lower Altitude ◽

Dewpoint Temperature ◽

Extreme Precipitation Events ◽

Daily Precipitation Data

The intensity and frequency of extreme precipitation events have increased globally and are likely to rise further under the warming climate. The Clausius-Clapeyron (CC) relationship (scaling) provides a physical basis to understand the relationship of precipitation extremes with temperature. Recent studies have used global sub-daily precipitation data from satellite, reanalysis and climate model outputs (due to the limited availability of long term observed sub-daily data at global scales) and have reported a higher sensitivity of sub-daily precipitation extremes to surface air temperature than for daily extremes. Moreover, at higher temperatures, moisture availability becomes the dominant driver of extreme precipitation, therefore, dewpoint temperature can be a better scaling variable to overcome humidity limitations as compared to air temperature. Here, we used hourly precipitation data from the Global Sub-daily Rainfall (GSDR) dataset and daily dewpoint temperature data (DPT) from the Met Office Hadley Centre observations dataset (HadISD) at 6695 locations across the United States of America, Australia, Europe, Japan, India and Malaysia. We found that more than 60% of locations (scaling estimated for individual location) show scaling greater than 7%/K (CC rate). Moreover, more than 55% of locations across Europe, Japan, Australia and Malaysia show scaling greater than 1.5CC. Furthermore, when locations across selected regions are pooled within similar climatic zones (based on Koppen Geiger classification), scaling curves show around 7%/K scaling. The scaling curves for locations at greater altitude (>400m MSL) are flat compared to locations at relatively lower altitude. The difference in scaling rates at-station and for pooled regions highlight the importance of understanding the thermodynamic and dynamic processes governing precipitation extremes at different spatial scales and indicate that local processes are driving the super-CC sensitivities in most regions.

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