Orographic effect on extreme precipitation statistics peaks at hourly times scales

Author(s):  
Francesco Marra ◽  
Moshe Armon ◽  
Marco Borga ◽  
Efrat Morin

<p>Preparedness to natural hazards in mountainous areas strongly relies on the knowledge of extreme rainfall probability. The presence of mountains influences the motion of air masses, thereby modifying the storms characteristics. Here, we use a novel statistical approach to quantify the orographic impact on the probability of occurrence of extreme rainfall of short duration (10-min to 6-hour). We find that mountains tend to decrease the mean annual maximum intensities at sub-hourly scales, thereby confirming the previously reported “reversed orographic effect”, and tend to decrease the tail heaviness, thereby decreasing the extremely high intensities such as the events occurring on average once in 100 years. The second effect is however non-monotonic, in that it increases between 10 minute and 1 hour and diminishes between 1 and 6 hours. Sub-hourly extremes could thus be higher than what can be estimated from hourly data alone, implying that the scaling assumptions typically adopted for risk assessment may systematically underestimate the risk of short-duration extremes</p>

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1177
Author(s):  
Yifan Liao ◽  
Bingzhang Lin ◽  
Xiaoyang Chen ◽  
Hui Ding

Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern.


2021 ◽  
Vol 5 (1) ◽  
pp. 25-41
Author(s):  
Nana Ama Browne Klutse ◽  
Kwesi Akumenyi Quagraine ◽  
Francis Nkrumah ◽  
Kwesi Twentwewa Quagraine ◽  
Rebecca Berkoh-Oforiwaa ◽  
...  

AbstractWe evaluate the capability of 21 models from the new state-of-the-art Coupled Model Intercomparison Project, Phase 6 (CMIP6) in the representation of present-day precipitation characteristics and extremes along with their statistics in simulating daily precipitation during the West African Monsoon (WAM) period (June–September). The study uses a set of standard extreme precipitation indices as defined by the Expert Team on Climate Change Detection and Indices constructed using CMIP6 models and observational datasets for comparison. Three observations; Global Precipitation Climatology Project (GPCP), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Tropical Applications of Meteorology using SATellite and ground-based observation (TAMSAT) datasets are used for the validation of the model simulations. The results show that observed datasets present nearly the same spatial pattern but discrepancies in the magnitude of rainfall characteristics. The models show substantial discrepancies in comparison with the observations and among themselves. A number of the models depict the pattern of rainfall intensity as observed but some models overestimate the pattern over the coastal parts (FGOALS-f3-L and GFDL-ESM4) and western part (FGOALS-f3-L) of West Africa. All model simulations explicitly show the pattern of wet days but with large discrepancies in their frequencies. On extreme rainfall, half of the models express more intense extremes in the 95th percentiles while the other half simulate less intense extremes. All the models overestimate the mean maximum wet spell length except FGOALS-f3-L. The spatial patterns of the mean maximum dry spell length show a good general agreement across the different models, and the observations except for four models that show an overestimation in the Sahara subregion. INM-CM4-8 and INM-CM5-0 display smaller discrepancies from their long-term average rainfall characteristics, in terms of extreme rainfall estimates than the other CMIP6 datasets. For the frequency of heavy rainfall, TaiESM1 and IPSL-CMGA-LR perform better when compared with observational datasets. MIROC6 and GFDL-ESM4 displayed the largest error in representing the frequency of heavy rainfall and 95th percentile extremes, and therefore, cannot be reliable. The study has assessed how rainfall extremes are captured in both observation and the models. Though there are some discrepancies, it gives room for improvement of the models in the next version of CMIP.


MAUSAM ◽  
2022 ◽  
Vol 46 (2) ◽  
pp. 175-180
Author(s):  
S. A. SASEENDRAN ◽  
K. K. SINGH ◽  
J. BAHADUR ◽  
O. N. DHAR

 The daily rainfall data for 80 years from 98 stations in Kerala region have been analysed to arrive at the Probable Maximum Precipitation (PMP) estimates for rainfall durations or 1 to 10 days. Hershfield's statistical technique has been adopted for the estimation of PMP from annual maximum data. The study will be useful in the estimation of extreme precipitation for computation of design floods, required for design of spillways of dams and other major hydraulic structures in the Kerala state.    


2021 ◽  
Vol 7 (9) ◽  
pp. 1620-1633
Author(s):  
Sertac Oruc

Natural or human-induced variability emerged from investigation of the traditional stationary assumption regarding extreme precipitation analyses. The frequency of extreme rainfall occurrence is expected to increase in the future and neglecting these changes will result in the underestimation of extreme events. However, applications of extremes accept the stationarity that assumes no change over time. Thus, non-stationarity of extreme precipitation of 5, 10, 15, and 30 minutes and 1-, 3-, 6-, and 24-hour data of 17 station in the Black Sea region were investigated in this study. Using one stationary and three non-stationary models for every station and storm duration, 136 stationary and 408 non-stationary models were constructed and compared. The results are presented as non-stationarity impact maps across the Black Sea Region to visualize the results, providing information about the spatial variability and the magnitude of impact as a percentage difference. Results revealed that nonstationary (NST) models outperformed the stationary model for almost all precipitation series at the 17 stations. The model in which time dependent location and scale parameter used (Model 1), performed better among the three different time variant non-stationary models (Model 1 as time variant location and scale parameters, Model 2 as time variant location parameter, and Model 3 as time variant scale parameter). Furthermore, non-stationary impacts exhibited site-specific behavior: Higher magnitudes of non-stationary impacts were observed for the eastern Black Sea region and the coastal line. Moreover, the non-stationary impacts were more explicit for the sub-hourly data, such as 5 minutes or 15 minutes, which can be one of the reasons for severe and frequent flooding events across the region. The results of this study indicate the importance of the selected covariate and the inclusion of it for the reliability of the model development. Spatial and temporal distribution of the nonstationary impacts and their magnitude also urges to further investigation of the impact on precipitation regime, intensification, severity. Doi: 10.28991/cej-2021-03091748 Full Text: PDF


1984 ◽  
Vol 16 (8-9) ◽  
pp. 93-100
Author(s):  
D M Hershfield

Storm data and climatological quantities from both dense raingage networks and individual stations are used to elucidate some of the important problems in developing drainage design criteria for small areas. Examples are presented displaying the variability of rainfall rates for very short durations of time over very small areas. An “average” time distribution curve is presented along with relationships between rainfall amounts for durations from 2- to 60-min. One example outlines a procedure for estimating and comparing six quantities from series of annual maximum rainfalls for several short durations. The quantities include a frequency factor, 100-yr value, the probable maximum rainfall, and the observed world maximum rainfalls.


2020 ◽  
Author(s):  
Ibrar Ul Hassan Akhtar

UNSTRUCTURED Current research is an attempt to understand the CoVID-19 pandemic curve through statistical approach of probability density function with associated skewness and kurtosis measures, change point detection and polynomial fitting to estimate infected population along with 30 days projection. The pandemic curve has been explored for above average affected countries, six regions and global scale during 64 days of 22nd January to 24th March, 2020. The global cases infection as well as recovery rate curves remained in the ranged of 0 ‒ 9.89 and 0 ‒ 8.89%, respectively. The confirmed cases probability density curve is high positive skewed and leptokurtic with mean global infected daily population of 6620. The recovered cases showed bimodal positive skewed curve of leptokurtic type with daily recovery of 1708. The change point detection helped to understand the CoVID-19 curve in term of sudden change in term of mean or mean with variance. This pointed out disease curve is consist of three phases and last segment that varies in term of day lengths. The mean with variance based change detection is better in differentiating phases and associated segment length as compared to mean. Global infected population might rise in the range of 0.750 to 4.680 million by 24th April 2020, depending upon the pandemic curve progress beyond 24th March, 2020. Expected most affected countries will be USA, Italy, China, Spain, Germany, France, Switzerland, Iran and UK with at least infected population of over 0.100 million. Infected population polynomial projection errors remained in the range of -78.8 to 49.0%.


Behaviour ◽  
1977 ◽  
Vol 60 (1-2) ◽  
pp. 115-121 ◽  
Author(s):  
V.J. De Ghett

AbstractDevelopmental changes in parameters of ultrasound production were investigated in M. montanus young. The rate of ultrasonic vocalization reached a peak on Day 2 of postnatal ontogeny and declined to zero on Day 15. A similar developmental pattern has been found in several other rodent species. However, the comparatively early peak rate is indicative of a degree of ontogenic precociousness. Other developmental changes, both behavioural and morphological, tend to confirm that M. montanus young are relatively precocious. The duration of ultrasonic vocalizations did not show a significant change across early development. The mean duration for each vocalization sampled was 22.92 msec. The distribution of these vocalizations showed that a considerable number of vocalizations were of very short duration (<30 msec). The developmental changes in the percentage of young emitting ultrasounds began to decline following Day 8 and reached zero percent on Day 15. This decline in the percentage of young vocalizing corresponded to changes in maternal behaviour. Both the rate of ultrasonic vocalization and the percentage of young vocalizing were significantly correlated with the age of the young. Being correlated with age, these parameters of ultrasound production have the possibility of having great communicative value for the purposes of maternal care.


2015 ◽  
Vol 16 (1) ◽  
pp. 278-294 ◽  
Author(s):  
Francesco Avanzi ◽  
Carlo De Michele ◽  
Salvatore Gabriele ◽  
Antonio Ghezzi ◽  
Renzo Rosso

Abstract This paper investigates how atmospheric circulation and orography affect the spatial variability of extreme precipitation in terms of depth–duration–frequency (DDF) curve parameters. To this aim, the Italian territory was considered because it is characterized by a complex orography and different precipitation dynamics and regimes. A database of 1494 time series with more than 20 years of maximum annual precipitation data was collected for the durations of 1, 3, 6, 12, and 24 h. For each data series, the parameters of DDF curves were estimated using a statistical simple scale invariance model. Hence, the combined effect of orography and atmospheric fields on parameter variability was investigated considering the spatial distribution of the parameters and their relation with elevation. The vertically integrated atmospheric moisture flux J was used as a measurement of the principal direction of the vapor transport at a given location. The analysis highlights the variability of DDF parameters and quantiles according to orography and precipitation climatology. This is confirmed by the evaluation of J modal direction over the study area. The variability of DDF parameters with mere elevation shows that maxima at high elevations seem to be upper bounded and more variable than those at lower elevations. Moreover, the mean of maximum annual precipitation of unit duration decreases with elevation. This last phenomenon is defined as “reverse orographic effect” on extreme precipitation of short durations.


2019 ◽  
Vol 19 (19) ◽  
pp. 12477-12494 ◽  
Author(s):  
Armin Sigmund ◽  
Korbinian Freier ◽  
Till Rehm ◽  
Ludwig Ries ◽  
Christian Schunk ◽  
...  

Abstract. To assist atmospheric monitoring at high-alpine sites, a statistical approach for distinguishing between the dominant air masses was developed. This approach was based on a principal component analysis using five gas-phase and two meteorological variables. The analysis focused on the Schneefernerhaus site at Zugspitze Mountain, Germany. The investigated year was divided into 2-month periods, for which the analysis was repeated. Using the 33.3 % and 66.6 % percentiles of the first two principal components, nine air mass regimes were defined. These regimes were interpreted with respect to vertical transport and assigned to the BL (recent contact with the boundary layer), UFT/SIN (undisturbed free troposphere or stratospheric intrusion), and HYBRID (influences of both the boundary layer and the free troposphere or ambiguous) air mass classes. The input data were available for 78 % of the investigated year. BL accounted for 31 % of the cases with similar frequencies in all seasons. UFT/SIN comprised 14 % of the cases but was not found from April to July. HYBRID (55 %) mostly exhibited intermediate characteristics, whereby 17 % of the HYBRID class suggested an influence from the marine boundary layer or the lower free troposphere. The statistical approach was compared to a mechanistic approach using the ceilometer-based mixing layer height from a nearby valley site and a detection scheme for thermally induced mountain winds. Due to data gaps, only 25 % of the cases could be classified using the mechanistic approach. Both approaches agreed well, except in the rare cases of thermally induced uplift. The statistical approach is a promising step towards a real-time classification of air masses. Future work is necessary to assess the uncertainty arising from the standardization of real-time data.


Author(s):  
C. Casse ◽  
M. Gosset

Abstract. A dramatic increase in the frequency and intensity of floods due to the Niger River in the city of Niamey (Niger) has been observed in the last decade. Previous studies highlighted the role of the land use changes on the flood increase since 1970s. In the last decade, observations have raised the issue of a possible increase in extreme rainfall in the Sahel, which may have caused the recent and extreme floods in Niamey in 2010, 2012 and 2013. The study focuses on the 125 000 km2 basin between Ansongo and Niamey. This is the drainage area of the monsoon rainfall that leads to the rapid flow rise occurring between June and October. To understand the possible role of rainfall in flood intensification, satellite rainfall estimate is attractive in a region where the operational gauge network is sparse. This paper analyses the evolution of the Niger hydrograph in Niamey based on discharge observations, hydrological modelling and the satellite product PERSIANN-CDR, over the 1983–2013 period. PERSIANN-CDR is first compared with four other rainfall products. The salient features of the observed changes, i.e. a marked change in the mean decadal hydrograph, is well mimicked by the simulations, implying that rainfall is the first driver to the observed changes. The increase of flooded years over the period is also well reproduced but with some uncertainties in the exact number of flood days per year.


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