Orographic effect on extreme precipitation statistics peaks at hourly times scales

<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>

Orographic effect in cosmic rays observing

The Baksan neutron monitor (NM) is installed at the Baksan neutrino observatory, the Northern Caucasus, which is located at the bottom of the Baksan gorge, at height of 1700 m above sea level. The cosmic rays flux recorded at the ground level depends on the amount of the substance (air), through which the particles are passing, from the uppermost layers of the atmosphere to a cosmic ray detector. So, besides the cosmic rays flux data, the station records pressure; the pressure meter recordings interval is 1 minute, like that of the cosmic rays. The perennial barometric data have been analysed to show that at the Baksan station one can often observe a daily pressure variation that is related to the topography features. In general, the local conditions (wind, local orographic effect) result in pressure variations, which do not occur in the cosmic rays, because they do not change the thickness of the atmosphere but result from the effect of the ground level. The barometric variation discovered is not so big (about 1 mb), but is also synchronously observed in the cosmic rays. It means that the pressure variation is not a local phenomenon. In this case, the NM detects the amount of the substance in the atmosphere, showing that pressure changes are not due to dynamic reasons (the Bernoulli effect) and it is the atmosphere strata that changes in reality. Hence, the orographic effect covers a significant part of the troposphere, resulting in the change of the atmosphere strata located over the NM. No similar pressure variation is observed in other NMs.

Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge

The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, and is guided by observed flows and the available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT-simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.

Correction and Informed Regionalization of Precipitation Data in a High Mountainous Region (Upper Indus Basin) and Its Effect on SWAT-Modelled Discharge

The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, guided by observed flows and available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT- simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.

Vertical Variation of Z-R Relationship at Hallasan Mountain during Typhoon Nakri in 2014

Hallasan Mountain is located at the center of Jeju Island, Korea. Even though the height of the mountain is just 1,950 m, the orographic effect is strong enough to cause heavy rainfall. In this study, a rainfall event, due to Typhoon Nakri in 2014, observed in Jeju Island was analyzed fully using the radar and rain gauge data. First, the Z-R relationship Z=ARb was derived for every 250 m interval from the sea level to the mountain top. The resulting Z-R relationships showed that the exponent b could be assumed as constant but that the parameter A showed a significant decreasing trend up to an altitude around 1,000 m before it increased again. The orographic effect was found to be most significant at this altitude of 1,000 m. Second, the derived Z-R relationships were applied to the corresponding altitude radar reflectivity data to generate the rain rate field over Jeju Island. This rain rate field was then used to derive the areal-average rain rate data. These data were found to be very similar to the rain gauge estimates but were significantly different from those derived from the application of the Marshall-Palmer equation to the 1.5 km CAPPI data, which is the data type that is generally used by the Korea Meteorological Administration (KMA).