ON INCREASING HEAVY PRECIPITATION DISASTER RISKS IN KYUSHU REGION AND THE MEASURES

2021 ◽  
Vol 77 (1) ◽  
pp. 158-166
Author(s):  
Toshimitsu KOMATSU ◽  
Akihiro HASHIMOTO ◽  
Hideo OSHIKAWA
Keyword(s):  
Heavy Precipitation

CONSIDERATION OF THE VALIDITY OF THE STATISTICAL CHARACTERISTICS OF pH IN SURFACE WATERS

2019 ◽  
Vol 13 (2) ◽  
pp. 52-58
Author(s):  
V. B. Korobov ◽  
I. V. Miskevich ◽  
A. S. Lokhov ◽  
K. A. Seredkin
Keyword(s):  
Field Measurements ◽  
Heavy Precipitation ◽  
The State ◽  
Statistical Characteristics ◽  
Mean Values ◽  
River Waters ◽  
Ph Values ◽  
State Of Water ◽  
Environment Temperature ◽  
Unit Characteristic

Abstract: pH is one of the most important parameters characterizing the state of water systems. The arithmetic mean values of samples are often used when averaging serial pH measurements in water bodies, as is usually done for other characteristics of the state of the natural environment (temperature, salinity, oxygen concentrations, suspended solids, etc.). However, in this case such an operation is illegal, since the addition of logarithms, which by definition are pH, is non-additive. The authors conducted a study to determine the extent to which pH variability in natural objects such an operation would not distort the results. For this, several samples of the pH index were generated in various ranges of its theoretically possible and natural variability. It was established that with pH variability of less than a unit characteristic of marine pH values, the statistical characteristics of the indicator and [H+ ] concentrations differ slightly, and the medians of the samples coincide. It is concluded that with such ranges characteristic of the waters of the oceans, there is no need to recalculate previously obtained results. However, for the estuaries of rivers flowing into tidal seas, as shown by field measurements, the pH variability in the mixing zone of sea and river waters is several times higher. Similar situations may occur when heavy precipitation falls on the water surface, as well as during floods. In these cases, a simple averaging of the pH values will no longer be correct. In such cases, the use of other averaging algorithms and the choice of stable statistical characteristics are required.

scholarly journals A Prototype Quantitative Precipitation Estimation Algorithm for Operational S-Band Polarimetric Radar Utilizing Specific Attenuation and Specific Differential Phase. Part II: Performance Verification and Case Study Analysis

2019 ◽  
Vol 20 (5) ◽  
pp. 999-1014 ◽  
Author(s):  
Stephen B. Cocks ◽  
Lin Tang ◽  
Pengfei Zhang ◽  
Alexander Ryzhkov ◽  
Brian Kaney ◽  
...  
Keyword(s):  
Real Time ◽  
Heavy Precipitation ◽  
Estimation Algorithm ◽  
Differential Phase ◽  
Specific Attenuation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Bias Ratio ◽  
Using Data ◽  
Precipitation Events

Abstract The quantitative precipitation estimate (QPE) algorithm developed and described in Part I was validated using data collected from 33 Weather Surveillance Radar 1988-Doppler (WSR-88D) radars on 37 calendar days east of the Rocky Mountains. A key physical parameter to the algorithm is the parameter alpha α, defined as the ratio of specific attenuation A to specific differential phase KDP. Examination of a significant sample of tropical and continental precipitation events indicated that α was sensitive to changes in drop size distribution and exhibited lower (higher) values when there were lower (higher) concentrations of larger (smaller) rain drops. As part of the performance assessment, the prototype algorithm generated QPEs utilizing a real-time estimated and a fixed α were created and evaluated. The results clearly indicated ~26% lower errors and a 26% better bias ratio with the QPE utilizing a real-time estimated α as opposed to using a fixed value as was done in previous studies. Comparisons between the QPE utilizing a real-time estimated α and the operational dual-polarization (dual-pol) QPE used on the WSR-88D radar network showed the former exhibited ~22% lower errors, 7% less bias, and 5% higher correlation coefficient when compared to quality controlled gauge totals. The new QPE also provided much better estimates for moderate to heavy precipitation events and performed better in regions of partial beam blockage than the operational dual-pol QPE.

scholarly journals PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mojtaba Sadeghi ◽  
Phu Nguyen ◽  
Matin Rahnamay Naeini ◽  
Kuolin Hsu ◽  
Dan Braithwaite ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Heavy Precipitation ◽  
Climate Data ◽  
Spatiotemporal Resolution ◽  
Data Record ◽  
Precipitation Estimation ◽  
Precipitation Estimates ◽  
Global Precipitation ◽  
Climate Data Record

AbstractAccurate long-term global precipitation estimates, especially for heavy precipitation rates, at fine spatial and temporal resolutions is vital for a wide variety of climatological studies. Most of the available operational precipitation estimation datasets provide either high spatial resolution with short-term duration estimates or lower spatial resolution with long-term duration estimates. Furthermore, previous research has stressed that most of the available satellite-based precipitation products show poor performance for capturing extreme events at high temporal resolution. Therefore, there is a need for a precipitation product that reliably detects heavy precipitation rates with fine spatiotemporal resolution and a longer period of record. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record (PERSIANN-CCS-CDR) is designed to address these limitations. This dataset provides precipitation estimates at 0.04° spatial and 3-hourly temporal resolutions from 1983 to present over the global domain of 60°S to 60°N. Evaluations of PERSIANN-CCS-CDR and PERSIANN-CDR against gauge and radar observations show the better performance of PERSIANN-CCS-CDR in representing the spatiotemporal resolution, magnitude, and spatial distribution patterns of precipitation, especially for extreme events.

scholarly journals Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1727
Author(s):  
Valerio Capecchi ◽  
Andrea Antonini ◽  
Riccardo Benedetti ◽  
Luca Fibbi ◽  
Samantha Melani ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Flash Floods ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Heavy Precipitation Event ◽  
The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

scholarly journals Changes in Intense Precipitation over the Central United States

2012 ◽  
Vol 13 (1) ◽  
pp. 47-66 ◽  
Author(s):  
Pavel Ya. Groisman ◽  
Richard W. Knight ◽  
Thomas R. Karl
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Heavy Precipitation ◽  
The Past ◽  
Extreme Precipitation Events ◽  
Intense Precipitation ◽  
Central United States ◽  
Extreme Rain ◽  
Rain Events ◽  
Precipitation Events

Abstract In examining intense precipitation over the central United States, the authors consider only days with precipitation when the daily total is above 12.7 mm and focus only on these days and multiday events constructed from such consecutive precipitation days. Analyses show that over the central United States, a statistically significant redistribution in the spectra of intense precipitation days/events during the past decades has occurred. Moderately heavy precipitation events (within a 12.7–25.4 mm day−1 range) became less frequent compared to days and events with precipitation totals above 25.4 mm. During the past 31 yr (compared to the 1948–78 period), significant increases occurred in the frequency of “very heavy” (the daily rain events above 76.2 mm) and extreme precipitation events (defined as daily and multiday rain events with totals above 154.9 mm or 6 in.), with up to 40% increases in the frequency of days and multiday extreme rain events. Tropical cyclones associated with extreme precipitation do not significantly contribute to the changes reported in this study. With time, the internal precipitation structure (e.g., mean and maximum hourly precipitation rates within each preselected range of daily or multiday event totals) did not noticeably change. Several possible causes of observed changes in intense precipitation over the central United States are discussed and/or tested.

scholarly journals Perturbing the potential vorticity field in mesoscale forecasts of two Mediterranean heavy precipitation events

2012 ◽  
Vol 64 (1) ◽  
pp. 17224 ◽  
Author(s):  
Maria-Del-Mar Vich ◽  
Romualdo Romero ◽  
Evelyne Richard ◽  
Philippe Arbogast ◽  
Karine Maynard
Keyword(s):  
Potential Vorticity ◽  
Heavy Precipitation ◽  
Vorticity Field ◽  
Precipitation Events

scholarly journals On the robustness of the estimates of centennial-scale variability in heavy precipitation from station data over Europe

2005 ◽  
Vol 32 (14) ◽  
pp. n/a-n/a ◽  
Author(s):  
Olga Zolina ◽  
Clemens Simmer ◽  
Alice Kapala ◽  
Sergey Gulev
Keyword(s):  
Heavy Precipitation ◽  
Station Data

scholarly journals Changes in magnitude and frequency of heavy precipitation across China and its potential links to summer temperature

2017 ◽  
Vol 547 ◽  
pp. 718-731 ◽  
Author(s):  
Xihui Gu ◽  
Qiang Zhang ◽  
Vijay P. Singh ◽  
Peijun Shi
Keyword(s):  
Heavy Precipitation ◽  
Summer Temperature

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

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