scholarly journals Orographic Signature on Extreme Precipitation of Short Durations

2015 ◽  
Vol 16 (1) ◽  
pp. 278-294 ◽  
Author(s):  
Francesco Avanzi ◽  
Carlo De Michele ◽  
Salvatore Gabriele ◽  
Antonio Ghezzi ◽  
Renzo Rosso
Keyword(s):  
Extreme Precipitation ◽  
Principal Direction ◽  
Moisture Flux ◽  
Annual Precipitation ◽  
Data Series ◽  
Atmospheric Moisture ◽  
The Mean ◽  
High Elevations ◽  
Invariance Model ◽  
Italian Territory

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.

Evaluation of climate model simulations in representing the precipitation non-stationarity by considering observational uncertainties

2021 ◽  
Author(s):  
Yongjing Wan ◽  
Jie Chen ◽  
Ping Xie ◽  
Chong-Yu Xu ◽  
Daiyuan Li
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Spatial Distributions ◽  
Model Simulations ◽  
The Mean ◽  
Climate Model Simulations

<p>The reliability of climate model simulations in representing the precipitation changes is one of the preconditions for climate-change impact studies. However, the observational uncertainties hinder the robust evaluation of these climate model simulations. The goal of the present study is to evaluate the capacities of climate model simulations in representing the precipitation non-stationarity in consideration of observational uncertainties. The mean of multiple observations (OBSE) from five observational precipitation datasets is used as a reference to quantify the uncertainty of observed precipitation and to evaluate the performance of climate model simulations. The non-stationarity of precipitation was represented using the mean and variance of annual total precipitation and annual maximum daily precipitation for the 1982–2015 period. The results show that the spatial distributions of annual and extreme precipitation are similar for various observational datasets, while there has less agreement in the variance changes of extreme precipitation. Climate models are capable of representing the spatial distributions of the annual and extreme precipitation amounts at the global scales. In terms of the non-stationarity, climate model simulations are capable of capturing the large-scale spatial pattern of the trend in mean for annual precipitation. On the contrary, the simulations are less reliable in reproducing the change of extreme precipitation, as well as the trend of variance for annual precipitation. Overall, climate models are more reliable in simulating the mean of precipitation than the variance, and they are more reliable in simulating annual precipitation than extreme. Besides, the uncertainties of precipitation for both observations and simulations are much larger in monsoon regions than in other regions. This study suggests that considering observational uncertainties is necessary when using observational datasets as the reference to project future climate change and assess the impact of climate change on environments.</p>

Comparative Analysis or Precipitation Variation Characteristics between Subtropical Monsoon Climate and Temperate Monsoon Climate-Take Changsha and Chengde for Example

2021 ◽  
Vol 7 (5) ◽  
pp. 1113-1122
Author(s):  
Bo Chen ◽  
Shi-jun Xu ◽  
Xin-ping Zhang ◽  
Yi Xie
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Precipitation Intensity ◽  
Annual Precipitation ◽  
Wet Season ◽  
Precipitation Frequency ◽  
Extreme Precipitation Events ◽  
Average Precipitation ◽  
Autumn And Winter ◽  
Average Annual Precipitation

Using the methods of literature review, regression analysis and moving average, this paper selects the daily precipitation of Changsha and Chengde from 1951 to 1986 as samples, and analyzes the average precipitation, precipitation frequency, precipitation intensity, extreme precipitation time and other indicators of Changsha and Chengde from the perspective of interannual and seasonal changes Trends. The researches show that: the average precipitation of Changsha in the 36 years is 1151.2mm, spring is the wet season, autumn and winter are the dry seasons, and the maximum average precipitation is in spring; the average annual precipitation, precipitation frequency in spring, summer and winter, annual precipitation frequency, annual precipitation intensity and extreme precipitation events show a decreasing trend. The average annual precipitation of Chengde city is 454.1 mm, wet season in summer and dry season in spring, autumn and winter; the average annual precipitation, precipitation in four seasons, annual precipitation frequency, precipitation frequency in spring, autumn and winter, annual precipitation intensity and extreme precipitation events show a decreasing trend, while the precipitation frequency in summer shows an increasing trend. The study of regional climate change based on the time series data of this stage is of great significance to comprehensively understand the law of regional climate change and predict the future trend of climate change.

How landscape and climate affect the spatial variability of the Italian rainfall extremes? Some initial clues based on I2-RED

2021 ◽  
Author(s):  
Paola Mazzoglio ◽  
Ilaria Butera ◽  
Pierluigi Claps
Keyword(s):  
Spatial Variability ◽  
Linear Regression Analysis ◽  
Alpine Region ◽  
Annual Rainfall ◽  
Mean Values ◽  
Rainfall Extremes ◽  
Geomorphological Parameters ◽  
The Mean ◽  
The Relationship ◽  
Italian Territory

<p>The intensity and the spatial distribution of precipitation depths are known to be highly dependent on relief and geomorphological parameters. Complex environments like mountainous regions are prone to intense and frequent precipitation events, especially if located near the coastline. Although the link between the mean annual rainfall and geomorphological parameters has received substantial attention, few literature studies investigate the relationship between the sub-daily maximum annual rainfall depth and geographical or morphological landscape features.<br>In this study, the mean of the rainfall extremes in Italy, recently revised in the so-called I<sup>2</sup>-RED dataset, are investigated in their spatial variability in comparison with some landscape and also some broad climatic characteristics. The database includes all sub-daily rainfall extremes recorded in Italy from 1916 until 2019 and this analysis considers their mean values (from 1 to 24 hours) in stations with at least 10 years of records, involving more than 3700 stations.<br>The geo-morpho-climatic factors considered range from latitude, longitude and minimum distance from the coastline on the geographic side, to elevation, slope, openness and obstruction morphological indices, and also include an often-neglected robust climatological information, as the local mean annual rainfall.<br>Obtained results highlight that the relationship between the annual maximum rainfall depths and the hydro-geomorphological parameters is not univocal over the entire Italian territory and over different time intervals. Considering the whole of Italy, the highest correlation is reached between the mean values of the 24-hours records and the mean annual precipitation (correlation coefficient greater than 0.75). This predominance remains also in sub-areas of the Italian territory (i.e., the Alpine region, the Apennines or the coastal areas) but correlation decreases as the time interval decreases, except for the Alpine region (0.73 for the 1-hour maximum). The other geomorphological parameters seem to act in conjunction, making it difficult to evaluate, with a simple linear regression analysis, their impact. As an example, the absolute value of the correlation coefficient between the elevation and the 1-hour extremes is greater than 0.35 for the Italian and the Alpine regions, while for the 24-hours interval it is greater than 0.35 over the coastal areas.<br>To further investigate the spatial variability of the relationship between rainfall and elevation, a spatial linear regression analysis has been undertaken. Local linear relationships have been fitted in circles centered on any of the 0.5-km size pixels in Italy, with 1 to 30 km radius and at least 5 stations included. Results indicate the need of more comprehensive terrain analysis to better understand the causes of local increasing or decreasing relations, poorly described in the available literature.</p>

Understanding Precipitation Characteristics of Afghanistan at Provincial Scale

2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma
Keyword(s):  
Extreme Precipitation ◽  
Asian Country ◽  
Annual Precipitation ◽  
Precipitation Pattern ◽  
Precipitation Trend ◽  
Extreme Precipitation Events ◽  
Changing Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

Abstract This study examines the pattern and trend of seasonal and annual precipitation along with extreme precipitation events in a data scare, south Asian country, Afghanistan. Seven extreme precipitation indices were considered based upon intensity, duration and frequency of precipitation events. The study revealed that precipitation pattern of Afghanistan is unevenly distributed at seasonal and yearly scales. Southern and Southwestern provinces remain significantly dry whereas, the Northern and Northeastern provinces receive comparatively higher precipitation. Spring and winter seasons bring about 80% of yearly precipitation in Afghanistan. However, a notable declining precipitation trend was observed in these two seasons. An increasing trend in precipitation was observed for the summer and autumn seasons, however; these seasons are the lean periods for precipitation. A declining annual precipitation trend was also revealed in many provinces of Afghanistan. Analysis of extreme precipitation indices reveals a general drier condition in Afghanistan. Large spatial variability was found in precipitation indices. In many provinces of Afghanistan, a significantly declining trends were observed in intensity-based (Rx1-day, RX5-day, SDII and R95p) and frequency-based (R10) precipitation indices. The duration-based precipitation indices (CDD and CWD) also infer a general drier climatic condition in Afghanistan. This study will assist the agriculture and allied sectors to take well-planned adaptive measures in dealing with the changing patterns of precipitation, and additionally, facilitating future studies for Afghanistan.

scholarly journals Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Xia Feng ◽  
Paul Houser
Keyword(s):  
Water Cycle ◽  
Spatial Scales ◽  
Atmospheric Moisture ◽  
Spatial Correlations ◽  
Climate Indicators ◽  
Terrestrial Water ◽  
The Mean ◽  
Atmospheric Moisture Content ◽  
Daily Total

In this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist of six water balance variables monitoring the mean conditions and extreme aspects of the changing water cycle. The variables include precipitation (P), evaporation (E), runoff (R), terrestrial water storage (dS/dt), moisture convergence flux (C), and atmospheric moisture content (dW/dt). Means are determined as the daily total value, while extremes include wet and dry extremes, defined as the upper and lower 10th percentile of daily distribution. Trends are assessed for annual and seasonal indicators at several different spatial scales. Our results indicate that significant changes have occurred in most of the indicators, and these changes are geographically and seasonally dependent. There are more upward trends than downward trends in all eighteen annual indicators averaged over the CONUS. The spatial correlations between the annual trends in means and extremes are statistically significant across the country and are stronger forP,E,R, andCcompared todS/dtanddW/dt.

scholarly journals Erosive rainfall in the Rio do Peixe Valley: Part III - Risk of extreme events

2018 ◽  
Vol 22 (1) ◽  
pp. 63-68
Author(s):  
Álvaro J. Back ◽  
Augusto C. Pola ◽  
Nilzo I. Ladwig ◽  
Hugo Schwalm
Keyword(s):  
Extreme Events ◽  
Annual Rainfall ◽  
Data Series ◽  
Rainfall Erosivity ◽  
Significance Level ◽  
Control Structures ◽  
Kolmogorov Smirnov ◽  
Runoff Control ◽  
The Mean ◽  
Erosive Rainfall

ABSTRACT Understanding the risks of extreme events related to soil erosion is important for adequate dimensioning of erosion and runoff control structures. The objective of this study was to determine the rainfall erosivity with different return periods for the Valley of the Rio do Peixe in Santa Catarina state, Brazil. Daily pluviographic data series from 1984 to 2014 from the Campos Novos, and Videira meteorological stations and from 1986 to 2014 from the Caçador station were used. The data series of maximum annual rainfall intensity in 30 min, maximum annual erosive rainfall, and total annual erosivity were analyzed for each station. The Gumbel-Chow distributions were adjusted and their adhesions were evaluated by the Kolmogorov-Smirnov test at a significance level of 5%. The Gumbel-Chow distribution was adequate for the estimation of all studied variables. The mean annual erosivity corresponds to the return period of 2.25 years. The data series of the annual maximum individual rainfall erosivity coefficients varied from 47 to 50%.

scholarly journals A Mass and Energy Conservation Analysis of Drift in the CMIP6 Ensemble

2021 ◽  
Author(s):  
Damien Irving
Keyword(s):  
Climate Models ◽  
Heat Content ◽  
Moisture Flux ◽  
Cmip5 Models ◽  
Energy Budgets ◽  
Freshwater Flux ◽  
Atmospheric Moisture ◽  
State Variables ◽  
Conservation Of Energy ◽  
Ocean Mass

Coupled climate models are prone to ‘drift’ (long-term unforced trends in state variables) due to incomplete spin-up and non-closure of the global mass and energy budgets. Here we assess model drift and the associated conservation of energy, mass and salt in CMIP6 and CMIP5 models. For most models, drift in globally-integrated ocean mass and heat content represents a small but non-negligible fraction of recent historical trends, while drift in atmospheric water vapor is negligible. Model drift tends to be much larger in time-integrated ocean heat and freshwater flux, net top-of-the-atmosphere radiation (netTOA) and moisture flux into the atmosphere (evaporation minus precipitation), indicating a substantial leakage of mass and energy in the simulated climate system. Most models are able to achieve approximate energy budget closure after drift is removed, but ocean mass budget closure eludes a number of models even after de-drifting and none achieve closure of the atmospheric moisture budget. The magnitude of the drift in the CMIP6 ensemble represents an improvement over CMIP5 in some cases (salinity and time-integrated netTOA) but is worse (time-integrated ocean freshwater and atmospheric moisture fluxes) or little changed (ocean heat content, ocean mass and time-integrated ocean heat flux) for others, while closure of the ocean mass and energy budgets after drift removal has improved.

scholarly journals Dynamical and Synoptic Characteristics of Heavy Rainfall Episodes in Southern Brazil

2007 ◽  
Vol 135 (2) ◽  
pp. 598-617 ◽  
Author(s):  
Mateusda Silva Teixeira ◽  
Prakki Satyamurty
Keyword(s):  
Heavy Rainfall ◽  
Moisture Flux ◽  
Southern Brazil ◽  
Mean Flow ◽  
Pressure Center ◽  
Average Rainfall ◽  
Meridional Winds ◽  
The Mean ◽  
Low Level Jet ◽  
Atmospheric Variables

Abstract The dynamical and synoptic characteristics that distinguish heavy rainfall episodes from nonheavy rainfall episodes in southern Brazil are discussed. A heavy rainfall episode is defined here as one in which the 50 mm day−1 isohyet encloses an area of not less than 10 000 km2 in the domain of southern Brazil. One hundred and seventy such events are identified in the 11-yr period of 1991–2001. The mean flow patterns in the period of 1–3 days preceding the episodes show some striking synoptic-scale features that may be considered forerunners of these episodes: (i) a deepening midtropospheric trough in the eastern South Pacific approaches the continent 3 days before, (ii) a surface low pressure center forms in northern Argentina 1 day before, (iii) a northerly low-level jet develops over Paraguay 2 days before, and (iv) a strong moisture flux convergence over southern Brazil becomes prominent 1 day before the episode. A parameter called rainfall quantity, defined as the product of the area enclosed by the 50 mm day−1 isohyet and the average rainfall intensity, is correlated with fields of atmospheric variables such as 500-hPa geopotential and 850-hPa meridional winds. Significant lag correlations show that the anomalies of some atmospheric variables could be viewed as precursors of heavy rainfall in southern Brazil that can be explored for use in improving the forecasts.

scholarly journals Isotopes of oxygen-18 and deuterium in precipitation in Slovakia / Izotopy kyslíka-18 A deutéria v zrážkach na Slovensku

2012 ◽  
Vol 60 (4) ◽  
pp. 265-276 ◽  
Author(s):  
Ladislav Holko ◽  
Michal Dóša ◽  
Juraj Michalko ◽  
Martin Šanda
Keyword(s):  
Isotopic Composition ◽  
Air Temperature ◽  
Meteoric Water ◽  
Precipitation Amount ◽  
Data Series ◽  
Water Line ◽  
Temperature And Precipitation ◽  
Meteoric Water Line ◽  
The Mean ◽  
Available Information

The article synthesizes available information on isotopic composition of precipitation in Slovakia (the Western Carpathians). Monthly δ18O data from eleven stations and period 1988-1997 were used to investigate correlations among the stations, altitude, air temperature and precipitation amount effects. The mean annual altitude and air temperature gradients of δ18O in precipitation were 0.21‰/100 m and 0.36‰/1°C, respectively. Maps of spatial distribution of mean annual δ18O in precipitation based on both gradients were constructed. The two maps do not significantly differ for the majority of Slovakia. δ2H data were available for only three stations. Local meteoric water line derived for the station with the longest data series (δ2H = = 7.86δ18O + 6.99) was close to the Global Meteoric Water line. Its parameters in periods 1991-1993 and 1991-2008 did not change. The study indicates that a more detailed monitoring of isotopic composition of precipitation in mountains should be carried out in the future. The highest station exhibited very small seasonal variability of δ18O in precipitation compared to other Slovak stations. The second highest mountain station had significantly higher deuterium excess than the neighboring stations located in the valley. In some analyses the data from the nearest stations situated abroad (Vienna, Krakow) were used.

scholarly journals Atmospheric moisture sources associated with extreme precipitation during the peak precipitation month

2020 ◽  
Vol 30 ◽  
pp. 100289
Author(s):  
Marta Vázquez ◽  
Raquel Nieto ◽  
Margarida L.R. Liberato ◽  
Luis Gimeno
Keyword(s):  
Extreme Precipitation ◽  
Atmospheric Moisture ◽  
Moisture Sources
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