Occurrence Of Rainfall Events Research Articles

A metastatistical approach to rainfall extremes

The traditional statistical theory of extreme events assumes an asymptotic regime in which the number of events per year is large enough for a limiting Generalized Extreme Value distribution to apply. This has been shown not to be applicable to many practical cases. We introduce here a Metastatistical Extreme Value (MEV) approach which is defined in terms of the distribution of the statistical parameters describing “ordinary” daily rainfall occurrence and intensity. The method does not require an asymptotic assumption, and naturally accounts for the influence of the bulk of the distribution of ordinary events on the distribution of annual maximum daily rainfall. Building on existing observations showing the distribution of daily rainfall to be Weibull right-tail equivalent, the MEV approach is then specialized to yield a compact and easily applicable formulation. We apply this formulation to Monte Carlo experiments based on Weibull statistics derived from the 3-century long rainfall time series observed in Padova (Italy). We find an excellent agreement between MEV estimates and the ‘observed’ frequency of occurrence of extreme events in the synthetic time series generated. GEV and Gumbel estimates, on the contrary, exhibit systematic errors. Tests with different rates of occurrence of rainfall events show slight improvements of the GEV and Gumbel estimation bias when the number of events/year is increased. However, a constant bias in GEV and Gumbel estimates is seen for (synthetic) climates where the number of events and the distribution of intensities is varied stochastically. The estimation root mean square error is also larger for the GEV and Gumbel distributions than for the MEV approach. Hence, GEV and Gumbel quantile estimates are more likely to be further away from the actual value than MEV estimates. Finally, the application of the new MEV approach to subsets of the long Padova time series identifies marked variabilities in rainfall extremes at the centennial time scale.

Litter decomposition rates of green manure as affected by soil erosion, transport and deposition processes, and the implications for the soil carbon balance of a rainfed olive grove under a dry Mediterranean climate

Soil erosion by water promotes the distribution of soil organic carbon (SOC) and nutrients within the landscape. Moreover, soil redistribution may have a large impact on litter decomposition dynamics. There is a current lack of information about the role of soil erosion in the SOC balance of sloping agricultural fields because its magnitude and direction depend on the dominant horizontal and vertical C fluxes at the different landform (eroding, transport and depositional) positions within the hillslope. Therefore, the significance of these lateral fluxes in the local C balance has to be assessed when interactions with vertical C fluxes (e.g., litter decay) are also taken into account. An experiment was designed to increase our understanding of the role of different phases of the soil erosion process in litter decomposition and the resulting impact on the soil C balance of a rain-fed olive grove under a dry Mediterranean climate, in which two or three high intensity-low frequency rainfall events are responsible for the majority of the annual soil erosion. To accomplish this, four replicate plots were installed at three different landform positions, according to erosion criteria (eroding, transport and depositional sites), and two litter types (Avena sativa L. or Vicia sativa L.) with contrasting initial litter chemistry (high C:N, low C:N) were deployed in the middle of the summer season, before the expected occurrence of rainfall events in the experimental area. Two successive rainfall events led to pronounced patterns of erosion and associated processes of soil transport and deposition, accounting for 99% of total soil loss in the experimental area and leading to the burial of most of the litterbags located at the depositional positions. The results indicate that soil erosion (lateral movement and soil mixing) may be an important mechanism of litter decomposition, as litter mass loss rates were related closely to the amount of soil infiltrated/deposited within the litterbags for both litter types, decay rates at depositional sites being about three-fold higher than at eroding and transport sites. Our results also indicate that soil mobilisation by erosion has significant impacts on C dynamics, causing lateral and vertical fluxes of C similar in magnitude to those induced by changes in land use or management. According to our estimates, soil C losses driven by land-use change could be compensated after 20 years of green manure incorporation in this rainfed Mediterranean olive grove.

A statistical approach for rain intensity differentiation using Meteosat Second Generation–Spinning Enhanced Visible and InfraRed Imager observations

Abstract. This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h-1) class, the light-to-moderate rainy class (0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the heavy–to-very-heavy-rainy class (rain rate value ≥ 4 mm h-1). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events. The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97% (96%), and when all the rainy classes are considered, it shows a Heidke skill score of 67% (62%), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81% (81%).

Observed trends and variations in rainfall events over Ratnagiri (Maharashtra) during southwest monsoon season

The observed trends and variations in rainfall during southwest (SW) monsoon season (June to September) of individual station Ratnagiri, have been analyzed by using 30 years (1980-2009) daily rainfall data. The analysis revealed decreasing but not significant trend in total amount of rainfall and number of rainy days, with increasing but not significant trend in average intensity of rainfall during rainy days of monsoon season. To verify this increase in average intensity of monsoon rainfall over the region, the trends in frequency of occurrence of rainfall events and percentage (%) contribution of rainfall events, to total monsoon rainfall in different categories of rainfall event, along with decadal variation during monsoon season are analyzed. The trend shows that frequency of occurrence of rainfall events and % contribution of rainfall events to total monsoon rainfall in category of light, moderate, rather heavy and heavy rainfall events decreased (but not significantly), whereas frequency of occurrence of rainfall events and % contribution of rainfall events to total monsoon rainfall in category of very heavy to exceptionally heavy rainfall events increased (but not significantly) during 30 years (1980-2009) over Ratnagiri indicating that increase in average intensity of monsoon rainfall is contributed by very heavy to exceptionally heavy rainfall events.Decadal analysis also shows that frequency of occurrence of rainfall events and % contribution of rainfall events to total monsoon rainfall in category of light, moderate, rather heavy and heavy rainfall events have decreased per decade. Whereas in category of very heavy to exceptionally heavy rainfall events it has increased per decade. This increased frequency of very heavy to exceptionally heavy rainfall events over the region may lead to an increase in frequency of floods, landslides and spoil agricultural crops and hence requires attention.

Evaluation of high-resolution satellite rainfall products using rain gauge data over complex terrain in southwest China

Availability of high-resolution satellite rainfall products provides a great opportunity to monitor precipitation frequently over large and remote areas. However, the accuracies of these products need thorough assessment before they can be widely used. The objective of this study is to evaluate the accuracies of Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis 3B42 products (TMPA V6 and TMPA V7) using a network of 75 rain gauges over Southwestern China. The study region has a complex terrain, which makes it challenging for TMPA rainfall products to give reliable estimates. The results show that the TMPA products tend to underestimate the occurrences of rainfall events. Furthermore, TMPA V6 always underestimates the precipitation, while V7 generally overestimates rainfall in wet season and underestimates it in dry season. Under- and overestimation of rainfall by the two products can be mainly attributed to false alarm events. The overall accuracies of the two products depend heavily on the time scale. At the daily scale, these products may not be reliable; however, the overall accuracies are improved substantially when the time scale is extended from daily to monthly and seasonal scales. Reliability of the TMPA precipitation estimates is also dependent on the climate zones and elevation to some extent and shows clear seasonal variations. In the wet months from May to September, the estimates for TMPA 3B42 V6 and V7 tend to be more accurate. In comparison, the accuracy of V7 is improved slightly over V6. However, V7 still has some major limitations in reproducing precipitation in dry seasons and in high-elevation regions with complex terrains, suggesting that further improvements in TMPA precipitation retrieval algorithms are still needed for this type of regions.

Impact of the El Niño–Southern Oscillation, Indian Ocean Dipole, and Southern Annular Mode on Daily to Subdaily Rainfall Characteristics in East Australia

Abstract The relationship between seasonal aggregate rainfall and large-scale climate modes, particularly the El Niño–Southern Oscillation (ENSO), has been the subject of a significant and ongoing research effort. However, relatively little is known about how the character of individual rainfall events varies as a function of each of these climate modes. This study investigates the change in rainfall occurrence, intensity, and storm interevent time at both daily and subdaily time scales in east Australia, as a function of indices for ENSO, the Indian Ocean dipole (IOD), and the southern annular mode (SAM), with a focus on the cool season months. Long-record datasets have been used to sample a large variety of climate events for better statistical significance. Results using both the daily and subdaily rainfall datasets consistently show that it is the occurrence of rainfall events, rather than the average intensity of rainfall during the events, which is most strongly influenced by each of the climate modes. This is shown to be most likely associated with changes to the time between wet spells. Furthermore, it is found that despite the recent attention in the research literature on other climate modes, ENSO remains the leading driver of rainfall variability over east Australia, particularly farther inland during the winter and spring seasons. These results have important implications for how water resources are managed, as well as how the implications of large-scale climate modes are included in rainfall models to best capture interannual and longer-scale variability.

Determination of Critical Rainfall Events for Quantitative Microbial Risk Assessment of Land-Applied Soil Amendments

The occurrence of rainfall events has been significantly linked to waterborne-disease outbreaks in the United States and other parts of the world, indicating that wet-weather events may have significant impacts on microbial risk. An important step in developing a quantitative microbial risk assessment for exposure to pathogens originating from land application of soil amendments is to characterize the risk of storm-induced infiltration and runoff, the hydrologic processes most likely to introduce soil amendment-associated pathogens to source water. This paper develops an approach to estimate the risks of producing sufficient infiltration to saturate the soil to the water table and runoff to surface water on the basis of widely available intensity-duration-frequency curves for rainfall events. An infiltration model is developed to determine the runoff volume and infiltration depth associated with specific storm events. For a given return period the maximum infiltration and maximum runoff (which will typically be produced by different storm events) are then associated with that return period. For a specified return period the maximum runoff is produced by intermediate duration events, as very short storms do not saturate the soil and very long duration storms are of lower intensity and generally do not exceed the infiltration capacity of the soil. Infiltration amounts tend initially to increase with duration and then plateau as longer duration events become less intense. The inverse of the return period of the critical rainfall events provide the probabilities of infiltration and runoff that may introduce fertilizer-associated pathogens to source waters. This approach provides a sound method for determining the storm events with the greatest potential for mobilization of pathogens in the environment and the greatest risk to human health.

Daily Precipitation Statistics for South America: An Intercomparison between NCEP Reanalyses and Observations

Abstract In this study, the authors document the extent to which the precipitation statistics of the new CFS reanalysis (CFSR) represent an improvement over the earlier reanalyses: the NCEP–NCAR reanalysis (R1) and the NCEP–DOE Second Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (R2). An intercomparison between the CFSR, R1, R2, and observations over South America was made for the period 1979–2006. The CFSR shows notable improvements in the large-scale precipitation patterns compared with the previous reanalyses (R1 and R2). In spite of these improvements, the CFSR has substantial biases in intensity and frequency of occurrence of rainfall events. Over west-central Brazil, the core region of the South American monsoon system (SAMS), the CFSR displays a dry bias during the onset phase of the SAMS wet season and a wet bias during the peak and decay phases of the SAMS wet season. The CFSR also displays a dry bias along the South American coast near the mouth of the Amazon and along the east coast of northeastern Brazil. A wet bias exists in all seasons over southeast Brazil and over the Andes Mountains.

Application of time-series analysis to urban storm drainage

In urban storm drainage, deterministic models, such as SWMM, HydroWorks and MOUSE are commonly used. However, comprehensive research programmes, including field surveys, have indicated that most processes related to urban storm drainage have stochastic characteristic, like the occurrence of rainfall events, the processes of rainfall-runoff and flow routing in sewer networks3etc.. Particularly, sediments found in sewers either in suspension or in deposition, cannot be considered as having a unique entity. Inhomogeneity and randomness are just the nature of sewer sediment behaviour. Most data required for urban storm drainage are time-series data, such as rainfall intensity, water level measured in an outfall, CSO discharge and pollutant load etc.. Consequently, time-series analysis should be an alternative for predicting some relationships of urban storm drainage, such as (net) rainfall-CSO discharge, rainfall-water level and CSO discharge-pollutant load.

Application of time-series analysis to urban storm drainage

In urban storm drainage, deterministic models, such as SWMM, HydroWorks and MOUSE are commonly used. However, comprehensive research programmes, including field surveys, have indicated that most processes related to urban storm drainage have stochastic characteristic, like the occurrence of rainfall events, the processes of rainfallrunoff and flow routing in sewer networks etc.. Particularly, sediments found in sewers, either in suspension or in deposition, cannot be considered as having a unique entity. Inhomogeneity and randomness are just the nature of sewer sediment behaviour. Most data required for urban storm drainage are time-series data, such as rainfall intensity, water level measured in an outfall, CSO discharge and pollutant load etc.. Consequently, time-series analysis should be an alternative for predicting some relationships of urban storm drainage, such as (net) rainfall-CSO discharge, rainfall-water level and CSO discharge-pollutant load.

Long‐term variations in regional rainfall in the south‐west of Western Australia and the difference between average and high intensity rainfalls

AbstractThe south‐west of Western Australia is characterized by a ‘Mediterranean’ climate with dominantly winter rainfall. It is the only Australian region where the annual rainfall has significantly decreased during the period 1911–1990. Based on daily rainfall records from 70 stations in the area, high intensity rainfall (which is closely related to flooding, soil erosion, and gully formation) does not show a concurrent decrease. Reasons for this unconformable trend include a greater temporal variability of high intensity rainfall and an increase in the frequency of occurrence of rainfall events at high intensities during the summer. This tends to balance out a decrease during the winter months. While it is unwise to assume that there will be similar trends for average rainfall and high intensity rainfall for a given region, evidence from the instrumental records supports, to some extent, the notion that in a CO2‐warmed world, high intensity rainfall could occur more frequently irrespective of local change to average rainfall.