Stochastic Modelling of the Daily Rainfall Frequency and Amount

2014 ◽  
Vol 39 (7) ◽  
pp. 5691-5702 ◽  
Author(s):  
Naeem Sadiq
Keyword(s):  
Daily Rainfall ◽  
Stochastic Modelling ◽  
Rainfall Frequency

scholarly journals Impact of downscaled rainfall biases on projected runoff changes

2020 ◽  
Vol 24 (6) ◽  
pp. 2981-2997
Author(s):  
Stephen P. Charles ◽  
Francis H. S. Chiew ◽  
Nicholas J. Potter ◽  
Hongxing Zheng ◽  
Guobin Fu ◽  
...  
Keyword(s):  
Water Supply ◽  
Grid Point ◽  
Daily Rainfall ◽  
Rainfall Runoff ◽  
Rainfall Frequency ◽  
Rainfall Runoff Model ◽  
Projected Changes ◽  
Runoff Model ◽  
Regional Water

Abstract. Realistic projections of changes to daily rainfall frequency and magnitude, at catchment scales, are required to assess the potential impacts of climate change on regional water supply. We show that quantile–quantile mapping (QQM) bias-corrected daily rainfall from dynamically downscaled WRF simulations of current climate produce biased hydrological simulations, in a case study for the state of Victoria, Australia (237 629 km2). While the QQM bias correction can remove bias in daily rainfall distributions at each 10 km × 10 km grid point across Victoria, the GR4J rainfall–runoff model underestimates runoff when driven with QQM bias-corrected daily rainfall. We compare simulated runoff differences using bias-corrected and empirically scaled rainfall for several key water supply catchments across Victoria and discuss the implications for confidence in the magnitude of projected changes for mid-century. Our results highlight the imperative for methods that can correct for temporal and spatial biases in dynamically downscaled daily rainfall if they are to be suitable for hydrological projection.

Stochastic Modelling Of Maximum Depths Of Daily Rainfall

1984 ◽  
Vol 4 (4) ◽  
pp. 145-148
Author(s):  
Huynh Ngoc Phien ◽  
Patnaik Debabrata
Keyword(s):  
Daily Rainfall ◽  
Stochastic Modelling

scholarly journals Spatial Coherence of Tropical Rainfall at the Regional Scale

2007 ◽  
Vol 20 (21) ◽  
pp. 5244-5263 ◽  
Author(s):  
Vincent Moron ◽  
Andrew W. Robertson ◽  
M. Neil Ward ◽  
Pierre Camberlin
Keyword(s):  
Regional Scale ◽  
Spatial Coherence ◽  
Daily Rainfall ◽  
Frequency Of Occurrence ◽  
Tropical Regions ◽  
Mean Intensity ◽  
Northwestern India ◽  
Rainfall Occurrence ◽  
Rainfall Frequency ◽  
Daily Time

Abstract This study examines the spatial coherence characteristics of daily station observations of rainfall in five tropical regions during the principal rainfall season(s): the Brazilian Nordeste, Senegal, Kenya, northwestern India, and northern Queensland. The rainfall networks include between 9 and 81 stations, and 29–70 seasons of observations. Seasonal-mean rainfall totals are decomposed in terms of daily rainfall frequency (i.e., the number of wet days) and mean intensity (i.e., the mean rainfall amount on wet days). Despite the diverse spatiotemporal sampling, orography, and land cover between regions, three general results emerge. 1) Interannual anomalies of rainfall frequency are usually the most spatially coherent variable, generally followed closely by the seasonal amount, with the daily mean intensity in a distant third place. In some cases, such as northwestern India, which is characterized by large daily rainfall amounts, the frequency of occurrence is much more coherent than the seasonal amount. 2) On daily time scales, the interstation correlations between amounts on wet days always fall to insignificant values beyond a distance of about 100 km. The spatial scale of daily rainfall occurrence is larger and more variable among the networks. 3) The regional-scale signal of the seasonal amount is primarily related to a systematic spatially coherent modulation of the frequency of occurrence.

scholarly journals Analisis Dampak Perubahan Tataguna Lahan Sub DAS Beringin di Bukit Semarang Baru Terhadap Peningkatan Debit Sungai Beringin Kota Semarang

2017 ◽  
Vol 19 (1) ◽  
pp. 31-38
Author(s):  
Sumiyadi -
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Impact Analysis ◽  
Water Discharge ◽  
Research Result ◽  
Daily Rainfall ◽  
Runoff Water ◽  
Watershed Area ◽  
Rainfall Frequency ◽  
Housing Area

The changes of landuse in watershed area of Beringin river, from rubber forest into housing area of Bukit Semarang Baru (BSB), is suspected as the cause of increase in water discharge into Beringin river. The research objective is to describe the rise in water discharge of Beringin river due to the changes of landuse in the watershed area of Beringin river which currently inhibited by BSB housing. According to statistics criteria, the distribution of maximum daily rainfall frequency for repeated period of 2, 5, 10 and 20 years was analyzed by distribution frequency Gumbel. Research result shows that there is an increase in water discharge of Beringin river due to the rise of runoff water as the consequence of land use change in BSB area. Ten years discharge before the land use change was = 7,94 m /dt, then raised into 113,49 m3 /dt following the change, so the water discharge of Beringin river is = 121,43 m3 /dt. This impact analysis can be an early information for the future researcher to find the solution of flood phenomena in Semarang.Perubahan tataguna lahan di sub DAS Beringin, dari hutan karet menjadi kawasan hunian Bukit Semarang Baru (BSB) diduga penyebab meningkatnya aliran limpasan yang masuk sungai Beringin. Tujuan penelitian untuk mengetahui peningkatan debit sungai Beringin, akibat dari perubahan tataguna lahan sub DAS Beringin di kawasan hunian BSB. Berdasarkan kriteria statistik, distribusi frekuensi hujan harian maksimum untuk periode ulang 2, 5, 10, dan 20 tahunan dilakukan analisis frekuensi agihan Gumbel. Hasil penelitian menunjukkan terjadi peningkatan debit di sungai Beringin karena bertambahnya aliran limpasan akibat dari perubahan tata guna lahan di kawasan BSB. Debit 10 tahunan sebelum perubahan tataguna lahan Q10 = 7,94 m3 /dt, setelah perubahan ada tambahan debit 113,49 m3 /dt, sehingga debit sungai beringin menjadi Q10 = 121,43 m3 /dt. Analisa dampak ini sebagai informasi awal bagi para peneliti, untuk mencari solusi terhadap masalah banjir di Semarang.

Stochastic Modelling Of Maximum Depths Of Daily Rainfall

1984 ◽  
Vol 4 (4) ◽  
pp. 149-152
Author(s):  
Huynh Ngoc Phien ◽  
Patnaik Debabrata
Keyword(s):  
Daily Rainfall ◽  
Stochastic Modelling

scholarly journals Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause

2015 ◽  
Vol 15 (5) ◽  
pp. 2313-2326 ◽  
Author(s):  
E. K. Bigg ◽  
S. Soubeyrand ◽  
C. E. Morris
Keyword(s):  
Pseudomonas Syringae ◽  
Leaf Surface ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Historical Record ◽  
Past Century ◽  
Long Term Effects ◽  
Power Stations ◽  
Ice Nuclei ◽  
Rainfall Frequency

Abstract. Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would automatically have reduced the influences on rainfall of those whose concentrations were related to previous rain, thereby leading to inhibition of feedback. The analytical methods described here provide means to map and delimit regions where rainfall feedback mediated by microorganisms is suspected to occur or has occurred historically, thereby providing rational means to establish experimental set-ups for verification.

scholarly journals Influence of Daily Rainfall Characteristics on Regional Summertime Precipitation over the Southwestern United States

2009 ◽  
Vol 10 (5) ◽  
pp. 1218-1230 ◽  
Author(s):  
Bruce T. Anderson ◽  
Jingyun Wang ◽  
Suchi Gopal ◽  
Guido Salvucci
Keyword(s):  
United States ◽  
Large Scale ◽  
Daily Precipitation ◽  
Daily Rainfall ◽  
Southwestern United States ◽  
Regional Variability ◽  
Rainfall Frequency ◽  
Circulation Patterns ◽  
Precipitation Characteristics ◽  
Precipitation Anomalies

Abstract The regional variability in the summertime precipitation over the southwestern United States is studied using stochastic chain-dependent models generated from 70 yr of station-based daily precipitation observations. To begin, the spatiotemporal structure of the summertime seasonal mean precipitation over the southwestern United States is analyzed using two independent spatial cluster techniques. Four optimal clusters are identified, and their structures are robust across the techniques used. Next, regional chain-dependent models—comprising a previously dependent occurrence chain, an empirical rainfall coverage distribution, and an empirical rainfall amount distribution—are constructed over each subregime and are integrated to simulate the regional daily precipitation evolution across the summer season. Results indicate that generally less than 50% of the observed interannual variance of seasonal precipitation in a given region lies outside the regional chain-dependent models’ stochastic envelope of variability; this observed variance, which is not captured by the stochastic model, is sometimes referred to as the “potentially predictable” variance. In addition, only a small fraction of observed years (between 10% and 20% over a given subregime) contain seasonal mean precipitation anomalies that contribute to this potentially predictable variance. Further results indicate that year-to-year variations in daily rainfall coverage are the largest contributors to potentially predictable seasonal mean rainfall anomalies in most regions, whereas variations in daily rainfall frequency contribute the least. A brief analysis for one region highlights how the identification of years with potentially predictable precipitation characteristics can be used to better understand large-scale circulation patterns that modulate the underlying daily rainfall processes responsible for year-to-year variations in regional rainfall.

scholarly journals From regional climate simulations to the hydrological information needed for basin scale impact studies

2010 ◽  
Vol 26 ◽  
pp. 25-31
Author(s):  
I. Portoghese ◽  
E. Bruno ◽  
M. Vurro
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Climate Change Impacts ◽  
Stochastic Modelling ◽  
Rain Gauge ◽  
Hydrological Processes ◽  
Rainfall Regime ◽  
Basin Scale

Abstract. The accuracy of local downscaling of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes because the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows, and groundwater recharge. In this study, the output of a regional climate model (RCM) is downscaled using a stochastic modelling of the point rainfall process able to adequately reproduce the daily rainfall intermittency which is one of the crucial aspects for the hydrological processes characterizing Mediterranean environments. The historical time-series from a dense rain-gauge network were used for the analysis of the RCM bias in terms of dry and wet daily period and then to investigate the predicted alteration in the local rainfall regime. A Poisson Rectangular Pulse (PRP) model (Rodriguez-Iturbe et al., 1987) was finally adopted for the stochastic generation of local daily rainfall as a continuous-time point process with forcing parameters resulting from the bias correction of the RCM scenario.

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