scholarly journals A Synoptic Weather-Typing Approach to Project Future Daily Rainfall and Extremes at Local Scale in Ontario, Canada

2011 ◽  
Vol 24 (14) ◽  
pp. 3667-3685 ◽  
Author(s):  
Chad Shouquan Cheng ◽  
Guilong Li ◽  
Qian Li ◽  
Heather Auld
Keyword(s):  
Daily Rainfall ◽  
Simulation Models ◽  
River Basins ◽  
Weather Type ◽  
Rainfall Simulation ◽  
Climate Data ◽  
Rainfall Events ◽  
Synoptic Weather ◽  
Weather Typing ◽  
Synoptic Weather Typing

Abstract This paper attempts to project possible changes in the frequency of daily rainfall events late in this century for four selected river basins (i.e., Grand, Humber, Rideau, and Upper Thames) in Ontario, Canada. To achieve this goal, automated synoptic weather typing as well as cumulative logit and nonlinear regression methods was employed to develop within-weather-type daily rainfall simulation models. In addition, regression-based downscaling was applied to downscale four general circulation model (GCM) simulations to three meteorological stations (i.e., London, Ottawa, and Toronto) within the river basins for all meteorological variables (except rainfall) used in the study. Using downscaled GCM hourly climate data, discriminant function analysis was employed to allocate each future day for two windows of time (2046–65, 2081–2100) into one of the weather types. Future daily rainfall and its extremes were projected by applying within-weather-type rainfall simulation models together with downscaled future GCM climate data. A verification process of model results has been built into the whole exercise (i.e., statistical downscaling, synoptic weather typing, and daily rainfall simulation modeling) to ascertain whether the methods are stable for projection of changes in frequency of future daily rainfall events. Two independent approaches were used to project changes in frequency of daily rainfall events: method I—comparing future and historical frequencies of rainfall-related weather types, and method II—applying daily rainfall simulation models with downscaled future climate information. The increases of future daily rainfall event frequencies and seasonal rainfall totals (April–November) projected by method II are usually greater than those derived by method I. The increase in frequency of future daily heavy rainfall events greater than or equal to 25 mm, derived from both methods, is likely to be greater than that of future daily rainfall events greater than or equal to 0.2 mm: 35%–50% versus 10%–25% over the period 2081–2100 derived from method II. In addition, the return values of annual maximum 3-day accumulated rainfall totals are projected to increase by 20%–50%, 30%–55%, and 25%–60% for the periods 2001–50, 2026–75, and 2051–2100, respectively. Inter-GCM and interscenario uncertainties of future rainfall projections were quantitatively assessed. The intermodel uncertainties are similar to the interscenario uncertainties, for both method I and method II. However, the uncertainties are generally much smaller than the projection of percentage increases in the frequency of future seasonal rain days and future seasonal rainfall totals. The overall mean projected percentage increases are about 2.6 times greater than overall mean intermodel and interscenario uncertainties from method I; the corresponding projected increases from method II are 2.2–3.7 times greater than overall mean uncertainties.

scholarly journals A Synoptic Weather Typing Approach to Simulate Daily Rainfall and Extremes in Ontario, Canada: Potential for Climate Change Projections

2010 ◽  
Vol 49 (5) ◽  
pp. 845-866 ◽  
Author(s):  
Chad Shouquan Cheng ◽  
Guilong Li ◽  
Qian Li ◽  
Heather Auld
Keyword(s):  
Model Development ◽  
Daily Rainfall ◽  
Simulation Models ◽  
Rainfall Simulation ◽  
Rainfall Events ◽  
Logit Regression ◽  
Synoptic Weather ◽  
Weather Typing ◽  
Synoptic Weather Typing ◽  
Cumulative Logit

Abstract An automated synoptic weather typing and stepwise cumulative logit/nonlinear regression analyses were employed to simulate the occurrence and quantity of daily rainfall events. The synoptic weather typing was developed using principal component analysis, an average linkage clustering procedure, and discriminant function analysis to identify the weather types most likely to be associated with daily rainfall events for the four selected river basins in Ontario. Within-weather-type daily rainfall simulation models comprise a two-step process: (i) cumulative logit regression to predict the occurrence of daily rainfall events, and (ii) using probability of the logit regression, a nonlinear regression procedure to simulate daily rainfall quantities. The rainfall simulation models were validated using an independent dataset, and the results showed that the models were successful at replicating the occurrence and quantity of daily rainfall events. For example, the relative operating characteristics score is greater than 0.97 for rainfall events with daily rainfall ≥10 or ≥25 mm, for both model development and validation. For evaluation of daily rainfall quantity simulation models, four correctness classifications of excellent, good, fair, and poor were defined, based on the difference between daily rainfall observations and model simulations. Across four selected river basins, the percentage of excellent and good simulations for model development ranged from 62% to 84% (of 20 individuals, 16 cases ≥ 70%, 7 cases ≥ 80%); the corresponding percentage for model validation ranged from 50% to 76% (of 20 individuals, 15 cases ≥ 60%, 6 cases ≥ 70%).

The Synoptic Climatology of Cool-Season Rainfall in the Central Wheatbelt of Western Australia

2012 ◽  
Vol 140 (1) ◽  
pp. 28-43 ◽  
Author(s):  
Michael J. Pook ◽  
James S. Risbey ◽  
Peter C. McIntosh
Keyword(s):  
Large Scale ◽  
Daily Rainfall ◽  
Growing Season ◽  
Synoptic Climatology ◽  
Rainfall Events ◽  
Synoptic Weather ◽  
Proportional Contribution ◽  
Cutoff Low ◽  
Highly Correlated

Abstract Synoptic weather systems form an important part of the physical link between remote large-scale climate drivers and regional rainfall. A synoptic climatology of daily rainfall events is developed for the Central Wheatbelt of southwestern Australia over the April–October growing season for the years 1965–2009. The climatology reveals that frontal systems contribute approximately one-half of the rainfall in the growing season while cutoff lows contribute about a third. The ratio of frontal rainfall to cutoff rainfall varies throughout the growing season. Cutoff lows contribute over 40% of rainfall in the austral autumn and spring, but this falls to about 20% in August when frontal rainfall climbs to more than 60%. The number of cutoff lows varies markedly from one growing season to another, but does not exhibit a significant long-term trend. The mean rainfall per cutoff system is also highly variable, but has gradually declined over the analysis period, particularly in the past decade. The decline in rainfall per frontal system is less significant. Cutoff low rainfall has contributed more strongly in percentage terms to the recent decline in rainfall in the Central Wheatbelt than the frontal component and accounts for more than half of the overall trend. Atmospheric blocking is highly correlated with rainfall in the region where cutoff low rainfall makes its highest proportional contribution. Hence, the decline in rain from cutoff low systems is likely to have been associated with changes in blocking and the factors controlling blocking in the region.

scholarly journals Synoptic weather typing applied to air pollution mortality among the elderly in 10 Canadian cities

2013 ◽  
Vol 126 ◽  
pp. 66-75 ◽  
Author(s):  
Jennifer K. Vanos ◽  
Sabit Cakmak ◽  
Corben Bristow ◽  
Vladislav Brion ◽  
Neil Tremblay ◽  
...  
Keyword(s):  
Air Pollution ◽  
The Elderly ◽  
Synoptic Weather ◽  
Weather Typing ◽  
Synoptic Weather Typing

scholarly journals SUPPORTING AGRICULTURAL INNOVATION IN UGANDA TO RESPOND TO CLIMATE RISK: LINKING CLIMATE CHANGE AND VARIABILITY WITH FARMER PERCEPTIONS

2011 ◽  
Vol 47 (2) ◽  
pp. 293-316 ◽  
Author(s):  
HENNY OSBAHR ◽  
PETER DORWARD ◽  
ROGER STERN ◽  
SARAH COOPER
Keyword(s):  
Climate Change ◽  
Methodological Approach ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Significant Shift ◽  
Climate Data ◽  
Rainfall Events ◽  
Agricultural Innovation ◽  
Climate Change And Variability ◽  
The Impact

SUMMARYThis paper investigates farmers’ perceptions of climate change and variability in southwest Uganda and compares them with daily rainfall and temperature measurements from the 1960s to the present, including trends in daily rainfall and temperature, seasonality, changing probability of risk and intensity of rainfall events. Statistical analyses and modelling of rainfall and temperature were performed and contrasted with qualitative data collected through a semi-structured questionnaire. The fieldwork showed that farmers perceived regional climate to have changed in the past 20 years. In particular, farmers felt that temperature had increased and seasonality and variability had changed, with the first rainy season between March and May becoming more variable. Farmers reported detailed accounts of climate characteristics during specific years, with recent droughts in the late 1990s and late 2000s confirming local perceptions that there has been a shift in climate towards more variable conditions that are less favourable to production. There is a clear signal that temperature has been increasing in the climate data and, to a lesser extent, evidence that the reliability of rains in the first season has decreased slightly. However, rainfall measurements do not show a downward trend in rainfall amount, a significant shift in the intensity of rainfall events or in the start and end of the rainy seasons. We explore why there are some differences between farmers’ perceptions and the climate data due to different associations of risk between ideal rainfall by farmers, including the amount and distribution needed for production, meteorological definitions of normal rainfall or the long-term statistical mean and its variation, and the impact of higher temperatures. The paper reflects on the methodological approach and considers the implications for communicating information about risk to users in order to support agricultural innovation.

scholarly journals Possible impacts of climate change on freezing rain in south-central Canada using downscaled future climate scenarios

2007 ◽  
Vol 7 (1) ◽  
pp. 71-87 ◽  
Author(s):  
C. S. Cheng ◽  
H. Auld ◽  
G. Li ◽  
J. Klaassen ◽  
Q. Li
Keyword(s):  
Function Analysis ◽  
Future Climate ◽  
Freezing Rain ◽  
Northern Ontario ◽  
Synoptic Weather ◽  
South Central ◽  
Weather Typing ◽  
Synoptic Weather Typing ◽  
Central Canada ◽  
Rain Events

Abstract. Freezing rain is a major atmospheric hazard in mid-latitude nations of the globe. Among all Canadian hydrometeorological hazards, freezing rain is associated with the highest damage costs per event. Using synoptic weather typing to identify the occurrence of freezing rain events, this study estimates changes in future freezing rain events under future climate scenarios for south-central Canada. Synoptic weather typing consists of principal components analysis, an average linkage clustering procedure (i.e., a hierarchical agglomerative cluster method), and discriminant function analysis (a nonhierarchical method). Meteorological data used in the analysis included hourly surface observations from 15 selected weather stations and six atmospheric levels of six-hourly National Centers for Environmental Prediction (NCEP) upper-air reanalysis weather variables for the winter months (November–April) of 1958/59–2000/01. A statistical downscaling method was used to downscale four general circulation model (GCM) scenarios to the selected weather stations. Using downscaled scenarios, discriminant function analysis was used to project the occurrence of future weather types. The within-type frequency of future freezing rain events is assumed to be directly proportional to the change in frequency of future freezing rain-related weather types The results showed that with warming temperatures in a future climate, percentage increases in the occurrence of freezing rain events in the north of the study area are likely to be greater than those in the south. By the 2050s, freezing rain events for the three colder months (December–February) could increase by about 85% (95% confidence interval – CI: ±13%), 60% (95% CI: &plusmn9%), and 40% (95% CI: ±6%) in northern Ontario, eastern Ontario (including Montreal, Quebec), and southern Ontario, respectively. The increase by the 2080s could be even greater: about 135% (95% CI: ±20%), 95% (95% CI: ±13%), and 45% (95% CI: ±9%). For the three warmer months (November, March, April), the percentage increases in future freezing rain events are projected to be much smaller with some areas showing either a decrease or little change in frequency of freezing rain. On average, northern Ontario could experience about 10% (95% CI: ±2%) and 20% (95% CI: ±4%) more freezing rain events by the 2050s and 2080s, respectively. However, future freezing rain events in southern Ontario could decrease about 10% (95% CI: ±3%) and 15% (95% CI: ±5%) by the 2050s and 2080s, respectively. In eastern Ontario (including Montreal, Quebec), the frequency of future freezing rain events is projected to remain the same as it is currently.

scholarly journals The Synoptic Decomposition of Cool-Season Rainfall in the Southeastern Australian Cropping Region

2006 ◽  
Vol 45 (8) ◽  
pp. 1156-1170 ◽  
Author(s):  
Michael J. Pook ◽  
Peter C. McIntosh ◽  
Gary A. Meyers
Keyword(s):  
Daily Rainfall ◽  
Growing Season ◽  
Seasonal Forecasts ◽  
Cool Season ◽  
Total Contribution ◽  
Rainfall Events ◽  
Southeastern Australia ◽  
Synoptic Weather ◽  
Frontal Systems ◽  
The Mean

Abstract Daily rainfall during the April–October growing season in a major cropping region of southeastern Australia has been related to particular types of synoptic weather systems over a period of 33 yr. The analysis reveals that cutoff lows were responsible for at least 50% of all growing-season rainfall and accounted for 80% of daily rainfall events exceeding 25 mm per station. The proportion of rainfall contributed by cutoff lows varies throughout the growing season. It is highest in austral autumn and spring (55% and 57%, respectively) and falls to a minimum in July (42%). By way of contrast, the total contribution of all types of frontal systems to growing-season rainfall is about 32%, although the monthly value reaches a maximum of 41% in July when mean cutoff rainfall reaches a minimum. Rainfall associated with fronts is strongly concentrated in the lower range of daily falls (less than 10 mm per station). Frontal rainfall is found to be more consistent from year to year than is cutoff rainfall. The number of cutoff lows per season is highly variable, and there is a significant correlation between the number of cutoff days and atmospheric blocking in the region south of Australia in each month of the growing season. The mean amount of rainfall per cutoff day is also variable and has declined by approximately 0.8 mm over the analysis period. An understanding of the mechanisms controlling year-to-year variability of cutoff rainfall is therefore an important step in improving seasonal forecasts for agriculture in southeastern Australia.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

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