Anomalous Extreme Rainfall Variability Over Europe ― Interaction Between Climate Variability and Climate Change

2018 ◽  
pp. 375-379 ◽  
Author(s):  
Hossein Tabari ◽  
Patrick Willems
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Rainfall Variability ◽  
Extreme Rainfall

scholarly journals Farmers’ Perceptions on Climate Variability and Adaptation Strategies to Climate Change in Cinzana, Mali

2016 ◽  
Vol 4 (3) ◽  
pp. 13 ◽  
Author(s):  
Touré Halimatou ◽  
Zampaligre Nouhoun ◽  
Traoré Kalifa ◽  
Kyei-Baffour Nicholas
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Meteorological Data ◽  
Rainfall Variability ◽  
Adaptation Strategies ◽  
Sub Saharan Africa ◽  
Farm Size ◽  
Annual Rainfall ◽  
Sub Saharan ◽  
Future Economic Development

Several studies predict that climate change will highly affect the African continent. These changes in climate and climate variability may be challenging issues for future economic development of the continent in general, and particularly in the region of sub Saharan Africa. Offering a case study of Sahelian zone of Mali in the present study aimed to understand farmers’ perceptions of climate variability and change and to evaluate adaptation options used by farmers in the Cinzana commune of Mali. One hundred and nineteen farmers were interviewed using a questionnaire designed with six sections. The result showed that all farmers interviewed were aware of climate change and climate variability. The Farmers perceived a decrease in annual rainfall variability and an increase of temperature as main factors of climate change and climate variability. The observed meteorological data, showed a decrease of precipitation distribution during the last 14 years of which was observed by farmers. Several strategies such as selling animals, use of improved crop varieties, new activities (outside agriculture) and credit were the commonly preferred adaptation strategies to deal with climate change and variability. Factors surveyed, age, gender, education, household size, farm size were found to be significantly correlated to self-reported to adaptation.

scholarly journals An Alternative to PCA for Estimating Dominant Patterns of Climate Variability, with Application to US Rainfall

2020 ◽  
Author(s):  
Stephen Jewson
Keyword(s):  
Climate Variability ◽  
Heat Waves ◽  
Rainfall Variability ◽  
Extreme Temperature ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Component Analysis ◽  
Identification Algorithm ◽  
Spatial Extremes ◽  
Preferred Direction

Floods and droughts are driven, in part, by patterns of extreme rainfall. Heat waves are driven, in part, by patterns of extreme temperature. The standard work-horse for understanding patterns of climate variability is Principal Component Analysis (PCA) and its variants. But PCA does not optimize for spatial extremes, and so there is no particular reason why the first PCA pattern should identify, or even approximate, the types of patterns that may drive these phenomena, even if the linear assumptions underlying PCA are correct. We present an alternative pattern identification algorithm that makes the same linear assumptions as PCA, but which can be used to explicitly optimize for spatial extremes. We call the method Directional Component Analysis (DCA), since it involves introducing a preferred direction, or metric, such as `sum of all points in the field'. We compare the first PCA and DCA patterns for US rainfall on a 6 month timescale, using the sum metric for the definition of DCA, and find that they are somewhat different. The definitions of PCA and DCA mean that the first PCA pattern has the larger explained variance of the two, while the first DCA pattern, when scaled appropriately, is both more likely and captures more rainfall. In combination these two patterns yield more insight into rainfall variability than either pattern on its own.

Climate Variability and Its Associated Community Losses in Gicumbi District, Northern Rwanda

2021 ◽  
Vol 4 (2) ◽  
pp. 35-45
Author(s):  
Lamek Nahayo ◽  
Lanhai Li ◽  
Christophe Mupenzi
Keyword(s):  
Climate Change ◽  
Data Analysis ◽  
Correlation Analysis ◽  
Climate Variability ◽  
Climate Change Adaptation ◽  
Rainfall Variability ◽  
Monthly Rainfall ◽  
P Value ◽  
Analysis Process ◽  
Strategic Measures

Climate change causes loss on lives and livelihoods while regular update strengthens resilience. This study aimed to analyze the rainfall variability impact on livelihoods in Northern Rwanda. The data on community losses due to rainfall variability were considered from 2013 to 2019. The GIS and SPSS helped the data analysis process. The results showed high mean monthly rainfall (119.345 and 90.05 mm) in 2013 and 2017, respectively. This caused landslide, flood, rainstorms, windstorms, lightning, and hailstorms occurrence, which killed/injured people, damaged houses and cropland, livestock loss, and destruction of infrastructures. The correlation analysis indicated a statistically significant p-value of 0.0151 lower than 0.05 and approved that rainfall variability negatively impacts livelihoods. This study can enable policymakers to better understand how changes in rainfall impact livelihoods and strategic measures to adopt for climate variability and climate change adaptation.

scholarly journals Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

2017 ◽  
Vol 31 (1) ◽  
pp. 369-385 ◽  
Author(s):  
Saman Armal ◽  
Naresh Devineni ◽  
Reza Khanbilvardi
Keyword(s):  
Climate Change ◽  
United States ◽  
Climate Variability ◽  
Surface Temperature ◽  
Multilevel Model ◽  
Extreme Rainfall ◽  
Temperature Anomalies ◽  
Global Surface Temperature ◽  
Global Surface ◽  
The U.S

AbstractThis study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1244 rainfall stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: trend can be attributed to changes in global surface temperature anomalies or to a combination of well-known cyclical climate modes with varying quasiperiodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypothesis is made based on the Watanabe–Akaike information criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the U.S. Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to El Niño–Southern Oscillation, the North Atlantic Oscillation, the Pacific decadal oscillation, and the Atlantic multidecadal oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the U.S. Northwest, West, and Southwest climate regions.

scholarly journals The double tragedy of agriculture vulnerability to climate variability in Africa: How vulnerable is smallholder agriculture to rainfall variability in Ghana?

2016 ◽  
Vol 8 (3) ◽  
Author(s):  
Emmanuel K. Derbile ◽  
Dramani J.M. File ◽  
Alfred Dongzagla
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Local Governance ◽  
Rainfall Variability ◽  
Unmet Need ◽  
Heavy Precipitation ◽  
Endogenous Development ◽  
Smallholder Agriculture ◽  
Regional Survey ◽  
Precipitation Events

This article analysed vulnerability of smallholder agriculture to climate variability, particularly the alternating incidences of drought and heavy precipitation events in Ghana. Although there is an unmet need for understanding the linkages between climate change and livelihoods, the urgent need for climate change adaptation planning (CCAP) in response to climate change makes vulnerability assessment even more compelling in development research. The data for analysis were collected from two complementary studies. These included a regional survey in the Upper West Region and an in-depth study in three selected communities in the Sissala East District. The results showed that smallholder agriculture is significantly vulnerable to climate variability in the region and that three layers of vulnerability can be identified in a ladder of vulnerability. Firstly, farmers are confronted with the double tragedy of droughts and heavy precipitation events, which adversely affect both crops and livestock. Secondly, farmers have to decide on crops for adaptation, but each option – whether indigenous crops, new early-maturing crops or genetically modified crops – predisposes farmers to a different set of risks. Finally, the overall impact is a higher-level vulnerability, namely the risk of total livelihood failure and food insecurity. The article recommended CCAP and an endogenous development (ED) approach to addressing agriculture vulnerability to climate variability within the framework of decentralisation and local governance in Ghana.Keywords: Climate variability; agriculture; vulnerability; endogenous development; Ghana

scholarly journals Extreme Floods in Small Mediterranean Catchments: Long-Term Response to Climate Variability and Change

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1008 ◽  
Author(s):  
Gerardo Benito ◽  
Yolanda Sanchez-Moya ◽  
Alicia Medialdea ◽  
Mariano Barriendos ◽  
Mikel Calle ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Catchment Area ◽  
Rainfall Variability ◽  
Climatic Variability ◽  
Maximum Flow ◽  
Annual Rainfall ◽  
Annual Maximum ◽  
Adaptation To Climate Change ◽  
Instrumental Records

Climate change implies changes in the frequency and magnitude of flood events. The influence of climate variability on flooding was evaluated by an analysis of sedimentary (palaeofloods) and documentary archives. A 500-year palaeoflood record at Montlleó River (657 km2 in catchment area), eastern Spain, revealed up to 31 palaeofloods with a range of discharges of 20–950 m3 s−1, and with at least five floods exceeding 740–950 m3 s−1. This information contrasts with the available gauged flood registers (since year 1971) with an annual maximum daily discharge of 129 m3 s−1. Our palaeoflood dataset indicates flood cluster episodes at (1) 1570–1620, (2) 1775–1795, (3) 1850–1890, and (4) 1920–1969. Flood rich periods 1 and 3 corresponded to cooler than usual (about 0.3 °C and 0.2 °C) climate oscillations, whereas 2 and 4 were characterised by higher inter-annual climatic variability (floods and droughts). This high inter-annual rainfall variability increased over the last 150 years, leading to a reduction of annual maximum flow. Flood quantiles (>50 years) calculated from palaeoflood+gauged data showed 30%–40% higher peak discharges than those using only instrumental records, whereas when increasing the catchment area (1500 km2) the discharge estimation variance decreased to ~15%. The results reflect the higher sensitivity of small catchments to changes on flood magnitude and frequency due to climate variability whereas a larger catchment buffers the response due to the limited extent of convective storms. Our findings show that extended flood records provide robust knowledge about hazardous flooding that can assist in the prioritization of low-regret actions for flood-risk adaptation to climate change.

African Climate Change: Taking the Shorter Route

2006 ◽  
Vol 87 (10) ◽  
pp. 1355-1366 ◽  
Author(s):  
Richard Washington ◽  
Mike Harrison ◽  
Declan Conway ◽  
Emily Black ◽  
Andrew Challinor ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Smallholder Farmers ◽  
Thought Experiment ◽  
Rainfall Variability ◽  
Climate Science ◽  
Limpopo Province ◽  
Interannual Rainfall Variability ◽  
Target Date ◽  
Development Goals

Numerous factors are associated with poverty and underdevelopment in Africa, including climate variability. Rainfall, and climate more generally, are implicated directly in the United Nations “Millennium Development Goals” to eradicate extreme poverty and hunger, and reduce child mortality and incidence of diseases such as malaria by the target date of 2015. But, Africa is not currently on target to meet these goals. We pose a number of questions from a climate science perspective aimed at understanding this background: Is there a common origin to factors that currently constrain climate science? Why is it that in a continent where human activity is so closely linked to interannual rainfall variability has climate science received little of the benefit that saw commercialization driving meteorology in the developed world? What might be suggested as an effective way for the continent to approach future climate variability and change? We make the case that a route to addressing the challenges of climate change in Africa rests with the improved management of climate variability. We start by discussing the constraints on climate science and how they might be overcome. We explain why the optimal management of activities directly influenced by interannual climate variability (which include the development of scientific capacity) has the potential to serve as a forerunner to engagement in the wider issue of climate change. We show this both from the perspective of the climate system and the institutions that engage with climate issues. We end with a thought experiment that tests the benefits of linking climate variability and climate change in the setting of smallholder farmers in Limpopo Province, South Africa.

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