Assessing the Impact of Climate Variability on Asian Rust Severity and Soybean Yields in Different Brazilian Mega-Regions

2021 ◽  
Author(s):  
I. M. Fattori ◽  
P. C. Sentelhas ◽  
F. R. Marin
Keyword(s):  
Climate Variability ◽  
Rust Severity ◽  
The Impact

scholarly journals Assessing Impact of Climate Variability in Southwest Coastal Bangladesh Using Livelihood Vulnerability Index

Climate ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 107
Author(s):  
Sabrina Mehzabin ◽  
M. Shahjahan Mondal
Keyword(s):  
Climate Variability ◽  
Linear Regression Analysis ◽  
Kendall Test ◽  
Vulnerability Index ◽  
Precipitation Anomaly ◽  
Primary Data ◽  
Precipitation Concentration Index ◽  
Coastal Bangladesh ◽  
Present Decade ◽  
The Impact

This study analyzed the variability of rainfall and temperature in southwest coastal Bangladesh and assessed the impact of such variability on local livelihood in the last two decades. The variability analysis involved the use of coefficient of variation (CV), standardized precipitation anomaly (Z), and precipitation concentration index (PCI). Linear regression analysis was conducted to assess the trends, and a Mann–Kendall test was performed to detect the significance of the trends. The impact of climate variability was assessed by using a livelihood vulnerability index (LVI), which consisted of six livelihood components with several sub-components under each component. Primary data to construct the LVIs were collected through a semi-structed questionnaire survey of 132 households in a coastal polder. The survey data were triangulated and supplemented with qualitative data from focused group discussions and key informant interviews. The results showed significant rises in temperature in southwest coastal Bangladesh. Though there were no discernable trends in annual and seasonal rainfalls, the anomalies increased in the dry season. The annual PCI and Z were found to capture the climate variability better than the currently used mean monthly standard deviation. The comparison of the LVIs of the present decade with the past indicated that the livelihood vulnerability, particularly in the water component, had increased in the coastal polder due to the increases in natural hazards and climate variability. The index-based vulnerability analysis conducted in this study can be adapted for livelihood vulnerability assessment in deltaic coastal areas of Asia and Africa.

From water to bioethanol: The impact of climate variability on the water footprint

2012 ◽  
Vol 444-445 ◽  
pp. 180-186 ◽  
Author(s):  
Anna Dalla Marta ◽  
Marco Mancini ◽  
Francesca Natali ◽  
Francesca Orlando ◽  
Simone Orlandini
Keyword(s):  
Climate Variability ◽  
Water Footprint ◽  
The Impact

South Africa’s increasing climate variability and its effect on food production

2021 ◽  
pp. 003072702110049
Author(s):  
Mashudu Tshikovhi ◽  
Roscoe Bertrum van Wyk
Keyword(s):  
South Africa ◽  
Climate Variability ◽  
Food Production ◽  
Fixed Effects ◽  
Crop Yields ◽  
Negative Impact ◽  
Secondary Data ◽  
Mean Annual Temperature ◽  
Fixed Effects Panel Regression ◽  
The Impact

This study examines the impact of increasing climate variability on food production in South Africa, focusing on maize and wheat yields. A two-way fixed effects panel regression model was used to assess the climate variability impacts, analysing secondary data for the period 2000 to 2019 for nine provinces in South Africa. The study found that increasing climate variability has a negative impact on maize and wheat production in South Africa. Specifically, the results indicated a negative correlation between mean annual temperature with both maize and wheat yields. A decrease in precipitation affected maize yields negatively, while the impact on wheat yields was positive, although insignificant. This analysis, therefore, depicted that crop yields generally increase with more annual precipitation and decrease with higher temperatures. The study recommends that funding initiatives to educate farmers on increasing climate variability and its effects on farming activities in South Africa should be prioritised.

Modeling the impact of climate variability on Black Sea anchovy recruitment and production

2014 ◽  
Vol 23 (5) ◽  
pp. 436-457 ◽  
Author(s):  
Ceren Güraslan ◽  
Bettina A. Fach ◽  
Temel Oguz
Keyword(s):  
Climate Variability ◽  
Black Sea ◽  
The Impact

scholarly journals Tree-ring-based spring precipitation reconstruction in the Sikhote-Alin' Mountain range

2021 ◽  
Vol 17 (2) ◽  
pp. 951-967
Author(s):  
Olga Ukhvatkina ◽  
Alexander Omelko ◽  
Dmitriy Kislov ◽  
Alexander Zhmerenetsky ◽  
Tatyana Epifanova ◽  
...  
Keyword(s):  
Climate Variability ◽  
Tree Ring ◽  
Southern Oscillation ◽  
Russian Far East ◽  
Pinus Koraiensis ◽  
Mountain Range ◽  
Korean Pine ◽  
Sikhote Alin ◽  
The Impact ◽  
Standard Tree

Abstract. Climate reconstructions provide important insight into past climate variability and help us to understand the large-scale climate drivers and impact of climate change. However, our knowledge about long-term year-to-year climate variability is still limited due to the lack of high-resolution reconstructions. Here, we present the first precipitation reconstructions based on tree rings from Pinus koraiensis (Korean pine) from three sites placed along a latitudinal (330 km) gradient in the Sikhote-Alin' mountains in the Russian Far East. The tree-ring width chronologies were built using standard tree-ring procedures. We reconstructed the April–June precipitation for the southern Sikhote-Alin' (SSA), March–June precipitation for the central Sikhote-Alin' (CSA) and March–July precipitation for the northwestern Sikhote-Alin' (NSA) over the years 1602 to 2013, 1804 to 2009 and 1858 to 2013, respectively. We found that an important limiting factor for Korean pine growth was precipitation within the period when the air current coming from the continent during the cold period is replaced with the impact of the wet ocean air current. We identified that common wet years for SSA, CSA and NSA occurred in 1805, 1853, 1877, 1903, 1906, 1927, 1983 and 2009 and common dry years occurred in 1821, 1869, 1919, 1949 and 2003. Our reconstructions have 3-, 15- and 60-year periods, which suggests the influence of the El Niño–Southern Oscillation and Pacific Decadal Oscillation on the region's climate and relevant processes. Despite the impact of various global processes, the main contribution to precipitation formation in the study area is still made by the Pacific Ocean, which determines their amount and periodicity.

scholarly journals Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model

2018 ◽  
Vol 10 (1) ◽  
pp. 88-100 ◽  
Author(s):  
Gbenga J. Abiodun ◽  
Peter J. Witbooi ◽  
Kazeem O. Okosun ◽  
Rajendra Maharaj
Keyword(s):  
Climate Variability ◽  
Malaria Transmission ◽  
Malaria Incidence ◽  
Principal Component ◽  
Wavelet Coherence ◽  
Human Malaria ◽  
Kwazulu Natal ◽  
The Impact ◽  
Wavelet Coherence Analysis ◽  
Malaria Model

Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

scholarly journals Climate and hydrological variability: the catchment filtering role

2015 ◽  
Vol 19 (1) ◽  
pp. 379-387 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Peak Flow ◽  
Flood Frequency ◽  
Annual Maximum ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Maximum Peak ◽  
Hydrological Variability ◽  
The Impact

Abstract. Measuring the impact of climate change on flood frequency is a complex and controversial task. Identifying hydrological changes is difficult given the factors, other than climate variability, which lead to significant variations in runoff series. The catchment filtering role is often overlooked and thus may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? This research aims to analytically derive the flood frequency distribution based on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The annual maximum peak flow probability distribution is analytically derived to quantify the filtering effect of the rainfall–runoff process on climate change. A sensitivity analysis is performed according to typical semi-arid Mediterranean climatic and hydrological conditions, assuming a simple but common scheme for the rainfall–runoff transformation in small-size ungauged catchments, i.e. the CN-SCS model. Variability in annual maximum peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that depending on changes in the annual number of rainfall events, the catchment filtering role is particularly significant, especially when the event rainfall volume distribution is not strongly skewed. Results largely depend on the return period: for large return periods, peak flow variability is significantly affected by the climatic input, while for lower return periods, infiltration processes smooth out the impact of climate change.

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