scholarly journals Observational evidence of climate change on extreme events over East Africa

2013 ◽  
Vol 2 (1) ◽  
pp. 2 ◽  
Author(s):  
Joshua Ngaina ◽  
Bethwel Mutai
Keyword(s):  
Climate Change ◽  
East Africa ◽  
Extreme Values ◽  
Southern Oscillation ◽  
Kendall Test ◽  
Significant Rise ◽  
Maximum Temperature ◽  
Sunspot Activity ◽  
Temperature Extremes ◽  
Time Pattern

Examination of trend patterns of rainfall and temperature extremes over East Africa (EA) was based on graphical, regression and Mann-Kendall test approaches, while perturbations of rainfall, sunspot activity (SA) and southern oscillation index (SOI) extremes were computed using moving average methods. Annual total rainfall generally decreased with heavy and extreme precipitation rates confined within short spells during wet days. Observed maximum temperature extremes increased while minimum temperature extremes decreased with a statistically significant rise in the number of hot days and warm nights and a decrease in number of cool days and cold nights. However, space-time pattern of observed changes were not well organized. Perturbations of rainfall, SA and SOI indicated that extreme values were changing with increasing frequency and magnitude. Similarities in observed rainfall over EA illustrated the existence of homogeneous zones of climate change clustered as either coastal (with SA dominant), lake Victoria (unique to both SA and SOI), dry continental (SOI) or wet continental areas (both SA and SOI dominant).

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

<p>In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981–2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.</p><p><strong>Keywords:</strong> climate change, temperature, extreme events, attribution, CMIP6</p><p> </p><p><strong>Acknowledgement:</strong> This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)</p>

scholarly journals Temperature trends in Fiji: a clear signal of climate change

2013 ◽  
Vol 31 (1) ◽  
pp. 27 ◽  
Author(s):  
Ravind Kumar ◽  
Mark Stephens ◽  
Tony Weir
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Pacific Islands ◽  
Extreme Values ◽  
Maximum Temperature ◽  
Temperature Trends ◽  
Clear Signal ◽  
Rate Of Increase ◽  
Significant Difference ◽  
Using Data

This paper analyses trends in temperature in Fiji, using data from more stations (10) and longer periods (52-78 years) than previous studies. All the stations analysed show a statistically significant trend in both maximum and minimum temperature, with increases ranging from 0.08 to 0.23°C per decade. More recent temperatures show a higher rate of increase, particularly in maximum temperature (0.18 to 0.69°C per decade from 1989 to 2008). This clear signal of climate change is consistent with that found in previous studies of temperatures in Fiji and other Pacific Islands. Trends in extreme values show an even stronger signal of climate change than that for mean temperatures. Our preliminary analysis of daily maxima at 6 stations indicates that for 4 of them (Suva, Labasa, Vunisea and Rotuma) there has been a tripling in the number of days per year with temperature >32°C between 1970 and 2008. The correlations between annual mean maximum (minimum) temperature and year are mostly strong: for about half the stations the correlation coefficient exceeds 60% over 50+ years. Trends do not vary systematically with location of station. At all 7 stations for which both trends are available there is no statistically significant difference between the trends in maximum and minimum temperatures.

Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary

2020 ◽  
Author(s):  
Csenge Dian ◽  
Attila Talamon ◽  
Rita Pongrácz ◽  
Judit Bartholy
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Energy Consumption ◽  
Extreme Values ◽  
Building Design ◽  
Temperature Time Series ◽  
Maximum Temperature ◽  
Design Parameters ◽  
Daily Average ◽  
Temperature Time

<p>Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people’s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, Pécs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).</p>

scholarly journals Comparing precipitation and temperature trends between inland and coastal locations

2019 ◽  
Vol 60 ◽  
pp. C109-C126 ◽  
Author(s):  
Joshua Hartigan ◽  
Shev MacNamara ◽  
Lance M Leslie
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Maximum Temperature ◽  
P Value ◽  
Wet Season ◽  
Intergovernmental Panel ◽  
The Past ◽  
The Mean

Motivated by the Millennium Drought and the current drought over much of southern and eastern Australia, this detailed statistical study compares trends in annual wet season precipitation and temperature between a coastal site (Newcastle) and an inland site (Scone). Bootstrap permutation tests reveal Scone precipitation has decreased significantly over the past 40 years (p-value=0.070) whereas Newcastle has recorded little to no change (p-value=0.800). Mean maximum and minimum temperatures for Newcastle have increased over the past 40 years (p-values of 0.002 and 0.015, respectively) while the mean maximum temperature for Scone has increased (p-value = 0.058) and the mean minimum temperature has remained stable. This suggests mean temperatures during the wet season for both locations are increasing. Considering these trends along with those for precipitation, water resources in the Hunter region will be increasingly strained as a result of increased evaporation with either similar or less precipitation falling in the region. Wavelet analysis reveals that both sites have similar power spectra for precipitation and mean maximum temperature with a statistically significant signal in the two to seven year period, typically indicative of the El-Nino Southern Oscillation climate driver. The El-Nino Southern Oscillation also drives the Newcastle mean minimum temperature, whereas the Scone power spectra has no indication of a definitive driver for mean minimum temperature. References R. A., R. L. Kitching, F. Chiew, L. Hughes, P. C. D. Newton, S. S. Schuster, A. Tait, and P. Whetton. Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution of Working Group II to the Fifth Assessment of the Intergovernmental Panel on Climate Change. Technical report, Intergovernmental Panel on Climate Change, 2014. URL https://www.ipcc.ch/report/ar5/wg2/. Bureau of Meteorology. Climate Glossary-Drought. URL http://www.bom.gov.au/climate/glossary/drought.shtml. K. M. Lau and H. Weng. Climate signal detection using wavelet transform: How to make a time series sing. B. Am. Meteorol. Soc., 76:23912402, 1995. doi:10.1175/1520-0477(1995)0762391:CSDUWT>2.0.CO;2. M. B. Richman and L. M. Leslie. Uniqueness and causes of the California drought. Procedia Comput. Sci., 61:428435, 2015. doi:10.1016/j.procs.2015.09.181. M. B. Richman and L. M. Leslie. The 20152017 Cape Town drought: Attribution and prediction using machine learning. Procedia Comput. Sci., 140:248257, 2018. doi:10.1016/j.procs.2018.10.323.

scholarly journals Effect of climate change and deforestation on vector borne diseases in the North-Eastern Indian state of Mizoram bordering Myanmar

2020 ◽  
Author(s):  
Balasubramani Karuppusamy ◽  
Devojit Kumar Sarma ◽  
Pachuau Lalmalsawma ◽  
Lalfakzuala Pautu ◽  
Krishanpal Karmodiya ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Forest Cover ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Monsoon Period ◽  
Vector Borne Diseases ◽  
Sen’S Slope ◽  
Mann Kendall Test ◽  
Vector Borne

Abstract Background Malaria and dengue are the two major vector-borne diseases in Mizoram. Malaria is endemic in Mizoram, and dengue was first reported only in 2012. It is well documented that climate change has a direct influence on the incidence and spread of vector-borne diseases. The study was designed to study the trends and impact of climate variables (temperature, rainfall and humidity) in the monsoon period (May to September) and deforestation on the incidence of dengue and malaria in Mizoram. Methods Temperature, rainfall and humidity data of Mizoram from 1979–2013 were obtained from the National Centers for Environmental Prediction Climate Forecast System Reanalysis and analyzed. Forest cover data of Mizoram was extracted from India State of Forest Report (IFSR) and Land Processes Distributed Active Archive Centre. Percent tree cover datasets of Advanced Very High Resolution Radiometer and Moderate Resolution Imaging Spectroradiometer missions were also used to study the association between deforestation and incidence of vector-borne diseases. The study used non-parametric tests to estimate long-term trends in the climate (temperature, rainfall, humidity) and forest cover variables. The trend and its magnitude are estimated through Mann-Kendall test and Sen's slope method. Year-wise dengue and malaria data were obtained from the State Vector Borne Disease Control Program, Mizoram. Results The Mann-Kendall test indicates that compared to maximum temperature, minimum temperature during the monsoon period is increasing (p < 0.001). The Sen’s slope estimation also shows an average annual 0.020C (0.01–0.03 at 95% CI) monotonic increasing trend of minimum temperature. The residuals of Sen’s estimate show that temperature is increasing at an average of about 0.10C/year after 2007.Trends indicate that both rainfall and humidity are increasing (p <. 0.001); on an average, there is a 20.45 mm increase in monsoon rainfall per year (5.90–34.37 at 95% CI), while there is a 0.08% (0.02–0.18 at 95% CI) increase in relative humidity annually. IFSR data shows that there is an annual average decrease of 162 sq.km (272.81–37.53 at 95% CI, p < 0.001) in the dense forest cover. Mizoram in 2012 was the last state in India to report the incidence of dengue. Malaria transmission continues to be stable in Mizoram; compared to 2007, the cases have increased in 2019. Conclusion Over the study period, there is an ~ 0.80C rise in the minimum temperature in the monsoon season which could have facilitated the establishment of Aedes aegypti, the major dengue vector in Mizoram. In addition, the increase in rainfall and humidity may have also helped the biology of Ae. aegypti. Deforestation could be one of the major factors responsible for the consistently high number of malaria cases in Mizoram.

scholarly journals Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-iMfolozi Park, South Africa: Impact of Recent Intense Drought

2018 ◽  
Author(s):  
Nkanyiso Mbatha ◽  
Sifiso Xulu
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Southern Oscillation ◽  
Kendall Test ◽  
Google Earth ◽  
Maximum Temperature ◽  
Sudden Increase ◽  
Area Index ◽  
Enhanced Vegetation Index ◽  
Temperature And Precipitation

The variability of meteorological parameters such as temperature and precipitation, and climatic conditions such as intense droughts, are known to impact vegetation health over southern Africa. Thus, understanding large-scale ocean&ndash;atmospheric phenomena like the El Ni&ntilde;o/Southern Oscillation (ENSO) and Indian Ocean Dipole/Dipole Mode Index (DMI) is important as these factors drive the variability of temperature and precipitation. In this study, 16 years (2002&ndash;2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform in order to analyze the response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP), during the study period. The MODIS-enhanced vegetation index and burned area index were also analyzed for this period. The area-averaged Modern Retrospective Analysis for Research Application (MERRA) model maximum temperature and precipitation were also extracted using the JavaScript code editor in the GEE platform. This procedure demonstrated a strong reversal of both the NDVI and Enhanced Vegetation Index (EVI), leading to signs of a sudden increase of burned areas (strong BAI) during the strongest El Ni&ntilde;o period. Both the Theilsen method and the Mann&ndash;Kendall test showed no significant greening or browning trends over the whole time series, although the annual Mann&ndash;Kendall test, in 2003 and 2014&ndash;2015, indicated significant browning trends due to the most recent strongest El Ni&ntilde;o. Moreover, a multi-linear regression model seems to indicate a significant influence of both ENSO activity and precipitation. Our results indicate that the recent 2014&ndash;2016 drought altered the vegetation condition in the HiP. We conclude that it is vital to exploit freely available GEE resources to develop drought monitoring vegetation systems, and to integrate climate information for analyzing its influence on protected areas, especially in data-poor counties.

scholarly journals Analysis of Anomalies and Trends of Climate Change Indices in Zacatecas, Mexico

Climate ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 55
Author(s):  
Oscar Pita-Díaz ◽  
David Ortega-Gaucin
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Agricultural Sector ◽  
Negative Impact ◽  
Southern Oscillation ◽  
Low Frequency ◽  
Climate Scenario ◽  
Data Availability ◽  
Sufficient Evidence ◽  
Maximum Temperature

Sufficient evidence is currently available to demonstrate the reality of the warming of our planet’s climate system. Global warming has different effects on climate at the regional and local levels. The detection of changes in extreme events using instrumental data provides further evidence of such warming and allows for the characterization of its local manifestations. The present study analyzes changes in temperature and precipitation extremes in the Mexican state of Zacatecas using climate change indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). We studied a 40-year period (1976–2015) using annual and seasonal time series. Maximum and minimum temperature data were used, as well as precipitation statistics from the Mexican climatology database (CLICOM) provided by the Mexican Meteorological Service. Weather stations with at least 80% of data availability for the selected study period were selected; these databases were subjected to quality control, homogenization, and data filling using Climatol, which runs in the R programming language. These homogenized series were used to obtain daily grids of the three variables at a resolution of 1.3 km. Results reveal important changes in temperature-related indices, such as the increase in maximum temperature and the decrease in minimum temperature. Irregular variability was observed in the case of precipitation, which could be associated with low-frequency oscillations such as the Pacific Decadal Oscillation and the El Niño–Southern Oscillation. The possible impact of these changes in temperature and the increased irregularity of precipitation could have a negative impact on the agricultural sector, especially given that the state of Zacatecas is the largest national bean producer. The most important problems in the short term will be related to the difficulty of adapting to these rapid changes and the new climate scenario, which will pose new challenges in the future.

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