scholarly journals The Fingerprint of Climate Change and Urbanization in South Korea

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 273 ◽  
Author(s):  
Won-Ho Nam ◽  
Guillermo Baigorria ◽  
Eun-Mi Hong ◽  
Taegon Kim ◽  
Yong-Sang Choi ◽  
...  
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Urban Areas ◽  
Temporal Trends ◽  
Weather Data ◽  
Maximum Temperature ◽  
Island Effect ◽  
Temperature Trends ◽  
Agricultural Areas ◽  
Precipitation And Temperature

Understanding long-term changes in precipitation and temperature patterns is important in the detection and characterization of climate change, as is understanding the implications of climate change when performing impact assessments. This study uses a statistically robust methodology to quantify long-, medium- and short-term changes for evaluating the degree to which climate change and urbanization have caused temporal changes in precipitation and temperature in South Korea. We sought to identify a fingerprint of changes in precipitation and temperature based on statistically significant differences at multiple-timescales. This study evaluates historical weather data during a 40-year period (1973–2012) and from 54 weather stations. Our results demonstrate that between 1993–2012, minimum and maximum temperature trends in the vicinity of urban and agricultural areas are significantly different from the two previous decades (1973–1992). The results for precipitation amounts show significant differences in urban areas. These results indicate that the climate in urbanized areas has been affected by both the heat island effect and global warming-caused climate change. The increase in the number of rainfall events in agricultural areas is highly significant, although the temporal trends for precipitation amounts showed no significant differences. Overall, the impacts of climate change and urbanization in South Korea have not been continuous over time and have been expressed locally and regionally in terms of precipitation and temperature changes.

Spatio-temporal variation of extreme indices derived from observed and reanalysis products for detection of climate change across India

2020 ◽  
Author(s):  
Sachidanand Kumar ◽  
Kironmala Chanda ◽  
Srinivas Pasupuleti
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Spatio Temporal ◽  
Precipitation And Temperature

<p><strong>Abstract</strong></p><p>This article reports the research findings in a recent study (Kumar et al., 2020) that utilizes eight indices of climate change recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) for analyzing spatio-temporal trends in extreme precipitation and temperature at the daily scale across India. Observed gridded precipitation (1971-2017) and temperature (1971-2013) datasets from India Meteorological Department (IMD) are used along with reanalysis products from Climate Prediction Centre (CPC). The trends are estimated using non-parametric Mann-Kendall (MK) test and regression analysis. The trends in ‘wet days’ (daily precipitation greater than 95<sup>th</sup> percentile) and ‘dry days’ (daily precipitation lower than 5<sup>th</sup> percentile) are examined considering the entire year (annual) as well as monsoon months only (seasonal). At the annual scale, about 13% of the grid locations indicated significant trend (either increasing or decreasing at 5% significance level) in the index R95p (rainfall contribution from extreme ‘wet days’) while 20% of the locations indicated significant trend in R5p (rainfall contribution from extreme ‘dry days’). For the seasonal analysis (June to September), the corresponding figures are nil and 21% respectively. The spatio-temporal trends in ‘warm days’ (daily maximum temperature greater than 95<sup>th</sup> percentile), ‘warm nights’ (daily minimum temperature greater than 95<sup>th</sup> percentile), ‘cold days’ (daily maximum temperature lower than 5<sup>th</sup> percentile) and ‘cold nights’ (daily minimum temperature lower than 5<sup>th</sup> percentile) are also investigated for the aforementioned period. The number of ‘warm days’ per year increased significantly at 14% of the locations, while the number of ‘cold days’, ‘warm nights’ and ‘cold nights’ per year decreased significantly at several (42%, 34% and 39%) of the locations. The extreme temperature indices are also investigated for the future using CanESM2 projected data for RCP8.5 after suitable bias correction. Most of the locations (49% to 84%) indicate significant increasing (decreasing) trend in ‘warm days’ (‘cold days’) in the three epochs, 2006-2040, 2041-2070 and 2071-2100. Moreover, most locations (60% to 81%) show an increasing trend in ‘warm nights’ and a decreasing trend in ‘cold nights’ in all the epochs. A similar investigation for the historical and future periods using CPC data as the reference indicates that the trends, on comparison with IMD observations, seem to be in agreement for temperature extremes but spatially more extensive in case of CPC precipitation extremes.</p><p><strong>Keywords: extreme precipitation and temperature, climate change indices, spatio-temporal variation, India</strong></p><p><strong>References:</strong></p><p>Kumar S., Chanda, K., Srinivas P., (2020), Spatiotemporal analysis of extreme indices derived from daily precipitation and temperature for climate change detection over India, Theoretical and Applied Climatology, Springer, In press, DOI: 10.1007/s00704-020-03088-5.</p>

scholarly journals Special Issue on Climate Migration

2021 ◽  
pp. 1-3
Author(s):  
Anda David ◽  
Frédéric Docquier
Keyword(s):  
Climate Change ◽  
Human Mobility ◽  
Economic Research ◽  
Special Issue ◽  
Low Latitude ◽  
Weather Shocks ◽  
Temperature Trends ◽  
Agricultural Areas ◽  
Slow Onset

How do weather shocks influence human mobility and poverty, and how will long-term climate change affect future migration over the course of the 21st century? These questions have gained unprecedented attention in public debates as global warming is already having severe impacts around the world, and prospects for the coming decades get worse. Low-latitude countries in general, and their agricultural areas in particular, have contributed the least to climate change but are the most adversely affected. The effect on people's voluntary and forced displacements is of major concern for both developed and developing countries. On 18 October 2019, Agence Française de Développement (AFD) and Luxembourg Institute of Socio-Economic Research (LISER) organized a workshop on Climate Migration with the aim of uncovering the mechanisms through which fast-onset variables (such as weather anomalies, storms, hurricanes, torrential rains, floods, landslides, etc.) and slow-onset variables (such as temperature trends, desertification, rising sea level, coastal erosion, etc.) influence both people's incentives to move and mobility constraints. This special issue gathers five papers prepared for this workshop, which shed light on (or predict) the effect of extreme weather shocks and long-term climate change on human mobility, and stress the implications for the development community.

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 Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

NDVI dynamics as reflected in climatic variables: spatial and temporal trends – a case study of Hungary

2019 ◽  
Vol 56 (4) ◽  
pp. 624-644 ◽  
Author(s):  
Szabó ◽  
Elemér ◽  
Kovács ◽  
Püspöki ◽  
Kertész ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Local Level ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Time Range ◽  
Climatic Data ◽  
Spatial Pattern Analysis ◽  
Short Period ◽  
Temporal Variance

Understanding climate change and revealing its future paths on a local level is a great challenge for the future. Beside the expanding sets of available climatic data, satellite images provide a valuable source of information. In our study we aimed to reveal whether satellite data are an appropriate way to identify global trends, given their shorter available time range. We used the CARPATCLIM (CC) database (1961–2010) and the MODIS NDVI images (2000–2016) and evaluated the time period covered by both (2000–2010). We performed a regression analysis between the NDVI and CC variables, and a time series analysis for the 1961–2008 and 2000–2008 periods at all data points. The results justified the belief that maximum temperature (TMAX), potential evapotranspiration and aridity all have a strong correlation with the NDVI; furthermore, the short period trend of TMAX can be described with a functional connection with its long period trend. Consequently, TMAX is an appropriate tool as an explanatory variable for NDVI spatial and temporal variance. Spatial pattern analysis revealed that with regression coefficients, macro-regions reflected topography (plains, hills and mountains), while in the case of time series regression slopes, it justified a decreasing trend from western areas (Transdanubia) to eastern ones (The Great Hungarian Plain). This is an important consideration for future agricultural and land use planning; i.e. that western areas have to allow for greater effects of climate change.

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.

scholarly journals The study of potential evapotranspiration in future periods due to climate change in west of Iran

2018 ◽  
Vol 10 (1) ◽  
pp. 161-177 ◽  
Author(s):  
Ahmad Rajabi ◽  
Zahra Babakhani
Keyword(s):  
Climate Change ◽  
Potential Evapotranspiration ◽  
Circulation Model ◽  
Weather Data ◽  
Maximum Temperature ◽  
Global Circulation Model ◽  
Content Type ◽  
Global Circulation ◽  
Change Effect ◽  
Climate Change Effect

Purpose This study aims to present the climate change effect on potential evapotranspiration (ETP) in future periods. Design/methodology/approach Daily minimum and maximum temperature, solar radiation and precipitation weather parameters have been downscaled by global circulation model (GCM) and Lars-WG outputs. Weather data have been estimated according to the Had-CM3 GCM and by A1B, A2 and B1 scenarios in three periods: 2011-2030, 2045-2046 and 2080-2099. To select the more suitable method for ETP estimation, the Hargreaves-Samani (H-S) method and the Priestly–Taylor (P-T) method have been compared with the Penman-Monteith (P-M) method. Regarding the fact that the H-S method has been in better accordance with the P-M method, ETP in future periods has been estimated by this method for different scenarios. Findings In all five stations, in all three scenarios and in all three periods, ETP will increase. The highest ETP increase will occur in the A1B scenario and then in the A1 scenario. The lowest increase will occur in the B1 scenario. In the 2020 decade, the highest ETP increase in three scenarios will occur in Khorramabad and then Hamedan. Kermanshah, Sanandaj and Ilam stations come at third to fifth place, respectively, with a close increase in amount. In the 2050 decade, ETP increase percentages in all scenarios are close to each other in all the five stations. In the 2080 decade, ETP increase percentages in all scenarios will be close to each other in four stations, namely, Kermanshah, Sanandaj, Khorramabad and Hamedan, and Ilam station will have a higher increase compared with the other four stations. Originality/value Meanwhile, the highest ETP increase will occur in hot months of the year, which are significant with regard to irrigation and water resources.

scholarly journals Impact of Climate Change on the Streamflow Modulated by Changes in Precipitation and Temperature in the North Latitude Watershed of Nepal

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 117
Author(s):  
Manisha Maharjan ◽  
Anil Aryal ◽  
Rocky Talchabhadel ◽  
Bhesh Raj Thapa
Keyword(s):  
Climate Change ◽  
Temperature Distribution ◽  
Assessment Tool ◽  
Rate Of Change ◽  
Maximum Temperature ◽  
Water Yield ◽  
Impact Of Climate Change ◽  
Northern Latitudes ◽  
The Impact ◽  
Precipitation And Temperature

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between −7% and +7%, and the minimum temperature rises from +0.7% to +5% in intermediate- and high-emission scenarios. In contrast, the streamflow in the basin varies from −40% to +85%. Thus, there is a significant trend in the temperature increase and precipitation reduction in the basin. Further, the relationship between precipitation and temperature with streamflow shows a substantial dependency between them. The variability in precipitation and streamflow is successfully represented by the water yield in the basin, which plays an important role in the sustainability of the water-related projects in the basin and downstream to it. This also helps quantify the amount of water available for hydropower generation, agricultural production, and the water ecosystem in the TBRB.

scholarly journals Neonates in Ahmedabad, India, during the 2010 Heat Wave: A Climate Change Adaptation Study

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Khyati Kakkad ◽  
Michelle L. Barzaga ◽  
Sylvan Wallenstein ◽  
Gulrez Shah Azhar ◽  
Perry E. Sheffield
Keyword(s):  
Climate Change ◽  
Heat Wave ◽  
Climate Change Adaptation ◽  
Vulnerable Populations ◽  
Urban Areas ◽  
Neonatal Morbidity ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Maternity Ward

Health effects from climate change are an international concern with urban areas at particular risk due to urban heat island effects. The burden of disease on vulnerable populations in non-climate-controlled settings has not been well studied. This study compared neonatal morbidity in a non-air-conditioned hospital during the 2010 heat wave in Ahmedabad to morbidity in the prior and subsequent years. The outcome of interest was neonatal intensive care unit (NICU) admissions for heat. During the months of April, May, and June of 2010, 24 NICU admissions were for heat versus 8 and 4 in 2009 and 2011, respectively. Both the effect of moving the maternity ward and the effect of high temperatures were statistically significant, controlling for each other. Above 42 degrees Celsius, each daily maximum temperature increase of a degree was associated with 43% increase in heat-related admissions (95% CI 9.2–88%). Lower floor location of the maternity ward within hospital which occurred after the 2010 heat wave showed a protective effect. These findings demonstrate the importance of simple surveillance measures in motivating a hospital policy change for climate change adaptation—here relocating one ward—and the potential increasing health burden of heat in non-climate-controlled institutions on vulnerable populations.

scholarly journals Impact Assessment of Climate Change on Paddy Yield: A Case Study of Nepal Agriculture Research Council (NARC), Tarahara, Nepal

1970 ◽  
Vol 8 (3) ◽  
pp. 147-167 ◽  
Author(s):  
Yam K Rai ◽  
Bhakta B Ale ◽  
Jawed Alam
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Research Council ◽  
Crop Yields ◽  
Rice Yield ◽  
Weather Data ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Impact

Climate change and global warming are burning issues, which significantly threat agriculture and global food security. Change in solar radiation, temperature and precipitation will influence the change in crop yields and hence economy of agriculture. It is possible to understand the phenomenon of climate change on crop production and to develop adaptation strategies for sustainability in food production, using a suitable crop simulation model. CERES-Rice model of DSSAT v4.0 was used to simulate the rice yield of the region under climate change scenarios using the historical weather data at Nepal Agriculture Research Council (NARC) Tarahara (1989-2008). The Crop Model was calibrated using the experimental crop data, climate data and soil data for two years (2000-2001) and was validated by using the data of the year 2002 at NARC Tarahara. In this study various scenarios were undertaken to analyze the rice yield. The change in values of weather parameters due to climate change and its effects on the rice yield were studied. It was observed that increase in maximum temperature up to 2°C and 1°C in minimum temperature have positive impact on rice yield but beyond that temperature it was observed negative impact in both cases of paddy production in ambient temperature. Similarly, it was observed that increased in mean temperature, have negative impacts on rice yield. The impact of solar radiation in rice yield was observed positive during the time of study period. Adjustments were made in the fertilizer rate, plant density per square meter, planting date and application of water rate to investigate suitable agronomic options for adaptation under the future climate change scenarios. Highest yield was obtained when the water application was increased up to 3 mm depth and nitrogen application rate was 140 kg/ha respectively. DOI: http://dx.doi.org/10.3126/jie.v8i3.5941 JIE 2011; 8(3): 147-167

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