On the other hand, the trend increases for five of the six combinations that are formed to determine the piecewise trends of the annual mean temperature data, and no trend evaluation for one of them is nearly similar for the m-MK and ITA methodologies. Nonetheless, there are trend increases in nine combinations, and partial trend decreases in two charts except for the 1871–19–2020 periods, according to the ITA methodology. The m-MK methodology regarding total annual precipitation data emphasizes that there is no trend in general except for the three combinations. The experts can find a chance with the TSRC to evaluate in detail the trend magnitudes for different numerical values. The average trend magnitudes have been calculated for 50% risk level by forming the Cumulative Distribution Function (CDF) charts of the trend increase (or decrease) percentages to define the trend magnitudes over a single magnitude for the ITA methodology. The numerical evaluation of the trends obtained through the ITA graphs has been made for the first time via TSRC.
This study is mainly proposed to suggest a new approach for the trend slope (magnitude) based on the ITA with Trend Slope Risk Charts (TSRC). The piecewise trends, their magnitudes, and stabilities have been determined in the study through modified Mann–Kendall (m-MK), Sen’s slope (SS), and Innovative Trend Analysis (ITA) methodologies.
In this study, the 250-year precipitation data, and the 200-year temperature data belonging to the Radcliffe station located in Oxford city of England have been analyzed. Given the limited human adaptability to heat stress, our results advocate for mitigation strategies targeted at reducing SUHI extremes in the most vulnerable and exposed city neighbourhoods. Within many cities there are hotspots where extreme SUHI intensity is 10–15 K higher compared to relatively cooler city parts. This can be linked with increasing urbanisation, more frequent heatwaves, and greening of the earth, processes that are all expected to continue in the coming decades. Over this period, SUHI extremes have increased more rapidly than warm-season medians, and averaged worldwide are now 1.04 K or 31% higher compared to 2003. Our results show that across urban areas worldwide over the period 2003–2020, 3-day SUHI extremes are on average more than twice as high as the warm-season median SUHI, with local exceedances up to 10 K. Here we develop a global long-term high-resolution dataset of daytime SUHI, offering an insight into the space–time variability of the urban–rural temperature differences which is unprecedented at global scale. Past global studies analysed this phenomenon aggregated at city scale or over seasonal and annual time periods, while human impacts strongly depend on shorter term heat stress experienced locally. This phenomenon, known as Surface Urban Heat Island (SUHI), increases the risk of heat-related human illnesses and mortality. Surface temperatures are generally higher in cities than in rural surroundings. A positive relationship was observed between decadal trends of annual/seasonal air temperature and precipitation for all urban and peri-urban areas, with a higher rate being observed for urban areas. Overall, cities located in dry areas, for example, in Africa, southern parts of North America, and Eastern Asia, showed a decrease in annual and seasonal precipitation, while wetter conditions were favorable for cities located in wet regions such as, southeastern South America, eastern North America, and northern Europe. There were not clear trend signatures (i.e., mix of increase or decrease) when comparing urban vs peri-urban precipitation in each selected city. Additionally, about 70% of the urban areas showed higher positive air temperature trends, compared with peri-urban areas. This observation suggests that appropriate trend analysis methodology for climate studies is necessary.
Through this study, it was evident that removal of the lag-k serial correlation caused a reduction of approximately 20 to 30% in significant trend observability for temperature and precipitation data. The urban and peri-urban areas were classified based on the percentage of land imperviousness. Multiple statistical tests were used to examine long-term trends in annual and seasonal precipitation and air temperature for the selected cities. In this study, the trends in precipitation and the air temperature were investigated for urban and peri-urban areas of 18 mega cities selected from six continents (representing a wide range of climatic patterns). Urbanization plays an important role in altering local to regional climate.