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Climate extremes are becoming more prevalent and hazardous as global climate change increases. The purpose of this study was to find out how often severe rainfall and temperature events occur, as well as the study area's spatial vulnerability indexes to extremes of both indices. Thirty years of daily rainfall and temperature data from 10 national meteorological stations were used. Four rainfall and eight temperature extremes were extracted using Climpact2 software tools. These variables were calculated for standardized anomaly and vulnerability indices and mapped using ArcMap. The results showed that the spatial variation of climatic extremes in the study area was significantly varied. Avery high rainfall (R95P) and extremely high rainfall (R99P) were widely experienced in the study area's west-south, but in the southeast, similar trends were rare. R95P had a statistically significant growing trend, but R99P did not. The warmest night temperature (TNx) event was widely observed in the east, southeast, and northwest, but the coldest night temperature (TNn) was only found in the eastern part. Extremely cold daytime temperatures (TXn) were more prevalent in the south and southeast of the study area, whereas extremely warm daytime temperatures (TXx) were more prevalent in the north. The number of dry spells (CDD), R95P, R99P, cold spells at night (TN10P), warm spells at night (TN90P), cold spells during the day (TX10P), and warm spells during the day (TX10P) frequency bell curves were skewed to the left side of the histogram. This suggests that the distribution of the variables was not symmetrical due to the fact that the negative anomaly frequencies of the variables were higher than the positive ones. The results of the spatial vulnerability study show that all provinces were vulnerable to the combined effects of climatic extremes, with scores ranging from 0.20 to 0.8, with none of them vulnerable and extremely vulnerable areas. Omo-Nada and Chora-Botor were particularly sensitive to climate change with an average score of 0.61. Only 12 of the 27 severe climate indexes were taken into account in this study, and the remaining 15 extreme indices will have to be investigated further., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Our study examines the urban vegetation - air temperature (T a ) - land surface temperature (LST) nexus at micro- and regional-scales to better understand urban climate dynamics and the uncertainty in using satellite-based LST for characterizing T a . While vegetated cooling has been repeatedly linked to reductions in urban LST, the effects of vegetation on T a , the quantity often used to characterize urban heat islands and global warming, and on the interactions between LST and T a are less well characterized. To address this need we quantified summer temporal and spatial variation in T a through a network of 300 air temperature sensors in three sub-regions of greater Los Angeles, CA, which spans a coastal to desert climate gradient. Additional sensors were placed within the inland sub-region at two heights (0.1m and 2m) within three groundcover types: bare soil, irrigated grass, and underneath citrus canopy. For the entire study region, we acquired new imagery data, which allowed calculation of the normalized difference vegetation index (NDVI) and LST. At the microscale, daytime T a measured along a vertical gradient, ranged from 6 to 3°C cooler at 0.1 and 2m, underneath tall canopy compared to bare ground respectively. At the regional scale NDVI and LST were negatively correlated (p<0.001). Relationships between diel variation in T a and daytime LST at the regional scale were progressively weaker moving away from the coast and were generally limited to evening and nighttime hours. Relationships between NDVI and T a were stronger during nighttime hours, yet effectiveness of mid-day vegetated cooling increased substantially at the most arid region. The effectiveness of vegetated T a cooling increased during heat waves throughout the region. Our findings suggest an important but complex role of vegetation on LST and T a and that vegetation may provide a negative feedback to urban climate warming., (Copyright © 2016 Elsevier B.V. All rights reserved.)