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Copyright of Arid Land Geography is the property of Chinese Academy of Sciences, Xinjiang Institute of Ecology & Geography and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study involved an investigation of the long-term seasonal rainfall patterns in central India at the district level during the period from 1991 to 2020, including various aspects such as the spatiotemporal seasonal trend of rainfall patterns, rainfall variability, trends of rainy days with different intensities, decadal percentage deviation in long-term rainfall patterns, and decadal percentage deviation in rainfall events along with their respective intensities. The central region of India was meticulously divided into distinct subparts, namely, Gujarat, Daman and Diu, Maharashtra, Goa, Dadra and Nagar Haveli, Madhya Pradesh, Chhattisgarh, and Odisha. The experimental outcomes represented the disparities in rainfall distribution across different districts of central India with the spatial distribution of mean rainfall ranges during winter (2.08 mm over Dadra and Nagar Haveli with an average of 24.19 mm over Odisha), premonsoon (6.65 mm over Gujarat to 132.89 mm over Odisha), monsoon (845.46 mm over Gujarat to 3188.21 mm over Goa), and post-monsoon (30.35 mm over Gujarat to 213.87 mm over Goa), respectively. Almost all the districts of central India displayed an uneven pattern in the percentage deviation of seasonal rainfall in all three decades for all seasons, which indicates the seasonal rainfall variability over the last 30 years. A noticeable variation in the percentage deviation of seasonal rainfall patterns has been observed in the following districts: Rewa, Puri, Anuppur, Ahmadabad, Navsari, Chhindwara, Devbhumi Dwarka, Amreli, Panch Mahals, Kolhapur, Kandhamal, Ratnagiri, Porbandar, Bametara, and Sabar Kantha. In addition, a larger number of rainy days of various categories occurred in the monsoon season in comparison to other seasons. A higher contribution of trace rainfall events was found in the winter season. The highest contributions of very light, light rainfall, moderate, rather high, and high events were found in the monsoon season in central India. The percentage of various categories of rainfall events has decreased over the last two decades (2001–2020) in comparison to the third decade (1991–2000), according to the mean number of rainfall events in the last 30 years. This spatiotemporal analysis provides valuable insights into the rainfall trends in central India, which represent regional disparities and the potential challenges impacted by climate patterns. This study contributes to our understanding of the changing rainfall dynamics and offers crucial information for effective water resource management in the region. [ABSTRACT FROM AUTHOR]

Climate parameters can be refined for use in a heritage context to capture climate‐based deterioration processes occurring on buildings and sites. The Scheffer index, which combines temperature and rainfall components, is commonly used as a metric of wood decay risk. Understanding how the index is likely to change is important for developing effective conservation strategies for timber heritage. However, there has been limited research assessing the agreement between climate model outputs for such heritage‐based metrics. This is especially important where capturing projected rainfall is known to be problematic, such as over regions of Africa. We address the following questions: to what extent is there model agreement over continental Africa for (i) the magnitude of the Scheffer index and (ii) the direction of change of future Scheffer indices. A multi‐model ensemble (MME) approach was used utilizing 13 CMIP6 models under the SPS585 scenario. Results showed that rainfall was important in determining the magnitude of the index. In regions where rainfall systems are not well captured by climate models, such as in eastern Africa, there was a large range in projected Scheffer values. To help with the transferability of the index to regions with a tropical climate, we suggest the addition of a Scheffer threshold for a very‐high risk of deterioration. Projections of future change to the index were found to be predominantly driven by changes in temperature, rather than rainfall. While there was considerable disagreement in the simulated magnitude of the Scheffer index, there was good agreement between models over the direction of change across Equatorial Africa, where the Scheffer index is greatest. Such agreement between models suggests that heritage decision makers can utilize the direction of change projected by models when shaping future conservation plans. [ABSTRACT FROM AUTHOR]

This study involved an investigation of the long-term seasonal rainfall patterns in central India at the district level during the period from 1991 to 2020, including various aspects such as the spatiotemporal seasonal trend of rainfall patterns, rainfall variability, trends of rainy days with different intensities, decadal percentage deviation in long-term rainfall patterns, and decadal percentage deviation in rainfall events along with their respective intensities. The central region of India was meticulously divided into distinct subparts, namely, Gujarat, Daman and Diu, Maharashtra, Goa, Dadra and Nagar Haveli, Madhya Pradesh, Chhattisgarh, and Odisha. The experimental outcomes represented the disparities in rainfall distribution across different districts of central India with the spatial distribution of mean rainfall ranges during winter (2.08 mm over Dadra and Nagar Haveli with an average of 24.19 mm over Odisha), premonsoon (6.65 mm over Gujarat to 132.89 mm over Odisha), monsoon (845.46 mm over Gujarat to 3188.21 mm over Goa), and post-monsoon (30.35 mm over Gujarat to 213.87 mm over Goa), respectively. Almost all the districts of central India displayed an uneven pattern in the percentage deviation of seasonal rainfall in all three decades for all seasons, which indicates the seasonal rainfall variability over the last 30 years. A noticeable variation in the percentage deviation of seasonal rainfall patterns has been observed in the following districts: Rewa, Puri, Anuppur, Ahmadabad, Navsari, Chhindwara, Devbhumi Dwarka, Amreli, Panch Mahals, Kolhapur, Kandhamal, Ratnagiri, Porbandar, Bametara, and Sabar Kantha. In addition, a larger number of rainy days of various categories occurred in the monsoon season in comparison to other seasons. A higher contribution of trace rainfall events was found in the winter season. The highest contributions of very light, light rainfall, moderate, rather high, and high events were found in the monsoon season in central India. The percentage of various categories of rainfall events has decreased over the last two decades (2001–2020) in comparison to the third decade (1991–2000), according to the mean number of rainfall events in the last 30 years. This spatiotemporal analysis provides valuable insights into the rainfall trends in central India, which represent regional disparities and the potential challenges impacted by climate patterns. This study contributes to our understanding of the changing rainfall dynamics and offers crucial information for effective water resource management in the region.

Climate change is predicted to impact agricultural production and affect food security in poor communities of developing countries due to the likely negative impacts on rainfall characteristics. South Africa is one of the largest producers of maize crops in the Southern African Development Community (SADC) region. The majority of crop production is rainfed with precipitation received during the summer growing season. This study evaluated the impact of climate change on maize yields using trend and multiple regression analysis in northern South Africa. Exposure and vulnerability of maize farmers to the impacts of climate change were also evaluated. Rainfall characteristics showed variability of 20.35% with rain days standard deviation of 10.25 days and coefficient of variation of 18.57%. The results revealed a weak relationship between annual rainfall and rainy days, and annual rainfall and maize yields, both showed an r² and p-values of less than 0.5 and 0.005, respectively. The study found that variations in rainfall did not significantly influence variation in maize yields. Despite a clear fluctuation in yields, the results demonstrate a rising trend that can be attributed to agricultural practices such as the use of fertilisers and planting drought resistant cultivars as opposed to climate variables. The study further found that maize producers were proactively adapting to climate change, thus, reducing their vulnerability to its impacts.

As an important indicator of climate change, precipitation variability is critical to the ecological environment in arid and semi-arid mountains. This study examined the variability and trends of precipitation and rain days in the Qilian Mountains based on meteorological station data during the rainy seasons of 1960–2017 using a non-parametric method. The results revealed the following. (1) Many major precipitation events occurred during the rainy season (precipitation amount and number of rain days accounted for > 80% and > 70% of the annual total, respectively) and the proportion of precipitation increased significantly with altitude. (2) The distribution of different intensity classes of precipitation was complex in different months and at different altitudes. The distribution of rain days of different intensity classes was similar to that of precipitation. Variation of precipitation and rain days was significant (not significant) in central and eastern parts (western parts and in the Hexi Corridor on the northern slopes) of the Qilian Mountains. Regions with significant (non-significant) increasing trends for both light and moderate rain were distributed above the upper portion, i.e., 2600–3200 m (in the Hexi Corridor on the northern slopes) of the Qilian Mountains. (3) Mutations of light rain and rain days occurred before the mid-1980s above the upper portion but late in the first decade of the twenty-first century in the lower portion (2000–2600 m). Mutations of moderate rain and moderate rain days occurred earlier than for light rain and light rain days; the abrupt change points occurred later with decreasing altitude. [ABSTRACT FROM AUTHOR]

A 21-year Enhanced Vegetation Index (EVI) time-series produced from MODIS satellite images was used to study the complex phenological cycle of the drought semi-deciduous shrub Phlomis fruticosa and additionally to identify and compare phenological events between two Mediterranean sites with different microclimates. In the more xeric Araxos site, spring leaf fall starts earlier, autumn revival occurs later, and the dry period is longer, compared with the more favorable Louros site. Accordingly, the control of climatic factors on phenological events was examined and found that the Araxos site is mostly influenced by rain related events while Louros site by both rain and temperature. Spring phenological events showed significant shifts at a rate of 1–4.9 days per year in Araxos, which were positively related to trends for decreasing spring precipitation and increasing summer temperature. Furthermore, the climatic control on the inter-annual EVI fluctuation was examined through multiple linear regression and machine learning approaches. For both sites, temperature during the previous 2–3 months and rain days of the previous 3 months were identified as the main drivers of the EVI profile. Our results emphasize the importance of focusing on a single species and small-spatial-scale information in connecting vegetation responses to the climate crisis.

Copyright of Journal of Arts & Social Sciences (JASS) is the property of Sultan Qaboos University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rainfall has been widely studied in terms of distribution over space, time and trends including onset and cessation. In any regional study of agricultural production rainfall is therefore of fundamental importance. This is very useful for decision making in issues of food security and other sectors affected by rainfall. This study seeks to assess rainfall variability in some selected stations in north eastern, Nigeria. The data used for this study are monthly rainfall in terms of amount and number of rain days. The data were collected from six (6) synoptic weather stations of the Nigerian Meteorological Agency (NIMET) for a period of thirty years (1983-2012). The selected stations include - Bauchi, Gombe, Maiduguri, Potiskum, Nguru, and Yola. Rainfall variability was assessed using mean and annual rainfall, rainfall anomaly index, coefficients of variance, and regional index techniques. Results showed Nguru recorded the least in both mean annual rainfall and rain days with the values of 402.40mm and 10days over the period, while the highest mean annual rainfall and rain days were recorded in Yola. The maximum amount of annual rainfall was observed in Bauchi with a value of 1621.10mm and the maximum number of rain days was recorded in Yola with 182 days. Variability was found to be highest in Maiduguri with coefficient of variability of 28% and the least was Gombe with 15%. In rain day, the station with highest variability was Yola with 29% and Gombe with the least variability at 14%. The year 2007 had the highest mean of rainfall and coefficient of variability on the number of rain days with the value of 79 days and 70% respectively. While, the lowest mean of rainfall and coefficient of variability on the number of rain days was 1983 and 2008 respectively. There was a genuine climatic trend within this period. All stations under study are characterized by uneven distribution of annual rainfall. The regional index is negative for about 40% of the years as opposed to 60% for positive values. These results also created a window for further studies to assess the influence of rainfall on crops and the periods of occurrence of drought in the study areas. [ABSTRACT FROM AUTHOR]

In this work, rain totals from 1960-2014, obtained during the warm season (May to October) from 52 meteorological stations, over Xinjiang, China were classified as either light, moderate, or heavy rain in two sub-regions (northern and southern). Spatial and temporal trends for rain amounts and days for the three rain classes were determined. All light, moderate, and heavy rain amounts displayed increasing trends over the two sub-regions. Furthermore, heavy rain amounts contributed the most to changes in total rain amounts. Light rain days in northern Xinjiang significantly decreased, in contrast to increasing light rain days in southern Xinjiang and moderate and heavy rain days within two sub-regions. Results obtained from correlation and relative weights analyses implied that lower-tropospheric specific humidity was the main factor responsible for light rain day trends in Xinjiang. Increasing temperatures were not found to have a significant effect. [ABSTRACT FROM AUTHOR]

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March-May season using the Mann-Kendall (MK) trend test and simple linear regression (SLR) over the period 2000-2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days (SLR = 0.181; MK = 0.350) and wet days (SLR = 0.092; MK = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: SLR = 0.020; MK = 0.279 and wet days: SLR = 0.146; MK = 0.376) was slightly greater than during the seventh dekad (light rain days: SLR = 0.014; MK = 0.018 and wet days: SLR = 0.061; MK = 0.315) dekad. Seventy-four percent accounted for 2-4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third (MK = 0.363) and seventh (MK = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43-0.72). [ABSTRACT FROM AUTHOR]

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March–May season using the Mann–Kendall ( M K ) trend test and simple linear regression ( S L R ) over the period 2000–2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days ( S L R = 0.181; M K = 0.350) and wet days ( S L R = 0.092; M K = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: S L R = 0.020; M K = 0.279 and wet days: S L R = 0.146; M K = 0.376) was slightly greater than during the seventh dekad (light rain days: S L R = 0.014; M K = 0.018 and wet days: S L R = 0.061; M K = 0.315) dekad. Seventy-four percent accounted for 2–4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third ( M K = 0.363) and seventh ( M K = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43–0.72).

Climate change is predicted to impact agricultural production and affect food security in poor communities of developing countries due to the likely negative impacts on rainfall characteristics. South Africa is one of the largest producers of maize crops in the Southern African Development Community (SADC) region. The majority of crop production is rainfed with precipitation received during the summer growing season. This study evaluated the impact of climate change on maize yields using trend and multiple regression analysis in northern South Africa. Exposure and vulnerability of maize farmers to the impacts of climate change were also evaluated. Rainfall characteristics showed variability of 20.35% with rain days standard deviation of 10.25 days and coefficient of variation of 18.57%. The results revealed a weak relationship between annual rainfall and rainy days, and annual rainfall and maize yields, both showed an r ² and p -values of less than 0.5 and 0.005, respectively. The study found that variations in rainfall did not significantly influence variation in maize yields. Despite a clear fluctuation in yields, the results demonstrate a rising trend that can be attributed to agricultural practices such as the use of fertilisers and planting drought resistant cultivars as opposed to climate variables. The study further found that maize producers were proactively adapting to climate change, thus, reducing their vulnerability to its impacts., Competing Interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article., (© 2022. The Authors.)

A 21-year Enhanced Vegetation Index (EVI) time-series produced from MODIS satellite images was used to study the complex phenological cycle of the drought semi-deciduous shrub Phlomis fruticosa and additionally to identify and compare phenological events between two Mediterranean sites with different microclimates. In the more xeric Araxos site, spring leaf fall starts earlier, autumn revival occurs later, and the dry period is longer, compared with the more favorable Louros site. Accordingly, the control of climatic factors on phenological events was examined and found that the Araxos site is mostly influenced by rain related events while Louros site by both rain and temperature. Spring phenological events showed significant shifts at a rate of 1–4.9 days per year in Araxos, which were positively related to trends for decreasing spring precipitation and increasing summer temperature. Furthermore, the climatic control on the inter-annual EVI fluctuation was examined through multiple linear regression and machine learning approaches. For both sites, temperature during the previous 2–3 months and rain days of the previous 3 months were identified as the main drivers of the EVI profile. Our results emphasize the importance of focusing on a single species and small-spatial-scale information in connecting vegetation responses to the climate crisis. [ABSTRACT FROM AUTHOR]