Rainfall Variability and Trends over the African Continent Using TAMSAT Data (1983–2020): Towards Climate Change Resilience and Adaptation

This study reveals rainfall variability and trends in the African continent using TAMSAT data from 1983 to 2020. In the study, a Mann–Kendall (MK) test and Sen’s slope estimator were used to analyze rainfall trends and their magnitude, respectively, under monthly, seasonal, and annual timeframes as an indication of climate change using different natural and geographical contexts (i.e., sub-regions, climate zones, major river basins, and countries). The study finds that the highest annual rainfall trends were recorded in Rwanda (11.97 mm/year), the Gulf of Guinea (river basin 8.71 mm/year), the tropical rainforest climate zone (8.21 mm/year), and the Central African region (6.84 mm/year), while Mozambique (−0.437 mm/year), the subtropical northern desert (0.80 mm/year), the west coast river basin of South Africa (−0.360 mm/year), and the Northern Africa region (1.07 mm/year) show the lowest annual rainfall trends. There is a statistically significant increase in the rainfall in the countries of Africa’s northern and central regions, while there is no statistically significant change in the countries of the southern and eastern regions. In terms of climate zones, in the tropical northern desert climates, tropical northern peninsulas, and tropical grasslands, there is a significant increase in rainfall over the entire timeframe of the month, season, and year. This implies that increased rainfall will have a positive effect on the food security of the countries in those climatic zones. Since a large percentage of Africa’s agriculture is based only on rainfall (i.e., rain-fed agriculture), increasing trends in rainfall can assist climate resilience and adaptation, while declining rainfall trends can badly affect it. This information can be crucial for decision-makers concerned with effective crop planning and water resource management. The rainfall variability and trend analysis of this study provide important information to decision-makers that need to effectively mitigate drought and flood risk.

Trend Analysis of Temperature and Rainfall of Rajasthan, India

Increasing temperature and declining and erratic rainfall is one of the greatest global challenges. This study presents the trend analysis of temperature and rainfall in five divisional headquarters of Rajasthan, namely, Bikaner, Jaipur, Jodhpur, Kota, and Udaipur. The historic data of minimum and maximum temperature and rainfall for a period of 49 years from 1971 to 2019 were collected from Climate Research and Services, India Meteorological Department, Pune. Detection of trends and change in magnitude was done using the Mann–Kendall (MK) test and Sen’s slope, respectively. The results of the study indicated a significant increase in both minimum and maximum temperature over time for all the five stations. However, rainfall showed a nonsignificant increasing trend for Kota and Udaipur district, whereas Bikaner, Jaipur, and Jodhpur detected a negative trend.

Variability and time series trend analysis of temperature over 1981-2018 in semi-arid Borana zone, southern Ethiopia

BackgroundUnderstanding the climate variability at local scale could help suggest local adaptation responses to manage climate driven impacts. This paper analyzed the variability and trends of temperature over the period 1981-2018 in semi-arid Borana zone of southern Ethiopia using Mann-Kendall (MK) test and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) daily temperature data was used to study variability at temporal and spatial scales. ResultsThe results revealed that monthly temperature shows a warming trend where February was the warmest month for both maximum and minimum temperature. Seasonally, the highest maximum and minimum temperatures were observed during Bega. Minimum temperature shows a warming trend during all seasons unlike maximum temperature. Both minimum and maximum temperature shows not significant warming trend at annual timescale. The later decades (20012018) have shown a warming trend compared to a period ahead especially for minimum temperature. The southwestern and southeastern areas across the zone were warmer than any other areas in the region during the studied period. ConclusionTemperature shows variability at shorter than longer timescales. There is a pronounced warming trend for minimum than maximum temperature. Warming condition advances from the northcentral parts towards the southwestern and southeastern areas. Internal variability was observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.

Water vapor pressure trends in south and southwest Iran

Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.

Analysis of temperature variability and trends over Tripura

Attempts have been made to study the temporal variations and trends in monthly, seasonal and annual temperature over two stations - Agartala and Kailashahar in Tripura, India for the period 1969 to 2014. Analysis has been carried for four temperature indices, namely - minimum temperature (Tmin), maximum temperature (Tmax), mean temperature (Tmean) and diurnal temperature range (DTR). Non-parametric Mann-Kendall (MK) test was used to detect the trends and the magnitude of the trends were determined with Sen’s estimator of slope. The analysis of the temperature data revealed significant increasing trends in Tmin, Tmax and Tmean variables at both the stations on annual scale, while decreasing trend in DTR was significant over Agartala only. On the seasonal scale, the increasing (decreasing) trends were observed in Tmin, Tmax and Tmean (DTR) temperature indices in all the four seasons - winter, pre-monsoon, monsoon and post-monsoon except non-significant decreasing trend in Tmax in winter season over Agatala. On the monthly scale, significant rising trends in Tmin, Tmax and Tmean were observed in the most of the months and significant decreasing trend in DTR was found only in the months of January and December.

Two decades of suspect evidence for adaptive molecular evolution - Negative selection confounding positive selection signals

There is a large literature in the last two decades affirming adaptive DNA sequences evolution between species. The main lines of evidence are from i) the McDonald-Kreitman (MK) test, which compares divergence and polymorphism data, and ii) the PAML test, which analyzes multi-species divergence data. Here, we apply these two tests concurrently on the genomic data of Drosophila and Arabidopsis. To our surprise, the >100 genes identified by the two tests do not overlap beyond random expectation. Because the non-concordance could be due to low powers leading to high false-negatives, we merge every 20 - 30 genes into a "supergene". At the supergene level, the power of detection is large but the calls still do not overlap. We rule out methodological reasons for the non-concordance. In particular, extensive simulations fail to find scenarios whereby positive selection can only be detected by either MK or PAML, but not both. Since molecular evolution is governed by positive and negative selection concurrently, a fundamental assumption for estimating one (say, positive selection) is that the other is constant. However, in a broad survey of primates, birds, Drosophila and Arabidopsis, we found that negative selection rarely stays constant for long in evolution. As a consequence, the variation in negative selection is often mis-construed as signals of positive selection. In conclusion, MK, PAML or any method that examines genomic sequence evolution has to explicitly address the variation in negative selection before estimating positive selection. In a companion study, we propose a possible path forward in two stages – first, by mapping out the changes in negative selection and then using this map to estimate positive selection. For now, the large literature on positive selection between species has to await the re-assessment.

Analysis of long-term climatic changes at Hodeidah-Yemen during the period between 1984 and 2019

Yemen is one of the Arab country that is vulnerable to climate changes, and this is clear from the indicators of impact on water resources, coastal zone environments, etc. This work focuses on studying the climatic variability at Hodeidah city-Yemen during the period between 1984 and 2019. This study aimed to characterize trends in mean monthly, seasonal and annual temperature. To attain these objectives the collected data were analyzed using both parametric (linear regression) and non-parametric (Mann–Kendall, Spearman and Sen's slope estimator tests) methods to detect the trend and the magnitudes of rates of changes of temperature over time. Analysis of data indicates clear climatic fluctuations of temperature. The annual means of temperature during the period of study were varied between 26.9°C and 30.1°C. The warmest years were observed during the more recent years of the study period ( 2005 to 2018). The increasing rate of annual temperature is about + 0.075°C /year, + 0.37°C/5year, + 0.75°C/decade ,+2.53°C, over the whole period of study(1985 to 2019), + 3.7°C/50 year and increase to + 4.85°C in 2050. On a monthly timescale, there are similar magnitudes of rates of change from December to September with highest rates in October and November. The results also showed that most months and seasons have significant positive trends in temperature and (Z-α/2) values of the MK Test > 1.96 and positive value of Sen’s slope estimator indicates significant an increasing trend towards warmer years. Anomalies of temperature confirm significant increasing trends towards warmer years (2000s to 2019).

Analysing recent meteorological trends and computation of reference evapotranspiration and its effect on crop yields in semi-arid region of Haryana

Yield data of major crops and corresponding meteorological trends for the last forty-five years (1972-2016) were analysed for arid region (Hisar) of Haryana. Reference evapotranspiration (ET0) for the region was calculated based on Penman-Monteith equation. Meteorological parameters were subjected to Man-Kendall (MK) test for testing the significance and Sen’s slope estimator for estimating the magnitude of trend. Similarly, variability index was employed for computing variability in seasonal and annual weather parameters. Yield data was also subjected to MK test to estimate the annual increasing/decreasing trend over the years. During the last 45 years wind speed, sunshine hours and reference evaporation declined at a rate of 5%, 3.3% and 2% year-1 respectively while minimum temperature increased at 1.8% year-1. Average rainfall deficit of 1122 mm over evapotranspiration (ET0) was observed although it registered a declining trend owing to decline in ET0. The increasing trend in yield was found to be more in kharif season crops as compared to the same during rabi season. Cotton lint yield increased at a maximum rate (17.5% year-1) followed by pearl millet (7.8% year-1), rice (3.1% year-1) and barely (2.7% year-1) while no significant trend was observed in wheat, gram and pigeon pea yield during the study period.

Trend analysis of potential evapotranspiration at peninsular Malaysia

Potential Evapotranspiration (PET) functions as an indicator to estimate the amount of water loss to atmosphere. Over the years, global climate change eventually led to the change of PET capacity and this had affected the agricultural sector and water resource management. The objective of this study was to determine the best PET estimation method as well as to carry out the trend analysis and stationarity test of PET in Peninsular Malaysia. The Mann-Kendall (MK) test and Sen's Slope estimator were applied for the trend analysis while the Augmented Dickey-Fuller (ADF) test and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test were applied for the stationarity test. The findings showed that Pulau Langkawi and Kuantan stations exhibited increasing trend while Bayan Lepas station exhibited decreasing trend for the daily, monthly, and annual PET time series. The daily, monthly, and annual PET time series at Bayan Lepas, Ipoh, Subang and Muadzam Shah stations were found to be stationary. Overall, the PET trend was found to be higher at the coastal regions and stationary at the mountainous region.

Extreme Droughts Change in the Mekong River Basin: A Multidisciplinary Analysis Based on Satellite Data

This study evaluates droughts in the Mekong River Basin (MKB) based on a multidisciplinary method, mainly using the Standardized Precipitation Index (SPI) and Mann–Kendall (MK) test. Precipitation data corresponding to the seasonality of the regional climate were retrieved from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement from 2001 to 2020, at a monthly temporal scale and 0.1 degree spatial resolution. Drought events and their average interval, duration, and severity were determined based on Run theory. Our results revealed the most extreme drought period was in January 2014, at the time the lowest precipitation occurred. Spatial extreme drought results indicated that Zone 2 in the upstream MKB has the highest frequency of drought, with 44 events observed during 19 years, and experiences the most severe droughts, whereas Zone 24 in the downstream MKB has the most prolonged drought duration of seven months. The periods and locations of extreme drought were identified using the SPI, corresponding to historic droughts of the MKB. Furthermore, the MK test shows an increasing trend of droughts in the lower MKB and the cluster analysis identified six clusters of times series. Overall, our study provides essential findings for international and national water resource stakeholders in identifying trends of extreme drought in the MKB.