Climate Trend Analysis Research Articles

Почвенный покров заповедников и национальных парков как отражение зонально-региональных особенностей территории Pоссии

The representation of the diversity of the main natural complexes of Russia in federal specially protected natural areas (SPNA) was assessed based on a comparison of their soil cover with the soil cover of territorial units of the Map of soil-ecological zoning of the Russian Federation (2019). A high representativeness in relation to the soil cover of the SPNA systems of the polar belt and a satisfactory one of the boreal belt was revealed. Moving southward, the representation of the diversity of natural complexes in the protected areas decreases markedly, taking the minimum values in the steppe and dry-steppe regions. In mountain protected areas the soil cover reflects the diversity of natural conditions of mountain soil provinces well and average, in most cases the soil cover of high mountains is well represented and significantly worse—of low mountains and the most fertile soils of the corresponding mountain provinces (soddy-calcareous, mountain chernozem-like, meadow-steppe). In spite of relative prosperity noted in the analysis at the level of soil zones (subzones), consideration at the level of plain soil provinces allowed revealing unfavorable regions in this respect. Six of the 14 plain soil provinces without SPNA are located in Western Siberia, where the flat relief, which determines the well-defined zonality of landscapes, allowed to trace the climatic trends of recent decades. This region has been chosen as a model to assess the need for additional SPNA due to climate change. Analysis of climatic trends in recent decades has revealed climatic changes most pronounced in the extreme climatic regions: the northern and southern flat soil zones (subzones). Moreover, in the coldest northern part of the region there is a maximum increase in air temperature, and in the arid southern part there is a maximum decrease in air humidity. The implementation of plans to create four new nature reserves in the south of Western Siberia will significantly increase the representativeness of the network of SPNA in relation to the soil cover and will optimize the state system of reference objects of background environmental monitoring.

Refractivity and Refractivity Gradient Estimation From Radar Phase Data: A Least Squares Based Approach

Tropospheric refractivity, related to temperature, pressure and humidity is an interesting parameter for weather analysis, prediction and study of climate trends. It has been shown to be useful for the detection and forecast of convective events. It has already been demonstrated that tropospheric refractivity can be estimated from radar phase measurements. In this paper a non-linear least squares based approach for the estimation of the tropospheric refractivity that simultaneously provides estimates of the refractivity vertical gradient is presented. A significant improvement of the presented technique is that it allows estimation of the refractivity over any terrain orography, flat or hilly. Furthermore, the method developed can be implemented on klystron as well as on magnetron based radars. Results for both radar types, at S- and C-band, located over flat and hilly terrain show the potential of the method.

A CHELSA-based analysis of climate change characteristics and trends in South and Southeast Asia (SSEA) during 1980-2018

A CHELSA-based analysis of climate change characteristics and trends in South and Southeast Asia (SSEA) during 1980-2018

Analysis of Climate Variability and Trends in The Context of Climate Changes: Case Study in Terengganu

Uncertainty of climate extreme nowadays causes an alteration in the local climate trend and variability. Terengganu, Malaysia recorded series of extreme drought and flood events throughout a year affected by North-East monsoonwhich will change the next climate pattern. Thus, itwill be affectingthe long-term planning and sustainability that related to the water resources in the long-term. The objective of this study was to analyse the trend changes of rainfall and temperature at Kuala Terengganu, Malaysia due to climate changes impact. The trends changes were analysed usingMan-Kendall and Sen’s Slope. The climate projection result shows the annual mean temperature is expected to have decreasing trend until end of century. However,Mar to June are expected to bit higher than historical reach to 29oCby RCP8.5. Then it will be dropped to 24oC (-5% from historical) during Northeast monsoon. Consistent to the annual rainfall, it was expected to have increasingtrendover time. The highest increasing trendwas expected to occur on Nov toDec more than40% by RCP8.5.

Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam

Understanding the effects of global change and human activities on water supplies depends greatly on surface water dynamics. A comprehensive examination of the hydroclimatic variations at the transboundary level is essential for the development of any adaptation or mitigation plans to deal with the negative effects of climate change. This research paper examines the hydroclimatic factors that contribute to the desiccation of the Doosti Dam’s basin in the transboundary area using multisensor satellite data from the Google Earth Engine (GEE) platform. The Mann–Kendall and Sens slope estimator test was applied to the satellite datasets to analyse the spatial and temporal variation of the hydroclimate variables and their trend over the transboundary area for 18 years from 2004 to 2021 (as the dam began operating in 2005). Statistical analysis results showed decreasing trends in temperature and an increase in rainfall with respect to station-observed available data. Evapotranspiration and irrigated area development followed the increasing pattern and a slight decrease in snow cover. The results confirmed a large expansion of the irrigated area, especially during the winter growing season. The increase in irrigated cultivated areas during both winter and summer seasons is possibly the main reason for the diversion of water to meet the irrigation requirements of the developed agriculture areas. The approach followed in this study could be applied to any location around the globe to evaluate the hydrological conditions and spatiotemporal changes in response to climate change, trend analysis and human activities.

Climate change simulation and trend analysis of extreme precipitation and floods in the mesoscale Rur catchment in western Germany until 2099 using Statistical Downscaling Model (SDSM) and the Soil & Water Assessment Tool (SWAT model).

Due to climate change and global warming, speed and intensity of the hydrological cycle will accelerate. In order to carry out regional risk assessment, integrated water resources management and flood protection, far reaching predictions and future scenarios of climate change effects on extreme precipitation and flooding are of particular relevance. In this study, trends in frequencies of extreme precipitation and floods until 2099 are analysed for the German Rur catchment, which is half located in highlands and half in lowlands and therefore has a high topographical and climatological contrast. To predict future trends, coupled modeling is performed based on NCEP reanalysis data and a General Circulation Model (GCM). Assuming HadCM3 future emission scenarios A2a and B2a, an empirical Statistical Downscaling Model (SDSM) is developed and daily precipitation amounts are projected until 2099 by a stochastic weather generator. The generated precipitation data are used as an input for the ecohydrological Soil & Water Assessment Tool (SWAT model) to simulate daily water discharge until 2099. Statistical trend analyses are implemented based on three annual extreme precipitation indices (EPIs) and the magnitudes of ten flood return periods derived with GEV and Gumbel extreme value distributions for 109 30-year moving periods using regression analyses and Mann-Kendall tendency tests to check for significant trends in the frequencies until 2099. As a result, it could be demonstrated for all EPIs that the frequency of extreme precipitation in the upper Rur catchment will significantly increase by +33% to +51% until 2099 compared to the base period 1961-1990, whereas mostly non-significant negative trends of extreme precipitation can be projected in the lowlands. For runoff, it was found that the magnitudes of the ten flood return periods will significantly increase by +31% for B2a to +36% for A2a until 2099 compared to the base period.

Perceived Climate Change and Determinants of Adaptation Responses by Smallholder Farmers in Central Ethiopia

Climate change is a global phenomenon but disproportionately affects smallholder farmers, prompting them to use various coping and adaptation strategies to counter the problem. This study aimed to examine the trends of climate parameters, assess farmers’ perception of climate change, and identify the strategies of adaptation measures in central Ethiopia. Climate data were obtained from the National Meteorological Agency. Survey data were collected from 120 randomly selected households in 2017 and complemented with focus group discussions. The Mann–Kendall approach was used to detect climate trends, while a rainfall anomaly was calculated using the rainfall anomaly index. Multinomial logit model was used to examine determinants of farmers’ adaptation to the perceived change. In most of the cases, farmers’ perceptions were in accordance with climate trend analyses. Farmers used crop diversification, adjustments of planting dates, destocking of livestock, seasonal migration, crop rotation, and climate information services to adapt to climate-related shocks. Empirical results showed that the age and education of the household heads, family size, access to extension services, and farm and nonfarm incomes had a significant association with the adaptation practices farmers took. The existence of strong correlations between the demographic, socio-institutional variables, and the choice of adaptation strategies suggests the need to strengthen local institutions to enhance the adaptation of smallholder farmers to climate change.

Combining stakeholder perception and ecological approaches for assessing vulnerability of floodplain wetlands in changing climate: a regional study.

Wetland fisheries are most vulnerable to climate and anthropogenic change, and therefore, vulnerability assessment is essential for the formulation of prudent management strategies. In the present study, vulnerability assessment was carried out in nine floodplain wetlands from three districts of West Bengal using stakeholder perception and ecological conditions. In absence of long-term time series data on ecology and fisheries of wetlands, stakeholder perception study was carried out to assess the vulnerability status to climate change. Phased interviews were conducted using structured questionnaires to study the stakeholder perception on climatic variability and changes in ecology and fisheries of wetlands over the past 15years. Climate data used for climate trend analysis was procured from Indian Meteorological Department. Ecological parameters were studied from the wetlands seasonally from January 2018 to December 2018. Analysis of climatic variables for last three decades revealed a warming trend and decreasing rainfall in the study area. The temperature anomaly ranged from + 0.07 to + 0.31°C while rainfall anomaly ranged from - 61.41 to - 372.62mm. Respondents showed high level of consensus (75.3%) on climate change awareness. The respondents were aware of the fact that climate anomaly affects ecology and fisheries of wetlands in most of the cases with consensus ranging from 67.8 to 94.7%. The studied wetlands showed 2 to 81.28% reduction in depth, 21.52-61.29% reduction in species diversity, and 30-95% macrophyte infestation. The stakeholder perception-based vulnerability scores ranged from 18 to 31 and indicated 6 out of 9 wetlands (66.6%) as highly vulnerable and the rest as moderately vulnerable. The ecological vulnerability scores ranged from 17 to 21 and indicated 5 out of 9 wetlands (55.6%) as highly vulnerable and 4 wetlands in the moderately vulnerable range. Although both the approaches used in the present study categorized the studied wetlands as moderately to highly vulnerable, the category of some of the wetlands varied in both the approaches. This suggests that utilizing a single approach may not give precise vulnerability status of an ecosystem. Use of combined approaches for construction of a composite vulnerability index covering different aspects impacted by climate change might present a better picture of the vulnerability status and aid in formulation of effective mitigation/management plan.

Climate variability trend and extreme indices for the Thanjavur Delta region of Tamil Nadu in South India

The Thanjavur delta region of Tamil Nadu vastly depends on agriculture. The current trend of agricultural production has been significantly affected due to changes in climatic condition. The observed parameters have been acquired from IMD (Indian Meteorological Department.) for the period 1971-2014 and CCAFS (Climate Change, Agricultural and Food Security) over the period 2015–2050 for climate trend and extremities analysis. This study indicated that observed maximum temperature (TMax) has significantly increased about 0.8 ºC, 1.5 ºC and 0.9 ºC in ARP, NPT and IMD grid respectively over the period 1971-2014. Besides that, minimum temperature (TMin) has shown an insignificant trend in ARP and NPT and a significant trend in the IMD grid (0.5 ºC) respectively. Moreover, the observed rainfall showed an insignificant trend in ARP (-3.8%), NPT (-11.1%) and IMD grid (+22.5%). The projected TMax & TMin showed a significant increasing trend ofabout1.05 °C and 1.1°C respectively and the rainfall projected to decrease insignificantly at 21% over the period 2015 to 2050. In the extreme analysis of the delta region, temperature indices showed a significant increasing trend in both the observed and future. The rainfall indices showed a larger variation in the observed and future period. The outcome of the study would be useful in framing the climate change adaptation strategies for agriculture and water sectors for the Thanjavur delta region.

Climate trend analysis for a semi-arid Borana zone in southern Ethiopia during 1981\u20132018

BackgroundUnderstanding the climate variability at local scale could help suggest local adaptation responses to manage climate associated risks. This paper analyzed the variability and trend of climate in semi-arid Borana zone of southern Ethiopia over the period 1981–2018 using Mann–Kendall (MK) test, Sen’s Slope Estimator (SEE) and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) climate data (daily precipitation, daily maximum temperature (Tmax) and minimum temperature (Tmin)) were collected from National Meteorology Agency (NMA) of Ethiopia.ResultsThe results revealed the study area received a mean monthly precipitation of 39.19 mm and a monthly mean Tmax and Tmin of 29.66 °C and 16.31 °C were observed respectively. Rainfall shows a significant increasing trend during August, October and November and extremely variable during December, January and February where CV > 100%. Tmax shows a significant warming trend during August but January, February, August and October exhibited similar trend for Tmin. Rainfall and Tmin shows a significant trend during Meher and no trend for the rest of the seasons. Mean annual rainfall shows a significant increase where no trend observed for both Tmax and Tmin at this timescale. Decadal rainfall and Tmin exhibited no trend but Tmax show significant warming trend during 2001–2010 decade. Better rainfall and cooler temperature were observed in the north central, northeastern and northwestern whereas the southeastern and southwestern regions were drier and warmer.ConclusionRainfall is highly variable than temperature both at temporal and spatial scales in Borana. The intensity of rainfall decreases from the northeastern and northwestern parts towards the southwest while temperature increased from the north central parts towards the southwest for Tmax and the southeast for Tmin. The effect of topography is substantial for the local scale variability observed in the study area. Internal variability is observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.

Spatio-temporal assessment of agro[sbnd]climatic indices and the monsoon pattern in the Banas River Basin, India

Climate change has intense environmental and socioeconomic consequences. It is a major challenge for farmers which directly affects the development of agriculture productivity through climatic factors like monsoon variability which is mainly involved in rain-fed agriculture. To analyze climate change in relation to agriculture, a wide variety of agro-climatic indices has been proposed by the scientific community. The trend of agro-climatic indices and changes in monsoon patterns were investigated using historical grid data in the Banas River basin, India. For this study, 43 years of gridded historical datasets of temperature and precipitation were collected from the India Meteorological Department (IMD) from 1971 to 2013. For climatic indices, trend analysis and test of significance using the Mann-Kendall method were performed. Rainfall deciles, standard precipitation index (SPI), and reconnaissance drought index (RDI) were analyzed to understand the spatio-temporal changes in the agroclimatic indices in the study basin. The results show that SPI and RDI had significantly decreased, whereas a non-significant rise was observed in the aridity index and the seasonality index. Further, the onset and offset of monsoons were also studied for two different historical periods to understand the changing patterns over the last few decades. It was observed that there is an increase in the monsoon duration in 1996–2013, as compared to the period of 1971–1995. The seasonality index (SI) and aridity index (AI) has increased in the north-eastern and south-western of the river basin in the last 43 years. Overall, it can be concluded from the study that the change in precipitation and temperature has put an impact on agro-climatic indices. Therefore, depending on the future climatic condition, if this trend continues, it can affect the cropping pattern of the region both negatively and positively. The present study can also help in predicting the future aspects and impacts of the changes in agro-climate indices based on past trends.

NDVI-based ecological dynamics of forest vegetation and its relationship to climate change in Romania during 1987–2018

Forests have become increasingly stressed by climate change, including in Romania over recent decades, but their response to climate dynamics has not yet been analysed in this country. This study aims to investigate, for the first time, recent ecological changes in forests across Romania, in relation to climate dynamics that affected the country from 1987 to 2018. To this end, countrywide remote sensing (Landsat) data were processed for forest boundaries over the 32 years, in order to compute annual (summer season data) Normalized Difference Vegetation Index (NDVI) datasets, which were subsequently investigated as trends using the Mann-Kendall test and Sen's slope estimator. Simultaneously, various climatic data (temperature, precipitation and reference evapotranspiration) were processed through interpolation techniques and via the same two statistical tools, and were subsequently used for exploring the impact of climate change on Romanian forestlands after 1987. The results highlighted general greening (increasing NDVI) trends of forests nationally (65% of all NDVI changes, which total over 30.000 km2 across Romania), which were dominated by widespread positive NDVI trends detected in the Carpathians region of Romania. This general ecological dynamic suggests a possible enhancement in vegetation productivity in the country’s high-altitude areas. Contrasting browning (decreasing NDVI) trends were found for 35% of Romanian forestlands marked by NDVI changes, especially apparent in the Extra-Carpathians (lowland) region, which indicates that in these cases forests were degraded or devitalized. However, the statistical significance of both greening and browning trends is limited across the country. The analysis of climatic trends and of correlations between annual NDVI and climate data indicated that recent warming throughout Carpathians may be an important driving force of forest greening in temperature-limited mountain regions. This finding is supported by an at least moderate intensity of air temperature – NDVI relationships (r correlation coefficient values of ∼50%, the highest of all eco-climatic relationships analysed), generally detected throughout mountain environments. At the same time, it seems that evapotranspiration increase accounted at least in part for forest browning in lowland areas, while the impact of precipitation in forest ecological dynamics remains unclear. All these findings can be useful for a better forest management under the future climate change conditions in Romania.

Climate Change and Trend Analysis of 24-Hourly Annual Maximum Series Using Mann-Kendall and Sen Slope Methods for Rainfall IDF Modeling

The aim of this study is the establishment of the existence of trend and variability on a typical 24-hourly sorted thirty years (1986-2015) annual maximum series (AMS) and maximum monthly series (MMS) rainfall data for Uyo metropolis in Nigeria. Data were downscaled into shorter durations of 0.25, 0.5, …,12 hours. The statistical tool applied for the study was the Mann-Kendall (MK) test and Sen Slope estimator. The results showed that there exists increasing trend for all durations analyzed with consistency in the test statistic results. The MK statistic lZl for the AMS varied between 3.1701 and 3.2827 while that of MMS was 4.756, were greater than critical Z = 1.96. Also, the computed p-value for the AMS varied between 0.0012 and 0.0015, and were lower than the significant level of alpha, = 0.05. Thus, the null hypothesis of no trend was rejected. Similarly, the Sen Slope estimator gave an average rate of change in rainfall as 2.1288 and 2.16 mm/year for AMS and MMS time series data, respectively. The result from the Sen Slope estimator indicated that the magnitude of the trend decreased as the duration of rainfall increased such that shorter duration exhibited more trend than higher duration. The results of the MK trend and Sen Slope analysis proved that both test exhibited high degree of consistency with statistically significant positive trend and variability. These results have provided further evidence of an accelerated alarming rate in climate change increasing trend in Uyo metropolis and perhaps the environs. Therefore, planning for effective and accurate rainfall prediction for annual maximum time series data with established variability in trend will require adoption of non-stationary concept to account for the influence of changing climatic parameters in intensity-duration-frequency (IDF) modeling.

A pragmatic approach for analysis of long-term climate trends for apple growing regions of Himachal Pradesh, India

The study assessed the long-term climate as well as the area and production trends for four representative decades (1985-2020) in three apple growing districts of Himachal Pradesh, India with the objective of understanding the impact of climate change on apple crop. A long term database was prepared for minimum temperature (Tmin), maximum temperature (Tmax) and rainfall, besides area and production for four decades for three districts of Himachal Pradesh, India. Trend analysis indicated that the temperature in apple growing regions of generally showed an increasing trend, whereas, decreasing trend was observed in the precipitation. The minimum temperature in apple growing regions of Kullu, Shimla and Kinnaur districts has shown an increase of 0.82º C, 1.09 º C and 0.03 ºC, respectively and the precipitation (rainfall) in the Kullu, Shimla and Kinnaur districts has shown a decrease by 5.3 mm, 3.3 mm and 0.9 mm, respectively. Increased warming in the mountain regions is elevating temperatures resulting in the reduction of chilling hours, pre-requisite for apple fruiting. However, in the higher elevation of Shimla, Kullu and Kinnaur districts, in spite of the increase in temperature, the areas are still suitable for apple farming. The study indicated that the area and production of all three districts of study are increasing because growers are slowly shifting to low chilling varieties (Varieties having chilling hours requirement less than 1000 hours). Also, the present ecosystem at lower elevations will not support high chilling requirement varieties and apple growers will have to shift to either low chilling varieties or alternate crops.

Farmers' Perception, Adaptation Strategies, their Determinants and Barriers to Climate Change in the Bundelkhand Region of Central India

This study is based on a farm house hold survey (818 households) collected from 4 districts of drought prone region of central India and examines that how farmers perceive the climate change and adaptation strategies adopted over the past few decades. Nearly, 80.9%, 93.6% and 95.2% farmers’ perceived that the average temperature has increased, rainfall has decreased and occurrence of drought is more frequent, respectively during last 25–30 years. A significant decreasing trend was observed in annual rainfall at all the studied locations with a rate of 2.1 to 5.8 mm year–1. In most of the locations both maximum and minimum temperature showed an increasing trend during winter season (July-October) in the range of 0.8 to 1.2 and 0.4–1.5ºC per 100 year, respectively. However, only two locations viz., Jhansi and Banda district showed increasing trend in maximum temperature in the range of 0.8 to 2.3oC per hundred years during rainy season. This study revealed that the perceptions of rural farmers on climate change and variability are consistent with the climate trend analysis. Econometric model suggested a positive influence of age, agriculture experience, educational qualification, size of land holding, adequate access to credit facility and crop insurance, intermittent dry spell and adequate extension services on climate change perceptions and adaptation. The results further revealed that 69.8% respondent have implemented adaptation measures in response to dry spell. Furthermore, analysis showed that agriculture experience, educational qualification and intermittent dry spell and access to extension services are the key factors for adoption of various adaptation strategies particularly, irrigations scheduling, use of high yielding improved varieties, pesticides and change of planting date. Inadequate availability of irrigation resources and frequent drought as well as intermittent dry spells were considered as the most critical barriers for adaptation measures to climate change by farmers.

Mixed Temperature-Moisture Signal in δ18O Records of Boreal Conifers from the Permafrost Zone

Global climatic changes have been observed for all natural biomes, with the greatest impact in the permafrost zone. The short series of direct observations of air temperature and precipitation from meteorological stations for this territory make it difficult to use them in studies of the impact of climate change on forest and forest-tundra ecosystems, but only longer series of gridded data expand the temporal-spatial resolution of this analysis. We compared local and gridded air temperature, precipitation and vapor pressure deficit (VPD) data, analyzed the trends of their changes over the last century for three sites in the permafrost zone (YAK and TAY in Russia, and CAN in Canada), and estimated the effect of their variability on oxygen isotopes in the tree-ring cellulose (δ18Ocell) of three different species (Larix cajanderi Mayr, Larix gmelinii Rupr. Rupr and Piceaglauca (Moench) Voss). Climate trend analysis showed strong changes after the 1980s, and even more pronounced from 2000 to 2020. We revealed that δ18Ocell-YAK showed mixed signals of the July temperature (r = 0.49; p = 0.001), precipitation (r = −0.37; p = 0.02) and vapor pressure deficit (VPD) (r = 0.31; p = 0.02), while δ18Ocell-CAN captured longer March–May (r = 0.37, p = 0.001) and July (r = 0.32, p < 0.05) temperature signals as well as spring VPD (r = 0.54, p = 0.001). The δ18Ocell-TAY showed a significant correlation with air temperature in July (r = 0.23, p = 0.04) and VPD in March (r = −0.26, p = 0.03). The obtained eco-hydrological relationships indicate the importance of temperature and moisture to varying degrees, which can be explained by site- and species-specific differences.

Climate Variability and Trend Analyses of Rainfall and Temperature Data of Imphal, Manipur

Understanding local climate variability and change is necessary for improving future climate forecasts and also aids preparation of informed area specific climate mitigation and adaptation strategies. Climate change at local scale is best revealed by studying observed variabilities and trends in rainfall and temperature data through statistical techniques. Therefore, this study employed standard deviation and coefficient of variability and Mann-Kendall test and Sen slope determination non-parametric techniques to perform variability and trends analyses across multiple temporal scales on climate data obtained at Imphal (Tulihal) station. The results indicate prevalence of different patterns between rainfall and temperature trends. Except for the positive trends in the month May (2mm/yr) and in the pre-monsoon season (9.49mm/yr), no other discernable patterns in rainfall data were observed. Temperature trends, on the other hand, witnessed significant positive increase in maximum, minimum and mean values. For mean temperature, all months registered significant increasing trends. At the annual and seasonal scales also, maximum, minimum and mean temperatures have increased although with varying rates. It is noteworthy to mention that temperature change has occurred at two distinct phases; before 1993 slow warming and after 1993 rapid warming. Temporal distribution of annual mean temperature captures this pattern more vividly as warming rate before 1993 was less than 0.01 compared to 0.450c/year in the latter phase. Overall, it can be said that rainfall has higher variability with very little or no pattern but temperature distribution suggests existence of strong trends in the observed data.

Analysis of climatic trends in the upper Blue Nile basin based on homogenized data

Analysis of climatic trends in the upper Blue Nile basin based on homogenized data

Performance Evaluation and Comparison of Satellite-Derived Rainfall Datasets over the Ziway Lake Basin, Ethiopia

Consistent time series rainfall datasets are important in performing climate trend analyses and agro-hydrological modeling. However, temporally consistent ground-based and long-term observed rainfall data are usually lacking for such analyses, especially in mountainous and developing countries. In the absence of such data, satellite-derived rainfall products, such as the Climate Hazard Infrared Precipitations with Stations (CHIRPS) and Global Precipitation Measurement Integrated Multi-SatellitE Retrieval (GPM-IMERG) can be used. However, as their performance varies from region to region, it is of interest to evaluate the accuracy of satellite-derived rainfall products at the basin scale using ground-based observations. In this study, we evaluated and demonstrated the performance of the three-run GPM-IMERG (early, late, and final) and CHIRPS rainfall datasets against the ground-based observations over the Ziway Lake Basin in Ethiopia. We performed the analysis at monthly and seasonal time scales from 2000 to 2014, using multiple statistical evaluation criteria and graphical methods. While both GPM-IMERG and CHIRPS showed good agreement with ground-observed rainfall data at monthly and seasonal time scales, the CHIRPS products slightly outperformed the GPM-IMERG products. The study thus concluded that CHIRPS or GPM-IMERG rainfall data can be used as a surrogate in the absence of ground-based observed rainfall data for monthly or seasonal agro-hydrological studies.

Analysis of Climate Variability and Trends in Southern Ethiopia

This study investigated the trends and variability of seasonal and annual rainfall and temperature data over southern Ethiopia using time series analysis for the period 1983–2016. Standard Anomaly Index (SAI), Coefficient of Variation (CV), Precipitations Concentration Index (PCI), and Standard Precipitation Index (SPI) were used to examine rainfall variability and develop drought indices over southern Ethiopia. Temporal changes of rainfall trends over the study period were detected using Mann Kendall (MK) trend test and Sen’s slope estimator. The results showed that the region experienced considerable rainfall variability and change that resulted in extended periods of drought and flood events within the study period. Results from SAI and SPI indicated an inter-annual rainfall variability with the proportions of years with below and above normal rainfall being estimated at 56% and 44% respectively. Results from the Mann Kendall trend test indicated an increasing trend of annual rainfall, Kiremt (summer) and Bega (dry) seasons whereas the Belg (spring) season rainfall showed a significant decreasing trend (p < 0.05). The annual rate of change for mean, maximum and minimum temperatures was found to be 0.042 °C, 0.027 °C, and 0.056 °C respectively. The findings from this study can be used by decision-makers in taking appropriate measures and interventions to avert the risks posed by changes in rainfall and temperature variability including extremes in order to enhance community adaptation and mitigation strategies in southern Ethiopia.