Pub Date : 2025-08-01Epub Date: 2025-06-17DOI: 10.1016/j.cliser.2025.100588
Liang Li’e, Wang Xiaohan, Chao Yan, Li Jiamin, Zhu Yonghua
Global warming leads to more frequent droughts. Therefore, in order to understand the development characteristics of drought, based on high-resolution climate data, the Mann-Kendall test, empirical orthogonal function decomposition and multi-threshold operation theory were adopted to analyze the characteristics of the multi-scale standardized precipitation index (SPI) and the standardized potential evapotranspiration index (SPEI) from 2002 to 2021. Based on CMIP6, the development trend of drought under different emission scenarios from 2021 to 2040 was predicted through multi-model ensemble (MME). The results show that both SPI and SPEI effectively identify the drought conditions in MUSL. The short-term scale (1/3 month) of SPI is stable in identifying drought with precipitation deficiency, and SPEI is more sensitive to sudden drought driven by high temperature. Both indicators on a long-term scale (6/12 months) can effectively monitor persistent drought. In the low-emission scenario (SSP126/245), drought is mainly dominated by precipitation changes. The results of SPI and SPEI are relatively consistent and both can be used for monitoring. In the high-emission scenario (SSP370/585), the increase in temperature intensifies evapotranspiration. SPEI can more accurately reflect the actual drought risk, while relying solely on SPI may underestimate the intensification effect of high temperature on drought. The comprehensive implementation of these measures will effectively enhance the resilience of the study area in responding to the increasingly severe drought challenges.
{"title":"Drought assessment and development trend in Mu Us Sandy Land based on standardized precipitation and potential evapotranspiration index","authors":"Liang Li’e, Wang Xiaohan, Chao Yan, Li Jiamin, Zhu Yonghua","doi":"10.1016/j.cliser.2025.100588","DOIUrl":"10.1016/j.cliser.2025.100588","url":null,"abstract":"<div><div>Global warming leads to more frequent droughts. Therefore, in order to understand the development characteristics of drought, based on high-resolution climate data, the Mann-Kendall test, empirical orthogonal function decomposition and multi-threshold operation theory were adopted to analyze the characteristics of the multi-scale standardized precipitation index (SPI) and the standardized potential evapotranspiration index (SPEI) from 2002 to 2021. Based on CMIP6, the development trend of drought under different emission scenarios from 2021 to 2040 was predicted through multi-model ensemble (MME). The results show that both SPI and SPEI effectively identify the drought conditions in MUSL. The short-term scale (1/3 month) of SPI is stable in identifying drought with precipitation deficiency, and SPEI is more sensitive to sudden drought driven by high temperature. Both indicators on a long-term scale (6/12 months) can effectively monitor persistent drought. In the low-emission scenario (SSP126/245), drought is mainly dominated by precipitation changes. The results of SPI and SPEI are relatively consistent and both can be used for monitoring. In the high-emission scenario (SSP370/585), the increase in temperature intensifies evapotranspiration. SPEI can more accurately reflect the actual drought risk, while relying solely on SPI may underestimate the intensification effect of high temperature on drought. The comprehensive implementation of these measures will effectively enhance the resilience of the study area in responding to the increasingly severe drought challenges.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100588"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-10DOI: 10.1016/j.cliser.2025.100576
Oladimeji Idowu Oladele, Mjabuliseni Simon C. Ngidi
{"title":"Corrigendum to “A content analysis of actionable guidelines for Climate-Smart agriculture implementation in South Africa- communication for behavioral changes” [Clim. Serv. 38 (2025) 100541]","authors":"Oladimeji Idowu Oladele, Mjabuliseni Simon C. Ngidi","doi":"10.1016/j.cliser.2025.100576","DOIUrl":"10.1016/j.cliser.2025.100576","url":null,"abstract":"","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100576"},"PeriodicalIF":4.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-06-28DOI: 10.1016/j.cliser.2025.100590
Yohannes Yona , Getachew Sime , Tafesse Matewos
Climate change-induced impacts have affected smallholder farmers and their livelihoods in developing countries. The situation in Ethiopia is especially severe due to the prevalence of rain-fed agriculture and the limited availability of climate information services. Smallholder farmers were unable to apply climate adaptation methods due to limited access to and use of climatic information. This study was carried out in Ethiopia’s Sidama region to analyze the current state and factors impacting access to and use of climate information services as decision-making tools for climate change adaptation. Employing a mixed research strategy, data was collected from 403 sample households, 32 key informants, and 6 focus group discussions to address the study objectives. The collected data was analyzed using both descriptive and inferential statistics. Specifically, the Heckman probit econometric model was employed to identify the factors that affect the access to and utilization of climate information services in the study districts. The study discovered that smallholder farmers obtain climate information through various sources, such as personal experience, community meetings, extension services, and mass-media. Despite 65.8 percent of surveyed households recognizing the importance of climate information for decision-making, only 44.4 percent of the respondents implemented it in their agricultural activities. This disparity can be attributed to various socioeconomic, institutional, and farmers’ characteristics. The study emphasized the need for capacity-building training, improved access to infrastructure like Farmer Training Centers (FTCs), and the integration of climate information with extension services to enhance the implementation of strategies to adapt to climate change in the region.
{"title":"Awareness, access and adoption of climate information services for climate change adaptation in Ethiopia","authors":"Yohannes Yona , Getachew Sime , Tafesse Matewos","doi":"10.1016/j.cliser.2025.100590","DOIUrl":"10.1016/j.cliser.2025.100590","url":null,"abstract":"<div><div>Climate change-induced impacts have affected smallholder farmers and their livelihoods in developing countries. The situation in Ethiopia is especially severe due to the prevalence of rain-fed agriculture and the limited availability of climate information services. Smallholder farmers were unable to apply climate adaptation methods due to limited access to and use of climatic information. This study was carried out in Ethiopia’s Sidama region to analyze the current state and factors impacting access to and use of climate information services as decision-making tools for climate change adaptation. Employing a mixed research strategy, data was collected from 403 sample households, 32 key informants, and 6 focus group discussions to address the study objectives. The collected data was analyzed using both descriptive and inferential statistics. Specifically, the Heckman probit econometric model was employed to identify the factors that affect the access to and utilization of climate information services in the study districts. The study discovered that smallholder farmers obtain climate information through various sources, such as personal experience, community meetings, extension services, and mass-media. Despite 65.8 percent of surveyed households recognizing the importance of climate information for decision-making, only 44.4 percent of the respondents implemented it in their agricultural activities. This disparity can be attributed to various socioeconomic, institutional, and farmers’ characteristics. The study emphasized the need for capacity-building training, improved access to infrastructure like Farmer Training Centers (FTCs), and the integration of climate information with extension services to enhance the implementation of strategies to adapt to climate change in the region.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100590"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144510824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human-induced climate change led to a rise in the occurrence and severity of extreme events, including droughts, on a global scale. The assessment of drought conditions is important in understanding and mitigating drought risk in the future. This study used 26 General Circulation Models (GCMs) of high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets and the standardized precipitation index (SPI) to assess the future of droughts in Central Europe (Poland) under four Shared Socioeconomic Pathways (SSPs) scenarios (i.e., SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5). For this purpose, precipitation in the near future (NF) (2031–2060) and far future (FF) (2071–2100) periods were projected, and then an assessment of droughts at time scales of SPI-01, SPI-06 and SPI-012 was carried out. The projection of spatial variability of precipitation in Poland revealed that it will increase slightly (10–30%) under SSP1–2.6 and SSP2–4.5 scenarios, while in the FF, it is projected to increase by 20–50% under SSP3–7.0 and SSP5–8.5 scenarios in the north/central and south of Poland, respectively. Assessment of the future of droughts demonstrated that in the NF, the frequency of droughts will decrease by approximately 20–60% in all SPI timescales (SPI-01, SPI-06, SPI-12) under all SSP scenarios. In the FF, drought frequency will increase significantly, particularly under SSP3–7.0 and SSP5–8.5 scenarios, with 50–100% increases for SPI-06 (agricultural drought) and SPI-12 (hydrological drought).
{"title":"Assessment of drought conditions under climate change scenarios in Central Europe (Poland) using the standardized precipitation index (SPI)","authors":"Babak Ghazi , Hossein Salehi , Rajmund Przybylak , Aleksandra Pospieszyńska","doi":"10.1016/j.cliser.2025.100591","DOIUrl":"10.1016/j.cliser.2025.100591","url":null,"abstract":"<div><div>Human-induced climate change led to a rise in the occurrence and severity of extreme events, including droughts, on a global scale. The assessment of drought conditions is important in understanding and mitigating drought risk in the future. This study used 26 General Circulation Models (GCMs) of high-resolution NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets and the standardized precipitation index (SPI) to assess the future of droughts in Central Europe (Poland) under four Shared Socioeconomic Pathways (SSPs) scenarios (i.e., SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5). For this purpose, precipitation in the near future (NF) (2031–2060) and far future (FF) (2071–2100) periods were projected, and then an assessment of droughts at time scales of SPI-01, SPI-06 and SPI-012 was carried out. The projection of spatial variability of precipitation in Poland revealed that it will increase slightly (10–30%) under SSP1–2.6 and SSP2–4.5 scenarios, while in the FF, it is projected to increase by 20–50% under SSP3–7.0 and SSP5–8.5 scenarios in the north/central and south of Poland, respectively. Assessment of the future of droughts demonstrated that in the NF, the frequency of droughts will decrease by approximately 20–60% in all SPI timescales (SPI-01, SPI-06, SPI-12) under all SSP scenarios. In the FF, drought frequency will increase significantly, particularly under SSP3–7.0 and SSP5–8.5 scenarios, with 50–100% increases for SPI-06 (agricultural drought) and SPI-12 (hydrological drought).</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100591"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-07-09DOI: 10.1016/j.cliser.2025.100596
Peng Wei , Huichun Ye , Chaojia Nie , Minghao Qin , Yue Zhang , Hongye Wang , Shanyu Huang , Ronghao Liu
Waterlogging and flood disasters, often induced by persistent heavy precipitation, present additional hurdles to China’s agricultural resilience.. Assessing the impact of waterlogging disasters on crops is an essential basis for guiding agricultural disaster prevention and mitigation, and is of great importance for stabilizing agricultural production and ensuring food security. Taking Sanjiang Plain as the research area, this paper selected five indicators including cumulative precipitation, topography, river network, crop type, and crop vulnerability from three aspects: the risk of disaster-causing factors, the sensitivity of the disaster-bearing environment, and the vulnerability of the carrier. A waterlogging impact evaluation index system was constructed, and the weighted comprehensive evaluation method was used to evaluate the impact of crop waterlogging disasters from 2020 to 2022. The evaluation results were then verified using crop yield data. The results show that the absolute correlation coefficients (|r|) between the mean values of the composite index of waterlogging and flood influence and yields per unit area for rice, maize, and soybean were 0.69, 0.74, and 0.71, respectively. These findings highlight the accuracy of the assessment index system for crop waterlogging and flood impacts. Over time, there were noticeable fluctuations in the contribution of disaster-causing factors and the disaster-breeding environment that breed them. Spatially, the contributions of disaster-causing factors and the disaster-breeding environment were unevenly distributed, whereas the impact on the carrier remained concentrated. Consistent with natural patterns, the results of this study provide essential technical support for agricultural disaster prevention and mitigation, aiding the sustainable development of agriculture in the Sanjiang Plain.
{"title":"Evaluating the impact of crop waterlogging and flood disasters using multi-source data: a case study of the Sanjiang Plain","authors":"Peng Wei , Huichun Ye , Chaojia Nie , Minghao Qin , Yue Zhang , Hongye Wang , Shanyu Huang , Ronghao Liu","doi":"10.1016/j.cliser.2025.100596","DOIUrl":"10.1016/j.cliser.2025.100596","url":null,"abstract":"<div><div>Waterlogging and flood disasters, often induced by persistent heavy precipitation, present additional hurdles to China’s agricultural resilience.. Assessing the impact of waterlogging disasters on crops is an essential basis for guiding agricultural disaster prevention and mitigation, and is of great importance for stabilizing agricultural production and ensuring food security. Taking Sanjiang Plain as the research area, this paper selected five indicators including cumulative precipitation, topography, river network, crop type, and crop vulnerability from three aspects: the risk of disaster-causing factors, the sensitivity of the disaster-bearing environment, and the vulnerability of the carrier. A waterlogging impact evaluation index system was constructed, and the weighted comprehensive evaluation method was used to evaluate the impact of crop waterlogging disasters from 2020 to 2022. The evaluation results were then verified using crop yield data. The results show that the absolute correlation coefficients (|r|) between the mean values of the composite index of waterlogging and flood influence and yields per unit area for rice, maize, and soybean were 0.69, 0.74, and 0.71, respectively. These findings highlight the accuracy of the assessment index system for crop waterlogging and flood impacts. Over time, there were noticeable fluctuations in the contribution of disaster-causing factors and the disaster-breeding environment that breed them. Spatially, the contributions of disaster-causing factors and the disaster-breeding environment were unevenly distributed, whereas the impact on the carrier remained concentrated. Consistent with natural patterns, the results of this study provide essential technical support for agricultural disaster prevention and mitigation, aiding the sustainable development of agriculture in the Sanjiang Plain.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100596"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-07-26DOI: 10.1016/j.cliser.2025.100595
Clara Linés , Micha Werner
Seasonal forecasts of water availability have clear potential benefit for decisions in irrigated agriculture. This potential depends in part on how accurate the information provided is. The actual benefit, however, depends on how the information is used in the decisions, by whom, and the outcome of those decisions. In this paper we assess how useful seasonal forecasts are in supporting drought management decisions by farmers at the irrigation district level. We model the decisions irrigated farmers make on what and when to plant in the Ebro basin (Spain), and the interconnected decisions reservoir operators make on whether to apply curtailments to the water allocated to farmers. The modelled farmers are supplied from a reservoir with capacity for a single irrigation season and therefore their decisions are conditioned by the expected water availability through to the end of the season. Different farmer behaviours are considered as a function of their risk averseness and their technical capacity. The value of seasonal streamflow forecasts to inform these decisions is compared against that of current practice using extrapolated historical records, as well as against a reference forecast based on climatology. Results show that seasonal forecasts of water availability have skill, albeit limited. How salient information is to the decisions that farmers make, however, differs for each type of farmer as they take key decisions at different points in the season. As a consequence, seasonal forecast information is found to not serve the various farmer types considered equally. Our results illustrate how assessing the usefulness of information to servicing a decision can be approached from a combined technical and user-centric perspective.
{"title":"How useful are seasonal forecasts for farmers facing drought? A user-based modelling approach","authors":"Clara Linés , Micha Werner","doi":"10.1016/j.cliser.2025.100595","DOIUrl":"10.1016/j.cliser.2025.100595","url":null,"abstract":"<div><div>Seasonal forecasts of water availability have clear potential benefit for decisions in irrigated agriculture. This potential depends in part on how accurate the information provided is. The actual benefit, however, depends on how the information is used in the decisions, by whom, and the outcome of those decisions. In this paper we assess how useful seasonal forecasts are in supporting drought management decisions by farmers at the irrigation district level. We model the decisions irrigated farmers make on what and when to plant in the Ebro basin (Spain), and the interconnected decisions reservoir operators make on whether to apply curtailments to the water allocated to farmers. The modelled farmers are supplied from a reservoir with capacity for a single irrigation season and therefore their decisions are conditioned by the expected water availability through to the end of the season. Different farmer behaviours are considered as a function of their risk averseness and their technical capacity. The value of seasonal streamflow forecasts to inform these decisions is compared against that of current practice using extrapolated historical records, as well as against a reference forecast based on climatology. Results show that seasonal forecasts of water availability have skill, albeit limited. How salient information is to the decisions that farmers make, however, differs for each type of farmer as they take key decisions at different points in the season. As a consequence, seasonal forecast information is found to not serve the various farmer types considered equally. Our results illustrate how assessing the usefulness of information to servicing a decision can be approached from a combined technical and user-centric perspective.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"39 ","pages":"Article 100595"},"PeriodicalIF":4.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The current work intends to reconstruct the spatiotemporal evolution of precipitation and the Normalized Differentiate Vegetation Index (NDVI) in the Loukkos watershed and provide scenarios for their recent and future evolution, therefore determining the degree of association. We conducted a study on the time series data of precipitation and NDVI from 1999 to 2019. The NDVI prediction is conducted using the CA-Markov model and the linear mixed-effects multi-level model (LME) with precipitation data from 2019 to 2040. The CA-Markov model was employed to predict the vegetation indices for 2029 and 2040 using 1999, 2009, and 2019 data. The model simulates future precipitation estimates for up to 2040 using different daily precipitation data series obtained from ten meteorological stations between 1999 and 2019. The accuracy of NDVI simulation is evaluated using kappa indices, specifically of 88%, of 86%, and of 83%, indicating that the consistency between the simulated NDVI map of 2019 and the actual one is nearly perfect, indicating statistical reliability of our model. The precipitation forecast for the Loukkos watershed predicts that average annual precipitation will decrease by 11.4% between 1999 and 2040. In contrast, based on 2019, there will be an increase in low vegetation areas and a decline in dense regions in the eastern and western parts of the basin in 2029 (−12.89%) and 2040 (−12.78%), respectively. The findings of this study suggest that by 2040, the Loukkos watershed will be exposed to future climate hazards, such as reduced precipitation and vegetation. The integration of geoinformation and prediction models is a great resource for optimizing environmental planning to prepare and potentially mitigate the harmful effects of climate change and its consequences for both humanity and the environment.
{"title":"Predicting precipitation and NDVI utilization of the multi-level linear mixed-effects model and the CA-markov simulation model","authors":"Fatima Belhaj , Hlila Rachid , Ouallali Abdessalam , Aqil Tariq , Belkendil Abdeldjalil , Beroho Mohamed , Hassan Alzahrani , Hajra Mustafa , Hesham Mohamed El-Askary","doi":"10.1016/j.cliser.2025.100554","DOIUrl":"10.1016/j.cliser.2025.100554","url":null,"abstract":"<div><div>The current work intends to reconstruct the spatiotemporal evolution of precipitation and the Normalized Differentiate Vegetation Index (NDVI) in the Loukkos watershed and provide scenarios for their recent and future evolution, therefore determining the degree of association. We conducted a study on the time series data of precipitation and NDVI from 1999 to 2019. The NDVI prediction is conducted using the CA-Markov model and the linear mixed-effects multi-level model (LME) with precipitation data from 2019 to 2040. The CA-Markov model was employed to predict the vegetation indices for 2029 and 2040 using 1999, 2009, and 2019 data. The model simulates future precipitation estimates for up to 2040 using different daily precipitation data series obtained from ten meteorological stations between 1999 and 2019. The accuracy of NDVI simulation is evaluated using kappa indices, specifically <span><math><msub><mi>K</mi><mrow><mi>location</mi></mrow></msub></math></span> of 88%, <span><math><msub><mi>K</mi><mrow><mi>n</mi><mn>0</mn></mrow></msub></math></span> of 86%, and <span><math><msub><mi>K</mi><mrow><mi>s</mi><mi>t</mi><mi>a</mi><mi>n</mi><mi>d</mi><mi>a</mi><mi>r</mi><mi>d</mi></mrow></msub></math></span> of 83%, indicating that the consistency between the simulated NDVI map of 2019 and the actual one is nearly perfect, indicating statistical reliability of our model. The precipitation forecast for the Loukkos watershed predicts that average annual precipitation will decrease by 11.4% between 1999 and 2040. In contrast, based on 2019, there will be an increase in low vegetation areas and a decline in dense regions in the eastern and western parts of the basin in 2029 (−12.89%) and 2040 (−12.78%), respectively. The findings of this study suggest that by 2040, the Loukkos watershed will be exposed to future climate hazards, such as reduced precipitation and vegetation. The integration of geoinformation and prediction models is a great resource for optimizing environmental planning to prepare and potentially mitigate the harmful effects of climate change and its consequences for both humanity and the environment.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"38 ","pages":"Article 100554"},"PeriodicalIF":4.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01Epub Date: 2025-01-30DOI: 10.1016/j.cliser.2025.100544
Siqi Zhang, Huanping Wu, Mei Li, Bei Liu, Pengcheng Shao
In recent years, the climate change has been attributed more attention by numerous governments. In response, the China Meteorological Administration (CMA) has developed the Climate Monitoring and Prediction Analysis System (CIPAS). Currently, CIPAS Version 3 (CIPAS 3) incorporates data from global massive meteorological station, satellite, predication models, and reanalysis datasets. Designed with a “Cloud + Client” architecture, CIPAS 3 utilizes distributed, multi-layer cloud computing to integrate, manage, and share climate data. CIPAS 3 offers over 1,300 operational functions, nearly 1,800 products, and 213 climate algorithms. Additionally, it plays a critical role in global, regional, and provincial climate monitoring, prediction, real-time verification, decision-making, and public climate services. The design and implementation of this system are instrumental in supporting research and informing government actions in the field of climate change.
{"title":"The development and application of the cloud-based climate operational platform","authors":"Siqi Zhang, Huanping Wu, Mei Li, Bei Liu, Pengcheng Shao","doi":"10.1016/j.cliser.2025.100544","DOIUrl":"10.1016/j.cliser.2025.100544","url":null,"abstract":"<div><div>In recent years, the climate change has been attributed more attention by numerous governments. In response, the China Meteorological Administration (CMA) has developed the Climate Monitoring and Prediction Analysis System (CIPAS). Currently, CIPAS Version 3 (CIPAS 3) incorporates data from global massive meteorological station, satellite, predication models, and reanalysis datasets. Designed with a “Cloud + Client” architecture, CIPAS 3 utilizes distributed, multi-layer cloud computing to integrate, manage, and share climate data. CIPAS 3 offers over 1,300 operational functions, nearly 1,800 products, and 213 climate algorithms. Additionally, it plays a critical role in global, regional, and provincial climate monitoring, prediction, real-time verification, decision-making, and public climate services. The design and implementation of this system are instrumental in supporting research and informing government actions in the field of climate change.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"38 ","pages":"Article 100544"},"PeriodicalIF":4.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate change has adversely affected the livelihoods of people in developing countries where a large proportion of the population is heavily dependent on agriculture. Indigenous people need to perceive that the climate is changing or likely could change, and they need to pay sufficient attention to this perception to take action. Understanding farmers’ perceptions about climate change and adaptation strategies can help support their efforts and develop interventions more suited to the local context. Hence, this study aimed to elucidate how farmers perceive climate change in their locality and how they adapt to observed changes in the Dendi district, West Shewa Zone, Oromia Regional State, Ethiopia. Semi-structured interviews were conducted to gather information on farmers’ perceptions of climate change, observed threats, and adaptation practices to observed changes from 144 sample farmers. Key informant interviews and focus group discussions were also conducted to gather more insights into trends in climate change, threats, and adaptation practices in the area. Additionally, climate data of the district from 1990 to 2021 were analyzed to assess trends in temperature and rainfall in the study area. The findings of the study revealed an increasing trend in maximum temperatures in the study area, while the mean minimum temperatures slightly decreased. Rainfall trends have significantly decreased over the past three decades, with seasonal rainfall also declining. The majority of the respondents replied that they perceived an increase in temperature and a decrease in rainfall. Specifically, 79.2% of the respondents perceived rising temperatures, while 16.7% perceived a decrease in temperature. Additionally, 77.1% of respondents replied that there was a decrease in both the amount and distribution of rainfall. The socio-economic analysis reveals that weather events in the study area vary in frequency across agroecologies. The major events identified include prolonged droughts with late-onset or early offset of rains (84.5%), floods/excessive moisture (71.6%), crop disease (70.8%), and erosion (56.9%). As rain-fed crop production relies on the timely and normal distribution of rainfall, these events significantly disrupt agricultural operations, particularly in mid-altitude and lowland areas. The impacts, sometimes, include total crop loss, reduced yields, smaller seeding areas, delayed planting and maturity, and increased crop pests. Respondents reported various climate change adaptation practices, including adjusting cropping calendars, changing crop types, diversifying livelihoods, and adopting improved crop varieties and irrigation. However, the effectiveness of these practices was limited by resource and skill constraints. To enhance resilience, it is crucial to provide reliable climate information, offer training on climate-smart agriculture, ensure access to updated climate data, and promote improved irrigation methods.
{"title":"Observed climate trends and farmers’ adaptation strategies in Dendi District, West Shewa Zone, Ethiopia","authors":"Busha Getachew , Gonfa Kewessa , Worku Hailu , Gezahegn Girma","doi":"10.1016/j.cliser.2025.100548","DOIUrl":"10.1016/j.cliser.2025.100548","url":null,"abstract":"<div><div>Climate change has adversely affected the livelihoods of people in developing countries where a large proportion of the population is heavily dependent on agriculture. Indigenous people need to perceive that the climate is changing or likely could change, and they need to pay sufficient attention to this perception to take action. Understanding farmers’ perceptions about climate change and adaptation strategies can help support their efforts and develop interventions more suited to the local context. Hence, this study aimed to elucidate how farmers perceive climate change in their locality and how they adapt to observed changes in the Dendi district, West Shewa Zone, Oromia Regional State, Ethiopia. Semi-structured interviews were conducted to gather information on farmers’ perceptions of climate change, observed threats, and adaptation practices to observed changes from 144 sample farmers. Key informant interviews and focus group discussions were also conducted to gather more insights into trends in climate change, threats, and adaptation practices in the area. Additionally, climate data of the district from 1990 to 2021 were analyzed to assess trends in temperature and rainfall in the study area. The findings of the study revealed an increasing trend in maximum temperatures in the study area, while the mean minimum temperatures slightly decreased. Rainfall trends have significantly decreased over the past three decades, with seasonal rainfall also declining. The majority of the respondents replied that they perceived an increase in temperature and a decrease in rainfall. Specifically, 79.2% of the respondents perceived rising temperatures, while 16.7% perceived a decrease in temperature. Additionally, 77.1% of respondents replied that there was a decrease in both the amount and distribution of rainfall. The socio-economic analysis reveals that weather events in the study area vary in frequency across agroecologies. The major events identified include prolonged droughts with late-onset or early offset of rains (84.5%), floods/excessive moisture (71.6%), crop disease (70.8%), and erosion (56.9%). As rain-fed crop production relies on the timely and normal distribution of rainfall, these events significantly disrupt agricultural operations, particularly in mid-altitude and lowland areas. The impacts, sometimes, include total crop loss, reduced yields, smaller seeding areas, delayed planting and maturity, and increased crop pests. Respondents reported various climate change adaptation practices, including adjusting cropping calendars, changing crop types, diversifying livelihoods, and adopting improved crop varieties and irrigation. However, the effectiveness of these practices was limited by resource and skill constraints. To enhance resilience, it is crucial to provide reliable climate information, offer training on climate-smart agriculture, ensure access to updated climate data, and promote improved irrigation methods.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"38 ","pages":"Article 100548"},"PeriodicalIF":4.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01Epub Date: 2025-05-15DOI: 10.1016/j.cliser.2025.100579
Joseph Daron , Katerina Michaelides , Khalid Hassaballah , Andrés Quichimbo , Rebecca Parfitt , Jessica Stacey , Anna Steynor , Catrina Johnson , David MacLeod , Michael Bliss Singer
Communities across the world are sensitive to the impacts of seasonal climate variability, particularly in regions where distinct rainfall seasons support livelihoods and economic activities. Timely and actionable warnings of hazardous seasonal conditions and advisories tailored to different sectors can enable people to respond, reduce risks, and seize opportunities. Yet despite advances in seasonal forecasting methods and capabilities, there remains a lack of “impact-based” seasonal climate outlooks that more directly serve societal needs while preserving uncertainty information for risk-based decision making. Here we present a new method to address this gap, focusing on implementation in Regional and National Climate Outlook Forums and targeted at intermediary users who support the communication of seasonal outlooks across scales. The Seasonal IMpact-Based OutLook (SIMBOL) method provides a simple and scalable approach for use in regions across the world. We describe the conceptual basis for the method, embedded in the Impact-Based Forecasting (IBF) framework, and demonstrate its application through a case study of seasonal total rainfall impacts on groundwater in Somalia, trialled at the Greater Horn of Africa Climate Outlook Forum (GHACOF) in February 2024. We elaborate the critical role of co-production amongst different knowledge holders for characterizing impacts across all potential outlook outcomes, avoiding advisories that are biased towards the “most likely” outcome. We also discuss the importance of objective evidence from impact modelling and observations to consider antecedent conditions. Lessons learned and challenges encountered in developing the method are discussed to inform opportunities for future development and implementation in different contexts.
{"title":"SIMBOL: A method to co-produce impact-based seasonal outlooks","authors":"Joseph Daron , Katerina Michaelides , Khalid Hassaballah , Andrés Quichimbo , Rebecca Parfitt , Jessica Stacey , Anna Steynor , Catrina Johnson , David MacLeod , Michael Bliss Singer","doi":"10.1016/j.cliser.2025.100579","DOIUrl":"10.1016/j.cliser.2025.100579","url":null,"abstract":"<div><div>Communities across the world are sensitive to the impacts of seasonal climate variability, particularly in regions where distinct rainfall seasons support livelihoods and economic activities. Timely and actionable warnings of hazardous seasonal conditions and advisories tailored to different sectors can enable people to respond, reduce risks, and seize opportunities. Yet despite advances in seasonal forecasting methods and capabilities, there remains a lack of “impact-based” seasonal climate outlooks that more directly serve societal needs while preserving uncertainty information for risk-based decision making. Here we present a new method to address this gap, focusing on implementation in Regional and National Climate Outlook Forums and targeted at intermediary users who support the communication of seasonal outlooks across scales. The Seasonal IMpact-Based OutLook (SIMBOL) method provides a simple and scalable approach for use in regions across the world. We describe the conceptual basis for the method, embedded in the Impact-Based Forecasting (IBF) framework, and demonstrate its application through a case study of seasonal total rainfall impacts on groundwater in Somalia, trialled at the Greater Horn of Africa Climate Outlook Forum (GHACOF) in February 2024. We elaborate the critical role of co-production amongst different knowledge holders for characterizing impacts across all potential outlook outcomes, avoiding advisories that are biased towards the “most likely” outcome. We also discuss the importance of objective evidence from impact modelling and observations to consider antecedent conditions. Lessons learned and challenges encountered in developing the method are discussed to inform opportunities for future development and implementation in different contexts.</div></div>","PeriodicalId":51332,"journal":{"name":"Climate Services","volume":"38 ","pages":"Article 100579"},"PeriodicalIF":4.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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