Representative Concentration Pathway Scenarios Research Articles

Analyzing exposure risk and change characteristics of wind-driven rain in China under future climate scenarios

Wind-driven rain (WDR) is the primary source of building moisture, and it has a direct impact on the durability and thermal performance of building envelopes. To suppress the impact of WDR on buildings under climate change, this study analyzed three representative concentration pathways (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) based on the climate data of Meteonorm and assesses China's forecasted WDR for the next 80 years. The WDR exposure maps and the WDR increase maps of China's three future emission scenarios in 2050, 2080, and 2100 were plotted, and the rate of increase of WDR was calculated. A total of ten representative cities in China were selected based on their WDR exposure. Using the ASHRAE 160-2021 standard, WDR patterns of 16 orientations of building facades in the ten selected cities in 2050, 2080, and 2100 under three future climate scenarios were obtained. The results show that China's overall WDR exposure will increase under the three future climate scenarios, with the increase under the RCP4.5 scenario being the largest. From a regional perspective, southeastern China is exposed to severe WDR in current scenarios and may also be exposed to the same in future scenarios; the absolute increase of WDR is also the largest. There are certain differences in WDR exposure and increase of WDR exposure in cities in different climate zones in China, and the increase in coastal areas is significantly greater than that in inland areas. Particularly, in Shanghai, the exposure of WDR evidently increases both in summer and winter.

Identification of ecological security pattern based on ecosystem service supply and demand in the Yangtze River Delta, China

The identification of ecological security pattern(ESP) is of great significance in solving regional ecological security problems. The study proposes two new perspectives for the study of ESP Firstly, a new method for identifying ecological supply and demand areas based on the ratio of ecosystem service supply and demand is proposed; The second is to combine socioeconomic pathways and representative concentration pathways (SSP-RCP) scenarios to predict the future supply and demand of regional ecosystem services under different climate scenarios, and to further predict the future regional ESPs under different climate scenarios. Finally, A planning proposal based on ESP of the Yangtze River Delta(YRD) based on the supply and demand perspective was put forward, with ‘two belts-four zones’. The results show that the ESP changes significantly under different climate scenarios, and the ecological demands under the three scenarios continue to increase during the study period.

Persistently Southward of the South Asian High During the Radiative Forcing Stabilization

AbstractThe South Asian high (SAH), a large‐scale anticyclone at 100 and 200 hPa on the Asian continent, is driven by South Asian summer monsoon rainfall and heating over the Tibetan Plateau. As one member of the Asian summer monsoon system, the changes of its location and intensity may cause other climate responses. Rainfall‐induced latent heating can affect the SAH change. Previous study revealed that rainfall responses in Indian Ocean are opposite in periods of increased and stabilizing radiative forcing (RF) due to the deep ocean warming over the Southern Ocean. SAH responses during RF increase and stabilization are studied with 13 models from the Extended Representative Concentration Pathway scenario 4.5 (ECP4.5) experiment. At 100 hPa, the SAH intensifies and moves equatorward in increased RF scenario; when RF stabilizing, SAH still shifts southward but with little change in intensity. At 200 hPa, the SAH changes little in both RF increase and stabilization. These opposite responses at different altitudes may be due to the maximum potential temperature at 150–200 hPa, leading to the opposite changes in vertical motion. Results of the linear baroclinic model indicate that (a) during RF increase, diabatic heating () contributes to SAH strengthening, both and the mean advection of stratification change (MASC) lead to SAH southward movement; (b) during RF stabilization, and MASC, contribute to the SAH equatorward displacement. Two components of , the latent heating and residual heating, are canceled out and lead to little change in SAH intensity.

Projected changes in extreme precipitation and temperature events over Central Africa from COSMO‐CLM simulations under the global warming level of 1.5°C and above

AbstractThis study explores the response of the increased global warning levels (GWLs) on the spatio‐temporal characteristics of extreme precipitation and temperature events over Central Africa (CA). For this purpose, eight indices proposed by the Expert Team on Climate Change Detection and Indices have been computed based on an ensemble‐mean of simulations from the COnsortium for Small‐scale MOdelling in CLimate Mode (CCLM) regional climate model, under the Representative Concentration Pathways scenario RCP8.5. The ability of CCLM to represent the climatology of considered daily hydro‐climatic extreme indices related to both precipitation and temperature was also assessed. The results showed that despite the presence of some biases, the precipitation and temperature indices are satisfactorily represented by CCLM, with some notable improvements compared to the GCMs driving fields. The climate change signals under 1.5°C GWL threshold show mostly increases (decreases) in SDII, CDD, R95PTOT, T10, T90, WSDI, and DTR (RR1) over CA throughout the year, and these effects intensify towards a warmer world. Singularly, the strongest changes in these extreme events are generally recorded during the JJA season over the northern part of CA. The results also show on one hand a widespread decrease in mean precipitation (up to 2 mm · day−1 corresponding to ~50%) associated with the increase/decrease in CDD/RR1, and on the other hand an increase in mean temperatures (up to 4°C corresponding to ~18%) associated with the increase in both lowest and highest temperatures (T10, T90). This study suggests that the CA region will be prone to droughts and floods as well as heat waves in a warmer world and calls for climate action and adaptation strategies to mitigate the risks associated with the above changes on rain‐fed agriculture, water resource, and human health.

Quantification of forest carbon flux and stock uncertainties under climate change and their use in regionally explicit decision making: Case study in Finland

Uncertainties are essential, yet often neglected, information for evaluating the reliability in forest carbon balance projections used in national and regional policy planning. We analysed uncertainties in the forest net biome exchange (NBE) and carbon stocks under multiple management and climate scenarios with a process-based ecosystem model. Sampled forest initial state values, model parameters, harvest levels and global climate models (GCMs) served as inputs in Monte Carlo simulations, which covered forests of the 18 regions of mainland Finland over the period 2015–2050. Under individual scenarios, the results revealed time- and region-dependent variability in the magnitude of uncertainty and mean values of the NBE projections. The main sources of uncertainty varied with time, by region and by the amount of harvested wood. Combinations of uncertainties in the representative concentration pathways scenarios, GCMs, forest initial values and model parameters were the main sources of uncertainty at the beginning, while the harvest scenarios dominated by the end of the simulation period, combined with GCMs and climate scenarios especially in the north. Our regionally explicit uncertainty analysis was found a useful approach to reveal the variability in the regional potentials to reach a policy related, future target level of NBE, which is important information when planning realistic and regionally fair national policy actions.

Global urban fractional changes at a 1 km resolution throughout 2100 under eight scenarios of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs)

Abstract. The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by global urbanization and climate change. Although future dynamics of urban extent were commonly modeled with conversion from non-urban to urban extent using cellular-automata (CA)-based models, gradual changes of impervious surface area (ISA) at the pixel level were limitedly explored in previous studies. In this paper, we developed a global dataset of urban fractional changes at a 1 km resolution from 2020 to 2100 (5-year interval), under eight scenarios of socioeconomic pathways and climate change. First, to quantify the gradual change of ISA within the pixel, we characterized ISA growth patterns over the past decades (i.e., 1985–2015) using a sigmoid growth model and annual global artificial impervious area (GAIA) data. Then, by incorporating the ISA-based growth mechanism with the CA model, we calibrated the state-specific urban CA model with quantitative evaluation at the global scale. Finally, we projected future urban fractional changes at 1 km resolution under eight development pathways based on the harmonized urban growth demand from Land Use Harmonization2 (LUH2). The evaluation results show that the ISA-based urban CA model performs well globally, with an overall R2 of 0.9 and a root mean square error (RMSE) of 0.08 between modeled and observed ISAs in 2015. With the inclusion of temporal contexts of urban sprawl gained from GAIA, the dataset of global urban fractional change shows good agreement with 30-year historical observations from satellites. The dataset can capture spatially explicit variations of ISA and gradual ISA change within pixels. The dataset of global urban fractional change is of great use in supporting quantitative analysis of urbanization-induced ecological and environmental change at a fine scale, such as urban heat islands, energy consumption, and human–nature interactions in the urban system. The developed dataset of global urban fractional change is available at https://doi.org/10.6084/m9.figshare.20391117.v4 (He et al., 2022).

Projected Changes in Spawning Ground Distribution of Mature Albacore Tuna in the Indian Ocean under Various Global Climate Change Scenarios

The present study utilised a geometric mean model in which sea surface temperature, oxygen, and sea surface salinity were used to predict the effects of climate change on the habitats of mature albacore tuna in the Indian Ocean under multiple representative concentration pathway (RCP) scenarios. Data pertaining to the albacore tuna fishing conducted by Taiwanese longline fisheries during the October–March period in 1998–2016 were analysed. The fishery data comprised fishing location (latitude and longitude), fishing effort (number of hooks used), number of catches, fishing time (month and year), and fish weight. Nominal catch per unit effort data were standardised to mitigate the potential effects of temporal and spatial factors in causing bias and overestimation. The Habitat Suitability Index (HSI) scores of potential habitats for mature albacore in the Indian Ocean are predicted to change considerably in response to varying levels of predicted climate change. Under projected warm climate conditions (RCP 8.5), the stratification of water is predicted to cause low HSI areas to expand and potential habitats for mature albacore to shift southward by 2100. The findings derived from these mature albacore habitat forecasts can contribute to the evaluation of potential hazards and feasible adaptation measures for albacore fishery resources in the context of climate change. The distribution trends pertaining to potential habitats for mature albacore should be used with caution and can provide resource stakeholders with guidance for decision-making.

Coupled effects of land use and climate change on water supply in SSP–RCP scenarios: A case study of the Ganjiang River Basin, China

Coupling land use and climate change under shared socioeconomic pathway and representative concentration pathway (SSP–RCP) scenarios can provide more accurate predictions of water supply risks, thereby supporting decision-making for spatial planning with a focus on climate adaptation. Climate change exhibits spatial and temporal differences. To meet the requirements of spatial planning, further research is needed to assess water supply risks at different basin or regional scales. In this study, we selected four SSP–RCP scenarios for analysis, considering the temporal scale of spatial planning. The climate modeling capabilities of five global climate models (GCMs) and a multi-model ensemble (MME) were evaluated using a Taylor diagram, which assesses the performance of climate element simulations. The modeling framework that consisted of system dynamics (SD), patch-generating land-use simulations (PLUS), and Soil and Water Assessment Tool (SWAT) was employed to analyze synergistic changes in climate, land use, and water supply. The Ganjiang River Basin (GRB) serves as a case study for climate-adaptive planning at the basin scale, given its characteristics of high agricultural water demand and vulnerability to droughts and floods. The study aims to provide decision-making support for such planning. In our projections, precipitation in the GRB showed a slightly increasing trend from 2021 to 2050. Monthly precipitation increases during the flood season in August and decreases during the dry season from October to December. The maximum and minimum temperatures showed an increasing trend on both the yearly and monthly scales, with slightly higher increases during fall and winter. During the planning phase, the land use quantities of SSP126 and SSP245 showed similar variations. SSP370 experienced the most significant reduction in farmland, while SSP585 displayed a more scattered and punctuated layout of construction land. The annual water supply in the GRB showed a slightly decreasing trend from 2021 to 2035 and 2036–2050, and the largest reduction was found in SSP370. The trend of variation in the monthly water supply was complex. There was a consistent trend of decreasing water supply during the dry season, whereas the changes during the flood season were more complex. Seasonal variations in water supply are a major water security concern for the basin’s future. It is necessary to strengthen the agricultural water security planning in the northern region of the basin and enhance its ability to adapt to droughts and floods.

An assessment of adaptation measures to enhance wheat productivity under climate change during early, mid and end of 21st century in Indian Punjab

AbstractCERES-Wheat model was used to simulate wheat yield with ensemble model data for three time slices (2030–2050, 2050–2070 and 2070–2090) and four representative concentration pathway (RCP) scenarios (2.6, 4.5, 6.0 and 8.5) for four agroclimatic zones (ACZs) of Punjab. The study was conducted for wheat cultivars (HD2967 and PBW725) with two adaptation measures, i.e. shift in sowing dates and shift in sowing date plus additional nitrogen doses. The results showed that 24th November was the optimized sowing date and the yield were higher when supplemented with higher N doses (190 and 230 kg/ha). For the three time slices under RCP2.6 scenario, an increase in yield with combined adaptation measures for four ACZs and respectively for cvs. HD2967 and PBW725 ranged 16–32 and 16–33% (ACZII), 11–39 and 22–43% (ACZIII), 8–47 and 20–51% (ACZIV) and 15–32 and 22–42% (ACZV). Similarly, under stabilization scenarios (RCP4.5 and 6.0) the yield increased with combined adaptation measures and respectively for cvs. HD2967 and PBW725 ranged 15–32 and 14–31% (ACZII), 10–40 and 19–52% (ACZIII), 5–44 and 7–53% (ACZIV) and 14–32 and 20–42% (ACZV). The shortening of the maturity period for the two cultivars ranged 24–34 (ACZII), 21–36 (ACZIII), 9–19 (ACZIV) and 21–32 (ACZV) days under the future scenarios. Under the RCP8.5 scenario, the wheat cultivars were unable to yield higher even with combined adaptation measures during the end of 21st century. Thus, wheat would be a sustainable crop option under climate change in the state, if the sowing date was shifted to 24th November and supplemented with higher N dose.

Adaptability of wheat to future climate change: Effects of sowing date and sowing rate on wheat yield in three wheat production regions in the North China Plain

Adjusting sowing dates and sowing rates is a key adaptation strategy for adapting to future climate change, and maintaining wheat production in the North China Plain (NCP). However, it is still unclear whether the current sowing date and sowing rate can adapt to future climate change, and how to adjust the sowing date and sowing rate to compensate for the adverse effects of climate change on wheat yields. This study predicts the adaptability of agricultural management practices like sowing dates and sowing rates, to future climate change in three wheat regions by referring to four global climate models (GCMs) and AquaCrop model. Population structure and yield were maximized for sowing dates from Oct.11–20 and sowing rates of 10–13 kg/667 m2 (or 13–16 kg/667 m2) in 2016–2021. Three wheat regions were expected to show a warming trend, while the total precipitation has large spatial fluctuations under both representative concentration pathways (rcp) scenarios in the 2022–2100. AquaCrop model could simulate yield with a good precision (RMSE≤1043.7 kg/ha). Compared to the average yield of the baseline period (2016–2021), in the 2022–2100, the average predicted wheat yields of three wheat regions simulated based on the current optimal sowing date and sowing rate decreased by 5.45 % ∼ 11.05 % (9.35 % ∼ 16.84 %) and 2.57 % ∼ 10.95 % (6.97 % ∼ 12.75 %) under the rcp4.5 (rcp8.5), respectively. Average wheat yield losses were effectively compensated when the combinations of Oct.15 and 14 kg/667 m2 for the dryland wheat, Oct.21 and 14 kg/667 m2 for the irrigated wheat, and Oct.21 and 13 kg/667 m2 for the high-yield-rainfed wheat were applied under both rcp scenarios, respectively, with predicted yield losses of −4.17 %, −3.50 %, and − 3.25 %. Thus, adjusting sowing dates and sowing rates are viable options to effectively address the adverse effects of future global climate change, thereby guaranteeing food security in the NCP.

Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate

The evaluation of bioclimatic viticulture indices (BVIs) zones, similar to any other crop, necessitates a comprehensive understanding of the spatial variability of climate data. This study focuses on assessing the suitability of BVIs in the Jabal Al Arab region, a significant viticulture area in the Eastern Mediterranean. The aim is to analyze four temperature-based bioclimatic indices and the hydrothermal coefficient (HTC) to map their patterns and spatial variation across the region under climate change scenarios. Daily temperature data from 15 meteorological stations and 57 rain gauges spanning 1984–2014 were utilized, along with downscaled future scenarios (the Representative Concentration Pathways (RCPs) based on the second generation Canadian Earth System Model (CanESM2)) for 2016–2100. Additionally, statistical analysis and hybrid interpolation (regression-kriging) were employed to accurately map the BVIs throughout the region. The results reveal substantial spatial variability in Jabal Al Arab’s climate, with heat accumulation and the hydrothermal index during the growing season significantly influenced by elevation and distance to the seacoast. Additionally, the viticulture zones vary based on the specific index used and the projected future climate scenarios compared to the current climate. Climate change projections indicate a trend toward warmer conditions in the future. Under the RCP scenarios, the region can be categorized into up to three bioclimatic classes for certain indices, in contrast to the current climate with six classes. These findings offer valuable insights into viticulture suitability within each climatic region and facilitate the identification of homogeneous zones. By employing consistent bioclimatic indices and advanced hybrid interpolation techniques, this study enables meaningful comparisons of Jabal Al Arab with other viticulture regions worldwide. Such information is crucial for selecting suitable grapevine varieties and assessing the potential for grape production in the future.

Thermokarst lake susceptibility assessment using machine learning models in permafrost landscapes of the Arctic

Ice-rich permafrost thaws in response to rapid Arctic warming, and ground subsidence facilitates the formation of thermokarst lakes. Thermokarst lakes transform the surface energy balance of permafrost, affecting geomorphology, hydrology, ecology, and infrastructure stability, which can further contribute to greenhouse gas emissions. Currently, the spatial distribution of thermokarst lakes at large scales remains a challenging task. Based on multiple high-resolution environmental factors and thermokarst lake inventories, we used machine learning methods to estimate the spatial distributions of present and future thermokarst lake susceptibility (TLS) maps. We also identified key environmental factors of the TLS map. At 1.8 × 106 km2, high and very high susceptible regions were estimated to cover about 10.4 % of the region poleward of 60°N, which were mainly distributed in permafrost-dominated lowland regions. At least 23.9 % of the area of TLS maps was projected to disappear under representative concentration pathway scenarios (RCPs), with increased susceptibility levels in northern Canada. The slope was the key conditioning factor for the occurrence of thermokarst lakes in Arctic permafrost regions. Compared with similar studies, the reliability of the TLS map was further evaluated using probability calibration curve and coefficient of variation (CV). Our results provide a means for assessing the spatial distribution of thermokarst lakes at the circum-Arctic scale but also improve the understanding of their dynamics in response to the climate system.

ENSO Impact on the Declining CO2 Sink Rate

The ocean and land processes which determine the rate of uptake of anthropogenic carbon dioxide emissions are many and complex. Simplified models of the net effect of all these processes can assist in the development of more detailed models. A simple time-dependent atmospheric CO2 budget model is shown to closely match yearly Mauna Loa CO2 concentrations during 1959-2021. The model assumes an anthropogenic CO2 source, and a constant yearly CO2 sink rate proportional to the excess of CO2 over a baseline equilibrium value determined by the Mauna Loa data. The yearly CO2 sink rate is found to be 2.02% of the atmospheric excess above 293.6 ppm, with a downward trend in the sink rate during 1959-2021 that disappears when El Niño – Southern Oscillation (ENSO) activity is empirically accounted for. Significant model departures from observations occurred for three years after the 1991 eruption of Mt. Pinatubo. Assuming no change in the sink rate, the latest Energy Information Administration CO2 global emissions projections to 2050, and extrapolated to 2100, lead to model-projected CO2 concentrations well below the highest Representative Concentration Pathways scenario RCP8.5.

Assessing coastal vulnerability and land use to sea level rise in Jeddah province, Kingdom of Saudi Arabia

Sea level rise is one of the most serious outcomes of increasing temperatures, leading to coastal flooding, beach erosion, freshwater contamination, loss of coastal habitats, increased soil salinity, and risk of damage to coastal infrastructures. This study estimates the vulnerability to inundation for 2100 in coastal zones in Jeddah Province, Kingdom of Saudi Arabia, under various sea level rise (SLR) scenarios of 1, 2, 5, and 10 m. The predicted flooding was estimated using a combination of factors, including SLR, the bathtub model, digital elevation model, climate scenarios, and land use and land cover. The climate scenarios used were Representative Concentration Pathway (RCP) scenarios 1.9, 2.6, 4.5, and 8.5. The results of the SLR scenarios of 1, 2, 5, and 10 m revealed that 1.6, 4.7, 14.9, and 30.6% (or 88, 214, 679, 1398 km2) of the study area's coast could be classified as inundated areas. The various SLR scenarios can inundate 3.3 to 34% of the road area/length. The inundated built-up and road areas were estimated to range between 0.31 and 0.79 km2, accounting respectively for 1.18 to 3.01% of the total class areas for 1-meter and 2-meter SLR scenarios. In contrast, the inundated area will be significant in the situation of 5 and 10 m SLR scenarios. Regarding the case of a 10-meter SLR scenario, the inundation will negatively impact the built-up and road infrastructure areas, inundating 8.9 km2, with industrial infrastructures affected by inundation estimated at 0.21 km2, followed by green space infrastructures at 0.013 km2. The spatial information based on various SLR scenario impact mapping for Jeddah Province can be highly valuable for decision-makers to better plan future civil engineering structures within the framework of sustainable development.

Contribution of prioritized urban nature-based solutions allocation to carbon neutrality

Nature-based solutions (NBS) are essential for carbon-neutral cities, yet how to effectively allocate them remains a question. Carbon neutrality requires city-led climate action plans that incorporate both indirect and direct contributions of NBS. Here we assessed the carbon emissions mitigation potential of NBS in European cities, focusing particularly on commonly overlooked indirect pathways, for example, human behavioural interventions and resource savings. Assuming maximum theoretical implementation, NBS in the residential, transport and industrial sectors could reduce urban carbon emissions by up to 25%. Spatially prioritizing different types of NBS in 54 major European Union cities could reduce anthropogenic carbon emissions by on average 17.4%. Coupling NBS with other existing measures in Representative Concentration Pathway scenarios could reduce total carbon emissions by 57.3% in 2030, with both indirect pathways and sequestration. Our results indicate that carbon neutrality will be near for some pioneering cities by 2030, while three can achieve it completely.

Analyzing the influences of the selection of the RCP scenario and the reference period on the evaluation results of EURO‐CORDEX simulations for Hungary

AbstractTemperature and precipitation simulations are evaluated for Hungary based on 11 regional climate model experiments with 0.1° horizontal resolution from the EURO‐CORDEX programme. The aim of the study is to assess the different simulations and the multi‐model (MM) mean as well for 1991–2005 and 2006–2020 separately, on a monthly basis. For the period 2006–2020, three different representative concentration pathway (RCP) scenarios, namely, RCP2.6, RCP4.5 and RCP8.5 are taken into consideration, so the uncertainty arising from the radiative forcing pathways can also be analysed. Specifically, we addressed three questions: (i) Which is the best model simulation for 1991–2005 and for 2006–2020? (ii) Which scenario is closer to the observations, regarding the period 2006–2020? (iii) Which has a greater effect: the selection of the model or the scenario? According to our results, the spatial and the annual distribution of temperature is simulated appropriately by the MM mean, however, in the case of precipitation the maximum values occur in spring, instead of summer. In 2006–2020, in the first half of the year, simulated temperature is closer to the observations, when the RCP8.5 scenario is taken into account. However, in the case of precipitation, the MM mean of RCP4.5 driven simulations generally performed the best. In the investigated period, the selection of the model simulation has a greater effect compared to the selection of the scenario.

Planning precision aquaculture activities in a changing and crowded sea

Extreme climate events are increasingly challenging the growth of the marine aquaculture sector, causing local influences on species performance and affecting production and yield - impacting where to locate cage aquaculture facilities. Here we produced scenario-based quantitative maps using modelled species-specific performance combined with predicted high-resolution future IPCC temperature scenarios. We ran a species-specific Dynamic Energy Budget mechanistic model for four model species, up to 2050, and mapped functional trait-based outcomes as: i) time to reach the commercial size, ii) feces produced and iii) uneaten food. A high spatial resolution suitability index allowed the sustainability of farming strategies for single- and multi-species to be identified across a 159.696 km2 surface extension (Italian Exclusive Economic Zone; 6% of the Mediterranean basin surface). Providing a good case study to shed light on difficult questions facing aquaculture planning around the world. Good future performance under both representative concentration pathway (RCP) scenarios were modelled for Sea bream and European seabass in inshore waters. Performance of Mediterranean mussels and Japanese oysters was found to decrease slightly when compared to the 2007–2010 time interval. Scenario-based quantitative maps represent a heterogeneous species-specific knowledge layer that is critical to better inform aquaculture management and development strategies. Yet this knowledge layer is missing from the process to develop climate-resilient risk maps and associated adaptation measures, as well as when informing stakeholders on potential site expansion and/or the establishment of nascent aquaculture industry sites.

Worldwide comparison between the potential distribution of Rhipicephalus microplus (Acari: Ixodidae) under climate change scenarios.

The cattle tick Rhipicephalus microplus (Acari: Ixodidae) has demonstrated its ability to increase its distribution raising spatially its importance as a vector for zoonotic hemotropic pathogens. In this study, a global ecological niche model of R. microplus was built in different scenarios using Representative Concentration Pathway (RCP), Socio-Economic Pathway (SSP), and a climatic dataset to determine where the species could establish itself and thus affect the variability in the presentation of the hemotropic diseases they transmit. America, Africa and Oceania showed a higher probability for the presence of R. microplus in contrast to some countries in Europe and Asia in the ecological niche for the current period (1970-2000), but with the climate change, there was an increase in the ratio between the geographic range preserved between the RCP and SSP scenarios obtaining the greatest gain in the interplay of RCP4.5-SSP245. Our results allow to determine future changes in the distribution of the cattle tick according to the increase in environmental temperature and socio-economic development influenced by human development activities and trends; this work explores the possibility of designing integral maps between the vector and specific diseases.

Projection of hydrological responses to changing future climate of Upper Awash Basin using QSWAT model

BackgroundProjecting future streamflow variation or the hydrological impact of climate change plays a pivotal role in the sustainable implication of planning water resources management. Therefore, this study predicts the potential of climate change’s impact on hydrological components in the Upper Awash Basin (UAB). The study applied a statistical downscaling model (SDSM) to generate future high-resolution climate data from the climate model output of the Canadian Second Generation Earth System Model (CanESM2) and the National Centers for Environmental Prediction (NCEP) under the representative concentration pathways (RCP4.5 and RCP8.5) scenarios. To analyze the trend of future rainfall and temperature, non-parametric Mann-Kendall, Modified Mann-Kendall tests, Sen’s slope estimator, and changing point (Pettit) tests were used. The output of downscaled climate data is used as input to a calibrated and validated Soil and Water Assessment Tool (QSWAT) model to assess the impact of future climate change on UAB hydrology.ResultsThe results show that annual rainfall and temperature are significantly increased (p < 0.05) in the UAB under RCP4.5 and 8.5 for the model ensemble mean for both short- and long-term scenarios. The change in the rainfall, the maximum and minimum temperature is mostly visible in the second period (the 2060s). Climate change is likely to cause persistent decreases in surface runoff (SUR_Q) and increases in actual evapotranspiration (ET) under all climate scenarios in the three periods. Reduction in SUR_Q despite an increase in rainfall could be due to an increment in both temperature and ET. The study also identified inconsistent seasonal changes in projected future precipitation that considerably impact overall climatic conditions.ConclusionsThis research is essential to develop an interdisciplinary approach that integrates environmental policies for the coherent use and management of water resources for future climate change and ecological protection in the basin, including other similar basins.

Thermokarst Lake Susceptibility Assessment Induced by Permafrost Degradation in the Qinghai–Tibet Plateau Using Machine Learning Methods

The rapidly warming climate on the Qinghai–Tibet Plateau (QTP) leads to permafrost degradation, and the thawing of ice-rich permafrost induces land subsidence to facilitate the development of thermokarst lakes. Thermokarst lakes exacerbate the instability of permafrost, which significantly alters regional geomorphology and hydrology, affecting biogeochemical cycles. However, the spatial distribution and future changes in thermokarst lakes have rarely been assessed at large scales. In this study, we combined various conditioning factors and an inventory of thermokarst lakes to assess the spatial distribution of susceptibility maps using machine-learning algorithms. The results showed that the extremely randomized trees (EXT) performed the best in the susceptibility modeling process, followed by random forest (RF) and logistic regression (LR). According to the assessment based on EXT, the high- and very high-susceptibility area of the present (2000–2016) susceptibility map was 196,222 km2, covering 19.67% of the permafrost region of the QTP. In the future (the 2070s), the area of the susceptibility map was predicted to shrink significantly under various representative concentration pathway scenarios (RCPs). The susceptibility map area would be reduced to 37.06% of the present area in RCP 8.5. This paper also performed correlation and importance analysis on the conditioning factors and thermokarst lakes, which indicated that thermokarst lakes tended to form in areas with flat topography and high soil moisture. The uncertainty of the susceptibility map was further assessed by the coefficient of variation (CV). Our results demonstrate a way to study the spatial distribution of thermokarst lakes at the QTP scale and provide a scientific basis for understanding thermokarst processes in response to climate change.