Representative Concentration Pathways RCP4 Research Articles

Inter‐Comparison of Precipitation Simulation and Future Projections Over China From an Ensemble of Multi‐GCM Driven RCM Simulations

AbstractAn analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing.

Testing CORDEX GCMs for Projecting Rainfall in Amhara, Ethiopia

Five CORDEX Global Circulation Models (GCMs): ICHEC-EC-EARTH, MIROC5, HadGEM2-ES, MPI-ESM-LR, and NorESM1-M were tested and validated for projecting rainfall in the Amhara regional state of Ethiopia. The GCMs were evaluated in terms of their performance during the historical period 1981-2020 and of the near-term, mid-term, and long-term future periods in three Representative Concentration Pathway (RCP) scenarios, RCP2.6, RCP4.5, and RCP8.5, across 71 grid points. Monthly observed rainfall data was used to compare the GCMs' performance and correct their biases using three non-parametric quartile mapping methods: robust empirical quartiles, empirical quartiles, and smoothing splines. The results show that HadGEM2-ES and MPI-ESM-LR had the best performance in the study area. The test and validation results for these two GCMs have come up with r = 0.8, NSE = 0.5-0.6, and RMSE = 64-70 mm/month. As there was a large discrepancy in historical and projected CORDEX rainfall data, bias correction was necessary, and the robust empirical quartiles method was found the best for the Amhara region. Compared to the historical, there will be a decrease in the monthly rainfall amount for the months of March, May, June, July, and October and an increase for the rest in all projected scenarios. The result concluded that using an ensemble of HadGEM2-ES & MPI-ESM-LR GCMs would better simulate the rainfall in the Amhara region

Changes in Temperature and Precipitation Trends in Selected Polish Cities Based on the Results of Regional EURO-CORDEX Climate Models in the 2030–2050 Horizon

This study presents the potential impacts of climate change in 49 Polish cities by analyzing seven climate indicators. The analysis was carried out for the following three horizons: the current climate conditions (an average period spanning 2006 to 2015), near-future conditions (an average period spanning 2026 to 2035), and future conditions (an average period spanning 2046 to 2055). Climate indices were computed with bias-corrected EURO-CORDEX model ensembles from two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5. The systematic error was reduced using the quantile mapping method with a non-parametric approach of robust empirical quantiles (RQUANT). Data were used as references in the period of current climate conditions, and those required for bias correction consisted of historical ground-based observations provided by the Institute of Meteorology and Water Management. The analysis encompassed various key climate indices, including the annual average temperature, the count of hot days, cold days, and frost days, the cumulative annual precipitation, the frequency of days with precipitation, and instances of extreme precipitation (defined as the days with precipitation exceeding 10 mm/day). These findings reveal a noteworthy rise in the average annual temperature of approximately 1 °C and an uptick in the number of hot days by 3.7 days. Conversely, a decline in the number of cold days by approximately 19 days and frost days by 8 days was observed. Additionally, there was an augmentation in the annual precipitation sum, reaching up to 80 mm in RCP 8.5, accompanied by an increase in the number of days with precipitation (up by 3.3 days) and days with extreme precipitation (up by 2 days).

Warmer and wetter: Outlining climate services for snow-dependent tourism in Norway – The case of Lofoten

Human-induced climate change potentially impacts nature-based activities in Lofoten and may limit the attractiveness of the destination for tourists seeking recreation and adventure in the mountains. As a climate service, we calculated climate indicators relevant to the tourism sector based on the representative concentration pathways RCP4.5 and RCP8.5 until 2060. We used high-resolution gridded climate data and projections to calculate indicators such as changes in the frequency and intensity of consecutive wet days, changes in precipitation type (snow, sleet, rain), changes in the number of skiing days on ungroomed, natural snow, and changes of the monthly 0 °C-isoline. We found a minor, but non-robust increase in the number of consecutive wet days with a precipitation intensity > 8 mm/day, and a clear change in the precipitation regime depending on altitude that leads to more precipitation falling as rain instead of snow. Also, a strong decrease in the number of skiing days is projected by the climate models as the monthly near-surface 0 °C-isoline increases. These are important findings for long-term planning and investments in the tourism sector in Lofoten, especially as tourism growth is considered an important tool for regional economic development. The analytical methods used in this study are transferable to analyses on a regional to national scale. National maps and data material for 11 regions were recently published on https://klimaservicesenter.no/kss/framskr/sno-sludd-regn.

A comprehensive assessment of RCP4.5 projections and bias-correction techniques in a complex coastal karstic aquifer in the Mediterranean

This study aims to assess the projected precipitation and temperature changes at the coastal karstic aquifer of Salento (Apulia, Southern Italy) under the Representative Concentration Pathway RCP4.5. For this purpose, an ensemble of twelve Regional Climate Models (RCMs) driven by several General Circulation Models (GCMs) were collected. Eight bias-correction (BC) methods were applied at daily time steps, and their results were assessed on monthly and annual time steps, using daily records from 19 and 11 precipitation and temperature (minimum and maximum) stations, respectively, for the period 1960–2005. Missing data in the observed dataset were filled-in applying the best performing techniques out of the 5 that were employed and tested. The Linear Scaling and the Power Transformation were found to be the most effective methods for precipitation BC at the case study, while all methods performed equally well in correcting air temperature datasets. Results of future climate projections show a decrease in precipitation of about 6% and an increase in temperature of 2°C until the end of this century, compared to the historical period (1971–2005). This study forms the first comprehensive attempt to test the scientific literature’s most widely used bias-correction methods over the study area. The case study may be considered a benchmark for circum-Mediterranean regions because of its high geomorphological and structural complexity, regional size, surface water scarcity, and significant water withdrawals for human activities.

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.

Evaluating climatic change effects on EC and runoff in the near future (2020–2059) and far future (2060–2099) in arid and semi-arid watersheds

This study investigates the effect of climate change on the runoff and electrical conductivity (EC) of the Marun watershed. It used 35 general circulation models (GCMs) and the identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) rainfall-runoff model for the hydrological simulation. Moreover, a non-parametric regression model based on the multivariate adaptive regression splines (MARS) was utilized to estimate the EC under representative concentration pathway RCP4.5 and RCP8.5 scenarios in the near future F1 (2020–2059) and far future F2 (2060–2099) periods. Also, it used the technique for order of preference by similarity to ideal solution (TOPSIS) method to determine the best GCMs for each region and the k-nearest neighbors (KNN) technique to combine the temperature (Tmean) and precipitation (PCP) outputs and reduce the GCM uncertainty in each cell. According to the results, the highest increase of EC relative to the historical period (1966–2005) that will occur in the F1 period under the RCP4.5 and RCP8.5 scenarios is 17.43% and 15.6%, and for the F2 period is 18.46% and 11.2%, respectively, during autumn. The changes of annual Tmean, PCP, runoff, and EC in F1 period are 8.6%, 2.1%,  − 10.7%, and  − 11%, respectively, under the RCP4.5 scenario and 10.5%, 5.9%,  − 3.5%, and  − 12.2%, respectively, under the RCP8.5 scenario. The same values for the F2 period are 12.9%,  − 0.1%,  − 14.9%, and  − 10%, respectively, under the RCP4.5 scenario and 22.6%, 5.2%, 1.2%, and  − 12.8%, respectively, under the RCP8.5 scenario relative to the historical period.

Water balance components and climate extremes over Brazil under 1.5°C and 2.0°C of global warming scenarios.

The online version contains supplementary material available at 10.1007/s10113-023-02042-1.

Observed and predicted trends in Icelandic snow conditions for the period 1930–2100

Abstract. This study presents an estimate of historical snow conditions in Iceland and a projection of these conditions, given different emission scenarios. Historical snow conditions were estimated using in situ observations from manned meteorological stations over the period 1930–2021 and by remotely sensed observations from the MODIS instruments over the period 2001–2021. Historical and future climate conditions, as described by each of the 21 general circulation models (GCM) from the 5th iteration of the Coupled Model Intercomparison Project (CMIP5) as contained in the NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP) dataset, were used to simulate snow conditions in Iceland over the period 1950–2100 under the Representative Concentration Pathways (RCP) RCP4.5 and RCP8.5 with the SNOW-17 model. The results show an increase in the average annual snow cover frequency (SCF) over the historical record detected both in the in situ (1930–2021) and remotely sensed data (2001–2021). Average annual snow depth measurements also revealed an increasing trend over the historical record. Simulated snow conditions show a substantial decrease in both snow water equivalent (SWE) and SCF over the period 1950–2100, a trend more pronounced under RCP8.5 as compared to RCP4.5.

Regional climate projections of heavy precipitation over the Balkan Peninsula

This article presents climate change projections of heavy (above a certain threshold) precipitation under the Representative Concentration Pathways RCP4.5 and RCP8.5 for the territory of the Balkan Peninsula. The focus is on convective rainfall which, if significant, can damage infrastructure and cause casualties. For this purpose, RegCM4.4.5 regional climate model with 20 km resolution was used for the periods 2021–2050 and 2071–2099 compared with the reference period 1975–2004. The change in the number of heavy rainfalls is determined by using the thresholds in the Meteoalarm program corresponding to the ‘yellow’ code. It is found that the largest changes in the number of convective precipitation events are in the coastal and mountainous areas. The increase in the number of cases of heavy rainfalls does not exclude the decrease in the amount of precipitation in these areas. This can be explained by the increase in the period in which these precipitations are possible due to the increase in temperatures.

气候变化驱动下黄土高原刺槐林气候适宜性和脆弱性

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化驱动下黄土高原刺槐林气候适宜性和脆弱性 DOI: 10.5846/stxb202003140544 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(42141007, 41877539);中国气象科学研究院基本科研业务费专项(2020Z004) Climate suitability and vulnerability of Robinia pseudoacacia forest driven by climate change on the Loess Plateau Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:刺槐是黄土高原乡土树种,具有优良的水土保持和固碳功能。黄土高原生态恢复实践中实施了大规模的植树造林,刺槐林面积占沟壑丘陵区人工植树造林面积90%以上。由于种植时没有考虑刺槐的气候适宜性,一些地区的刺槐林出现了退化现象。采用最大熵模型,在0.5km×0.5km空间精度上分别模拟了1961-1990、1966-1995、1971-2000、1976-2005、1981-2010,以及2100年(典型浓度路径RCP4.5和RCP8.5气候情景下)黄土高原刺槐的气候适宜性和敏感性。模拟结果显示:黄土高原刺槐分布及其动态变化主要受到最冷月温度、极端低温、降水量、年辐射量等气候因子影响,低温(最冷月温度、极端低温)是影响刺槐的最关键因子。黄土高原西北和北部广大地区,自然环境条件不适合刺槐林生长;黄土高原东南部(关中平原和山西南部)比较适合刺槐生长。相对1961-1990年,1961-2010年期间刺槐林适宜区分布格局基本没有改变,RCP4.5和RCP8.5气候情景下刺槐林适宜区分布格局也没有显著改变。图层叠加分析发现,刺槐的气候适宜度(即存在概率)发生了明显改变。黄土高原西部和北部属于不适宜刺槐生长的非敏感区,东部和东南部是适宜刺槐生长的区域,尤其是山西中南部和陕西关中平原对气候变化非常敏感,展示了刺槐气候脆弱性的一面。研究结果对植树造林,优化人工林空间分布格局,应对气候变化风险和维持黄土高原森林生态系统可持续健康发展具有重要参考价值。 Abstract:Robinia pseudoacacia is a native tree species on the Loess Plateau, which has excellent functions of soil and water conservation, and carbon sequestration. Large scale afforestation was carried out in the practice of ecological restoration in the Loess Plateau, and the area of Robinia pseudoacacia forest accounted for more than 90% of artificial afforestation in the gully and hilly areas. However, Robinia pseudoacacia forest degenerated in some areas because climate suitability of Robinia pseudoacacia was not considered during afforestation. In this study, MaxEnt (maximum entropy model) was used to simulate the climate suitability and sensitivity of Robinia pseudoacacia on the Loess Plateau in 1961-1990, 1966-1995, 1971-2000, 1976-2005, 1981-2010, and 2100 (under the climate scenarios of Representative concentration pathway RCP4.5 and RCP8.5, respectively) at the spatial resolution of 0.5 km × 0.5 km. The simulation results showed that the distribution and dynamic changes of Robinia pseudoacacia on the Loess Plateau were mainly affected by the coldest month temperature, extreme low temperature, annual precipitation, annual radiation and other climate factors. Low temperature (the coldest month temperature, extreme low temperature) was the most important factor affecting Robinia pseudoacacia. The natural environment was not suitable for Robinia pseudoacacia forest in the northwest and the north of the Loess Plateau, but it was suitable in the southeast (the Guanzhong Plain and the south of Shanxi Province) of the Loess Plateau. Compared with the period of 1961-1990, the geographical distribution pattern of Robinia pseudoacacia forest was basically unchanged during 1961-2010, and its geographical distribution pattern was not significantly changed under the climate scenarios of RCP4.5 and RCP8.5. Overlay analysis showed that climate suitability (namely exist probability) of Robinia pseudoacacia changed significantly. The regions in the west and north of the Loess Plateau were not suitable for Robinia pseudoacacia, where belonged to non-sensitive areas. The regions in the east and southeast were suitable for Robinia pseudoacacia, where was very sensitive to climate change, especially in the south central of Shanxi Province and the Guanzhong Plain in Shaanxi Province, showing significant climate vulnerability. This study has important reference value for choosing suitable area for afforestation, optimizing the spatial distribution of plantation, coping with climate change risk, maintaining the sustainable and healthy development of forest ecosystem on the Loess Plateau. 参考文献 相似文献 引证文献

Potential for redistribution of post-moult habitat for Eudyptes penguins in the Southern Ocean under future climate conditions.

Anthropogenic climate change is resulting in spatial redistributions of many species. We assessed the potential effects of climate change on an abundant and widely distributed group of diving birds, Eudyptes penguins, which are the main avian consumers in the Southern Ocean in terms of biomass consumption. Despite their abundance, several of these species have undergone population declines over the past century, potentially due to changing oceanography and prey availability over the important winter months. We used light-based geolocation tracking data for 485 individuals deployed between 2006 and 2020 across 10 of the major breeding locations for five taxa of Eudyptes penguins. We used boosted regression tree modelling to quantify post-moult habitat preference for southern rockhopper (E. chrysocome), eastern rockhopper (E. filholi), northern rockhopper (E. moseleyi) and macaroni/royal (E. chrysolophus and E. schlegeli) penguins. We then modelled their redistribution under two climate change scenarios, representative concentration pathways RCP4.5 and RCP8.5 (for the end of the century, 2071-2100). As climate forcings differ regionally, we quantified redistribution in the Atlantic, Central Indian, East Indian, West Pacific and East Pacific regions. We found sea surface temperature and sea surface height to be the most important predictors of current habitat for these penguins; physical features that are changing rapidly in the Southern Ocean. Our results indicated that the less severe RCP4.5 would lead to less habitat loss than the more severe RCP8.5. The five taxa of penguin may experience a general poleward redistribution of their preferred habitat, but with contrasting effects in the (i) change in total area of preferred habitat under climate change (ii) according to geographic region and (iii) the species (macaroni/royal vs. rockhopper populations). Our results provide further understanding on the regional impacts and vulnerability of species to climate change.

Climate change implications for olive flowering in Crete, Greece: projections based on historical data

Climate change is expected to pose major challenges for olive cultivation in many Mediterranean countries. Predicting the development phases of olive trees is important for agronomic management purposes to foresee future climate impact and proactively act toward adaptation and mitigation strategies. In this study, a statistical model was developed based on winter chill accumulation and, in sequence, on heat accumulation to assess the changes in flowering occurrence for Olea europaea cv. Koroneiki, in the island of Crete, Greece. The model was based on and calibrated with long-term phenological observations and temperature data from four different sites in the island, spanning an elevation gradient between 45 and 624 m a.s.l. This model was used to assess the changes in flowering emergence under two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5, as projected by seven high-resolution Euro-CORDEX Regional Climate Models. Changes in chill accumulation were determined using the Dynamic Model. Reduction rates in chill accumulation for the whole chilling season ranged between 12.0 and 28.3% for the near future (2021–2060) and 22.7 and 70.9% for the far future (2061–2100), in comparison to the reference period of 1979–2019. Flowering was estimated to occur between 6 and 10 days earlier in the near future and between 12 and 26 days earlier in the far future, depending on the elevation and the climate change scenario.

(Digital Presentation) Evaluation of Two Methods of Bias Correction of Precipitations on Improvement of Hydrological Simulation:Case of Chiffa Basin-Northern Algeria-

This work aim to assess the “basic-quantile”and“gamma-mapping” bias correction methods in order to improve hydrological simulations of the Chiffa watershed. The results are provided by the conceptual rainfall-runoff GR2M model in the R environment, coupled with the outputs of rainfall data simulations from the RCA4 model of CORDEX-AFRICA forced by two global circulation models (MPI-ESM-LR and CRNM-CM5) under two Representative Concentration Pathways (RCP) RCP4.5 and RCP 8.5 .The validation of GR2M hydrological model on the Chiffa basin using Nash criteria made it possible to simulate future flows over the period 2074-2099. The results showed that the future flows simulated from raw rainfall data are not in adequacy with the evolution of future rainfall simulations whereas the flows simulated from the corrected rainfall data shown better results, which highlights the importance of bias correction for hydrological impact studies. Finally, the regional climate models simulate a 9% decrease in winter, and a 6% increase in spring under RCP4.5 by the end of the 21st century Figure 1

Climate change projection over Mainland Southeast Asia and the Lancang‐Mekong River basin based on a set of RegCM4 simulations

AbstractWe investigate the projected climate change over Mainland Southeast Asia (also known as the Indochina Peninsula) and the Lancang‐Mekong River basin, a region with complex topography and unique weather and climate systems, but limited availability of published high‐resolution regional climate model (RCM) studies. The study is based on an unprecedented ensemble of 21st century projections with the RegCM4 RCM driven by five different general circulation models (GCMs) at a grid spacing of 25 km under the representative concentration pathways RCP4.5 and RCP8.5. We focus on mean temperature and precipitation in the dry season November–March (NDJFM), the wet season May–September (MJJAS), and the whole year. Intercomparison between the RegCM4 simulations with the driving GCMs is provided to illustrate the added value of the RegCM4 experiments. RegCM4 reproduces greater and more realistic spatial detail of the present day temperature and precipitation distribution compared to the driving GCMs, but some biases are found, such as an overestimation of precipitation over high topography regions. The spatial pattern of biases shows some consistencies across the GCMs and, for NDJFM the RegCM4, although weak correlation is found between the GCM and nested RegCM4 biases. A generally lower warming is projected in the future by the RegCM4 in different seasons and the whole year. For precipitation, while prevailing increases are found in the GCM projections, large areas of decrease occur in the RegCM ones, in particular during the wet season, possibly due to the more detailed topographical representation. The change patterns of precipitation show consistencies across the GCMs and the RegCM4, especially in MJJAS. The projected changes of extreme indices indicate a general decrease/increase of extreme cold/warm events. Drought events are projected to be more frequent over the southwestern, while a general increase of heavy rain events prevails over most parts of the region.

Spatiotemporal variation in precipitation concentration and its potential relationship with drought under different scenarios in Inner Mongolia, China

AbstractGlobal warming has altered the uniformity of precipitation in Inner Mongolia, China, eventually leading to droughts. Further studies are necessary to determine the relationship between the concentration of precipitation and drought. Therefore, we assessed the spatial and temporal characteristics of the precipitation concentration degree (PCD), precipitation concentration period (PCP), and standardized precipitation evapotranspiration index (SPEI) in Inner Mongolia in the past (1961–2017) and predict changes in the three indices under different scenarios in the future (2018–2100) using measured model data and Sen's slope and Mann–Kendall trend analysis. The correlation between PCD/PCP and SPEI was explored using Pearson's correlation coefficient. The results showed that the spatial distribution of PCD and PCP in Inner Mongolia exhibited significant east–west differences. The PCD values were 0.42–0.76, with high‐value areas in the east. PCD showed a decreasing trend in both historical and future scenarios, indicating an even distribution of precipitation and an increased risk of drought. The PCP values were 190°–226°, with high‐value areas mainly in the western region. Except for in the Representative Concentration Pathways RCP4.5 and RCP8.5, PCP values in the historical and RCP2.6 scenarios showed a decreasing trend, indicating an earlier onset of maximum precipitation. SPEI values ranged between −1.23 and 1.17, with all future scenarios showing a decreasing trend and the historical scenario showing an increasing trend. The stations with positive correlation between SPEI and PCD accounted for 89.13, 67.39, 91.3, and 95.65% of Inner Mongolia, while those with positive correlation with PCP accounted for 43.47, 60.87, 56.52, and 4.35%, indicating that the correlation between drought variation and precipitation concentration is strong. These results can help reduce and prevent droughts and floods caused by changes in precipitation patterns and provide a basis for the rational use of water resources for preventing droughts and making relief decisions.

Evaluating the uncertainty of climate model structure and bias correction on the hydrological impact of projected climate change in a Mediterranean catchment

Study regionCrati River Basin, Southern Italy, Central Mediterranean. Study focusWe evaluate the combined effect of multiple global and regional climate model (GCM-RCM) combinations and bias correction (BC) methods on the hydrological impact of projected climate change. Under the representative concentration pathway RCP4.5, 15 EURO-CORDEX members, combining 6 GCMs and five high-resolution (0.11°) RCMs, provide the meteorological input for a spatially distributed hydrological model. RCM-derived input data are uncorrected and corrected through three empirical methods, leading to 60 different simulations for three ~30-year future periods in 2020–2096, compared to the baseline 1975–2005. The combined uncertainty of the climate models and correction methods is evaluated for the main hydrological variables using an analysis of variance (ANOVA) method. New hydrological insights for the regionResults highlight a considerable agreement in projecting a decreasing trend of available water resources (on average, −70 % for snow, −8 % for root zone soil moisture and −17 % for river runoff in the period 2070–2096), due to the remarkable mean temperature increase and less accentuated precipitation reduction. The uncertainty evaluation shows that (1) the primary source of uncertainty is the driving GCM, and (2) BC methods smooth the projected hydrological impact in a not negligible way, especially concerning discharge (for each future period, the reduction projected without bias correction is about 3 % higher than with BC), therefore contributing to the total uncertainty.

Future Changes of PNA-like MJO Teleconnections in CMIP6 Models: Underlying Mechanisms and Uncertainty

Abstract Future changes in boreal winter MJO teleconnections over the Pacific–North America (PNA) region are examined in 15 Coupled Model Intercomparison Project phase 6 models (CMIP6s) under SSP585 (i.e., Shared Socioeconomic Pathway 5 following approximately the representative concentration pathway RCP8.5) scenarios. The most robust and significant change is an eastward extension (∼4° eastward for the multimodel mean) of MJO teleconnections in the North Pacific. Other projected changes in MJO teleconnections include a northward extension, more consistent patterns between different MJO events, stronger amplitude, and shorter persistence; however, these changes are more uncertain and less significant with a large intra- and intermodel spread. Mechanisms of the eastward teleconnection extension are investigated by comparing impacts of the future MJO and basic state changes on the anomalous Rossby wave source (RWS) and teleconnection pathways with a linear baroclinic model (LBM). The eastward extended jet in the future plays a more important role than the eastward-extended MJO in influencing the east–west position of MJO teleconnections. It leads to more eastward teleconnection propagation along the jet due to the eastward extension of turning latitudes before they propagate into North America. MJO teleconnections thus are positioned 2.9° more eastward in the North Pacific in the LBM. The eastward extended MJO, on the other hand, helps to generate a more eastward-extended RWS. However, negligible change is found in the east–west position of MJO teleconnections (only 0.3° more eastward in the LBM) excited from this RWS without the jet impacts. The above results suggest the dominant role of the jet change in influencing future MJO teleconnection position by altering their propagation pathways.

Landslide Susceptibility Mapping Using Machine Learning: A Danish Case Study

Mapping of landslides, conducted in 2021 by the Geological Survey of Denmark and Greenland (GEUS), revealed 3202 landslides in Denmark, indicating that they might pose a bigger problem than previously acknowledged. Moreover, the changing climate is assumed to have an impact on landslide occurrences in the future. The aim of this study is to conduct the first landslide susceptibility mapping (LSM) in Denmark, reducing the geographical bias existing in LSM studies, and to identify areas prone to landslides in the future following representative concentration pathway RCP8.5, based on a set of explanatory variables in an area of interest located around Vejle Fjord, Jutland, Denmark. A subset from the landslide inventory provided by GEUS is used as ground truth data. Three well-established machine learning (ML) algorithms—Random Forest, Support Vector Machine, and Logistic Regression—were trained to classify the data samples as landslide or non-landslide, treating the ML task as a binary classification and expressing the results in the form of a probability in order to produce susceptibility maps. The classification results were validated through the test data and through an external data set for an area located outside of the region of interest. While the high predictive performance varied slightly among the three models on the test data, the LR and SVM demonstrated inferior accuracy outside of the study area. The results show that the RF model has robustness and potential for applicability in landslide susceptibility mapping in low-lying landscapes of Denmark in the present. The conducted mapping can become a step forward towards planning for mitigative and protective measures in landslide-prone areas in Denmark, providing policy-makers with necessary decision support. However, the map of the future climate change scenario shows the reduction of the susceptible areas, raising the question of the choice of the climate models and variables in the analysis.

Climate Change, Climate Action and Cultural Heritage Collections in Australia

ABSTRACT The Australian Institute for the Conservation of Cultural Material has published a range of resources that promote environmentally aware collection care and management practices including climate-specific Environmental Guidelines, the Sustainable Collections wiki and the Climate Adaptation resource. The Climate Adaptation resource provides access to 180 maps illustrating potential future climate scenarios for Australia in 2030 and 2090, using the two Representative Concentration Pathways RCP4.5 and RCP8.5. These maps were produced as part of research undertaken in 2019–2020 by Pagliarino and Meredith and supplement those published in volume 41 (issue 1) of the AICCM Bulletin. The release of updated climate change projections in the Sixth Assessment Report from the Intergovernmental Panel on Climate Change (IPCC) – Climate Change 2021: The Physical Science Basis – precipitated a review of the Climate Adaptation resource to confirm the continued veracity of the maps. This paper provides the results of that assessment, which confirmed the resource’s ongoing accuracy and currency. In addition, the paper includes discussion of the new IPCC future climate scenarios of Shared Socioeconomic Pathways, which supersede RCP, and a summary of the state of the climate in Australia with warming, humidity, fire, weather and sea level rise investigated in more detail.