Japanese plum, like other temperate fruit tree species, has cultivar-specific temperature requirements during dormancy for proper flowering. Knowing the temperature requirements of this species is of increasing interest due to the great genetic variability that exists among the available Japanese plum-type cultivars, since most of them are interspecific hybrids. The reduction of winter chilling caused by climate change is threatening their cultivation in many regions. In this work, the adaptation perspectives of 21 Japanese plum-type cultivars were analyzed in two of the main plum-growing regions in Spain, Badajoz and Zaragoza, to future climate conditions. Endodormancy release for subsequent estimation of chilling and heat requirements was determined through empirical experiments conducted during dormancy at least over two years. Chill requirements were calculated using three models [chilling hours (CH), chilling units (CU) and chilling portions (CP)] and heat requirements using growing degree hours (GDH). Chilling requirements ranged 277-851 CH, 412-1,030 CU and 26-51 CP, and heat requirements ranged from 4,343 to 9,525 GDH. The potential adaption of the cultivars to future warmer conditions in both regions was assessed using climate projections under two Representative Concentration Pathways (RCP), RCP4.5 (effective reduction of greenhouse gas emissions) and RCP8.5 (continuous increase in greenhouse gas emissions), in two time horizons, from the middle to the end of 21st century, with temperature projections from 15 Global Climate Models. The probability of satisfying the estimated cultivar-specific chilling requirements in Badajoz was lower than in Zaragoza, because of the lower chill availability predicted. In this region, the cultivars analyzed herein may have limited cultivation because the predicted reduction in winter chill may result in the chilling requirements not being successfully fulfilled.

The hydrological regimes of watersheds might be drastically altered by climate change, a majority of Pakistan\'s watersheds are experiencing problems with water quality and quantity as a result precipitation changes and temperature, necessitating evaluation and alterations to management strategies. In this study, the regional water security in northern Pakistan is examined about anthropogenic climate change on runoff in the Kunhar River Basin (KRB), a typical river in northern Pakistan using Soil and Water Assessment tool (SWAT) and flow durarion curve (FDC). Nine general circulation models (GCMs) were successfully utilized following bias correction under two latest IPCC shared socioeconomic pathways (SSPs) emission scenarios. Correlation coefficients (R2), Nash-Sutcliffe efficiency coefficients (NSE), and the Percent Bias (PBIAS) are all above 0.75. The conclusions demonstrate that the SWAT model precisely simulates the runoff process in the KRB on monthly and daily timescales. For the two emission scenarios of SSP2-4.5 and SSP5-8.5, the mean annual precipitation is predicted to rise by 3.08 % and 5.86 %, respectively, compared to the 1980-2015 baseline. The forecasted rise in mean daily high temperatures is expected to range from 2.08 °C to 3.07 °C, while the anticipated increase in mean daily low temperatures is projected to fall within the range of 2.09 °C-3.39 °C, spanning the years 2020-2099. Under the two SSPs scenarios, annual runoff is estimated to increase by 5.47 % and 7.60 % due to climate change during the same period. Future socioeconomic growth will be supported by a sufficient water supply made possible by the rise in runoff. However, because of climate change, there is a greater possibility of flooding because of increases in both rainfall and runoff. As a result, flood control and development plans for KRB must consider the climate change\'s possible effects. There is a chance that the peak flow will move backwards relative to the baseline.

Climate models predict meteorological variables for outdoor spaces. Nevertheless, most people work indoors and are affected by heat indoors. We present an approach to transfer climate projections from outdoors to climate projections of indoor air temperature (Ti) and thermal comfort based on a combination of indoor sensors, artificial neural networks (ANNs), and 22 regional climate projections. Human thermal comfort and Ti measured by indoor sensors at 90 different workplaces in the Upper Rhine Valley were used as training data for ANN models predicting indoor conditions as a function of outdoor weather. Workplace-specific climate projections were modeled for the time period 2070-2099 and compared to the historical period 1970-1999 using the same ANNs, but ERA5-Land reanalysis data as input. It is shown that heat stress indoors will increase in intensity, frequency, and duration at almost all investigated workplaces. The rate of increase depends on building and room properties, the workplace purpose, and the representative concentration pathway (RCP2.6, RCP4.5, or RCP8.5). The projected increase of the mean air temperature in the summer (JJA) outdoors, by + 1.6 to + 5.1 K for the different RCPs, is higher than the increase in Ti at all 90 workplaces, which experience on average an increase of + 0.8 to + 2.5 K. The overall frequency of heat stress is higher at most workplaces than outdoors for the historical and the future period. The projected hours of indoor heat stress will increase on average by + 379 h, + 654 h, and + 1209 h under RCP2.6, RCP4.5, and RCP8.5, respectively.

Greenhouse gas (GHG) emissions from reservoirs are influenced by many factors, including the reservoir\'s morphology, watershed, and local climate. Failure to account for diversity in waterbody characteristics contributes to uncertainties in estimates of total waterbody GHG emissions and limits the ability to extrapolate patterns from one set of reservoirs to another. Hydropower reservoirs are of particular interest given recent studies that show variable - and sometimes very high - measurements and estimates of emissions. This study uses characteristics describing reservoir surface morphology and location within the watershed to identify US hydropower reservoir archetypes that represent the diversity of reservoir features relevant to GHG emissions. The majority of reservoirs are characterized by smaller watersheds, smaller surface areas, and lower elevations. Downscaled climate projections of temperature and precipitation mapped onto the archetypes show large variability in hydroclimate stresses (i.e., changes in precipitation and air temperature) within and across different reservoir types. Average air temperatures are projected to increase for all reservoirs by the end of the century, relative to historical conditions, while projected precipitation is much more variable across all archetypes. Variability in projected climate suggests that despite similar morphology-related traits, reservoirs may experience different shifts in climate, potentially resulting in a divergence in carbon processing and GHG emissions from historical conditions. Low representation in published GHG emission measurements among several reservoir archetypes (roughly 14 % of the population of hydropower reservoirs), highlights a potential limit to the generalization of current measurements and models. This multi-dimensional analysis of waterbodies and their local hydroclimate provides valuable context for the growing body of GHG accounting literature and ongoing empirical and modeling studies.

For each assessment cycle of the Intergovernmental Panel on Climate Change (IPCC), researchers in the life sciences are called upon to provide evidence to policymakers planning for a changing future. This research increasingly relies on highly technical and complex outputs from climate models. The strengths and weaknesses of these data may not be fully appreciated beyond the climate modelling community; therefore, uninformed use of raw or preprocessed climate data could lead to overconfident or spurious conclusions. We provide an accessible introduction to climate model outputs that is intended to empower the life science community to robustly address questions about human and natural systems in a changing world.

The effect of the Southern Ocean on global climate change is assessed using Earth system model projections following an idealized 1% annual rise in atmospheric CO2. For this scenario, the Southern Ocean plays a significant role in sequestering heat and anthropogenic carbon, accounting for 40% ± 5% of heat uptake and 44% ± 2% of anthropogenic carbon uptake over the global ocean (with the Southern Ocean defined as south of 36°S). This Southern Ocean fraction of global heat uptake is however less than in historical scenarios with marked hemispheric contrasts in radiative forcing. For this idealized scenario, inter-model differences in global and Southern Ocean heat uptake are strongly affected by physical feedbacks, especially cloud feedbacks over the globe and surface albedo feedbacks from sea-ice loss in high latitudes, through the top-of-the-atmosphere energy balance. The ocean carbon response is similar in most models with carbon storage increasing from rising atmospheric CO2, but weakly decreasing from climate change with competing ventilation and biological contributions over the Southern Ocean. The Southern Ocean affects a global climate metric, the transient climate response to emissions, accounting for 28% of its thermal contribution through its physical climate feedbacks and heat uptake, and so affects inter-model differences in meeting warming targets. This article is part of a discussion meeting issue \'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities\'.

The study projects climate over the Upper Indus Basin (UIB), covering geographic areas in India, Pakistan, Afghanistan, and China, under the two Representative Concentration Pathways (RCPs), viz., RCP4.5 and RCP8.5 by the late twenty-first century using the best-fit climate model validated against the climate observations from eight meteorological stations. GFDL CM3 performed better than the other five evaluated climate models in simulating the climate of the UIB. The model bias was significantly reduced by the Aerts and Droogers statistical downscaling method, and the projections overall revealed a significant increase in temperature and a slight increase in precipitation across the UIB comprising of Jhelum, Chenab, and Indus sub-basins. According to RCP4.5 and RCP8.5, the temperature and precipitation in the Jhelum are projected to increase by 3 °C and 5.2 °C and 0.8% and 3.4% respectively by the late twenty-first century. The temperature and precipitation in the Chenab are projected to increase by 3.5 °C and 4.8 °C and  8% and 8.2% respectively by the late twenty-first century under the two scenarios. The temperature and precipitation in the Indus are projected to increase by 4.8 °C and 6.5 °C and 2.6% and 8.7% respectively by the late twenty-first century under RCP4.5 and RCP8.5 scenarios. The late twenty-first century projected climate would have significant impacts on various ecosystem services and products, irrigation and socio-hydrological regimes, and various dependent livelihoods. It is therefore hoped that the high-resolution climate projections would be useful for impact assessment studies to inform policymaking for climate action in the UIB.

As an important food crop in China, changes in suitable areas for rice planting are critical to agricultural production. In this study, the maximum entropy model (MaxEnt) was utilized to pick the main climatic factors affecting single-season rice planting distribution and project the potential changes under RCP4.5 and RCP8.5 scenarios. It was clear that rice planting distribution was significantly affected by annual total precipitation, the accumulated temperature during a period in which daily temperature was ≥ 10 °C, the moisture index, total precipitation during April-September, and continuous days during the period of daily temperature ≥ 18 °C, with their contribution being 97.6%. There was a continuous decrease in the area of good and high suitability for rice planting projected from 2021-2040 to 2061-2080, with a respective value ranging from 1.49 × 106 km2 to 0.93 × 106 km2 under the RCP4.5 scenario and from 1.42 × 106 km2 to 0.66 × 106 km2 under RCP8.5 scenarios. In 2081-2100, there was a bit increase in the area of good and high suitability under the RCP4.5 scenario. The most significant increases in good and high suitability were detected in Northeast China, while obvious decreases were demonstrated in the Yangtze River Basin which might be exposed to extreme temperature threat. The spatial potential planting center was characterized by the largest planting area in 25°N-37°N and 98°E-134°E. The north boundary and center of rice cultivation arose to 53.5°N and 37.52°N, respectively. These potential distributions for single-season rice under future climate change can provide a theoretical basis for optimizing rice planting layout, improving cultivation, and adjusting variety and management systems in response to climate change.

This work aimed to evaluate changes in water balance components (precipitation, evapotranspiration, and water availability) and precipitation extremes projected under global warming levels (GWLs) of 1.5 °C and 2 °C, in Brazil. An ensemble of eight twenty-first-century projections with the Eta Regional Climate Model and their driving Global Climate Models (CanESM2, HadGEM2-ES, MIROC5, and BESM) were used. Projections of two Representative Concentration Pathway scenarios, RCP4.5 and RCP8.5, considered intermediate and high concentration, respectively, were used. The results indicate that the RCP8.5 scenario under 2 °C GWL is likely to have a higher impact on the water balance components, amplifying trends in drier conditions and increasing the number of consecutive dry days in some regions of Brazil, particularly in the North and Northeast regions. On the other hand, the projections indicate the opposite sign for the South region, with trends toward wetter conditions and significant increases in extreme rainfall. The 0.5 °C difference between the GWLs contributes to intensifying reductions (increases) from 4 to 7% in water availability, mainly in the North-Northeast (South) regions. The projected changes could have serious consequences, such as increases in the number of drought events in hydrographic regions of the Northeast region of Brazil and increases in flood events in the South of the country. The results here presented can contribute to the formulation of adaptive planning strategies aimed at ensuring Brazil\'s water security towards climate change.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s10113-023-02042-1.

Driven by climate change, marine biodiversity is undergoing a phase of rapid change that has proven to be even faster than changes observed in terrestrial ecosystems. Understanding how these changes in species composition will affect future marine life is crucial for conservation management, especially due to increasing demands for marine natural resources. Here, we analyse predictions of a multiparameter habitat suitability model covering the global projected ranges of >33,500 marine species from climate model projections under three CO2 emission scenarios (RCP2.6, RCP4.5, RCP8.5) up to the year 2100. Our results show that the core habitat area will decline for many species, resulting in a net loss of 50% of the core habitat area for almost half of all marine species in 2100 under the high-emission scenario RCP8.5. As an additional consequence of the continuing distributional reorganization of marine life, gaps around the equator will appear for 8% (RCP2.6), 24% (RCP4.5), and 88% (RCP8.5) of marine species with cross-equatorial ranges. For many more species, continuous distributional ranges will be disrupted, thus reducing effective population size. In addition, high invasion rates in higher latitudes and polar regions will lead to substantial changes in the ecosystem and food web structure, particularly regarding the introduction of new predators. Overall, our study highlights that the degree of spatial and structural reorganization of marine life with ensued consequences for ecosystem functionality and conservation efforts will critically depend on the realized greenhouse gas emission pathway.