Tropical cyclones (TCs), the most destructive natural disasters of this century, have significantly impacted climate change in humid subtropical China. Utilizing high-resolution climate proxy indicators to study the historical activity of TCs can enhance our understanding of climate changes caused by TCs and aid in risk management. Intra-annual density fluctuations (IADFs), reflecting short-term climate events in tree rings, can capture extreme climate data related to the variability of TCs. In this study, we established a chronology of the frequency of latewood intra-annual density fluctuations (L-IADFs) of Pinus massoniana Lamb. in humid subtropical China. The frequency of L-IADFs was positively related to the sea surface temperature in the regions surrounding the South China Sea and the western Pacific from July to September, August precipitation and the Standardized Precipitation Evapotranspiration Index in 1956-2015. By combining the daily growth rates simulated by the Vaganov-Shahikin model with the measured positions of L-IADFs (54-71%) in the tree rings, it was calculated that L-IADFs occurred mainly from June to September. Linear regression of TC precipitation/total precipitation from July to September explained approximately 30% of the variance in the stable frequency of L-IADFs. Consequently, IADFs can serve as an effective climate proxy to study the impact of TC precipitation in humid subtropical China. Future research can further expand the sample area and tree species, using L-IADFs to reconstruct the history of TCs over a longer timescale, providing a scientific basis for predicting and responding to climate change.

Global preharvest crop forecasting is a field of research that has emerged since the 2010s. Such research is expected to contribute to making globally interconnected agri-food systems more climate resilient. In November 2024, the global preharvest crop forecasting system entered in its operational phase at the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC). Using the APCC multi-model ensemble (MME) temperature and precipitation forecasts as main inputs, the system provides monthly information on climate-induced changes in the yields of maize, rice, wheat, and soybean in the ongoing season, 6 to 3 mo before the harvest. This information is a key outcome of the research project jointly conducted by the National Agriculture and Food Research Organization (NARO), Japan, and APCC, Republic of Korea, for the period 2017-2023. To commemorate this milestone, this Opinion Piece briefly summarizes the global crop forecasting research done by our team and possible avenues for future research to make such forecasts more reliable and widely adopted by societies.

Researching future changes in rainfall variability is critical for mitigating the possible effects of global warming, especially in areas where vulnerability is high, such as Indochina. While changes in mean and extreme rainfall have received a great deal of attention, rainfall variability has been poorly researched, despite its importance. We endeavored to determine the anticipated changes in rainfall variability during the mainland Indochina southwest monsoon (MSWM) by utilizing data derived from 5 ensemble models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Employing band pass filtering techniques on daily rainfall data, we discerned variability across an expansive spectrum of temporal scales. Our research indicates that, in the event of global warming, the variability in MSWM rainfall is expected to increase by approximately 10-25% throughout the whole region. Notably, this increased unpredictability appears uniformly throughout a wide range of time intervals. Changes in average rainfall significantly aid in explaining the majority of the intermodal variance in the predicted MSWM rainfall variability. To gain further insight into this phenomenon, we examined the effects of elevated atmospheric moisture content through the estimation of modifications resulting from idealized local thermodynamic enhancement. We showed that increased atmospheric moisture, as suggested by the Clausius-Clapeyron relation, accounts for most of the predicted changes in rainfall variability at all time scales.

Recent scholarship argues for more research to resolve the ‘Holocene temperature conundrum’, an apparent discrepancy between decreasing proxy-reconstructed and increasing model-simulated long-term temperature trends during the late Holocene. Here, we argue that the observed proxy-model offset likely results from inappropriate comparisons of different seasonal and spatial signals in the reconstructed and simulated palaeo-data. Since proxy archives have been used to reconstruct global annual mean temperatures, they have been compared against model simulations of the same seasonal and spatial domains. However, we suggest that most of the proxy-based large-scale reconstructions are biased towards Northern Hemisphere summer temperatures, and as such model comparisons have predominantly focused on the wrong target data. Further to advancing our understanding of long-term temperature trends, we recommend prioritising the refinement of proxy networks and climate reconstructions to preserve the full spectrum of naturally forced, interannual to multi-millennial variations needed to contextualise recent anthropogenic changes against past Holocene ranges.

Information about the climate change impacts on river discharge of 2 tributary basins of the Irtysh River, the Oba and Ulbi, is important for effective management of the water resources of the Shulba reservoir in Kazakhstan. The main aim of the study was to investigate potential changes in water resource availability in the study basins. To assess the projected changes, the process-based eco-hydrological model SWIM was used under 2 Representative Concentration Pathway (RCP) climate scenarios obtained from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Our results show an increase in mean annual temperature of 6.1°C, an increase in average annual precipitation of 7.5 to 14%, an increase in annual average discharge for the Oba (6 to 8%) and smaller discharge changes (below 5%) for the Ulbi at the end of the century under RCP8.5—a scenario of comparatively high greenhouse gas emissions—compared to the reference period (1981-2010). Seasonal variations are marked by the peak discharge occurring up to a month earlier, a decrease in the duration of snow accumulation and a reduction in discharge during the summer months. The peak discharge period is prolonged in time, and a slight increase in river discharge could be expected from October to December. Possible future changes in climate may have serious impacts on water resources, agriculture and economic development in the case study basins. The results of this study can be extrapolated to other neighboring basins in Kazakhstan with similar climatic and geophysical characteristics.

We present a new, modified version of the reconnaissance drought index (RDI), named the N-RDI. To calculate the N-RDI, precipitation and potential evapotranspiration (PET) were replaced with spatially normalized precipitation and PET. To assess the capability of N-RDI, the RDI and N-RDI were computed at monthly, seasonal, and annual time scales over Iran based on a climatic data series of 12 stations from 1967-2019. Interpolated maps of the RDI, N-RDI, and annual yield of rain-fed winter wheat were then prepared using the inverse distance weighting method. Four regions in Iran (with different climate conditions) were then selected, and 30 random points were chosen in each area. Finally, the capabilities of N-RDI and RDI were compared based on the correlation coefficient (CC) between the difference in the mean rain-fed winter wheat yield (DMRWWY) and the difference in the average RDI (Da-RDI) and the average N-RDI (Da-N-RDI) at selected points, in different regions at different time scales. The CCs were higher between DMRWWY and Da-N-RDI than between DMRWWY and Da-RDI in humid (H) and semi-arid (SA) regions, in H and hyper-arid (HA), in SA and arid (A), in SA and HA, and in A and HA regions in 88.23% of selected periods. Moreover, CCs were greater between DMRWWY and Da-N-RDI than between DMRWWY and Da-RDI in H and A regions in 76.47% of selected periods. The results showed that the capability of the N-RDI for assessing drought in large basins is greater than that of the RDI.

The North Atlantic marine ecosystem has been expected to adjust imminently to a negative phase of the Atlantic Multidecadal Oscillation (AMO). Recent results suggest, however, that the AMO is not a regular internal source of variability, but has been driven by both volcanism and sulphate aerosol emissions that have influenced temperature negatively, and a period of greenhouse gas accumulation causing temperatures to be higher than normal. The demise of the AMO removes the expected and imminent cyclical change from the current warm phase to a negative cool phase in the North Atlantic. Here, we discuss the implications of this new finding for the near-future of North Atlantic marine ecosystems in a context of rapid climate warming.

Drift models are commonly used to study the transport of early life stages of fish and other marine organisms. Various approaches may be applied to examine the distribution and variability of ocean trajectory pathways. In the present study, we compare results using passive Eulerian tracers and Lagrangian float trajectories that are embedded in numerical models. We supplement this analysis by applying an offline model for drift computations. The contrasts in the results from the various configurations are mainly due to differences in drift depth. Simulations were performed using horizontal resolutions of 4 and 0.8 km. The higher-resolution experiment gives somewhat more realistic results for the drift time from Lofoten to the Tromsøflaket bank at the southwestern entrance of the Barents Sea. Furthermore, differences in results between simulation years are much larger than the differences that arise from the choice of model configuration. Climate variability at high latitudes on a multi-decadal time scale is dominated by large interannual variability superimposed on an underlying moderate warming trend. We conclude that a properly configured offline drift model using hourly or 2-hourly results from a simulation with a horizontal resolution of 1 km or finer is the best approach for investigations of trajectory pathways. The flexibility of an offline drift model is also highly advantageous in biological contexts, as it easily allows for a variety of ways in which behavioural characteristics can be parameterized, including descriptions that are defined after the ocean circulation simulation has been executed.

Over the last few decades, there have been substantial changes in sectoral anthropogenic emissions over India, modifying the region’s air quality and radiation budget. However, these sectoral contributions are still poorly understood. This study attempts to estimate the anthropogenic aerosols and SO2 emissions from different sectors over the Indian subcontinent and their implications for regional climate and human health using the RegCM4.4 regional climate model and the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) global model. We consider current emissions as well as emissions with a mitigation scenario for the year 2030. The RegCM simulations with ECLIPSE v5a as emissions inventory for 2000 and 2015 show high SO2 emissions from the energy sector, substantially contributing to anthropogenic aerosol optical depth (AODanthro) and climate forcing. The residential and transport sectors’ imprint on climate forcing is increased in 2015 compared to 2000. Higher AODanthro (0.35-0.45) occurrence days substantially decrease under a mitigation scenario by 5-10% over the Indo-Gangetic Plain. In particular, over 5�megacities (Delhi, Kolkata, Mumbai, Chennai, and Bangalore) of India, the concentrations of black carbon, organic carbon, and particulate matter ≤2.5 µm in diameter (PM2.5) are substantially reduced under the mitigation scenario; however, SO2 is increased. The reduction of pollutants contributes to significantly reducing life expectancy loss in all cities. This study advocates the need for future emission control policies with a synergy between air quality and climate change.