Long-term climate variability over monsoon Asia as revealed by some proxy sources

Studies on climate variability over the region of monsoon Asia mostly during the Quaternary, based on various sources of proxy data have been reviewed. Increasing interest to understand the processes of monsoon system over the Asian region as well as the availability of data from variety of reliable proxy sources such as, ocean sediments, ice cores and historical documents have encouraged the palaeoclimatic studies in this region. Inferences drawn from the multiproxy sources indicate good association of glacial and inter-glacial phases with over all monsoon flow. Warm and wet periods are generally characterized by strong summer monsoon, where as, weak monsoonal activities were observed during cold and dry periods. All India monsoon rainfall since early 17th century based on dendroclimatic reconstructions shows trend-less nature with large interannual variability as seen in the instrumental record of recent century. Historical evidences over this region are a potential source of information on contemporary climate change.

The Connection between Extreme Precipitation Variability over Monsoon Asia and Large-Scale Circulation Patterns

Spatial and temporal variability in precipitation has been dramatically changed due to climate variability and climate change over the global domain. Increasing in extreme precipitation events are pronounced in various regions, including monsoon Asia (MA) in recent decades. The present study evaluated precipitation variability in light of intensity, duration, and frequency with several extreme precipitation climate change indices developed by the Expert Team on Climate Change Detection Indices (ETCCDI) over the MA region. This study uses an improved version (APHRO_V1901) of the Asian Precipitation Highly Resolved Observation Data Integration Towards Evaluation of extreme events (APHRODITE-2) gridded rainfall product. Results showed that the spatial variability of the extreme precipitation climate change indices is reflected in the annual mean rainfall distribution in MA. Maximum one-day precipitation (R × 1) and precipitation contributed from extremes (R95) depict a peak in decadal mean rainfall values over topography regions. A significant positive trend in R × 1 (with a slope of 0.3 mm/yr) and precipitation greater than the 95th percentile (R95: with a slope of 0.5 mm/yr) are predominantly observed in decadal trends in regional average extreme precipitation climate change indices over MA. Maritime continental countries exhibit an inclined trend in R10, whereas central Asian arid regions show a decreasing tendency in continuous dry days (CDD). The positive trend in R95 is observed over central India, the monsoon region in China, countries that reside over the equator and some parts of Japan, and the Philippines. When comparing the influence of surface temperature (T) and total column water vapor (TCW) on precipitation climate change indices, TCW seems to be a crucial attributor to climate change indices meridional variability. The mutual correlation analysis depicts that precipitation contributed from extremes (R95) strongly correlates in terms of temporal variability with all extreme precipitation indices. Among various global circulation patterns, the prevalent conditions of sea surface temperature (SST) over the equatorial Pacific Ocean have a significant influence on decadal variability in extreme precipitation climate change indices. R10 and R95 possess a relatively significant correlation (0.86 and 0.91) with the Southern Oscillation Index. The maximum number of consecutive dry days (CDD) shows an increasing trend with a positive phase of the North Atlantic Oscillation Index.

Vernacular Knowledge, Natural Disasters, and Climate Change in Monsoon Asia

In Monsoon Asia, home to more than half of the world’s population, extreme climatic events are expected to become more frequent and intense due to climate change. Modern disaster management to date has focused on assessing the risks of natural hazards based on historical data, responding to disasters through prevention and mitigation techniques, and information campaigns, instead of vernacular knowledge cultivated in the local environment. This has led the public to a dangerous complacency about the power of technology over nature, and neglecting the possibility of “unforeseen” events. Climate change has not only made it more difficult to assess the risks of natural hazards, but has also diminished local resilience to them. However, since the adoption of the Hyogo Framework for Action in 2005, Monsoon Asia has begun multi-sectoral efforts to build local resilience to natural hazards by integrating vernacular knowledge into modern disaster management. Whereas in the past, experts and government agencies regarded the public as mere recipients of their services, they have now become acutely aware of the need to build partnerships with local communities to compensate for current technological limitations in disaster management, and to imaginatively prepare for the increasing risks of climatic contingencies. To achieve these goals, vernacular knowledge can be a useful resource, and a number of efforts have been initiated in the region to preserve such knowledge in imaginative forms to pass it on to future generations.

Special Issue on e-ASIA JRP: Development of a Landslide Monitoring and Prediction System in Monsoon Asia

This special issue summarizes some of the findings of the first half of our international joint research between Japan, Thailand, and Vietnam. This collaborative research is based on the framework of the e-ASIA Joint Research Program (e-ASIA JRP) and lasts for three years. Rainfall-induced landslides are a common disaster in many Asian countries. Our goal is to develop a practical method for landslide susceptibility mapping so that there are fewer landslide disasters in the future. The e-ASIA JRP is an international joint initiative of public funding organizations in the East Asia Summit member countries. Based on the co-funding mechanism, support for the research teams is received from the funding organizations in their respective countries. Since 2019, the Japanese, Thai, and Vietnamese teams have been supported by the Japan Science and Technology Agency (JST), the National Science and Technology Development Agency of Thailand (NSTDA), and the Ministry of Science and Technology of Vietnam (MOST), respectively. In the first half of our project, we completed the basic steps for developing the system. In this special issue, we are proud to present some of our achievements, including studies on slope failure analysis, landslide prevention works, meteorological observations, landslide monitoring, statistical or wide-area risk evaluations, mathematical models, and flash flood control. In addition to the above, we also present other valuable research achievements that related members have provided to help ensure the achievement of our goals. In total, 20 papers are published here. We believe that our comprehensive research activities will dramatically increase future landslide disaster mitigation, especially in monsoon Asia, and will strongly augment the roadmap for achieving the global Sustainable Development Goals (SDGs) as a common desire of humanity.

Rigorous Analysis of Stress-Dependent Landslide Movements with Groundwater Fluctuations Applicable to Disaster Prevention in Monsoon Asia

In this study, novel finite element approaches are proposed for numerical analysis of stress-dependent landslide movement with groundwater fluctuation by rainfall. Two new constitutive parameters that are capable of directly controlling the relationship between the apparent factor of safety and sliding velocity are incorporated into a specific material formulation used in finite element analysis for the first time. For the numerical simulation of the measured time history of the sliding displacement caused by the groundwater fluctuations, such required analytical parameters can also approximately be determined by back analysis. The proposed models are applied to a landslide field experiment on a natural slope caused by rainfall in real time in Futtsu City, Chiba Prefecture of Japan to check its applicability. The predicted and measured time histories along the horizontal direction on the upper, middle, and lower slope are compared. In addition, the deformation pattern, shear strain pattern, and possible failure mechanisms of the natural slope of such a field experiment landslide are discussed in detail based on the analysis results of the finite element method (FEM)-based numerical simulation. Moreover, the creeping landslides and possible landslide sites for further application of the proposed models are briefly discussed in the cases of Nepal and Japan as examples in Asia. It is believed that the proposed newly developed numerical models will help in understanding the secondary creep behavior of landslides triggered by extreme rainfall, and at the same time, long-term management of such landslides will be much easier in monsoon Asia. Finally, it is expected that this study will be extended for simulation of the tertiary creep behavior of landslides induced by rainfall in the near future.

Non-stationary Modeling of Extreme Precipitation over Monsoon Asia – Role of Teleconnection Time Lags

<p>Extreme precipitation events are increasing due to climate change and leading to frequent flooding and severe droughts. These events vary in both space and time and are positively correlated with the climate teleconnections representing the oscillations of the ocean-atmospheric system. However, large numbers of climate signals and the precipitation response may vary at certain time lags with each climate indices. This study identifies time lags for climate indices using cross-correlation analysis between extreme precipitation and climate indices. These time-lagged climate indices are used as a covariate to fit a non-stationary generalized extreme value (NS-GEV) model over Monsoon Asia. The best NS-GEV model among non-stationary models is selected based on Akaike information criteria (AICc). Results show that the correlation between precipitation and different climate indices is spatially non-uniform. Incorporating time lag climate indices as covariate improves the performance of the non-stationary models. This study helps in understanding the teleconnections influencing the variation of extreme precipitation in a non-stationary framework and to revise the infrastructure designs and flood risk assessment.</p>