Major wildfire seasons in recent years include the exceptional fire outbreaks in Eurasia and North America in 2017 and 2018, and in the Amazon and Australia in 2019 and 2020. These events are known to inject considerable biomass and particulate organic matter into the atmosphere, absorbing solar radiation and reflecting it to space, with the net effect of heating the atmosphere and cooling the surface. But are these effects strong enough to trigger other climate responses that are detectable in the presence of internal variability? In this work, simulations using the Community Earth System Model Version 2 (CESM2) are used to estimate the climate effects of these recent wildfires. It is found that the fires have the capability to substantially alter both the global top-of-atmosphere energy imbalance and its inter hemispheric contrast, driving changes in the large scale energy flows within the climate system. In the deep tropics, these energetic shifts are manifested in a displacement of the ITCZ away from the hemisphere in which major wildfires occur. The shift is consistent with that seen for major volcanic eruptions, in which the ITCZ shifts away from the cooled hemisphere to enhance cross equatorial transports of dry static energy and reduce inter hemispheric thermal contrasts. Interactions with ENSO are also identified and assessed.

In this study, we examined the response of crop yield (maize, rice, soybean, and wheat) in the Asian monsoon region to meteorological drought along 1981-2016. The meteorological drought index was developed based on multiple timescale SPI (Standardized Precipitation Index) using a global precipitation dataset. The crop yield response was assessed using de-trended crop yield based on the global dataset of historical yields in a 0.5 grid resolution. Monthly indices were then obtained in the harvest month of each crop to consider the crop growing period annually. Then the crop yield response to drought was estimated by Pearson correlation and linear regression analysis. Results show that crop yield anomaly is more associated with 9-month aggregation of SPI than the other time scales used in this study (1-12 months). The drought events variations explain approximately 13%, 16%, 8%, and 15% of the total available grids for maize, rice, soybean, and wheat crop, respectively, in the region (p-value < 0.05). By country, China, India, and Indonesia, the three largest crop producers account for around 77% of the total significantly affected grids in the region. Based on this historical analysis, this study implies that droughts tend to affect crop yield in this region, whose climatic conditions are strongly driven by various global phenomena (e.g., El Niño–Southern Oscillation). This study is also essential for understanding crop-drought vulnerability in the future, particularly for the Asian monsoon region.

Floods are disastrous natural hazards accused of human live losses. As a flood-prone area, Mainland Southeast Asia (MSEA) has often been hit by floods, resulting in the highest fatality in the world. Despite the destructive flood impacts, how has flood occurrence changed over the past decades, and to what extent did floods affect the MSEA are not yet clear. Using the Dartmouth Flood Observatory large flood data archive, we aim to assess the trend of flood occurrence in the MSEA in 1985–2018 and quantify the associated impacts on humans. Particularly, the contribution of tropical cyclone (TC) landfall-induced floods (TCFloods) is quantified, because of the frequent TC landfalls. Results show that (a) occurrence and maximum magnitude of floods by all causes (ALLFloods) have significantly increased (p < .01), but not for TCFloods; (b) On average, TCFloods accounted for 24.6% occurrence of ALLFloods; (c) TCFloods caused higher mortality and displacement rate than ALLFloods did. As low flood protection standards in Cambodia and Myanmar are considered a reason for high flood-induced mortalities, building higher flood protection standards should be taken as a priority for mitigating potential flood impacts. With quantifying flood occurrence and impacts, this study offers scientific understandings for better flood risk management.

We present findings to date of a multidisciplinary investigation into ecosystem-based adaptation approaches for small island developing states using as a case study Tanna Island, Vanuatu. Our multi-disciplinary approach incorporates oceanographic & coastal process modelling to understand risks of erosion and inundation, assessment of forest and coral reef ecosystem condition, social surveys of stakeholder issues, micro-economic cost benefit analysis including valuation of ecosystem service benefits, and integrated risk assessment taking into account the benefits from retaining the ecosystems and natural resources upon which the local communities depend. Working in partnership with the local communities and the Provincial Government, we have identified key risks, costed adaptation solutions, and developed a range of decision support materials and tools. While multi-disciplinary research poses many challenges, such approaches are essential to help plan for climate resilient development pathways for communities facing the multi-faceted threats driven by climate change, along with pressures from a growing modern economy and population.

The emergence of novel and disappearing climates globally is one of the most significant dimensions of climate change. The evaluation of these changes' rate may inform us about species range displacement and the evolution of novel communities in respective biomes. The Koppen-Geiger climate classification is employed to bio-climatically distribute the biomes based on temperature, precipitation, and natural vegetation sensitivity to different climatic thresholds. According to a global study, under the RCP 8.5 scenario, nearly 20% of the global land area will experience a change in its local climate by the end of this century. Thus, the classification and comparison of the past and future climate classes may reveal important information about the emergence of novel and disappearing climate. We conducted an assessment of the shifts in climatic zones in the future compared to the past over India using observational datasets and a high resolution coupled ocean-atmosphere regional model (ROM) with a 0.22 X 0.22ᵒ resolution. We also quantified the percentage change in the land area experiencing a novel or disappearing climate in each time slice as a function of mean temperature. ROM shows a promising skill in the representation of the regional climate in terms of temperature and precipitation. The climate types and the area under different climate classes are also well captured by ROM. The land area under the temperate dry winter hot summer climate class over India was decreasing, and the land area under tropical savannah climate class expanded. Our study reveals the importance of the pace of shifting climate zones that greatly influence the velocity of the climate migrants tracking climate change. The results can be utilized to reform the species conservation and climate-mitigation policies accordingly.

The study proposes the analysis of some fundamental physical quantities in the surface layer and in the soil, in the geographical domain that involves most of the Alpine region and the Po basin (delimited by the meridians 5-15° E and the parallels 43-48° N), using the UTOPIA (University of Turin model of land Processes Interaction with Atmosphere) and the CLIPS (CLImatology of the Parameters at the Surface) method. The data refer to a period of 67 years, from 1948 to 2014, and were extracted by the GLDAS database. The analysis includes the comparison by altitude, soil type and vegetation type of the components of the energy and hydrological balance (temperature, net radiation, latent heat flux, sensible heat flux, conductive heat flux in the soil, humidity, precipitation, evapotranspiration, surface runoff) and the comparison with the data of the NOAH MultiPhisics Land Surface Model. This work aims to create a climatological mapping of the soil and to confirm the validity of the UTOPIA model, with the aim of being the starting point for studies relating to potential changes in the components of surface balances, under certain future climatic conditions

Weather forecasts over mountainous terrains are challenging due to the complexities of topography that actual local-area models necessarily smooth. As complex mountainous territories represent 20% of the Earth's surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer (ABL) is crucial. We present an application of the Weather Research and Forecasting model in a truly complex mountainous terrain area located in the north-western Italian Alps, reaching the grid spacing of 0.5 km and high-vertical resolution in the ABL (20 levels below 1000 m a.g.l.). In this region, at a high-altitude plateau (Alpe Veglia 1736 m a.s.l.), a micrometeorological station is installed in September 2018, equipped to measure standard meteorological variables, turbulence and soil properties. The simulation outputs are compared with the observation of nine weather station distributed around Alpe Veglia and the observations taken at Alpe Veglia. The aim is to test the weather model resolution in complex terrain and its ability to resolve ABL phenomena, such as slope winds and katabatic flows. In complex terrain territories, a ready-to-use, reliable and high-resolution weather forecast is a need since mountainous areas are inhabited and used for business, leisure and tourism activities. Furthermore, they represent a fragile environment, subject to mass-wasting and weathering processes. For these reasons, they need a more in-depth knowledge of the atmospheric-related processes and their modelling.