Could Weather Modification Technology Mitigate the Risk of Forest Fires and Local Climate Change?

Annual and seasonal rainfall trends in the Limbang River Basin (LRB), located in the equatorial tropics of Malaysian Borneo, have been characterised through Mann-Kendall and Spearman’s Rho non-parametric tests. Rainfall from 13 rain gauge stations in the LRB for the period 1948–2016 was examined in the present study. Basic statistical analysis of rainfall in the region indicates normal distribution, low missing percentage and homogenous characteristics of precipitation. Annual and seasonal rainfall in the LRB shows spatial variation while considering different rain gauge stations. In annual rainfall, eight stations showed a decreasing trend and five stations showed an increasing trend. Rain gauge stations which showed a statistically significant increase in annual rainfall were Limbang DID (2.77 and 2.85 mm/year) and Long Napir (3.65 and 3.77 mm/year). In recognising the two annual monsoon seasons in this area, a significant increase in rainfall was noticed in Long Napir (2.79 and 2.88 mm/year) during the Southwest monsoon (SWM) period. During the Northeast monsoon (NEM), along with Long Napir (3.90 and 3.95 mm/year), Limbang DID (2.86 and 3.02 mm/year), Pandaruan (1.82 and 1.87 mm/year) and Medamit Nanga (1.93 and 2.00 mm/year) also showed a significant increase in rainfall. At the same time, a distinct trend was noticed in rainfall amounts during the inter-monsoon (IM) periods. During the first inter-monsoon month (April), seven rain gauge stations showed an increasing trend in rainfall, whereas in the second inter-monsoon month (October), nine stations showed a decreasing rainfall trend. In April, Long Napir (1.86 and 1.95 mm/year) indicated a significant increasing trend, whereas in the month of October, the rain gauge station at Ukong showed a significant decreasing trend (− 2.45 and − 2.37 mm/year). Though minor spatial changes in trend characteristics were observed among the rain gauge stations, the LRB as a whole showed a consistent increasing (significant and non-significant) trend in annual and seasonal rainfall.

Peat and forest fire have become an annual disaster and one of which is due to low rainfall. The highest insecurity of forest and peatland fires thus occurs in the dry season, where rainfall is very low, and the intensity of the sun is high. The smoke and carbon emitted result in rising air temperatures and cause global warming. Mitigation and control measures before they happen are necessary. Weather Modification Technology (WMT) serves as one of the technological solutions to control forest fires by increasing rainfall in potentially affected locations. This study aims at examining the level of effectiveness of WMT performance in mitigating forest fires in Riau Province conducted in 2020 measured by rainfall intensity, hotspots decreased, and land water level increased. We used descriptive and inferential statistical approaches using Groundwater Level (GwL) measured data as the parameter for forest and land fire mitigation. The flammable peatland indicator is when the water level is lower than 40 cm below the surface of the peatland. In addition, we also utilized rainfall, surface peat water level, and hotspots. The study was conducted in Riau Province from July 24 – October 31, 2020. The results showed that the operation of WMT increased rainfall by 19.4% compared to the historical average in the same period. Rain triggered by WMT contributed to maintaining zero hotspots with a confidence level of 80%. The regression analysis of GwL to rainfall (RF) as depicted by Gwl = - 0.66 + 0.001 RF shows a positive correlation between the two. It thus confirms that WMT can be used as a technology to mitigate forest and land fire disasters.

PurposeThe purpose of this study is to measure local climate change response capacity and identify the existing gaps between local climate change action plans and land use plans.Design/methodology/approachThis study uses content analysis method to statistically analyze 40 pioneering local jurisdictions' climate change action plans and land use plans.FindingsThe results show significant gaps in the two types of plans. Local climate change action plans have a higher quality of plan components including factual basis, targets, coordination, and communication than local land use plans. However, local land use plans have an even higher quality of policy plan components than action plans.Originality/valueThis study has extended established climate change concepts and practices by incorporating climate change considerations into the existing framework of local decision making.

This paper synthesizes pioneering work based on a comprehensive modeling suite that combines biophysical, sub-national and global economic models to assess the global and local effects of a changing climate on growth and household incomes in three countries in the Middle East and North Africa: Syria, Tunisia and Yemen. This cross country comparison is important given these countries’ location in a region that is consistently projected to be amongst the hardest hit by climate change. Results show that even under perfect climate change mitigation, the world market prices for food are projected to increase affecting the three economies differently. Higher global prices for food negatively affect most sectors of the economy in Syria, except for agriculture, which benefits from the higher prices. However, Syrian real household incomes decline, particularly those of poor rural nonfarm households. In Tunisia, higher food prices pose challenges to its poor and in Yemen, results from the DCGE model suggest that higher global prices for food will lower Yemen’s overall GDP growth, raise agricultural GDP, and decrease real household incomes. Effects on agricultural GDP vary by agroecological zone depending on the production structure in place. Local climate change impacts alone will lead to lower crop yields for all of the countries. In Syria, the agricultural sector suffers as a result of long-term declines in yields, and different agroecological zones will be affected differently. In Tunisia, local climate change shocks operate on the sector and on households through reduced crop yields. Results from the Tunisian DCGE model shows that local climate change is welfare reducing for all household groups under both GCM scenarios, however, farm households are most adversely affected by these yield reductions. Finally for Yemen, the local impacts of climate change are different under the two climate scenarios considered where under the MIROC scenario, agricultural GDP is somewhat higher compared to the baseline. Rural incomes are expected to rise due to the higher yields and the lower prices for sorghum and millet, whereas the urban households are largely unaffected because they hardly consume those commodities. Under the CSIRO scenario, positive and negative yield changes cancel each other out so agricultural GDP and incomes for all three household groups hardly change over the period of analysis compared to the baseline. Over the long-term, the adverse effects of both global and local climate change impacts are felt throughout the three countries. In Syria, combining local and global climate change effects slows GDP growth in all sectors. Rural households (both farm and nonfarm households) suffer the most from climate change, but urban households are also worse off when compared with the perfect mitigation scenario. Across Tunisia, the combined climate change effects lead to negative effects on the overall economy, the agricultural sector, and a total reduction of household incomes and in Yemen, the long-term implications of climate change (local and global) lead to a reduction in household welfare under both the MIROC and the CSIRO scenarios. Those reductions in welfare accumulate over time and rural households suffer more from climate change than urban households. However, under the MIROC scenario, farm households benefit from the increasing yields but rural nonfarm households do not and suffer both in relative and absolute terms under the MIROC and CSIRO scenarios. Given the strong global and local impacts of climate change, a diverse set of policy actions at different levels will be required to mitigate the negative socioeconomic effects. Moreover, global price increases, declining crop yields, and droughts affect different sectors and households differently, which underscores the necessity to consider a variety of mitigation and adaptation tools including global and national action plans, investments in agriculture, social protection, and disaster risk management.

Land and forest fire in 2019 adversely affected Indonesia, one of them occurred in West Kalimantan. The government has been trying to develop an early warning system that is FDRS. However, the utilization of FDRS still requires verification on fire events in the field, especially in West Kalimantan, and the study of its relationship to the distribution of hotspots and rainfall. The study aims to analyze and verify FDRS parameters in land and forest fire events in West Kalimantan in 2019 and its relationship to hotspots and rainfall. The data used in the study were FDRS data from LAPAN, climate data from meteorological observations, hotspot data from MODIS Terra-Aqua, and location of the burned area from the Ministry of Environment and Forestry for verification. The analysis method in this study used correlation analysis (r) and coefficient of determination (R2). The results showed that the parameter values of FFMC, DC, ISI, and FWI in the area of forest and land fires ranged from 48 to 89, 6 to 733, 0 to 5, 0 to 23. The FDRS parameter is strongly influenced by rainfall conditions 21 days before the fire event (\(\overline{r}\)= −0.54 to −0.66) and the number of days with light rainfall before the fire event (\(\overline{r}\) = 0.54–0.61). About 27.85% of fire events are affected by rainfall conditions 21 days before the fire event, which is the lower the accumulation of rainfall 21 days before the fire event, the potential for fire events will increase. About 28.51% of fire events are affected by the number of days with light rainfall (<20 mm/day) before the fire event; the longer of the day with rainfall <20 mm, the greater the potential for fire events. The number of hotspots (\(\overline{r}\) = 0.62–0.68) and the burned area (\(\overline{r}\) = 0.64–0.74) have possibility can increase along with the classification of parameter FDRS. The results also showed that about 70.48% of fire events could be identified based on the number of hotspots, and FWI has an excellent ability to be used as an early warning indicator of land and forest fire in West Kalimantan.KeywordsRainfallFDRSHotspotWest KalimantanLand and forest fire

This study used statistical indicators such as rainfall detection thresholds, total rainfall, and correlation coefficients to compare and evaluate the quality of satellite rainfall data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) against daily, monthly, seasonal, and annual rainfall data from four meteorological stations in Hanoi for the period 1981-2023.The evaluation results showed that the correlation between satellite rainfall data and observed rainfall data was strong on a monthly period (R > 0.8), though it decreased for annual and seasonal periods (R ranging from 0.57 to 0.8), but remained at or above a moderate level.Although the correlation for daily rainfall was low (R < 0.4), satellite rainfall did reflect rainfall phenomena with a forecast accuracy (PC) ranging from 0.65 to 0.68.Additionally, the paper evaluated rainfall trends using the Mann-Kendall test and estimated Sen's slope.The research results indicated that annual and seasonal rainfall in Hanoi is quite stable, with slight increasing trends.Within the year, August and September show a significant increase in rainfall, particularly in August, where rainfall increased by up to 1.99 mm/year and reached statistical significance ( = 0.1).The spatial variation trend of satellite rainfall in Hanoi is uniform, but the magnitude of variation differs by region.

The present investigation attempts to understand the near-term (up to 2050) and distant (up to 2100) future climatic changes over Maharashtra. Trend analysis of projected monsoon rainfall and temperature was carried out with the use of parametric and non-parametric statistical techniques. All the meteorological sub-divisions in Maharashtra reveal a significant increase in monsoon rainfall during 2015–2100 (by 150–210 mm), except Konkan. In a near-term future, parts of the Vidarbha Sub-division and Western Ghats exhibit a significant increase in rainfall by 82–225 mm. Almost the entire state is very likely to experience a rise in annual mean temperature (AMT) by 0.5–2.5 °C up to 2050. The state is very likely to experience considerably warmer conditions post-2033. In particular, parts of Konkan and Madhya Maharashtra Sub-divisions will register significant warming (by 1–2.5 °C). The estimations also signify a marginal increase in AMT during the post-2070 period. The annual maximum temperature (AMXT) does not show a considerable rise; however, the annual minimum temperature (AMNT) is expected to increase (by < 1.2 °C) significantly over about 80% of the districts in Maharashtra. These climatic changes are very likely to affect the productivity of principal crops in Maharashtra including sorghum, pearl millet, sugarcane, wheat, rice and cotton. Under the future climate change scenario, therefore, it will be a great challenge for agronomist and policymakers to formulate a judicial plan for sustainable agriculture.

ABSTRACTTropical dry forests occupy more area and are more endangered than rainforests, yet their regeneration ecology has received less study and is consequently poorly understood. We recorded the flowering and fruiting phenology of a tropical dry forest in Jamaica over a period of 26 mo within ten 15 × 15‐m plots. Community‐wide recruitment reached a maximum in the wet season, whereas no recruitment occurred during the dry season. We observed a unimodal peak in rainfall and fruit production, and the periodicity and intensity of seed production were significantly correlated with rainfall seasonality (the optimal time for germination). Flowering at the community and system levels lagged behind a significant increase and subsequent decrease in rainfall by 7 and 3 mo, respectively, indicating that the dominant factor controlling flowering periodicity is the passage of the major (4‐mo long) rainy season and changes in soil moisture conditions. Fruiting lagged behind flowering by 2 mo and a significant increase in fruiting occurred 2 mo prior to a significant increase in rainfall. At the population level, a correspondence analysis identified a major dichotomy in the patterns of flowering and fruiting between species and indicated two broad species groups based on their time of peak fruiting and the number of times they were in fruit. These were either individuals which were usually in peak fruit 1–2 mo prior to the start of the major rainy season or those that were in fruit more or less continuously throughout the year with no peak fruiting time. This study supports the view that seasonal variation in rainfall and hence soil water availability constitutes both the proximate and the ultimate cause of flowering periodicity in tropical dry forests.

Global Climate change (CC) is featured by long-term changes in the mean values of climatic parameters (predominantly mean temperature) and in the profile of extreme weather events (e.g., increase in frequency, intensity, lengthening, and persistence). These climatic changes are supposed to have a deterioration impact on forest fire and flood disasters. Greece, an east Mediterranean country, is featured by a wide variety of micro-climates due to its unique geographical diversity, including hot and dry summers in the eastern part of the country (where a large amount of precipitation falls in the form of showers and thunderstorms) and wet winters in the western part. The combination of certain climatic zones with unfavorable land use and land cover changing patterns has resulted in several regions being prone to flooding and forest fires. The authors, based on relevant records, consider central and south Greece as flood and forest fire hotspots and attempt to: (a) present scientific estimations of local climate changes; (b) outline recent trends in the number of respective disasters and the amount of losses in these regions; (c) address recent changes in local climatic factors that might have influenced flood and forest fire hazard and risk in these regions; and (d) study the perceptions of the lay public and management authorities regarding the accountability of CC for flood and forest fire risk and hazard changes. The results show the variability of climate changes between neighboring areas, which directly affect the risk of forest fires and floods. Especially since the beginning of the 21st century, central Greece has been experiencing dramatic increases in both risks, while in south Greece the latter remain relatively stable. With regard to the perceptions of citizens and management authorities, the mental connection of local CC with forest fires and floods is still weak if not totally missing. Since knowledge and perceptions of the local “history” of forest fires and floods and the interconnections with CC by region is very important for the local communities to take appropriate mitigation and adaptation measures, this paper outlines a methodological path for similar studies to be conducted also in other regions of the Mediterranean basin and beyond.

Local and seasonal climate change and its influence on the hydrological cycle in a mountainous forested catchment

Compounding food and income insecurity in Yemen: Challenges from climate change

Climate change impacts vary wildly across different geographical contexts and their effects are primarily felt on the local level, generating demand for local solutions. The local level plays a key role in the adaptation to climate change. Nevertheless, in most European countries adaptation has yet to be integrated comprehensively into local policy agendas. To further our understanding of this slow pace of local adaptation progress, we study 21 Swiss Alpine municipalities exposed to a variety of natural hazards and issues exacerbated by local climate change impacts. Building on established research on local natural hazard management and climate change adaptation, we expect four factors to play decisive roles, either on their own or in combination with each other: Past extreme events, risk exposure, perceived climate risk and existing adaptation policies at superordinate levels. We test these expectations using qualitative comparative analysis (QCA). We find that significant past extreme events and high perceived climate risk come close to being necessary conditions for local adaptation measures. High perceived climate risk on its own is also a sufficient condition for local adaptation measures to be taken while its absence is sufficient for no local adaptation measures to be taken. Thus, the importance of climate risk perception exceeds our expectation as it has clearly been revealed to be the most important factor. Future research should focus on disentangling different levels of public risk perception further and investigate the role different levels of perception or acceptance among different actor groups play in climate policy decisions.

The effect of long-term climatic variability on wild mammal populations in a tropical forest hotspot: A business intelligence framework

Abstract. Flooding is one of the most damaging natural disasters, intensified by climate change, urban development, and land-use changes. Effective flood monitoring and management are crucial to mitigating the negative impacts, especially in regions with complex hydrological dynamics. This study focuses on the Kupa River basin in Croatia, a flood-prone region, and presents an integrated approach for flood mapping and climate impact assessment using open-source Earth observation (EO) data and free tools. Combining a different remote sensing datasets; Sentinel-1 Synthetic Aperture Radar (SAR), Sentinel-2 Normalized Difference Vegetation Index (NDVI), and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation datasets, all accessed through Google Earth Engine (GEE), this research demonstrates a cost-effective and scalable solution for monitoring flood dynamics and climate change insights on a focused area. Sentinel-1 SAR, with its cloud-penetrating capabilities, is used to detect surface water changes, while Sentinel-2 through the NDVI complemented vegetation health before and after flood events. CHIRPS data, with daily precipitation estimates, contextualizes the meteorological conditions that contribute to flooding. The integration of these datasets offers a comprehensive analysis of flood events and their environmental impacts, providing actionable insights for local flood management and climate change adaptation. The use of open-access and freely available data and free tools highlights the potential for replicable flood monitoring in regions with limited infrastructure, further supporting the development of early-warning systems and informed decision-making.

Weather Modification Technology (WMT) is one of reliable solution that is often used in forest fire mitigation activity in Indonesia. Through the process of physically engineering clouds into rain and rewetting peatlands, it is hoped to help suppress hotspots and prevent forest fires from spreading. In this study, an analysis of forest fire mitigation activities in the area of Sumatra Island, Indonesia, shows that WMT can increase rainfall by up to 30% during its implementation period. WMT activity is also able to assist in suppressing the escalation of hotspots in the targeted areas. By increasing rainfall, WMT also plays a role in maintaining the wetness of peatlands, thus minimizing the potential for fire expansion. This study also explains that the role of the Indonesian Government in implementing WMT for forest fire mitigation continues to experience development.