Mean annual temperature and total annual precipitation trends at Canadian biosphere reserves

Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques

Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical information for improved water resource planning. However, the spatiotemporal changing behavior of rainfall is much less understood in a tropical monsoon-dominated country like Bangladesh. To this end, this research aims to analyze spatiotemporal variations in rainfall for the period 1980-2020 over Bangladesh at seasonal and monthly scales using MAKESENS, the Pettitt test, and innovative trend analysis. Multilayer Perception (MLP) neural network was used to predict the next 8 years' rainfall changes nationally in Bangladesh. To investigate the spatial pattern of rainfall trends, the inverse distance weighting model was adopted within the ArcGIS environment. Results show that mean annual rainfall is 2432.6 mm, of which 57.6% was recorded from July to August. The Mann-Kendall trend test reveals that 77% of stations are declining, and 23% have a rising trend in the monthly rainfall. More than 80% of stations face a declining trend from November to March and August. There is a declining trend for seasonal rainfall at 82% of stations during the pre-monsoon, 75% during the monsoon, and 100% during the post-monsoon. A significant decline trend was identified in the north-center during the pre-monsoon, the northern part during the monsoon, and the southern and northwestern portions during the post-monsoon season. Predicted rainfall by MLP till 2030 suggests that there will be little rain from November to February, and the maximum fluctuating rainfall will occur in 2025 and 2027-2029. The ECMWF ERA5 reanalysis data findings suggested that changing rainfall patterns in Bangladesh may have been driven by rising or reducing convective precipitation rates, low cloud cover, and inadequate vertically integrated moisture divergence. Given the shortage of water resources and the anticipated rise in water demand, the study's findings have some implications for managing water resources in Bangladesh.

Ten years of pluviometric analyses in Italy for civil protection purposes

The concept of climate change has grown in recent decades, influencing the scientific community to conduct research on meteorological parameters and their variabilities. Research on global warming, as well as on its possible economic and environmental consequences, has spread over the last 20 years. Diffused changes in trends have been stated by several authors throughout the world, with different developments observed depending on the continent. Following a period of approximately 40 days of almost continuous rain that occurred from October to November 2019 across the Italian territory and caused several hazards (e.g., floods and landslides), a relevant question for decision-makers and civil protection actors emerged regarding the relative frequencies of given rainfall events in the Warning Hazard Zones (WHZs) of Italy. The derived products of this work could answer this question for both weather and hydrogeological operators thanks to the frequency and spatio-temporal distribution analyses conducted on 10-year daily rainfall data over the entire Italian territory. This work aspires to be an additional tool used to analyse events that have occurred, providing further information for a better understanding of the probability of occurrence and distribution of future events.

Spatial Variability of Rainfall Trends in Sri Lanka from 1989 to 2019 as an Indication of Climate Change

Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.

Changes of Annual Precipitation and Probability Distributions for Different Climate Types of the World

Analysis of Spatio-temporal changes in precipitation (Pre) on the land surface of the earth was the focus of this study. Thiel-Sen median slopes and Modified Mann-Kendall (MMK) test were utilized to draw inferences. Majority of the regions were identified to show an increasing trend of annual precipitation except some of the low to mid-latitude regions in Northern hemisphere. The trends of wet-day frequency (Wet) were found in agreement with precipitation for most of the regions, but the inverse relationship was found for the subtropical regions of Northern hemisphere. These changes were examined for the world climate types based on Koppen-Gieger climate classes. Also, it was tried to find the probability distribution, which best describes the annual precipitation pattern in different climate types of the world among 21 commonly assumed probability distributions.

Assessment of recent environmental changes in New Brunswick (Canada) lakes based on paleolimnological shifts in diatom species assemblages

New Brunswick lakes are subjected to multiple environmental stressors, such as atmospheric acid deposition and climate change. In the absence of long-term environmental data, the impacts of these stressors are not well understood. Long-term effects of environmental change on diatom species assemblages were assessed in the sediments of 16 New Brunswick lakes using paleolimnological approaches. A regional trend of increasing Cyclotella stelligera Cleve & Gunrow and decreasing Aulacoseira species complex was recorded in most lakes. Detailed paleolimnological analyses of Wolfe, Cundy, and West Long lakes revealed varying degrees of species change, with assemblage shifts beginning ca. 1900 CE (common era). These species trends are not consistent with acidification. However, linear regression of mean July temperature with time for two New Brunswick historical instrumental temperature records revealed statistically significant warming over the past century. The shift from heavily silicified tychoplanktonic Aulacoseira species to small planktonic diatom species, such as C. stelligera, is consistent with paleolimnological inferences of warming trends recorded in several other lake regions of the Northern Hemisphere. These assemblage shifts are likely due to recent climate change and may be mediated by reduced ice cover and (or) increased thermal stability (decreased lake mixing) during the open water period.