An analysis of a suite of climatological indices was undertaken on the basis of long-term (1979–2019) climatological data from the Polish Polar Station in Hornsund, SW Spitsbergen. It was followed by an attempt to assess the scale of their impact on the local environment. The temperature and precipitation indices were based on percentiles of the variables calculated for a population of daily values from the climate normals for 1981–2010. A greater share of both cyclonic and anticyclonic circulations from the S and SW sectors, forcing the advection of warm air masses from the south, was decisive for the trends of change in comparison with the long-term mean. Both extreme precipitation and drought events depend on the 500 hPa geopotential height and precipitable water anomalies, determined by the baric field over the North Atlantic. Climate changes impact on the dynamics of local geoecosystems by causing faster glacier ablation and retreat, permafrost degradation, intensification of the hydrological cycle in glaciated and unglaciated catchments, and changes in the condition and growth of tundra vegetation.

Ethiopia has lost sizable forest resources due to rapid population growth and subsequent increase in the demand for agricultural land and fuel woods. In this study, GIS and remote sensing techniques were used to detect forest cover changes in relation to climate variability in the Kafa zone, southwest Ethiopia. Landsat Thematic Mapper (TM) images of 1986 and 1990, Enhanced Thematic Mapper plus (ETM+) image of 2010 and Landsat-8 Operational Land Imager (OLI-8) image of 2018 were acquired at a resolution of 30 m to investigate spatial-temporal forest cover and land use changes. A supervised image classification was made using a maximum likelihood method in ERDAS imagine V9.2 to identify the various land use and land cover classes. Both spectral (normalised difference vegetation index – NDVI) and post classification change detection methods were used to determine the forest cover changes. To examine the extent and rate of forest cover changes, post classification comparisons were made using ArcGIS V 10.4.1. A net forest cover change of 1168.65 ha (12%) was detected during the study period from 1986 to 2018. The drop in the NDVI from 0.06–0.64 in 1986 to (–0.08)–0.12 in 2018 indicated a marked forest cover change in the study area. The correlation of NDVI values with climate data indicated the forest was not in a stable condition. The declining of the forest cover was most likely caused by climate variability in the study area.