Search

This study is the first to examine vegetation change on Kilimanjaro from 2000 to 2022, using the Normalised Difference Vegetation Index (NDVI) at a spatial resolution of 250 m via the Moderate Resolution Imaging Spectrometer (MODIS). There is a long-term increase in vegetation on an annual basis, but with decreases in the long/short rains at low/high elevations. Temperature significantly influences NDVI across all elevations and seasons. Precipitation effects are more variable and often delayed, especially in the forest zone. The study explores how El Nino Southern Oscillation (ENSO) events affect NDVI differently at contrasting elevations, indicating the need for further elevation-specific remote sensing research and field data. [ABSTRACT FROM AUTHOR]

The Arctic has experienced the most rapid warming in the world in recent decades. Complex topography combines with low solar elevation to create distinct microclimates in Arctic regions, and for many applications such as ecological response and cryospheric change it is critical to obtain reliable temperature trends at the local scale. Due to lack of weather stations, satellite land surface temperature (LST) is increasingly important as a proxy for air temperature (Tair), but how accurately it can represent microclimates is unknown. For the first time, we compare 10 years (2007–2017) of Tair recorded over a dense network of 65 sites (~25 km2) around Kevo Subarctic Research Station in Finland with equivalent moderate resolution imaging spectroradiometer (MODIS) LST at 1 km resolution from MOD11A2/MYD11A2 8‐day products. We assess whether LST can pick up the extreme local gradients in air temperature (>20 °C/km) caused by cold air drainage. Although there is a high correspondence between LST and Tair anomalies on a synoptic timescale, small‐scale patterns in Tair (lapse rates, aspect contrasts) are not picked up by LST. Temperature gradients in Tair become positive (temperature inversions) in winter, and at night, but LST gradients show almost the reverse. Aspect contrasts in Tair peak in spring and autumn during the day, but LST shows biggest differences in the evening. Land cover has a large influence on LST, tundra heating up/cooling down more than birch or pine forest. The conflation between land cover and elevation means that differential land‐cover response dominates the elevational LST signal. Contrasts between Tair and LST cannot be explained by the number of stations measuring Tair in a pixel, elevation error, timing differences or the frequency of cloud cover within the 8‐day composite. Important features of the Arctic climate such as microscale cold air drainage are thus potentially obscured by land‐cover effects. Complex topography in the Arctic leads to distinct microclimates as cold air sinks into valleys creating low temperatures. We have measured air temperatures at 65 sites in the Kevo valley, Finnish Lapland, shown above, and compare with land surface temperature (LST) measured from MODIS. LST does not pick up the cold air drainage and microclimate patterns and should thus be used with caution to extrapolate temperatures and examine climate changes in areas where weather stations do not exist. [ABSTRACT FROM AUTHOR]

Mountains are globally distributed environments that provide significant societal benefits, a function that is increasingly compromised by climatic change, environmental stress, political and socioeconomic transformations, and unsustainable use of natural resources. Gaps in our understanding of these processes and their interactions limit our capacity to inform decisions, where both generalities of mountain regions (eg climate processes) and specificities (eg context-specific manifestations of climate risks) matter. The Global Network for Observations and Information on Mountain Environments (GEO-GNOME), a Group on Earth Observations initiative, aims to fill these gaps through accessible Earth Observation (EO) as well as in-situ data and information on global change drivers, conditions, and trends. A workshop convened by the Mountain Research Initiative (MRI) revised GEO-GNOME's work plan, galvanizing a network that promotes relevant monitoring of global change in mountains and is responsive to the integrated knowledge needs of policy, research, and management. [ABSTRACT FROM AUTHOR]