The climate system responds to changes in the structure and physiology of vegetation. These changes can be induced by seasonal growing cycles, anthropogenic land cover changes (LCCs), and precipitation extremes. The extent to which vegetation changes impact the climate depends on the type of ecosystem, the season, and the intensity of perturbations from LCCs and precipitation extremes. Under the growing impacts of climate change and human modification of natural vegetation cover, understanding and monitoring the underlying biogeophysical processes through which vegetation affects the climate are central to the development and implementation of effective land use plans and mitigation measures.
In Eastern Africa (EA) the vegetation is characterized by multiple growing cycles and affected by agricultural expansion as well as recurrent and severe drought events. Nonetheless, the degrees to which vegetation changes affect the surface energy budget and land surface temperature (LST) remain uncertain. Moreover, the relative contributions of various biogeophysical mechanisms to land surface warming or cooling across biomes, seasons, and scales (regional to local) are unknown. The objective of this thesis was to analyze and quantify the climatic impacts of land changes induced by vegetation seasonal dynamics, agricultural expansion, and precipitation extremes in EA. In particular, this thesis investigated these impacts across biomes and spatio-temporal scales. To address this objective, satellite observation and meteorological data were utilized along with empirical models, observation-based metrics, and statistical methods.
The results showed that rainfall–vegetation interaction had a strong impact on LST seasonality across ecoregions and rainfall modality patterns. Furthermore, seasonal LST dynamics were largely controlled by evapotranspiration (ET) changes that offset the albedo impact on the surface radiation balance. Forest loss disturbed the LST dynamics and increased local LST consistently and notably during dry seasons, whereas during the wet season its impact was limited because of strong rainfall–vegetation interaction. Moreover, drought events affected LST anomalies; however, the impact of droughts on temperature anomalies was highly regulated by vegetation greening.
In addition, the conversion of forest to cropland generated the highest net warming (1.3 K) compared with other conversion types (savanna, shrubland, grassland, and cropland). Warming from the reduction of ET and surface roughness was up to ~10 times stronger than the cooling effect from albedo increases (−0.12 K). Furthermore, large scale analysis revealed a comparable warming magnitude during bushland-to-cropland conversion associated with the dominant impact of latent heat (LE) flux reduction, which outweighed the albedo effect by up to ~5 times. A similar mechanism dominated the surface feedback during precipitation extremes; where LE flux anomalies dominated the energy exchange causing the strongest LST anomaly in grassland, followed by savanna. By contrast, the impact was negligible in forest ecosystems.
In conclusion, the results of this thesis clarify the mechanics and magnitude of the impacts of vegetation dynamics on LST across biomes and seasons. These results are crucial for guiding land use planning and climate change mitigation efforts in EA. The methods and results of this thesis can assist in the development of ecosystem-based mitigation strategies that are tailored to EA biomes. Moreover, they can be used for assessing the performance of climate models and observation-based global scale studies that focus on the biogeophysical impacts of LCCs.

Keywords: LST seasonality; Land cover change; Bushland (Acacia-Commiphora); Biophysical effects; Precipitation extremes; Satellite observation.
Original languageEnglish
Awarding Institution
  • University of Helsinki
  • Pellikka, Petri, Supervisor
  • Heiskanen, Janne, Supervisor
  • Maeda, Eduardo, Supervisor
Award date17 Apr 2020
Print ISBNs978-951-51-4928-2
Electronic ISBNs978-951-51-4929-9
Publication statusPublished - 6 Mar 2020
MoE publication typeG5 Doctoral dissertation (article)

Cite this