Lars Gerlitz

Using fuzzified regression trees for statistical downscaling and regionalization of near surface temperatures in complex terrain

High mountain regions are characterized by a large climatic heterogeneity which is not sufficiently represented by state-of-the-art climate models or reanalysis products. With regard to the increasing demand for high-resolution temperature data for climate impact studies, a statistical approach is presented, which allows estimating high-resolution near-surface temperature fields in complex terrain. High-resolution free air temperatures are derived from climate model data by considering the current stratification of the atmosphere. The residuals compared with in situ observation of near-surface temperatures are subsequently analyzed using a regression tree approach with suitable large-scale atmospheric and local-scale terrain parameters as predictors. The model identifies the predominant synoptic and topographic controls for the local-scale distribution of residuals and can be used to regionalize residual fields with high spatial resolution. The disadvantage that a tree-structured model generates stepwise constant predictant values can be overcome by integrating a fuzzifying routine. A fuzzified regression tree model was applied to analyze and predict the spatial and temporal variability of topographically induced temperatures for a target area in the Central Himalayas. Large-scale atmospheric variables, derived from the ERA-Interim reanalysis, and local terrain parameters were used as potential predictors. The model sufficiently identified the main influencing factors for the temperature heterogeneity. The potential solar insolation was found to be the predominant predictor, but also, hydroclimatic large-scale variables were found to be crucial. During clear nights, the model showed a distinct elevation dependency of residuals which indicates the importance of nocturnal cold air drainage and accumulation for the local-scale temperature distribution in the highly structured target area.

Treeline Responsiveness to Climate Warming: Insights from a Krummholz Treeline in Rolwaling Himal, Nepal

At a global scale, the elevational position of natural upper treelines is determined by low temperatures during growing season. Thus, climate warming is expected to induce treelines to advance to higher elevations. Empirical studies in diverse mountain ranges, however, give evidence of both advancing alpine treelines as well as rather insignificant responses. Himalayan treeline ecotones show considerable differences in altitudinal position as well as in physiognomy and species composition. To assess the sensitivity of a near-natural treeline to climate warming at local scale, we analysed the relations between changes of growth parameters and temperature gradients along the elevational gradient in the treeline ecotone in Rolwaling valley, Nepal, by a multispecies approach. We observed species-specific transition patterns (diameter at breast height, height, tree and recruit densities) and varying degrees of abruptness of these transitions across the treeline ecotone resulting in a complex stand structure. Soil temperatures are associated with physiognomic transitions, treeline position and spatial regeneration patterns. In conclusion, treeline tree species have the potential to migrate upslope in future. Upslope migration, however, is controlled by a dense krummholz belt of Rhododendron campanulatum. Currently, the treeline is rather stable; however we found a prolific regeneration as well as signs of stand densification. Given the spatial heterogeneity of Himalayan treeline ecotones, further studies are needed to fully understand the complex conditions for the establishment and development of tree seedlings and the responsiveness of Himalayan treeline ecotones to climate change.

Climate Change and Treeline Dynamics in the Himalaya

Treelines are sensitive to changing climatic conditions, in particular to temperature increases, and the majority of global alpine treelines has shown a response to recent climate change. High temperature trends in the Himalaya suggest a treeline advance to higher elevations; it is largely unknown, however, how broader-scale climate inputs interact with local-scale factors and processes to govern treeline response patterns. This paper reviews and synthesizes the current state of knowledge regarding sensitivity and response of Himalayan treelines to climate warming, based on extensive field observations, published results in the widely scattered literature and novel data from ongoing research of the present authors.

Recent Climate Change over High Asia

Though elevated regions have generally been spotted as climate change hotspots due to amplified signal of change observed over recent decades, such evidence for the Tibetan Plateau and its neighboring regions is supported only by a sparse observational network, less representative for the high-altitude regions. Using a larger database of widely used gridded observations (CRU and UDEL) and reanalysis datasets (NCEP-CFSR, ERA-Interim, and its downscaled variant ERA-WRF) along with high-quality homogeneous station observations, we report recent changes in mainly the mean monthly near-surface air temperature and its elevation dependence, as well as changes in precipitation over the Tibetan Plateau, its neighboring mountain ranges, and the basins of major rivers originating from them. Our station-based analysis suggests a well-agreed warming over and around the Tibetan Plateau, which is more pronounced mainly during winter and spring months and generally in agreement but higher in magnitude than that of previously reported. We found a varying skillset of considered gridded and reanalysis datasets in terms of suggesting robust spatial and elevation-dependent patterns of trends and their magnitudes. The UDEL, ERA-Interim, and CRU datasets, respectively, exhibit high- to medium-level agreement with the station observations in terms of their trend magnitudes, which are generally underestimated. We found that all datasets agree with station observations as well as among each other for a strongest warming and drying in March over the northwestern region, for wet conditions in May over the southeastern Tibetan Plateau and Myanmar regions, as well as for the general warming pattern. Similarly, a strongest EDW rate per 1000 m elevation found in January is well agreed qualitatively among all datasets, except ERA-WRF. We also confirm high inter-dataset agreement for higher warming rates for highlands (above 2000 m asl) as compared to lowlands in December and January and with a mild agreement during the growing season (April–September). Except for winter months, NCEP-CFSR reanalysis largely contradicts the elevation-dependent warming signal. Our findings suggest that well-agreed likely changes in the prevailing climate will severely impact the geo-ecosystems of the High Asia and will have substantial influence on almost all dimensions of life in the region.