Scientific knowledge and knowledge needs in climate adaptation policy: a case study of diverse mountain regions

Mountain ecosystems around the world are recognized to be among the most vulnerable to the impacts of climate change. The need to develop sound adaptation strategies in these areas is growing. Knowledge from the natural sciences has an important role to play in the development of adaptation strategies. However, the extent of and gaps in such knowledge have not been systematically investigated for mountain areas. This paper analyzes the status of knowledge from natural science disciplines and research needs relevant to the national and subnational climate adaptation policies of 1 US state (Washington) and 7 countries (Austria, Bhutan, Colombia, Germany, Nepal, Peru, and Switzerland), in particular the elements of those policies focused on mountain areas. In addition, we asked key individuals involved in drafting those policies to answer a short questionnaire. We found that research needs mainly concern impact and vulnerability assessments at regional and local levels, integrated assessments, and improved climate and socioeconomic data. These needs are often related to the challenges to data coverage and model performance in mountainous areas. In these areas, the base data are often riddled with gaps and uncertainties, making it particularly difficult to formulate adaptation strategies. In countries where data coverage is less of an issue, there is a tendency to explore quantitative forms of impact and vulnerability assessments. We highlight how the knowledge embedded in natural science disciplines is not always useful to address complex vulnerabilities in coupled human and natural systems and briefly refer to alternative pathways to adaptation in the form of no-regret, flexible, and adaptive management solutions. Finally, in recognition of the trans- and interdisciplinary nature of climate change adaptation, we raise the question of which knowledge production paradigms are best able to deliver sustainable adaptations to growing environmental stressors in mountain regions

Robust climate scenarios for sites with sparse observations: a two-step bias correction approach

Observed and projected climatic changes demand for robust assessments of climate impacts on various environmental and anthropogenic systems. Empirical-statistical downscaling (ESD) methods coupled to output from climate model projections are promising tools to assess impacts at regional to local scale. ESD methods correct for common model deficiencies in accuracy (e.g. model biases) and scale (e.g. grid vs point scale). However, most ESD methods require long observational time series at the target sites, and this often restricts robust impact assessments to a small number of sites. This paper presents a method to generate robust climate model based scenarios for target sites with short and (or) sparse observational data coverage. The approach is based on the well-established quantile mapping method and incorporates two major steps: (1) climate model bias correction to the most representative station with long-term measurements and (2) spatial transfer of bias-corrected model data to represent target site characteristics. Both steps are carried out using the quantile mapping technique. The resulting output can serve as end user–tailored input for climate impact models. The method allows for multivariate and multi-model ensemble scenarios and additionally enables to approximately reconstruct data for non-measured periods. The method's applicability is validated using (1) long-term weather stations across the topographically and climatologically complex territory of Switzerland and (2) sparse data sets from Swiss permafrost research sites located in challenging conditions at high altitudes. It is shown that the two-step approach performs well and offers attractive quality, even for extreme target locations. Uncertainties, however, remain and primarily depend on (1) data availability and (2) the considered variable. The two-step approach itself involves large uncertainties when applied to short reference data sets or spatially heterogeneous variables (e.g. precipitation, wind speed). For temperature, results are promising even when using very short calibration periods

Permafrost model sensitivity to seasonal climatic changes and extreme events in mountainous regions

Climate models project considerable ranges and uncertainties in future climatic changes. To assess the potential impacts of climatic changes on mountain permafrost within these ranges of uncertainty, this study presents a sensitivity analysis using a permafrost process model combined with climate input based on delta-change approaches. Delta values comprise a multitude of coupled air temperature and precipitation changes to analyse long-term, seasonal and seasonal extreme changes on a typical low-ice content mountain permafrost location in the Swiss Alps. The results show that seasonal changes in autumn (SON) have the largest impact on the near-surface permafrost thermal regime in the model, and lowest impacts in winter (DJF). For most of the variability, snow cover duration and timing are the most important factors, whereas maximum snow height only plays a secondary role unless maximum snow heights are very small. At least for the low-ice content site of this study, extreme events have only short-term effects and have less impact on permafrost than long-term air temperature trends

Influence of different digital terrain models (DTMs)on alpine permafrost modeling

The thawing of alpine permafrost due to changes in atmospheric conditions can have a severe impact, e.g., on the stability of rock walls. The energy balance model, PERMEBAL, was developed in order to simulate the changes and distribution of ground surface temperature (GST) in complex high-mountain topography. In such environments, the occurrence of permafrost depends greatly on the topography, and thus, the digital terrain model (DTM) is an important input of PERMEBAL. This study investigates the influence of the DTM on the modeling of the GST. For this purpose, PERMEBAL was run with six different DTMs. Five of the six DTMs are based on the same base data, but were generated using different interpolators. To ensure that only the topographic effect on the GST is calculated, the snow module was turned off and uniform conditions were assumed for the whole test area. The analyses showed that the majority of the deviations between the different model outputs related to a reference DTM had only small differences of up to 1 K, and only a few pixels deviated more than 1 K. However, we also observed that the use of different interpolators for the generation of a DTM can result in large deviations of the model output. These deviations were mainly found at topographically complex locations such as ridges and foot of slope

Towards improved understanding of cascading and interconnected risks from concurrent weather extremes: Analysis of historical heat and drought extreme events

Weather extremes can affect many different assets, sectors and systems of the human environment, including human security, health and well-being. Weather extremes that compound, such as heat and drought, and their interconnected risks are complex, difficult to understand and thus a challenge for risk analysis and management, because (in intertwined systems) impacts can propagate through multiple sectors. In a warming climate, extreme concurrent heat and drought events are expected to increase in frequency, intensity and duration, posing growing risks to societies. To gain a better understanding of compound extremes and associated risks, we analyze eight historical heat and drought extreme events in Europe, Africa and Australia. We investigated and visualized the direct and indirect impact paths through different sectors and systems together with the impacts of response and adaptation measures. We found the most important cascading processes and interlinkages centered around the health, energy and agriculture and food production sectors. The key cascades result in impacts on the economy, the state and public services and ultimately also on society and culture. Our analysis shows that cascading impacts can propagate through numerous sectors with far reaching consequences, potentially being able to destabilize entire socio-economic systems. We emphasize that the future challenge in research on and adaptation to concurrent extreme events lies in the integration of assets, sectors and systems with strong interlinkages to other sectors and with a large potential for cascading impacts, but for which we cannot resort to historical experiences. Integrating approaches to deal with concurrent extreme events should furthermore consider the effects of possible response and adaptation mechanisms to increase system resilience

Future trends in compound concurrent heat extremes in Swiss cities - An assessment considering deep uncertainty and climate adaptation options

The interaction of multiple hazards across various spatial and temporal scales typically causes compound climate and extreme weather events. Compound concurrent hot day and night (CCHDNs) extremes that combine daytime and nighttime heat are of greater concern for health than individual hot days (HDs) or hot nights (HNs), even though their frequency is lower. We utilize a bottom-up exploratory approach to investigate how adaptation options and various unfolding future scenarios alleviate the impacts of the heatwaves and affect the frequency and intensity of CCHDNs. We use climate observations (1981–2020) and Switzerland's future climate model scenarios (CH2018) to analyze historical and future trends of the individual hot day followed by a hot night (HDNs, first metric), and the length and frequency of CCHDNs (second and third metrics) in the near-future (2020–2050) and far-future (2070–2100). Results show more frequent and lengthier HDNs in cities under all emission scenarios, notably significant under high emissions scenarios. The highest increase of HDNs occur in i) Lugano with 65.8 days (decade−1) in the historical period and 110 (371) days (decade−1) in near-future (far-future), ii) Geneva with historical 48 days (decade−1) to 108 (362) (decade−1), iii) Basel with 48–74 (217) days in the future, followed by iv) Bern with 15–44 (213) days and v) Zürich with 14–50 (217) days (decade−1) in the near-future and far-future, respectively. We consistently project that the CCHDNs in April–October become more likely and intense in all cities under all emission scenarios, with higher increases under the RCP8.5 scenario and after the 2050s. The frequency of compound extreme heatwaves (exceeding both historical thresholds of night and day temperatures) may increase by 3.5–7.8-fold and become 3.3–5.3-fold lengthier in all cities of Switzerland in the far-future. We find that the adaptation options targeting higher tolerance to increased minimum temperatures contribute more to reducing compound extreme events' frequency and intensity than adaptation options that address the maximum daily temperature

Glacier monitoring and capacity building: important ingredients for sustainable mountain development

Glacier observation data from major mountain regions of the world are key to improving our understanding of glacier changes: they deliver fundamental baseline information for climatological, hydrological, and hazard assessments. In many mountain ecosystems, as well as in the adjacent lowlands, glaciers play a crucial role in freshwater provision and regulation. This article first presents the state of the art on glacier monitoring and related strategies within the framework of the Global Terrestrial Network for Glaciers (GTN-G). Both in situ measurements of changes in glacier mass, volume, and length as well as remotely sensed data on glacier extents and changes over entire mountain ranges provide clear indications of climate change. Based on experiences from capacity-building activities undertaken in the Tropical Andes and Central Asia over the past years, we also review the state of the art on institutional capacity in these regions and make further recommendations for sustainable mountain development. The examples from Peru, Ecuador, Colombia, and Kyrgyzstan demonstrate that a sound understanding of measurement techniques and of the purpose of measurements is necessary for successful glacier monitoring. In addition, establishing durable institutions, capacity-building programs, and related funding is necessary to ensure that glacier monitoring is sustainable and maintained in the long term. Therefore, strengthening regional cooperation, collaborating with local scientists and institutions, and enhancing knowledge sharing and dialogue are envisaged within the GTN-G. Finally, glacier monitoring enhances the resilience of the populations that depend on water resources from glacierized mountains or that are affected by hazards related to glacier changes. We therefore suggest that glacier monitoring be included in the development of sustainable adaptation strategies in regions with glaciated mountains

Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes

We present an updated, spatially resolved estimate of 2003–2008 glacier surface elevation changes for the entire region of High Mountain Asia (HMA) from ICESat laser altimetry data. The results reveal a diverse pattern that is caused by spatially greatly varying glacier sensitivity, in particular to precipitation availability and changes. We introduce a spatially resolved zonation where ICESat samples are grouped into units of similar glacier behaviour, glacier type and topographic settings. In several regions, our new zonation reveals local differences and anomalies that have not been described previously. Glaciers in the Eastern Pamirs, Kunlun Shan and central TP were thickening by 0.1–0.7 m a−1, and the thickening anomaly has a crisp boundary in the Eastern Pamirs that continues just north of the central Karakoram. Glaciers in the south and east of the TP were thinning, with increasing rates towards southeast. We attribute the glacier thickening signal to a stepwise increase in precipitation around ∼1997–2000 on the Tibetan Plateau (TP). The precipitation change is reflected by growth of endorheic lakes in particular in the northern and eastern TP. We estimate lake volume changes through a combination of repeat lake extents from Landsat data and shoreline elevations from ICESat and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for over 1300 lakes. The rise in water volume contained in the lakes corresponds to 4–25 mm a−1, when distributed over entire catchments, for the areas where we see glacier thickening. The precipitation increase is also visible in sparse in situ measurements and MERRA-2 climate reanalysis data but less visible in ERA-Interim reanalysis data. Taking into account evaporation loss, the difference between average annual precipitation during the 1990s and 2000s suggested by these datasets is 34–100 mm a−1, depending on region, which can fully explain both lake growth and glacier thickening (Kunlun Shan) or glacier geometry changes such as thinning tongues while upper glacier areas were thickening or stable (eastern TP). The precipitation increase reflected in these glacier changes possibly extended to the northern slopes of the Tarim Basin, where glaciers were nearly in balance in 2003–2008. Along the entire Himalaya, glaciers on the first orographic ridge, which are exposed to abundant precipitation, were thinning less than glaciers in the dryer climate of the inner ranges. Thinning rates in the Tien Shan vary spatially but are rather stronger than in other parts of HMA

Re-analysis of seasonal mass balance at Abramov glacier 1968–2014

Abramov glacier, located in the Pamir Alay, Kyrgyzstan, is a reference glacier within the Global Terrestrial Network for Glaciers. Long-term glaciological measurements exist from 1968 to 1998 and a mass-balance monitoring programme was re-established in 2011. In this study we re-analyse existing mass-balance data and use a spatially distributed mass-balance model to provide continuous seasonal time series of glacier mass balance covering the period 1968–2014. The model is calibrated to seasonal mass-balance surveys and then applied to the period with no measurements. Validation and recalibration is carried out using snowline observations derived from satellite imagery and, after 2011, also from automatic terrestrial camera images. We combine direct measurements, remote observations and modelling. The results are compared to geodetic glacier volume change over the past decade and to a ground-penetrating radar survey in the accumulation zone resolving several layers of accumulation. Previously published geodetic mass budget estimates for Abramov glacier suggest a close-to-zero mass balance for the past decade, which contradicts our results. We find a low plausibility for equilibrium conditions over the past 15 years. Instead, we suggest that the glacier's sensitivity to increased summer air temperature is decisive for the substantial mass loss during the past decade

Mass balance re-analysis of Findelengletscher, Switzerland; benefits of extensive snow accumulation measurements

A re-analysis is presented here of a 10 year mass balance series at Findelengletscher, a temperate mountain glacier in Switzerland. Calculating glacier-wide mass balance from the set of glaciological point balance observations using conventional approaches, such as the profile or contour method, resulted in significant deviations from the reference value given by the geodetic mass change over a 5 year period. This is attributed to the sparsity of observations at high elevations and to the inability of the evaluation schemes to adequately estimate accumulation in unmeasured areas. However, measurements of winter mass balance were available for large parts of the study period from snow probings and density pits. Complementary surveys by helicopter-borne ground-penetrating radar (GPR) were conducted in three consecutive years. The complete set of seasonal observations was assimilated using a distributed mass balance model. This model-based extrapolation revealed a substantial mass loss at Findelengletscher of −0.43 m w.e.a⁻¹ between 2004 and 2014, while the loss was less pronounced for its former tributary, Adlergletscher (−0.30 m w.e.a⁻¹). For both glaciers, the resulting time series were within the uncertainty bounds of the geodetic mass change. We show that the model benefited strongly from the ability to integrate seasonal observations. If no winter mass balance measurements were available and snow cover was represented by a linear precipitation gradient, the geodetic mass balance was not matched. If winter balance measurements by snow probings and snow density pits were taken into account, the model performance was substantially improved but still showed a significant bias relative to the geodetic mass change. Thus, the excellent agreement of the model-based extrapolation with the geodetic mass change was owed to an adequate representation of winter accumulation distribution by means of extensive GPR measurements