ALBERT

Description: Starting in 2016, the Taroko Earth Surface Observatory (TESO), a catchment-wide geomorphic observatory was set up in the Liwu catchment in the Taroko National Park in Taiwan. The set up consists of two basic station types: combined seismic and weather stations, featuring a broadband seismometer logging and a multi-parameter weather sensor, and hydrometric stations, the instrumentation of which are specific at each location. Seismic data hosted by the GEOFON database is openly accessible in real time.

Description: A line of 6 broadband seismometers have been deployed across a ridge in the Hualien County (Eastern Taiwan). From March 2015 to June 2016 the network has been continuously recording waves incoming from the Taiwanese regional seismicity. During that period, more than 2000 earthquakes with magnitudes Ml〉3 and distant from less than 200km were recorded. The hill is well approximated by a triangular topography of 3600m in length by 900m in height. Waveform data are open and available from the GEOFON data centre, under network code 5K.

Description: This dataset was used to analyse the link between chemical weathering and erosion rates across the southern tip of Taiwan. The weathering of silicate minerals is a key component of Earth’s long-term carbon cycle, and it stabilises Earth’s climate by sequestering carbon dioxide (CO2) from the atmosphere – thereby balancing CO2-emissions from the mantle. Conversely, the weathering of accessory carbonate and sulphides acts as a CO2 source. Chemical weathering is fundamentally dependent on the exposure of fresh minerals by erosion. With these data we investigated the link between the exposure of rocks by erosion and the chemical weathering of silicates, carbonates, and sulphides across a landscape with a significant erosion-rate gradient and comparatively little variation in runoff and lithology. This dataset includes new major element chemistry and water isotopes of river waters collected from across the southern tip of Taiwan as well as associated topographic and lithologic data (tab 1 in the excel table). Moreover, the data include a compilation of published 10Be-derived erosion rates from a subset of the sampled rivers (tab 2 in the excel file) and available major element chemistry from hotsprings in the region (tab 3 in the excel file). Using a mixing model, we derived the cation contributions from silicate and carbonate weathering as well as from hotspring and cyclic sources. Further, we estimated the erosion rates for each sample from the compiled 10Be data and the steepness of river channels, and we estimated saturation and pH in the weathering zone. For more information please refer to the associated data description file and especially to Bufe et al. (2021).

Description: Flooding is one of the major disasters in Taiwan, significantly impacting society and the economy. Under climate change, rainfall patterns have become denser and more intense than they used to be. Under this change, more water-related disasters may happen more commonly, such as flooding due to difficulty draining the water quickly. Various research for assessing climate change's impact on flooding has been well done, relying on knowledge and technology improvement. However, the high uncertainty of climate change still needs more studies to understand. Data quality has been critical for climate change modeling and impact assessment research. Few observation data usually cause significant uncertainty for future climate prediction. Nowadays, simulation climate datasets have been widely accepted for understanding the impact of climate change in various research. Taiwan still lacks a robust climate database for future climate research. Database for Policy Decision-Making for Future Climate Change (d4PDF) has proved to have high applicability on Taiwan catchments by Chang et al. However, the application of d4PDF has not been used in practical research. This research demonstrates the application of d4PDF in Taiwan on future flooding assessment. The results illustrate the inundation area under the interaction of pluvial and fluvial floods using 3000 years of d4PDF historical simulation data in southwest Taiwan. Also, demonstrate the inundation change under the climate condition of a +4K temperature increase. Moreover, based on the simulation results, we assess the potential economic loss change due to the shifting inundation area, providing more precise and comprehensive flooding control works.

Description: Global water models (GWMs) simulate the terrestrial water cycle, on the global scale, and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modeling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how state-of-the-art GWMs are designed. We analyze water storage compartments, water flows, and human water use sectors included in 16 GWMs that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to further enhance model improvement, intercomparison, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Seven models used six compartments, while three models (JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPI-HM) simulate only water used by humans for the irrigation sector. We conclude that even though hydrologic processes are often based on similar equations, in the end, these equations have been adjusted or have used different values for specific parameters or specific variables. Our results highlight that the predictive uncertainty of GWMs can be reduced through improvements of the existing hydrologic processes, implementation of new processes in the models, and high-quality input data.

Description: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is 〉 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge 〉 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

Description: The terrestrial carbon sink provides a critical negative feedback to climate warming, yet large uncertainty exists on its long-term dynamics. Here we combined terrestrial biosphere models (TBMs) and climate projections, together with climate-specific land use change, to investigate both the trend and interannual variability (IAV) of the terrestrial carbon sink from 1986 to 2099 under two representative concentration pathways RCP2.6 and RCP6.0. The results reveal a saturation of the terrestrial carbon sink by the end of this century under RCP6.0 due to warming and declined CO2 effects. Compared to 1986-2005 (0.96±0.44 Pg C yr-1), during 2080-2099 the terrestrial carbon sink would decrease to 0.60±0.71 Pg C yr-1 but increase to 3.36±0.77 Pg C yr-1, respectively, under RCP2.6 and RCP6.0. The carbon sink caused by CO2, land use change and climate change during 2080-2099 is -0.08±0.11 Pg C yr-1, 0.44±0.05 Pg C yr-1, and 0.24±0.70 Pg C yr-1 under RCP2.6, and 4.61±0.17 Pg C yr-1, 0.22±0.07 Pg C yr-1, and -1.47±0.72 Pg C yr-1 under RCP6.0. In addition, the carbon sink IAV shows stronger variance under RCP6.0 than RCP2.6. Under RCP2.6, temperature shows higher correlation with the carbon sink IAV than precipitation in most time, which however is the opposite under RCP6.0. These results suggest that the role of terrestrial carbon sink in curbing climate warming would be weakened in a no-mitigation world in future, and active mitigation efforts are required as assumed under RCP2.6.

Description: This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Description: Drought risk threatens pastoralism in rangelands, which are already under strain from climatic and socioeconomic changes. We examine the future drought risk (2031–2060 and 2071–2100) to rangeland productivity across Eurasia (West, Central, and East Asia) using a well-tested process-based ecosystem model and projections of five climate models under three shared socioeconomic pathway (SSP) scenarios of low (SSP1−2.6), medium (SSP3−7.0), and high (SSP5−8.5) warming relative to 1985–2014. We employ a probabilistic approach, with risk defined as the expected productivity loss induced by the probability of hazardous droughts (determined by a precipitation-based index) and vulnerability (the response of rangeland productivity to hazardous droughts). Drought risk and vulnerability are projected to increase in magnitude and area across Eurasian rangelands, with greater increases in 2071–2100 under the medium and high warming scenarios than in 2031–2060. Increasing risk in West Asia is caused by longer and more intense droughts and vulnerability, whereas higher risk in Central and East Asia is mainly associated with increased vulnerability, indicating overall risk is higher where vulnerability increases. These findings suggest that future droughts may exacerbate livestock feed shortages and negatively impact pastoralism. The results have practical implications for rangeland management that should be adapted to the ecological and socioeconomic contexts of the different countries in the region. Existing traditional ecological knowledge can be promoted to adapt to drought risk and embedded in a wider set of adaptation measures involving management improvements, social transformations, capacity building, and policy reforms addressing multiple stakeholders.

Description: Global hydrological models (GHMs) are widely used to assess the impact of climate change on streamflow, floods, and hydrological droughts. For the 'model evaluation and impact attribution' part of the current round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a), modelling teams generated historical simulations based on observed climate and direct human forcings with updated model versions. Here we provide a comprehensive evaluation of daily and maximum annual discharge based on ISIMIP3a simulations from nine GHMs by comparing the simulations to observational data from 644 river gauge stations. We also assess low flows and the effects of different river routing schemes. We find that models can reproduce variability in daily and maximum annual discharge, but tend to overestimate both quantities, as well as low flows. Models perform better at stations in wetter areas and at lower elevations. Discharge routed with the river routing model CaMa-Flood can improve the performance of some models, but for others, variability is overestimated, leading to reduced model performance. This study indicates that areas for future model development include improving the simulation of processes in arid regions and cold dynamics at high elevations. We further suggest that studies attributing observed changes in discharge to historical climate change using the current model ensemble will be most meaningful in humid areas, at low elevations, and in places with a regular seasonal discharge as these are the regions where the underlying dynamics seem to be best represented.