High-resolution climate projection dataset based on CMIP6 for Peru and Ecuador: BASD-CMIP6-PE

Here, we present BASD-CMIP6-PE, a high-resolution (1d, 10 km) climate dataset for Peru and Ecuador based on the bias-adjusted and statistically downscaled CMIP6 climate projections of 10 GCMs. This dataset includes both historical simulations (1850-2014) and future projections (2015-2100) for precipitation and minimum, mean, and maximum temperature under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5). The BASD-CMIP6-PE climate data were generated using the trend-preserving Bias Adjustment and Statistical Downscaling (BASD) method. The BASD performance was evaluated using observational data and through hydrological modeling across Peruvian and Ecuadorian river basins in the historical period. Results demonstrated that BASD significantly reduced biases between CMIP6-GCM simulations and observational data, enhancing long-term statistical representations, including mean and extreme values, and seasonal patterns. Furthermore, the hydrological evaluation highlighted the appropriateness of adjusted GCM simulations for simulating streamflow, including mean, low, and high flows. These findings underscore the reliability of BASD-CMIP6-PE in assessing regional climate change impacts on agriculture, water resources, and hydrological extremes.

Anthropogenic influence on extreme temperature and precipitation in Central Asia

We investigate the contribution of anthropogenic forcing to the extreme temperature and precipitation events in Central Asia (CA) during the last 60 years. We bias-adjust and downscale two Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) ensemble outputs, with natural (labelled as hist-nat, driven only by solar and volcanic forcing) and natural plus anthropogenic forcing (labelled as hist, driven by all-forcings), to [Formula: see text] spatial resolution. Each ensemble contains six models from ISIMIP, based on the Coupled Model Inter-comparison Project phase 6 (CMIP6). The presented downscaling methodology is necessary to create a reliable climate state for regional climate impact studies. Our analysis shows a higher risk of extreme heat events (factor 4 in signal-to-noise ratio) over large parts of CA due to anthropogenic influence. Furthermore, a higher likelihood of extreme precipitation over CA, especially over Kyrgyzstan and Tajikistan, can be attributed to anthropogenic forcing (over 100[Formula: see text] changes in intensity and 20[Formula: see text] in frequency). Given that these regions show a high risk of rainfall-triggered landslides and floods during historical times, we report that human-induced climate warming can contribute to extreme precipitation events over vulnerable areas of CA. Our high-resolution data set can be used in impact studies focusing on the attribution of extreme events in CA and is freely available to the scientific community.

Cross-sectoral impacts of the 2018-2019 Central European drought and climate resilience in the German part of the Elbe River basin

The 2018-2019 Central European drought was probably the most extreme in Germany since the early sixteenth century. We assess the multiple consequences of the drought for natural systems, the economy and human health in the German part of the Elbe River basin, an area of 97,175 km² including the cities of Berlin and Hamburg and contributing about 18% to the German GDP. We employ meteorological, hydrological and socio-economic data to build a comprehensive picture of the drought severity, its multiple effects and cross-sectoral consequences in the basin. Time series of different drought indices illustrate the severity of the 2018-2019 drought and how it progressed from meteorological water deficits via soil water depletion towards low groundwater levels and river runoff, and losses in vegetation productivity. The event resulted in severe production losses in agriculture (minus 20-40% for staple crops) and forestry (especially through forced logging of damaged wood: 25.1 million tons in 2018-2020 compared to only 3.4 million tons in 2015-2017), while other economic sectors remained largely unaffected. However, there is no guarantee that this socio-economic stability will be sustained in future drought events; this is discussed in the light of 2022, another dry year holding the potential for a compound crisis. Given the increased probability for more intense and long-lasting droughts in most parts of Europe, this example of actual cross-sectoral drought impacts will be relevant for drought awareness and preparation planning in other regions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10113-023-02032-3.

User tailored results of a regional climate model ensemble to plan adaption to the changing climate in Germany

Abstract. In the German regional climate modeling project ReKliEs-De the existing EURO-CORDEX simulations have been systematically complemented by new simulations to derive more robust ranges of possible future climate change. The focus of the project lay on user tailored results, which are required for the planning of measures to adapt to the changing climate. Changes in temperature and precipitation indices are calculated from a multi model ensemble for the end of the 21st century. The results for the mitigation scenario RCP2.6 are compared to the results of the “business as usual” scenario RCP8.5. Averaged over Germany the increase of mean annual temperature and of the number of summer days will be around 3 times higher for RCP8.5 than for RCP2.6. In summer, the increase of dry days could be twice as high in RCP8.5 compared to RCP2.6.

Bias adjustment for threshold-based climate indicators

Abstract. A method is presented which applies bias adjustments to climate indicators that are based on fixed thresholds, e.g., the number of hot days with the maximum temperature exceeding 30 ∘C or the number of days with heavy precipitation in exceedance of 20 mm rainfall. The bias adjustment first identifies the percentile of the required threshold value in reference climate data. Then it computes the value of this percentile for the individual historical climate model simulations – here an ensembles of EURO-CORDEX model runs, including dynamical and statistical models. Finally, the climate indicator is re-calculated for each model. The method is applied to climate projections as well, giving further insight into the projected development of the ensemble for extreme conditions. It is assessed that communication to the public and decision makers is improved by expressing these changes in extremes based on absolute values.

Influence of diazepam and methylphenidate on identification of rapidly presented letter strings: diazepam enhances visual masking

The effect of diazepam (0, 5, 10 mg) and methylphenidate (0, 5, 10 mg) on the identification of briefly displayed letter strings composing words was investigated. Each letter was presented for 70 ms. The interstimulus interval (ISI) between two successive letters was 10, 100 or 200 ms. The length of the words (WL) was three, five, seven or nine letters. The dependent variable was the number of correctly identified words. As predicted, strong visual masking effects, the strength of which was dependent on ISI and WL, appeared. In the 10 ms condition, diazepam at both doses, but not methylphenidate, further enhanced masking. It is suggested that the results reflect the effect of GABA on masking, and support certain psychological theories about the inhibitory neuronal pathways that are involved in masking. The human peripheral visual system is a promising model for the experimental assessment and integration of pharmacodynamic, neurophysiological and psychological observations.