Jan Rajczak

Last Name

Rajczak

First Name

Jan

ORCID

0000-0002-8893-0012

Organisational unit

01709 - Lehre Umweltsystemwissenschaften

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Publications 1 - 10 of 12

Seamless Multimodel Postprocessing for Air Temperature Forecasts in Complex Topography
Keller, Regula; Rajczak, Jan; Bhend, Jonas; et al. (2021)
Weather and Forecasting
Statistical postprocessing is applied in operational forecasting to correct systematic errors of numerical weather prediction models (NWP) and to automatically produce calibrated local forecasts for end-users. Postprocessing is particularly relevant in complex terrain, where even state-of-the-art high-resolution NWP systems cannot resolve many of the small-scale processes shaping local weather conditions. In addition, statistical postprocessing can also be used to combine forecasts from multiple NWP systems. Here we assess an ensemble model output statistics (EMOS) approach to produce seamless temperature forecasts based on a combination of short-term ensemble forecasts from a convection-permitting limited-area ensemble and a medium-range global ensemble forecasting model. We quantify the benefit of this approach compared to only postprocessing the high-resolution NWP. The multimodel EMOS approach (“mixed EMOS”) is able to improve forecasts by 30% with respect to direct model output from the high-resolution NWP. A detailed evaluation of mixed EMOS reveals that it outperforms either one of the single-model EMOS versions by 8%–12%. Temperature forecasts at valley locations profit in particular from the model combination. All forecast variants perform worst in winter (DJF); however, calibration and model combination improves forecast quality substantially. In addition to increasing skill as compared to single-model postprocessing, it also enables us to seamlessly combine multiple forecast sources with different time horizons (and horizontal resolutions) and thereby consolidates short-term to medium-range forecasting time horizons in one product without any user-relevant discontinuity. © 2021 American Meteorological Society
Systematic investigation of gridding-related scaling effects on annual statistics of daily temperature and precipitation maxima: A case study for south-east Australia
Avila, Francia B.; Dong, Siyan; Menang, Kaah P.; et al. (2015)
Weather and Climate Extremes
Using daily station observations over the period 1951–2013 in a region of south-east Australia, we systematically compare how the horizontal resolution, interpolation method and order of operation in generating gridded data sets affect estimates of annual extreme indices of temperature and precipitation maxima (hottest and wettest days). Three interpolation methods (natural neighbors, cubic spline and angular distance weighting) are used to calculate grids at five different horizontal gridded resolutions ranging from 0.25° to 2.5°. In each case the order of operation in which the grid values of the hottest and wettest day are calculated is varied: either they are estimated from daily grids or from station points and then gridded. We find that the grid resolution-despite showing more regional detail at high resolution – has relatively limited effect when considering regional averages. However, the interpolation method and the order of operation can substantially influence the actual gridded values. And while the difference due to the order of operation is not substantial when using natural neighbor and cubic spline interpolation, it is particularly apparent for indices calculated from daily gridded estimates using the angular distance weighting method. As expected given the high spatial variability of precipitation fields, precipitation extremes are most sensitive to method, but temperature extremes also exhibit substantial differences. For the annual maximum values averaged over the study area, the differences may be up to 2.8 °C for temperature and 60 mm (about a factor 2) for precipitation. Differences are seen most prominently in return period estimates where a 1 in 100 year return value calculated using the angular distance weighting daily gridded method is equivalent to about a 1 in 5 year return value in most of the other methods. Despite substantial differences in the actual values of gridded extremes, analyses suggest that the impact on long-term trends and inter-annual variability is small.
Changing seasonality of moderate and extreme precipitation events in the Alps
Brönnimann, Stefan; Rajczak, Jan; Fischer, Erich M.; et al. (2018)
Natural Hazards and Earth System Sciences
The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius–Clapeyron relation, whereas weaker events or precipitation averages increase at a smaller rate than expected from the Clausius–Clapeyron relation. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present, and future. In order to make the data comparable, they are quantile mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 years and an increase of 10%–20% until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius–Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early autumn, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behaviour more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during the hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.
21st Century alpine climate change
Kotlarski, Sven; Gobiet, Andreas; Morin, Samuel; et al. (2023)
Climate Dynamics
A comprehensive assessment of twenty-first century climate change in the European Alps is presented. The analysis is based on the EURO-CORDEX regional climate model ensemble available at two grid spacings (12.5 and 50 km) and for three different greenhouse gas emission scenarios (RCPs 2.6, 4.5 and 8.5). The core simulation ensemble has been subject to a dedicated evaluation exercise carried out in the frame of the CH2018 Climate Scenarios for Switzerland. Results reveal that the entire Alpine region will face a warmer climate in the course of the twenty-first century for all emission scenarios considered. Strongest warming is projected for the summer season, for regions south of the main Alpine ridge and for the high-end RCP 8.5 scenario. Depending on the season, medium to high elevations might experience an amplified warming. Model uncertainty can be considerable, but the major warming patterns are consistent across the ensemble. For precipitation, a seasonal shift of precipitation amounts from summer to winter over most parts of the domain is projected. However, model uncertainty is high and individual simulations can show change signals of opposite sign. Daily precipitation intensity is projected to increase in all seasons and all sub-domains, while the wet-day frequency will decrease in the summer season. The projected temperature change in summer is negatively correlated with the precipitation change, i.e. simulations and/or regions with a strong seasonal mean warming typically show a stronger precipitation decrease. By contrast, a positive correlation between temperature change and precipitation change is found for winter. Among other indicators, snow cover will be strongly affected by the projected climatic changes and will be subject to a widespread decrease except for very high elevation settings. In general and for all indicators, the magnitude of the change signals increases with the assumed greenhouse gas forcing, i.e., is smallest for RCP 2.6 and largest for RCP 8.5 with RCP 4.5 being located in between. These results largely agree with previous works based on older generations of RCM ensembles but, due to the comparatively large ensemble size and the high spatial resolution, allow for a more decent assessment of inherent projection uncertainties and of spatial details of future Alpine climate change.
Projections of Heavy Precipitation Characteristics Over the Greater Alpine Region Using a Kilometer-Scale Climate Model Ensemble
Estermann, Rebekka; Rajczak, Jan; Velasquez Alvarez, Patricio; et al. (2025)
Journal of Geophysical Research: Atmospheres
This study presents a detailed analysis of the CORDEX-FPS multi-model ensemble of convection-permitting climate simulations over the greater Alpine region. These simulations cover 10-year time slices and were obtained by downscaling global climate model (GCM) projections, using regional climate models (RCMs) and kilometer-scale convection-permitting models (CPMs). Our analysis over the Alpine area agrees with previous studies in terms of projected summer precipitation changes for the end of the century, in particular regarding a decrease in mean precipitation and increases in hourly precipitation intensities. In addition, we assess projected changes over different subregions, provide analyses at monthly and seasonal basis for temporal aggregations ranging from 1 hr to 5 days, address different extreme precipitation indices, and present validation against an Alpine-scale daily precipitation data set and an hourly precipitation product based on 3 Doppler radars. The evaluation reveals that CPMs show a refinement of spatial patterns, reduce the overestimation of precipitation frequency, and better capture intense precipitation characteristics. The improvements are especially apparent on the sub-daily scale and in the summer season. Convection-Permitting Model climate projections show an increase in precipitation intensity for all seasons and across all temporal aggregations in all regions, except for the Mediterranean in summer. The projections from different CPMs qualitatively agree, despite significant differences in the GCMs circulation changes, suggesting that the increase in heavy events is primarily due to thermodynamic effects. We also present a hypothesis explaining why projections of relative changes in hourly precipitation percentiles are similar between CPMs and RCMs, despite large biases in RCMs.
User-tailored sub-selection of climate model ensemble members for impact studies
Sikorska-Senoner, Anna E.; Rajczak, Jan; Zappa, Massimiliano; et al. (2024)
Science of The Total Environment
Climate model ensembles serve as an input to all impact studies that use sector-specific models (e.g., hydrological, ecological, crop models, fire hazard) at regional or local scales. These models require regionally scaled climate information to simulate the potential environmental and socio-economic sectoral impacts of climate change. Such simulations are based on comprehensive multi-member climate ensembles derived from the bias-adjusted and downscaled global and regional climate models. Due to limited computational resources, users of climate scenarios often can only include a small number of the ensemble members in their calculations, and therefore they often select them at random. A pre-selection of meaningful, consistent and case-specific members is therefore desired by the climate data users. In this work, we aim to fill this gap and present a novel user-tailored procedure for sub-selecting ensemble members for a variety of applications. Our method is based on the ranking of the climate change signal (CCS) calculated for a set of climate indices (e.g., mean temperature or number of hot days). Based on the CCS strength, three ensemble members representing the strongest, weakest, and median CCS are selected for each application. We also demonstrate the robustness of our approach in a specific hydrological impact model framework. Providing a systematic procedure not only assists impact modelers in selecting appropriate members, but also improves the consistency and comparability of different impact studies.
Analysis of Alpine precipitation extremes using generalized extreme value theory in convection-resolving climate simulations
Ban, Nikolina; Rajczak, Jan; Schmidli, Juerg; et al. (2020)
Climate Dynamics
Percentile indices for assessing changes in heavy precipitation events
Schär, Christoph; Ban, Nikolina; Fischer, Erich M.; et al. (2016)
Climatic Change
Many climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events.
Climate Scenarios for Switzerland CH2018 – Approach and Implications
Fischer, Andreas M.; Strassmann, Kuno M.; Croci Maspoli, Mischa; et al. (2022)
Climate Services
To make sound decisions in the face of climate change, government agencies, policymakers and private stakeholders require suitable climate information on local to regional scales. In Switzerland, the development of climate change scenarios is strongly linked to the climate adaptation strategy of the Confederation. The current climate scenarios for Switzerland CH2018 - released in form of six user-oriented products - were the result of an intensive collaboration between academia and administration under the umbrella of the National Centre for Climate Services (NCCS), accounting for user needs and stakeholder dialogues from the beginning. A rigorous scientific concept ensured consistency throughout the various analysis steps of the EURO-CORDEX projections and a common procedure on how to extract robust results and deal with associated uncertainties. The main results show that Switzerland's climate will face dry summers, heavy precipitation, more hot days and snow-scarce winters. Approximately half of these changes could be alleviated by mid-century through strong global mitigation efforts. A comprehensive communication concept ensured that the results were rolled out and distilled in specific user-oriented communication measures to increase their uptake and to make them actionable. A narrative approach with four fictitious persons was used to communicate the key messages to the general public. Three years after the release, the climate scenarios have proven to be an indispensable information basis for users in climate adaptation and for downstream applications. Potential for extensions and updates has been identified since then and will shape the concept and planning of the next scenario generation in Switzerland.
Semi-automated calibration method for modelling of mountain permafrost evolution in Switzerland
Marmy, Antoine; Rajczak, Jan; Delaloye, Reynald; et al. (2016)
The Cryosphere
Permafrost is a widespread phenomenon in mountainous regions of the world such as the European Alps. Many important topics such as the future evolution of permafrost related to climate change and the detection of permafrost related to potential natural hazards sites are of major concern to our society. Numerical permafrost models are the only tools which allow for the projection of the future evolution of permafrost. Due to the complexity of the processes involved and the heterogeneity of Alpine terrain, models must be carefully calibrated, and results should be compared with observations at the site (borehole) scale. However, for large-scale applications, a site-specific model calibration for a multitude of grid points would be very time-consuming. To tackle this issue, this study presents a semi-automated calibration method using the Generalized Likelihood Uncertainty Estimation (GLUE) as implemented in a 1-D soil model (CoupModel) and applies it to six permafrost sites in the Swiss Alps. We show that this semi-automated calibration method is able to accurately reproduce the main thermal condition characteristics with some limitations at sites with unique conditions such as 3-D air or water circulation, which have to be calibrated manually. The calibration obtained was used for global and regional climate model (GCM/RCM)-based long-term climate projections under the A1B climate scenario (EU-ENSEMBLES project) specifically downscaled at each borehole site. The projection shows general permafrost degradation with thawing at 10 m, even partially reaching 20 m depth by the end of the century, but with different timing among the sites and with partly considerable uncertainties due to the spread of the applied climatic forcing.

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Jan Rajczak

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