Subsampling impact on the climate change signal over poland based on simulations from statistical and dynamical downscaling

Most impact studies using downscaled climate data as input assume that the selection of few global climate models (GCMs) representing the largest spread covers the likely range of future changes. This study shows that including more GCMs can result in a very different behavior. We tested the influence of selecting various subsets of GCMs on the climate change signal over Poland from simulations based on dynamical and empirical-statistical downscaling methods. When the climate variable is well simulated by the GCM, such as temperature, results showed that both downscaling methods agree on a warming over Poland by up to 2° or 5°C assuming intermediate or high emission scenarios, respectively, by 2071-2100. As a less robust simulated signal through GCMs, precipitation is expected to increase by up to 10% by 2071-2100 assuming the intermediate emission scenario. However, these changes are uncertain when the high emission scenario and the end of the twenty-first century are of interest. Further, an additional bootstrap test revealed an underestimation in the warming rate varying from 0.5° to more than 4°C over Poland that was found to be largely influenced by the selection of few driving GCMs instead of considering the full range of possible climate model outlooks. Furthermore, we found that differences between various combinations of small subsets from the GCM ensemble of opportunities can be as large as the climate change signal. © 2019 American Meteorological Society

CHASE-PL Climate Projection dataset over Poland - Bias adjustment of EURO-CORDEX simulations

The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Climate Projections – Gridded Daily Precipitation and Temperature dataset 5 km (CPLCP-GDPT5) consists of projected daily minimum and maximum air temperatures and precipitation totals of nine EURO-CORDEX regional climate model outputs bias corrected and downscaled to a 5 km  ×  5 km grid. Simulations of one historical period (1971–2000) and two future horizons (2021–2050 and 2071–2100) assuming two representative concentration pathways (RCP4.5 and RCP8.5) were produced. We used the quantile mapping method and corrected any systematic seasonal bias in these simulations before assessing the changes in annual and seasonal means of precipitation and temperature over Poland. Projected changes estimated from the multi-model ensemble mean showed that annual means of temperature are expected to increase steadily by 1 °C until 2021–2050 and by 2 °C until 2071–2100 assuming the RCP4.5 emission scenario. Assuming the RCP8.5 emission scenario, this can reach up to almost 4 °C by 2071–2100. Similarly to temperature, projected changes in regional annual means of precipitation are expected to increase by 6 to 10 % and by 8 to 16 % for the two future horizons and RCPs, respectively. Similarly, individual model simulations also exhibited warmer and wetter conditions on an annual scale, showing an intensification of the magnitude of the change at the end of the 21st century. The same applied for projected changes in seasonal means of temperature showing a higher winter warming rate by up to 0.5 °C compared to the other seasons. However, projected changes in seasonal means of precipitation by the individual models largely differ and are sometimes inconsistent, exhibiting spatial variations which depend on the selected season, location, future horizon, and RCP. The overall range of the 90 % confidence interval predicted by the ensemble of multi-model simulations was found to likely vary between −7 % (projected for summer assuming the RCP4.5 emission scenario) and +40 % (projected for winter assuming the RCP8.5 emission scenario) by the end of the 21st century. Finally, this high-resolution bias-corrected product can serve as a basis for climate change impact and adaptation studies for many sectors over Poland. The CPLCP-GDPT5 dataset is publicly available at https://doi.org/10.4121/uuid:e940ec1a-71a0-449e-bbe3-29217f2ba31d

Assessment of climate change and associated impact on selected sectors in Poland

The present paper offers a brief assessment of climate change and associated impact in Poland, based on selected results of the Polish–Norwegian CHASE-PL project. Impacts are examined in selected sectors, such as water resources, natural hazard risk reduction, environment, agriculture and health. Results of change detection in long time series of observed climate and climate impact variables in Poland are presented. Also, projections of climate variability and change are provided for time horizons of 2021–2050 and 2071–2100 for two emission scenarios, RCP4.5 and RCP8.5 in comparison with control period, 1971–2000. Based on climate projections, examination of future impacts on sectors is also carried out. Selected uncertainty issues relevant to observations, understanding and projections are tackled as well

Decadal solar irradiance variability in northern Europe

Shortwave (SW) radiation from the Sun is the external energy source on Earth and the fundamental input of energy into the climate system. Variations of the SW radiation and its transfer through the atmosphere can have important consequences for the living conditions on our planet. Previous studies have reported decadal to multi-decadal variations of SW irradiance at the surface of the Earth of magnitudes comparable to those of greenhouse gas forcing. The observed SW trends are known as global dimming (decreasing SW irradiance) and brightening (increasing SW irradiance). Varying amounts of atmospheric aerosols, humidity, and clouds, and interactions among these factors are likely candidates to explain the observed SW irradiance variability. Understanding the causes of SW irradiance variations is important because it is informative of the past and future of dimming and brightening: SW irradiance variations that are due to anthropogenic activity will continue to depend on the action of humans; SW irradiance variability that is associated with natural climate variability is not within our control, but can be predicted provided that the variations of the climate system are predictable and well understood. The aim of this thesis is to investigate the observed decadal variability of SW irradiance in northern Europe. The thesis consists of four papers that all concern aspects of atmospheric transfer of SW radiation through the atmosphere including the relationship between clouds and SW irradiance. Papers I–III consider the role of clouds and large scale atmospheric circulation plays for dimming and brightening in northern Europe. To this end, we develop empirical-statistical models of solar and cloud variables based on the frequency distribution of the Grosswetterlagen (GWL), a classification of European large scale metorological weather patterns. The GWL models are used to evaluate how the frequencies of cyclonic and anti-cyclonic weather patterns influence the SW radiative climate at different sites. In Bergen, Norway, a decrease of SW irradiance and concurrent increase in cloudiness is observed from the 1960s to around 1990. This cloud-induced dimming is traced to an increasing frequency of cyclones and decreasing occurrence of blocking anti-cyclonic systems. The observed large scale circulation changes influence the radiative climate in other parts of northern Europe too, but results presented in paper III indicate that other more local factors such as varying aerosol emissions may have a more dominant influence at some sites (Stockholm, Sodankyla). In the last two decades, a significant increase in SW irradiance is found at many sites in northern Europe in spring (March–April). Our model indicates that this brightening cannot be explained by observed large-scale circulation shifts and we conclude that decreasing aerosol emissions since the late 1980s may be a likely explanation. Paper IV deals with the absorption of SW radiation by clouds. It connects to the issue of dimming and brightening because the SW absorptivity of clouds influence the SW signal that satellites retrieve. Hence investigating dimming and brightening via satellite data will depend on the correct estimate of cloud absorption. This thesis provides an introduction to the factors that influence SW irradiance and their potential contribution to the observed dimming and brightening. We conclude, based on results presented in the four papers, that the relative importance of the large scale atmospheric circulation, clouds, and other factors that influence SW irradiance may vary from site to site and period to period. Therefore, a regional and local scale may be preferable to a global or continental perspective when studying the causes and effects of dimming and brightening

Shortwave absorptance in a tropical cloudy atmosphere: Reconciling calculations and observations

[1] The absorption of shortwave (SW) radiation by clouds is a topic surrounded by contradictory reports and controversy. Some studies have shown large discrepancies between observed SW absorption and absorption predicted by models, while others have found no significant difference. In this study, values of column SW absorptance obtained by combining collocated top-of-atmosphere (TOA) and surface observations at an island site in the tropical western Pacific are compared to radiative transfer model (RTM) output. To compensate for the field of view difference between satellite and surface instruments, the surface data are averaged over time. Scatterplots and statistical measures show that there is a significant discrepancy between models and observations with the RTMs apparently underestimating SW absorptance. The large variability of the absorptance computed from the observations, including negative values, suggests that the field of view mismatch between satellite and surface observations remains even after averaging of the surface data. This mismatch may contribute to the observation-model bias. In previous observational studies showing highly enhanced absorption compared to models, the slope of a linear fit to dαTOA/dT (the derivative of TOA albedo with respect to transmittance) was used to quantify cloud SW absorption, while nonlinearity of dα TOA/dT was interpreted as a sign of sampling issues. Here the models produce a steeper slope (about −0.9) than observations (−0.6 to −0.8), indicating that models predict too little cloud SW absorption. However, when the surface observations are averaged over a longer period, their slope grows steeper, and the root-mean-square difference between linear and quadratic fits to dα TOA/dT is reduced. This implies that insufficient averaging of surface data contributes to the observed SW absorption discrepancy. Reexamination of the observational data using the difference between cloud fraction estimated from satellite and surface measurements as an estimate of field of view mismatch supports this hypothesis. High measured absorptance values are shown to correspond to occasions of large field of view mismatch. When such data are excluded, the difference between the linear and quadratic fits is reduced, and the slope of the best fit line becomes steeper. We conclude that averaging surface data over 3 h or less is not always sufficient to eliminate sampling issues. However, the possibility that shortcomings of the RTMs contribute to the discrepancy in SW absorption values cannot be excluded

Source code and data for Barents climate atlas

A collection of R-scripts and data (R-binary) used for climate analysis, downscaling and presenting climate outlooks for the Barents region. These have been used to make an atlas with maps of temperature change and analysis of precipitation and storms.<br

R-markdown for NHESS-2016-229

R-markdown script for the analysis in paper NHESS-2016-229 by Benestad et al. <br

Climate change and projections for the Barents region: what is expected to change and what will stay the same?

We present an outlook for a number of climate parameters for temperature, precipitation, and storm statistics in the Barents region. Projected temperatures exhibited strongest increase over northern Fennoscandia and the high Arctic, exceeding 7 °C by 2099 for a typical ‘warm winter’ under the RCP4.5 scenario. More extreme temperatures may be expected with the RCP8.5, with an increase exceeding 18 °C in some places. The magnitude of the day-to-day variability in temperature is likely to decrease with higher temperatures. The skill of the downscaling models was moderate for the wet-day frequency for which the projections indicated both increases and decreases within the range of −5–+10% by 2099. The downscaled results for the wet-day mean precipitation was poor, but for the warming associated with RCP 4.5, it could result in wet-day mean precipitation being intensified by as much as 70% in 2099. The number of synoptic storms over the Barents Sea was found to increase with a warming in the Arctic, however, other climate parameters may not change much, such as the persistence of the temperature and precipitation. These climate change projections were derived using a new strategy for empirical-statistical downscaling, making use of principal component analysis to represent the local climate parameters and large ensembles of global climate model (GCM) simulations to provide information about the large scales. The method and analysis were validated on three different levels: (a) the representativeness of the GCMs, (b) traditional validation of the downscaling method, and (c) assessment of the ensembles of downscaled results in terms of past trends and interannual variability

A simple equation to study changes in rainfall statistics

We test an equation for the probability of heavy 24 h precipitation amounts Pr ( X  >  x ) as a function of the wet-day frequency and the wet-day mean precipitation. The expression was evaluated against 9817 daily rain gauge records world-wide and was subsequently used to derive mathematical expressions for different rainfall statistics in terms of the wet-day frequency and the wet-day mean precipitation. This framework comprised expressions for probabilities, mean, variance, and return-values. We differentiated these statistics with respect to time and compared them to trends in number of rainy days and the mean rainfall intensity based on 1875 rain gauge records with more than 50 years of valid data over the period 1961–2018. The results indicate that there has been a general increase in the probability of precipitation exceeding 50 mm/day. The main cause for this increase has been a boost in the intensity of the rain, but there were also some cases where it has been due to more rainy days. In some limited regions there has also been an increase in Pr ( X  > 50 mm/day) that coincided with a decrease in the number of rainy days. We also found a general increasing trend in the variance and the 10-year return-value over 1961–2018 due to increasing wet-day frequency and wet-day mean precipitation