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Sven Kotlarski
,
Frank Paul
, and
Daniela Jacob

Abstract

A coupling interface between the regional climate model REMO and a distributed glacier mass balance model is presented in a series of two papers. The first part describes and evaluates the reanalysis-driven regional climate simulation that is used to force a mass balance model for two glaciers of the Swiss mass balance network. The detailed validation of near-surface air temperature, precipitation, and global radiation for the European Alps shows that the basic spatial and temporal patterns of all three parameters are reproduced by REMO. Compared to the Climatic Research Unit (CRU) dataset, the Alpine mean temperature is underestimated by 0.34°C. Annual precipitation shows a positive bias of 17% (30%) with respect to the uncorrected gridded ALP-IMP (CRU) dataset. A number of important and systematic model biases arise in high-elevation regions, namely, a negative temperature bias in winter, a bias of seasonal precipitation (positive or negative, depending on gridbox altitude and season), and an underestimation of springtime and overestimation of summertime global radiation. These can be expected to have a strong effect on the simulated glacier mass balance. It is recommended to account for these shortcomings by applying correction procedures before using the RCM output for subsequent mass balance modeling. Despite the obvious model deficiencies in high-elevation regions, the new interface broadens the scope of application of glacier mass balance models and will allow for a straightforward assessment of future climate change impacts.

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Tido Semmler
,
Daniela Jacob
,
K. Heinke Schlünzen
, and
Ralf Podzun

Abstract

The Arctic plays a major role in the global circulation, and its water and energy budget is not as well explored as that in other regions of the world. The aim of this study is to calculate the climatological mean water and energy fluxes depending on the season and on the North Atlantic Oscillation (NAO) through the lower, lateral, and upper boundaries of the Arctic atmosphere north of 70°N. The relevant fluxes are derived from results of the regional climate model (REMO 5.1), which is applied to the Arctic region for the time period 1979–2000. Model forcing data are a combination of 15-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-15) data and analysis data. The annual and seasonal total water and energy fluxes derived from REMO 5.1 results are very similar to the fluxes calculated from observational and reanalysis data, although there are some differences in the components. The agreement between simulated and observed total fluxes shows that these fluxes are reliable. Even if differences between high and low NAO situations occur in our simulation consistent with previous studies, these differences are mostly smaller than the large uncertainties due to a small sample size of the NAO high and low composites.

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Tido Semmler
,
Daniela Jacob
,
K. Heinke Schlünzen
, and
Ralf Podzun

Abstract

The influence of two simple descriptions for the sea ice distribution on boundary layer values is investigated by comparing model results from the regional climate model REMO with measured data in the Fram Strait in April 1999. One method for determining the sea ice distribution in REMO is to diagnose the sea ice cover from the prescribed surface temperature and allow each grid cell to be either completely free of ice or completely covered by ice (REMO-original). The other one is to employ a partial sea ice concentration in each REMO grid cell with the input data derived from satellite data (REMO-partial). Surface fluxes are average values of the ice and water partial fluxes. There is a clearly better agreement between measured and simulated surface and boundary layer temperatures and humidities when using REMO-partial compared to REMO-original. The closed ice cover in REMO-original leads to downward sensible heat fluxes over ice, whereas the ice cover with leads and polynyas in REMO-partial leads to smaller downward or even upward sensible heat fluxes. The introduction of the partial sea ice concentration smoothes unrealistically sharp gradients between ice-covered and ice-free regions. which can influence cloud cover and precipitation. An additional result of the study is that the simulation of the albedo could be improved in allowing a larger range of sea ice albedos and introducing a water albedo dependent on sun zenith angle.

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Bettina Steuri
,
Elisabeth Viktor
,
Juliane El Zohbi
, and
Daniela Jacob

Abstract

In recent years, climate service has emerged as a new field to better connect climate data providers and users of climate change–related information. The aim is to transform climate-related information into customized, user-centered products. This transformation of data is increasingly sought after by decision-makers due to public and regulatory pressure. As one of the first institutions to provide climate services, the Climate Service Center Germany (GERICS) has collected a wide range of different experiences in the field of climate services. Based on this know-how, GERICS has identified three distinct roles—we call them hats—that the institute commonly assumes as a climate service provider: the facilitator, the developer, and the trendsetter. The definition and tasks related to each of these distinct hats is presented alongside examples. The key ingredient for the success of a service product heavily depends on successful user engagement. While wearing any of the three hats and depending on a project’s context as well as the project stage, GERICS makes use of several methods to codevelop services with users. Based on past experiences, four different styles of user engagement, distinguished by the degree of intensity of participation, were established: information, consultation, dialog, and partnership. The connection of the three hats and the four styles of user engagement creates a structure in which climate service providers operate. It may help other climate service providers to reflect upon the general outline of their services and enhance the effectiveness of their engagement with users in transdisciplinary research settings.

Open access
Heiko Paeth
,
Kai Born
,
Robin Girmes
,
Ralf Podzun
, and
Daniela Jacob

Abstract

Human activity is supposed to affect the earth’s climate mainly via two processes: the emission of greenhouse gases and aerosols and the alteration of land cover. While the former process is well established in state-of-the-art climate model simulations, less attention has been paid to the latter. However, the low latitudes appear to be particularly sensitive to land use changes, especially in tropical Africa where frequent drought episodes were observed during recent decades. Here several ensembles of long-term transient climate change experiments are presented with a regional climate model to estimate the future pathway of African climate under fairly realistic forcing conditions. Therefore, the simulations are forced with increasing greenhouse gas concentrations as well as land use changes until 2050. Three different scenarios are prescribed in order to assess the range of options inferred from global political, social, and economical development. The authors find a prominent surface heating and a weakening of the hydrological cycle over most of tropical Africa, resulting in enhanced heat stress and extended dry spells. In contrast, the large-scale atmospheric circulation in upper levels is less affected, pointing to a primarily local effect of land degradation on near-surface climate. In the model study, it turns out that land use changes are primarily responsible for the simulated climate response. In general, simulated climate changes are not concealed by internal variability. Thus, the effect of land use changes has to be accounted for when developing more realistic scenarios for future African climate.

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Ruud Hurkmans
,
Wilco Terink
,
Remko Uijlenhoet
,
Paul Torfs
,
Daniela Jacob
, and
Peter A. Troch

Abstract

Because of global warming, the hydrologic behavior of the Rhine basin is expected to shift from a combined snowmelt- and rainfall-driven regime to a more rainfall-dominated regime. Previous impact assessments have indicated that this leads, on average, to increasing streamflow by ∼30% in winter and spring and decreasing streamflow by a similar value in summer. In this study, high-resolution (0.088°) regional climate scenarios conducted with the regional climate model REMO (REgional MOdel) for the Rhine basin are used to force a macroscale hydrological model. These climate scenarios are based on model output from the ECHAM5–Max Planck Institute Ocean Model (MPI-OM) global climate model, which is in turn forced by three Special Report on Emissions Scenarios (SRES) emission scenarios: A2, A1B, and B1. The Variable Infiltration Capacity model (VIC; version 4.0.5) is used to examine changes in streamflow at various locations throughout the Rhine basin. Average streamflow, peak flows, low flows, and several water balance terms are evaluated for both the first and second half of the twenty-first century. The results reveal a distinct contrast between those periods. The first half is dominated by increased precipitation, causing increased streamflow throughout the year. During the second half of the century, a streamflow increase in winter/spring and a decrease in summer is found, similar to previous studies. This is caused by 1) temperature and evapotranspiration, which are considerably higher during the second half of the century; 2) decreased precipitation in summer; and 3) an earlier start of the snowmelt season. Magnitudes of peak flows increase during both periods, and the magnitudes of streamflow droughts increase only during the second half of the century.

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Hanna Hueging
,
Rabea Haas
,
Kai Born
,
Daniela Jacob
, and
Joaquim G. Pinto

Abstract

The impact of climate change on wind power generation potentials over Europe is investigated by considering ensemble projections from two regional climate models (RCMs) driven by a global climate model (GCM). Wind energy density and its interannual variability are estimated based on hourly near-surface wind speeds. Additionally, the possible impact of climatic changes on the energy output of a sample 2.5-MW turbine is discussed. GCM-driven RCM simulations capture the behavior and variability of current wind energy indices, even though some differences exist when compared with reanalysis-driven RCM simulations. Toward the end of the twenty-first century, projections show significant changes of energy density on annual average across Europe that are substantially stronger in seasonal terms. The emergence time of these changes varies from region to region and season to season, but some long-term trends are already statistically significant in the middle of the twenty-first century. Over northern and central Europe, the wind energy potential is projected to increase, particularly in winter and autumn. In contrast, energy potential over southern Europe may experience a decrease in all seasons except for the Aegean Sea. Changes for wind energy output follow the same patterns but are of smaller magnitude. The GCM/RCM model chains project a significant intensification of both interannual and intra-annual variability of energy density over parts of western and central Europe, thus imposing new challenges to a reliable pan-European energy supply in future decades.

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Barbara Früh
,
Hendrik Feldmann
,
Hans-Jürgen Panitz
,
Gerd Schädler
,
Daniela Jacob
,
Philip Lorenz
, and
Klaus Keuler

Abstract

To determine return values at various return periods for extreme daily precipitation events over complex orography, an appropriate threshold value and distribution function are required. The return values are calculated using the peak-over-threshold approach in which only a reduced sample of precipitation events exceeding a predefined threshold is analyzed. To fit the distribution function to the sample, the L-moment method is used. It is found that the deviation between the fitted return values and the plotting positions of the ranked precipitation events is smaller for the kappa distribution than for the generalized Pareto distribution.

As a second focus, the ability of regional climate models to realistically simulate extreme daily precipitation events is assessed. For this purpose the return values are derived using precipitation events exceeding the 90th percentile of the precipitation time series and a fit of a kappa distribution. The results of climate simulations with two different regional climate models are analyzed for the 30-yr period 1971–2000: the so-called consortium runs performed with the climate version of the Lokal Modell (referred to as the CLM-CR) at 18-km resolution and the Regional Model (REMO)–Umweltbundesamt (UBA) simulations at 10-km resolution. It was found that generally the return values are overestimated by both models. Averaged across the region the overestimation is higher for REMO–UBA compared to CLM-CR.

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Alain T. Tamoffo
,
Leonard K. Amekudzi
,
Torsten Weber
,
Derbetini A. Vondou
,
Edmund I. Yamba
, and
Daniela Jacob

Abstract

Two regional climate models (RCMs) participating in the CORDEX–Coordinated Output for Regional Evaluations (CORDEX-CORE) project feature a dipole-type rainfall bias during March–May (MAM) and September–November (SON) over central equatorial Africa (CEA), consisting of positive bias in west central equatorial Africa (WCEA) and negative bias in east central equatorial Africa (ECEA). One is the Regional Model version 2015 (REMO2015) and the other is the fourth version of the Regional Climate Model (RegCM4-v7). RCMs are nested in three Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), and in the reanalysis ERA-Interim, at ∼25-km spacing grid resolution. This study highlights misrepresented underlying physical processes associated with these rainfall biases through a process-based evaluation. Both RCMs produce a weaker Congo basin cell, associated with a weaker land–ocean zonal surface pressure gradient. Consequently, less water vapor enters the region, and little is transported from WCEA to ECEA, resulting in higher moisture availability in the west than in the east. This leads to an unevenly distributed moisture across the region, favoring a stronger atmospheric instability in WCEA where the moist static energy (MSE) anomalously increases through an enhanced latent static energy (LSE). Moisture arrives at a slower pace in ECEA, associated with the weak cell’s strength. The intensity of ascent motions in response to the orographic constraint is weak to destabilize atmospheric stability in the lower layers, necessary for initiating deep convection. Therefore, the convection is shallow in ECEA related to underestimating the MSE due to the reduced LSE.

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Philippe Lucas-Picher
,
Jens H. Christensen
,
Fahad Saeed
,
Pankaj Kumar
,
Shakeel Asharaf
,
Bodo Ahrens
,
Andrew J. Wiltshire
,
Daniela Jacob
, and
Stefan Hagemann

Abstract

The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmöller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

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