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Bent H. Sass and Jens H. Christensen

Abstract

A framework is designed for efficient experimentation with atmospheric forecast models on a limited area. It is shown that extended range atmospheric simulations on a limited area, using analyzed boundary values from a global model may be used as a tool to diagnose model deficiencies. Examples are given of model diagnosis on a limited area centered over Northern Europe, based on simulations with the High-Resolution Limited-Area Model over periods of one month. The effect of the lateral boundaries is investigated by comparing simulation results with forecasts from the global model up to a range of 10 days. The diagnosis is consistent with operational experiences with the limited-area model. The potential of the experimental framework is further investigated by testing the impact of two alternative parameterization schemes for radiation and condensation, respectively. The radiation scheme has not previously been tested in a forecast model. It is shown that these schemes have a marked positive impact on the model's vertical bias structure for temperature and humidity.

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Ole B. Christensen, Jens H. Christensen, Bennert Machenhauer, and Michael Botzet

Abstract

The hydrological cycle on a regional scale is poorly represented with a present-day coarse resolution general circulation model (GCM). With a dynamical downscaling technique, in which a regional higher-resolution climate model (RCM) is nested into the GCM, this starts to become feasible. Here the authors go one step further with a double nesting approach, applying an RCM at 19-km horizontal resolution nested into an RCM at 57-km resolution over an area covering the Scandinavian Peninsula. A 9-yr-long time-slice simulation is performed with the driving boundary conditions taken from a fully coupled ocean–atmosphere GCM experiment, the recently completed ECHAM4/OPYC3 control simulation performed by the Max Planck Institute for Meteorology in Hamburg. With increasing resolution, local effects playing a significant role in the hydrological budget become better and better resolved and are more realistically simulated. It is found in particular that in mountainous regions the high-resolution simulation shows improvements in the simulation of hydrologically relevant fields such as runoff and snow cover. Also, the distribution of precipitation on different intensity classes is most realistically simulated in the high-resolution simulation. It does, however, inherit certain large-scale systematic errors from the driving GCM. In many cases these errors increase with increasing resolution. Model verification of near-surface temperature and precipitation is made using a new gridded climatology based on a high-density station network for the Scandinavian countries compiled for the present study. The simulated runoff is compared with observed data from Sweden extracted from a Swedish climatological atlas. These runoff data indicate that the precipitation analyses are underestimating the true precipitation by as much as 96% on an annual basis in the most mountainous region of Sweden. This fact as well as estimates of the underestimation in other areas of Scandinavia make the high-resolution RCM simulations appear more realistic.

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Philippe Lucas-Picher, Fredrik Boberg, Jens H. Christensen, and Peter Berg

Abstract

To retain the sequence of events of a regional climate model (RCM) simulation driven by a reanalysis, a method that has not been widely adopted uses an RCM with frequent reinitializations toward its driving field. In this regard, this study highlights the benefits of an RCM simulation with frequent (daily) reinitializations compared to a standard continuous RCM simulation. Both simulations are carried out with the RCM HIRHAM5, driven with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data, over the 12-km-resolution European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain covering the period 1989–2009. The analysis of daily precipitation shows improvements in the sequence of events and the maintenance of the added value from the standard continuous RCM simulation. The validation of the two RCM simulations with observations reveals that the simulation with reinitializations indeed improves the temporal correlation. Furthermore, the RCM simulation with reinitializations has lower systematic errors compared to the continuous simulation, which has a tendency to be too wet. A comparison of the distribution of wet day precipitation intensities shows similar added value in the continuous and reinitialized simulations with higher variability and extremes compared to the driving field ERA-Interim. Overall, the results suggest that the finescale climate dataset of the RCM simulation with reinitializations better suits the needs of impact studies by providing a sequence of events matching closely the observations, while limiting systematic errors and generating reliable added value. Downsides of the method with reinitializations are increased computational costs and the introduction of temporal discontinuities that are similar to those of a reanalysis.

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Kerstin Stahl, Lena M. Tallaksen, Lukas Gudmundsson, and Jens H. Christensen

Abstract

Land surface models and large-scale hydrological models provide the basis for studying impacts of climate and anthropogenic changes on continental- to regional-scale hydrology. Hence, there is a need for comparison and validation of simulated characteristics of spatial and temporal dynamics with independent observations. This study introduces a novel validation framework that relates to common hydrological design measures. The framework is tested by comparing anomalies of runoff from a high-resolution climate-model simulation for Europe with a large number of streamflow observations from small near-natural basins. The regional climate simulation was performed as a “poor man’s reanalysis,” involving a dynamical downscaling of the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) with the Danish “HIRHAM5” model. For 19 different anomaly levels, two indices evaluate the temporal agreement (i.e., the occurrence and frequency of dry and wet events based on daily anomalies), whereas two other indices compare the interannual variability and trends based on annual anomalies. Benchmarks on each index facilitated a comparison across indices, anomaly levels, and basins. The lowest agreement of observed and simulated anomalies was found for dry anomalies. Weak to moderately wet anomalies agreed best, but agreement dropped again for the wettest anomalies. The results could guide the decision on thresholds if this regional climate model were used for the assessment of climate change scenario impacts on flood and drought statistics. Indices vary across Europe, but a gradient with decreasing correspondence between observed and simulated runoff characteristics from west to east, from lower to higher elevations, and from fast to slowly responding basins can be distinguished. The suggested indices can easily be adapted to other study areas and model types to assist in assessing the reliability of predictions of hydrological change.

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Sebastian H. Mernild, Glen E. Liston, Christopher A. Hiemstra, and Jens H. Christensen

Abstract

Fluctuations in the Greenland ice sheet (GrIS) surface mass balance (SMB) and freshwater influx to the surrounding oceans closely follow climate fluctuations and are of considerable importance to the global eustatic sea level rise. A state-of-the-art snow-evolution modeling system (SnowModel) was used to simulate variations in the GrIS melt extent, surface water balance components, changes in SMB, and freshwater influx to the ocean. The simulations are based on the Intergovernmental Panel on Climate Change scenario A1B modeled by the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere–ocean general circulation model (AOGCM) from 1950 through 2080. In situ meteorological station [Greenland Climate Network (GC-Net) and World Meteorological Organization (WMO) Danish Meteorological Institute (DMI)] observations from inside and outside the GrIS were used to validate and correct RCM output data before they were used as input for SnowModel. Satellite observations and independent SMB studies were used to validate the SnowModel output and confirm the model’s robustness. The authors simulated an ∼90% increase in end-of-summer surface melt extent (0.483 × 106 km2) from 1950 to 2080 and a melt index (above 2000-m elevation) increase of 138% (1.96 × 106 km2 × days). The greatest difference in melt extent occurred in the southern part of the GrIS, and the greatest changes in the number of melt days were seen in the eastern part of the GrIS (∼50%–70%) and were lowest in the west (∼20%–30%). The rate of SMB loss, largely tied to changes in ablation processes, leads to an enhanced average loss of 331 km3 from 1950 to 2080 and an average SMB level of −99 km3 for the period 2070–80. GrIS surface freshwater runoff yielded a eustatic rise in sea level from 0.8 ± 0.1 (1950–59) to 1.9 ± 0.1 mm (2070–80) sea level equivalent (SLE) yr−1. The accumulated GrIS freshwater runoff contribution from surface melting equaled 160-mm SLE from 1950 through 2080.

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Sebastian H. Mernild, Glen E. Liston, Christopher A. Hiemstra, Jens H. Christensen, Martin Stendel, and Bent Hasholt

Abstract

A regional atmospheric model, the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere–ocean general circulation model (AOGCM), was downscaled to a 500-m gridcell increment using SnowModel to simulate 131 yr (1950–2080) of hydrologic cycle evolution in west Greenland’s Kangerlussuaq drainage. Projected changes in the Greenland Ice Sheet (GrIS) surface mass balance (SMB) and runoff are relevant for potential hydropower production and prediction of ecosystem changes in sensitive Kangerlussuaq Fjord systems. Mean annual surface air temperatures and precipitation in the Kangerlussuaq area were simulated to increase by 3.4°C and 95 mm water equivalent (w.eq.), respectively, between 1950 and 2080. The local Kangerlussuaq warming was less than the average warming of 4.8°C simulated for the entire GrIS. The Kangerlussuaq SMB loss increased by an average of 0.3 km3 because of a 0.4 km3 rise in precipitation, 0.1 km3 rise in evaporation and sublimation, and 0.6 km3 gain in runoff (1950–2080). By 2080, the spring runoff season begins approximately three weeks earlier. The average modeled SMB and runoff is approximately −0.1 and 1.2 km3 yr−1, respectively, indicating that ∼10% of the Kangerlussuaq runoff is explained by the GrIS SMB net loss. The cumulative net volume loss (1950–2080) from SMB was 15.9 km3, and runoff was 151.2 km3 w.eq. This runoff volume is expected to have important hydrodynamic and ecological impacts on the stratified salinity in the Kangerlussuaq Fjord and on the transport of freshwater to the ocean.

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John E. Walsh, William L. Chapman, Vladimir Romanovsky, Jens H. Christensen, and Martin Stendel

Abstract

The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

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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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Jonathan Spinoni, Paulo Barbosa, Edoardo Bucchignani, John Cassano, Tereza Cavazos, Jens H. Christensen, Ole B. Christensen, Erika Coppola, Jason Evans, Beate Geyer, Filippo Giorgi, Panos Hadjinicolaou, Daniela Jacob, Jack Katzfey, Torben Koenigk, René Laprise, Christopher J. Lennard, M. Levent Kurnaz, Delei Li, Marta Llopart, Niall McCormick, Gustavo Naumann, Grigory Nikulin, Tugba Ozturk, Hans-Juergen Panitz, Rosmeri Porfirio da Rocha, Burkhardt Rockel, Silvina A. Solman, Jozef Syktus, Fredolin Tangang, Claas Teichmann, Robert Vautard, Jürgen V. Vogt, Katja Winger, George Zittis, and Alessandro Dosio

Abstract

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas.

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Christopher J. Anderson, Raymond W. Arritt, Zaitao Pan, Eugene S. Takle, William J. Gutowski Jr., Francis O. Otieno, Renato da Silva, Daniel Caya, Jens H. Christensen, Daniel Lüthi, Miguel A. Gaertner, Clemente Gallardo, Filippo Giorgi, René Laprise, Song-You Hong, Colin Jones, H-M. H. Juang, J. J. Katzfey, John L. McGregor, William M. Lapenta, Jay W. Larson, John A. Taylor, Glen E. Liston, Roger A. Pielke Sr., and John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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