scholarly journals Impact of RCM Spatial Resolution on the Reproduction of Local, Subdaily Precipitation

2015 ◽  
Vol 16 (2) ◽  
pp. 534-547 ◽  
Author(s):  
Jonas Olsson ◽  
Peter Berg ◽  
Akira Kawamura
Keyword(s):  
Spatial Resolution ◽  
Climate Model ◽  
Positive Impact ◽  
Regional Climate ◽  
Low Frequency ◽  
Small Scale ◽  
Hydrological Hazards ◽  
Change Impact ◽  
Urban Catchments ◽  
Intensity Duration Frequency

Abstract Many hydrological hazards are closely connected to local precipitation (extremes), especially in small and urban catchments. The use of regional climate model (RCM) data for small-scale hydrological climate change impact assessment has long been nearly unfeasible because of the low spatial resolution. The RCM resolution is, however, rapidly increasing, approaching the size of small catchments and thus potentially increasing the applicability of RCM data for this purpose. The objective of this study is to explore to what degree subhourly temporal precipitation statistics in an RCM converge to observed point statistics when gradually increasing the resolution from 50 to 6 km. This study uses precipitation simulated by RCA3 at seven locations in southern Sweden during 1995–2008. A positive impact of higher resolution was most clearly manifested in 10-yr intensity–duration–frequency (IDF) curves. At 50 km the intensities are underestimated by 50%–90%, but at 6 km they are nearly unbiased, when averaged over all locations and durations. Thus, at 6 km, RCA3 apparently generates low-frequency subdaily extremes that resemble the values found in point observations. Also, the reproduction of short-term variability and less extreme maxima were overall improved with increasing resolution. For monthly totals, a slightly increased overestimation with increasing resolution was found. The bias in terms of wet fraction and wet spell characteristics was overall not strongly dependent on resolution. These metrics are, however, influenced by the cutoff threshold used to separate between wet and dry time steps as well as the wet spell definition.

Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM

2013 ◽  
Vol 52 (10) ◽  
pp. 2296-2311 ◽  
Author(s):  
Kristina Trusilova ◽  
Barbara Früh ◽  
Susanne Brienen ◽  
Andreas Walter ◽  
Valéry Masson ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Climate Model ◽  
Spatial Scales ◽  
Regional Climate ◽  
Coupled Model ◽  
Urban Land ◽  
Urban Land Use ◽  
Small Scale ◽  
Model Simulations ◽  
Scale Modelling

AbstractAs the nonhydrostatic regional model of the Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM) is increasingly employed for studying the effects of urbanization on the environment, the authors extend its surface-layer parameterization by the Town Energy Budget (TEB) parameterization using the “tile approach” for a single urban class. The new implementation COSMO-CLM+TEB is used for a 1-yr reanalysis-driven simulation over Europe at a spatial resolution of 0.11° (~12 km) and over the area of Berlin at a spatial resolution of 0.025° (~2.8 km) for evaluating the new coupled model. The results on the coarse spatial resolution of 0.11° show that the standard and the new models provide 2-m temperature and daily precipitation fields that differ only slightly by from −0.1 to +0.2 K per season and ±0.1 mm day−1, respectively, with very similar statistical distributions. This indicates only a negligibly small effect of the urban parameterization on the model's climatology. Therefore, it is suggested that an urban parameterization may be omitted in model simulations on this scale. On the spatial resolution of 0.025° the model COSMO-CLM+TEB is able to better represent the magnitude of the urban heat island in Berlin than the standard model COSMO-CLM. This finding shows the importance of using the parameterization for urban land in the model simulations on fine spatial scales. It is also suggested that models could benefit from resolving multiple urban land use classes to better simulate the spatial variability of urban temperatures for large metropolitan areas on spatial scales below ~3 km.

scholarly journals A new estimator of heat periods for decadal climate predictions – a complex network approach

2016 ◽  
Vol 23 (4) ◽  
pp. 307-317 ◽  
Author(s):  
Michael Weimer ◽  
Sebastian Mieruch ◽  
Gerd Schädler ◽  
Christoph Kottmeier
Keyword(s):  
Climate Model ◽  
Extreme Values ◽  
Regional Climate ◽  
Low Frequency ◽  
Research Field ◽  
Temperature Threshold ◽  
Fixed Temperature ◽  
Correlation Threshold ◽  
Decadal Climate ◽  
Decadal Predictions

Abstract. Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for eight regions in Europe and quantify the skill of the model alternatively by constructing time-evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to estimate the low-frequency dynamics of heat periods is superior for decadal predictions with respect to the typical approach of using a fixed temperature threshold for estimating the number of heat periods in Europe.

scholarly journals Regional Climate Models Add Value to Global Model Data: A Review and Selected Examples

2011 ◽  
Vol 92 (9) ◽  
pp. 1181-1192 ◽  
Author(s):  
Frauke Feser ◽  
Burkhardt Rockel ◽  
Hans von Storch ◽  
Jörg Winterfeldt ◽  
Matthias Zahn
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Spatial Scales ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Small Scale ◽  
Model Data ◽  
Polar Lows

An important challenge in current climate modeling is to realistically describe small-scale weather statistics, such as topographic precipitation and coastal wind patterns, or regional phenomena like polar lows. Global climate models simulate atmospheric processes with increasingly higher resolutions, but still regional climate models have a lot of advantages. They consume less computation time because of their limited simulation area and thereby allow for higher resolution both in time and space as well as for longer integration times. Regional climate models can be used for dynamical down-scaling purposes because their output data can be processed to produce higher resolved atmospheric fields, allowing the representation of small-scale processes and a more detailed description of physiographic details (such as mountain ranges, coastal zones, and details of soil properties). However, does higher resolution add value when compared to global model results? Most studies implicitly assume that dynamical downscaling leads to output fields that are superior to the driving global data, but little work has been carried out to substantiate these expectations. Here a series of articles is reviewed that evaluate the benefit of dynamical downscaling by explicitly comparing results of global and regional climate model data to the observations. These studies show that the regional climate model generally performs better for the medium spatial scales, but not always for the larger spatial scales. Regional models can add value, but only for certain variables and locations—particularly those influenced by regional specifics, such as coasts, or mesoscale dynamics, such as polar lows. Therefore, the decision of whether a regional climate model simulation is required depends crucially on the scientific question being addressed.

scholarly journals Applying an isotope-enabled regional climate model over the Greenland ice sheet: effect of spatial resolution on model bias

2021 ◽  
Vol 17 (4) ◽  
pp. 1685-1699
Author(s):  
Marcus Breil ◽  
Emanuel Christner ◽  
Alexandre Cauquoin ◽  
Martin Werner ◽  
Melanie Karremann ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Ice Cores ◽  
Arctic Region ◽  
The Arctic ◽  
Simulation Results ◽  
The Arctic Region

Abstract. In order to investigate the impact of spatial resolution on the discrepancy between simulated δ18O and observed δ18O in Greenland ice cores, regional climate simulations are performed with the isotope-enabled regional climate model (RCM) COSMO_iso. For this purpose, isotope-enabled general circulation model (GCM) simulations with the ECHAM5-wiso general circulation model (GCM) under present-day conditions and the MPI-ESM-wiso GCM under mid-Holocene conditions are dynamically downscaled with COSMO_iso for the Arctic region. The capability of COSMO_iso to reproduce observed isotopic ratios in Greenland ice cores for these two periods is investigated by comparing the simulation results to measured δ18O ratios from snow pit samples, Global Network of Isotopes in Precipitation (GNIP) stations and ice cores. To our knowledge, this is the first time that a mid-Holocene isotope-enabled RCM simulation is performed for the Arctic region. Under present-day conditions, a dynamical downscaling of ECHAM5-wiso (1.1∘×1.1∘) with COSMO_iso to a spatial resolution of 50 km improves the agreement with the measured δ18O ratios for 14 of 19 observational data sets. A further increase in the spatial resolution to 7 km does not yield substantial improvements except for the coastal areas with its complex terrain. For the mid-Holocene, a fully coupled MPI-ESM-wiso time slice simulation is downscaled with COSMO_iso to a spatial resolution of 50 km. In the mid-Holocene, MPI-ESM-wiso already agrees well with observations in Greenland and a downscaling with COSMO_iso does not further improve the model–data agreement. Despite this lack of improvement in model biases, the study shows that in both periods, observed δ18O values at measurement sites constitute isotope ratios which are mainly within the subgrid-scale variability of the global ECHAM5-wiso and MPI-ESM-wiso simulation results. The correct δ18O ratios are consequently not resolved in the GCM simulation results and need to be extracted by a refinement with an RCM. In this context, the RCM simulations provide a spatial δ18O distribution by which the effects of local uncertainties can be taken into account in the comparison between point measurements and model outputs. Thus, an isotope-enabled GCM–RCM model chain with realistically implemented fractionating processes constitutes a useful supplement to reconstruct regional paleo-climate conditions during the mid-Holocene in Greenland. Such model chains might also be applied to reveal the full potential of GCMs in other regions and climate periods, in which large deviations relative to observed isotope ratios are simulated.

scholarly journals Is bias correction of Regional Climate Model (RCM) simulations possible for non-stationary conditions?

2012 ◽  
Vol 9 (11) ◽  
pp. 12765-12795 ◽  
Author(s):  
C. Teutschbein ◽  
J. Seibert
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Change Impact ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Conditions ◽  
Impact Studies ◽  
Split Sample ◽  
Sample Test ◽  
Change Impact

Abstract. In hydrological climate-change impact studies, Regional Climate Models (RCMs) are commonly used to transfer large-scale Global Climate Model (GCM) data to smaller scales and to provide more detailed regional information. However, there are often considerable biases in RCM simulations, which have led to the development of a number of bias correction approaches to provide more realistic climate simulations for impact studies. Bias correction procedures rely on the assumption that RCM biases do not change over time, because correction algorithms and their parameterizations are derived for current climate conditions and assumed to apply also for future climate conditions. This underlying assumption of bias stationarity is the main concern when using bias correction procedures. It is in principle not possible to test whether this assumption is actually fulfilled for future climate conditions. In this study, however, we demonstrate that it is possible to evaluate how well bias correction methods perform for conditions different from those used for calibration. For five Swedish catchments, several time series of RCM simulated precipitation and temperature were obtained from the ENSEMBLES data base and different commonly-used bias correction methods were applied. We then performed a differential split-sample test by dividing the data series into cold and warm respective dry and wet years. This enabled us to evaluate the performance of different bias correction procedures under systematically varying climate conditions. The differential split-sample test resulted in a large spread and a clear bias for some of the correction methods during validation years. More advanced correction methods such as distribution mapping performed relatively well even in the validation period, whereas simpler approaches resulted in the largest deviations and least reliable corrections for changed conditions. Therefore, we question the use of simple bias correction methods such as the widely used delta-change approach and linear scaling for RCM-based climate-change impact studies and recommend using higher-skill bias correction methods.

scholarly journals Added Value of Atmosphere-Ocean Coupling in a Century-Long Regional Climate Simulation

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 537 ◽  
Author(s):  
Fanni Dóra Kelemen ◽  
Cristina Primo ◽  
Hendrik Feldmann ◽  
Bodo Ahrens
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Climate Simulation ◽  
Climatic Research Unit ◽  
Small Scale ◽  
Limited Area ◽  
Regional Climate Simulation ◽  
Marginal Seas ◽  
The Impact

A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive coupling of the marginal seas, namely the Mediterranean, the North and the Baltic Seas, to the atmosphere in the European region gives a comprehensive modelling system. It is expected to be able to describe the climatological features of this geographically complex area even more precisely than an atmosphere-only climate model. The investigated variables are precipitation and 2 m temperature. Sensitivity studies are used to assess the impact of SST (sea surface temperature) changes over land areas. The different SST values affect the continental precipitation more than the 2 m temperature. The simulated variables are compared to the CRU (Climatic Research Unit) observational data, and also to the HOAPS/GPCC (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, Global Precipitation Climatology Centre) data. In the coupled simulation, added skill is found primarily during winter over the eastern part of Europe. Our analysis shows that, over this region, the coupled system is dryer than the uncoupled system, both in terms of precipitation and soil moisture, which means a decrease in the bias of the system. Thus, the coupling improves the simulation of precipitation over the eastern part of Europe, due to cooler SST values and in consequence, drier soil.

Small-scale circulation in regional climate model: the hydrostatic approximation influence

2021 ◽  
Author(s):  
Alexander Titov ◽  
Alexander Khoperskov ◽  
Konstantin Firsov ◽  
Evgeny Baskakov
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Small Scale ◽  
Hydrostatic Approximation
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