Impact of Lateral Boundary Errors on the Simulation of Clouds with a Nonhydrostatic Regional Climate Model

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

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Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

10.21203/rs.3.rs-725819/v1 ◽

2021 ◽

Author(s):

Antoine Doury ◽

Samuel Somot ◽

Sébastien Gadat ◽

Aurélien Ribes ◽

Lola Corre

Keyword(s):

Climate Change ◽

Network Architecture ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Future Climate ◽

Near Surface ◽

The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

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Dependence of benefits of convection permitting models on large-scale conditions

10.5194/egusphere-egu2020-16822 ◽

2020 ◽

Author(s):

Danijel Belusic ◽

Petter Lind ◽

Oskar Landgren ◽

Dominic Matte ◽

Rasmus Anker Pedersen ◽

...

Keyword(s):

Large Scale ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Rapid Change ◽

Winter Season ◽

Storm Track ◽

Summer Precipitation ◽

Weather Conditions ◽

Special Focus

Current literature strongly indicates large benefits of convection permitting models for subdaily summer precipitation extremes. There has been less insight about other variables, seasons and weather conditions. We examine new climate simulations over the Nordic region, performed with the HCLIM38 regional climate model at both convection permitting and coarser scales, searching for benefits of using convection permitting resolutions. The Nordic climate is influenced by the North Atlantic storm track and characterised by large seasonal contrasts in temperature and precipitation. It is also in rapid change, most notably in the winter season when feedback processes involving retreating snow and ice lead to larger warming than in many other regions. This makes the area an ideal testbed for regional climate models. We explore the effects of higher resolution and better reproduction of convection on various aspects of the climate, such as snow in the mountains, coastal and other thermal circulations, convective storms and precipitation with a special focus on extreme events. We investigate how the benefits of convection permitting models change with different variables and seasons, and also their sensitivity to different circulation regimes.

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Do Convection-Permitting Regional Climate Models Improve Projections of Future Precipitation Change?

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-15-0004.1 ◽

2017 ◽

Vol 98 (1) ◽

pp. 79-93 ◽

Cited By ~ 121

Author(s):

Elizabeth J. Kendon ◽

Nikolina Ban ◽

Nigel M. Roberts ◽

Hayley J. Fowler ◽

Malcolm J. Roberts ◽

...

Keyword(s):

Climate Change ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Global Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Climate Projections ◽

Convective Storms ◽

Wide Range

Abstract Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.

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How uncertain are climate model projections of water availability indicators across the Middle East?

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2010.0174 ◽

2010 ◽

Vol 368 (1931) ◽

pp. 5117-5135 ◽

Cited By ~ 31

Author(s):

Debbie Hemming ◽

Carlo Buontempo ◽

Eleanor Burke ◽

Mat Collins ◽

Neil Kaye

Keyword(s):

Middle East ◽

Water Availability ◽

Large Scale ◽

Drought Index ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

General Distribution ◽

The North ◽

Run Off

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961–1990 and 2021–2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between −5 and −25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

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Increased variability in Greenland Ice Sheet runoff from satellite observations

Nature Communications ◽

10.1038/s41467-021-26229-4 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Thomas Slater ◽

Andrew Shepherd ◽

Malcolm McMillan ◽

Amber Leeson ◽

Lin Gilbert ◽

...

Keyword(s):

Ocean Circulation ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Global Climate Model ◽

Regional Climate ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Model Simulations ◽

Climate Model Simulations

AbstractRunoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems, and it now accounts for most of the contemporary mass imbalance. Estimates of runoff are typically derived from regional climate models because satellite records have been limited to assessments of melting extent. Here, we use CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

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Alternative Formulations for Incorporating Lateral Boundary Data into Limited-Area Models

Monthly Weather Review ◽

10.1175/2010mwr3179.1 ◽

2010 ◽

Vol 138 (7) ◽

pp. 2867-2882 ◽

Cited By ~ 15

Author(s):

Martina Tudor ◽

Piet Termonia

Keyword(s):

Large Scale ◽

Prediction Models ◽

Weather Prediction ◽

Scale Model ◽

Coupling Scheme ◽

Lateral Boundary Condition ◽

Limited Area ◽

Lateral Boundary ◽

Coupling Interval ◽

Temporal Interpolation

Abstract Limited-area models (LAMs) use higher resolutions and more advanced parameterizations of physical processes than global numerical weather prediction models, but suffer from one additional source of error—the lateral boundary condition (LBC). The large-scale model passes the information on its fields to the LAM only over the narrow coupling zone at discrete times separated by a coupling interval of several hours. The LBC temporal resolution can be lower than the time necessary for a particular meteorological feature to cross the boundary. A LAM user who depends on LBC data acquired from an independent prior analysis or parent model run can find that usual schemes for temporal interpolation of large-scale data provide LBC data of inadequate quality. The problem of a quickly moving depression that is not recognized by the operationally used gridpoint coupling scheme is examined using a simple one-dimensional model. A spectral method for nesting a LAM in a larger-scale model is implemented and tested. Results for a traditional flow-relaxation scheme combined with temporal interpolation in spectral space are also presented.

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Boundary condition and oceanic impacts on the atmospheric water balance in limited area climate model ensembles

Scientific Reports ◽

10.1038/s41598-021-85744-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Klaus Goergen ◽

Stefan Kollet

Keyword(s):

Boundary Conditions ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Moisture Flux ◽

Limited Area ◽

Atmospheric Moisture ◽

Atmospheric Water ◽

Flux Divergence ◽

Water Budgets

AbstractRegional climate models (RCMs) are indispensable in climate research, albeit often characterized by biased terrestrial precipitation and water budgets. This study identifies excess oceanic evaporation, in conjunction with the RCMs’ boundary conditions, as drivers contributing to these biases in RCMs with forced sea surface temperatures in a CORDEX RCM ensemble over Europe. The RCMs are relaxed to the prescribed lateral boundary conditions originating from a global model, effectively matching the driving model's overall atmospheric moisture flux divergence. As a consequence, excess oceanic evaporation results in positive precipitation biases over land due to forced internal recycling of moisture to maintain the overall flux divergence prescribed by the boundary conditions. This systematic behaviour is shown through an analysis of long-term atmospheric water budgets and atmospheric moisture exchange between oceanic and continental areas in a multi-model ensemble.

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Vortex streets to the lee of Madeira in a km-resolution regional climate model

10.5194/egusphere-egu21-5302 ◽

2021 ◽

Author(s):

Qinggang Gao ◽

Christian Zeman ◽

Jesus Vergara Temprado ◽

Peter Molnar ◽

Christoph Schär

Keyword(s):

Vortex Shedding ◽

Large Scale ◽

Climate Model ◽

False Positive Rate ◽

Regional Climate ◽

Limited Area ◽

Identification Algorithm ◽

Vortex Identification ◽

Vortex Streets

Atmospheric vortex streets are one of the widely studied dynamical effects of isolated islands. However, the study of vortex shedding is still limited by the availability of observational wind &#64257;elds of high spatial and temporal resolutions. Although the geometry, kinematics, and dynamics of vortex streets have been intensively investigated in numerous theoretical, numerical, and observational studies, our understanding of vortex shedding in the real atmosphere and atmospheric models is still insufficient.Using the non-hydrostatic limited-area COSMO model driven by the ERA-Interim reanalysis, we simulated a mesoscale domain in high spatial (grid spacing 1 km) and temporal resolutions over one decade. This enabled us to investigate vortex streets within the planetary boundary layer despite limited observations. The basic properties of vortex streets are analyzed and validated through a 6-day-long case study in the lee of the Madeira island. The simulation compares well with satellite and aerial observations, and with the existing literature on idealized simulations.Our results show a strong dependency of vortex shedding on local and synoptic flow conditions, which are to a large extent governed by the location, shape, and magnitude of the Azores high, which represents one pole of the North Atlantic Oscillation. As part of the case study, we have developed a vortex identification algorithm, consisting of a wavelet analysis using a set of objective criteria. The algorithm shows good performance in terms of false-positive rate and enables us to develop a climatology of vortex shedding in this region for the 10-year simulation period. Based on the long term analysis, we can identify an increasing vortex shedding rate from April to August and a sudden decrease in September, which can be well explained by the large-scale wind conditions.

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Constraining hydrological impact simulations over Europe through weighting the climatic forcing

10.5194/egusphere-egu2020-15892 ◽

2020 ◽

Author(s):

Peter Greve ◽

Peter Burek ◽

Renate Wilcke ◽

Lukas Brunner ◽

Carol McSweeney ◽

...

Keyword(s):

Input Data ◽

Large Scale ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Hydrological Impact ◽

Model Ensembles ◽

Hydrological Extreme ◽

Impact Simulations

Global hydrological models (GHMs) have become an established tool to simulate water resources on continental scales. To assess the future of water availability and various impacts related to hydrological extreme events, these models usually use sets of atmospheric variables (such as e.g., precipitation, humidity, temperature) obtained from (regional) climate model simulations as input data. The uncertainty associated with the climate projections is transferred onwards into the impact simulations and is usually accounted for through the use of large model ensembles. These ensembles thus enable assessments addressing the robustness of projected hydrological changes and impacts. Given recent efforts within the European Climate Prediction (EUCP) project to test existing and develop new techniques to constrain/weight climate model ensembles, we use here different methods to specify the large-scale meteorological input to an ensemble of regional climate models that provide the input data for a state-of-the-art GHM. The climate models are weighted/constrained based on the key large-scale climatic and meteorological drivers shaping the hydrological characteristics in different regions and large river basins across Europe. To assess the potential benefits of the different techniques, we compare simulation ensembles using unweighted input data obtained from the full ensemble of regional climate models against an ensemble based on constrained/weighted forcing data. Given the large uncertainties usually associated with hydrological impact simulations forced by the full range of available climate models, processing the ensemble output of GHMs based on uncertainty assessments of the underlying climate forcing could lead to more robust projections of water resources in general and hydrological extreme events in particular.

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Quantification of the Lateral Boundary Forcing of a Regional Climate Model Using an Aging Tracer

Monthly Weather Review ◽

10.1175/2008mwr2448.1 ◽

2008 ◽

Vol 136 (12) ◽

pp. 4980-4996 ◽

Cited By ~ 30

Author(s):

Philippe Lucas-Picher ◽

Daniel Caya ◽

Sébastien Biner ◽

René Laprise

Keyword(s):

Regional Climate Model ◽

Atmospheric Circulation ◽

Climate Model ◽

Regional Climate ◽

Internal Variability ◽

Limited Area ◽

Lateral Boundary ◽

Time Step ◽

Lateral Boundary Conditions ◽

Residency Time

Abstract The present work introduces a new and useful tool to quantify the lateral boundary forcing of a regional climate model (RCM). This tool, an aging tracer, computes the time the air parcels spend inside the limited-area domain of an RCM. The aging tracers are initialized to zero when the air parcels enter the domain and grow older during their migrations through the domain with each time step in the integration of the model. This technique was employed in a 10-member ensemble of 10-yr (1980–89) simulations with the Canadian RCM on a large domain covering North America. The residency time is treated and archived as the other simulated meteorological variables, therefore allowing computation of its climate diagnostics. These diagnostics show that the domain-averaged residency time is shorter in winter than in summer as a result of the faster winter atmospheric circulation. The residency time decreases with increasing height above the surface because of the faster atmospheric circulation at high levels dominated by the jet stream. Within the domain, the residency time increases from west to east according to the transportation of the aging tracer with the westerly general atmospheric circulation. A linear relation is found between the spatial distribution of the internal variability—computed with the variance between the ensemble members—and residency time. This relation indicates that the residency time can be used as a quantitative indicator to estimate the level of control exerted by the lateral boundary conditions on the RCM simulations.

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