Model Horizontal Resolution Research Articles

The Climatology and the Midwinter Suppression of the Cold Season North Pacific Storm Track in CMIP6 Models

AbstractThe reproducibility of climatology and the midwinter suppression of cold season North Pacific storm track (NPST) in historical runs of 18 CMIP6 models is evaluated against the NCEP reanalysis data. The results show that the position of the climatological peak area of 850 hPa meridional eddy heat flux (v′t′850) is well captured by these models. The spatial patterns of climatological v′t′850 are basically consistent with the NCEP reanalysis. Generally, NorESM2-LM and CESM2-WACCM present a relatively strong capability to reproduce the climatological amplitude of v′t′850 with lower RMSE than the other models. Compared with CMIP5 models, the inter-model spread of v′t′850 climatology among the CMIP6 models is smaller, and their multi-model ensemble is closer to the NCEP reanalysis. The geographical distribution in more than half of the selected models is further south and east. For the subseasonal variability of v′t′850, nearly half of the models exhibit a double-peak structure. In contrast, the apparent midwinter suppression in the NPST represented by the 250 hPa filtered meridional wind variance (v′v′250) is reproduced by all the selected models.In addition, the present study investigates the possible reasons for simulation biases regarding climatological NPST amplitude. It is found that a higher model horizontal resolution significantly intensifies the climatological v′v′250. There is a significant in-phase relationship between climatological v′t′250 and the intensity of the East Asian winter monsoon (EAWM). However, the climatological v′t′850 is not sensitive to the model grid spacing. Additionally, the climatological low-tropospheric atmospheric baroclinicity is uncorrelated with climatological v′v′250. The stronger climatological baroclinic energy conversion is associated with the stronger climatological v′t′850.

Consequences of permafrost degradation for Arctic infrastructure – bridging the model gap between regional and engineering scales

Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate-warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally coupled 1D heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilisation due to talik formation in the ground beside the road rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-Arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after the exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally coupled 1D model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D and 3D models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service lifetime (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

The importance of horizontal model resolution on simulated precipitation in Europe – from global to regional models

Abstract. Precipitation is a key climate variable that affects large parts of society, especially in situations with excess amounts. Climate change projections show an intensified hydrological cycle through changes in intensity, frequency, and duration of precipitation events. Still, due to the complexity of precipitation processes and their large variability in time and space, climate models struggle to represent precipitation accurately. This study investigates the simulated precipitation in Europe in available climate model ensembles that cover a range of horizontal model resolutions. The ensembles used are global climate models (GCMs) from CMIP5 and CMIP6 (∼100–300 km horizontal grid spacing at mid-latitudes), GCMs from the PRIMAVERA project at sparse (∼80–160 km) and dense (∼25–50 km) grid spacing, and CORDEX regional climate models (RCMs) at sparse (∼50 km) and dense (∼12.5 km) grid spacing. The aim is to seasonally and regionally over Europe investigate the differences between models and model ensembles in the representation of the precipitation distribution in its entirety and through analysis of selected standard precipitation indices. In addition, the model ensemble performances are compared to gridded observations from E-OBS. The impact of model resolution on simulated precipitation is evident. Overall, in all seasons and regions the largest differences between resolutions are seen for moderate and high precipitation rates, where the largest precipitation rates are seen in the RCMs with the highest resolution (i.e. CORDEX 12.5 km) and the smallest rates in the CMIP GCMs. However, when compared to E-OBS, the high-resolution models most often overestimate high-intensity precipitation amounts, especially the CORDEX 12.5 km resolution models. An additional comparison to a regional data set of high quality lends, on the other hand, more confidence to the high-resolution model results. The effect of resolution is larger for precipitation indices describing heavy precipitation (e.g. maximum 1 d precipitation) than for indices describing the large-scale atmospheric circulation (e.g. the number of precipitation days), especially in regions with complex topography and in summer when precipitation is predominantly caused by convective processes. Importantly, the systematic differences between low resolution and high resolution also remain when all data are regridded to common grids of 0.5∘×0.5∘ and 2∘×2∘ prior to analysis. This shows that the differences are effects of model physics and better resolved surface properties and not due to the different grids on which the analysis is performed. PRIMAVERA high resolution and CORDEX low resolution give similar results as they are of similar resolution. Within the PRIMAVERA and CORDEX ensembles, there are clear differences between the low- and high-resolution simulations. Once reaching ∼50 km the difference between different models is often larger than between the low- and high-resolution versions of the same model. For indices describing precipitation days and heavy precipitation, the difference between two models can be twice as large as the difference between two resolutions, in both the PRIMAVERA and CORDEX ensembles. Even though increasing resolution improves the simulated precipitation in comparison to observations, the inter-model variability is still large, particularly in summer when smaller-scale processes and interactions are more prevalent and model formulations (such as convective parameterisations) become more important.

Photochemical environment over Southeast Asia primed for hazardous ozone levels with influx of nitrogen oxides from seasonal biomass burning

Abstract. Mainland and maritime Southeast Asia is home to more than 655 million people, representing nearly 10 % of the global population. The dry season in this region is typically associated with intense biomass burning activity, which leads to a significant increase in surface air pollutants that are harmful to human health, including ozone (O3). Latitude-based differences in the dry season and land use distinguish two regional biomass burning regimes: (1) burning on the peninsular mainland peaking in March and (2) burning across Indonesia peaking in September. The type and amount of material burned in each regime impact the emissions of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOCs), which combine to produce ozone. Here, we use the nested GEOS-Chem atmospheric chemistry transport model (horizontal resolution of 0.25∘ × 0.3125∘), in combination with satellite observations from the Ozone Monitoring Instrument (OMI) and ground-based observations from Malaysia, to investigate ozone photochemistry over Southeast Asia in 2014. Seasonal cycles of tropospheric ozone columns from OMI and GEOS-Chem peak with biomass burning emissions. Compared to OMI, the model has a mean annual bias of −11 % but tends to overestimate tropospheric ozone near areas of seasonal fire activity. We find that outside these burning areas, the underlying photochemical environment is generally NOx-limited and dominated by anthropogenic NOx and biogenic non-methane VOC emissions. Pyrogenic emissions of NOx play a key role in photochemistry, shifting towards more VOC-limited ozone production and contributing about 30 % of the regional ozone formation potential during both biomass burning seasons. Using the GEOS-Chem model, we find that biomass burning activity coincides with widespread ozone exposure at levels that exceed world public health guidelines, resulting in about 260 premature deaths across Southeast Asia in March 2014 and another 160 deaths in September. Despite a positive model bias, hazardous ozone levels are confirmed by surface observations during both burning seasons.

Impact of the Benguela coastal low-level jet on the southeast tropical Atlantic SST bias in a regional ocean model

The current generation of coupled ocean–atmosphere climate models, which are widely used for studying the dynamics of the climate system and to make projections of future climate, suffers from erroneously warm (exceeding 5 °C) sea surface temperature (SST) simulation in the eastern boundary upwelling systems (EBUS) in the Atlantic and Pacific oceans. While recent improvements in the horizontal resolution of coupled model components helped to alleviate this issue in the North and South Pacific and North Atlantic oceans, the warm bias in the Southeast Tropical Atlantic (SETA) region still remains above 5 °C. Recent studies have highlighted the importance of inaccuracies in the near-coastal winds, especially in the Benguela low-level coastal jet (BLLCJ), in the formation of this warm SST bias. In addition, unique ocean circulation features like the poleward flowing coastal current and the presence of a strong coastal SST front were argued to contribute to the complexity in simulating realistic SST in the SETA region. In this study, we investigate how ocean model resolution and the spatial structure and strength of the BLLCJ affect the SST warm bias in the SETA. We conducted a suite of ocean model experiments with varying horizontal resolutions (81–3 km) and different atmospheric forcing products. We found that the accuracy in the magnitude of BLLCJ’s alongshore component and in the spatial structure of BLLCJ are the primary factors in reducing the warm SST bias in SETA and the ocean model horizontal resolution is of only secondary importance. A weaker alongshore component of the BLLCJ leads to a weaker upwelling through Ekman transport and fails to generate a downwind equatorward surface jet in the ocean. When the core of the BLLCJ is too far offshore, the broad wind stress curl zone gives rise to anomalous poleward depth integrated flow through Sverdrup balance and weakens the wind stress curl induced Ekman pumping near the coast. Both the presence of a poleward current, which can transport warm equatorial waters farther south, and the absence of the equatorward surface jet contributes to the warm SST bias. Heat budget analysis shows that the contribution from the anomalous poleward flow is a bigger contributor to the warm bias than the weak upwelling. With more realistic, high-resolution winds, an ocean model resolution increase from 27 to 9 km slightly reduces the extent and magnitude of SST bias. However, no such improvement occurs with coarse resolution less realistic winds. Sensitivity experiments using atmospheric forcing fields from different sources confirm that the major contribution to the warm SST bias is in fact from the erroneous winds rather than other atmospheric forcing fields like net shortwave and downward longwave radiation. Further studies are needed to understand whether eddy heat advection or mean flow heat advection primarily cause the warm SST bias.

An Unprecedented Set of High‐Resolution Earth System Simulations for Understanding Multiscale Interactions in Climate Variability and Change

AbstractWe present an unprecedented set of high‐resolution climate simulations, consisting of a 500‐year pre‐industrial control simulation and a 250‐year historical and future climate simulation from 1850 to 2100. A high‐resolution configuration of the Community Earth System Model version 1.3 (CESM1.3) is used for the simulations with a nominal horizontal resolution of 0.25° for the atmosphere and land models and 0.1° for the ocean and sea‐ice models. At these resolutions, the model permits tropical cyclones and ocean mesoscale eddies, allowing interactions between these synoptic and mesoscale phenomena with large‐scale circulations. An overview of the results from these simulations is provided with a focus on model drift, mean climate, internal modes of variability, representation of the historical and future climates, and extreme events. Comparisons are made to solutions from an identical set of simulations using the standard resolution (nominal 1°) CESM1.3 and to available observations for the historical period to address some key scientific questions concerning the impact and benefit of increasing model horizontal resolution in climate simulations. An emerging prominent feature of the high‐resolution pre‐industrial simulation is the intermittent occurrence of polynyas in the Weddell Sea and its interaction with an Interdecadal Pacific Oscillation. Overall, high‐resolution simulations show significant improvements in representing global mean temperature changes, seasonal cycle of sea‐surface temperature and mixed layer depth, extreme events and in relationships between extreme events and climate modes.

Multidecadal preconditioning of the Maud Rise polynya region

Abstract. In this paper, we consider Maud Rise polynya formation in a long (250-year) high-resolution (ocean 0.1∘, atmosphere 0.5∘ horizontal model resolution) of the Community Earth System Model. We find a dominant multidecadal timescale in the occurrence of these Maud Rise polynyas. Analysis of the results leads us to the interpretation that a preferred timescale can be induced by the variability of the Weddell Gyre, previously identified as the Southern Ocean Mode. The large-scale pattern of heat content variability associated with the Southern Ocean Mode modifies the stratification in the Maud Rise region and leads to a preferred timescale in convection through preconditioning of the subsurface density and consequently to polynya formation.

Comparison of Tropical Cyclone Activities over the Western North Pacific in CORDEX-East Asia Phase I and II Experiments

AbstractThis study evaluated tropical cyclone (TC) activity simulated by two regional climate models (RCMs) incorporated in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework with two different horizontal resolutions. Evaluation experiments with two RCMs (RegCM4 and MM5) forced by reanalysis data were conducted over the CORDEX-East Asia domain for phases I and II. The main difference between phases I and II is horizontal resolution (50 and 25 km). The 20-yr (1989–2008) mean performances of the experiments were investigated in terms of TC genesis, track, intensity, and TC-induced precipitation. In general, the simulated TC activities over the western North Pacific (WNP) varied depending on the model type and horizontal resolution. For both models, higher horizontal resolution improved the simulation of TC tracks near the coastal regions of East Asia, whereas the coarser horizontal resolution led to underestimated TC genesis compared with the best track data because of greater convective precipitation and enhanced atmospheric stabilization. In addition, the increased horizontal resolution prominently improved the simulation of TCs landfalling in East Asia and associated precipitation around coastal regions. This finding implies that high-resolution RCMs can improve the simulation of TC activities over the WNP (i.e., added value by increasing model resolution); thus, they have an advantage in climate change assessment studies.

Changes in spatial patterns of ammonia dry deposition flux and deposition threshold exceedance according to dispersion model formalism and horizontal resolution.

Ammonia (NH3) emitted into the atmosphere from agricultural sources may affect nearby sensitive ecosystems due to high dry deposition fluxes on vegetation and soil surfaces, contributing to critical load exceedances. Ammonia fluxes near sources are simulated by either short-range atmospheric models or regional models using large grid cell sizes. However, studies are missing on the comparison of the results simulated by these two types of models. This paper presents the effect of model formalism, input factors, especially grid cell size and wind speed and the choice of deposition threshold on the spatial patterns of NH3 dry deposition fluxes and deposition threshold exceedances. We used the Eulerian chemistry-transport model CHIMERE and the Gaussian plume model OPS-ST on two study domains characterised by contrasting land use. We showed that the average annual NH3 dry deposition fluxes over each whole domain are similar for both models. By contrast, NH3 dry deposition fluxes near sources are higher when simulated with OPS-ST that provides analytical solutions that can be sampled with small grid cell sizes (i.e., from 25 to 1600m in this study), than with CHIMERE, which uses large grid cell sizes (i.e., 800 and 1600m). As a result, the spatial patterns of deposition threshold exceedance were very different between both models. These patterns depend mainly on grid cell size, the input factors and the choice of the deposition threshold value. We show that the model formalism has a relatively small effect on the results and that the differences result mainly from the spatial resolutions to which they can be applied. Simulation results must therefore be interpreted carefully, taking into account the simulation conditions.

Convection‐permitting modelling improves simulated precipitation over the central and eastern Tibetan Plateau

AbstractThe Tibetan Plateau (TP) plays an essential role in influencing the global climate, and precipitation is one of its most important water‐cycle components. However, accurately simulating precipitation over the TP is a long‐standing challenge. In this study, a convection‐permitting model (CPM; with 4 km grid spacing) that covers the entire TP was conducted and compared to two mesoscale models (MSMs; with model horizontal resolutions of 13 and 35 km) over the course of a summer. The results showed that the two MSMs have notable wet biases over the TP and can overestimate the summer precipitation by more than 4.0 mm·day−1 in some parts of the Three Rivers Source region. Moreover, both MSMs have more frequent light rainfall; increasing horizontal resolution of the MSMs alone does not reduce the excessive precipitation. Further investigation reveals that the MSMs have a spurious early‐afternoon rainfall peak, which can be linked to a strong dependence on convective available potential energy (CAPE) that dominates the wet biases. Herein, we highlight that the sensitivity of CAPE to surface temperatures may cause the MSMs to have a spurious hydrological response to surface warming. Users of climate projections should be aware of this potential model uncertainty when investigating future hydrological changes over the TP. In comparison, the CPM removes the spurious afternoon rainfall and thus significantly reduces the wet bias simulated by the MSMs. In addition, the CPM also better depicts the precipitation frequency and intensity, and is therefore a promising tool for dynamic downscaling over the TP.

Modelling mineral dust emissions and atmospheric dispersion with MADE3 in EMAC v2.54

Abstract. It was hypothesized that using mineral dust emission climatologies in global chemistry climate models (GCCMs), i.e. prescribed monthly-mean dust emissions representative of a specific year, may lead to misrepresentations of strong dust burst events. This could result in a negative bias of model dust concentrations compared to observations for these episodes. Here, we apply the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) as part of the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model. We employ two different representations of mineral dust emissions for our model simulations: (i) a prescribed monthly-mean climatology of dust emissions representative of the year 2000 and (ii) an online dust parametrization which calculates wind-driven mineral dust emissions at every model time step. We evaluate model results for these two dust representations by comparison with observations of aerosol optical depth from ground-based station data. The model results show a better agreement with the observations for strong dust burst events when using the online dust representation compared to the prescribed dust emissions setup. Furthermore, we analyse the effect of increasing the vertical and horizontal model resolution on the mineral dust properties in our model. We compare results from simulations with T42L31 and T63L31 model resolution (2.8∘×2.8∘ and 1.9∘×1.9∘ in latitude and longitude, respectively; 31 vertical levels) with the reference setup (T42L19). The different model versions are evaluated against airborne in situ measurements performed during the SALTRACE mineral dust campaign (Saharan Aerosol Long-range Transport and Aerosol-Cloud Interaction Experiment, June–July 2013), i.e. observations of dust transported from the Sahara to the Caribbean. Results show that an increased horizontal and vertical model resolution is able to better represent the spatial distribution of airborne mineral dust, especially in the upper troposphere (above 400 hPa). Additionally, we analyse the effect of varying assumptions for the size distribution of emitted dust but find only a weak sensitivity concerning these changes. The results of this study will help to identify the model setup best suited for future studies and to further improve the representation of mineral dust particles in EMAC-MADE3.

Highly resolved WRF-BEP/BEM simulations over Barcelona urban area with LCZ

This study evaluates the performance of urban schemes integrated in the Weather Research and Forecasting model (WRF) using Local Climate Zones (LCZ) as land use classification. We applied two multi-layer urban schemes: 1) Building Effect Parameterization (BEP) and 2) Building Energy Model coupled with BEP (BEP + BEM), over the Metropolitan Area of Barcelona (MAB) at 1km2 horizontal resolution for July 2016. These two simulations were compared with observations and a standard WRF simulation (BULK approach). Corine Land Cover 2012 provides background information for the entire simulation domain, while the LCZ covers MAB classifying the land cover into 10 classes according to urban morphology and thermal properties.BULK and multi-layer urban scheme experiments present a similar general error trend: overestimation of relative humidity and planetary boundary layer height and underestimation of temperature. Although BEP has the best correlation with observations, this is the scheme with the highest value of bias and RMSE for temperature and relative humidity, in particular during the night/morning. On the other hand, BEP + BEM performed with the minimum RMSE associated for temperature and relative humidity in the entire domain. BEP + BEM has shown to be more sensitive than the other schemes over locations where the land use in the model grid differs to the real one, which is a common consequent limitation of horizontal model resolution. This study also suggests that depending on the synoptic condition the scheme accuracy on determining PBLH might change considerably.

Effects of Convection Representation and Model Resolution on Diurnal Precipitation Cycle Over the Indian Monsoon Region: Toward a Convection‐Permitting Regional Climate Simulation

AbstractThis study investigated the reproducibility of rainfall characteristics of the Indian summer monsoon using a regional climate model (RCM), focusing on the convection representation and model horizontal grid resolution. To understand the importance of convection representation and model horizontal grid resolution, the study employed the Weather Research and Forecasting model WRFv3.8.1 as the RCM. Two series of experiments, that is, cumulus parameterization on/off (CON/COFF), were performed for the monsoon with three different spatial resolutions. Three contrasting monsoon years were selected for the simulations. The simulated rainfalls were evaluated with the India Meteorological Department data set and Tropical Rainfall Measurement Mission 3B42 Version 7. The results revealed that COFF captured fundamental aspects of the rainfall characteristics, such as diurnal cycle, rainfall intensity, and rainfall frequency. Over central India, in COFF, the diurnal precipitation peaks were simulated in afternoon/evening in close agreement with the observations. However, the diurnal precipitation peak in CON appeared 3–6 hr earlier than the observations. The diurnal precipitation variation was more associated with the horizontal grid resolution of the numerical model than representation of convection. Additionally, COFF could simulate diurnally propagating rainfall systems over the Bay of Bengal. Over the Indian land area, COFF simulated less‐frequent intense precipitation systems, whereas CON simulated more‐frequent widespread weak precipitation. This study demonstrated that convection representation is very important for simulation of diurnal rainfall systems over the Indian monsoon region, although refinement of model horizontal grid resolution is required over mountainous regions, where precipitation is closely related to orography.

Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations

Abstract. This work evaluates the statistical predictability of the Arctic sea ice volume (SIV) anomaly – here defined as the detrended and deseasonalized SIV – on the interannual timescale. To do so, we made use of six datasets, from three different atmosphere–ocean general circulation models, with two different horizontal grid resolutions each. Based on these datasets, we have developed a statistical empirical model which in turn was used to test the performance of different predictor variables, as well as to identify optimal locations from where the SIV anomaly could be better reconstructed and/or predicted. We tested the hypothesis that an ideal sampling strategy characterized by only a few optimal sampling locations can provide in situ data for statistically reproducing and/or predicting the SIV interannual variability. The results showed that, apart from the SIV itself, the sea ice thickness is the best predictor variable, although total sea ice area, sea ice concentration, sea surface temperature, and sea ice drift can also contribute to improving the prediction skill. The prediction skill can be enhanced further by combining several predictors into the statistical model. Applying the statistical model with predictor data from four well-placed locations is sufficient for reconstructing about 70 % of the SIV anomaly variance. As suggested by the results, the four first best locations are placed at the transition Chukchi Sea–central Arctic–Beaufort Sea (79.5∘ N, 158.0∘ W), near the North Pole (88.5∘ N, 40.0∘ E), at the transition central Arctic–Laptev Sea (81.5∘ N, 107.0∘ E), and offshore the Canadian Archipelago (82.5∘ N, 109.0∘ W), in this respective order. Adding further to six well-placed locations, which explain about 80 % of the SIV anomaly variance, the statistical predictability does not substantially improve taking into account that 10 locations explain about 84 % of that variance. An improved model horizontal resolution allows a better trained statistical model so that the reconstructed values better approach the original SIV anomaly. On the other hand, if we inspect the interannual variability, the predictors provided by numerical models with lower horizontal resolution perform better when reconstructing the original SIV variability. We believe that this study provides recommendations for the ongoing and upcoming observational initiatives, in terms of an Arctic optimal observing design, for studying and predicting not only the SIV values but also its interannual variability.

Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

The impact of regional climate model formulation and resolution on simulated precipitation in Africa

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs (SMHI-RCA4 and HCLIM38-ALADIN) are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100, and 200 km. In addition to the two RCMs, two different parameter settings (configurations) of the same RCA4 are used. By contrasting different downscaling experiments, it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation, while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle in precipitation is completely controlled by model formulation (convection scheme), while its amplitude is a function of resolution. However, the impact of higher resolution on the time-mean climate is mixed. An improvement in one region/season (e.g. reduction in dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). At the same time, higher resolution leads to a more realistic distribution of daily precipitation. Consequently, even if the time-mean climate is not always greatly sensitive to resolution, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and can, in general, not be considered as an added value of downscaling.

Assessment of a Coastal Offshore Wind Climate by Means of Mesoscale Model Simulations Considering High-Resolution Land Use and Sea Surface Temperature Data Sets

In this study, offshore wind climate assessments are carried out by using mesoscale model Weather Research and Forecasting (WRF) and validated by measurement at a demonstration site located 3.1 km offshore of Choshi. An optimal nudging method is investigated by using offshore and meteorological observations. The land-use datasets are then created from a higher-resolution land-use data by using a maximum area sampling scheme according to the horizontal resolution of the mesoscale model. Finally, the sea surface temperature datasets are corrected by observation data. It is found that the relative error of annual wind speed is reduced from 7.3% to 2.2% and the correlation coefficient between predicted and measured wind speed is improved from 0.80 to 0.84 by considering the effects of land-use and sea surface temperature.

Impact of horizontal resolution on sea surface temperature bias and air–sea interactions over the tropical Indian Ocean in CFSv2 coupled model

AbstractThe cold bias in sea surface temperature (SST) over the Tropical Indian Ocean (TIO) in Climate Forecast System version 2 (CFSv2) has been a limiting hurdle in predicting the Indian summer monsoon rainfall (ISMR). The present study addresses the impact of increasing horizontal resolution of the atmospheric model of CFSv2 from a low resolution (T126, ~100 km) to a high resolution (T382, ~38 km) in improving the SST and Ocean mixed layer simulation. The high resolution run has reasonably reduced the SST cold bias (−0.8 to −0.2°C) over southern TIO and (−0.69 to 0.07°C) over northern TIO, however, a moderate warm bias of 0.37°C is observed over the tropical Pacific Ocean in T382 run. We have conducted a mixed layer heat budget analysis to understand the causative factors responsible for improved SST simulation. The improvement in net heat fluxes resulted in reduced biases in SST over TIO in T382 simulation. Better simulation of the entrainment process has further improved SST over Southern TIO. The high‐resolution atmospheric model is able to resolve convection centres reasonably well, therefore resulted in better simulation of winds, which enabled better prediction of Ocean mixed layer. The low and middle clouds are also better resolved in high resolution run, the total cloud cover is well predicted by the T382 run, hence the biases in radiative and heat fluxes are decreased significantly compared with its lower resolution model, which improved the radiation fluxes and responsible for the observed improvement in SST and mixed layer prediction. The dominance of biases in net shortwave radiation resulting in moderate positive SST biases over the Northern tropical Pacific Ocean.

Configuration of Statistical Postprocessing Techniques for Improved Low-Level Wind Speed Forecasts in West Texas

Abstract The wind energy industry needs accurate forecasts of wind speeds at turbine hub height and in the rotor layer to accurately predict power output from a wind farm. Current numerical weather prediction (NWP) models struggle to accurately predict low-level winds, partially due to systematic errors within the models due to deficiencies in physics parameterization schemes. These types of errors are addressed in this study with two statistical postprocessing techniques—model output statistics (MOS) and the analog ensemble (AnEn)—to understand the value of each technique in improving rotor-layer wind forecasts. This study is unique in that it compares the techniques using a sonic detection and ranging (SODAR) wind speed dataset that spans the entire turbine rotor layer. This study uses reforecasts from the Weather Research and Forecasting (WRF) Model and observations in west Texas over periods of up to two years to examine the skill added to forecasts when applying both MOS and the AnEn. Different aspects of the techniques are tested, including model horizontal and vertical resolution, number of predictors, and training set length. Both MOS and the AnEn are applied to several levels representing heights in the turbine rotor layer (40, 60, 80, 100, and 120 m). This study demonstrates the degree of improvement that different configurations of each technique provides to raw WRF forecasts, to help guide their use for low-level wind speed forecasts. It was found that both AnEn and MOS show significant improvement over the raw WRF forecasts, but the two methods do not differ significantly from each other.

Simulation of mixed-phase clouds with the ICON large-eddy model in the complex Arctic environment around Ny-Ålesund

Abstract. Low-level mixed-phase clouds have a substantial impact on the redistribution of radiative energy in the Arctic and are a potential driving factor in Arctic amplification. To better understand the complex processes around mixed-phase clouds, a combination of long-term measurements and high-resolution modeling able to resolve the relevant processes is essential. In this study, we show the general feasibility of the new high-resolution icosahedral nonhydrostatic large-eddy model (ICON-LEM) to capture the general structure, type and timing of mixed-phase clouds at the Arctic site Ny-Ålesund and its potential and limitations for further detailed research. To serve as a basic evaluation, the model is confronted with data streams of single instruments including a microwave radiometer and cloud radar and also with value-added products like the CloudNet classification. The analysis is based on a 11 d long time period with selected periods studied in more detail focusing on the representation of particular cloud processes, such as mixed-phase microphysics. In addition, targeted statistical evaluations against observational data sets are performed to assess (i) how well the vertical structure of the clouds is represented and (ii) how much information is added by higher horizontal resolutions. The results clearly demonstrate the advantage of high resolutions. In particular, with the highest horizontal model resolution of 75 m, the variability of the liquid water path can be well captured. By comparing neighboring grid cells for different subdomains, we also show the potential of the model to provide information on the representativity of single sites (such as Ny-Ålesund) for a larger domain.