Towards European-Scale Convection-Resolving Climate Simulations

Abstract. The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Using horizontal grid spacings of O(1km), convection-resolving weather and climate models allow to explicitly resolve deep convection. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in supercomputing have led to new hybrid node designs, mixing conventional multicore CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to these architectures is the COSMO model. Here we demonstrate the convection-resolving COSMO model on continental scales using a version of the model capable of using GPU accelerators. The verification of a week-long simulation containing winter storm Kyrill shows that, for this case, convection-parameterizing simulations and convection-resolving simulations agree well. Furthermore we demonstrate the applicability of the approach to longer simulations by conducting a three-month long simulation of the summer season 2006. Its results corroborate the findings found on smaller domains such as more credible representation of the diurnal cycle of precipitation in convection-resolving models and a tendency to produce more intensive hourly precipitation events. Both simulations also show how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. This includes the formation of sharp cold frontal structures, convection embedded in fronts and small eddies, or the formation and organization of propagating cold pools. Finally we assess the performance gain from using heterogeneous hardware equipped with GPUs with respect to multi-core hardware. With the COSMO model, we now use a climate model that has all the necessary modules required for real-case convection-resolving climate simulations on GPUs.

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Towards European-scale convection-resolving climate simulations with GPUs: a study with COSMO 4.19

Geoscientific Model Development ◽

10.5194/gmd-9-3393-2016 ◽

2016 ◽

Vol 9 (9) ◽

pp. 3393-3412 ◽

Cited By ~ 40

Author(s):

David Leutwyler ◽

Oliver Fuhrer ◽

Xavier Lapillonne ◽

Daniel Lüthi ◽

Christoph Schär

Keyword(s):

Graphics Processing Units ◽

Climate Models ◽

Climate Model ◽

Deep Convection ◽

Regional Climate ◽

Small Scale ◽

Moist Convection ◽

Cosmo Model ◽

Climate Simulations ◽

Weather And Climate

Abstract. The representation of moist convection in climate models represents a major challenge, due to the small scales involved. Using horizontal grid spacings of O(1km), convection-resolving weather and climate models allows one to explicitly resolve deep convection. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in supercomputing have led to new hybrid node designs, mixing conventional multi-core hardware and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to these architectures is the COSMO (Consortium for Small-scale Modeling) model.Here we present the convection-resolving COSMO model on continental scales using a version of the model capable of using GPU accelerators. The verification of a week-long simulation containing winter storm Kyrill shows that, for this case, convection-parameterizing simulations and convection-resolving simulations agree well. Furthermore, we demonstrate the applicability of the approach to longer simulations by conducting a 3-month-long simulation of the summer season 2006. Its results corroborate the findings found on smaller domains such as more credible representation of the diurnal cycle of precipitation in convection-resolving models and a tendency to produce more intensive hourly precipitation events. Both simulations also show how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. This includes the formation of sharp cold frontal structures, convection embedded in fronts and small eddies, or the formation and organization of propagating cold pools. Finally, we assess the performance gain from using heterogeneous hardware equipped with GPUs relative to multi-core hardware. With the COSMO model, we now use a weather and climate model that has all the necessary modules required for real-case convection-resolving regional climate simulations on GPUs.

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GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1719842115 ◽

2018 ◽

Vol 115 (18) ◽

pp. 4577-4582 ◽

Cited By ~ 9

Author(s):

Kathleen A. Schiro ◽

Fiaz Ahmed ◽

Scott E. Giangrande ◽

J. David Neelin

Keyword(s):

Climate Models ◽

Climate Model ◽

Deep Convection ◽

Potential Temperature ◽

Strong Relationship ◽

Field Campaign ◽

Convective Systems ◽

Tropical Oceans ◽

Mesoscale Convective ◽

Environmental Air

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014–2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation–buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

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Tropical convection regimes in climate models: evaluation with satellite observations

10.5194/acp-2017-669 ◽

2017 ◽

Author(s):

Andrea K. Steiner ◽

Bettina C. Lackner ◽

Mark A. Ringer

Keyword(s):

Climate Models ◽

Lower Stratosphere ◽

Deep Convection ◽

Atmospheric Temperature ◽

Tropical Convection ◽

Specific Humidity ◽

Moist Convection ◽

Tropopause Region ◽

Tropical Troposphere ◽

Unique Source

Abstract. High quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent high updraft or downdraft velocities. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 % to 30 % over oceans whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next generation climate models.

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Influence of parallel computational uncertainty on simulations of the Coupled General Climate Model

Geoscientific Model Development ◽

10.5194/gmd-5-313-2012 ◽

2012 ◽

Vol 5 (2) ◽

pp. 313-319 ◽

Cited By ~ 10

Author(s):

Z. Song ◽

F. Qiao ◽

X. Lei ◽

C. Wang

Keyword(s):

Climate Models ◽

Climate Model ◽

Quality Standard ◽

Ensemble Member ◽

Climate System ◽

Climate System Model ◽

Climate Simulations ◽

Computational Uncertainty ◽

The Impact ◽

General Climate

Abstract. This paper investigates the impact of the parallel computational uncertainty due to the round-off error on climate simulations using the Community Climate System Model Version 3 (CCSM3). A series of sensitivity experiments have been conducted and the analyses are focused on the Global and Nino3.4 average sea surface temperatures (SST). For the monthly time series, it is shown that the amplitude of the deviation induced by the parallel computational uncertainty is the same order as that of the climate system change. However, the ensemble mean method can reduce the influence and the ensemble member number of 15 is enough to ignore the uncertainty. For climatology, the influence can be ignored when the climatological mean is calculated by using more than 30-yr simulations. It is also found that the parallel computational uncertainty has no distinguishable effect on power spectrum analysis of climate variability such as ENSO. Finally, it is suggested that the influence of the parallel computational uncertainty on Coupled General Climate Models (CGCMs) can be a quality standard or a metric for developing CGCMs.

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A suite of Early Eocene (~55 Ma) climate model boundary conditions

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-529-2014 ◽

2014 ◽

Vol 7 (1) ◽

pp. 529-562 ◽

Cited By ~ 3

Author(s):

N. Herold ◽

J. Buzan ◽

M. Seton ◽

A. Goldner ◽

J. A. M. Green ◽

...

Keyword(s):

Boundary Conditions ◽

Climate Models ◽

Climate Model ◽

Drake Passage ◽

Climate Modelling ◽

Early Eocene ◽

Tidal Dissipation ◽

Isthmus Of Panama ◽

Climate Simulations ◽

First Time

Abstract. We describe a set of Early Eocene (~55 Ma) climate model boundary conditions constructed in a self-consistent reference frame and incorporating recent data and methodologies. Given the growing need for uniform experimental design within the Eocene climate modelling community, we make publically available our datasets of Eocene topography, bathymetry, tidal dissipation, vegetation, aerosol distributions and river runoff. Particularly our Eocene topography and bathymetry has been significantly improved compared to previously utilized boundary conditions. Major improvements include the paleogeography of Antarctica, Australia, Europe, the Drake Passage and the Isthmus of Panama, and our boundary conditions include modelled estimates of Eocene aerosol distributions and tidal dissipation for the first time, both consistent with our paleotopography and paleobathymetry. The resolution of our datasets (1° × 1°) is also unprecedented and will facilitate high resolution climate simulations. In light of the inherent uncertainties involved in reconstructing global boundary conditions for past time periods these datasets should be considered as one interpretation of the available data. This paper marks the beginning of a process for reconstructing a set of accurate, open-access Eocene boundary conditions for use in climate models.

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Coupling of a sediment diagenesis model (MEDUSA) and an Earth system model (CESM1.2): a contribution toward enhanced marine biogeochemical modelling and long-term climate simulations

10.5194/gmd-2019-231 ◽

2019 ◽

Author(s):

Takasumi Kurahashi-Nakamura ◽

André Paul ◽

Guy Munhoven ◽

Ute Merkel ◽

Michael Schulz

Keyword(s):

Climate Models ◽

Climate Model ◽

Coupled Model ◽

Earth System Model ◽

System Model ◽

Future Application ◽

Coupling Scheme ◽

Earth System ◽

Climate Simulations

Abstract. We developed a coupling scheme for the Community Earth System Model version 1.2 (CESM1.2) and the Model of Early Diagenesis in the Upper Sediment of Adjustable complexity (MEDUSA), and explored the effects of the coupling on solid components in the upper sediment and on bottom seawater chemistry by comparing the coupled model's behaviour with that of the uncoupled CESM having a simplified treatment of sediment processes. CESM is a fully-coupled atmosphere-ocean-sea ice-land model and its ocean component (the Parallel Ocean Program version 2, POP2) includes a biogeochemical component (BEC). MEDUSA was coupled to POP2 in an off-line manner so that each of the models ran separately and sequentially with regular exchanges of necessary boundary condition fields. This development was done with the ambitious aim of a future application for long-term (spanning a full glacial cycle; i.e., ~ 105 years) climate simulations with a state-of-the-art comprehensive climate model including the carbon cycle, and was motivated by the fact that until now such simulations have been done only with less-complex climate models. We found that the sediment-model coupling already had non-negligible immediate advantages for ocean biogeochemistry in millennial-time-scale simulations. First, the MEDUSA-coupled CESM outperformed the uncoupled CESM in reproducing an observation-based global distribution of sediment properties, especially for organic carbon and opal. Thus, the coupled model is expected to act as a better bridge between climate dynamics and sedimentary data, which will provide another measure of model performance. Second, in our experiments, the MEDUSA-coupled model and the uncoupled model had a difference of 0.2‰ or larger in terms of δ13C of bottom water over large areas, which implied potential significant model biases for bottom seawater chemical composition due to a different way of sediment treatment. Such a model bias would be a fundamental issue for paleo model–data comparison often relying on data derived from benthic foraminifera.

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Improving snowfall representation in climate simulations via statistical models informed by air temperature and total precipitation

10.5194/nhess-2020-352 ◽

2020 ◽

Author(s):

Flavio Maria Emanuele Pons ◽

Davide Faranda

Keyword(s):

Bias Correction ◽

Climate Models ◽

Climate Model ◽

Accurate Estimation ◽

Near Surface ◽

Temperature And Precipitation ◽

Climate Simulations ◽

Threshold Temperatures ◽

Out Of Sample

Abstract. The description and analysis of compound extremes affecting mid and high latitudes in the winter requires an accurate estimation of snowfall. Such variable is often missing for in-situ observations, and biased in climate model outputs, both in magnitude and number of events. While climate models can be adjusted using bias correction (BC), snowfall presents additional challenges compared to other variables, preventing from applying traditional univariate BC methods. We extend the existing literature on the estimation of the snowfall fraction from near-surface temperature, which usually involves binary thresholds or fitting parametric nonlinear functions. We show that, combining breakpoint search algorithms to define threshold temperatures and segmented regression models, it is possible to obtain accurate out-of-sample estimates of snowfall over Europe in ERA5 reanalysis, and to perform effective BC on the IPSL-WRF high resolution EURO-CORDEX climate model only relying on bias adjusted temperature and precipitation. This method offers a feasible way to reconstruct or adjust snowfall observations without requiring multivariate or conditional bias correction and stochastic generation of unobserved events.

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Role of Convection–circulation Coupling in the Propagation Mechanism of the Madden–Julian Oscillation over the Maritime Continent in Climate Models

10.21203/rs.3.rs-343249/v1 ◽

2021 ◽

Author(s):

Yi-Chi Wang ◽

Wan-Ling Tseng ◽

Huang-Hsiung Hsu

Keyword(s):

Climate Models ◽

Environmental Changes ◽

Deep Convection ◽

Ocean Model ◽

Cumulus Parameterization ◽

Propagation Mechanism ◽

Madden Julian Oscillation ◽

Moist Convection ◽

Maritime Continent

Abstract This study investigates the role of convection–circulation coupling on the simulated eastward propagation of the Madden–Julian Oscillation (MJO) over the Maritime Continent (MC). Experiments are conducted with the European Centre Hamburg Model Version 5 (ECHAM5) coupled with the one-column ocean model – Snow-Ice-Thermocline (SIT) and two different cumulus schemes, Nordeng (E5SIT-Nord) and Tiedtke (E5SIT-Tied). During the early phase of MJO composites, the E5SIT-Nord simulation reveals stronger intraseasonal anomalies in the apparent heat source (Q1) over the convective center, however, the E5SIT-Tied produces a stronger background Q1, suggesting that deep convection prevails over the MC but does not couple with the MJO circulation. Similarly, in the E5SIT-Tied simulation, in-column moisture is kept mostly by local deep convection over the MC, which is in contrast to the well-correlated relationship between moisture anomaly and MJO circulation in E5SIT-Nord. A case study based on an observational MJO reveals similar biases concerning of convection–circulation coupling emerges within a few days of simulations. The E5SIT-Tied simulation produces weaker heating at the convective center of the MJO than the E5SIT-Nord a few days after model initiation, resulting weaker subsidence to the east and less favorable for propagation. The present findings highlight the instantaneous responses of cumulus parameterization schemes to MJO-related environmental changes can further affect intraseasonal variability through altering convection–circulation coupling over the MC. Physical schemes of moist convection are essential to realistically represent this coupling and thereby improve the simulation of the eastward propagation of the MJO.

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Reconciling the BDC response in climate models to the volcanic forcings with reanalyses

10.5194/egusphere-egu2020-17508 ◽

2020 ◽

Author(s):

Mohamadou Diallo ◽

Hella Garny ◽

Roland Eichinger ◽

Valentina Aquila ◽

Manfred Ern ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Model Simulations ◽

Current Climate ◽

Climate Simulations ◽

Pinatubo Eruption ◽

Speed Up ◽

Stratospheric Circulation ◽

Volcanic Aerosols ◽

Climate Model Simulations

The stratospheric Brewer--Dobson circulation (BDC) is an important element of climate system as it determines the concentration of radiatively active trace gases like water vapor, ozone and aerosol above the tropopause. Climate models predict that increasing greenhouse gas levels speed up the stratospheric circulation. BDC changes is substantially modulated by different modes of climate variability (QBO, ENSO, solar cycle), including the volcanic aerosols. However, such variability is often not reliably included or represented in current climate model simulations, challenging the evaluation of models&#8217; behavior against observations and constituting a major uncertainty in current climate simulations.&#160;Here, we investigate the main differences between the reanalysis and the CCMI/CMIP6 climate models&#8217; response to stratospheric volcanic forcings regarding the depth/strength of the stratospheric BDC, with a focus on potential changes in the deep and shallow circulation branches. We also discuss the key reasons of the discrepancies (incl. uncertainties associated with volcanological forcing datasets and missing direct aerosol heating in the reanalysis) in the BDC response between reanalysis-driven and climate model simulations in the lower, mid and upper stratosphere. Finally, we assess the dynamical mechanisms involved in the volcanically-induced BDC changes to understand the opposite regime between lower, middle and upper stratosphere after the Mt Pinatubo eruption.

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Assessing Sting-Jets in Convection-Permitting Climate Simulations

10.5194/egusphere-egu2020-9158 ◽

2020 ◽

Author(s):

Colin Manning ◽

Elizabeth Kendon ◽

Hayley Fowler ◽

Nigel Roberts ◽

Ségolène Berthou

Keyword(s):

Climate Models ◽

Climate Model ◽

Surface Wind ◽

Severity Index ◽

Added Value ◽

Reanalysis Dataset ◽

Objective Indicator ◽

Wind Speeds ◽

Climate Simulations ◽

Strong Winds

This study assesses the added-value offered by a regional convection-permitting climate model (CPM) in its representation of sting-jets (SJs); a mesoscale slanted core of strong winds within a Shapiro-Keyser type of cyclone that can lead to extremely damaging surface wind speeds close to southern side of a cyclone&#8217;s centre. Low-resolution climate models cannot resolve SJs, and so estimates of risk posed by extreme winds due to SJs are difficult to determine and will likely be underestimated in coarse-resolution climate simulations.We analyse three 10-year simulations from the UK Met Office, run at a 2.2km resolution over a European domain. The simulations include a hindcast driven by the ERA-Interim reanalysis dataset (ERAI) for the period 2001-2010, as well as a present day (2001-2010) and future simulation (2100-2109) that follows the RCP8.5 scenario. Both climate simulations are driven by a 25km GCM. To diagnose potential SJ storms in each simulation, we firstly identify cyclone tracks with a cyclone tracking algorithm and apply an objective indicator that identifies the warm seclusion of a Shapiro-Keyser cyclone and the slanted core of strong winds of the sting-jet.Within this presentation, we will present the objective indicator as well as results of the added value seen in the CPM. In order to identify any added value of the CPM, we analyse differences between the CPM and its respective driving data, in terms of storm severity metrics and their future projections. &#160;An example metric used is the Storm Severity Index that quantifies the overall severity of a storm. In all simulations, the conditional PDF of SSI for sting-jet storms is shifted towards higher values compared to PDF of the SSI from all storms within the studied domain. However, we see little difference in the SSI derived from the CPM and its respective driving model/reanalysis when CPM wind speeds are upscaled to the respective driving reanalysis/GCM grid. In further analysis, we will look to explore the added value at a local scale on the native CPM grid.

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