Visualization of high-resolution climate model output in a Visualization dome

2020 ◽  
Author(s):  
Florian Ziemen ◽  
Niklas Röber ◽  
Dela Spickermann ◽  
Michael Böttinger
Keyword(s):  
Data Storage ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Second Phase ◽  
Great Level ◽  
Model Output ◽  
Data Generation ◽  
Max Planck ◽  
Earth Planet

<p>The new generation of global storm-resolving climate models yields model output at unprecedented resolution, going way beyond what can be displayed on a state-of-the-art computer screen. This data can be visualized in photo-realistic renderings that cannot be easily distinguished from satellite data (e.g. Stevens et al, 2019). The EU-funded Centre of Excellence in Simulation of Weather and Climate in Europe (ESiWACE) enables this kind of simulations through improvements of model performance, data storage and processing. It is closely related with the DYAMOND model intercomparison project. The Max-Planck-Institute for Meteorology (MPI-M) will contribute to the second phase of the DYAMOND intercomparison with coupled global 5 km-resolving atmosphere-ocean climate simulations, internally called DYAMOND++.<br><br>Because of the great level of detail, these simulations are especially appealing for scientific outreach. In this PICO presentation we will illustrate how we turn the output of a DYAMOND++ test simulation into a movie clip for dome theaters, as used in the WISDOME contest of the IEEE EUROVIS conference and in planetaria and science centers. Our presentation outlines the main steps of this process from data generation via pre-processing to the methods employed in the rendering of the scenes.</p><p>Stevens, B., Satoh, M., Auger, L. et al.: DYAMOND: the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains. Prog Earth Planet Sci (2019) 6: 61. https://doi.org/10.1186/s40645-019-0304-z</p>

scholarly journals The HAMMONIA Chemistry Climate Model: Sensitivity of the Mesopause Region to the 11-Year Solar Cycle and CO2 Doubling

2006 ◽  
Vol 19 (16) ◽  
pp. 3903-3931 ◽  
Author(s):  
H. Schmidt ◽  
G. P. Brasseur ◽  
M. Charron ◽  
E. Manzini ◽  
M. A. Giorgetta ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Solar Cycle ◽  
General Circulation ◽  
Climate Model ◽  
Temperature Response ◽  
Circulation Model ◽  
Max Planck ◽  
Dynamical Processes ◽  
Mesopause Region ◽  
Height Range

Abstract This paper introduces the three-dimensional Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), which treats atmospheric dynamics, radiation, and chemistry interactively for the height range from the earth’s surface to the thermosphere (approximately 250 km). It is based on the latest version of the ECHAM atmospheric general circulation model of the Max Planck Institute for Meteorology in Hamburg, Germany, which is extended to include important radiative and dynamical processes of the upper atmosphere and is coupled to a chemistry module containing 48 compounds. The model is applied to study the effects of natural and anthropogenic climate forcing on the atmosphere, represented, on the one hand, by the 11-yr solar cycle and, on the other hand, by a doubling of the present-day concentration of carbon dioxide. The numerical experiments are analyzed with the focus on the effects on temperature and chemical composition in the mesopause region. Results include a temperature response to the solar cycle by 2 to 10 K in the mesopause region with the largest values occurring slightly above the summer mesopause. Ozone in the secondary maximum increases by up to 20% for solar maximum conditions. Changes in winds are in general small. In the case of a doubling of carbon dioxide the simulation indicates a cooling of the atmosphere everywhere above the tropopause but by the smallest values around the mesopause. It is shown that the temperature response up to the mesopause is strongly influenced by changes in dynamics. During Northern Hemisphere summer, dynamical processes alone would lead to an almost global warming of up to 3 K in the uppermost mesosphere.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

Evaluating the Consistency between Statistically Downscaled and Global Dynamical Model Climate Change Projections

2008 ◽  
Vol 21 (22) ◽  
pp. 6052-6059 ◽  
Author(s):  
B. Timbal ◽  
P. Hope ◽  
S. Charles
Keyword(s):  
Global Warming ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Specific Humidity ◽  
Model Output ◽  
Winter Rainfall ◽  
Direct Model ◽  
The Impact

Abstract The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

scholarly journals Interhemispheric differences of mesosphere/lower thermosphere winds and tides investigated from three whole atmosphere models and meteor radar observations

2021 ◽  
Author(s):  
Gunter Stober ◽  
Ales Kuchar ◽  
Dimitry Pokhotelov ◽  
Huixin Liu ◽  
Han-Li Liu ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Lower Thermosphere ◽  
Winter Season ◽  
General Circulation Models ◽  
Meteor Radar ◽  
Radar Observations ◽  
Seasonal Characteristics

Abstract. Long-term and continuous observations of mesospheric/lower thermospheric winds are rare, but they are important to investigate climatological changes at these altitudes on time scales of several years, covering a solar cycle and longer. Such long time series are a natural heritage of the mesosphere/lower thermosphere climate, and they are valuable to compare climate models or long term runs of general circulation models (GCMs). Here we present a climatological comparison of wind observations from six meteor radars at two conjugate latitudes to validate the corresponding mean winds and atmospheric diurnal and semidiurnal tides from three GCMs, namely Ground-to-Topside Model of Atmosphere and Ionosphere for Aeronomy (GAIA), Whole Atmosphere Community Climate Model Extension (Specified Dynamics) (WACCM-X(SD)) and Upper Atmosphere ICOsahedral Non-hydrostatic (UA-ICON) model. Our results indicate that there are interhemispheric differences in the seasonal characteristics of the diurnal and semidiurnal tide. There also are some differences in the mean wind climatologies of the models and the observations. Our results indicate that GAIA shows a reasonable agreement with the meteor radar observations during the winter season, whereas WACCM-X(SD) shows a better agreement with the radars for the hemispheric zonal summer wind reversal, which is more consistent with the meteor radar observations. The free running UA-ICON tends to show similar winds and tides compared to WACCM-X(SD).

scholarly journals Deep Learning for Climate Model Output Statistics

2021 ◽  
Author(s):  
Michael Steininger ◽  
Daniel Abel ◽  
Katrin Ziegler ◽  
Anna Krause ◽  
Heiko Paeth ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Deep Learning ◽  
Climate Models ◽  
Climate Model ◽  
Model Output ◽  
Climate Change Effects ◽  
Climate Model Output ◽  
Improved Performance ◽  
Model Output Statistics

<p>Climate models are an important tool for the assessment of prospective climate change effects but they suffer from systematic and representation errors, especially for precipitation. Model output statistics (MOS) reduce these errors by fitting the model output to observational data with machine learning. In this work, we explore the feasibility and potential of deep learning with convolutional neural networks (CNNs) for MOS. We propose the CNN architecture ConvMOS specifically designed for reducing errors in climate model outputs and apply it to the climate model REMO. Our results show a considerable reduction of errors and mostly improved performance compared to three commonly used MOS approaches.</p>

scholarly journals Net effect of the QBO in a chemistry climate model

2008 ◽  
Vol 8 (21) ◽  
pp. 6505-6525 ◽  
Author(s):  
H. J. Punge ◽  
M. A. Giorgetta
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Meridional Circulation ◽  
Vortex Formation ◽  
General Circulation Models ◽  
Quasi Biennial Oscillation ◽  
The Mean ◽  
The Tropics

Abstract. The quasi-biennial oscillation (QBO) of zonal wind is a prominent mode of variability in the tropical stratosphere. It affects not only the meridional circulation and temperature over a wide latitude range but also the transport and chemistry of trace gases such as ozone. Compared to a QBO less circulation, the long-term climatological means of these quantities are also different. These climatological net effects of the QBO can be studied in general circulation models that extend into the middle atmosphere and have a chemistry and transport component, so-called Chemistry Climate Models (CCMs). In this work we show that the CCM MAECHAM4-CHEM can reproduce the observed QBO variations in temperature and ozone mole fractions when nudged towards observed winds. In particular, it is shown that the QBO signal in transport of nitrogen oxides NOx plays an important role in reproducing the observed ozone QBO, which features a phase reversal slightly below the level of maximum of the ozone mole fraction in the tropics. We then compare two 20-year experiments with the MAECHAM4-CHEM model that differ by including or not including the QBO. The mean wind fields differ between the two model runs, especially during summer and fall seasons in both hemispheres. The differences in the wind field lead to differences in the meridional circulation, by the same mechanism that causes the QBO's secondary meridional circulation, and thereby affect mean temperatures and the mean transport of tracers. In the tropics, the net effect on ozone is mostly due to net differences in upwelling and, higher up, the associated temperature change. We show that a net surplus of up to 15% in NOx in the tropics above 10 hPa in the experiment that includes the QBO does not lead to significantly different volume mixing ratios of ozone. We also note a slight increase in the southern vortex strength as well as earlier vortex formation in northern winter. Polar temperatures differ accordingly. Differences in the strength of the Brewer-Dobson circulation and in further trace gas concentrations are analysed. Our findings underline the importance of a representation of the QBO in CCMs.

scholarly journals Effect of prescribed sea surface conditions on the modern and future Antarctic surface climate simulated by the ARPEGE atmosphere general circulation model

2019 ◽  
Vol 13 (11) ◽  
pp. 3023-3043
Author(s):  
Julien Beaumet ◽  
Michel Déqué ◽  
Gerhard Krinner ◽  
Cécile Agosta ◽  
Antoinette Alias
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Model ◽  
Sea Surface ◽  
Coupled Climate Model ◽  
Surface Climate ◽  
Late 21St Century ◽  
The Antarctic

Abstract. Owing to increase in snowfall, the Antarctic Ice Sheet surface mass balance is expected to increase by the end of the current century. Assuming no associated response of ice dynamics, this will be a negative contribution to sea-level rise. However, the assessment of these changes using dynamical downscaling of coupled climate model projections still bears considerable uncertainties due to poorly represented high-southern-latitude atmospheric circulation and sea surface conditions (SSCs), that is sea surface temperature and sea ice concentration. This study evaluates the Antarctic surface climate simulated using a global high-resolution atmospheric model and assesses the effects on the simulated Antarctic surface climate of two different SSC data sets obtained from two coupled climate model projections. The two coupled models from which SSCs are taken, MIROC-ESM and NorESM1-M, simulate future Antarctic sea ice trends at the opposite ends of the CMIP5 RCP8.5 projection range. The atmospheric model ARPEGE is used with a stretched grid configuration in order to achieve an average horizontal resolution of 35 km over Antarctica. Over the 1981–2010 period, ARPEGE is driven by the SSCs from MIROC-ESM, NorESM1-M and CMIP5 historical runs and by observed SSCs. These three simulations are evaluated against the ERA-Interim reanalyses for atmospheric general circulation as well as the MAR regional climate model and in situ observations for surface climate. For the late 21st century, SSCs from the same coupled climate models forced by the RCP8.5 emission scenario are used both directly and bias-corrected with an anomaly method which consists in adding the future climate anomaly from coupled model projections to the observed SSCs with taking into account the quantile distribution of these anomalies. We evaluate the effects of driving the atmospheric model by the bias-corrected instead of the original SSCs. For the simulation using SSCs from NorESM1-M, no significantly different climate change signals over Antarctica as a whole are found when bias-corrected SSCs are used. For the simulation driven by MIROC-ESM SSCs, a significant additional increase in precipitation and in winter temperatures for the Antarctic Ice Sheet is obtained when using bias-corrected SSCs. For the range of Antarctic warming found (+3 to +4 K), we confirm that snowfall increase will largely outweigh increases in melt and rainfall. Using the end members of sea ice trends from the CMIP5 RCP8.5 projections, the difference in warming obtained (∼ 1 K) is much smaller than the spread of the CMIP5 Antarctic warming projections. This confirms that the errors in representing the Southern Hemisphere atmospheric circulation in climate models are also determinant for the diversity of their projected late 21st century Antarctic climate change.

scholarly journals The 1986–1989 ENSO cycle in a chemical climate model

2006 ◽  
Vol 6 (12) ◽  
pp. 4669-4685 ◽  
Author(s):  
S. Brönnimann ◽  
M. Schraner ◽  
B. Müller ◽  
A. Fischer ◽  
D. Brunner ◽  
...  
Keyword(s):  
North Atlantic ◽  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Circulation Model ◽  
Enso Cycle ◽  
Atlantic Sector ◽  
Ensemble Simulations ◽  
Chemical Climate ◽  
Middle Stratosphere

Abstract. A pronounced ENSO cycle occurred from 1986 to 1989, accompanied by distinct dynamical and chemical anomalies in the global troposphere and stratosphere. Reproducing these effects with current climate models not only provides a model test but also contributes to our still limited understanding of ENSO's effect on stratosphere-troposphere coupling. We performed several sets of ensemble simulations with a chemical climate model (SOCOL) forced with global sea surface temperatures. Results were compared with observations and with large-ensemble simulations performed with an atmospheric general circulation model (MRF9). We focus our analysis on the extratropical stratosphere and its coupling with the troposphere. In this context, the circulation over the North Atlantic sector is particularly important. Relative to the La Niña winter 1989, observations for the El Niño winter 1987 show a negative North Atlantic Oscillation index with corresponding changes in temperature and precipitation patterns, a weak polar vortex, a warm Arctic middle stratosphere, negative and positive total ozone anomalies in the tropics and at middle to high latitudes, respectively, as well as anomalous upward and poleward Eliassen-Palm (EP) flux in the midlatitude lower stratosphere. Most of the tropospheric features are well reproduced in the ensemble means in both models, though the amplitudes are underestimated. In the stratosphere, the SOCOL simulations compare well with observations with respect to zonal wind, temperature, EP flux, meridional mass streamfunction, and ozone, but magnitudes are underestimated in the middle stratosphere. With respect to the mechanisms relating ENSO to stratospheric circulation, the results suggest that both, upward and poleward components of anomalous EP flux are important for obtaining the stratospheric signal and that an increase in strength of the Brewer-Dobson circulation is part of that signal.

scholarly journals Does Quantile Mapping of Simulated Precipitation Correct for Biases in Transition Probabilities and Spell Lengths?

2016 ◽  
Vol 29 (5) ◽  
pp. 1605-1615 ◽  
Author(s):  
Jan Rajczak ◽  
Sven Kotlarski ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Transition Probabilities ◽  
Weather Generator ◽  
Mapping Technique ◽  
Model Output ◽  
Quantile Mapping ◽  
Stochastic Weather Generator ◽  
Simulated Precipitation ◽  
Climate Model Output

Abstract Climate impact studies constitute the basis for the formulation of adaptation strategies. Usually such assessments apply statistically postprocessed output of climate model projections to force impact models. Increasingly, time series with daily resolution are used, which require high consistency, for instance with respect to transition probabilities (TPs) between wet and dry days and spell durations. However, both climate models and commonly applied statistical tools have considerable uncertainties and drawbacks. This paper compares the ability of 1) raw regional climate model (RCM) output, 2) bias-corrected RCM output, and 3) a conventional weather generator (WG) that has been calibrated to match observed TPs to simulate the sequence of dry, wet, and very wet days at a set of long-term weather stations across Switzerland. The study finds systematic biases in TPs and spell lengths for raw RCM output, but a substantial improvement after bias correction using the deterministic quantile mapping technique. For the region considered, bias-corrected climate model output agrees well with observations in terms of TPs as well as dry and wet spell durations. For the majority of cases (models and stations) bias-corrected climate model output is similar in skill to a simple Markov chain stochastic weather generator. There is strong evidence that bias-corrected climate model simulations capture the atmospheric event sequence more realistically than a simple WG.

scholarly journals Climate Model Biases in the Width of the Tropical Belt

2016 ◽  
Vol 29 (5) ◽  
pp. 1935-1954 ◽  
Author(s):  
Nicholas Davis ◽  
Thomas Birner
Keyword(s):  
Seasonal Cycle ◽  
Climate Models ◽  
Climate Model ◽  
Large Fraction ◽  
Horizontal Resolution ◽  
Hadley Cell ◽  
Second Phase ◽  
Cell Width ◽  
Mean Width ◽  
The Mean

Abstract Earth’s arid subtropics are situated at the edges of the tropical belt, which encircles the planet along the equator and covers half of its surface area. The climate of the tropical belt is strongly influenced by the Hadley cells, with their subsidence and easterly trade winds both sustaining the aridity at the belt’s edges. The understanding of Earth’s past, present, and future climates is contingent on understanding the dynamics influencing this region. An important but unanswered question is how realistically climate models reproduce the mean state of the tropical belt. This study augments the existing literature by examining the mean width and seasonality of the tropical belt in climate models from phase 5 of CMIP (CMIP5) and experiments from the second phase of the Chemistry–Climate Model Validation (CCMVal-2) activity of the Stratospheric Processes and Their Role in Climate (SPARC) project. While the models overall reproduce the structure of the tropical belt width’s seasonal cycle, they underestimate its amplitude and cannot consistently reproduce the seasonal cycle lag between the Northern Hemisphere Hadley cell edge and subtropical jet latitudes found in observations. Additionally, up to 50% of the intermodel variation in mean tropical belt width can be attributed to model horizontal resolution, with finer resolution leading to a narrower tropical belt. Finer resolution is associated with an equatorward shift and intensification of subtropical eddy momentum flux convergence, which via the Coriolis torque explains essentially all of the grid-size bias and a large fraction of the total intermodel variation in Hadley cell width.

Sign in / Sign up

Export Citation Format

Share Document