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

2012 ◽  
Vol 5 (2) ◽  
pp. 313-319 ◽  
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.

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

2011 ◽  
Vol 4 (4) ◽  
pp. 3295-3312
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 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 sea surface temperatures. 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 simulated errors. 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 effect on the simulated periods 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.

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (20) ◽  
pp. 9441-9458 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to reproduce the present-day climate adequately. The present study illustrates the impact of these uncertainties on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA for daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. The differences in average present-day concentrations between the simulations were equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentrations between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations of 5–10 μg m−3 in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased 0.5–1.0 μg m−3 in North-West Europe and the Po Valley, but these numbers are rather uncertain: overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two climate runs did not agree on the sign of the change. This illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Volcano impacts on climate and biogeochemistry in a coupled carbon-climate model

2012 ◽  
Vol 3 (1) ◽  
pp. 279-323 ◽  
Author(s):  
D. Rothenberg ◽  
N. Mahowald ◽  
K. Lindsay ◽  
S. C. Doney ◽  
J. K. Moore ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Climate System ◽  
Dynamical Response ◽  
Good Test ◽  
Important Species ◽  
Climate System Model ◽  
Temperature And Precipitation ◽  
Wrong Reason

Abstract. Volcanic eruptions induce a dynamical response in the climate system characterized by short-term, global reductions in both surface temperature and precipitation, as well as a response in biogeochemistry. The available observations of these responses to volcanic eruptions, such as to Pinatubo, provide a valuable method to compare against model simulations. Here, the Community Climate System Model Version 3 (CCSM3) reproduces the physical climate response to volcanic eruptions in a realistic way, as compared to direct observations from the 1991 eruption of Mount Pinatubo. The model biogeochemical response to eruptions is smaller in magnitude than observed, but because of the lack observations, it is not clear why or where the modeled carbon response is not strong enough. Comparison to other models suggests that this model response is much weaker in the tropical land; however the precipitation response in other models is not accurate, suggesting that other models could be getting the right response for the wrong reason. The underestimated carbon response in the model compared to observations could also be due to the ash and lava input of biogeochemical important species to the ocean, which are not included in the simulation. A statistically significant reduction in the simulated carbon dioxide growth rate is seen at the 90% level in the average of 12 large eruptions over the period 1870–2000, and the net uptake of carbon is primarily concentrated in the tropics with large spatial variability. In addition, a method for computing the volcanic response in model output without using a control ensemble is tested against a traditional methodology using two separate ensembles of runs; the method is found to produce similar results. These results suggest that not only is simulating volcanoes a good test of coupled carbon-climate models, but also that this test can be performed without a control simulation in cases where it is not practical to run separate ensembles with and without volcanic eruptions.

scholarly journals The impact of differences in large-scale circulation output from climate models on the regional modeling of ozone and PM

2012 ◽  
Vol 12 (5) ◽  
pp. 12245-12285 ◽  
Author(s):  
A. M. M. Manders ◽  
E. van Meijgaard ◽  
A. C. Mues ◽  
R. Kranenburg ◽  
L. H. van Ulft ◽  
...  
Keyword(s):  
Air Quality ◽  
Climate Models ◽  
Climate Model ◽  
Transport Model ◽  
Global Climate Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Climate Simulations ◽  
The Impact

Abstract. Climate change may have an impact on air quality (ozone, particulate matter) due to the strong dependency of air quality on meteorology. The effect is often studied using a global climate model (GCM) to produce meteorological fields that are subsequently used by chemical transport models. However, climate models themselves are subject to large uncertainties and fail to adequately reproduce the present-day climate. The present study illustrates the impact of this uncertainty on air quality. To this end, output from the SRES-A1B constraint transient runs with two GCMs, i.e. ECHAM5 and MIROC-hires, has been dynamically downscaled with the regional climate model RACMO2 and used to force a constant emission run with the chemistry transport model LOTOS-EUROS in a one-way coupled run covering the period 1970–2060. Results from the two climate simulations have been compared with a RACMO2-LOTOS-EUROS (RLE) simulation forced by the ERA-Interim reanalysis for the period 1989–2009. Both RLE_ECHAM and RLE_MIROC showed considerable deviations from RLE_ERA in daily maximum temperature, precipitation and wind speed. Moreover, sign and magnitude of these deviations depended on the region. Differences in average concentrations for the present-day simulations were found of equal to (RLE_MIROC) or even larger than (RLE_ECHAM) the differences in concentration between present-day and future climate (2041–2060). The climate simulations agreed on a future increase in average summer ozone daily maximum concentrations (5–10 μg m−3) in parts of Southern Europe and a smaller increase in Western and Central Europe. Annual average PM10 concentrations increased (0.5–1.0 μg m−3) in North-West Europe and the Po Valley, but these numbers are rather uncertain. Overall, changes for PM10 were small, both positive and negative changes were found, and for many locations the two runs did not agree on the sign of the change. The approach taken here illustrates that results from individual climate runs can at best indicate tendencies and should therefore be interpreted with great care.

scholarly journals Bayesian Design and Analysis for Superensemble-Based Climate Forecasting

2008 ◽  
Vol 21 (9) ◽  
pp. 1891-1910 ◽  
Author(s):  
L. Mark Berliner ◽  
Yongku Kim
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Climate System ◽  
System Model ◽  
Climate System Model ◽  
Bayesian Hierarchical ◽  
Climate Forecasting ◽  
Forecasting Analysis ◽  
States Of Nature

Abstract The authors develop statistical data models to combine ensembles from multiple climate models in a fashion that accounts for uncertainty. This formulation enables treatment of model specific means, biases, and covariance matrices of the ensembles. In addition, the authors model the uncertainty in using computer model results to estimate true states of nature. Based on these models and principles of decision making in the presence of uncertainty, this paper poses the problem of superensemble experimental design in a quantitative fashion. Simple examples of the resulting optimal designs are presented. The authors also provide a Bayesian climate modeling and forecasting analysis. The climate variables of interest are Northern and Southern Hemispheric monthly averaged surface temperatures. A Bayesian hierarchical model for these quantities is constructed, including time-varying parameters that are modeled as random variables with distributions depending in part on atmospheric CO2 levels. This allows the authors to do Bayesian forecasting of temperatures under different Special Report on Emissions Scenarios (SRES). These forecasts are based on Bayesian posterior distributions of the unknowns conditional on observational data for 1882–2001 and climate system model output for 2002–97. The latter dataset is a small superensemble from the Parallel Climate Model (PCM) and the Community Climate System Model (CCSM). After summarizing the results, the paper concludes with discussion of potential generalizations of the authors’ strategies.

scholarly journals Evaluating Climate Emulation: Unit Testing of Simple Climate Models

2018 ◽  
Author(s):  
Adria K. Schwarber ◽  
Steven J. Smith ◽  
Corinne A. Hartin ◽  
Benjamin Aaron Vega-Westhoff ◽  
Ryan Sriver
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Chemical Species ◽  
Climate System ◽  
Unit Testing ◽  
Physically Based ◽  
Mean Climate ◽  
Numerical Representations ◽  
The Impact ◽  
Unit Tests

Abstract. Simple climate models (SCMs) are numerical representations of the Earth’s gas cycles and climate system. SCMs are easy to use and computationally inexpensive, making them an ideal tool in both scientific and decision-making contexts (e.g., complex climate model emulation; parameter estimation experiments; climate metric calculations; and probabilistic analyses). Despite their prolific use, the fundamental responses of SCMs are often not directly characterized. In this study, we use unit tests of three chemical species (CO2, CH4, and BC) to understand the fundamental gas cycle and climate system responses of several SCMs (Hector v2.0, MAGICC 5.3, MAGICC 6.0, FAIR v1.0, and AR5-IR). We find that while idealized SCMs are widely used, they fail to capture important global mean climate response features, which can produce biased temperature results. Comprehensive SCMs, which have non-linear forcing and physically-based carbon cycle representations, show improved responses compared to idealized SCMs. Even some comprehensive SCMs fail to capture response timescales of more complex models under BC or CO2 forcing perturbations. These results suggest where improvements should be made to SCMs. Further, we provide a set of fundamental tests that we recommend as a standard validation suite for any SCM. Unit tests allow users to understand differences in model responses and the impact of model selection on results.

scholarly journals Quantifying Agulhas Leakage in a High-Resolution Climate Model

2016 ◽  
Vol 29 (19) ◽  
pp. 6881-6892 ◽  
Author(s):  
Yu Cheng ◽  
Dian Putrasahan ◽  
Lisa Beal ◽  
Ben Kirtman
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Climate Model ◽  
Critical Role ◽  
Meridional Overturning Circulation ◽  
Climate System ◽  
Climate System Model ◽  
Mean Fields ◽  
Meridional Overturning ◽  
The Indian Ocean

Abstract The leakage of warm and salty water from the Indian Ocean via the Agulhas system into the South Atlantic may play a critical role in climate variability by modulating the buoyancy fluxes associated with the meridional overturning circulation (MOC). New climate models, such as the Community Climate System Model, version 3.5 (CCSM3.5), are now able to resolve the Agulhas retroflection and constrain the inertially choked Agulhas leakage to more realistic values. These ocean-eddy-resolving climate models are poised to bolster understanding of the sensitivity and influence of Agulhas leakage in the coupled climate system. Here, a strategy is devised to quantify Agulhas leakage in CCSM3.5 by applying an offline Lagrangian particle-tracking approach, finding a mean interbasin transport of 11.2 Sv (1 Sv ≡ 106 m3 s−1). It is shown that monthly mean outputs can be used to produce a reliable time series of Agulhas leakage variability on longer-than-seasonal time scales (correlation coefficient r = 0.88; p < 0.01) by comparing to a parallel simulation that archives daily mean fields every 5 days. The results show that Agulhas leakage variability at longer-than-seasonal time scales is less sensitive to the temporal resolution of the velocity fields than is the mean leakage transport.

scholarly journals Volcano impacts on climate and biogeochemistry in a coupled carbon–climate model

2012 ◽  
Vol 3 (2) ◽  
pp. 121-136 ◽  
Author(s):  
D. Rothenberg ◽  
N. Mahowald ◽  
K. Lindsay ◽  
S. C. Doney ◽  
J. K. Moore ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Climate System ◽  
Dynamical Response ◽  
Good Test ◽  
Important Species ◽  
Climate System Model ◽  
Temperature And Precipitation ◽  
Wrong Reason

Abstract. Volcanic eruptions induce a dynamical response in the climate system characterized by short-term global reductions in both surface temperature and precipitation, as well as a response in biogeochemistry. The available observations of these responses to volcanic eruptions, such as to Pinatubo, provide a valuable method to compare against model simulations. Here, the Community Climate System Model Version 3 (CCSM3) reproduces the physical climate response to volcanic eruptions in a realistic way, as compared to direct observations from the 1991 eruption of Mount Pinatubo. The model's biogeochemical response to eruptions is smaller in magnitude than observed, but because of the lack of observations, it is not clear why or where the modeled carbon response is not strong enough. Comparison to other models suggests that this model response is much weaker over tropical land; however, the precipitation response in other models is not accurate, suggesting that other models could be getting the right response for the wrong reason. The underestimated carbon response in the model compared to observations could also be due to the ash and lava input of biogeochemically important species to the ocean, which are not included in the simulation. A statistically significant reduction in the simulated carbon dioxide growth rate is seen at the 90% level in the average of 12 large eruptions over the period 1870–2000, and the net uptake of carbon is primarily concentrated in the tropics, with large spatial variability. In addition, a method for computing the volcanic response in model output without using a control ensemble is tested against a traditional methodology using two separate ensembles of runs; the method is found to produce similar results in the global average. These results suggest that not only is simulating volcanoes a good test of coupled carbon–climate models, but also that this test can be performed without a control simulation in cases where it is not practical to run separate ensembles with and without volcanic eruptions.

scholarly journals Evaluating climate emulation: fundamental impulse testing of simple climate models

2019 ◽  
Vol 10 (4) ◽  
pp. 729-739 ◽  
Author(s):  
Adria K. Schwarber ◽  
Steven J. Smith ◽  
Corinne A. Hartin ◽  
Benjamin Aaron Vega-Westhoff ◽  
Ryan Sriver
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Chemical Species ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate System ◽  
Physically Based ◽  
Mean Climate ◽  
The Impact

Abstract. Simple climate models (SCMs) are numerical representations of the Earth's gas cycles and climate system. SCMs are easy to use and computationally inexpensive, making them an ideal tool in both scientific and decision-making contexts (e.g., complex climate model emulation, parameter estimation experiments, climate metric calculations, and probabilistic analyses). Despite their prolific use, the fundamental responses of SCMs are often not directly characterized. In this study, we use fundamental impulse tests of three chemical species (CO2, CH4, and black carbon – BC) to understand the fundamental gas cycle and climate system responses of several comprehensive (Hector v2.0, MAGICC 5.3, MAGICC 6.0) and idealized (FAIR v1.0, AR5-IR) SCMs. We find that while idealized SCMs are widely used, they fail to capture the magnitude and timescales of global mean climate responses under emissions perturbations, which can produce biased temperature results. Comprehensive SCMs, which have physically based nonlinear forcing and carbon cycle representations, show improved responses compared to idealized SCMs. Even the comprehensive SCMs, however, fail to capture the response timescales to BC emission perturbations seen recently in two general circulation models. Some comprehensive SCMs also generally respond faster than more complex models to a 4×CO2 concentration perturbation, although this was not evident for lower perturbation levels. These results suggest where improvements should be made to SCMs. Further, we demonstrate here a set of fundamental tests that we recommend as a standard evaluation suite for any SCM. Fundamental impulse tests allow users to understand differences in model responses and the impact of model selection on results.

scholarly journals Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

2015 ◽  
Vol 8 (7) ◽  
pp. 1943-1954 ◽  
Author(s):  
D. R. Feldman ◽  
W. D. Collins ◽  
J. L. Paige
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Coupled Model ◽  
Climate System ◽  
Spectral Measurements ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Detection And Attribution ◽  
Long Wave ◽  
Hadley Centre

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm−1 at 8 nm and 1 cm−1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

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