scholarly journals On the Usage of Spectral and Broadband Satellite Instrument Measurements to Differentiate Climate Models with Different Cloud Feedback Strengths

2013 ◽  
Vol 26 (17) ◽  
pp. 6561-6574 ◽  
Author(s):  
Daniel R. Feldman ◽  
Daniel M. Coleman ◽  
William D. Collins
Keyword(s):  
Near Infrared ◽  
Climate Models ◽  
Longwave Radiation ◽  
Cloud Feedback ◽  
Climate System ◽  
Spectral Radiance ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Cloud Feedbacks ◽  
The Difference

Abstract Top-of-atmosphere radiometric signals associated with different high- and low-cloud–radiative feedbacks have been examined through the use of an observing system simulation experiment (OSSE). The OSSE simulates variations in the spectrally resolved and spectrally integrated signals that are due to a range of plausible feedbacks of the climate system when forced with CO2 concentrations that increase at 1% yr−1. This initial version of the OSSE is based on the Community Climate System Model, version 3 (CCSM3), and exploits the fact that CCSM3 exhibits different cloud feedback strengths for different model horizontal resolutions. In addition to the conventional broadband shortwave albedos and outgoing longwave fluxes, a dataset of shortwave spectral reflectance and longwave spectral radiance has been created. These data have been analyzed to determine simulated satellite instrument signals of poorly constrained cloud feedbacks for three plausible realizations of Earth's climate system produced by CCSM3. These data have been analyzed to estimate the observational record length of albedo, outgoing longwave radiation, shortwave reflectance, or longwave radiance required to differentiate these dissimilar Earth system realizations. Shortwave spectral measurements in visible and near-infrared water vapor overtone lines are best suited to differentiate model results, and a 33% difference in shortwave–cloud feedbacks can be detected with 20 years of continuous measurements. Nevertheless, at most latitudes and with most wavelengths, the difference detection time is more than 30 years. This suggests that observing systems of sufficiently stable calibration would be useful in addressing the contribution of low clouds to the spread of climate sensitivities currently exhibited by the models that report to the Intergovernmental Panel on Climate Change (IPCC).

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.

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.

El Niño and Greenhouse Warming: Results from Ensemble Simulations with the NCAR CCSM

2005 ◽  
Vol 18 (22) ◽  
pp. 4669-4683 ◽  
Author(s):  
Hein Zelle ◽  
Geert Jan van Oldenborgh ◽  
Gerrit Burgers ◽  
Henk Dijkstra
Keyword(s):  
Response Pattern ◽  
Climate System ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Ensemble Simulations ◽  
System A ◽  
Global Mean Surface Temperature ◽  
Wind Response ◽  
Business As Usual ◽  
Global Mean

Abstract The changes in model ENSO behavior due to an increase in greenhouse gases, according to the Intergovernmental Panel on Climate Change (IPCC) Business-As-Usual scenario, are investigated using a 62-member ensemble 140-yr simulation (1940–2080) with the National Center for Atmospheric Research Community Climate System Model (CCSM; version 1.4). Although the global mean surface temperature increases by about 1.2 K over the period 2000–80, there are no significant changes in the ENSO period, amplitude, and spatial patterns. To explain this behavior, an analysis of the simulation results is combined with results from intermediate complexity coupled ocean–atmosphere models. It is shown that this version of the CCSM is incapable of simulating a correct meridional extension of the equatorial wind stress response to equatorial SST anomalies. The wind response pattern is too narrow and its strength is insensitive to background SST. This leads to a more stable Pacific climate system, a shorter ENSO period, and a reduced sensitivity of ENSO to global warming.

scholarly journals On the Longwave Climate Feedbacks

2013 ◽  
Vol 26 (19) ◽  
pp. 7603-7610 ◽  
Author(s):  
Yi Huang
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Longwave Radiation ◽  
Feedback Mechanism ◽  
Cloud Feedback ◽  
Climate Feedbacks ◽  
Stratospheric Water Vapor ◽  
Surface Warming ◽  
Transient Climate Change ◽  
Positive Feedback Mechanism

Abstract This paper mainly addresses two issues that concern the longwave climate feedbacks. First, it is recognized that the radiative forcing of greenhouse gases, as measured by their impact on the outgoing longwave radiation (OLR), may vary across different climate models even when the concentrations of these gases are identically prescribed. This forcing variation contributes to the discrepancy in these models' projections of surface warming. A method is proposed to account for this effect in diagnosing the sensitivity and feedbacks in the models. Second, it is shown that the stratosphere is an important factor that affects the OLR in transient climate change. Stratospheric water vapor and temperature changes may both act as a positive feedback mechanism during global warming and cannot be fully accounted as a “stratospheric adjustment” of radiative forcing. Neglecting these two issues may cause a bias in the longwave cloud feedback diagnosed as a residual term in the decomposition of OLR variations. There is no consensus among the climate models on the sign of the longwave cloud feedback after accounting for both issues.

scholarly journals The impact of parametrized convection on cloud feedback

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140414 ◽  
Author(s):  
Mark J. Webb ◽  
Adrian P. Lock ◽  
Christopher S. Bretherton ◽  
Sandrine Bony ◽  
Jason N. S. Cole ◽  
...  
Keyword(s):  
Climate Models ◽  
Correction Method ◽  
Cloud Feedback ◽  
Temperature Perturbation ◽  
Cloud Feedbacks ◽  
Stratocumulus Clouds ◽  
Shallow Clouds ◽  
Convection Schemes ◽  
The Individual ◽  
The Impact

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

scholarly journals Does Antarctic glaciation cool the world?

2012 ◽  
Vol 8 (4) ◽  
pp. 2645-2693 ◽  
Author(s):  
A. Goldner ◽  
M. Huber ◽  
R. Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Ice Sheet ◽  
Cloud Feedback ◽  
Modern World ◽  
Antarctic Ice Sheet ◽  
Cloud Feedbacks ◽  
Wide Range ◽  
The Antarctic

Abstract. In this study we compare the simulated climatic impact of adding the Antarctic Ice Sheet to the "Greenhouse World" of the Eocene and removing the Antarctic Ice Sheet from the Modern world. The Modern surface temperature anomaly (ΔT) induced by Antarctic Glaciation ranges from −1.22 to −0.18 K when CO2 is dropped from 2240 to 560 ppm, whereas the Eocene ΔT is nearly constant at −0.3 K. We calculate the climate sensitivity parameter S[Antarctica] which is defined as the change in surface temperature (ΔT) divided by the change in radiative forcing (ΔQAntarctica) imposed by prescribing the glacial properties of Antarctica. While the ΔT associated with the imposed Antarctic properties is relatively consistent across the Eocene cases, the radiative forcing is not. This leads to a wide range of S[Antarctica], with Eocene values systematically smaller than Modern. This differing temperature response in Eocene and Modern is partially due to the smaller surface area of the imposed forcing over Antarctica in the Eocene and partially due to the presence of strong positive sea-ice feedbacks in the Modern. The system's response is further mediated by differing shortwave cloud feedbacks which are large and of opposite sign operating in Modern and Eocene configurations. A negative cloud feedback warms much of the Earth's surface as a large ice sheet is introduced in Antarctica in the Eocene, whereas in the Modern this cloud feedback is positive and acts to enhance cooling introduced by adding an ice sheet. Because of the importance of cloud feedbacks in determining the final temperature sensitivity of the Antarctic Ice Sheet our results are likely to be model dependent. Nevertheless, these model results show that the radiative forcing and feedbacks induced by the Antarctic Ice Sheet did not significantly decrease global mean surface temperature across the Eocene-Oligocene transition (EOT) and that other factors like declining atmospheric CO2 are more important for cooling across the EOT. The results indicate that climate transitions associated with glaciation depend on the climate background state. This means that using paleoclimate proxy data by itself, from the EOT to estimate Earth System Sensitivity, into the future, is made difficult without relying on climate models and consequently these modelling estimates will have large uncertainty, largely due to low clouds.

scholarly journals Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

2012 ◽  
Vol 25 (11) ◽  
pp. 3715-3735 ◽  
Author(s):  
Mark D. Zelinka ◽  
Stephen A. Klein ◽  
Dennis L. Hartmann
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Grid Point ◽  
Cloud Fraction ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Feedbacks ◽  
Low Clouds

This study proposes a novel technique for computing cloud feedbacks using histograms of cloud fraction as a joint function of cloud-top pressure (CTP) and optical depth (τ). These histograms were generated by the International Satellite Cloud Climatology Project (ISCCP) simulator that was incorporated into doubled-CO2 simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. The authors use a radiative transfer model to compute top of atmosphere flux sensitivities to cloud fraction perturbations in each bin of the histogram for each month and latitude. Multiplying these cloud radiative kernels with histograms of modeled cloud fraction changes at each grid point per unit of global warming produces an estimate of cloud feedback. Spatial structures and globally integrated cloud feedbacks computed in this manner agree remarkably well with the adjusted change in cloud radiative forcing. The global and annual mean model-simulated cloud feedback is dominated by contributions from medium thickness (3.6 < τ ≤ 23) cloud changes, but thick (τ > 23) cloud changes cause the rapid transition of cloud feedback values from positive in midlatitudes to negative poleward of 50°S and 70°N. High (CTP ≤ 440 hPa) cloud changes are the dominant contributor to longwave (LW) cloud feedback, but because their LW and shortwave (SW) impacts are in opposition, they contribute less to the net cloud feedback than do the positive contributions from low (CTP > 680 hPa) cloud changes. Midlevel (440 < CTP ≤ 680 hPa) cloud changes cause positive SW cloud feedbacks that are 80% as large as those due to low clouds. Finally, high cloud changes induce wider ranges of LW and SW cloud feedbacks across models than do low clouds.

scholarly journals Insights into low-latitude cloud feedbacks from high-resolution models

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140415 ◽  
Author(s):  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Limited Area ◽  
Slight Reduction ◽  
Low Latitude ◽  
Cloud Feedbacks ◽  
Cloud Regimes

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: ‘thermodynamic’ cloudiness reduction from warming of the atmosphere–ocean column, ‘radiative’ cloudiness reduction from CO 2 - and H 2 O-induced increase in atmospheric emissivity aloft, ‘stability-induced’ cloud increase from increased lower tropospheric stratification, and ‘dynamical’ cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

scholarly journals Predictability of Seasonal Streamflow Forecasting Based on CSM: Case Studies of Top Three Largest Rivers in China

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 162
Author(s):  
Lyuliu Liu ◽  
Ying Wu ◽  
Peiqun Zhang ◽  
Jianqing Zhai ◽  
Li Zhang ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Climate Models ◽  
Initial Conditions ◽  
Global Climate Models ◽  
Climate System ◽  
Hydrological Models ◽  
Streamflow Forecasting ◽  
Relative Operating Characteristic ◽  
Climate System Model ◽  
Seasonal Streamflow

Accurate seasonal streamflow forecasting is important in reservoir operation, watershed planning, and water resource management, and streamflow forecasting is often based on hydrological models driven by coupled global climate models (CGCMs). To understand streamflow forecasting predictability, this study considered the three largest rivers in China and explored deterministic and probabilistic skill metrics on the monthly scale according to ensemble streamflow hindcasts from the hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) driven by multiple climate forcings from the climate system model by the Beijing Climate Center (BCC_CSM1.1m). The effects of initial conditions (ICs) and meteorological forcings (MFs) on skill were investigated using the conventional ensemble streamflow prediction (ESP) and reverse-ESP (revESP). The results revealed the following: (1) Skill declines as lead time increases, and forecasting is generally the most skillful for lead month 1; (2) skill is higher for dry rivers than wet rivers, and higher for dry target months than wet months for the Yellow and Yangtze Rivers, suggesting greater skill in potential drought forecasting than flood forecasting; (3) the relative operating characteristic (ROC) area is greater for abnormal terciles than the near-normal tercile for all three rivers, greater for the above-normal tercile than the below-normal tercile for the Yellow and Yangtze Rivers, but slightly greater for the below-normal tercile than the above-normal tercile for the Xijiang River; and (4) the influence of ICs outweighs that of MFs in dry months, and the period of influence varies from 1 to 3 months; however, the influence of MFs is dominant in wet target months. These findings will help improve the understanding of both the seasonal streamflow forecasting predictability based on coupled climate system/hydrological models and of streamflow forecasting for variable rivers and seasons.

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