Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators

2012 ◽  
Vol 25 (15) ◽  
pp. 5190-5207 ◽  
Author(s):  
J. E. Kay ◽  
B. R. Hillman ◽  
S. A. Klein ◽  
Y. Zhang ◽  
B. Medeiros ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Marine Boundary Layer ◽  
Climate Model ◽  
Substantial Improvement ◽  
Satellite Observations ◽  
Cloud Properties ◽  
Community Atmosphere Model ◽  
Realistic Representation ◽  
Model Cloud ◽  
Atmosphere Model

Abstract Satellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model–observation comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are known to explain intermodel differences in cloud feedbacks and climate sensitivity. More generally, this study demonstrates that simulator-facilitated evaluation of cloud properties, such as amount by vertical level and optical depth, can robustly expose large and at times radiatively compensating climate model cloud biases.

scholarly journals An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

2018 ◽  
Vol 31 (6) ◽  
pp. 2299-2320 ◽  
Author(s):  
Hua Song ◽  
Zhibo Zhang ◽  
Po-Lun Ma ◽  
Steven J. Ghan ◽  
Minghuai Wang
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Marine Boundary Layer ◽  
Detection Threshold ◽  
Satellite Observation ◽  
Cloud Fraction ◽  
Cloud Properties ◽  
Community Atmosphere Model ◽  
Direct Model ◽  
Atmosphere Model

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

scholarly journals Anthropogenic forcing and response yield observed positive trend in Earth’s energy imbalance

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shiv Priyam Raghuraman ◽  
David Paynter ◽  
V. Ramaswamy
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Solar Spectrum ◽  
Internal Variability ◽  
Satellite Observations ◽  
Positive Trend ◽  
Energy Imbalance ◽  
Model Simulations ◽  
Heat Uptake ◽  
Climate Model Simulations

AbstractThe observed trend in Earth’s energy imbalance (TEEI), a measure of the acceleration of heat uptake by the planet, is a fundamental indicator of perturbations to climate. Satellite observations (2001–2020) reveal a significant positive globally-averaged TEEI of 0.38 ± 0.24 Wm−2decade−1, but the contributing drivers have yet to be understood. Using climate model simulations, we show that it is exceptionally unlikely (<1% probability) that this trend can be explained by internal variability. Instead, TEEI is achieved only upon accounting for the increase in anthropogenic radiative forcing and the associated climate response. TEEI is driven by a large decrease in reflected solar radiation and a small increase in emitted infrared radiation. This is because recent changes in forcing and feedbacks are additive in the solar spectrum, while being nearly offset by each other in the infrared. We conclude that the satellite record provides clear evidence of a human-influenced climate system.

scholarly journals Atmospheric circulation and hydroclimate impacts of alternative warming scenarios for the Eocene

2017 ◽  
Vol 13 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
Henrik Carlson ◽  
Rodrigo Caballero
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Cloud Albedo ◽  
Cloud Properties ◽  
Atmospheric Co2 Concentrations ◽  
Global Mean

Abstract. Recent work in modelling the warm climates of the early Eocene shows that it is possible to obtain a reasonable global match between model surface temperature and proxy reconstructions, but only by using extremely high atmospheric CO2 concentrations or more modest CO2 levels complemented by a reduction in global cloud albedo. Understanding the mix of radiative forcing that gave rise to Eocene warmth has important implications for constraining Earth's climate sensitivity, but progress in this direction is hampered by the lack of direct proxy constraints on cloud properties. Here, we explore the potential for distinguishing among different radiative forcing scenarios via their impact on regional climate changes. We do this by comparing climate model simulations of two end-member scenarios: one in which the climate is warmed entirely by CO2 (which we refer to as the greenhouse gas (GHG) scenario) and another in which it is warmed entirely by reduced cloud albedo (which we refer to as the low CO2–thin clouds or LCTC scenario) . The two simulations have an almost identical global-mean surface temperature and equator-to-pole temperature difference, but the LCTC scenario has  ∼  11 % greater global-mean precipitation than the GHG scenario. The LCTC scenario also has cooler midlatitude continents and warmer oceans than the GHG scenario and a tropical climate which is significantly more El Niño-like. Extremely high warm-season temperatures in the subtropics are mitigated in the LCTC scenario, while cool-season temperatures are lower at all latitudes. These changes appear large enough to motivate further, more detailed study using other climate models and a more realistic set of modelling assumptions.

scholarly journals Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing

2011 ◽  
Vol 11 (4) ◽  
pp. 10875-10933 ◽  
Author(s):  
I. Cionni ◽  
V. Eyring ◽  
J. F. Lamarque ◽  
W. J. Randel ◽  
D. S. Stevenson ◽  
...  
Keyword(s):  
Time Series ◽  
Ozone Depletion ◽  
Tropospheric Ozone ◽  
Radiative Forcing ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Satellite Observations ◽  
High Latitudes ◽  
The Future ◽  
Column Ozone

Abstract. A continuous tropospheric and stratospheric vertically resolved ozone time series, from 1850 to 2099, has been generated to be used as forcing in global climate models that do not include interactive chemistry. A multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde measurements is used for the stratospheric zonal mean dataset during the well-observed period from 1979 to 2009. In addition to terms describing the mean annual cycle, the regression includes terms representing equivalent effective stratospheric chlorine (EESC) and the 11-yr solar cycle variability. The EESC regression fit coefficients, together with pre-1979 EESC values, are used to extrapolate the stratospheric ozone time series backward to 1850. While a similar procedure could be used to extrapolate into the future, coupled chemistry climate model (CCM) simulations indicate that future stratospheric ozone abundances are likely to be significantly affected by climate change, and capturing such effects through a regression model approach is not feasible. Therefore, the stratospheric ozone dataset is extended into the future (merged in 2009) with multi-model mean projections from 13 CCMs that performed a simulation until 2099 under the SRES (Special Report on Emission Scenarios) A1B greenhouse gas scenario and the A1 adjusted halogen scenario in the second round of the Chemistry-Climate Model Validation (CCMVal-2) Activity. The stratospheric zonal mean ozone time series is merged with a three-dimensional tropospheric data set extracted from simulations of the past by two CCMs (CAM3.5 and PUCCINI) and of the future by one CCM (CAM3.5). The future tropospheric ozone time series continues the historical CAM3.5 simulation until 2099 following the four different Representative Concentration Pathways (RCPs). Generally good agreement is found between the historical segment of the ozone database and satellite observations, although it should be noted that total column ozone is overestimated in the southern polar latitudes during spring and tropospheric column ozone is slightly underestimated. Vertical profiles of tropospheric ozone are broadly consistent with ozonesondes and in-situ measurements, with some deviations in regions of biomass burning. The tropospheric ozone radiative forcing (RF) from the 1850s to the 2000s is 0.23 W m−2, lower than previous results. The lower value is mainly due to (i) a smaller increase in biomass burning emissions; (ii) a larger influence of stratospheric ozone depletion on upper tropospheric ozone at high southern latitudes; and possibly (iii) a larger influence of clouds (which act to reduce the net forcing) compared to previous radiative forcing calculations. Over the same period, decreases in stratospheric ozone, mainly at high latitudes, produce a RF of −0.08 W m−2, which is more negative than the central Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) value of −0.05 W m−2, but which is within the stated range of −0.15 to +0.05 W m−2. The more negative value is explained by the fact that the regression model simulates significant ozone depletion prior to 1979, in line with the increase in EESC and as confirmed by CCMs, while the AR4 assumed no change in stratospheric RF prior to 1979. A negative RF of similar magnitude persists into the future, although its location shifts from high latitudes to the tropics. This shift is due to increases in polar stratospheric ozone, but decreases in tropical lower stratospheric ozone, related to a strengthening of the Brewer-Dobson circulation, particularly through the latter half of the 21st century. Differences in trends in tropospheric ozone among the four RCPs are mainly driven by different methane concentrations, resulting in a range of tropospheric ozone RFs between 0.4 and 0.1 W m−2 by 2100. The ozone dataset described here has been released for the Coupled Model Intercomparison Project (CMIP5) model simulations in netCDF Climate and Forecast (CF) Metadata Convention at the PCMDI website (http://cmip-pcmdi.llnl.gov/).

scholarly journals Numerical framework and performance of the new multiple-phase cloud microphysics scheme in RegCM4.5: precipitation, cloud microphysics, and cloud radiative effects

2016 ◽  
Vol 9 (7) ◽  
pp. 2533-2547 ◽  
Author(s):  
Rita Nogherotto ◽  
Adrian Mark Tompkins ◽  
Graziano Giuliani ◽  
Erika Coppola ◽  
Filippo Giorgi
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Regional Climate ◽  
Cloud Microphysics ◽  
Microphysics Scheme ◽  
Additional Information ◽  
Mixing Ratios ◽  
Multiple Phase ◽  
Realistic Representation ◽  
And Performance

Abstract. We implement and evaluate a new parameterization scheme for stratiform cloud microphysics and precipitation within regional climate model RegCM4. This new parameterization is based on a multiple-phase one-moment cloud microphysics scheme built upon the implicit numerical framework recently developed and implemented in the ECMWF operational forecasting model. The parameterization solves five prognostic equations for water vapour, cloud liquid water, rain, cloud ice, and snow mixing ratios. Compared to the pre-existing scheme, it allows a proper treatment of mixed-phase clouds and a more physically realistic representation of cloud microphysics and precipitation. Various fields from a 10-year long integration of RegCM4 run in tropical band mode with the new scheme are compared with their counterparts using the previous cloud scheme and are evaluated against satellite observations. In addition, an assessment using the Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP) for a 1-year sub-period provides additional information for evaluating the cloud optical properties against satellite data. The new microphysics parameterization yields an improved simulation of cloud fields, and in particular it removes the overestimation of upper level cloud characteristics of the previous scheme, increasing the agreement with observations and leading to an amelioration of a long-standing problem in the RegCM system. The vertical cloud profile produced by the new scheme leads to a considerably improvement of the representation of the longwave and shortwave components of the cloud radiative forcing.

scholarly journals Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations

2013 ◽  
Vol 13 (8) ◽  
pp. 4057-4072 ◽  
Author(s):  
K. W. Bowman ◽  
D. T. Shindell ◽  
H. M. Worden ◽  
J.F. Lamarque ◽  
P. J. Young ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Outgoing Longwave Radiation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Longwave Radiation ◽  
Satellite Observations ◽  
Ensemble Mean ◽  
High Bias

Abstract. We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.

scholarly journals Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

2017 ◽  
Vol 17 (7) ◽  
pp. 4731-4749 ◽  
Author(s):  
Chenglai Wu ◽  
Xiaohong Liu ◽  
Minghui Diao ◽  
Kai Zhang ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Nucleation And Growth ◽  
Ice Nucleation ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Model Version ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Ice Water

Abstract. In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ −40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

Relating Satellite-Observed Cloud Properties from MODIS to Meteorological Conditions for Marine Boundary Layer Clouds

2010 ◽  
Vol 23 (6) ◽  
pp. 1374-1391 ◽  
Author(s):  
Guang J. Zhang ◽  
Andrew M. Vogelmann ◽  
Michael P. Jensen ◽  
William D. Collins ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
Meteorological Parameters ◽  
Marine Boundary Layer ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Liquid Water Path ◽  
Near Surface ◽  
Cloud Properties ◽  
Lower Tropospheric Stability

Abstract This study examines 6 yr of cloud properties observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra satellite in five prominent marine boundary layer (MBL) cloud regions (California, Peru, Canary, Angola, and Australia) and investigates their relationships with near-surface meteorological parameters obtained from NCEP reanalyses. About 62 000 independent scenes are used to examine the instantaneous relationships between cloud properties and meteorological parameters that may be used for global climate model (GCM) diagnostics and parameterization. Cloud liquid water path (LWP) generally increases with lower-tropospheric stability (LTS) and lifting condensation level (LCL), whereas cloud drizzle frequency is favored by weak LTS and negligible cold air advection. Cloud fraction (CF) depends strongly on variations in LTS, and to a lesser extent on surface air temperature advection and LCL, although the relationships vary from region to region. The authors propose capturing the effects of these three parameters on CF via their linear combination in terms of a single parameter, the effective lower-tropospheric stability (eLTS). Results indicate that eLTS offers a marked improvement over LTS alone in explaining the median CF variations within the different study regions. A parameterization of CF in terms of eLTS is provided, which produces results that are improved over those of Klein and Hartmann’s LTS-only parameterization. However, the new parameterization may not predict the observed variability correctly, and the authors propose a method that might address this shortcoming via a statistical approach.

scholarly journals Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing

2014 ◽  
Vol 14 (12) ◽  
pp. 17749-17816 ◽  
Author(s):  
R. A. Scanza ◽  
N. Mahowald ◽  
S. Ghan ◽  
C. S. Zender ◽  
J. F. Kok ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Mineral Soil ◽  
Model Development ◽  
Spatial And Temporal Variability ◽  
Model Version ◽  
Mineral Aerosols ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Aerosol Module

Abstract. The mineralogy of desert dust is important due to its effect on radiation, clouds and biogeochemical cycling of trace nutrients. This study presents the simulation of dust radiative forcing as a function of both mineral composition and size at the global scale using mineral soil maps for estimating emissions. Externally mixed mineral aerosols in the bulk aerosol module in the Community Atmosphere Model version 4 (CAM4) and internally mixed mineral aerosols in the modal aerosol module in the Community Atmosphere Model version 5.1 (CAM5) embedded in the Community Earth System Model version 1.0.5 (CESM) are speciated into common mineral components in place of total dust. The simulations with mineralogy are compared to available observations of mineral atmospheric distribution and deposition along with observations of clear-sky radiative forcing efficiency. Based on these simulations, we estimate the all-sky direct radiative forcing at the top of the atmosphere as +0.05 W m−2 for both CAM4 and CAM5 simulations with mineralogy and compare this both with simulations of dust in release versions of CAM4 and CAM5 (+0.08 and +0.17 W m−2) and of dust with optimized optical properties, wet scavenging and particle size distribution in CAM4 and CAM5, −0.05 and −0.17 W m−2, respectively. The ability to correctly include the mineralogy of dust in climate models is hindered by its spatial and temporal variability as well as insufficient global in-situ observations, incomplete and uncertain source mineralogies and the uncertainties associated with data retrieved from remote sensing methods.

scholarly journals Surprising similarities in model and observational aerosol radiative forcing estimates

2020 ◽  
Vol 20 (1) ◽  
pp. 613-623 ◽  
Author(s):  
Edward Gryspeerdt ◽  
Johannes Mülmenstädt ◽  
Andrew Gettelman ◽  
Florent F. Malavelle ◽  
Hugh Morrison ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Liquid Water Path ◽  
Intergovernmental Panel ◽  
Aerosol Radiative Forcing ◽  
Aerosol Forcing ◽  
Cloud Properties ◽  
The Impact

Abstract. The radiative forcing from aerosols (particularly through their interaction with clouds) remains one of the most uncertain components of the human forcing of the climate. Observation-based studies have typically found a smaller aerosol effective radiative forcing than in model simulations and were given preferential weighting in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). With their own sources of uncertainty, it is not clear that observation-based estimates are more reliable. Understanding the source of the model and observational differences is thus vital to reduce uncertainty in the impact of aerosols on the climate. These reported discrepancies arise from the different methods of separating the components of aerosol forcing used in model and observational studies. Applying the observational decomposition to global climate model (GCM) output, the two different lines of evidence are surprisingly similar, with a much better agreement on the magnitude of aerosol impacts on cloud properties. Cloud adjustments remain a significant source of uncertainty, particularly for ice clouds. However, they are consistent with the uncertainty from observation-based methods, with the liquid water path adjustment usually enhancing the Twomey effect by less than 50 %. Depending on different sets of assumptions, this work suggests that model and observation-based estimates could be more equally weighted in future synthesis studies.

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