scholarly journals Comparison of ice particle characteristics simulated by the Community Atmosphere Model (CAM5) with in-situ observations

2014 ◽  
Vol 14 (6) ◽  
pp. 7637-7681 ◽  
Author(s):  
T. Eidhammer ◽  
H. Morrison ◽  
A. Bansemer ◽  
A. Gettelman ◽  
A. J. Heymsfield

Abstract. Detailed measurements of ice crystals in cirrus clouds were used to compare with results from the Community Atmospheric Model Version 5 (CAM5) global climate model. The observations are from two different field campaigns with contrasting conditions: Atmospheric Radiation Measurements Spring Cloud Intensive Operational Period in 2000 (ARM-IOP), which was characterized primarily by midlatitude frontal clouds and cirrus, and Tropical Composition, Cloud and Climate Coupling (TC4), which was dominated by anvil cirrus. Results show that the model typically overestimates the slope parameter of the exponential size distributions of cloud ice and snow, while the variation with temperature (height) is comparable. The model also overestimates the ice/snow number concentration (0th moment of the size distribution) and underestimates higher moments (2nd through 5th), but compares well with observations for the 1st moment. Overall the model shows better agreement with observations for TC4 than for ARM-IOP in regards to the moments. The mass-weighted terminal fallspeed is lower in the model compared to observations for both ARM-IOP and TC4, which is partly due to the overestimation of the size distribution slope parameter. Sensitivity tests with modification of the threshold size for cloud ice to snow autoconversion (Dcs) do not show noticeable improvement in modeled moments, slope parameter and mass weighed fallspeed compared to observations. Further, there is considerable sensitivity of the cloud radiative forcing to Dcs, consistent with previous studies, but no value of Dcs improves modeled cloud radiative forcing compared to measurements. Since the autoconversion of cloud ice to snow using the threshold size Dcs has little physical basis, future improvement to combine cloud ice and snow into a single category, eliminating the need for autoconversion, is suggested.

2014 ◽  
Vol 14 (18) ◽  
pp. 10103-10118 ◽  
Author(s):  
T. Eidhammer ◽  
H. Morrison ◽  
A. Bansemer ◽  
A. Gettelman ◽  
A. J. Heymsfield

Abstract. Detailed measurements of ice crystals in cirrus clouds were used to compare with results from the Community Atmospheric Model Version 5 (CAM5) global climate model. The observations are from two different field campaigns with contrasting conditions: Atmospheric Radiation Measurements Spring Cloud Intensive Operational Period in 2000 (ARM-IOP), which was characterized primarily by midlatitude frontal clouds and cirrus, and Tropical Composition, Cloud and Climate Coupling (TC4), which was dominated by anvil cirrus. Results show that the model typically overestimates the slope parameter of the exponential size distributions of cloud ice and snow, while the variation with temperature (height) is comparable. The model also overestimates the ice/snow number concentration (0th moment of the size distribution) and underestimates higher moments (2nd through 5th), but compares well with observations for the 1st moment. Overall the model shows better agreement with observations for TC4 than for ARM-IOP in regards to the moments. The mass-weighted terminal fall speed is lower in the model compared to observations for both ARM-IOP and TC4, which is partly due to the overestimation of the size distribution slope parameter. Sensitivity tests with modification of the threshold size for cloud ice to snow autoconversion (Dcs) do not show noticeable improvement in modeled moments, slope parameter and mass weighed fall speed compared to observations. Further, there is considerable sensitivity of the cloud radiative forcing to Dcs, consistent with previous studies, but no value of Dcs improves modeled cloud radiative forcing compared to measurements. Since the autoconversion of cloud ice to snow using the threshold size Dcs has little physical basis, future improvement to combine cloud ice and snow into a single category, eliminating the need for autoconversion, is suggested.


2014 ◽  
Vol 27 (5) ◽  
pp. 1845-1862 ◽  
Author(s):  
Ming Zhao

Abstract This study explores connections between process-level modeling of convection and global climate model (GCM) simulated clouds and cloud feedback to global warming through a set of perturbed-physics and perturbed sea surface temperature experiments. A bulk diagnostic approach is constructed, and a set of variables is derived and demonstrated to be useful in understanding the simulated relationship. In particular, a novel bulk quantity, the convective precipitation efficiency or equivalently the convective detrainment efficiency, is proposed as a simple measure of the aggregated properties of parameterized convection important to the GCM simulated clouds. As the convective precipitation efficiency increases in the perturbed-physics experiments, both liquid and ice water path decrease, with low and middle cloud fractions diminishing at a faster rate than high cloud fractions. This asymmetry results in a large sensitivity of top-of-atmosphere net cloud radiative forcing to changes in convective precipitation efficiency in this limited set of models. For global warming experiments, intermodel variations in the response of cloud condensate, low cloud fraction, and total cloud radiative forcing are well explained by model variations in response to total precipitation (or detrainment) efficiency. Despite significant variability, all of the perturbed-physics models produce a sizable increase in precipitation efficiency to warming. A substantial fraction of the increase is due to its convective component, which depends on the parameterization of cumulus mixing and convective microphysical processes. The increase in convective precipitation efficiency and associated change in convective cloud height distribution owing to warming explains the increased cloud feedback and climate sensitivity in recently developed Geophysical Fluid Dynamics Laboratory GCMs. The results imply that a cumulus scheme using fractional removal of condensate for precipitation and inverse calculation of the entrainment rate tends to produce a lower climate sensitivity than a scheme using threshold removal for precipitation and the entrainment rate formulated inversely dependent on convective depth.


2021 ◽  
Author(s):  
Ulrike Proske ◽  
Sylvaine Ferrachat ◽  
David Neubauer ◽  
Ulrike Lohmann

<p>Clouds are of major importance for the climate system, but the radiative forcing resulting from their interaction with aerosols remains uncertain. To improve the representation of clouds in climate models, the parameterisations of cloud microphysical processes (CMPs) have become increasingly detailed. However, more detailed climate models do not necessarily result in improved accuracy for estimates of radiative forcing (Knutti and Sedláček, 2013; Carslaw et al., 2018). On the contrary, simpler formulations are cheaper, sufficient for some applications, and allow for an easier understanding of the respective process' effect in the model.</p><p>This study aims to gain an understanding which CMP parameterisation complexity is sufficient through simplification. We gradually phase out processes such as riming or aggregation from the global climate model ECHAM-HAM, meaning that the processes are only allowed to exhibit a fraction of their effect on the model state. The shape of the model response as a function of the artificially scaled effect of a given process helps to understand the importance of this process for the model response and its potential for simplification. For example, if partially removing a process induces only minor alterations in the present day climate, this process presents as a good candidate for simplification. This may be then further investigated, for example in terms of computing time.<br>The resulting sensitivities to CMP complexity are envisioned to guide CMP model simplifications as well as steer research towards those processes where a more accurate representation proves to be necessary.</p><p> </p><p><br>Carslaw, Kenneth, Lindsay Lee, Leighton Regayre, and Jill Johnson (Feb. 2018). “Climate Models Are Uncertain, but We Can Do Something About It”. In: Eos 99. doi: 10.1029/2018EO093757</p><p>Knutti, Reto and Jan Sedláček (Apr. 2013). “Robustness and Uncertainties in the New CMIP5 Climate Model Projections”. In: Nature Climate Change 3.4, pp. 369–373. doi: 10.1038/nclimate1716</p>


2020 ◽  
Vol 13 (2) ◽  
pp. 673-684
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho

Abstract. We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a subcolumn cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50 % more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ∼20 % in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.


2009 ◽  
Vol 66 (4) ◽  
pp. 1033-1040 ◽  
Author(s):  
O. E. García ◽  
A. M. Díaz ◽  
F. J. Expósito ◽  
J. P. Díaz ◽  
A. Redondas ◽  
...  

Abstract The influence of mineral dust on ultraviolet energy transfer is studied for two different mineralogical origins. The aerosol radiative forcing ΔF and the forcing efficiency at the surface ΔFeff in the range 290–325 nm were estimated in ground-based stations affected by the Saharan and Asian deserts during the dusty seasons. UVB solar measurements were taken from the World Ozone and Ultraviolet Data Center (WOUDC) for four Asian stations (2000–04) and from the Santa Cruz Observatory, Canary Islands (2002–03), under Gobi and Sahara Desert influences, respectively. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth at 550 nm was used to characterize the aerosol load τ, whereas the aerosol index provided by the Total Ozone Mapping Spectrometer (TOMS) sensor was employed to identify the mineral dust events. The ΔF is strongly affected by the aerosol load, the values found being comparable in both regions during the dusty seasons. Under those conditions, ΔF values as large as −1.29 ± 0.53 W m−2 (τ550 = 0.48 ± 0.24) and −1.43 ± 0.38 W m−2 (τ550 = 0.54 ± 0.26) were reached under Saharan and Asian dust conditions, respectively. Nevertheless, significant differences have been observed in the aerosol radiative forcing per unit of aerosol optical depth in the slant path, τS. The maximum ΔFeff values associated with dust influences were −1.55 ± 0.20 W m−2 τS550−1 for the Saharan region and −0.95 ± 0.11 W m−2 τS550−1 in the Asian area. These results may be used as a benchmark database for establishing aerosol corrections in UV satellite products or in global climate model estimations.


2010 ◽  
Vol 23 (15) ◽  
pp. 4121-4132 ◽  
Author(s):  
Dorian S. Abbot ◽  
Itay Halevy

Abstract Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations.


2019 ◽  
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho

Abstract. We revisit Cloud Vertical Structure (CVS) classes we have previously employed to classify the planet’s cloudiness. The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an Atmospheric Global Climate Model (AGCM), specifically NASA’s GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Determination of CVS and associated radiation in the model is possible thanks to the implementation of a subcolumn cloud generator which is paired with the model’s radiative transfer algorithm. We assess GEOS-5 cloudiness in terms of the statistics and geographical distributions of the CVS classes, as well as features of their associated Cloud Radiative Effect (CRE). We decompose the model’s CVS-specific CRE errors into component errors stemming from biases in the frequency of occurrence of the CVSs, and biases in their internal radiative characteristics. Our framework sheds additional light into the verisimilitude of cloudiness in large scale models and can be used to complement cloud evaluations that take advantage of satellite simulator implementations.


2017 ◽  
Vol 30 (20) ◽  
pp. 8033-8044 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin

Abstract The total amount of precipitation integrated across a precipitation feature (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released (i.e., the power of the disturbance). The probability distribution of cluster power is examined over the tropics using Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite-retrieved rain rates and global climate model output. Observed distributions are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability drops rapidly. After establishing an observational baseline, precipitation from the High Resolution Atmospheric Model (HiRAM) at two horizontal grid spacings (roughly 0.5° and 0.25°) is compared. When low rain rates are excluded by choosing a minimum rain-rate threshold in defining clusters, the model accurately reproduces observed cluster power statistics at both resolutions. Middle and end-of-century cluster power distributions are investigated in HiRAM in simulations with prescribed sea surface temperatures and greenhouse gas concentrations from a “business as usual” global warming scenario. The probability of high cluster power events increases strongly by end of century, exceeding a factor of 10 for the highest power events for which statistics can be computed. Clausius–Clapeyron scaling accounts for only a fraction of the increased probability of high cluster power events.


2007 ◽  
Vol 7 (5) ◽  
pp. 14939-14987 ◽  
Author(s):  
X. Ma ◽  
K. von Salzen ◽  
J. Li

Abstract. A size-dependent sea salt aerosol parameterization was developed based on the piecewise log-normal approximation (PLA) for aerosol size distributions. Results of this parameterization from simulations with a global climate model produce good agreement with observations at the surface and for vertically-integrated volume size distributions. The global and annual mean of the sea salt burden is 10.1 mg m−2. The direct radiative forcing is calculated to be −1.52 and −0.60 W m−2 for clear sky and all sky, respectively. The first indirect radiative forcing is about twice as large as the direct forcing for all-sky (−1.34 W m−2). The results also show that the total indirect forcing of sea salt is −2.9 W m−2 if climatic feedbacks are taken into account. The sensitivity of the forcings to changes in the burdens and sizes of sea salt particles was also investigated based on additional simulations with a different sea salt source function.


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