Search Results

You are looking at 1 - 5 of 5 items for

  • Author or Editor: Jason N. S. Cole x
  • User-accessible content x
Clear All Modify Search
Daniel T. Pawlak, Eugene E. Clothiaux, Michael F. Modest, and Jason N. S. Cole

Abstract

The full-spectrum correlated k-distribution (FSCK) method, originally developed for applications in combustion systems, is adapted for use in shortwave atmospheric radiative transfer. By weighting k distributions by the solar source function, the FSCK method eliminates the requirement that the Planck function be constant over a spectral interval. As a consequence, integration may be carried out across the full spectrum as long as the assumption of correlation from one atmospheric level to the next remains valid. Problems with the lack of correlation across the full spectrum are removed by partitioning the spectrum at a wavelength of 0.68 μm into two bands. The resulting two-band approach in the FSCK formalism produces broadband rms clear-sky flux and heating rate errors less than 1% and 6%, respectively, relative to monochromatic calculations and requires only 15 quadrature points per layer, which represents a 60%–90% reduction in computation time relative to other models currently in use.

An evaluation of fluxes calculated by the FSCK method in cases with idealized clouds demonstrates that gray cloud scattering in two spectral bands is sufficient to reproduce line-by-line generated fluxes. Two different approaches for modeling absorption by cloud drops were also examined. Explicitly including nongray cloud absorption in solar source function-weighted k distributions results in realistic in-cloud heating rates, although in-cloud heating rates were underpredicted by approximately 8%–12% as compared to line-by-line results. A gray cloud absorption parameter chosen to fit line-by-line results optimally for one cloud or atmospheric profile but applied to different cloud combinations or profiles, also closely approximated line-by-line heating rates.

Full access
Howard W. Barker, Jason N. S. Cole, Jiangnan Li, Bingqi Yi, and Ping Yang

Abstract

Solar flux densities and heating rates predicted by a broadband, multilayer δ-Eddington two-stream approximation are compared to estimates from a Monte Carlo model that uses detailed descriptions of cloud particle phase functions and facilitates locally nonzero net horizontal flux densities. Results are presented as domain averages for 256-km sections of cloudy atmospheres inferred from A-Train satellite data: 32 632 samples for January 2007 between 70°S and 70°N with total cloud fraction C > 0.05. The domains are meant to represent grid cells of a conventional global climate model and consist of columns of infinite width across track and Δx ≈ 1 km along track. The δ-Eddington was applied in independent column approximation (ICA) mode, while the Monte Carlo was applied using both Δx → ∞ (i.e., ICA) and Δx ≈ 1 km. Mean-bias errors due to the δ-Eddington’s neglect of phase function details and horizontal transfer, as functions of cosine of solar zenith angle μ0, are comparable in magnitude and have the same signs.

With minor dependence on cloud particle sizes, the δ-Eddington over- and underestimates top-of-atmosphere reflected flux density for the cloudy portion of domains by ~10 W m−2 for μ0 > 0.9 and −3 W m−2 for μ0 < 0.2; full domain averages are ~8 and −2 W m−2, respectively, given mean C > 0.75 for all μ0. These errors are reversed in sign, but slightly larger, for net surface flux densities. The δ-Eddington underestimates total atmospheric absorption by ~2.5 W m−2 on average. Hence, δ-Eddington mean-bias errors for domain-averaged layer heating rates are usually negative but can be positive. Rarely do they exceed ±10% of the mean heating rate; the largest errors are when the sides of liquid clouds are irradiated by direct beams.

Full access
Xianglei Huang, Jason N. S. Cole, Fei He, Gerald L. Potter, Lazaros Oreopoulos, Dongmin Lee, Max Suarez, and Norman G. Loeb

Abstract

The cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM’s radiation code is uniquely valuable for GCM evaluation because 1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and 2) the fractional contribution of each band to the LW broadband CRE (f CRE) is sensitive to cloud-top height but largely insensitive to cloud fraction, thereby presenting a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band-by-band quantities from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations. A study is presented here that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs—the GFDL Atmospheric Model version 2 (GFDL AM2), NASA Goddard Earth Observing System version 5 (GEOS-5), and the fourth-generation AGCM of the Canadian Centre for Climate Modelling and Analysis (CCCma CanAM4)—forced by observed SST. The models agree with observation on the annual-mean LW broadband CRE over the tropical oceans within ±1 W m−2. However, the differences among these three GCMs in some bands can be as large as or even larger than ±1 W m−2. Observed seasonal cycles of f CRE in major bands are shown to be consistent with the seasonal cycle of cloud-top pressure for both the amplitude and the phase. However, while the three simulated seasonal cycles of f CRE agree with observations on the phase, the amplitudes are underestimated. Simulated interannual anomalies from GFDL AM2 and CCCma CanAM4 are in phase with observed anomalies. The spatial distribution of f CRE highlights the discrepancies between models and observation over the low-cloud regions and the compensating biases from different bands.

Full access
Xianglei Huang, Xiuhong Chen, Gerald L. Potter, Lazaros Oreopoulos, Jason N. S. Cole, Dongmin Lee, and Norman G. Loeb

Abstract

Longwave (LW) spectral flux and cloud radiative effect (CRE) are important for understanding the earth’s radiation budget and cloud–radiation interaction. Here, the authors extend their previous algorithms to collocated Atmospheric Infrared Sounder (AIRS) and Cloud and the Earth’s Radiant Energy System (CERES) observations over the entire globe and show that the algorithms yield consistently good performances for measurements over both land and ocean. As a result, the authors are able to derive spectral flux and CRE at 10-cm−1 intervals over the entire LW spectrum from all currently available collocated AIRS and CERES observations. Using this multiyear dataset, they delineate the climatology of spectral CRE, including the far IR, over the entire globe as well as in different climate zones. Furthermore, the authors define two quantities, IR-effective cloud-top height (CTHeff) and cloud amount (CAeff), based on the monthly-mean spectral (or band by band) CRE. Comparisons with cloud fields retrieved by the CERES–Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm indicate that, under many circumstances, the CTHeff and CAeff can be related to the physical retrievals of CTH and CA and thus can enhance understandings of model deficiencies in LW radiation budgets and cloud fields. Using simulations from the GFDL global atmosphere model, version 2 (AM2); NASA’s Goddard Earth Observing System, version 5 (GEOS-5); and Environment Canada’s Canadian Centre for Climate Modelling and Analysis (CCCma) Fourth Generation Canadian Atmospheric General Circulation Model (CanAM4) as case studies, the authors further demonstrate the merits of the CTHeff and CAeff concepts in providing insights on global climate model evaluations that cannot be obtained solely from broadband LW flux and CRE comparisons.

Full access
Jonathan H. Jiang, Hui Su, Chengxing Zhai, T. Janice Shen, Tongwen Wu, Jie Zhang, Jason N. S. Cole, Knut von Salzen, Leo J. Donner, Charles Seman, Anthony Del Genio, Larissa S. Nazarenko, Jean-Louis Dufresne, Masahiro Watanabe, Cyril Morcrette, Tsuyoshi Koshiro, Hideaki Kawai, Andrew Gettelman, Luis Millán, William G. Read, Nathaniel J. Livesey, Yasko Kasai, and Masato Shiotani

Abstract

Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S–40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by −4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models.

Full access