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Yi-Hsuan Chen, Xianglei Huang, Xiuhong Chen, and Mark Flanner

Abstract

This study quantifies the impact of the inclusion of realistic surface spectral emissivity in the Sahara and Sahel on the simulated local climate and beyond. The surface emissivity in these regions can be as low as 0.6–0.7 over the infrared window band while close to unity in other spectral bands, but such spectral dependence has been ignored in current climate models. Realistic surface spectral emissivities over the Sahara and Sahel are incorporated into the Community Earth System Model (CESM) version 1.1.1, while treatments of surface emissivity for the rest of the globe remain unchanged. Both the modified and standard CESM are then forced with prescribed climatological SSTs and fixed present-day forcings for 35-yr simulations. The outputs from the last 30 years are analyzed. Compared to the standard CESM, the modified CESM has warmer surface air temperature, as well as a warmer and wetter planetary boundary layer over the Sahara and Sahel. The modified CESM thus favors more convection in these regions and has more convective rainfall, especially in the Sahara. The moisture convergence induced by such inclusion of surface spectral emissivity also contributes to the differences in simulated precipitation in the Sahel and the region south to it. Compared to observations, inclusion of surface spectral emissivity reduces surface temperature biases in the Sahara and precipitation biases in the Gulf of Guinea but exacerbates the wet biases in the Sahara. Such realistic representation of surface spectral emissivity can help unmask other factors contributing to regional biases in the original CESM.

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Xiuhong Chen, Xianglei Huang, Norman G. Loeb, and Heli Wei

Abstract

The far-IR spectrum plays an important role in the earth’s radiation budget and remote sensing. The authors compare the near-global (80°S–80°N) outgoing clear-sky far-IR flux inferred from the collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations in 2004 with the counterparts computed from reanalysis datasets subsampled along the same satellite trajectories. The three most recent reanalyses are examined: the ECMWF Interim Re-Analysis (ERA-Interim), NASA Modern-Era Retrospective Analysis for Research and Application (MERRA), and NOAA/NCEP Climate Forecast System Reanalysis (CFSR). Following a previous study by X. Huang et al., clear-sky spectral angular distribution models (ADMs) are developed for five of the CERES land surface scene types as well as for the extratropical oceans. The outgoing longwave radiation (OLR) directly estimated from the AIRS radiances using the authors’ algorithm agrees well with the OLR in the collocated CERES Single Satellite Footprint (SSF) dataset. The daytime difference is 0.96 ±2.02 W m−2, and the nighttime difference is 0.86 ±1.61 W m−2. To a large extent, the far-IR flux derived in this way agrees with those directly computed from three reanalyses. The near-global averaged differences between reanalyses and observations tend to be slightly positive (0.66%–1.15%) over 0–400 cm−1 and slightly negative (−0.89% to −0.44%) over 400–600 cm−1. For all three reanalyses, the spatial distributions of such differences show the largest discrepancies over the high-elevation areas during the daytime but not during the nighttime, suggesting discrepancies in the diurnal variation of such areas among different datasets. The composite differences with respect to temperature or precipitable water suggest large discrepancies for cold and humid scenes.

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Xianglei Huang, Xiuhong Chen, Daniel K. Zhou, and Xu Liu

Abstract

While current atmospheric general circulation models (GCMs) still treat the surface as a blackbody in their longwave radiation scheme, recent studies suggest the need for taking realistic surface spectral emissivity into account. There have been few measurements available for the surface emissivity in the far IR (<650 cm−1). Based on first-principle calculation, the authors compute the spectral emissivity over the entire longwave spectrum for a variety of surface types. MODIS-retrieved mid-IR surface emissivity at 0.05° × 0.05° spatial resolution is then regressed against the calculated spectral emissivity to determine the surface type for each grid. The derived spectral emissivity data are then spatially averaged onto 0.5° × 0.5° grids and spectrally integrated onto the bandwidths used by the RRTMG_LW—a longwave radiation scheme widely used in current climate and numerical weather models. The band-by-band surface emissivity dataset is then compared with retrieved surface spectral emissivities from Infrared Atmospheric Sounding Interferometer (IASI) measurements. The comparison shows favorable agreement between two datasets in all the bands covered by the IASI measurements. The authors further use the dataset in conjunction with ERA-Interim to evaluate its impact on the top-of-atmosphere radiation budget. Depending on the blackbody surface assumptions used in the original calculation, the globally averaged difference caused by the inclusion of realistic surface emissivity ranges from −1.2 to −1.5 W m−2 for clear-sky OLR and from −0.67 to −0.94 W m−2 for all-sky OLR. Moreover, the difference is not spatially uniform and has a distinct spatial pattern.

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Xianglei Huang, Hui-Wen Chuang, Andrew Dessler, Xiuhong Chen, Kenneth Minschwaner, Yi Ming, and V. Ramaswamy

Abstract

Both observational analysis and GCM simulations indicate that the tropical Walker circulation is becoming weaker and may continue to weaken as a consequence of climate change. Here, the authors use a conceptual radiative–convective equilibrium (RCE) framework to interpret the weakening of the Walker circulation as simulated by the GFDL coupled GCM. Based on the modeled lapse rate and clear-sky cooling rate profiles, the RCE framework can directly compute the change of vertical velocity in the descending branch of the Walker circulation, which agrees with the counterpart simulated by the GFDL model. The results show that the vertical structure of clear-sky radiative cooling rate QR will change in response to the increased water vapor as the globe warms. The authors explain why the change of QR is positive in the uppermost part of the troposphere (<300 hPa) and is negative for the rest of the troposphere. As a result, both the change of clear-sky cooling rate and the change of tropospheric lapse rate contribute to the weakening of circulation. The vertical velocity changes due to the two factors are comparable to each other from the top of the planetary boundary layer to 600 hPa. From 600 to 300 hPa lapse rate changes are the dominant cause of the weakening circulation. Above 300 hPa, the change due to QR is opposite to the change due to lapse rate, which forces a slight increase in vertical velocity that is seen in the model simulation.

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Xianglei Huang, Xiuhong Chen, Mark Flanner, Ping Yang, Daniel Feldman, and Chaincy Kuo

Abstract

Surface longwave emissivity can be less than unity and vary significantly with frequency. However, most climate models still assume a blackbody surface in the longwave (LW) radiation scheme of their atmosphere models. This study incorporates realistic surface spectral emissivity into the atmospheric component of the Community Earth System Model (CESM), version 1.1.1, and evaluates its impact on simulated climate. By ensuring consistency of the broadband surface longwave flux across different components of the CESM, the top-of-the-atmosphere (TOA) energy balance in the modified model can be attained without retuning the model. Inclusion of surface spectral emissivity, however, leads to a decrease of net upward longwave flux at the surface and a comparable increase of latent heat flux. Global-mean surface temperature difference between the modified and standard CESM simulation is 0.20 K for the fully coupled run and 0.45 K for the slab-ocean run. Noticeable surface temperature differences between the modified and standard CESM simulations are seen over the Sahara Desert and polar regions. Accordingly, the climatological mean sea ice fraction in the modified CESM simulation can be less than that in the standard CESM simulation by as much as 0.1 in some regions. When spectral emissivities of sea ice and open ocean surfaces are considered, the broadband LW sea ice emissivity feedback is estimated to be −0.003 W m−2 K−1, assuming flat ice emissivity as sea ice emissivity, and 0.002 W m−2 K−1, assuming coarse snow emissivity as sea ice emissivity, which are two orders of magnitude smaller than the surface albedo feedback.

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Qing Yue, Brian H. Kahn, Eric J. Fetzer, Mathias Schreier, Sun Wong, Xiuhong Chen, and Xianglei Huang

Abstract

The authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs show the TOA radiative sensitivity of cloud types to unit cloud fraction change as observed by the A-Train. Therefore, a combination of observation-based CRKs with cloud changes observed by these instruments over time will provide an estimate of the short-term cloud feedback by maintaining consistency between CRKs and cloud responses to climate variability.

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Xianwen Jing, Xianglei Huang, Xiuhong Chen, Dong L. Wu, Peter Pilewskie, Odele Coddington, and Erik Richard

Abstract

Not only total solar irradiance (TSI) but spectral solar irradiance (SSI) matter for our climate. Different surfaces can have different reflectivity for the visible (VIS) and near-infrared (NIR). The recent NASA TSIS-1 mission has provided more accurate SSI observations than before. The TSI observed by TSIS-1 differs from the counterpart used by climate models by no more than 1 W m–2. However, the SSI difference in a given VIS (e.g., 0.44–0.63 μm) and NIR (e.g., 0.78–1.24 μm) band can be as large as 4 W m–2 with opposite signs. Using the NCAR CESM2, we study to what extent such different VIS and NIR SSI partitions can affect the simulated climate. Two sets of simulations with identical TSI are carried out, one with SSI partitioning as observed by the TSIS-1 mission and the other with what has been used in the current climate models. Due to different VIS-NIR spectral reflectance contrasts between icy (or snowy) surfaces and open water, the simulation with more SSI in the VIS has less solar absorption by the high-latitude surfaces, ending up with colder polar surface temperature and larger sea ice coverage. The difference is more prominent over the Antarctic than over the Arctic. Our results suggest that, even for the identical TSI, the surface albedo feedback can be triggered by different SSI partition between the VIS and NIR. The results underscore the importance of continuously monitoring SSI and the use of correct SSI in climate simulations.

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Chunpeng Wang, Zhengzhao Johnny Luo, Xiuhong Chen, Xiping Zeng, Wei-Kuo Tao, and Xianglei Huang

Abstract

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

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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.

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Xu Liu, Wan Wu, Bruce A. Wielicki, Qiguang Yang, Susan H. Kizer, Xianglei Huang, Xiuhong Chen, Seiji Kato, Yolanda L. Shea, and Martin G. Mlynczak

Abstract

Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Previous studies have evaluated the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. The present study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky conditions. A 0.04-K (k = 2; 95% confidence) radiometric calibration requirement baseline is derived using a spectral fingerprinting method. It is also demonstrated that the requirement is spectrally dependent and that some spectral regions can be relaxed as a result of the hyperspectral nature of the CLARREO instrument. Relaxing the requirement to 0.06 K (k = 2) is discussed further based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in the time to detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.

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