scholarly journals An Observationally Based Global Band-by-Band Surface Emissivity Dataset for Climate and Weather Simulations

2016 ◽  
Vol 73 (9) ◽  
pp. 3541-3555 ◽  
Author(s):  
Xianglei Huang ◽  
Xiuhong Chen ◽  
Daniel K. Zhou ◽  
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.

2019 ◽  
Vol 15 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Marina Suzuki

Abstract. There remain substantial uncertainties in future projections of Arctic climate change. There is a potential to constrain these uncertainties using a combination of paleoclimate simulations and proxy data, but such a constraint must be accompanied by physical understanding on the connection between past and future simulations. Here, we examine the relevance of an Arctic warming mechanism in the mid-Holocene (MH) to the future with emphasis on process understanding. We conducted a surface energy balance analysis on 10 atmosphere and ocean general circulation models under the MH and future Representative Concentration Pathway (RCP) 4.5 scenario forcings. It is found that many of the dominant processes that amplify Arctic warming over the ocean from late autumn to early winter are common between the two periods, despite the difference in the source of the forcing (insolation vs. greenhouse gases). The positive albedo feedback in summer results in an increase in oceanic heat release in the colder season when the atmospheric stratification is strong, and an increased greenhouse effect from clouds helps amplify the warming during the season with small insolation. The seasonal progress was elucidated by the decomposition of the factors associated with sea surface temperature, ice concentration, and ice surface temperature changes. We also quantified the contribution of individual components to the inter-model variance in the surface temperature changes. The downward clear-sky longwave radiation is one of major contributors to the model spread throughout the year. Other controlling terms for the model spread vary with the season, but they are similar between the MH and the future in each season. This result suggests that the MH Arctic change may not be analogous to the future in some seasons when the temperature response differs, but it is still useful to constrain the model spread in the future Arctic projection. The cross-model correlation suggests that the feedbacks in preceding seasons should not be overlooked when determining constraints, particularly summer sea ice cover for the constraint of autumn–winter surface temperature response.


2007 ◽  
Vol 7 (20) ◽  
pp. 5391-5400 ◽  
Author(s):  
K. M. Nissen ◽  
K. Matthes ◽  
U. Langematz ◽  
B. Mayer

Abstract. We introduce the improved Freie Universität Berlin (FUB) high-resolution radiation scheme FUBRad and compare it to the 4-band standard ECHAM5 SW radiation scheme of Fouquart and Bonnel (FB). Both schemes are validated against the detailed radiative transfer model libRadtran. FUBRad produces realistic heating rate variations during the solar cycle. The SW heating rate response with the FB scheme is about 20 times smaller than with FUBRad and cannot produce the observed temperature signal. A reduction of the spectral resolution to 6 bands for solar irradiance and ozone absorption cross sections leads to a degradation (reduction) of the solar SW heating rate signal by about 20%. The simulated temperature response agrees qualitatively well with observations in the summer upper stratosphere and mesosphere where irradiance variations dominate the signal. Comparison of the total short-wave heating rates under solar minimum conditions shows good agreement between FUBRad, FB and libRadtran up to the middle mesosphere (60–70 km) indicating that both parameterizations are well suited for climate integrations that do not take solar variability into account. The FUBRad scheme has been implemented as a sub-submodel of the Modular Earth Submodel System (MESSy).


2021 ◽  
Vol 13 (21) ◽  
pp. 4464
Author(s):  
Jiawen Xu ◽  
Xiaotong Zhang ◽  
Chunjie Feng ◽  
Shuyue Yang ◽  
Shikang Guan ◽  
...  

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).


1985 ◽  
Vol 6 ◽  
pp. 238-241 ◽  
Author(s):  
Takashi Yamanouchi ◽  
Sadao Kawaguchi

Effects of drifting snow are examined from measurements of radiation fluxes at Mizuho Station in the katabatic wind zone, Antarctica. A good correlation is found between the difference of downward longwave fluxes measured at two heights and wind speed used as an index of drifting snow. The wind increases the downward flux at a rate of 2 W m-2/m s-2 when wind speed is higher than 13 m/s. Drifting snow suppresses the net longwave cooling at the surface. Direct solar radiation is depleted greatly by the drifting snow; however, the global flux decreases only slightly, compensated by the large increase of the diffuse flux, at a rate of about 1% for each 1 m/s increase in wind speed. At Mizuho Station, the effect on longwave radiation prevails throughout the year. The relation between snow drift content and wind speed is obtained from shortwave optical depth measurements as a function of wind speed. A simple parameterization of radiative properties is given.


2012 ◽  
Vol 25 (17) ◽  
pp. 6036-6056 ◽  
Author(s):  
Minghong Zhang ◽  
Shuanglin Li ◽  
Jian Lu ◽  
Renguang Wu

Abstract This study examines the skills in simulating interannual variability of northwestern Pacific (NWP) summer climate in 12 atmospheric general circulation models (AGCMs) attending the Atmospheric Model Intercomparison Project phase 2 (AMIP II). The models show a wide range of skills, among those version 1 of the Hadley Centre Global Atmosphere Model (HadGAM1) showed the highest fidelity and thus may be a better choice for studying East Asian–NWP summer climate. To understand the possible causes for the difference among the models, five models {HadGAM1; ECHAM5; the Geophysical Fluid Dynamics Laboratory Atmosphere Model, version 2.1 (AM2.1); Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)]; and the fourth-generation National Center for Atmospheric Research Community Atmosphere Model (CAM3)} that have various skill levels, ranging from the highest to the moderate to the minor, were selected for analyses. The simulated teleconnection of NWP summer climate with sea surface temperatures (SSTs) in the tropical Indian and Pacific Oceans was first compared. HadGAM1 reproduces suppressed (intensified) rainfall during El Niño (La Niña) events and captures well the remote connection with the tropical Indian Ocean, while the other models either underestimate [ECHAM5, AM2.1, MIROC3.2(hires)] or fail to reproduce (CAM3) these teleconnections. The Walker cell and diabatic heating were further compared to shed light on the underlying physical mechanisms for the difference. Consistent with the best performance in simulating interannual rainfall, HadGAM1 exhibits the highest-level skill in capturing the observed climatology of the Walker cell and diabatic heating. These results highlight the key roles of the model’s background climatology in the Walker cell and diabatic heating, thus providing important clues to improving the model’s ability.


1992 ◽  
Vol 97 (D18) ◽  
pp. 20421 ◽  
Author(s):  
Robert D. Cess ◽  
Gerald L. Potter ◽  
W. Lawrence Gates ◽  
Jean-Jacques Morcrette ◽  
Lisa Corsetti

2015 ◽  
Vol 12 (12) ◽  
pp. 12649-12701 ◽  
Author(s):  
J.-P. Vidal ◽  
B. Hingray ◽  
C. Magand ◽  
E. Sauquet ◽  
A. Ducharne

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs) and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. The QE-ANOVA framework was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large dataset of transient hydrological projections that combines in a comprehensive way 11 runs from 4 different GCMs, 3 SDMs with 10 stochastic realizations each, as well as 6 diverse HMs. The change signal is a decrease in yearly low flows of around −20 % in 2065, except for the most elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal on 30 year low-flow averages is however around 2035, i.e. for time slices starting in 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.


2021 ◽  
pp. 1-55
Author(s):  
Deepashree Dutta ◽  
Steven C. Sherwood ◽  
Katrin J. Meissner ◽  
Alex Sen Gupta ◽  
Daniel J. Lunt ◽  
...  

AbstractWhen simulating past warm climates, such as the early Cretaceous and Paleogene periods, general circulation models (GCMs) underestimate the magnitude of warming in the Arctic. Additionally, model intercomparisons show a large spread in the magnitude of Arctic warming for these warmer-than-modern climates. Several mechanisms have been proposed to explain these disagreements, including the unrealistic representation of polar clouds or underestimated poleward heat transport in the models. This study provides an intercomparison of Arctic cloud and atmospheric heat transport (AHT) responses to strong imposed polar-amplified surface ocean warming across four atmosphere-only GCMs. All models simulate an increase in high clouds throughout the year; the resulting reduction in longwave radiation loss to space acts to support the imposed Arctic warming. The response of low and mid-level clouds varies considerably across the models, with models responding differently to surface warming and sea ice removal. The AHT is consistently weaker in the imposed warming experiments due to a large reduction in dry static energy transport that offsets a smaller increase in latent heat transport, thereby opposing the imposed surface warming. Our idealised polar amplification experiments require very large increases in implied ocean heat transport (OHT) to maintain steady state. Increased CO2 or tropical temperatures that likely characterised past warm climates, reduces the need for such large OHT increases.


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