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A computationally efficient method is presented to account for the horizontal cloud inhomogeneity by using a radiatively equivalent plane-parallel homogeneous (PPH) cloud. The algorithm can accurately match the calculations of the reference (rPPH) independent column approximation (ICA) results but uses only the same computational time required for a single plane-parallel computation. The effective optical depth of this synthetic sPPH cloud is derived by exactly matching the direct transmission to that of the inhomogeneous ICA cloud. The effective scattering asymmetry factor is found from a precalculated albedo inverse lookup table that is allowed to vary over the range from −1.0 to 1.0. In the special cases of conservative scattering and total absorption, the synthetic method is exactly equivalent to the ICA, with only a small bias (about 0.2% in flux) relative to ICA resulting from imperfect interpolation in using the lookup tables. In principle, the ICA albedo can be approximated accurately regardless of cloud inhomogeneity. For a more complete comparison, the broadband shortwave albedo and transmission calculated from the synthetic sPPH cloud and averaged over all incident directions have RMS biases of 0.26% and 0.76%, respectively, for inhomogeneous clouds over a wide variation of particle size. The advantages of the synthetic PPH method are that 1) it is not required that all the cloud subcolumns have uniform microphysical characteristic, 2) it is applicable to any 1D radiative transfer scheme, and 3) it can handle arbitrary cloud optical depth distributions and an arbitrary number of cloud subcolumns with uniform computational efficiency.

The Clouds and Earth’s Radiant Energy System (CERES) has been monitoring clouds and radiation since 2000 using algorithms developed before 2002 for CERES Edition 2 (Ed2) products. To improve cloud amount accuracy, CERES Edition 4 (Ed4) applies revised algorithms and input data to Terra and Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) radiances. The Ed4 cloud mask uses 5–7 additional channels, new models for clear-sky ocean and snow/ice-surface radiances, and revised Terra MODIS calibrations. Mean Ed4 daytime and nighttime cloud amounts exceed their Ed2 counterparts by 0.035 and 0.068. Excellent consistency between average Aqua and Terra cloud fraction is found over nonpolar regions. Differences over polar regions are likely due to unresolved calibration discrepancies. Relative to Ed2, Ed4 cloud amounts agree better with those from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). CALIPSO comparisons indicate that Ed4 cloud amounts are more than or as accurate as other available cloud mask systems. The Ed4 mask correctly identifies cloudy or clear areas 90%–96% of the time during daytime over nonpolar areas depending on the CALIPSO–MODIS averaging criteria. At night, the range is 88%–95%. Accuracy decreases over land. The polar day and night accuracy ranges are 90%–91% and 80%–81%, respectively. The mean Ed4 cloud fractions slightly exceed the average for seven other imager cloud masks. Remaining biases and uncertainties are mainly attributed to errors in Ed4 predicted clear-sky radiances. The resulting cloud fractions should help CERES produce a more accurate radiation budget and serve as part of a cloud property climate data record.

Background Colorectal cancer (CRC) is among the most frequent and lethal malignancies worldwide. Although great advances have been made in the treatment of CRC, prognosis remains poor. Our previous study indicated that tripartite motif-containing 14 (TRIM14) was upregulated in CRC samples. Methods In the current study, the association between TRIM14 and CRC was investigated. Protein expression was determined by Western blotting and immunohistochemistry. Further, the biological roles of TRIM14 in CRC cell proliferation and apoptosis were explored both in vitro and in vivo. Results We observed that increased TRIM14 expression in CRC tissues was closely related with aggressive clinicopathological characteristics and poor prognosis. TRIM14 knockdown markedly reduced proliferation and increased apoptosis in HT-29 and SW620 cells, whereas TRIM14 overexpression in LoVo cells displayed opposite results. Xenograft experiments using HT-29 cells confirmed suppression of tumor growth and induction of apoptosis upon TRIM14 knockdown in vivo. Furthermore, downregulation of TRIM14 inhibited the AKT pathway, as indicated by reduced levels of phosphorylated AKT, Bcl-2 and Cyclin D1, and elevated levels of phosphatase and tensin homology (PTEN) and p27. In addition, TRIM14 colocalized with PTEN in the cytoplasm and induced PTEN ubiquitination. Moreover, PTEN overexpression significantly inhibited pro-proliferative effects of TRIM14, indicating an involvement of PTEN/AKT signaling in mediating TRIM14 functions. Conclusions The present data demonstrate that TRIM14 overexpression promotes CRC cell proliferation, suggesting TRIM14 as an attractive therapeutic target for CRC.

Stratospheric radiative damping increases as atmospheric carbon dioxide concentration rises. We use the one-dimensional mechanistic models of the quasi-biennial oscillation (QBO) to conduct sensitivity experiments and find that the simulated QBO period shortens due to the enhancing of radiative damping in the stratosphere. This result suggests that increasing stratospheric radiative damping due to rising CO2 may play a role in determining the QBO period in a warming climate along with wave momentum flux entering the stratosphere and tropical vertical residual velocity, both of which also respond to increasing CO2.

Increasing evidence indicates that environmental pollutants can change human gut microbiota. Microcystin–leucine arginine (MC-LR), considered a major hazard to mammals, is one of the important contaminants. However, little is known about the long-term influence of MC-LR on gut microbial communities. We aimed to investigate the effect of MC-LR on gut microbiota composition and functions by conducting a chronic exposure of male mice to MC-LR via the oral route. Using 16S rRNA gene sequencing analysis on cecum samples of mice, our results showed that significant changes of species diversity were observed in the gut microbiota of MC-LR-exposed mice. In addition, comparative analysis of the microbial communities showed that the reduction of the Actinobacteria and Saccharibacteria populations was detected in MC-LR-exposed mice. Collectively, our study highlighted the significant effects of MC-LR on the shift of gut microbial communities which could contribute to the development of metabolic syndromes.

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800–1250 cm(−1)). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300–600 cm(−1)) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ~3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important. The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%–4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m(2), and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m(2) and 1.8 W/m(2), respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6W/m(2), −1.1 W/m(2), and −2.5 W/m(2), respectively. The global scattering impact of 2.7 W/m(2) on the OLR is small when compared to the typical global OLR value of 240W/m(2), but it is significant when compared to cloud LW radiative forcing (30W/m(2)) and net cloud forcing (−14W/m(2)). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO(2).

Background Colorectal cancer (CRC) is among the most frequent and lethal malignancies worldwide. Although great advances have been made in the treatment of CRC, prognosis remains poor. Our previous study indicated that tripartite motif-containing 14 (TRIM14) was upregulated in CRC samples. Methods In the current study, the association between TRIM14 and CRC was investigated. Protein expression was determined by Western blotting and immunohistochemistry. Further, the biological roles of TRIM14 in CRC cell proliferation and apoptosis were explored both in vitro and in vivo. Results We observed that increased TRIM14 expression in CRC tissues was closely related with aggressive clinicopathological characteristics and poor prognosis. TRIM14 knockdown markedly reduced proliferation and increased apoptosis in HT-29 and SW620 cells, whereas TRIM14 overexpression in LoVo cells displayed opposite results. Xenograft experiments using HT-29 cells confirmed suppression of tumor growth and induction of apoptosis upon TRIM14 knockdown in vivo. Furthermore, downregulation of TRIM14 inhibited the AKT pathway, as indicated by reduced levels of phosphorylated AKT, Bcl-2 and Cyclin D1, and elevated levels of phosphatase and tensin homology (PTEN) and p27. In addition, TRIM14 colocalized with PTEN in the cytoplasm and induced PTEN ubiquitination. Moreover, PTEN overexpression significantly inhibited pro-proliferative effects of TRIM14, indicating an involvement of PTEN/AKT signaling in mediating TRIM14 functions. Conclusions The present data demonstrate that TRIM14 overexpression promotes CRC cell proliferation, suggesting TRIM14 as an attractive therapeutic target for CRC.

Using the Earth׳s reflected solar spectrum for climate change fingerprinting is an emerging research area. The spectral fingerprinting approach directly retrieves the changes in climate variables from the mean spectral data averaged across large space and time scales. To investigate this fingerprinting concept, we use ten years of satellite data to simulate the monthly and annual mean reflected solar spectra and the associated spectral fingerprints for different regions over the ocean. The interannual variations in the spectral data are derived and attributed to the interannual variations in the relevant climate variables. The fingerprinting retrieved changes in climate variables are then compared with the actual underlying variable changes from the observational data to evaluate the fingerprinting retrieval accuracy. Two important errors related to the fingerprinting approach, the nonlinearity error and the averaging error in the mean fingerprints, and their impact on the retrieval accuracy, are investigated. It is found that the averaging error increases but the nonlinearity error decreases as the region size increases. The averaging error has minimal effect on the fingerprinting retrieval accuracy in small regions but has more of an impact in large regions. In comparison, the effect of nonlinearity error on the retrieval accuracy decreases as the region size increases. It is also found that the fingerprinting retrieval accuracy is more sensitive to the nonlinearity error than to the averaging error. In addition, we compare the fingerprinting accuracy between using the monthly mean data and the annual mean data. The results show that on average higher retrieval accuracy is achieved when the annual mean data are used for the fingerprinting retrieval.

Attribution of averaged spectral variation over large spatial and temporal scales to different climate variables is central to climate change fingerprinting. Using 10 years of satellite data for simulation, the authors generate a group of observation-based spectral fingerprints and a time series of monthly mean reflectance spectra over the ocean in five large latitude regions and globally. Next, these fingerprints and the interannual variation spectra are used to retrieve the interannual changes in the relevant climate variables to test the concept of using the spectral fingerprinting approach for climate change attribution. Comparing the fingerprinting retrieval of climate variable change to the actual underlying variable change, the RMS differences between the two are less than twice as large as the monthly variability for all variables in all regions. Instances where larger errors are observed correspond to those variables with large nonlinear radiative response, such as the cloud optical depth and the ice particle size. Using the linear fingerprinting approach and accounting for the nonlinear radiative error in fingerprints results in significantly higher retrieval accuracy; the RMS errors are reduced to less than the monthly variability for nearly all variables, indicating the profound impact of the nonlinear error on fingerprinting retrieval. Another important finding is that if the cloud fraction is known a priori, the retrieval accuracy in cloud optical depth would be improved substantially. Moreover, a better retrieval for the water vapor amount and aerosol optical depth can be achieved from the clear-sky data only. The test results demonstrate that climate change fingerprinting based on reflected solar benchmark spectra is possible.

Background Colorectal cancer (CRC) is one of the most lethal malignancies. Tripartite Motif Containing 14 (TRIM14) is a member of TRIM family proteins, which are involved in the pathogenesis of various cancers. This study aimed to investigate TRIM14 expression in CRC tissues, and its effects on the migration and invasion of CRC cell lines. Methods TRIM14 mRNA expression was detected by real-time PCR analysis. Cell migration and invasion were measured by Transwell assays. Protein expression was assessed by western blot analysis. Results The expression of TRIM14 was significantly higher in CRC tissues than in matched non-cancerous tissues. TRIM14 knockdown by specific short hairpin RNA (shRNA) attenuated CRC cell migration and invasion, whereas TRIM14 overexpression caused reverse effect. Moreover, TRIM14 positively regulated the protein levels of sphingosine kinase 1 (SPHK1) and phosphorylated STAT3 (p-STAT3), as well as the mRNA and protein expression of matrix metalloproteinase 2, MMP9 and vascular endothelial growth factor, which are transcriptional targets of the STAT3 signaling pathway. Importantly, the blockage of the SPHK1/STAT3 signaling pathway by SKI-II or AG490 could reverse the TRIM14-promoted CRC cell migration and invasion. Conclusions Our results reveal a critical role for TRIM14 in promoting migration and invasion of CRC cells, and suggest TRIM14 may serve as a potential molecular target to prevent CRC metastasis. Electronic supplementary material The online version of this article (10.1186/s12935-018-0701-1) contains supplementary material, which is available to authorized users.

The foundation for future space mission Climate Absolute Radiance and Refractivity Observatory (CLARREO) is the ability to produce climate change benchmark records and provide on-orbit calibration standard through the highly accurate and Systeme Internationale -traceable observations. The accuracy of CLARREO measurements is set to 0.3% $(k=2)$ for spectrally resolved reflectance. The instrument sensitivity to polarization and polarization of reflected light at the top of atmosphere are the sources for systematic uncertainty. In this paper, we estimate radiometric errors due to polarization effects for CLARREO benchmark and reference intercalibration observations. Data from the Polarization and Anisotropy of Reflectance for Atmospheric Sciences coupled with Observations from Lidar (PARASOL) instrument, a spaceborne polarimeter, have been used in combination with the orbital modeling of Earth's sampling. For the CLARREO benchmark data, we used simulated annual nadir sampling for the polar orbit with 90° inclination, and for the intercalibration with cross-track sensors on the JPSS, such as CERES and VIIRS, we simulated on-orbit matched data sampling. Selected PARASOL data over one full solar year provided polarization parameters in visible (VIS) spectral range. For estimating polarization in near infrared (NIR) spectral range, we used a radiative transfer model. Our results show that to limit error contribution due to polarization to half of the allowed total, the sensitivity to polarization of CLARREO reflected solar instrument should not exceed 0.5% $(k=2)$ in spectral range from VIS to NIR.

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to conduct highly accurate and International System of Unit-traceable decadal change observations and provide an on-orbit intercalibration standard with high accuracy for relevant Earth observing sensors. The goal of reference intercalibration is to enable rigorous observations of critical climate change variables, including reflected broadband radiation, cloud properties, and changes in surface albedo, including snow and ice albedo feedback, to be made consistently among different sensors. This requires the CLARREO Reflected Solar Spectrometer (RSS) to provide highly accurate spectral reflectance measurements to establish an on-orbit reference with a radiometric accuracy requirement better than 0.3% $(\mathrm{k} =2) $ for existing sensors. In this paper, MODTRAN-simulated top-of-atmosphere spectral data and spectral measurements from the SCIAMACHY instrument on Envisat are used to determine sensitivity of intercalibration uncertainty on key design parameters of the CLARREO spectrometer: spectral range, sampling and resolution. Their impact on intercalibration uncertainty for MODIS and VIIRS imagers is estimated for various surface types (ocean, vegetation, desert, snow, deep convective clouds, clouds and all-sky) . Results indicate that for the visible to near-infrared spectral region (465–856 nm) , the RSS instrument under current design concept produces uncertainties of 0.16% for the spectral range and 0.3% for the sampling and resolution. However, for the water vapor absorption bands in the short wavelength infrared region (1242–1629 nm) , the same requirement is not met for sampling and resolution due to their high sensitivity to the influence of atmospheric water vapor.

A successor version 3 of DISORT (DISORT3) is presented with important upgrades that improve the accuracy, efficiency, and stability of the algorithm. Compared with version 2 (DISORT2 released in 2000) these upgrades include (a) a redesigned BRDF computation that improves both speed and accuracy, (b) a revised treatment of the single scattering correction, and (c) additional efficiency and stability upgrades for beam sources. In DISORT3 the BRDF computation is improved in the following three ways: (i) the Fourier decomposition is prepared "off-line", thus avoiding the repeated internal computations done in DISORT2; (ii) a large enough number of terms in the Fourier expansion of the BRDF is employed to guarantee accurate values of the expansion coefficients (default is 200 instead of 50 in DISORT2); (iii) in the post processing step the reflection of the direct attenuated beam from the lower boundary is included resulting in a more accurate single scattering correction. These improvements in the treatment of the BRDF have led to improved accuracy and a several-fold increase in speed. In addition, the stability of beam sources has been improved by removing a singularity occurring when the cosine of the incident beam angle is too close to the reciprocal of any of the eigenvalues. The efficiency for beam sources has been further improved from reducing by a factor of 2 (compared to DISORT2) the dimension of the linear system of equations that must be solved to obtain the particular solutions, and by replacing the LINPAK routines used in DISORT2 by LAPACK 3.5 in DISORT3. These beam source stability and efficiency upgrades bring enhanced stability and an additional 5-7% improvement in speed. Numerical results are provided to demonstrate and quantify the improvements in accuracy and efficiency of DISORT3 compared to DISORT2.

Additional file 1: Figure S1. TRIM14 affected the migration and invasion of CRC cells. HT-29 (A) and SW620 cells (B) were transduced with shTRIM14#1 or shNC. LoVo cells (C) were transduced with pLVX-TRIM14 or pLVX. Transwell migration and invasion assays were performed to determine the effect of TRIM14 expression on the migration and invasion of CRC cell lines at 12 h after treatment. Cells without any treatment were served as negative Control. The stained cells were counted in five random fields at 200× magnification, and the average number was taken. The average number of Control group was set as 100%, and relative migration and invasion of other groups was calculated by comparison of the cell number with the average number of control group. ***P

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

The CALIPSO satellite mission consistently measures volume (including molecule and particulate) light depolarization ratio of ∼2% for smoke, compared to ∼1% for marine aerosols and ∼15% for dust. The observed ∼2% smoke depolarization ratio comes primarily from the nonspherical habits of particles in the smoke at certain particle sizes. In this study, the depolarization of linearly polarized light by small sphere aggregates and irregular Gaussian-shaped particles is studied, to reveal the physics between the depolarization of linearly polarized light and smoke aerosol shape and size. It is found that the depolarization ratio curves of Gaussian-deformed spheres are very similar to sphere aggregates in terms of scattering-angle dependence and particle size parameters when particle size parameter is smaller than 1.0 π . This demonstrates that small randomly oriented nonspherical particles have some common depolarization properties as functions of scattering angle and size parameter. This may be very useful information for characterization and active remote sensing of smoke particles using polarized light. We also show that the depolarization ratio from the CALIPSO measurements could be used to derive smoke aerosol particle size. From the calculation results for light depolarization ratio by Gaussian-shaped smoke particles and the CALIPSO-measured light depolarization ratio of ∼2% for smoke, the mean particle size of South-African smoke is estimated to be about half of the 532 nm wavelength of the CALIPSO lidar.

[1] Atmospheric and surface properties have been measured from space with various spatial resolutions for decades. It is very challenging to derive the mean solar spectral radiance or reflectance over large temporal and spatial scales by explicit radiative transfer computations from the large volume of instantaneous data, especially at high spectral resolution. We propose a procedurally simple but effective method to compute the solar spectral reflectance in large climate domains, in which the probability distribution function (PDF) of cloud optical depth is used to account for the wide variation of cloud properties in different sensor footprints, and to avoid the repeated computations for footprints with similar conditions. This approach is tested with MODIS/CERES data and evaluated with SCIAMACHY measured spectral reflectance. The mean difference between model and observation is about 3% for the monthly global mean reflectance. This PDF-based approach provides a simple, fast, and effective way to simulate the mean spectral reflectance over large time and space scales with a large volume of high-resolution satellite data.

A fast and accurate principal component-based radiative transfer model in the solar spectral region (PCRTM-SOLAR) has been developed. The algorithm is capable of simulating reflected solar spectra in both clear sky and cloudy atmospheric conditions. Multiple scattering of the solar beam by the multilayer clouds and aerosols are calculated using a discrete ordinate radiative transfer scheme. The PCRTM-SOLAR model can be trained to simulate top-of-atmosphere radiance or reflectance spectra with spectral resolution ranging from 1 cmsup-1/supresolution to a few nanometers. Broadband radiances or reflectance can also be calculated if desired. The current version of the PCRTM-SOLAR covers a spectral range from 300 to 2500 nm. The model is valid for solar zenith angles ranging from 0 to 80 deg, the instrument view zenith angles ranging from 0 to 70 deg, and the relative azimuthal angles ranging from 0 to 360 deg. Depending on the number of spectral channels, the speed of the current version of PCRTM-SOLAR is a few hundred to over one thousand times faster than the medium speed correlated-k option MODTRAN5. The absolute RMS error in channel radiance is smaller than 10sup-3/sup mW/cmsup2/sup/sr/cmsup-1/supand the relative error is typically less than 0.2%.

A computationally efficient method is developed to simulate the radiances in a scattering and absorbing atmosphere along an arbitrary path in the spectral region ranging from visible to far-infrared with a spectral resolution of 1 cm ! 1 . For a given spectral region, the method is based on fitting radiances pre-calculated from the discrete ordinate radiative transfer (DISORT) at several wavenumbers. Radiances at other wavenumbers are interpolated based on the pre-computed total absorption and scattering optical thicknesses and the surface albedo. The computational efficiency and accuracy of the method are tested in comparison with rigorous simulations for various scenarios under the same conditions. For both clear-sky and cloud atmospheres, the present method is at least 140 times faster than the direct application of DISORT. Across the spectral range, the standard relative differences between the new method and the DISORT are less than 2% for clear-sky conditions. Root-mean-square (RMS) differences of the top of the atmosphere (TOA) brightness temperatures between the new method and DISORT, for atmospheric infrared sounder (AIRS) channels over clear-sky, ice cloudy and water cloudy skies, are within the noise equivalent differential temperature (NEDT) of the AIRS sensor. The fast method is also applied to simulations of the spectral downwelling radiance measured by the Fourier transform infrared (FTIR) interferometer, and to the simulations of the AIRS upwelling radiances under clear-sky and cloudy conditions.

We investigated the single scattering optical properties of snow for different ice particle shapes and degrees of microscopic scale roughness. These optical properties were implemented and tested in a coupled atmosphere-snow radiative transfer model. The modeled surface spectral albedo and radiance distribution were compared with surface measurements. The results show that the reflected radiance and irradiance over snow are sensitive to the snow grain size and its vertical profile. When inhomogeneity of the particle size distribution in the vertical is taken into account, the measured spectral albedo can be matched, regardless of the particle shapes. But this is not true for the modeled radiance distribution, which depends a lot on the particle shape. The usual “equivalent spheres” assumption significantly overestimates forward reflected radiances, and underestimates backscattering radiances, around the principal plane. On average, the aggregate shape assumption has the best agreement with the measured radiances to a mean bias within 2%. The snow optical properties with the aggregate assumption were applied to the retrieval of snow grain size over the Antarctic plateau. The retrieved grain sizes of the top layer showed similar and large seasonal variation in all years, but only small year to year variation. Using the retrieved snow grain sizes, the modeled spectral and broadband radiances showed good agreements with MODIS and CERES measurements over the Antarctic plateau. Except for the MODIS 2.13 μm channel, the mean relative model-observation differences are within few percent. The modeled MODIS radiances using measured surface reflectance at Dome C also showed good agreement in visible channels, where radiation is not sensitive to snow grain size and the measured surface bidirectional reflectance is applicable over the Antarctic plateau. But modeled radiances using local, surface-measured reflectance in the near infrared yielded large errors because of the high sensitivity to the snow grain size, which varies spatially and temporally. The CERES broadband shortwave radiance is moderately sensitive to the snow grain size, comparable to the MODIS 0.86 μm channel. The variation of broadband snow reflectance due to the seasonal variation in snow grain size is about 5% in a year over the Antarctic plateau. CERES broadband radiances simulated with grain sizes retrieved using MODIS are about 2% larger than those observed.

Several drugs are effective in attenuating intestinal ischemia-reperfusion injury (IRI); however little is known about the effect of montelukast. Fifty rats were randomly assigned to 3 groups: model group (operation with clamping), sham group (operation without clamping) and study group (operation with clamping and 0.2, 2 and 20 mg/kg montelukast pretreatment). Intestinal ischemia-reperfusion was performed by occlusion (clamping) of the arteria mesenterica anterior for 45 min, followed by 24 h reperfusion. Intestinal IRI in the model group led to severe damage of the intestinal mucosa, liver and kidney. The Chiu scores of the intestines from the study group (2 and 20 mg/kg) were lower than that of the model group. Intestinal IRI induced a marked increase in CysLTR1, Caspase-8 and -9 expression in intestine, liver and kidney, which were markedly reduced by preconditioning with 2 mg/kg montelukast. Preconditioning with 2 g/kg montelukast significantly attenuated hepatic tissue injury and kidney damage and decreased plasma interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) levels in plasma after intestinal IRI. In conclusion, preconditioning with montelukast could attenuate intestinal IRI and the subsequent systemic inflammatory response in rats.

Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol layer is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident, AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method’s accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but are too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward-viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

Spectral and broadband radiances and irradiances (fluxes) were measured from surface, airborne, and spaceborne platforms in the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. The radiation data obtained on the 4 clear days over ocean during CLAMS are analyzed here with the Coupled Ocean–Atmosphere Radiative Transfer (COART) model. The model is successively compared with observations of broadband fluxes and albedos near the ocean surface from the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) sea platform and a low-level OV-10 aircraft, of near-surface spectral albedos from COVE and OV-10, of broadband radiances at multiple angles and inferred top-of-atmosphere (TOA) fluxes from CERES, and of spectral radiances at multiple angles from Airborne Multiangle Imaging Spectroradiometer (MISR), or “AirMISR,” at 20-km altidude. The radiation measurements from different platforms are shown to be consistent with each other and with model results. The discrepancies between the model and observations at the surface are less than 10 W m−2 for downwelling and 2 W m−2 for upwelling fluxes. The model–observation discrepancies for shortwave ocean albedo are less than 8%; some discrepancies in spectral albedo are larger but less than 20%. The discrepancies between low-altitude aircraft and surface measurements are somewhat larger than those between the model and the surface measurements; the former are due to the effects of differences in height, aircraft pitch and roll, and the noise of spatial and temporal variations of atmospheric and oceanic properties. The discrepancy between the model and the CERES observations for the upwelling radiance is 5.9% for all angles; this is reduced to 4.9% if observations within 15° of the sun-glint angle are excluded. The measurements and model agree on the principal impacts that ocean optical properties have on upwelling radiation at low levels in the atmosphere. Wind-driven surface roughness significantly affects the upwelling radiances measured by aircraft and satellites at small sun-glint angles, especially in the near-infrared channel of MISR. Intercomparisons of various measurements and the model show that most of the radiation observations in CLAMS are robust, and that the coupled radiative transfer model used here accurately treats scattering and absorption processes in both the air and the water.

A coupled atmosphere–ocean radiative transfer model has been applied to analyze a full year of broadband solar irradiances (up and down) measured over an ocean site 25 km east of the coast of Virginia in the Atlantic. The coupled model treats absorption and scattering by layers for both the atmosphere and the ocean explicitly and consistently. Key input parameters for the model (aerosol optical depth, wind speed, and total precipitable water) are also from in situ measurements. Having more observations to specify properties of the atmosphere than of the ocean, better model–observation agreement is obtained for the downwelling irradiance, which depends primarily on the atmospheric optical properties, than for the upwelling irradiance, which depends heavily on the ocean optical properties. The mean model–observation differences for the ocean surface albedo are generally less than 0.01. However, the modeled upwelling irradiances and albedo over the ocean surface are mostly less than the observations...

Advanced Very High Resolution Radiometer (AVHRR) images of arctic snow reflectance, observed from different satellite passes with the closest pass times on the same day, show different patterns that are related to the sun-satellite geometry. The variation of snow reflectance with view angle can be large or small, depending on the view geometry. Thus, the snow reflectances of a common target, observed from different viewing angles, can be very different and hard to compare. Unfortunately, none represent the actual physical snow albedo, and the error in the converted broadband top of atmosphere (TOA) albedo could easily be larger than 10%, which implies a great effect on the solar radiation balance at TOA. For an accurate estimate of the solar energy budget from satellite observations, an anisotropic correction is required not only for those reflectance images with obvious angular variation, but also for seemingly “isotropic” scenes because this latter case might incorrectly estimate the albedo under general conditions. Two methods, one based on a radiative transfer model and the other on National Oceanic and Atmospheric Administration's (NOAA) Earth Radiation Budget (ERB) experimental data, have been applied to AVHRR data to implement an anisotropic correction. The results show that both methods can remove the systematic variation of snow reflectance with view angle and can significantly reduce the large observed differences in reflectances from different satellite observations of a common snow target. The radiative transfer model-based method, however, unlike the NOAA experimental method, corrects the reflectances in the two AVHRR channels separately, has higher angular resolution than the NOAA experimental method, and can account for variations in snow condition (e.g., grain size). Moreover, the model-based anisotropic correction shows superior self-consistency compared to that produced by NOAA's experimental-based method. Finally, the model-based method provides a sound theoretical basis for anisotropic correction of satellite images of arctic snow reflectance.

Cloud top height is an important variable for both scientific and operational meteorological applications. Unfortunately, direct observations of cloud top height are generally not routinely made. This article develops a new hybrid method for estimating cloud top height from Advanced Very High Resolution Radiometer (AVHRR) data to help provide more abundant and accurate cloud top height estimates at low cost. It takes into account arbitrary viewing and illumination conditions which can affect the accuracy of both cloud shadow detection and cloud shadow-based cloud top height retrievals. Results were validated with data taken by NASA's ER-2 Cloud LIDAR System (CLS). The mean differences between the AVHRR-based cloud height estimates and the LIDAR observations for the two validation images analyzed are 0.45 km and 0.67 km. The sensitivity of the results to the parametrizations used by the new algorithm was also evaluated. Parameters can be chosen to minimize their effect on retrieved cloud top heights; the procedure executes quickly. Given the accuracy of the cloud top height retrievals, the method could be used routinely to provide cloud top heights for a wide variety of meteorological and hydrometeorological applications (e.g., numerical weather prediction, drought monitoring). With the improved spatial resolution (and reduced cost) of data from soon to be launched new satellite observing systems, proportionally higher accuracy and resolution for cloud top heights can be achieved economically using this method.

The computer codes that calculate the energy budget of solar and thermal radiation in Global Climate Models (GCMs), our most advanced tools for predicting climate change, have to be computationally efficient in order to not impose undue computational burden to climate simulations. By using approximations to gain execution speed, these codes sacrifice accuracy compared to more accurate, but also much slower, alternatives. International efforts to evaluate the approximate schemes have taken place in the past, but they have suffered from the drawback that the accurate standards were not validated themselves for performance. The manuscript summarizes the main results of the first phase of an effort called "Continual Intercomparison of Radiation Codes" (CIRC) where the cases chosen to evaluate the approximate models are based on observations and where we have ensured that the accurate models perform well when compared to solar and thermal radiation measurements. The effort is endorsed by international organizations such as the GEWEX Radiation Panel and the International Radiation Commission and has a dedicated website (i.e., http://circ.gsfc.nasa.gov) where interested scientists can freely download data and obtain more information about the effort's modus operandi and objectives. In a paper published in the March 2010 issue of the Bulletin of the American Meteorological Society only a brief overview of CIRC was provided with some sample results. In this paper the analysis of submissions of 11 solar and 13 thermal infrared codes relative to accurate reference calculations obtained by so-called "line-by-line" radiation codes is much more detailed. We demonstrate that, while performance of the approximate codes continues to improve, significant issues still remain to be addressed for satisfactory performance within GCMs. We hope that by identifying and quantifying shortcomings, the paper will help establish performance standards to objectively assess radiation code quality, and will guide the development of future phases of CIRC

[1] We have analyzed the correlation between measurements by three different satellite sensors (SCIAMACHY, MODIS, and CERES) on two independent space platforms (Envisat and Terra). Though the instantaneous measurements from the two satellites are not collocated due to orbit offset, the monthly mean broadband and narrowband reflectances and their anomalies from the three instruments are highly correlated when averaged over large latitude regions. The mean reflectance from MODIS in each of those large domains is nearly the same as that derived from SCIAMACHY spectrum convolved with the filter function of the corresponding MODIS channel, with all correlation coefficients higher than 0.93. The interannual variability of monthly mean reflectance is also correlated with the variations of mean cloud and surface properties in large climate zones. The reflectance variation is correlated with the cloud fraction in low and middle latitude regions with correlation coefficients higher than 0.76 and with the snow and sea ice changes in the polar regions with correlation coefficients higher than 0.6. These correlations indicate that the nadir sampling strategy as proposed for CLARREO is sufficient for climate benchmarking of the reflected solar spectrum and provide the physical foundation for climate fingerprinting. However, the results also show the relatively large differences in trends in reflectance due to different instrument degradations and inconsistent calibrations which will affect the attribution of radiative signals of long-term climate change.

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.