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- Author or Editor: Xianglei Huang x
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Abstract
The spectral radiative kernel technique is used to derive spectrally resolved relative humidity (RH) feedbacks for 16 GCMs that participated in CMIP5. Examining spectral and spatial details of these RH feedbacks leads to three findings. First, while the global average of broadband RH feedbacks is close to zero for all the GCMs, there exist wide discrepancies in the spectral details among the GCMs. Second, the spatial pattern of the RH feedbacks varies with spectral frequency; for a given frequency, the spatial feedback pattern correlates well with the spatial pattern of RH changes over the vertical layer to which the top-of-atmosphere spectral flux at the same frequency is most sensitive. Third, the nearly zero global average of broadband RH feedback is a result of spatial compensation and spectral compensation. Since GCMs have produced consistent RH feedbacks and RH changes to a large extent in the high latitudes, the tropical Atlantic, and the deep tropical Pacific, radiative RH kernels are further used to infer mean changes in RH vertical profiles from spectral RH feedbacks averaged over the three broad regions. Good agreements are demonstrated by comparing such inferences against the actual RH changes in the GCMs. This study suggests that the spectral dimension of RH feedback could provide an additional constraint to climate models and the understanding of vertical features of RH changes when they are obtainable from future observations.
Abstract
The spectral radiative kernel technique is used to derive spectrally resolved relative humidity (RH) feedbacks for 16 GCMs that participated in CMIP5. Examining spectral and spatial details of these RH feedbacks leads to three findings. First, while the global average of broadband RH feedbacks is close to zero for all the GCMs, there exist wide discrepancies in the spectral details among the GCMs. Second, the spatial pattern of the RH feedbacks varies with spectral frequency; for a given frequency, the spatial feedback pattern correlates well with the spatial pattern of RH changes over the vertical layer to which the top-of-atmosphere spectral flux at the same frequency is most sensitive. Third, the nearly zero global average of broadband RH feedback is a result of spatial compensation and spectral compensation. Since GCMs have produced consistent RH feedbacks and RH changes to a large extent in the high latitudes, the tropical Atlantic, and the deep tropical Pacific, radiative RH kernels are further used to infer mean changes in RH vertical profiles from spectral RH feedbacks averaged over the three broad regions. Good agreements are demonstrated by comparing such inferences against the actual RH changes in the GCMs. This study suggests that the spectral dimension of RH feedback could provide an additional constraint to climate models and the understanding of vertical features of RH changes when they are obtainable from future observations.
Abstract
In the absence of scattering, thermal contrast in the atmosphere is the key to infrared remote sensing. Without the thermal contrast, the amount of absorption will be identical to the amount of emission, making the atmospheric vertical structure undetectable using remote sensing techniques. Here we show that, even in such an isothermal atmosphere, the scattering of clouds can cause a distinguishable change in upwelling radiance at the top of the atmosphere. A two-stream analytical solution, as well as a budget analysis based on Monte Carlo simulations, are used to offer a physical explanation of such influence on an idealized isothermal atmosphere by cloud scattering: it increases the chance of photons being absorbed by the atmosphere before they can reach the boundaries (both top and bottom), which leads to a reduction of TOA upwelling radiance. Actual sounding profiles and cloud properties inferred from satellite observations within 6-h time frames are fed into a more realistic and comprehensive radiative transfer model to show such cloud scattering effect, under nearly isothermal circumstances in the lower troposphere, can lead to ∼1–1.5-K decrease in brightness temperature for the nadir-view MODIS 8.5-μm channel. The study suggests that cloud scattering can provide signals useful for remote sensing applications even for such an isothermal environment.
Abstract
In the absence of scattering, thermal contrast in the atmosphere is the key to infrared remote sensing. Without the thermal contrast, the amount of absorption will be identical to the amount of emission, making the atmospheric vertical structure undetectable using remote sensing techniques. Here we show that, even in such an isothermal atmosphere, the scattering of clouds can cause a distinguishable change in upwelling radiance at the top of the atmosphere. A two-stream analytical solution, as well as a budget analysis based on Monte Carlo simulations, are used to offer a physical explanation of such influence on an idealized isothermal atmosphere by cloud scattering: it increases the chance of photons being absorbed by the atmosphere before they can reach the boundaries (both top and bottom), which leads to a reduction of TOA upwelling radiance. Actual sounding profiles and cloud properties inferred from satellite observations within 6-h time frames are fed into a more realistic and comprehensive radiative transfer model to show such cloud scattering effect, under nearly isothermal circumstances in the lower troposphere, can lead to ∼1–1.5-K decrease in brightness temperature for the nadir-view MODIS 8.5-μm channel. The study suggests that cloud scattering can provide signals useful for remote sensing applications even for such an isothermal environment.
Abstract
In this short note, a misinterpretation of the Voigt line profile is pointed out, which is in several popular textbooks of atmospheric physics. The correct interpretation is given based on mathematical and physical arguments, as well as numerical verification.
Abstract
In this short note, a misinterpretation of the Voigt line profile is pointed out, which is in several popular textbooks of atmospheric physics. The correct interpretation is given based on mathematical and physical arguments, as well as numerical verification.
Abstract
In response to a comment on their previous note about the Voigt line profile, here the authors clarify relevant statements and numeric algorithms in the original note.
Abstract
In response to a comment on their previous note about the Voigt line profile, here the authors clarify relevant statements and numeric algorithms in the original note.
Abstract
Clouds and the Earth’s Radiant Energy System (CERES) daytime longwave (LW) radiances are determined from the difference between a total (TOT) channel (0.3–200 μm) measurement and a shortwave (SW) channel (0.3–5 μm) measurement, while nighttime LW radiances are obtained directly from the TOT channel. This means that a drift in the SW channel or the SW portion of the TOT channel could impact the daytime longwave radiances, but not the nighttime ones. This study evaluates daytime and nighttime CERES LW radiances for a possible secular drift in CERES LW observations using spectral radiances observed by Atmospheric Infrared Sounder (AIRS). By examining the coincidental AIRS and CERES Flight Model 3 (FM3) measurements over the tropical clear-sky oceans for all of January and July months since 2005, a secular drift of about −0.11% yr−1 in the daytime CERES-FM3 longwave unfiltered radiance can be identified in the CERES Single Scanner Footprint (SSF) Edition 2 product. This provides an upper-bound estimation for the drift in daytime outgoing longwave radiation, which is approximately −0.323 W m−2 yr−1. This estimation is consistent with the independent assessment concluded by the CERES calibration team. Such secular drift has been greatly reduced in the latest CERES SSF Edition 3 product. Comparisons are conducted for the CERES window channel as well, and it shows essentially no drift. This study serves as a practical example illustrating how the measurements of spectrally resolved radiances can be used to help evaluate data products from other narrowband or broadband measurements.
Abstract
Clouds and the Earth’s Radiant Energy System (CERES) daytime longwave (LW) radiances are determined from the difference between a total (TOT) channel (0.3–200 μm) measurement and a shortwave (SW) channel (0.3–5 μm) measurement, while nighttime LW radiances are obtained directly from the TOT channel. This means that a drift in the SW channel or the SW portion of the TOT channel could impact the daytime longwave radiances, but not the nighttime ones. This study evaluates daytime and nighttime CERES LW radiances for a possible secular drift in CERES LW observations using spectral radiances observed by Atmospheric Infrared Sounder (AIRS). By examining the coincidental AIRS and CERES Flight Model 3 (FM3) measurements over the tropical clear-sky oceans for all of January and July months since 2005, a secular drift of about −0.11% yr−1 in the daytime CERES-FM3 longwave unfiltered radiance can be identified in the CERES Single Scanner Footprint (SSF) Edition 2 product. This provides an upper-bound estimation for the drift in daytime outgoing longwave radiation, which is approximately −0.323 W m−2 yr−1. This estimation is consistent with the independent assessment concluded by the CERES calibration team. Such secular drift has been greatly reduced in the latest CERES SSF Edition 3 product. Comparisons are conducted for the CERES window channel as well, and it shows essentially no drift. This study serves as a practical example illustrating how the measurements of spectrally resolved radiances can be used to help evaluate data products from other narrowband or broadband measurements.
A Neural Network–Based Cloud Mask for PREFIRE and Evaluation with Simulated ObservationsAbstract
The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) will fill a gap in our understanding of polar processes and the polar climate by offering widespread, spectrally resolved measurements through the far-infrared (FIR) with two identical CubeSat spacecraft. While the polar regions are typically difficult for skillful cloud identification due to cold surface temperatures, the reflection by bright surfaces, and frequent temperature inversions, the inclusion of the FIR may offer increased spectral sensitivity, allowing for the detection of even thin ice clouds. This study assesses the potential skill, as well as limitations, of a neural network (NN)-based cloud mask using simulated spectra mimicking what the PREFIRE mission will capture. Analysis focuses on the polar regions. Clouds are found to be detected approximately 90% of time using the derived neural network. The NN’s assigned confidence for whether a scene is “clear” or “cloudy” proves to be a skillful way in which quality flags can be attached to predictions. Clouds with higher cloud-top heights are typically more easily detected. Low-altitude clouds over polar surfaces, which are the most difficult for the NN to detect, are still detected over 80% of the time. The FIR portion of the spectrum is found to increase the detection of clear scenes and increase mid- to high-altitude cloud detection. Cloud detection skill improves through the use of the overlapping fields of view produced by the PREFIRE instrument’s sampling strategy. Overlapping fields of view increase accuracy relative to the baseline NN while simultaneously predicting on a sub-FOV scale.
Significance Statement
Clouds play an important role in defining the Arctic and Antarctic climates. The purpose of this study is to explore the potential of never-before systematically measured radiative properties of the atmosphere to aid in the detection of polar clouds, which are traditionally difficult to detect. Satellite measurements of emitted radiation at wavelengths longer than 15 μm, combined with complex machine learning methods, may allow us to better understand the occurrence of various cloud types at both poles. The occurrence of these clouds can determine whether the surface warms or cools, influencing surface temperatures and the rate at which ice melts or refreezes. Understanding the frequencies of these various clouds is increasingly important within the context of our rapidly changing climate.
Abstract
The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) will fill a gap in our understanding of polar processes and the polar climate by offering widespread, spectrally resolved measurements through the far-infrared (FIR) with two identical CubeSat spacecraft. While the polar regions are typically difficult for skillful cloud identification due to cold surface temperatures, the reflection by bright surfaces, and frequent temperature inversions, the inclusion of the FIR may offer increased spectral sensitivity, allowing for the detection of even thin ice clouds. This study assesses the potential skill, as well as limitations, of a neural network (NN)-based cloud mask using simulated spectra mimicking what the PREFIRE mission will capture. Analysis focuses on the polar regions. Clouds are found to be detected approximately 90% of time using the derived neural network. The NN’s assigned confidence for whether a scene is “clear” or “cloudy” proves to be a skillful way in which quality flags can be attached to predictions. Clouds with higher cloud-top heights are typically more easily detected. Low-altitude clouds over polar surfaces, which are the most difficult for the NN to detect, are still detected over 80% of the time. The FIR portion of the spectrum is found to increase the detection of clear scenes and increase mid- to high-altitude cloud detection. Cloud detection skill improves through the use of the overlapping fields of view produced by the PREFIRE instrument’s sampling strategy. Overlapping fields of view increase accuracy relative to the baseline NN while simultaneously predicting on a sub-FOV scale.
Significance Statement
Clouds play an important role in defining the Arctic and Antarctic climates. The purpose of this study is to explore the potential of never-before systematically measured radiative properties of the atmosphere to aid in the detection of polar clouds, which are traditionally difficult to detect. Satellite measurements of emitted radiation at wavelengths longer than 15 μm, combined with complex machine learning methods, may allow us to better understand the occurrence of various cloud types at both poles. The occurrence of these clouds can determine whether the surface warms or cools, influencing surface temperatures and the rate at which ice melts or refreezes. Understanding the frequencies of these various clouds is increasingly important within the context of our rapidly changing climate.
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.
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.
Abstract
The Atmospheric Infrared Sounder (AIRS) level-1b radiances have been shown to be well calibrated (~0.3 K or higher) and have little secular drift (~4 mK yr−1) since operation started in September 2002. This paper investigates the linear trends of 10 years (2003–12) of AIRS global-mean radiances in the CO2 v 2 band that are sensitive to emissions from the stratosphere (stratospheric channels). AIRS lower-stratospheric channels have a cooling trend of no more than 0.23 K decade−1 whereas the midstratospheric channels consistently show a statistically significant cooling trend as large as 0.58 K decade−1. The 95% confidence interval for the trend is ~±0.20 K decade−1. Two sets of synthetic AIRS radiances are computed using the principal component–based radiative transfer model (PCRTM), one based on a free-running GFDL Atmospheric Model, version 3 (AM3), over the same period and one based on ERA-Interim. The GFDL AM3 simulations overestimate the cooling trends in the mid- to upper-stratospheric channels but slightly underestimate them in the lower-stratospheric channels. The synthetic radiances based on ERA-Interim, however, have statistically significant positive trends at virtually all stratospheric channels. This confirms the challenge to the GCM modeling and reanalysis community to create a better simulation or assimilation of the stratospheric climate. It is shown that the linear trends in AIRS radiances can be reproduced to a large extent by the spectral radiative kernel technique and the trends from the AIRS L2 temperature retrievals and from the change of CO2. This suggests a closure between AIRS L1 radiances and L2 retrievals and the potential merit of AIRS data in studies of stratosphere changes.
Abstract
The Atmospheric Infrared Sounder (AIRS) level-1b radiances have been shown to be well calibrated (~0.3 K or higher) and have little secular drift (~4 mK yr−1) since operation started in September 2002. This paper investigates the linear trends of 10 years (2003–12) of AIRS global-mean radiances in the CO2 v 2 band that are sensitive to emissions from the stratosphere (stratospheric channels). AIRS lower-stratospheric channels have a cooling trend of no more than 0.23 K decade−1 whereas the midstratospheric channels consistently show a statistically significant cooling trend as large as 0.58 K decade−1. The 95% confidence interval for the trend is ~±0.20 K decade−1. Two sets of synthetic AIRS radiances are computed using the principal component–based radiative transfer model (PCRTM), one based on a free-running GFDL Atmospheric Model, version 3 (AM3), over the same period and one based on ERA-Interim. The GFDL AM3 simulations overestimate the cooling trends in the mid- to upper-stratospheric channels but slightly underestimate them in the lower-stratospheric channels. The synthetic radiances based on ERA-Interim, however, have statistically significant positive trends at virtually all stratospheric channels. This confirms the challenge to the GCM modeling and reanalysis community to create a better simulation or assimilation of the stratospheric climate. It is shown that the linear trends in AIRS radiances can be reproduced to a large extent by the spectral radiative kernel technique and the trends from the AIRS L2 temperature retrievals and from the change of CO2. This suggests a closure between AIRS L1 radiances and L2 retrievals and the potential merit of AIRS data in studies of stratosphere changes.
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.
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.
Abstract
Analysis of observations from 1979 to 2002 shows that the seasonal transition from winter to spring in East Asia is marked with a distinctive event—the onset of the south China spring rain (SCSR). In late February, the reduced thermal contrast between ocean and land leads to weakening of the Asian winter monsoon as well as the Siberian high and the Aleutian low. Meanwhile, convection over Australia and the western Pacific Maritime Continent is suppressed on the passage of the dry phase of a Madden–Julian oscillation (MJO). In conjunction with the seasonal march of monsoon circulation in the Indonesian–Australian sector, this MJO passage weakens the local thermally direct cell in the East Asia–Australia sector. This development is further accompanied by a series of adjustments in both the tropics and midlatitudes. These changes include attenuation of the planetary stationary wave, considerable weakening of the westerly jet stream over much of the central Pacific adjacent to Japan, and reduction of baroclinicity near the East Asian trough. The influence of concurrent local processes in midlatitudes on the SCSR onset is also important. The weakened jet stream is associated with confinement of frontal activities to the coastal regions of East Asia as well as with rapid expansion of the subtropical Pacific high from the eastern Pacific to the western Pacific. A parallel analysis using output from an experiment with a GFDL-coupled GCM shows that the above sequence of circulation changes is well simulated in that model.
Abstract
Analysis of observations from 1979 to 2002 shows that the seasonal transition from winter to spring in East Asia is marked with a distinctive event—the onset of the south China spring rain (SCSR). In late February, the reduced thermal contrast between ocean and land leads to weakening of the Asian winter monsoon as well as the Siberian high and the Aleutian low. Meanwhile, convection over Australia and the western Pacific Maritime Continent is suppressed on the passage of the dry phase of a Madden–Julian oscillation (MJO). In conjunction with the seasonal march of monsoon circulation in the Indonesian–Australian sector, this MJO passage weakens the local thermally direct cell in the East Asia–Australia sector. This development is further accompanied by a series of adjustments in both the tropics and midlatitudes. These changes include attenuation of the planetary stationary wave, considerable weakening of the westerly jet stream over much of the central Pacific adjacent to Japan, and reduction of baroclinicity near the East Asian trough. The influence of concurrent local processes in midlatitudes on the SCSR onset is also important. The weakened jet stream is associated with confinement of frontal activities to the coastal regions of East Asia as well as with rapid expansion of the subtropical Pacific high from the eastern Pacific to the western Pacific. A parallel analysis using output from an experiment with a GFDL-coupled GCM shows that the above sequence of circulation changes is well simulated in that model.
