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Abstract
Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.
Abstract
Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.
Abstract
The existence, scale, and growth rates of subsynoptic-scale warm-core circulations are investigated with a simple parameterization for latent heat release in a nonconvective basic state using a linear two-layer shallow-water model. For a range of baroclinic flows from moderate to high Richardson number, conditionally stable lapse rates approaching saturated adiabats consistently yield the most unstable modes with a warm-core structure and a Rossby number ∼O(1), with higher Rossby numbers stabilized. This compares to the corresponding most unstable modes for the dry cases that have cold-core structures and Rossby numbers ∼O(10−1) or in the quasigeostrophic range. The maximum growth rates of 0.45 of the Coriolis parameter are an order of magnitude greater than those for the corresponding most unstable dry modes. Because the Rossby number of the most unstable mode for nearly saturated conditions is virtually independent of Richardson number, the preferred scale of these warm-core modes varies directly with the mean vertical shear for a given static stability.
This scale relation suggests that the requirement to maintain nearly saturated conditions on horizontal scales sufficient for development can be met more easily on the preferred subsynoptic horizontal scales associated with weak vertical shear. Conversely, the lack of instability for higher Rossby numbers implies that stronger vertical shears stabilize smaller subsynoptic regions that are destabilized for weaker vertical shears. This has implications for the scale and existence of warm-core circulations in the tropics, such as those assumed a priori in wind-induced surface heat exchange (WISHE).
Abstract
The existence, scale, and growth rates of subsynoptic-scale warm-core circulations are investigated with a simple parameterization for latent heat release in a nonconvective basic state using a linear two-layer shallow-water model. For a range of baroclinic flows from moderate to high Richardson number, conditionally stable lapse rates approaching saturated adiabats consistently yield the most unstable modes with a warm-core structure and a Rossby number ∼O(1), with higher Rossby numbers stabilized. This compares to the corresponding most unstable modes for the dry cases that have cold-core structures and Rossby numbers ∼O(10−1) or in the quasigeostrophic range. The maximum growth rates of 0.45 of the Coriolis parameter are an order of magnitude greater than those for the corresponding most unstable dry modes. Because the Rossby number of the most unstable mode for nearly saturated conditions is virtually independent of Richardson number, the preferred scale of these warm-core modes varies directly with the mean vertical shear for a given static stability.
This scale relation suggests that the requirement to maintain nearly saturated conditions on horizontal scales sufficient for development can be met more easily on the preferred subsynoptic horizontal scales associated with weak vertical shear. Conversely, the lack of instability for higher Rossby numbers implies that stronger vertical shears stabilize smaller subsynoptic regions that are destabilized for weaker vertical shears. This has implications for the scale and existence of warm-core circulations in the tropics, such as those assumed a priori in wind-induced surface heat exchange (WISHE).
Abstract
Ice cloud properties in Northern Hemisphere winter extratropical cyclones are examined using the Atmospheric Infrared Sounder (AIRS), version 6, cloud products. The cloud thermodynamic phase product indicates that warm frontal clouds are dominated by ice, liquid-phase clouds occur outside of the warm frontal region, and supercooled or mixed-phase clouds are found in the southwestern quadrant of the cyclones. Stratiform ice clouds populate the warm frontal region and portions of the cold sector while convective ice clouds populate southeastern portions of the warm front and the southeastern quadrant. Total cloud cover is smaller in land cyclones than in ocean cyclones, especially in the southwestern quadrant and the warm frontal region. Ice cloud cover is less over land in the warm frontal region, because land cyclones are generally weaker and drier than ocean cyclones. The impact of cyclone average precipitable water (PW) and the magnitude of 850-hPa vertical ascent ω 850 on the thermodynamic phase, occurrence of stratiform or convective ice cloud, ice particle effective diameter, optical thickness, and cloud-top temperature are discussed. When comparing land and ocean cyclones with similar PW and ω 850, ice cloud coverage is found to be greater over land. Convective ice cloud occurs more often and is deeper over land. Supercooled cloud appears to persist to colder temperatures over ocean than over land, especially in the warm frontal region. These results suggest that, over land, ice cloud formation in warm fronts is possibly more efficient because of a greater aerosol amount from local or regional sources.
Abstract
Ice cloud properties in Northern Hemisphere winter extratropical cyclones are examined using the Atmospheric Infrared Sounder (AIRS), version 6, cloud products. The cloud thermodynamic phase product indicates that warm frontal clouds are dominated by ice, liquid-phase clouds occur outside of the warm frontal region, and supercooled or mixed-phase clouds are found in the southwestern quadrant of the cyclones. Stratiform ice clouds populate the warm frontal region and portions of the cold sector while convective ice clouds populate southeastern portions of the warm front and the southeastern quadrant. Total cloud cover is smaller in land cyclones than in ocean cyclones, especially in the southwestern quadrant and the warm frontal region. Ice cloud cover is less over land in the warm frontal region, because land cyclones are generally weaker and drier than ocean cyclones. The impact of cyclone average precipitable water (PW) and the magnitude of 850-hPa vertical ascent ω 850 on the thermodynamic phase, occurrence of stratiform or convective ice cloud, ice particle effective diameter, optical thickness, and cloud-top temperature are discussed. When comparing land and ocean cyclones with similar PW and ω 850, ice cloud coverage is found to be greater over land. Convective ice cloud occurs more often and is deeper over land. Supercooled cloud appears to persist to colder temperatures over ocean than over land, especially in the warm frontal region. These results suggest that, over land, ice cloud formation in warm fronts is possibly more efficient because of a greater aerosol amount from local or regional sources.
Abstract
A global climatology of height-resolved variance scaling within the troposphere is presented using derived temperature (T) and water vapor (q) profiles from the Atmospheric Infrared Sounder (AIRS). The power-law exponent of T variance scaling approaches 1.0 outside of the tropics at scales >500–800 km, but it is closer to 0.3 at scales <500 km, similar to exponents obtained from aircraft campaigns, numerical modeling, and theoretical studies. The T exponents in the tropics at all scales become less than 0.3, with a similar pattern observed within the boundary layer in some extratropical regions. For q, the variance scaling differs substantially from T with exponents near 0.5–0.6 in parts of the tropics and subtropics with little to no scale break, showing some consistency with a very limited set of aircraft and satellite studies. Scaling differences as a function of land and ocean, altitude, and cloudy- and clear-sky scenes are quantified. Both T and q exponents indicate peak magnitudes in the midtroposphere and reductions are observed near the boundary layer and upper troposphere. Seasonal variations of T and q scaling reveal a stronger seasonal cycle over land than ocean, especially for T at large length scales. While the zonal variations of T and q exponents vary significantly for scales <500 km, the seasonal variations are much smaller in magnitude. The exponents derived from AIRS could eventually be extrapolated to smaller scales in the absence of additional scale breaks <150 km to provide useful information for constraining subgrid-scale cloud parameterizations.
Abstract
A global climatology of height-resolved variance scaling within the troposphere is presented using derived temperature (T) and water vapor (q) profiles from the Atmospheric Infrared Sounder (AIRS). The power-law exponent of T variance scaling approaches 1.0 outside of the tropics at scales >500–800 km, but it is closer to 0.3 at scales <500 km, similar to exponents obtained from aircraft campaigns, numerical modeling, and theoretical studies. The T exponents in the tropics at all scales become less than 0.3, with a similar pattern observed within the boundary layer in some extratropical regions. For q, the variance scaling differs substantially from T with exponents near 0.5–0.6 in parts of the tropics and subtropics with little to no scale break, showing some consistency with a very limited set of aircraft and satellite studies. Scaling differences as a function of land and ocean, altitude, and cloudy- and clear-sky scenes are quantified. Both T and q exponents indicate peak magnitudes in the midtroposphere and reductions are observed near the boundary layer and upper troposphere. Seasonal variations of T and q scaling reveal a stronger seasonal cycle over land than ocean, especially for T at large length scales. While the zonal variations of T and q exponents vary significantly for scales <500 km, the seasonal variations are much smaller in magnitude. The exponents derived from AIRS could eventually be extrapolated to smaller scales in the absence of additional scale breaks <150 km to provide useful information for constraining subgrid-scale cloud parameterizations.
Abstract
The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will, for the first time, systematically document the far-infrared (15–54 µm) spectral region from space. The environmental sampling characteristics of the PREFIRE CubeSats, defined in terms of surface temperature (T sfc) and column water vapor (CWV) are evaluated for a range of possible orbit scenarios for both clear-sky and all-sky conditions over a variety of surface types (land, ocean, sea ice, snow, glacier ice) at both poles. Using NASA Aqua’s Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) retrievals to define the climatological ranges of T sfc and CWV, the fraction of environmental regimes observed by distinct PREFIRE configurations are evaluated. The sampling rates within any single year for two-orbit CubeSat launches spanning both polar regions are ~75% for clear-sky and ~85% for all-sky compared to the AIRS/AMSU climatology. Decreasing mission duration from 12 to 3 months decreases sampling much more (10%–20%) than decreasing the swath width from 15 to 8 footprints (6%–9%). For a single CubeSat launch, a 98° orbital inclination provides slightly better sampling than either 93° or 103°. For a two-orbit CubeSat launch, a combination of 93° + 98° is somewhat preferable to 103° + 98°. Finally, a 50% data loss rate simulated by dropping out every other orbit leads to only a modest 7%–8% reduction in sampling from full data coverage. This statistical analysis demonstrates that low-cost platforms could offer similar coverage as present-day flagship missions for sampling wide-ranging T sfc and CWV states over polar regions.
Abstract
The Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will, for the first time, systematically document the far-infrared (15–54 µm) spectral region from space. The environmental sampling characteristics of the PREFIRE CubeSats, defined in terms of surface temperature (T sfc) and column water vapor (CWV) are evaluated for a range of possible orbit scenarios for both clear-sky and all-sky conditions over a variety of surface types (land, ocean, sea ice, snow, glacier ice) at both poles. Using NASA Aqua’s Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) retrievals to define the climatological ranges of T sfc and CWV, the fraction of environmental regimes observed by distinct PREFIRE configurations are evaluated. The sampling rates within any single year for two-orbit CubeSat launches spanning both polar regions are ~75% for clear-sky and ~85% for all-sky compared to the AIRS/AMSU climatology. Decreasing mission duration from 12 to 3 months decreases sampling much more (10%–20%) than decreasing the swath width from 15 to 8 footprints (6%–9%). For a single CubeSat launch, a 98° orbital inclination provides slightly better sampling than either 93° or 103°. For a two-orbit CubeSat launch, a combination of 93° + 98° is somewhat preferable to 103° + 98°. Finally, a 50% data loss rate simulated by dropping out every other orbit leads to only a modest 7%–8% reduction in sampling from full data coverage. This statistical analysis demonstrates that low-cost platforms could offer similar coverage as present-day flagship missions for sampling wide-ranging T sfc and CWV states over polar regions.
Abstract
In all outputs of the 1% yr−1 increase in CO2 climate model experiments archived under the World Climate Research Programme’s (WCRP) phase 5 of the Coupled Model Intercomparison Project (CMIP5), regions exist in the low latitudes where both the clear-sky and all-sky OLR decrease with surface warming. These are identified as regions of positive longwave feedback and are regions of a super greenhouse effect (SGE). These SGE regions are identified from feedback analysis of the 4 × CO2 abrupt experiments of CMIP5, and despite their existence, there is little agreement across models as to the magnitude of the effect. The general effects of clouds on the SGE are to amplify the clear-sky SGE, but there is also poor agreement on the magnitude of the amplification that varies by an order of magnitude across models. Sensitivity analyses indicate that localized SGE regions are spatially aligned with a large moistening of the upper troposphere. The reduction in clear-sky OLR arises from a reduction in emission in the far IR with nonnegligible contributions from mid-IR emission from the midtroposphere. When viewed in the broader context of meridional heat transport, it is found that of the 1.03-PW rate of heat gained globally, 0.8 PW is absorbed in the tropics and is contributed almost equally by reductions in clear-sky longwave emission (i.e., the clear-sky SGE) and increased absorbed clear-sky solar radiation associated with increased water vapor. The processes that define the clear-sky SGE are shown to be fundamental to the way models accumulate heat and then transport it poleward.
Abstract
In all outputs of the 1% yr−1 increase in CO2 climate model experiments archived under the World Climate Research Programme’s (WCRP) phase 5 of the Coupled Model Intercomparison Project (CMIP5), regions exist in the low latitudes where both the clear-sky and all-sky OLR decrease with surface warming. These are identified as regions of positive longwave feedback and are regions of a super greenhouse effect (SGE). These SGE regions are identified from feedback analysis of the 4 × CO2 abrupt experiments of CMIP5, and despite their existence, there is little agreement across models as to the magnitude of the effect. The general effects of clouds on the SGE are to amplify the clear-sky SGE, but there is also poor agreement on the magnitude of the amplification that varies by an order of magnitude across models. Sensitivity analyses indicate that localized SGE regions are spatially aligned with a large moistening of the upper troposphere. The reduction in clear-sky OLR arises from a reduction in emission in the far IR with nonnegligible contributions from mid-IR emission from the midtroposphere. When viewed in the broader context of meridional heat transport, it is found that of the 1.03-PW rate of heat gained globally, 0.8 PW is absorbed in the tropics and is contributed almost equally by reductions in clear-sky longwave emission (i.e., the clear-sky SGE) and increased absorbed clear-sky solar radiation associated with increased water vapor. The processes that define the clear-sky SGE are shown to be fundamental to the way models accumulate heat and then transport it poleward.
Abstract
The authors investigate if atmospheric water vapor from remote sensing retrievals obtained from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS) and the water vapor budget from the NASA Goddard Space Flight Center (GSFC) Modern Era Retrospective-analysis for Research and Applications (MERRA) are physically consistent with independently synthesized precipitation data from the Tropical Rainfall Measuring Mission (TRMM) or the Global Precipitation Climatology Project (GPCP) and evaporation data from the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF). The atmospheric total water vapor sink (Σ) is estimated from AIRS water vapor retrievals with MERRA winds (AIRS–MERRA Σ) as well as directly from the MERRA water vapor budget (MERRA–MERRA Σ). The global geographical distributions as well as the regional wavelet amplitude spectra of Σ are then compared with those of TRMM or GPCP precipitation minus GSSTF surface evaporation (TRMM–GSSTF and GPCP–GSSTF P − E, respectively). The AIRS–MERRA and MERRA–MERRA Σs reproduce the main large-scale patterns of global P − E, including the locations and variations of the ITCZ, summertime monsoons, and midlatitude storm tracks in both hemispheres. The spectra of regional temporal variations in Σ are generally consistent with those of observed P − E, including the annual and semiannual cycles, and intraseasonal variations. Both AIRS–MERRA and MERRA–MERRA Σs have smaller amplitudes for the intraseasonal variations over the tropical oceans. The MERRA P − E has spectra similar to that of MERRA–MERRA Σ in most of the regions except in tropical Africa. The averaged TRMM–GSSTF and GPCP–GSSTF P − E over the ocean are more negative compared to the AIRS–MERRA, MERRA–MERRA Σs, and MERRA P − E.
Abstract
The authors investigate if atmospheric water vapor from remote sensing retrievals obtained from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS) and the water vapor budget from the NASA Goddard Space Flight Center (GSFC) Modern Era Retrospective-analysis for Research and Applications (MERRA) are physically consistent with independently synthesized precipitation data from the Tropical Rainfall Measuring Mission (TRMM) or the Global Precipitation Climatology Project (GPCP) and evaporation data from the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF). The atmospheric total water vapor sink (Σ) is estimated from AIRS water vapor retrievals with MERRA winds (AIRS–MERRA Σ) as well as directly from the MERRA water vapor budget (MERRA–MERRA Σ). The global geographical distributions as well as the regional wavelet amplitude spectra of Σ are then compared with those of TRMM or GPCP precipitation minus GSSTF surface evaporation (TRMM–GSSTF and GPCP–GSSTF P − E, respectively). The AIRS–MERRA and MERRA–MERRA Σs reproduce the main large-scale patterns of global P − E, including the locations and variations of the ITCZ, summertime monsoons, and midlatitude storm tracks in both hemispheres. The spectra of regional temporal variations in Σ are generally consistent with those of observed P − E, including the annual and semiannual cycles, and intraseasonal variations. Both AIRS–MERRA and MERRA–MERRA Σs have smaller amplitudes for the intraseasonal variations over the tropical oceans. The MERRA P − E has spectra similar to that of MERRA–MERRA Σ in most of the regions except in tropical Africa. The averaged TRMM–GSSTF and GPCP–GSSTF P − E over the ocean are more negative compared to the AIRS–MERRA, MERRA–MERRA Σs, and MERRA P − E.
Abstract
Precipitation (from TMPA) and cloud structures (from MODIS) in extratropical cyclones (ETCs) are modulated by phases of large-scale moisture flux convergence (from MERRA-2) in the sectors of ETCs, which are studied in a new coordinate system with directions of both surface warm fronts (WFs) and surface cold fronts (CFs) fixed. The phase of moisture flux convergence is described by moisture dynamical convergence Q cnvg and moisture advection Q advt. Precipitation and occurrence frequencies of deep convective clouds are sensitive to changes in Q cnvg, while moisture tendency is sensitive to changes in Q advt. Increasing Q cnvg and Q advt during the advance of the WF is associated with increasing occurrences of both deep convective and high-level stratiform clouds. A rapid decrease in Q advt with a relatively steady Q cnvg during the advance of the CF is associated with high-level cloud distribution weighting toward deep convective clouds. Behind the CF (cold sector or area with polar air intrusion), the moisture flux is divergent with abundant low- and midlevel clouds. From deepening to decaying stages, the pre-WF and WF sectors experience high-level clouds shifting to more convective and less stratiform because of decreasing Q advt with relatively steady Q cnvg, and the CF experiences shifting from high-level to midlevel clouds. Sectors of moisture flux divergence are less influenced by cyclone evolution. Surface evaporation is the largest in the cold sector and the CF during the deepening stage. Deepening cyclones are more efficient in poleward transport of water vapor.
Abstract
Precipitation (from TMPA) and cloud structures (from MODIS) in extratropical cyclones (ETCs) are modulated by phases of large-scale moisture flux convergence (from MERRA-2) in the sectors of ETCs, which are studied in a new coordinate system with directions of both surface warm fronts (WFs) and surface cold fronts (CFs) fixed. The phase of moisture flux convergence is described by moisture dynamical convergence Q cnvg and moisture advection Q advt. Precipitation and occurrence frequencies of deep convective clouds are sensitive to changes in Q cnvg, while moisture tendency is sensitive to changes in Q advt. Increasing Q cnvg and Q advt during the advance of the WF is associated with increasing occurrences of both deep convective and high-level stratiform clouds. A rapid decrease in Q advt with a relatively steady Q cnvg during the advance of the CF is associated with high-level cloud distribution weighting toward deep convective clouds. Behind the CF (cold sector or area with polar air intrusion), the moisture flux is divergent with abundant low- and midlevel clouds. From deepening to decaying stages, the pre-WF and WF sectors experience high-level clouds shifting to more convective and less stratiform because of decreasing Q advt with relatively steady Q cnvg, and the CF experiences shifting from high-level to midlevel clouds. Sectors of moisture flux divergence are less influenced by cyclone evolution. Surface evaporation is the largest in the cold sector and the CF during the deepening stage. Deepening cyclones are more efficient in poleward transport of water vapor.
Abstract
This paper describes a cloud type radiance record derived from NOAA polar-orbiting weather satellites using cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR) and spectral brightness temperatures (T b ) observed by the High Resolution Infrared Radiation Sounder (HIRS). The authors seek to produce a seamless, global-scale, long-term record of cloud type and T b statistics intended to better characterize clouds from seasonal to decadal time scales. Herein, the methodology is described in which the cloud type statistics retrieved from AVHRR are interpolated onto each HIRS footprint using two cloud classification methods. This approach is tested over the northeast tropical and subtropical Pacific Ocean region, which contains a wide variety of cloud types during a significant ENSO variation from 2008 to 2009. It is shown that the T b histograms sorted by cloud type are realistic for all HIRS channels. The magnitude of T b biases among spatially coincident satellite intersections over the northeast Pacific is a function of cloud type and wavelength. While the sign of the bias can change, the magnitudes are generally small for NOAA-18 and NOAA-19, and NOAA-19 and MetOp-A intersections. The authors further show that the differences between calculated standard deviations of cloud-typed T b well exceed intersatellite calibration uncertainties. The authors argue that consideration of higher-order statistical moments determined from spectral infrared observations may serve as a useful long-term measure of small-scale spatial changes, in particular cloud types over the HIRS–AVHRR observing record.
Abstract
This paper describes a cloud type radiance record derived from NOAA polar-orbiting weather satellites using cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR) and spectral brightness temperatures (T b ) observed by the High Resolution Infrared Radiation Sounder (HIRS). The authors seek to produce a seamless, global-scale, long-term record of cloud type and T b statistics intended to better characterize clouds from seasonal to decadal time scales. Herein, the methodology is described in which the cloud type statistics retrieved from AVHRR are interpolated onto each HIRS footprint using two cloud classification methods. This approach is tested over the northeast tropical and subtropical Pacific Ocean region, which contains a wide variety of cloud types during a significant ENSO variation from 2008 to 2009. It is shown that the T b histograms sorted by cloud type are realistic for all HIRS channels. The magnitude of T b biases among spatially coincident satellite intersections over the northeast Pacific is a function of cloud type and wavelength. While the sign of the bias can change, the magnitudes are generally small for NOAA-18 and NOAA-19, and NOAA-19 and MetOp-A intersections. The authors further show that the differences between calculated standard deviations of cloud-typed T b well exceed intersatellite calibration uncertainties. The authors argue that consideration of higher-order statistical moments determined from spectral infrared observations may serve as a useful long-term measure of small-scale spatial changes, in particular cloud types over the HIRS–AVHRR observing record.
Abstract
Observations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability within the A-Train era (July 2002–June 2017). Short-term cloud feedbacks by cloud type are investigated both globally and locally by three different definitions in the literature: 1) the global-mean cloud feedback parameter λ GG from regressing the global-mean cloud-induced TOA radiation anomaly ΔR G with the global-mean surface temperature change ΔT GS; 2) the local feedback parameter λ LL from regressing the local ΔR with the local surface temperature change ΔT S ; and 3) the local feedback parameter λ GL from regressing global ΔR G with local ΔT S . Observations show significant temporal variability in the magnitudes and spatial patterns in λ GG and λ GL, whereas λ LL remains essentially time invariant for different cloud types. The global-mean net λ GG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative λ GG from low clouds and an increased positive λ GG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in λ GL is intrinsically linked to its dependence on global ΔR G , and the scaling of λ GL with surface temperature change patterns to obtain global feedback λ GG does not hold. Despite the shortness of the A-Train record, statistically robust signals can be obtained for different cloud types and regions of interest.
Abstract
Observations from multiple sensors on the NASA Aqua satellite are used to estimate the temporal and spatial variability of short-term cloud responses (CR) and cloud feedbacks λ for different cloud types, with respect to the interannual variability within the A-Train era (July 2002–June 2017). Short-term cloud feedbacks by cloud type are investigated both globally and locally by three different definitions in the literature: 1) the global-mean cloud feedback parameter λ GG from regressing the global-mean cloud-induced TOA radiation anomaly ΔR G with the global-mean surface temperature change ΔT GS; 2) the local feedback parameter λ LL from regressing the local ΔR with the local surface temperature change ΔT S ; and 3) the local feedback parameter λ GL from regressing global ΔR G with local ΔT S . Observations show significant temporal variability in the magnitudes and spatial patterns in λ GG and λ GL, whereas λ LL remains essentially time invariant for different cloud types. The global-mean net λ GG exhibits a gradual transition from negative to positive in the A-Train era due to a less negative λ GG from low clouds and an increased positive λ GG from high clouds over the warm pool region associated with the 2015/16 strong El Niño event. Strong temporal variability in λ GL is intrinsically linked to its dependence on global ΔR G , and the scaling of λ GL with surface temperature change patterns to obtain global feedback λ GG does not hold. Despite the shortness of the A-Train record, statistically robust signals can be obtained for different cloud types and regions of interest.