Clear-sky Scenes Research Articles

Analysis of actinic flux profiles measured from an ozonesonde balloon

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

Modeling polarized solar radiation for CLARREO inter-calibration applications: Validation with PARASOL data

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a high-priority NASA Decadal Survey mission recommended by the National Research Council in 2007. The CLARREO objectives are to conduct highly accurate decadal climate-change observations and to provide an on-orbit inter-calibration standard for relevant Earth observing sensors. The inter-calibration approach is based on providing highly accurate spectral reflectance measurements from the CLARREO Reflected Solar Spectrometer (RSS) as the reference for existing sensors and to monitor and characterize their response function parameters including gain, offset, non-linearity, optics spectral response, and sensitivity to polarization of light. The inter-calibration of instrument sensitivity to polarization requires on-orbit knowledge of polarization state of light as function of observed scene type and viewing geometry. In this study, we validate polarization parameters calculated with the adding-doubling radiative transfer model (ADRTM) for developing the Polarization Distribution Models (PDMs). These model results are compared with observations from the Polarization and Anisotropy of Reflectances for Atmospheric Science instrument coupled with Observations from a Lidar (PARASOL) data. Good agreement between model results and satellite data is shown for both liquid water clouds and ice clouds. Difference between model results and satellite measurements for clear-sky oceans is explained as due to the presence of undetected clouds, that are super-thin or whose spatial and temporal mean optical depth is small, in the PARASOL clear-sky scenes. These results demonstrate that the ADRTM provides a reliable approach for building spectral PDMs for the inter-calibration applications of the CLARREO mission.

Principal Components of Multifrequency Microwave Land Surface Emissivities. Part II: Effects of Previous-Time Precipitation

Abstract The microwave land surface emissivity (MLSE) over the continental United States was examined during 2011 as a function of prior rainfall conditions using two independent emissivity estimation techniques, one providing instantaneous estimates based on a clear-scene emissivity principal component (PC) analysis and the other based on physical radiative transfer modeling. Results show that over grass, closed shrub, and cropland, prior rainfall can cause the horizontally polarized 10-GHz brightness temperature (TB) to drop by as much as 20 K, with a corresponding emissivity drop of approximately 0.06, whereby prior rain exhibited little influence on the emissivity over forest because of the dense vegetation. The correlation between emissivity and its leading principal components and the prior rainfall over grass, closed shrub, and cropland is −0.6, while it is only −0.1 over forested areas. Forward-simulated TB using the PC-based emissivity derived from instantaneous Tropical Rainfall Measuring Mission (TRMM) satellite overpasses agrees much better with TRMM Microwave Imager (TMI) observations relative to a climatologically based emissivity, especially after a period of heavy rain. Two potential applications of the PC-based emissivity are demonstrated. The first exploits the time history change of the MLSE to estimate the amount of prior rainfall. The second application is a method to estimate the emissivity underneath precipitating radiometric scenes by first adjusting the surface-sensitive principal components that were derived under clear-sky scenes and then by reconstructing the joint emissivity (all channels simultaneously) from the modified PC structure. The results are applicable to future overland passive microwave rainfall retrieval algorithms to simultaneously detect and estimate precipitation amounts under dynamically changing surface conditions.

Tropospheric carbon monoxide variability from AIRS under clear and cloudy conditions

Abstract. We study the carbon monoxide (CO) variability in the last decade measured by NASA's Atmospheric InfraRed Sounder (AIRS) on the Earth Observing System (EOS)/Aqua satellite. The focus of this study is to analyze CO variability and short-term trends separately for background CO and fresh CO emissions based on a new statistical approach. The AIRS Level 2 (L2) retrieval algorithm utilizes cloud clearing to treat cloud contaminations in the signals, and this increases the data coverage significantly to a yield of more than 50% of the total measurements. We first study if the cloud clearing affects CO retrievals and the subsequent trend studies by using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask to identify AIRS clear sky scenes. We then carry out a science analysis using AIRS CO data individually for the clear and cloud-cleared scenes to identify any potential effects due to cloud clearing. We also introduce a new technique to separate background and recently emitted CO observations, which aims to constrain emissions using only satellite CO data. We validate the CO variability of the recent emissions estimated from AIRS against other emission inventory databases (i.e., Global Fire Emissions Database – GFED3 and the MACC/CityZEN UE – MACCity) and calculate that the correlation coefficients between the AIRS CO recently emitted and the emission inventory databases are 0.726 for the Northern Hemisphere (NH) and 0.915 for the Southern Hemisphere (SH). The high degree of agreement between emissions identified using only AIRS CO and independent inventory sources demonstrates the validity of this approach to separate recent emissions from the background CO using one satellite data set.

Intercomparison of retrieval algorithms for the specific surface area of snow from near-infrared satellite data in mountainous terrain, and comparison with the output of a semi-distributed snowpack model

Abstract. This study compares different methods to retrieve the specific surface area (SSA) of snow from satellite radiance measurements in mountainous terrain. It aims at addressing the effect on the retrieval of topographic corrections of reflectance, namely slope and aspect of terrain, multiple reflections on neighbouring slopes and accounting (or not) for the anisotropy of snow reflectance. Using MODerate resolution Imaging Spectrometer (MODIS) data for six different clear sky scenes spanning a wide range of snow conditions during the winter season 2008–2009 over a domain of 46 × 50 km in the French Alps, we compared SSA retrievals with and without topographic correction, with a spherical or non-spherical snow reflectance model and, in spherical case, with or without anisotropy corrections. The retrieved SSA values were compared to field measurements and to the results of the detailed snowpack model Crocus, fed by driving data from the SAFRAN meteorological analysis. It was found that the difference in terms of surface SSA between retrieved values and SAFRAN-Crocus output was minimal when the topographic correction was taken into account, when using a retrieval method assuming disconnected spherical snow grains. In this case, the root mean square deviation was 9.4 m2 kg−1 and the mean difference was 0.1 m2 kg−1, based on 3170 pairs of observation and simulated values. The added-value of the anisotropy correction was not significant in our case, which may be explained by the presence of mixed pixels and surface roughness. MODIS retrieved data show SSA variations with elevation and aspect which are physically consistent and in good agreement with SAFRAN-Crocus outputs. The variability of the MODIS retrieved SSA within the topographic classes of the model was found to be relatively small (3.9 m2 kg−1). This indicates that semi-distributed snowpack simulations in mountainous terrain with a sufficiently large number of classes provides a representation of the snowpack variability consistent with the scale of MODIS 500 m pixels.

Radiative Flux Estimation from a Broadband Radiometer Using Synthetic Angular Models in the EarthCARE Mission Framework. Part II: Evaluation

AbstractThe instantaneous top-of-atmosphere (TOA) radiance-to-flux conversion for the broadband radiometer (BBR) on board the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) was assessed in Part I of this paper, by developing theoretical angular distribution models (ADMs) specifically designed for the instrument viewing configuration. This paper validates the BBR ADMs by comparing derived flux estimates with flux retrievals obtained from the Clouds and the Earth’s Radiant Energy System (CERES) Terra models. A CERES BBR-like database is employed in the assessment, which is an optimum dataset to validate the BBR algorithms and to determine the benefits of the multiangular conversion procedures in the BBR instrument. The validation of theoretical results with empirical data is essential to prepare the conversion algorithms prior to the launch of EarthCARE. This paper demonstrates that the application of a linear combination method is not recommended when outgoing radiances do not follow the response modeled in the radiative transfer calculations. An effective radiance averaged model outperforms all other developed models, in terms of the coefficient of variation of the root-mean-square error, in the validation study of the shortwave (SW) regime (clear sky 1.9%; cloudy 7.1%) while an effective radiance along-track model obtains the best comparisons for the longwave (LW) regime (clear sky 1.4%; cloudy 1.5%). The evaluation of the multiangular models with scenes with high anisotropy shows that multiview flux conversion algorithms can statistically improve CERES ADM results when CERES flux discrepancies of a target are higher than 4 W m−2 in the LW domain and SW clear-sky scenes and higher than 20 W m−2 in scenes with cloudy conditions.

Observations of the Terra Nova Bay (Antarctica) polynya by MODIS ice surface temperature imagery from 2005 to 2010

Ice surface temperature (IST) imagery from the thermal infrared bands of the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to analyze the activity of the Terra Nova Bay polynya from 2005 to 2010. In clear sky conditions, the shape of the open water area of the polynya (i.e. the portion of the ocean free of sea-ice) is revealed by the skin sea-ice temperatures close to the water freezing point provided by the MODIS-derived IST product. The swaths of the MODIS sensors onboard Terra and Aqua satellites over the Terra Nova Bay consist of about 5500 scenes per year, useful to estimate the cloud cover too. The open water area was extracted from clear sky scenes and from scenes affected by fog but providing continuity of the shape of the polynya. Using about 40% of the available swaths, the polynya was detected for more than 80% of the sea-ice period with a revisit time below 24h and for more than 50% with a revisit time below 3h. The open water area was extracted using thresholds of IST based on the IST values detected within the open water area and within the band of sea-ice surrounding the polynya, obtained scene by scene. An ice free area larger than 100km2 was observed near the Nansen Ice Shelf for more than 70% of time (larger than 500km2 for 50% of time). The mean annual open water area, around 900km2, was close to the lower limit of the reported range except during 2006, around 600km2, due to the limited activity in the second half of the cold season. The largest extents, between 6000 and 8500km2, occurred in different periods of the Antarctic winter and exceeded maxima estimated in previous studies by thermal infrared data. Polynya openings developed from a few hours to several days, in the latter case sustained by subsequent katabatic events visible in the IST sequence. Peaks of growing rate above 300km2/h were observed during intense katabatic events with gusts of 50m/s. The fluctuations of the open water area resulted well correlated with wind records available from local Automatic Weather Stations within the main katabatic routes, and followed katabatic events at intervals between 0 and 6h. The analysis of the IST data set derived from the thermal infrared bands of MODIS provides new polynya observations of high horizontal resolution (1km) and frequent revisit time during the winter season, complementing previously available observations with passive microwave imagery.

Long-Term Trends in Downwelling Spectral Infrared Radiance over the U.S. Southern Great Plains

Abstract A trend analysis was applied to a 14-yr time series of downwelling spectral infrared radiance observations from the Atmospheric Emitted Radiance Interferometer (AERI) located at the Atmospheric Radiation Measurement Program (ARM) site in the U.S. Southern Great Plains. The highly accurate calibration of the AERI instrument, performed every 10 min, ensures that any statistically significant trend in the observed data over this time can be attributed to changes in the atmospheric properties and composition, and not to changes in the sensitivity or responsivity of the instrument. The measured infrared spectra, numbering more than 800 000, were classified as clear-sky, thin cloud, and thick cloud scenes using a neural network method. The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. The AERI data also show many statistically significant trends on annual, seasonal, and diurnal time scales, with different trend signatures identified in the separate scene classifications. Given the decadal time span of the dataset, effects from natural variability should be considered in drawing broader conclusions. Nevertheless, this dataset has high value owing to the ability to infer possible mechanisms for any trends from the observations themselves and to test the performance of climate models.

A Global Climatology of Temperature and Water Vapor Variance Scaling from the Atmospheric Infrared Sounder

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.

Using microwave observations to assess large-scale control of free tropospheric water vapor in the mid-latitudes

[1] The hypothesis of large scale control of midlatitude water vapor is evaluated through reconstructions of the water vapor field using a Lagrangian advection-condensation model without microphysics or diffusion. The reconstruction is validated against satellite observations in the 183.31 ± 1 GHz band from the AMSU-B radiometer following a model-to-satellite approach. Because microwave radiation can penetrate clouds, the validation can be performed for cloudy as well as clear sky scenes, with the exception of very cold or precipitating clouds, which are screened out. The results show very good agreement between the simulated top of the atmosphere radiation and the observations, in clear as well as cloudy regions, with a general bias of less than 2K. The results suggest that cloud microphysics and small scale mixing play at most a secondary role in determining midlatitude free tropospheric humidity except perhaps indirectly through their effect on large scale circulation.

Study of the stability of the ScaRaB shortwave channel. Application: Determination of uniform desert zones

The first flight model of ScaRaB (Scanner for Earth Radiation Budget) on board the Russian Meteor-3/07 weather satellite (altitude 1200 km; inclination, 82.56 ) transmitted data over a period of 1 year (24 February 1994-5 March 1995). We use solar channel (shortwave radiation, 0.2 mu m-4.0 mu m) data over desert regions (clear-sky scenes) to study the stability of the radiometer signal. We consider 1.25 1.25 areas in desert regions and we compute bi-directional reflectance for these areas. These values, depending on the three angles defined by the Sun-target-satellite geometry, are grouped by a similar angular configuration for each area. In this way it is possible to compare reflectance, with the same illumination and observation geometry, for different months, for each area. The results show great stability of the reflectance values, demonstrating the stability of the radiometer signal. For computing variability of the reflectance for each area (the relative standard deviation over an area) we study uniform desert zones. The low-variability zones agree very well with uniform zones selected by Cosnefro' for CNES (Centre National d'Etudes Spatiales, France) in the Saharan and Arabian deserts, from Meteosat-4 data. This demonstrates the high quality of the ScaRaB shortwave radiometer which scans with a pixel size 540 times greater than Meteostat-4.

Mesoscale Variations of Water Vapor Inferred from the Millimeter-Wave Imaging Radiometer during TOGA COARE

Abstract Autocorrelation analysis was applied to data acquired by NASA’s Millimeter-wave Imaging Radiometer during the 1992–93 Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment to quantify the spatial variability of tropical mid- and upper-tropospheric water vapor. Scenes including thin cirrus (as confirmed by lidar measurements) are associated with greater spatial variability of relative humidity (RH) than clear-sky scenes. Typical clear-sky RH spatial variabilities range between 2% and 3%, whereas values for some cirrus scenes are well above 5%. For both cirrus and clear-sky scenes, most of the RH spatial variability is on spatial scales of less than 10 km. Both the amplitude and spatial scale of observed brightness temperature variabilities are in fair quantitative agreement with a model based on the effects of adiabatic vertical displacements generated by boundary layer–forced gravity waves.