Information Content and Uncertainties in Thermodynamic Profiles and Liquid Cloud Properties Retrieved from the Ground-Based Atmospheric Emitted Radiance Interferometer (AERI)

2014 ◽  
Vol 53 (3) ◽  
pp. 752-771 ◽  
Author(s):  
D. D. Turner ◽  
U. Löhnert
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Retrieval Algorithm ◽  
Electromagnetic Spectrum ◽  
Slight Reduction ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Mean Square Errors

AbstractThe Atmospheric Emitted Radiance Interferometer (AERI) observes spectrally resolved downwelling radiance emitted by the atmosphere in the infrared portion of the electromagnetic spectrum. Profiles of temperature and water vapor, and cloud liquid water path and effective radius for a single liquid cloud layer, are retrieved using an optimal estimation–based physical retrieval algorithm from AERI-observed radiance data. This algorithm provides a full error covariance matrix for the solution, and both the degrees of freedom for signal and the Shannon information content. The algorithm is evaluated with both synthetic and real AERI observations. The AERI is shown to have approximately 85% and 70% of its information in the lowest 2 km of the atmosphere for temperature and water vapor profiles, respectively. In clear-sky situations, the mean bias errors with respect to the radiosonde profiles are less than 0.2 K and 0.3 g kg−1 for heights below 2 km for temperature and water vapor mixing ratio, respectively; the maximum root-mean-square errors are less than 1 K and 0.8 g kg−1. The errors in the retrieved profiles in cloudy situations are larger, due in part to the scattering contribution to the downwelling radiance that was not accounted for in the forward model. Scattering is largest in one of the spectral regions used in the retrieval, however, and removing this spectral region results in a slight reduction of the information content but a considerable improvement in the accuracy of the retrieved thermodynamic profiles.

scholarly journals Potential of Dual-Frequency Radar and Microwave Radiometer Synergy for Water Vapor Profiling in the Cloudy Trade Wind Environment

2020 ◽  
Vol 37 (11) ◽  
pp. 1973-1986
Author(s):  
Sabrina Schnitt ◽  
Ulrich Löhnert ◽  
René Preusker
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Degrees Of Freedom ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Cloud Layer ◽  
Trade Wind ◽  
Dual Frequency ◽  
Shallow Convection ◽  
Brightness Temperatures

AbstractHigh-resolution boundary layer water vapor profile observations are essential for understanding the interplay between shallow convection, cloudiness, and climate in the trade wind atmosphere. As current observation techniques can be limited by low spatial or temporal resolution, the synergistic benefit of combining ground-based microwave radiometer (MWR) and dual-frequency radar is investigated by analyzing the retrieval information content and uncertainty. Synthetic MWR brightness temperatures, as well as simulated dual-wavelength ratios of two radar frequencies are generated for a combination of Ka and W band (KaW), as well as differential absorption radar (DAR) G-band frequencies (167 and 174.8 GHz, G2). The synergy analysis is based on an optimal estimation scheme by varying the configuration of the observation vector. Combining MWR and KaW only marginally increases the retrieval information content. The synergy of MWR with G2 radar is more beneficial due to increasing degrees of freedom (4.5), decreasing retrieval errors, and a more realistic retrieved profile within the cloud layer. The information and profile below and within the cloud is driven by the radar observations, whereas the synergistic benefit is largest above the cloud layer, where information content is enhanced compared to an MWR-only or DAR-only setup. For full synergistic benefits, however, G-band radar sensitivities need to allow full-cloud profiling; in this case, the results suggest that a combined retrieval of MWR and G-band DAR can help close the observational gap of current techniques.

scholarly journals Ground-based temperature and humidity profiling: combining active and passive remote sensors

2021 ◽  
Vol 14 (4) ◽  
pp. 3033-3048
Author(s):  
David D. Turner ◽  
Ulrich Löhnert
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Great Plains ◽  
Optimal Estimation ◽  
Differential Absorption ◽  
Southern Great Plains ◽  
Atmospheric Research ◽  
Remote Sensors ◽  
Central Portugal ◽  
Atmospheric Radiation Measurement

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.

scholarly journals Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

2010 ◽  
Vol 3 (6) ◽  
pp. 1589-1598 ◽  
Author(s):  
D. Martynenko ◽  
T. Holzer-Popp ◽  
H. Elbern ◽  
M. Schroedter-Homscheidt
Keyword(s):  
Content Analysis ◽  
Information Content ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Degrees Of Freedom ◽  
Surface Albedo ◽  
Water Soluble ◽  
Retrieval Algorithm ◽  
Aerosol Types ◽  
Reflectance Measurements

Abstract. An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo. The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to discern between this aerosol types. The results of the work will be further used for the development of the promising methodology of the construction error covariance matrices in the assimilation system.

scholarly journals A Combined Multisensor Optimal Estimation Retrieval Algorithm for Oceanic Warm Rain Clouds

2009 ◽  
Vol 48 (11) ◽  
pp. 2242-2256 ◽  
Author(s):  
Anita D. Rapp ◽  
G. Elsaesser ◽  
C. Kummerow
Keyword(s):  
Deep Convection ◽  
Optimal Estimation ◽  
Hydrologic Cycle ◽  
Retrieval Algorithm ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Tropical Rainfall ◽  
Cloud Properties ◽  
Warm Rain ◽  
Rain Cloud

Abstract The complicated interactions between cloud processes in the tropical hydrologic cycle and their responses to changes in environmental variables have been the focus of many recent investigations. Most studies that examine the response of the hydrologic cycle to temperature changes focus on deep convection and cirrus production, but recent results suggest that warm rain clouds may be more sensitive to temperature changes. These clouds are prevalent in the tropics and make considerable contributions to the radiation budget and to total tropical rainfall, as well as serving to moisten and precondition the atmosphere for deep convection. A change in the properties of these clouds in climate-change scenarios could have significant implications for the hydrologic cycle. Existing microwave and visible retrievals of warm rain cloud liquid water path (LWP) disagree over the range of sea surface temperatures (SST) observed in the tropical western Pacific Ocean. Although both retrieval methods show similar behavior for nonraining clouds, the two methods show very different warm-rain-cloud LWP responses to SST, both in magnitude and trend. This makes changes to the relationship between precipitation and cloud properties in changing temperature regimes difficult to interpret. A combined optimal estimation retrieval algorithm that takes advantage of the strengths of the different satellite measurements available on the Tropical Rainfall Measuring Mission (TRMM) satellite has been developed. Deconvolved TRMM Microwave Imager brightness temperatures are combined with cloud fraction from the Visible and Infrared Scanner and rainwater estimates from the TRMM precipitation radar to retrieve the cloud LWP in warm rain systems. This algorithm is novel in that it takes into account the water in the rain and estimates the LWP due to only the cloud water in a raining cloud, thus allowing investigation of the effects of precipitation on cloud properties.

scholarly journals Ground-based Temperature and Humidity Profiling: Combining Active and Passive Remote Sensors

2020 ◽  
Author(s):  
David D. Turner ◽  
Ulrich Löhnert
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Great Plains ◽  
Optimal Estimation ◽  
Differential Absorption ◽  
Southern Great Plains ◽  
Atmospheric Research ◽  
Remote Sensors ◽  
Central Portugal ◽  
Atmospheric Radiation Measurement

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations, or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigao field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties), and that the combined IR+MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR+DIAL and MW+DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is slight increase in the information content in the retrieved temperature profile using the IR+DIAL relative to the IR-only; this was not observed in the MW+DIAL retrieval.

scholarly journals An online aerosol retrieval algorithm using OMI near-UV observations based on the optimal estimation method

2015 ◽  
Vol 15 (12) ◽  
pp. 16615-16654 ◽  
Author(s):  
U. Jeong ◽  
J. Kim ◽  
C. Ahn ◽  
O. Torres ◽  
X. Liu ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Degrees Of Freedom ◽  
Northeast Asia ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Single Scattering ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Near Ultraviolet ◽  
Aerosol Retrieval

Abstract. An online version of the OMI (Ozone Monitoring Instrument) near-ultraviolet (UV) aerosol retrieval algorithm was developed to retrieve aerosol optical thickness (AOT) and single scattering albedo (SSA) based on the optimal estimation (OE) method. Instead of using the traditional look-up tables for radiative transfer calculations, it performs online radiative transfer calculations with the Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model to eliminate interpolation errors and improve stability. The OE-based algorithm has the merit of providing useful estimates of uncertainties simultaneously with the inversion products. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in Northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved AOT and SSA. The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The estimated retrieval noise and smoothing error perform well in representing the envelope curve of actual biases of AOT at 388 nm between the retrieved AOT and AERONET measurements. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface albedo at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for future studies.

scholarly journals Improved Retrieval of Cloud Liquid Water from CloudSat and MODIS

2016 ◽  
Vol 55 (8) ◽  
pp. 1831-1844 ◽  
Author(s):  
Jussi Leinonen ◽  
Matthew D. Lebsock ◽  
Graeme L. Stephens ◽  
Kentaroh Suzuki
Keyword(s):  
Liquid Water ◽  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Radar Signal ◽  
Retrieval Algorithm ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Cloud Optical Depth ◽  
Cloud Water Content ◽  
Most Significant Change

AbstractA revised version of the CloudSat–MODIS cloud liquid water retrieval algorithm is presented. The new algorithm, which combines measurements of radar reflectivity and cloud optical depth, addresses issues discovered in the current CloudSat–MODIS cloud water content (CWC) product. This current product is shown to be underconstrained by observations and to be too dependent on prior information incorporated into the Bayesian optimal-estimation algorithm. The most significant change made to the algorithm in this study was decreasing the number of independent variables to allow the observations to constrain the retrieved values better. The retrieval was also reformulated for improved compliance with the mathematical assumptions of the optimal-estimation algorithm. To validate the accuracy of the revised algorithm, the path-integrated attenuation (PIA) of the CloudSat radar signal was computed from the algorithm results. These modeled values were compared with independent measurements of the PIA that were obtained using a surface reference technique. This comparison shows that the cloud liquid water retrieved by the algorithm is close to being unbiased. The revised algorithm was also found to be an improvement over the current CloudSat CWC product and, to a lesser degree, the MODIS-derived cloud liquid water path.

AMSU-B Observations of Mixed-Phase Clouds over Land

2005 ◽  
Vol 44 (1) ◽  
pp. 72-85 ◽  
Author(s):  
M. N. Deeter ◽  
J. Vivekanandan
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Mixed Phase ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effects ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Properties ◽  
Mixed Phase Clouds

Abstract Measurements from passive microwave satellite instruments such as the Advanced Microwave Sounding Unit B (AMSU-B) are sensitive to both liquid and ice cloud particles. Radiative transfer modeling is exploited to simulate the response of the AMSU-B instrument to mixed-phase clouds over land. The plane-parallel radiative transfer model employed for the study accounts for scattering and absorption from cloud ice as well as absorption and emission from trace gases and cloud liquid. The radiative effects of mixed-phase clouds on AMSU-B window channels (i.e., 89 and 150 GHz) and water vapor line channels (i.e., 183 ± 1, 3, and 7 GHz) are studied. Sensitivities to noncloud parameters, including surface temperature, surface emissivity, and atmospheric temperature and water vapor profiles, are also quantified. Modeling results indicate that both cloud phases generally have significant radiative effects and that the 150- and 183 ± 7-GHz channels are typically the most sensitive channels to integrated cloud properties (i.e., liquid water path and ice water path). However, results also indicate that AMSU-B measurements alone are probably insufficient for retrieving all mixed-phase cloud properties of interest. These results are supported by comparisons of AMSU-B observations of a mixed-phase cloud over the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site with corresponding calculated clear-sky values.

scholarly journals Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (3) ◽  
pp. 2121-2135
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. McGarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

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