High-resolution Retrieval Research Articles

Spatiotemporal Dynamics of Suspended Particulate Matter in Water Environments: A Review

Suspended particulate matter (SPM) is an indispensable component of water environments. Its fate and transport involve various physical and biogeochemical cycles. This paper provides a comprehensive review of SPM dynamics by integrating insights from biogeochemical processes, spatiotemporal observation techniques, and numerical modeling approaches. It also explores methods for diagnosing SPM-mediated biogeochemical processes, such as the flocculation kinetics test and organic matter composition analysis. Advances in remote sensing, in situ monitoring, and high-resolution retrieval algorithms are discussed, highlighting their significance in detecting and quantifying SPM concentrations across varying spatial and temporal scales. Furthermore, this review examines integrated models that incorporate population balance equations on the basis of flocculation kinetics into multi-dimensional sediment transport models. The results from this study provide valuable insights into SPM dynamics, ultimately enhancing our knowledge of SPM behavior and transport in water environments. However, uncertainties remain due to limited field data on flocculation kinetics and the need for parameter optimization in numerical models. Addressing these gaps through enhanced fieldwork and model refinement will significantly improve our ability to predict and manage SPM dynamics, which is critical for sustainable aquatic ecosystem management in an era of rapid environmental change.

Estimation of ionospheric Faraday rotation over ocean areas using L-band spaceborne PolSAR data

ABSTRACT L-band spaceborne polarimetric synthetic aperture radar (PolSAR) data has been well used for the high-resolution retrieval of the ionospheric Faraday rotation (FR). A vast majority of these retrievals were, however, conducted on PolSAR data of lands, with only a very few over oceans. For the global imaging of the Earth’s ionosphere, the retrieval of oceanic ionosphere is indispensable. This paper aims to furnish a deep insight into the FR retrieval on oceans using the widely used Bickel-Bates estimator based on the two cross-circular polarizations Z 12 and Z 21 . The FR estimates (FRE) on oceans are evaluated in detail by comparing with those on lands on four ALOS PALSAR datasets. The achieved oceanic FRE are shown to possess comparable or even better quality than those on lands. It occurs in three of the four scenes that the selected ocean sub-area holds a smaller standard deviation (STD) of FRE (less than 0.7000°) than all the selected land sub-areas. Especially, the quality of FRE is shown to be closely linked to the dispersed degree of the magnitude of the conjugate product of Z 12 and Z 21 via the analysis of coefficient of variation (CV), according to which the unusual occurrence of larger magnitude level corresponding to larger STD of FRE can be explained. Nevertheless, compared with CV, the magnitude of the polarimetric coherence between Z 12 and Z 21 (i.e. γ ) is identified as a better index to measure the quality of FRE. A smaller STD of FRE appears along with a larger γ . Three of the four scenes show that the selected ocean sub-area bears a larger mean of γ (greater than 0.9890) in comparison with all the selected land sub-areas. This work can promote the ionospheric research over oceans and to the correction of ionospheric effects in oceanic L-band spaceborne polarimetric radar data as well.

A Subsolar Metallicity on the Ultra-short-period Planet HIP 65Ab

Studying and understanding the physical and chemical processes that govern hot Jupiters gives us insights on the formation of these giant planets. Having a constraint on the molecular composition of their atmosphere can help us pinpoint their evolution timeline. Namely, the metal enrichment and carbon-to-oxygen ratio can give us information about where in the protoplanetary disk a giant planet may have accreted its envelope, and, subsequently, indicate if it went through migration. Here we present the first analysis of the atmosphere of the hot Jupiter HIP 65Ab. Using near-infrared high-resolution observations from the IGRINS spectrograph, we detect H2O and CO absorption in the dayside atmosphere of HIP 65Ab. Using a high-resolution retrieval framework, we find a CO abundance of log(CO) = −3.85−0.36+0.33 , which is slightly underabundant with expectation from solar composition models. We also recover a low-water abundance of log(H2O) = −4.42 ± 0.18, depleted by 1 order of magnitude relative to a solar-like composition. Upper limits on the abundance of all other relevant major carbon- and oxygen-bearing molecules are also obtained. Overall, our results are consistent with a sub-stellar metallicity but slightly elevated C/O. Such a composition may indicate that HIP 65Ab accreted its envelope from beyond the water snowline and underwent a disk-free migration to its current location. Alternatively, some of the oxygen on HIP 65Ab could be condensed out of the atmosphere, in which case the observed gas-phase abundances would not reflect the true bulk envelope composition.

Estimation of high-resolution aerosol optical depth (AOD) from Landsat and Sentinel images using SEMARA model over selected locations in South Asia

The study investigates a high-resolution retrieval of AOD over complex surfaces and various aerosol regimes of South Asian countries such as China, Bangladesh and Nepal from Landsat 7/8/9 and Sentinel 2 images. To estimate AOD from these satellite images, unlike the conventional radiative transfer-based look-up-table (LUT) approach, this study uses SEMARA coupled model which combines a simplified and robust surface reflection estimation (SREM) model and a simplified aerosol retrieval algorithm (SARA). The SEMARA model uses top-of-atmospheric reflectance (TOA) and land surface reflectance (LSR), solar and sensors viewing geometries, including the in-situ AOD data from the Aerosol Robotic Network (AERONET) station to simulate AOD at 30 m and 10 m spatial resolutions. The results are compared with AERONET and MODIS-based AOD for the validation sites in the South Asian countries. A high degree of agreement with AERONET AOD is obtained over Beijing in China (R2 > 0.9) for all sensors, while it varies for the validation AERONET stations over Nepal and Bangladesh (R2 = 0.40–0.86). The accuracy metrices suggest a low uncertainty over China Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) for Beijing: 0.07 and 0.13), while it remains higher for stations over Nepal and Bangladesh (MAE and RMSE: 0.33, and 0.41; 0.15–0.27, respectively). >85% of the modelled observations fall within expected error (EE) for China, while 20–75% of observations fall within EE for Nepal and Bangladesh. We have also obtained a proximity effect for the accuracy of the estimated AOD from the SEMARA model. The findings, in general, suggest that the complexity in surface cover and aerosol type produce a higher offset with respect to AERONET observations over Bangladesh and Nepal, and therefore further validation studies are needed for other parts of the globe to measure the consistency of the model.

High resolution retrieval of leaf chlorophyll content over Himalayan pine forest using Visible/IR sensors mounted on UAV and radiative transfer model

Forests play an essential role towards net primary productivity, biological cycles and provide habitat to flora & fauna. To monitor key physiological activities in forest canopies such as photosynthesis, respiration, transpiration, spatially-explicit and precise information of the biochemical (biological) variables such as Leaf Chlorophyll Content (LCC) is required. While lookup-table (LUT)-based Radiative Transfer Model (RTM) inversion against optical remote sensing imagery is regarded as a physically sound and robust approach for retrieving biochemical and biophysical variables, regularization procedures are required to offset the problem of ill-posedness. To optimize the RTM inversion of LCC over a sub-tropical pine forest plantation, in the Western Himalaya, we investigated the role of: (1) cost functions (CFs), (2) added noise, and (3) multiple finest solutions in LUT inversion. Principal CFs were evaluated belonging to three categories: information measures, M-estimates, and minimal contrast approaches. The inversion approaches were applied to a LUT produced by the coupled leaf-canopy model known as PROSAIL RTM and tested in contrast field spectral data obtained from reflectance data derived from UAV (Unmanned Aerial Vehicle) images taken over the canopies of covered pine forests. The Bhattacharyya divergence, an information measure, outperformed all other CFs in LCC inversion, with R2 of 0.94, RMSE of 6.20 μg/cm2 and NRMSE of 12.27% during the validation. The optimized inversion strategy was subsequently applied to a UAV-acquired multispectral image at an 8.2 cm pixel resolution for detailed landscape forest LCC mapping. The associated residuals as provided by the LUT-based inversion provided insights in the spatial consistency of the LCC map.

Enabling Variable High Spatial Resolution Retrieval From a Long Pulse BOTDA Sensor

Spatial resolution (SR) is one of the most important parameters of Brillouin optical time-domain analysis (BOTDA) sensors, which determines the minimum length that a perturbation event can be distinguished. In the field of Internet of Things (IoT), there is an urgent need for sensors with large-scale high-precision sensing capability for scenarios, such as intelligent monitoring of production lines and urban infrastructure. Conventionally, the SR is normally restricted to be longer than 1 m due to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 10$ </tex-math></inline-formula> -ns acoustic lifetime limitation in silica optical fibers. For long-distance smart monitoring systems, the SR is generally on the order of several meters or even worse. However, it does not meet the needs of many applications. Therefore, there is an urgent need to achieve SR in the submeter magnitude. In this work, for the first time to the best of our knowledge, we propose a convolutional neural network (CNN) to process the data of conventional BOTDA sensors, which achieves unprecedented performance improvement that allows to directly retrieve submeter SR from the sensing system that use long pump pulses. By using the simulated Brillouin gain spectrums (BGSs) as the CNN input and the corresponding high SR Brillouin frequency shift (BFS) as the output target, the trained CNN is able to obtain an SR higher than the theoretical value determined by the pump pulse width. In the experiment, the CNN accurately retrieves 0.5-m hotspots from the measured BGS with pump pulses from 20 to 50 ns, and the acquired BFS is in great agreement with 45/40 ns differential pulse-width pair (DPP) measurement results. Compared with the DPP technique, the proposed CNN demonstrates a twofold improvement in BFS uncertainty with only half the measurement time. In addition, by changing the training data sets, the proposed CNN can obtain tunable high SR retrieval based on conventional BOTDA sensors that use long pulses without any requirement of hardware modifications. It is worth mentioning that the proposed method is also applicable to larger pulse widths to retrieve a submeter SR. The proposed data post-processing approach paves the way to enable novel high SR BOTDA sensors, which brings substantial improvement over the state-of-the-art techniques in terms of system complexity, measurement time, reliability, etc.

High spatial resolution fast Brillouin optical time-domain analysis enabled by frequency-agility digital optical frequency comb.

A significant spatial resolution enhancement scheme for digital optical frequency comb (DOFC)-based fast Brillouin optical time-domain analysis (BOTDA) is proposed and experimentally demonstrated by using frequency-agility probes, without sacrificing the frequency resolution. The proposed system ensures high spatial resolution by using short frame duration, meanwhile enabling high frequency resolution retrieval of the Brillouin gain spectrum using frequency interleaving of multiple frequency-agility DOFC probes. Additionally, quadratic phase coding is introduced to release the influence of the high peak to average power ratio of the probes. Eventually, the proposed BOTDA sensor achieves a record 5-m spatial resolution over 10-km fiber with less than 2-MHz frequency uncertainty, and a 1-GHz dynamic measurement range. For proof of concept, 10-Hz vibration sensing is also successfully demonstrated at a 40-Hz sampling rate, showing great potential for fast measurement. It is worth mentioning that a higher spatial resolution can be achieved by using more frequency-agility DOFC probes, albeit at the expense of increasing the measurement time.

Influence of convection on the upper-tropospheric O&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; and NO&amp;lt;sub&amp;gt;&amp;lt;i&amp;gt;x&amp;lt;/i&amp;gt;&amp;lt;/sub&amp;gt; budget in southeastern China

Abstract. Thunderstorms can significantly influence the air composition via strong updraft and lightning nitrogen oxides (LNOx). In this study, the ozonesondes and TROPOMI (TROPOspheric Monitoring Instrument) nitrogen dioxide (NO2) observations for two cases are combined with a model to investigate the effects of typical strong convection on vertical redistribution of air pollutants in Nanjing, southeastern China. The ozonesonde observations show higher O3 and water vapor mixing ratios in the upper troposphere (UT) after convection, indicating the strong updraft transporting lower-level air masses into the UT and the possible downward O3-rich air near the top of UT over the convective period. During the whole convection life cycle, the UT O3 production is driven by the chemistry (5–10 times the magnitude of dynamic contribution) and reduced by the LNOx (−40 %). Sensitivity tests demonstrate that neglecting LNOx in standard TROPOMI NO2 products causes overestimated air mass factors over fresh lightning regions and the opposite for outflow and aged lightning areas. Therefore, a new high-resolution retrieval algorithm is applied to estimate the LNOx production efficiency. Our work shows the demand for high-resolution modeling and satellite observations on LNOx emissions of both active and dissipated convection, especially small-scale storms.

A Review for Retrieving Wind Fields by Spaceborne Synthetic Aperture Radar

A high-resolution sea surface wind field (SSWF) has high application requirements, such as weather forecast, wind energy evaluation, and oil spill monitoring. The models for retrieving SSWFs based on spaceborne synthetic aperture radar (SAR) are important methods for obtaining high-resolution SSWFs. These models are continuously updated and improved from the prototype to the model to achieve high-resolution and high-precision SSWF retrieval. With the development of SAR technology and the gradual maturation of global ocean observations, SSWF quantitative estimation using SAR has developed from scientific research to operational monitoring. This study summarises the principles and methods of SSWF with multipolarized SAR. Finally, research suggestions and future development directions are put forward.

A New Algorithm for the Retrieval of Sun Induced Chlorophyll Fluorescence of Water Bodies Exploiting the Detailed Spectral Shape of Water-Leaving Radiance

Sun induced chlorophyll fluorescence (SICF) emitted by phytoplankton provides considerable insights into the vital role of the carbon productivity of the earth’s aquatic ecosystems. However, the SICF signal leaving a water body is highly affected by the high spectral variability of its optically active constituents. To disentangle the SICF emission from the water-leaving radiance, a new high spectral resolution retrieval algorithm is presented, which significantly improves the fluorescence line height (FLH) method commonly used so far. The proposed algorithm retrieves the reflectance without SICF contribution by the extrapolation of the reflectance from the adjacent regions. Then, the SICF emission curve is obtained as the difference of the reflectance with SICF, the one actually obtained by any remote sensor (apparent reflectance), and the reflectance without SICF, the one estimated by the algorithm (true reflectance). The algorithm first normalizes the reflectance spectrum at 780 nm, following the similarity index approximation, to minimize the variability due to other optically active constituents different from chlorophyll. Then, the true reflectance is estimated empirically from the normalized reflectance at three wavelengths using a machine learning regression algorithm (MLRA) and a cubic spline fitting adjustment. Two large reflectance databases, representing a wide range of coastal and ocean water components and scattering conditions, were independently simulated with the radiative transfer model HydroLight and used for training and validation of the MLRA fitting strategy. The best results for the high spectral resolution SICF retrieval were obtained using support vector regression, with relative errors lower than 2% for the SICF peak value in 81% of the samples. This represents a significant improvement with respect to the classic FLH algorithm, applied for OLCI bands, for which the relative errors were higher than 40% in 59% of the samples.

High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite

Optical properties of clouds and heavy aerosol retrieved from satellite measurements are the most important elements for calculating surface solar radiation (SSR). The Himawari-8/Advanced Himawari Imager (AHI) satellite measurements receive high spatial, temporal and spectral signals, which provides an opportunity to estimate cloud, aerosol and SSR accurately.In this study, we developed the AHI official cloud property product (version 1.0) for JAXA P-Tree system. A look-up table (LUT) method was used to calculate high-temporal (10 min) and high-spatial (5 km) SSR from AHI cloud properties. First, the LUT of the SSR estimation was optimized through a radiative transfer model to account for solar zenith angle, cloud optical thickness (COT), effective particle radius (CER), aerosol optical thickness and surface albedo. Following this, COT and CER were retrieved from the AHI data, with ice cloud parameters being retrieved from an extended Voronoi ice crystal scattering database and water cloud parameters being retrieved from the Mie–Lorenz scattering model. The retrieved COT and CER for water clouds were compared well with MODIS collection 6 cloud property products, with correlation coefficients of 0.77 and 0.82, respectively. The COT of ice cloud also shows good consistency, with a correlation coefficient of 0.85. Finally, the SSR was calculated based on the SSR LUT and the retrieved cloud optical parameters. The estimated SSR was validated at 122 radiation stations from several observing networks covering the disk region of Himawari-8. The root-mean-square error (RMSE) at CMA (China Meteorological Administration) stations was 101.86 Wm−2 for hourly SSR and 31.42 Wm−2 for daily SSR; RMSE at non-CMA stations was 119.07 Wm−2 for instantaneous SSR, 81.10 Wm−2 for hourly SSR and 26.58 Wm−2 for daily SSR. Compared with the SSR estimated from conventional geostationary satellites, the accuracy of the SSR obtained in this study was significantly improved.

Regional Models for High-Resolution Retrieval of Chlorophyll a and TSM Concentrations in the Gorky Reservoir by Sentinel-2 Imagery

The possibilities of chlorophyll a (Chl a) and total suspended matter (TSM) retrieval using Sentinel-2/MSI imagery and in situ measurements in the Gorky Reservoir are investigated. This water body is an inland freshwater ecosystem within the territory of the Russian Federation. During the algal bloom period, the optical properties of water are extremely heterogeneous and vary on scales of tens of meters. Additionally, they vary in time under the influence of currents and wind forcing. In this case, the usage of the traditional station-based sampling to describe the state of the reservoir may be uninformative and not rational. Therefore, we proposed an original approach based on simultaneous in situ measurements of the remote sensing reflectance by a single radiometer and the concentration of water constituents by an ultraviolet fluorescence LiDAR from a high-speed gliding motorboat. This approach provided fast data collection including 4087 synchronized LiDAR and radiometric measurements with high spatial resolutions of 8 m for two hours. A part of the dataset was coincided with Sentinel-2 overpass and used for the development of regional algorithms for the retrieval of Chl a and TSM concentrations. For inland waters of the Russian Federation, such research was performed for the first time. The proposed algorithms can be used for regular environmental monitoring of the Gorky Reservoir using ship measurements or Sentinel-2 images. Additionally, they can be adapted for neighboring reservoirs, for example, for other seven reservoirs on the Volga River. Moreover, the proposed ship measurement approach can be useful in the practice of limnological monitoring of inland freshwater ecosystems with high spatiotemporal variability of the optical properties.

Reflected ray retrieval from radio occultation data using radio holographic filtering of wave fields in ray space

Abstract. Linear and non-linear representations of wave fields constitute the basis of modern algorithms for analysis of radio occultation (RO) data. Linear representations are implemented by Fourier Integral Operators, which allow for high-resolution retrieval of bending angles. Non-linear representations include Wigner Distribution Function (WDF), which equals the pseudo-density of energy in the ray space. Representations allow for filtering wave fields by suppressing some areas of the ray space and mapping the field back from the transformed space to the initial one. We apply this technique to the retrieval of reflected rays from RO observations. The use of reflected rays may increase the accuracy of the retrieval of the atmospheric refractivity. Reflected rays can be identified by the visual inspection of WDF or spectrogram plots. Numerous examples from COSMIC data indicate that reflections are mostly observed over oceans or snow, in particular over Antarctica. We introduce the reflection index that characterizes the relative intensity of the reflected ray with respect to the direct ray. The index allows for the automatic identification of events with reflections. We use the radio holographic estimate of the errors of the retrieved bending angle profiles of reflected rays. A comparison of indices evaluated for a large base of events including the visual identification of reflections indicated a good agreement with our definition of reflection index.

Intercomparison of AIRS and HIRDLS stratospheric gravity wave observations

Abstract. We investigate stratospheric gravity wave observations by the Atmospheric InfraRed Sounder (AIRS) aboard NASA's Aqua satellite and the High Resolution Dynamics Limb Sounder (HIRDLS) aboard NASA's Aura satellite. AIRS operational temperature retrievals are typically not used for studies of gravity waves, because their vertical and horizontal resolution is rather limited. This study uses data of a high-resolution retrieval which provides stratospheric temperature profiles for each individual satellite footprint. Therefore the horizontal sampling of the high-resolution retrieval is 9 times better than that of the operational retrieval. HIRDLS provides 2-D spectral information of observed gravity waves in terms of along-track and vertical wavelengths. AIRS as a nadir sounder is more sensitive to short-horizontal-wavelength gravity waves, and HIRDLS as a limb sounder is more sensitive to short-vertical-wavelength gravity waves. Therefore HIRDLS is ideally suited to complement AIRS observations. A calculated momentum flux factor indicates that the waves seen by AIRS contribute significantly to momentum flux, even if the AIRS temperature variance may be small compared to HIRDLS. The stratospheric wave structures observed by AIRS and HIRDLS often agree very well. Case studies of a mountain wave event and a non-orographic wave event demonstrate that the observed phase structures of AIRS and HIRDLS are also similar. AIRS has a coarser vertical resolution, which results in an attenuation of the amplitude and coarser vertical wavelengths than for HIRDLS. However, AIRS has a much higher horizontal resolution, and the propagation direction of the waves can be clearly identified in geographical maps. The horizontal orientation of the phase fronts can be deduced from AIRS 3-D temperature fields. This is a restricting factor for gravity wave analyses of limb measurements. Additionally, temperature variances with respect to stratospheric gravity wave activity are compared on a statistical basis. The complete HIRDLS measurement period from January 2005 to March 2008 is covered. The seasonal and latitudinal distributions of gravity wave activity as observed by AIRS and HIRDLS agree well. A strong annual cycle at mid- and high latitudes is found in time series of gravity wave variances at 42 km, which has its maxima during wintertime and its minima during summertime. The variability is largest during austral wintertime at 60∘ S. Variations in the zonal winds at 2.5 hPa are associated with large variability in gravity wave variances. Altogether, gravity wave variances of AIRS and HIRDLS are complementary to each other. Large parts of the gravity wave spectrum are covered by joint observations. This opens up fascinating vistas for future gravity wave research.

Evaluation of a Support Vector Machine–Based Single-Doppler Wind Retrieval Algorithm

AbstractWind retrieval algorithms are required for Doppler weather radars. In this article, a new wind retrieval algorithm of single-Doppler radar with a support vector machine (SVM) is analyzed and compared with the original algorithm with the least squares technique. Through an analysis of coefficient matrices of equations corresponding to the optimization problems for the two algorithms, the new algorithm, which contains a proper penalization parameter, is found to effectively reduce the condition numbers of the matrices and thus has the ability to acquire accurate results, and the smaller the analysis volume is, the smaller the condition number of the matrix. This characteristic makes the new algorithm suitable to retrieve mesoscale and small-scale and high-resolution wind fields. Afterward, the two algorithms are applied to retrieval experiments to implement a comparison and a discussion. The results show that the penalization parameter cannot be too small, otherwise it may cause a large condition number; it cannot be too large either, otherwise it may change the properties of equations, leading to retrieved wind direction along the radial direction. Compared with the original algorithm, the new algorithm has definite superiority with the appropriate penalization parameters for small analysis volumes. When the suggested small analysis volume dimensions and penalization parameter values are adopted, the retrieval accuracy can be improved by 10 times more than the traditional method. As a result, the new algorithm has the capability to analyze the dynamical structures of severe weather, which needs high-resolution retrieval, and the potential for quantitative applications such as the assimilation in numerical models, but the retrieval accuracy needs to be further improved in the future.

A search for TiO in the optical high-resolution transmission spectrum of HD 209458b: Hindrance due to inaccuracies in the line database

The spectral signature of an exoplanet can be separated from the spectrum of its host star using high-resolution spectroscopy. During such observations, the radial component of the planet's orbital velocity changes, resulting in a significant Doppler shift which allows its spectral features to be extracted. Aims: In this work, we aim to detect TiO in the optical transmission spectrum of HD 209458b. Gaseous TiO has been suggested as the cause of the thermal inversion layer invoked to explain the dayside spectrum of this planet. Method: We used archival data from the 8.2m Subaru Telescope taken with the High Dispersion Spectrograph of a transit of HD209458b in 2002. We created model transmission spectra which include absorption by TiO, and cross-correlated them with the residual spectral data after removal of the dominating stellar absorption features. We subsequently co-added the correlation signal in time, taking into account the change in Doppler shift due to the orbit of the planet. Results: We detect no significant cross-correlation signal due to TiO, though artificial injection of our template spectra into the data indicates a sensitivity down to a volume mixing ratio of ~10E-10. However, cross-correlating the template spectra with a HARPS spectrum of Barnard's star yields only a weak wavelength-dependent correlation, even though Barnard's star is an M4V dwarf which exhibits clear TiO absorption. We infer that the TiO line list poorly match the real positions of TiO lines at spectral resolutions of ~100,000. Similar line lists are also used in the PHOENIX and Kurucz stellar atmosphere suites and we show that their synthetic M-dwarf spectra also correlate poorly with the HARPS spectra of Barnard's star and five other M-dwarfs. We conclude that the lack of an accurate TiO line list is currently critically hampering this high-resolution retrieval technique.

Retrieval of a Temporal High-Resolution Leaf Area Index (LAI) by Combining MODIS LAI and ASTER Reflectance Data

This paper aims to retrieve temporal high-resolution LAI derived by fusing MOD15 products (1 km resolution), field-measured LAI and ASTER reflectance (15-m resolution). Though the inversion of a physically based canopy reflectance model using high-resolution satellite data can produce high-resolution LAI products, the obstacle to producing temporal products is obvious due to the low temporal resolution of high resolution satellite data. A feasible method is to combine different source data, taking advantage of the spatial and temporal resolution of different sensors. In this paper, a high-resolution LAI retrieval method was implemented using a dynamic Bayesian network (DBN) inversion framework. MODIS LAI data with higher temporal resolution were used to fit the temporal background information, which is then updated by new, higher resolution data, herein ASTER data. The interactions between the different resolution data were analyzed from a Bayesian perspective. The proposed method was evaluated using a dataset collected in the HiWater (Heihe Watershed Allied Telemetry Experimental Research) experiment. The determination coefficient and RMSE between the estimated and measured LAI are 0.80 and 0.43, respectively. The research results suggest that even though the coarse-resolution background information differs from the high-resolution satellite observations, a satisfactory estimation result for the temporal high-resolution LAI can be produced using the accumulated information from both the new observations and background information.

HTS and HTSn: New shape descriptors based on Hough transform statistics

With the widespread proliferation of computers, many human activities entail the use of automatic image analysis. The basic features used for image analysis include color, texture, and shape. In this paper, we propose a new shape description method, called Hough Transform Statistics (HTS), which uses statistics from the Hough space to characterize the shape of objects or regions in digital images. A modified version of this method, called Hough Transform Statistics neighborhood (HTSn), is also presented. Experiments carried out on three popular public image databases showed that the HTS and HTSn descriptors are robust, since they presented precision-recall results much better than several other well-known shape description methods. When compared to Beam Angle Statistics (BAS) method, a shape description method that inspired their development, both the HTS and the HTSn methods presented inferior results regarding the precision-recall criterion, but superior results in the processing time and multiscale separability criteria. The linear complexity of the HTS and the HTSn algorithms, in contrast to BAS, make them more appropriate for shape analysis in high-resolution image retrieval tasks when very large databases are used, which are very common nowadays.

One-dimensional variational (1D-Var) retrieval of middle to upper tropospheric humidity using AIRS radiance data

A one-dimensional variational analysis (1D-Var retrieval) of tropospheric humidity was conducted using hyper-spectral radiance data from the Atmospheric Infrared Sounder (AIRS). For the vertical range of the atmosphere between 200 and 600 hPa, the same high-resolution retrieval of humidity profiles as for clear-sky conditions was possible over low clouds if the cloud height was lower than 800 hPa. Global analyses from a global data assimilation system were used for initial profiles, and clear conditions over 800 hPa height were determined from AIRS radiance data. Results of analyses for 50 days of global radiosonde matchup data from 21 December 2008 to 8 February 2009 revealed that our 1D-Var calculations derived humidity profiles were closer to the sonde profiles than those of a global analysis at a height over 600 hPa. Furthermore, the results of 1D-Var retrieval often represented high and supersaturated relative humidity around the supposed ice clouds. The altitudes of the high humidity region agreed with the height of ice clouds that had been detected by CloudSat/CALIPSO. As well as possibly improving the humidity profiles in a numerical model by data assimilation, it is expected that these humidity analyses using AIRS radiance data will provide additional information for the study of ice clouds in the middle to upper troposphere.

High-resolution (375 m) cloud microstructure as seen from the NPP/VIIRS satellite imager

Abstract. VIIRS (Visible Infrared Imaging Radiometer Suite), onboard the Suomi NPP (National Polar-orbiting Partnership) satellite, has an improved resolution of 750 m with respect to the 1000 m of the Moderate Resolution Imaging Spectroradiometer for the channels that allow retrieving cloud microphysical parameters such as cloud drop effective radius (re). VIIRS also has an imager with five channels of double resolution of 375 m, which was not designed for retrieving cloud products. A methodology for a high-resolution retrieval of re and microphysical presentation of the cloud field based on the VIIRS imager was developed and evaluated with respect to MODIS in this study. The tripled microphysical resolution with respect to MODIS allows obtaining new insights for cloud–aerosol interactions, especially at the smallest cloud scales, because the VIIRS imager can resolve the small convective elements that are sub-pixel for MODIS cloud products. Examples are given for new insights into ship tracks in marine stratocumulus, pollution tracks from point and diffused sources in stratocumulus and cumulus clouds over land, deep tropical convection in pristine air mass over ocean and land, tropical clouds that develop in smoke from forest fires and in heavy pollution haze over densely populated regions in southeastern Asia, and for pyro-cumulonimbus clouds. It is found that the VIIRS imager provides more robust physical interpretation and refined information for cloud and aerosol microphysics as compared to MODIS, especially in the initial stage of cloud formation. VIIRS is found to identify significantly more fully cloudy pixels when small boundary layer convective elements are present. This, in turn, allows for a better quantification of cloud–aerosol interactions and impacts on precipitation-forming processes.