Satellite-based Retrievals Research Articles

Real-time mesoscale forecast support during the CLAMS field campaign

This paper reports the use of a specialized, mesoscale, numerical weather prediction (NWP) system and a satellite imaging and prediction system that were set up to support the CLAMS (Chesapeake Lighthouse and Aircraft Measurements for Satellites) field campaign during the summer of 2001. The primary objective of CLAMS was to validate satellite-based retrievals of aerosol properties and vertical profiles of the radiative flux, temperature and water vapor. Six research aircraft were deployed to make detailed coincident measurements of the atmosphere and ocean surface with the research satellites that orbited overhead. The mesoscale weather modeling system runs in real-time to provide high spatial and temporal resolution for forecasts that are delivered via the World Wide Web along with a variety of satellite imagery and satellite location predictions. This system is a multi-purpose modeling system capable of both data analysis/assimilation and multi-scale NWP ranging from cloud-scale to larger than regional scale. This is a three-dimensional, nonhydrostatic compressible model in a terrain-following coordinate. The model employs advanced numerical techniques and contains detailed interactive physical processes. The utility of the forecasting system is illustrated throughout the discussion on the impact of the surface-wind forecast on BRDF (Bidirectional Reflectance Distribution Function) and the description of the cloud/moisture forecast versus the aircraft measurement.

Airborne Retrievals of Snow Microwave Emissivity at AMSU Frequencies Using ARTS/SCEM-UA

Abstract The remote sounding, by satellite, of atmospheric temperature and humidity is an important source of data for assimilation into operational weather forecasting routines. For retrievals of these variables near the surface, wavebands with low optical depths are monitored to allow penetration through the overlying atmosphere. Brightness temperatures in these relatively transparent bands are also sensitive to the land surface emissivity and effective temperature. Inadequate understanding of these land surface emissivities is a major issue when assimilating Advanced Microwave Sounding Unit data for the land-covered portion of the globe. One approach for estimating the emissivity of snow-covered surfaces is an empirical model derived from satellite-based and land-based retrievals of emissivity for a variety of snow types. The Met Office’s Hercules C-130 aircraft flew over snow-covered Arctic terrain of northern Finland during the Polar Experiment (POLEX) of March 2001. On these flights, microwave radiometers provided microwave brightness temperatures at 23.8, 50.3, 89.0, 157, and 183 GHz. The work presented here uses these data along with a robust multiparameter optimization routine [Shuffled Complex Evolution Metropolis (SCEM-UA)] coupled to the Atmospheric Radiative Transfer Simulator (ARTS) to retrieve emissivities at the measured frequencies. These results are then used to validate an empirical model. This latter model predicts 23.8–157-GHz emissivities with an RMSE of less than 0.02 and bias of less than 0.01 when compared with data at an incidence angle of 40°. Nonmonotonic behavior in the emissivity spectrum for this campaign, reported in earlier work, is confirmed by the retrievals presented here.

Measurements of the foreign-broadened continuum of water vapor in the 63 μm band at −30 °C

The foreign-broadened continuum of water vapor in the nu2 band (5-7.7 microm, 1300-2000 cm(-1)) is important for satellite-based retrievals of water vapor in the upper troposphere, where temperatures are below -25 degrees C. Continuum coefficients have previously been measured mostly at or above +23 degrees C. We present continuum coefficients in the nu(2) band retrieved from measurements made in Antarctica at temperatures near -30 degrees C: atmospheric transmission at South Pole Station and atmospheric emission at Dome C. The continuum coefficients derived from these measurements are generally in agreement with the widely used Mlawer, Tobin-Clough, Kneizys, Davies continuum. Differences are at most 30%, corresponding to a 6% relative error in retrieved upper-tropospheric humidity.

Large scale measurements of soil moisture for validation of remotely sensed data: Georgia soil moisture experiment of 2003

A series of soil moisture experiments were conducted in 2003 (SMEX03) to develop enhanced datasets necessary to improve spatiotemporal characterization of soil moisture and to enhance satellite-based retrievals. One component of this research was conducted in South Central Georgia of the US, from June 17th to July 21st (SMEX03 GA). This study analyzes measurements of soil moisture and temperature collected during SMEX03 GA. A network of in situ soil moisture measurement devices, established to provide validation data for the satellite collections and for long-term estimation of soil moisture conditions throughout the region, provided continuous measurements at 19 sites. Additional soil moisture and temperature validation data were collected daily from 49 field sites. These sites represented a diversity of land covers including forest, cotton, peanut, and pasture. Precipitation that occurred prior to June 22nd and from June 29th through July 2nd produced drying conditions from June 23rd to June 28th and gradual wetting from June 29th through July 2nd. Soil moisture in the top 0–1 cm of the soil was found to be more responsive to precipitation and to have greater variability than soil moisture at the 0–3 or 3–6 cm layers. Within different land covers, soil moisture followed the same trends, but varied with land use. Pasture sites were consistently the wettest while row-crop sites were normally the driest. Good agreement was observed between soil moisture measurements collected with the in situ network and the 49 SMEX sites. For the study period, soil moisture across the entire 50 km by 75 km region and five of the six 25 km by 25 km EASE-Grids demonstrated time stable characteristics. Time stability analysis and statistical tests demonstrated the in situ stations had a small dry bias as compared to the SMEX03 GA measurements. These results indicate that the in situ network will be a good resource for long-term calibration of remotely sensed soil moisture and provide a new and unique source for future satellite product validation.

Suborbital Measurements of Spectral Aerosol Optical Depth and Its Variability at Subsatellite Grid Scales in Support of CLAMS 2001

Abstract As part of the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) experiment, 10 July–2 August 2001, off the central East Coast of the United States, the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the University of Washington’s Convair 580 (CV-580) research aircraft during 10 flights (∼45 flight hours). One of the main research goals in CLAMS was the validation of satellite-based retrievals of aerosol properties. The goal of this study in particular was to perform true over-ocean validations (rather than over-ocean validation with ground-based, coastal sites) at finer spatial scales and extending to longer wavelengths than those considered in previous studies. Comparisons of aerosol optical depth (AOD) between the Aerosol Robotic Network (AERONET) Cimel instrument at the Chesapeake Lighthouse and airborne measurements by AATS-14 in its vicinity showed good agreement with the largest r-square correlation coefficients at wavelengths of 0.38 and 0.5 μm (>0.99). Coordinated low-level flight tracks of the CV-580 during Terra overpass times permitted validation of over-ocean Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (MOD04_L2) multiwavelength AOD data (10 km × 10 km, nadir) in 16 cases on three separate days. While the correlation between AATS-14- and MODIS-derived AOD was weak with an r square of 0.55, almost 75% of all MODIS AOD measurements fell within the prelaunch estimated uncertainty range Δτ = ±0.03 ± 0.05τ. This weak correlation may be due to the small AODs (generally less than 0.1 at 0.5 μm) encountered in these comparison cases. An analogous coordination exercise resulted in seven coincident over-ocean matchups between AATS-14 and Multiangle Imaging Spectroradiometer (MISR) measurements. The comparison between AATS-14 and the MISR standard algorithm regional mean AODs showed a stronger correlation with an r square of 0.94. However, MISR AODs were systematically larger than the corresponding AATS values, with an rms difference of ∼0.06. AATS data collected during nine extended low-level CV-580 flight tracks were used to assess the spatial variability in AOD at horizontal scales up to 100 km. At UV and midvisible wavelengths, the largest absolute gradients in AOD were 0.1–0.2 per 50-km horizontal distance. In the near-IR, analogous gradients rarely reached 0.05. On any given day, the relative gradients in AOD were remarkably similar for all wavelengths, with maximum values of 70% (50 km)−1 and more typical values of 25% (50 km)−1. The implications of these unique measurements of AOD spatial variability for common validation practices of satellite data products and for comparisons to large-scale aerosol models are discussed.

Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets

Abstract Understanding the impact of aerosols on the earth’s radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth’s Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product. This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

Effect of Broken Clouds on Satellite-Based Columnar Water Vapor Retrieval

We investigate the effect of broken clouds on the satellite-based retrieval of columnar water vapor using a near-infrared radiance ratio technique. A typical difference between the retrieval using only pixels directly illuminated by the Sun and pixels with mixed illumination containing direct sunlight as well as cloud shadows is found to be within 3%.

Hydrologic Scales, Cloud Variability, Remote Sensing, and Models: Implications for Forecasting Snowmelt and Streamflow

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures.

A Stratified Diagnosis of the Indian Monsoon—Eurasian Snow Cover Relationship

Abstract This study is aimed at reconciling inconsistencies between modeling studies of the Indian monsoon–Eurasian snow cover relationship, which support the Blanford hypothesis, and recent diagnostic studies, which have largely failed to show its existence. Recently released version 2 NOAA/NESDIS satellite-based retrievals of snow cover are used. A focus is given to diagnosing (a) spatial and temporal complexity in the Eurasian snow cover distribution, (b) the role of ENSO in modulating the snow cover–all-India rainfall (AIR) relationship, and (c) the spatial distribution of the rainfall association within India. With these goals in mind, the climatological distribution of snow cover and its interannual variability are first assessed. While snow cover is largest in northern Eurasia, its variability is most pronounced in southwestern (SW) Asia between the Black and Caspian Seas, and across the northern Indian, Himalayan, and Tibetan Plateau (NIHT) regions. In regions of large variability, and for Eurasia...

Satellite- and ground-based observations of atmospheric water vapor absorption in the [formula omitted] region

Ground-based measurements of direct absorption of solar radiation between 9000 and 13,000 cm −1 (770– 1100 nm ) with a spectral resolution of 0.05 cm −1 are compared with line-by-line simulations of atmospheric absorption based on different molecular databases (HITRAN 2000, HITRAN 99, HITRAN 96 and ESA-WVR). Differences between measurements and simulations can be reduced to a great amount by scaling the individual line intensities with spectral and database dependent scaling factors. Scaling factors are calculated for the selected databases using a Marquardt non-linear least-squares fit together with a forward model for 100 cm −1 wide intervals between 10,150 and 11,250 cm −1 as well as for the water vapor absorption channels of the Medium Resolution Imaging Spectrometer (MERIS) onboard the European Space Agency's (ESA) ENVISAT platform and the Modular Optoelectronic Scanner (MOS) on the Indian IRSP-3 platform, developed by the German Aerospace Centre (DLR). For the latter, the scaling coefficients are converted into correction factors for retrieved total columnar water vapor content and used for a comparison of MOS-based retrievals of total columnar atmospheric water vapor above cloud-free land surfaces with radio soundings. The scaling factors determined for 100 cm −1 wide intervals range from 0.85 for the ESA-WVR molecular database to 1.15 for HITRAN 96. The best agreement between measurements and simulations is achieved with HITRAN 99 and HITRAN 2000, respectively, using scaling factors between 0.9 and 1. The effects on the satellite-based retrievals of columnar atmospheric water vapor range from 2% (HITRAN 2000) to 12% (ESA-WVR).

SURFRAD—A National Surface Radiation Budget Network for Atmospheric Research

A surface radiation budget observing network (SURFRAD) has been established for the United States to support satellite retrieval validation, modeling, and climate, hydrology, and weather research. The primary measurements are the downwelling and upwelling components of broadband solar and thermal infrared irradiance. A hallmark of the network is the measurement and computation of ancillary parameters important to the transmission of radiation. SURFRAD commenced operation in 1995. Presently, it is made up of six stations in diverse climates, including the moist subtropical environment of the U.S. southeast, the cool and dry northern plains, and the hot and arid desert southwest. Network operation involves a rigorous regimen of frequent calibration, quality assurance, and data quality control. An efficient supporting infrastructure has been created to gather, check, and disseminate the basic data expeditiously. Quality controlled daily processed data files from each station are usually available via the Internet within a day of real time. Data from SURFRAD have been used to validate measurements from NASA's Earth Observing System series of satellites, satellite-based retrievals of surface erythematogenic radiation, the national ultraviolet index, and real-time National Environmental Satellite, Data, and Information Service (NESDIS) products. It has also been used for carbon sequestration studies, to check radiative transfer codes in various physical models, for basic research and instruction at universities, climate research, and for many other applications. Two stations now have atmospheric energy flux and soil heat flux instrumentation, making them full surface energy balance sites. It is hoped that eventually all SURFRAD stations will have this capability. A surface radiation budget observing network (SURFRAD) has been established for the United States to support satellite retrieval validation, modeling, and climate, hydrology, and weather research. The primary measurements are the downwelling and upwelling components of broadband solar and thermal infrared irradiance. A hallmark of the network is the measurement and computation of ancillary parameters important to the transmission of radiation. SURFRAD commenced operation in 1995. Presently, it is made up of six stations in diverse climates, including the moist subtropical environment of the U.S. southeast, the cool and dry northern plains, and the hot and arid desert southwest. Network operation involves a rigorous regimen of frequent calibration, quality assurance, and data quality control. An efficient supporting infrastructure has been created to gather, check, and disseminate the basic data expeditiously. Quality controlled daily processed data files from each station are usually available via the Internet within a day of real time. Data from SURFRAD have been used to validate measurements from NASA's Earth Observing System series of satellites, satellite-based retrievals of surface erythematogenic radiation, the national ultraviolet index, and real-time National Environmental Satellite, Data, and Information Service (NESDIS) products. It has also been used for carbon sequestration studies, to check radiative transfer codes in various physical models, for basic research and instruction at universities, climate research, and for many other applications. Two stations now have atmospheric energy flux and soil heat flux instrumentation, making them full surface energy balance sites. It is hoped that eventually all SURFRAD stations will have this capability.

In place merging of satellite based atmospheric water vapour measurements

Atmospheric water vapour plays a key role in the climatology of the Earth. It has traditionally been measured using radiosondes for reasons of instrumental simplicity but these offer limited opportunities for spatial and continuous measurements of dynamic water vapour changes over large areas of the Earth's atmosphere. Efforts have recently turned to using satellite remote sensing instruments with different spectral and spatial capabilities to derive measurements of total water vapour content in atmospheric columns or simply precipitable water. The merging of remote sensing data with different spectral and spatial capabilities can result in large biases when independent measurements are not nested correctly to produce the final product. Consequently, such merging of data must take into account the intrinsic time dynamics of measured parameters. In this paper, the impact of atmospheric water vapour dynamics on the merging of satellite-based retrieval of precipitable water estimates is investigated by comparing independent measurements obtained at different spatial resolutions from the High Resolution Infrared Sounder (HIRS) and the Advanced Very High Resolution Radiometer (AVHRR). Correlations are used to infer optimal merging parameters depending on the observational conditions. The authors conclude that the merging technique reproduces HIRS-based retrievals in cloud-free and partly cloudy locations from AVHRR soundings.

A Study of SSM/I-Derived Columnar Water Vapor over the Global Oceans

Abstract Four years of columnar water vapor (CWV) data from July 1987 through June 1991 derived from a satellite-based physical retrieval method are analysed using microwave observations from the Special Sensor Microwave/Imager. This retrieval along with three statistically based retrievals were compared to radiosonde data compiled for the GEWEX Water Vapor Project. It is shown that the root-mean-square (rms) difference (R) between the radiosonde data and these satellite retrievals ranges from 4.66 kg m−2 to 5.08 kg m−2. The rms difference was found to have a seasonal variability of up to 1.0 kg m−2 with the highest R in JJA. It was also found to significantly depend on the specified time and spatial coincidence of the satellite pixels with the radiosonde observation. The rms difference decreased by about 0.65 kg m−2 when the time constraint was reduced from 2 h to 0.5 h, but R increased by about 0.3 kg m−2 when the spatial coincidence was reduced from 50 to 20 km. The relationship between 4 yr of CWV and...

Behavior of an Inversion-Based precipitation Retrieval Algorithm with High-Resolution AMPR Measurements Including a Low-Frequency 10.7-GHz Channel

A microwave-based, profile-type precipitation retrieval algorithm has been used to analyze high-resolution passsive microwave measurements over an ocean background, obtained by the Advanced Microwave Precipitation Radiometer (AMPR) flown on a NASA ER-2 aircraft. The analysis is designed to first determine the improvements that can be gained by adding brightness temperature information from the AMPR low-frequency channel (10.7 GHz) to a multispectral retrieval algorithm nominally run with satellite information at 19, 37, and 85 GHz. The impact of spatial resolution degradation of the high-resolution brightness temperature information on the retrieved rain/cloud liquid water contents and ice water contents is then quantified in order to assess the possible biases inherent to satellite-based retrieval. Careful inspection of the high-resolution aircraft dataset reveals five distinctive brightness temperature features associated with cloud structure and scattering effects that are not generally detectable in current passive microwave satellite measurements. Results suggest that the inclusion of 10.7-GHz information overcomes two basic problems associated with three-channel retrieval. Intercomparisons of retrievals carried out at high-resolution and then averaged to a characteristic satellite scale to the corresponding retrievals in which the brightness temperatures are first convolved down to the satellite scale suggest that with the addition of the 10.7-GHz channel, the rain liquid water contents will not be negatively impacted by special resolution degradation. That is not the case with the ice water contents as they appear ti be quite sensitive to the imposed scale, the implication being that as spatial resolution is reduced, ice water contents will become increasingly underestimated.

Cloud detection and analysis: A review of recent progress

The major types of cloud retrieval algorithms are reviewed with special emphasis being placed upon recent (i.e., post 1981/1982) developments and novel techniques. Satellite-based retrieval algorithms can be grouped into three classes: threshold methods, statistical procedures, and radiative transfer techniques, although each algorithm depends upon implicit, if not overt, inversion of the radiative transfer equation. The fourth type of retrieval differs very considerably from the satellite-based techniques as it depends upon surface-based measurements which are generally, but not always, human rather than computer based. There is a tendency to assume that surface-based observations, especially of total cloud amount, are “correct” but that they may differ from satellite-based retrievals because of the differences in viewing geometry. Actually the literature reveals surprisingly few intercomparison studies. None of the satellite-based techniques have yet been well-validated in a variety of situations, while surface-based observations are made in all terrain and climate regimes. Overall there seems to be good reason to believe that surface-based observations of cloud amount and especially of low cloud amount, character, and base height, can add significantly to satellite-based global nephanalyses now operational or currently being planned.

Combined Surface- and Satellite-Based Microwave Temperature Profile Retrieval

Abstract Remote sensing of vertical temperature profiles by combined satellite- and surface-based microwave radiometers is evaluated. For both clear and cloudy conditions, realistic simulations of retrieval accuracy for three climatologies with highly variable temperature structure suggest that rms retrieval accuracies from 1.0 to 2.0 K can be obtained from the surface to 300 mb using the combined passive measurements. When the height of the tropopause, as measured by ground-based radars, is used in a retrieval algorithm, simulations show that retrievals are improved over a broad altitude range, and that retrieval accuracies better than ∼2 K rms from the surface to 100 mb can be achieved.

Nonlinear Functions of Satellite-Measured Spectral Radiance as Estimators of Tropopause Height

Abstract This study deals with atmospheric tropopause detection by satellite. It is found that incorrect forecasting of the tropopause height yields a systematic bias in temperature profile estimates which use an algorithm (specifically, the “minimum information” method) operating on satellite-measured spectral infrared radiances and forecast temperature profiles as first guess fields. This bias follows from the general inability of linear satellite-based temperature retrieval schemes to substantially correct “shape” errors in the first guess field, owing to the rather low vertical resolving power of such schemes. A non-linear approach to tropopause detection which makes use of certain selected ratios of measured spectral radiances is shown to have some power for correcting these biases.

Improving Cloud and Moisture Representation in Weather Prediction Model Analyses with Geostationary Satellite Information

This paper develops a methodology for an experiment with several parallel regional Weather Research and Forecasting (WRF) model simulations initialized with satellite-based retrievals. The intent is to clarify the impact of observations, in the form of retrievals, from the Geostationary Operational Environmental Satellite (GOES) Sounder on 12, 24, and 36-hour WRF model forecasts of precipitable water. Two experimental analyses are built from a CIMSS Regional Assimilation System (CRAS) pre-forecast spin-up. The CRAS assimilates precipitable water and cloud products derived from the GOES Sounder. An experimentation period between late September and early October 2011 found that the majority of impact in the experimental simulations compared to the control is recognized in the total precipitable water field over the first 12 hours.Â