Showing papers on "Radiometer published in 2013"

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Abstract: Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available—expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.

First-Light Imagery from Suomi NPP VIIRS

Abstract: The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011, heralding the next generation of operational U.S. polar-orbiting satellites. It carries the Visible– Infrared Imaging Radiometer Suite (VIIRS), a 22-band visible/infrared sensor that combines many of the best aspects of the NOAA Advanced Very High Resolution Radiometer (AVHRR), the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. VIIRS has nearly all the capabilities of MODIS, but offers a wider swath width (3,000 versus 2,330 km) and much higher spatial resolution at swath edge. VIIRS also has a day/night band (DNB) that is sensitive to very low levels of visible light at night such as those produced by moonlight reflecting off low clouds, fog, dust, ash plumes, and snow cover. In addition, VIIRS detects light emissions from cities, ships, oil flares, and ...

Enhancement of aerosol characterization using synergy of lidar and sun - photometer coincident observations: the GARRLiC algorithm

Abstract: . This paper presents the GARRLiC algorithm (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) that simultaneously inverts coincident lidar and radiometer observations and derives a united set of aerosol parameters. Such synergetic retrieval results in additional enhancements in derived aerosol properties because the back-scattering observations by lidar improve sensitivity to the columnar properties of aerosol, while radiometric observations provide sufficient constraints on aerosol amount and type that are generally missing in lidar signals. GARRLiC is based on the AERONET algorithm, improved to invert combined observations by radiometer and multi-wavelength elastic lidar observations. The algorithm is set to derive not only the vertical profile of total aerosol concentration but it also differentiates between the contributions of fine and coarse modes of aerosol. The detailed microphysical properties are assumed height independent and different for each mode and derived as a part of the retrieval. The GARRLiC inversion retrieves vertical distribution of both fine and coarse aerosol concentrations as well as the size distribution and complex refractive index for each mode. The potential and limitations of the method are demonstrated by the series of sensitivity tests. The effects of presence of lidar data and random noise on aerosol retrievals are studied. Limited sensitivity to the properties of the fine mode as well as dependence of retrieval accuracy on the aerosol optical thickness were found. The practical outcome of the approach is illustrated by applications of the algorithm to the real lidar and radiometer observations obtained over Minsk AERONET site.

SMOS first data analysis for sea surface salinity determination

Abstract: Soil Moisture and Ocean Salinity SMOS, launched on 2 November 2009, is the first satellite mission addressing sea surface salinity SSS measurement from space. Its unique payload is the Microwave Imaging Radiometer using Aperture Synthesis MIRAS, a new two-dimensional interferometer designed by the European Space Agency ESA and operating at the L-band frequency. This article presents a summary of SSS retrieval from SMOS observations and shows initial results obtained one year after launch. These results are encouraging, but also indicate that further improvements at various data processing levels are needed and hence are currently under investigation.

An Evaluation of Microwave Land Surface Emissivities Over the Continental United States to Benefit GPM-Era Precipitation Algorithms

Abstract: Passive microwave (PMW) satellite-based precipitation over land algorithms rely on physical models to define the most appropriate channel combinations to use in the retrieval, yet typically require considerable empirical adaptation of the model for use with the satellite measurements. Although low-frequency channels are better suited to measure the emission due to liquid associated with rain, most techniques to date rely on high-frequency, scattering-based schemes since the low-frequency methods are limited to the highly variable land surface background, whose radiometric contribution is substantial and can vary more than the contribution of the rain signal. Thus, emission techniques are generally useless over the majority of the Earth's surface. As a first step toward advancing to globally useful physical retrieval schemes, an intercomparison project was organized to determine the accuracy and variability of several emissivity retrieval schemes. A three-year period (July 2004-June 2007) over different targets with varying surface characteristics was developed. The PMW radiometer data used includes the Special Sensor Microwave Imagers, SSMI Sounder, Advanced Microwave Scanning Radiometer (AMSR-E), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Advanced Microwave Sounding Units, and Microwave Humidity Sounder, along with land surface model emissivity estimates. Results from three specific targets in North America were examined. While there are notable discrepancies among the estimates, similar seasonal trends and associated variability were noted. Because of differences in the treatment surface temperature in the various techniques, it was found that comparing the product of temperature and emissivity yielded more insight than when comparing the emissivity alone. This product is the major contribution to the overall signal measured by PMW sensors and, if it can be properly retrieved, will improve the utility of emission techniques for over land precipitation retrievals. As a more rigorous means of comparison, these emissivity time series were analyzed jointly with precipitation data sets, to examine the emissivity response immediately following rain events. The results demonstrate that while the emissivity structure can be fairly well characterized for certain surface types, there are other more complex surfaces where the underlying variability is more than can be captured with the PMW channels. The implications for Global Precipitation Measurement-era algorithms suggest that physical retrievals are feasible over vegetated land during the warm seasons.

Intercalibration of Microwave Radiometer Brightness Temperatures for the Global Precipitation Measurement Mission

Abstract: A technique for comparing spaceborne microwave radiometer brightness temperatures (Tb) is described in the context of the upcoming National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission. The GPM mission strategy is to measure precipitation globally with high temporal resolution by using a constellation of satellite radiometers logically united by the GPM core satellite, which will be in a non-sun-synchronous medium inclination orbit. The usefulness of the combined product depends on the consistency of precipitation retrievals from the various microwave radiometers. The Tb calibration requirement to achieve such consistency demands first that Tb's from the individual radiometers be free of instrument and measurement artifacts and, second, that these self-consistent Tb's will be translated to a common standard (GPM core) for the unification of the precipitation retrieval. The intersatellite radiometric calibration technique described herein serves both the purposes by comparing individual radiometer observations to radiative transfer model (RTM) simulations (for “self-consistency” check) and by using a double-difference technique (to establish a linear calibration transfer function from one radiometer to another). This double-difference technique subtracts the RTM-simulated difference from the observed difference between a pair of radiometer Tb's. To establish a linear inter-radiometer calibration transfer function, comparisons at both the cold (ocean) and the warm (land) end of the Tb's are necessary so that, using these two points, slope and offset coefficients are determined. To this end, a simplified calibration transfer technique at the warm end (over the Amazon and Congo rain forest) is introduced. Finally, an error model is described that provides an estimate of the uncertainty of the radiometric bias estimate between comparison radiometer channels.

Galactic Noise and Passive Microwave Remote Sensing from Space At L-Band

Abstract: The spectral window at L-band (1.413 GHz) is important for passive remote sensing of soil moisture and ocean salinity from space, parameters that are needed to understand the hydrological cycle and ocean circulation. At this frequency, radiation from celestial (mostly Galactic) sources is strong and, unlike the constant cosmic background, this radiation is spatially variable. This paper presents a modern radiometric map of the celestial sky at L-band and a solution for the problem of determining what portion of the sky is seen by a down-looking radiometer in orbit. The data for the radiometric map are derived from recent radio astronomy surveys and are presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Near the Galactic plane, the contribution can exceed several kelvin.

Path Delays in the Neutral Atmosphere

Abstract: This part describes the effects of the troposphere—strictly speaking the neutral atmosphere—on the propagation delay of space geodetic signals. A theoretical description of this tropospheric propagation delay is given as well as strategies for correcting for it in the data analysis of the space geodetic observations. The differences between the tropospheric effects for microwave techniques, like the Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI), and those for optical techniques, like Satellite Laser Ranging (SLR), are discussed. Usually, residual tropospheric delays are estimated in the data analysis, and the parameterization needed to do so is presented. Other possibilities of correcting for the tropospheric delays are their calculation by ray-tracing through the fields of numerical weather models and by utilizing water vapor radiometer measurements. Finally, we shortly discuss how space geodetic techniques can be used in atmospheric analysis in meteorology and climatology.

The LYRA Instrument Onboard PROBA2: Description and In-Flight Performance

Abstract: The Large Yield Radiometer (LYRA) is an XUV–EUV–MUV (soft X-ray to mid-ultraviolet) solar radiometer onboard the European Space Agency Project for On-Board Autonomy 2 (PROBA2) mission, which was launched in November 2009. LYRA acquires solar-irradiance measurements at a high cadence (nominally 20 Hz) in four broad spectral channels, from soft X-ray to MUV, which have been chosen for their relevance to solar physics, space weather, and aeronomy. We briefly review the design of the instrument, give an overview of the data products distributed through the instrument website, and describe how the data are calibrated. We also briefly present a summary of the main fields of research currently under investigation by the LYRA consortium.

New approaches to removing cloud shadows and evaluating the 380 nm surface reflectance for improved aerosol optical thickness retrievals from the GOSAT/TANSO‐Cloud and Aerosol Imager

Abstract: [1] A satellite aerosol retrieval algorithm was developed to utilize a near-ultraviolet band of the Greenhouse gases Observing SATellite/Thermal And Near infrared Sensor for carbon Observation (GOSAT/TANSO)-Cloud and Aerosol Imager (CAI). At near-ultraviolet wavelengths, the surface reflectance over land is smaller than that at visible wavelengths. Therefore, it is thought possible to reduce retrieval error by using the near-ultraviolet spectral region. In the present study, we first developed a cloud shadow detection algorithm that uses first and second minimum reflectances of 380 nm and 680 nm based on the difference in Rayleigh scattering contribution for these two bands. Then, we developed a new surface reflectance correction algorithm, the modified Kaufman method, which uses minimum reflectance data at 680 nm and the NDVI to estimate the surface reflectance at 380 nm. This algorithm was found to be particularly effective at reducing the aerosol effect remaining in the 380 nm minimum reflectance; this effect has previously proven difficult to remove owing to the infrequent sampling rate associated with the three-day recursion period of GOSAT and the narrow CAI swath of 1000 km. Finally, we applied these two algorithms to retrieve aerosol optical thicknesses over a land area. Our results exhibited better agreement with sun-sky radiometer observations than results obtained using a simple surface reflectance correction technique using minimum radiances.

Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale

Abstract: Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are providing long-term time series information. Assessing the quality of remote sensing-based temperature measurements provides feedback to the climate modeling community and other users by identifying agreements and discrepancies when compared to temperature records from meteorological stations. This paper presents a comparison of state-of-the-art remote sensing-based land surface temperature data with air temperature measurements from meteorological stations on a pan-arctic scale (north of 60° latitude). Within this study, we compared land surface temperature products from (A)ATSR, MODIS and AVHRR with an in situ air temperature (Tair) database provided by the National Climate Data Center (NCDC). Despite analyzing the whole acquisition time period of each land surface temperature product, we focused on the inter-annual variability comparing land surface temperature (LST) and air temperature for the overlapping time period of the remote sensing data (2000–2005). In addition, land cover information was included in the evaluation approach by using GLC2000. MODIS has been identified as having the highest agreement in comparison to air temperature records. The time series of (A)ATSR is highly variable, whereas inconsistencies in land surface temperature data from AVHRR have been found.

Evaluation of cloud microphysics schemes in simulations of a winter storm using radar and radiometer measurements

Abstract: [1] Using observations from a space-borne radiometer and a ground-based precipitation profiling radar, the impact of cloud microphysics schemes in the WRF model on the simulation of microwave brightness temperature (Tb), radar reflectivity, and Doppler velocity (Vdop) is studied for a winter storm in California. The unique assumptions of particles size distributions, number concentrations, shapes, and fall speeds in different microphysics schemes are implemented into a satellite simulator and customized calculations for the radar are performed to ensure consistent representation of precipitation properties between the microphysics schemes and the radiative transfer models. [2] Simulations with four different schemes in the WRF model, including the Goddard scheme (GSFC), the WRF single-moment 6-class scheme (WSM6), the Thompson scheme (THOM), and the Morrison double-moment scheme (MORR), are compared directly with measurements from the sensors. Results show large variations in the simulated radiative properties. General biases of ~20 K or larger are found in (polarization-corrected) Tb, which is linked to an overestimate of the precipitating ice aloft. The simulated reflectivity with THOM appears to agree well with the observations, while high biases of ~5−10 dBZ are found in GSFC, WSM6 and MORR. Peak reflectivity in MORR exceeds other schemes. These biases are attributable to the snow intercept parameters or the snow number concentrations. Simulated Vdop values based on GSFC agree with the observations well, while other schemes appear to have a ~1 m s-1 high bias in the ice layer. In the rain layer, the model representations of Doppler velocity vary at different sites.

New approach for severe marine weather study using satellite passive microwave sensing

Abstract: [1] A methodology, based on model simulations and neural networks inversion, is proposed to jointly retrieve sea surface wind speed, sea surface temperature, atmospheric water vapor content, cloud liquid water content, and total atmospheric absorption at 10.65 GHz using Advanced Microwave Scanning Radiometer 2 measurements. In particular, estimation of the total atmospheric absorption at 10.65 GHz, which can be done with high accuracy due to the not so strong influence of liquid water and especially water vapor, helps to refine a new filter to considerably reduce masking ocean areas for severe weather systems, characterized by high wind speeds and moderate atmospheric absorption, appropriate for studying winter extratropical cyclone and polar low systems. A polar low case study has demonstrated significant improvement in the coverage of the ocean area available for geophysical retrievals: Only less than 1% of high wind speed pixels were masked comparatively to the 40–70% masking given by other methods.

A new method for nocturnal aerosol measurements with a lunar photometer prototype

Abstract: . This paper presents the preliminary results of nocturnal Aerosol Optical Depth (τa) and Angstrom Exponent (α) obtained from a new lunar photometer prototype, trade name Cimel CE-318U. Due to the variation of the moon's illumination inherent to the lunar cycle, the typical Langley-plot Method used in solar photometry to calibrate these instruments cannot be applied. In this paper, we propose three different methods to carry out the lunar-photometer calibration. In order to validate the results, we have selected three events which encompass seven nights and ten days under different atmospheric conditions, including several saharan dust intrusions episodes. Method#1 is introduced in this work as a modification of the usual Langley Method. This technique, called Lunar-Langley Method, requires the extraterrestrial irradiances from a lunar irradiance model, providing similar accuracies on τa to those of AERONET (±0.01–0.02). It makes comparable daytime and nighttime measurements. Method#2 consists of transferring the current calibration from a master used by sunphotometers. Its results are again within the limit of accuracy expected for the instrument. Method#3 uses an integrating sphere and the methodology proposed by Li et al. (2008) to determine sky calibration coefficients (Cj) and the instrument's solid angle field-of-view (Ω), respectively. We observe significant τa differences between Method#1 and #3 (up to 0.07), which might be attributed to the errors propagation in Method#3. The good results obtained from the comparison against a second CE-318U prototype, and against daytime data from a Precision Filter Radiometer (PFR), constitute a valuable assessment of CE-318U performance. Results of α and its spectral variation (δ α) show good agreement between daytime and nighttime, being able to identify the aerosol properties associated with each event.

Downscaling Geostationary Land Surface Temperature Imagery for Urban Analysis

Abstract: Although Earth observation data have been used in urban thermal applications extensively, these studies are often limited by the choices made in data selection, i.e., either using data with high spatial and low temporal resolution, or data with high temporal and low spatial resolution. The challenge of advancing the low spatial (3-5 km) resolution of geostationary land surface temperature (LST) images to 1 km-while maintaining the excellent temporal resolution of 15 min-is approached in this letter. The downscaling was performed using different advanced regression algorithms, such as support vector regression machines, neural networks, and regression trees, and its performance was improved using gradient boosting. The methodologies were tested on Meteosat Second Generation (MSG) SEVIRI LST images over an area of 19 600 km2 centered in Athens, Greece. The output 1-km downscaled LST images were assessed against coincident LST maps derived from the thermal infrared imagery of the Moderate Resolution Imaging Spectroradiometer, the Advanced Very High Resolution Radiometer, and the Advanced Along Track Scanning Radiometer. The results showed that support vector machines coupled with gradient boosting proved to be a robust high-performance methodology reaching correlation coefficients from 0.69 to 0.81 when compared with the other satellite-derived LST maps.

Investigation of ground-based microwave radiometer calibration techniques at 530 hPa

Abstract: . Ground-based microwave radiometers (MWR) are becoming more and more common for remotely sensing the atmospheric temperature and humidity profile as well as path-integrated cloud liquid water content. The calibration accuracy of the state-of-the-art MWR HATPRO-G2 (Humidity And Temperature Profiler – Generation 2) was investigated during the second phase of the Radiative Heating in Underexplored Bands Campaign (RHUBC-II) in northern Chile (5320 m above mean sea level, 530 hPa) conducted by the Atmospheric Radiation Measurement (ARM) program conducted between August and October 2009. This study assesses the quality of the two frequently used liquid nitrogen and tipping curve calibrations by performing a detailed error propagation study, which exploits the unique atmospheric conditions of RHUBC-II. Both methods are known to have open issues concerning systematic offsets and calibration repeatability. For the tipping curve calibration an uncertainty of ±0.1 to ±0.2 K (K-band) and ±0.6 to ±0.7 K (V-band) is found. The uncertainty in the tipping curve calibration is mainly due to atmospheric inhomogeneities and the assumed air mass correction for the Earth curvature. For the liquid nitrogen calibration the estimated uncertainty of ±0.3 to ±1.6 K is dominated by the uncertainty of the reflectivity of the liquid nitrogen target. A direct comparison between the two calibration techniques shows that for six of the nine channels that can be calibrated with both methods, they agree within the assessed uncertainties. For the other three channels the unexplained discrepancy is below 0.5 K. Systematic offsets, which may cause the disagreement of both methods within their estimated uncertainties, are discussed.

Monitoring Satellite Radiance Biases Using NWP Models

Abstract: Radiances measured by satellite radiometers are often subject to biases due to limitations in their radiometric calibration. In support of the Global Space-based Inter-Calibration System project, to improve the quality of calibrated radiances from atmospheric sounders and imaging radiometers, an activity is underway to compare routinely measured radiances with those simulated from operational global numerical weather prediction (NWP) fields. This paper describes the results obtained from the first three years of these comparisons. Data from the High-resolution Infrared Radiation Sounder, Spinning Enhanced Visible and Infrared Imager, Advanced Along-Track Scanning Radiometer, Advanced Microwave Sounding Unit, and Microwave Humidity Sounder radiometers, together with the Atmospheric Infrared Sounder, a spectrometer, and the Infrared Atmospheric Sounding Interferometer, an interferometer, were included in the analysis. Changes in mean biases and their standard deviations were used to investigate the temporal stability of the bias and radiometric noise of the instruments. A double difference technique can be employed to remove the effect of changes or deficiencies in the NWP model which can contribute to the biases. The variation of the biases with other variables is also investigated, such as scene temperature, scan angle, location, and time of day. Many of the instruments were shown to be stable in time, with a few exceptions, but measurements from the same instrument on different platforms are often biased with respect to each other. The limitations of the polar simultaneous nadir overpasses often used to monitor biases between polar-orbiting sensors are shown with these results due to the apparent strong dependence of some radiance biases on scene temperature.

Microwave thermometry for microwave ablation systems

Abstract: A microwave ablation system incorporates a microwave thermometer that couples to a microwave transmission network connecting a microwave generator to a microwave applicator to measure noise temperature. The noise temperature is processed to separate out components the noise temperature including the noise temperature of the tissue being treated and the noise temperature of the microwave transmission network. The noise temperature may be measured by a radiometer while the microwave generator is generating the microwave signal or during a period when the microwave signal is turned off. The microwave ablation system may be configured as a modular system having one or more thermometry network modules that are connectable between a microwave applicator and a microwave generator. Alternatively, the modular system includes a microwave generator, a microwave applicator, and a microwave cable that incorporate a microwave thermometry network module.

Evaluation of land surface temperature and emissivities retrieved from MSG/SEVIRI data with MODIS land surface temperature and emissivity products

Abstract: Land surface temperature LST and land surface emissivity LSE are two key parameters in global climate study. This article aims to cross-validate LST/LSE products retrieved from data of the Spinning Enhanced Visible and Infrared Imager SEVIRI on board the first geostationary satellite, Meteosat Second Generation MSG, with Moderate Resolution Imaging Spectroradiometer MODIS LST/LSE version 5 products over the Iberian Peninsula and over Egypt and the Middle East. Besides time matching, coordinate matching is another requirement of the cross-validation. An area-weighted aggregation algorithm was used to aggregate SEVIRI and MODIS LST/LSE products into the same spatial resolution. According to the quality control QC criterion and the view angle, the cross-validation was completed under clear-sky conditions and within a view angle difference of less than 5° for the two instruments to prevent land surface anisotropic effects. The results showed that the SEVIRI LST/LSE products are consistent with MODIS LST/LSE products and have the same trend over the two study areas during both the daytime and the night-time. The SEVIRI LST overestimates the temperature by approximately 1.0 K during the night-time and by approximately 2.0 K during the daytime compared to MODIS products over these two study areas. The SEVIRI LSE underestimates by about 0.015 in 11 μm and by about 0.025 in 12 μm over the Iberian Peninsula. However, both LSEs agree and show a difference of less than 0.01 over Egypt and the Middle East.

The Red Versa NIR Plane to Retrieve Broken-Cloud Optical Depth from Ground-Based Measurements

Abstract: A new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the red (RED) and near-infrared (NIR) spectral regions is introduced. Because zenith radiance does not have a oneto-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval. On the other side, algebraic combinations of spectral radiances, such as normalized difference cloud index (NDCI), while largely removing nonuniqueness and the radiative effects of cloud inhomogeneity, can result in poor retrievals due to its insensitivity to cloud fraction. Instead, both RED and NIR radiances as points on the ‘‘RED versus NIR’’ plane are proposed to be used for retrieval. The proposed retrieval method is applied to Cimel measurements at the Atmospheric Radiation Measurements (ARM) site in Oklahoma. Cimel, a multichannel sun photometer, is a part of the Aerosol Robotic Network (AERONET)—a ground-based network for monitoring aerosol optical properties. The results of retrieval are compared with the ones from microwave radiometer (MWR) and multifilter rotating shadowband radiometer (MFRSR) located next to Cimel at the ARM site. In addition, the performance of the retrieval method is assessed using a fractal model of cloud inhomogeneity and broken cloudiness. The preliminary results look very promising both theoretically and from measurements.

Snow and ice products from Suomi NPP VIIRS

Abstract: [1] The Visible Infrared Imager Radiometer Suite (VIIRS) instrument was launched in October 2011 on the satellite now known as the Suomi National Polar-orbiting Partnership. VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). VIIRS snow and ice products include sea ice surface temperature, sea ice concentration, sea ice characterization, a binary snow map, and fractional snow cover. Validation results with these “provisional” level maturity products show that ice surface temperature has a root-mean-square error of 0.6–1.0 K when compared to aircraft data and a similar MODIS product, the measurement accuracy and precision of ice concentration are approximately 5% and 15% when compared to passive microwave retrievals, and the accuracy of the binary snow cover (snow/no-snow) maps is generally above 90% when compared to station data. The ice surface temperature and snow cover products meet their accuracy requirements with respect to the Joint Polar Satellite System Level 1 Requirements Document. Sea Ice Characterization, which consists of two age categories, has not been observed to meet the 70% accuracy requirements of ice classification. Given their current performance, the ice surface temperature, snow cover, and sea ice concentration products should be useful for both research and operational applications, while improvements to the sea ice characterization product are needed before it can be used for these applications.

Combining ground‐based with satellite‐based measurements in the atmospheric state retrieval: Assessment of the information content

Abstract: [1] Remote sensing techniques offer the unique possibility to continuously and automatically monitor the atmospheric state from ground and space Ground-based microwave radiometers (MWRs), for example, are frequently used for temperature and humidity profiling of the lower troposphere In order to improve the profiles in the middle and upper troposphere, further information is needed In this respect, satellite measurements are expected to be very useful In this study, the synergy benefit in temperature and humidity clear-sky profiling using different combinations of state-of-the-art microwave and infrared ground- and satellite-based instruments is assessed The synergy benefit is regarded as the information gain in light of ground-based MWR observations together with some climatological a priori knowledge The maximum information content for this kind of synergy is estimated by assuming optimum conditions, eg, no forward model uncertainties and a horizontal homogeneous atmosphere For a midlatitude site, the ground-based MWR gives about 44 and 24 independent pieces of information on the temperature and humidity profile, respectively For the temperature profile, the combination with Improved Atmospheric Sounding in the Infrared (IASI) and Atmospheric Microwave Sounding Unit-A/Microwave Humidity Sounder (AMSU-A/MHS) increases the information by a factor of about 18 and 15, respectively, with highest benefit in warm and/or humid conditions The vertical information on humidity is significantly improved by highly spectrally resolved IR observations from ground or space when the atmosphere is cold and dry; the vertical information is more than tripled If measurements from AMSU-A/MHS, IASI, or Spinning Enhanced Visible and Infrared Imager are included, retrieval uncertainties in the middle and upper troposphere are significantly reduced by up to 68%

Expected improvements in the atmospheric humidity profile retrieval using the Megha‐Tropiques microwave payload

Abstract: The microwave payload of the Megha-Tropiques mission is explored to quantify the expected improvements in the retrieval of relative humidity profiles Estimations of the profiles are performed using a generalized additive model that uses cubic smoothing splines to address the nonlinear dependencies between the brightness temperatures (TB) in the 18331 GHz band and the relative humidity of specified tropospheric layers Under clear-sky and oceanic situations, the six-channel configuration of the SAPHIR radiometer clearly improves the retrieval and reduces by a factor of two the variance of the residuals with respect to the current space-borne humidity sounders that have three channels in this band (AMSU-B, MHS) Additional information from the MADRAS radiometer (at 238 and 157 GHz) further improves the restitution with correlation coefficient higher than 089 throughout the troposphere

Microwave radiometer to retrieve temperature profiles from the surface to the stratopause

Abstract: . TEMPERA (TEMPERature RAdiometer) is a new ground-based radiometer which measures in a frequency range from 51–57 GHz radiation emitted by the atmosphere. With this instrument it is possible to measure temperature profiles from ground to about 50 km. This is the first ground-based instrument with the capability to retrieve temperature profiles simultaneously for the troposphere and stratosphere. The measurement is done with a filterbank in combination with a digital fast Fourier transform spectrometer. A hot load and a noise diode are used as stable calibration sources. The optics consist of an off-axis parabolic mirror to collect the sky radiation. Due to the Zeeman effect on the emission lines used, the maximum height for the temperature retrieval is about 50 km. The effect is apparent in the measured spectra. The performance of TEMPERA is validated by comparison with nearby radiosonde and satellite data from the Microwave Limb Sounder on the Aura satellite. In this paper we present the design and measurement method of the instrument followed by a description of the retrieval method, together with a validation of TEMPERA data over its first year, 2012.

Sensitivity of aerosol retrieval to geometrical configuration of ground-based sun/sky radiometer observations [Discussion paper]

Abstract: Abstract. A sensitivity study of aerosol retrievals to the geometrical configuration of the ground-based sky radiometer observations is carried out through inversion tests. Specifically, this study is focused on principal plane and almucantar observations, since these geometries are employed in AERONET (AErosol RObotic NETwork). The following effects have been analyzed with simulated data for both geometries: sensitivity of the retrieval to variability of the observed scattering angle range, uncertainties in the assumptions of the aerosol vertical distribution, surface reflectance, possible instrument pointing errors, and the effects of the finite field of view. The synthetic observations of radiometer in the tests were calculated using a previous climatology data set of retrieved aerosol properties over three AERONET sites: Mongu (Zambia) for biomass burning aerosol, Goddard Space Flight Center (GSFC; Maryland, USA) for urban aerosol and Solar Village (Saudi Arabia) for desert dust aerosol. The results show that almucantar retrievals, in general, are more reliable than principal plane retrievals in presence of the analyzed error sources. This fact partially can be explained by practical advantages of the almucantar geometry: the symmetry between its left and right branches that helps to eliminate some observational uncertainties and the constant value of optical mass during the measurements, that make almucantar observations nearly independent of the vertical variability of aerosol. Nevertheless, almucantar retrievals present instabilities at high sun elevations due to the reduction of the scattering angle range coverage, resulting in decrease of information content. It is in such conditions that principal plane retrievals show a better stability, as shown by the simulation analysis of the three different aerosol models. The last part of the study is devoted to the identification of possible differences between the aerosol retrieval results obtained from real AERONET data using both geometries. In particular, we have compared AERONET retrievals at the same sites used in the simulation analysis: Mongu (biomass burning), GSFC (urban) and Solar Village (desert dust). Overall, this analysis shows robust consistency between the retrievals from simultaneous observations in principle plane and almucantar All identified differences are within the uncertainties estimated for the AERONET operational aerosol retrieval. The differences in the size distribution are generally under 10% for radii between 0.1 μm and 5 μm, and outside this size range, the differences can be as large as 50%. For the absorption parameters, i.e., single scattering albedo and the imaginary part of the refractive index, the differences are typically under 0.01 and 0.003, respectively. The real part of the refractive index showed a difference of 0.01 for biomass burning and urban aerosol, and a difference of around 0.03 for desert dust. Finally, it should be noted that the whole data set includes only 200 pairs, which have been taken under very stable atmospheric conditions; therefore, in a general case, differences between principal plane (PPL) and almucantar (ALM) are expected to be higher. Though the observed differences between ALM and PPL are rather small, it should be noted that this analysis has been conducted using a limited set of 200 observation pairs selected under stable atmospheric conditions.