Showing papers on "Radiometer published in 2014"

Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

Abstract: The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the on-orbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

The Soil Moisture Active Passive Experiments (SMAPEx): Toward Soil Moisture Retrieval From the SMAP Mission

Abstract: NASA's Soil Moisture Active Passive (SMAP) mission will carry the first combined spaceborne L-band radiometer and Synthetic Aperture Radar (SAR) system with the objective of mapping near-surface soil moisture and freeze/thaw state globally every 2-3 days. SMAP will provide three soil moisture products: i) high-resolution from radar (~3 km), ii) low-resolution from radiometer (~36 km), and iii) intermediate-resolution from the fusion of radar and radiometer (~9 km). The Soil Moisture Active Passive Experiments (SMAPEx) are a series of three airborne field experiments designed to provide prototype SMAP data for the development and validation of soil moisture retrieval algorithms applicable to the SMAP mission. This paper describes the SMAPEx sampling strategy and presents an overview of the data collected during the three experiments: SMAPEx-1 (July 5-10, 2010), SMAPEx-2 (December 4-8, 2010) and SMAPEx-3 (September 5-23, 2011). The SMAPEx experiments were conducted in a semi-arid agricultural and grazing area located in southeastern Australia, timed so as to acquire data over a seasonal cycle at various stages of the crop growth. Airborne L-band brightness temperature (~1 km) and radar backscatter (~10 m) observations were collected over an area the size of a single SMAP footprint (38 km × 36 km at 35° latitude) with a 2-3 days revisit time, providing SMAP-like data for testing of radiometer-only, radar-only and combined radiometer-radar soil moisture retrieval and downscaling algorithms. Airborne observations were supported by continuous monitoring of near-surface (0-5 cm) soil moisture along with intensive ground monitoring of soil moisture, soil temperature, vegetation biomass and structure, and surface roughness.

Tests of the SMAP Combined Radar and Radiometer Algorithm Using Airborne Field Campaign Observations and Simulated Data

Abstract: A soil moisture retrieval algorithm is proposed that takes advantage of the simultaneous radar and radiometer measurements by the forthcoming NASA Soil Moisture Active Passive (SMAP) mission. The algorithm is designed to downscale SMAP L-band brightness temperature measurements at low resolution ( ~ 40 km) to 9-km brightness temperature by using SMAP's L-band synthetic aperture radar (SAR) backscatter measurements at high resolution (1-3 km) in order to estimate soil moisture at 9-km resolution. The SMAP L-band SAR and radiometer instruments are designed to provide coincident observations at constant incidence angle, but at different spatial resolutions, across a wide swath. The algorithm described here takes advantage of the correlation between temporal fluctuations of brightness temperature and backscatter observed when viewing targets simultaneously at the same angle. Surface characteristics that affect the brightness temperature and backscatter measurements influence the signals at different time scales. This feature is applied in an approach in which fine-scale spatial heterogeneity detected by SAR observations is applied on coarser-scale radiometer measurements to produce an intermediate-resolution disaggregated brightness temperature field. These brightness temperatures are then used with established radiometer-based algorithms to retrieve soil moisture at the intermediate resolution. The capability of the overall algorithm is demonstrated using data acquired by the airborne passive and active L-band system from field campaigns and also by simulated global dataset. Results indicate that the algorithm has the potential to retrieve soil moisture at 9-km resolution, with the accuracy required for SMAP, over regions having vegetation up to 5- kg/m2 vegetation water content. The results show a reduction in root mean square error of volumetric soil moisture (40% improvement in the statistics) from the minimum performance defined as the soil moisture retrieved using radiometer measurements re-sampled to the intermediate scale.

Radio-Frequency Interference Mitigation for the Soil Moisture Active Passive Microwave Radiometer

Abstract: The Soil Moisture Active Passive (SMAP) radiometer operates in the L-band protected spectrum (1400-1427 MHz) that is known to be vulnerable to radio-frequency interference (RFI). Although transmissions are forbidden at these frequencies by international regulations, ground-based, airborne, and spaceborne radiometric observations show substantial evidence of out-of-band emissions from neighboring transmitters and possibly illegally operating emitters. The spectral environment that SMAP faces includes not only occasional large levels of RFI but also significant amounts of low-level RFI equivalent to a brightness temperature of 0.1-10 K at the radiometer output. This low-level interference would be enough to jeopardize the success of a mission without an aggressive mitigation solution, including special flight hardware and ground software with capabilities of RFI detection and removal. SMAP takes a multidomain approach to RFI mitigation by utilizing an innovative onboard digital detector back end with digital signal processing algorithms to characterize the time, frequency, polarization, and statistical properties of the received signals. Almost 1000 times more measurements than what is conventionally necessary are collected to enable the ground processing algorithm to detect and remove harmful interference. Multiple RFI detectors are run on the ground, and their outputs are combined for maximum likelihood of detection to remove the RFI within a footprint. The capabilities of the hardware and software systems are successfully demonstrated using test data collected with a SMAP radiometer engineering test unit.

The emission and scattering of L‐band microwave radiation from rough ocean surfaces and wind speed measurements from the Aquarius sensor

Abstract: In order to achieve the required accuracy in sea surface salinity (SSS) measurements from L-band radiometers such as the Aquarius/SAC-D or SMOS (Soil Moisture and Ocean Salinity) mission, it is crucial to accurately correct the radiation that is emitted from the ocean surface for roughness effects. We derive a geophysical model function (GMF) for the emission and backscatter of L-band microwave radiation from rough ocean surfaces. The analysis is based on radiometer brightness temperature and scatterometer backscatter observations both taken on board Aquarius. The data are temporally and spatially collocated with wind speeds from WindSat and F17 SSMIS (Special Sensor Microwave Imager Sounder) and wind directions from NCEP (National Center for Environmental Prediction) GDAS (Global Data Assimilation System). This GMF is the basis for retrieval of ocean surface wind speed combining L-band H-pol radiometer and HH-pol scatterometer observations. The accuracy of theses combined passive/active L-band wind speeds matches those of many other satellite microwave sensors. The L-band GMF together with the combined passive/active L-band wind speeds is utilized in the Aquarius SSS retrieval algorithm for the surface roughness correction. We demonstrate that using these L-band wind speeds instead of NCEP wind speeds leads to a significant improvement in the SSS accuracy. Further improvements in the roughness correction algorithm can be obtained by adding VV-pol scatterometer measurements and wave height (WH) data into the GMF.

Inter-Calibration of Satellite Passive Microwave Land Observations from AMSR-E and AMSR2 Using Overlapping FY3B-MWRI Sensor Measurements

Abstract: The development and continuity of consistent long-term data records from similar overlapping satellite observations is critical for global monitoring and environmental change assessments. We developed an empirical approach for inter-calibration of satellite microwave brightness temperature (Tb) records over land from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Microwave Scanning Radiometer 2 (AMSR2) using overlapping Tb observations from the Microwave Radiation Imager (MWRI). Double Differencing (DD) calculations revealed significant AMSR2 and MWRI biases relative to AMSR-E. Pixel-wise linear relationships were established from overlapping Tb records and used for calibrating MWRI and AMSR2 records to the AMSR-E baseline. The integrated multi-sensor Tb record was largely consistent over the major global vegetation and climate zones; sensor biases were generally well calibrated, though residual Tb differences inherent to different sensor configurations were still present. Daily surface air temperature estimates from the calibrated AMSR2 Tb inputs also showed favorable accuracy against independent measurements from 142 global weather stations (R2 ≥ 0.75, RMSE ≤ 3.64 °C), but with slightly lower accuracy than the AMSR-E baseline (R2 ≥ 0.78, RMSE ≤ 3.46 °C). The proposed method is promising for generating consistent, uninterrupted global land parameter records spanning the AMSR-E and continuing AMSR2 missions.

Portable Remote Imaging Spectrometer coastal ocean sensor: design, characteristics, and first flight results

Abstract: The design, characteristics, and first test flight results are described of the Portable Remote Imaging Spectrometer, an airborne sensor specifically designed to address the challenges of coastal ocean remote sensing. The sensor incorporates several technologies that are demonstrated for the first time, to the best of our knowledge, in a working system in order to achieve a high performance level in terms of uniformity, signal-to-noise ratio, low polarization sensitivity, low stray light, and high spatial resolution. The instrument covers the 350–1050 nm spectral range with a 2.83 nm sampling per pixel, and a 0.88 mrad instantaneous field of view, with 608 cross-track pixels in a pushbroom configuration. Two additional infrared channels (1240 and 1610 nm) are measured by a spot radiometer housed in the same head. The spectrometer design is based on an optically fast (F/1.8) Dyson design form coupled to a wide angle two-mirror telescope in a configuration that minimizes polarization sensitivity without the use of a depolarizer. A grating with minimum polarization sensitivity and broadband efficiency was fabricated as well as a slit assembly with black (etched) silicon surface to minimize backscatter. First flight results over calibration sites as well as Monterey Bay in California have demonstrated good agreement between in situ and remotely sensed data, confirming the potential value of the sensor to the coastal ocean science community.

Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site

Abstract: The objective of this paper is to report the improvements in an empirical absolute calibration model developed at South Dakota State University using Libya 4 (+28.55 deg, +23.39 deg) pseudo invariant calibration site (PICS). The approach was based on use of the Terra MODIS as the radiometer to develop an absolute calibration model for the spectral channels covered by this instrument from visible to shortwave infrared. Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm, was used to extend the model to cover visible and near-infrared regions. A simple Bidirectional Reflectance Distribution function (BRDF) model was generated using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Libya 4 and the resulting model was validated with nadir data acquired from satellite sensors such as Aqua MODIS and Landsat 7 (L7) Enhanced Thematic Mapper (ETM+). The improvements in the absolute calibration model to account for the BRDF due to off-nadir measurements and annual variations in the atmosphere are summarized. BRDF models due to off-nadir viewing angles have been derived using the measurements from EO-1 Hyperion. In addition to L7 ETM+, measurements from other sensors such as Aqua MODIS, UK-2 Disaster Monitoring Constellation (DMC), ENVISAT Medium Resolution Imaging Spectrometer (MERIS) and Operational Land Imager (OLI) onboard Landsat 8 (L8), which was launched in February 2013, were employed to validate the model. These satellite sensors differ in terms of the width of their spectral bandpasses, overpass time, off-nadir-viewing capabilities, spatial resolution and temporal revisit time, etc. The results demonstrate that the proposed empirical calibration model has accuracy of the order of 3% with an uncertainty of about 2% for the sensors used in the study.

Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite

Abstract: Soil moisture retrievals from China’s recently launched meteorological Fengyun-3B satellite are presented. An established retrieval algorithm – the Land Parameter Retrieval Model (LPRM) – was applied to observations of the Microwave Radiation Imager (MWRI) onboard this satellite. The newly developed soil moisture retrievals from this satellite mission may be incorporated in an existing global microwave-based soil moisture database. To reach consistency with an existing data set of multi-satellite soil moisture retrievals, an intercalibration step was applied to correct brightness temperatures for sensor differences between MWRI and the radiometer of the Tropical Rainfall Measuring Mission’s (TRMM’s) Microwave Imager (TMI), resulting from their individual calibration procedures. The newly derived soil moisture and vegetation optical depth product showed a high degree of consistency with parallel retrievals from both TMI and WindSat, the two satellites that are observing during the same time period and are ...

Two-Dimensional TSVD to Enhance the Spatial Resolution of Radiometer Data

Abstract: A reconstruction technique, based on the 2-D truncated singular value decomposition, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. The technique is very computer time effective when the kernel is a 2-D tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically based generalized cross-validation approach. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical 2-D radiometer scene is processed in seconds by a standard PC processor.

Triple-Frequency Radar Reflectivity Signatures of Snow: Observations and Comparisons with Theoretical Ice Particle Scattering Models

Abstract: An observation-based study is presented that utilizes aircraft data from the 2003 Wakasa Bay Advanced Microwave Scanning Radiometer Precipitation Validation Campaign to assess recent advances in the modeling of microwave scattering properties of nonspherical ice particles in the atmosphere. Previous work has suggested that a triple-frequency (Ku–Ka–W band) reflectivity framework appears capable of identifying key microphysical properties of snow, potentially providing much-needed constraints on significant sources of uncertainty in current snowfall retrieval algorithms used for microwave remote sensing instruments. However, these results were based solely on a modeling framework. In contrast, this study considers the triple-frequency approach from an observational perspective using airborne radar observations from the Wakasa Bay field campaign. After accounting for several challenges with the observational dataset, such as beam mismatching and attenuation, observed dual-wavelength ratio results ar...

Design and characterization of a 32-channel heterodyne radiometer for electron cyclotron emission measurements on experimental advanced superconducting tokamak

Abstract: A 32-channel heterodyne radiometer has been developed for the measurement of electron cyclotron emission (ECE) on the experimental advanced superconducting tokamak (EAST). This system collects X-mode ECE radiation spanning a frequency range of 104–168 GHz, where the frequency coverage corresponds to a full radial coverage for the case with a toroidal magnetic field of 2.3 T. The frequency range is equally spaced every 2 GHz from 105.1 to 167.1 GHz with an RF bandwidth of ∼500 MHz and the video bandwidth can be switched among 50, 100, 200, and 400 kHz. Design objectives and characterization of the system are presented in this paper. Preliminary results for plasma operation are also presented.

Calibration of a 32 channel electron cyclotron emission radiometer on the HL-2A tokamak

Abstract: A novel 32-channel electron cyclotron emission radiometer has been designed and tested for the measurement of electron temperature profiles on the HL-2A tokamak. This system is based on the intermediate frequency filter detection technique, and has the features of wide working frequency range and high spatial resolution. Two relative calibration methods have been investigated: sweeping the toroidal magnetic field and hopping the output frequency of the local oscillator. Preliminary results show that both methods can ensure reasonable profiles.

Validation of precipitation retrievals over land from satellite‐based passive microwave sensors

Abstract: Precipitation retrievals from spaceborne passive microwave (PMW) radiometers are the backbone of modern satellite-based global precipitation data sets. The error characteristics in these individual retrievals directly affect the merged end products and applications but have not been systematically studied. This paper focuses on extensive and systematic validation of PMW precipitation retrievals and quantification of their error characteristics. Retrievals from 12 PMW radiometers were evaluated and intercompared at instantaneous scale (5 min) over continental United States. These precipitation-sensing radiometers include both imagers (Tropical Rainfall Measuring Mission Microwave Imager, Advanced Microwave Scanning Radiometer for the Earth Observing System, Special Sensor Microwave Imager, and Special Sensor Microwave Imager/Sounder) and sounders (advanced microwave sounding unit-B and Microwave Humidity Sounders). A high-resolution ground radar-based data set over the continental United States was used as the ground reference data. The high spatial and temporal resolution of the reference data allows collocation within 5 min and relatively more precise comparison with the satellite overpasses. Our results show that PMW sensor retrievals exhibit fairly systematic biases depending on season and precipitation intensity, with overestimates in summer at moderate to high precipitation rates and underestimates in winter at low and moderate precipitation rates. Retrievals from the microwave imagers have notably better performance than those from the sounders. The latter tend to have a narrower dynamic range, higher biases, and random errors.

Evaluation of wet troposphere path delays from atmospheric reanalyses and radiometers and their impact on the altimeter sea level

Abstract: . The assessment of long-term errors in altimeter sea level measurements is essential for studies related to the mean sea level (MSL) evolution. One of the main contributors to the long-term sea level uncertainties is the correction of the altimeter range from the wet troposphere path delay, which is provided by onboard microwave radiometers for the main altimeter missions. The wet troposphere correction (WTC) derived from the operational European Centre for Medium-Range Weather Forecast (ECMWF) atmospheric model is usually used as a reference for comparison with the radiometer WTC. However, due to several improvements in the processing, this model is not homogenous over the altimetry period (from 1993 onwards), preventing the detection of errors in the radiometer WTC, especially in the first altimetry decade. In this study, we determine the quality of WTC provided by the operational ECMWF atmospheric model in comparison with the fields derived from the ERA-Interim (ECMWF) and the National Centers for Environmental Predictions/National Center for Atmospheric Research (NCEP/NCAR) reanalyses. Separating our analyses on several temporal and spatial scales, we demonstrate that ERA-Interim provides the best modeled WTC for the altimeter sea level at climate scales. This allows us to better evaluate the radiometer WTC errors, especially for the first altimetry decade (1993–2002), and thus to improve the altimeter MSL error budget. This work also demonstrates the relevance of the interactions between the "altimetry" and "atmosphere" communities, since the expertise of each is of benefit to the other.

Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data

Abstract: For the soil moisture retrieval from passive microwave sensors, such as ESA’s Soil Moisture and Ocean Salinity (SMOS) and the NASA Soil Moisture Active and Passive (SMAP) mission, a good knowledge about the vegetation characteristics is indispensable. Vegetation cover is a principal factor in the attenuation, scattering and absorption of the microwave emissions from the soil; and has a direct impact on the brightness temperature by way of its canopy emissions. Here, brightness temperatures were measured at three altitudes across the TERENO (Terrestrial Environmental Observatories) Rur catchment site in Germany to achieve a range of spatial resolutions using the airborne Polarimetric L-band Multibeam Radiometer 2 (PLMR2). The L-band Microwave Emission of the Biosphere (L-MEB) model which simulates microwave emissions from the soil–vegetation layer at L-band was used to retrieve surface soil moisture for all resolutions. A Monte Carlo approach was developed to simultaneously estimate soil moisture and the vegetation parameter b ’ describing the relationship between the optical thickness τ and the Leaf Area Index (LAI). LAI was retrieved from multispectral RapidEye imagery and the plant specific vegetation parameter b ′ was estimated from the lowest flight altitude data for crop, grass, coniferous forest, and deciduous forest. Mean values of b’ were found to be 0.18, 0.07, 0.26 and 0.23, respectively. By assigning the estimated b ′ to higher flight altitude data sets, a high accuracy soil moisture retrieval was achieved with a Root Mean Square Difference (RMSD) of 0.035 m 3 m −3 when compared to ground-based measurements.

On the Spatial Resolution Enhancement of Microwave Radiometer Data in Banach Spaces

Abstract: A reconstruction technique, mathematically based on a generalization of the gradient method in Banach spaces, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. This approach allows reducing the over-smoothing effects and the oscillations that are often present in standard Hilbert-spaces procedures without any drawback on the numerical complexity. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the accuracy and the effectiveness of the proposed technique. A typical radiometer scene is processed in few minutes by a standard PC processor. Furthermore, since the proposed approach is iterative, the processing time increases slowly with the problem's size.

Baltic Sea Ice Concentration Estimation Based on C-Band Dual-Polarized SAR Data

Abstract: High-resolution ice concentration information is required for navigation purposes, validating ice models, and data assimilation. The currently available operational ice concentration products are based on microwave radiometer data, and their typical resolution is several kilometers. We present an algorithm for the estimation of ice concentration based on dual-polarized (HH/HV) C-band synthetic aperture radar (SAR) data. The algorithm is based on the multilayer perceptron (MLP) neural network. Ice concentration estimated based on the HH channel is used as one MLP input, and the local incidence angle is used as another. The additional inputs are based on the HV channel. Digitized Finnish Ice Service ice charts, which were also used as the training data, the SAR-based HH-channel ice concentration, and the ice concentration based on a radiometer algorithm are used as reference data sets. The results for the dual-polarized algorithm show improvement compared to the algorithm based on HH-polarized SAR data only.

Adaptive Reduction of Striping for Improved Sea Surface Temperature Imagery fromSuomi National Polar-Orbiting Partnership(S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS)

Abstract: The Suomi National Polar-Orbiting Partnership (S-NPP) satellite was successfully launched on 28 October 2011. It carries five new-generation instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS is a whiskbroom radiometer that scans the surface of the earth using a rotating telescope assembly, a double-sided half-angle mirror, and 16 individual detectors. Substantial efforts are being made to accurately calibrate all detectors in orbit. As of this writing, VIIRS striping is reduced to levels below those seen in corresponding Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) bands and meets the program specifications and requirements. However, the level 2 SST products derived from level 1 sensor data records (SDRs) thermal emissive bands still show residual striping. These artifacts reduce the accuracy of SST measurements and adversely affect cloud masking and the output of downstream applications, such as thermal front detection. To improve the ...

Tropospheric water vapour and relative humidity profiles from lidar and microwave radiometry

Abstract: . In this paper, we outline an iterative method to calibrate the water vapour mixing ratio profiles retrieved from Raman lidar measurements. Simultaneous and co-located radiosonde data are used for this purpose and the calibration results obtained during a radiosonde campaign in summer and autumn 2011 are presented. The water vapour profiles measured during night-time by the Raman lidar and radiosondes are compared and the differences between the methodologies are discussed. Then, a new approach to obtain relative humidity profiles by combination of simultaneous profiles of temperature (retrieved from a microwave radiometer) and water vapour mixing ratio (from a Raman lidar) is addressed. In the last part of this work, a statistical analysis of water vapour mixing ratio and relative humidity profiles obtained during 1 year of simultaneous measurements is presented.

Miniaturized Laser Heterodyne Radiometer for Measurements of CO2 in the Atmospheric Column

Abstract: We have developed a low-cost, miniaturized laser heterodyne radiometer for highly sensitive measurements of carbon dioxide (CO2) in the atmospheric column. In this passive design, sunlight that has undergone absorption by CO2 in the atmosphere is collected and mixed with continuous wave laser light that is step-scanned across the absorption feature centered at 1,573.6 nm. The resulting radio frequency beat signal is collected as a function of laser wavelength, from which the total column mole fraction can be de-convolved. We are expanding this technique to include methane (CH4) and carbon monoxide (CO), and with minor modifications, this technique can be expanded to include species such as water vapor (H2O) and nitrous oxide (N2O).

Solar irradiances measured using SPN1 radiometers: uncertainties and clues for development

Abstract: . The fast development of solar radiation and energy applications, such as photovoltaic and solar thermodynamic systems, has increased the need for solar radiation measurement and monitoring, for not only the global but also the diffuse and direct components. End users look for the best compromise between getting close to state-of-the-art measurements and keeping low capital, maintenance and operating costs. Among the existing commercial options, SPN1 is a relatively low cost solar radiometer that estimates global and diffuse solar irradiances from seven thermopile sensors under a shading mask and without moving parts. This work presents a comprehensive study of SPN1 accuracy and sources of uncertainty, drawing on laboratory experiments, numerical modelling and comparison studies between measurements from this sensor and state-of-the art instruments for six diverse sites. Several clues are provided for improving the SPN1 accuracy and agreement with state-of-the art measurements.

SOVAP/Picard, a Spaceborne Radiometer to Measure the Total Solar Irradiance

Abstract: The Picard spacecraft was successfully launched on 15 June 2010, into a Sun-synchronous orbit. The mission represents one of the European contributions to solar observations and Essential Climate Variables (ECVs) measurements. The payload is composed of a Solar Diameter Imager and Surface Mapper (SODISM) and two radiometers: SOlar VAriability Picard (SOVAP) and PREcision MOnitor Sensor (PREMOS). SOVAP, a dual side-by-side cavity radiometer, measures the total solar irradiance (TSI). It is the sixth of a series of differential absolute-radiometer-type instruments developed and operated in space by the Royal Meteorological Institute of Belgium. The measurements of SOVAP in the summer of 2010 yielded a TSI value of 1362.1 W m−2 with an uncertainty of ± 2.4 W m−2 (k=1). During the periods of November 2010 and January 2013, the amplitude of the changes in TSI has been on the order of 0.18 %, corresponding to a range of about 2.4 W m−2.

Assessment and Correction of on-Orbit Radiometric Calibration for FY-3 VIRR Thermal Infrared Channels

Abstract: FengYun-3 (FY-3) Visible Infrared Radiometer (VIRR), along with its predecessor, Multispectral Visible Infrared Scanning Radiometer (MVISR), onboard FY-1C&D have had continuous global observation more than 14 years. This data record is valuable for weather prediction, climate monitoring, and environment research. Data quality is vital for satellite data assimilations in Numerical Weather Prediction (NWP) and quantitative remote sensing applications. In this paper, the accuracies of radiometric calibration for VIRR onboard FY-3A and FY-3B, in thermal infrared (TIR) channels, are evaluated using the Low Earth Orbit (LEO)-LEO simultaneous nadir overpass intercalibration method. Hyperspectral and high-quality observations from Infrared Atmosphere Sounding Instrument (IASI) onboard METOP-A are used as reference. The biases of VIRR measurements with respect to IASI over one-and-a-half years indicate that the TIR calibration accuracy of FY-3B VIRR is better than that of FY-3A VIRR. The brightness temperature (BT) measured by FY-3A/VIRR is cooler than that measured by IASI with monthly mean biases ranging from −2 K to −1 K for channel 4 and −1 K to 0.2 K for channel 5. Measurements from FY-3B/VIRR are more consistent with that from IASI, and the annual mean biases are 0.84 ± 0.16 K and −0.66 ± 0.18 K for channels 4 and 5, respectively. The BT biases of FY-3A/VIRR show scene temperature-dependence and seasonal variation, which are not found from FY-3B/VIRR BT biases. The temperature-dependent biases are shown to be attributed to the nonlinearity of detectors. New nonlinear correction coefficients of FY-3A/VIRR TIR channels are reevaluated using various collocation samples. Verification results indicate that the use of the new nonlinear correction can greatly correct the scene temperature-dependent and systematic biases.

A sea ice concentration estimation algorithm utilizing radiometer and SAR data

Abstract: We have studied the possibility of combining the high-resolution synthetic aperture radar (SAR) segmentation and ice concentration estimated by radiometer brightness temperatures. Here we present an algorithm for mapping a radiometer-based concentration value for each SAR segment. The concentrations are estimated by a multi-layer perceptron (MLP) neural network which has the AMSR-2 (Advanced Microwave Scanning Radiometer 2) polarization ratios and gradient ratios of four radiometer channels as its inputs. The results have been compared numerically to the gridded Finnish Meteorological Institute (FMI) ice chart concentrations and high-resolution AMSR-2 ASI (ARTIST Sea Ice) algorithm concentrations provided by the University of Hamburg and also visually to the AMSR-2 bootstrap algorithm concentrations, which are given in much coarser resolution. The differences when compared to FMI daily ice charts were on average small. When compared to ASI ice concentrations, the differences were a bit larger, but still small on average. According to our comparisons, the largest differences typically occur near the ice edge and sea–land boundary. The main advantage of combining radiometer-based ice concentration estimation and SAR segmentation seems to be a more precise estimation of the boundaries of different ice concentration zones.

Measurement and Modeling of Particle Radiation in Coal Flames

Abstract: This work aims at developing a methodology that can provide information of in-flame particle radiation in industrial-scale flames. The method is based on a combination of experimental and modeling work. The experiments have been performed in the high-temperature zone of a 77 kWth swirling lignite flame. Spectral radiation, total radiative intensity, gas temperature, and gas composition were measured, and the radiative intensity in the furnace was modeled with an axisymmetric cylindrical radiation model using Mie theory for the particle properties and a statistical narrow-band model for the gas properties. The in-flame particle radiation was measured with a Fourier transform infrared (FTIR) spectrometer connected to a water-cooled probe via fiber optics. In the cross-section of the flame investigated, the particles were found to be the dominating source of radiation. Apart from giving information about particle radiation and temperature, the methodology can also provide estimates of the amount of soot radiation and the maximum contribution from soot radiation compared to the total particle radiation. In the center position in the flame, the maximum contribution from soot radiation was estimated to be less than 40% of the particle radiation. As a validation of the methodology, the modeled total radiative intensity was compared to the total intensity measured with a narrow angle radiometer and the agreement in the results was good, supporting the validity of the used approach.

The Solar Irradiance Spectrum at Solar Activity Minimum Between Solar Cycles 23 and 24

Abstract: On 7 February 2008, the SOLAR payload was placed onboard the International Space Station. It is composed of three instruments, two spectrometers and a radiometer. The two spectrometers allow us to cover the 16 – 2900 nm spectral range. In this article, we first briefly present the instrumentation, its calibration and its performance in orbit. Second, the solar spectrum measured during the transition between Solar Cycles 23 to 24 at the time of the minimum is shown and compared with other data sets. Its accuracy is estimated as a function of wavelength and the solar atmosphere brightness-temperature is calculated and compared with those derived from two theoretical models.

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

Abstract: Uncertainties in the retrievals of microwave land-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.