Showing papers on "Radiometer published in 2017"

A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data

Abstract: . Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7 m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias.

SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit

Abstract: The Soil Moisture Active–Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4% volumetric accuracy at 40-km spatial resolution. SMAP is NASA’s first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of the radiometer include a large 6-m rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate that the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEDT 1 MHz and 1/f noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate that the instrument is operating as expected.

Comprehensive Study of Optical, Physical, Chemical, and Radiative Properties of Total Columnar Atmospheric Aerosols over China: An Overview of Sun-Sky Radiometer Observation Network (SONET) Measurements

Abstract: An overview of Sun–Sky Radiometer Observation Network (SONET) measurements in China is presented. Based on observations at 16 distributed SONET sites in China, atmospheric aerosol parameters are acquired via standardization processes of operational measurement, maintenance, calibration, inversion, and quality control implemented since 2010. A climatology study is performed focusing on total columnar atmospheric aerosol characteristics, including optical (aerosol optical depth, AngstrOm exponent, fine-mode fraction, single-scattering albedo), physical (volume particle size distribution), chemical composition (black carbon; brown carbon; fine-mode scattering component, coarse-mode component; and aerosol water), and radiative properties (aerosol radiative forcing and efficiency). Data analyses show that aerosol optical depth is low in the west but high in the east of China. Aerosol composition also shows significant spatial and temporal variations, leading to noticeable diversities in optical and phy...

A global satellite environmental data record derived from AMSR-E and AMSR2 microwave Earth observations

Abstract: . Spaceborne microwave remote sensing is widely used to monitor global environmental changes for understanding hydrological, ecological, and climate processes. A new global land parameter data record (LPDR) was generated using similar calibrated, multifrequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2). The resulting LPDR provides a long-term (June 2002–December 2015) global record of key environmental observations at a 25 km grid cell resolution, including surface fractional open water (FW) cover, atmosphere precipitable water vapor (PWV), daily maximum and minimum surface air temperatures (Tmx and Tmn), vegetation optical depth (VOD), and surface volumetric soil moisture (VSM). Global mapping of the land parameter climatology means and seasonal variability over the full-year records from AMSR-E (2003–2010) and AMSR2 (2013–2015) observation periods is consistent with characteristic global climate and vegetation patterns. Quantitative comparisons with independent observations indicated favorable LPDR performance for FW (R ≥ 0.75; RMSE ≤ 0.06), PWV (R ≥ 0.91; RMSE ≤ 4.94 mm), Tmx and Tmn (R ≥ 0.90; RMSE ≤ 3.48 °C), and VSM (0.63 ≤ R ≤ 0.84; bias-corrected RMSE ≤ 0.06 cm3 cm−3). The LPDR-derived global VOD record is also proportional to satellite-observed NDVI (GIMMS3g) seasonality (R ≥ 0.88) due to the synergy between canopy biomass structure and photosynthetic greenness. Statistical analysis shows overall LPDR consistency but with small biases between AMSR-E and AMSR2 retrievals that should be considered when evaluating long-term environmental trends. The resulting LPDR and potential updates from continuing AMSR2 operations provide for effective global monitoring of environmental parameters related to vegetation activity, terrestrial water storage, and mobility and are suitable for climate and ecosystem studies. The LPDR dataset is publicly available at http://files.ntsg.umt.edu/data/LPDR_v2/ .

Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates.

Abstract: SMAP (Soil Moisture Active and Passive) radiometer observations at ∼40km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9-km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatio-temporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9-km surface and root-zone soil moisture simulations with in situ measurements from 9-km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations.

Capability of the SMAP Mission to Measure Ocean Surface Winds in Storms

Abstract: The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission was launched in January 2015 and has been providing science data since April 2015. Though designed to measure soil moisture, the SMAP radiometer has an excellent capability to measure ocean winds in storms at a resolution of 40 km with a swath width of 1,000 km. SMAP radiometer channels operate at a very low microwave frequency (L band, 1.41 GHz, 21.4 cm), which has good sensitivity to ocean surface wind speed even in very high winds and with very little impact by rain. This gives SMAP a distinct advantage over many spaceborne ocean wind sensors such as C-band [Advanced Scatterometer (ASCAT)] or Ku-band [Rapid Scatterometer (RapidScat)] scatterometers and radiometers operating at higher frequencies [Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), WindSat, Advanced Microwave Scanning Radiometer (AMSR), and Global Precipitation Measurement (...

First Results on the Epoch of Reionization from First Light with SARAS 2

Abstract: Long-wavelength spectral distortions in the cosmic microwave background arising from the 21 cm transition in neutral hydrogen are a key probe of the Cosmic Dawn and the Epoch of Reionization. These features may reveal the nature of the first stars and ultra-faint galaxies that transformed the spin temperature and ionization state of the primordial gas. SARAS. 2 is a spectral radiometer purposely designed for the precision measurement of these monopole or all-sky global 21 cm spectral distortions. We use 63. hr nighttime observations of the radio background in the frequency band 110-200. MHz, with the radiometer deployed at the Timbaktu Collective in Southern India, to derive likelihoods for plausible redshifted 21 cm signals predicted by theoretical models. First light with SARAS 2 disfavors the class of models that feature weak X-ray heating (with f(X) = 120 mK per unit redshift interval).

A cloud detection algorithm-generating method for remote sensing data at visible to short-wave infrared wavelengths

Abstract: To realize highly precise and automatic cloud detection from multi-sensors, this paper proposes a cloud detection algorithm-generating (CDAG) method for remote sensing data from visible to short-wave infrared (SWIR) bands. Hyperspectral remote sensing data with high spatial resolution were collected and used as a pixel dataset of cloudy and clear skies. In this paper, multi-temporal AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data with 224 bands at visible to SWIR wavelengths and a 20 m spatial resolution were used for the dataset. Based on the pixel dataset, pixels of different types of clouds and land cover were distinguished artificially and used for the simulation of multispectral sensors. Cloud detection algorithms for the multispectral remote sensing sensors were then generated based on the spectral differences between the cloudy and clear-sky pixels distinguished previously. The possibility of assigning a pixel as cloudy was calculated based on the reliability of each method. Landsat 8 OLI (Operational Land Imager), MODIS (Moderate Resolution Imaging Spectroradiometer) Terra and Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer) were used for the cloud detection test with the CDAG method, and the results from each sensor were compared with the corresponding artificial results, demonstrating an accurate detection rate of more than 85%.

Calibration and Cross Validation of a Global Wind and Wave Database of Altimeter, Radiometer, and Scatterometer Measurements

Abstract: A combined satellite dataset consisting of nine altimeter, 12 radiometer, and two scatterometer missions of wind speed and wave height is calibrated in a consistent manner against NDBC data and independently validated against a separate buoy dataset. The data are investigated for stability as a function of time. Instances where there are discontinuities or drift in the data are identified and accounted for in the calibration. The performance of each of the instruments at extreme values is investigated using quantile–quantile comparisons with buoy data. The various instruments are cross validated at matchup locations where satellite ground tracks cross. The resulting calibrated and cross-validated dataset is believed to represent the largest global oceanographic dataset of its type, which includes multiple instrument types calibrated in a similar fashion.

The MASCOT Radiometer MARA for the Hayabusa 2 Mission

Abstract: The MASCOT radiometer MARA is a multi-spectral instrument which measures net radiative flux in six wavelength bands. MARA uses thermopile sensors as sensing elements, and the net flux between the instrument and the surface in the $18^{\circ }$ field of view is determined by evaluating the thermoelectric potential between the sensors’ absorbing surface and the thermopile’s cold-junction. MARA houses 4 bandpass channels in the spectral range of 5.5–7, 8–9.5, 9.5–11.5, and 13.5–15.5 μm, as well as one long-pass channel, which is sensitive in the $>3~\upmu \mbox{m}$ range. In addition, one channel is similar to that used by the Hayabusa 2 orbiter thermal mapper, which uses a wavelength range of 8–12 μm. The primary science objective of the MARA instrument it the determination of the target asteroid’s surface brightness temperature, from which surface thermal inertia can be derived. In addition, the spectral bandpass channels will be used to estimate the spectral slope of the surface in the thermal infrared wavelength range. The instrument has been calibrated using a cavity blackbody, and the temperature uncertainty is 1 K in the long pass channel for target temperatures of $>173~\mbox{K}$ . Measurement uncertainty in the spectral bandpasses is 1 K for target temperatures above 273 K.

Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates

Abstract: SMAP (Soil Moisture Active and Passive) radiometer observations at ∼40km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9-km SMAP Level-4 Soil Moisture product This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatio-temporal accuracy of soil moisture estimates Radar observations were assimilated either separately from or simultaneously with radiometer observations Assimilation impact was assessed by comparing 3-hourly, 9-km surface and root-zone soil moisture simulations with in situ measurements from 9-km SMAP core validation sites and sparse networks, from May 2015 to December 2016 The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral Relatively larger improvements were obtained from SMAP assimilation The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations

A Time-Series Approach to Estimating Soil Moisture From Vegetated Surfaces Using L-Band Radar Backscatter

Abstract: Many previous studies have shown the sensitivity of radar backscatter to surface soil moisture content, particularly at L-band. Moreover, the estimation of soil moisture from radar for bare soil surfaces is well-documented, but estimation underneath a vegetation canopy remains unsolved. Vegetation significantly increases the complexity of modeling the electromagnetic scattering in the observed scene, and can even obstruct the contributions from the underlying soil surface. Existing approaches to estimating soil moisture under vegetation using radar typically rely on a forward model to describe the backscattered signal and often require that the vegetation characteristics of the observed scene be provided by an ancillary data source. However, such information may not be reliable or available during the radar overpass of the observed scene (e.g., due to cloud coverage if derived from an optical sensor). Thus, the approach described herein is an extension of a change-detection method for soil moisture estimation, which does not require ancillary vegetation information, nor does it make use of a complicated forward scattering model. Novel modifications to the original algorithm include extension to multiple polarizations and a new technique for bounding the radar-derived soil moisture product using radiometer-based soil moisture estimates. Soil moisture estimates are generated using data from the Soil Moisture Active/Passive (SMAP) satellite-borne radar and radiometer data, and are compared with up-scaled data from a selection of in situ networks used in SMAP validation activities. These results show that the new algorithm can consistently achieve rms errors less than 0.07 m3/m3 over a variety land cover types.

Baltic Sea Ice Concentration Estimation Using SENTINEL-1 SAR and AMSR2 Microwave Radiometer Data

Abstract: Sea ice concentration (SIC) is an important sea ice parameter for sea ice navigation, environmental research, and weather and ice forecasting. We have developed and tested a method for estimation of the Baltic Sea SIC using SENTINEL-1 synthetic aperture radar (SAR) and Advanced Microwave Scanning Radiometer 2 passive microwave radiometer (MWR) data. Here, we present the method and results for January 2016. Ice concentration grids of Finnish Meteorological Institute daily ice charts have been used as reference data in this paper. We present a comparison of four SIC estimation methods with our reference data. In addition to the combined SAR/MWR SIC estimation method, we also compare SIC estimates produced using SAR alone and two MWR-based methods. The main target of this paper was to develop and test a high-resolution SIC estimation method suitable for operational use.

SARAS 2 constraints on global 21-cm signals from the Epoch of Reionization

Abstract: Spectral distortions in the cosmic microwave background over the 40--200~MHz band are imprinted by neutral hydrogen in the intergalactic medium prior to the end of reionization. This signal, produced in the redshift range $z = 6-34$ at the rest frame wavelength of 21 cm, has not been detected yet; and poor understanding of high redshift astrophysics results in a large uncertainty in the expected spectrum. The SARAS~2 radiometer was purposely designed to detect the sky-averaged 21-cm signal. The instrument, deployed at the Timbaktu Collective (Southern India) in April--June 2017, collected 63~hr of science data, which were examined for the presence of the cosmological 21-cm signal. In our previous work the first-light data from SARAS~2 radiometer were analyzed with Bayesian likelihood-ratio tests using $264$ plausible astrophysical scenarios. In this paper we re-examine the data using an improved analysis based on the frequentist approach and forward modeling. We show that SARAS~2 data rejects 27 models, out of which 25 are rejected at a significance $>5\sigma$. All the rejected models share the scenario of inefficient heating of the primordial gas by the first population of X-ray sources along with rapid reionization.

The assimilation of Cross-track Infrared Sounder radiances at ECMWF

Abstract: Cross-track Infrared Sounder (CrIS) is a Michelson interferometer providing radiance data on 1,305 channels in the wavenumber range 650–2550 cm. CrIS was launched into an afternoon orbit in October 2011 and it shares the Suomi-NPP satellite platform with the Advanced Technology Microwave Sounder (ATMS), Visible Infrared Radiometer Suite (VIIRS), and Ozone Mapping and Profiler Suite (OMPS). CrIS samples the infrared spectrum in three distinct bands with nominal spectral resolutions 0.625, 1.25, and 2.5 cm in long-wave, mid-wave, and short-wave bands, respectively, The field-of-view (FOV) diameter is 13.5 km in nadir and global coverage is produced every 12 hours. We aim at operational assimilation of CrIS radiances in the global Numerical Weather Prediction (NWP) system of the European Centre for Medium-range Weather Forecasts (ECMWF). Past experience gathered from experimental and operational assimilation of hyper-spectral radiances, including those from the Atmospheric Infrared Sounder (AIRS; McNally et al. (2006)) and Infrared Atmospheric Sounding Interferometer (IASI; Collard and McNally (2009)), is applied as far as possible: in experiments carried out so far, the assimilation of CrIS radiances is restricted to cloud-free channels over sea and sea ice, and the emphasis is put on efficient use of temperature sounding channels in the 15μm CO2 absorption band. In contrast to the operational assimilation of AIRS and IASI radiances, however, we deploy an aggressive approach by assimilating a large number of channels that are adjacent to each other in the observed infrared spectrum. Together with a relatively aggressive specification of observation error standard deviation this is hoped to compensate for the effect of poorer spectral resolution of CrIS instrument. A non-diagonal observation error covariance matrix is applied to account for the effect of the signal apodization. This paper is structured as follows: we start by discussing the trade-off between instrument noise and spectral resolution in Section 2. Section 3 documents the baseline assimilation system that has produced a good impact on forecast system performance in recent experiments run using a slightly out-of-date version of the Integrated Forecasting System (IFS) at ECMWF. Section 4 describes further improvements to the assimilation system and results from experiments using the currently-operational version of the IFS. Planned future experiments are discussed in Section 5.

The Camera of the MASCOT Asteroid Lander on Board Hayabusa 2

Abstract: The MASCOT Camera (MasCam) is part of the Mobile Asteroid Surface Scout (MASCOT) lander’s science payload. MASCOT has been launched to asteroid (162173) Ryugu onboard JAXA’s Hayabusa 2 asteroid sample return mission on Dec 3rd, 2014. It is scheduled to arrive at Ryugu in 2018, and return samples to Earth by 2020. MasCam was designed and built by DLR’s Institute of Planetary Research, together with Airbus-DS Germany. The scientific goals of the MasCam investigation are to provide ground truth for the orbiter’s remote sensing observations, provide context for measurements by the other lander instruments (radiometer, spectrometer and magnetometer), the orbiter sampling experiment, and characterize the geological context, compositional variations and physical properties of the surface (e.g. rock and regolith particle size distributions). During daytime, clear filter images will be acquired. During night, illumination of the dark surface is performed by an LED array, equipped with $4\times36$ monochromatic light-emitting diodes (LEDs) working in four spectral bands. Color imaging will allow the identification of spectrally distinct surface units. Continued imaging during the surface mission phase and the acquisition of image series at different sun angles over the course of an asteroid day will contribute to the physical characterization of the surface and also allow the investigation of time-dependent processes and to determine the photometric properties of the regolith. The MasCam observations, combined with the MASCOT hyperspectral microscope (MMEGA) and radiometer (MARA) thermal observations, will cover a wide range of observational scales and serve as a strong tie point between Hayabusa 2’s remote-sensing scales ( $10^{3}$ – $10^{-3}\mbox{ m}$ ) and sample scales ( $10^{-3}$ – $10^{-6}\mbox{ m}$ ). The descent sequence and the close-up images will reveal the surface features over a broad range of scales, allowing an assessment of the surface’s diversity and close the gap between the orbital observations and those made by the in-situ measurements. The MasCam is mounted inside the lander slightly tilted, such that the center of its 54.8° square field-of-view is directed towards the surface at an angle of 22° with respect to the surface plane. This is to ensure that both the surface close to the lander and the horizon are observable. The camera optics is designed according to the Scheimpflug principle, thus that the entire scene along the camera’s depth of field (150 mm to infinity) is in focus. The camera utilizes a $1024\times1024$ pixel CMOS sensor sensitive in the 400–1000 nm wavelength range, peaking at 600–700 nm. Together with the f-16 optics, this yields a nominal ground resolution of 150 micron/px at 150 mm distance (diffraction limited). The camera flight model has undergone standard radiometric and geometric calibration both at the component and system (lander) level. MasCam relies on the use of wavelet compression to maximize data return within stringent mission downlink limits. All calibration and flight data products will be generated and archived in the Planetary Data System in PDS image format.

Sea-surface emissivity parametrization from microwaves to millimetre waves

Abstract: In preparation for new observations on board the next generation of the European operational meteorological satellite (EUMETSAT Polar System—Second Generation (EPS-SG)), a parametrization of the sea-surface emissivity is proposed from 10–700 GHz: Tool to Estimate Sea-Surface Emissivity from Microwaves to sub-Millimeter waves (TESSEM2). It is based on the community model FAST microwave Emissivity Model (FASTEM) at frequencies up to 200 GHz, where FASTEM has been calibrated and validated operationally. It follows a physical emissivity model at higher frequencies. A preliminary evaluation of TESSEM2 has been conducted with success, by comparison with airborne International Sub-Millimetre Airborne Radiometer (ISMAR) observations from 118–325 GHz, under low wind speed (3–5 m s−1) off the coast of Scotland. TESSEM2 is a fast parametrization that can easily be implemented in a community radiative transfer model. The code is available to the community and will be distributed with the next version of Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV).

Results from the Fourth WMO Filter Radiometer Comparison for aerosol optical depth measurements

Abstract: . This study presents the results of the Fourth Filter Radiometer Comparison that was held in Davos, Switzerland, between 28 September and 16 October 2015. Thirty filter radiometers and spectroradiometers from 12 countries participated including reference instruments from global aerosol networks. The absolute differences of all instruments compared to the reference have been based on the World Meteorological Organization (WMO) criterion defined as follows: 95% of the measured data has to be within 0.005 ± 0.001∕m (where m is the air mass). At least 24 out of 29 instruments achieved this goal at both 500 and 865 nm, while 12 out of 17 and 13 out of 21 achieved this at 368 and 412 nm, respectively. While searching for sources of differences among different instruments, it was found that all individual differences linked to Rayleigh, NO2, ozone, water vapor calculations and related optical depths and air mass calculations were smaller than 0.01 in aerosol optical depth (AOD) at 500 and 865 nm. Different cloud-detecting algorithms used have been compared. Angstrom exponent calculations showed relatively large differences among different instruments, partly because of the high calculation uncertainty of this parameter in low AOD conditions. The overall low deviations of these AOD results and the high accuracy of reference aerosol network instruments demonstrated a promising framework to achieve homogeneity, compatibility and harmonization among the different spectral AOD networks in the near future.

Knudsen pump inspired by Crookes radiometer with a specular wall

Abstract: A rarefied gas is considered in a channel consisting of two infinite parallel plates between which an evenly spaced array of smaller plates is arranged normal to the channel direction. Each of these smaller plates is assumed to possess one ideally specularly reflective and one ideally diffusively reflective side. When the temperature of the small plates differs from the temperature of the sidewalls of the channel, these boundary conditions result in a temperature profile around the edges of each small plate which breaks the reflection symmetry along the channel direction. This in turn results in a force on each plate and a net gas flow along the channel. The situation is analysed numerically using the direct simulation Monte Carlo (DSMC) method and compared with analytical results where available. The influence of the ideally specularly reflective wall is assessed by comparing with simulations using a finite accommodation coefficient at the corresponding wall. The configuration bears some similarity with a Crookes radiometer, where a non-symmetric temperature profile at the radiometer vanes is generated by different temperatures on each side of the vane, resulting in a motion of the rotor. The described principle may find applications in pumping gas on small scales driven by temperature gradients.

Arctic Radiation-IceBridge Sea and Ice Experiment: The Arctic Radiant Energy System during the Critical Seasonal Ice Transition

Abstract: The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties during the critical late summer to autumn sea ice minimum and commencement of refreezing The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014 ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began The most c

Retrieval of Sun Brightness Temperature and Precipitating Cloud Extinction Using Ground-Based Sun-Tracking Microwave Radiometry

Abstract: Sun-tracking (ST) microwave radiometry is a technique where the Sun is used as a microwave signal source and it is here rigorously summarized. The antenna noise temperature of a ground-based microwave radiometer is measured by alternately pointing toward-the-Sun and off-the-Sun while tracking it along its diurnal ecliptic. During clear sky the brightness temperature of the Sun disk emission at K and Ka band and in the unexplored millimeter-wave frequency region at V and W band can be estimated by adopting different techniques. Using a unique dataset collected during 2015 through a ST multifrequency radiometer, the Sun brightness temperature shows a decreasing behavior with frequency with values from about 9000 K at K band down to about 6600 K at W band. In the presence of precipitating clouds the ST technique can also provide an accurate estimate of the atmospheric extinction up to about 32 dB at W band with the current radiometric system. Parametric prediction models for retrieving all-weather atmospheric extinction from ground-based microwave radiometers are then tested and their accuracy evaluated.

Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data

Abstract: The Soil Moisture Active Passive (SMAP) satellite makes coincident global measurements of soil moisture using an L-band radar instrument and an L-band radiometer. It is crucial to evaluate the errors in the newest L-band SMAP satellite-derived soil moisture products, before they are routinely used in scientific research and applications. This study represents the first evaluation of the SMAP radiometer soil moisture product over China. In this paper, a preliminary evaluation was performed using sparse in situ measurements from 655 China Meteorological Administration (CMA) monitoring stations between 1 April 2015 and 31 August 2016. The SMAP radiometer-derived soil moisture product was evaluated against two schemes of original soil moisture and the soil moisture anomaly in different geographical zones and land cover types. Four performance metrics, i.e., bias, root mean square error (RMSE), unbiased root mean square error (ubRMSE), and the correlation coefficient (R), were used in the accuracy evaluation. The results indicated that the SMAP radiometer-derived soil moisture product agreed relatively well with the in situ measurements, with ubRMSE values of 0.058 cm3·cm−3 and 0.039 cm3·cm−3 based on original data and anomaly data, respectively. The values of the SMAP radiometer-based soil moisture product were overestimated in wet areas, especially in the Southwest China, South China, Southeast China, East China, and Central China zones. The accuracies over croplands and in Northeast China were the worst. Soil moisture, surface roughness, and vegetation are crucial factors contributing to the error in the soil moisture product. Moreover, radio frequency interference contributes to the overestimation over the northern portion of the East China zone. This study provides guidelines for the application of the SMAP-derived soil moisture product in China and acts as a reference for improving the retrieval algorithm.