Earth Incidence Angle Research Articles

Influences of Earth Incidence Angle on FY-3/MWRI SST Retrieval and Evaluation of Reprocessed SST

Influences of Earth Incidence Angle on FY-3/MWRI SST Retrieval and Evaluation of Reprocessed SST

Angular-Dependent Polarized Characteristics of Surface Emissivity at 150 GHz Over Saharan and Taklimakan Deserts

This study characterizes the marginally-known angular-dependent polarization difference of the land surface emissivity (LSE), using the microwave humidity sounder (MWHS) onboard China’s sun-synchronous satellite FengYun-3B (FY-3B). The instrument has two quasi-polarization channels at 150 GHz in addition to the three water-vapor absorption channels in the vicinity of 183 GHz, allowing observations at quasi vertical and horizontal polarizations with its cross-track scanning geometry. The Saharan and Taklimakan deserts are taken as examples due to the relatively homogeneous surface conditions. In the two 150 GHz channels of MWHS, the polarization bias is corrected according to the measurements at the Earth incidence angle (EIA) of 0°. The monthly-mean quasi-polarization difference (QPD) at 150 GHz is found to be varying with the EIA and exhibits seasonal variations over deserts. The QPD reaches a maximum value at the EIA of ~35°, while the zero value appears near the EIA of ~53° (equal to the satellite viewing angle of 45°) as expected. In contrast to the relatively stable and low QPD over Sahara, the QPD, quasi polarized emissivity difference and pure polarized emissivity difference are generally larger in the Taklimakan Desert, where the maximum monthly QPD is ~4 K and the polarized emissivity difference increases monotonously to ~0.2 at the EIA of 50°. The complex surface parameters and temporal variabilities impinge on the uncertainties of the land polarization. The increasing soil moisture due to precipitation damps the dichroic ability of the land surface, while the frozen surface due to snowfalls in cold seasons enhances the polarization.

Special Sensor Microwave Imager/Sounder Updates for the Global Precipitation Measurement V07 Data Suite

Observations from the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the Defense Meteorological Satellite Program F16, F17, F18, and F19 spacecrafts provide a significant portion of the microwave radiometer data within the Global Precipitation Measurement (GPM) mission constellation. In preparation for the GPM Version 7 (V07) data release, SSMIS corrections developed over a decade ago and incorporated in GPM Version 5 (V05) are reexamined and updated. The calibration updates presented here include pointing parameters affecting geolocation and viewing geometry, along-scan bias adjustments to account for scan edge falloffs and sun angle corrections to account for heating anomalies including an emissive reflector. To address errors in the V05 geolocation, the sensor roll, pitch, yaw, half cone angle, and timing offsets are reanalyzed and updated. The along-scan bias adjustment is updated in a manner consistent with recent Special Sensor Microwave Imager updates to account for variations in scene temperature. Finally, significant improvements to the SSMIS sun angle correction are made by using data from the entire mission, extending the corrections to include the higher frequency channels, and deriving a more consistent channel-to-channel correction. From V05 to V07, the geolocation adjustment is approximately 5–10 km, the earth incidence angle difference is 0–0.4°, and the average brightness temperature change is 0–2 K, but individual pixels may be up to several kelvin difference depending on sensor and channel. The result of these updates is a significant improvement in the quality and long-term consistency of the SSMIS data that are included in the GPM V07 dataset.

Ku- and Ka-Band Ocean Surface Radar Backscatter Model Functions at Low-Incidence Angles Using Full-Swath GPM DPR Data

This paper presents the results of the first characterization of coincident Ku- and Ka-band ocean surface normalized radar cross section measurements at earth incidence angles 0°–18° using one year of wide swath Global Precipitation Measurement (GPM) mission dual frequency precipitation radar (DPR) data. Empirical geophysical model functions were derived for both bands, isotropic and directorial sensitivity were assessed, and finally, sea surface temperature (SST) dependence of radar backscatter, at both bands, were investigated. The Ka-band exhibited higher vector wind sensitivity for a low-to-moderate wind speeds regime, and the SST effects were also observed to be substantially larger at Ka-band than at Ku-band.

The MIRS Microwave Radiometer–Spectrometer as the Basis for the Convergence Space Experiment

The MIRS microwave radiometer–spectrometer is described. The instrument is being developed using a conceptual design that was the first stage of ground preparations for the Convergence Space Experiment (SE). At the next stage of SE implementation, it is planned to use the proposed technical solutions as design documentation for manufacturing test and flight prototypes. MIRS is a multi-frequency scanner and sounder intended to record the characteristic radiothermal radiation emitted by the system of the Earth’s surface and atmosphere. The set of frequencies of the received radiation is in the range of 10 to 200 GHz. The device is to be installed on the Russian Orbital Segment (ROS) of the International Space Station (ISS). Conical scanning of the Earth’s surface is done by rotating an antenna unit mounted on a fixed base. With a 1.3 s period of rotation and a constant Earth incidence angle of 53.1 deg, continuous coverage of the Earth’s surface is ensured in a swath 800 km wide with spatial resolution of 10 km for the highest-frequency channels. Nine radiometer–polarimeters laid out as a full-power radiometer are used as radiation receivers. The MIRS antenna system is an offset parabolic antenna with separated irradiators. The optimum design solutions allowing the main problems of the SE to be solved and the MIRS parameters to be maintained under operating conditions on board the ISS are chosen for the conceptual design.

Beyond the Pixel: Using Patterns and Multiscale Spatial Information to Improve the Retrieval of Precipitation from Spaceborne Passive Microwave Imagers.

The quantitative estimation of precipitation from orbiting passive microwave imagers has been performed for more than 30 years. The development of retrieval methods consists of establishing physical or statistical relationships between the brightness temperatures (TBs) measured at frequencies between 5 and 200 GHz and precipitation. Until now, these relationships have essentially been established at the "pixel" level, associating the average precipitation rate inside a predefined area (the pixel) to the collocated multispectral radiometric measurement. This approach considers each pixel as an independent realization of a process and ignores the fact that precipitation is a dynamic variable with rich multiscale spatial and temporal organization. Here we propose to look beyond the pixel values of the TBs and show that useful information for precipitation retrieval can be derived from the variations of the observed TBs in a spatial neighborhood around the pixel of interest. We also show that considering neighboring information allows us to better handle the complex observation geometry of conical-scanning microwave imagers, involving frequency-dependent beamwidths, overlapping fields of view, and large Earth incidence angles. Using spatial convolution filters, we compute "nonlocal" radiometric parameters sensitive to spatial patterns and scale-dependent structures of the TB fields, which are the "geometric signatures" of specific precipitation structures such as convective cells. We demonstrate that using nonlocal radiometric parameters to enrich the spectral information associated to each pixel allows for reduced retrieval uncertainty (reduction of 6%-11% of the mean absolute retrieval error) in a simple k-nearest neighbors retrieval scheme.

A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures

Abstract. The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) comprises inter-calibrated and homogenized brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder SSMIS radiometers. It covers the time period from October 1978 to December 2015 including all available data from the SMMR radiometer aboard Nimbus-7 and all SSM/I and SSMIS radiometers aboard the Defense Meteorological Satellite Program (DMSP) platforms. SMMR, SSM/I, and SSMIS data are used for a variety of applications, such as analyses of the hydrological cycle, remote sensing of sea ice, or as input into reanalysis projects. The improved homogenization and inter-calibration procedure ensures the long-term stability of the FCDR for climate-related applications. All available raw data records from different sources have been reprocessed to a common standard, starting with the calibration of the raw Earth counts, to ensure a completely homogenized data record. The data processing accounts for several known issues with the instruments and corrects calibration anomalies due to along-scan inhomogeneity, moonlight intrusions, sunlight intrusions, and emissive reflector. Corrections for SMMR are limited because the SMMR raw data records were not available. Furthermore, the inter-calibration model incorporates a scene dependent inter-satellite bias correction and a non-linearity correction in the instrument calibration. The data files contain all available original sensor data (SMMR: Pathfinder level 1b) and metadata to provide a completely traceable climate data record. Inter-calibration and Earth incidence angle normalization offsets are available as additional layers within the data files in order to keep this information transparent to the users. The data record is complemented with noise-equivalent temperatures (NeΔT), quality flags, surface types, and Earth incidence angles. The FCDR together with its full documentation, including evaluation results, is freely available at: https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003 (Fennig et al., 2017).

Comparison of the Sentinel-1B Synthetic Aperture Radar With Airborne Microwave Sensors in an Extra-Tropical Cyclone

In Winter 2017, the University of Massachusetts Amherst's Imaging Wind and Rain Airborne Profiler (IWRAP) was flown on a National Oceanic and Atmospheric Administration (NOAA) WP-3D Hurricane Hunter aircraft under the direction of scientists from Center for Satellite Applications and Research (STAR) at NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) over the North Atlantic ocean out of Shannon, Ireland. IWRAP is a dual-frequency, conically scanning, profiling Doppler radar initially developed by Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts Amherst that is routinely installed on the NOAA WP-3D research aircraft. The flight on February 6, 2017, targeted a region of high winds (greater than 30 m/s) that was also observed by the Sentinel-1B satellite's synthetic aperture radar. Sentinel-1B was configured to observe in extended wide swath mode in both VV- and VH-polarizations, whereas the IWRAP C-band radar was configured to measure all of VV-, VH-, and HH-polarizations. IWRAP and Sentinel-1B VV and VH normalized radar cross section (NRCS) at the same Earthincidence angle along the flight path match reasonably well during the entire flight, but some additional trends between aircraft and satellite can be observed. IWRAP VV-polarized NRCS generally match the CMOD5.h geophysical model function (GMF), suggesting errors in the Sentinel-1B processing chain.

A Passive Microwave Retrieval Algorithm with Minimal View-Angle Bias: Application to the TEMPEST-D CubeSat Mission

AbstractThe rapid development of miniaturized satellite instrument technology has created a new opportunity to deploy constellations of passive microwave (PMW) radiometers to permit retrievals of the same Earth scene with very high temporal resolution to monitor cloud evolution and processes. For such a concept to be feasible, it must be shown that it is possible to distinguish actual changes in the atmospheric state from the variability induced by making observations at different Earth incidence angles (EIAs). To this end, we present a flexible and physical optimal estimation-based algorithm designed to retrieve profiles of atmospheric water vapor, cloud liquid water path, and cloud ice water path from cross-track PMW sounders. The algorithm is able to explicitly account for the dependence of forward model errors on EIA and atmospheric regime. When the algorithm is applied to data from the Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) CubeSat mission, its retrieved products are generally in agreement with those obtained from the similar but larger Microwave Humidity Sounder instrument. More importantly, when forward model brightness temperature offsets and assumed error covariances are allowed to change with EIA and sea surface temperature, view-angle-related biases are greatly reduced. This finding is confirmed in two ways: through a comparison with reanalysis data and by making use of brief periods in early 2019 during which the TEMPEST-D spacecraft was rotated such that its scan pattern was along track, allowing dozens of separate observations of any given atmospheric feature along the satellite’s ground track.

An Optimal Estimation Retrieval Algorithm for Microwave Humidity Sounding Channels with Minimal Scan Position Bias

AbstractA flexible and physical optimal estimation-based inversion algorithm for retrieving atmospheric water vapor and cloud liquid water path from passive microwave radiometers over the global oceans is presented. The algorithm’s main strength lies in its ability to explicitly account for forward model errors that depend on the Earth incidence angle (EIA) at which a given radiometer measurement is made. Validation of total precipitable water (TPW) retrieved from Microwave Humidity Sounder (MHS) measurements against near-coincident estimates of TPW from SuomiNet GPS ground stations shows that retrieved TPW values agree closely with SuomiNet estimates, and somewhat better than values from the Microwave Integrated Retrieval System that are retrieved from the same MHS instruments. More importantly, it is found that the inclusion of appropriate forward model error assumptions, which are tailored to the EIA and sea surface temperature of the scene being considered, are able to almost entirely eliminate EIA-dependent biases in retrieved TPW. This result holds true across all satellites currently carrying an MHS instrument, despite the fact that only measurements from one satellite are used to estimate forward model errors. The consistency achieved by the retrieval algorithm across all view angles suggests that other inversion algorithms, particularly those for cross-track-scanning radiometers and potential future constellations of small satellites, would benefit from the inclusion of nuanced error assumptions that consider the effect of EIA.

A Satellite-Derived Lower-Tropospheric Atmospheric Temperature Dataset Using an Optimized Adjustment for Diurnal Effects

Abstract Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is a lower-tropospheric temperature product constructed using measurements made by the Microwave Sounding Unit channel 2 and the Advanced Microwave Sounding Unit channel 5. The temperature weighting functions for these channels peak in the middle to upper troposphere. By using a weighted average of measurements made at different Earth incidence angles, the effective weighting function can be lowered so that it peaks in the lower troposphere. Previous versions of this dataset used general circulation model output to remove the effects of drifting local measurement time on the measured temperatures. This paper presents a method to optimize these adjustments using information from the satellite measurements themselves. The new method finds a global-mean land diurnal cycle that peaks later in the afternoon, leading to improved agreement between measurements made by co-orbiting satellites. The changes result in global-scale warming [global trend (70°S–80°N, 1979–2016) = 0.174°C decade−1], ~30% larger than our previous version of the dataset [global trend (70°S–80°N, 1979–2016) = 0.134°C decade−1]. This change is primarily due to the changes in the adjustment for drifting local measurement time. The new dataset shows more warming than most similar datasets constructed from satellites or radiosonde data. However, comparisons with total column water vapor over the oceans suggest that the new dataset may not show enough warming in the tropics.

MWR Smear Effect: A Counts-Level Empirical Correction and Possible Causes

The microwave radiometer (MWR) is a Dicke radiometer on board of the Aquarius (AQ)/SAC-D satellite. It was developed by Argentine space agency, Comision Nacional De Actividades Espaciales (CONAE), and operates at 23.8 and 36.5 GHz frequencies. After MWR initially turned on, the first brightness temperature ( $\text{T}_{\text{B}}$ ) measurements were obtained, observing an anomalous recurrent effect when analyzing land/water crossings. The effect is present for all frequencies and earth incidence angles (EIAs) and results in a smearing of $\text{T}_{\text{B}}$ observations near strong contrast radiometric scenes. This paper summarizes the main features and discoveries around this anomaly leading to a general description of the problem: coupling of sequential MWR measurements. Consequently, an empirical correction algorithm is derived and validated. Also, possible causes are investigated.

Improved Geolocation and Earth Incidence Angle Information for a Fundamental Climate Data Record of the SSM/I Sensors

The long-term data record of microwave imager data from the series of six Special Sensor Microwave/Imagers (SSM/Is) on board the Defense Meteorological Satellite Program (DMSP) spacecraft has been used to produce global multidecadal time series of a number of geophysical parameters, including precipitation, total precipitable water, ocean surface wind speed, and sea ice extent. As part of an effort to produce an intercalibrated fundamental climate data record (CDR) of the brightness temperature (Tb) data from the SSM/I, an examination of geolocation errors and the subsequent impact on the view angle [or the Earth incidence angle (EIA)] is performed. Using a combination of techniques, estimates of changes in the sensor/spacecraft attitude, including deviations in roll, pitch, and yaw, have been computed for the life of each of the SSM/I sensors. Applying these corrections results in an improved pixel geolocation, but more importantly, it provides accurate estimates of the EIA across the scan and throughout each orbit. An analysis of uncertainties in the calculation of EIA shows mean errors within 0.1 °, which translates to errors in the calibration of less than 0.2 K for all channels. The availability of these precise estimates of EIA is extremely important for producing CDRs since the mean EIA decreases over time due to the decay in the DMSP orbits, which will lead to an artificial climate trend if not properly accounted for by the geophysical retrieval algorithms.

Trends and variations of ocean surface latent heat flux: Results from GSSTF2c data set

Trends and variations of Goddard Satellite‐based Surface Turbulent Fluxes (GSSTF) version 2c (GSSTF2c) latent heat flux (LHF) are examined. This version of LHF takes account of the correction in Earth incidence angle. The trend of global mean LHF for GSSTF2c is much reduced relative to GSSTF version 2b Set 1 and Set 2 for the same period 1988–2008. Temporal increase of GSSTF2c LHF in the two decades is 11.0%, in which 3.1%, 5.8%, and 2.1% are attributed to the increase in wind, the increase in sea surface saturated air humidity, and the decrease in near‐surface air humidity, respectively. The first empirical orthogonal function of LHF is a conventional El Niño Southern Oscillation (ENSO) mode. However, the trends in LHF are independent of conventional ENSO phenomena. After removing ENSO signal, the pattern of LHF trends is primarily determined by the pattern of air‐sea humidity difference trends.

The Emissivity of the Ocean Surface Between 6 and 90 GHz Over a Large Range of Wind Speeds and Earth Incidence Angles

We present a model function for the emissivity of the wind roughened ocean surface for microwave frequencies between 6 and 90 GHz. It is an update, refinement, and extension of model functions we had developed previously. The basis of our analysis are brightness temperature (TB) measurements from the spaceborne microwave radiometer WindSat and the Special Sensor Microwave/Imager, which are collocated with independent measurements of surface wind speeds and directions. This allows the determination of the emissivity model function for Earth incidence angles (EIA) around 55°. We demonstrate that an essential part in the model development is the absolute calibration of the radiometer measurements over the ocean to the computed TB of the radiative transfer model, one of whose components the emissivity model function is. We combine our results with other established measurements for lower EIA and finally obtain a model function which can be used over the whole EIA range between 0° and 65°. Results for both the isotropic, wind direction independent part as well as the four Stokes parameters of the wind direction signal are presented. Special emphasis is made on the behavior at high wind speeds between 20 and 40 m/s by conducting a comparison with data from the step frequency microwave radiometer.

Hurricane Wind Speed Measurements in Rainy Conditions Using the Airborne Hurricane Imaging Radiometer (HIRAD)

This paper describes a realistic computer simulation of airborne hurricane surveillance using the recently developed microwave remote sensor, the hurricane imaging radiometer (HIRAD). An end-to-end simulation is described of HIRAD wind speed and rain rate measurements during two hurricanes while flying on a high-altitude aircraft. This simulation addresses the particular challenge which is accurate hurricane wind speed measurements in the presence of intense rain rates. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for future hurricane flights including the NASA GRIP hurricane field program that was conducted in summer of 2010. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with two different numerical hurricane models data are made. Special emphasis is provided on the wind speed measurement error, and statistical results are presented over a broad range of wind and rain conditions over the full measurement swath (earth incidence angle).

An Improved C-Band Ocean Surface Emissivity Model at Hurricane-Force Wind Speeds Over a Wide Range of Earth Incidence Angles

An improved microwave radiometric ocean surface emissivity model has been developed to support forward radiative transfer modeling of brightness temperature and geophysical retrieval algorithms for the next-generation airborne Hurricane Imaging Radiometer instrument. This physically based C-band emissivity model extends current model capabilities to hurricane-force wind speeds over a wide range of incidence angles. It was primarily developed using brightness temperature observations during hurricanes with coincident high-quality surface-truth wind speeds, which were obtained using the airborne Stepped-Frequency Microwave Radiometer. Also, other ocean emissivity models available through the published literature and the spaceborne WindSat radiometer measurements were used.

Two Approaches for Inter-Satellite Radiometer Calibrations between TMI and WindSat

This paper presents recent progress in inter-satellite microwave radiometric cross-calibration to eliminate brightness temperature measurement biases between a pair of radiometer channels operating at slightly different frequencies and incidence angles. The motivation of this research is to develop robust analytical cross-calibration techniques for inter-calibration of various satellite radiometer instruments, with the first projected application being the multi-satellite Global Precipitation Measurement (GPM) constellation to be launched in 2013. The significance of this work is that it will allow the formation of consistent multi-decadal time series of geophysical measurements for multiple satellite microwave radiometers that are free of instrumental biases and other long-term changes in radiometric calibration, which will allow researchers to study global climate change. Descriptions are given for two independent calibration techniques: a Taylor series expansion of the oceanic brightness temperature (Tb) spectrum between dissimilar radiometer channels and a non-linear regression among multi-channel Tb measurements. In the first approach, predictions were made of Tb's at a destination frequency from Tb's of a close by source frequency by expansion of the oceanic brightness temperature spectrum in a Taylor series centered at the source frequency. The relationships between Tb's and frequencies were derived from simulations using a radiative transfer model (RTM), which accounts for the total collected emissions from the ocean surface and the atmosphere. Further, earth incidence angle differences between radiometer channels were transformed in a similar manner using the partial derivatives of Tb with incidence angle derived from RTM simulations. In the second approach, we used a prediction algorithm that relies on the correlation between radiometer Tb's at various frequencies and polarizations and which uses a regression on the Tb's and their non-linear transformations developed using an independent radiative transfer model. As a demonstration, near-simultaneous pair-wise ocean Tb comparisons are presented between the TRMM Microwave Imager (TMI), which is not sun synchronous, and the sun-synchronous polar orbiting WindSat, using oceanic Tb observations from 2003-04. The corresponding results between these two inter-satellite calibration techniques are highly correlated, and results demonstrate that fixed channel-by-channel differences, of order 1-2 K exist between TMI and WindSat. These are significant radiometric calibration differences, which can be removed prior to forming joint data sets of geophysical parameter retrievals.

Observations of tropical cyclone structure from WindSat

Passive microwave (PMW) radiometric observations of clouds from multichannel imaging sensors onboard low Earth-orbiting environmental satellites are now a vital operational dataset. The first operational passive microwave sensor was the Special Sensor Microwave/Imager onboard the Defense Meteorological Satellite Program satellites, which has been gathering hydrological data records since 1987, and continued with the Tropical Rainfall Measuring Mission (TRMM) and the Advanced Microwave Scanning Radiometer onboard Aqua. These sensors view the underlying scene with an Earth incidence angle near 53/spl deg/ and with a variable azimuthal angle, depending upon the orbit direction and scan position. The WindSat sensor onboard the Coriolis satellite, launched in January 2003, is a five-channel polarimetric PMW radiometer designed to optimize ocean surface wind vector retrievals. While it does not have 85-GHz channels, an added feature is its unique fore-aft viewing capability across a portion of its fore scan swath. This provides a view of the underlying scene from two separate azimuthal directions, which provides added information on the three-dimensional (3-D) structure of clouds and their evolution. In this paper, we compare WindSat and TRMM Precipiation Radar observations of tropical cyclones (TCs) with Monte Carlo radiative transfer simulations performed on idealized 3-D convective cloud structures. The TC 3-D structure and possible tilt in the convective cloud structure are inferred from the difference between the 37-GHz equivalent blackbody brightness temperatures (T/sub B/) from the corresponding fore and aft view observations. The information gained from this analysis is important since asymmetries in the cloud vertical and horizontal structure may be an indication of upper level wind shear, which plays a major role in influencing changes of the TC intensity.

An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures

We analyze the wind direction signal for vertically (v) and horizontally (h) polarized microwave radiation at 37 GHz, 19 GHz, and 11 GHz; and an Earth incidence angle of 53/spl deg/. We use brightness temperatures from SSM/I and TMI and wind vectors from buoys and the QUIKSCAT scatterometer. The wind vectors are space and time collocated with the radiometer measurements. Water vapor, cloud water and sea surface temperature are obtained from independent measurements and are uncorrelated with the wind direction. We find a wind direction signal that is noticeably smaller at low and moderate wind speeds than a previous analysis had indicated. We attribute the discrepancy to errors in the atmospheric parameters that were present in the data set of the earlier study. We show that the polarization combination 2v-h is almost insensitive to atmospheric changes and agrees with the earlier results. The strength of our new signals agrees well with JPL aircraft radiometer measurements. It is significantly smaller than the prediction of the two-scale sea surface emission model for low and intermediate wind speeds.