Spencer Farrar

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

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

Intercalibration of the GPM Microwave Radiometer Constellation

AbstractThe Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration difference...

An empirical correction for the MWR brightness temperature smear effect

The Microwave Radiometer (MWR), on board of the SAC-D/Aquarius satellite, is a Dicke radiometer, operating at 23.8 and 36.5 GHz that was developed by Argentine Space Agency, CoNAE. Since the first earth surface TB images, there has been an anomalous effect when observing strong contrast radiometric scenes, such as land/water crossings. This effect is present in all push-broom beams and results in a “smearing” of TB observations near high contrast areas. This paper presents the initial findings on this MWR brightness temperature anomaly that is best described as a coupling of sequential MWR feed horn measurements. In the present work, an empirical approach is used to mitigate this anomalous effect.

Advantages of Calibration Attitude Maneuvers for spaceborne microwave radiometer missions

Earth observing satellite microwave radiometers have been in use since the 1960s providing geoscientists invaluable insight into the complex interaction of the atmosphere, ocean and land in the climate of our planet. Such key instruments must be vetted of any calibration issues so as to provide the utmost accurate and stabilized dataset for scientific analysis. There are several post-launch radiometric calibration methods currently in use, and most require multiple ancillary data sets and a lengthy duration (typically one year) of on-orbit brightness temperature observations to obtain conclusive results. However, one on-orbit calibration method that can provide accurate and early results is the Calibration Attitude Maneuver (CAM), which encompasses Deep Space Calibration (DSC) and a new use of the near-Nadir Second Stokes (SS) analysis. This paper provides examples of CAMs that have aided in the calibration of the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and the Global Precipitation Measurement Microwave Imager (GMI). Excellent results obtained suggest the use of the CAM as a recommended tool for on-orbit calibration for microwave radiometers.

The Hurricane Imaging Radiometer: Present and future

The Hurricane Imaging Radiometer (HIRAD) is an airborne passive microwave radiometer designed to provide high resolution, wide swath imagery of surface wind speed in tropical cyclones from a low profile planar antenna with no mechanical scanning. Wind speed and rain rate images from HIRADs first field campaign (GRIP, 2010) are presented here followed, by a discussion on the performance of the newly installed thermal control system during the 2012 HS3 campaign. The paper ends with a discussion on the next generation dual polarization HIRAD antenna (already designed) for a future system capable of measuring wind direction as well as wind speed.

Corruption of the TRMM microwave imager cold sky mirror due to RFI

By its end of mission in 2015, the Tropical Rainfall Measuring Mission (TRMM) far exceeded its three-year design life, providing over 17 years of invaluable Earth observations. This paper details how a previously undiscovered source of calibration error for the TRMM Microwave Imager (TMI) has been recently detected and how a simple mitigation technique may be applied for correcting bogus data. The source of error is believed to be Radio Frequency Interference (RFI) from geostationary satellites transmitters that are collected by the TMI Cold Sky Reflector antenna beams as they sweep through the equatorial plane. This paper details how this source of error was discovered, its characteristics, and how to flag and correct for the upcoming TMI 1B11 Archive/Legacy Data.

GPM Microwave Imager on-orbit radiometric calbration using a satellite deep space calibration maneuver

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) is designed to be the radiometric calibration standard for a group of satellites with passive microwave instruments known as the GPM constellation. Because GMI is the transfer standard, it is crucial to vet its calibration accuracy in an extensive post-launch Calibration/Validation campaign. One important element of this campaign is a special set of satellite maneuvers known as Deep Space Calibration (DSC). During the DSC maneuver, the satellite pitch attitude is adjusted to cause the microwave instrument to view space, which is an isotropic non-polarized scene of known brightness temperature. Because of the delay in the GPM launch and the associated DSC, this paper focuses on the predecessor TRMM Microwave Imager (TMI) DSC maneuvers to gain insight into the GMI DSC results.

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, Comisión Nacional De Actividades Espaciales (CONAE), and operates at 23.8 and 36.5 GHz frequencies. After MWR initially turned on, the first brightness temperature (TB) 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 TB 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.

Hurricane wind speed and rain rate measurements using the airborne Hurricane Imaging Radiometer (HIRAD)

Microwave remote sensing of surface wind speed and rain rate in hurricanes is critical to predict their growth and movement as they develop and make landfall. The Hurricane Imaging Radiometer (HIRAD) is an experimental airborne microwave radiometer developed by NASA Marshall Space Flight Center (MSFC) to provide ocean surface wind speed and rain rate measurements in hurricanes. It is intended to expand the current NOAA and US Air Force hurricane surveillance capability, particularly by extending the operational Stepped Frequency Microwave Radiometer (SFMR) measurement to a large swath. HIRAD also has potential for space applications. This paper will describe the HIRAD instrument and its flight history, to date, and present wind speed and rain rate retrievals from observed brightness temperatures (Tbs) in a flight over Hurricane Earl in 2010 as part of NASAs GRIP mission. A comparison between HIRAD and SFMR retrievals will be shown.

Microwave Radiometer (MWR) oceanic integrated rain rate algorithm for Aquarius/SAC-D

The Microwave Radiometer (MWR) flying on the Aquarius/SAC-D mission is a Dicke radiometer operating at 23.8 and 36.5 GHz that is developed by the Argentina Space Agency CONAE. This instrument will complement Aquarius (NASAs L-band radiometer/scatterometer) by providing simultaneous spatially collocated environmental measurements such as oceanic wind speed and rain rate. This paper describes the development of the pre-launch MWR rain rate algorithm using simulated MWR brightness temperatures from actual WindSat radiometer observations. WindSat provides high spatial resolution brightness temperatures that are spatially averaged to simulate the resolution of MWR. Also WindSat provides retrieved environmental parameters (EDRs), which includes rain rate for developing the statistical regression algorithm. Examples of simulated MWR rain retrievals are presented.