David W. Draper

The Global Precipitation Measurement (GPM) Microwave Imager (GMI): Instrument Overview and Early On-Orbit Performance

The Global Precipitation Measurement (GPM) mission is an international satellite mission that uses measurements from an advanced radar/radiometer system on a core observatory as reference standards to unify and advance precipitation estimates made by a constellation of research and operational microwave sensors. The GPM core observatory was launched on February 27, 2014 at 18:37 UT in a 65° inclination nonsun-synchronous orbit. GPM focuses on precipitation as a key component of the Earths water and energy cycle, and has the capability to provide near-real-time observations for tracking severe weather events, monitoring freshwater resources, and other societal applications. The GPM microwave imager (GMI) on the core observatory provides the direct link to the constellation radiometer sensors, which fly mainly in polar orbits. The GMI sensitivity, accuracy, and stability play a crucial role in unifying the measurements from the GPM constellation of satellites. The instrument has exhibited highly stable operations through the duration of the calibration/validation period. This paper provides an overview of the GMI instrument and a report of early on-orbit commissioning activities. It discusses the on-orbit radiometric sensitivity, absolute calibration accuracy, and stability for each radiometric channel.

Assessing Calibration Stability Using the Global Precipitation Measurement (GPM) Microwave Imager (GMI) Noise Diodes

With rising demand for smaller, lower mass microwave instruments, internal calibration using noise diodes is becoming increasingly more attractive for space-borne radiometer applications. Since noise diodes can exhibit on-orbit excess temperature drift, internally calibrated systems typically require vicarious on-orbit recharacterization. The GMI is the first instrument of its kind to include both internal (noise diodes) and external (hot load/cold sky) calibration systems. The dual-calibration system provides the unprecedented capability to directly measure transient behaviors in the hot load, cold sky view, and receiver nonlinearity. Furthermore, the behavior of the noise diodes can be directly evaluated, which may shed light on improvements to internal calibration for future missions. This paper directly examines the behavior of the GMI noise diodes using the hot load and cold sky views for the first 6 months of operations. Two of the seven channels with noise diodes have exhibited on-orbit noise diode excess temperature drift of about 1 K. The other noise diodes have remained exceptionally stable. The noise diodes are used to evaluate transient behaviors in the GMI hot load, cold sky view, and nonlinearity. The hot-load brightness temperature variation due to gradients is re-evaluated and shown to be smaller at the lower frequencies than at preflight calibration. Radio frequency interference (RFI) in the cold view is evaluated using the noise diode backup calibration. The on-orbit nonlinearity is trended over the first 6 months and shown to be stable over that time period.

On-Orbit Absolute Calibration of the Global Precipitation Measurement Microwave Imager

AbstractThe Global Precipitation Measurement (GPM) Core Observatory was launched on 27 February 2014. One of the principal instruments on the spacecraft is the GPM Microwave Imager (GMI). This paper describes the absolute calibration of the GMI antenna temperature (TA) and the earth brightness temperature (TB). The deep-space observations taken on 20 May 2014, supplemented by nadir-viewing data, are used for the TA calibration. Data from two backlobe maneuvers are used to determine the primary reflector’s cold-space spillover, which is required to convert the TA into TB. The calibrated GMI observations are compared to predictions from an ocean radiative transfer model (RTM) using collocated WindSat ocean retrievals as input. The mean difference when averaged globally over 13 months does not exceed 0.1 K for any of the nine channels from 11 to 89 GHz. The RTM comparisons also show that there are no significant solar intrusion errors in the GMI hot load. The absolute accuracy of the GMI instrument is define...

Global Precipitation Measurement Microwave Imager Prelaunch Hot Load Calibration

For typical scanning microwave radiometers, a significant source of calibration error arises from thermal gradients on the hot load. Even when direct or reflected solar illumination is blocked, hot load gradients arise from thermal coupling between the target and the surface facing the target which is heated and cooled as the instrument orbits the earth. For the GlobalL Precipitation Measurement (GPM) Microwave Imager (GMI), a rotating metal annular ring called the “hot load tray” serves to guard the hot load against solar intrusion, and is the surface immediately facing the hot load during the majority of the scan. The planned GMI calibration algorithm corrects for the target gradients induced by thermal coupling between the hot load tray and hot load. The correction uses an empirically derived relationship between the target gradient and the temperature differential between the target and the tray. The correction is derived using target-level and GMI system-level calibration testing. The dual calibration of GMI, in connection with thermal vacuum calibration measurements, is a key aid to determining and correcting the hot load gradients.

Assessing the quality of SeaWinds rain measurements

While SeaWinds was designed to measure ocean winds, it can also measure rain over the ocean. SeaWinds on QuikSCAT active measurements of integrated columnar rain rate obtained via simultaneous wind/rain retrieval are evaluated via Monte Carlo simulation and the Crame/spl acute/r-Rao lower bound on estimate accuracy. Although sufficiently accurate in many conditions, the simultaneous wind/rain retrieval method used with SeaWinds on QuikSCAT data is ill-conditioned for certain wind directions and measurement geometries, sometimes yielding spurious rain rates in zero-rain conditions. To assess the validity of SeaWinds-derived rain rates, a simple empirically based rain thresholding scheme is presented, derived from simulated data. Thresholded QuikSCAT rain rates are compared to Tropical Rainfall Measuring Mission Microwave Imager monthly-averaged data, demonstrating good correlation for monthly-averaged data.

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...

GPM Microwave Imager design, predicted performance and status

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technologies Corporation (Ball) for the GPM program at NASA Goddard.

An assessment of radio frequency interference using the GPM Microwave Imager

A simple data-driven algorithm is used to assess radio frequency interference (RFI) in Global Precipitation Measurement (GPM) Microwave Imager (GMI) data. RFI originates from land-based and space-based sources, affecting the GMI 10 and 18 GHz bands. Land-based RFI demonstrably impacts the GMI 10 GHz data over Europe, China, Japan, and Mexico. Land-based RFI also affects the 18 GHz channels to a lesser degree over particular countries such as Belarus, Libya and Chile. Reflected RFI from the earth surface at 18 GHz from direct broadcast satellites is observed around the continental United States and Hawaii. Geosynchronous direct-broadcast satellites also provide a source of RFI in the GMI cold view. The cold-view RFI is detected and removed in the operational algorithm.

GPM microwave imager key performance and calibration results

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) instrument was launched onboard the GPM core spacecraft in February 2014. The instrument has exhibited highly stable operations through the duration of the calibration/validation period. This paper provides an overview of the GMI instrument and a report of early on-orbit commissioning activities. It discusses the on-orbit radiometric sensitivity and stability for each channel, hot load performance, noise diode stability and early indicators of absolute calibration performance.

An advanced point-wise ambiguity selection algorithm: application to SeaWinds

The scatterometer wind estimation process results in several possible wind vectors (ambiguities) at each resolution cell. The current ambiguity selection technique applied to SeaWinds on QuikSCAT data requires outside data as part of the initialization. An advanced ambiguity selection algorithm known as BYU point-wise does not use nudging data; rather, it utilizes a low-order Karhunen Loeve (KL) wind field model to promote self-consistency. In application to a subset of SeaWinds data, BYU point-wise selects 93% of the same ambiguities as the JPL method. On a set of non-storm error regions, BYU point-wise performed subjectively better in 55% of regions and subjectively worse in only 11% of regions. In cyclonic-storm cases, BYU pointwise performed subjectively better in 11% of regions while performing worse in 23% of regions. Thus, BYU point-wise generally produces more consistent results in non-storm regions without the aid of external nudging data.