Cantrell, Eric

Lang, Timothy J.

Meyer, Paul

Roberts, Jason B.

Wolff, David

NASA Technical Reports Server

AMPR and radar observations from IPHEx: Data quality control and product generation
Timothy Lang, Brent Roberts, Paul Meyer, Eric Cantrell, David Wolff
Contact Info: Timothy Lang, NASA MSFC (ZP11),
Huntsville, AL 80512; (256) 961-7861, timothy.j.lang@nasa.gov
Funding for this work has come from the NASA GPM GV Office
1. Advanced Microwave Precipitation Radiometer (AMPR) 2. NPOL Radar Quality Control and IPHEx Data Fusion
Initiate
Terminate
NASA Precipitation Measurement Missions
PMM Science Team Meeting July 2015
T. Ashcraft
NASA’s S-band polarimetric radar (NPOL) was deployed near the SC/NC border during
IPHEx. Significant beam blockage from nearby terrain was expected based on pre-campaign
modeling. However, observations revealed additional blockage from other obstacles. All of
this blockage is in the process being corrected using techniques that exploit the self-
consistency of polarimetric radar variables in pure rain (Lang et al. 2009; JTECH). A new
Python module (PyBlock) has been developed to simplify this process and is currently being
open sourced.
AMPR is a cross-track scanning, airborne passive
microwave radiometer maintained by NASA
Marshall Space Flight Center. It has four
microwave frequencies (10.7, 19.35, 37.1 and 85.5
GHz). Cross-track scanning results in a rotating
polarization basis as function of scan angle
• Channel A: Left edge full V, right edge full H
• Channel B: Left edge full H, right edge full V AMPR Instrument in its Marshall Lab
Version 2 AMPR data from the Integrated Precipitation and Hydrology Experiment (IPHEx) are
now available. New for IPHEx is that AMPR data are released in Network Common Data
Format 4.0 (netCDF4) format, greatly simplifying data ingest.
Version 2.0 Highlights
• Data quality flag for each 
channel
• Incidence angle
• High-resolution land/water 
fraction (250-m MODIS)
Good Data Characteristics
• QC Incidence Angle = 1
• Pixel FOV < 0.1 or Pixel FOV 
> 0.9, (i.e. mostly land or 
mostly water)
• QC Flag Value <= 3
Python AMPR Data Toolkit (PyAMPR) open sourced
and available on NASA’s official GitHub repository
PyAMPR reads new IPHEx netCDF as well as
legacy ASCII-format data from past projects. Demo
and testing IPython notebooks available on GitHub
Quicklook imagery with 
QC flagging (blue lines)QC flags are integer-based, the higher the value the worse the data likely 
are. Based on 2D behavior of TB values. Sensitive to noise, coastal 
regions, and sharp gradients near convection 
Example 85 GHz (A) with noise Example 85 GHz (A) convective 
overpass
85 GHz (A) Quality Flag 85 GHz (A) Quality Flag
Sample PyBlock output, analyzing corrections needed for 
reflectivity and differential reflectivity on 15 May 2014.
Pre-campaign 
modeling (left) 
suggested only 
blockage to the NW, 
but actual NPOL 
observations (right) 
show significant 
blockage at 
additional azimuths
New NASA software (DualPol) interfaces with the DOE 
Python ARM Radar Toolkit (Py-ART) and CSU retrieval 
software (CSU_RadarTools) to simplify the estimation of 
precipitation characteristics from polarimetric radar data.
ER-2 instrument imagery from ~2140 UTC on 12 June 
2014. AMPR (above via PyAMPR), HIWRAP (below).
Example of multi-radar data fusion (NPOL + NEXRAD), 
powered by Py-ART. Precipitation retrievals are gridded 
along with standard variables like reflectivity.
Data Fusion
Ongoing work is seeking to merge precipitation 
information (e.g., Z, D0, R, etc.) from multiple 
platforms to create 4D microphysical datasets 
grids for the 11-12 June 2014  significant 
hydrometeorological event
https://ntrs.nasa.gov/search.jsp?R=20150022943 2019-08-31T05:05:55+00:00Z


AMPR and Radar Observations from Iphex: Data Quality Control and Product Generation

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