2nd IPWG
25-28 October 2004
Monterey, CA
1. General Remarks
 The WMO Space Programme – Don Hinsman
 Review of WMO’s Global Observing System; about 10 partners
 IPWG program co-chairs comments – Gruber and Levizzani
 IPWG established June 2001
 First meeting – Sept 2002 – Madrid; established 3 working groups (Operational Applications,
Research, Validation); 21 WG recommendations
 Accomplishments:
1. Web Site: www.isac.cnr.it/~ipwg
2. Requirements for MW frequency protection
3. Climate data sets inventory
4. Validation & links
5. Links to training
6. Co-sponsor with GPCP on IPCC Assessment
7. Algorithm inventory and downloadable code
 IPWG/GPCP validation intercomparison project – CONUS, Australia, Europe

2. International Projects and Satellite Programs
 Report of the Rapporteur to the CGMS – Jim Purdom
 Review of linkages between IPWG and bigger picture CGMS activities. Plans are to move forward
with virtual laboratory and “electronic workbook”. IPWG members should revisit material on
web site and make sure information is up to date.
 CGMS high priority items to IPWG – IPCC Assessment, solid precip, precip over complex terrarin,
ongoing validation activities







Research & Operational Application of TRMM-based, fine time scale precipitation analysis –
George Huffman for Bob Adler
V6 converging with PR better than V5; now within 5% over ocean
TRMM is working well and used in operations; awaiting NAS recommendation on future of TRMM.
TRMM has enough fuel for controlled reentry through 2005, without that, it could go into 2011 (and
overlap with GPM). TRMM costs $4M/yr to operate (full cost, include FTE’s). NASA safety group
does not require controlled reentry.
A variety of application examples of TRMM rainfall shown – tropical cyclone rainfall, ENSO onset
Index, etc.
Microphysical Considerations in Remote Sensing – Vincenzo for Rosenfeld
Rosenfeld and Lensky (BAMS, 1998) – classification of convective clouds into microphysical zones
according to the shape of the temperature profile (IR) and effective radius (near-IR) – applied to
MSG data
Differences between maritime and continental cloud systems (and orographic); continental has larger
drops, but smaller rain rates while maritime smaller drops, but higher rain rates. Translates into
lower reflectivity (Z) in maritime rain, factor of 2-4. Can use this information to develop improved
passive MW databases/libraries; something that will be addressed via RAINCLOUDS, if funded by
E.C.


GPCC Assessment for IPCC – Arnie Gruber
Review of outline/proposal; draft to be ready by Jan 2005 with a follow-up workshop in March/April
2005, with a final version due by Sept. 2005.
3. Operationally-Oriented Precipitation Datasets
 Integration of the EUMETSAT MPE in an Operational realtime processing environment – T.
Heinemann (EUMETSAT)
 Flash floods are rare, but a real concern in Europe. There is a need for real time processing. Plus, for
Africa and Asia, there is no other data but satellites.
 The MPE – IR and MW combined algorithm (METEOSAT+SSMI); within the Nowcasting SAF;
real-time. Same ideas and philosophy as we employ with MSPPS.
 Will eventually bring in TRMM data















The SEVIRI Precipitating clouds product of the Nowcasting SAF – A. Thoss (SMHI) +
Bennartz
Two products – Precipitating Clouds (PC) and Convective Rain Rate (CRR)
PC product – 3 classes – no rain, 1-5 mm/hr, >5 mm/hr; developed from AVHRR and BALTEX
radar data + surface temperature data and adopted for MSG (vis, near-IR and IR)
Daily mapping of 24-hour rainfall at pixel scale over South Africa – G. Pegram (South Africa)
Merging data sets; S. Africa is between GOES and METEOSAT and has sparse gauges and radars as
well
Multispectral rain technique to identify raining pixels (vis, IR, WV), then use IR for rain rate
They generate daily maps and it gets posted on the S.A. Met Service web site
EPPrePMEx: A real time rainfall estimation system based on GOES-IR Imagery – J. Sanchez
(IMTA/Mexico)
Roots from CST originally adapted for hurricane rainfall, later, adapted for general use
Working collaboratively with NOAA/OH
Real time generation and web posted (http://nimbus.imta.mx); basin generated amounts as well
Comparisons with Autoestimator during 1998; appears to do better than AE. Also, comparisons with
RFC gauges in Texas/Mexico region


Moving towards multispectral, multiplatform operational rainfall at NESDIS – Bob K.
Overview of GOES based rainfall work; SAB customer, automated, real-time use, etc.
Need to move towards blending measurements and platforms – SCaMPR; transitioning to run in real
time
SCaMPR appears to outperform AE and GMSRA for rainfall >20 mm in six hours
Possible use of lightning data; GOES-R possibility?

Status of NOAA/NESDIS AMSU algorithm – Ralph F.


TRMM TMI Algorithm – V6 and Beyond – Chris K.
V5 to V6; new databases (ASCII, available on web)



Validation – AMSR-E and TMI similar, V6 land on Melbourne, FL -10%; regional biases
V7. Why? 10-15% difference between PR and TMI. Also, many new sensors like SSMIS and
Windsat  parametric algorithms. Also, V7 should eliminate all screening routines and instead use
probability of rain and confidence of using the correct database. So, like a 50% probability of rain or
greater will be close to what V6 is producing now.
Future … more attention to land and extratropics. More coordination needed; how do we transition
from empirical to physical methods? Version numbers, standards, QA, etc.





CMORPH – Bob J.
Uses 8 satellites – POES, DMSP, AMSR-E, TMI for MW; 5 for GOES
Cloud motion from IR to move MW rain
Validation looks great
Comparisons with CMORPH with GMORPH




The status of the MPA and insights gained from adding new data sets – George H.
TRMM 3B42RT and 3B42
Testing AMSU-B and AMSR-E
Discussion on validation and error estimates


Cloud motion winds diffusion scheme for quantitative rainfall estimation – F. Tapiador (Spain)
Motion vector approach – similar in concept to CMORPH, but uses IR derived winds and model
winds (like GMORPH) to propagate MW precip.
A more physical method than an image processing technique – consider “diffusion” approach where
cloud motion is treated as a fluid.







A combined TMI-SSMI rainfall estimation technique for W. Africa – J. Schulz (Germany)
PR, TMI, SSMI, MSG
Uses PC analysis and temporal averages to remove background MW signature (Bauer, Petty); 7 day
average used
Rain Rate – PR calibrated rain index; Petty HSS method

Operational rainfall retrieval based on cloud microphysical properties – T. Nauss (Germany)
Active Convective Technique (ACT) – vis, near-IR, IR, WV used for conv./stratiform, advective
scheme and cloud optical properties
Plans to implement for SEVERI




Precipitation observational capabilities at the Brazilian Inst. for Space Research – C. Angelis
They run the HE; want to develop new techniques to improve on the HE for different climate regimes
They maintain 16 weather radars in Brazil, Argentina and Paraguay
Web access to obtain gauge data http://www.cptec.inpe.br

The global satellite mapping of precipitation project (GSMAP): Integration of MW and IR
radiometers for a global precipitation map – T. Ushio (Japan)



HOAPS II: Global ocean precipitation database – C. Klepp (Germany)
www.hoaps.org
Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data = HOAPS







15 years of data – 1987-2002; primarily from SSMI (precip, OWS) + AVHRR (SST)
Use all satellites available, intersatellite calibration
HOAPS-G – 0.5 degree, pentad, monthly, climo; HOAPS-S – orbital
GPCP is greater than HOAPS
No trends on global scale, but regional trends in 15-year period.
Klepp et al, 2003
Something seems wrong with his implementation of SSMI/Ferraro; contact him and follow up
with code check.
4. Validation and Error Analysis
 Estimating bias of satellite-based precipitation estimates relative to in-situ meas. – Tom Smith
 For climate scale, biases need to be assessed and adjusted for. Use gauges as reference.
 Bias depends on both spatial and time scale; for climate scale, e-folding distance ~750 to 1000 km
 Uses OI scheme to analyze bias fields; bias for various satellite techniques ~1-2 mm/day, but it has
spatial structure
 Ocean is a real problem since no gauges to adjust to; use TRMM?




Rainfall Estimation using satellite data – C. Oria Rojas (CPN/Peru)
Peru – very sparse gauge network and no radar; satellites extremely important for rainfall monitoring
Use 2 IR techniques – AE and GMSRA; showed validation. GMSRA appears to do better in Peru.
Developed some corrections for the algorithms – cirrus filters, TPW, etc.



IPWG Validation-Intercomparison Study – Beth Ebert (BMRC/Australia)
Stimulated by first IPWG plus precipitation needs in Australia gauge void areas
Also model precip. validation, but interestingly, model and satellite are complimentary – NWP better
in stratiform, satellite better in convective
Focus is only daily rainfall and on data sets that are produced daily













CONUS Validation-Intercomparison Study – John Janowiak
Modeled after Beth’s web site
Showed some results; merged MW/IR seems to do the best, but the NCEP model still is better in
winter seasons
Case study over Montana showed how the satellite estimates were in error due to low level RH/evap.
European Validation-Intercomparison Study – Chris Kidd (Univ. Birmingham, U.K.)
European continent – lots of coastlines, diverse topography and precipitation types
Also, plenty of light rain intensities
Main data to validate so far – ECMWF, CMORPH, CPCMW, 3B40-42 + locally generated
algorithms
Data remapped to common projection; stats at 20 and 50 km
Radar as validation
Add AMSU to his validation
Joyce/AMSU low bias in Europe?



Verifying Precipitation Events using composite statistics – J. Nachamkin (NRL)
Looking for rain > 25 km; rather large events; compare PDF’s
BMRC gauge analysis vs. Turks blended product. Results show that for winter, satellite grossly low
while in summer, satellite did very well, maybe too high in heaviest rainfall






Verifying TRaP over Australia for 2003-04 – Beth Ebert
2003-04 season – 6 land falling storms
Appears to be issues with SSM/I algorithm w.r.t. max rain rate; AMSU seems to do fine
Those TRaP’s that were vetted by SAB did seem to be worse than those that were operational
By sensor, AMSU seems to be best closely followed by TRMM, then SSMI worst
CRA/blob verification – pattern error was most important (48%), followed by volume (34%), then
track error (18%)
Several areas of improvement – include storm rotation, better algorithms, atmospheric moisture/shear
corrections, smoother to remove stripes in TRaP, etc.
Future – ensemble TRaP, probability forecasts




Describing diurnal cycle of precipitation from satellite observations – Phil Arkin
Use of CMORPH to look at various diurnal cycle features over CONUS and globe; interesting
results. Even showed diurnal cycle trends in Hurricane Isabelle (midnight max)




Land gauge analysis – Bruno Rudolph (DWD, Germany)
Discussion of GPCC
Monitoring product – 7000 stations – available 2 months delay
Severe problems due to wind (up to 20%) and solid precipitation (factor of 3)





Rainfall estimation using an image classification approach – Y. Hong (UC-Irvine)
PERSIANN – for hydrological applications
Cloud classification scheme – location, cloud top temp, cloud size, texture and dynamics
Develop a cloud type – rainfall data base (ground and MW rain rates)
Doing snowfall retrievals – Sfc. Temp + elevation; future to use PR and NN technique
5. Research Activities
 The need for experimental data to support IPWG research activities – B. Bizzari (CNR-Italy)
 An action from IPWG#1 and CGMS – Space agencies need to support the development of
experimental data sets (e.g., aircraft) for precipitation/cloud modeling and instrument definition.
 Geared towards need for GOMAS (Geostationary Observatory for MW Atmospheric Sounding) –
scan 1/12 disk every 15 minutes with 10-30 km resolution. It would have bands around 54, 118, 183,
380 and 425 GHz.
 Working with ETL/Gaisewski – promoting use of PSR; hope for flights in 2005 and 2006




NASA GEOS Rainfall Assimilation – Art Hou
Focus on TRMM on global model
A model needs physical consistency between rainfall and other variables; if the rainfall is incorrect,
then something else is incorrect. Satellite retrieval algorithms should be concerned with the same
issues. NWP rainfall is thus a forecast, not an analysis of precipitation based on observations and
model information.
Results pulling in TMI, SSMI and AMSR-E translates into a 10% reduction in OLR errors



Mesoscale convective system life cycle over Del Plata Basin – D. Vila (INA, Argentina)
The FORTRACC technique – based on the fact that many GOES images are missed, so how do you
account for this?
Case studies/validation/applications







Precipitation characteristics of landfalling typhoons in Taiwan – D. Jou (Taiwan Univ.)
4-doppler radars on small island of Taiwan
Tropical storms – devastating floods
Focus of this talk – use radar to study precip. structure changes of Typhoons
Typhoon Nari – Sept 16, 2001 – affected Taiwan for many days.
RR increase 2%/hr during 12 hours before landfall, but 8%/hr 2 hrs before and 3 hr after landfall
Also looking at TRaP (tell Sheldon)



High Latitude Precip – Ralf Bennartz
Snowfall represents a large fraction of precipitation at mid and high latitudes
We can observe radiances and reflectivities, but not cloud microphysics, thus, we need models that
relate the cloud microphysics to the radiometric measurements
Bennartz and Petty microphysics model (2001) – ice density and size of ice relative to liquid particles
– can get consistent description of Z/fall speed/particle number concentration
Using AMSU and AMSR-E with Baltex radar data for RTE simulations; then used Tripoli CRM
Get fairly good agreement at 89 and 150 GHz; can expand to other frequencies to see how they might
respond on future sensors (TB Jacobians) – example, 118 GHz
These cases had a precip. layer thickness of no more than 2 km.
Urges that snowfall algorithm cooperation be guided by IPWG, in particular, cloud microphysical
models – Gruber mentions that the recent GRP is also suggesting a workshop on solid precipitation.
We need channels that are surface blind!











EGPM/Snowfall simulations – E. Smith for A. Mugnai
EGPM; ESA has put it on hold and redirected to another funding pot; review of mission
CRM simulations/working with Tripoli
3 case studies presented (East coast U.S. – 1/25/2000; Gotland; U.K.)
Summary – Snowfall over land/snow cover – high frequency and sounding channels needed; over
ocean, have to deal with melting near SST. Radar will aid in the retrievals. For light rainfall over
land, use of sounding channels is important.



Cloudsat snowfall/light rain algorithms – T. L’Ecuyer
Review of CloudSat – 94 GHz radar with -20 Dbz sensitivity; flown as part of “A-Train”
Cloudsat mainly for clouds, but shows promise for light precipitation; CRYSTAL-FACE, Wakasa
Bay examples
TRMM radar (18 DbZ) misses quite a lot of light rainfall than contributes ~2-5% of rainfall in tropics
and Colorado (but presumably, much more at higher latitudes)
Retrieval algorithm – Uses Rodgers optimal estimation formulation of inverse problem; get vertical
profiles of IWC/LWC
Synthetic retrievals – seems like you can do well for rain rates <= 5 mm/hr
Snowfall retrieval algorithm developed in similar manner; uses 89 and 150 GHz (Wakasa Bay)
Both algorithms require PIA or PWP constraints







DSD and Surface Wind using dual-freq and X-band Radiometer – S. Brown (Univ. Michigan)
13.4 and 35.6 GHz radar


DSD from pointing rain radars – A. Battaglia (Univ. Bonn/Germany)
Microwave Rain Radar (MRR)



GPM Era Precip. Algorithms – E. Smith
Formulation phase started 10/01 to be completed by 12/05
Review of mission status: GMI selection 12/04; DPR expected 4/05; H2A core launch mid 2010-11,
still TBD, so that puts hold on EGPM (ESA’s Earth Watch Program, new, but not funded yet).
GPM Algorithm structure – include L2 DSD profiles, rainrate profiles and latent heat profiles. GV
program for L2 products. L3 products include core satellite prodoucts, blended/intercalibrated
passive MW products, Morphed MW/IR products
Discussion on GPM core reference algorithm – DPR-GMI Bayesian Algorithm
Looking for guidance from IPWG on algorithm requirements, formats, etc.














Evaluation of RTTOV8 at AMSU frequencies – Una O’Keeffe (UKMO)
RTTOV8 vs. N16 and ARTS (another RTE model)
Use mesoscale model as input into RTE
RTTOV 8Results – good at 89 GHz, but did not do well at 183 +/-7 GHz – could not handle precip.
scattering; ARTS appears to do better. Why? Most likely, treatment of cloud microphysics/ice.
Probably not accounting for enough large ice particles
Possible new size distributions to use: UK field campaign data (Field, 2004, QJRM, submitted)
Model works well for AMSU-A  CLW retrieval
Radiometer channel optimization for precipitation remote sensing – Peter Bauer (ECMWF)
Window (18, 23, 37, 89, 157) vs. sounding channels (50.3, 118.75 GHz); sounding channels have
gotten more recent attention because of their constant weighting functions and being surface blind in
clouds/precipitation.
1-D var; advantage over cloud profile database since they are not tuned to CRM’s, however, they still
require constraints (and may not converge). They are more computationally expensive.
Examination of signal to noise for a variety of precipitation systems; results as you might expect; 89,
118 and 150 GHz best over land, lower over ocean. Lower channels over land suffer from
noise/errors in surface emissivity.
Channel optimization for rain, cloud water and snow: sounding channels seem to be better over land,
window over ocean


Rainfall type estimation from the information of life stage of deep convection – T.Inoue (Japan)
Recognize that IR is less physical than MW, but we have GOES based temporal sampling. If IR
information on life stage of convection is obtained, then maybe better rain rate estimates can be
made.

Satellite precipitation estimates and the Central America FFG system - Rosario Alfaro (Costa
Rica)
Running AE/HE in Central America. https://cds.imn.ac.cr

6. Working Groups (Operational, Research, Validation)
Other Actions:



Look at Jorge Schulz’s EUMETSAT paper on TPW kriging
Tristan L./ESSIC Seminar, CICS, etc.
GRP/IPWG/GPM/JCSDA sponsored solid precip workshop w/Bennartz
Operational Working Group
Attendees: Bob Joyce (chair), Ralph Ferraro, Joe Turk, Jim Purdom, George Huffman, Arnie Gruber,
Vincenzo Leviazzani, Deborah Smith, Jorge Sanchez-Sesma, Yang Hong, Rosario Alfaro, Tomoo Ushio,
Thomas Heinemann,

Review of last years AI’s:
STANDARD/COMMON PROCEDURES:
Recommendation 1: Export algorithms. Tadipor algorithm is on IPWG web site and has been accessed over
13 times; no feedback has been received. Arkin has done inventory of algorithms and they are on the IPWG
web site.
More are still needed. All GEO data are now in McIDAS format. This should accelerate the use of
algorithms such as HE as an IPWG export algorithm. Sanchez-Sesma recommends addition of the CST also.
Any others? Simple microwave – Ferraro? What about GPROF - Kummerow? Remember, the goal here is
to provide algorithms for use by international agencies as a learning tool, not necessarily to run the state of
the art algorithm (one can always get these operational DERIVED PRODUCTS from an operational agency).
Accountability – algorithm champion needs to be identified.
Algorithm information and web pages needs to be reviewed and updated, make sure there is sufficient
material to aid in training (i.e., this algorithm is best for flash flooding, orography, etc.). Links needed to
IPWG validation pages for each specific product. Need basic description of rainfall products. Links to
getting archived data.
Include training on precipitation products within the WMO, EUMETSAT and NOAA (for example) training
courses.
Suggest on the 4th bullet, soften the wording as a “requirement” to a “suggestion”
CONTINUING
Recommendation 2: Establish and Maintain IPWG Web Site.
maintains it, although it is not complete.
Vincenzo L. has developed this and
Again, IPWG members are urged to review and update information on the web site, make sure there is
sufficient material to aid in training (i.e., this algorithm is best for flash flooding, orography, etc.).
New/Expanded Actions: There was discussion on McIDAS format? Can IPWG post a converter? A new
action would be to post images of the products on the web site on IPWG via direct links (the web page has a
page on this, but it has not been developed yet). Needs to be restricted to regularly generated algorithm?
Template for product description should be developed and sent out (VL and AG) above and beyond what is
already there (“more information”, like COMET training modules). Those that are being validated on the
IPWG validation pages? Probably need to have a user feedback mechanism on the web site as well. Can we
post PDF versions of references related to algorithms on IPWG web site? Regarding case studies, maybe
solicit for links to case studies only, could just be GIF’s or PPT files (DS).
CONTINUING
COMBINE RECOMMENDATIONS 1 & 2 INTO SINGLE ONE
Recommendation 3: Coordinate applications of non-traditional uses of precipitation
CANCEL
RESEARCH:
Recommendation 1: Data sets for case studies
Not Feasible – On Hold/Continuing
Recommendation 2: Encourage continued development, refinement, validation of research-status
precipitation techniques
Many algorithms were reported on at the 2nd IPWG. Several blended algorithms (e.g., CMORPH) have
advanced and should be made available for distribution and inclusion on IPWG web page (earlier
recommendation – add to inventory). Also, progress is being made on other problem areas like solid
precipitation and orographic rain (some to the point of being pre-operational) and we urge that these effort
continue.
CONCLUDED/BUT CONTINUING.
Recommendation 3: Climate data sets for 1 DD are needed and be reprocessed
Nothing reported on at this meeting per se, but George Huffman gave the WG a short report on this – Data
available at NCDC from 10/96 to present. Action on GH to write a paragraph on this and it will be included
in 2nd IPWG report posted on web page.
CONTINUING
FUTURE SENSORS:
Recommendation 1: Recommendation on GEO lightning sensor.
MOVED TO RESEARCH AT REQUEST OF B. BIZZARI
OPEN ITEMS:
Recommendation 1: Provide means for better communication
Don Hinsman set up mailing lists for IPWG and each WG. Action on Joe Turk and Don Hinsman to update
these lists based on 2nd IPWG participants.
Reporting done on 6-month basis. It is suggested that the WG co-chairs report back to IPWG co-chairs
every six months.
CONTINUING
Recommendation 2: Better temporal coverage needed for South America from GOES
Has this been raised to satellite operators? Check with Hinsman and Vila on this.
NEW ITEMS

What role does IPWG have in insuring that satellite missions continue or new missions not
cancelled? How do we interface with CGMS on this?

4 CGMS items requested by Jim Purdom:

Mike Goodman’s L2 File Content Standards: Blank filling of missing scan lines is not needed, but
scan number is a needed parameter. Filling of missing FOV’s within a scan line (non-zero) is needed.
What if entire orbit/granule is needed? Dates/Times need to be in actual units (year, month, day, hour, ).
Julian day may or may not be needed. For metadata, orbit number would be useful, as well as number of
leading/trailing duplicated files. Calibration source and version for L1 required. Need to include scale
factor/offsets and units number. Concern over NPOESS/METOP – partial orbits – orbit number should
be a real number. Data standards. Concur what is there. Want lat/lon for each FOV. Time at beginning
of scan is all that is needed, but reference time is TBD. Precipitation units are coupled with precipitation
parameter name. Precipitation quality estimates should be required, but is informal at this point with
more information to be provided in an accompanying document. Sensor/geolocation quality flag useful
but not always needed. Precipitation regime type provided if the algorithm is able to provide it.
Probability of non-zero precipitation may be required for certain algorithms (eg GPOF V7). Common
documentation format encouraged (TBD).

Hi-Res Precipitation Products Evaluation (from Phil Arkin): The group applauds and encourages the
four goals of this proposed effort, which will require continued validation projects as started already by
the validation working group. The details of the implementation (science plan, funding sources, etc)
were not well enough defined and the group did not further discuss these.

Our reply to the recommendations given to us by the CMGS rapporteur. A workshop in early August at
the Univ of Maryland regarding a GPCP assessment for the IPCC. The report on GPCP assessment is
being co-sponsored by the IPWG with the GPCP. It was recently revised by the GRP.