# Presentation: 029521

## The 2A12 Land Rain Algorithm – The Good, The Bad, The Unknown... and a Roadmap for Improvements

- Ralph Ferraro1,2, Nai-Yu Wang2,  Chris Kummerow3, Ed Zipser4, Chuntau Liu4
- 1NOAA/NESDIS, College Park, MD
- 2Cooperative Institute for Climate Studies, College Park, MD
- 3Colorado State University, Fort Collins, CO
- 4University of Utah, Salt Lake City, UT

## The Good...

- Produces realistic rainfall fields when compared with radar, gauges, climatology, etc.
- 2A12 land is used in virtually all “blended” rainfall products
- Usually serves as “anchor” for other estimates
- Product is used in a variety of real-time and climate analysis and applications

## The Bad...

- Regional biases
- Compared to PR
- Compared to gauges
- Unrealistic rain rate PDF’s in various regions?
- “Strange” conditional rates
- Underlying surface
- Systematic biases. Why?
- Unrealistic profiles in database
- Bias towards tropical, _ocean_ type systems
- Not enough precip. regimes
- Other “dirty laundry”
- Surface snow
- Inland water bodies

- Liu and Zipser

## The Unknown...

- Complex, outdated, “engineered” screening
- How did we get here?
- Developed for SSM/I
- Different FOV size, etc.
- Confusion over zero rain and indeterminate rain.  Example:
- Limitations over cold, dry land.  Is this an indeterminate rain rate or assumed to be zero?
- Surface ε effects
- Evaporation in dryer climate regimes
- Vastly different ice scattering to rain rate relationships

-       ! 11/02 Set pixel_status to invalid surface type and the
-       !       surface rainrate its negative value for ambiguous
-       !       rain retrievals
-       ! 03/03 Assigned covect the probable convective rain.  If type of rain
-       !       cannot be determined, convect is left as missing.
-       ! 09/03 Pixel_status is no longer set to -21 for ambiguous rain_status
-       !       All retrieved fields are set to their negative value for
-       !          pixels with an ambiguous rain_status
-       ! 03/04 All retrieved fields for a pixel with an ambiguous rain_status
-       !          are no longer set to their negative value

- Courtesy of G. Huffman

## Outline

- 2A12 land algorithm history
- Current status/evaluation
- Areas for improvement & possible solutions
- Screening
- Diversify the land data base and better utilization of Bayesian retrieval
- Convective classification (warm season bias)
- Anomalous surfaces:
- Semi-arid land & deserts
- Coastlines/small water bodies
- Snow within convective cells
- Summary

## 2A12 Land Background

- 2A12 V4
- GSCAT
- 2A12 V5
- Retrofitting/Engineering/Forcing/Replicating... NESDIS algorithm within GPROF
- Find profiles that match 22V-85V in NESDIS “calibration” relationship
- 2A12 V6
- Addressing deficiencies in unrealistic database and NESDIS relationship through match ups with PR and TMI
- Convective/Stratiform relationships
- Improved overall performance in terms of bias and correlation
- (Improvement) coastline rainfall
- 2A12 V7
- Will be carried out under auspices of AMSR-E project and to a lesser extent, PMM (focus on HF/cold season)

## How does 2A12 land compare?

- Courtesy of CRDC@CSU

- ~10% > 2A25
- Comparable to
- GPCP and GPCC

## How does 2A12 land compare?

- Courtesy of CRDC@CSU

- 2A12 ~ 2A25
- Comparable to
- GPCP and GPCC

## Improvement Philosophy

- We will not be developing “quick fixes”
- Experience shows its not real effective...
- Look at GPROF improvements across ALL platforms
- GPM era
- Need to think “out of the box”
- “Things get old, fast”
- Past screening now archaic
- Relied on SSM/I and discriminant functions
- Did not want to rely on “others”
- Data production and delivery reliability
- Lack of experience in the user community
- Radiometer only
- Availability of useful ancillary data
- Not freely available
- Did not meet specifications

## Areas for Improvement

- Screening
- “Modernize”
- Standardization of use of flags
- GPM era, need commonality across platforms!
- Diversify the land data base and better utilization of Bayesian retrieval
- Land systems, all seasons
- Emissivity models
- All channel measurements
- Convective classification (warm season bias)
- Anomalous surfaces:
- Semi-arid land & deserts
- Coastlines/small water bodies
- Snow within convective cells

## Confused yet?

- Warm 85H,cold 22V  *MASKO*
- Other 85H,cold 22V
- Grody polarization  *MASKP*
- Ice polarization  *MASKP*
- Arid polarization  *MASKP*
- Not ambiguous  *0*

- Grody cold sfc.  *MASKI*
- Grody polarization  *MASKP*
- Ice polarization  *MASKP*
- Arid polarization  *MASKP*
- “missing” in 5x5  *33*
- Low sd
- Intermediate sd  *13*
- Not ambiguous  *0*

- Really cold sfc.  *MASKI*
- Ambiguous  14

**Current GPROF Screening**
- Courtesy of G. Huffman

- Compute sd[T(85h)]

- After this, screening code tries to resolve the ambiguous regions.
- Non-scattering zero-rain flags (-51, -61) aren’t treated.
- Regions of positive (ambiguous) flags are evaluated for surrounding flag values:
- If perimeter is all negative, the area is set to the first negative found;
- if perimeter is zero and negative, the area is set to 13;
**if perimeter is zero, the area is set to *****0*****.**
**Unresolved ambiguous values are set to *****-15*****.**
- After this, “enough scattering” is checked in the rain code.

- MASKS = -21
- MASKP = -41
- MASKI = -31
- MASKO = -51
- MASKC = -61

## New Approaches for Sfc. Identification

- 85 GHz Emissivity

- Through utilization of both operational and research data sets that
- are routinely available, we should be able to conquer the land surface
- screening problem with relative ease.

## Standardization of Flags

- Current flags were designed to:
- “Diagnostics” for algorithm developers
- Geared for limited set of “early” users
- GPCP - Key concern was zero rain vs. indeterminate rain
- New, desired attributes include:
- Proper survey of user community of their needs
- A nomenclature that everyone can understand
- A set of flags that is useful for everyone
- Commonality across all sensors in GPM era
- Will be handled through PMM

## GPROF databases and Rain Retrieval

- Examine and improve land databases
- GPROF land profiles are _limited_ in diversity
- Predominantly from tropical oceanic systems
- Not diverse nor realistic enough for true physical retrieval
- Look at excellent data sets from a variety of sources
- C3VP, CloudSat, NOAA’s HMT (West Coast U.S./Winter)
- Expand previous TMI/PR studies with full 10-year data
- Working with PMM science team members...
- Retrieval needs to expand to more than just 22V-85V
- Published studies show other combinations are better in different precipitation regimes

## NOAA HMT 2005 

- T and q  profiles from HMT RAOB
- and current land database

- HMT S-band  radar reflectivity
- Freezing level is around 2.5 km
- Database lacks such profiles

## Convective/Stratiform

- Current method (a combination of 3 published methods) was improvement in V6 from V5, but still has problems.  This is the culprit of the warm season bias.
- Why?
- Resolution – TMI is coarser than PR?  Spreads out rain?
- Beam filling?  Underestimate intense rain

- Need to work with PR scientists to help improve
- convective probability in 2A12

## Special (Seasonal) Situations

- False snow (ambiguous) inside of thunderstorm:
- Usually the heaviest RR’s in storm system
- V6 attempts to filter these out, but it doesn’t always work
- Why? Ice scattering at 22V (rare); similar characteristic to snow cover
- Solution  use of snowcover climatology and land surface temperature
- Arid regions (e.g., Sahel)
- Screening removes potential rain areas BUT...
- Also isn’t 100% effective, so false alarms result
- False alarms create unrealistic conditional rain rates
- Solution better utilization of emissivity calculations and surface type information
- What’s going on with small water bodies?
- Is it called coast or land?
- Applying the wrong algorithm to the wrong surface type? OR
- Is it a mixed pixel effect?
- Does it have seasonal effects due to vegetation cover?
- Impact is at the low end (onset) of rainfall
- Solution Examine current 2A12 land/sea/coast mask as a starting point...

## Courtesy of M. Diederich

- TRMM

- AMSR-E

- SSM/I

## High Resolution Land/Water Mask

## Filtering out smaller water bodies

## Summary

- 2A12 land is utilized in a number of applications and has proven useful
- Despite this, feedback of V6 by the user community suggest several critical issues that need to be resolved for V7
- We will try to prioritize which problems we can solve
- Looking towards more generic fixes for GPM era rather than band aids for TRMM...
- We need your help!
- Send us your results on the good, the bad, the ...
- Looking to hire good young scientists at CICS to work with our team

**4th Workshop of the International Precipitation Working Group (IPWG)**
**Beijing, China October 13 – 17**
- _[http://www.isac.cnr.it/~ipwg/IPWG.html](http://www.isac.cnr.it/~ipwg/IPWG.html)_
**Ralph.R.Ferraro@noaa.gov**