# Presentation: 934937

## Validation of Mid- and High-Latitude Ocean Precipitation Retrievals fromAMSR-EGrant W. PettyLongtao WuUniversity of Wisconsin-Madison

## Overview

- A variety of quasi-standard global precipitation products are now being routinely produced from AMSR-E data.
- e.g., GPROF (US), Wilheit (US), Liu (JAXA), Petty (JAXA),  Wentz (US/RSS)
- High-latitude precipitation, especially snowfall, presents the greatest challenge:
*Greatest* disagreement between different algorithms
*No* direct validation to date
- Selected island weather stations at high latitudes show promise for validation of ocean retrievals but require careful assessment for measurement biases.

## Slide 3

## Slide 4

## Climatology of Fractional Time Precipitating (DJF)

## Climatology of snow occurrence – Northern Hemis. Winter

## Mid- and high-latitude islands with existing WMO stations – neglected resource?

## WMO stations on mid- and high-latitude islands

- Unlike Morrissey's tropical atoll stations, these islands are neither *very* small nor *very* flat.
- Issues with respect to use as validation for ocean precipitation:
- Accuracy of measurements of local precipitation
- Undercatch of snowfall, especially when windy
- Representativeness with respect to surrounding open ocean
- Orographic enhancement or rain shadows
- Frictionally induced convergence
- Differential heating

## Mid- and high-latitude islands with existing WMO stations – neglected resource?

- Jan Mayen

- Nikol’skaya

- Thorshavn

- Marion Isl.

## Comparison details

- Monthly precipitation from a variety of quasi-standard AMSR-E algorithms (latest publicly available version)
- averaged over 2.5 degree box, excluding land and coast.
- 36 months (Jan. 2003 - Dec. 2005)
- Initially: uncorrected gauge totals as reported in routine synoptic reports
*No algorithm evaluated has been tuned to these island reports.*

## Validation Statistics

- Correlation coefficient
- Measures tendency of algorithm to match the shape of the time series from the gauge, without regard to possible biases
- Poor correlation indicates algorithm and gauges are not “seeing the same thing” -- potentially hard to correct
- Good correlation hard to achieve by chance (N=36) –> strong circumstantial evidence that both retrieval and validation data are fundamentally sound, apart from possible biases
- Ratio of the means
- Reveals *systematic biases* in either algorithm or station data
- Biases may or may not be easily correctable, depending on source
- RMS difference
- small RMS difference requires *both* good correlation and small bias
- good measure of *overall* agreement, but poor diagnostic statistic

## Jan Mayen

## Jan Mayen comparisons

## Jan Mayen comparisons

-           NObs   Ratio    Corr    RMS
- Petty       36    **1.38    0.81   33.85**
- GPROF       36    0.05    0.38   64.32
- Liu         36    0.18    0.54   55.53
- (Note: Daqing Yang's gauge correction, which is NOT applied above, increases Jan Mayen's annual precip by 14%, with most of the increase occurring during winter months)

## Thorshavn (Faeroe Isl.)

##           NObs   Ratio    Corr    RMS

-           NObs   Ratio    Corr    RMS
- Petty       36    **0.81    0.75   41.94**
- GPROF       36    0.31    0.59   91.98
- Liu         36    0.29    0.63   92.14
- (Note: Daqing Yang's gauge correction, which is NOT applied above, increases Thorshavn's annual precip by 6%, with most of the increase occurring during winter months)

## Bering Island

## Nikol'skoe, Bering Isl.

## Nikol'skoe comparisons

##           NObs   Ratio    Corr    RMS

-           NObs   Ratio    Corr    RMS
- Petty       36    **1****.38    0.47   37.88**
- GPROF       36    0.26    0.08   50.30
- Liu         36    0.46    0.22   46.38
- (Note: Daqing Yang's gauge correction, which is NOT applied above, increases Nikol'skoe's annual precip by 35%, with most of the increase occurring during winter months)

##           NObs   Ratio    Corr    RMS

-           NObs   Ratio    Corr    RMS
- Petty       22    **1.12**    **0.21**   **50.82**
- GPROF       22    0.41    0.13  104.88
- Liu         22    0.58    0.06   89.98
- Wilheit     22    0.62    0.01   77.10
**Note very poor correlations with all algorithms!**

## A closer look at Marion Island

- Note position of meteorological
- station in the lee of a large mountain –
- likely rain shadow!
- Measured precipitation will probably be biased relative to the open ocean, as well as varying strongly with direction of the prevailin wind.
- Conclusion:  Marion Isl. Is probably NOT a suitable validation site for AMSR-E precipitation!

## Summary of Raw Results – Correlation Coeff.

-                  Lat  MaxEl   Petty   GPROF    Liu   Wilheit
- JAN MAYEN       70.93   638    **0.81**    0.38    0.54     ---
- THORSHAVN       62.02   736    **0.75**    0.59    0.63     ---
- ST PAUL ISL.    57.17   173    0.75    **0.77**    0.61     ---
- NIKOL'SKOE      55.21   510    **0.47**    0.08    0.22     ---
- HORTA           38.52  2260    0.84    **0.87**    0.85    0.82
- PONTA DELGADA   37.75   868    **0.86**    0.77    0.84    0.70
- SANTA MARIA     36.97   575    0.81    **0.85**    0.80    0.77
- LORD HOWE ISL  -31.53   103    **0.65**    0.61    0.61    0.41
- ISL. JUAN FER  -33.62   857    **0.84    0.84**    0.75    0.70
- GOUGH ISL      -40.35   861    0.54    0.55    0.28    **0.58**
- CHATHAM ISLAN  -43.95   271    0.63    **0.68**    0.50    0.45
- MARION ISL     -46.88  1171    **0.21**    0.13    0.06    0.01
- PORT-AUX-FRAN  -49.35   878    0.40    **0.44**    0.34    0.02
- FALKLAND ISL.  -51.82   433    **0.71**    0.64    0.56    0.17
- MACQUARIE ISL  -54.48   360    **0.68**    0.55    0.63    0.32

## Summary of Raw Results – Ratios of Means

-                  Lat  MaxEl   Petty   GPROF    Liu   Wilheit
- JAN MAYEN       70.93   638    **1.38**    0.05    0.18     ---
- THORSHAVN       62.02   736    **0.81**    0.31    0.29     ---
- ST PAUL ISL.    57.17   173    2.32    0.35    **0.73**     ---
- NIKOL'SKOE      55.21   510    **1.38**    0.26    0.46     ---
- HORTA           38.52  2260    **0.91**    0.51    0.64    0.73
- PONTA DELGADA   37.75   868    **0.64**    0.38    0.52    0.57
- SANTA MARIA     36.97   575    1.12    0.65    0.86    **1.02**
- LORD HOWE ISL  -31.53   103    **0.93**    0.57    0.75    0.88
- ISL. JUAN FER  -33.62   857    **0.32**    0.19    0.16    0.29
- GOUGH ISL      -40.35   861    **0.54**    0.27    0.35    0.35
- CHATHAM ISLAN  -43.95   271    **1.01**    0.48    0.59    1.04
- MARION ISL     -46.88  1171    **1.12**    0.41    0.58    0.62
- PORT-AUX-FRAN  -49.35   878    2.43    0.79    **1.15**    1.97
- FALKLAND ISL.  -51.82   433    0.73    0.26    0.35    **1.13**
- MACQUARIE ISL  -54.48   360    1.52    0.43    0.41    **1.00**

## Summary of Raw Results – RMS Difference (mm/month)

-                  Lat  MaxEl   Petty   GPROF    Liu   Wilheit
- JAN MAYEN       70.93   638     **34.**     64.     56.     ---
- THORSHAVN       62.02   736     **42.**     92.     92.     ---
- ST PAUL ISL.    57.17   173     66.     36.     **33.**     ---
- NIKOL'SKOE      55.21   510     **38.**     50.     46.     ---
- HORTA           38.52  2260     **34.**     59.     45.     43.
- PONTA DELGADA   37.75   868     **45.**     71.     54.     57.
- SANTA MARIA     36.97   575     **40.**     46.     41.     41.
- LORD HOWE ISL  -31.53   103     **53.**     74.     65.     62.
- ISL. JUAN FER  -33.62   857     **80.**     97.     97.     91.
- GOUGH ISL      -40.35   861    **144.**    214.    197.    192.
- CHATHAM ISLAN  -43.95   271     45.     49.     57.     **44.**
- MARION ISL     -46.88  1171     **51.**    105.     90.     77.
- PORT-AUX-FRAN  -49.35   878     66.     **20.**     28.     54.
- FALKLAND ISL.  -51.82   433     **21.**     40.     38.     38.
- MACQUARIE ISL  -54.48   360     57.     56.     58.     **53.**

## Hot off the press: Wentz algo.(2003 only)

- Petty
- GPROF
- Wentz

- Petty
- GPROF
- Wentz

- Petty
- GPROF
- Wentz

- Petty
- GPROF
- Wentz

- Corr.  Ratio

- Corr.  Ratio

- Corr.  Ratio

- Corr.  Ratio

## Hotter off the press:  Corrected gauge values from Daqing Yang

- Accounts for
- Gauge type and height above ground
- Precipitation phase
- Wind speed at time of precipitation
- Temperature

## WMO ID   Name                      Lat      Lon
 01001   JAN MAYEN                70.93    -8.67
          NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
Petty       26    1.46    1.30    0.79    0.81   37.07   32.11
GPROF       26    0.04    0.04    0.54    0.52   61.70   69.73
Liu         26    0.16    0.14    0.49    0.44   54.64   62.83

06011   THORSHAVN                62.02    -6.77
          NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
Petty       26    0.83    0.78    0.81    0.81   34.76   41.00
GPROF       26    0.29    0.28    0.51    0.51   89.12   97.14
Liu         26    0.24    0.22    0.55    0.55   93.52  101.33

70308   ST PAUL ISL.             57.17  -170.22
          NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
Petty       26    2.36    1.66    0.68    0.56   67.31   58.41
GPROF       26    0.33    0.23    0.65    0.43   35.83   57.75
Liu         26    0.76    0.54    0.49    0.30   34.58   52.63

-  01001   JAN MAYEN                70.93    -8.67
-           NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
- Petty       26    1.46    1.30    0.79    0.81   37.07   32.11
- GPROF       26    0.04    0.04    0.54    0.52   61.70   69.73
- Liu         26    0.16    0.14    0.49    0.44   54.64   62.83
- 06011   THORSHAVN                62.02    -6.77
-           NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
- Petty       26    0.83    0.78    0.81    0.81   34.76   41.00
- GPROF       26    0.29    0.28    0.51    0.51   89.12   97.14
- Liu         26    0.24    0.22    0.55    0.55   93.52  101.33
- 70308   ST PAUL ISL.             57.17  -170.22
-           NObs   Ratio  Ratio_PC  Corr  Corr_PC   RMS   RMS_PC
- Petty       26    2.36    1.66    0.68    0.56   67.31   58.41
- GPROF       26    0.33    0.23    0.65    0.43   35.83   57.75
- Liu         26    0.76    0.54    0.49    0.30   34.58   52.63

## Conclusions

- Despite two decades of ocean precipitation retrievals from SSM/I, TMI, and AMSR-E and multiple algorithm intercomparisons, this analysis represents the first known *direct* validation of mid- and high-latitude *amounts*.
- Except for Petty algorithm, *apparent* tendency by standard algorithms to underestimate and/or miss precipitation at high latitudes, especially snowfall.
- For greater confidence in the detailed validation results, we urgently need
- Careful assessment of *station biases* relative to surrounding ocean (e.g., importance of local orographic suppression or enhancement of precip)
- Correction of *gauge biases* due to wind+snow, etc., using methodology of Yang et al. applied to S.H. stations.

## Ongoing Work

- Acquire high resolution topography of all islands (not as easy as it sounds!)
- Run mesoscale model simulations of precipitation events to assess orographic influences.
- Funding permitting:  Site visits to assess gauge siting, maintenance, etc.  Also, may place additional recording gauges to assess variability.

## Slide 31

## Slide 32

## Slide 33

## Passive microwave methods over ocean

- Emission/attenuation based methods (10-37 Ghz)
- Viable when reasonably deep rain layer present  (not always true!)
- Quasi-direct when effective rain layer depth can be estimated.
- Complementary spatial and intensity information from different frequencies.
- Use of normalized polarization (e.g., Petty, GPROF) greatly reduces ambiguities due to scattering and background variability.
- Scattering based methods (89 Ghz) viable
- Viable when ice-phase precipitation present in column (not always true!)
- Indirect (statistical) relationship between ice scattering aloft and surface precipitation rate; also, scattering signature may be weak.
- Can complement emission-based retrievals when liquid phase is present.
- Use of polarization (e.g., Spencer, Petty, GPROF) allows separation of cold strongly polarized ocean from cold weakly polarized precipitation.

## Example over the Baltic Sea (Bennartz et al.)

## Passive and active MW aircraft observations of shallow convective snowfall – Wakasa Bay