Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J....
-
Upload
kelly-hunt -
Category
Documents
-
view
216 -
download
0
Transcript of Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J....
![Page 1: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/1.jpg)
Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes
G.J. Huffman1,2, R.F. Adler1, D.T. Bolvin1,2, E.J. Nelkin1,2
1: NASA/GSFC Laboratory for Atmospheres2: Science Systems and Applications, Inc.
Outline
1. The Problem
2. Prior Work
3. Instantaneous Rates
4. Next Steps
5. Summary
![Page 2: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/2.jpg)
1. THE PROBLEM
Retrievals are more challenging at high latitudes
- Different T, RH profiles; sfc. T; tropopause and melting levels
- Generally light precipitation
- Frozen/icy surface knocks out scattering channels
Validation is also more challenging
- Gauges are sparse
- Gauge undercatch more severe
- Radar hasdifficulties with snow and bright band
![Page 3: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/3.jpg)
2. PRIOR WORK
Best solution involves high-frequency microwave channels
- Try to slice atmospheric signal away from difficult surface issues
Some approximate alternatives already exist that can
- Provide answers relatively quickly
- Fill inter-swath gaps in the high-frequency estimates when they arrive
- Stand in for high-frequency estimates where they falter
- Provide a multi-decadal record
One alternative is to work with OLR Precipitation Index (OPI)
- Xie and Arkin (1998) showed that deviations in OLR from local climatology are related to deviations in precip from local climatology
- GPCP uses this OPI in the pre-SSM/I period at high latitudes
- It is available in monthly and pentad files; we have not pursued it at the instantaneous level due to the higher information content used in the next product
![Page 4: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/4.jpg)
2. PRIOR WORK (cont.)
The alternative we chose is working with satellite soundings
- Susskind et al. (1997) developed a calibrated cloud volume proxy from TOVS
Precip = revised cloud depth * cloud fraction * ƒ ( latitude, season )
- The calibration is TOVS swath data vs. daily FGGE station precip data
- Results show low precip rates, very high fractional occurrence
• done as a regression• uses instantaneous data as a proxy for daily data• has only one sample for the day
cloud top ht. – ( scaled RH + scaled cloud fraction )
0 = sat. sfc500 mb9 = dry “
0 = overcast4.5 = clear
![Page 5: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/5.jpg)
2. PRIOR WORK –GPCP Monthly SG
Version 1 deficiencies
- Data voids at high lat.
- Low values in high-lat. ocean
Susskind et al. (1997) TOVS adapted for use in Version 2
- Recalibrated to SSM/I at mid-lat., gauge at high lat.
The accuracy of interannual fluctuations at high lat. is not yet resolved
TOVS algorithm currently applied to AIRS (beginning May 2005)
GPCP V.1 (mm/d) 1988-99
GPCP V.2 (mm/d) 1988-99
![Page 6: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/6.jpg)
2. PRIOR WORK – GPCP One-Degree Daily
SG experience encouraged us to use TOVS at high lat. in 1DD
- By month, at 40°N and 40°S separately, compute rate and occurrence adjustment to daily TOVS to match low-latitude results (from Threshold Matched Precipitation Index), and apply in the appropriate hemisphere 40°-pole
- Very appealing results; minimal data boundaries
TOVS algorithm currently applied to AIRS (beginning May 2005)
QuickTime™ and aVideo decompressor
are needed to see this picture.
![Page 7: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/7.jpg)
2. PRIOR WORK – GPCP One-Degree Daily (cont.)
Daily averages over the Baltic Sea basin show good skill
- Bias is related to gauge adjustment from monthly product
- Day-to-day events entirely driven by TOVS (in parallel to IR in the band 40°N-S)
Figure courtesy of B. Rudolf, DWD/GPCC
![Page 8: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/8.jpg)
3. INSTANTANEOUSRATES
How best to develop an instantaneous sounding-based scheme?
As we got serious, the A-Train showed up!
- CloudSat provides a “curtain” of cloud/ precip data at all latitudes
- AMSR-E provides 2D maps of precip
- Here, sfc-based CloudSat echo corresponds to AMSR-E rain area
- CloudSat echo based above the sfc shows up in AIRS, but not AMSR-E
A
B
C
A
B
C
C B A
Reflectivity Low High
AMSR-E AIRS
CloudSat
![Page 9: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/9.jpg)
3. INSTANTANEOUS RATES (cont.)
As a first step, we calibrated Susskind et al. (1997) AIRS to AMSR-E for Jan. 2004
- Compare AIRS, AMSR-E, calibrated AIRS for one descending node
- Qualitative agreement
0416-0505 UTC 19 January 2004
AMSR-E AIRS Cal. AIRS
![Page 10: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/10.jpg)
3. INSTANTANEOUS RATES (cont.)
Example of AIRS filling in a feature over snow where AMSR cannot reliably estimate
AMSR-E
CalibratedAIRS
16 January 2004 mm/d
16 January 2004 mm/d
Land precip feature
![Page 11: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/11.jpg)
3. INSTANTANEOUS RATES (cont.)
Month-average of Susskind et al. (1997) AIRS calibrated to AMSR-E for July 2006
- calibration by lat. bands:
Ocean: 90-30°N, 30°N-S, 30-90°SLand: 90-40°N, 40·°N-S, (40-90°S)Coast: global Cal.AIRS (mm/d) July 2006
AMSR (mm/d) July 2006
Diff. (mm/d) July 2006
- Note opposing within-band (east-west) differences
- Implies regime dependence – same scaled cloud volume maps to different AMSR-E rain rates in different places
![Page 12: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/12.jpg)
4. NEXT STEPS
Design and implement a new AIRS cloud volume scheme based on comparison with AMSR-E and CloudSat
Develop a merged AMSR-E / AIRS swath dataset
- How can we gracefully transition from AMSR-E to AIRS at high latitudes and in cold/frozen land?
Apply the revised cloud volume scheme to ATOVS and TOVS to develop an improved long-term record at high latitudes
Throughout, particularly with the operational ATOVS, sounding retrievals work best in clear cases and worst (or fail) for precipitating cases
Explore model data- Include model precip in high-lat. comparisons- Consider similar profile-based estimates for models (T and RH profiles better
than precip?)- Look toward combinations of observation- and model-based estimates
![Page 13: Near-Term Prospects for Improving Quantitative Precipitation Estimates at High Latitudes G.J. Huffman 1,2, R.F. Adler 1, D.T. Bolvin 1,2, E.J. Nelkin 1,2.](https://reader031.fdocuments.us/reader031/viewer/2022032200/56649f495503460f94c6acea/html5/thumbnails/13.jpg)
5. SUMMARY
Historically, we lack the physically direct sensors for high-latitude and cold-region precip that are available for tropical rain
The Susskind et al. (1997) scaled cloud volume algorithm for TOVS (and AIRS) has seen successful use in GPCP Version 2 monthly and 1DD
Early development work with AMSR-E and CloudSat data seems promising for an instantaneous version
Once high-frequency microwave sensors/algorithms are in place, scaled cloud volume could serve at high latitudes as IR serves at low, by providing
- Lower instantaneous skill, but availability to fill holes
- A long record