This document presents a quantitative analysis of orographic precipitation over the Himalayas using TRMM/PR satellite data and a dense network of rain gauges from APHRODITE. The study compares 10 years of monthly TRMM/PR precipitation data to APHRODITE rain gauge observations in 0.05 degree grids. It finds TRMM/PR significantly underestimates summer precipitation over the Himalayas compared to rain gauges. Correlations between the two datasets vary by elevation zone, with TRMM/PR underestimating in most zones except some lower elevations in spring. The monthly PR climatology is adjusted based on regressions with rain gauges and filtered considering slope aspects. The final dataset

1. QUANTITATIVE ESTIMATION OF
OROGRAPHIC PRECIPITATION OVER
THE HIMALAYAS BY USING
APHRODITE’S DENSE NETWORK OF
RAIN-GAUGES AND TRMM/PR
Akiyo Yatagai
（Solar-Terrestrial Environment Laboratory,
Nagoya University, Japan)

2. ASIAN PRECIPITATION -- HIGHLY RESOLVED
OBSERVATIONAL DATA INTEGRATION
TOWARDS EVALUATION OF THE WATER RESOURCES
(APHRODITE’S WATER RESOURCES)
Project Term: I) May 2006 – March 2009, II) April 2009 – March 2011
Yatagai et al. (2009, SOLA),
Yatagai et al. (2012, BAMS)

3. APHRODITE’S ANALYSIS FLOW
Yatagai et al. (2009, SOLA),
Yatagai et al. (2012, BAMS)

4. FOR FURTHER IMPROVEMENT
 Input daily precipitation data
 Input more data
 Improve quality control (QC) algorithm
 Algorithm
 Analysis method (interpolation)
 Analysis strategy (ratio/anomaly interpolation)
 Better climatology
Rain-gauge climatology
GIS technique for ungauged region
(Daly et al., 1994; Hijiman et al.,2001)
Rain-gauge + TRMM/PR

5. INPUT MORE RAIN GAUGES
APHRODITE’s water resources project
Russia
Yatagai et al. (2009)

6. INFORMATION TO THE MODELERS
Yatagai, Xie and Kitoh (2005)
GPCP1DD
Rain-gauge
0.05deg clim
20km model

7. Yatagai et al. (2005)
Xie et al. (2007)
based on
GHCN and
PRISM (China)

8. In 0.05deg. box

9. 0.05 degree
Yatagai and Kawamoto (2008)

10. METHOD (STRATEGY)
 Compare TRMM/PR with rain-gauge observation as
a climatology (10 year average)
 Compare at 0.05 degree grid box (5.5 km square box)
 Concerning about precipitation type (rain/snow)
→compare according to month
→compare according to the altitude

11. MEAN PRECIPITATION AND DIFFERENCE
Rain Gauge PR (NSR) Difference Diff/RG
Jan 18.5 13.1 -5.4 0.29
Feb 16.6 24.4 +7.8 0.47
Mar 24.1 30.9 +6.8 0.28
April 28.8 48.9 +20.0 0.69
May 58.3 88.4 +30.0 0.51
Jun 160.7 148.7 -12.0 0.07
Jul 312.0 209.3 -102.7 0.33
Aug 288.2 180.0 -108.6 0.38
Sep 184.8 133.7 -51.1 0.28
Oct 59.2 49.2 -10.0 0.17
Nov 10.8 8.6 -1.9 0.18
Dec 9.3 6.7 -2.7 0.28
Compared with the RG observations, the PR significantly underestimated
precipitation by 28–38% in summer (July–September), and overestimated in
spring. Yatagai and Kawamoto (2008)

12. CORRELATION AT DIFFERENT LEVELS
FOR ANNUAL PRECIPITATION
Level (m) N R A B
ALL 2695 0.786 0.697 124.210
Z >=4,500 24 0.436 0.136 118.175
3,000> Z >=4,500 127 0.638 0.398 127.305
1,500 > Z >=3,000 241 0.762 0.653 266.799
1,000 > Z >=1,500 153 0.489 0.364 904.554
500 > Z >=1,000 268 0.749 0.790 89.459
250 > Z >= 500 647 0.769 0.775 4.826
0 > Z >= 250 1231 0.817 0.660 155.795
Regression
{PR}=A*{RG}+B
Yatagai and Kawamoto (2008)

13. CORRELATIONS AT DIFFERENT ELEVATION
Yatagai and Kawamoto (2008)

14. JULY
Yatagai and Kawamoto (2008)

15. COMPARISON FOR APRIL
PR underestimates RG ?
higher than 1,500 m a.s.l
PR over estimates RG ?
lower than 1,500 m a.s.l.
PR over estimates RG in
Feb (250- 1000 level)
March (0-1000 level)
April (0- 1500 level)
Yatagai and Kawamoto (2008)

16. N NE E SE S SW W NW
1 degree

18. Summary
• The PR data acquired by the TRMM over 10 years of observation are used to show the
monthly rainfall patterns over the Himalayas.
• To validate and adjust these patterns, we used APHRODITE’s dense network of rain gauges to
measure daily precipitation over Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and
China.
• We then compared TRMM/PR and RG data in 0.05-degree grid cells (an approximately 5.5-km
mesh). Compared with the RG observations, the PR significantly underestimated precipitation
by 28–38% in summer (July–September).
• Significant correlation between TRMM/PR and RG data was found for all months, but the
correlation is relatively low in winter. The relationship is investigated for different elevation
zones, and the PR was found to underestimate RG data in most zones, except for certain zones
in February (250–1000m), March (0–1000m), and April (0–1500m).
• Monthly PR climatology was adjusted on the basis of monthly regressions between the two
sets.
• The RG adjusted PR climatology was filtered which considers the aspect of slopes to remove
random noise.
• The finally available data show clearer double rain-band along the Himalayas and show no
penetrated (interpolated) precipitation to dry Tibet region.

19. References
• Yatagai, A., Xie, P., Kitoh, A. (2005): Utilization of a new gauge-based daily preciptiation dataset
over monsoon Asia for validation of the daily precipitation cliamtology simulated by the MRI/JMA
20-km-mesh AGCM, SOLA, 1, 193-196, doi:10.2151/sola.2005-050.
• Yatagai, A., and H. Kawamoto (2008): Quantitative estimation of orographic precipitation over the
Himalayas by using TRMM/PR and a dense network of rain gauges, SPIE, 7148-11,
doi:10.1117/12.811943.
• Yatagai, A., O. Arakawa and K. Kamiguchi, H. Kawamoto, M. I. Nodzu, A. Hamada (2009): A 44-year
daily gridded precipitation dataset for Asia based on a dense network of rain gauges, SOLA, 5,
137-140, doi:10.2151/sola.2009-035.
• Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi and A. Kitoh (2012): APHRODITE:
Constructing a Long-term Daily Gridded Precipitation Dataset for Asia based on a Dense Network
of Rain Gauges, Bulletin of American Meteorological Society, 93,1401-1415,
• doi:http://dx.doi.org/10.1175/BAMS-D-11-00122.1.
• Yatagai, A., T. N. Krishnamurti, V. Kumar, A. K. Mishra and A. Simon (2014): Use of APHRODITE
rain-gauge based precipitation and TRMM3B43 products for improving Asian monsoon seasonal
precipitation forecasts, J. Climate , 27, 1062-1069.

20. Data used in old version
GHCN
China
Input more gauges
FAO
ASEAN
India
Bhutan
Nepal
Bangladesh
Myanmar
Pakistan
Raingauges used in this study
Orography
0.05 degree
QC
Yatagai and Kawamoto (2008)

21. Annual Precipitation June-September Precipitation
2695 stations 2695 stations
Annual precipitation:
r=0.786 (N>=10)
{PR}=0.697*{RG}+124.2
Monsoon precipitation:
r=0.764 (N>=10)
{PR}=0.586*{RG}+118.0
Yatagai and Kawamoto (2008)