1. Investigation of Atmospheric Recycling Rate from Observation and Model PI: Xun Jiang1; Co-I: Yuk L. Yung2
1 Department of Earth & Atmospheric Sciences, Univ. of Houston
2 Division of Geological & Planetary Sciences, Caltech
NEWS Science Team Meeting, May 1-2, 2012

2. Overview Motivation Data & Model Observational Study Model Results
Conclusions

3. Motivation
The recycling rate (or resident time) of atmospheric moisture is an important index of the climate change.
Spatial patterns of temporal variations in precipitation, water vapor, and recycling rate will enrich our knowledge of the hydrological cycle
To better understand the response of hydrological cycle to global warming

4. Data & Model Data I) Water Vapor
Special Sensor Microwave/Imager (SSM/I) (V6)
Spatial: 0.25º× 0.25º; Temporal: 1988-present
II) Precipitation
Global Precipitation Climatology Project (GPCP)
Spatial: 2.5º× 2.5º; Temporal:
SSM/I (V6)
Model
NASA Goddard Institute for Space Studies (GISS)-HYCOM Model
Historic Run: Historic greenhouse gases are included.
Control Run: Concentrations of greenhouse gases are fixed.

5. Recycling Rate Total Monthly Precipitation (P)
Recycling Rate (R) = _________________________________________
Mean Precipitable Water Vapor (W)
_ _ _
∆R / R = ∆P / P - ∆W / W
(The ratio of temporal variation to time mean)
[Chahine et al., 1997]

6. Trends in Oceanic Precipitation, Water Vapor, and Recycling Rates [Li et al., ERL 2011]
Deseasonalized & Lowpass Filtered Time Series
SSM/I: 0.13 ± 0.63 %/decade
GPCP: 0.33 ± 0.54 %/decade
SSM/I: 0.97 ± 0.37 %/decade
Recycling 1 = (SSM/I P)/(SSM/I W)
Recycling 1: ± 1.11 %/decade
Recycling 2 = (GPCP P)/(SSM/I W)
Recycling 2: ± 0.51 %/decade
ENSO Signals have been removed by a multiple regression method.
Lowpass filter has been applied to remove high frequency signals.

7. Recycling Rate Positive at ITCZ // Negative at two sides of ITCZ
Recycling Rate1 = (SSM/I Precipitation)/(SSM/I H2O)

8. Precipitation & Water Vapor
Temporal variation is stronger in precipitation than in water vapor, which results to the positive (negative) trend of recycling rate in the high (low) precipitation region.

9. Spatial Pattern of the Mean Precipitation

10. Temporal Variations of Precipitation
Wet Area
(P > 200 mm/mon)
6.57 ± 4.72 mm/decade
Dry Area
(P < 50 mm/mon)
-0.98 ± 0.91 mm/decade
ENSO Signals have been removed by a multiple regression method.
Lowpass filter has been applied to remove high frequency signals.

11. GISS Model Results Wet Area Dry Area Lowpass Filtered Precipitation
0.002 ± 0.02 mm/decade
3.8 ± 1.71 mm/decade
Wet Area
Dry Area
± mm/decade
-0.48 ± 0.42 mm/decade
Control Run (fixed)
Historic Run

12. GISS Model Results Wet Area Dry Area Lowpass Filtered Column Water
-0.06 ± 0.02 mm/decade
1.15 ± 0.16 mm/decade
Wet Area
Dry Area
0.06 ± 0.02 mm/decade
0.49 ± 0.12 mm/decade
Control Run (fixed)
Historic Run

13. Conclusions
The recycling rate has increased in the ITCZ and decreased in the neighboring regions over the past two decades.
2) Temporal variation is stronger in precipitation than in water vapor, which results to the positive (negative) trend of recycling rate in the high (low) precipitation region.
3) Model suggests that the increasing greenhouse gas forcing affects the temporal variation of precipitation, contributing to precipitation extremes.
References:
Li, L., X. Jiang, M. Chahine, E. Olsen, E. Fetzer, L. Chen, and Y. Yung, 2011: Recycling rate of atmospheric mositure over the past two decades ( ), Environmental Research Letters, doi: / /6/3/ Paper was highlighted by the editor of the Environmental Research Letters.
Trammell, J., X. Jiang, L. Li, M. Liang, and J. Zhou, 2013: Investigation of Precipitation over wet and dry areas from observation and model, To be submitted to Environmental Research Letters.

14. Acknowledgments Thank You! NASA ROSES-2010 NEWS grant NNX13AC04G
Liming Li (UH), James H. Trammell (UH), Eric J. Fetzer (JPL), Moustafa T. Chahine (JPL), Edward T. Olsen (JPL)
Thank You!

16. Trends in Precipitation and Water Vapor
Deseasonalized & Lowpass Filtered Timeseries
SSM/I+GPCP: 0.26 ± 0.41 %/decade
GPCP: 0.08 ± 0.43 %/decade
SSM/I: 1.01 ± 0.39 %/decade
[Li et al., ERL 2011]
Weak linear trend in precipitation is much smaller than the linear trend
(1.4 ± 0.5% per decade) in the previous study (Wentz et al., 2007).

17. GISS Model Results Wet Area Dry Area Lowpass Filtered Temperature
-0.04 ± 0.01 mm/decade
0.61 ± 0.1 mm/decade
Wet Area
Dry Area
-0.04 ± 0.01 mm/decade
0.52 ± 0.07 mm/decade
Control Run (fixed)
Historic Run

18. GISS Model Results Wet Area Dry Area Lowpass Filtered Omega (dP/dt)
± 0.37 Pa/day/decade
-0.32 ± 0.23 Pa/day/decade
Wet Area
Dry Area
-0.04 ± 0.28 Pa/day/decade
-0.03 ± 0.15 Pa/day/decade
Control Run (fixed)
Historic Run