1 Department of Earth & Atmospheric Sciences, Univ. of Houston

1. Investigation of Atmospheric Recycling Rate from Observation and ModelPI: 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: 1979-2012 SSM/I (V6) Spatial: 0.25º× 0.25º; Temporal: 1988-present 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: -0.82 ± 1.11 %/decade Recycling 2 = (GPCP P)/(SSM/I W) Recycling 2: -0.65 ± 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 RatePositive 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 Lowpass Filtered Precipitation 0.002 ± 0.02 mm/decade 3.8 ± 1.71 mm/decade Wet Area Dry Area -0.48 ± 0.42 mm/decade -0.003 ± 0.006 mm/decade Control Run (fixed) Historic Run

12. GISS Model Results Lowpass Filtered Column Water -0.06 ± 0.02 mm/decade 1.15 ± 0.16 mm/decade Wet Area Dry Area 0.49 ± 0.12 mm/decade 0.06 ± 0.02 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 (1988-2009), Environmental Research Letters, doi:10.1088/1748-9326/6/3/034017. 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 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 Lowpass Filtered Temperature -0.04 ± 0.01 mm/decade 0.61 ± 0.1 mm/decade Wet Area Dry Area 0.52 ± 0.07 mm/decade -0.04 ± 0.01 mm/decade Control Run (fixed) Historic Run

18. GISS Model Results Lowpass Filtered Omega (dP/dt) -0.016 ± 0.37 Pa/day/decade -0.32 ± 0.23 Pa/day/decade Wet Area Dry Area -0.03 ± 0.15 Pa/day/decade -0.04 ± 0.28 Pa/day/decade Control Run (fixed) Historic Run