Zeng-Zhen Hu (1) Edwin. K. Schneider (1,2) Uma S. Bhatt (3) Benjamin P. Kirtman (1,2) (1)COLA, Calverton, MD (2) SCS, George Mason University, Fairfax, VA (3) IARC/Frontier, U. of Alaska, AK Potential Mechanism for Response of ENSO Variability to Change in Land Surface Energy Budget

Questions Q1: Is there any influence of the land surface property change on ocean and on air-sea coupling, including the mean state of tropical climate and ENSO variability ? Q2: What is the mechanism behind the influence ? For example, what are the relative contributions of the changed mean state and ‘atmospheric noise’ on the tropical climate and how is the sensitivity change?

Models AGCM: COLA spectral, T30 (5˚ lon by 4˚ lat), L18 Mass flux convection scheme Predictive clouds Prognostic land surface, Simplified SiB Deep convection parameterized OGCM: Princeton GFDL MOM2 3˚ by 3˚ (+ enhanced tropical resolution), 20 levels (4000m) Realistic boundaries & bottom topography Sub-grid eddies not parameterized Thermodynamic sea ice CGCM: No flux corrections Air-sea exchanges every 24 hours Remove climate trends by demean, Lanczos filter (20 yr) lower frequencies, linearly de-trend Model Details in Dewitt and Schneider (1999), Mon. Wea. Rev., 127,

Experiments COUOCN Active Components Atmosphere, Ocean, & Land Atmosphere & Ocean Length of Simulations 190 years82 years OCN (Sensitivity run) Layer 2-3 soil wetness fixed to COU annual cycle, fully coupled between ocean and atmosphere COU (Control run) Fully coupled among land, atmosphere, ocean Deep Soil Zone Layer 3: ~ m Surface zone layer 1: ~0.02m Root soil zone Layer 2: ~ m Soil wetness specification Simulations About the experiments: Bhatt, U. S., E. K. Schneider, and D. G. Dewitt, 2003: Influence of North American land processes on North Atlantic SST variability. Global and Planetary Change, 37, doi: /S (02)00190-X.

Land Surface Becomes an Energy Sink in the Sensitivity Run (unexpected and unphysical) Surface Energy Budget: Sink over land, source over E. Tropical Pacific; SH: Sink over the land; LH: Source over the E. Tropical Pacific;

The Land Surface Energy Sink may be reinforced by unexpected feedback processes: permanent soil moisture source-more evaporation and cloud-less downward shortwave radiation- cooling land surface

Mean State Change of Tropical Climate A: TS: Reduces E-W temperature contrast; Precipitation: Shifts land/sea partition of P toward the oceans; SLP: Favors a negative phase of SO.

Mean State Change of Tropical Climate A: Ocean subsurface T: Reduces E-W temperature contrast;

Mean State Change of Tropical Climate B: (X-Z cross section along Equator) Temperature: Cools land & warms oceans; U: Modifies Walker cell; Div/Con: Div. over land & Con. over oceans, consistent with T/U change.

Mean State Change of Tropical Climate C: Ocean Wind Stress: Convergence in E. Tropical Pacific; W: Downwelling in E. Tropical Pacific; Thermocline Depth: Deepening in E. Tropical Pacific;

SST Variance Decreases in Central & Eastern Tropical Pacific in the Sensitivity Experiment

The ENSO becomes Less Energetic in the Sensitivity Experiment

The ENSO Frequencies do not be Changed much in the Sensitivity Experiment

Changes of the Mean State of the Tropical Climate & ENSO variability Fixing deep soil moisture results in a unphysical surface energy sink over land, which may be reinforced by an unexpected feedback. The energy sink causes the following mean state and ENSO variability changes: A: Reduces SST contrast between the eastern and western tropical Pacific; B: Favors negative SO; C: Shifts the land/sea partition of precipitation toward the oceans; D: Changes the wind fields and their divergences; E: Causes downwelling & deepening the thermocline in the eastern tropical Pacific; F: Reduces SST variability in the central and eastern tropical Pacific; Makes the ENSO variability less energetic; G: Has a small influence on the ENSO frequencies.

Intermediate Coupled Model & Experiment Designs Model: Zebiak-Cane model modified by Kirtman and Shopf (1998). The model with self-sustained ENSO cycle of about 5 years. Experiments: Test the influence of ‘atmospheric noise (1 mon -1 yr)’ and the mean state changes on the ENSO variability. Details of the model are given in: Kirtman & Shopf: 1998, J. Climate.

Possible Mechanism A: Atmospheric noise Role of atmospheric noise (time scales < 1 year) is small.

Possible Mechanism B: Mean state change The role of mean wind stress differences is crucial

Possible Mechanism C: Sensitivity change

Interpretation of the Sensitivity Chang 1.Definition of Sensitivity: Covariance of the wind stress and Nino 3 SST divided by the variance of Nino 3 SST. 2.Means of positive differences (OCN-COU) in the central and eastern tropical Pacific are: (a) Given the same wind stress anomaly, the OCN simulation would have a weaker Nino 3 SSTA than COU. (b) The Nino 3 SST variability becomes less sensitive to the zonal wind stress in OCN than in COU. Therefore, from the view of sensitivity change, the Nino 3 SST variability would become smaller in OCN than in COU if the wind stress was the same. (c) But the wind stress is different. The westerly anomalies of wind stress of OCN-COU further reinforce the weakening in the sensitivity.

Possible Mechanism A: Mean state change plays a key role in determining the ENSO variance change. B: The change of the sensitivity of air- sea coupling favors the reduction of ENSO variance. C: The influence of amplitude change of atmospheric noise on ENSO variance change is minor.

1.Fixing deep soil moisture results in a unphysical and unexpected surface energy sink over land, which may be reinforced by unexpected feedbacks, cooling in the tropical land. 2.The cooling alters the mean state of tropical climate and makes the ENSO variability less energetic, but the influence on ENSO frequency is small. 3. Mean state change, not the decreased atmosphere noise amplitude, plays a crucial role in determining the ENSO variance change. 4.The unexpected land surface energy sink shows the potential impact of natural and anthropogenic induced change in the land-surface energy budget on ENSO variability and also on mean state of tropical climate. 5.To study tropical climate variability, should use a land-ocean- atmosphere fully coupled model. Summary

Two Implications: 1.In global warming scenario: Warming over land is normally larger than that over ocean  ENSO variability may increase in global warming scenario. 2. Amazon deforestation : When the Amazonian tropical forests were replaced by degraded grass, there was an increase in tropical land Ts, which might lead to an increase in ENSO variability. This is true in our new experiments.

Further Information and Acknowledgements : Further Information : Web page: Submission: J. Geophy. Res., Acknowledgements : This research was supported by the Center for Land Atmosphere Ocean Studies (COLA), the Frontier Research System for Global Change through IARC/Frontier, NSF (ATM , AMM , & ATM ), NOAA (NA 96-GP0056), NASA (NAG ), and DOE (De-FG02-01ER63526). The authors are indebted to L. Bengtsson, P. Schopf, F.-F. Jin, B. Huang, L. Marx, P. Dirmeyer, D. Straus, and M. Zhao for their discussion and suggestions. We would like to thank Christopher Swingley (IARC/Frontier) for assistance with computer issues.

1.Fixing deep soil moisture results in a unphysical and unexpected surface energy sink over land, which my be reinforced by unexpected feedbacks, cooling in the tropical land. 2.The cooling alters the mean state of tropical climate and makes the ENSO variability less energetic, but the influence on ENSO frequency is small. 3. Mean state change, not the decreased atmosphere noise amplitude, plays a crucial role in determining the ENSO variance change. 4.The unexpected land surface energy sink shows the potential impact of natural and anthropogenic induced change in the land-surface energy budget on ENSO variability and also on mean state of tropical climate. 5.To study tropical climate variability, should use a land-ocean- atmosphere fully coupled model. Summary

Atmospheric Noise Change

Implication I: Global warming Scenario (IPCC, 2001) Figure 9.10: The multi-model ensemble annual mean change of the temperature (color shading), its range (thin blue isolines) (Unit: °C) and the multi-model mean change divided by the multi-model standard deviation (solid green isolines, absolute values) for the CMIP2 scenarios at the time of CO2-doubling. Warming over land is larger than that over ocean; It amplifies the ENSO variability.

Implication II: Land use change (Nobre, Sellers, & Shukla, 1991, J. Climate) When the Amazonian tropical forests were replaced by degraded grass, there was a significant increase in tropical Ts and in subtropical precipitation, and a decrease in tropical precipitation. Based on the conclusion of the present study, cooling (warming) over the Amazon might result in a reduction (enhancement) of ENSO variability. Thus, Amazon deforestation might lead to an increase in ENSO variability.

1000 hPa Specific Humidity

1000 hPa Relative Humidity

Long-wave and Short-wave Radiations

The Results of Kirtman and Shopf (1998, J. Climate, ) Detailed change of surface wind stress is important !!

The Results of Kirtman and Shopf (1998, J. Climate, )