Evaluation of ACME coupled simulation Jack Reeves Eyre, Michael Brunke, and Xubin Zeng (PI) University of Arizona 4/19/3017

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1 Evaluation of ACME coupled simulation Jack Reeves Eyre, Michael Brunke, and Xubin Zeng (PI) University of Arizona 4/19/ Introduction We look at surface variables in the tropical Pacific from a coupled run of ACME ( beta0.A_WCYCL1850S.ne30_oEC_ICG.edison), ERA-Interim and a pre-industrial control run of CESM. We look at meridional means (5 o S to 5 o N) both long term (40-50 years) annual averages and evolution of absolute values and anomalies through 10 years that include a relatively strong El Niño event. The events peak in approximately January of year 251 for ACME, January 252 for CESM, and January 1998 for ERA-Interim (based on Niño 3.4 region sea surface temperature anomaly). Anomalies are calculated for every grid point before taking meridional averages, by subtracting that grid point s monthly climatology. 2. Summary ACME has notable mean state biases in: mixed layer depth (too shallow MLD and too weak zonal gradient in magnitude in ACME); zonal wind stress (associated with over-strong easterly trade winds); net radiation and net heat flux (positive biases in the west Pacific that seem to be related to cloud fraction biases in that region). The spatio-temporal evolution of several fields in ACME differs from ERA-Interim and CESM: sea surface temperature, mixed layer depth, wind stress, radiation and heat fluxes lack clear progression of anomalies from west to east during El Niño events. Key findings and recommendations from these diagnostics and evaluations: The combination of positive net heat flux biases and ocean mixed layer depth (MLD) biases in the west Pacific should lead to a positive SST bias in ACME, but the SST bias is negative. Where is the excess heat going? To address this question, the results from the ACME ocean-only run [driven by near-surface atmospheric data (i.e., the CORE forcing data) with seasonal and interannual variability, rather than with mean seasonal cycle] should be checked. Why doesn t ACME have a clear progression of anomalies from west to east during El Niño events? This could be caused by the ocean-atmosphere coupling (which would be very difficult to diagnose). It is still useful to check the results from the ACME oceanonly run [driven by near-surface atmospheric data (i.e., the CORE forcing data) with seasonal and interannual variability, rather than with mean seasonal cycle]. Check the results from the ACME atmosphere-only (i.e., AMIP) run (driven by observed SST and sea ice with seasonal and interannual variability, rather than with mean seasonal cycle): does it have the same negative cloud bias and positive net radiation flux bias over the western Pacific? does it have the same negative zonal wind stress bias over the western Pacific? These diagnostics would help answer whether the atmospheric model bias, the ocean model bias (e.g., in mixed layer depth and horizontal heat transport), or the ocean-atmosphere coupling is primarily responsible for the deficiencies identified in this Report. 1

2 3. Results 3.1 Sea surface temperature In Figure 1, ERA-Interim shows a clear movement of positive SST anomalies from west Pacific to East Pacific over the year before the El Niño peak (late 1996 to 1998). CESM has a similar feature. ACME has no clear west Pacific to east Pacific movement: the SST anomalies are almost uniformly positive across the Pacific. Mean state (Figure 3a): ACME has a cold bias relative to ERA-Interim, as does CESM (albeit smaller and more uniform). Over east Pacific, ACME s SST changes little or increases slight eastward, in contrast to the decrease of SST in ERA-Interim (or CESM). This difference in SST gradient has possible implications for atmospheric dynamics. 3.2 Surface zonal wind stress and 10 m wind speed (For wind stress, positive values mean wind flowing from west Pacific to east Pacific.) Figure 2 shows that CESM and ERA-Interim both have positive values over the western Pacific (i.e., reversal of trade winds) during the year leading up to the peak El Niño. In contrast, the absolute values remain largely negative in ACME. ERA-Interim and ACME show a progression of positive anomalies from west Pacific to east over this period, while ACME does not show this progression. The annual mean values (Fig. 3b) show ACME has a notable negative bias (easterly trade winds too strong) in the west Pacific. ACME also has a small positive bias in absolute wind speed (Fig. 3c) though this does not result in a positive latent heat flux bias (Fig. 3d), possibly due to the SST bias. 3.3 Net radiation flux (Rnet = SWd SWu + LWd - LWu) ACME has positive long term average Rnet biases in the west Pacific and negative biases in the east (Fig. 3i). The bias in the east is comparable to that of CESM, though that in the west is larger. The bias in Rnet follows the pattern in net shortwave radiation (Rns; Fig. 3g), which is consistent with the cloud bias (Fig. 3f): too little cloud in the west Pacific and too much in the east. Interestingly the pattern of bias in downward longwave radiation (Rdl; Fig. 3h), being negative across the basin (compared with ERA-Interim), goes against the intuitive directly proportional relationship with cloud amount. The negative Rdl bias partially but not totally compensates for the positive Rns bias in the west Pacific, and adds to the negative Rns bias in the east. In terms of the evolution of Rnet during the El Niño events, ACME has a weaker signature then ERA-Interim and CESM (not shown). 3.4 Net heat flux (Qnet = Rnet LHF SHF) This is dominated in the tropical Pacific by radiative and latent heat components, and thus ACME inherits errors from Rnet. In particular, ACME s long term average has a positive bias in the west Pacific (Fig. 3j). CESM has a similar overall pattern of biases, but these are generally smaller than in ACME. As with Rnet, the signal in anomalies is too weak in ACME. Of note in the evolution during El Niño events (not shown) is the sign of Qnet: ERA-Interim and CESM both have a 2

3 net transfer of energy from ocean to atmosphere in the west and central Pacific leading up to and during the El Niño peak; this is largely absent in ACME. 3.5 Ocean mixed layer depth (MLD) (There is a difference in the quantities available for this analysis: for CESM, the monthly maximum MLD calculated by the model is used, while for ACME, the monthly mean calculated by post-processing algorithms is used. We are unsure how this affects comparisons of the absolute values and anomalies. However, the biases compared to CESM are broadly similar to biases relative to Holte-Talley in the standard diagnostic package, reproduced below [Fig. 5].) ACME has a much shallower MLD than CESM (Fig. 4) over the entire tropical Pacific, though part of this may be due to the calculation types, mentioned above. The gradient of ACME s temperature-threshold MLD (tthreshmld in Fig. 4) is of the right sign (long term annual average MLD deeper in the west, consistent with CESM and the Holte-Talley data), but the gradient is much weaker than that from CESM in magnitude. Furthermore, ACME MLD s using the other three methods have the opposite gradient from CESM. The evolution of MLD during El Niño events also differs significantly between CESM and ACME (Fig. 6). CESM has clear coherent anomalous regions (in the El Niño event, but at other times too) while the ACME field is much more noisy. In CESM, negative MLD anomalies build from the west Pacific more than a year before the peak of the El Niño event, while positive anomalies develop in the east Pacific. The situation quickly reverses after the peak of the El Niño, as a strong La Niña develops. In ACME, there is virtually no visually clear pattern of MLD anomalies immediately before, during or after the El Niño event. 3

4 ACME CESM ERA-Interim Figure 1. Monthly mean zonally averaged (5 S to 5 N) sea surface temperature and anomalies. From left to right, ACME absolute values, ACME anomalies, CESM absolute, CESM anomalies, ERA-Interim absolute and ERA-Interim anomalies. The x-axis shows longitude in degrees east. El Niño events occur around January 251 (adjacent to the 251 tickmark) for ACME, January 252 for CESM, and January 1998 for ERA-Interim. For CESM and ERA-Interim, these are followed by La Niña events. Weaker El Niño events also occur in winter of 1992 and 1995 in ERA-Interim. 4

5 ACME CESM ERA-Interim Figure 2. As in Figure 1 but for zonal wind stress (negative values correspond to wind flow from east to west). El Niño events are at 251 (ACME), 252 (CESM) and 1998 (ERA-Interim). 5

6 Figure 3. Long term annual averages of meridional mean (5 o S to 5 o N) for various quantities across the tropical Pacific from ACME, CESM and ERA-Interim. The quantities shown are (left to right, top to bottom): sea surface temperature (as in Fig. 1); zonal wind stress (as in Fig. 2); 10 m wind speed; latent heat flux; sensible heat flux; total cloud amount; net shortwave flux at the surface; downward longwave flux at the surface; net radiation at the surface; net heat flux at the surface. 6

7 Figure 4. As in Fig. 3 but for mixed layer depth, from ACME and CESM only. Note that the quantities displayed differ between ACME (monthly mean MLD) and CESM (monthly maximum MLD). Note also that four different calculation methods are used for ACME MLD. 7

8 Figure 5. Annual mean mixed layer depth from ACME beta0 coupled run (top), observations (middle) and bias (ACME minus observations; bottom). Note the negative bias along the equatorial Pacific, mostly in the range -10 to -75 m. 8

9 ACME CESM Figure 6. As in Fig. 1 but for ocean mixed layer depth. From left to right: ACME monthly mean; anomalies of ACME monthly mean; CESM monthly maximum; anomalies of CESM monthly maximum. 9

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