Toward an Optimal Observational Array for Improving Two Flavors of El Niño Predictions in the Whole Pacific

This paper investigates the optimal observational array for improving the prediction of the El Niño-Southern Oscillation (ENSO) by exploring sensitive areas for target observations of two types of El Niño events in the whole Pacific. A target observation method based on the particle filter and pre-industrial control runs from six coupled model outputs in Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments are used to quantify the relative importance of the initial accuracy of sea surface temperature (SST) in different Pacific areas. The initial accuracy of the tropical Pacific, subtropical Pacific, and extratropical Pacific can all exert influences on both types of El Niño predictions. The relative importance of different areas changes along with different lead times of predictions. Tropical Pacific observations are crucial in decreasing the root mean square error of predictions of all lead times. Subtropical and extratropical observations play an important role in decreasing the prediction uncertainty, especially when the prediction is made before and throughout boreal spring. To consider different El Niño types and different start months for predictions, a quantitative frequency method based on frequency distribution is applied to determine the optimal observations of ENSO predictions. The final optimal observational array contains 31 grid points, including 21 grid points in the equatorial Pacific and 10 grid points in the north Pacific, suggesting the importance of the initial SST conditions for ENSO predictions not only in the tropical Pacific but also in the area outside the tropics. Furthermore, the predictions made by assimilating SST in sensitive areas have better prediction skills in the verification experiment, which can indicate the validity of the optimal observational array designed in this study.

The dependence of mean climate state on shortwave absorption by water vapor

State-of-the-art climate models exhibit significant spread in the climatological value of atmospheric shortwave absorption (SWA). This study investigates both the possible causes and climatic impacts of this SWA inter-model spread. The inter-model spread of global-mean SWA largely originates from the inter-model difference in water vapor shortwave absorptivity. Hence, we alter the water vapor shortwave absorptivity in the Community Earth System Model, version 1, with Atmosphere Model, version 4 (CESM1-CAM4). Increasing the water vapor shortwave absorptivity leads to a reduction in global-mean precipitation and a La Niña-like cooling over the tropical Pacific. The global-mean atmospheric energy budget suggests that the precipitation is suppressed as a way to compensate for the increased SWA. The precipitation reduction is driven by the weakened surface winds, stabilized planetary boundary layer, and surface cooling. The La Niña-like cooling over the tropical Pacific is attributed to the zonal asymmetry of climatological evaporative damping efficiency and the low cloud enhancement over the eastern basin. Complementary fixed SSTs simulations suggest that the latter is more fundamental and that it primarily arises from atmospheric processes. Consistent with our experiments, the CMIP5/6 models with a higher global-mean SWA tend to exhibit the tropical Pacific toward a more La Niña-like mean state, highlighting the possible role of water vapor shortwave absorptivity for shaping the mean-state climate patterns.

A Dynamic Statistical Subseasonal Forecast Model for OLR Over Tropical Pacific Region

How to improve the subseasonal forecast skills of dynamic models has always been an important issue in atmospheric science and service. This study proposes a new dynamical-statistical forecast method and a stable components dynamic statistical forecast (STsDSF) for subseasonal outgoing long-wave radiation (OLR) over the tropical Pacific region in January-February from 2004 to 2008. Compared with 11 advanced multi-model ensemble (MME) daily forecasts, the STsDSF model was able to capture the change characteristics of OLR better when the lead time was beyond 30 days in 2005 and 2006. The average pattern correlation coefficients (PCC) of STsDSF are 0.24 and 0.16 in 2005 and 2006, while MME is 0.10 and 0.05, respectively. In addition, the average value of PCC of the STsDSF model in five years is higher than MME in 7–11 pentads. Although both the STsDSF model and MME show a similar temporal correlation coefficient (TCC) pattern over the tropical Pacific region, the STsDSF model error grows more slowly than the MME error during 8–12 pentads in January 2005. This phenomenon demonstrates that STsDSF can reduce dynamical model error in some situations. According to the comparison of subseasonal forecasts between STsDSF and MME in five years, STsDSF model skill depends strictly on the predictability of the dynamical model. The STsDSF model shows some advantages when the dynamical model could not forecast well above a certain level. In this study, the STsDSF model can be used as an effective reference for subseasonal forecast and could feasibly be used in real-time forecast business in the future.

Improving statistical prediction and revealing nonlinearity of ENSO using observations of ocean heat content in the tropical Pacific

It is well-known that the upper ocean heat content (OHC) variability in the tropical Pacific contains valuable information about dynamics of El Niño–Southern Oscillation (ENSO). Here we combine sea surface temperature (SST) and OHC indices derived from the gridded datasets to construct a phase space for data-driven ENSO models. Using a Bayesian optimization method, we construct linear as well as nonlinear models for these indices. We find that the joint SST-OHC optimal models yield significant benefits in predicting both the SST and OHC as compared with the separate SST or OHC models. It is shown that these models substantially reduces seasonal predictability barriers in each variable – the spring barrier in the SST index and the winter barrier in the OHC index. We also reveal the significant nonlinear relationships between the ENSO variables manifesting on interannual scales, which opens prospects for improving yearly ENSO forecasting.

Reduced El Niño variability in the mid-Pliocene according to the PlioMIP2 ensemble

The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period during which atmospheric CO2 levels were similar to recent historical values (∼400 ppm). Several proxy reconstructions for the mid-Pliocene show highly reduced zonal sea surface temperature (SST) gradients in the tropical Pacific Ocean, indicating an El Niño-like mean state. However, past modelling studies do not show these highly reduced gradients. Efforts to understand mid-Pliocene climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies. In this work, we study El Niño–Southern Oscillation (ENSO) variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period, spatial structure and “flavour”, as well as the tropical Pacific annual mean state in mid-Pliocene and pre-industrial simulations. Results show a reduced ENSO amplitude in the model-ensemble mean (−24 %) with respect to the pre-industrial, with 15 out of 17 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–4-year band. The spatial structure of the dominant empirical orthogonal function shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Although the time-mean zonal SST gradient in the equatorial Pacific decreases for 14 out of 17 models (0.2 ∘C reduction in the ensemble mean), there does not seem to be a correlation with the decrease in ENSO amplitude. The models showing the most “El Niño-like” mean state changes show a similar ENSO amplitude to that in the pre-industrial reference, while models showing more “La Niña-like” mean state changes generally show a large reduction in ENSO variability. The PlioMIP2 results show a reasonable agreement with both time-mean proxies indicating a reduced zonal SST gradient and reconstructions indicating a reduced, or similar, ENSO variability.

A numerical study of the response of tropical Pacific SST to atmospheric forcing

Two sets of atmospheric forcing from NCEP/NCAR 40-year reanalysis project, one based on monthly averaged climatological data and the other on 1982-83 monthly averaged data, are used to derive the global Miami Isopycnic Coordinate Ocean Model (MICOM). These two runs are referred to as the climatological experiments and 1982-83 El Nino experiments. Sensitivity tests of tropical Pacific SST to different bulk parameterizations of air-sea heat and momentum fluxes are carried out in the two experiments. Primary results show that constant transfer coefficients (1.2 × 10-3) for heat flux greatly overestimate the tropical Pacific SST, whereas the Liu-Katsaros-Businger (Liu et al. 1979) method can significantly improve the SST simulation especially under very low-wind speed conditions. On the other hand, Large and Pond (1982) formulation of the drag coefficient made little difference on the tropical Pacific SST simulation although it might modify the surface ocean circulation. The SST seasonal cycle and interannual variability of tropical Pacific SST are also examined in this study. Since SST is the most important oceanic parameter that provides the link between the atmosphere and the ocean, this evaluation of different parameterization schemes may facilitate future studies on coupling ocean-atmospheric numeric models.

A new genus and seven new species of chrysopetalids (Annelida, Chrysopetalidae) from the Tropical Eastern Pacific

Chrysopetalids annelids have been little studied in the Tropical Eastern Pacific (TEP), with only 24 species recorded in the region. Most records are from northwestern Mexico and Costa Rica, leaving many sites along the Tropical Pacific coast of America unexplored. Furthermore, there are species recorded and described from the region with problems in their status, including questionable records, modest illustrations or descriptions, and lost type material. This paper aims to improve the knowledge of this family in the TEP. Almost 290 specimens were revised, provided from five scientific collections, covering 51 sites along the TEP and nearby. Two subfamilies: Calamyzinae and Chrysopetalinae, nine genera and 20 species were determined. Of these, ten species have been previously recorded, three are indeterminable and seven are new species: Paleanotus karlyae n. sp., Arichlidon mucropaleum n. sp., Bhawania bastidai n. sp., Chrysopetalum mexicanum n. sp., C. tovarae n. sp. A new genus is proposed, Bhawatsonia n. gen. which includes two new species, B. fusa n. sp. as its type species, B. nenoae n. sp. and, the new combination and neotype of B. purpurea n. comb. An updated and revised checklist of all chrysopetalids species recorded in the region is included, currently composed of 16 genera, 30 species, and four morphospecies.