Awaji, Toshiyuki

The interannual-decadal variability of the wintertime mixed layer depths (MLDs) over the North Pacific is investigated from an empirical orthogonal function (EOF) analysis of an ensemble of global ocean reanalyses. The first leading EOF mode represents the interannual MLD anomalies centered in the eastern part of the central mode water formation region in phase opposition with those in the eastern subtropics and the central Alaskan Gyre. This first EOF mode is highly correlated with the Pacific decadal oscillation index on both the interannual and decadal time scales. The second leading EOF mode represents the MLD variability in the subtropical mode water (STMW) formation region and has a good correlation with the wintertime West Pacific (WP) index with time lag of 3 years, suggesting the importance of the oceanic dynamical response to the change in the surface wind field associated with the meridional shifts of the Aleutian Low. The above MLD variabilities are in basic agreement with previous observational and modeling findings. Moreover the reanalysis ensemble provides uncertainty estimates. The interannual MLD anomalies in the first and second EOF modes are consistently represented by the individual reanalyses and the amplitudes of the variabilities generally exceed the ensemble spread of the reanalyses. Besides, the resulting MLD variability indices, spanning the 1948–2012 period, should be helpful for characterizing the North Pacific climate variability. In particular, a 6-year oscillation including the WP teleconnection pattern in the atmosphere and the oceanic MLD variability in the STMW formation region is first detected.

Intercomparison and evaluation of the global ocean surface mixed layer depth (MLD) fields estimated from a suite of major ocean syntheses are conducted. Compared with the reference MLDs calculated from individual profiles, MLDs calculated from monthly mean and gridded profiles show negative biases of 10–20 m in early spring related to the re-stratification process of relatively deep mixed layers. Vertical resolution of profiles also influences the MLD estimation. MLDs are underestimated by approximately 5–7 (14–16) m with the vertical resolution of 25 (50) m when the criterion of potential density exceeding the 10-m value by 0.03 kg m−3 is used for the MLD estimation. Using the larger criterion (0.125 kg m−3) generally reduces the underestimations. In addition, positive biases greater than 100 m are found in wintertime subpolar regions when MLD criteria based on temperature are used. Biases of the reanalyses are due to both model errors and errors related to differences between the assimilation methods. The result shows that these errors are partially cancelled out through the ensemble averaging. Moreover, the bias in the ensemble mean field of the reanalyses is smaller than in the observation-only analyses. This is largely attributed to comparably higher resolutions of the reanalyses. The robust reproduction of both the seasonal cycle and interannual variability by the ensemble mean of the reanalyses indicates a great potential of the ensemble mean MLD field for investigating and monitoring upper ocean processes.

Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.

Monthly averaged total volume transport of the Indonesian throughflow (ITF) estimated by 14 global ocean data assimilation (ODA) products that are decade to multi-decade long are compared among themselves and with observations from the INSTANT Program (2004-2006). The ensemble averaged, time-mean value of ODA estimates is 13.6 Sv (1 Sv = 106 m3/s) for the common 1993-2001 period and 13.9 Sv for the 2004-2006 INSTANT Program period. These values are close to the 15-Sv estimate derived from INSTANT observations. All but one ODA time-mean estimate fall within the range of uncertainty of the INSTANT estimate. In terms of temporal variability, the average scatter among different ODA estimates is 1.7 Sv, which is substantially smaller than the magnitude of the temporal variability simulated by the ODA systems. Therefore, the overall “signal-to-noise” ratio for the ensemble estimates is larger than one. The best consistency among the products occurs on seasonal-to-interannual time scales, with generally stronger (weaker) ITF during boreal summer (winter) and during La Nina (El Nino) events. The averaged scatter among different products for seasonal-to-interannual time scales is approximately 1 Sv. Despite the good consistency, systematic difference is found between most ODA products and the INSTANT observations. All but the highest-resolution (18-km) ODA product show a dominant annual cycle while the INSTANT estimate and the 18-km product exhibit a strong semi-annual signal. The coarse resolution is an important factor that limits the level of agreement between ODA and INSTANT estimates. Decadal signals with periods of 10-15 years are seen. The most conspicuous and consistent decadal change is a relatively sharp increase in ITF transport during 1993-2000 associated with the strengthening tropical Pacific trade wind. Most products do not show a weakening ITF after the mid-1970s’ associated with the weakened Pacific trade wind. The scatter of ODA estimates is smaller after than before 1980, reflecting the impact of the enhanced observations after the 1980s. To assess the representativeness of using the average over a three-year period (e.g., the span of the INSTANT Program) to describe longer-term mean, we investigate the temporal variations of the three-year low-pass ODA estimates. The median range of variation is about 3.2 Sv, which is largely due to the increase of ITF transport from 1993 to 2000. However, the three-year average during the 2004-2006 INSTANT Program period is within 0.5 Sv of the long-term mean for the past few decades.

Spurred by the sustained operation and new development of satellite and in-situ observing systems, global ocean state estimation efforts that gear towards climate applications have flourished in the past decade. A hierarchy of estimation methods is being used to routinely synthesize various observations with global ocean models. Many of the estimation products are available through public data servers. There have been an increasingly large number of applications of these products for a wide range of research topics in physical oceanography as well as other disciplines. These studies often provide important feedback for observing systems design. This white paper describes the approaches used by these estimation systems in synthesizing observations and model dynamics, highlights the applications of their products for climate research, and addresses the challenges ahead in relation to the observing systems. Additional applications to study climate variability using an ensemble of state estimation products are described also by a white paper by Stammer et al.

Analyzing ocean variability, understanding its importance for the climate system, and quantifying its socio-economic impacts are among the primary motivations for obtaining ongoing global ocean observations. There are several possible approaches to address these tasks. One with much potential for future ocean information services and for climate predictions is called ocean synthesis, and is concerned with merging all available ocean observations with the dynamics embedded in an ocean circulation model to obtain estimates of the changing ocean that are more accurate than either system alone can provide. The field of ocean synthesis has matured over the last decade. Several global ocean syntheses exist today and can be used to investigate key scientific questions, such as changes in sea level, heat content, or transports. This CWP summarizes climate variability as “seen” by several ocean syntheses, describes similarities and differences in these solutions and uses results to highlight developments necessary over the next decade to improve ocean products and services. It appears that multi-model ensemble approaches can be useful to obtain better estimates of the ocean. To make full use of such a system, though, one needs detailed error information not only about data and models, but also about the estimated states. Results show that estimates tend to cluster around methodologies and therefore are not necessarily independent from each other. Results also reveal the impact of a historically under-sampled ocean on estimates of inter-decadal variability in the ocean. To improve future estimates, we need not only to sustain the existing observing system but to extend it to include full-depth ARGO-type measurements, enhanced information about boundary currents and transports through key regions, and to keep all important satellite sensors flying indefinitely, including altimetry, gravimetry and ice thickness, microwave SST observations, wind stress measurements and ocean color. We also need to maintain ocean state estimation as an integral part of the ocean observing and information system.