SST Fields Research Articles

Tree Rings Reveal ENSO in the Last Millennium

AbstractWe present new climate field reconstructions (CFR) of tropical Pacific ENSO sea surface temperatures (HadISST) for the boreal winter season using a circum‐Pacific tree‐ring network from known El Niño rainfall impact regions. We use two different CFR methods: Point‐by‐Point Regression (PPR) and reduced‐space Orthogonal Spatial Regression (OSR). Both methods produce reconstructions with high validation skill, but OSR is preferred because it has less spatial noise and is more efficient. Only the leading EOF of the SST field (EOF1) can be skillfully reconstructed by either method; EOF2 does not validate. The success of EOF1 reflects its importance for ENSO rainfall impacts over land; the failure with EOF2 is from the lack of these impacts. EOF1 allows for the reconstruction of many ENSO indices, including the ENSO Longitudinal Index (ELI). We also find evidence in our reconstructions for a recent increase in ENSO activity.

A Simple Statistical Postprocessing Scheme for Enhancing the Skill of Seasonal SST Predictions in the Tropics

Abstract Seasonal prediction systems are subject to systematic errors, including those introduced during the initialization procedure, that may degrade the forecast skill. Here we use a novel statistical postprocessing correction scheme that is based on canonical correlation analysis (CCA) to relate errors in ocean temperature arising during initialization with errors in the predicted sea surface temperature fields at 1–12-month lead time. In addition, the scheme uses CCA of simultaneous SST fields from the prediction and corresponding observations to correct pattern errors. Finally, simple scaling is used to mitigate systematic location and phasing errors as a function of lead time and calendar month. Applying this scheme to an ensemble of seven seasonal prediction models suggests that moderate improvement of prediction skill is achievable in the tropical Atlantic and, to a lesser extent, in the tropical Pacific and Indian Ocean. The scheme possesses several adjustable parameters, including the number of CCA modes retained, and the regions of the left and right CCA patterns. These parameters are selected using a simple tuning procedure based on the average of four skill metrics. The results of the present study indicate that errors in ocean temperature fields due to imperfect initialization and SST variability errors can have a sizable negative impact on SST prediction skill. Further development of prediction systems may be able to remedy these impacts to some extent. Significance Statement The prediction of year-to-year climate variability patterns, such as El Niño, offers potential benefits to society by aiding mitigation and adaptation efforts. Current prediction systems, however, may still have substantial room for improvement due to systematic model errors and due to imperfect initialization of the oceanic state at the start of predictions. Here we develop a statistical correction scheme to improve prediction skill after forecasts have been completed. The scheme shows some moderate success in improving the skill for predicting El Niño and similar climate patterns in seven prediction systems. Our results not only indicate a potential for improving prediction skill after the fact but also point to the importance of improving the way prediction systems are initialized.

The Roles of Atmospheric and Air–Sea Interaction Processes in Causing the Eastward Extension of the Western North Pacific Monsoon Trough in Boreal Summer

What causes the eastward extension of the climatological monsoon trough over the western North Pacific in the boreal summer was investigated through both observational analyses and numerical simulations. It was found that the highest SST is always located to the east of maximum precipitation, and this asymmetric SST pattern favors the eastward extension of the monsoon trough through SST induced boundary layer convergence. A mixed-layer heat budget analysis further indicates that the SST asymmetry arises primarily from the asymmetric pattern of cloud-modified downward shortwave radiation. In addition, two internal atmospheric mechanisms are identified. Firstly, there is a zonal asymmetry in the lower-tropospheric moisture advection. Southeasterlies to the east of the convection, in association with the subtropical high advect high mean moisture from south, leads to low-level moistening to the east of the convective center. Secondly, the heating-induced Kelvin wave response leads to a boundary layer convergence ahead of the convection. Both the processes lead to the setup of a convectively unstable stratification to the east, favoring the eastward extension of the monsoon trough. Two sets of the WRF model experiments that specify a fixed and a time-dependent SST field confirm the roles of the aforementioned atmospheric internal processes as well as the air–sea interaction process in causing the eastward progression of the climatological monsoon trough over the western North Pacific.

The China Coastal Front from Himawari-8 AHI SST Data—Part 1: East China Sea

High-resolution (2 km) high-frequency (hourly) SST data from 2015–2020 provided by the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8 geostationary satellite positioned over 140.7°E were used to study spatial and temporal variability of the China Coastal Front (CCF) in the East China Sea. This dataset was processed with the Belkin and O’Reilly algorithm to generate long-term mean monthly maps of the SST gradient magnitude (GM) and frontal frequency (FF). The horizontal structure of the SST field in the vicinity of the CCF was also investigated from the cross-frontal distributions of SST along eight parallels between 31°N and 24°N. The monthly mean distributions of SST along these 8 parallels were used to determine inshore and offshore boundaries of the CCF and to calculate the CCF strength defined as the total cross-frontal step (range) dSST calculated as the difference between offshore and inshore SST. The CCF emerges in November, fully develops in December, and peaks in strength in January–February. The front’s fragmentation and shrinking/weakening begins in February and March, respectively. In winter (December–February), the front’s strength dSST exceeds 5 °C offshore the Zhejiang-Fujian coast and could be as high as 7.5 °C when nearshore waters cool down to 7 °C. In winter, the front’s strength decreases downstream between 31°N and 24°N. The CCF changes its physical nature as the seasons progress. In winter, the CCF is a water mass front between the cold and fresh water coming from the north and the warm and salty water coming from the south. In summer, the CCF becomes a coastal upwelling front maintained largely by southerly winds. In winter, the CCF’s cross-frontal structure in the SST field is ramp-shaped, with SST increasing monotonously in the offshore direction. In summer, the CCF’s cross-frontal structure in the SST field is V-shaped or U-shaped, featuring a minimum SST formed by cold upwelled water at some distance from the shore. Thus, the summer SST structure effectively consists of two parallel fronts, an inshore one and an offshore one, with a minimum SST in between. Across the inshore/offshore front, the SST decreases/increases in the offshore direction.

Atmospheric response to SST isolation on the interannual variability scale during ENSO episodes

This study aimed to evaluate the impact of SST, isolated on an interannual scale, on the dynamics of atmospheric circulation, especially in the tropical region of the Pacific and Atlantic Oceans. Although there are several studies based on observations and numerical modeling, the isolated effects caused by a specific mode of variability are not yet fully known. For this purpose, the Brazilian Global Atmospheric Model (BAM) forced with an isolated interannual SST, obtained by Moura et al. (2022; Clim Res 87:67–80), was used as a surface boundary condition. To quantify the response of the atmosphere to this time scale, anomalous atmospheric fields were obtained from a reference numerical experiment, where unfiltered SST fields were used as boundary conditions. The effects of the interannual time scale on the dynamics of atmospheric circulation were evaluated for the positive and negative phases of ENSO. In general, when the atmosphere is forced by the isolated interannual variability mode, the atmospheric circulation patterns become weaker than the variability obtained by the non-isolated mode. This weakening is statistically significant and independent of the positive or negative phase of ENSO. The isolated interannual mode significantly reduced the areas of precipitation and its intensity in South America, especially over the Amazon basin and northeastern Brazil. However, changes in precipitation in these regions are more evident in the positive phase of ENSO than in the negative phase. The SST filtering methodology and the use of an atmospheric general circulation model applied in this study adequately revealed the purely dynamic effects of the isolated interannual mode on the atmosphere.

ENSO Asymmetry in CMIP6 Models

Abstract An interesting aspect of the El Niño–Southern Oscillation (ENSO) phenomenon is the asymmetry between its two phases. This paper evaluates the simulations of this property of ENSO by the Coupled Model Intercomparison Project phase 6 (CMIP6) models. Both the surface and subsurface signals of ENSO are examined for this purpose. The results show that the models still underestimate ENSO asymmetry as shown in the SST field, but do a better job in the subsurface. A much weaker negative feedback from the net surface heat flux during La Niña in the models is identified as a factor causing the degradation of the ENSO asymmetry at the surface. The simulated asymmetry in the subsurface is still weaker than the observations owing to a weaker dynamic coupling between the atmosphere and ocean. Consistent with the finding of a weaker dynamic coupling strength, the precipitation response to the SST changes is also found to be weaker in the models. The results underscore that a more objective assessment of the simulation of ENSO by climate models may have to involve the examination of the subsurface signals. Future improvements in simulating ENSO will likely require a better simulation of the surface heat flux feedback from the atmosphere as well as the dynamical coupling strength between the atmosphere and ocean. Significance Statement The ENSO phenomenon affects weather and climate worldwide. An interesting aspect of this phenomenon is the asymmetry between its two phases. Previous studies have reported a weaker asymmetry in the simulations by climate models. But these studies have focused on the ENSO asymmetry at the surface. Here by examining the ENSO asymmetry at the surface and the subsurface, we have found that ENSO asymmetry is better simulated in the subsurface than at the surface. We have also identified factors that are responsible for the degradation of the ENSO asymmetry at the surface as well as the remaining weakness in the subsurface, pointing out specific pathways to take to further improve ENSO simulations by coupled climate models.

Effective ensemble learning approach for SST field prediction using attention-based PredRNN

Effective ensemble learning approach for SST field prediction using attention-based PredRNN

СЕЗОННЫЕ ВАРИАЦИИ ТЕМПЕРАТУРЫ ПОВЕРХНОСТИ ОХОТСКОГО МОРЯ И ПРИЛЕГАЮЩИХ РАЙОНОВ ПО ДАННЫМ СПУТНИКОВЫХ НАБЛЮДЕНИЙ И РЕАНАЛИЗА ERA5

Using the method of harmonic analysis and EOF decomposition of SST data for the surface of the Sea of Okhotsk and adjacent water areas (42–60° N, 135–160° E, SakhNIRO database and ERA5 reanalysis for 1998–2020), the main features of seasonal variations in thermal conditions were determined. It was revealed that the amplitude of the annual harmonic, which plays a decisive role in the seasonal variations of SST, generally decreases in the direction from west to east throughout the study area, the lowest values are in the zones of quasi- stationary upwellings. The phase increases along the northwest-southeast axis, the total shift is 24–25° (about 3 weeks). In the spatial distribution of the first mode (all values are positive), the water area of the Sea of Japan, the NWPO, and the southwestern part of the Sea of Okhotsk are characterized by high values. Its time function is characterized by a pronounced annual cycle, with a maximum in August–September and a minimum in February–March. The spatial distribution of the second mode has a nodal line running along the Kuril Islands from the Sea of Okhotsk side. The mode values vary along the northwest–southeast axis, with maximum positive values on the northwestern shelf of the Sea of Okhotsk and negative values in the remote part of the NWPO. The time function of the second mode has a positive maximum in July–August and a negative minimum in November–December. This nature of the second mode shows that, against the background of the main SST field described by the first mode, a peculiar seasonal “heat wave” is distinguished, propagating from the northwest to the southeast and passing along this axis in about three weeks, which is an important specific feature of the thermal regime of the study area.

Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation

Abstract. Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.

Cross-spectral analysis of the SST/10-m wind speed coupling resolved by satellite products and climate model simulations

This study aims to determine the spatial–temporal scales where the SST forcing of the near-surface winds takes places, and its relationship with the action of coherent ocean eddies. Here, cross-spectral statistics are used to examine the relationship between satellite-based SST and 10-m wind speed (w) fields at scales between 10 $$^2$$ –10 $$^4$$ km and 10 $$^1$$ –10 $$^3$$ days. It is shown that the transition from negative SST/w correlations at large-scales to positive at oceanic mesoscales occurs at wavelengths coinciding with the atmospheric first baroclinic Rossby radius of deformation; and that the dispersion of positively-correlated signals resembles tropical instability waves near the equator, and Rossby waves in the extratropics. Transfer functions are used to estimate the SST-driven w response in physical space ( $$w_c$$ ), a signal that explains 5–40% of the mesoscale w variance in the equatorial cold tongues, and 2–15% at extratropical SST fronts. The signature of ocean eddies is clearly visible in $$w_c$$ , accounting for 20–60% of its variability in eddy-rich regions. To provide further insight on the role of ocean eddies in the SST-driven coupling, the analysis is repeated for two climate model (CCSM) simulations using ocean grid resolutions of $$1^\circ$$ (eddy-parameterized, LR) and $$0.1^\circ$$ (eddy-resolving, HR). The lack of resolved eddies in LR leads to a significantly underestimated mesoscale w variance relative to HR. Conversely, the $$w_c$$ variability in HR can exceed the satellite estimates by a factor of two at extratropical SST fronts and underestimate it by a factor of almost six near the equator, reflecting shortcomings of the CCSM to be addressed in its future developments.

Advances in Sea Surface Layer Temperature Measurements with Fast Responding Thermistor Arrays on Drifting Buoys

A precise and accurate ocean temperature measurement system is essential for better understanding and knowledge of the spatial and temporal variability of thermal stratification of the upper-ocean layers is fundamental. The National Institute of Ocean Technology, Chennai has indigenously developed a novel negative temperature coefficient (NTC) thermistor based sensor array with RS232 digital output for drifting buoy (Pradyu) (DB) wherein, it is mainly used in ocean observation applications. The DB is built with Indian satellite (INSAT) for real time data telemetry. The NTC sensing element is used in developing the temperature sensor for the measurement of sea surface layer temperature. The Steinhart–Hart equation and coefficients are applied on each sampling to zero down the error components involved in temperature measurements which corresponds to the nonlinear functionality of the NTC element. In-house developed SST sensor and sensor array are calibrated and extensively tested in laboratory conditions. The results of the SST and sensor array laboratory calibrations and field validations are briefly presented here with significant data sets collected in the Bay of Bengal warm pool regions.

Atmosphere-ocean feedbacks in a coastal upwelling system

The COAWST (Coupled Ocean-Atmosphere-Wave-Sediment Transport) modelling system is used in different configurations to simulate the Iberian upwelling during the 2012 summer, aiming to assess the atmosphere-ocean feedbacks in the upwelling dynamics. When model results are compared with satellite measurements and in-situ data, two-way coupling is found to have a moderate impact in data-model statistics. A significant reinforcement of atmosphere-ocean coupling coefficients is, however, observed in the two-way coupled run, and in the WRF and ROMS runs forced by previously simulated SST and wind fields, respectively. The increasing in the coupling coefficient is associated with slight, but potentially important changes in the low-level coastal jet in the atmospheric marine boundary layer. While these results do not imply the need for fully coupled simulations in many applications, they show that in seasonal numerical studies such simulations do not degrade the overall model performance, and contribute to produce better dynamical fields.

Fusion of Multisensor SSTs Based on the Spatiotemporal Hierarchical Bayesian Model

AbstractThis study focuses on merging MODIS-mapped SSTs with 4-km spatial resolution and AMSR-E optimally interpolated SSTs at 25-km resolution. A new data fusion method was developed—the Spatiotemporal Hierarchical Bayesian Model (STHBM). This method, which is implemented through the Markov chain Monte Carlo technique utilized to extract inferential results, is specified hierarchically by decomposing the SST spatiotemporal process into three subprocesses, that is, the spatial trend process, the seasonal cycle process, and the spatiotemporal random effect process. Spatial-scale transformation and spatiotemporal variation are introduced into the fusion model through the data model and model parameters, respectively, with suitably selected link functions. Compared with two modern spatiotemporal statistical methods—the Bayesian maximum entropy and the robust fixed rank kriging—STHBM has the following strength: it can simultaneously meet the expression of uncertainties from data and model, seamless scale transformation, and SST spatiotemporal process simulation. Utilizing multisensors’ complementation, merged data with complete spatial coverage, high resolution (4 km), and fine spatial pattern lying in MODIS SSTs can be obtained through STHBM. The merged data are assessed for local spatial structure, overall accuracy, and local accuracy. The evaluation results illustrate that STHBM can provide spatially complete SST fields with reasonably good data values and acceptable errors, and that the merged SSTs collect fine spatial patterns lying in MODIS SSTs with fine resolution. The accuracy of merged SSTs is between MODIS and AMSR-E SSTs. The contribution to the accuracy and the spatial pattern of the merged SSTs from the original MODIS SSTs is stronger than that of the original AMSR-E SSTs.

Impact of SST on heavy rainfall events on eastern Adriatic during SOP1 of HyMeX

The season of late summer and autumn is favourable for intensive precipitation events (IPE) in the central Mediterranean. During that period the sea surface is warm and contributes to warming and moistening of the lowest portion of the atmosphere, particularly the planetary boundary layer (PBL). Adriatic sea is surrounded by mountains and the area often receives substantial amounts of precipitation in short time (24h). The IPEs are a consequence of convection triggered by topography acting on the southerly flow that has brought the unstable air to the coastline. Improvement in prediction of high impact weather events is one of the goals of The Hydrological cycle in the Mediterranean eXperiment (HyMeX). This study examines how precipitation patterns change in response to different SST forcing. We focus on the IPEs that occurred on the eastern Adriatic coast during the first HyMeX Special observing period (SOP1, 6 September to 5 November 2012). The operational forecast model ALADIN uses the same SST as the global meteorological model (ARPEGE from Meteo France), as well as the forecast lateral boundary conditions (LBCs). First we assess the SST used by the operational atmospheric model ALADIN and compare it to the in situ measurements, ROMS ocean model, OSTIA and MUR analyses. Results of this assessment show that SST in the eastern Adriatic was overestimated by up to 10K during HyMeX SOP1 period. Then we examine the sensitivity of 8km and 2km resolution forecasts of IPEs to the changes in the SST during whole SOP1 with special attention to the intensive precipitation event in Rijeka. Forecast runs in both resolutions are performed for the whole SOP1 using different SST fields prescribed at initial time and kept constant during the model forecast. Categorical verification of 24h accumulated precipitation did not show substantial improvement in verification scores when more realistic SST was used. Furthermore, the results show that the impact of introducing improved SST in the analysis on the precipitation forecast varies for different cases. There is generally a larger sensitivity to the SST in high resolution than in the lower one, although the forecast period of the latter is longer.

Description and evaluation of the Earth System Regional Climate Model (Reg CM‐ES)

AbstractWe describe a new, state‐of‐the‐art, Earth System Regional Climate Model (RegCM‐ES), which includes the coupling between the atmosphere, ocean, and land surface, as well as a hydrological and ocean biogeochemistry model, with the capability of using a variety of physical parameterizations. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains and more regional settings featuring climatically important coupled phenomena. Regional coupled ocean‐atmosphere models can be especially useful tools to provide information on the mechanisms of air‐sea interactions and feedbacks occurring at fine spatial and temporal scales. RegCM‐ES shows a good representation of precipitation and SST fields over the domains tested, as well as realistic simulations of coupled air‐sea processes and interactions. The RegCM‐ES model, which can be easily implemented over any regional domain of interest, is open source, making it suitable for usage by the broad scientific community.

North-western Mediterranean sea-breeze circulation in a regional climate system model

In the Mediterranean basin, moisture transport can occur over large distance from remote regions by the synoptic circulation or more locally by sea breezes, driven by land-sea thermal contrast. Sea breezes play an important role in inland transport of moisture especially between late spring and early fall. In order to explicitly represent the two-way interactions at the atmosphere-ocean interface in the Mediterranean region and quantify the role of air-sea feedbacks on regional meteorology and climate, simulations at 20 km resolution performed with WRF regional climate model (RCM) and MORCE atmosphere-ocean regional climate model (AORCM) coupling WRF and NEMO-MED12 in the frame of HyMeX/MED-CORDEX are compared. One result of this study is that these simulations reproduce remarkably well the intensity, direction and inland penetration of the sea breeze and even the existence of the shallow sea breeze despite the overestimate of temperature over land in both simulations. The coupled simulation provides a more realistic representation of the evolution of the SST field at fine scale than the atmosphere-only one. Temperature and moisture anomalies are created in direct response to the SST anomaly and are advected by the sea breeze over land. However, the SST anomalies are not of sufficient magnitude to affect the large-scale sea-breeze circulation. The temperature anomalies are quickly damped by strong surface heating over land, whereas the water vapor mixing ratio anomalies are transported further inland. The inland limit of significance is imposed by the vertical dilution in a deeper continental boundary-layer.

Impacts of coastal upwelling off east Vietnam on the regional winds system: An air-sea-land interaction

In this study, we analyze the influence of coastal upwelling off southeast Vietnam (CUEV) on local wind field using numerical simulations based on atmospheric model of Weather Research and Forecasting (WRF). Several scenarios are simulated by forcing identical model configurations with different SST fields. Based on simulation results, the relationship between CUEV and reduction of wind forcing is numerically evidenced. With the influence of a typical cold patch with a temperature drop of 3–5°C, the local wind speeds can drop to less than 70% of original level. We find that the mechanism of response of the wind reduction to CUEV is enhancement of sea-breeze induced wind modulation. Onshore sea-breeze will enhance, while the contrast between land and sea is even more striking due to the contribution of a distinct coastal upwelling. This implies that air-sea-land interaction dominates the process of local wind system modulation in response to transient CUEV. This result sheds a new light on the air-sea interaction process within the SCS basin.

Lagrangian Coherent Structures in a coastal upwelling environment

A unique spatiotemporal perspective of evolving surface currents off the northern California coast is provided with Lagrangian Coherent Structures (LCSs) determined from attracting Finite-Time Lyapunov Exponents (FTLEs). The FTLEs are calculated from hourly 2-D surface current velocities obtained with HF radars. Attracting FTLE field maxima can identify confluence and shear in flows which can be useful in mapping dynamics associated with fronts. FTLE and SST fields are compared during three time periods in 2009: late March, early September, and late September. During strong upwelling-favorable winds in late March the FTLE and SST fields were not strongly related indicating that frontal dynamics were not strongly influencing surface circulation. Exceptions to this occurred when FTLE ridges calculated from a shorter integration period captured the evolution of a cold water filament and when a FTLE ridge migrated offshore along with an upwelling front. During the two September cases an improved relationship between the FTLE and SST fields was found although occasionally they became shifted. The shifts occurred when the FTLE integration period spanned backwards in time through periods of relaxed and upwelling-favorable winds. This suggests that frontal dynamics captured by LCSs during relaxed winds can subsequently become advected after the onset of wind-forcing by a surface mixed layer decoupled from stably stratified water below the surface mixed layer. Additionally, the LCSs were found to be useful in mapping the origin and destination of surface trajectories, the confluence associated with a persistent eddy-like feature, and retention zones off coastal promontories.

Dynamic-analogue correction of the decadal change of East Asian summer precipitation in the late 1990s

This paper systematically evaluates the deviations that appear in the hindcasts of the East Asian summer precipitation (EASP) decadal change in the late 1990s in two global coupled models (BCC_CGCM and BCC_CSM). The possible causes for the deviations between the model hindcasts and observations are analyzed. The results show that the hindcasts of EASP by BCC_CGCM and BCC_CSM deviate from observations, with the anomaly correlation coefficient (ACC) being -0.01 and -0.09 for the two models, respectively. The SST anomalies in North and West Pacific and the SST index values predicted by the two models also deviate from the observations, indicating that inconsistent SST fields may be the key factor leading to the deviation in the prediction of the EASP decadal shift. Thus, a dynamic-analogue scheme is proposed to correct the precipitation hindcasts by using SSTs, where SST and EASP are highly correlated, to select historical analogue cases. Cross validations show that the average ACC of the temporal-latitude distribution of the EASP between the corrected hindcasts and observations is 0.18 for BCC_CGCM and 0.02 for BCC_CSM; both are much higher than the uncorrected hindcasts. Applying the dynamic-analogue correction scheme in both models successfully improves prediction of the EASP decadal change in the late 1990s.

Evaluation of ocean data assimilation in CAS-ESM-C: Constraining the SST field

A weakly coupled assimilation system, in which SST observations are assimilated into a coupled climate model (CASESM-C) through an ensemble optimal interpolation scheme, was established. This system is a useful tool for historical climate simulation, showing substantial advantages, including maintaining the atmospheric feedback, and keeping the oceanic fields from drifting far away from the observation, among others. During the coupled model integration, the bias of both surface and subsurface oceanic fields in the analysis can be reduced compared to unassimilated fields. Based on 30 model years of output from the system, the climatology and interannual variability of the climate system were evaluated. The results showed that the system can reasonably reproduce the climatological global precipitation and SLP, but it still suffers from the double ITCZ problem. Besides, the ENSO footprint, which is revealed by ENSO-related surface air temperature, geopotential height and precipitation during El Nino evolution, is basically reproduced by the system. The system can also simulate the observed SST–rainfall relationships well on both interannual and intraseasonal timescales in the western North Pacific region, in which atmospheric feedback is crucial for climate simulation.