Impacts of Wave and Current on Drag Coefficient and Wind Stress over the Tropical and Northern Pacific

By taking into consideration the effects of ocean surface wave-induced Stokes drift velocity Un, and current velocity Uc on the drag coefficient, the spatial distributions of drag coefficient and wind stress in 2004 are computed over the tropical and northern Pacific using an empirical drag coefficient parameterization formula based on wave steepness and wind speed. The global ocean current field is generated from the Hybrid Coordinate Ocean Model （HYCOM） and the wave data are generated from Wavewatch Ill （WW3）. The spatial variability of the drag coefficient and wind stress is analyzed. Preliminary results indicate that the ocean surface Stokes drift velocity and current velocity exert an important influence on the wind stress. The results also show that consideration of the effects of the ocean surface Stokes drift velocity and current velocity on the wind stress can significantly improve the modeling of ocean circulation and air-sea interaction processes.

Interannual Variability of SST,SLA and Wind Waves in the Hawaii Area and Their Responses to ENSO

Time series of sea surface temperature （SST）, wind speed and significant wave height （SWH） from meteorological buoys of the National Data Buoy Center （NDBC） are useful for studying the interannual variability and trend of these quantities at the buoy areas. The measurements from 4 buoys （B51001, B51002, B51003 and B51004） in the Hawaii area are used to study the responses of the quantities to El Nino and Southern Oscillation （ENSO）. Long-term averages of these data reflect precise seasonal and climatological characteristics of SST, wind speed and SWH around the Hawaii area. Buoy observations from B51001 suggest a significant warming trend which is, however, not very clear from the other three buoys. Compared with the variability of SST and SWH, the wind speeds from the buoy observations show an increasing trend. The impacts of EI Nifio on SST and wind waves are also shown. Sea level data observed by altimeter during October 1992 to September 2006 are analyzed to investigate the variability of sea level in the Hawaii area. The results also show an increasing trend in sea level anomaly （SLA）. The low-passed SLA in the Hawaii area is consistent with the inverse phase of the low-passed SOI （Southern Oscillation Index）. Compared with the low-passed SOl and PDO （Pacific Decadal Oscillation）, the low-passed PNA （Pacific-North America Index） has a better correlation with the low-passed SEA in the Hawaii area.

Implementing Marine XML for Observed CTD Data in a Marine Data Exchange Platform

In order to archive, quality control and disseminate a large variety of marine data in a marine data exchange platfonn, a marine XML has been developed to encapsulate marine data, which provides an efficient means to store, transfer and display marine data. This paper first presents the details of the main marine XML elements and then gives an example showing how to transform CTD-observed data into Marine XML format, which illustrates the XML encapsulation process of marine observed data.

Last Glacial Maximum Sea Surface Temperatures: A Model-Data Comparison

In this study,the authors investigated changes in Last Glacial Maximum （LGM） sea surface temperature （SST） simulated by the Paleoclimate Modelling Intercomparison Project （PMIP） multimodels and reconstructed by the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface （MARGO） project,focusing on model-data comparison.The results showed that the PMIP models produced greater ocean cooling in the North Pacific and Tropical Ocean than the MARGO,particularly in the northwestem Pacific,where the modeldata mismatch was larger.All the models failed to capture the anomalous east-west SST gradient in the North Atlantic.In addition,large discrepancies among the models were observed in the mid-latitude ocean,particularly with models in the second phase of the PMIP.Although these models showed better agreement with the MARGO,the latest models in the third phase of the PMIP did not show substantial progresses in simulating LGM ocean surface conditions.That is,improvements in the modeling community are still needed to describe SST for a better understanding of climate during the LGM.

Design and testing of a global climate prediction system based on a coupled climate model

A global climate prediction system （PCCSM4） was developed based on the Community Climate System Model, version 4.0, developed by the National Center for Atmospheric Research （NCAR）, and an initialization scheme was designed by our group. Thirty-year （1981-2010） one-month-lead retrospective summer climate ensemble predictions were carded out and analyzed. The results showed that PCCSM4 can efficiently capture the main characteristics of JJA mean sea surface temperature （SST）, sea level pressure （SLP）, and precipitation. The prediction skill for SST is high, especially over the central and eastern Pacific where the influence of E1 Nino-Southem Oscillation （ENSO） is dominant. Temporal correlation coefficients between the pre- dicted Nino3.4 index and observed Nino3.4 index over the 30 years reach 0.7, exceeding the 99% statistical significance level. The prediction of 500-hPa geopotential height, 850-hPa zonal wind and SLP shows greater skill than for precipitation. Overall, the predictability in PCCSM4 is much higher in the tropics than in global terms, or over East Asia. Furthermore, PCCSM4 can simulate the summer climate in typical ENSO years and the interannual variability of the Asian summer monsoon well. These preliminary results suggest that PCCSM4 can be applied to real-time prediction after further testing and improvement.

The correctness to the spuriously simulated semi-annual cycle of the sea surface temperature in the equatorial eastern Pacific

One of the challenges faced by the climate model of the Community Climate System Model version 3 (CCSM3) is the spuriously simulated semi-annual cycle of the sea surface temperature (SST) in the equatorial eastern Pacific. This model bias has limited the performance of the climate simulation and prediction. Based on the surface wave-circulation coupled theory, an atmosphere-wave-ocean coupled model was developed, which incorporates the MASNUM (key laboratory of Marine Sciences and Numerical Modeling) wave number spectral model into CCSM3. The new coupled atmosphere-wave-ocean model successfully removes the spurious semi-annual cycle simulated by the original CCSM3 and reasonably produces an SST annual cycle with warm and cold phases in April and August, respectively. The correlation between the simulated and observed SST in the equatorial eastern Pacific is improved from 0.66 to 0.93. The ocean surface layer heat budget analysis indicates that the wave-induced vertical mixing is responsible for improving the simulation of the SST seasonal cycle in the equatorial eastern Pacific.

Improved decadal climate prediction in the North Atlantic using EnOI-assimilated initial condition

Decadal prediction experiments of Beijing Climate Center climate system model version 1.1 （BCC- CSM1.1） participated in Coupled Model Intercomparison Project Phase 5 （CMIPS） had poor skill in extratropics of the North Atlantic, the initialization of which was done by relaxing modeled ocean temperature to the Simple Ocean Data Assimilation （SODA） reanalysis data. This study aims to improve the prediction skill of this model by using the assimilation technique in the initialization. New ocean data are firstly generated by assimilating the sea surface temperature （SST） of the Hadley Centre Sea Ice and Sea Surface Temperature （HadlSST） dataset to the ocean model of BCC-CSM1.1 via Ensemble Optimum Interpolation （EnOI）. Then a suite of decadal reforecasts launched annually over the period 1961- 2005 is carried out with simulated ocean temperature restored to the assimilated ocean data. Comparisons between the re-forecasts and previous CMIP5 forecasts show that the re-forecasts are more skillful in mid-to-high latitude SST of the North Atlantic. Improved prediction skill is also found for the Atlantic multi-decadal oscillation （AMO）, which is consistent with the better skill of Atlantic meridional overturning circulation （AMOC） predicted by the re-forecasts. We conclude that the EnOl assimilation generates better ocean data than the SODA reanalysis for initializing decadal climate prediction of BCC-CSM1.1 model.