Tropical Atmosphere Ocean Data Research Articles

TAO Data Support the Existence of Large High Frequency Variations in Cross‐Equatorial Overturning Circulation

AbstractLarge amplitude oscillations in the meridional overturning circulation (MOC) have been found near the equator in all major ocean basins in the NEMO ocean general circulation model. With periods of 3–15 days and amplitudes of ∼±100 Sv in the Pacific, these oscillations have been shown to correspond to zonally integrated equatorially trapped waves forced by winds within 10°N/S of the equator. Observations of dynamic height from the Tropical Atmosphere Ocean (TAO) mooring array in the equatorial Pacific also exhibit spectral peaks consistent with the dispersion relation for equatorially trapped waves. Here, we revisit the TAO observations to confirm that the amplitude of the oscillations is consistent with the simulations, supporting the modeled large amplitude MOC oscillations. We also show that the zonal structure of the frequency spectrum in both observations and simulations is predicted by changes in the baroclinic wave speed with variation in stratification across the ocean basin.

Influence of El Niño on atmospheric CO2 over the tropical Pacific Ocean: Findings from NASA's OCO-2 mission.

Spaceborne observations of carbon dioxide (CO2) from the Orbiting Carbon Observatory-2 are used to characterize the response of tropical atmospheric CO2 concentrations to the strong El Niño event of 2015-2016. Although correlations between the growth rate of atmospheric CO2 concentrations and the El Niño-Southern Oscillation are well known, the magnitude of the correlation and the timing of the responses of oceanic and terrestrial carbon cycle remain poorly constrained in space and time. We used space-based CO2 observations to confirm that the tropical Pacific Ocean does play an early and important role in modulating the changes in atmospheric CO2 concentrations during El Niño events-a phenomenon inferred but not previously observed because of insufficient high-density, broad-scale CO2 observations over the tropics.

Influence of availability of TAO data on NCEP ocean data assimilation systems along the equatorial Pacific

AbstractIt is reasonable to assume that the quality of an ocean reanalysis will depend not only on the ocean data assimilation system but also on the availability of observational data. Among the data assimilated in the tropical Pacific, observations from the Tropical Atmosphere Ocean (TAO) moored array are an important contributor. Due to various reasons, in the last couple of years, TAO had a very low data delivery rate at some of the mooring sites. In this work, we examined the influence of the availability of in situ TAO data from all 10 equatorial mooring sites in 1999–2014 by comparing ocean temperature from two data assimilation systems at National Centers for Environmental Prediction (NCEP): the Global Ocean Data Assimilation System (GODAS) and the Climate Forecast System Reanalysis (CFSR). Our working hypothesis is that missing of in situ observational data should lead to less observational constraint, and consequently, larger divergence between ocean reanalyses. Compared with periods of no in situ TAO observations, the disagreements of ocean temperature between CFSR and GODAS are indeed smaller when in situ TAO observations are available. The disagreements are largest along the thermocline due to its being the region of strongest variability. Thus, it is suggested that without the constraint of in situ TAO observations, the inconsistency between the ocean reanalyses from two NCEP data assimilation systems is larger, highlighting the contribution of TAO observations. Moreover, it is also suggested that the disagreement of ocean temperature between GODAS and CFSR is mainly caused by the difference of the models used in the assimilation systems and the impact of in situ TAO availability plays a secondary, but important role. To improve the quality of the assimilation products, it is necessary both to reduce model bias and to assimilate more high‐quality data.

Wind Speed Retrieval Based on Sea Surface Roughness Measurements from Spaceborne Microwave Radiometers

AbstractWind speed is the main factor responsible for the increase in ocean thermal emission because sea surface emissivity strongly depends on surface roughness. An alternative approach to estimate the surface wind speed (SWS) as a function of surface roughness is developed in this study. For the sea surface emissivity, the state-of-the-art forward Fast Microwave Emissivity Model, version 3 (FASTEM-3), which is applicable for a wide range of microwave frequencies at incidence angles of less than 60°, is used. Special Sensor Microwave Imager and Advanced Microwave Scanning Radiometer (AMSR-E) observations are simulated using FASTEM-3 and the Global Data Assimilation and Prediction System operated by the Korea Meteorological Administration. The performance of the SWS retrieval algorithm is assessed by comparing its SWS output to that of the Global Data Assimilation System operated by the National Centers for Environmental Prediction. The surface roughness is computed using the Hong approximation and characteristics of the polarization ratio. When compared with the Tropical Atmosphere–Ocean data, the bias and root-mean-square error (RMSE) of the SWS outputs from the proposed wind speed retrieval algorithm were found to be 0.32 m s−1 (bias) and 0.37 m s−1 (RMSE) for the AMSR-E 18.7-GHz channel, 0.38 m s−1 (bias) and 0.42 m s−1 (RMSE) for the AMSR-E 23.8-GHz channel, and 0.45 m s−1 (bias) and 0.49 m s−1 (RMSE) for the AMSR-E 36.5-GHz channel. Consequently, this research provides an alternative method to retrieve the SWS with minimal a priori information on the sea surface.

Analysis of a Reconstructed Oceanic Kelvin Wave Dynamic Height Dataset for the Period 1974–2005

Abstract Intraseasonal oceanic Kelvin waves are the dominant mode of variability in the thermocline of the equatorial Pacific. Dynamic height data from the Tropical Atmosphere Ocean (TAO) Array of buoys moored in the tropical Pacific offer a convenient grid on which to study the waves but can only be effectively applied to study basinwide wave activity since about 1988 because of insufficient data at earlier times. Kelvin wave signals are also present in sea level data from island and coastal sites from the University of Hawaii Sea Level Center, some of which are available from before 1970 and up to 2003. This work describes a technique for reconstructing equatorial dynamic height data back to 1974, by utilizing regression relationships between the TAO data and daily sea level time series from 11 stations in the tropical Pacific. The reconstructed data are analyzed for skill in approximating Kelvin wave signals when TAO data are available. Reconstructed Kelvin wave signals prior to the TAO period are then analyzed for consistency with the wind stress anomalies that are responsible for generating the waves. A regression analysis showing intraseasonal patterns of convection and winds that occur during periods of adjustment toward El Niño conditions is applied during the period 1974–87 for comparison with an earlier result calculated from TAO data for 1988–2005. Systematic changes in Kelvin wave phase speed with respect to ENSO documented for the latter period are confirmed in the earlier reconstructed dataset.

Impact of Ocean Observation Systems on Ocean Analysis and Seasonal Forecasts

Abstract The relative merits of the Tropical Atmosphere–Ocean (TAO)/Triangle Trans-Ocean Buoy Network (TAO/TRITON) and Pilot Research Moored Array in the Tropical Atlantic mooring networks, the Voluntary Observing Ship (VOS) expendable bathythermograph (XBT) network, and the Argo float network are evaluated through their impact on ocean analyses and seasonal forecast skill. An ocean analysis is performed in which all available data are assimilated. In two additional experiments the moorings and the VOS datasets are withheld from the assimilation. To estimate the impact on seasonal forecast skill, the set of ocean analyses is then used to initialize a corresponding set of coupled ocean–atmosphere model forecasts. A further set of experiments is conducted to assess the impact of the more recent Argo array. A key parameter for seasonal forecast initialization is the depth of the thermocline in the tropical Pacific. This depth is quite similar in all of the experiments that involve data assimilation, but withdrawing the TAO data has a bigger effect than withdrawing XBT data, especially in the eastern half of the basin. The forecasts mainly indicate that the TAO/TRITON in situ temperature observations are essential to obtain optimum forecast skill. They are best combined with XBT, however, because this results in better predictions for the west Pacific. Furthermore, the XBTs play an important role in the North Atlantic. The ocean data assimilation performs less well in the tropical Atlantic. This may be partly a result of not having adequate observations of salinity.

Calculation of the Bowen ratio in the tropical Pacific using sea surface temperature data

The equilibrium Bowen ratio (Bo*) can be estimated empirically from the sea surface temperature (SST) only when the air is saturated with water vapor at the sea surface. However, since most of the sea surface is not saturated with water vapor, several studies have been conducted for the empirical Bowen ratio (BoE = Bo*(SST)), which was formulated with many sources of data from many areas. Hicks and Hess' [1977] linear regression formula for the BoE as a function of SST alone was used to estimate the empirical Bowen ratio in the tropical Pacific. Climatological and long‐term time series Optimum Interpolation Sea Surface Temperature (OISST) data was used for the climatological study of the BoE. The climatological mean Bowen ratio showed the regions, where the latent heat flux was most dominant. The Bowen ratio in the western Pacific warm pool (WPWP) area (O (0.04)) was 10% smaller than those in the upwelling coastal areas (O (0.14)). Along 5°N and 5°S, a 0.7 correlation coefficient between the BoE and the bulk formulated Bowen ratio (BoB), using climatological data, was found in the weak wind zone of the doldrums. BoB is the ratio of the bulk formulated sensible heat flux to the bulk formulated latent heat flux. EOF analysis was used to find out dominant temporal and spatial signals of the BoE. The first temporal EOF of the BoE, using 156 months (1986–1999) of OISST anomaly was related to El Niño events with an approximate 12‐month lag when compared to the El Niño‐Southern Oscillation (ENSO) index (SOI). The second and third temporal EOF showed annual and interannual signals, respectively. In order to estimate the discrepancy between the BoE and the BoB and to correct for the wind effect and the humidity effect, long‐term time series of Tropical Atmosphere Ocean (TAO) data was used. Our results showed that the eastern Pacific demonstrated a stronger correlation between the BoB and the BoE than the western Pacific. However, the Bowen ratio differences (BoD = |BoE − BoB|) were small in the western Pacific, and a larger margin of error was found at the eastern Pacific, where ocean dynamics perturb the upper ocean heat balance. The sensitivity of the humidity and the winds on the BoE was tested using linear correlation of the BoD while varying the winds and humidity. The BoD was small, especially in the southwest Pacific, where there are weak winds and high levels of the humidity. Thus the BoE in our study will be more useful to study involving heat fluxes in the WPWP area rather than those in the eastern Pacific. The correction of the humidity and the wind was applied using a linear regression of the humidity and the winds. After the corrections, the BoD was reduced by an average of 70.2%. Using TAO data, we obtained BoE = 0.033Bo* in the western Pacific with Bo*'s standard deviation of 0.008 at sea surface temperature 29.27°C ± 0.54°C.

Comparisons between the TAO Buoy and NASA Scatterometer Wind Vectors

There was an opportunity to compare 10 months of collocated National Aeronautics and Space Administration scatterometer (NSCAT) wind vectors with those from the Tropical Atmosphere Ocean (TAO) buoy array, located in the tropical Pacific Ocean. Over 5500 data pairs, from nearly 70 buoys, were collocated in the calibration/ validation effort for NSCAT. These data showed that the wind speeds produced from the NSCAT-1 model function were low by about 7%‐8% compared with TAO buoy winds. The revised model function, NSCAT-2, produces wind speeds with a bias of about 1%. The scatterometer directions were within 208 (rms), meeting accuracy requirements, when compared to TAO data. The mean direction bias between the TAO and the NSCAT vectors (regardless of model function) is about 98 with the scatterometer winds to the right of the TAO winds, which may be due to swell. The statistics of the two datasets are discussed, using component biases in lieu of the speed bias, which is naturally skewed. Using ocean currents and buoy winds measured along the equator, it is shown that the scatterometer measures the wind relative to the moving ocean surface. In addition, a systematic effect of rain on the NSCAT wind retrievals is noted. In all analyses presented here, winds less than 3 m s 21 are removed, due to the difficulty in making accurate low wind measurements.

Generalized Inverse of a Reduced Gravity Primitive Equation Ocean Model and Tropical Atmosphere–Ocean Data

A nonlinear 2‰-layer reduced gravity primitive equations (PE) ocean model is used to assimilate sea surface temperature (SST) data from the Tropical Atmosphere‐Ocean (TAO) moored buoys in the tropical Pacific. The aim of this project is to hindcast cool and warm events of this part of the ocean, on seasonal to interannual timescales. The work extends that of Bennett et al., who used a modified Zebiak‐Cane coupled model. They were able to fit a year of 30-day averaged TAO data to within measurement errors, albeit with significant initial and dynamical residuals. They assumed a 100-day decorrelation timescale for the dynamical residuals. This long timescale for the residuals reflects the neglect of resolvable processes in the intermediate coupled model, such as horizontal advection of momentum. However, the residuals in the nonlinear PE model should be relatively short timescale errors in parameterizations. The scales for these residuals are crudely estimated from the upper ocean turbulence studies of Peters et al. and Moum. The assimilation is performed by minimizing a weighted least squares functional expressing the misfits to the data and to the model throughout the tropical Pacific and for 18 months. It is known that the minimum lies in the ‘‘data subspace’’ of the state or solution space. The minimum is therefore sought in the data subspace, by using the representer method to solve the Euler‐Lagrange (EL) system. Although the vector space decomposition and solution method assume a linear EL system, the concept and technique are applied to the nonlinear EL system (resulting from the nonlinear PE model), by iterating with linear approximations to the nonlinear EL system. As a first step, the authors verify that sequences of solutions of linear iterates of the forward PE model do converge. The assimilation is also used as a significance test of the hypothesized means and covariances of the errors in the initial conditions, dynamics, and data. A ‘‘strong constraint’’ inverse solution is computed. However, it is outperformed by the ‘‘weak constraint’’ inverse. A cross validation by withheld data is presented, as well as an inversion with the model forced by the Florida State University winds, in place of a climatological wind forcing used in the former inversions.

An evaluation of expendable bathythermograph and Tropical Atmosphere‐Ocean Array data for monitoring tropical ocean variability

Two important sources of information for monitoring and predicting the El Niño‐Southern Oscillation are the Tropical Atmosphere Ocean (TAO) buoy array and the volunteer observing ship expendable bathythermograph (VOS XBT) network. The subsurface ocean temperature measurements of these two networks are evaluated in the context of analysis and monitoring of medium‐ to low‐frequency variability in the tropical Pacific Ocean. It is shown that both systems capture the principal features that characterize variability in the equatorial central and eastern Pacific Ocean but only TAO can capture the higher temporal fluctuations in detail. In the western Pacific, the VOS XBT network is able to capture the slowly moving, westward propagating Rossby waves and their reflection and interaction with the western boundary. TAO is limited in this respect because of its equatorial focus. The accuracy of temperature maps is estimated using the rms analysis error variance. The accuracy of the VOS XBT network fluctuates in space and time but is relatively steady averaged over the tropical region, while that of TAO has gradually improved as the basin wide array has been implemented. Case studies using VOS XBT data only, TAO data only, and the combined full data set indicate the networks are complementary and supportive, evaluated basin wide and over the tropical region. The high temporal resolution and regularity of the equatorially focused TAO network are complemented by the broad‐scale, irregular tropical VOS XBT sampling in the equatorial region and by VOS coverage outside the domain of TAO. A proxy for net information content is derived from the estimated rms error variance of the analysis. For the equatorial region, TAO now provides in excess of 70% of the information, its dominance beginning in 1992. For the tropical region (20°S–20°N) the net information content of the respective systems is of comparable magnitude, each equivalent to in excess of 100 independent samples per 10‐day period in 1994, reinforcing the notion that both systems are valuable sources of subsurface ocean information for monitoring medium‐ to low‐frequency tropical variability.