Voluntary Observing Ships Research Articles

Observation of atmospheric oxygen/nitrogen ratio aboard a cargo ship using gas chromatography/thermal conductivity detector

Measurements of atmospheric O2/N2 ratio and CO2 concentration have been used to analyze the −ΔO2/ΔCO2 ratio to obtain information on CO2 sources, e.g., anthropogenic or terrestrial biogenic sources (respiration or wildfire). In this study we report on the development of a shipboard system for measuring atmospheric O2/N2 ratio by using the gas chromatography/thermal conductivity detector (GC/TCD) technique. The standard error for a one hour average (N = 6) is found to be ± 5 per meg (±1 ppm). The shipboard measurements have been conducted since the end of September 2007 on the Voluntary Observing Ship TRANS FUTURE 5, a cargo ship sailing between Japan, Australia, and New Zealand every six weeks. Spatially, the observation covers latitudes between 41°S and 33°N over the western Pacific. Air masses with high CO2 concentration are observed along the coastline of Australia and New Zealand. In more than two thirds of the cases (17 of 23 events) detected between September 2007 and July 2009, values of the −ΔO2/ΔCO2 ratio are less than 1.15, indicating dominance of biogenic sources (e.g., respiration or wildfire) of CO2.

Probability Distribution Characteristics for Surface Air–Sea Turbulent Heat Fluxes over the Global Ocean

Abstract To analyze the probability density distributions of surface turbulent heat fluxes, the authors apply the two-parametric modified Fisher–Tippett (MFT) distribution to the sensible and latent turbulent heat fluxes recomputed from 6-hourly NCEP–NCAR reanalysis state variables for the period from 1948 to 2008. They derived the mean climatology and seasonal cycle of the location and scale parameters of the MFT distribution. Analysis of the parameters of probability distributions identified the areas where similar surface turbulent fluxes are determined by the very different shape of probability density functions. Estimated extreme turbulent heat fluxes amount to 1500–2000 W m−2 (for the 99th percentile) and can exceed 2000 W m−2 for higher percentiles in the subpolar latitudes and western boundary current regions. Analysis of linear trends and interannual variability in the mean and extreme fluxes shows that the strongest trends in extreme fluxes (more than 15 W m−2 decade−1) in the western boundary current regions are associated with the changes in the shape of distribution. In many regions changes in extreme fluxes may be different from those for the mean fluxes at interannual and decadal time scales. The correlation between interannual variability of the mean and extreme fluxes is relatively low in the tropics, the Southern Ocean, and the Kuroshio Extension region. Analysis of probability distributions in turbulent fluxes has also been used in assessing the impact of sampling errors in the Voluntary Observing Ship (VOS)-based surface flux climatologies, allowed for the estimation of the impact of sampling in extreme fluxes. Although sampling does not have a visible systematic effect on mean fluxes, sampling uncertainties result in the underestimation of extreme flux values exceeding 100 W m−2 in poorly sampled regions.

Onboard measurement system of atmospheric carbon monoxide in the Pacific by voluntary observing ships

Abstract. Long-term monitoring of carbon monoxide (CO) mixing ratios in the atmosphere over the Pacific Ocean is being carried out on commercial cargo vessels participating in the National Institute for Environmental Studies Voluntary Observing Ships program. The program provides a regular platform for measurement of atmospheric CO along four cruise routes: from Japan to Oceania, the United States, Canada, and Southeast Asia. Flask samples are collected during every cruise for subsequent analysis in the laboratory, and in 2005, continuous shipboard CO measurements were initiated on three of the routes. Here, we describe the system we developed for onboard measurement of CO mixing ratios with a commercially available gas filter correlation CO analyzer. The fully automated system measures CO in ambient air, and the detector sensitivity and background signals are calibrated by referencing the measurements to a CO-in-air standard gas (~1 ppmv) and to CO-free air scrubbed with a catalyst, respectively. We examined the artificial production of CO in the high-pressure working gas standards during storage by referencing the measurements to CO standard gases maintained as our primary scale before and after use on the ships. The onboard performance of the continuous CO measurement system was evaluated by comparing its data with data from laboratory analyses of flask samples using gas chromatography with a reduction gas detector. The reasonably good consistency between the two independent measurement methods demonstrated the good performance of both methods over the course of 3–5 years. The continuous measurement system was more useful than the flask sampling method for regionally polluted air masses, which were often encountered on Southeast Asian cruises.

Air–Sea fluxes from ICOADS: the construction of a new gridded dataset with uncertainty estimates

AbstractThe methods used to calculate a new in situ global dataset of air–sea exchanges, called the NOCS Flux Dataset v2.0, are described. The fluxes have been derived from in situ weather reports from Voluntary Observing Ships (VOS) covering the period 1973–2006. The reports have been adjusted for known biases and residual uncertainties estimated. The dataset is constructed using Optimal Interpolation (OI) using new estimates of random uncertainty in the observations. Daily fields have been calculated on a 1° latitude by 1° longitude grid, each grid box and time step have an associated uncertainty estimate. Monthly fields have been calculated from simple averages of the daily fields and monthly uncertainty estimates from the daily uncertainties, using estimates of the autocorrelation between the daily uncertainty estimates. The uncertainties due to the choice of flux parameterisation have not been accounted for. Bias adjustments applied to the data are shown to reduce trends in the data and to improve the consistency of estimates of air temperature, sea surface temperature (SST) and specific humidity. The bias adjustments also improve the agreement of NOCS v2.0 with independent data from research moorings. Cross‐validation of the dataset suggests that the uncertainty estimates are realistic, but that the uncertainties are probably underestimated in high variability regions and overestimated in regions with lower variability. Copyright © 2009 Royal Meteorological Society

A gridded sea surface salinity data set for the tropical Pacific with sample applications (1950–2008)

We present a gridded data set of Sea Surface Salinity (SSS) for the tropical Pacific (120°E–70°W; 30°N–30°S), with a grid resolution of 1° longitude, 1° latitude and 1 month, from 1950 to 2008. The product, together with its associated error field, is derived from an objective analysis of about 10 million validated SSS records, with most of the data originating from Voluntary Observing Ships, TAO/TRITON moorings and Argo profilers (during the most recent period). We expect this product to benefit studies in oceanography, meteorology and paleoceanography. As examples of applications, we analyse: (a) the seasonal and ENSO (El Niño Southern Oscillation) modes of observed SSS variability, (b) the ability of 23 coupled models used in the Intergovernmental Panel for Climate Change 4th Assessment Report (IPCC AR4) to simulate the mean SSS and these two time varying modes, and (c) the usefulness of the SSS product and of its associated error field in calibrating and validating the paleo-salinity time series. We anticipate improvements and regular updates to our product, as more SSS data become available from in situ networks and from the ongoing and near-future satellite-derived observations by SMOS (Soil Moisture and Ocean Salinity) and Aquarius.

Spatiotemporal variations of <i>f</i>CO<sub>2</sub> in the North Sea

Abstract. Data from two Voluntary Observing Ship (VOS) (2005–2007) augmented with data subsets from ten cruises (1987–2005) were used to investigate the spatiotemporal variations of the CO2 fugacity in seawater (fCO2sw) in the North Sea at seasonal and inter-annual time scales. The observed seasonal fCO2sw variations were related to variations in sea surface temperature (SST), biology plus mixing, and air-sea CO2 exchange. Over the study period, the seasonal amplitude in fCO2sw induced by SST changes was 0.4–0.75 times those resulting from variations in biology plus mixing. Along a meridional transect, fCO2sw normally decreased northwards (−12 μatm per degree latitude), but the gradient disappeared/reversed during spring as a consequence of an enhanced seasonal amplitude of fCO2sw in southern parts of the North Sea. Along a zonal transect, a weak gradient (−0.8 μatm per degree longitude) was observed in the annual mean fCO2sw. Annually and averaged over the study area, surface waters of the North Sea were CO2 undersaturated and, thus, a sink of atmospheric CO2. However, during summer, surface waters in the region 55.5–54.5° N were CO2 supersaturated and, hence, a source for atmospheric CO2. Comparison of fCO2sw data acquired within two 1°×1° regions in the northern and southern North Sea during different years (1987, 2001, 2002, and 2005–2007) revealed large interannual variations, especially during spring and summer when year-to-year fCO2sw differences (≈160–200 μatm) approached seasonal changes (≈200–250 μatm). The springtime variations resulted from changes in magnitude and timing of the phytoplankton bloom, whereas changes in SST, wind speed and total alkalinity may have contributed to the summertime interannual fCO2sw differences. The lowest interannual variation (10–50 μatm) was observed during fall and early winter. Comparison with data reported in October 1967 suggests that the fCO2sw growth rate in the central North Sea was similar to that in the atmosphere.

Basin‐scale pCO2 maps estimated from ARGO float data: A model study

A novel method for mapping surface pCO2 on a basin scale using ARGO floats is presented and tested in the framework of an eddy‐resolving biogeochemical model of the North Atlantic. Voluntary observing ship (VOS) and ARGO float coverage of the year 2005 is applied to the model to generate synthetic “observations.” The model‐generated VOS line “observations” of pCO2, SST, and SSS form a training data set for a self‐organizing neural network. The trained neural network is subsequently applied locally to estimate pCO2 from the model‐generated ARGO float SST and SSS data. The local pCO2 estimates at the simulated float positions are extrapolated using objective mapping. The accuracy of the nearly basinwide pCO2 estimates is assessed by comparing against the pCO2 output of the model that serves as synthetic “ground truth.” For an ARGO float coverage of the year 2005, the resulting monthly mean pCO2 maps cover 70% of the considered area (15°N to 65°N) with an RMS error of 15.9 μatm. Compared to remote sensing‐based estimates that suffer from large regional gaps in optical satellite data coverage, the RMS error in reproducing the annual cycle of pCO2 can be reduced by 42% when the more evenly distributed ARGO float‐based data are used.

Seasonal variability of fCO 2 in the Angola-Benguela region

The data reported were collected on 28 cruises using volunteer observing ships (VOS) along the QUIMA-VOS line to gauge the fugacity of CO 2 ( fCO 2) over surface water in the south east Atlantic Ocean, over 3 years, from July 2005 to June 2008. The VOS line crosses the region from west to east, approaching the coast along the southern latitudes, and revealing the effects of offshore filaments in the northern areas, plus direct upwelled water in the southern areas. A complex pattern of distribution appears, with areas of super-saturation and low CO 2 concentrations, associated with temperature variability and ocean circulation, with the highest variability associated to the most significant upwelling cells. Climatological seasonal cycles of sea surface temperature (SST) and fCO 2 for the southern Benguela region presented increased monthly anomalies and a bi-modal seasonal SST cycle, related to the proximity to coastal waters and seasonal upwelled water between September and March, reducing the maximum summer temperature. The biological drawdown of fCO 2, controlled by the seasonality thanks to the upwelling activity, contributed with values ranging from 150 to over 250 μatm. From 2005 to 2008, the temperature sharply increased in the southern Benguela region, by 0.47 °C yr −1 whereas the fCO 2 in seawater decreased from 2.5 μatm yr −1 in the northern Namibia cell, to 0.4 μatm yr −1 in the southern Benguela area. The latter suggests higher biological activity related to an increase in the upwelling index together with the intrusion of lower inorganic carbon content seawater in the southern area from the Agulhas bank. south of 20°S, the east Atlantic Ocean acts as a net sink of CO 2, with CO 2 fluxes for the year 2007 increasing from −0.56 mol m −2 yr −1 (20–24°S) to −3.24 mol m −2 yr −1 (32–34°S). In the coastal area of South Africa, the constant biologically mediated CO 2 drawdown reduces the fCO 2 drastically, and maintains the partial CO 2 pressure below the levels to be found in the atmosphere all year round.

A New Air–Sea Interaction Gridded Dataset from ICOADS With Uncertainty Estimates

The exchange, or flux, of heat between the oceans and atmosphere is an important driver of the global oceanic and atmospheric circulations but remains poorly quantified. Direct measurement of heat flux remains a research activity and so global heat flux datasets are generated using observations of winds, air and sea temperatures, and humidity as input to heat flux parameterizations known as “bulk formulas.” We remain dependent on the observations from merchant ships in the Voluntary Observing Ships (VOS) program, which are archived in the International Comprehensive Ocean-Atmosphere Dataset (ICOADS); measurements from buoys are sparse and satellites cannot accurately recover all the variables required for heat flux calculation. Careful analysis of VOS data is necessary to produce gridded datasets of meteorological variables and fluxes with the accuracy required for climate research. Past in situ flux datasets have averaged observations on monthly timescales to reduce random uncertainty. It has therefore been hard to understand the contributions to observed variability from measurement errors, poor sampling, or natural variability. The new dataset, which covers the period 1973 to 2006, avoids this problem by first constructing daily mean fields using optimal interpolation. This allows each component of variability to be handled correctly and, for the first time, uncertainty estimates to be produced. New bias adjustments have also been developed and applied. The new dataset is described and a preliminary comparison with flux estimates from moored buoys, satellites, and atmospheric reanalysis models is presented.

Neural network‐based estimates of North Atlantic surface pCO2 from satellite data: A methodological study

A new method is proposed to estimate ocean surface pCO2 from remotely sensed surface temperature and chlorophyll data. The method is applied to synthetic observations provided by an eddy‐resolving biogeochemical model of the North Atlantic. The same model also provides a perfectly known simulated pCO2 “ground truth” used to quantitatively assess the success of the estimation method. Model output is first sampled according to realistic voluntary observing ship (VOS) and satellite coverage. The model‐generated VOS “observations” are then used to train a self‐organizing neural network that is subsequently applied to model‐generated “satellite data” of surface temperature and surface chlorophyll in order to derive basin‐wide monthly maps of surface pCO2. The accuracy of the estimated pCO2 maps is analyzed with respect to the “true” surface pCO2 fields simulated by the biogeochemical circulation model. We also investigate the accuracy of the estimated pCO2 maps as a function of VOS line coverage, remote sensing errors, and the interpolation of missing remote sensing data due to cloud cover and low solar irradiation in winter. For a simulated “sampling” corresponding to VOS lines and patterns of optical satellite coverage of the year 2005, the neural net can successfully reproduce pCO2 from model‐generated “remote sensing data” of SST and Chl. Basin‐wide RMS errors amount to 19.0 μatm for a hypothetical perfect interpolation scheme for remote sensing data gaps and 21.1 μatm when climatological surface temperature and chlorophyll values are used to fill in areas lacking optical satellite coverage.

Optimal evaluation of the surface ocean CO2 system in the northern North Atlantic using data from voluntary observing ships

This work evaluates whether an accurate calculation of the entire CO2 system in the northern North Atlantic can be carried out using a combination of in situ fugacity of CO2 (fCO2) and ancillary data often measured on Voluntary Observing Ships (VOS), i.e., sea surface temperature (SST) and sea surface salinity (SSS), as well as nitrate (NO3−). Two approaches are tested: (I) determination of At from SSS and then calculating Ct from measured fCO2 and estimated At; and (II) determination of Ct from SSS, SST, and NO3− and then calculating At from measured fCO2 and estimated Ct. The optimal approach was found to be determination of At from SSS and then calculating Ct from measured fCO2 and estimated At. This allowed At to be determined with a mean bias of −1.8 µmol kg−1 and root mean square (rms) deviation 6.2 µmol kg−1 and then Ct to be calculated with a mean bias of −1.0 µmol kg−1 and standard error of calculation of 7.4 µmol kg−1, as validated using independent data sets.

Ocean acidification of the Greater Caribbean Region 1996–2006

The global oceans serve as the largest sustained natural sink for increasing atmospheric carbon dioxide (CO2) concentrations. As this CO2 is absorbed by seawater, it not only reacts causing a reduction in seawater pH (or acidification) but also decreases the carbonate mineral saturation state (Ω), which plays an important role in calcification for many marine organisms. Ocean acidification could affect some of the most fundamental biological and geochemical processes of the sea in coming decades. Observations obtained in situ from Volunteer Observing Ships and multiple geochemical surveys have been extended using satellite remote sensing and modeled environmental parameters to derive estimates of sea‐surface alkalinity (AT) and carbon dioxide partial pressure (pCO2,sw). Pairing estimates of AT and pCO2,sw have permitted characterization of the changes in sea‐surface Ω, which have transpired over the past decade throughout the Greater Caribbean Region as a consequence of ocean acidification. The results reveal considerable spatial and temporal variability throughout the region. Despite this variability, we observed a strong secular decrease in aragonite saturation state (Ωarg) at a rate of approximately −0.012 ± 0.001 Ωarg yr−1 (r2 = 0.97, P < 0.001).

An Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) for Deployment aboard Volunteer Observing Ships (VOS)

Abstract The infrared SST autonomous radiometer (ISAR) is a self-calibrating instrument capable of measuring in situ sea surface skin temperature (SSTskin) to an accuracy of 0.1 K. Extensive field deployments alongside two independent research radiometers measuring SSTskin using different spectral and geometric configurations show that, relatively, ISAR SSTskin has a zero bias ±0.14 K rms. The ISAR instrument has been developed for satellite SST validation and other scientific programs. The ISAR can be deployed continuously on voluntary observing ships (VOS) without any service requirement or operator intervention for periods of up to 3 months. Five ISAR instruments have been built and are in sustained use in the United States, China, and Europe. This paper describes the ISAR instrument including the special design features that enabled a single channel radiometer with a spectral bandpass of 9.6–11.5 μm to be adapted for autonomous use. The entire instrument infrared optical path is calibrated by viewing two blackbody reference cavities at different temperatures to maintain high accuracy while tolerating moderate contamination of optical components by salt deposition. During bad weather, an innovative storm shutter, triggered by a sensitive optical rain gauge, automatically seals the instrument from the external environment. Data are presented that verify the instrument calibration and functionality in such situations. A watchdog timer and auto-reboot function support automatic data logging recovery in case of power outages typically encountered on ships. An RS485 external port allows supporting instruments that are not part of the core ISAR package (e.g., a solarimeter) to be logged using the ISAR system. All data are processed by the ISAR instrument and are relayed to a host computer via the RS232 serial link as (National Electronics Manufacturers Association) NEMA-style strings allowing easy integration into many commercial onboard scientific data logging systems. In case of a communications failure, data are stored on board using a CompactFlash card that can be retrieved when the instrument is serviced. The success of the design is demonstrated using results obtained over 21 months in the English Channel and Bay of Biscay as part of a campaign to validate SSTskin observations derived from the Environmental Satellite (Envisat) Advanced Along-Track Scanning Radiometer (AATSR).

Estimation of the oceanic pCO<sub>2</sub> in the North Atlantic from VOS lines in-situ measurements: parameters needed to generate seasonally mean maps

Abstract. Automated instruments on board Volunteer Observing Ships (VOS) have provided high-frequency pCO2 measurements over basin-wide regions for a decade or so. In order to estimate regional air-sea CO2 fluxes, it is necessary to interpolate between in-situ measurements to obtain maps of the marine pCO2. Such an interpolation remains, however, a difficult task because VOS lines are too distant from each other to capture the high pCO2 variability. Relevant physical parameters available at large scale are thus necessary to serve as a guide to estimate the pCO2 values between the VOS lines. Satellites do not measure pCO2 but they give access to parameters related to the processes that control its variability, such as sea surface temperature (SST). In this paper we developed a method to compute pCO2 maps using satellite data (SST and CHL, the chlorophyll concentration), combined with a climatology of the mixed-layer depth (MLD). Using 15 401 measurements of surface pCO2 acquired in the North Atlantic between UK and Jamaica, between June 1994 and August 1995, we show that the parameterization of pCO2 as a function of SST, CHL and MLD yields more realistic pCO2 values than parameterizations that have been widely used in the past, based on SST, latitude, longitude or SST only. This parameterization was then used to generate seasonal maps of pCO2 over the North Atlantic. Results show that our approach yields the best marine pCO2 estimates, both in terms of absolute accuracy, when compared with an independent data set, and of geographical patterns, when compared to the climatology of Takahashi et al. (2002). This suggests that monitoring the seasonal variability of pCO2 over basin-wide regions is possible, provided that sufficient VOS lines are available.

The Underway Conductivity–Temperature–Depth Instrument

Abstract The development of the Underway Conductivity–Temperature–Depth (UCTD) instrument is motivated by the desire for inexpensive profiles of temperature and salinity from underway vessels, including volunteer observing ships (VOSs) and research vessels. The UCTD operates under the same principle as an expendable probe. By spooling tether line both the probe and a winch aboard ship, the velocity of the line through the water is zero, the line drag is negligible, and the probe can get arbitrarily deep. Recovery is accomplished by reeling the line back in. Recovering the UCTD has some advantages: 1) the cost per profile decreases with increasing use, 2) sensors can be calibrated postdeployment, 3) the UCTD carries a pressure sensor so depth is measured directly, and 4) no hazardous materials are left behind. The design goal for the UCTD was to obtain profiles deeper than 100 m at 20 kt (typical of a VOS). This goal has been surpassed, as it is able to profile to over 150 m at 20 kt and to over 400 m at 10 kt. The first operational use of the UCTD occurred during a May–June 2004 cruise, the purpose of which was to examine the effect of internal waves and spice on long-range acoustic propagation. Over 160 UCTD casts were completed, resulting in a hydrographic section with resolutions of 10 km horizontally and 5 m vertically.

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.

Metadata from WMO Publication No. 47 and an Assessment of Voluntary Observing Ship Observation Heights in ICOADS

Abstract It is increasingly recognized that metadata can significantly improve the quality of scientific analyses and that the availability of metadata is particularly important for the study of climate variability. The International Comprehensive Ocean–Atmosphere Data Set (ICOADS) contains in situ observations frequently used in climate studies, and this paper describes the ship metadata that are available to complement ICOADS. This paper highlights the metadata available in World Meteorological Organization Publication No. 47 that include information on measurement methods and observation heights. Changing measurement methods and heights are known to be a cause of spurious change in the climate record. Here the authors focus on identifying measurement heights for air temperature and wind speed and also give information on SST measurement depths.

Estimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part II: Impact on Trends and Interannual Variability

Abstract Using the same approach as in Part I, here it is shown how sampling problems in voluntary observing ship (VOS) data affect conclusions about interannual variations and secular changes of surface heat fluxes. The largest uncertainties in linear trend estimates are found in relatively poorly sampled regions like the high-latitude North Atlantic and North Pacific as well as the Southern Ocean, where trends can locally show opposite signs when computed from the regularly sampled and undersampled data. Spatial patterns of shorter-period interannual variability, quantified through the EOF analysis, also show remarkable differences between the regularly sampled and undersampled flux datasets in the Labrador Sea and northwest Pacific. In particular, it is shown that in the Labrador Sea region, in contrast to regularly sampled NCEP–NCAR reanalysis fluxes, VOS-like sampled NCEP–NCAR reanalysis fluxes neither show significant interannual variability nor significant trends. These regions, although quite localized covering small parts of the globe, play a crucial role for the coupled atmosphere–ocean system. In the Labrador Sea, for instance, interannual and decadal-scale changes of the surface net heat fluxes are known to affect oceanic convection and, thus, the meridional overturning circulation of the Atlantic Ocean. From a discussion of current atmospheric data assimilation systems it is argued that in poorly sampled regions reanalysis products are superior to VOS-based products for studying interannual and interdecadal variations of atmosphere–ocean interaction. In well-sampled regions, on the other hand, conclusions about surface heat flux variations are relatively insensitive to the choice of the flux products used (VOS versus reanalysis data). The results are confirmed for two different datasets, that is, ECMWF 40-yr Re-Analysis (ERA-40) data and seasonal integrations with a recent version of the ECMWF model in which no actual data were assimilated.

Estimation of the Impact of Sampling Errors in the VOS Observations on Air–Sea Fluxes. Part I: Uncertainties in Climate Means

Abstract Sampling uncertainties in the voluntary observing ship (VOS)-based global ocean–atmosphere flux fields were estimated using the NCEP–NCAR reanalysis and ECMWF 40-yr Re-Analysis (ERA-40) as well as seasonal forecasts without data assimilation. Air–sea fluxes were computed from 6-hourly reanalyzed individual variables using state-of-the-art bulk formulas. Individual variables and computed fluxes were subsampled to simulate VOS-like sampling density. Random simulation of the number of VOS observations and simulation of the number of observations with contemporaneous sampling allowed for estimation of random and total sampling uncertainties respectively. Although reanalyses are dependent on VOS, constituting an important part of data assimilation input, it is assumed that the reanalysis fields adequately reproduce synoptic variability at the sea surface. Sampling errors were quantified by comparison of the regularly sampled (i.e., 6 hourly) and subsampled monthly fields of surface variables and fluxes. In poorly sampled regions random sampling errors amount to 2.5°–3°C for air temperature, 3 m s−1 for the wind speed, 2–2.5 g kg−1 for specific humidity, and 15%–20% of the total cloud cover. The highest random sampling errors in surface fluxes were found for the sensible and latent heat flux and range from 30 to 80 W m−2. Total sampling errors in poorly sampled areas may be higher than random ones by 60%. In poorly sampled subpolar latitudes of the Northern Hemisphere and throughout much of the Southern Ocean the total sampling uncertainty in the net heat flux can amount to 80–100 W m−2. The highest values of the uncertainties associated with the interpolation/extrapolation into unsampled grid boxes are found in subpolar latitudes of both hemispheres for the turbulent fluxes, where they can be comparable with the sampling errors. Simple dependencies of the sampling errors on the number of samples and the magnitude of synoptic variability were derived. Sampling errors estimated from different reanalyses and from seasonal forecasts yield qualitatively comparable spatial patterns, in which the actual values of uncertainties are controlled by the magnitudes of synoptic variability. Finally, estimates of sampling uncertainties are compared with the other errors in air–sea fluxes and the reliability of the estimates obtained is discussed.

Variability of the Winter Wind Waves and Swell in the North Atlantic and North Pacific as Revealed by the Voluntary Observing Ship Data

Abstract This paper analyses secular changes and interannual variability in the wind wave, swell, and significant wave height (SWH) characteristics over the North Atlantic and North Pacific on the basis of wind wave climatology derived from the visual wave observations of voluntary observing ship (VOS) officers. These data are available from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) collection of surface meteorological observations for 1958–2002, but require much more complicated preprocessing than standard meteorological variables such as sea level pressure, temperature, and wind. Visual VOS data allow for separate analysis of changes in wind sea and swell, as well as in significant wave height, which has been derived from wind sea and swell estimates. In both North Atlantic and North Pacific midlatitudes winter significant wave height shows a secular increase from 10 to 40 cm decade−1 during the last 45 yr. However, in the North Atlantic the patterns of trend changes for wind sea and swell are quite different from each other, showing opposite signs of changes in the northeast Atlantic. Trend patterns of wind sea, swell, and SWH in the North Pacific are more consistent with each other. Qualitatively the same conclusions hold for the analysis of interannual variability whose leading modes demonstrate noticeable differences for wind sea and swell. Statistical analysis shows that variability in wind sea is closely associated with the local wind speed, while swell changes can be driven by the variations in the cyclone counts, implying the importance of forcing frequency for the resulting changes in significant wave height. This mechanism of differences in variability patterns of wind sea and swell is likely more realistic than the northeastward propagation of swells from the regions from which the wind sea signal originates.