1,721,017 research outputs found
Air–Sea fluxes from ICOADS: the construction of a new gridded dataset with uncertainty estimates
No full textThe 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
A new air-sea interaction gridded dataset from ICOADS with uncertainty estimates.
No full textThe 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 parameterisations known as "bulk formulae". 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 in order 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.<br/
A Dynamically Consistent ENsemble of Temperature at the Earth surface since 1850 from the DCENT dataset
No full textAccurate historical records of Earth’s surface temperatures are central to climate research and policy development. Widely- used estimates based on instrumental measurements from land and sea are, however, not fully consistent at either global or regional scales. To address these challenges, we develop the Dynamically Consistent ENsemble of Temperature (DCENT), a 200-member ensemble of monthly surface temperature anomalies relative to the 1982–2014 climatology. Each DCENT member starts from 1850 and has a 5⇥5 resolution. DCENT leverages several updated or recently-developed approaches of data homogenization and bias adjustments: an optimized pairwise homogenization algorithm for identifying breakpoints in land surface air temperature records, a physics-informed inter-comparison method to adjust systematic offsets in sea-surface temperatures recorded by ships, and a coupled energy balance model to homogenize continental and marine records. Each approach was published individually, and this paper describes a combined approach and its application in developing a gridded analysis. A notable difference of DCENT relative to existing temperature estimates is a cooler baseline for 1850–1900 that implies greater historical warming
Metadata from WMO Publication No. 47 and an Assessment of Voluntary Observing Ship Observation Heights in ICOADS
No full textIt 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.<br/
Can a state of the art atmospheric general circulation model reproduce recent NAO related variability at the air-sea interface?
Full text linkRecent studies claim that useful predictability of the North Atlantic Oscillation (NAO) up to several years in advance may be possible using atmospheric models in which the sea surface temperature (SST) is specified from observations. Achieving this goal requires that such models adequately capture the observed variation in the NAO at interannual as well as interdecadal timescales. We investigate whether this is the case by comparing interannual variability in the HadAM3 atmospheric model with observations in the SOC air-sea flux dataset for 1980-1995. We find that the model NAO time variation does not correspond to that observed, thus claims of multiannual predictability need to be viewed with caution. In addition, analysis of the observations reveals that NAO related SST anomalies do not exert a significant heat flux feedback on the atmosphere at seasonal to interannual timescales
Intercomparison of satellite-derived SST with logger data in the Caribbean—Implications for coral reef monitoring
Full text linkSince the early 1980s measurements of Sea Surface Temperature (SST) derived from satellite-borne instruments have provided a wide range of global gridded products documenting changes in SST. However, there are many sources of uncertainty in these records and significant differences exist among them. One use of these products is identification of coral bleaching events, and the predictions of the impact of future warming on coral reefs. This relies on an understanding of how temperatures near reefs as recorded by SST products differ from the in-situ SST experienced by the corals. This difference is a combination of real spatio-temporal variations, inadequate in product resolution and errors in the products. This paper investigates the relationship between the local temperature measured in-situ by loggers at coral sites in the western tropical Atlantic and two high resolution satellite SST products. Using differences among ESA SST CCI v2.1 (CCI analysis SST), NOAA CoralTemp SST products and in-situ logger data from coral reefs, an assessment of the satellite products with focus on coral reef monitoring is carried out. Discrepancies between the two products can be large, especially in coastal areas and for the warmest and coldest months when there is a particular risk of bleaching. By comparison to the stable CCI analysis SST product, CoralTemp was found to overestimate the rise in SST by as much as 0.20°C per decade. In almost all cases SSTs from CCI analysis SST were more consistent with temperatures measured near the corals than those from CoralTemp
Assessing the health of the global surface marine observing system
Full text linkThe in situ surface marine climate observing system includes contributions from several different types of observing platforms. Most observations come from mobile platforms, e.g. ships or surface drifting buoys. Climate applications using marine observations often require fields of environmental parameters to be constructed on regular spatiotemporal grids. User requirements are therefore typically presented in terms of parameter uncertainty at particular space and timescales. It is therefore important to relate the characteristics of marine observations, in terms of their expected quality and sampling distribution, to these requirements. A simple method to estimate the instrumental uncertainty in fields derived from a mixture of observation types is presented. This method enables preliminary assessment of the extent to which the available observations meet the stated user requirements.Example observing system adequacy assessments are presented for two climate variables, sea surface temperature (SST) and marine air temperature (MAT) using in situ data. The method is also applicable to gridded data sets constructed from combined in situ and satellite data. While the global metrics for SST show an improvement in observing system adequacy over time, the adequacy for MAT is declining. The assessments can determine the most efficient approach to improving observing system adequacy. For in situ SST the best approach would be to increase the number of different platforms making observations. For MAT, increasing the number of observations overall, regardless of platform and increasing the geographical coverage is required to reduce the uncertainty.The assessments would be improved by more extensive evaluation of uncertainties associated with each different variable for each platform type. It would also be beneficial to review the completeness of the user requirements: e.g. to include user requirements relating to the stability of averages on large space and timescales required for climate monitoring, or for constructing estimates of air–sea exchange
A comparison of oceanic skin effect parameterisations using ship borne radiometer data
Full text linkSea surface temperature data from a shipborne radiometer were used to assess the thermal skin effect parameterization schemes of Saunders [1967], Hasse [1971], Schlüssel et al. [1990], and Soloviev and Schlüssel [1994]. Under low-wind, high-insolation conditions, the presence of a near surface thermocline resulted in an apparent skin effect which depended on the history of the surface heating. Neglecting these cases, the Saunders [1967] and other schemes which omit solar radiation were the most effective. The observed variation with wind speed of the adjustable coefficient, ? s , in the Saunders formulae was similar to that predicted by Soloviev and Schlüssel [1994], but the values were significantly higher, resulting in a greater magnitude of the observed skin effect. For the conditions occurring in this data set the better formulae predicted the skin effect with a standard deviation of ±0.16° C compared to a variation of the observed skin effect of nearly ±0.3°C
A probabilistic approach to ship voyage reconstruction in ICOADS
Full text linkThe International Comprehensive Ocean-Atmosphere Data Set (ICOADS) provides the main archive for surface marine observations for the past approximately 150 years. ICOADS ship identifier (ID) information is often missing or unusable, preventing the linking of reports to an individual ship. A method for the reconstruction of ship voyages in ICOADS is presented, by which groups of reports can be associated with an individual ship or ship track. The method defines a function representing the probability density function (pdf) of any particular report being associated with a group of reports. The parameters of the pdf are calculated from the ship data themselves, giving the likely variation of a ship report perpendicular to its overall direction of travel. For groups of reports with ID information, the PDF is used to associate reports without ID information with the known-ID track. Reports without ID information are then clustered together to form the most probable track. Results are shown for the period 1855–1969. Both the percentage of reports associated with tracks and the length of those tracks increase substantially following tracking. Initial validation of the results was performed by visual inspection: the model implementation was then refined to improve the results. Confidence in the tracking is increased by a demonstration that the method clusters together reports with similar sea surface temperature characteristics. Issues in the data were found to be one of the main challenges in implementing the tracking technique. Particular problems encountered included the coarse resolution of some position information; reports that were mispositioned in either space or time; unidentified duplicate reports; and the fragmentation of voyages between different ICOADS acquisition sources. Some of these effects could be ameliorated by pre-processing of ICOADS reports, however a full reprocessing of the historical input sources to ICOADS would be required to make further improvements
A comparison of SSM/I-derived global marine surface specific humidity datasets
Full text linkSatellite-based microwave sensors have, since the 1980s, provided a means to retrieve near-surface marine specific humidity (qa), accurate estimation of which is necessary for climate and air–sea interaction applications. Seven satellite measurement-derived monthly mean humidity datasets are compared with one another and with a dataset constructed from in situ measurements. The means, spatial and temporal structures of the datasets are shown to be markedly different, with a range of yearly, global mean qa of ?1?g?kg–1. Comparison of the datasets derived using the same satellite measurements of brightness temperature reveals differences in qa that depend on the source of satellite data; the processing and quality control applied to the data; and the algorithm used to derive qa from the satellite measurements of brightness temperature. Regional differences between satellite-derived qa due to the choice of input data, quality control and retrieval algorithm can all exceed the accuracy requirements for surface flux calculation of ?0.3?g?kg–1 and in some cases can be several g kg–1 in monthly means for some periods and regions
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