1,721,044 research outputs found
Use of WMO47 Metadata in a Global Flux Climatology
Full text linkThe SOC Flux Climatology (Josey et al., 1998) is unique in its use of Voluntary Observing Ship (VOS) metadata to improve the quality of ocean surface flux estimates obtained from merchant ship data within the Comprehensive Ocean-Atmosphere Data Set Release 1a (COADS, Woodruff et al. 1993). Corrections to the ship data combined two WMOsponsored data sources: firstly the VOS Special Observing Project - North Atlantic (VSOP-NA) which identified errors in merchant ship weather observations and secondly the metadata collected by Port Meteorological Officers around the world and published annually by the WMO (WMO47, e.g. WMO 1994). The metadata were merged with COADS individual reports giving instrument types and heights for most VOS weather reports. These metadata allowed the identification of those reports that required correction following the recommendations of the VSOP-NA.The resulting fluxes are now starting to be validated and the total heat flux from the SOC climatology agrees well with high quality research data from buoys where that is available
Ships Observing Marine Climate: a catalogue of the VOS participating in the VSOP-NA
Full text linkOur present knowledge of the marine climate, as represented by data sets such as COADS (Woodruff et al., 1987), is based on meteorological observations from the Voluntary Observing Ships (VOS). Because the VOS are merchant ships, rather than specially designed meteorological platforms, errors and biases exist in the data. However there is little information readily available to the climatologist either on the nature of the VOS fleet or on the observing practises which are used. This report, describing the forty-six ships that participated in the Voluntary Observing Ships' Special Observing Project - North Atlantic (VSOP-NA), therefore serves two purposes:(i) it provides a reference document to aid analysis of the VSOP-NA data set,(ii) it gives a detailed description of a subset of the VOS, which will be of value in the interpretation of marine climate data sets.This report is in two parts, Part 1 is an overall summary of the ship characteristics, Part 2 is a ship by ship description. The next section will briefly describe the VSOP-NA project, followed by a summary of the characteristics of the VSOP-NA ships (Section 3). Since these ships were specially selected (Section 2.2), the degree to which they are representative of the whole VOS fleet will be carefully considered. The meteorological instrumentation used by the VOS varies depending on which meteorological agency recruited the ships. That used on the chosen VSOP-NA ships is typical of VOS recruited by the countries bordering the North Atlantic, and will be described in Section 4. Section 5 is a summary of Part 1 of the report.Part 2 presents the VSOP-NA ship catalogue. This includes, for each ship, diagrams of the layout (indicating in particular the exposure of the sensors), a summary of the geographical positions at which observations were obtained, and details of the instrumentation used.<br/
Toward estimating climatic trends in SST. Part III: systematic biases
No full textA method is developed to quantify systematic errors in two types of sea surface temperature (SST) observations: bucket and engine-intake measurements. A simple linear model is proposed where the SST measured using a bucket is cooled or warmed by a fraction of the air–sea temperature difference and the SST measured using an engine intake has a constant bias. The model is applied to collocated nighttime observations made at moderate wind speeds, allowing the effects of solar radiation and strong vertical gradients in the upper ocean to be neglected. The analysis is complicated by large random errors in all of the variables used. To estimate coefficients in this model, a novel type of linear regression, where errors in two variables are correlated with each other, is introduced. Because of the uncertainty in a priori estimates of the error covariance matrix, a Bayesian analysis of the regression problem is developed, and maximum likelihood approximations to the posterior distributions of the model parameters are obtained.Results show that the temperature change in bucket SST resulting from the air–sea temperature difference can be detected. The analysis suggests that bucket SST may be in error by a fraction from 0.12° ± 0.02° to 0.16° ± 0.02°C of the air–sea temperature difference. When this temperature change of the bucket SST is accounted for, a warm bias in engine-intake SST in the mid- to late 1970s and the 1980s was found to be smaller than that suggested by previous studies, ranging between 0.09° ± 0.06° and 0.18° ± 0.05°C. For the early 1990s the model suggests that the engine-intake SSTs may have a cold bias of ?0.13° ± 0.07°C.<br/
The effect of instrument exposure on marine air temperatures: an assessment using VOSClim data
No full textObservations of marine air temperature (MAT) by Voluntary Observing Ships (VOS) are known to contain significant biases due to solar heating of the sensor environment. MAT and humidity observations are usually made using wet- and dry-bulb thermometers housed in Stevenson screens, or with psychrometers. These instruments are typically mounted in the bridge wings or on the wheel-house top. If not sited carefully then the instruments can be poorly exposed to the undisturbed environmental conditions and have inadequate ventilation, leading to biased observations of both MAT and humidity.In this paper we use observations collected as part of the VOS Climate (VOSClim) project to investigate the relationship between instrument exposure and heating errors. The heating errors are estimated as the difference between the observed MAT and the collocated output of a numerical weather prediction model. The instrument exposures are assessed from hotographs of the instruments. Currently, photographs of the instruments and sufficient observations exist for 17 VOSClim ships.Two methods of assessing the instrument exposure using the observations are presented. The first method is based on the skewness of the distribution of estimated heating errors for individual ships. The second method is based on a correction developed to correct the heating errors and uses the ratio of the heating to cooling terms in the correction. When ships are ranked both on the skewness and on the ratio of the heating to cooling terms, there is a statistically significant correspondence between the rankings and the visual assessments of instrument exposure. The skewness of the distribution of estimated errors in MAT is proposed as a simple indicator of instrument exposure
Marine data and climatology workshops and recommendations.
No full textThis document provides information on the series of JCOMM Workshops on Advances in Marine Climatology (CLIMAR) (latest in 2003) which have alternated (approximately every two years since 1999) with the International Workshops on Advances in the Use of Historical Marine Climate Data (MARCDAT), (latest in 2005). The Team will also be informed regarding the planning status for the upcoming CLIMARIII Session, tentatively scheduled for Poland in May 2008, and about the consolidated Recommendations now being tracked from both workshop series at: www.marineclimatology.net
WMO Publication 47: Consistency Checking and Gap Filling, Version 1.0
Full text linkWMO Publication 47 (Pub. 47) contains information on the Voluntary Observing Ship (VOS) observations contained within ICOADS. However, this data has been collected over a
50 year period by numerous countries and in a number of different formats, ranging from 13 fields in the 1950’s up to around 120 fields in the modern editions. The changing formats and contents of Pub. 47 are described in Kent et al. (2006). The addition of new fields leads to information becoming available which may be valid for records in earlier editions. As a result, it should be possible to increase the amount of information available from Pub. 47 by
copying new fields into earlier additions as they become available.
Due to the operational nature of Pub. 47 and its collection by different agencies there are a large number of coding differences and typographical errors in the metadata. Also, due to WMO regulations, once data has been added to Pub. 47 by a country that data persists until the next entry from that country. This leads to out of date metadata and may lead to ambiguous entries where multiple records for the same ship from different countries exist in the same edition.
This report describes the process used to homogenize the metadata data set, correct typographic and coding errors and to copy information into the earlier editions when new
fields are added. Section 2 describes the process of homogenizing the dataset and section 3 makes an assessment of the homogenization
The accuracy of meteorological observations from Voluntary Observing ships: Present status and future requirements
Full text linkQuantifying random measurement errors in Voluntary Observing Ships' meteorological observations
No full textEstimates of the random measurement error contained in surface meteorological observations from Voluntary Observing Ships (VOS) have been made on a 30° area grid each month for the period 1970 to 2002. Random measurement errors are calculated for all the basic meteorological variables: surface pressure, wind speed, air temperature, humidity and sea-surface temperature. The random errors vary with space and time, the quality assurance applied and the types of instrument used to make the observations. The estimates of random measurement error are compared with estimates of total observational error, which includes uncertainty due both to measurement errors and to observational sampling. In tropical regions the measurement error makes a significant contribution to the total observational error in a single observation, but in higher latitudes the sampling error can be much larger
Assessment of the Marine Observing System (ASMOS): Final Report
No full textThe definition of user requirements for the marine observing system is not a simple process. When asked, users have a tendency to ask "what can you provide?" or reply "as much as possible". Sometimes there is not enough information or data at the outset to do more than guess at the requirement. There are also pragmatic considerations. The importance of well characterised user requirements is easy to demonstrate. Those observing programs that have clear user requirements, particularly when those requirements can be stated simply, have prospered in the developing Global Climate Observing System (GCOS). Examples are the Argo program of ocean profiling floats and the drifting buoy network for observing sea surface temperature (SST). The clear definition of user requirements, and in particular the point at which a particular component of the GCOS can be considered complete, has allowed funding agencies to target resources at these projects and to easily report back on the impact that their funding has had. Even more desirable is the ability to prove that the investment is reaping rewards, for example that the money spent on operational satellite programs can be demonstrated to have improved weather forecasting in a quantitative way.The assessment of observing system adequacy against user requirements is made easier when the contributing observing platforms sample regularly and predictably and the characteristics of the uncertainty in the components of the measurement system is known. Particularly difficult to assess are observing systems made up of a large number of observing platforms, where the characteristics of those observing platforms are variable and sometimes unknown, where details of the sampling is unpredictable, where the spatial and temporal characteristics of the observed field are poorly known and the signal to noise ratio is not particularly favourable. These are the characteristics of the marine surface meteorological observing system, currently made up of contributions from the JCOMM Voluntary Observing Ships (VOS) program managed by the Ship Observations Team (SOT, http://www.jcommops.org/sot/), a network of moored and drifting buoys co-ordinated by the Data Buoy Co-operation Panel (DBCP, http://www.dbcp.noaa.gov/) and satellite observations.This report will consider only the in situ component of the marine surface meteorological observing system. It should be remembered that the satellite observing system contributes substantially to observations of SST, winds, cloud and precipitation. All of the satellite-derived parameters require in situ ground truth for calibration, validation or bias correction. Surface air temperature, humidity and heat fluxes are examples of parameters which cannot be derived with usable accuracy from space-based platforms.<br/
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