Estimates 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 signif...
Sea Surface Temperature (SST) represents the marine component of surface global temperature, the ind...
ABSTRACT The differences between sea water temperature reported in the Log of Ship's Weather Ob...
International audienceLack of reliable observational metadata represents a key barrier to understand...
The random observational errors for meteorological variables within the Comprehensive Ocean–Atmosphe...
Random observational errors for sea surface temperature (SST) are estimated using merchant ship repo...
This paper considers the problem of the accuracy of Voluntary Observing Ship (VOS) wind and wave dat...
Rawinsonde data used for sounding-array budget computations have random errors, both instrumental er...
Observations of marine air temperature (MAT) by Voluntary Observing Ships (VOS) are known to contain...
Wind observations from voluntary Observing Ships (VOS) are either visual “Beaufort Scale ” estimates...
Short abstract Taking advantage of high resolution, reliable uncertainty estimates, and in situ dat...
This paper describes development and validation of a global climatology of basic wave parameters bas...
The in situ surface marine climate observing system includes contributions from several different ty...
Sampling patterns and sampling errors from various scatterometer datasets are examined. Four single ...
Sampling patterns and sampling errors from various scatterometer datasets are examined. Four single ...
A new approach to the analysis of systematic and random observation errors is presented in which the...
Sea Surface Temperature (SST) represents the marine component of surface global temperature, the ind...
ABSTRACT The differences between sea water temperature reported in the Log of Ship's Weather Ob...
International audienceLack of reliable observational metadata represents a key barrier to understand...
The random observational errors for meteorological variables within the Comprehensive Ocean–Atmosphe...
Random observational errors for sea surface temperature (SST) are estimated using merchant ship repo...
This paper considers the problem of the accuracy of Voluntary Observing Ship (VOS) wind and wave dat...
Rawinsonde data used for sounding-array budget computations have random errors, both instrumental er...
Observations of marine air temperature (MAT) by Voluntary Observing Ships (VOS) are known to contain...
Wind observations from voluntary Observing Ships (VOS) are either visual “Beaufort Scale ” estimates...
Short abstract Taking advantage of high resolution, reliable uncertainty estimates, and in situ dat...
This paper describes development and validation of a global climatology of basic wave parameters bas...
The in situ surface marine climate observing system includes contributions from several different ty...
Sampling patterns and sampling errors from various scatterometer datasets are examined. Four single ...
Sampling patterns and sampling errors from various scatterometer datasets are examined. Four single ...
A new approach to the analysis of systematic and random observation errors is presented in which the...
Sea Surface Temperature (SST) represents the marine component of surface global temperature, the ind...
ABSTRACT The differences between sea water temperature reported in the Log of Ship's Weather Ob...
International audienceLack of reliable observational metadata represents a key barrier to understand...