Factors Affecting Ship and Buoy Data Quality: A Data Assimilation Perspective

Abstract

Ship and buoy reports of wind, air pressure, temperature, humidity, and sea temperature for 2007 and 2008 have been compared with values from the operational Met Office global numerical weather prediction (NWP) system. Ship reports have been categorized by vessel type, recruiting country, and manual or automatic reporting. Most estimated ship winds (except Dutch ones) are too strong and are better treated as measured winds. After height adjustment, the average ship wind speeds are reasonably consistent with buoy wind speeds, but the global model winds are 6%-12% weaker. Extra care is needed when comparing/assimilating values close to the coast. Ship air temperatures are too warm during the afternoon due to solar heating of the ship. Adjustment of the pressure to sea level is a problem for some larger ships. Passenger ship reports are relatively poor quality for several variables and their winds are rather strong. Automated ship reports and those from research and coast guard vessels tend to be of good quality but some of the winds are slightly too weak. In most respects buoy data have the best quality. A number of improvements to the Met Office observation processing system are being made, notably tightening of the quality checks and better height adjustment of winds.

Comparison between satellite and in situ sea surface temperature data in the Western Mediterranean Sea

“…The sign of the bias cannot be explained in either case by the average depth at which these measurements are taken (Table 1), because ship data are the deepest (4 m depth in average) and drifter data are one of the shallowest (0.06 m depth in average). Our results agree with other works that account for a cold bias in drifter data respect to ship data (e.g., Emery et al 2001a;Ingleby 2010), and a warm bias in ship data (e.g., Kent et al 1993Kent et al , 2010, more specifically in engine room intake measurements. Given that the ship data set we are using consists mostly of engine room intake measurements (78.5%), the observed warm bias must be mostly due to this effect.…”

Assessing equatorial surface currents in the FOAM Global and Indian Ocean models against observations from the global tropical moored buoy array

“…In 2007-2008 the short-range Numerical Weather Prediction wind speed was about 10% too weak (ie, not westward enough) compared to tropical moored buoy observations. 27 The Eastern Pacific thermocline is also too deep (ie, the east-west thermocline slope is less than observed) in the non-assimilative V0 run compared to the assimilative V0 run (not shown), which is also consistent with a too weak westward equatorial wind stress. The westward surface current error is evident in the assimilative run which assimilates a high volume of temperature and salinity profiles from the moored buoy array and therefore might be expected to have a reasonably accurate representation of the near equatorial density structure (and associated density driven flows).…”

Evolution and Accuracy of Surface Humidity Reports*

“…Preliminary results from monitoring in the Met Office global NWP system suggest that the fit of aircraft humidity to shortrange forecasts is broadly similar to that of radiosonde humidity, with the fit being slightly better for AMDAR than TAMDAR data. Ingleby (2010) discusses the availability of marine humidity reports and their performance relative to shortrange forecasts: the comparison is worse in daylight than at night and buoy reports appear somewhat better than ship reports.…”

“…On the whole, these studies did not look at biases; however, Simmons et al (2010) noted dry biases in low-level humidity from some types of radiosonde, especially around the 1990s. In the Met Office NWP system, surface humidity is assimilated in both regional and global models (Ingleby et al 2013) and also used to update soil moisture (Dharssi et al 2011). In NWP high relative humidity (RH) conditions are particularly important, as they are linked to poor visibility [in the regional U.K. forecasting system, visibility reports can have a significant effect on the humidity analysis; see Clark et al (2008)].…”