Operational Sea Surface Temperature And Sea Ice Analysis Research Articles

The Effect of Variable Sea Surface Temperature on Forecasting Sea Fog and Sea Breezes: A Case Study

AbstractA preliminary study of the effect of sea surface temperature (SST) temporal and spatial variability on regional coastal weather forecasts is described. A high-resolution numerical weather forecast model from the Met Office is run for the U.K. region with hourly updates of SST data obtained from a shelf sea model. When compared with a control run in which SST is maintained with Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data, it is found that there are significant differences in the coastal-region forecasts for sea breezes and fog formation. The control run underestimates surface temperature and the strength of the sea breeze when compared with the run with hourly SST updates.

Daily, Global, High-Resolution SST and Sea Ice Reanalysis for 1985–2007 Using the OSTIA System

Abstract A sea surface temperature (SST) and sea ice reanalysis has been produced at the Met Office based on the Operational SST and Sea Ice Analysis (OSTIA) system. The OSTIA reanalysis produces daily, high-resolution, global foundation SST and sea ice concentration fields from 1 January 1985 to 31 December 2007. The SST reanalysis uses reprocessed satellite and in situ observations that are assimilated using a multiscale optimal-interpolation-type scheme similar to that used in the near-real-time OSTIA system. Validation of the SST analysis using assimilated in situ observation-minus-background statistics shows that the accuracy of the analysis increases throughout the reanalysis period; the global root-mean-square difference is approximately 0.50 K by 2007. This approach to validation is supported in the recent period by results from comparisons with independent near-surface Argo data against which a global standard deviation error of 0.55 K was calculated. Assessment of the OSTIA reanalysis at high latitudes demonstrates that the SST and sea ice fields are more consistent with one another in the Southern Hemisphere than in the Northern Hemisphere. Comparison of the sea ice extents to those in a similar reanalysis shows OSTIA to have larger extents in the Northern Hemisphere, and the Southern Hemisphere extents are similar. The OSTIA reanalysis SSTs are shown to be regionally comparable with similar reanalyses, with the largest differences occurring at high latitudes in the summer hemisphere. Differences are observed around the ice edge and in regions with high SST gradients. The OSTIA reanalysis provides a valuable high-resolution addition to the satellite period SST data record that makes use of the (Advanced) Along-Track Scanning Radiometer [(A)ATSR] multimission data.

The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system

This paper describes a new Sea surface temperature (SST) analysis that is produced with global coverage on a daily basis at the Met Office called the Operational SST and Sea Ice Analysis (OSTIA) system. OSTIA uses satellite SST data provided by international agencies via the Group for High Resolution SST (GHRSST) Regional/Global Task Sharing (R/GTS) framework. GHRSST products include data from microwave and infrared satellite instruments with accompanying uncertainty estimates. The system also uses in situ SST data available over the Global Telecommunications System (GTS) and a sea-ice concentration product from the EUMETSAT Ocean and Sea Ice Satellite Applications Facility (OSI-SAF). The SST analysis is a multi-scale optimal interpolation that is designed for applications in numerical weather prediction and ocean forecasting systems. The background error covariance matrix is specified using ocean model data and the analysis uses correlation length scales of 10km and 100km. The OSTIA system produces a foundation SST estimate (SSTfnd, which is the SST free of diurnal variability) at an output grid resolution of 1/20° (~6km) although the smallest analysis feature resolution is based on the correlation length scale of 10km. All satellite SST data are adjusted for bias errors based on a combination of ENVISAT Advanced Along Track Scanning Radiometer (AATSR) SST data and in situ SST measurements from drifting buoys. Data are filtered (based on surface wind speed data) to remove diurnal variability and AATSR data are adjusted to represent the SST at the same depth as drifting buoy measurements (0.2–1m) before bias adjustments are made. Global coverage outputs are provided each day in GHRSST L4 netCDF format. A variety of secondary products are also provided including weekly and monthly mean data sets. OSTIA products are continuously monitored and validation/verification activities demonstrate that SST products have zero mean bias and an accuracy of ~0.57K compared to in situ measurements. OSTIA is now used operationally as a boundary condition for all weather forecast models at the Met Office and at European Centre for Medium-range Weather Forecasting (ECMWF). OSTIA is produced by the Met Office as part of the European Union Global Monitoring for Environment and Security (GMES) MyOcean project.

Impacts of the High-Resolution Sea Surface Temperature Distribution on Modeled Snowfall Formation over the Yellow Sea during a Cold-Air Outbreak

Abstract High-resolution sea surface temperature (SST) products and idealized SST distributions were used to simulate snowfall over the Yellow Sea during 30–31 December 2007 using the Weather Research and Forecasting Model (WRF). Large differences were found between the SST distributions in the New Generation Sea Surface Temperature (NGSST) and Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) datasets near the Yellow Sea coast. Idealized SST datasets were defined to examine the influence of this difference in detail. The SST differences influenced the cloud streets and resultant snowfall formation. In simulations with the idealized SST distributions, convection developed and intensified later when the SST gradient was increased. In addition, the intensity of cloud streets was enhanced along the center of the flow. The simulations using the NGSST dataset showed widely distributed cloud streets and snowfall and heavier snowfall over the western Korean Peninsula, while those using the OSTIA dataset showed a concentrated distribution of cloud streets and snowfall along the center of airflow and more intense snowfall over North Jeolla Province, Korea, than in other regions. Comparing real SST products with observations qualitatively and quantitatively, OSTIA is found to have simulated the distribution and intensity of snowfall better than NGSST.

Impact of the high-resolution sea surface temperature distribution on modeled snowfall formation over the Yellow Sea during a cold air outbreak

High-resolution sea surface temperature (SST) products and idealized SST distributions were used to simulate snowfall over the Yellow Sea during 30–31 December 2007 using the Weather Research and Forecasting Model (WRF). Large differences were found between the SST distributions in the New Generation Sea Surface Temperature (NGSST) and Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) datasets near the Yellow Sea coast. Idealized SST datasets were defined to examine the influence of this difference in detail. The SST differences influenced the cloud streets and resultant snowfall formation. In simulations with the idealized SST distributions, convection developed and intensified later when the SST gradient was increased. In addition, the intensity of cloud streets was enhanced along the center of the flow. The simulations using the NGSST dataset showed widely distributed cloud streets and snowfall and heavier snowfall over the western Korean Peninsula, while those using the OSTIA dataset showed a concentrated distribution of cloud streets and snowfall along the center of airflow and more intense snowfall over North Jeolla Province, Korea, than in other regions. Comparing real SST products with observations qualitatively and quantitatively, OSTIA is found to have simulated the distribution and intensity of snowfall better than NGSST.

The SST Quality Monitor (SQUAM)

Abstract The National Environmental Satellite, Data, and Information Service (NESDIS) has been operationally generating sea surface temperature (SST) products (TS) from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA and MetOp-A satellites since the early 1980s. Customarily, TS are validated against in situ SSTs. However, in situ data are sparse and are not available globally in near–real time (NRT). This study describes a complementary SST Quality Monitor (SQUAM), which employs global level 4 (L4) SST fields as a reference standard (TR) and performs statistical analyses of the differences ΔTS = TS − TR. The results are posted online in NRT. The TS data that are analyzed are the heritage National Environmental Satellite, Data, and Information Service (NESDIS) SST products from NOAA-16, -17, -18, and -19 and MetOp-A from 2001 to the present. The TR fields include daily Reynolds, real-time global (RTG), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Ocean Data Analysis System for Marine Environment and Security for the European Area (MERSEA) (ODYSSEA) analyses. Using multiple fields facilitates the distinguishing of artifacts in satellite SSTs from those in the L4 products. Global distributions of ΔTS are mapped and their histograms are analyzed for proximity to Gaussian shape. Outliers are handled using robust statistics, and the Gaussian parameters are trended in time to monitor SST products for stability and consistency. Additional TS checks are performed to identify retrieval artifacts by plotting ΔTS versus observational parameters. Cross-platform TS biases are evaluated using double differences, and cross-L4 TR differences are assessed using Hovmöller diagrams. SQUAM results compare well with the customary in situ validation. All satellite products show a high degree of self- and cross-platform consistency, except for NOAA-16, which has flown close to the terminator in recent years and whose AVHRR is unstable.

고해상도 해수면온도자료가 한반도 남동해안 풍력자원 수치모의에 미치는 영향

Accurate simulation of the meteorological field is very important to assess the wind resources. Some researchers showed that sea surface temperature (SST) plays a leading role on the local meterological simulation. New Generation Sea Surface Temperature (NGSST), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Real-Time Global Sea Surface Temperature (RTG SST) have different spatial distribution near the coast and OSTIA shows the best accuracy compared with buoy data in the southeastern coast of the Korean Peninsula. Those SST products are used to initialize the Weather Research and Forecasting (WRF) Model for November 13-23 2008. The simulation of OSTIA shows better result in comparison with NGSST and RTG SST. NGSST shows a large difference with OSTIA in horizontal and vertical wind fields during the weak synoptic condition, but wind power density shows a large difference during strong synoptic condition. RTG SST shows the similar patterns but smaller the magnitude and the extent.

An easterly tip jet off Cape Farewell, Greenland. II: Simulations and dynamics

AbstractAn easterly tip jet that occurred on 21 February 2007 off Cape Farewell, Greenland, is examined. In Part I of this article aircraft observations were described. Now, in Part II, numerical simulations and an analysis of the dynamical forcing mechanisms are presented. The simulations make use of a limited‐area 12 km resolution configuration of the Met Office's Unified Model. Sea‐surface temperatures and sea‐ice concentrations have been replaced using the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) product, addressing a boundary‐layer temperature bias, while roughness lengths over sea ice have been updated, addressing a wind‐speed bias. These modifications ensured a reasonably accurate simulation: generally within 1–2 K and 2–3 m s−1 when compared with dropsonde observations. A momentum‐budget analysis along a curved locus through the core of the jet has been derived. Off southeast Greenland, the easterly tip jet was in cross‐jet geostrophic balance, but was being accelerated downstream by an along‐jet pressure gradient. Over the curved part of the locus, as the jet rounded Cape Farewell, a cross‐jet residual suggests that the jet was unbalanced at the height of the jet core. This residual decreases with height so that an approximate gradient wind balance applies in the upper part of the jet. The anticyclonic curvature, characteristic of easterly tip jets, was caused by a dramatic decrease in the cross‐jet pressure‐gradient force at the end of the barrier, after which the jet aligned with the synoptic‐scale isobars and returned to approximate geostrophic balance. The momentum budget is shown to be robust and applicable to other cases. Copyright © 2009 Royal Meteorological Society