The ocean surface wind mediates exchanges between the ocean and the atmosphere. These air–sea exchange processes are critical for understanding and predicting atmosphere, ocean, and wave phenomena on many time and space scales. A cross-calibrated multiplatform (CCMP) long-term data record of satellite ocean surface winds is available from 1987 to 2008 with planned extensions through 2012. A variational analysis method (VAM) is used to combine surface wind data derived from conventional and in situ sources and multiple satellites into a consistent nearglobal analysis at 25-km resolution, every 6 h. The input data are cross-calibrated wind speeds derived from the Special Sensor Microwave Imager (SSM/I; F08–F15), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and wind vectors from SeaWinds on the NASA Quick Scatterometer (QuikSCAT) and on the second Japanese Advanced Earth Observing Satellite (ADEOS-... Abstract The ocean surface wind mediates exchanges between the ocean and the atmosphere. These air–sea exchange processes are critical for understanding and predicting atmosphere, ocean, and wave phenomena on many time and space scales. A cross-calibrated multiplatform (CCMP) long-term data record of satellite ocean surface winds is available from 1987 to 2008 with planned extensions through 2012. A variational analysis method (VAM) is used to combine surface wind data derived from conventional and in situ sources and multiple satellites into a consistent nearglobal analysis at 25-km resolution, every 6 h. The input data are cross-calibrated wind speeds derived from the Special Sensor Microwave Imager (SSM/I; F08–F15), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and wind vectors from SeaWinds on the NASA Quick Scatterometer (QuikSCAT) and on the second Japanese Advanced Earth Observing Satellite (ADEOS-...

The Special Sensor Microwave Imagers (SSM/I) aboard three DMSP satellites have provided a large dataset of surface wind speeds over the global oceans from July 1987 to the present. These data are characterized by high resolution, coverage, and accuracy, but their application has been limited by the lack of directional information. In an effort to extend the applicability of these data, methodology has been developed to assign directions to the SSM/I wind speeds and to produce analyses using these data. Following extensive testing, this methodology has been used to generate a seven and one-half year dataset (from July 1987 through December 1994) of global SSM/I wind vectors. These data are currently being used in a variety of atmospheric and oceanic applications and are available to interested investigators. Recent results presented in this paper show the accuracy of the SSM/I wind velocities, the ability of these data to improve surface wind analyses, and the propagation of a synoptic-scale conve... Abstract The Special Sensor Microwave Imagers (SSM/I) aboard three DMSP satellites have provided a large dataset of surface wind speeds over the global oceans from July 1987 to the present. These data are characterized by high resolution, coverage, and accuracy, but their application has been limited by the lack of directional information. In an effort to extend the applicability of these data, methodology has been developed to assign directions to the SSM/I wind speeds and to produce analyses using these data. Following extensive testing, this methodology has been used to generate a seven and one-half year dataset (from July 1987 through December 1994) of global SSM/I wind vectors. These data are currently being used in a variety of atmospheric and oceanic applications and are available to interested investigators. Recent results presented in this paper show the accuracy of the SSM/I wind velocities, the ability of these data to improve surface wind analyses, and the propagation of a synoptic-scale conve...

Polar regions have great sensitivity to climate forcing; however, understanding of the physical processes coupling the atmosphere and ocean in these regions is relatively poor. Improving our knowledge of high-latitude surface fluxes will require close collaboration among meteorologists, oceanographers, ice physicists, and climatologists, and between observationalists and modelers, as well as new combinations of in situ measurements and satellite remote sensing. This article describes the deficiencies in our current state of knowledge about air–sea surface fluxes in high latitudes, the sensitivity of various high-latitude processes to changes in surface fluxes, and the scientific requirements for surface fluxes at high latitudes. We inventory the reasons, both logistical and physical, why existing flux products do not meet these requirements. Capturing an annual cycle in fluxes requires that instruments function through long periods of cold polar darkness, often far from support services, in situations sub... Polar regions have great sensitivity to climate forcing; however, understanding of the physical processes coupling the atmosphere and ocean in these regions is relatively poor. Improving our knowledge of high-latitude surface fluxes will require close collaboration among meteorologists, oceanographers, ice physicists, and climatologists, and between observationalists and modelers, as well as new combinations of in situ measurements and satellite remote sensing. This article describes the deficiencies in our current state of knowledge about air–sea surface fluxes in high latitudes, the sensitivity of various high-latitude processes to changes in surface fluxes, and the scientific requirements for surface fluxes at high latitudes. We inventory the reasons, both logistical and physical, why existing flux products do not meet these requirements. Capturing an annual cycle in fluxes requires that instruments function through long periods of cold polar darkness, often far from support services, in situations sub...

As operational forecast and data assimilation (DA) systems evolve, observing system simulation experiment (OSSE) systems must evolve in parallel. Expected development of operational systems—especially the use of data that are currently not used or are just beginning to be used, such as all-sky and surface-affected microwave radiances—will greatly challenge our ability to construct realistic OSSE systems. An additional set of challenges will arise when future DA systems strongly couple the different Earth system components. In response, future OSSE systems will require coupled models to simulate nature and coupled observation simulators. The requirements for future evolving OSSE systems and potential solutions to satisfy these requirements are discussed. It is anticipated that in the future the OSSE technique will be applied to diverse and coupled domains with the use of increasingly advanced and sophisticated simulations of nature and observations.