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Abstract
The impact of the number of satellite altimeters providing sea surface height anomaly (SSHA) information for a data assimilation system is evaluated using two comparison frameworks and two statistical methodologies. The Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) dynamically interpolates satellite SSHA track data measured from space to produce high-resolution (eddy resolving) fields. The Modular Ocean Data Assimilation System (MODAS) uses the NLOM SSHA to produce synthetic three-dimensional fields of temperature and salinity over the global ocean. A series of case studies is defined where NLOM assimilates different combinations of data streams from zero to three altimeters. The resulting NLOM SSHA fields and the MODAS synthetic profiles are evaluated relative to independently observed ocean temperature and salinity profiles for the years 2001–03. The NLOM SSHA values are compared with the difference of the observed dynamic height from the climatological dynamic height. The synthetics are compared with observations using a measure of thermocline depth. Comparisons are done point for point and for 1° radius regions that are linearly fit over 2-month periods. To evaluate the impact of data outliers, statistical evaluations are done with traditional Gaussian statistics and also with robust nonparametric statistics. Significant error reduction is obtained, particularly in high SSHA variability regions, by including at least one altimeter. Given the limitation of these methods, the overall differences between one and three altimeters are significant only in bias. Data outliers increase Gaussian statistical error and error uncertainty compared to the same computations using nonparametric statistical methods.
Abstract
The impact of the number of satellite altimeters providing sea surface height anomaly (SSHA) information for a data assimilation system is evaluated using two comparison frameworks and two statistical methodologies. The Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) dynamically interpolates satellite SSHA track data measured from space to produce high-resolution (eddy resolving) fields. The Modular Ocean Data Assimilation System (MODAS) uses the NLOM SSHA to produce synthetic three-dimensional fields of temperature and salinity over the global ocean. A series of case studies is defined where NLOM assimilates different combinations of data streams from zero to three altimeters. The resulting NLOM SSHA fields and the MODAS synthetic profiles are evaluated relative to independently observed ocean temperature and salinity profiles for the years 2001–03. The NLOM SSHA values are compared with the difference of the observed dynamic height from the climatological dynamic height. The synthetics are compared with observations using a measure of thermocline depth. Comparisons are done point for point and for 1° radius regions that are linearly fit over 2-month periods. To evaluate the impact of data outliers, statistical evaluations are done with traditional Gaussian statistics and also with robust nonparametric statistics. Significant error reduction is obtained, particularly in high SSHA variability regions, by including at least one altimeter. Given the limitation of these methods, the overall differences between one and three altimeters are significant only in bias. Data outliers increase Gaussian statistical error and error uncertainty compared to the same computations using nonparametric statistical methods.
To support climate research, the World Climate Research Programme (WCRP) initiated a new radiometric network, the Baseline Surface Radiation Network (BSRN). The network aims at providing validation material for satellite radiometry and climate models. It further aims at detecting long-term variations in irradiances at the earth's surface, which are believed to play an important role in climate change. The network and its instrumentation are designed 1) to cover major climate zones, 2) to provide the accuracy required to meet the objectives, and 3) to ensure homogenized standards for a long period in the future. The limits of the accuracy are defined to reach these goals. The suitable instruments and instrumentations have been determined and the methods for observations and data management have been agreed on at all stations. Measurements of irradiances are at 1 Hz, and the 1-min statistics (mean, standard deviation, and extreme values) with quality flags are stored at a centralized data archive at the WCRP's World Radiation Monitoring Center (WRMC) in Zurich, Switzerland. The data are quality controlled both at stations and at the WRMC. The original 1-min irradiance statistics will be stored at the WRMC for 10 years, while hourly mean values will be transferred to the World Radiation Data Center in St. Petersburg, Russia. The BSRN, consisting of 15 stations, covers the earth's surface from 80°N to 90°S, and will soon be joined by seven more stations. The data are available to scientific communities in various ways depending on the communication environment of the users. The present article discusses the scientific base, organizational and technical aspects of the network, and data retrieval methods; shows various application possibilities; and presents the future tasks to be accomplished.
To support climate research, the World Climate Research Programme (WCRP) initiated a new radiometric network, the Baseline Surface Radiation Network (BSRN). The network aims at providing validation material for satellite radiometry and climate models. It further aims at detecting long-term variations in irradiances at the earth's surface, which are believed to play an important role in climate change. The network and its instrumentation are designed 1) to cover major climate zones, 2) to provide the accuracy required to meet the objectives, and 3) to ensure homogenized standards for a long period in the future. The limits of the accuracy are defined to reach these goals. The suitable instruments and instrumentations have been determined and the methods for observations and data management have been agreed on at all stations. Measurements of irradiances are at 1 Hz, and the 1-min statistics (mean, standard deviation, and extreme values) with quality flags are stored at a centralized data archive at the WCRP's World Radiation Monitoring Center (WRMC) in Zurich, Switzerland. The data are quality controlled both at stations and at the WRMC. The original 1-min irradiance statistics will be stored at the WRMC for 10 years, while hourly mean values will be transferred to the World Radiation Data Center in St. Petersburg, Russia. The BSRN, consisting of 15 stations, covers the earth's surface from 80°N to 90°S, and will soon be joined by seven more stations. The data are available to scientific communities in various ways depending on the communication environment of the users. The present article discusses the scientific base, organizational and technical aspects of the network, and data retrieval methods; shows various application possibilities; and presents the future tasks to be accomplished.
Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.
Constellations of driftsonde systems— gondolas floating in the stratosphere and able to release dropsondes upon command— have so far been used in three major field experiments from 2006 through 2010. With them, high-quality, high-resolution, in situ atmospheric profiles were made over extended periods in regions that are otherwise very difficult to observe. The measurements have unique value for verifying and evaluating numerical weather prediction models and global data assimilation systems; they can be a valuable resource to validate data from remote sensing instruments, especially on satellites, but also airborne or ground-based remote sensors. These applications for models and remote sensors result in a powerful combination for improving data assimilation systems. Driftsondes also can support process studies in otherwise difficult locations—for example, to study factors that control the development or decay of a tropical disturbance, or to investigate the lower boundary layer over the interior Antarctic continent. The driftsonde system is now a mature and robust observing system that can be combined with flight-level data to conduct multidisciplinary research at heights well above that reached by current research aircraft. In this article we describe the development and capabilities of the driftsonde system, the exemplary science resulting from its use to date, and some future applications.
