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Observing and Monitoring the Climate System
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Updated 1 December 2007
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Observing and Monitoring the Climate System |
Observing and Monitoring the Climate SystemRecent Accomplishments
Additional Past Accomplishments:
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The following are selected highlights of observations and monitoring activities supported by CCSP participating agencies, as reported in the fiscal year 2008 edition of the annual report, Our Changing Planet. The principal focus is on describing progress in implementing the observations that contribute to the CCSP mission. As a result, the chapter touches on some observing systems that are crucial to CCSP but are not included within the CCSP budget because they primarily serve other purposes. Selected highlights of observation and monitoring activities supported by CCSP- participating agencies follow. The principal focus of this chapter is on describing progress in implementing the observations that contribute to the CCSP mission. As a result, the chapter touches on some observing systems that are crucial to CCSP but are not included within the CCSP budget because they primarily serve other purposes. Observations and MonitoringTropical Moored Buoy Network Extended into the Indian Ocean. Working in close collaboration with Indian Ocean and Asian partners, a series of moored buoys have been deployed in the Indian Ocean for measurement of a comprehensive suite of
ocean-atmosphere climate variables. This westward extension of the equatorial Pacific Tropical Atmosphere Ocean/Triangle Trans-Ocean (TAO) array, whose long-term data have revolutionized understanding of the evolution of El Niño, is necessary to understand changes in Indian Ocean sea surface temperatures, which have recently been shown to influence regional climate variability and change (including prolonged drought in the mid-latitudes, including the United States). Since 2005, eight new TAO buoys were installed in the Indian Ocean in collaboration with partners from India, Indonesia, and France. Plans call for a total of 39 TAO buoys in the Indian Ocean by 2013.
Global Coverage Achieved by the Argo Profiling Array.Argo profiling floats, measuring upper ocean temperature and salinity, have now been deployed in all oceans. The United States operates approximately half of the global array in cooperation with 22 countries operating the other half. The floats drift at depth and periodically rise to the sea surface, collecting data along the way, and report their observations in real-time via satellite communications. This global data set is used together with complementary data from satellites and other in situ systems to document ocean heat content and global sea-level change.Satellite Observations of Atmosphere, Land, and Oceans. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been operating successfully on NASA's Earth Observing System (EOS) Terra mission for over 6 years and on the Aqua mission for over 4 years. The MODIS instruments have provided daily global observations of atmospheric, land, and ocean features with unprecedented detail, due to the 250- to 1,000-m spatial resolution coupled with multi-spectral capability in 36 carefully selected spectral bands extending from the visible to the thermal infrared portions of the electromagnetic spectrum. Observing the atmosphere, MODIS has produced advanced, detailed observations of the global and regional extent of aerosols from natural and anthropogenic activity. Analysis not only produces accurate
determinations of the extent of cloudiness–including that associated with thin, wispy cirrus–that profoundly affects Earth's radiation
balance, but also cloud properties such as cloud phase (water or ice), optical depth (i.e., cloud thickness), and effective droplet radius. The MODIS instruments are also providing more detailed observations of land features such as surface reflectance (albedo), surface temperature, snow and ice cover, and the variability of vegetation type and vigor associated with seasonal and climatic (e.g., above and below average moisture) variability. The capability of MODIS to classify vegetation types and the photosynthetic activity of vegetation over the land as well as in the surface waters of the world's oceans (i.e., phytoplankton) is leading to more accurate evaluation of spatial and seasonal changes in the global net productivity of Earth's biosphere. The capability of MODIS to observe global processes and trends is leading to better understanding of natural and anthropogenic effects on the Earth-atmosphere system, and to better performance of general circulation models (GCMs). An example of the latter is the use of atmospheric winds derived from MODIS observations over the polar regions of the globe. These observations have been shown to improve the global predictive skill of several GCMs, both in the polar regions that are undergoing rapid change, and in the mid-latitudes.
Climate Sensitivity, Cloud Feedback, and Global Albedo.1,2 Recent analyses of state-of-the-art climate model simulations show that uncertainties in cloud feedback continue to dominate uncertainties in climate sensitivity. These studies have also shown that cloud feedback is linearly proportional to changes in cloud radiative forcing, and that low cloudiness appears to dominate the cloud feedback uncertainty. The combination of studies suggests that changes in Earth's albedo through changing low-altitude cloudiness are one of the most critical observations. Analysis of global albedo using broadband satellite observations made from the Clouds and the Earth's Radiant Energy System (CERES) instrument showed that the interannual variations in global albedo are dominated by changes in the tropics. Examination of the year-to-year variability of tropical and global cloud properties observed by CERES and MODIS identified the need for a highly accurate satellite data set of 20 years or more to achieve a sufficient signal-to-noise ratio to estimate decadal changes in cloud radiative forcing representative of cloud feedback in the climate system. These studies have highlighted the increased capability of simultaneous measurements of a wide range of climate variables to allow the clarification of key relationships in major portions of the climate system.
QuikSCAT. 3,4 The SeaWinds instrument aboard the Quick Scatterometer (QuikSCAT) satellite has measured the speed and direction of wind over the surface of the oceans since 1999. Although launched as an experimental instrument, it has been assimilated pre-operationally into atmospheric weather prediction models (NOAA's National Centers for Environmental Prediction, the European Centre for Medium-Range Weather Forecasts, and others) for the past 2 years. It is providing new insights on air-sea exchanges. Furthermore, the underlying radar backscatter data have been applied to climate change research concerning terrestrial high latitudes through studies of ice layer formation.
Clues to Variability in Arctic Minimum Sea Ice Extent.5 Polar systems are especially
sensitive to changing conditions and provide early indications of climate change. Perennial sea ice is a primary indicator of Arctic climate change. From 1979 to 2007, it decreased in extent by about 40%. Analysis of new satellite-derived fields of winds, radiative forcing, and transported heat energy reveals distinct regional differences in the relative roles of these parameters in explaining variability in the position of the northernmost ice edge. In all six peripheral seas studied, downwelling longwave
radiation flux anomalies explain the most variability–approximately 40%–while northward wind anomalies are important in areas north of Siberia, particularly earlier in the melt season. Anomalies in the amount of solar energy absorbed by the surface are negatively correlated with perennial ice retreat in all regions, suggesting that the effect of solar flux anomalies is overwhelmed by the long-wave influence on ice edge position. This work has taken on new urgency with the 2007 Arctic sea ice minimum extent being the lowest in the 1978 to 2007 satellite record.
ICESat.6The Ice, Cloud, and Land Elevation Satellite (ICESat), launched in 2003, has made significant contributions to CCSP's polar observations. The lidar instrument on ICESat measures surface elevations of ice and land, vertical distributions of clouds and aerosols, vegetation canopy heights, and other features with unprecedented accuracy and sensitivity. The primary purpose of ICESat has been to acquire time series of ice sheet elevation changes for determination of the present-day mass balance of the ice sheets, study of associations between observed ice changes and polar climate, and improvement of estimates of the present and future contributions to global sea-level rise. ICESat has achieved remarkable successes with first-of-their-kind observations:
Solar Variability: SORCE Mission.7 The Sun is the Earth's primary energy source and external driver of climate variability. The Solar Radiation and Climate Experiment (SORCE) satellite, launched in 2003, is equipped with four instruments that measure variations in solar radiation much more accurately than previous instruments. SORCE is now making the first contiguous observations of solar variability across the full solar spectrum, from far ultraviolet to near-infrared wavelengths. SORCE's operational life extends across the 2006-2007 solar
minimum, a crucial period for estimating any long-term trend, such as that indicated by indirect measurements of past solar forcing. The mission is expected to overlap with the Glory mission that will carry forward the total solar irradiance record after 2008. The continued measurements previously planned by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) through the Total Solar Irradiance Sensor (including a Total Solar Irradiance Monitor and Spectral Irradiance Monitor) were deleted from the NPOESS program during the Nunn-McCurdy
recertification process completed in June 2006. Agencies are currently assessing the impacts of this decision for solar irradiance monitoring.
High-Resolution Vertical Profiles of Atmospheric Temperature and Moisture.8The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) relies on radio occultation of signals from the Global Positioning System satellites. COSMIC satellites take 2,500 vertical profile measurements every 24 hours in a nearly uniform distribution around the globe, filling in current data gaps over vast stretches of the oceans. The data's high vertical resolution complements the high horizontal resolution of other conventional weather satellite measurements. This is the first time that the technique of radio occultation has been used on a global scale and in real- time to provide continuous monitoring of worldwide atmospheric conditions. COSMIC builds on a series of previous research-oriented satellites, which were used to develop the measurement technique and establish the usefulness of the data in operational forecast systems. The remarkable stability, consistency, and accuracy of the measurements are a new precision tool to help scientists in quantifying long-term climate change trends. COSMIC was successfully launched on 14 April 2006, and its constellation of six small satellites will be transmitting atmospheric data to Earth for the next 5 or more years.
Observing Earth's Mass Distribution Changes from Space.9 The Gravity Recovery and Climate Experiment (GRACE) is a two-spacecraft mission, developed under a
partnership between NASA and the German Aerospace Center. After five successful years of mission operation, significant multidisciplinary results using GRACE
observations have been reported. The unprecedented accuracy of the measurements provides the opportunity to observe time variability in the Earth's gravity field due to changes in mass distribution. The month-to-month gravity variations obtained from GRACE provide information about changes in the distribution of mass within the Earth and at its surface. The largest time-variable gravity signals are the result of changes in the distribution of water and snow stored on land. Analyses of these time variable gravity fields provide global observations of changes in total water storage (vertically integrated water content), averaged over scales of a few hundred kilometers and greater. Usefully accurate surface water storage estimates from GRACE allow quantitative comparisons to be made on seasonal and longer time scales. A recent study compared GRACE surface water storage estimates to the outputs of five models. All of the models reproduce the global annual pattern of storage amplitude and the seasonal cycle. However, global average agreements were found to mask systematic model biases at low latitudes. Identifying these errors in the models will allow improved parameterization of water stores in the land models and alleviate precipitation biases. Both processes are difficult to formulate and the satellite data will greatly aid in improving the veracity of the models.
Surface-Based Observatories of Clouds and Radiation. 10,11The primary goal of the Atmospheric Radiation Measurement (ARM) program is to improve the treatment of cloud and radiation physics in global climate models in order to improve the climate simulation capabilities of these models. These efforts have been enhanced by the addition of the ARM mobile facility (AMF) to study cloud and radiation processes in multiple climatic regimes. The AMF can be deployed to sites around the world for durations of 6 to 18 months. Data streams produced by the AMF will be available to the atmospheric community for use in testing and improving parameterizations in global climate models. The AMF was deployed in Niamey, Niger from January through December 2006 and measured radiation, cloud, and aerosol properties during the monsoon and dry seasons. Using measurements from the ARM Mixed-Phase Arctic Cloud Experiment (M-PACE), a data set has been created that allows climate and cloud models to simulate Arctic weather allowing for direct comparison of observations and model simulations.
Baseline Surface Radiation Network.The Baseline Surface Radiation Network has acquired 15 years of surface radiation budget data at its original half-dozen sites and has since expanded to more than 38 international sites. These observations combined with historic records have detected interdecadal annual mean variations on the order of about 2%, which exceeds previous expected variations that are not replicated in climate models. Contributing effects from clouds and aerosols are suspected to be the most likely cause of these variations.Data Management and InformationSelected data management and information activities supported by CCSP-participating agencies follow.REASoN Program.12 Forty Cooperative Agreement projects that are part of NASA's Earth Science Research, Education, and Applications Solutions Network (REASoN ) have completed their first year. The REASoN projects are part of NASA's strategy to work with its partners to improve its existing data systems, guide the development and management of future data systems, and focus performance outcomes to further Earth science research objectives. In order to achieve these goals, the REASoN
projects are organized to engage the science community and peer review process in the development of higher level science products; to use these products to advance Earth system research; to develop and demonstrate new technologies for data
management and distribution; and to contribute to interagency efforts to improve the maintenance and accessibility of data and information systems.
Global Change Master Directory.13The Global Change Master Directory (GCMD) is an extensive directory of descriptive and spatial information about data sets relevant to global change research. The GCMD provides a comprehensive resource where a researcher, student, or interested individual can access sources of Earth science data and related tools and services. At present the GCMD database contains over 18,200 metadata descriptions of data sets from approximately 2,800 government agencies, research institutions, archives, and universities worldwide; updates are made at the rate of 900 descriptions per month. GCMD contains descriptions of data sets covering all disciplines that produce and use data to help understand our changing planet. Although much research is focused on climate change, the GCMD includes metadata from disciplines including atmospheric science, oceanography, ecology, geology, hydrology, and human dimensions of climate change. This interdisciplinary approach is aimed at researchers exploring the interconnections and interrelations of multidisciplinary global change variables (e.g., how climate change may affect human health). The GCMD has made it easier for such data users to locate the information desired. The latest version of the GCMD software was released in May 2007 as MD9.7. Software upgrades are made in response to user needs and to capitalize on new technology. A portal has been created in support of the Global Earth Observation System of Systems (GEOSS). Additional Past Accomplishments:References1) Bony, S. and J.L. Dufresne, 2005: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophysical Research Letters, 32, L20806, doi:10.1029/2005GL023851.2) Soden, B.J. and I.M. Held, 2006: An assessment of climate feedbacks in coupled ocean-atmosphere models. Journal of Climate, 19, 3354-3360. 3) Chelton, D.B., M.G. Schlax, M.H. Freilich, and R.F. Milliff, 2004: Satellite measurements reveal persistent small-scale features in ocean winds. Science, 303, 978-983. 4) Nghiem, S.V., K. Steffen, G. Neumann, and R. Huff, 2005: Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet. Journal of Geophysical Research, 110, F02017, doi:10.1029/2004JF000234. 5) Parkinson, C.L. and D.J. Cavalieri, 2007: Arctic sea ice extents, areas, and trends, 1979-2006. Journal of Geophysical Research – Oceans (accepted). 6) See icesat.gsfc.nasa.gov. 7) See lasp.colorado.edu/sorce. 8) See cosmic.ucar.edu/about.html. 9) Swenson, S.C. and P.C.D. Milly, 2006: Climate model biases in seasonality of continental water storage revealed by satellite gravimetry. Water Resources Research, 42, W03201, doi:10.1029/2005WR004628. 10) See www.arm.gov/sites/amf.stm. 11) Xie, S., S.A. Klein, M. Zhang, J.J. Yio, R.T. Cederwall, and R. McCoy, 2006: Developing large-scale forcing data for single-column models and cloud-resolving models from the Mixed-Phase Arctic Cloud Experiment. Journal of Geophysical Research, 111, D19104, doi:10.1029/2005JD006950. 12) A list of ongoing activities under this program is available at web. 13) See globalchange.nasa.gov or gcmd.nasa.gov. 14) See glory.giss.nasa.gov. 15) Hansen, J., L. Nazarenko, R. Ruedy, M. Sato, J. Wiollis, A. Del Genio, D. Koch, A. Lacis, K. Lo, S. Menon, T. Novakov, J. Perlwitz, G. Russell, G.A. Schmidt, and N. Tausnev, 2005: Earth's energy imbalance: Confirmation and implications. Science, 308, 1431-1435. 16) NSTC, 2007: A Plan for a U. S. National Land Imaging Program. Future of Land Imaging Interagency Working Group, Washington, DC, 84 pp. Available at website. 17) See www.ocean.us
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