New Climate Data Record Focuses on Water
A new “hydrobundle” Climate Data Record (CDR) at NCEI pulls together several types of water data to provide a clearer, broader picture of Earth’s climate. This CDR, a long-term record of complementary hydrological data, includes total precipitable water, surface temperature, rainfall, sea ice, and snow. It can be used for forecasting trends and changes within these observations.
Developed through a NOAA program grant, the CDR combines observations from operational microwave sounding sensors and microwave humidity sounders from several satellites, including the polar orbiting NOAA and EUMETSAT series (European Organisation for the Exploitation of Meteorological Satellites) used primarily for weather forecasting. The record compiles data over nearly a dozen years starting in 2000 and includes observation channels that see primarily Earth’s surface (known as window channels) and those that are sensitive to atmospheric water vapor. The combination of these channels allows scientists to examine various aspects of Earth’s hydrological cycles.
When grouped thematically, the hydrobundle CDR includes total precipitable water, cloud liquid water, land surface temperature, land surface emissivity, sea-ice concentration, ice water path, rain rate, snow cover, and snow water equivalent. Developers of the hydrobundle CDR intend to continue the record through the end of 2016 applying the same user standards. NCEI maintains 37 CDRs and applies the same methods to present-day and future satellite measurements.
Commitment to Quality CDRs
NOAA’s CDR program aims to add value to datasets. The program encourages the application of modern analytical tools to historical observations to improve their usefulness. CDRs must be of sufficient length, consistency, and continuity for researchers and climate observers to gain a valid measure of variability and change in climate over time. As with all operational CDRs made available through NCEI, the new CDR had to meet rigorous quality standards recommended by the National Academy of Sciences and other expert organizations. Chiefly, the CDR produces consistent, reliable, and scientifically defensible data.
A broad range of groups have a stake in CDR data: energy, water resources, agriculture, human health, national security, coastal community, and other public and private interest groups. CDRs have been developed with the goal that their applicability can improve resiliency to climate events, improve national security, and provide insight to economic outlooks due to climate changes.
Developing the Hydrological CDR
To develop the hydrobundle CDR, researchers had to account for inconsistencies in the raw data caused by sensor artifacts and post-launch changes, especially as the satellite ages, and add additional metadata to provide important information that may have been missing in the initial collection. Also, because files came from separate sensors and data streams, different approaches based on the source of the observation had to be considered to make the data more consistent for use in climate studies. In essence, the 11-year CDR from six different satellites is calibrated in a consistent manner as if the record came from just one sensor.
The process to create the new hydrobundle record began in 2010 and was completed in 2016 by a team of developers from several parts of NOAA/NESDIS, including the Center for Satellite Applications and Research (STAR), and its Satellite Climate Studies Branch. Scientists from the University of Maryland, Cooperative Institute for Climate and Satellites (CICS) were key contributors to the project.
Developers of the new CDR have found the data to be most useful when combined with similar CDR’s generated from other satellites that span longer time periods. Additionally, because the NOAA and EUMETSAT satellites are configured to observe Earth approximately every four hours, a more accurate depiction of the daily hydrological cycle can be obtained from this particular CDR. For example, a reinsurance company has successfully used the rainfall CDR to obtain a better estimate of global flooding potential regions than using other precipitation datasets that do not represent the daily cycle of rain adequately.