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CLPX Data

Cold Land Processes Field Experiment

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Scientists preparing to collect CLPX data near Buffalo Pass, Colorado USA.
Scientists preparing to collect CLPX data for the first Intensive Observation Period (IOP1) near Buffalo Pass, Colorado USA on 24 February 2002. Image courtesy of NSIDC.

CLPX Overview

The Cold Land Processes Field Experiment (CLPX) was focused on developing quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment emphasized the development of a strong synergism between process-oriented understanding, land surface models, and microwave remote sensing by using a multi-sensor, multi-scale approach. Within a framework of nested study areas ranging from 1 ha to 160,000 km2, intensive ground, airborne, and spaceborne observations were collected. Data collection occured during two seasons: mid-winter, when conditions are generally frozen and dry, and early spring, a transitional period when both frozen and thawed, and dry and wet conditions are widespread. CLPX was conducted in the central Rocky Mountains of the western United States where large physiographic gradients provided a rich array of different terrain, snow, soil, and ecological characteristics.

Between the Winter of 2002 and the Spring of 2003, two Intensive Observation Periods (IOPs) were conducted each year to coincide with both a dry period (February) and a wet period (March). Thus, IOP1 was carried out in February 2002, IOP2 in March 2002, IOP3 in February 2003, and IOP4 in March 2003. To maintain consistency, the IOPs were conducted on the same day-of-year (DOY) schedule.

The specific objectives of CLPX included the following:

  • Evaluate and improve snow water equivalent retrieval algorithms for spaceborne passive microwave sensors such as SSM/I and AMSR-E;
  • Evaluate and improve radar retrieval algorithms for snow depth, density, and wetness, and soil freeze/thaw status;
  • Improve radar retrieval algorithms to enable discrimination of freeze/thaw status of different surfaces. For example, snow, soil, and vegetation;
  • Examine the effects of scale (spatial resolution) on the skill of active and passive microwave remote sensing retrieval algorithms for snow and freeze/thaw status;
  • Evaluate and improve spatially distributed, uncoupled snow/soil models and coupled cold land surface schemes from point scales to typical mesoscale grid-resolutions, typically 25 km;
  • Examine the feasibility of coupling forward microwave radiative-transfer schemes to spatially distributed snow/soil models to improve assimilation of microwave remote sensing data;
  • Examine the spatial variability of snow and frozen soil distributions in different environments, and improve the representation of subgrid-scale variability of snow and frozen soil in coupled and uncoupled land surface models, and improve the representation of orographic precipitation (snowfall) in atmospheric models;
  • Examine methods of extending local-scale, process-oriented equations describing important cold-land hydrologic and boundary layer properties to larger scales typical of regional and global atmospheric and hydrologic models.

For complete information about CLPX, please visit the NASA CLPX Web site.


CLPX Data

CLPX Data Set Table

Related Resources

Additional information regarding CLPX study areas and campaign at NASA's CLPX Web site

NASA Cold Land Process Field Experiment Overview and Preliminary Results (PDF)

Improving water and climate forecasts using CLPX data