Cold Land Processes Field Experiment Plan - December 7, 2001

1. OVERVIEW
    1.1. SCIENTIFIC OBJECTIVES
    1.2. APPROACH
    1.3. RISK REDUCTION STRATEGY
    1.4. SUMMARY OF KEY MEASUREMENTS AND DATA PRODUCTS


1. OVERVIEW


The Cold-land Processes Field Experiment has been designed to advance our understanding of the terrestrial cryosphere - cold areas of the Earth's land surface where water is frozen either seasonally or permanently. These areas, where snow, ice, and frozen soils and vegetation are common, have a large influence on global water, energy, and biogeochemical cycles. The storage of large amounts of fresh water in seasonal snow covers is a critical element of the Earth's hydrologic cycle. On average, over 60% of the northern hemisphere land surface has snow cover in midwinter, and over 30% of Earth's total land surface has seasonal snow [Robinson, et al., 1993]. In many high-latitude and mountainous regions of the Earth, the majority of total annual precipitation occurs as snowfall [e.g. Serreze et al., 2000], and snowmelt is responsible for most of the total annual streamflow. Seasonal snow covers are a large energy sink in the Earth's energy cycle, and through their effects on land surface albedo, the net radiation balance, and boundary layer stability, have profound affects on weather patterns over large areas. Frozen soils also have large effects on the Earth's water and energy cycles. Frozen soils also have large effects on Earth's water, energy, and carbon cycles. Seasonally and permanently frozen soils occur throughout higher latitudes and at high elevations; they are thought to occur over at least 35% of the Earth's land surface [Williams and Smith, 1989], including approximately 50% of northern hemisphere land areas [Zhang, et al., 1999]. Seasonal and permanent frost in soils reduce both infiltration into and migration of water through soils, and severely reduce the amount of water that can be stored in soils [Kane and Chacho, 1990]. By reducing infiltration, frozen soils can dramatically increase the runoff generated from melting snow. An estimated 7.2% (4 GT) of the world's organic carbon [Schlesinger, 1991] resides in the annually thawing surface layer of tundra soils alone. In these environments, vegetation growing seasons are determined primarily by the thawed period. In turn, the timing of the spring thaw and the duration of the growing season are strongly linked to the carbon balance of seasonally frozen ecosystems. The influence of seasonally and permanently frozen land surfaces extends to engineering in cold regions, trafficability for humans and other species, and a variety of hazards and costs associated with living in cold lands.

The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. Synergistic advancement on these fronts requires the following four major science questions to be addressed together:

  1. Process Understanding. How do the extent and evolution of snow and frozen landscapes affect fluxes, storage, and transformations of water, energy, and carbon?

    2.  
  2. Spatial Variability. At what scales does spatial variability of key state variables in the terrestrial cryosphere, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed conditions, control fluxes and transformations of water, energy, and carbon, and can remote sensing resolve this variability at these scales?

    3.  
  3. Temporal Variability. What are the rates of change of the dominant cold land processes and can remote sensing resolve these with sufficient accuracy to diagnose and improve land surface models?

    4.  
  4. Uncertainty. How do the various uncertainties associated with remote sensing observations and models of cold land processes constrain/affect data assimilation and the ability to improve prediction?
The Cold Land Processes Field Experiment is designed to help reach these objectives.
 

1.1. SCIENTIFIC OBJECTIVES

The Cold Land Processes Field Experiment will focus on developing the 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 will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing.

Microwave sensors appear ideal to measure properties of the terrestrial cryosphere because the microwave signal is sensitive to the dielectric constant of surface materials, which in turn is sensitive to the phase of water, ice or liquid [Koh, 1992]. Passive microwave sensors are sensitive to the physical temperature of surface materials. Both active and passive microwave sensors have demonstrated sensitivity to snow properties and the freeze/thaw status of soils [Goodison and Walker, 1993; Chang, et al., 1996; Shi and Dozier, 2000]. Microwave signal response is influenced by snow depth, density, wetness, crystal size and shape, ice crusts and layer structure, surface roughness, vegetation characteristics, soil moisture, and soil freeze/thaw status [Davis et al., 1987; Hall et al., 1986; McDonald and Ulaby, 1993; Josberger et al., 1996, Kim, 1999; Rosenfeld and Grody, 2000]. While visible and near-infrared sensors cannot see through clouds and require adequate solar illumination, which is a frequent and severe limitation in cold regions during winter [Cline and Carroll, 1999], measurements of the Earth surface in the microwave spectral regions can be largely insensitive to weather conditions and solar illumination. These properties make microwave remote sensing attractive for providing spatially distributed information to improve and update land-surface models for cold regions, either through assimilation of state-variable information estimated from microwave remote sensing observations using inversion algorithms, or possibly even through direct assimilation of microwave remote sensing data themselves.

The specific objectives of the Cold Land Processes Field Experiment are to:

Each of these objectives is scientifically important in its own right. Furthermore, all are important elements of a programmatic objective for the field experiment: NASA's Earth Science Enterprise has identified the need for improved measurement of snow properties and frozen soils via an exploratory space-flight mission in the next decade [NASA Earth Science Enterprise, 2000]. Scientifically and programmatically, planning for this mission requires a thorough understanding of the complex relationships between a) relevant physical processes, b) measurement capabilities and characteristics, and c) the specific needs of predictive land surface models and the ability to effectively assimilate measurements into the models. These three elements are intrinsically linked by the related concepts of scale and uncertainty. The fundamental objective of the experiment is therefore to provide the comprehensive data sets necessary to develop an understanding of these relationships, and the associated uncertainties, across multiple scales.
 

1.2. APPROACH

The experimental design described here is a multi-sensor, multi-scale approach to providing the comprehensive data set necessary to address the objectives stated above. A set of nested study areas, ranging from 1 ha to 160,000 km2, provides the framework necessary to permit a detailed examination of cold land processes, modeling, and measurement over a wide range of physiographic conditions and spatial scales ( Figure 1 ). Within this framework, intensive ground, airborne, and spaceborne observations will be collected, and land surface model data sets generated, to produce a comprehensive data base sufficient to meet the science objectives.

The experiment study sites and schedule have been designed to efficiently provide a wide range of snow and frozen soil, topography, and vegetation conditions, with strong consideration given to winter accessibility and safety issues. The experiment will be conducted in the complex terrain of northern Colorado, USA, where elevation gradients and slope/aspect variations provide a wide range of conditions over relatively short distances. Study sites have been selected that range from low-relief (flat topography), unforested areas with shallow snow covers, to high-relief (complex topography), densely forested areas with deep snow covers. The experiment will also exploit seasonal variations in snow and frozen soil conditions. Field campaigns will be conducted in late winter (mid-February), when predominantly frozen conditions and dry snow covers are expected, and in early spring (late-March), when transitional (e.g. frozen and thawed) conditions and predominantly wet snow covers are expected ( Figure 2 ). The field campaigns will be conducted in 2002 and 2003.

Data collection during the experiment will focus on 1) active- and passive-microwave remote sensing observations from ground, aircraft, and satellite platforms, 2) intensive in situ observations of snow and soil characteristics, and 3) in situ meteorological observations. In situ snow and soil data collection plans are based on three scales of observation. At the smallest scale (1 ha), data collection will focus on intense characterization and monitoring of the vertical structure of the snow pack and underlying soil, together with in situ meteorological observations and stationary ground-based microwave sensors. Ground-based active- and passive-microwave remote sensing data sets will be collected using several sensors with frequencies ranging from 0.5 to 110 GHz. At the next larger scale (1 km2), data collection will focus on measuring the spatial distribution of snow and frozen soil characteristics in different landscapes, again with in situ meteorological observations. At the next larger scale (625 km2), data collection will focus on airborne measurements from five sensors. The NASA AIRSAR instrument, flown aboard the NASA DC-8 aircraft, will collect synthetic aperture radar measurements at three frequencies (P-, L-, and C-bands) in both polarimetric and interferometric modes. The NASA POLSCAT instrument, also flown aboard the DC-8 aircraft, will collect Ku-band scatterometer measurements. The NOAA PSR-A instrument, also flown aboard the DC-8 during the 2002 campaigns, will collect passive microwave measurements at five frequencies ranging from 10.7- to 89-GHz. The similar AESMIR instrument will be flown aboard the NASA P-3B during the 2003 campaigns to collect passive microwave measurements (all AMSR-E frequencies from 6.9- to 89-GHz, and possibly 1.4-GHz). The NOAA GAMMA instrument, flown aboard the NOAA AC690A aircraft, will measure terrestrial and atmospheric gamma radiation, which will be used to determine snow water equivalent using standard operational algorithms. At the two largest scales (33,000 km2 and 142,000 km2), data collection will be focused on spaceborne measurements from several active and passive microwave and optical sensors.

In addition to ground and airborne data collection, analyses from mesoscale and regional atmospheric model will be gathered for a variety of uses in the experiment. Hourly atmosphere and surface analyses will be collected for the full experiment study area, and for the full snow season (e.g., September through June), from 1) the Rapid Update Cycle (RUC2; Benjamin et al, [1998]) at 20-km horizontal grid increment, and 2) the Local Analysis and Prediction System (LAPS; Albers et al., [1996]) at 10-km horizontal grid increment.

Finally, a comprehensive GIS database has been developed for the experiment. It contains a wide variety of gridded geophysical data sets, as well as numerous spatial data sets describing relevant logistical and infrastructure information.
 

1.3. RISK REDUCTION STRATEGY

All field experiments have certain risks associated with them. Many factors may compromise the chances of a successful experiment. In this case, major risk factors include: 1) the use of large aircraft that are in high-demand, 2) the availability of necessary satellite data sets, 3) winter conditions.

The use of NASA's large aircraft (DC-8 and P-3B) and NOAA's small aircraft (AC690A) in this experiment significantly increases the risk of scheduling problems, conflicts with other experiments, and field delays due to weather or mechanical problems. Scheduling NASA aircraft for this experiment has and will continue to require significant coordination among several groups, including other experiments. Other factors, such as delays in the availability of necessary satellite data (i.e. launch-slips for the AQUA platform and the AMSR-E instrument) also complicate experiment planning and create risk. Validation of the AMSR-E snow algorithms and products is an important part of this experiment, therefore launch delays present an unavoidable complication to the experiment plan. The fact that this experiment is focused on cold regions with winter conditions also complicates the experiment plan. Because significant resources are required to begin the experiment (e.g. background data collection, installation of instruments, organization of field personnel, etc.), it is essential to mitigate risks due to aircraft schedule changes, satellite launch changes, and effects of winter conditions.

The primary approach to risk reduction in this experiment is to conduct the experiment over two years. While this increases the total cost of the experiment, the increase is not proportional to the added benefits and the reduced risk. This approach accomplishes five things:

  1. It increases the scientific value of the data sets by extending their range, improving representativeness, and enabling limited investigation of inter-annual characteristics;
  2. It prorates the startup-costs across a larger and more valuable data set;
  3. It provides flexibility to respond to changing aircraft schedules;
  4. It provides flexibility to take advantage of, but not depend on new instrument developments (i.e. Ku-band radar and AESMIR, discussed below).
  5. It protects against risks of poor weather conditions, aircraft mechanical problems, or other unavoidable problems, by increasing the opportunities for successful data collection.
All ground observations will be conducted in both years of the experiment. Aircraft active and passive microwave measurements, and airborne gamma radiation measurements of snow water equivalent will be conducted in both years as well. This allows necessary flexibility to coordinate the use of NASA's aircraft with other experiments.

Other risk reduction measures include several steps to maximize the efficiency and success of field data collection, discussed throughout this plan. These include a strong focus on field safety, navigation, and communication to prevent accidents and injury, which are serious risks in backcountry winter conditions. Besides the obvious need to ensure safety for the sake of field personnel, accidents and injuries can also compromise the success of the experiment. Reducing the total risk in the experiment is a constant and overarching theme of this plan.
 

1.4. SUMMARY OF KEY MEASUREMENTS AND DATA PRODUCTS

Location


Background Data Collection


Intensive Observing Periods


Instruments and Aircraft


Satellite Data Acquisitions


Ground Sampling Activities


Major Products