ARM data are used to evaluate the utility of satellite derived land-atmosphere coupling metrics that can provide information on drought monitoring.
In the absence of strong advective influences, land-atmosphere (LA) coupling drives the diurnal cycle of clouds and precipitation that can greatly impact the water cycle. Satellite data offer the ability to obtain values of some of the variables important for land-atmosphere coupling globally and routinely, but the utility of these derived data need to be assessed. This study assesses the utility and uncertainty of data from the Aqua satellite for application to a coupling drought index (CDI) by comparing them with in situ observations from the ARM Southern Great Plains (SGP) site and reanalysis datasets.
Overall, this work demonstrates that there is sufficient information in the simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information to the applications of drought monitoring and coupling metrics that can be used to evaluate global climate models. Additionally, the ARM and satellite remote sensing CDI provides a unique combination of observations that allows for an evaluation of model data at local and large scales that could be exploited in future studies.
Feedbacks between the land and the atmosphere can play an important role in the water cycle, and a number of studies have quantified land-atmosphere (LA) interactions and feedbacks through observations and prediction models. Because of the complex nature of LA interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in situ data from the ARM Southern Great Plains site and reanalysis products. NASA’s Aqua satellite and retrievals of soil moisture and lower-tropospheric temperature and humidity properties are used as input. Overall, the Aqua-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in situ and reanalysis products. In addition, this work represents the first time that in situ observations were utilized for the coupling classification and CDI. The combination of in situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics.
Contacts (BER PM)
ARM Program Manager
NASA Goddard Space Flight Center
This research was partially supported by an appointment to the NASA Postdoctoral Program at the Goddard Space Flight Center, administered by Oak Ridge Associated Universities. Data were obtained from the Atmospheric Radiation Measurement (ARM) Program sponsored by the U.S. Department of Energy.
Roundy J. and J. Santanello. "Utility of Satellite Remote Sensing for Land-Atmosphere Coupling and Drought Metrics." Journal of Hydrometeorology, 18(3) (2017). [DOI:10.1175/JHM-D-16-0171.1]
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]
May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]
May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]
May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]
Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]
List all highlights (possible long download time)