TY - JOUR
T1 - Developing a drought-monitoring index for the contiguous US using SMAP
AU - Sadri, Sara
AU - Wood, Eric F.
AU - Pan, Ming
N1 - Funding Information:
Acknowledgements. This work was supported by NASA grant CNV1003235. This paper benefited greatly from the reviewers’ comments. We thank them for their time and support.
Publisher Copyright:
© Author(s) 2018.
PY - 2018/12/21
Y1 - 2018/12/21
N2 - Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe (between 85.044° N/S) using an L-band (1.4 GHz) microwave radiometer in 2-3 days depending on location. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for meaningful assessment of its indices. This study presents initial insights about using SMAP for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS). SMAP soil moisture data from April 2015 to December 2017 at both near-surface (5 cm) SPL3SMP, or Level 3, at ∼ 36 km resolution, and root-zone SPL4SMAU, or Level 4, at ∼ 9 km resolution, were fitted to beta distributions and were used to construct probability distributions for warm (May-October) and cold (November-April) seasons. To assess the data adequacy and have confidence in using short-term SMAP for a drought index estimate, we analyzed individual grids by defining two filters and a combination of them, which could separate the 5815 grids covering CONUS into passed and failed grids. The two filters were (1) the Kolmogorov-Smirnov (KS) test for beta-fitted long-term and the short-term variable infiltration capacity (VIC) land surface model (LSM) with 95% confidence and (2) good correlation (≥ 0:4) between beta-fitted VIC and beta-fitted SPL3SMP. To evaluate which filter is the best, we defined a mean distance (MD) metric, assuming a VIC index at 36 km resolution as the ground truth. For both warm and cold seasons, the union of the filters - which also gives the best coverage of the grids throughout CONUS - was chosen to be the most reliable filter. We visually compared our SMAP-based drought index maps with metrics such as the U.S. Drought Monitor (from D0-D4), 1-month Standard Precipitation Index (SPI) and near-surface VIC from Princeton University. The root-zone drought index maps were shown to be similar to those produced by the root-zone VIC, 3- month SPI, and the Gravity Recovery and Climate Experiment (GRACE). This study is a step forward towards building a national and international soil moisture monitoring system without which quantitative measures of drought and pluvial conditions will remain difficult to judge.
AB - Since April 2015, NASA's Soil Moisture Active Passive (SMAP) mission has monitored near-surface soil moisture, mapping the globe (between 85.044° N/S) using an L-band (1.4 GHz) microwave radiometer in 2-3 days depending on location. Of particular interest to SMAP-based agricultural applications is a monitoring product that assesses the SMAP near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for meaningful assessment of its indices. This study presents initial insights about using SMAP for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS). SMAP soil moisture data from April 2015 to December 2017 at both near-surface (5 cm) SPL3SMP, or Level 3, at ∼ 36 km resolution, and root-zone SPL4SMAU, or Level 4, at ∼ 9 km resolution, were fitted to beta distributions and were used to construct probability distributions for warm (May-October) and cold (November-April) seasons. To assess the data adequacy and have confidence in using short-term SMAP for a drought index estimate, we analyzed individual grids by defining two filters and a combination of them, which could separate the 5815 grids covering CONUS into passed and failed grids. The two filters were (1) the Kolmogorov-Smirnov (KS) test for beta-fitted long-term and the short-term variable infiltration capacity (VIC) land surface model (LSM) with 95% confidence and (2) good correlation (≥ 0:4) between beta-fitted VIC and beta-fitted SPL3SMP. To evaluate which filter is the best, we defined a mean distance (MD) metric, assuming a VIC index at 36 km resolution as the ground truth. For both warm and cold seasons, the union of the filters - which also gives the best coverage of the grids throughout CONUS - was chosen to be the most reliable filter. We visually compared our SMAP-based drought index maps with metrics such as the U.S. Drought Monitor (from D0-D4), 1-month Standard Precipitation Index (SPI) and near-surface VIC from Princeton University. The root-zone drought index maps were shown to be similar to those produced by the root-zone VIC, 3- month SPI, and the Gravity Recovery and Climate Experiment (GRACE). This study is a step forward towards building a national and international soil moisture monitoring system without which quantitative measures of drought and pluvial conditions will remain difficult to judge.
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U2 - 10.5194/hess-22-6611-2018
DO - 10.5194/hess-22-6611-2018
M3 - Article
AN - SCOPUS:85059424682
SN - 1027-5606
VL - 22
SP - 6611
EP - 6626
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
IS - 12
ER -