Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

Rolf H. Reichle; Qing Liu; Randal D. Koster; Wade T. Crow; Gabrielle J.M. De Lannoy; John S. Kimball; Joseph V. Ardizzone; David Bosch; Andreas Colliander; Michael Cosh; Jana Kolassa; Sarith P. Mahanama; John Prueger; Patrick Starks; Jeffrey P. Walker

doi:10.1029/2019MS001729

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

Rolf H. Reichle, Qing Liu, Randal D. Koster, Wade T. Crow, Gabrielle J.M. De Lannoy, John S. Kimball, Joseph V. Ardizzone, David Bosch, Andreas Colliander, Michael Cosh, Jana Kolassa, Sarith P. Mahanama, John Prueger, Patrick Starks, Jeffrey P. Walker

Numeric Terradynamic Simulation Group

Research output: Contribution to journal › Article › peer-review

133 Scopus citations

Abstract

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L.4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted root-mean-square error in Version 4 is 0.039 m³/m³ for surface and 0.026 m³/m³ for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m³/m³) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

Original language	English
Pages (from-to)	3106-3130
Number of pages	25
Journal	Journal of Advances in Modeling Earth Systems
Volume	11
Issue number	10
DOIs	https://doi.org/10.1029/2019MS001729
State	Published - Oct 1 2019

Keywords

Catchment land surface model
L-band passive microwave
Soil Moisture Active Passive
data assimilation
runoff
soil moisture

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10.1029/2019MS001729

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Reichle, R. H., Liu, Q., Koster, R. D., Crow, W. T., De Lannoy, G. J. M., Kimball, J. S., Ardizzone, J. V., Bosch, D., Colliander, A., Cosh, M., Kolassa, J., Mahanama, S. P., Prueger, J., Starks, P., & Walker, J. P. (2019). Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product. Journal of Advances in Modeling Earth Systems, 11(10), 3106-3130. https://doi.org/10.1029/2019MS001729

@article{6099107498c7488aa711ecd0fd7a3f6d,

title = "Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product",

abstract = "The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L.4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted root-mean-square error in Version 4 is 0.039 m3/m3 for surface and 0.026 m3/m3 for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m3/m3) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.",

keywords = "Catchment land surface model, L-band passive microwave, Soil Moisture Active Passive, data assimilation, runoff, soil moisture",

author = "Reichle, {Rolf H.} and Qing Liu and Koster, {Randal D.} and Crow, {Wade T.} and {De Lannoy}, {Gabrielle J.M.} and Kimball, {John S.} and Ardizzone, {Joseph V.} and David Bosch and Andreas Colliander and Michael Cosh and Jana Kolassa and Mahanama, {Sarith P.} and John Prueger and Patrick Starks and Walker, {Jeffrey P.}",

note = "Publisher Copyright: {\textcopyright} 2019. The Authors.",

year = "2019",

month = oct,

day = "1",

doi = "10.1029/2019MS001729",

language = "English",

volume = "11",

pages = "3106--3130",

journal = "Journal of Advances in Modeling Earth Systems",

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Reichle, RH, Liu, Q, Koster, RD, Crow, WT, De Lannoy, GJM, Kimball, JS, Ardizzone, JV, Bosch, D, Colliander, A, Cosh, M, Kolassa, J, Mahanama, SP, Prueger, J, Starks, P & Walker, JP 2019, 'Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product', Journal of Advances in Modeling Earth Systems, vol. 11, no. 10, pp. 3106-3130. https://doi.org/10.1029/2019MS001729

TY - JOUR

T1 - Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

AU - Reichle, Rolf H.

AU - Liu, Qing

AU - Koster, Randal D.

AU - Crow, Wade T.

AU - De Lannoy, Gabrielle J.M.

AU - Kimball, John S.

AU - Ardizzone, Joseph V.

AU - Bosch, David

AU - Colliander, Andreas

AU - Cosh, Michael

AU - Kolassa, Jana

AU - Mahanama, Sarith P.

AU - Prueger, John

AU - Starks, Patrick

AU - Walker, Jeffrey P.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L.4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted root-mean-square error in Version 4 is 0.039 m3/m3 for surface and 0.026 m3/m3 for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m3/m3) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

AB - The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L.4_SM) product provides global, 3-hourly, 9-km resolution estimates of surface (0–5 cm) and root zone (0–100 cm) soil moisture with a mean latency of ~2.5 days. The underlying L4_SM algorithm assimilates SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. In Version 4 of the L4_SM modeling system the upward recharge of surface soil moisture from below under nonequilibrium conditions was reduced, resulting in less bias and improved dynamic range of L4_SM surface soil moisture compared to earlier versions. This change and additional technical modifications to the system reduce the mean and standard deviation of the observation-minus-forecast Tb residuals and overall soil moisture analysis increments while maintaining the skill of the L4_SM soil moisture estimates versus independent in situ measurements; the average, bias-adjusted root-mean-square error in Version 4 is 0.039 m3/m3 for surface and 0.026 m3/m3 for root zone soil moisture. Moreover, the coverage of assimilated SMAP observations in Version 4 is near global owing to the use of additional satellite Tb records for algorithm calibration. L4_SM soil moisture uncertainty estimates are biased low (by 0.01–0.02 m3/m3) against actual errors (computed versus in situ measurements). L4_SM runoff estimates, an additional product of the L4_SM algorithm, are biased low (by 35 mm/year) against streamflow measurements. Compared to Version 3, bias in Version 4 is reduced by 46% for surface soil moisture uncertainty estimates and by 33% for runoff estimates.

KW - Catchment land surface model

KW - L-band passive microwave

KW - Soil Moisture Active Passive

KW - data assimilation

KW - runoff

KW - soil moisture

UR - http://www.scopus.com/inward/record.url?scp=85074289293&partnerID=8YFLogxK

U2 - 10.1029/2019MS001729

DO - 10.1029/2019MS001729

M3 - Article

AN - SCOPUS:85074289293

SN - 1942-2466

VL - 11

SP - 3106

EP - 3130

JO - Journal of Advances in Modeling Earth Systems

JF - Journal of Advances in Modeling Earth Systems

IS - 10

ER -

Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product

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