Joseph V. Ardizzone
Goddard Space Flight Center
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Featured researches published by Joseph V. Ardizzone.
Journal of Hydrometeorology | 2017
Rolf H. Reichle; Gabrielle De Lannoy; Q. Liu; Joseph V. Ardizzone; Andreas Colliander; Austin Conaty; Wade T. Crow; Thomas J. Jackson; Lucas A. Jones; John S. Kimball; Randal D. Koster; Sarith P. P. Mahanama; Edmond B. Smith; Aaron A. Berg; Simone Bircher; David D. Bosch; Todd G. Caldwell; Michael H. Cosh; Ángel González-Zamora; Chandra D. Holifield Collins; Karsten H. Jensen; Stan Livingston; Ernesto Lopez-Baeza; Heather McNairn; Mahta Moghaddam; Anna Pacheco; Thierry Pellarin; John H. Prueger; Tracy L. Rowlandson; Mark S. Seyfried
AbstractThe Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requiremen...
Journal of Hydrometeorology | 2017
Rolf H. Reichle; Gabrielle De Lannoy; Q. Liu; Randal D. Koster; John S. Kimball; Wade T. Crow; Joseph V. Ardizzone; Purnendu Chakraborty; Douglas W. Collins; Austin Conaty; Manuela Girotto; Lucas A. Jones; Jana Kolassa; Hans Lievens; Robert Lucchesi; Edmond B. Smith
The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under ~3 K), the soil moisture increments (under ~0.01 m3 m-3), and the surface soil temperature increments (under ~1 K). Typical instantaneous values are ~6 K for O-F residuals, ~0.01 (~0.003) m3 m-3 for surface (root-zone) soil moisture increments, and ~0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.
international geoscience and remote sensing symposium | 2016
Rolf H. Reichle; G. de Lannoy; Q. Liu; Joseph V. Ardizzone; John S. Kimball; R. Koster
The SMAP Level 4 soil moisture (L4_SM) product provides global estimates of surface and root zone soil moisture, along with other land surface variables and their error estimates. These estimates are obtained through assimilation of SMAP brightness temperature observations into the Goddard Earth Observing System (GEOS-5) land surface model. The L4_SM product is provided at 9 km spatial and 3-hourly temporal resolution and with about 2.5 day latency. The soil moisture and temperature estimates in the L4_SM product are validated against in situ observations. The L4_SM product meets the required target uncertainty of 0.04 m3m-3, measured in terms of unbiased root-mean-square-error, for both surface and root zone soil moisture.
Archive | 2015
Joe Glassy; John S. Kimball; Lucas A. Jones; Rolf H. Reichle; Joseph V. Ardizzone; Gi-Kong Kim; Robert Lucchesi; Edmond B. Smith; Barry H. Weiss
Archive | 2016
Rolf H. Reichle; Gabrielle De Lannoy; R. Koster; John S. Kimball; Wade T. Crow; Q. Liu; Joseph V. Ardizzone; Aaron A. Berg; David D. Bosch; Todd G. Caldwell; Andreas Colliander; Austin Conaty; Michael H. Cosh; David C. Goodrich; Thomas J. Jackson; Stan Livingston; John H. Prueger; Tracy L. Rowlandson; Patrick J. Starks
Archive | 2016
Rolf H. Reichle; G. De Lannoy; Q. Liu; Joseph V. Ardizzone
Archive | 2016
Rolf H. Reichle; Gabrielle De Lannoy; Q. Liu; Joseph V. Ardizzone; Fan Chen; Andreas Colliander; Austin Conaty; Wade T. Crow; Thomas J. Jackson; John S. Kimball; Randal D. Koster; E. Brent Smith
Archive | 2016
Rolf H. Reichle; Q. Liu; Gabrielle De Lannoy; Joseph V. Ardizzone
Archive | 2015
Rolf H. Reichle; Joseph V. Ardizzone; Gi-Kong Kim; Robert Lucchesi; Edmond B. Smith; Barry H. Weiss
Archive | 2015
Joe Glassy; John S. Kimball; Lucas A. Jones; Rolf H. Reichle; Joseph V. Ardizzone; Gi-Kong Kim; Robert Lucchesi; Edmond B. Smith; Barry H. Weiss