Validation of the SMAP freeze/thaw product using categorical triple collocation

Li, Xinlu; McColl, Kaighin A.; Lyu, Haobo; Xu, Xiaolan; Derksen, Chris; Lu, Hui; Entekhabi, Dara

doi:10.1109/igarss.2017.8127277

Cited by 2 publications

(4 citation statements)

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“…This finding is significant because SMAP observations are coarse (about 36 km 3 36 km) and roads would have an insignificant contribution to the signal received at the SMAP sensor. However, previous studies of SMAP data by other groups showed that SMAP tends to detect thaw early relative to natural soils (11,(15)(16)(17). Those works suggested that this may be as a result of SMAP responding to the earlier occurring thaw of other landscape elements, in particular snow.…”

Section: Discussionmentioning

confidence: 93%

“…A bare road surface would likely initiate thaw at a similar time as the landscape due to concurring exposure of warm air temperatures and directly impinging solar radiation. Other research groups have already noted that SMAP thaw signals from L3_FT_P tend to occur earlier than soil thaw, and that this may be due to other landscape elements thawing earlier (i.e., snow) (11,(15)(16)(17). The signal of a thawing snowpack within the greater landscape would likely be readily detected by the algorithm used to generate L3_FT_P, because it uses the microwave polarization difference index, which is a wellknown wet/dry discriminator (18,19).…”

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confidence: 95%

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Remotely Sensed Freeze-Thaw from the Soil Moisture Active Passive Instrument to Inform the Timing of Seasonal Load Restrictions in Alaska

Kraatz

Miller

Jacobs

2019

Transportation Research Record

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To balance the competing interests of minimizing road damage while maximizing economic opportunities on low-volume roadways located in seasonal frost areas, road management agencies typically apply spring load restrictions (SLR). The Alaska Department of Transportation and Public Facilities (ADOT&PF) uses an observational approach to determine SLR, which utilizes temperature data probes (TDP). Although their TDP network is fairly extensive, comprehensive coverage of all roads within the ADOT&PF domain is not feasible. Passive microwave spaceborne freeze and thaw (FT) observations may be useful for bridging these observational gaps. This study compared satellite FT retrievals with TDP data at 15 sites in Alaska to determine whether satellite-retrieved FT can inform on road FT; whether there are substantial morning (AM) and afternoon (PM) satellite-retrieved FT differences; and assess how Soil Moisture Active Passive (SMAP)-based SLR application dates compare with ADOT&PF SLR-applied dates. Our evaluation showed that SMAP AM (PM) FT retrievals are highly representative of FT in roads with an overall accuracy of 79% (83%). SMAP-retrieved FT states corresponded to individual TDP locations 52–95% of the time, and FT accuracy exceeded 80% at 9 (11) out of 15 TDP sites for AM (PM) data. SMAP thaw detection was very consistent with respect to road data: (1) interannual variation of FT accuracy at individual TDP sites was low (16%) and (2) strong SMAP thaw signals were detected about 10-days ahead of all roads having thawed according to TDP data.

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Section: Discussionmentioning

confidence: 93%

mentioning

confidence: 95%

Remotely Sensed Freeze-Thaw from the Soil Moisture Active Passive Instrument to Inform the Timing of Seasonal Load Restrictions in Alaska

Kraatz

Miller

Jacobs

2019

Transportation Research Record

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“…NASA SMAP FT accuracy has been reported at variable time scales including the period of record of the active radar (April-July 2015) or a full year [19,20]. Derksen et al (2017) reported that there are relatively more errors of commission during summer than winter [19].…”

Section: Temporal Subsetsmentioning

confidence: 99%

“…SMAP CVSs are densely sampled and usually consist of about ten stations covering a spatial extent of about 40 km by 40 km. Previous studies have used boreal (>45 • N) latitude CVSs to validate the FT product [19,20]. Sites below 45 • N have been used for soil moisture validation [21], but some of these sites should also be well-suited to assess SMAP FT retrievals at mid-latitudes.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of SMAP Freeze/Thaw Retrieval Accuracy at Core Validation Sites in the Contiguous United States

et al. 2018

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Seasonal freeze-thaw (FT) impacts much of the northern hemisphere and is an important control on its water, energy, and carbon cycle. Although FT in natural environments extends south of 45°N, FT studies using the L-band have so far been restricted to boreal or greater latitudes. This study addresses this gap by applying a seasonal threshold algorithm to Soil Moisture Active Passive (SMAP) data (L3_SM_P) to obtain a FT product south of 45°N (‘SMAP FT’), which is then evaluated at SMAP core validation sites (CVS) located in the contiguous United States (CONUS). SMAP landscape FT retrievals are usually in good agreement with 0–5 cm soil temperature at SMAP grids containing CVS stations (>70%). The accuracy could be further improved by taking into account specific overpass time (PM), the grid-specific seasonal scaling factor, the data aggregation method, and the sampling error. Annual SMAP FT extent maps compared to modeled soil temperatures derived from the Goddard Earth Observing System Model Version 5 (GEOS-5) show that seasonal FT in CONUS extends to latitudes of about 35–40°N, and that FT varies substantially in space and by year. In general, spatial and temporal trends between SMAP and modeled FT were similar.

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Validation of the SMAP freeze/thaw product using categorical triple collocation

Cited by 2 publications

References 10 publications

Remotely Sensed Freeze-Thaw from the Soil Moisture Active Passive Instrument to Inform the Timing of Seasonal Load Restrictions in Alaska

Remotely Sensed Freeze-Thaw from the Soil Moisture Active Passive Instrument to Inform the Timing of Seasonal Load Restrictions in Alaska

Evaluation of SMAP Freeze/Thaw Retrieval Accuracy at Core Validation Sites in the Contiguous United States

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