Comparison of in-situ, aircraft, and satellite land surface temperature measurements over a NOAA Climate Reference Network site

Krishnan, P.; Kochendorfer, John; Dumas, Edward J.; Guillevic, Pierre; Baker, C. Bruce; Meyers, Tilden P.; Martos, Borja

doi:10.1016/j.rse.2015.05.011

Cited by 45 publications

(33 citation statements)

References 90 publications

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“…Notwithstanding the comparable performance of SSEBop ET and MOD16-NB in reproducing the basin-level GFET, we note high discrepancies between SSEBop ET and MOD16-NB for wetlands and forest (with MOD16-NB being up to 232 mm/yr lower) and rainfed agriculture (with SSEBop ET being up to 178 mm/yr lower). The former differences are partly attributed to the soil water stress parameterization in the MOD16-NB that uses the atmospheric vapor pressure deficit (VPD) and the relative humidity, particularly for the wetland located in a semi-arid climate; whereas the latter could be associated with the limitation of the 1-km scale MODIS T s (i.e., one of the major input to SSEBop), as also noted in McCabe et al [63] and Krishnan et al [65], to capture the spatial variability of T s where there is significant sub-pixel heterogeneity.…”

Section: Discussionmentioning

confidence: 96%

“…Of all of the land-cover classes, agricultural land cover shows a relatively high variability (wider confidence interval) on the mean annual ET estimates. As discussed in Section 3.2.1, this is perhaps attributed to the limitation of the coarse (1 km) spatial scale of MODIS T s to capture the spatial variability of T s as marked in Krishnan et al [65] and McCabe et al [63] since agriculture in this basin is mainly the plot scale. Additionally, the year-to-year variation in types of crops growing in the field might also contribute to the wider confidence interval.…”

Section: The Assessment Of the Uncertainties On The Et Estimatesmentioning

confidence: 99%

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Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

et al. 2017

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Actual evapotranspiration (ET) is a major water use flux in a basin water balance with crucial significance for water resources management and planning. Mapping ET with good accuracy has been the subject of ongoing research. Such mapping is even more challenging in heterogeneous and data-scarce regions. The main objective of our research is to estimate ET using daily Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and Global Land Data Assimilation System (GLDAS) weather datasets based on the operational simplified surface energy balance (SSEBop) algorithm at a 1-km spatial scale and 8-day temporal resolution for the Mara Basin (Kenya/Tanzania). Unlike previous studies where the SSEBop algorithm was used, we use a seasonally-varying calibration coefficient for determining the "cold" reference temperature. Our results show that ET is highly variable, with a high inter-quartile range for wetlands and evergreen forest (24% to 29% of the median) and even up to 52% of the median for herbaceous land cover and rainfed agriculture. The basin average ET accounts for about 66% of the rainfall with minimal inter-annual variability. The basin scale validation using nine-years of monthly, gridded global flux tower-based ET (GFET) data reveals that our ET is able to explain 64% of the variance in GFET while the MOD16-NB (Nile Basin) explains 72%. We also observe a percent of bias (PBIAS) of 1.1% and 2.8%, respectively for SSEBop ET and MOD16-NB, indicating a good reliability in the ET estimates. Additionally, the SSEBop ET explains about 52% of the observed variability in the Normalized Difference Vegetation Index (NDVI) for a 16-day temporal resolution and 81% for the annual resolution, pointing to an increased reliability for longer aggregation periods. The annual SSEBop ET estimates are also consistent with the underlying primary (i.e., water and energy) and secondary (i.e., soil, topography, geology, land cover, etc.) controlling factors across the basin. This paper demonstrated how to effectively estimate and evaluate spatially-distributed and temporally-varying ET in data-scarce regions that can be applied elsewhere in the world where observed hydro-meteorological variables are limited.

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Section: Discussionmentioning

confidence: 96%

Section: The Assessment Of the Uncertainties On The Et Estimatesmentioning

confidence: 99%

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

et al. 2017

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“…When possible, the biases and RMSEs included in Table 1 correspond specifically to the same satellite products used in the current study. For MODIS, most of the results included correspond to cases where the gridded (Level 3) product MOD11A1 in its collection 5 was used ( [12][13][14]22]), although ( [15,16], and [13] for the rice crop area) the swath product MOD11_L2 was used, which is prior to the gridded one. For the ETM+ studies [18], local-radiosonde profiles were used to retrieve the atmospheric parameters in RTE instead of the synthetic ones generated by the web-tool calculator described in Section 2.1, while [17] compared both methodologies over a homogeneous surface, obtaining better results for the interpolated profiles.…”

Section: In Situ Lst Field Datamentioning

confidence: 99%

“…Generally, averages from several ground measurements taken over different parts of the area of interest were preferred ( [12,[15][16][17][18]22]), although [22] obtained better results with a single measurement from a four-component net radiometer located at 6 m height over a strong heterogeneous site. Ref.…”

Section: Previous Validations Of Satellite-derived Lstmentioning

confidence: 99%

“…Most studies comparing satellite measurements and direct measurements of LST occur in homogeneous areas ( [12][13][14][15][16][17][18]; etc.). There are a few studies for heterogeneous areas, like the downscaling ones of [19,20] between MODIS and ETM+ sensors, or LST validation campaign of [16,21,22] where LST satellite data was compared with in situ measurements. It is usually concluded that errors are higher in heterogeneous areas than in homogeneous ones (a summary is shown in Table 1).…”

Section: Introductionmentioning

confidence: 99%

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Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

et al. 2016

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Land Surface Temperature (LST) as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean), with an area of about 1 km 2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE) of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area.

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Temporal and spatial variability of daytime land surface temperature in Houston: Comparing DISCOVER‐AQ aircraft observations with the WRF model and satellites

Huang

Lee²,

McNider

et al. 2016

JGR Atmospheres

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Based on a semiempirical diurnal temperature cycle model and aircraft observations taken at different times of the day, daytime land surface temperature (LST) is derived at six locations in the Greater Houston area on the least cloudy day during NASA's DISCOVER‐AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaign in September 2013. The aircraft‐derived daytime LSTs show ranges (max‐min) of 11–25°K varying by location, with the daily maxima occurring near 1300–1400 local time. Two Weather Research and Forecasting model simulations that were configured differently are compared with these aircraft‐derived LST, indicating location‐ and time‐dependent performance. The NOAA GOES geostationary satellite observed similar LST spatial patterns in Houston to those in finer resolution from two polar‐orbiting satellite instruments (Moderate Resolution Imaging Spectroradiometer and Visible Infrared Imaging Radiometer Suite), and it provided useful information of the LST temporal variability missing from the polar‐orbiting satellite products. However, spatial‐ and time‐varying discrepancies are found among LSTs from these various platforms, which are worth further evaluation in order to benefit model evaluation and improvement. The aircraft and satellite LSTs are overall anticorrelated with satellite vegetation indexes. This emphasizes the importance of vegetation cover in urban planning due to its cooling effect and further impact on biogenic emissions and regional air quality. The approaches shown in this study are also suitable for applications under cloudless conditions at other locations and times, such as during the remaining DISCOVER‐AQ deployments conducted in three other populated regions with diverse land uses.

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Comparison of in-situ, aircraft, and satellite land surface temperature measurements over a NOAA Climate Reference Network site

Cited by 45 publications

References 90 publications

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

Temporal and spatial variability of daytime land surface temperature in Houston: Comparing DISCOVER‐AQ aircraft observations with the WRF model and satellites

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