Using microwave brightness temperature diurnal cycle to improve emissivity retrievals over land

Norouzi, Hamidreza; Rossow, William B.; Temimi, Marouane; Prigent, Catherine; Azarderakhsh, M.; Boukabara, Sid; Khanbilvardi, R.

doi:10.1016/j.rse.2012.04.015

Cited by 56 publications

(39 citation statements)

References 42 publications

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“…Many contributing factors (e.g., soil moisture, superficial profile of soil temperature, and phenology) are required to explain the behavior of the two passive microwave indices in Alice Springs and Sturt Plains. In particular, in these sparse vegetated sites, the observed radiation was not simply produced at the air/soil interface, and FI variations can be explained by variations of temperature profile, in agreement with previous works [Parinussa et al, 2011;Norouzi et al, 2012].…”

Section: Discussionsupporting

confidence: 92%

“…However, over some areas such as sand dunes, small brightness temperature diurnal cycles have been observed, which are not consistent with the diurnal variations of skin temperature [Prigent et al, 1999;Norouzi et al, 2012]. These studies show that in sandy soils, the observed microwave emission comes from deeper layers rather than from the surface skin and the observed signal depends on the frequency and soil temperature profile [Prigent et al, 1999].…”

Section: Introductionmentioning

confidence: 71%

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Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

et al. 2014

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This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00 h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R 2 ) was found between FI and PI with precipitation (R 2 > 0.5) and soil moisture (R 2 > 0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R 2 > 0.7) and evapotranspiration (R 2 > 0.5), while PI varied with vegetation phenology. Significant differences (p < 0.01) were found among FI values calculated at the four local times.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 71%

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

et al. 2014

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“…However, in some other channels, such as 37V, the differences between TMI and WindSat could reach 3 K (Wilheit, 2013), which can have a non-negligible influence on emissivity estimates. This difference causes about 0.01 difference in emissivity estimates, which is significant especially in regions where emissivity values are higher than 0.95 (Norouzi et al, 2012).…”

Section: Resultsmentioning

confidence: 97%

“…In desert, unlike rain forest regions, maximum differences are at lower frequencies and agreements relatively improve at higher frequencies, particularly in the horizontal polarization values. The deeper penetration of the microwave signal especially at low frequencies in desert which leads to differences in the diurnal amplitude and phase of skin temperature and microwave brightness temperature can introduce considerable error in emissivity retrievals (Norouzi et al, 2012). This issue is more highlighted in desert areas due to moisture scarcity and minimal vegetation interferences.…”

Section: Resultsmentioning

confidence: 99%

Assessment of the consistency among global microwave land surface emissivity products

et al. 2015

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Abstract. The goal of this work is to intercompare four global land surface emissivity products over various landcover conditions to assess their consistency. The intercompared land emissivity products were generated over a 5-year period (2003)(2004)(2005)(2006)(2007) using observations from the Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and WindSat. First, all products were reprocessed in the same projection and spatial resolution as they were generated from sensors with various configurations. Then, the mean value and standard deviations of monthly emissivity values were calculated for each product to assess the spatial distribution of the consistencies/inconsistencies among the products across the globe. The emissivity products were also compared to soil moisture estimates and a satellite-based vegetation index to assess their sensitivities to changes in land surface conditions.Results show the existence of systematic differences among the products. Also, it was noticed that emissivity values in each product have similar frequency dependency over different land-cover types. Monthly means of emissivity values from AMSR-E in the vertical and horizontal polarizations seem to be systematically lower than the rest of the products across various land-cover conditions which may be attributed to the 01:30/13:30 LT overpass time of the sensor and possibly a residual skin temperature effect in the product. The standard deviation of the analyzed products was lowest (less than 0.01) in rain forest regions for all products and highest at northern latitudes, above 0.04 for AMSR-E and SSM/I and around 0.03 for WindSat. Despite differences in absolute emissivity estimates, all products were similarly sensitive to changes in soil moisture and vegetation. The correlation between the emissivity polarization differences and normalized difference vegetation index (NDVI) values showed similar spatial distribution across the products, with values close to the unit except over densely vegetated and desert areas.

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“…MW radiometers with a Ka-band channel are available from several low Earth orbiting satellites 30 that sample at different times of the day. Together they can be used to construct a diurnal cycle of brightness temperature for each location on Earth (Holmes et al, 2013b;Norouzi et al, 2012). This diurnal brightness temperature can then be scaled to match the diurnal temperature cycle as measured by TIR imagers (Holmes et al, 2015(Holmes et al, , 2016.…”

Section: Introductionmentioning

confidence: 99%

Microwave implementation of two-source energy balance approach for estimating evapotranspiration

Holmes¹,

Hain²,

Crow³

et al. 2017

Preprint

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Abstract.A newly developed microwave (MW) land surface temperature (LST) product is used to substitute thermal infrared (TIR) based LST in the two-source energy balance approach (TSEB) for estimating ET from space. This TSEB land surface scheme, the Atmosphere Land Exchange Inverse (ALEXI) model framework, is an approach that minimizes sensitivity to absolute biases in 10 input records of LST through the analysis of the rate of temperature change in the morning. This experiment is therefore an important test of the ability to retrieve diurnal temperature information from a constellation of satellites with microwave radiometers that together provide 6-8 observations of Ka-band brightness temperature per location per day. This represents the first ever attempt at a global implementation of ALEXI with MW-based LST and is intended as the first step towards providing all-weather capability to the ALEXI framework. The leveraging of all sky capability of MW sensors is the main motivation of this work, as TIR-based 15 ALEXI is limited to clear sky conditions. The analysis is based on a 9-year long record of ALEXI ET generated with MW-LST as an input, which is compared to an existing implementation of the same framework with thermal infrared based LST. In this study, the MW-LST sampling is restricted to the same clear sky days as in the IR-based implementation to be able to analyse the impact of changing the LST dataset separately from the impact of sampling all-sky conditions. The results show that long-term bulk ET estimates agree with a spatial correlation of 92% 20 for total ET in the Europe/Africa domain and agreement in seasonal (3-month) totals of 83-97 % depending on the time of year.Most importantly, the ALEXI-MW also matches ALEXI-IR very closely in terms of 3-month inter-annual anomalies, demonstrating its ability to capture the development and extent of drought conditions. The weekly ET output from the two parallel ALEXI implementations is further compared to a common ground measured reference provided by the FLUXNET consortium. Overall, they indicate a surprisingly close match in both performance metrics (correlation and RMSE) for all but the most challenging sites in 25 terms of spatial heterogeneity and level of aridity. Moreover, merging MW-and IR-based ALEXI may provide estimates of ET with a reduced uncertainty, even during nominally clear sky days. It is concluded that a constellation of MW satellites can effectively be used to provide LST for estimating ET through TSEB, which is an important step towards all-sky satellite-based ET estimates.

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Using microwave brightness temperature diurnal cycle to improve emissivity retrievals over land

Cited by 56 publications

References 42 publications

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

Assessment of the consistency among global microwave land surface emissivity products

Microwave implementation of two-source energy balance approach for estimating evapotranspiration

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