scholarly journals Climatology of the Combined ASTER MODIS Emissivity over Land (CAMEL) Version 2

2020 ◽  
Vol 13 (1) ◽  
pp. 111
Author(s):  
Michelle Loveless ◽  
E. Eva Borbas ◽  
Robert Knuteson ◽  
Kerry Cawse-Nicholson ◽  
Glynn Hulley ◽  
...  
Keyword(s):  
Land Surface ◽  
Thermal Emission ◽  
Atmospheric Sounding ◽  
Stable Representation ◽  
Improved Stability ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Processing Errors

The Combined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) MODIS (Moderate Resolution Imaging Spectroradiometer) Emissivity over Land (CAMEL) Version 2 (V002) has been available since March 2019 from the NASA LP DAAC (Land Processes Distributed Active Archive Center) and provides global, monthly infrared land surface emissivity and uncertainty at 0.05 degrees (~5 km) resolution. A climatology of the CAMEL V002 product is now available at the same spatial, temporal, and spectral resolution, covering the CAMEL record from 2000 to 2016. Characterization of the climatology over case sites and IGBP (International Geosphere-Biosphere Programme) land cover categories shows the climatology is a stable representation of the monthly CAMEL emissivity. Time series of the monthly CAMEL V002 product show realistic seasonal changes but also reveal subtle artifacts known to be from calibration and processing errors in the MODIS MxD11 emissivity. The use of the CAMEL V002 climatology mitigates many of these time dependent errors by providing an emissivity estimate which represents the complete 16-year record. The CAMEL V002 climatology’s integration into RTTOV (Radiative Transfer for TOVS) v12 is demonstrated through the simulation of IASI (Infrared Atmospheric Sounding Interferometer) radiances. Improved stability in CAMEL Version 3 is expected in the future with the incorporation of the new MxD21 and VIIRS VNP21 emissivity products in MODIS Collection 6.1.

scholarly journals A Slight Temperature Warming Trend Occurred over Lake Ontario from 2001 to 2018

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1315
Author(s):  
Xiaoying Ouyang ◽  
Dongmei Chen ◽  
Shugui Zhou ◽  
Rui Zhang ◽  
Jinxin Yang ◽  
...  
Keyword(s):  
Land Surface ◽  
Lake Ontario ◽  
Kendall Test ◽  
Warming Trend ◽  
Linear Regression Method ◽  
Ground Measurement ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Mean Square Difference

Satellite-derived lake surface water temperature (LSWT) measurements can be used for monitoring purposes. However, analyses based on the LSWT of Lake Ontario and the surrounding land surface temperature (LST) are scarce in the current literature. First, we provide an evaluation of the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LSWT/LST (MOD11A1 and MYD11A1) using in situ measurements near the area of where Lake Ontario, the St. Lawrence River and the Rideau Canal meet. The MODIS datasets agreed well with ground sites measurements from 2015–2017, with an R2 consistently over 0.90. Among the different ground measurement sites, the best results were achieved for Hill Island, with a correlation of 0.99 and centered root mean square difference (RMSD) of 0.73 K for Aqua/MYD nighttime. The validated MODIS datasets were used to analyze the temperature trend over the study area from 2001 to 2018, through a linear regression method with a Mann–Kendall test. A slight warming trend was found, with 95% confidence over the ground sites from 2003 to 2012 for the MYD11A1-Night datasets. The warming trend for the whole region, including both the lake and the land, was about 0.17 K year−1 for the MYD11A1 datasets during 2003–2012, whereas it was about 0.06 K year−1 during 2003–2018. There was also a spatial pattern of warming, but the trend for the lake region was not obviously different from that of the land region. For the monthly trends, the warming trends for September and October from 2013 to 2018 are much more apparent than those of other months.

scholarly journals Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

2014 ◽  
Vol 7 (2) ◽  
pp. 1671-1707
Author(s):  
J. Kala ◽  
J. P. Evans ◽  
A. J. Pitman ◽  
C. B. Schaaf ◽  
M. Decker ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Albedo ◽  
Land Surface Model ◽  
Surface Model ◽  
Parameter Uncertainties ◽  
Australian Continent ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo. We compare results from two offline simulations over the Australian continent, one with prescribed background snow-free and vegetation-free soil albedo derived from MODIS (the control), and the other with a simple parameterisation based on soil moisture and colour. The control simulation shows that CABLE simulates albedo over Australia reasonably well, with differences with MODIS within an acceptable range. Inclusion of the parameterisation for soil albedo however introduced large errors for the near infra red albedo, especially for desert regions of central Australia. These large errors were not fully explained by errors in soil moisture or parameter uncertainties, but are similar to errors in albedo in other land surface models which use the same soil albedo scheme. Although this new parameterisation has introduced larger errors as compared to prescribing soil albedo, dynamic soil moisture-albedo feedbacks are now enabled in CABLE. Future directions for albedo parameterisations development in CABLE are discussed.

Spatiotemporal variability of land surface temperature in north-western Ethiopia

2021 ◽  
Author(s):  
Getachew Bayable ◽  
Getnet Alemu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatiotemporal Variability ◽  
Environmental Challenges ◽  
Annual Variations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
North Western

Abstract The aggravating deforestation, industrialization and urbanization are increasingly becoming the principal causes for environmental challenges worldwide. As a result, satellite-based remote sensing helps to explore the environmental challenges spatially and temporally. This investigation analyzed the spatiotemporal discrepancies in Land Surface Temperature (LST) and the link with elevation in Amhara region, Ethiopia. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST data (2001–2020) was used. The pixel-based linear regression model was employed to explore the spatiotemporal discrepancies of LST changes pixel-wise. Furthermore, Sen's slope and Mann-Kendall were used for determining the extent of temporal shifts of the areal average LST and evaluating trends in areal average LST values, respectively. Coefficient of Variation (CV) was calculated to examine spatial and temporal discrepancies in seasonal and annual LST for each pixel. The distribution of average seasonal LST spatially ranged from 43.45–16.62℃, 39.89–14.59℃, 50.39-21.102℃ and 43.164–20.39℃ for autumn (September-November), summer (June-August), spring (March-May) and winter (December-February) seasons, respectively. The seasonal LST CV varied from1.096-10.72%, 0.7–11.06%, 1.29–14.76% and 2.19–10.35% for average autumn, summer, spring and winter seasons, respectively. The seasonal spatial LST trend varied from − 0.7 − 0.16, -0.4-0.224, 0.6 − 0.19 and − 0.6 − 0.32 for average autumn, summer, spring and winter seasons, respectively. Besides, the annual spatial LST slope varied from − 0.58 − 0.17. An insignificantly declining trend in LST shown at 0.036℃ yr− 1, 0.041℃ yr− 1, 0.074℃ yr− 1, 0.005℃ yr− 1 in autumn, summer, spring and winter seasons (P < 0.05), respectively. Moreover, the annual variations of mean LST decreased insignificantly at 0.046℃ yr− 1. Generally, the LST is tremendously variable in space and time and negatively correlated with an elevation.

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