scholarly journals CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere

2018 ◽  
Vol 11 (4) ◽  
pp. 2485-2500 ◽  
Author(s):  
Anne Garnier ◽  
Thierry Trémas ◽  
Jacques Pelon ◽  
Kam-Pui Lee ◽  
Delphine Nobileau ◽  
...  
Keyword(s):  
Satellite Observation ◽  
Calibration Procedure ◽  
Latitude Range ◽  
Brightness Temperatures ◽  
Depth Analysis ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Individual ◽  
Semi Empirical ◽  
Global Bias

Abstract. Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30∘ N. These biases – of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) – were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30–60∘ N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR–MODIS BTDs in the 30–60∘ N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1–MODIS29. For IIR2–MODIS31 and IIR3–MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3–MODIS32 in June, where the night-minus-day difference is around −0.1 K.

scholarly journals CALIPSO IIR Version 2 Level 1b calibrated radiances: analysis and reduction of residual biases in the Northern Hemisphere

2018 ◽  
Author(s):  
Anne Garnier ◽  
Thierry Trémas ◽  
Jacques Pelon ◽  
Kam-Pui Lee ◽  
Delphine Nobileau ◽  
...  
Keyword(s):  
Satellite Observation ◽  
Calibration Procedure ◽  
Latitude Range ◽  
Brightness Temperatures ◽  
Depth Analysis ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Individual ◽  
Semi Empirical ◽  
Global Bias

Abstract. A new Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) onboard the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases, of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3), were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30° N-60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR-MODIS BTDs in the 30° N-60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1-MODIS29. For IIR2-MODIS31 and IIR3-MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3-MODIS32 in June where the night-minus-day difference is around −0.1 K.

Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data

2016 ◽  
Vol 29 (17) ◽  
pp. 6065-6083 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Cloud Amount ◽  
Satellite Observation ◽  
Skill Score ◽  
Global Climate Models ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Cloud cover is one of the largest uncertainties in model predictions of the future Arctic climate. Previous studies have shown that cloud amounts in global climate models and atmospheric reanalyses vary widely and may have large biases. However, many climate studies are based on anomalies rather than absolute values, for which biases are less important. This study examines the performance of five atmospheric reanalysis products—ERA-Interim, MERRA, MERRA-2, NCEP R1, and NCEP R2—in depicting monthly mean Arctic cloud amount anomalies against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2000 to 2014 and against Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations from 2006 to 2014. All five reanalysis products exhibit biases in the mean cloud amount, especially in winter. The Gerrity skill score (GSS) and correlation analysis are used to quantify their performance in terms of interannual variations. Results show that ERA-Interim, MERRA, MERRA-2, and NCEP R2 perform similarly, with annual mean GSSs of 0.36/0.22, 0.31/0.24, 0.32/0.23, and 0.32/0.23 and annual mean correlation coefficients of 0.50/0.51, 0.43/0.54, 0.44/0.53, and 0.50/0.52 against MODIS/CALIPSO, indicating that the reanalysis datasets do exhibit some capability for depicting the monthly mean cloud amount anomalies. There are no significant differences in the overall performance of reanalysis products. They all perform best in July, August, and September and worst in November, December, and January. All reanalysis datasets have better performance over land than over ocean. This study identifies the magnitudes of errors in Arctic mean cloud amounts and anomalies and provides a useful tool for evaluating future improvements in the cloud schemes of reanalysis products.

scholarly journals Aerosol Characteristics and Their Impact on the Himalayan Energy Budget

2021 ◽  
Vol 14 (1) ◽  
pp. 179
Author(s):  
Kesar Chand ◽  
Jagdish Chandra Kuniyal ◽  
Shruti Kanga ◽  
Raj Paul Guleria ◽  
Gowhar Meraj ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Radiative Forcing ◽  
Satellite Observation ◽  
Transfer Model ◽  
Hysplit Model ◽  
Aerosol Radiative Forcing ◽  
Alpine Regions ◽  
Himalayan Glaciers ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

The extensive work on the increasing burden of aerosols and resultant climate implications shows a matter of great concern. In this study, we investigate the aerosol optical depth (AOD) variations in the Indian Himalayan Region (IHR) between its plains and alpine regions and the corresponding consequences on the energy balance on the Himalayan glaciers. For this purpose, AOD data from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD-L3), Aerosol Robotic Network (AERONET), India, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) were analyzed. Aerosol radiative forcing (ARF) was assessed using the atmospheric radiation transfer model (RTM) integrated into AERONET inversion code based on the Discrete Ordinate Radiative Transfer (DISORT) module. Further, air mass trajectory over the entire IHR was analyzed using a hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We estimated that between 2001 and 2015, the monthly average ARF at the surface (ARFSFC), top of the atmosphere (ARFTOA), and atmosphere (ARFATM) were −89.6 ± 18.6 Wm−2, −25.2 ± 6.8 Wm−2, and +64.4 ± 16.5 Wm−2, respectively. We observed that during dust aerosol transport days, the ARFSFC and TOA changed by −112.2 and −40.7 Wm−2, respectively, compared with low aerosol loading days, thereby accounting for the decrease in the solar radiation by 207% reaching the surface. This substantial decrease in the solar radiation reaching the Earth’s surface increases the heating rate in the atmosphere by 3.1-fold, thereby acting as an additional forcing factor for accelerated melting of the snow and glacier resources of the IHR.

Comparison of NOAA's Operational AVHRR-Derived Cloud Amount to Other Satellite-Derived Cloud Climatologies

2004 ◽  
Vol 17 (24) ◽  
pp. 4805-4822 ◽  
Author(s):  
Sarah M. Thomas ◽  
Andrew K. Heidinger ◽  
Michael J. Pavolonis
Keyword(s):  
High Resolution ◽  
Phase 1 ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Detection Scheme ◽  
Noaa Avhrr ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Individual ◽  
Cloud Mask

Abstract A comparison is made between a new operational NOAA Advanced Very High Resolution Radiometer (AVHRR) global cloud amount product to those from established satellite-derived cloud climatologies. The new operational NOAA AVHRR cloud amount is derived using the cloud detection scheme in the extended Clouds from AVHRR (CLAVR-x) system. The cloud mask within CLAVR-x is a replacement for the Clouds from AVHRR phase 1 (CLAVR-1) cloud mask. Previous analysis of the CLAVR-1 cloud climatologies reveals that its utility for climate studies is reduced by poor high-latitude performance and the inability to include data from the morning orbiting satellites. This study demonstrates, through comparison with established satellite-derived cloud climatologies, the ability of CLAVR-x to overcome the two main shortcomings of the CLAVR-1-derived cloud climatologies. While systematic differences remain in the cloud amounts from CLAVR-x and other climatologies, no evidence is seen that these differences represent a failure of the CLAVR-x cloud detection scheme. Comparisons for July 1995 and January 1996 indicate that for most latitude zones, CLAVR-x produces less cloud than the International Satellite Cloud Climatology Project (ISCCP) and the University of Wisconsin High Resolution Infrared Radiation Sounder (UW HIRS). Comparisons to the Moderate Resolution Imaging Spectroradiometer (MODIS) for 1–8 April 2003 also reveal that CLAVR-x tends to produce less cloud. Comparison of the seasonal cycle (July–January) of cloud difference with ISCCP, however, indicates close agreement. It is argued that these differences may be due to the methodology used to construct a cloud amount from the individual pixel-level cloud detection results. Overall, the global cloud amounts from CLAVR-x appear to be an improvement over those from CLAVR-1 and compare well to those from established satellite cloud climatologies. The CLAVR-x cloud detection results have been operational since late 2003 and are available in real time from NOAA.

scholarly journals Dust altitude and infrared optical depth from AIRS

2004 ◽  
Vol 4 (7) ◽  
pp. 1813-1822 ◽  
Author(s):  
C. Pierangelo ◽  
A. Chédin ◽  
S. Heilliette ◽  
N. Jacquinet-Husson ◽  
R. Armante
Keyword(s):  
Optical Depth ◽  
Current Knowledge ◽  
Saharan Dust ◽  
Space Distribution ◽  
High Spectral Resolution ◽  
Brightness Temperatures ◽  
Moderate Resolution ◽  
Sensitivity Studies ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. We show that mineral dust optical depth and altitude can be retrieved from the Aqua - Advanced Infrared Radiation Sounder (AIRS) measurements. Sensitivity studies performed with a high spectral resolution radiative transfer code show that dust effect on brightness temperatures may reach about 10 Kelvins for some channels. Using a Look-Up-Table approach, we retrieve not only the 10 µm optical depth but also the altitude of Saharan dust layer, above the Atlantic Ocean, from April to September 2003. A key point of our method is its ability to retrieve dust altitude from satellite observations. The time and space distribution of the optical depth is in good agreement with the Moderate resolution Imaging Spectroradiometer (MODIS) products. Comparing MODIS and AIRS aerosol optical depths, we find that the ratio between infrared and visible optical depths decreases during transport from 0.35 to 0.22, revealing a loss in coarse particles caused by gravitational settling. The evolution of dust altitude from spring to summer is in agreement with current knowledge on transport seasonality.

scholarly journals CORRECTION FOR THE CIRRUS CLOUD TOP HEIGHT OF MODIS BASED ON CALIPSO IN BEIJING-TIANJIN-HEBEI REGION

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 203-210
Author(s):  
B. Y. Yang ◽  
J. Liu ◽  
X. Jia
Keyword(s):  
Remote Sensing ◽  
Satellite Observation ◽  
Orthogonal Polarization ◽  
Cirrus Cloud ◽  
Weather System ◽  
Cloud Optical Depth ◽  
Lower Cloud ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

Abstract. Cirrus plays an important role in atmospheric radiation. It affects weather system and climate change. Satellite remote sensing is an important kind of observation for cloud. As a passive remote sensing instrument, large bias was found for thin cirrus cloud top height retrieval from MODIS (Moderate Resolution Imaging Spectroradiometer). Comparatively, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) aboard CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) which is an active remote sensing instrument can acquire more accurate characteristics of thin cirrus cloud. In this study, CALIPSO cirrus cloud top height data was used to correct MODIS cirrus cloud top height. The data analysis area was selected in Beijing-Tianjin-Hebei region and data came from 2013 to 2017. Linear fitting method was selected based on cross-validation method between MODIS and CALIPSO data. The results shows that the difference between MODIS and CALIPSO changes from −3~2 km to −2.0~2.5 km, and the maximum difference changes from about −0.8 km to about 0.2 km. In the context of different vertical levels and cloud optical depth, MODIS cirrus cloud top height is improved after correcting, which is more obvious at lower cloud top height and optical thinner cirrus.

scholarly journals Analysis of global three-dimensional aerosol structure with spectral radiance matching

2019 ◽  
Vol 12 (12) ◽  
pp. 6541-6556 ◽  
Author(s):  
Dong Liu ◽  
Sijie Chen ◽  
Chonghui Cheng ◽  
Howard W. Barker ◽  
Changzhe Dong ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Satellite Observation ◽  
Eastern Coast ◽  
Spectral Radiance ◽  
Ground Track ◽  
Vertical Distributions ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ground Based Lidar ◽  
Relative Errors

Abstract. A method is assessed which expands aerosol vertical profiles inferred from nadir-pointing lidars to cross-track locations next to nadir columns. This is achieved via matching of passive radiances at off-nadir locations with their counterparts that are collocated with lidar data. This spectral radiance matching (SRM) method is tested using profiles inferred from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations and collocated Moderate Resolution Imaging Spectroradiometer (MODIS) passive imagery for the periods 10–25 April and 14–29 September 2015. CALIPSO profiles are expanded out to 100 km on both sides of the daytime ground track. Reliability of constructed profiles that are removed from the ground track by number of kilometers are tested by requiring the algorithm to reconstruct profiles using only profiles that are removed from it along track by more than the number of kilometers. When sufficient numbers of pixels and columns are available, the SRM method can correctly match ∼75 % and ∼68 % of aerosol vertical structure at distances of 30 and 100 km from the ground track, respectively. The construction algorithm is applied to the eastern coast of Asia during spring 2015. Vertical distributions of different aerosol subtypes indicate that the region was dominated by dust and polluted dust transported from the continent. It is shown that atmospheric profiles and aerosol optical depth (AOD) inferred from ground-based measurements agree with those constructed by the SRM method. For profiles, the relative errors between those measured by ground-based lidar and those constructed in the surrounding area are similar to the relative errors between the ground-based station and CALIPSO overpass at the closest distance. For AOD, the measurements from the ground-based network agree with those inferred from constructed aerosol structure better than direct observations from CALIPSO and close to those inferred from MODIS radiances.

scholarly journals The Spatial–Spectral–Environmental Extraction Endmember Algorithm and Application in the MODIS Fractional Snow Cover Retrieval

2020 ◽  
Vol 12 (22) ◽  
pp. 3693
Author(s):  
Hongyu Zhao ◽  
Xiaohua Hao ◽  
Jian Wang ◽  
Hongyi Li ◽  
Guanghui Huang ◽  
...  
Keyword(s):  
Snow Cover ◽  
Absolute Error ◽  
Satellite Observation ◽  
Landsat 8 ◽  
Endmember Extraction ◽  
Analysis Model ◽  
Fractional Snow Cover ◽  
Extraction Algorithm ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Endmember extraction is a primary and indispensable component of the spectral mixing analysis model applicated to quantitatively retrieve fractional snow cover (FSC) from satellite observation. In this study, a new endmember extraction algorithm, the spatial–spectral–environmental (SSE) endmember extraction algorithm, is developed, in which spatial, spectral and environmental information are integrated together to automatically extract different types of endmembers from moderate resolution imaging spectroradiometer (MODIS) images. Then, combining the linear spectral mixture analysis model (LSMA), the SSE endmember extraction algorithm is practically applied to retrieve FSC from standard MODIS surface reflectance products in China. The new algorithm of MODIS FSC retrieval is named as SSEmod. The accuracy of SSEmod is quantitatively validated with 16 higher spatial-resolution FSC maps derived from Landsat 8 binary snow cover maps. Averaged over all regions, the average root-mean-square-error (RMSE) and mean absolute error (MAE) are 0.136 and 0.092, respectively. Simultaneously, we also compared the SSEmod with MODImLAB, MODSCAG and MOD10A1. In all regions, the average RMSE of SSEmod is improved by 2.3%, 2.6% and 5.3% compared to MODImLAB for 0.157, MODSCAG for 0.157 and MOD10A1 for 0.189. Therefore, our SSE endmember extraction algorithm is reliable for the MODIS FSC retrieval and may be also promising to apply other similar satellites in view of its accuracy and efficiency.

scholarly journals Joint 3D-Wind Retrievals with Stereoscopic Views from MODIS and GOES

2019 ◽  
Vol 11 (18) ◽  
pp. 2100 ◽  
Author(s):  
James L. Carr ◽  
Dong L. Wu ◽  
Robert E. Wolfe ◽  
Houria Madani ◽  
Guoqing (Gary) Lin ◽  
...  
Keyword(s):  
Height Measurement ◽  
Wildfire Smoke ◽  
Brightness Temperatures ◽  
Potential Applications ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Wind Retrievals ◽  
Atmospheric Motion Vectors ◽  
Along Track

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

scholarly journals Analysis of co-located MODIS and CALIPSO observations near clouds

2012 ◽  
Vol 5 (2) ◽  
pp. 389-396 ◽  
Author(s):  
T. Várnai ◽  
A. Marshak
Keyword(s):  
Multispectral Imaging ◽  
Satellite Observation ◽  
Orthogonal Polarization ◽  
Combining Data ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Statistical Relationships ◽  
Aerosol Cloud Interactions ◽  
Aerosol Radiative Effects ◽  
The Impact

Abstract. This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the MODIS (MODerate resolution Imaging Spectroradiometer) imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar measurements about the systematic aerosol changes that occur near clouds. The statistical analysis of a yearlong dataset of co-located global maritime observations from the Aqua and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellites reveals that MODIS's multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on Aqua and CALIPSO yield very similar pictures, and that the discrepancies – due mainly to wind drift and differences in view angle – do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, MODIS reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in MODIS and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when MODIS cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4–5 km range.

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