Study of Atmospheric Radiative Properties at Infrared Bands under Ice Clouds Based on Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Observation

AbstractThis paper summarizes the Collection-6 refinements in the Moderate Resolution Imaging Spectroradiometer (MODIS) operational cloud-top properties algorithm. The focus is on calibration improvements and on cloud macrophysical properties including cloud-top pressure–temperature–height and cloud thermodynamic phase. The cloud phase is based solely on infrared band measurements. In addition, new parameters will be provided in Collection 6, including cloud-top height and a flag for clouds near the tropopause. The cloud parameters are improved primarily through 1) improved knowledge of the spectral response functions for the MODIS 15-μm carbon dioxide bands gleaned from comparison of coincident MODIS and Atmospheric Infrared Sounder (AIRS) radiance measurements and 2) continual comparison of global MODIS and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) instantaneous cloud products throughout the course of algorithm refinement. Whereas the cloud-top macrophysical parameters were provided through Collection 5 solely at 5-km spatial resolution, these parameters will be available additionally at 1-km spatial resolution in Collection 6.

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Tropospheric carbon monoxide variability from AIRS and IASI under clear and cloudy conditions

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-16337-2013 ◽

2013 ◽

Vol 13 (6) ◽

pp. 16337-16366 ◽

Cited By ~ 1

Author(s):

J. Warner ◽

F. Carminati ◽

Z. Wei ◽

W. Lahoz ◽

J.-L. Attié

Keyword(s):

Carbon Monoxide ◽

Emission Inventory ◽

Correlation Coefficients ◽

Retrieval Algorithm ◽

Atmospheric Infrared Sounder ◽

Fire Emissions ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Cloud Mask

Abstract. We study the Carbon Monoxide (CO) variability in the last decade measured by NASA's Atmospheric InfraRed Sounder (AIRS) on the Earth Observing Systems (EOS)/Aqua satellite and Europe's Infrared Atmospheric Sounder Interferometer (IASI) on MetOp platform. The focus of this study is to analyze CO variability and short-term trends separately for background CO and new emissions based on a new statistical approach. The AIRS Level 2 (L2) retrieval algorithm, as well as the IASI products from NOAA, utilizes cloud clearing to treat cloud contaminations in the signals; and this increases the data coverage significantly to a yield of more than 50% of the total measurements (Susskind et al., 2003). We first study if the cloud clearing affects CO retrievals and the subsequent trend studies by using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) (Ackerman et al., 1998) cloud mask to identify AIRS clear sky scenes. We then separate AIRS CO data into clear and cloud-cleared scenes and into background and new emissions, respectively. Furthermore, we carry out a similar study for the IASI CO and discuss the consistency with AIRS. We validate the CO variability of the emissions developed from AIRS against other emission inventory databases (i.e., Global Fire Emissions Database – GFED3 and the MACC/CityZEN UE – MACCity) and calculate that the correlation coefficients between the AIRS CO emissions and the emission inventory databases are 0.726 for the Northern Hemisphere (NH) and 0.915 for the Southern Hemisphere (SH).

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Technical note: a new day- and night-time Meteosat Second Generation Cirrus Detection Algorithm MeCiDA

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-7-10933-2007 ◽

2007 ◽

Vol 7 (4) ◽

pp. 10933-10969

Author(s):

W. Krebs ◽

H. Mannstein ◽

L. Bugliaro ◽

B. Mayer

Keyword(s):

Second Generation ◽

Detection Efficiency ◽

Detection Algorithm ◽

Technical Note ◽

High Temporal Resolution ◽

Night Time ◽

Ice Clouds ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. A new cirrus detection algorithm for the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG), MeCiDA, is presented. The algorithm uses the seven infrared channels of SEVIRI and thus provides a consistent scheme for cirrus detection at day and night. MeCiDA combines morphological and multi-spectral threshold tests and detects optically thick and thin ice clouds. The thresholds were determined by a comprehensive theoretical study using radiative transfer simulations for various atmospheric situations as well as by manually evaluating actual satellite observations. The retrieved cirrus masks have been validated by comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) Cirrus Reflection Flag. To study possible seasonal variations in the performance of the algorithm, one scene per month of the year 2004 was randomly selected and compared with the standard MODIS cirrus product. 81% of the pixels were classified identically by both algorithms. On average, MeCiDA detected 60% of the MODIS cirrus. A lower detection efficiency is to be expected for MeCiDA, as the spatial resolution of MODIS is considerably better and as we used only the thermal infrared channels in contrast to the MODIS algorithm which uses infrared and visible radiances. The advantage of MeCiDA compared to retrievals for polar orbiting instruments or previous geostationary satellites is that it allows to derive quantitative data every 15 min, 24 h a day. This high temporal resolution allows the study of diurnal variations and life cycle aspects. MeCiDA is fast enough for near real-time applications.

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Cloud phase characteristics over Southeast Asia from A-Train satellite observations

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-8267-2020 ◽

2020 ◽

Vol 20 (13) ◽

pp. 8267-8291

Author(s):

Yulan Hong ◽

Larry Di Girolamo

Keyword(s):

Southeast Asia ◽

Southern Oscillation ◽

Lower Troposphere ◽

Satellite Observations ◽

Ice Clouds ◽

Spectral Signatures ◽

Clear Sky ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. This study examines the climatology of cloud phase over Southeast Asia (SEA) based on A-Train satellite observations. Using the combined CloudSat–CALIPSO (CC) data, five main cloud groups are investigated: ice-only, ice-above-liquid, liquid-only, ice-above-mixed, and mixed-only clouds that have annual mean frequencies of 28.6 %, 20.1 %, 16.0 %, 9.3 %, and 6.7 %, respectively. Liquid-only clouds tend to occur in relatively cold, dry, and stable lower troposphere. The other four cloud groups appear more frequently in relatively warm, humid, and unstable conditions, and their seasonal distributions move with the Asian monsoon and the Intertropical Convergence Zone (ITCZ). Liquid clouds are found to be highly inhomogeneous based on the heterogeneity index (Hσ) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), while ice-only and mixed-only clouds are often very smooth. Ice-above-liquid clouds are more heterogeneous than ice-only clouds owing to ice clouds being optically thin. We demonstrate that the distribution of clear-sky Hσ has a long tail towards heterogeneous values that are caused by undetected subpixel cloud within both CC and MODIS datasets. The reflectance at 0.645 µm (R0.645) and brightness temperature at 11 µm (BT11) of CC ice-only, liquid-only, and ice-above-liquid clouds show peak frequencies near that of clear sky (R0.645∼0.02; BT11∼294 K), which explains why up to 30 % of these CC cloud groups are classified as clear by MODIS. In contrast, mixed-only clouds are thick (average top ∼13 km), bright (average R0.645∼0.6), and cold (average BT11 ∼234 K). Cloud phase comparison between CC and MODIS reveals only modest agreement, with the best agreement (73 %) occurring between CC ice-above-mixed and MODIS ice clouds. The intraseasonal and interannual behaviors of the all-sky Hσ and spectral signatures follow that of cloud phase and vary with the Madden–Julian oscillation (MJO) and the El Niño–Southern Oscillation (ENSO) phases.

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Surface Irradiances Consistent with CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances

Journal of Climate ◽

10.1175/jcli-d-12-00436.1 ◽

2013 ◽

Vol 26 (9) ◽

pp. 2719-2740 ◽

Cited By ~ 261

Author(s):

Seiji Kato ◽

Norman G. Loeb ◽

Fred G. Rose ◽

David R. Doelling ◽

David A. Rutan ◽

...

Keyword(s):

Radiant Energy ◽

Energy System ◽

Global Scale ◽

Atmospheric Infrared Sounder ◽

Surface Irradiance ◽

Uncertainty Estimates ◽

Moderate Resolution ◽

Resolution Imaging ◽

Rms Error ◽

Moderate Resolution Imaging Spectroradiometer

Abstract The estimate of surface irradiance on a global scale is possible through radiative transfer calculations using satellite-retrieved surface, cloud, and aerosol properties as input. Computed top-of-atmosphere (TOA) irradiances, however, do not necessarily agree with observation-based values, for example, from the Clouds and the Earth’s Radiant Energy System (CERES). This paper presents a method to determine surface irradiances using observational constraints of TOA irradiance from CERES. A Lagrange multiplier procedure is used to objectively adjust inputs based on their uncertainties such that the computed TOA irradiance is consistent with CERES-derived irradiance to within the uncertainty. These input adjustments are then used to determine surface irradiance adjustments. Observations by the Atmospheric Infrared Sounder (AIRS), Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) that are a part of the NASA A-Train constellation provide the uncertainty estimates. A comparison with surface observations from a number of sites shows that the bias [root-mean-square (RMS) difference] between computed and observed monthly mean irradiances calculated with 10 years of data is 4.7 (13.3) W m−2 for downward shortwave and −2.5 (7.1) W m−2 for downward longwave irradiances over ocean and −1.7 (7.8) W m−2 for downward shortwave and −1.0 (7.6) W m−2 for downward longwave irradiances over land. The bias and RMS error for the downward longwave and shortwave irradiances over ocean are decreased from those without constraint. Similarly, the bias and RMS error for downward longwave over land improves, although the constraint does not improve downward shortwave over land. This study demonstrates how synergetic use of multiple instruments (CERES, MODIS, CALIPSO, CloudSat, AIRS, and geostationary satellites) improves the accuracy of surface irradiance computations.

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Comparing MODIS and AIRS Infrared-Based Cloud Retrievals

Journal of Applied Meteorology and Climatology ◽

10.1175/2010jamc2603.1 ◽

2011 ◽

Vol 50 (5) ◽

pp. 1057-1072 ◽

Cited By ~ 12

Author(s):

Shaima L. Nasiri ◽

H. Van T. Dang ◽

Brian H. Kahn ◽

Eric J. Fetzer ◽

Evan M. Manning ◽

...

Keyword(s):

Brightness Temperature ◽

Single Layer ◽

Satellite System ◽

Atmospheric Infrared Sounder ◽

Retrieval Method ◽

Spatial Response ◽

Comparison Approach ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

AbstractComparisons are described for infrared-derived cloud products retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) using measured spatial response functions obtained from prelaunch AIRS calibration. One full day (1 January 2005) of global collection-5 MODIS and version-5 AIRS retrievals of cloud-top temperature Tc, effective cloud fraction f, and derived effective brightness temperature Tb,e is investigated. Comparisons of Tb,e demonstrate that MODIS and AIRS are essentially radiatively consistent and that MODIS Tb,e is 0.62 K higher than AIRS Tb,e for all scenes, increasing to 1.43 K for cloud described by AIRS as single layer and decreasing to 0.50 K for two-layer clouds. Somewhat larger differences in Tc and f are observed between the two instruments. The magnitudes of differences depend partly on whether MODIS uses a CO2-slicing or 11-μm brightness temperature window retrieval method. Some cloud- and regime-type differences and similarities between AIRS and MODIS cloud products are traceable to the assumptions made about the number of cloud layers in AIRS and also to the MODIS retrieval method. This (partially) holistic comparison approach should be useful for ongoing algorithm refinements, rigorous assessments of climate applicability, and establishment of the capability of synergistic MODIS and AIRS retrievals for improved cloud quantities and also should be useful for future observations to be made by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP).

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Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16081379 ◽

2019 ◽

Vol 16 (8) ◽

pp. 1379 ◽

Cited By ~ 4

Author(s):

Zhenzhen Wang ◽

Jianjun Zhao ◽

Jiawen Xu ◽

Mingrui Jia ◽

Han Li ◽

...

Keyword(s):

Northeast China ◽

Arable Land ◽

Pollution Index ◽

Air Pollutant ◽

Thermal Anomalies ◽

Pollutant Concentrations ◽

Moderate Resolution ◽

Resolution Imaging ◽

Straw Burning ◽

Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

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A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

Remote Sensing ◽

10.3390/rs13152895 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2895

Author(s):

Maria Gavrouzou ◽

Nikolaos Hatzianastassiou ◽

Antonis Gkikas ◽

Christos J. Lolis ◽

Nikolaos Mihalopoulos

Keyword(s):

Mediterranean Basin ◽

Eastern Mediterranean ◽

Mean Value ◽

Early Spring ◽

Dust Aerosol ◽

Ozone Monitoring Instrument ◽

Central Mediterranean ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

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