scholarly journals Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train

2016 ◽  
Vol 29 (6) ◽  
pp. 2023-2040 ◽  
Author(s):  
Qing Yue ◽  
Brian H. Kahn ◽  
Eric J. Fetzer ◽  
Mathias Schreier ◽  
Sun Wong ◽  
...  

Abstract The authors present a new method to derive both the broadband and spectral longwave observation-based cloud radiative kernels (CRKs) using cloud radiative forcing (CRF) and cloud fraction (CF) for different cloud types using multisensor A-Train observations and MERRA data collocated on the pixel scale. Both observation-based CRKs and model-based CRKs derived from the Fu–Liou radiative transfer model are shown. Good agreement between observation- and model-derived CRKs is found for optically thick clouds. For optically thin clouds, the observation-based CRKs show a larger radiative sensitivity at TOA to cloud-cover change than model-derived CRKs. Four types of possible uncertainties in the observed CRKs are investigated: 1) uncertainties in Moderate Resolution Imaging Spectroradiometer cloud properties, 2) the contributions of clear-sky changes to the CRF, 3) the assumptions regarding clear-sky thresholds in the observations, and 4) the assumption of a single-layer cloud. The observation-based CRKs show the TOA radiative sensitivity of cloud types to unit cloud fraction change as observed by the A-Train. Therefore, a combination of observation-based CRKs with cloud changes observed by these instruments over time will provide an estimate of the short-term cloud feedback by maintaining consistency between CRKs and cloud responses to climate variability.

2016 ◽  
Vol 17 (7) ◽  
pp. 1999-2011 ◽  
Author(s):  
Steven D. Miller ◽  
Fang Wang ◽  
Ann B. Burgess ◽  
S. McKenzie Skiles ◽  
Matthew Rogers ◽  
...  

Abstract Runoff from mountain snowpack is an important freshwater supply for many parts of the world. The deposition of aeolian dust on snow decreases snow albedo and increases the absorption of solar irradiance. This absorption accelerates melting, impacting the regional hydrological cycle in terms of timing and magnitude of runoff. The Moderate Resolution Imaging Spectroradiometer (MODIS) Dust Radiative Forcing in Snow (MODDRFS) satellite product allows estimation of the instantaneous (at time of satellite overpass) surface radiative forcing caused by dust. While such snapshots are useful, energy balance modeling requires temporally resolved radiative forcing to represent energy fluxes to the snowpack, as modulated primarily by varying cloud cover. Here, the instantaneous MODDRFS estimate is used as a tie point to calculate temporally resolved surface radiative forcing. Dust radiative forcing scenarios were considered for 1) clear-sky conditions and 2) all-sky conditions using satellite-based cloud observations. Comparisons against in situ stations in the Rocky Mountains show that accounting for the temporally resolved all-sky solar irradiance via satellite retrievals yields a more representative time series of dust radiative effects compared to the clear-sky assumption. The modeled impact of dust on enhanced snowmelt was found to be significant, accounting for nearly 50% of the total melt at the more contaminated station sites. The algorithm is applicable to regional basins worldwide, bearing relevance to both climate process research and the operational management of water resources.


Author(s):  
K. H. Lee ◽  
K. T. Lee

The paper presents currently developing method of volcanic ash detection and retrieval for the Geostationary Korea Multi-Purpose Satellite (GK-2A). With the launch of GK-2A, aerosol remote sensing including dust, smoke, will begin a new era of geostationary remote sensing. The Advanced Meteorological Imager (AMI) onboard GK-2A will offer capabilities for volcanic ash remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Based on the physical principles for the current polar and geostationary imagers are modified in the algorithm. Volcanic ash is estimated in detection processing from visible and infrared channel radiances, and the comparison of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every 15 min for volcanic ash for pixel sizes of 2 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously, both over water and land. The algorithm has been tested with proxy data generated from existing satellite observations and forward radiative transfer simulations. Operational assessment of the algorithm will be made after the launch of GK-2A scheduled in 2018.


2010 ◽  
Vol 10 (5) ◽  
pp. 12629-12664 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods were employed. First, a ray-matching technique was used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest were taken into account for the comparison. Second, collocated MODIS cloud products were used as inputs to a radiative transfer model to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, the three-dimensional radiative effect of clouds was taken into account and was subtracted from the simulated reflectance to remove the simulation bias caused by the plane-parallel assumption. Third, an independent method used the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although the three methods were not in perfect agreement, the results suggest that calibration accuracies were within 5–10% for the Meteosat-8 0.640-μm channel, 4–9% for the Meteosat-9 0.640-μm channel, and up to 20% for the MTSAT-1R 0.724-μm channel. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.


2009 ◽  
Vol 66 (12) ◽  
pp. 3721-3731 ◽  
Author(s):  
Joonsuk Lee ◽  
Ping Yang ◽  
Andrew E. Dessler ◽  
Bo-Cai Gao ◽  
Steven Platnick

Abstract To understand the radiative impact of tropical thin cirrus clouds, the frequency of occurrence and optical depths of these clouds have been derived. “Thin” cirrus clouds are defined here as being those that are not detected by the operational Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask, corresponding to an optical depth value of approximately 0.3 or smaller, but that are detectable in terms of the cirrus reflectance product based on the MODIS 1.375-μm channel. With such a definition, thin cirrus clouds were present in more than 40% of the pixels flagged as “clear sky” by the operational MODIS cloud mask algorithm. It is shown that these thin cirrus clouds are frequently observed in deep convective regions in the western Pacific. Thin cirrus optical depths were derived from the cirrus reflectance product. Regions of significant cloud fraction and large optical depths were observed in the Northern Hemisphere during the boreal spring and summer and moved southward during the boreal autumn and winter. The radiative effects of tropical thin cirrus clouds were studied on the basis of the retrieved cirrus optical depths, the atmospheric profiles derived from the Atmospheric Infrared Sounder (AIRS) observations, and a radiative transfer model in conjunction with a parameterization of ice cloud spectral optical properties. To understand how these clouds regulate the radiation field in the atmosphere, the instantaneous net fluxes at the top of the atmosphere (TOA) and at the surface were calculated. The present study shows positive and negative net forcings at the TOA and at the surface, respectively. The positive (negative) net forcing at the TOA (surface) is due to the dominance of longwave (shortwave) forcing. Both the TOA and surface forcings are in a range of 0–20 W m−2, depending on the optical depths of thin cirrus clouds.


2011 ◽  
Vol 24 (16) ◽  
pp. 4435-4450 ◽  
Author(s):  
Shan Zeng ◽  
Frédéric Parol ◽  
Jérôme Riedi ◽  
Céline Cornet ◽  
François Thieuleux

Abstract The Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL) and Aqua are two satellites on sun-synchronous orbits in the A-Train constellation. Aboard these two platforms, the Polarization and Directionality of Earth Reflectances (POLDER) and Moderate Resolution Imaging Spectroradiometer (MODIS) provide quasi simultaneous and coincident observations of cloud properties. The similar orbits but different detecting characteristics of these two sensors call for a comparison between the derived datasets to identify and quantify potential uncertainties in retrieved cloud properties. To focus on the differences due to different sensor spatial resolution and coverage, while minimizing sampling and weighting issues, the authors have recomputed monthly statistics directly from the respective official level-2 products. The authors have developed a joint dataset that contains both POLDER and MODIS level-2 cloud products collocated on a common sinusoidal grid. The authors have then computed and analyzed monthly statistics of cloud fractions corresponding either to the total cloud cover or to the “retrieved” cloud fraction for which cloud optical properties are derived. These simple yet crucial cloud statistics need to be clearly understood to allow further comparison work of the other cloud parameters. From this study, it is demonstrated that on average POLDER and MODIS datasets capture correctly the main characteristics of global cloud cover and provide similar spatial distributions and temporal variations. However, each sensor has its own advantages and weaknesses in discriminating between clear and cloudy skies in particular situations. Also it is shown that significant differences exist between the MODIS total cloud fraction (day mean) and the “retrieved” cloud fraction (combined mean). This study found a global negative difference of about 10% between POLDER and MODIS day-mean cloud fraction. On the contrary, a global positive difference of about 10% exists between POLDER and MODIS combined-mean cloud fraction. These statistical biases show both global and regional distributions that can be driven by sensors characteristics, environmental factors, and also carry potential information on cloud cover structure. These results provide information on the quality of cloud cover derived from POLDER and MODIS and should be taken into account for the use of other cloud products.


2018 ◽  
Author(s):  
Falguni Patadia ◽  
Robert Levy ◽  
Shana Mattoo

Abstract. Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon Moderate Resolution Imaging Spectroradiometer (MODIS, onboard Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, onboard Suomi-NPP) sensors, use wavelength bands in “window” regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper we use High-resolution TRANsmission (HITRAN) database and Line-by-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are “similar”, they are different enough that applying MODIS specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases up to 0.07. As recent studies are attempting to create a long-term data record by joining multiple satellite datasets, including MODIS and VIIRS, the consistency of gas correction becomes even more crucial.


2019 ◽  
Vol 36 (3) ◽  
pp. 369-386 ◽  
Author(s):  
Seung-Hee Ham ◽  
Seiji Kato ◽  
Fred G. Rose

AbstractBecause of the limitation of the spatial resolution of satellite sensors, satellite pixels identified as cloudy are often partly cloudy. For the first time, this study demonstrates the bias in shortwave (SW) broadband irradiances for partly cloudy pixels when the cloud optical depths are retrieved with an overcast and homogeneous assumption, and subsequently, the retrieved values are used for the irradiance computations. The sign of the SW irradiance bias is mainly a function of viewing geometry of the cloud retrieval. The bias in top-of-atmosphere (TOA) upward SW irradiances is positive for small viewing zenith angles (VZAs) <~60° and negative for large VZAs >~60°. For a given solar zenith angle and viewing geometry, the magnitude of the bias increases with the cloud optical depth and reaches a maximum at the cloud fraction between 0.2 and 0.8. The sign of the SW surface net irradiance bias is opposite of the sign of TOA upward irradiance bias, with a similar magnitude. As a result, the bias in absorbed SW irradiances by the atmosphere is smaller than the biases in both TOA and surface irradiances. The monthly mean biases in SW irradiances due to partly cloudy pixels are <1.5 W m−2 when cloud properties are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua.


2005 ◽  
Vol 62 (11) ◽  
pp. 3993-4009 ◽  
Author(s):  
Fu-Lung Chang ◽  
Zhanqing Li

Abstract The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible (0.65 μm) and infrared (11 μm) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth &lt;∼4 (emissivity &lt;∼0.85). For more than two-layer clouds, its validity depends on the thickness of the upper-layer cloud. A preliminary validation is conducted by comparing against ground-based active remote sensing data. Pixel-by-pixel retrievals and error analyses are presented. It is demonstrated that retrievals based on a single-layer assumption can result in systematic biases in the retrieved cloud top and optical properties for overlapped clouds. Such biases can be removed or lessened considerably by applying the new algorithm.


2010 ◽  
Vol 10 (22) ◽  
pp. 11131-11149 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods are employed. Total eight months during the 2004–2007 period are used for SEVIRI, and total seven months during the 2007–2008 period are used for MTSAT-1R. First, a ray-matching technique is used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest are taken into account for the comparison. Second, collocated MODIS cloud products are used as inputs to a radiative transfer model (RTM) to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, cloud three-dimensional (3-D) radiative effect associated with subgrid variations is taken into account using the lognormal-independent column approximation (LN-ICA) to minimize the simulation bias caused by the plane-parallel homogeneous assumption. Third, an independent method uses the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although all three methods are not in perfect agreement, the results suggest that calibration coefficients of Meteosat-8/9 0.640-μm channels are underestimated by 6–7%. On the other hand, the calibration accuracy of MTSAT-1R visible channel appears to be variable with the target reflectance itself because of an underestimate of calibration coefficient (up to 20%) and a non-zero space offset. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.


2021 ◽  
Vol 13 (2) ◽  
pp. 227
Author(s):  
Arthur Elmes ◽  
Charlotte Levy ◽  
Angela Erb ◽  
Dorothy K. Hall ◽  
Ted A. Scambos ◽  
...  

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.


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