scholarly journals Exploration of the MODIS Cloud-Top Property Products for the Investigation of Equatorial Wave Systems

2010 ◽  
Vol 49 (9) ◽  
pp. 2050-2057 ◽  
Author(s):  
Yue Li ◽  
Gerald R. North ◽  
Ping Yang ◽  
Bryan A. Baum

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) observations provide an unprecedented opportunity for studying cloud macrophysical (cloud-top pressure, temperature, height, and phase), microphysical (effective particle size), and optical (optical thickness) properties. Given the length of time these MODIS products have been available, it is found that the cloud products can provide a wealth of information about equatorial wave systems. In this study, more than six years of the MODIS cloud-top properties inferred from the Aqua MODIS observations are used to investigate equatorial waves. It is shown that the high-resolution daily gridded cloud-top temperature product can be used to quantitatively study convective clouds. Various modes of convectively coupled equatorial waves including Kelvin, n = 1 equatorial Rossby, mixed Rossby–gravity, n = 0 eastward inertial-gravity waves, and the Madden–Julian oscillation are identified on the basis of space–time spectral analysis. The application of spectral analysis to cirrus cloud optical thickness, retrieved from MODIS cirrus reflectance, confirms the convective signals at high altitudes. A cluster of Kelvin pulses is found to propagate eastward around the globe at a phase speed approximately 15 m s−1. The Madden–Julian oscillation propagates at a slower speed and is most prominent over the Indian–Pacific Oceans region. The consistency between the present results with those of previous studies demonstrates that the MODIS cloud-top property products are valuable for studying phenomena associated with atmospheric dynamics.

2012 ◽  
Vol 25 (13) ◽  
pp. 4699-4720 ◽  
Author(s):  
Robert Pincus ◽  
Steven Platnick ◽  
Steven A. Ackerman ◽  
Richard S. Hemler ◽  
Robert J. Patrick Hofmann

Abstract The properties of clouds that may be observed by satellite instruments, such as optical thickness and cloud-top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through “instrument simulators,” diagnostic tools that map the model representation to synthetic observations so that differences can be interpreted as model error. But simulators may themselves be restricted by limited information or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP), two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail datasets developed for comparison with global models using ISCCP and MODIS simulators. In nature MODIS observes less midlevel cloudiness than ISCCP, consistent with the different methods used to determine cloud-top pressure; aspects of this difference are reproduced by the simulators. Differences in observed distributions of optical thickness, however, are not captured. The largest differences can be traced to different approaches to partly cloudy pixels, which MODIS excludes and ISCCP treats as homogeneous. These cover roughly 15% of the planet and account for most of the optically thinnest clouds. Instrument simulators cannot reproduce these differences because there is no way to synthesize partly cloudy pixels. Nonetheless, MODIS and ISCCP observations are consistent for all but the optically thinnest clouds, and models can be robustly evaluated using instrument simulators by integrating over the robust subset of observations.


Author(s):  
Daeho Jin ◽  
Lazaros Oreopoulos ◽  
Dongmin Lee ◽  
Jackson Tan ◽  
Nayeong Cho

AbstractIn order to better understand cloud-precipitation relationships, we extend the concept of cloud regimes (CRs) developed from two-dimensional joint histograms of cloud optical thickness and cloud top pressure from the Moderate Resolution Imaging Spectroradiometer (MODIS), to include precipitation information. Taking advantage of the high-resolution Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation dataset, we derive cloud-precipitation “hybrid” regimes by implementing a k-means clustering algorithm with advanced initialization and objective measures to determine the optimal number of clusters. By expressing the variability of precipitation rates within 1-degree grid cells as histograms and varying the relative weight of cloud and precipitation information in the clustering algorithm, we obtain several editions of hybrid cloud-precipitation regimes (CPRs), and examine their characteristics.In the deep tropics, when precipitation is weighted weakly, the cloud part centroids of the hybrid regimes resemble their counterparts of cloud-only regimes, but combined clustering tightens the cloud-precipitation relationship by decreasing each regime’s precipitation variability. As precipitation weight progressively increases, the shape of the cloud part centroids becomes blunter, while the precipitation part sharpens. When cloud and precipitation are weighted equally, the CPRs representing high clouds with intermediate to heavy precipitation exhibit distinct enough features in the precipitation parts of the centroids to allow us to project them onto the 30-min IMERG domain. Such a projection overcomes the temporal sparseness of MODIS cloud observations associated with substantial rainfall, suggesting great application potential for convection-focused studies where characterization of the diurnal cycle is essential.


2009 ◽  
Vol 2 (5) ◽  
pp. 2707-2748 ◽  
Author(s):  
J. Joiner ◽  
A. P. Vasilkov ◽  
P. K. Bhartia ◽  
G. Wind ◽  
S. Platnick ◽  
...  

Abstract. The detection of multiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, and the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from the A-train CloudSat radar. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (12 km×24 km at nadir) and at the 5 km×5 km MODIS resolution for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 5% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (~20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find significantly higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.


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.


2015 ◽  
Vol 54 (5) ◽  
pp. 1009-1020 ◽  
Author(s):  
Ning An ◽  
Kaicun Wang

AbstractClouds determine the amount of solar radiation incident to the surface. Accurately quantifying cloud fraction is of great importance but is difficult to accomplish. Satellite and surface cloud observations have different fields of view (FOVs); the lack of conformity of different FOVs may cause large discrepancies when comparing satellite- and surface-derived cloud fractions. From the viewpoint of surface-incident solar radiation, this paper compares Moderate Resolution Imaging Spectroradiometer (MODIS) level-2 cloud-fraction data with three surface cloud-fraction datasets at five Surface Radiation Network (SURFRAD) sites. The correlation coefficients between MODIS and the surface cloud fractions are in the 0.80–0.91 range and vary at different SURFRAD sites. In a number of cases, MODIS observations show a large cloud-fraction bias when compared with surface data. The variances between MODIS and the surface cloud-fraction datasets are more apparent when small convective or broken clouds exist in the FOVs. The magnitude of the discrepancy between MODIS and surface-derived cloud fractions depends on the satellite’s view zenith angle (VZA). On average, relative to surface cloud-fraction data, MODIS observes a larger cloud fraction at VZA > 40° and a smaller cloud fraction at VZA < 20°. When comparing long-term MODIS averages with surface datasets, Aqua MODIS observes a higher annual mean cloud fraction, likely because convective clouds are better developed in the afternoon when Aqua is observing.


2018 ◽  
Author(s):  
Sarah A. Strode ◽  
Junhua Liu ◽  
Leslie Lait ◽  
Róisín Commane ◽  
Bruce Daube ◽  
...  

Abstract. GEOS-5 forecasts and analyses show considerable skill in predicting and simulating the CO distribution and the timing of CO enhancements observed during the ATom-1 aircraft mission. Using tagged tracers for CO, we find a dominant contribution from non-biomass burning sources along the ATom transects except over the tropical Atlantic, where African biomass burning makes a large contribution to the CO concentration. One of the goals of ATom is to provide a chemical climatology over the oceans, so it is important to consider whether August 2016 was representative of typical summer conditions. Using satellite observations of 700 hPa and column CO from the Measurement of Pollution in the Troposphere (MOPITT) instrument, 215 hPa CO from the Microwave Limb Sounder (MLS), and aerosol optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS), we find that CO concentrations and aerosol optical thickness in August 2016 were within the observed range of the satellite observations, but below the decadal median for many of the regions sampled. This suggests that the ATom-1 measurements may represent relatively clean but not exceptional conditions for lower tropospheric CO.


2012 ◽  
Vol 5 (2) ◽  
pp. 2795-2820 ◽  
Author(s):  
P. R. Colarco ◽  
L. A. Remer ◽  
R. A. Kahn ◽  
R. C. Levy ◽  
E. J. Welton

Abstract. We assess the impact of swath width on the statistics of aerosol optical thickness (AOT) retrieved by satellite, as inferred from observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS). Using collocated AERONET sun photometer observations we develop a correction to the MODIS data to account for calibration and algorithmic view angle dependency in the retrieved AOT. We sub-sample and correct the AOT data from the MODIS Aqua instrument along several candidate swaths of various widths for the years 2003–2011. We find that over ocean the global, annual mean AOT is within ± 0.01 of the full swath AOT for all of our sub-samples. Over land, however, most of our sub-samples are outside of this criterion range in the global, annual mean. Moreover, at smaller spatial and temporal scales we find wide deviation in the sub-sample AOT relative to the full swath over both land and ocean. In all, the sub-sample AOT is within ± 0.01 of the full swath value less than 25% of the time over land, and less than 50% of the time over ocean (less than 35% for all but the widest of our sub-sample swaths). These results suggest that future aerosol satellite missions having only narrow swath views may not sample the true AOT distribution sufficiently to reduce significantly the uncertainty in aerosol direct forcing of climate.


2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Murtadha A. Fadhil ◽  
Kais J. Al-Jumaily

Studying clouds is a top priority among many atmospheric scientists because clouds are one of the greatest unknown factors in predicting changes in the Earth’s climate. Clouds play an important role in maintaining the energy balance because they can reflect, absorb, and radiate energy. The aim of this research is to investigate the properties of clouds over Iraq using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)on board Aqua Satellite for water and ice clouds. The results showed that daily mean cloud top pressure patterns during spring months are higher than other months and cloud top temperature patterns reached their highest values during summer months. The results also indicated that the ice cloud effective particle radius is relatively large during summer while cloud optical thickness assume its largest values in winter months. It was found that the highest values of precipitation rate over Iraq occurred during March to mid-April. Correlation aanalysis between optical thickness and liquid water path over Iraq that these two parameters are positively correlated and the correlation for water cloud was better that that for ice clouds. Case studies of heavy precipitation events over Iraq showed that the maximum values of the most cloud properties variables were located ahead of the storm center. 


2019 ◽  
Vol 58 (11) ◽  
pp. 2469-2478
Author(s):  
Richard A. Frey ◽  
W. Paul Menzel

AbstractThis paper compares the cloud parameter data records derived from High Resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements from the years 2003 through 2013. Cloud-top pressure (CTP) and effective emissivity (εf; cloud emissivity multiplied by cloud fraction) are derived using the 15-μm spectral bands in the CO2 absorption band and implementing the CO2-slicing technique; the approach is robust for high semitransparent clouds but weak for low clouds with little thermal contrast from clear-sky radiances. The high-cloud (HiCld; with CTP less than 440 hPa) seasonal cycles of HIRS and MODIS observations are found to be in sync, but the HIRS frequency of detection is about 10% higher than that of MODIS (which is attributed to a lower threshold for cloud detection in the HIRS CO2 bands). Differences are largest during nighttime and at the beginning of the time series (2003–06). Both show Northern Hemisphere (NH) and Southern Hemisphere (SH) seasonal HiClds are out of phase and both agree within 2% on NH–SH HiCld differences. During the summer, maximum HiCld frequency averages 5% more in the NH.


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