doi:10.1007/s00376-017-7070-x

An N., K. C. Wang, 2015: A comparison of MODIS-derived cloud fraction with surface observations at five SURFRAD sites.Journal of Applied Meteorology and Climatology54,1009-1020,https://doi.org/10.1175/JAMC-D-14-0206.1.10.1175/JAMC-D-14-0206.1

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015JApMC..54.1009A

http://journals.ametsoc.org/doi/10.1175/JAMC-D-14-0206.1Clouds 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 degrees and a smaller cloud fraction at VZA < 20 degrees. 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.

Bilal M., J. E. Nichol, 2015: Evaluation of MODIS aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events.J. Geophys. Res.,120,7941-7957,https://doi.org/10.1002/2015JD023082.10.1002/2015JD023082

c9397041c4dc238c5911504542a76d88

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2015JD023082%2Fpdf

http://onlinelibrary.wiley.com/doi/10.1002/2015JD023082/pdfAbstract This study evaluates the performance of different MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms during fine particle pollution events over the Beijing-Tianjin-Hebei region using Aerosol Robotic Network aerosol optical depth (AOD). These algorithms include the Deep Blue (DB) Collection 5.1 (C5) and Collection 6 (C6) algorithms at 1065km resolution, the Dark Target (DT) C5 and C6 algorithms at 1065km, the DT C6 algorithm at 365km, and the Simplified Aerosol Retrieval Algorithm (SARA) at 50065m, 365km, and 1065km resolutions. The DB C6 retrievals have 34–39% less uncertainties, 2–3 times smaller root-mean-square error (RMSE), and 3–4 times smaller mean absolute error (MAE) than DB C5 retrievals. The DT C6 has 4–8% lower bias, 4–12% less overestimation, and smaller RMSE and MAE errors than DT C5. Due to underestimation of surface reflectance and the use of inappropriate aerosol schemes, 87–89% of the collocations of the DT C6 at 365km fall above the expected error (EE), with overestimation of 64–79% which is 15–27% higher than that for the DT C6 at 1065km. The results suggest that the DT C6 at 365km resolution is less reliable than that at 1065km. The SARA AOD has small RMSE and MAE errors with 90–96% of the collocations falling within the EE. Overall, the SARA showed 15–16% less uncertainty than the DB C6 (1065km), 69–72% less than the DT C6 (1065km), and 79–83% less than the DT C6 (365km) retrievals.

Che, H., Coauthors, 2014: Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements.Atmos. Chem. Phys.14,2125-2138,https://doi.org/10.5194/acp-14-2125-2014.10.5194/acp-14-2125-2014

e051582973681ddeab4b01abc2a4b15f

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014ACP....14.2125C

http://www.atmos-chem-phys.net/14/2125/2014/In January 2013, North China Plain experienced several serious haze events.Cimel sunphotometer measurements at seven sites over rural, suburban andurban regions of North China Plain from 1 to 30 January 2013 wereused to further our understanding of spatial-temporal variation of aerosoloptical parameters and aerosol radiative forcing (ARF). It was found thatAerosol Optical Depth at 500 nm (AODsub500 nm/sub) during non-pollution periodsat all stations was lower than 0.30 and increased significantly to greaterthan 1.00 as pollution events developed. The Angstrom exponent (Alpha) waslarger than 0.80 for all stations most of the time. AODsub500 nm/sub averagesincreased from north to south during both polluted and non-polluted periodson the three urban sites in Beijing. The fine mode AOD during pollutionperiods is about a factor of 2.5 times larger than that during thenon-pollution period at urban sites but a factor of 5.0 at suburban andrural sites. The fine mode fraction of AODsub675 nm/sub was higher than80% for all sites during January 2013. The absorption AODsub675 nm/sub atrural sites was only about 0.01 during pollution periods, while~0.03–0.07 and 0.01–0.03 during pollution and non-pollutionperiods at other sites, respectively. Single scattering albedo variedbetween 0.87 and 0.95 during January 2013 over North China Plain. The sizedistribution showed an obvious tri-peak pattern during the most seriousperiod. The fine mode effective radius in the pollution period was about0.01–0.08 μm larger than during non-pollution periods, while thecoarse mode radius in pollution periods was about 0.06–0.38 μm lessthan that during non-pollution periods. The total, fine and coarse modeparticle volumes varied by about 0.06–0.34 μmsup3/sup, 0.03–0.23 μmsup3/sup, and 0.03–0.10 μmsup3/sup, respectively, throughout January2013. During the most intense period (1–16 January), ARF atthe surface exceeded 6150 W msup612/sup, 61180 W msup612/sup, and 61200 W msup612/sup at rural, suburban, and urban sites, respectively. The ARFreadings at the top of the atmosphere were approximately 6130 W msup612/sup inrural and 6140–60 W msup612/sup in urban areas. Positive ARF at the top of theatmosphere at the Huimin suburban site was found to be different from othersas a result of the high surface albedo due to snow cover.

Che H. Z., G. Y. Shi, X. Y. Zhang, R. Arimoto, J. Q. Zhao, L. Xu, B. Wang, and Z. H. Chen, 2005: Analysis of 40 years of solar radiation data from China,1961-2000.Geophys. Res. Lett.,32,L06803,https://doi.org/10.1029/2004GL022322.

10.1029/2004GL022322

c0265c56c2bffc0477eed36170a4b7d2

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2004GL022322%2Ffull

http://onlinelibrary.wiley.com/doi/10.1029/2004GL022322/fullTrends in Chinese global radiation, direct horizontal radiation, diffuse radiation, clearness index, diffuse fraction and percentage of possible sunshine duration for the period 1961-2000 were evaluated based on data for daily surface solar radiation and monthly sunshine duration. Annual means for all six variables were calculated for each station and for China as a whole. Linear regression analysis was used to characterize long-term annual trends in these variables. Over the latter half of the 20th century, there have been significant decreases in global radiation (-4.5 W/mper decade), direct radiation (-6.6 W/mper decade), clearness index (-1.1% per decade), and the percentage of possible sunshine duration (-1.28% per decade), but diffuse fraction has increased (1.73% per decade). Although there is some evidence that conditions have improved in the last decade, the consistent spatial and temporal variations of these variables support the theory that increased aerosol loadings were at least partially responsible for the observed decreases in global radiation and direct radiation, the clearness index, and the monthly percentage of possible sunshine duration over much of China.

Che H. Z., X. Y. Zhang, Y. Li, Z. J. Zhou, and J. J. Qu, 2007: Horizontal visibility trends in China 1981-2005.Geophys. Res. Lett.,34,L24706,https://doi.org/10.1029/2007GL031450.10.1029/2007GL031450

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2007GL031450%2Fpdf

http://doi.wiley.com/10.1029/2007GL031450Trends in Chinese horizontal visibility, the frequency of visibility >19 km, and haziness for the period between 1981 and 2005 were evaluated based on data for daily horizontal visibility. Annual means were calculated for each station and for China as a whole. Linear regression analysis was used to characterize long-term annual trends in these variables. Over the past 25 years, there has been a significant decrease in horizontal visibility (-2.1 km per decade from 1990 to 2005) and the frequency of visibility >19 km (-3.5% per decade) but a significant increase in the 75th percentile annual extinction coefficients (25% per 25 year). According to rapid increase of total energy consumption, the consistent spatial and temporal variations of visibility and haze support the speculation that increased aerosol loadings were responsible for the observed decreases in horizontal visibility over much of East China.

Chen H. P., H. J. Wang, 2015: Haze Days in North China and the associated atmospheric circulations based on daily visibility data from 1960 to 2012.J. Geophys. Res.,120,5895-5909,https://doi.org/10.1002/2015JD023225.10.1002/2015JD023225

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2015JD023225%2Fpdf

年度引用Abstract Haze is a severe hazard that greatly influences traffic and daily life with great economic losses and threats to human health. To enhance understanding of the haze occurrences, this study examined the haze variations over North China and their associated atmospheric circulations for the period of 1960–2012 using daily visibility data. Results indicate that the haze events over this region primarily occur in boreal winter of year and mainly in the morning of day. The results of the analysis of the long-term variations indicate that the annual haze days were relatively few in the 1960s but increased steeply in the 1970s and have remained stable to the present. Some differences are obvious among seasons. A stably increasing trend is discernable in summer and autumn, relatively low in the 1960s and the 1990s–2000s and relatively high in the 1970s–1980s in spring and winter. Haze variations in urban regions are quite similar to haze variations in rural regions but with more haze days in urban regions because of the high aerosol emissions. Further analyses indicate that the occurrences of severe haze events in boreal winter generally correlate with the weakened northerly winds and the development of inversion anomalies in the lower troposphere, the weakened East Asian trough in the midtroposphere, and the northward East Asian jet in the high troposphere. All of these factors provide a favorable atmospheric background for the maintenance and development of haze events in this region.

CMDSSS, 2009: China Meteorological Data Sharing Service System. China Meteorological Administration,Beijing, China. [Available at http://www.cma.gov.cn.]

Dybbroe A., K.-G. Karlsson, and A. Thoss, 2005: NWCSAF AVHRR cloud detection and analysis using dynamic thresholds and radiative transfer modeling Part I: Algorithm description. J. Appl. Meteor.,44,39-54,https://doi.org/10.1175/JAM-2188.1.10.1175/JAM-2188.1

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http%3A%2F%2Fdialnet.unirioja.es%2Fservlet%2Farticulo%3Fcodigo%3D1108105

http://journals.ametsoc.org/doi/abs/10.1175/JAM-2188.1New methods and software for cloud detection and classification at high and midlatitudes using Advanced Very High Resolution Radiometer (AVHRR) data are developed for use in a wide range of meteorological, climatological, land surface, and oceanic applications within the Satellite Application Facilities (SAFs) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), including the SAF for Nowcasting and Very Short Range Forecasting Applications (NWCSAF) project. The cloud mask employs smoothly varying (dynamic) thresholds that separate fully cloudy or cloud-contaminated fields of view from cloud-free conditions. Thresholds are adapted to the actual state of the atmosphere and surface and the sun-satellite viewing geometry using cloud-free radiative transfer model simulations. Both the cloud masking and the cloud-type classification are done using sequences of grouped threshold tests that employ both spectral and textural features. The cloud-type classification divides the cloudy pixels into 10 different categories: 5 opaque cloud types, 4 semitransparent clouds, and 1 subpixel cloud category. The threshold method is fuzzy in the sense that the distances in feature space to the thresholds are stored and are used to determine whether to stop or to continue testing. They are also used as a quality indicator of the final output. The atmospheric state should preferably be taken from a short-range NWP model, but the algorithms can also run with climatological fields as input.

Feister U., H. Möller T. Sattler, J. Shields, U. Görsdorf, and J. Güldner, 2010: Comparison of macroscopic cloud data from ground-based measurements using VIS/NIR and IR instruments at Lindenberg,Germany.Atmos. Res.,96,395-407,https://doi.org/10.1016/j.atmosres.2010.01. 012.10.1016/j.atmosres.2010.01.012

387b5d6f7310b87f295cf6f5676c77eb

http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809510000232

http://linkinghub.elsevier.com/retrieve/pii/S0169809510000232A comparison between different types of ground-based sensors has been carried out to derive macroscopic cloud data such as cloud cover and cloud-base heights. The instruments compared in the campaign at the Meteorological Observatory Lindenberg in the period May to September 2006 include an infrared (IR) sky scanner called Nubiscope, a Daylight VIS/NIR Whole Sky Imager (WSI), a ceilometer LD-40 measuring in the near infrared region (NIR) and a Ka band cloud radar measuring in the micro wave band (extremely high frequency or EHF) region. In addition, our data analysis included regular hourly cloud observations by weather observers, and vertical profiles of temperature, humidity and winds taken from six-hourly radio soundings at the site. The comparison has been focused on performance and features of the Nubiscope as a prototype instrument for automatic cloud observations. Cloud cover (CC) derived from the Nubiscope cloud algorithm compares quite well with CC derived from both WSI and from observations. CC differences are within 2 Okta in 67% of cases between Nubiscope and observations, and in 90% of cases between Nubiscope and WSI. The cloud detection capability as derived from the zenith signals of Nubiscope and WSI shows coincidence in about 90% of cases. For cloud-base heights (CBHs) from Nubiscope data and ceilometer as well as from radar reflectivity, the comparison showed a general good correspondence in the lower and middle troposphere up to heights of about 6 km with some systematic difference due to the different detection methods. For the upper troposphere above 6 km the differences become widespread and more random. Cloud detection capabilities of the instruments are also illustrated by a case study of moving clouds with patterns similar to contrails that were erroneously classified as such by the weather observer mainly due to lack of height information that the ceilometer did not provide. By combined information from WSI, radio sonde humidity and radar, they were shown not to be contrails, but most likely low-level water clouds either of natural origin or built from aircraft at their ascent or descent flight close to the airport.

Fontana F., D. Lugrin, G. Seiz, M. Meier, and N. Foppa, 2013: Intercomparison of satellite- and ground-based cloud fraction over Switzerland (2000-2012).Atmos. Res.,128,1-12,https://doi.org/10.1016/j.atmosres.2013.01.013.

10.1016/j.atmosres.2013.01.013

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http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809513000525

http://linkinghub.elsevier.com/retrieve/pii/S016980951300052578 MODIS mid-morning cloud fraction data set derived from the Terra/MODIS MOD35 cloud mask product between (03/2000–02/2012) 78 MODIS early-afternoon cloud fraction data set derived from the Aqua/MODIS MYD35 cloud mask product (07/2000–02/2012) 78 High spatial resolution (0.05°) cloud cover climatology over the Swiss Alps 78 Validation with Synop observations over the full time period 78 Close agreement between satellite- and ground-based observations of cloud cover

Green M., S. Kondragunta, P. Ciren, and C. Y. Xu, 2009: Comparison of GOES and MODIS aerosol optical depth (AOD) to aerosol robotic network (AERONET) AOD and IMPROVE PM_2.5mass at Bondville,Illinois.Journal of the Air & Waste Management Association,59,1082-1091,https://doi.org/10.3155/1047-3289.59.9.1082.10.3155/1047-3289.59.9.1082

19785275

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http%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpubmed%2F19785275

http://www.ncbi.nlm.nih.gov/pubmed/19785275Collocated Interagency Monitoring of Protected Visual Environments (IMPROVE) particulate matter (PM) less than 2.5 microm in aerodynamic diameter (PM2.5) chemically speciated data, mass of PM less than 10 microm in aerodynamic diameter (PM10), and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and size distribution at Bondville, IL, were compared with satellite-derived AOD. This was done to evaluate the quality of the Geostationary Operational Environmental Satellite (GOES) and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD data and their potential to predict surface PM2.5 concentrations. MODIS AOD correlated better to AERONET AOD (r = 0.835) than did GOES AOD (r = 0.523). MODIS and GOES AOD compared better to AERONET AOD when the particle size distribution was dominated by fine mode. For all three AOD methods, correlation between AOD and PM2.5 concentration was highest in autumn and lowest in winter. The AERONET AOD-PM2.5 relationship was strongest with moderate relative humidity (RH). At low RH, AOD attributable to coarse mass degrades the relationship; at high RH, added AOD from water growth appears to mask the relationship. For locations such as many in the central and western United States with substantial coarse mass, coarse mass contributions to AOD may make predictions of PM2.5 from AOD data problematic. Seasonal and diurnal variations in particle size distributions, RH, and seasonal changes in boundary layer height need to be accounted for to use satellite AOD to predict surface PM2.5.

Hahn C. J., S. G. Warren, and J. London, 1992: The effect of moonlight on observation of cloud cover at night, and application to cloud climatology. J. Climate, 8,1429-1446, https://doi.org/10.1175/1520-0442(1995)008<1429:TEOMOO>2.0.CO;2.10.1175/1520-0442(1995)0082.0.CO;2

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1995JCli....8.1429H

http://adsabs.harvard.edu/abs/1995JCli....8.1429HVisual observations of cloud cover are hindered at night due to inadequate illumination of the clouds. This usually leads to an underestimation of the average cloud cover at night, especially for the amounts of middle and high clouds, in climatologies based on surface observations. The diurnal cycles of cloud amounts, if based on all the surface observations, are therefore in error, but they can be obtained more accurately if the nighttime observations are screened to select those made under sufficient moonlight. Ten years of nighttime weather observations from the Northern Hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6℃, light from a partial moon at higher elevation, or twilight from the sun less than 9℃ below the horizon. It permits the use of about 38 % of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit ofthe moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. Cloud cover is greater at night than during the day over the open oceans far from the continents, particularly in summer. However, near-noon maxima are still evident in the coastal regions, so that the global annual average oceanic cloud cover is still slightly greater during the day than at night by 0.3 %. Over land, where daytime maxima are still obtained but with reduced amplitude, average cloud cover is 3.3 % greater during the daytime. The diurnal cycles of total cloud cover we obtain are compared with those of ISCCP for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed 10 years (1982-91) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog, and precipitation. The global average cloud cover (average of day and night) is about 2 % higher if the moonlight criterion is imposed than if all observations are used. The difference is greater in winter than in summer, because of the fewer hours of darkness in summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-91 is found to be 55 % for Northern Hemisphere land, 53 % for Southern Hemisphere land, 66 % for Northern Hemisphere ocean, and 70 % for Southern Hemisphere ocean, giving a global average of 64 %. The global average for daytime is 64.6 %; for nighttime 63.3 %

Hall D. K., G. A. Riggs, and V. Salomonson, 2006: MODIS snow and sea ice products. Earth Science Satellite Remote Sensing,Qu et al., Eds.,Springer,Berlin Heidelberg,154-181,https://doi.org/10.1007/978-3-540-37293-6_9.

Heidinger A. K., V. R. Anne, and C. Dean, 2002: Using MODIS to estimate cloud contamination of the AVHRR data record. J. Atmos. Oceanic Technol, 19, 586-601, https://doi.org/10.1175/1520-0426(2002)019<0586:UMTECC>2.0.CO;2.10.1175/1520-0426(2002)0192.0.CO;2

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2002JAtOT..19..586H

http://adsabs.harvard.edu/abs/2002JAtOT..19..586HFocuses on a study concerning the improvement in a cloud-masking capability of data from a Moderate Resolution Imaging Spectroradiometer (MODIS) relative to data from an Advanced Very High Resolution Radiometer (AVHRR). Comparison of cloud masks; Analysis of the cloud-mask results between AVHRR and MODIS; Conclusions.

Holz R. E., S. A. Ackerman, F. W. Nagle, R. Frey, S. Dutcher, R. E. Kuehn, M. A. Vaughan, and B. Baum, 2008: Global moderate resolution imaging spectro radiometer (MODIS) cloud detection and height evaluation using CALIOP.J. Geophys. Res.,113,D00A19,https://doi.org/10.1029/2008JD009837.10.1029/2008JD009837

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http://onlinelibrary.wiley.com/doi/10.1029/2008JD009837/full[1] A global 2-month comparison is presented between the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Moderate Resolution Imaging Spectroradiometer (MODIS) for both cloud detection and cloud top height (CTH) retrievals. Both CALIOP and MODIS are part of the NASA A-Train constellation of satellites and provide continuous near-coincident measurements that result in over 28 million cloud detection comparisons and over 5 million CTH comparisons for the months of August 2006 and February 2007. To facilitate the comparison, a computationally efficient and accurate collocation methodology is developed. With the collocated MODIS and CALIOP retrievals, nearly instantaneous comparisons are compiled regionally and globally. Globally, it is found that the MODIS 1-km cloud mask and the CALIOP 1-km averaged layer product agreement is 87% for cloudy conditions for both August 2006 and February 2007. For clear-sky conditions the agreement is 85% (86%) for August (February). The best agreement is found for nonpolar daytime and the poorest agreement in the polar regions. Differences in cloud top heights depend strongly on cloud type. Globally, MODIS underestimates the CTH relative to CALIOP by 1.4 脗 2.9 km for both August 2006 and February 2007. This value of 1.4 km is obtained using the CALIOP 1 km layer products. When compared to the CALIOP 5-km products, the differences increase to 2.6 脗 3.9 km as a result of CALIOP's increased sensitivity to optically thin cirrus. When only high clouds above 5 km are considered, the differences are found to be greater than 4 km with individual comparisons having differences larger than 10 km. These large differences (>10 km) represent approximately 16% of the nonpolar high cloud retrievals (>5 km). For high clouds it is found that MODIS retrieves a cloud top height for 90% of the clouds detected by the CALIOP 5-km layer products. The large MODIS underestimates for optically thin cirrus occur for cases when MODIS reverts to a window brightness temperature retrieval instead of CO2 slicing. A systematic bias is found for marine low-level stratus clouds, with MODIS overestimating the CTH by over 1 km in dense marine stratocumulus regions. The cause of the bias was identified in the MODIS Collection 5 algorithm; an application of a modified algorithm reduced this bias.

Hsu N. C., S. C. Tsay, M. D. King, and J. R. Herman, 2004: Aerosol properties over bright-reflecting source regions. IEEE Transactions on Geoscience and Remote Sensing, 42, 557-569, https://doi.org/10.1109/TGRS.2004.824067

10.1109/TGRS.2004.824067

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http%3A%2F%2Fieeeexplore.com%2Fxpls%2Ficp.jsp%3Farnumber%3D1273587

http://ieeeexplore.com/xpls/icp.jsp?arnumber=1273587Retrieving aerosol properties from satellite remote sensing over a bright surface is a challenging problem in the research of atmospheric and land applications. In this paper we propose a new approach to retrieve aerosol properties over surfaces such...

Huo J., D. R. Lu, 2012: Comparison of cloud cover from all-sky imager and meteorological observer.J. Atmos. Oceanic Technol.,29,1093-1101,https://doi.org/10.1175/JTECH-D-11-00006.1.10.1175/JTECH-D-11-00006.1

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2012JAtOT..29.1093H

http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-11-00006.1ABSTRACT Naked-eye observation of cloud cover has widely resisted automation. Replacement of human observation by instruments is an inexorable trend for the development of ground-based macroscopic cloud observation. In this paper, cloud covers from an all-sky imager (AST) are compared with those from a meteorological observer (MO) through field experiments performed at three sites in China. The correlation coefficient between ASI and MO is 0.77 for all cases. The ASI cloud fractions have great agreement with MO for clear sky, overcast sky, and sky loaded with low- and middle-level clouds. About 78% of the ASI cases had deviations between +/- 1 tenth compared to MO cloud cover. High-level cloud (or aerosol) is the main reason causing this difference. It is partially due to MO, who takes aerosol as high, thin cloud. Another reason might be that ASI made a wrong estimation for high-level cloud (or aerosol) because of its detector and the cloud-determination algorithm. Distinguishing high, thin cloud from aerosol is a challenge, and is the main problem that needs to be resolved for future developments of ASI. A new, improved method is discussed at the end of this paper.

Kästner, M., P. Bissolli, K. Hoppner, 2004: Comparison of a satellite based Alpine cloud climatology with observations of synoptic stations.Meteor. Z.,13,233-243,https://doi.org/10.1127/0941-2948/2004/0013-0233.10.1127/0941-2948/2004/0013-0233

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http://www.schweizerbart.de/papers/metz/detail/13/53203/Comparison_of_a_satellite_based_Alpine_cloud_clima?af=crossrefA five-year cloud climatology (1992 to 1996) of the Alpine region in a 15-km resolution has been evaluated by means of the APOLLO cloud detection algorithm applied to daytime AVHRR data of several NOAA satellites. The study area comprises three different climatic regions, the moderate climate north of the Alps, the Alpine climate and the Mediterranean climate in the Po-valley. Synoptic observations of the total cloud cover at 40 stations have been compared to the satellite based monthly mean data. Hourly ground observations allowed to estimate the variance in the monthly mean diurnal cycle of total cloud cover due to the fact that the satellite overpass time shifts from noon to afternoon for the NOAA-11 platform and for different NOAA satellites as well. This time shift of satellite observation effects the cloud climatology only slightly, because the changes of the cloud cover between 11 and 16 UTC are in most cases considerably smaller than the yearto-year variability. Furthermore, these cloud cover variations due to the time of the day are in monthly means below the validation accuracy. The comparison of monthly means reveals an overestimation of the satellite cloud cover of about 10% mainly due to additional detection of thin cirrus. A good agreement is found in the Alpine and rural moderate climates (corr. coeff. r > 0.75), whereas the cloud detection in the satellite data is too high in the Mediterranean zone due to urban and aerosol haze effects. In both data sets a rather small amplitude of the annual cycle of cloud cover results in the mountains compared to the lowlands. The high spatial variability of cloud cover in mountainous terrain is obvious with the satellite data and is substantiated by the sparse synoptic stations within the Alps. Eine 5-j01hrige (1992–1996) Wolkenklimatologie der Alpenregion in einer 15-km-Aufl02sung wurde mit dem APOLLO Wolkenerkennungsalgorithmus erzeugt. Sie basiert auf t01glichen AVHRR-Daten (Mittags überflüge) von verschiedenen NOAA-Satelliten. Das Auswertegebiet umfasst drei verschiedene Klimaregionen: das gem0108igte Klima n02rdlich der Alpen, das Alpenklima und das mediterrane Klima in der Po-Ebene. Synoptische Beobachtungen der Gesamtwolkenbedeckung an 40 SYNOP-Stationen wurden mit den satellitengestützten, monatlich gemittelten Daten verglichen. Die stündlichen Stationsbeobachtungen erm02glichen eine Absch01tzung der 02nderung der Gesamtbew02lkung im Tagesgang und damit den Einfluss aus unterschiedlichen 05berflugzeiten der Satelliten. Dies ist insbesondere für den NOAA-11-Satelliten wichtig, dessen 05berflugzeit sich im Laufe der Jahre von Mittag auf Nachmittag verschob, bei den anderen NOAA-Satelliten ist es 01hnlich. Es zeigte sich, dass diese Zeitverschiebung der Satellitenbeobachtung die Ergebnisse der Wolkenklimatologie nur wenig beeinflusst, weil die Ver01nderungen der Wolkenbedeckung zwischen 11 und 16 UTC im Monatsmittel in den meisten F01llen betr01chtlich kleiner als die Jahr-zu-Jahr Variabilit01t sind. Ferner liegen diese tageszeitlichen Ver01nderungen unterhalb der Validierungsgenauigkeit. Der Vergleich der Monatsmittelwerte zeigt eine 05bersch01tzung der Satelliten-Wolkenbedeckung von ca. 10% zu den Bodenstationen, haupts01chlich bedingt durch die zus01tzliche Erkennung von dünnem Zirrus in den Satellitendaten. Insgesamt besteht eine recht gute 05bereinstimmung für das alpine und das gem0108igte Klima in l01ndlichen Gebieten (Korr. koeff. r0,75), w01hrend in der Mittelmeerzone und in Gro08st01dten die Satellitendaten die Bew02lkung übersch01tzen, was auf Aerosol- und Dunsteffekte zurückzuführen ist. Beide Datens01tze weisen eine geringe Amplitude des Jahresgangs der Bew02lkung über Bergen im Vergleich zum Flachland auf. Die hohe r01umliche Variabilit01t des Bedeckungsgrades im gebirgigen Gel01nde wird besonders deutlich in den Satellitendaten und gleichfalls best01tigt durch die r01umlich weniger gut aufgel02sten Stationsbeobachtungen im Alpengebiet.

Kazantzidis A., P. Tzoumanikas, A. F. Bais, S. Fotopoulos, and G. Economou, 2012: Cloud detection and classification with the use of whole-sky ground-based images.Atmos. Res.,113,80-88,https://doi.org/10.1016/j.atmosres.2012.05.005.

10.1016/j.atmosres.2012.05.005

0e2721cbecaa772f7937cd5f2af8d801

http%3A%2F%2Fwww.springerlink.com%2Fcontent%2Ffulltext.pdf%3Fid%3Ddoi%3A10.1007%2F978-3-642-29172-2_49

http://linkinghub.elsevier.com/retrieve/pii/S0169809512001342A simple whole sky imaging system, based on a commercial digital camera with a fish-eye lens and a hemispheric dome, is used for the automatic estimation of total cloud coverage and classification. For the first time, a multi color criterion is applied on sky images, in order to improve the accuracy in detection of broken and overcast clouds under large solar zenith angles. The performance of the cloud detection algorithm is successfully compared with ground based weather observations. A simple method is presented for the detection of raindrops standing on the perimeter of hemispheric dome. Based on previous works on cloud classification, an improved k-Nearest-Neighbor algorithm is presented, based not only on statistical color and textural features, but taking also into account the solar zenith angle, the cloud coverage, the visible fraction of solar disk and the existence of raindrops in sky images. The successful detection percentage of the classifier ranges between 78 and 95% for seven cloud types.

Key E. L., P. J. Minnett, and R. A. Jones, 2004: Cloud distributions over the coastal Arctic Ocean: Surface-based and satellite observations.Atmos. Res.,72,57-88,https://doi.org/10.1016/j.atmosres.2004.03.029.

10.1016/j.atmosres.2004.03.029

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http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809504000651

http://linkinghub.elsevier.com/retrieve/pii/S0169809504000651All-weather Arctic cloud analyses primarily derived from a surface-based hemispheric all-sky imager are compared against ISCCP D-1 cloud amount, type, and phase during the sunlit polar season. Increasing surface temperatures and decreasing ice cover over the past decade have altered heat and moisture fluxes around the Arctic, providing conditions more conducive for cloud generation. Shipboard and ice camp measurements from field experiments conducted over an 8-year period show cloudy skies in 7095% of the record. Most of these occurrences are stratiform or multi-level, multi-form cloud, increasing in amount with time through the season. Collocated ISCCP retrievals underestimate cloud amount at small solar zenith angles and overestimate at large angles, sometimes by as much as 50%. Satellite assessments of cloud form classify 95% of scenes as having multiple cloud types, the majority of which are mid-level ice cloud and low-level liquid cloud. Despite large discrepancies in diurnal cloud amount, regional averages of ISCCP pixel cloudiness over the length of the experiments agree within 5% of surface observations.

Kotarba A. Z., 2009: A comparison of MODIS-derived cloud amount with visual surface observations.Atmos. Res.,92,522-530,https://doi.org/10.1016/j.atmosres.2009.02.001.

10.1016/j.atmosres.2009.02.001

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http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809509000593

http://linkinghub.elsevier.com/retrieve/pii/S0169809509000593Two main sources for global cloud climatologies are visual surface observations and observations made by spaceborne sensors. Satellite observations compared with surface data show in most cases differences ranging from 610215% up to 61021%, depending on sensor and observation conditions. These differences are partially controlled by sensors' cloud detection capabilities — a higher number of spectral bands and higher spatial resolution are believed to allow discrimination of clouds from land/ocean/snow background. A Moderate-Resolution Imaging Spectroradiometer (MODIS) produces images of the atmosphere in 36 spectral bands with a spatial resolution of 250–1000m, thus having a capacity for cloud detection far more advanced than other operating sensors. In this study, instantaneous MODIS cloud observations were compared with surface data for Poland for January (winter) and July (summer) 2004. It was found that MODIS observed 4.38% greater cloud amount in summer conditions and 7.28% in winter conditions. Differences were greater at night (7–8%) than in daytime (0.5–7%) and correlations ranged between 0.577 (winter night) and 0.843 (winter day, summer day and night).

Kotarba A. Z., 2015: Evaluation of ISCCP cloud amount with MODIS observations.Atmos. Res.,153,310-317,https://doi.org/10.1016/j.atmosres.2014.09.006.10.1016/j.atmosres.2014.09.006

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http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809514003639

http://linkinghub.elsevier.com/retrieve/pii/S0169809514003639The goal of the International Satellite Cloud Climatology Project (ISCCP) is to provide global cloud amount statistics for atmospheric radiation flux modeling, which is a key element of climate change studies. However, ISCCP estimates rely on two spectral channels only, while the most advanced satellite sensors offer over 20 spectral bands, and thus a higher probability of correct cloud detection. We validated the accuracy of ISCCP mean monthly cloud amount statistics using the state-of-the-art, 36-spectral channel Moderate-resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra and Aqua satellites. Based on the MODIS Level 2 Cloud Mask we developed a dedicated Level 3 product for Central Europe (2004–2009). For the first time, MODIS swath data were projected onto an ISCCP equal-area grid, which guaranteed an exact geometrical agreement between both climatologies. Results showed that there was a close correlation between ISCCP and MODIS data (ρ02=020.872, α02=020.99), especially at warmer part of the year (ρ02≥020.940, α02>020.99). However, ISCCP estimations were found to be unreliable in wintertime when surface was covered with snow. The presence of snow resulted in a significant underestimate of cloud amount by 0.45 for individual ISCCP grid boxes. Our results suggest that MODIS cloud climatology is more reliable when estimates of mean monthly cloud amount are required.

Levy R. C., L. A. Remer, and O. Dubovik, 2007a: Global aerosol optical properties and application to Moderate Resolution Imaging Spectro radiometer aerosol retrieval over land.J. Geophys. Res.,112,D13210,https://doi.org/10.1029/2006JD007815.

Levy R. C., L. A. Remer, S. Mattoo, E. F. Vermote, and Y. J. Kaufman, 2007b: Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectro radiometer spectral reflectance.J. Geophys. Res.,112,D13211,https://doi.org/10.1029/2006JD007811.10.1029/2006JD007811

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http://www.sciencedirect.com/science/article/pii/S0005796799000467[1] Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from Moderate Resolution Imaging Spectroradiometer (MODIS) observed spectral reflectance. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the surface reflectance assumptions, the set of aerosol model optical properties, and the aerosol lookup table (LUT). This second-generation operational algorithm performs a simultaneous inversion of two visible (0.47 and 0.66 μ m) and one shortwave-IR (2.12 μ m) channel, making use of the coarse aerosol information content contained in the 2.12 μ m channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth ( τ ) at 0.55 μ m, the nondust or fine weighting ( η ), and the surface reflectance at 2.12 μ m. Retrievals of small-magnitude negative τ values (down to 610.05) are considered valid, thus balancing the statistics of τ in near zero τ conditions. Preliminary validation of this algorithm shows much improved retrievals of τ , where the MODIS/Aerosol Robotic Network τ (at 0.55 μ m) regression has an equation of: y = 1.01x + 0.03, R = 0.90. Global mean τ for the test bed is reduced from 650.28 to 650.21.

Levy R. C., S. Mattoo, L. A. Munchak, L. A. Remer, A. M. Sayer, and N. C. Hsu, 2013: The Collection 6 MODIS aerosol products over land and ocean.Atmospheric Measurement Techniques Discussions6,159-259,https://doi.org/10.5194/amtd-6-159-2013.10.5194/amt-6-2989-2013

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http://www.atmos-meas-tech-discuss.net/6/159/2013/The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target"(DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue"(DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (# 1 and # 2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O-3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to <= 84 degrees) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream"changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.

Li X. Y., 2016: Empirical analysis of the smog factors in Beijing-Tianjin-Hebei region.Ecological Economy32,144- 150,https://doi.org/10.3969/j.issn.1671-4407.2016.03.029.(in Chinese)

Li, Z., Coauthors, 2013: Aerosol physical and chemical properties retrieved from ground-based remote sensing measurements during heavy haze days in Beijing winter.Atmos. Chem. Phys.13,10 171-10 183,https://doi.org/10.5194/acp-13-10171-2013.10.5194/acpd-13-5091-2013

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http%3A%2F%2Fwww.oalib.com%2Fpaper%2F2701099

http://www.atmos-chem-phys.net/13/10171/2013/With the development of economy in the past thirty years, many large cities in the eastern and southwestern China are experiencing increased haze events and atmospheric pollution, causing significant impacts on the regional environment and even climate. However, knowledge on the aerosol physical and chemical properties in heavy haze conditions is still insufficient. In this study, two winter heavy haze events in Beijing occurred in 2011 and 2012 were selected and investigated by using the ground-based remote sensing measurements. We used CIMEL CE318 sun-sky radiometer to derive haze aerosol optical, physical and chemical properties, including aerosol optical depth (AOD), size distribution, complex refractive indices and fractions of chemical components like black carbon (BC), brown carbon (BrC), mineral dust (DU), ammonium sulfate-like (AS) components and aerosol water content (AW). The retrieval results from a total of five haze days showed that the aerosol loading and properties during the two winter haze events were relatively stable. Therefore, a parameterized heavy haze characterization was drawn to present a research case for future studies. The averaged AOD is 3.2 at 440 nm and ngstrm exponent is 1.3 from 440870 nm. The coarse particles occupied a considerable fraction of the bimodal size distribution in winter haze events, with the mean particle radius of 0.21 and 2.9 m for the fine and coarse mode respectively. The real part of the refractive indices exhibited a relatively flat spectral behavior with an average value of 1.48 from 440 to 1020 nm. The imaginary part showed obviously spectral variation with the value at 440 nm (about 0.013) higher than other three wavelengths (e.g. about 0.008 at 675 nm). The chemical composition retrieval results showed that BC, BrC, DU, AS and AW occupied 1%, 2%, 49%, 15% and 33% respectively on average for the investigated haze events. The comparison of these remote sensing results with in situ BC and PMlt;subgt;2.5lt;/subgt; measurements were also presented in the paper.

Liang F., X. A. Xia, 2005: Long-term trends in solar radiation and the associated climatic factors over China for 1961-2000.Annales Geophysicae23,2425-2432,https://doi.org/10.5194/angeo-23-2425-2005.10.5194/angeo-23-2425-2005

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http://www.ann-geophys.net/23/2425/2005/Long-term trends in downwelling solar irradiance and associated climatic factors over China are studied in the paper. Decreasing trends in global and direct radiation are observed over much of China. The largest decrease occurs in South and East China (east of about 100℃ E and south of about 40℃ N). The spatial pattern of observed trends in diffuse irradiance is complex and inhomogeneous. An intriguing aspect of trends in global and direct irradiance is the rather abrupt decrease in annual and seasonal mean values from 1978 onward. The decreasing trends in solar radiation in China did not persist into the 1990s. The spatial and temporal patterns of trends in sunshine duration are consistent with that of global and direct irradiance. A decreasing trend in rainy days is observed over much of China, which is in agreement with the secular trend in cloud amount. The fact that trends in cloud amount and solar radiation are quite similar suggests that the cloud amount is not the primary cause for the decrease in solar radiation. Visibility in the eastern part of China has deteriorated heavily as a result of the rapid increase in aerosol loading. The statistical analysis showed that atmospheric transmission under clear conditions decreased rapidly. These facts suggest that the rapid increase in aerosol loading should be one of the principle causes for the decrease in solar radiation. The observed diurnal temperature range decreases remarkably in China, which is closely related to the increase in aerosols. The effects of anthropogenic air pollutants on climate should be further studied and included in the simulation of climate and projection of climate scenario.Keywords. Atmospheric composition and structure (Aerosol and particles; General or miscellaneous) Meteorology and atmospheric dynamics (Radiative processes)

Lu H., Y. W. Zhang, and J. Cai, 2015: Consistency and differences between remotely sensed and surface observed total cloud cover over China.Int. J. Remote Sens.,36,4160-4176,https://doi.org/10.1080/01431161.2015.1072651.

10.1080/01431161.2015.1072651

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http%3A%2F%2Fwww.tandfonline.com%2Fdoi%2Ffull%2F10.1080%2F01431161.2015.1072651

http://www.tandfonline.com/doi/full/10.1080/01431161.2015.1072651In this study, we conducted a comparison between surface-observed total cloud cover (TCCs) and Moderate Resolution Imaging Spectroradiometer (MODIS)-derived total cloud cover (TCCm) over China. A statistical method was applied to estimate the average field of view (FOV) of surface observers, and the radius range of FOV was 20–25, 25–35, 35–50, and 25–4502km for spring, summer, autumn, and winter, respectively. More differences would be added in the comparison when the satellite’s FOV was smaller or larger than the average FOV. Monthly mean TCCs was 74.78%, 74.41%, 66.5%, and 74.06% for each season and the corresponding TCCm was 75.27%, 78.34%, 73.82%, and 82.12%. The correlation between two data sets was stronger in spring (0.727) and summer (0.736) than in autumn (0.710) and winter (0.667). Over 60% of the differences were within the 6110% to 10% range, and more differences occurred for smaller TCCs. As a special feature, we found that the dust, haze, and snow cover over specific regions in China were the possible causes of the significant differences. Generally, these two data sets were in good agreement over China, and can complement each other especially in those significant difference cases to provide more accurate TCC data sets.

Luo Y. F., D. R. Lu, X. J. Zhou, W. L. Li, and Q. He, 2001: Characteristics of the spatial distribution and yearly variation of aerosol optical depth over China in last 30 years.J. Geophys. Res.,106,14 501-14 513,https://doi.org/10.1029/2001JD900030.10.1029/2001JD900030http://doi.wiley.com/10.1029/2001JD900030

Ma J. J., H. Wu, C. Wang, X. Zhang, Z. Q. Li, and X. H. Wang, 2014: Multiyear satellite and surface observations of cloud fraction over China.J. Geophys. Res.,119,7655-7666,https://doi.org/10.1002/2013JD021413.10.1002/2013JD021413

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2013JD021413%2Fabstract

http://onlinelibrary.wiley.com/doi/10.1002/2013JD021413/abstractAbstract Earth observation satellites can provide systematic and continuous monitoring of clouds. High spatial resolution (565km) cloud fraction data are retrieved from the Moderate Resolution Imaging Spectroradiometer cloud mask products of Terra (1265years) and Aqua (965years) over China. Long-term trends of cloud fraction for morning and afternoon observations clearly reflected seasonal variations. We found more clouds in the afternoon than in the morning. There is a strong correlation between satellite and surface observations of the daily cloud fraction for the period of 2012, with correlation coefficients of 0.678 and 0.7 for morning and afternoon, respectively. However, the analyses of the monthly mean cloud fraction between satellite and surface observations showed a larger discrepancy in the winter. In order to investigate the differences between satellite and ground-based cloud fraction over different underlying surfaces, a statistical test was carried out for six areas. The results indicated statistically significant increased correlations ( p 65<650.0001) between satellite and ground-based cloud fraction in northern China after removing winter data, especially in Northeastern Forest and Taklimakan Desert, while the correlation coefficients in southern China did not show significant changes.

Maddux B. C., S. A. Ackerman, and S. Platnick, 2010: Viewing geometry dependencies in MODIS cloud products.J. Atmos. Oceanic Technol.27,1519-1528,https://doi.org/10.1175/2010JTECHA1432.1.10.1175/2010JTECHA1432.1

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http://journals.ametsoc.org/doi/abs/10.1175/2010JTECHA1432.1Characterizing the earth's global cloud field is important for the proper assessment of the global radiation budget and hydrologic cycle. This characterization can only be achieved with satellite measurements. For complete daily coverage across the globe, polar-orbiting satellites must take observations over a wide range of sensor zenith angles. This paper uses Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 data to determine the effect that sensor zenith angle has on global cloud properties including the cloud fraction, cloud-top pressure, effective radii, and optical thickness. For example, the MODIS cloud amount increases from 57% to 71% between nadir and edge-of-scan (0903046700°) observations, for clouds observed between 3500°N and 3500°S latitude. These increases are due to a combination of factors, including larger pixel size and longer observation pathlength at more oblique sensor zenith angles. The differences caused by sensor zenith angle bias in cloud properties are not readily apparent in monthly mean regional or global maps because the averaging of multiple satellite overpasses together 'washes out' the zenith angle artifact. Furthermore, these differences are not constant globally and are dependent on the cloud type being observed.

Mao F. Y., M. M. Duan, Q. L. Min, W. Gong, Z. X. Pan, and G. Y. Liu, 2015: Investigating the impact of haze on MODIS cloud detection.J. Geophys. Res.,120,12 237-12 247,https://doi.org/10.1002/2015JD023555.10.1002/2015JD023555

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2015JD023555%2Fpdf

http://onlinelibrary.wiley.com/doi/10.1002/2015JD023555/pdfAbstract The cloud detection algorithm for passive sensors is usually based on a fuzzy logic system with thresholds determined from previous observations. In recent years, haze and high aerosol concentrations with high aerosol optical depth (AOD) occur frequently in China and may critically impact the accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection. Thus, we comprehensively explore this impact by comparing the results from MODIS/Aqua (passive sensor), Cloud-Aerosol Lidar with Orthogonal Polarization/CALIPSO (lidar sensor), and Cloud Profiling Radar/CloudSat (microwave sensor) of the A-Train suite of instruments using an averaged AOD as an index for an aerosol concentration value. Case studies concerning the comparison of the three sensors indicate that MODIS cloud detection is reduced during haze events. In addition, statistical studies show that an increase in AOD creates an increase in the percentage of uncertain flags and a decrease in hit rate, a consistency index between consecutive sets of cloud retrievals. On average, AOD values lower than 0.1 give hit rate values up to 80.0% and uncertainty values lower than 16.8%, while AOD values greater than 1.0 reduce the hit rate below to 66.6% and increase the percentage of uncertain flags up to 46.6%. Therefore, we can conclude that the ability of MODIS cloud detection is weakened by large concentrations of aerosols. This suggests that use of the MODIS cloud mask, and derived higher-level products, in situations with haze requires caution. Further improvement of this retrieval algorithm is desired as haze studies based on MODIS products are of great interest in a number of related fields.

Meerkötter, R., C. König, P. Bissolli, G. Gesell, H. Mannstein, 2004: A 14-year European Cloud Climatology from NOAA/ AVHRR data in comparison to surface observations.Geophys. Res. Lett.,31,L15103,https://doi.org/10.1029/2004GL020098.10.1029/2004GL020098

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2004GL020098%2Ffull

http://doi.wiley.com/10.1029/2004GL020098A 14-year (1990-2003) high resolution European Cloud Climatology has been generated by use of NOAA/AVHRR data. For selected areas we present spatially averaged monthly means of total cloud cover derived from noon overpasses and compare them with surface SYNOP observations. The climatologies do not reveal a significant trend of cloud cover over the 14-year period. However, both data sets show a clear latitudinal variability and a seasonal dependence which is more pronounced in the satellite than in the SYNOP observations. Mean differences between satellite and SYNOP data range from about -2% to -10% in all seasons except summer when the mean difference is as large as -15.3%. As a special feature we notice the broad minimum of cloud cover during the extreme dry and hot summer in 2003 in Central Europe.

Menzel, W. P., Coauthors, 2008: MODIS global cloud-top pressure and amount estimation: Algorithm description and results.Journal of Applied Meteorology and Climatology47,1175-1198,https://doi.org/10.1175/2007JAMC1705.1.10.1175/2007JAMC1705.1

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2008JApMC..47.1175M

http://journals.ametsoc.org/doi/abs/10.1175/2007JAMC1705.1The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua platforms provides unique measurements for deriving global and regional cloud properties. MODIS has spectral coverage combined with spatial resolution in key atmospheric bands, which is not available on previous imagers and sounders. This increased spectral coverage/spatial resolution, along with improved onboard calibration, enhances the capability for global cloud property retrievals. MODIS operational cloud products are derived globally at spatial resolutions of 5 km (referred to as level-2 products) and are aggregated to a 1℃ equal-angle grid (referred to as level-3 product), available for daily, 8-day, and monthly time periods. The MODIS cloud algorithm produces cloud-top pressures that are found to be within 50 hPa of lidar determinations in single-layer cloud situations. In multilayer clouds, where the upper-layer cloud is semitransparent, the MODIS cloud pressure is representative of the radiative mean between the two cloud layers. In atmospheres prone to temperature inversions, the MODIS cloud algorithm places the cloud above the inversion and hence is as much as 200 hPa off its true location. The wealth of new information available from the MODIS operational cloud products offers the promise of improved cloud climatologies. This paper 1) describes the cloud-top pressure and amount algorithm that has evolved through collection 5 as experience has been gained with in-flight data from NASA Terra and Aqua platforms; 2) compares the MODIS cloud-top pressures, converted to cloud-top heights, with similar measurements from airborne and space-based lidars; and 3) introduces global maps of MODIS and High Resolution Infrared Sounder (HIRS) cloud-top products.

Minnis P., D. A. Spangenberg, and V. Chakrapani, 2003: Distribution and validation of cloud cover derived from AVHRR data over the Arctic Ocean during the SHEBA year. Proceedingsofthe13thARMScienceTeamMeeting, Broomfield, Colorado.

Platnick S., M. D. King, S. Ackerman, W. P. Menzel, B. A. Baum, J. C. Riédi, and R. A. Frey, 2003: The MODIS cloud products: Algorithms and examples from Terra. IEEE Transactionson Geoscience and Remote Sensing, 41, 459-473, https://doi.org/10.1109/TGRS.2002.808301.10.1109/TGRS.2002.808301

ca58c77901ee7f11bdb92bb064999fa4

http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Ficp.jsp%3Farnumber%3D1196061

http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=1196061The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System (EOS) platform launched in December 1999. After achieving final orbit, MODIS began Earth observations in late February 2000 and has been acquiring data since that time. The instrument is also being flown on the Aqua spacecraft, launched in May 2002. A comprehensive set of remote sensing algorithms for cloud detection and the retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various algorithms being used for the remote sensing of cloud properties from MODIS data with an emphasis on the pixel-level retrievals (referred to as Level-2 products), with 1-km or 5-km spatial resolution at nadir. An example of each Level-2 cloud product from a common data granule (5 min of data) off the coast of South America will be discussed. Future efforts will also be mentioned. Relevant points related to the global gridded statistics products (Level-3) are highlighted though additional details are given in an accompanying paper in this issue.

Qiu J. H., L. Q. Yang, 2000: Variation characteristics of atmospheric aerosol optical depths and visibility in North China during 1980-1994.Atmos. Environ.34,603-609,https://doi.org/10.1016/S1352-2310(99)00173-9

10.1016/S1352-2310(99)00173-9

c7ab851991a3e694d3cdc7062c1646d1

http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1352231099001739

http://linkinghub.elsevier.com/retrieve/pii/S1352231099001739Using a method developed by Qiu (Qiu, J., 1998. A method to determine atmospheric aerosol optical depth using total direct solar radiation. J. Atmos. Sci. 55, 734–758), 0.75 μm aerosol optical depths at five meteorological observatories in north China during 1980–1994 are retrieved from global direct solar radiation, and variation characteristics of the depths and visibility are analyzed. These observatories are located in the cities of Wulumuqi, Geermu, Harbin, Beijing and Zhengzhou. It is found that during 1980–1994 the aerosol optical depths show an increasing trend at all five sites. During winter the trend is stronger. In winter at Beijing and Wulumuqi, the depth increased by a factor of about two in 15 years. Pollution caused due to the burning of fossil fuel is the main cause of the change. In spring at Geermu the depth is larger and its increase is the quickest among the four seasons, mainly due to desert dust events. The Pinatubo volcanic eruption in 1991 had a significant influence on the aerosol optical depth. The yearly averaged depths over five sites in 1992 after the eruption increased by 0.068 to 0.212, compared to those in 1990, while from 1992 to 1994 they generally show a decreasing trend. In some cities such as Zhengzhou and Geermu, both visibility and optical depth show an increasing trend during 1980–1994, a possible reason for this is that the aerosol particle vertical distribution shifts up in the troposphere. At Geermu, Harbin, Beijing and Zhengzhou, optical depths in summer are larger, which may be because of the growth of aerosol particles growing in the moist summer. Apart from Geermu, at the other four sites visibility in winter is smaller, especially at Wulumuqi and Harbin. At Harbin, visibility in summer is about twice larger than that in winter, but the difference between depths is small, implying the turbid lower troposphere in winter and the larger extinction coefficient in the upper troposphere during summer.

Ramanathan V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the earth radiation budget experiment.Science243,57-63,https://doi.org/10.1126/science.243.4887.57.10.1126/science.243.4887.57

17780422

e98b5dbbe38b45093133cf7c39ac264c

http%3A%2F%2Feuropepmc.org%2Fabstract%2FMED%2F17780422

http://www.sciencemag.org/cgi/doi/10.1126/science.243.4887.57The study of climate and climate change is hindered by a lack of information on the effect of clouds on the radiation balance of the earth, referred to as the cloud-radiative forcing. Quantitative estimates of the global distributions of cloud-radiative forcing have been obtained from the spaceborne Earth Radiation Budget Experiment (ERBE) launched in 1984. For the April 1985 period, the global shortwave cloud forcing [-44.5 watts per square meter (W/m(2))] due to the enhancement of planetary albedo, exceeded in magnitude the longwave cloud forcing (31.3 W/m(2)) resulting from the greenhouse effect of clouds. Thus, clouds had a net cooling effect on the earth. This cooling effect is large over the mid-and high-latitude oceans, with values reaching -100 W/m(2). The monthly averaged longwave cloud forcing reached maximum values of 50 to 100 W/m(2) over the convectively disturbed regions of the tropics. However, this heating effect is nearly canceled by a correspondingly large negative shortwave cloud forcing, which indicates the delicately balanced state of the tropics. The size of the observed net cloud forcing is about four times as large as the expected value of radiative forcing from a doubling of CO(2). The shortwave and longwave components of cloud forcing are about ten times as large as those for a CO(2) doubling. Hence, small changes in the cloud-radiative forcing fields can play a significant role as a climate feedback mechanism. For example, during past glaciations a migration toward the equator of the field of strong, negative cloud-radiative forcing, in response to a similar migration of cooler waters, could have significantly amplified oceanic cooling and continental glaciation.

Remer, L. A., Coauthors, 2005: The MODIS aerosol algorithm,products, and validation.J. Atmos. Sci.,62,947-973,https://doi.org/10.1175/JAS3385.1.10.1175/JAS3385.1

5b67dee8b37912cd420fb47325523d46

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2005JAtS...62..947R

http://journals.ametsoc.org/doi/abs/10.1175/JAS3385.1The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard both NASA0964s Terra and Aqua satellites is making near-global daily observations of the earth in a wide spectral range (0.4109“15 0204m). These measurements are used to derive spectral aerosol optical thickness and aerosol size parameters over both land and ocean. The aerosol products available over land include aerosol optical thickness at three visible wavelengths, a measure of the fraction of aerosol optical thickness attributed to the fine mode, and several derived parameters including reflected spectral solar flux at the top of the atmosphere. Over the ocean, the aerosol optical thickness is provided in seven wavelengths from 0.47 to 2.13 0204m. In addition, quantitative aerosol size information includes effective radius of the aerosol and quantitative fraction of optical thickness attributed to the fine mode. Spectral irradiance contributed by the aerosol, mass concentration, and number of cloud condensation nuclei round out the list of available aerosol products over the ocean. The spectral optical thickness and effective radius of the aerosol over the ocean are validated by comparison with two years of Aerosol Robotic Network (AERONET) data gleaned from 132 AERONET stations. Eight thousand MODIS aerosol retrievals collocated with AERONET measurements confirm that one standard deviation of MODIS optical thickness retrievals fall within the predicted uncertainty of 02”0367 = 00±0.03 00±0.050367 over ocean and 02”0367 = 00±0.05 00± 0.150367 over land. Two hundred and seventy-one MODIS aerosol retrievals collocated with AERONET inversions at island and coastal sites suggest that one standard deviation of MODIS effective radius retrievals falls within 02”reff = 00±0.11 0204m. The accuracy of the MODIS retrievals suggests that the product can be used to help narrow the uncertainties associated with aerosol radiative forcing of global climate.

Rossow W. B., A. W. Walker, and L. C. Garder, 1993: Comparison of ISCCP and other cloud amounts. J. Climate, 6, 2394-2418, https://doi.org/10.1175/1520-0442(1993)006 <2394:COIAOC>2.0.CO;2.10.1175/1520-0442(1993)0062.0.CO;2

6581247cd34be410c27fb935594a8f12

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1993jcli....6.2394r

http://adsabs.harvard.edu/abs/1993jcli....6.2394rA new 8-year global cloud climatology has been produced by the International Satellite Cloud Climatology Project (ISCCP) that provides information every 3 h at 280-km spatial resolution covering the period from July 1983 through June 1991. If cloud detection errors and differences in area sampling are neglected, individual ISCCP cloud amounts agree with individual surface observations to within 15% rms with biases of only a few percent. When measurements of small-scale, broken clouds are isolated in the comparison, the rms differences between satellite and surface cloud amounts are about 25%, similar to the rms difference between ISCCP and Landsat determinations of cloud amount. For broken clouds, the average ISCCP cloud amounts are about 5% smaller than estimated by surface observers (difference between earth cover and sky cover), but about 5% larger than estimated from very high spatial resolution satellite observations (overestimate due to low spatial resolution offset by underestimate due to finite radiance thresholds). Detection errors, caused by errors in the ISCCP clear-sky radiances or incorrect radiance threshold magnitude are the dominant source of error in monthly average cloud amounts. The ISCCP cloud amounts appear to he too low over land by about 10%, somewhat less in summer and somewhat more in winter, and about right (maybe slightly low) over oceans. In polar regions, ISCCP cloud amounts are probably too low by about 15%–25% in summer and 5%–10% in winter. Comparison of the ISCCP climatology to three other cloud climatologies shows excellent agreement in the geographic distribution and seasonal variation of cloud amounts; there is little agreement about day/night contrasts in cloud amount. Notable results from ISCCP are that the global annual mean cloud amount is about 63%, being about 23% higher over oceans than over land, that it varies by <1% rms from month to month, and that it has varied by about 4% on a time wale ≈2–4 years. The magnitude of interannual variations of local (280-km scale) monthly mean cloud amounts is about 7%–9%. Longitudinal contrasts in cloud amount are just as large as latitudinal contrasts. The largest seasonal variation of cloud amount occurs in the tropics, being larger in summer than in winter; the seasonal variation in middle latitudes has the opposite phase. Polar regions may have little seasonal variability in cloud amount. The ISCCP results show slightly more nighttime than daytime cloud amount over oceans and more daytime than nighttime cloud amount over land.

Shang H. Z., L. F. Chen, J. H. Tao, L. Su, and S. L. Jia, 2014: Synergetic use of MODIS cloud parameters for distinguishing high aerosol loadings from clouds over the North China Plain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 4879-4886, https://doi.org/10.1109/JSTARS.2014.2332427.10.1109/JSTARS.2014.2332427

adb63bf2eb2c05e1af8b240c3742cff6

http%3A%2F%2Fieeexplore.ieee.org%2Fdocument%2F6858034%2F

http://ieeexplore.ieee.org/document/6858034/The Moderate Resolution Imaging Spectroradiometer (MODIS) standard cloud product is prone to misidentifying areas that are heavily polluted with aerosols as cloudy regions over the North China Plain (NCP) and to retrieving aerosol characteristics as cloud parameters. Based on the differences in physical and optical properties between aerosols and clouds, we propose a new approach to distinguish aerosol-laden areas from cloudy regions using MODIS level 2 cloud properties (e.g., cloud fraction, cloud phase, and cloud top pressure products). The approach was applied to 22 haze-fog cases that occurred in the 2011 and 2012 winters over the NCP. The aerosol identification results were then compared with MODIS-flagged aerosol areas, which were inferred from the noncloud obstruction flag and the suspended dust flag in the MODIS cloud mask product. The results indicated that approximately 60% of the MODIS-flagged aerosol areas were correctly identified using our approach. Among the analyzed cases, two cases exhibited substantial differences; the aerosol areas detected using the newly proposed method were approximately 2.5 times larger than that of the MODIS-flagged area. Further comparisons with aerosol distributions along the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) orbit for the two cases demonstrated that approximately 60%-80% of the CALIOP observed aerosols were identified using our method, while less than 10% of the CALIOP observed aerosols were consistent with the MODIS flagging.

Wang H., G. Y. Shi, X. Y. Zhang, S. L. Gong, S. C. Tan, B. Chen, H. Z. Che, and T. Li, 2015b: Mesoscale modelling study of the interactions between aerosols and PBL meteorology during a haze episode in China Jing-Jin-Ji and its near surrounding region-Part 2: Aerosols' radiative feedback effects.Atmos. Chem. Phys.15,3277-3287,https://doi.org/10.5194/acp-15-3277-2015.10.5194/acp-15-3277-2015

4b332565a42bbfd9a27ce344913302d9

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2015ACP....15.3277W

http://www.atmos-chem-phys.net/15/3277/2015/Two model experiments, namely a control (CTL) experiment without aerosol–radiation feedbacks and a experiment with online aerosol–radiation (RAD) interactions, were designed to study the radiative feedback on regional radiation budgets, planetary boundary layer (PBL) meteorology and haze formation due to aerosols during haze episodes over Jing–Jin–Ji, China, and its near surroundings (3JNS region of China: Beijing, Tianjin, Hebei, East Shanxi, West Shandong and North Henan) with a two-way atmospheric chemical transport model. The impact of aerosols on solar radiation reaching Earth's surface, outgoing long-wave emission at the top of the atmosphere, air temperature, PBL turbulence diffusion, PBL height, wind speeds, air pressure pattern and PM2.5 has been studied focusing on a haze episode during the period from 7 to 11 July 2008. The results show that the mean solar radiation flux that reaches the ground decreases by about 15% in 3JNS and 20 to 25%in the region with the highest aerosol optical depth during the haze episode. The fact that aerosol cools the PBL atmosphere but warms the atmosphere above it leads to a more stable atmospheric stratification over the region, which causes a decrease in turbulence diffusion of about 52% and a decrease in the PBL height of about 33%. This consequently forms a positive feedback on the particle concentration within the PBL and the surface as well as the haze formation. Additionally, aerosol direct radiative forcing (DRF) increases PBL wind speed by about 9% and weakens the subtropical high by about 14 hPa, which aids the collapse of haze pollution and results in a negative feedback to the haze episode. The synthetic impacts from the two opposite feedbacks result in about a 14% increase in surface PM2.5. However, the persistence time of both high PM2.5 and haze pollution is not affected by the aerosol DRF. On the contrary over offshore China, aerosols heat the PBL atmosphere and cause unstable atmospheric stratification, but the impact and its feedback on the planetary boundary layer height, turbulence diffusion and wind is weak, with the exception of the evident impacts on the subtropical high.

Wang, H., Coauthors, 2015c: Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing-Jin-Ji (China) and its nearby surrounding region-Part 1: Aerosol distributions and meteorological features.Atmos. Chem. Phys.15,3257-3275,https://doi.org/10.5194/acp-15-3257-2015.

Wang H. J., H. P. Chen, and J. P. Liu, 2015a: Arctic sea ice decline intensified haze pollution in eastern China.Atmos. Oceanic Sci. Lett.,8,1-9,https://doi.org/10.3878/AOSL20140081.bc1eb6775d7f06e1a616a8a3ca9df3b9

http%3A%2F%2Fkns.cnki.net%2FKCMS%2Fdetail%2Fdetail.aspx%3Ffilename%3Daosl201501001%26dbname%3DCJFD%26dbcode%3DCJFQ

年度引用

Wang, H. J., Coauthors, 2015d: A review of seasonal climate prediction research in China.Adv. Atmos. Sci.,32,149-168,https://doi.org/10.1007/s00376-014-0016-7.10.1007/s00376-014-0016-7

196c93b450f9b7319044acb951ce5545

http%3A%2F%2Fwww.cqvip.com%2FQK%2F84334X%2F201502%2F663762639.html

http://link.springer.com/10.1007/s00376-014-0016-7The ultimate goal of climate research is to produce climate predictions on various time scales. In China, efforts to predict the climate started in the 1930 s. Experimental operational climate forecasts have been performed since the late 1950 s,based on historical analog circulation patterns. However, due to the inherent complexity of climate variability, the forecasts produced at that time were fairly inaccurate. Only from the late 1980 s has seasonal climate prediction experienced substantial progress, when the Tropical Ocean and Global Atmosphere project of the World Climate Research program(WCRP) was launched. This paper, following a brief description of the history of seasonal climate prediction research, provides an overview of these studies in China. Processes and factors associated with the climate variability and predictability are discussed based on the literature published by Chinese scientists. These studies in China mirror aspects of the climate research effort made in other parts of the world over the past several decades, and are particularly associated with monsoon research in East Asia. As the climate warms, climate extremes, their frequency, and intensity are projected to change, with a large possibility that they will increase. Thus, seasonal climate prediction is even more important for China in order to effectively mitigate disasters produced by climate extremes, such as frequent floods, droughts, and the heavy frozen rain events of South China.

Warren S. G., R. M. Eastman, and C. J. Hahn, 2007: A survey of changes in cloud cover and cloud types over land from surface observations,1971-96.J. Climate,20,717-738,https://doi.org/10.1175/JCLI4031.1.10.1175/JCLI4031.1

92818a7b32e09d28a3aff0f0bdee972b

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2007jcli...20..717w

http://journals.ametsoc.org/doi/abs/10.1175/JCLI4031.1In the middle latitudes of both hemispheres, seasonal anomalies of cloud cover are positively correlated with surface temperature in winter and negatively correlated in summer, as expected if the direction of causality is from clouds to temperature.

Xia X., 2010: A closer looking at dimming and brightening in China during 1961-2005.Annales Geophysicae28,1121-1132,https://doi.org/10.5194/angeo-28-1121-2010.10.5194/angeo-28-1121-2010

9c58ae90204fd2fb2f5ba8ecdd38f870

http%3A%2F%2Fwww.oalib.com%2Fpaper%2F1367863

http://www.ann-geophys.net/28/1121/2010/This study investigates dimming and brightening of surface solar radiation (SSR) during 1961–2005 in China as well as its relationships to total cloud cover (TCC). This is inferred from daily ground-based observational records at 45 pyranometer stations. A statistical method is introduced to study contributions of changes in the frequency of TCC categories and their atmospheric transparency to the secular SSR trend. The surface records suggest a renewed dimming beyond 2000 in North China after the stabilization in the 1990s; however, a slight brightening appears beyond 2000 in South China. Inter-annual variability of SSR is negatively correlated with that of TCC, but there is a positive correlation between decadal variability of SSR and TCC in most cases. The dimming during 1961–1990 is exclusively attributable to decreased atmospheric transparency, a portion of which is offset by TCC frequency changes in Northeast and Southwest China. The dimming during 1961–1990 in Northwest and Southeast China primarily results from decreased atmospheric transparency under all sky conditions and the percentage of dimming stemming from TCC frequency changes is 11% in Northwest and 2% in Southeast China. Decreased atmospheric transparencies during 1991–2005 in North China in most cases lead to the dimming. TCC frequency changes also contribute to the dimming during this period in North China. This feature is more pronounced in summer and winter when TCC frequency changes can account for more than 80% of dimming. In South China, increased atmospheric transparencies lead to the brightening during 1991–2005. A substantial contribution by TCC frequency changes to the brightening is also evident in spring and autumn.

Zhang, R., Coauthors, 2013: Chemical characterization and source apportionment of PM_2.5 in Beijing: Seasonal perspective.Atmos. Chem. Phys.13,7053-7074,https://doi.org/10.5194/acp-13-7053-2013.10.5194/acp-13-7053-2013http://www.atmos-chem-phys.net/13/7053/2013/