types of cloud cover

Meteorol. J. Appl. On the other hand, Africa, the Middle East and Australia are dominated by clear skies. Cloud, any visible mass of water droplets, ice crystals, or a mixture of both that is suspended in the air, usually at a considerable height (see video). Even though instantaneous cloud properties may not be very accurate and might include scene dependent biases, the synergy of different variables and data sets provide invaluable potential for improving our understanding of cloud processes. Amer. Atmos. [1] Okta is the usual unit of measurement of the cloud cover. Menzel, W. P., R. A. Frey, H. Zhang, D. P. Wylie, C. C. Moeller, R. E. Holz, B. Maddux, B. Active lidar, IR sounding and IR spectral differences are powerful for thin cirrus identification (with decreasing sensitivity from the former to the latter). (from Stubenrauch et al. 2012. 2). and R.A. Schiffer, 1991: ISCCP Cloud Data Products. Another way to reduce uncertainties is by organizing statistics by mesoscale cloud regimes or weather states (e. g. Jakob and Tselioudis 2003, Tselioudis et al. Probability - High Temperatures - Low Temperatures - Cloud Cover - Wind - Relative Humidity - Dewpoint - Snowfall SEASONAL FORECASTS - Temperature - Precipitation Meteor. "The Climate Data Guide: Cloud Dataset Overview." [6], On a regional scale, it can be also worthy of note that some extensive areas of Earth experience cloudy conditions virtually all time such as South America's Amazon Rainforest while other ones experience clear-sky conditions virtually all time such as Africa's Sahara Desert.[6]. To complement this information a coupling with the radar of the CloudSat mission is necessary, but still their instantaneous Earth coverage is very small (5%). Global cloud amount (CA) is about 0.68 ± 0.03, considering clouds with COD > 0.1. Color: White or gray. source: fun-in-first.blogspot.com. These meteorological satellites, however, see more than clouds and cloud systems. Phys., 17, 13625-13644, doi :10.5194/acp-17-13625-2017. Their success has been shown in many published analyses, also in combination with other observations. Nature gave scientists an example of how even a small change in cloud cover could have a significant effect Stubenrauch, Claudia & National Center for Atmospheric Research Staff (Eds). Res., 100, 1137-1147. Retrieved from https://climatedataguide.ucar.edu/climate-data/cloud-dataset-overview. Though they vary in shape and size, all clouds are basically formed in the same way through the vertical of air above the condensation level. A weather satellite is a type of satellite that is primarily used to monitor the weather and climate of the Earth. Polar stratospheric clouds are located in a layer of the atmosphere called the stratosphere. A comparison between AIRS and CALIPSO (Stubenrauch et al. Wylie, D. P., D. L. Jackson, W. P. Menzel, and J. J. Bates, 2005: Trends in Global Cloud Cover in two Decades of HIRS Observations, J. Nadir viewing with cross-track scanning capabilities, they have a spatial resolution from about 0.5 to 7 km (at nadir) and are the only sensors aboard geostationary weather satellites.Multi-spectral imagers aboard SSO satellites are the Advanced Very High Resolution Radiometer (AVHRR, with 5 spectral channels) and the MODerate resolution Imaging Spectroradiometer (MODIS with 36 spectral channels). Amer. Geosci. However, one has to keep in mind that these simulators contain the observation biases identified by the GEWEX cloud assessment and may still include other biases. Cloud cover may also influence temperatures at the surface of the planet. 2012), Figure 4: Normalized frequency distributions of CP in tropics (15N-15S), midlatitudes (30°-60°) and polar latitudes (60°-90°), separately over ocean and over land, during daytime. Cirrus - Cirrus clouds are high level clouds that are thin and wispy. 1995), almost 70% of the high-level clouds in the tropics have a diffuse cloud top, leading to an average positive bias of ISCCP in cloud top pressure of about 150 hPa. Stubenrauch C. J., W. B. Rossow, S. Kinne, S. Ackerman, G. Cesana, H. Chepfer, L. Di Girolamo, B. Getzewich, A. Guignard, A. Heidinger, B. C. Maddux, W. P. Menzel, P. Minnis, C. Pearl, S. Platnick, C. Poulsen,  J. Riedi, S. Sun-Mack, A. Walther, D. Winker, S. Zeng, and G. Zhao, Assessment of Global Cloud Datasets from Satellites: Project and Database initiated by the GEWEX Radiation Panel. If a number of different layers of cloud are present the partial amount of each one will be reported. The latter can be interpreted as the amount of all low-level clouds relative to all clouds. The type and amount of clouds that commonly form over a region impact the precipitation conditions. Shape: Rows of small patchy clouds. Meteor. Differences in average cloud properties, especially in high-level cloud amount, are mostly explained by instrument performance to detect and/or identify thin cirrus. They generally form from convection, with air parcels rising vertically into the atmosphere (called updrafts) and condensing into the puffy, cotton-like clouds that we all know and love. A. Baum, K. I. Strabala, and L. E. Gumley, 2008: MODIS Global Cloud-Top Pressure and Amount Estimation: Algorithm Description and Results. This value is lower (0.56) when considering clouds with an optical depth larger than 2, and higher when counting subvisible cirrus clouds. The CO2 slicing retrieval employed by HIRS-NOAA is not applicable to low-level clouds, while a weighted c2 retrieval of TOVS Path-B and AIRS-LMD may be applied to all clouds. Since 2006 the CALIPSO lidar and CloudSat radar, together, determine cloud top and base heights of all cloud layers. However, diurnal variation in cloud physical properties and seasonal variation of optical and microphysical properties show still some inconsistencies. [3], Cloud cover values only vary by 0.03 from year to year, whereas the local, day to day variability in cloud amount typically rises to 0.3 over the globe. Chem. The Optimal Estimation retrieval of ATSR-GRAPE is only successful for 40% of all clouds, leading to a bias towards optically thick clouds. When comparing to climate models, observation time and view from above as well as retrieval filtering have to be taken into account. Stratus clouds. The types of clouds in the sky include the stratus, cumulus, stratocumulus, altocumulus, altostratus, cirrus, cirrostratus, cirrocumulus, cirrostratus, nimbostratus, and cumulonimbus. A. Guignard, and N. Lamquin, 2010: A six-year global cloud climatology from the Atmospheric InfraRed Sounder aboard the Aqua Satellite: statistical analysis in synergy with CALIPSO and CloudSat. 2010) or by more sophisticated ones, like the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (Bodas-Salcedo et al. Therefore high-level clouds correspond to all high-level cloud situations, including single and multiple cloud layers, whereas mid-level and low-level clouds correspond only to situations with no higher altitude clouds above. On the other hand, the long path leads to detection of subvisible (very thin) cirrus. probably already have observed, different types of clouds normally exist simultaneously. 2012), Figure 3: Regional maximum differences of CA, CAHR, and CALR within six cloud data sets (ISCCP, PATMOS-x, MODIS-ST, MODIS-CE, AIRS-LMD and TOVS Path-B). About 40% (COD > 0.1) – 50% (COD > 0.01) of all clouds seen from above are high-level clouds. Bull. Climate, 18, 3021-3031. Oceanic Technol., 26, 2310–2323. Also the cloud amount day-night correction has not been applied, leading to a slight degradation of the original data. CEM and COD are quite complementary, as CEM better resolves differences in thinner cirrus clouds, while it saturates at 1 when COD still can distinguish the optically thickest clouds. Rossow, W.B. The very sharp peak of PATMOS-x seems to be suspect, though the PATMOS-x retrieval had been trained by CALIPSO data. About 40% (±3%) of all clouds are single-layered low-level clouds. POLDER), it corresponds to a location even deeper inside the cloud. Res., 108, 10.1029/2002JD002801. However, CAHR shows a spread from 12% to 55%. These 10 types of clouds are then characterized into the different altitudes in which they typically are found. Such a cloud would be known as fog, ice fog, or mist.The types of clouds can be divided into three levels, each in turn with its own ma… J. Partial cloud amount is the fraction of the sky covered by each type or layer of cloud as if it was the only type or layer of cloud in the sky. Climate, 26, 7734-7746. However the retrieval method employed in Collection 5 led to some misidentification of very thin cirrus as low-level clouds. Clouds may also form in contact with the ground surface, too. This type of day includes some clouds and some bright sunshine. Platnick, S., M. D. King, S. A. Ackerman, W. P. Menzel, B. Effective particle sizes (CRE) influences more the spectral behaviour of emitted to reflected radiation, especially for small particles. The GEWEX cloud assessment (2005-2012, Stubenrauch et al. ISCCP DEFINITION OF CLOUD TYPES Cloud Parameter Definitions And Measurement Methods. IR sounders use IR channels along the CO2 absorption band to determine cloud height and emissivity. Z. Trepte, W. L. Smith, Jr., J. K. Ayers, S. C. Gibson, W. F. Miller, V. Chakrapani, Y. Takano, K.-N. Liou, Y. Xie, and P. Yang, 2011: CERES Edit, Parol, F., J. C. Buriez, C. Vanbauce, J. Riedi, L. C. Labonnote, M. Doutriaux-Boucher, M. Vesperini, G. Sèze, P. Couvert, M. Viollier, F. M. Bréon, 2004: Capabilities of multi-angle polarization cloud measurements from satellite: POLDER results, Adv. Monitoring long-term climate variability is difficult with these data sets. Infrared (day and night) Cloud Tops Alert (day and night) Mon. Climatol, Minnis, P., S. Sun-Mack, D. F. Young, P. W. Heck, D. P. Garber, Y. Chen, D. A. Spangenberg, R. F. Arduini, Q. Walther, A., and A. Heidinger, 2012: Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x. ... Isolated cirrus occur in fair weather. a climatology of total cloud cover and the amounts of nine cloud types. Amer. Machado, L.A.T., and W.B. The following was submitted by Dr. Claudia Stebenrauch, CNRS, LMB, France, in June 2018: Cloud properties derived from space observations are extremely valuable for climate studies and model evaluation: Multi-spectral imagers are radiometers that measure reflected, emitted and scattered radiation at a few discrete wavelengths, usually from the solar to thermal infrared spectrum. Multi-angle, multi-spectral imagers make measurements of the same scene with different viewing angles, allowing a stereoscopic retrieval of cloud top height. Cirrocumulus… 2. Height: High. Stubenrauch C. and coAuthors: 2013: Assessment of Global Cloud Datasets from Satellites: Project and Database initiated by the GEWEX Radiation Panel. Soc., 94, 1034-1049. J. Geophys. Using Clouds to Predict the Weather Cumulus Clouds: All Is Fair. From CALIPSO we deduced that these cases constitute about 20% of all clouds, each contributing to an overestimation of about 10% in global CAMR and an underestimation in CAHR by ISCCP. However, high-level clouds may be misidentified as mid-level clouds in the case of thin cirrus during night and thin cirrus overlying low-level clouds during day. Substantiating and Figure 1 illustrates cloud types distinguished by cloud base height and morphology, as initially classified by surface observers. Outliers are HIRS-NOAA with 26% (only one IR channel for low-level clouds), MODIS-ST with 53% (misidentification of very thin cirrus in collection 5) and MISR with 62% (good spatial resolution but only visible information). Light blue areas to indigo represent a partly cloudy sky condition. This is the reason why average values of CP (CT / CZ) may be ambiguous and why it is better to use, in addition to averages over all clouds, the height-stratified averages of the different cloud properties. 2): Whereas active lidar and IR spectral information determine the cloud properties of the cirrus (CALIPSO-ST, CALIPSO-GOCCP, HIRS-NOAA, TOVS Path-B, AIRS-LMD, MODIS-ST, MODIS-CE, PATMOS-x), IR – VIS methods (ISCCP, ATSR-GRAPE) provide the properties corresponding to a radiative mean from both clouds and VIS-only methods emphasize the clouds underneath (MISR, POLDER). While the global range between these six datasets corresponds to only 0.08 in CA and 20% in CAHR and CALR (Fig. These agree quite well, when one considers retrieval filtering or possible biases due to partly cloudy pixels and due to ice-water misidentification. GRL 30, 2082, doi:10.1029/2003GL018367. Climatol., 51, 1371-1390. (from Stubenrauch et al. 3. Whereas the lidar is highly sensitive and can even detect sub-visible cirrus, its beam reaches cloud base only for clouds with an optical depth less than 3. Specific care has been given to the averaging procedure from instantaneous L2 to monthly, gridded L3 cloud products: 1) averaging the original L2 cloud products over each grid cell (1° x 1°) for each specific local time and 2) averaging these grid cell averages over the month. Meteor. Foster, and A. Walther, 2012: A Naïve Bayesian Cloud Detection Scheme Derived from CALIPSO and Applied within PATMOS-x. This is a 9 page free download half-page printable book. 2. Remote Sens., 41, 459-473. The variable atmospheric opacity of the many channels of these IR sounding instruments allows a reliable identification of cirrus (semi-transparent ice clouds), day and night. Clouds cover about 70% of the earth's surface. Bull. Recent Infographics. In general, passive remote sensing provides cloud properties as observed from above. Cloud cover (also known as cloudiness, cloudage, or cloud amount) refers to the fraction of the sky obscured by clouds when observed from a particular location. The PATMOS-x data show improvement in the identification of cirrus. nighttime, thin cirrus overlaying low-level clouds, highly reflective or cold surfaces) and depend on instrument spectral domain and retrieval methodology. J. Appl. http://climserv.ipsl.polytechnique.fr/gewexca/index-1.html, https://doi.org/10.1175/BAMS-D-12-00117.1, The GEWEX Cloud Assessment Database, created by the participating teams (see Technical Notes), contains monthly means, variability and distributions of many cloud properties, also stratified by height and thermodynamic phase, Link to description and download of individual datasets that were used in the database (see also Technical Notes), Stubenrauch, C. J., and Coauthors, 2013: Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel. 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