International Satellite Cloud Climatology Project: Extending the Record

ISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1°?grid, all other gridded products at 1.0°-equivalent equal-area, separate-satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data), expanded documentation, the processing code and an Operations Guide are available online. Notable changes are: (1) a lowered ice-liquid temperature threshold, (2) a treatment of the radiative effects of aerosols and surface temperature inversions, (3) refined specification of the assumed cloud microphysics, and (4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events.

Examining Cloud Macrophysical Changes over the Pacific for 2007–2017 Using CALIPSO, CloudSat, and MODIS Observations

Cloud macrophysical changes over the Pacific from 2007 to 2017 are examined by combining CALIOP and CloudSat (CALCS) active-sensor measurements, and these are compared with MODIS passive-sensor observations. Both CALCS and MODIS capture well-known features of cloud changes over the Pacific associated with meteorological conditions during El Niño-Southern Oscillation (ENSO) events. For example, mid (cloud tops at 3–10 km) and high (cloud tops at 10–18 km) cloud amounts increase with relative humidity (RH) anomalies. However, a better correlation is obtained between CALCS cloud volume and RH anomalies, confirming more accurate CALCS cloud boundaries than MODIS. Both CALCS and MODIS show that low cloud (cloud tops at 0–3 km) amounts increase with EIS and decrease with SST over the eastern Pacific, consistent with earlier studies. It is also further shown that the low cloud amounts do not increase with positive EIS anomalies if SST anomalies are positive. While similar features are found between CALCS and MODIS low cloud anomalies, differences also exist. First, compared to CALCS, MODIS shows stronger anti-correlation between low and mid/high cloud anomalies over the central and western Pacific, which is largely due to the limitation in detecting overlapping clouds from passive MODIS measurements. Second, compared to CALCS, MODIS shows smaller impacts of mid and high clouds on the low troposphere (< 3 km). The differences are due to the underestimation of MODIS cloud layer thicknesses of mid and high clouds.

Can machine learning correct microwave humidity radiances for the influence of clouds?

A methodology based on quantile regression neural networks (QRNNs) is presented that identifies and corrects the cloud impact on microwave humidity sounder radiances at 183 GHz. This approach estimates the posterior distributions of noise-free clear-sky (NFCS) radiances, providing nearly bias-free estimates of clear-sky radiances with a full posterior error distribution. It is first demonstrated by application to a present sensor, the MicroWave Humidity Sounder 2 (MWHS-2); then the applicability to sub-millimetre (sub-mm) sensors is also analysed. The QRNN results improve upon what operational cloud filtering techniques like a scattering index can achieve but are ultimately imperfect due to limited information content on cirrus impact from traditional microwave channels – the negative departures associated with high cloud impact are successfully corrected, but thin cirrus clouds cannot be fully corrected. In contrast, when sub-mm observations are used, QRNN successfully corrects most cases with cloud impact, with only 2 %–6 % of the cases left partially corrected. The methodology works well even if only one sub-mm channel (325 GHz) is available. When using sub-mm observations, cloud correction usually results in error distributions with a standard deviation less than typical channel noise values. Furthermore, QRNN outputs predicted quantiles for case-specific uncertainty estimates, successfully representing the uncertainty of cloud correction for each observation individually. In comparison to deterministic correction or filtering approaches, the corrected radiances and attendant uncertainty estimates have great potential to be used efficiently in assimilation systems due to being largely unbiased and adding little further uncertainty to the measurements.

Impacts of Stratospheric Ozone Extremes on Arctic High Cloud

&lt;p&gt;Stratospheric ozone depletion in the Antarctic is well known to cause changes in Southern Hemisphere tropospheric climate; however, because of its smaller magnitude in the Arctic, the effects of stratospheric ozone depletion on Northern Hemisphere tropospheric climate are not as obvious or well understood. Recent research using both global climate models and observational data has determined that the impact of ozone depletion on ozone extremes can affect interannual variability in tropospheric circulation in the Northern Hemisphere in spring. To further this work, we use a coupled chemistry&amp;#8211;climate model to examine the difference in high cloud between years with anomalously low and high Arctic stratospheric ozone concentrations. We find that low ozone extremes during the late twentieth century, when ozone-depleting substances (ODS) emissions are higher, are related to a decrease in upper tropospheric stability and an increase in high cloud fraction, which may contribute to enhanced Arctic surface warming in spring through a positive longwave cloud radiative effect. A better understanding of how Arctic climate is affected by ODS emissions, ozone depletion, and ozone extremes will lead to improved predictions of Arctic climate and its associated feedbacks with atmospheric fields as ozone levels recover.&lt;/p&gt;

Intraseasonal Variability of Cloud Cover in Midlatitudes during Boreal Winter

&lt;p&gt;We investigated the spatial structure of the intraseasonal variation (15-30 day) in cloud cover in the mid-latitudes during winter. We attempted to interpret the spatial pattern of clouds in&amp;#12288;the context of Rossby waves.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;We used the total cloud cover in H-series dataset (1984-2016) by the International Satellite Cloud Climatology Project (ISCCP) based on the satellite observations, and ERA-Interim re-analysis data (1980-2016) including high, medium, and low cloud covers defined by &amp;#963; coordinate.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;We calculated correlation coefficients between the geopotential height at 300hPa (Z300) at a certain position and the cloud covers, meridional wind, and vertical velocity in the surrounding area. The positions of the maximum of high (0.45&amp;#8807;&amp;#963;) and medium cloud cover (0.8&amp;#8807;&amp;#963;&amp;#65310;0.45) relative to Z300 are longitudinally constant for all longitudes except the region from east Asia to western part of the Pacific. The position of the maximum of the high cloud cover is located just west of the ridge and just east of the maximum positions of the upward motions of re-analysis vertical velocity and its adiabatic component. These results suggest that the adiabatic upward motion in the southerly wind region west of the ridge contributes to the generation of high cloud cover. In contrast, the position of the maximum of medium cloud cover is located just east of the trough. The position of the maximum of diabatic upward motion, which is consider to be due to condensation process is located near the maximum of medium cloud cover. These results suggest that Rossby waves modulate activity of short-period disturbances with precipitation. Apart from high and medium cloud covers, the position of the maximum of low cloud cover (&amp;#963;&amp;#65310;0.8) has large longitudinal dependency. While the position of the maximum is located at almost the same as that of medium cloud cover mainly over the continent, the position of the maximum is located just east of the ridge mainly over the ocean.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The correlation coefficients between ISCCP total cloud cover and Z300 are statistically significant only over the continent, where the positions of the maximum of high, medium, and low cloud covers are all located east of the trough and west of the ridge.&lt;/p&gt;

Can machine learning correct microwave humidity radiances for the influence of clouds?

A methodology based on quantile regression neural networks (QRNN) is presented that identifies and corrects the cloud impact on microwave humidity sounder radiances at 183 GHz. This approach estimates the posterior distributions of noise free clear-sky (NFCS) radiances, providing nearly bias-free estimates of clear-sky radiances with a full posterior error distribution. It is first demonstrated by application to a present sensor, the MicroWave Humidity Sounder-2 (MWHS-2), then the applicability to sub-millimeter (sub-mm) sensors is also analysed. The QRNN results improve upon what operational cloud filtering techniques like a scattering index can achieve, but are ultimately imperfect due to limited information content on cirrus impact from traditional microwave channels – the negative departures associated with high cloud impact are successfully corrected, but thin cirrus clouds cannot be fully corrected. In contrast, when sub-mm observations are used, QRNN successfully corrects most cases with cloud impact, with only 2–6 % of the cases left partially corrected. The methodology works well even if only one sub-mm channel (325 GHz) is available. When using sub-mm observations, cloud correction usually results in error distributions with standard deviation less than typical channel noise values. Furthermore, QRNN outputs predicted quantiles for case-specific uncertainty estimates, successfully representing the uncertainty of cloud correction for each observation individually. In comparison to deterministic correction or filtering approaches, the corrected radiances and attendant uncertainty estimates have great potential to be used efficiently in assimilation systems due to being largely unbiased and adding little further uncertainty to the measurements.

Study of regional heterogeneity of cloud properties during different rainfall scenarios over monsoon-dominated region

Variability in precipitation pattern is increasing even at regional scale due to advancement in global warming, which could be of higher importance in study for monsoon-dominated region such as India. Precipitation varies with region, thus present study focus on two types of heterogeneous regions: a region closer to coast and an inland region. Long-term analysis over inland region show high cloud fraction and low penetration of outgoing radiation at top of the atmosphere may be due to presence of thicker clouds during southwest monsoon. Further study of cloud parameters show domination of stratiform clouds over nearby coastal region with high range specific humidity (6.67 × 10−6–1.81 × 10−2 kg/kg) and higher cloud effective radius (13.35–15.75 μm), probably due to fewer hygroscopic nuclei. Heterogeneity in rainfall may also depend on types of monsoon (namely, normal, excess and deficit) by altering cloud formation processes. During deficit rain over coastal, clouds are observed at low altitude with high cloud top temperature (−0.52 ± 3.08 °C) but have low specific humidity and lower cloud effective radius, which depict mixed characteristics of stratiform and convective clouds. Thus, it has been observed that cloud characteristics depend largely on the region than rainfall scenario. Such studies can be useful to understand uneven rainfall patterns.

Impacts of Stratospheric Ozone Extremes on Arctic High Cloud

Stratospheric ozone depletion in the Antarctic is well known to cause changes in Southern Hemisphere tropospheric climate; however, because of its smaller magnitude in the Arctic, the effects of stratospheric ozone depletion on Northern Hemisphere tropospheric climate are not as obvious or well understood. Recent research using both global climate models and observational data has determined that the impact of ozone depletion on ozone extremes can affect interannual variability in tropospheric circulation in the Northern Hemisphere in spring. To further this work, we use a coupled chemistry–climate model to examine the difference in high cloud between years with anomalously low and high Arctic stratospheric ozone concentrations. We find that low ozone extremes during the late twentieth century, when ozone-depleting substances (ODS) emissions are higher, are related to a decrease in upper tropospheric stability and an increase in high cloud fraction, which may contribute to enhanced Arctic surface warming in spring through a positive longwave cloud radiative effect. A better understanding of how Arctic climate is affected by ODS emissions, ozone depletion, and ozone extremes will lead to improved predictions of Arctic climate and its associated feedbacks with atmospheric fields as ozone levels recover.

Improved Detection of Interannual Cloud Variability over the Southern Hemisphere Using Legacy Satellites

Shifts in deep tropical convection and midlatitude jet streams both manifest themselves in high cloud anomalies. Such anomalies may play a significant role in local to global climate processes. This work investigates how high cloud properties covary with two primary interannual modes of variability in the Southern Hemisphere (SH): El Niño–Southern Oscillation (ENSO) and the southern annular mode (SAM). In contrast to several recent studies that utilize the latest remote sensing datasets (e.g., CloudSat), we employ a novel combination of imager and sounder data from legacy satellite instruments. Using these legacy data, we confirm the poleward shift of high cloud fields in the SH midlatitudes with SAM seen in other recent studies and characterize the opposing impacts of SAM and ENSO on the South Pacific convergence zone and Southern Hemisphere storm tracks. Furthermore, we demonstrate that the standard deviation of brightness temperature data from the window channel acts as a surrogate for high cloud fraction in the tropics and midlatitudes. Our results reconcile apparent differences in recent studies and suggest that brightness temperature standard deviations are climate relevant, in addition to being largely insensitive to instrument calibration.