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Ryan Eastman and Robert Wood

Abstract

The evolution of subtropical stratocumulus clouds and the boundary layer is studied on daily time scales from the Lagrangian perspective, following the flow. Measures of humidity above the boundary layer and of inversion strength are obtained from reanalysis data, and their effects on the Lagrangian evolution of cloud cover and the boundary layer are compared. An analysis that disentangles these variables and tests their effects independently is developed. Increased inversion strength and increased humidity above the boundary layer lead to anomalously persistent cloud cover and slower Lagrangian deepening of the boundary layer. These parameters affect the stratocumulus boundary layer in different ways: inversion strength controls the buoyancy difference across the inversion, while humidity differences affect both the radiation balance and rate of cloud drop evaporation at cloud top. The relative strengths of the two effects of humidity are compared using two products: the entraining humidity in the layer directly above the inversion and the radiating humidity, which is the mean humidity in the column above the entraining humidity. Results show that the variability in the radiating humidity is the primary driver of Lagrangian boundary layer depth changes, but entraining humidity variation is mostly responsible for altering cloud lifetime.

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Ryan Eastman and Robert Wood

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A Lagrangian technique is developed to sample satellite data to quantify and understand factors controlling temporal changes in low-cloud properties (cloud cover, areal-mean liquid water path, and droplet concentration). Over 62 000 low-cloud scenes over the eastern subtropical/tropical oceans are sampled using the A-Train satellites. Horizontal wind fields at 925 hPa from the ERA-Interim are used to compute 24-h, two-dimensional, forward, boundary layer trajectories with trajectory locations starting on the CloudSat/CALIPSO track. Cloud properties from MODIS and AMSR-E are sampled at the trajectory start and end points, allowing for direct measurement of the temporal cloud evolution. The importance of various controls (here, boundary layer depth, lower-tropospheric stability, and precipitation) on cloud evolution is evaluated by comparing cloud evolution for different initial values of these controls. Viewing angle biases are removed and cloud anomalies (diurnal and seasonal cycles removed) are used throughout to quantify cloud evolution relative to the climatological-mean evolution. Cloud property anomalies show temporal changes similar to those expected for a stochastic red noise process, with linear relationships between initial anomalies and their mean 24-h changes. This creates a potential bias when comparing the evolutions of sets of trajectories with different initial anomalies; three methods are introduced and evaluated to account for this. Results provide statistically robust observational support for theoretical/modeling studies by showing that low clouds in deep boundary layers and under weak inversions are prone to break up. Precipitation shows a more complex and less statistically significant relationship with cloud breakup. Cloud cover in shallow precipitating boundary layers is more persistent than in deep precipitating boundary layers. Liquid water path and cloud droplet concentration decrease more rapidly for precipitating clouds and in deep boundary layers.

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Ryan Eastman and Stephen G. Warren

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An archive of land-based, surface-observed cloud reports has been updated and now spans 39 years from 1971 through 2009. Cloud-type information at weather stations is available in individual reports or in long-term, seasonal, and monthly averages. A shift to a new data source and the automation of cloud reporting in some countries has reduced the number of available stations; however, this dataset still represents most of the global land area.

Global-average trends of cloud cover suggest a small decline in total cloud cover, on the order of 0.4% per decade. Declining clouds in middle latitudes at high and middle levels appear responsible for this trend. An analysis of zonal cloud cover changes suggests poleward shifts of the jet streams in both hemispheres. The observed displacement agrees with other studies.

Changes seen in cloud types associated with the Indian monsoon are consistent with previous work suggesting that increased pollution (black carbon) may be affecting monsoonal precipitation, causing drought in northern India. A similar analysis over northern China does not show an obvious aerosol connection.

Past reports claiming a shift from stratiform to cumuliform cloud types over Russia were apparently partially based on spurious data. When the faulty stations are removed, a trade-off of stratiform and cumuliform cloud cover is still observed, but muted, over much of northern Eurasia.

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Ryan Eastman and Stephen G. Warren

Abstract

Sea ice extent and thickness may be affected by cloud changes, and sea ice changes may in turn impart changes to cloud cover. Different types of clouds have different effects on sea ice. Visual cloud reports from land and ocean regions of the Arctic are analyzed here for interannual variations of total cloud cover and nine cloud types, and their relation to sea ice.

Over the high Arctic, cloud cover shows a distinct seasonal cycle dominated by low stratiform clouds, which are much more common in summer than winter. Interannual variations of cloud amounts over the Arctic Ocean show significant correlations with surface air temperature, total sea ice extent, and the Arctic Oscillation. Low ice extent in September is generally preceded by a summer with decreased middle and precipitating clouds. Following a low-ice September there is enhanced low cloud cover in autumn. Total cloud cover appears to be greater throughout the year during low-ice years.

Multidecadal trends from surface observations over the Arctic Ocean show increasing cloud cover, which may promote ice loss by longwave radiative forcing. Trends are positive in all seasons, but are most significant during spring and autumn, when cloud cover is positively correlated with surface air temperature. The coverage of summertime precipitating clouds has been decreasing over the Arctic Ocean, which may promote ice loss.

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Ryan Eastman and Stephen G. Warren

Abstract

Visual cloud reports from land and ocean regions of the Arctic are analyzed for total cloud cover. Trends and interannual variations in surface cloud data are compared to those obtained from Advanced Very High Resolution Radiometer (AVHRR) and Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) satellite data. Over the Arctic as a whole, trends and interannual variations show little agreement with those from satellite data. The interannual variations from AVHRR are larger in the dark seasons than in the sunlit seasons (6% in winter, 2% in summer); however, in the surface observations, the interannual variations for all seasons are only 1%–2%. A large negative trend for winter found in the AVHRR data is not seen in the surface data. At smaller geographic scales, time series of surface- and satellite-observed cloud cover show some agreement except over sea ice during winter. During the winter months, time series of satellite-observed clouds in numerous grid boxes show variations that are strangely coherent throughout the entire Arctic.

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Ryan Eastman and Stephen G. Warren

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A worldwide climatology of the diurnal cycles of low clouds is obtained from surface observations made eight or four times daily at 3- or 6-h intervals from weather stations and ships. Harmonic fits to the daily cycle are made for 5388 weather stations with long periods of record, and for gridded data on a 5° × 5° or 10° × 10° latitude–longitude grid over land and ocean areas separately.

For all cloud types, the diurnal cycle has larger amplitude over land than over ocean, on average by a factor of 2. Diurnal cycles of cloud amount appear to be proprietary to each low cloud type, showing the same cycle regardless of whether that type dominates the diurnal cycle of cloud cover. Stratiform cloud amounts tend to peak near sunrise, while cumuliform amounts peak in the afternoon; however, cumulonimbus amounts peak in the early morning over the ocean. Small latitudinal and seasonal variation is apparent in the phase and amplitude of the diurnal cycles of each type. Land areas show more seasonality compared to ocean areas with respect to which type dominates the diurnal cycle.

Multidecadal trends in low cloud cover are small and agree between day and night regardless of the local climate.

Diurnal cycles of base height are much larger over land than over the ocean. For most cloud types, the bases are highest in the midafternoon or early evening.

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Ryan Eastman, Robert Wood, and Christopher S. Bretherton

Abstract

The Lagrangian evolution of cloud cover and cloud-controlling variables is well approximated using red noise processes with different autocorrelation time scales for each variable. Trajectories within the subtropical marine boundary layer are generated using winds from ECMWF Re-Analysis data for low cloud decks in four eastern subtropical ocean basins. Cloud cover, liquid water path, and boundary layer depth are sampled at 12-h intervals using A-Train satellites, and droplet concentration is sampled every 24 h. Lower-tropospheric stability and vertical velocity are sampled concurrently using reanalysis data. Samples are converted to seasonal and diurnal anomalies. Data are spatially averaged over a range of length scales. The e-folding decay times τ for autocorrelation are calculated for each variable based on lag times of 12, 24, 36, and 48 h. Using lag 24 h and an averaging radius of 100 km, τ ≈ 15–17 h for liquid water path and vertical velocity, τ ≈ 19 h for cloud cover, τ ≈ 24–25 h for boundary layer depth and droplet concentration, and τ ≈ 53 h for lower-tropospheric stability.

Time scales vary somewhat between regions and are shortest in the eastern Indian Ocean. Decay time τ increases with averaging scale and the autocorrelation e-folding length of a variable at a fixed time. Diurnal analysis shows cloud cover anomalies have a stronger memory during morning breakup, while other variables show stronger memory as clouds reform in the evening. Lagrangian cloud anomalies are less persistent than anomalies at a fixed location. For the latter, estimated τ values can vary significantly at different lag times, so a red noise assumption is inappropriate.

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Ryan Eastman, Matthew Lebsock, and Robert Wood

Abstract

Collocated CloudSat rain rates and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 89-GHz brightness temperature T b retrievals allow for the development of an algorithm to estimate light, warm rain statistics as a function of AMSR-E 89-GHz T b for shallow marine clouds. Four statistics are calculated from CloudSat rainfall rate estimates within each 4 km × 6 km T b pixel sampled by both sensors: the probability of rainfall, the mean rain rate, the mean rate when raining, and the maximum rain rate. Observations with overlying cold clouds are removed from the analysis. To account for confounding variables that modify T b, curves are fit to the mean relationships between T b and these four statistics within bins of constant column-integrated water vapor from AMSR-E, and sea surface temperature and wind speed from reanalysis grids. The coefficients that define these curves are then applied to all available AMSR-E T b retrievals to estimate rain rate throughout the eastern subtropical oceans. A preliminary analysis shows strong agreement between AMSR-E rain rates and the CloudSat training dataset. Comparison with an existing microwave precipitation product shows that the new statistical product has an improved sensitivity to light rain. A climatology for the year 2007 shows that precipitation rates tend to be heavier where the sea surface is warmer and that rain is most frequent where stratocumulus transitions to trade cumulus in the subtropics.

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Ryan Eastman, Robert Wood, and Kuan Ting O

Abstract

Prior work has shown that deeper planetary boundary layers (PBLs) are associated with cloud breakup and reduced droplet concentration in subtropical stratocumulus cloud decks, motivating a need for a thorough understanding of PBL mechanics. Here, 169 000 boundary layer trajectories are calculated in four eastern subtropical ocean basins following reanalysis winds at 925 mb (1 mb = 1 hPa). These trajectories combined with a twice-daily cloud-top-height-inferred PBL depth product allow for a comprehensive Lagrangian analysis of the stratocumulus (Sc)-topped PBL as the cloud deck transitions from Sc to trade cumulus (Cu). Month-to-month variations of this PBL product are strongly positively correlated with an independent PBL product derived from GPS radio occultation.

A climatology shows the PBL deepening offshore in every region. The yearly cycle of PBL depth varies in opposition to the yearly cycle of lower-tropospheric stability (LTS), but high-frequency variation between LTS and PBL depth is more complex. Observed geographical patterns of Lagrangian PBL deepening rates appear nonuniform between and within study regions, with smaller regions of maximum deepening rates. A Lagrangian analysis suggests that many variables act to alter the PBL: increased sea surface temperature and droplet concentration act to deepen the PBL, while increases in upper-level humidity, LTS, precipitation, upper-level temperature, and subsidence lead to PBL shallowing.

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Ryan Eastman, Christopher R. Terai, Daniel P. Grosvenor, and Robert Wood

Abstract

A Lagrangian framework is developed to show the daily-scale time evolution of low clouds over the eastern subtropical oceans. An identical framework is applied to two general circulation models (GCMs): the CAM5 and UKMET and a set of satellite observations. This approach follows thousands of parcels as they advect downwind in the subtropical trade winds, comparing cloud evolution in time and space. This study tracks cloud cover, in-cloud liquid water path (CLWP), droplet concentration N d, planetary boundary layer (PBL) depth, and rain rate as clouds transition from regions with predominately stratiform clouds to regions containing mostly trade cumulus. The two models generate fewer clouds with greater N d relative to observations. Models show stronger Lagrangian cloud cover decline and greater PBL deepening when compared with observations. In comparing frequency distributions of cloud variables over time, it is seen that models generate increasing frequencies of nearly clear conditions at the expense of overcast conditions, whereas observations show transitions from overcast to cloud amounts between 50% and 90%. Lagrangian decorrelation time scales (e-folding time τ) of cloud cover and CLWP are between 11 and 19 h for models and observations, although they are a bit shorter for models. A Lagrangian framework applied here resolves and compares the time evolution of cloud systems as they adjust to environmental perturbations in models and observations. Increasing subsidence in the overlying troposphere leads to declining cloud cover, CLWP, PBL depth, and rain rates in models and observations. Modeled cloud responses to other meteorological variables are less consistent with observations, suggesting a need for continuing mechanical improvements in GCMs.

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