Abstract
The characteristics of ice clouds with a wide range of optical depths are studied based on satellite retrievals and radiative transfer modeling. Results show that the global-mean ice cloud ...optical depth, ice water path, and effective radius are approximately 2, 109 g m−2, and 48 , respectively. Ice cloud occurrence frequency varies depending not only on regions and seasons, but also on the types of ice clouds as defined by optical depth values. Ice clouds with different values show differently preferential locations on the planet; optically thinner ones ( < 3) are most frequently observed in the tropics around 15 km and in midlatitudes below 5 km, while thicker ones ( > 3) occur frequently in tropical convective areas and along midlatitude storm tracks. It is also found that ice water content and effective radius show different temperature dependence among the tropics, midlatitudes, and high latitudes. Based on analyzed ice cloud frequencies and microphysical properties, cloud radiative forcing is evaluated using a radiative transfer model. The results show that globally radiative forcing due to ice clouds introduces a net warming of the earth–atmosphere system. Those with < 4.0 all have a positive (warming) net forcing with the largest contribution by ice clouds with ~ 1.2. Regionally, ice clouds in high latitudes show a warming effect throughout the year, while they cause cooling during warm seasons but warming during cold seasons in midlatitudes. Ice cloud properties revealed in this study enhance the understanding of ice cloud climatology and can be used for validating climate models.
Although it is well established that cirrus warms Earth, the radiative effect of the entire spectrum of ice clouds is not well understood. In this study, the role of all ice clouds in Earth’s ...radiation budget is investigated by performing radiative transfer modeling using ice cloud properties retrieved from CloudSat and CALIPSO measurements as inputs. Results show that, for the 2008 period, the warming effect (∼21.8 ± 5.4 W m−2) induced by ice clouds trapping longwave radiation exceeds their cooling effect (∼−16.7 ± 1.7 W m−2) caused by shortwave reflection, resulting in a net warming effect (∼5.1 ± 3.8 W m−2) globally on the earth–atmosphere system. The net warming is over 15 W m−2 in the tropical deep convective regions, whereas cooling occurs in the midlatitudes, which is less than 10 W m−2 in magnitude. Seasonal variations of ice cloud radiative effects are evident in the midlatitudes where the net effect changes from warming during winter to cooling during summer, whereas warming occurs all year-round in the tropics. Ice cloud optical depth τ is shown to be an important factor in determining the sign and magnitude of the net radiative effect. Ice clouds with τ < 4.6 display a warming effect with the largest contributions from those with τ ≈ 1.0. In addition, ice clouds cause vertically differential heating and cooling of the atmosphere, particularly with strong heating in the upper troposphere over the tropics. At Earth’s surface, ice clouds produce a cooling effect no matter how small the τ value is.
Southern Ocean sea-ice cover exerts critical control on local albedo and Antarctic precipitation, but simulated Antarctic sea-ice concentration commonly disagrees with observations. Here we show that ...the radiative effects of precipitating ice (falling snow) contribute substantially to this discrepancy. Many models exclude these radiative effects, so they underestimate both shortwave albedo and downward longwave radiation. Using two simulations with the climate model CESM1, we show that including falling-snow radiative effects improves the simulations relative to cloud properties from CloudSat-CALIPSO, radiation from CERES-EBAF and sea-ice concentration from passive microwave sensors. From 50-70°S, the simulated sea-ice-area bias is reduced by 2.12 × 106 km2 (55%) in winter and by 1.17 × 106 km2 (39%) in summer, mainly because increased wintertime longwave heating restricts sea-ice growth and so reduces summer albedo. Improved Antarctic sea-ice simulations will increase confidence in projected Antarctic sea level contributions and changes in global warming driven by long-term changes in Southern Ocean feedbacks.
Recent Arctic sea ice retreat has been quicker than in most general circulation model (GCM) simulations. Internal variability may have amplified the observed retreat in recent years, but reliable ...attribution and projection requires accurate representation of relevant physics. Most current GCMs do not fully represent falling ice radiative effects (FIREs), and here we show that the small set of Coupled Model Intercomparison Project Phase 5 (CMIP5) models that include FIREs tend to show faster observed retreat. We investigate this using controlled simulations with the CESM1-CAM5 model. Under 1pctCO2 simulations, including FIREs results in the first occurrence of an “ice-free” Arctic (monthly mean extent <1×106 km2) at 550 ppm CO2, compared with 680 ppm otherwise. Over 60–90∘ N oceans, snowflakes reduce downward surface shortwave radiation and increase downward surface longwave radiation, improving agreement with the satellite-based CERES EBAF-Surface dataset. We propose that snowflakes' equivalent greenhouse effect reduces the mean sea ice thickness, resulting in a thinner pack whose retreat is more easily triggered by global warming. This is supported by the CESM1-CAM5 surface fluxes and a reduced initial thickness in perennial sea ice regions by approximately 0.3 m when FIREs are included. This explanation does not apply across the CMIP5 ensemble in which inter-model variation in the simulation of other processes likely dominates. Regardless, we show that FIRE can substantially change Arctic sea ice projections and propose that better including falling ice radiative effects in models is a high priority.
The characteristics of ice clouds with a wide range of optical depths are studied based on satellite retrievals and radiative transfer modeling. Results show that the global-mean ice cloud optical ...depth, ice water path, and effective radius are approximately 2, 109 g m−2, and 48μm, respectively. Ice cloud occurrence frequency varies depending not only on regions and seasons, but also on the types of ice clouds as defined by optical depthτvalues. Ice clouds with differentτvalues show differently preferential locations on the planet; optically thinner ones (τ< 3) are most frequently observed in the tropics around 15 km and in midlatitudes below 5 km, while thicker ones (τ< 3) occur frequently in tropical convective areas and along midlatitude storm tracks. It is also found that ice water content and effective radius show different temperature dependence among the tropics, midlatitudes, and high latitudes. Based on analyzed ice cloud frequencies and microphysical properties, cloud radiative forcing is evaluated using a radiative transfer model. The results show that globally radiative forcing due to ice clouds introduces a net warming of the earth–atmosphere system. Those withτ< 4.0 all have a positive (warming) net forcing with the largest contribution by ice clouds withτ∼ 1.2. Regionally, ice clouds in high latitudes show a warming effect throughout the year, while they cause cooling during warm seasons but warming during cold seasons in midlatitudes. Ice cloud properties revealed in this study enhance the understanding of ice cloud climatology and can be used for validating climate models.
This study examines the climatology of cloud phase over
Southeast Asia (SEA) based on A-Train satellite
observations. Using the combined CloudSat–CALIPSO (CC) data, five main cloud
groups ...are investigated: ice-only, ice-above-liquid, liquid-only,
ice-above-mixed, and mixed-only clouds that have annual mean frequencies of
28.6 %, 20.1 %, 16.0 %, 9.3 %, and 6.7 %, respectively. Liquid-only
clouds tend to occur in relatively cold, dry, and stable lower
troposphere. The other four cloud groups appear more frequently in
relatively warm, humid, and unstable conditions, and their seasonal
distributions move with the Asian monsoon and the Intertropical Convergence
Zone (ITCZ). Liquid clouds are found to be highly inhomogeneous based on the
heterogeneity index (Hσ) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), while ice-only and
mixed-only clouds are often very smooth. Ice-above-liquid clouds are more
heterogeneous than ice-only clouds owing to ice clouds being optically
thin. We demonstrate that the distribution of clear-sky
Hσ has a long tail towards heterogeneous values
that are caused by undetected subpixel cloud within both CC and MODIS
datasets. The reflectance at 0.645 µm (R0.645) and brightness
temperature at 11 µm (BT11) of CC ice-only, liquid-only, and
ice-above-liquid clouds show peak frequencies near that of clear sky (R0.645∼0.02; BT11∼294 K), which explains why up to
30 % of these CC cloud groups are classified as clear by MODIS. In
contrast, mixed-only clouds are thick (average top ∼13 km),
bright (average R0.645∼0.6), and cold (average BT11
∼234 K). Cloud phase comparison between CC and MODIS reveals
only modest agreement, with the best agreement (73 %) occurring between CC
ice-above-mixed and MODIS ice clouds. The intraseasonal and interannual
behaviors of the all-sky Hσ and spectral signatures follow that of cloud
phase and vary with the Madden–Julian oscillation (MJO) and the El
Niño–Southern Oscillation (ENSO) phases.
The World Meteorological Organizations' International Cloud Atlas recognizes 10 basic cloud genera for classifying clouds. Many of these have been used for over 200 years and are based on cloud ...appearance and base altitude as seen from surface. Over the satellite era, several missions and programs provide public products that classify clouds into these cloud genera. Here, we provide the first comparison of three such satellite climatologies of cloud genera with surface observations. Specifically, we analyse 10 years (2007–2016) of CloudSat, 4 years (2007–2010) of joint CloudSat‐CALIPSO, 13 years (2000–2012) of ISCCP‐H, and 11 years (1998–2008) of the EECRA data between 50°N and 50°S for eight cloud genera. Averaged over this latitude range, the total cloud amounts for these datasets range from 0.56 to 0.65, with Cumulus (Cu) ranging from 0.06 to 0.14; Stratus (St) from 0.14 to 0.38; Altostratus (As) from 0.05 to 0.13; Altocumulus (Ac) from 0.07 to 0.17; Nimbostratus (Ns) from 0.03 to 0.06; Cirrus (Ci) from 0.1 to 0.19; and Deep‐convective (Dc) from 0.01 to 0.04. The largest disagreement among the sensors is observed for Dc cloud with the coefficient of variation of 44%. On the other hand, the cloud datasets show the best agreement for Ci cloud with the coefficient of variation of 24.1%. Regionally, however, the level of agreement and disagreement can vary drastically. For example, in Indian summer monsoon region (ISM 60°–90°E, 10°–30°N) Ci cloud shows a variation of 28%, whereas the Dc cloud shows 16% variation, which is the opposite of their near‐global feature. The observed discrepancies in cloud genera are discussed in terms of observing characteristics, including instrument, methods, and sampling. Greater effort is still required to reduce discrepancies among these datasets, and the assessment provided here can act as a guide for their use in climate studies.
Clouds affect the global energy and the water cycle, the magnitude of which depends on the individual cloud types. Here, we present the first comparative assessment of the near‐global view of individual cloud types from four state‐of‐the‐art satellite and in situ datasets. The discrepancy of cloud fraction for different cloud genera and regions can be attributed to the sensors' ability in identifying specific cloud types.
A full understanding of the climatological properties of aerosols is an important step towards characterizing their effects on climate. Utilizing the observations from Cloud‐Aerosol Lidar and ...Infrared Pathfinder Satellite Observations, we study cloud‐free and cloudy aerosol properties with attention on aerosol and cloud layer relative vertical positions. On a global scale, the cloud‐free aerosols account for about 56% of all detected aerosols with a mean optical depth (τ¯a ${\bar{\tau }}_{a}$) and mean uncertainty of 0.135 ± 0.047. The cloudy aerosols, accounting for 44%, have a larger τ¯a ${\bar{\tau }}_{a}$ and larger mean uncertainty of 0.143 ± 0.074 compared to the cloud‐free aerosols. The above‐cloud aerosols (∼4%), primarily composed of elevated smoke, dust/volcanic ash and polluted dust, have a much smaller τ¯a ${\bar{\tau }}_{a}$ of (0.056 ± 0.038). The below‐cloud aerosols (∼21%) have τ¯a ${\bar{\tau }}_{a}$ ∼ 0.165 ± $\pm \,$ 0.087. The below‐cloud and cloud‐free aerosols show close τa ${\tau }_{a}$ probability density distributions and similar aerosol types, indicating that cloud‐free aerosol climatologies from passive sensors are likely representative of all‐sky conditions. In addition, about 27% of the detected aerosol profiles are found to have cloud layers vertically connected to the detected aerosol layers. The lidar backscatter profiles of these aerosols have larger median values than the cloud‐free, above‐cloud and below‐cloud aerosols. The seasonal variations of the cloud‐free and the cloudy aerosols significantly vary with regions. Our results imply that quantifying the impact of clouds, particularly cirrus due to the wide coverage of cirrus‐aerosol overlap, on aerosol direct radiative effect is crucial to assess aerosols' roles in the Earth‐climate system.
Key Points
This study reveals that the below‐cloud aerosols may share similar properties with those without overlying clouds
The wide coverage of the below‐cloud aerosols indicates a likely significant impact of cirrus on aerosol direct radiative effect
Regional and seasonal variations of the cloud‐free and cloudy aerosols strongly depend on the local climate and long‐range transport
Cloud‐top heights (CTH) from the Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra constitute our longest‐running single‐platform CTH ...record from a stable orbit. Here, we provide the first evaluation of the Terra Level 2 CTH record against collocated International Space Station Cloud‐Aerosol Transport System (CATS) lidar observations between 50ºN and 50ºS. Bias and precision of Terra CTH relative to CATS is shown to be strongly tied to cloud horizontal and vertical heterogeneity and altitude. For single‐layered, unbroken, optically thick clouds observed over all altitudes, the uncertainties in MODIS and MISR CTH are −540 ± 690 m and −280 ± 370 m, respectively. The uncertainties are generally smaller for lower altitude clouds and larger for optically thin clouds. For multi‐layered clouds, errors are summarized herein using both absolute CTH and CATS‐layer‐altitude proximity to Terra CTH. We show that MISR detects the lower cloud in a two‐layered system, provided top‐layer optical depth <∼0.3, but MISR low‐cloud CTH errors are unaltered by the presence of thin cirrus. Systematic and random errors are propagated to explain inter‐sensor disagreements, as well as to provide the first estimate of the MISR stereo‐opacity bias. For MISR, altitude‐dependent wind‐retrieval bias (−90 to −110 m) and stereo‐opacity bias (−60 to −260 m) and for MODIS, CO2‐slicing bias due to geometrically thick cirrus leads to overall negative CTH bias. MISR’s precision is largely driven by precision in retrieved wind‐speed (3.7 m s−1), whereas MODIS precision is driven by forward‐modeling uncertainty.
Plain Language Summary
Cloud‐top height (CTH) is an essential climate variable that impacts the Earth’s energy budget and hydrological cycle. We are greatly interested in CTHs for their possible application in detecting signatures of forced climate change in the more than two‐decade long (2000–present) CTH record from NASA’s enduring mission, Terra. Since Terra has offered longevity and orbital stability, the remaining criterion for a successful climate dataset is an in‐depth understanding and quantification of uncertainty in the data. To ascertain the uncertainty of CTH retrievals from two Terra instruments, namely MISR and MODIS, we compare a subset of their observations against a lidar called CATS that operated from the International Space Station from 2015 to 2017. We determined that both MISR and MODIS have provided us with robust CTHs, with MISR being about twice as accurate and precise as MODIS. Each instrument demonstrates strengths and weaknesses depending on the types of clouds being observed. We note that the MISR error budget is self‐contained and that we were able to close the error budget. This study has also provided needed CTH error characteristics that can help inform future satellite architecture for observing CTH.
Key Points
We present the first semi‐global (50°N–50°S) comparison of Terra cloud‐top heights with coincident samples from a space‐based lidar
Using lidar as truth, Terra cloud‐top height bias and precision are summarized as a function of cloud geometrical and optical properties
With the first measurement of stereo‐opacity bias (−60 to −260 m, depending on cloud type), MISR cloud height error‐budget is closed
The cloud drop effective radius (Re) of the drop size distribution
derived from passive satellite sensors is a key variable used in climate
research. Validation of these satellite products has often ...taken place under
stratiform cloud conditions that favor the assumption of cloud horizontal
homogeneity used by the retrieval techniques. However, many studies have noted
concerns with respect to significant biases in retrieved Re arising from cloud
heterogeneity, for example, in cumulus cloud fields. Here, we examine data
collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines
Experiment” (CAMP2Ex), which, in part, targeted the objective of
providing the first detailed evaluation of Re retrieved across multiple
platforms and techniques in a cumulus and congestus cloud region. Our
evaluation consists of cross-comparisons of Re between the Moderate Resolution
Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research
Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ
measurements from both the NASA P-3 and Learjet aircraft that are all taken in
close spatiotemporal proximity to the same cloud fields. A particular advantage
of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral
MODIS approach and a polarimetric approach, which allows for the evaluation of
bi-spectral and polarimetric Re retrievals from an airborne perspective using
the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the
RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of
9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4
(10.8 ± 3.8) µm, respectively. These values are far lower than the values of
15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the
bi-spectral retrievals of RSP and MODIS, respectively. Similar results are
observed when Re is segregated by cloud-top height and in detailed case
studies. The clouds sampled during CAMP2Ex consist of mostly small
(mean transect length ∼ 1.4 km) and low clouds (mean cloud-top
height ∼ 1 km), which had more numerous small clouds than the
trade wind cumuli sampled in past field campaigns such as Rain in Shallow
Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The
overestimates of Re from the RSP bi-spectral technique compared with the polarimetric
technique increased as cloud size and cloud optical depth decreased.
Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not
closely correlated with the overestimate of bi-spectral Re. For
shallow clouds that dominated the liquid cloud cover for the CAMP2Ex
region and period, we show that 3-D radiative transfer and cloud heterogeneity,
particularly for the optically thin and small clouds, appear to be the
leading cause of the large positive biases in bi-spectral retrievals.
Because this bias varies with the underlying structure of the cloud field,
caution continues to be warranted in studies that use bi-spectral Re
retrievals in cumulus cloud fields.
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