Characterizing the Radiation Fields in the Atmosphere Using a Cloud-Aerosol-Radiation Product from Integrated CERES, MODIS, CALIPSO and CloudSat Data

CloudSat and CALIPSO cloud and aerosol information is convolved with CERES and MODIS cloud and radiation data to produce a merged 3-dimensional cloud and radiation dataset

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains

Evaluation Of CMIP5 Simulated Clouds And TOA Radiation Budgets Using NASA Satellite Observations

A large degree of uncertainty in global climate models (GCMs) can be attributed to the representation of clouds and how they interact with incoming solar and outgoing longwave (Earth emitted) radiation. In this study, the simulated total cloud fraction (CF), cloud water path (CWP), top-of-atmosphere (TOA) radiation budgets and cloud radiative forcings (CRFs) from 28 CMIP5 AMIP models are evaluated and compared to multiple satellite observations from CERES, MODIS, ISCCP, CloudSat, and CALIPSO. The multimodel ensemble mean CF (58.6 %) is, on global average, under estimated by nearly 7 % compared to CERES-MODIS (CM) and ISCCP results, with an even larger negative bias (16.7 %) compared to the CloudSat/CALIPSO result. The CWP bias is similar in comparison to the CF result; the multimodel ensemble mean is under estimated (16.4 gm−2) when compared to CM. The model simulated and CERES EBAF observed TOA reflected shortwave (SW) and outgoing longwave (LW) radiation fluxes, on average, differ by 1.6 and −0.9 Wm−2, respectively, and is contrary to physical theory. The global averaged SW, LW, and net CRFs form CERES EBAF are −47.2, 26.2, and −21.0 Wm−2, respectively, indicating a net cooling effect due to clouds on the TOA radiation budget. Global biases in the SW and LW CRFs from the multimodel ensemble mean are −1.1 and −1.3 Wm−2, respectively, resulting in a greater net cooling effect of 2.4 Wm−2 in the model simulations. A further investigation of cloud properties and CRFs reveals the GCM biases in atmospheric upwelling (15 °S − 15 °N, ocean-only) regimes are much less than their downwelling (15 ° − 45 °N/S, ocean-only) counterparts. Sensitivity studies have shown that the magnitude of SW cloud radiative cooling increases significantly with increasing CF at similar rates ( −1.20 and −1.31 Wm−2 %−1) in both regimes. The LW cloud radiative warming increases with increasing CF but is regime dependent, demonstrated by the different slopes over the upwelling and downwelling regimes (0.81 and 0.22 Wm %−1, respectively). Through a comprehensive error analysis, we found that CF is a primary modulator of warming (or cooling) in the atmosphere. The comparisons and statistical results from this study may provide helpful insight for improving GCM simulations of clouds and TOA radiation budgets in future versions of CMIP

Remote sensing of tropical tropopause layer radiation balance using A-train measurements

Determining the level of zero net radiative heating (LZH) is critical to understanding parcel trajectory in the Tropical Tropopause Layer (TTL) and associated stratospheric hydration processes. Previous studies of the TTL radiative balance have focused on using radiosonde data, but remote sensing measurements from polar-orbiting satellites may provide the relevant horizontal and vertical information for assessing TTL solar heating and infrared cooling rates, especially across the Pacific Ocean. CloudSat provides a considerable amount of vertical information about the distribution of cloud properties relevant to heating rate analysis. The ability of CloudSat measurements and ancillary information to constrain LZH is explored. We employ formal error propagation analysis for derived heating rate uncertainty given the CloudSat cloud property retrieval algorithms. Estimation of the LZH to within approximately 0.5 to 1 km is achievable with CloudSat, but it has a low-altitude bias because the radar is unable to detect thin cirrus. This can be remedied with the proper utilization of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar backscatter information. By utilizing an orbital simulation with the GISS data set, we explore the representativeness of non-cross-track scanning active sounders in terms of describing the LZH distribution. In order to supplement CloudSat, we explore the ability of Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) to constrain LZH and find that these passive sounders are useful where the cloud top height does not exceed 7 km. The spatiotemporal distributions of LZH derived from CloudSat and CALIPSO measurements are presented which suggest that thin cirrus have a limited effect on LZH mean values but affect LZH variability

The CALIPSO Mission: A Global 3D View of Aerosols and Clouds

Aerosols and clouds have important effects on Earth's climate through their effects on the radiation budget and the cycling of water between the atmosphere and Earth's surface. Limitations in our understanding of the global distribution and properties of aerosols and clouds are partly responsible for the current uncertainties in modeling the global climate system and predicting climate change. The CALIPSO satellite was developed as a joint project between NASA and the French space agency CNES to provide needed capabilities to observe aerosols and clouds from space. CALIPSO carries CALIOP, a two-wavelength, polarization-sensitive lidar, along with two passive sensors operating in the visible and thermal infrared spectral regions. CALIOP is the first lidar to provide long-term atmospheric measurements from Earth's orbit. Its profiling and polarization capabilities offer unique measurement capabilities. Launched together with the CloudSat satellite in April 2006 and now flying in formation with the A-train satellite constellation, CALIPSO is now providing information on the distribution and properties of aerosols and clouds, which is fundamental to advancing our understanding and prediction of climate. This paper provides an overview of the CALIPSO mission and instruments, the data produced, and early results

Diurnal cycles of cloud cover and its vertical distribution over the Tibetan Plateau revealed by satellite observations, reanalysis datasets, and CMIP6 outputs

Diurnal variations in cloud cover and cloud vertical distribution are of great importance to Earth–atmosphere system radiative budgets and climate change. However, thus far these topics have received insufficient attention, especially on the Tibetan Plateau (TP). This study focuses on the diurnal variations in total cloud cover, cloud vertical distribution, and cirrus clouds and their relationship to meteorological factors over the TP based on active and passive satellite observations, reanalysis data, and CMIP6 outputs. Our results are consistent with previous studies but provide new insights. The results show that total cloud cover peaks at 06:00–09:00 UTC, especially over the eastern TP, but the spatial and temporal distributions of clouds from different datasets are inconsistent. This could to some extent be attributed to subvisible clouds missed by passive satellites and models. Compared with satellite observations, the amplitudes of the diurnal variations in total cloud cover obtained by the reanalysis and CMIP6 models are obviously smaller. CATS can capture the varying pattern of the vertical distribution of clouds and corresponding height of peak cloud cover at middle and high atmosphere levels, although it underestimates the cloud cover of low-level clouds, especially over the southern TP. Compared with CATS, ERA5 cannot capture the complete diurnal variations in vertical distribution of clouds and MERRA-2 has a poorer performance. We further find that cirrus clouds, which are widespread over the TP, show significant diurnal variations with averaged peak cloud cover over 0.35 at 15:00 UTC. Unlike in the tropics, where thin cirrus (0.03&lt; optical depth &lt;0.3) dominate, opaque cirrus clouds (0.3&lt; optical depth &lt;3) are the dominant cirrus clouds over the TP. The seasonal and regional averaged cloud cover of opaque cirrus reaches a daily maximum of 0.18 at 11:00 UTC, and its diurnal cycle is strong positive correlation with that of 250 hPa relative humidity and 250 hPa vertical velocity. Although subvisible clouds (optical depth &lt;0.03), which have a potential impact on the radiation budget, are the fewest among cirrus clouds over the TP, the seasonal and regional averaged peak cloud cover can reach 0.09 at 22:00 UTC, and their diurnal cycle correlates with that of the 250 hPa relative humidity, 2 m temperature, and 250 hPa vertical velocity. Our results will be helpful to improve the simulation and retrieval of total cloud cover and cloud vertical distribution and further provide an observational constraint for simulations of the diurnal cycle of surface radiation budget and precipitation over the TP region.</p

The role of cloud-radiative effects and diabatic processes for the dynamics of the North Atlantic Oscillation on synoptic time-scales

Clouds shape weather and climate by regulating the latent and radiative heating in the atmosphere. Recent work demonstrated the importance of cloud-radiative effects (CRE) for the mean circulation of the extratropical atmosphere and its response to global warming. In contrast, little research has been done regarding the impact of CRE on internal variability. During the northern hemisphere winter the dominant mode of atmospheric variability over the North Atlantic and the surrounding continental areas of North America and Europe is the North Atlantic Oscillation (NAO). Here, we study how clouds and the NAO couple on synoptic time-scales during northern hemisphere winter via CRE within the atmosphere (ACRE) in observations and model simulations. A regression analysis based on 5-day-mean data from CloudSat/CALIPSO reveals a robust dipole of cloud-incidence anomalies during a positive NAO, with increased high-level clouds along the storm track (near 45°N) and the subpolar Atlantic, and decreased high-level clouds poleward and equatorward of it. Opposite changes occur for low-level cloud incidence. Satellite retrievals from CloudSat/CALIPSO, CERES and GERB as well as ERA-Interim short-term forecast data show that these cloud anomalies lead to an anomalous column-mean heating due to ACRE over the region of the Iceland low, and to a cooling over the region of the Azores high. To quantify the impact of the ACRE anomalies on the NAO, and to thereby test the hypothesis of a cloud-radiative feedback on the NAO persistence, we apply the surface pressure tendency equation (PTE) to ERA-Interim short-term forecast data. The NAO-related surface pressure tendency anomalies due to ACRE amplify the NAO-related surface pressure anomalies over the Azores high but have no area-averaged impact on the Iceland low. In contrast, surface pressure tendency anomalies due to total diabatic heating, including latent heating and clear-sky radiation, strongly amplify the NAO-related surface pressure anomalies over both the Azores high and the Iceland low, and their impact is much more spatially coherent. This suggests that while ACRE lead to an increase in NAO persistence on synoptic time-scales, their impact is relatively minor and much smaller compared to other diabatic processes. To test the robustness of our PTE-based hypothesis, numerical simulations in ICON are carried out. The PTE analysis in ICON shows results that are qualitatively consistent with the observational analysis, in particular regarding the feedback mechanisms of ACRE and total diabatic heating, which is dominated by latent heating. These PTE-based results are further tested by means of sensitivity simulations in ICON, where a NAO-related diabatic heating pattern is imposed either due to ACRE or total diabatic heating. These heating patterns are based on 5-day-mean NAO regressions of either ACRE or total diabatic heating. The sensitivity simulations confirm the observational hypothesis and show that ACRE feed back positively by up to 1–2% of 1σ NAO, while the total diabatic heating feeds back positively by up to 10% of 1σ NAO. Overall, the observational and modeling work both illustrate the substantial impact of the total diabatic heating for the NAO, while ACRE play a minor role. This highlights that diabatic processes are essential for understanding and accurately modeling the NAO short-term dynamics

Cloud Impact Parameters Derived from A-Train Satellite, ERA-Interim, MERRA-2 and Their Relationship to the Environment

Cloud feedback remains one of the largest sources of uncertainty in model climate sensitivity estimates, partly because of the complicated interactions between convective processes, radiative effects, and the large-scale circulation. Cloud radiative effects and precipitation processes have been linked in both deep convective clouds (DC) and low cloud regimes, which points to the importance of understanding the connections between the latent heating from precipitation and surface and atmospheric cloud radiative effects. In this paper, cloud impact parameters (CIPs), including Gvc, Avc and Nvc and energy and water coupling parameters (EWCPs) are examined. The two EWCPs, the surface radiative cooling efficiency, Rvc and the atmospheric heating efficiency, Rvh are used to characterize how efficiently a cloud can heat the atmosphere or cool the surface per unit rain. EWCPs link both cloud radiative properties and precipitation properties together to demonstrate the synergistic effects of the cloud-precipitation-radiation interaction (CPRI). Global distributions of CIPs and EWCPs are highly dependent on cloud regimes and reanalyses fail to simulate strong Rvc and Rvh over deep convection regions in the Indo-Pacific warm pool region, but produce stronger Rvc and Rvh over marine stratocumulus regions. Together, these indicate the possibility that the variability of the Walker circulation simulated by reanalysis is underestimated. To understand how the environment modulates the EWCPs, the EWCPs from A-Train observations, ERA-Interim and MERRA-2 datasets are conditionally sampled by dynamic and thermodynamic variables including vertical pressure velocity (w), sea surface temperature (SST), and column water vapor (CWV). The dynamic regime controls the sign of Rvh, while the CWV appears to be the larger control on the magnitude. The magnitude of Rvc is highly coupled to the dynamic regime. Observations also show two thermodynamic regions of strong Rvc, at low SST and CWV and at high SST and CWV, only the former of which is captured by the reanalyses. The results in this paper can be a reference for improving parameterizations important for coupling the energy and water cycles in global climate models

Satellite Remote Sensing of Mid-level Clouds

This dissertation aims to study the mid-level clouds using satellite observations. It consists of two major parts: characteristics (including cloud top/base heights, cloud top pressure and temperature, and cloud thickness) and thermodynamic phase of mid-level clouds. Each part devotes to a particular issue of significant importance for satellite-based remote sensing of mid-level clouds. The first part of this dissertation focuses on the impacts of three definitions of the mid-level clouds based on cloud top pressure, cloud top height, and cloud base height on mid-level cloud characteristics. The impacts of multi-layer clouds on satellite-based global statistics of clouds at different levels, particularly for mid- level clouds, are demonstrated. Mid-level clouds are found to occur more frequently than underlying upper-level clouds. Comparisons of cloud amounts between a merged CALIPSO, CloudSat, CERES, and MODIS (CCCM) dataset and International Satellite Cloud Climatology Project (ISCCP) climatology are made between July 2006 and December 2009. Midlevel cloud characteristics are shown to be sensitive to perturbations in midlevel boundary pressures and heights. The second part focuses on the thermodynamic phase of mid-level clouds. A new algorithm to detect cloud phase using Atmospheric Infrared Sounder (AIRS) high spectral measurements is introduced. The AIRS phase algorithm is based on the newly developed High-spectral-resolution cloudy-sky Radiative Transfer Model (HRTM). The AIRS phase algorithm is evaluated using the CALIPSO cloud phase products for single-layer, heterogeneous, and multi-layer scenes. The AIRS phase algorithm has excellent performance (>90%) in detecting ice clouds compared to the CALIPSO ice clouds. It is capable of detecting optically thin ice clouds in tropics and clouds in the mid-temperature range. Thermodynamic phase of mid-level clouds are investigated using the spatially collocated AIRS phase and CALIPSO phase products between December 2007 and November 2008. Overall, the statistics show that ice, liquid water, and mixed-phase of the mid-level clouds are approximately 20%, 40%, and 40%, globally