Cloud Radiative Feedback Research Articles

Turbulent vertical mixing in hot exoplanet atmospheres

Abstract Turbulent vertical transport driven by double-diffusive shear instabilities is identified as likely important in hot exoplanet atmospheres. In hot Jupiter atmospheres, the resulting vertical mixing appears sufficient to alleviate the nightside cold trap, thus facilitating the maintenance of nocturnal clouds on these planets. The strong level of vertical mixing expected near hot Jupiter thermal photospheres will impact their atmospheric chemistry and even their vertical structures where cloud radiative feedback proves important.

Satellite‐Based Detection of Daytime Supercooled Liquid‐Topped Mixed‐Phase Clouds Over the Southern Ocean Using the Advanced Himawari Imager

AbstractInaccurate mixed‐phase cloud parameterizations over the Southern Ocean remain one of the largest sources of disagreement among global models in determining shortwave cloud radiative feedbacks. Suitable global observations supporting model improvements are currently unavailable. The conventional satellite cloud phase retrieval from passive radiometers is strongly biased toward cloud top without further information on the subcloud phase. Mixed‐phase clouds with the liquid‐top mixed‐phase (LTMP) structures are often classified simply as supercooled liquid. This paper presents a daytime multispectral detection algorithm for LTMP clouds, based on differential absorption between liquid and ice in shortwave infrared bands (1.61 and 2.25 μm). The LTMP algorithm, previously developed for polar‐orbiting sensors, is applied to Himawari‐8 Advanced Himawari Imager (the first of the next‐generation geostationary satellites) to probe subcloud phase for mixed‐phase clouds over the Southern Ocean. The results are compared with spaceborne active sensor data from CloudSat and CALIPSO. Ship‐based field experiment measurements are examined for selected cases to provide a more direct assessment of algorithm performance. The results show that applying the LTMP algorithm to geostationary satellites has potential to provide advanced time‐resolved observations for mixed‐phase clouds globally with improved sublayer cloud phase information that can support enhancement and validation of global models.

Modeled Temperature-dependent Clouds with Radiative Feedback in Hot Jupiter Atmospheres

Abstract Using a general circulation model with newly implemented cloud modeling, we investigate how radiative feedback can self-consistently shape condensate cloud distributions, temperatures, and fluxes in a hot Jupiter atmosphere. We apply a physically motivated but simple parameterization of condensate clouds in which the temperature determines the cloud distribution, and we evaluate how different assumptions of vertical mixing and aerosol opacity affect predictions. We compare results from cases in which the aerosols are simply included in the last step of the simulation (i.e., postprocessed) to cases in which clouds and their radiative feedback are actively included throughout the duration of the simulation. When clouds and radiative feedback were actively included, cloud cover decreased at equatorial regions and increased toward the poles relative to the postprocessed solutions. The resulting phase curves also differed between the two approaches; the postprocessed cloud simulations predicted weaker day–night contrasts in emission and greater eastward shifts in the maximum emission compared to the active cloud modeling. This illustrates the importance of cloud radiative feedback and shows that postprocessing can provide inaccurate solutions when clouds are thick enough to provide significant scattering.

Evaluating Cloud Feedbacks and Rapid Responses in the ACCESS Model

AbstractA cloud feedback diagnostic package is implemented in the Australian Community Climate and Earth‐System Simulator General Circulation Model, based on the methodology of “cloud radiative kernels.” Using separate increased sea surface temperature and CO2 experiments, both the “rapid response” cloud contribution to forcing and temperature‐mediated cloud feedbacks are analyzed. Under increased temperature and CO2 changes, temperature‐mediated cloud radiative feedback dominates over the rapid response in the final radiative response. Cloud feedback is positive in both long and short wave, with short wave dominating global values. Contributing most to this are low to mid‐level clouds, of medium‐to‐high optical thickness. As a means of illustration of the methodology, a number of key parameters related to clouds, precipitation, and convection that are typically used in “tuning” in the model are modified. These changes result in substantial impacts on the model's current climate, but only modest changes to rapid response and feedbacks occur globally, regionally, and as a function of cloud optical thickness and height. This limited set of experiments shows that cloud adjustments and feedbacks in this model are robust under these changes, lending confidence that both model climate change projections and the conclusions of attribution studies are not overly sensitive to such parameterization tuning. Of course, a considerably larger set of experiments would be needed to demonstrate that feedbacks and rapid response are robust under the wider set of tuning adjustments commonly undertaken.

Impacts of Radiation and Upper-Tropospheric Temperatures on Tropical Cyclone Structure and Intensity

Abstract Potential intensity theory predicts that the upper-tropospheric temperature acts as an important constraint on tropical cyclone (TC) intensity. The physical mechanisms through which the upper troposphere impacts TC intensity and structure have not been fully explored, however, due in part to limited observations and the complex interactions between clouds, radiation, and TC dynamics. In this study, idealized Weather Research and Forecasting Model ensembles initialized with a combination of three different tropopause temperatures and with no radiation, longwave radiation only, and full diurnal radiation are used to examine the physical mechanisms in the TC–upper-tropospheric temperature relationship on weather time scales. Simulated TC intensity and structure are strongly sensitive to colder tropopause temperatures using only longwave radiation, but are less sensitive using full radiation and no radiation. Colder tropopause temperatures result in deeper convection and increased ice mass aloft in all cases, but are more intense only when radiation was included. Deeper convection leads to increased local longwave cooling rates but reduced top-of-the-atmosphere outgoing longwave radiation, such that the total radiative heat sink is reduced from a Carnot engine perspective in stronger storms. We hypothesize that a balanced response in the secondary circulation described by the Eliassen equation arises from upper-troposphere radiative cooling anomalies that lead to stronger tangential winds. The results of this study further suggest that radiation and cloud–radiative feedbacks have important impacts on weather time scales.

Intraseasonal Variability in a Cloud-Permitting Near-Global Equatorial Aquaplanet Model

Abstract Recent studies have suggested that the Madden–Julian oscillation is a result of an instability driven mainly by cloud–radiation feedbacks, similar in character to self-aggregation of convection in nonrotating, cloud-permitting simulations of radiative–convective equilibrium (RCE). Here we bolster that inference by simulating radiative–convective equilibrium states on a rotating sphere with constant sea surface temperature, using the cloud-permitting System for Atmospheric Modeling (SAM) with 20-km grid spacing and extending to walls at 46° latitude in each hemisphere. Mechanism-denial experiments reveal that cloud–radiation interaction is the quintessential driving mechanism of the simulated MJO-like disturbances, but wind-induced surface heat exchange (WISHE) feedbacks are the primary driver of its eastward propagation. WISHE may also explain the faster Kelvin-like modes in the simulations. These conclusions are supported by a linear stability analysis of RCE states on an equatorial beta plane.

Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM

AbstractWe study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (SP). The mean cloud radiative effect feedback turns out to be remarkably neutral across all of our simulations, despite some radical changes in both cloud microphysical parameter settings and cloud‐resolving model grid resolution. The overall low cloud response to warming is a positive low cloud feedback over land, a negative feedback (driven by cloud optical depth increase) at high latitudes, and weak feedback over the low‐latitude oceans. The most distinct effects of UP result from tuning decisions impacting high‐latitude cloud feedback. UP's microphysics is tuned to optimize the model present‐day, top‐of‐atmosphere radiation fluxes against CERES observations, by lowering the cloud ice‐liquid phase shift temperature ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice fall speed. This reduces high‐latitude low cloud amounts and damps the optical depth feedback at high latitudes, leading to a slightly more positive global cloud feedback compared to SP. A sensitivity test that isolates these microphysical impacts from UP's grid resolution confirms that the microphysical settings are mostly responsible for the differences between SP and UP cloud feedback.

Mechanisms for Generation and Development of the Ningaloo Niño

AbstractGeneration and development mechanisms of the Ningaloo Niño are investigated using ocean and atmospheric general circulation model experiments. Consistent with previous studies, northerly wind anomalies off the West Australian coast are critical in generating warm sea surface temperature (SST) anomalies of the Ningaloo Niño, which induce SST warming through reduced turbulent heat loss toward the atmosphere (by decreasing surface wind speed), enhanced Leeuwin Current heat transport, and weakened coastal upwelling. Our results further reveal that northerly wind anomalies suppress the cold dry air transport from the Southern Ocean to the Ningaloo Niño region, which also contributes to the reduced turbulent heat loss. A positive cloud–radiation feedback is also found to play a role. Low stratiform cloud is reduced by the underlying warm SSTAs and the weakened air subsidence, which further enhances the SST warming by increasing downward solar radiation. The enhanced Indonesian Throughflow also contributes to the Ningaloo Niño, but only when La Niña co-occurs. Further analysis show that northerly wind anomalies along the West Australian coast can be generated by both remote forcing from the Pacific Ocean (i.e., La Niña) and internal processes of the Indian Ocean, such as the positive Indian Ocean dipole (IOD). Approximately 40% of the Ningaloo Niño events during 1950–2010 co-occurred with La Niña, and 30% co-occurred with positive IOD. There are also ~30% of the events independent of La Niña and positive IOD, suggesting the importance of other processes in triggering the Ningaloo Niño.

A Further Study on the Simulation of Cloud-Radiative Feedbacks in the ENSO Cycle in the Tropical Pacific with a Focus on the Asymmetry

The El Nino-Southern Oscillation (ENSO) cycle has been used as a surrogate to gauge the accuracy of simulated cloud-radiative feedbacks. However, previous studies have largely ignored the potential differences in the cloud response to sea surface temperature (SST) changes between the two phases of ENSO. Here we underscore this issue by contrasting the differences in the responses of shortwave- and longwave- cloud radiative forcing (SWCRF and LWCRF) to SST changes between the two phases of ENSO in observations and in CMIP5 simulations. In observations, the responses of SWCRF and LWCRF to SST changes in the cold phase had weaker magnitude and more westward positioning than the warm phase. This asymmetric feature in cloud-radiative feedbacks is linked to the corresponding differences in the precipitation feedback. In examining this asymmetry aspect of cloud-radiative feedbacks in the CMIP5 simulations, we divided the models into high-skill-models (HSM) and low-skill-models (LSM). The HSM were found to simulate the cloud-radiative feedbacks equally well in both phases, whereas the LSM had distinctly better simulations in the cold phase than the warm phase, to the extent that it matched the simulations by the HSM. Thus the difference in the simulation of cloud-radiative feedbacks between the HSM and LSM primarily arises from the difference in the warm phase. This is because the cold bias in mean SST in coupled models had a greater impact on the cloud-radiative feedbacks during the warm phase than during the cold phase. Implications for how to further improve cloud-radiative feedback simulations were also discussed.

Dynamic moisture mode versus moisture mode in MJO dynamics: importance of the wave feedback and boundary layer convergence feedback

The Madden–Julian oscillation (MJO) is an equatorial eastward moving system with a planetary-scale coupled Kelvin–Rossby wave structure. The equatorial waves and their interaction with convection are expected to play an important role in MJO dynamics. Using the trio-interaction model for essential MJO dynamics, this study investigates the importance of dynamic feedback that includes wave feedback (WF) and boundary layer convergence feedback (BLCF), by comparing the moisture mode (MM) that contains only moisture feedback (MF) and cloud-radiative feedback (CRF), with the dynamic moisture mode (DMM) that includes additional WF and BLCF. It is shown that the dynamic feedbacks fundamentally change the properties of the MJO mode. For the MM, the MF alone yields a damping and quasi-stationary mode on wavenumber 2–4. The CRF can destabilize the MM, but it cannot produce planetary wave selection. By including the dynamic feedbacks (WF and BLCF), the resultant DMM is an unstable mode with a preferred planetary scale, which moves eastward slowly, yielding a 30–90-day period. The dynamic feedbacks produce the planetary scale selection of the DMM through generating more eddy available moist static energy on the longer wavelengths. The WF can significantly change the structure of the MM and links the propagation of the DMM to the Kelvin and Rossby wave components, with stronger Kelvin (Rossby) wave favoring faster (slower) propagation. The BLCF enhances the Kelvin wave component on the longer wavelengths, changing the horizontal structures and accelerating the eastward propagation. The WF relates the dispersion feature of the DMM to the properties of the Kelvin and Rossby waves. Since the Kelvin-wave (Rossby-wave) frequency increases (decreases) with increasing wavenumber, their coupling in the DMM yields a quasi-constant frequency at the planetary scales (wavenumber 1–3).

Simulating the cloudy atmospheres of HD 209458 b and HD 189733 b with the 3D Met Office Unified Model

Aims.To understand and compare the 3D atmospheric structure of HD 209458 b and HD 189733 b, focusing on the formation and distribution of cloud particles, as well as their feedback on the dynamics and thermal profile.Methods.We coupled the 3D Met Office Unified Model (UM), including detailed treatments of atmospheric radiative transfer and dynamics, to a kinetic cloud formation scheme. The resulting model self-consistently solves for the formation of condensation seeds, surface growth and evaporation, gravitational settling and advection, cloud radiative feedback via absorption, and crucially, scattering. We used fluxes directly obtained from the UM to produce synthetic spectral energy distributions and phase curves.Results.Our simulations show extensive cloud formation in both HD 209458 b and HD 189733 b. However, cooler temperatures in the latter result in higher cloud particle number densities. Large particles, reaching 1μm in diameter, can form due to high particle growth velocities, and sub-μm particles are suspended by vertical flows leading to extensive upper-atmosphere cloud cover. A combination of meridional advection and efficient cloud formation in cooler high latitude regions, results in enhanced cloud coverage for latitudes above 30° and leads to a zonally banded structure for all our simulations. The cloud bands extend around the entire planet, for HD 209458 b and HD 189733 b, as the temperatures, even on the day side, remain below the condensation temperature of silicates and oxides. Therefore, the simulated optical phase curve for HD 209458 b shows no “offset”, in contrast to observations. Efficient scattering of stellar irradiation by cloud particles results in a local maximum cooling of up to 250 K in the upper atmosphere, and an advection-driven fluctuating cloud opacity causes temporal variability in the thermal emission. The inclusion of this fundamental cloud-atmosphere radiative feedback leads to significant differences with approaches neglecting these physical elements, which have been employed to interpret observations and determine thermal profiles for these planets. This suggests that readers should be cautious of interpretations neglecting such cloud feedback and scattering, and that the subject merits further study.

Sensitivity of Polar Amplification to Varying Insolation Conditions

The mechanism of polar amplification in the absence of surface albedo feedback is investigated using an atmospheric model coupled to an aquaplanet slab ocean forced by a CO2 doubling. In particular, we examine the sensitivity of polar surface warming response under different insolation conditions from equinox (EQN) to annual mean (ANN) to seasonally varying (SEA). Varying insolation greatly affects the climatological static stability. The equinox condition, with the largest polar static stability, exhibits a bottom-heavy vertical profile of polar warming response that leads to the strongest polar amplification. In contrast, the polar warming response in ANN and SEA exhibits a maximum in the midtroposphere, which leads to only weak polar amplification. The midtropospheric warming maximum, which results from an increased poleward atmospheric energy transport in response to the tropics-to-pole energy imbalance, contributes to polar surface warming via downward clear-sky longwave radiation. However, it is cancelled by negative cloud radiative feedbacks locally. Furthermore, the polar lapse rate feedback, calculated from radiative kernels, is negative due to the midtropospheric warming maximum, and hence is not able to promote the polar surface warming. On the other hand, the polar lapse rate feedback in EQN is positive due to the bottom-heavy warming response, contributing to the strong polar surface warming. This contrast suggests that locally induced positive radiative feedbacks are necessary for strong polar amplification. Our results demonstrate how interactions among climate feedbacks determine the strength of polar amplification.

MJO Prediction Skill of the Subseasonal-to-Seasonal Prediction Models

Abstract The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides a major source of tropical and extratropical predictability on a subseasonal time scale. This study conducts a quantitative evaluation of the MJO prediction skill in state-of-the-art operational models, participating in the subseasonal-to-seasonal (S2S) prediction project. The relationship of MJO prediction skill with model biases in the mean moisture fields and in the longwave cloud–radiation feedbacks is also investigated. The S2S models exhibit MJO prediction skill out to a range of 12 to 36 days. The MJO prediction skills in the S2S models are affected by both the MJO amplitude and phase errors, with the latter becoming more important at longer forecast lead times. Consistent with previous studies, MJO events with stronger initial MJO amplitude are typically better predicted. It is found that the sensitivity to the initial MJO phase varies notably from model to model. In most models, a notable dry bias develops within a few days of forecast lead time in the deep tropics, especially across the Maritime Continent. The dry bias weakens the horizontal moisture gradient over the Indian Ocean and western Pacific, likely dampening the organization and propagation of the MJO. Most S2S models also underestimate the longwave cloud–radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelope. The models with smaller bias in the mean horizontal moisture gradient and the longwave cloud–radiation feedbacks show higher MJO prediction skills, suggesting that improving those biases would enhance MJO prediction skill of the operational models.

Contrasting Cloud Radiative Feedbacks during Warm Pool and Cold Tongue El Niños

Contrasting Cloud Radiative Feedbacks during Warm Pool and Cold Tongue El Niños

Seasonal Synchronization of a Simple Stochastic Dynamical Model Capturing El Niño Diversity

Recently, a simple stochastic dynamical model was developed that automatically captures the diversity and intermittency of El Niño–Southern Oscillation (ENSO) in nature, where state-dependent stochastic wind bursts and nonlinear advection of sea surface temperature (SST) are coupled to simple ocean–atmosphere processes that are otherwise deterministic, linear, and stable. In the present article, it is further shown that the model can reproduce qualitatively the ENSO synchronization (or phase locking) to the seasonal cycle in nature. This goal is achieved by incorporating a cloud radiative feedback that is derived naturally from the model’s atmosphere dynamics with no ad hoc assumptions and accounts in simple fashion for the marked seasonal variations of convective activity and cloud cover in the eastern Pacific. In particular, the weak convective response to SSTs in boreal fall favors the eastern Pacific warming that triggers El Niño events while the increased convective activity and cloud cover during the following spring contributes to the shutdown of those events by blocking incoming shortwave solar radiations. In addition to simulating the ENSO diversity with realistic non-Gaussian statistics in different Niño regions, the eastern Pacific moderate and super El Niño and the central Pacific El Niño and La Niña show a realistic chronology with a tendency to peak in boreal winter as well as decreased predictability in spring consistent with the persistence barrier in nature. The incorporation of other possible seasonal feedbacks in the model is also documented for completeness.

Interdecadal change in the summer SST-precipitation relationship around the late 1990s over the South China Sea

An interdecadal change in the air-sea interaction over the South China Sea (SCS) after the late 1990s has been identified using a local contemporaneous precipitation-sea surface temperature (SST) and precipitation-SST tendency relationship. During 1979–1998, there is a negative precipitation-SST relationship over the SCS, with a larger magnitude over the northeastern SCS (NESCS) than over the southwestern SCS (SWSCS). The remote effect of warmer SST over the tropical Indian Ocean plays a crucial role in a strong anticyclone and suppressed rainfall over the SCS and western North Pacific. Due to greater mixed-layer depth over the SWSCS than over the NESCS, entrainment heat flux makes a larger contribution to a positive precipitation-SST tendency over the SWSCS than over the NESCS. The cloud-radiation effect has a dominant and positive contribution to the SST tendency over the NESCS, whereas it has a negative contribution to SST tendency over the SWSCS. In contrast, the precipitation-SST correlation becomes weakly negative over the NESCS and significantly positive over the SWSCS during 1999–2013. The CESM-CAM5 model demonstrates that cooler SST over the tropical central-eastern Pacific (TCEP) triggers a weak anticyclone, slightly suppressing rainfall over the SCS. The cloud-radiation effect still contributes mostly to a positive SST tendency over the NESCS. Warmer SST over the SWSCS induces an increase in surface evaporation and low-level moisture convergence and causes enhanced rainfall. That offsets the remote effect of TCEP SST and results in a negative precipitation-SST tendency with negative cloud-radiation feedback. The interdecadal change in remote forcing to SCS rainfall around the late 1990s is related to the evolution of TCEP SST anomalies from the preceding winter to summer, which is possibly modulated by the phase of the Pacific Decadal Oscillation.

The role of 1-D and 3-D radiative heating in the organization of shallow cumulus convection and the formation of cloud streets

Abstract. The formation of shallow cumulus cloud streets was historically attributed primarily to dynamics. Here, we focus on the interaction between radiatively induced surface heterogeneities and the resulting patterns in the flow. Our results suggest that solar radiative heating has the potential to organize clouds perpendicular to the sun's incidence angle. To quantify the extent of organization, we performed a high-resolution large-eddy simulation (LES) parameter study. We varied the horizontal wind speed, the surface heat capacity, the solar zenith and azimuth angles, and radiative transfer parameterizations (1-D and 3-D). As a quantitative measure we introduce a simple algorithm that provides a scalar quantity for the degree of organization and the alignment. We find that, even in the absence of a horizontal wind, 3-D radiative transfer produces cloud streets perpendicular to the sun's incident direction, whereas the 1-D approximation or constant surface fluxes produce randomly positioned circular clouds. Our reasoning for the enhancement or reduction of organization is the geometric position of the cloud's shadow and its corresponding surface fluxes. Furthermore, when increasing horizontal wind speeds to 5 or 10 m s−1, we observe the development of dynamically induced cloud streets. If, in addition, solar radiation illuminates the surface beneath the cloud, i.e., when the sun is positioned orthogonally to the mean wind field and the solar zenith angle is larger than 20°, the cloud-radiative feedback has the potential to significantly enhance the tendency to organize in cloud streets. In contrast, in the case of the 1-D approximation (or overhead sun), the tendency to organize is weaker or even prohibited because the shadow is cast directly beneath the cloud. In a land-surface-type situation, we find the organization of convection happening on a timescale of half an hour. The radiative feedback, which creates surface heterogeneities, is generally diminished for large surface heat capacities. We therefore expect radiative feedbacks to be strongest over land surfaces and weaker over the ocean. Given the results of this study we expect that simulations including shallow cumulus convection will have difficulties producing cloud streets if they employ 1-D radiative transfer solvers or may need unrealistically high wind speeds to excite cloud street organization.

Evolution of surface sensible heat over the Tibetan Plateau under the recent global warming hiatus

Based on regular surface meteorological observations and NCEP/DOE reanalysis data, this study investigates the evolution of surface sensible heat (SH) over the central and eastern Tibetan Plateau (CE-TP) under the recent global warming hiatus. The results reveal that the SH over the CE-TP presents a recovery since the slowdown of the global warming. The restored surface wind speed together with increased difference in ground-air temperature contribute to the recovery in SH. During the global warming hiatus, the persistent weakening wind speed is alleviated due to the variation of the meridional temperature gradient. Meanwhile, the ground surface temperature and the difference in ground-air temperature show a significant increasing trend in that period caused by the increased total cloud amount, especially at night. At nighttime, the increased total cloud cover reduces the surface effective radiation via a strengthening of atmospheric counter radiation and subsequently brings about a clear upward trend in ground surface temperature and the difference in ground-air temperature. Cloud–radiation feedback plays a significant role in the evolution of the surface temperature and even SH during the global warming hiatus. Consequently, besides the surface wind speed, the difference in ground-air temperature becomes another significant factor for the variation in SH since the slowdown of global warming, particularly at night.

Relationships between radiation, clouds, and convection during DYNAMO.

The relationships between radiation, clouds, and convection on an intraseasonal time scale are examined with data taken during the Dynamics of the Madden-Julian Oscillation (MJO) field campaign. Specifically, column-net, as well as vertical profiles of radiative heating rates, computed over Gan Island in the central Indian Ocean (IO) are used along with an objective analysis of large-scale fields to examine three MJO events that occurred during the 3 month period (October to December 2011) over this region. Longwave (LW) and shortwave radiative heating rates exhibit tilted structures, reflecting radiative effects associated with the prevalence of shallow cumulus during the dry, suppressed MJO phase followed by increasing deep convection leading into the active phase. As the convection builds going into the MJO active phase, there are increasingly top-heavy anomalous radiative heating rates while the column-net radiative cooling rate <Qr > progressively decreases. Temporal fluctuations in the cloud radiative forcing, being quite sensitive to changes in high cloudiness, are dominated by LW effects with an intraseasonal variation of ~0.4-0.6 K/d. While both the water vapor and cloud fields are inextricably linked, it appears that the tilted radiative structures are more related to water vapor effects. The intraseasonal variation of column-net radiative heating <Qr > enhances the convective signal in the mean by ~20% with a minimum in this enhancement ~10 days prior to peak MJO rainfall and maximum ~7 days after. This suggests that as MJO convective envelope weakens over the central IO, cloud-radiative feedbacks help maintain the mature MJO as it moves eastward.

Cloud-Base Height Estimation from VIIRS. Part II: A Statistical Algorithm Based on A-Train Satellite Data

AbstractKnowledge of cloud-base height (CBH) is important to describe cloud radiative feedbacks in numerical models and is of practical relevance to the aviation community. Whereas satellite remote sensing with passive radiometers traditionally has provided a ready means for estimating cloud-top height (CTH) and cloud water path (CWP), assignment of CBH requires heavy assumptions on the distribution of CWP within the cloud profile. An attempt to retrieve CBH has been included as part of the VIIRS environmental data records, produced operationally as part of the Suomi–National Polar-Orbiting Partnership (SNPP) and the forthcoming Joint Polar Satellite System. Through formal validation studies tied to the program, it was found that the operational CBH algorithm failed to meet performance specifications in many cases. This paper presents a new methodology for retrieving CBH of the uppermost cloud layer, developed through statistical analyses relating cloud geometric thickness (CGT) to CTH and CWP. The semiempirical approach, which relates these parameters via piecewise fitting, enlists A-Train satellite data [CloudSat cloud profiling radar (CPR), CALIPSO/CALIOP, and Aqua MODIS]. CBH is provided as the residual difference between CTH and CGT. By eliminating cloud type–dependent assumptions on CWP distribution, artifacts common to the operational algorithm (which contribute to high errors) are reduced. Special accommodations are made for handling optically thin cirrus and deep convection. An application to SNPP VIIRS is demonstrated, and the results are compared against global CloudSat observations. From the VIIRS–CloudSat daytime matchups (September–October 2013 and January–May 2015), the new algorithm outperforms the operational SNPP VIIRS algorithm, particularly when the retrieved CTH is accurate. Best performance is expected for single-layer liquid-phase clouds.