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Comments on "The Sensitivity Study of Radiative-Convective Equilibrium in the Tropics with a Convective Resolving Model"

In general, there are two broad scientific objectives when using cloud resolving models (CRMs or cloud ensemble models-CEMs) to study tropical convection. The first one is to use them as a physics resolving models to understand the dynamic and microphysical processes associated with the tropical water and energy cycles and their role in the climate system. The second approach is to use the CRMs to improve the representation of moist processes and their interaction with radiation in large-scale models. In order to improve the credibility of the CRMs and achieve the above goals, CRMs using identical initial conditions and large-scale influences need to produce very similar results. Two CRMs produced different statistical equilibrium (SE) states even though both used the same initial thermodynamic and wind conditions. Sensitivity tests to identify the major physical processes that determine the SE states for the different CRM simulations were performed. Their results indicated that atmospheric horizontal wind is treated quite differently in these two CRMs. The model that had stronger surface winds and consequently larger latent and sensible heat fluxes from the ocean produced a warmer and more humid modeled thermodynamic SE state. In addition, the domain mean thermodynamic state is more unstable for those experiments that produced a warmer and more humid SE state. Their simulated wet (warm and humid) SE states are thermally more stable in the lower troposphere (from the surface to 4-5 km in altitude). The large-scale horizontal advective effects on temperature and water vapor mixing ratio are needed when using CRMs to perform long-term integrations to study convective feedback under specified large-scale environments. In addition, it is suggested that the dry and cold SE state simulated was caused by enhanced precipitation but not enough surface evaporation. We find some problems with the interpretation of these three phenomena.

Tao, W.-K.↗

An Initial Analysis of the Pixel-Level Uncertainties in Global MODIS Cloud Optical Thickness and Effective Particle Size Retrievals

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical thickness and effective particle radius employ well-known solar reflectance techniques using pre-calculated reflectance look-up tables. We evaluate the quantitative uncertainty in simultaneous retrievals of cloud optical thickness and particle size for this type of algorithm. The technique uses sensitivity calculations derived from the reflectance look-up tables, coupled with estimates for the effect of various error terms on the uncertainty in inferring the actual cloud-top reflectance. The error terms include the effects of instrument calibration, surface spectral albedo, and atmospheric corrections on both water and ice cloud retrievals. Because particle shapes in ice clouds are highly variable, the effect of particle shape is analyzed separately with a more approximate method. Results will deal exclusively with pixel-level uncertainties associated with plane-parallel clouds; real-world radiative departures from a plane-parallel model are an additional consideration. While we demonstrate the uncertainty technique with operational 1 km MODIS retrievals from the Terra and Aqua satellite platforms, the technique is applicable to any reflectance-based satellite- or air-borne sensor retrieval using similar spectral channels.

Platnick, S.↗

Cloud Inhomogeneity from MODIS

Two full months (July 2003 and January 2004) of MODIS Atmosphere Level-3 data from the Terra and Aqua satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that MODIS is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.

Oreopoulos, Lazaros↗

Dissecting the Roles of Stability and Dynamic Regimes in Tropical Cloud Feedbacks Simulated from an Upgraded Multiscale Modeling Framework (MMF)

In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature perturbation experiment performed with a multiscale modeling framework (MMF). We sort the monthly-mean cloud and radiative properties according to circulation and stability regimes. It is found that the dynamic component of cloud feedback for a given dynamic regime dominates the thermodynamic component in terms of the absolute magnitude.

Kuan-Man Xu↗

Reduction of Spectral Radiance Reflectance During the Annular Solar Eclipse of 21 June 2020 from DSCOVR/EPIC

We have analyzed three EPIC images during the annular solar eclipse on June 21, 2020 when centers of the eclipse were in the Arabian Peninsula (mostly desert), the Himalayas (mostly barren land), and China (mostly cloudy over vegetation) and compared with two images for 2017 American solar eclipse over Casper, WY and Columbia, MO (vegetated surface for both). We found that the global average reductions of spectral reflectance for the three images during 2020 solar eclipse are quite different while the reductions of spectral reflectance for the two images for 2017 solar eclipse are similar. Radiative transfer model simulations suggest that different surface spectral albedo and cloud fraction attribute to the different reduction of spectral reflectance for three images during 2020 eclipse while similar spectral albedo of vegetated surface around Casper and Columbia are the main cause for the similar spectral reflectance reduction for the two images during 2017 solar eclipse.

solar eclipse↗

The Land Ice Representation in the NASA Goddard Seasonal Forecasting System

Models used in seasonal forecasting systems have aimed for a level of sophistication comparable to Earth system models by incorporating complex physical processes, including those relevant to the polar regions. Here, we examine the polar surface climate in version 3 of the NASA Goddard Earth Observing System Sub-seasonal to Seasonal prediction system (GEOS S2S v3). The model is composed of the ⅟₂̊ resolution Jason4.0version of the GEOS AGCM and the MOM5 ocean model at ⅟₄̊ resolution. The GEOSS2S model incorporates interactive aerosols and two-moment cloud microphysics. As compared to version 2, the model incorporates improved radiative transfer and are designed diurnal cycle atmosphere-ocean interface layer. This study aims to understand how the version 3 model compares with version 2, and with contemporary Earth system models.

Richard I Cullather↗

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra and Aqua CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS imagers to determine cloud properties that are used in the angular distribution model scene selection required to convert the CERES observed radiances into flux values. Once the Terra and Aqua orbits start drifting outside of their 15-minute window, the CERES project will rely solely on the NOAA-20 CERES observations. A seamless transition of fluxes and clouds can only occur if the analogous MODIS and VIIRS channels are properly inter-calibrated. The visible band (0.65 µm) in MODIS (band 1) and VIIRS (M5 or I1) is critical for retrieving the cloud mask and optical depth. The spectral response functions (SRF) of these bands differ noticeably and will require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Fortunately, the VIIRS I1 and M5 bands are calibrated using the same solar diffuser as a reference, which implies that band reflectance differences must be due to the spectral disparity. The coincident I1 and M5 TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, Hyperion, and radiative transfer model-based scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study will evaluate the SCIAMACHY, GOME-2, Hyperion, and RTM based SBAFs over tropical ocean targets used in SNO inter-calibration of MODIS and VIIRS, including clear-sky ocean, deep convective clouds (DCC), and liquid cloud targets in terms of their applicability to absolute intercomparison of visible imagers. The large SCIAMACHY and GOME-2 footprints and the lack of Hyperion cloudy scenes will impact the resulting SBAFs and necessitates the need for future CLARREO hyper-spectral reflectances to decrease SBAF uncertainties Preliminary results indicate that the SCIAMACHY and GOME-2 based SBAFs for the VIIRS I1 and M5 band pairs may differ by 1.5% for some ATO scene types. Because most of the modern GEOs visible band SRFs encompass the VIIRS I1 band SRF, these evaluations are critical to ensure that the MODIS, VIIRS, and GEO clouds and fluxes are consistent. SBAFs for Libya-4, Dome-C and other Earth invariant target will also be evaluated.

D. R. Doelling↗

Low-Level Liquid-Bearing Clouds Contribute to Seasonal Lower Atmosphere Stability and Surface Energy Forcing over a High-Mountain Watershed Environment

Measurements of atmospheric structure and surface energy budgets distributed along a high-altitude moun tain watershed environment near Crested Butte, Colorado, from two separate, but coordinated, field campaigns, Surface Atmosphere Integrated field Laboratory (SAIL) and Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH), are analyzed. This study identifies similarities and differences in how clouds influence the radiative budget over one snow-free summer season (2022) and two snow-covered seasons (2021/22; 2022/23) for this alpine location. A relationship between lower-tropospheric stability stratification and longwave radiative flux from the presence or absence of clouds is identified. When low clouds persisted, often with signatures of supercooled liquid in win ter, the lower troposphere experienced weaker stability, while radiatively clear skies that are less likely to be influenced by liquid droplets were associated with appreciably stronger lower-tropospheric stratification. Corresponding surface turbu lent heat fluxes partitioned differently based upon the cloud–stability stratification regime derived from early morning radiosounding profiles. Combined with the differences in the radiative budget largely resulting from dramatic seasonal dif ferences in surface albedo, the lower atmosphere stratification, surface energy budget, and near-surface thermodynamics are shown to be modified by the effective longwave radiative forcing of clouds. The diurnal evolution of thermodynamics and surface energy components varied depending on the early morning stratification state. Thus, the importance of quies cent versus synoptically active large-scale meteorology is hypothesized as a critical forcing for cloud properties and associ ated surface energy budget variations. The physical relationships between clouds, radiation, and stratification can provide a useful suite of metrics for process understanding and to evaluate numerical models in such an undersampled, highly com plex terrain environment.

54 ENVIRONMENTAL SCIENCES↗

Ice water path estimation and characterization using passive microwave radiometry

Model computations of top-of-atmospheric microwave brightness temperatures T(B) from layers of precipitation-sized ice of variable bulk density and ice water content (IWC) are presented. It is shown that the 85-GHz T(B) depends essentially on the ice optical thickness. The results demonstrate the potential usefulness of scattering-based channels for characterizing the ice phase and suggest a top-down methodology for retrieval of cloud vertical structure and precipitation estimation from multifrequency passive microwave measurements. Attention is also given to radiative transfer model results based on the multiparameter radar data initialization from the Cooperative Huntsville Meteorological Experiment (COHMEX) in northern Alabama. It is shown that brightness temperature warming effects due to the inclusion of a cloud liquid water profile are especially significant at 85 GHz during later stages of cloud evolution.

Vivekanandan, J.↗

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗

Extensive MRO CRISM Observations of 1.27 micron O2 Airglow in Mars Polar Night and Their Comparison to MRO MCS Temperature Profiles and LMD GCM Simulations

The Martian polar night distribution of 1.27 micron (0-0) band emission from O2 singlet delta [O2(1Delta(sub g))] is determined from an extensive set of Mars Reconnaissance Orbiter (MRO) Compact Reconnaissance Imaging Spectral Mapping (CRISM) limb scans observed over a wide range of Mars seasons, high latitudes, local times, and longitudes between 2009 and 2011. This polar nightglow reflects meridional transport and winter polar descent of atomic oxygen produced from CO2 photodissociation. A distinct peak in 1.27 micron nightglow appears prominently over 70-90NS latitudes at 40-60 km altitudes, as retrieved for over 100 vertical profiles of O2(1Delta(sub g)) 1.27 micron volume emission rates (VER). We also present the first detection of much (x80+/-20) weaker 1.58 micron (0-1) band emission from Mars O2(1Delta(sub g)). Co-located polar night CRISM O2(1Delta(sub g)) and Mars Climate Sounder (MCS) (McCleese et al., 2008) temperature profiles are compared to the same profiles as simulated by the Laboratoire de Météorologie Dynamique (LMD) general circulation/photochemical model (e.g., Lefèvre et al., 2004). Both standard and interactive aerosol LMD simulations (Madeleine et al., 2011a) underproduce CRISM O2(1Delta(sub g)) total emission rates by 40%, due to inadequate transport of atomic oxygen to the winter polar emission regions. Incorporation of interactive cloud radiative forcing on the global circulation leads to distinct but insufficient improvements in modeled polar O2(1Delta(sub g)) and temperatures. The observed and modeled anti-correlations between temperatures and 1.27 mm band VER reflect the temperature dependence of the rate coefficient for O2(1Delta(sub g)) formation, as provided in Roble (1995).

Atmosphere↗

Calculations of surface radiation in arid regions - A case study

The surface and satellite data measured during the preliminary field experiment for the Land-Atmosphere Interactions Experiment conducted at the Heihe River basin in western China are used to investigate the difficulties encountered in the derivation of the surface radiation budget in arid regions. The surface radiation is derived by coupling theoretical radiative transfer calculations with satellite cloud retrievals. For cloud-free cases, the modeled downward solar fluxes are systematically larger than the measured fluxes. It is found that the error can be reduced and that good agreement between the computed and measured surface solar fluxes can be obtained by using an aerosol single-scattering albedo of 0.5 and an optical thickness of about 0.2 in the afternoon hours. For all the cases studied when both surface and satellite data are available, the mean errors are 4.3 and -4.7 W/sq m for the net downward surface solar flux and the downward surface IR flux, respectively. The rms errors are 17.4 and 22.1 W/sq m for the respective surface fluxes. The importance of aerosols in surface radiation calculations is underscored.

Chou, Ming-Dah↗

Overlap Properties of Clouds Generated by a Cloud Resolving Model

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

Oreopoulos, L.↗

A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.

Tao, Wei-Kuo↗

A Coupled GCM-Cloud Resolving Modeling System, and A Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

Tao, Wei-Kuo↗

Model atmospheres for SN 1987A and the distance to the Large Magellanic Cloud

A code which simultaneously solves the non-LTE equations of statistical equilibrium and the time-independent equation of radiation transport in an expanding atmosphere is applied to analyze the spectrum of SN 1987A. The behavior of a model atmosphere in which the density structure is a power-law function of radius has been studied and compared closely with SN 1987A data. This model atmosphere is used to derive corrections to the expanding photosphere method for determining distances to supernovae. The distance to the Large Magellanic Cloud derived from SN 1987A observations by this 'custom yardstick' is 49 + or - 6 kpc in excellent accord with results for RR Lyrae stars and for Cepheids. This empirical test of the expanding photosphere method provides the basis for hope that it may make a significant contribution to the extragalactic distance scale at cosmologically interesting distances.

Eastman, Ronald G.↗