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NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2008

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Yang, Yuekui↗
NASA NTRS2008

Sensitivity of Photolysis Frequencies and Key Tropospheric Oxidants in a Global Model to Cloud Vertical Distributions and Optical Properties

As a follow-up study to our recent assessment of the radiative effects of clouds on tropospheric chemistry, this paper presents an analysis of the sensitivity of such effects to cloud vertical distributions and optical properties in a global 3-D chemical transport model (GEOS4-Chem CTM). GEOS-Chem was driven with a series of meteorological archives (GEOS1-STRAT, GEOS-3 and GEOS-4) generated by the NASA Goddard Earth Observing System data assimilation system, which have significantly different cloud optical depths (CODs) and vertical distributions. Clouds in GEOS1-STRAT and GEOS-3 have more similar vertical distributions while those in GEOS-4 are optically much thinner in the tropical upper troposphere. We find that the radiative impact of clouds on global photolysis frequencies and hydroxyl radical (OH) is more sensitive to the vertical distribution of clouds than to the magnitude of column CODs. Model simulations with each of the three cloud distributions all show that the change in the global burden of O3 due to clouds is less than 5%. Model perturbation experiments with GEOS-3, where the magnitude of 3-D CODs are progressively varied by -100% to 100%, predict only modest changes (<5%) in global mean OH concentrations. J(O1D), J(NO2) and OH concentrations show the strongest sensitivity for small CODs and become insensitive at large CODs due to saturation effects. Caution should be exercised not to use in photochemical models a value for cloud single scattering albedo lower than about 0.999 in order to be consistent with the current knowledge of cloud absorption at the UV wavelength. Our results have important implications for model intercomparisons and climate feedback on tropospheric photochemistry.

Liu, Hongyu↗
NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗
NASA NTRS2011

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits or Instrument Simulators

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds m-e represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail data sets developed for comparison with global models using ISCCP and MODIS simulators, In nature MODIS observes less mid-level doudines!> than ISCCP, consistent with the different methods used to determine cloud top pressure; aspects of this difference are reproduced by the simulators running in a climate modeL But stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15 k of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Ackerman, Steven A.↗
NASA NTRS2005

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗
NASA NTRS2006

Analysis of Rapidly Developing Low Cloud Ceilings in a Stable Environment

Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low cloud ceilings at the Space Shuttle Landing Facility (TTS) to support Space Shuttle landings. Mission verification statistics have shown ceilings to be the number one forecast challenge for SMG. More specifically, forecasters at SMG are concerned with any rapidly developing clouds/ceilings below 8000 ft in a stable, capped thermodynamic environment. Therefore, the Applied Meteorology Unit (AMU) was tasked to examine archived events of rapid stable cloud formation resulting in ceilings below 8000 ft, and document the atmospheric regimes favoring this type of cloud development. The AMU examined the cool season months of November to March during the years of 1993-2003 for days that had low-level inversions and rapid, stable low cloud formation that resulted in ceilings violating the Space Shuttle Flight Rules. The AMU wrote and modified existing code to identify inversions from the morning (-10 UTC) Cape Canaveral, FL rawinsonde (XMR) during the cool season and output pertinent sounding information. They parsed all days with cloud ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Days with precipitation or noticeable fog burn-off situations were excluded from the database. In the first phase of this work, only the daytime hours were examined for possible ceiling development events since low clouds are easier to diagnose with visible satellite imagery. Phase II of this work includes expanding the database to include nighttime cases which is underway as this abstract is being written. For the nighttime cases, the AMU will analyze both the 00 UTC soundings and the 10 UTC soundings to examine those data for the presence of a low-level inversion. The 00 UTC soundings will probably not have a surface-based inversion, but the presence of inversions or "neutral" layers aloft and below 8,000 ft will most likely help define the stable regime, being a thermodynamically "capped" environment. Occurrences of elevated low-level inversions or stable layers will be highlighted in conjunction with nights that experienced a possible development or onset of cloud ceilings below 8,000 ft. Using these criteria to narrow down the database, the AMU will then use archived IR satellite imagery for these possible events. This presentation summarizes the composite meteorological conditions for 20 daytime event days with rapid low cloud ceiling formation and 48 non-events days consisting of advection or widespread low cloud ceilings and describes two sample cases of daytime rapidly-developing low cloud ceilings. The authors will also summarize the work from the nighttime cases and describe a representative sample case from this data set.

Bauman, William H., III↗
NASA NTRS2012

Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value.

Torres, O.↗
NASA NTRS2012

The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

Meyer, Kerry↗
NASA NTRS2011

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗
NASA NTRS2012

2D Radiative Processes Near Cloud Edges

Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near cloud edges, the transition zone between clouds and cloud free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near cloud edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach cloud edges. For this, the study relies on radiative simulations performed for a multiyear dataset of clouds observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase cloud profiles as well as wind measurements and ARM cloud classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near cloud edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as cloud type and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.

Varnai, T.↗
NASA NTRS2012

The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

Tao, Wei-Kuo↗
NASA NTRS2012

Sensitivity of Cirrus and Mixed-phase Clouds to the Ice Nuclei Spectra in McRAS-AC: Single Column Model Simulations

The salient features of mixed-phase and ice clouds in a GCM cloud scheme are examined using the ice formation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of LP and BN ice nucleation parameterizations were assessed in the GEOS-5 AGCM using the McRAS-AC cloud microphysics framework in single column mode. Four dimensional assimilated data from the intensive observation period of ARM TWP-ICE campaign was used to drive the fluxes and lateral forcing. Simulation experiments where established to test the impact of each parameterization in the resulting cloud fields. Three commonly used IN spectra were utilized in the BN parameterization to described the availability of IN for heterogeneous ice nucleation. The results show large similarities in the cirrus cloud regime between all the schemes tested, in which ice crystal concentrations were within a factor of 10 regardless of the parameterization used. In mixed-phase clouds there are some persistent differences in cloud particle number concentration and size, as well as in cloud fraction, ice water mixing ratio, and ice water path. Contact freezing in the simulated mixed-phase clouds contributed to transfer liquid to ice efficiently, so that on average, the clouds were fully glaciated at T approximately 260K, irrespective of the ice nucleation parameterization used. Comparison of simulated ice water path to available satellite derived observations were also performed, finding that all the schemes tested with the BN parameterization predicted 20 average values of IWP within plus or minus 15% of the observations.

Betancourt, R. Morales↗
NASA NTRS2012

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Chiu, J. C.↗
NASA NTRS2012

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)< 1 cm/s and v(sub f)> 10 cm/s, N(sub i)/N(sub IN)<< 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)< 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Fridlin, Ann↗
NASA NTRS2015

A Linearized Prognostic Cloud Scheme in NASAs Goddard Earth Observing System Data Assimilation Tools

A linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA's Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest.

Precipitation↗
NASA NTRS2015

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

Sun-Mack, Sunny↗
NASA NTRS2015

Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint Level

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Taylor, Patrick C.↗