Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles

NASA Technical Reports Server (NTRS)

Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

2009-01-01

A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.

Reducing Surface Clutter in Cloud Profiling Radar Data

NASA Technical Reports Server (NTRS)

Tanelli, Simone; Pak, Kyung; Durden, Stephen; Im, Eastwood

2008-01-01

An algorithm has been devised to reduce ground clutter in the data products of the CloudSat Cloud Profiling Radar (CPR), which is a nadir-looking radar instrument, in orbit around the Earth, that measures power backscattered by clouds as a function of distance from the instrument. Ground clutter contaminates the CPR data in the lowest 1 km of the atmospheric profile, heretofore making it impossible to use CPR data to satisfy the scientific interest in studying clouds and light rainfall at low altitude. The algorithm is based partly on the fact that the CloudSat orbit is such that the geodetic altitude of the CPR varies continuously over a range of approximately 25 km. As the geodetic altitude changes, the radar timing parameters are changed at intervals defined by flight software in order to keep the troposphere inside a data-collection time window. However, within each interval, the surface of the Earth continuously "scans through" (that is, it moves across) a few range bins of the data time window. For each radar profile, only few samples [one for every range-bin increment ((Delta)r = 240 m)] of the surface-clutter signature are available around the range bin in which the peak of surface return is observed, but samples in consecutive radar profiles are offset slightly (by amounts much less than (Delta)r) with respect to each other according to the relative change in geodetic altitude. As a consequence, in a case in which the surface area under examination is homogenous (e.g., an ocean surface), a sequence of consecutive radar profiles of the surface in that area contains samples of the surface response with range resolution (Delta)p much finer than the range-bin increment ((Delta)p << r). Once the high-resolution surface response has thus become available, the profile of surface clutter can be accurately estimated by use of a conventional maximum-correlation scheme: A translated and scaled version of the high-resolution surface response is fitted to the observed low-resolution profile. The translation and scaling factors that optimize the fit in a maximum-correlation sense represent (1) the true position of the surface relative to the sampled surface peak and (2) the magnitude of the surface backscatter. The performance of this algorithm has been tested on CloudSat data acquired over an ocean surface. A preliminary analysis of the test data showed a surface-clutter-rejection ratio over flat surfaces of >10 dB and a reduction of the contaminated altitude over ocean from about 1 km to about 0.5 km (over the ocean). The algorithm has been embedded in CloudSat L1B processing as of Release 04 (July 2007), and the estimated flat surface clutter is removed in L2B-GEOPROF product from the observed profile of reflectivity (see CloudSat product documentation for details and performance at http://www.cloudsat.cira.colostate.edu/ dataSpecs.php?prodid=1).

Global snowfall: A combined CloudSat, GPM, and reanalysis perspective.

NASA Astrophysics Data System (ADS)

Milani, Lisa; Kulie, Mark S.; Skofronick-Jackson, Gail; Munchak, S. Joseph; Wood, Norman B.; Levizzani, Vincenzo

2017-04-01

Quantitative global snowfall estimates derived from multi-year data records will be presented to highlight recent advances in high latitude precipitation retrievals using spaceborne observations. More specifically, the analysis features the 2006-2016 CloudSat Cloud Profiling Radar (CPR) and the 2014-2016 Global Precipitation (GPM) Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) observational datasets and derived products. The ERA-Interim reanalysis dataset is also used to define the meteorological context and an independent combined modeling/observational evaluation dataset. An overview is first provided of CloudSat CPR-derived results that have stimulated significant recent research regarding global snowfall, including seasonal analyses of unique snowfall modes. GMI and DPR global annual snowfall retrievals are then evaluated against the CloudSat estimates to highlight regions where the datasets provide both consistent and diverging snowfall estimates. A hemispheric seasonal analysis for both datasets will also be provided. These comparisons aim at providing a unified global snowfall characterization that leverages the respective instrument's strengths. Attention will also be devoted to regions around the globe that experience unique snowfall modes. For instance, CloudSat has demonstrated an ability to effectively discern snowfall produced by shallow cumuliform cloud structures (e.g., lake/ocean-induced convective snow produced by air/water interactions associated with seasonal cold air outbreaks). The CloudSat snowfall database also reveals prevalent seasonal shallow cumuliform snowfall trends over climate-sensitive regions like the Greenland Ice Sheet. Other regions with unique snowfall modes, such as the US East Coast winter storm track zone that experiences intense snowfall rates directly associated with strong low pressure systems, will also be highlighted to demonstrate GPM's observational effectiveness. Linkages between CloudSat and GPM global snowfall analyses and independent ERA-Interim datasets will also be presented as a final evaluation exercise.

Using Observations from GPM and CloudSat to Produce a Climatology of Precipitation over the Ocean

NASA Astrophysics Data System (ADS)

Hayden, L.; Liu, C.

2017-12-01

Satellite based instruments are essential to the observation of precipitation at a global scale, especially over remote oceanic regions. Each instrument has its own strengths and limitations when it comes to accurately determining the rate of precipitation occurring at the surface. By using the complementary strengths of two satellite based instruments, we attempt to produce a more complete climatology of global oceanic precipitation. The Global Precipitation Measurement (GPM) Core Osbervatory's Dual-frequency Precipitation Radar (DPR) is capable of measuring precipitation producing radar reflectivity above 12 dBZ [Hamada and Takayabu 2016]. The CloudSat satellite's Cloud Profiling Radar (CPR) uses higher frequency C band (94 GHz) radiation, and is therefore capable of measuring precipitation occurring at low precipitation rates which are not detected by the GPM DPR. The precipitation estimates derived by the two satellites are combined and the results are examined. CloudSat data from July 2006 to December 2010 are used. GPM data from March 2014 through May 2016 are used. Since the two datasets do not temporally overlap, this study is conducted from a climatological standpoint. The average occurrence for different precipitation rates is calculated for both satellites. To produce the combined dataset, the precipitation from CloudSat are used for the low precipitation rates while CloudSat precipitation amount is greater than that from GPM DPR, until GPM DPR precipitation amount is higher than that from CloudSat, at which precipitation rate data from the GPM are used. By combining the two datasets, we discuss the seasonal and geo-graphical distribution of weak precipitation detected by CloudSat that is beyond the sensitivity of GPM DPR. We also hope to gain a more complete picture of the precipitation that occurs over oceanic regions.

Diagnosing AIRS Sampling with CloudSat Cloud Classes

NASA Technical Reports Server (NTRS)

Fetzer, Eric; Yue, Qing; Guillaume, Alexandre; Kahn, Brian

2011-01-01

AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.

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

NASA Technical Reports Server (NTRS)

Molthan, A. L.; Haynes, J. A.; Jedlovec, G. L.; Lapenta, W. M.

2009-01-01

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.

Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles

NASA Astrophysics Data System (ADS)

Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

2010-01-01

A cloud frequency of occurrence matrix is generated using merged cloud vertical profiles derived from the satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud profiling radar. The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical profiles can be related by a cloud overlap matrix when the correlation length of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches random overlap with increasing distance separating cloud layers and that the probability of deviating from random overlap decreases exponentially with distance. One month of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data (July 2006) support these assumptions, although the correlation length sometimes increases with separation distance when the cloud top height is large. The data also show that the correlation length depends on cloud top hight and the maximum occurs when the cloud top height is 8 to 10 km. The cloud correlation length is equivalent to the decorrelation distance introduced by Hogan and Illingworth (2000) when cloud fractions of both layers in a two-cloud layer system are the same. The simple relationships derived in this study can be used to estimate the top-of-atmosphere irradiance difference caused by cloud fraction, uppermost cloud top, and cloud thickness vertical profile differences.

A comparison between CloudSat and aircraft data for mixed-phase and cirrus clouds

NASA Astrophysics Data System (ADS)

Mioche, G.; Gayet, J.-F.; Minikin, A.; Herber, A.; Pelon, J.

2009-04-01

Nowadays, space remote sensing measurements are a very useful way to study the atmosphere on a global scale. Among the numerous scientific satellites in space, the A-Train is a constellation of 6 satellites flying together with on board complementary instruments of new generation (radiometers, radar, lidar, spectrometers…) to study all parts of the atmosphere: gas composition, clouds and aerosols distribution and properties, and radiation budget. Among these satellites, two of them where launched in 2006: CALIPSO and CloudSat, respectively with a Lidar (532 and 1064 nm channels with depolarization) and a 94 GHz radar on board. They are especially dedicated to the study of clouds and aerosols, and will allow to obtain for the first time the vertical profiles of clouds and aerosols on a global scale during 3 years. However, to determine clouds and aerosols properties from space raw data, retrieval methods need to be developed. In order to validate these retrieved techniques, and thus the clouds and aerosols properties, numerous validation plans take place around the world, included different ways as ground based measurements, in situ measurements, or airborne remote sensing instruments in collocation with the satellite tracks. In this context, the ASTAR-2007 and POLARCAT-2008 campaigns took place respectively in the Arctic region of Spitzbergen-Norway in April 2007 and in North part of Sweden in April 2008 to study mixed-phase clouds and the CIRCLE-2 campaign was carried out in Western Europe in May 2007 to sample mid-latitude cirrus clouds. The main objectives are the study of microphysical and optical properties of mixed-phase and ice clouds with particular interest on the validation of clouds products derived from CloudSat and CALIPSO data during co-located remote and in situ observations. The airborne microphysical instruments include the Polar Nephelometer probe to measure the scattering phase function and asymmetry parameter of cloud particles, the high resolution Cloud Particle Imager probe (CPI) for imaging the ice particle morphology (2.3 microns pixels size) and standard PMS probes: 2D-C, FSSP-100 and FSSP-300. This presentation focuses on the validation of the standard parameter of the Cloud Profiling Radar (CPR) of CloudSat (equivalent radar reflectivity factor Z). The different IWC(ice water content)-Z relationships determined from combined CloudSat and in situ data are then discussed. The method to derive equivalent reflectivity factor from the CPI data is first presented. According to the particle shape, a mass-diameter relationship and thus a reflectivity factor is determined for each type of ice crystal. This technique noticeably decreases the discrepancies of radar reflectivity-derived values due to the natural variability of ice crystal shapes. Comparisons of the reflectivity factor deduced from CPI and those from CloudSat for various types of clouds are then discussed. The next step to the interpretation of the CloudSat product is to derive IWC-Z relationships for assessing IWC distributions on a global scale, which is an important improvement to constrain global scale modelling. Several IWC-Z relationships are determined from in situ measurements according to the various case studies including Arctic mixed-phase clouds, Arctic and mid-latitude cirrus. The improvements on the results by using the CPI data-processing method are discussed. Acknowledgements: This work was funded by the Centre National d'Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR BLAN06-1_137670), the Institut National des Sciences de l'Univers (INSU/CNRS), the Institut Polaire Français Paul Emile Victor (IPEV), the Alfred Wegener Institute (AWI) and the Deutsches Zentrum für Luft-und Raumfahrt (DLR). The CloudSat data are courtesy of the CloudSat Data Processing Center.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

2012-01-01

The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny

2010-01-01

Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

Estimating vertical profiles of water-cloud droplet effective radius from SWIR satellite measurements via a statistical model derived from CloudSat observations

NASA Astrophysics Data System (ADS)

Nagao, T. M.; Murakami, H.; Nakajima, T. Y.

2017-12-01

This study proposes an algorithm to estimate vertical profiles of cloud droplet effective radius (CDER-VP) for water clouds from shortwave infrared (SWIR) measurements of Himawari-8/AHI via a statistical model of CDER-VP derived from CloudSat observation. Several similar algorithms in previous studies utilize a spectral radiance matching on the assumption of simultaneous observations of CloudSat and Aqua/MODIS. However, our algorithm does not assume simultaneous observations with CloudSat. First, in advance, a database (DB) of CDER-VP is prepared by the following procedure: TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI are simulated using CDER-VP and cloud optical depth vertical profile (COD-VP) contained in the CloudSat 2B-CWC-RVOD and 2B-TAU products. Cloud optical thickness (COT), Column-CDER and cloud top height (CTH) are retrieved from the simulated radiances using a traditional retrieval algorithm with vertically homogeneous cloud model (1-SWIR VHC method). The CDER-VP is added to the DB by using the COT and Column-CDER retrievals as a key of the DB. Then by using principal component (PC) analysis, up to three PC vectors of the CDER-VPs in the DB are extracted. Next, the algorithm retrieves CDER-VP from actual AHI measurements by the following procedure: First, COT, Column-CDER and CTH are retrieved from TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI using by 1-SWIR VHC method. Then, the PC vectors of CDER-VP is fetched from the DB using the COT and Column-CDER retrievals as the key of the DB. Finally, using coefficients of the PC vectors of CDER-VP as variables for retrieval, CDER-VP, COT and CTH are retrieved from TOA radiances at 0.65, 1.6, 2.3, 3.9 and 10.4-μm bands of the AHI based on optimal estimation method with iterative radiative transfer calculation. The simulation result showed the CDER-VP retrieval errors were almost smaller than 3 - 4 μm. The CDER retrieval errors at the cloud base were almost larger than the others (e.g. CDER at cloud top), especially when COT and CDER was large. The tendency can be explained by less sensitivities of SWIRs to CDER at cloud base. Additionally, as a case study, this study will attempt to apply the algorithm to the AHI's high-frequency observations, and to interpret the time series of the CDER-VP retrievals in terms of temporal evolution of water clouds.

Rain Floods Central Texas

NASA Image and Video Library

2007-06-28

This image was taken on June 26, 2007, UTC 20:00. In this image an obvious storm hangs over the middle of the United States. Figure 1 shows NASA CloudSat data looking, in profile, at the cloud in this storm.

Observing relationships between lightning and cloud profiles by means of a satellite-borne cloud radar

NASA Astrophysics Data System (ADS)

Buiat, Martina; Porcù, Federico; Dietrich, Stefano

2017-01-01

Cloud electrification and related lightning activity in thunderstorms have their origin in the charge separation and resulting distribution of charged iced particles within the cloud. So far, the ice distribution within convective clouds has been investigated mainly by means of ground-based meteorological radars. In this paper we show how the products from Cloud Profiling Radar (CPR) on board CloudSat, a polar satellite of NASA's Earth System Science Pathfinder (ESSP), can be used to obtain information from space on the vertical distribution of ice particles and ice content and relate them to the lightning activity. The analysis has been carried out, focusing on 12 convective events over Italy that crossed CloudSat overpasses during significant lightning activity. The CPR products considered here are the vertical profiles of cloud ice water content (IWC) and the effective radius (ER) of ice particles, which are compared with the number of strokes as measured by a ground lightning network (LINET). Results show a strong correlation between the number of strokes and the vertical distribution of ice particles as depicted by the 94 GHz CPR products: in particular, cloud upper and middle levels, high IWC content and relatively high ER seem to be favourable contributory causes for CG (cloud to ground) stroke occurrence.

Assessing modelled spatial distributions of ice water path using satellite data

NASA Astrophysics Data System (ADS)

Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

2010-05-01

The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Khatri, P.; Iwabuchi, H.; Saito, M.

2017-12-01

High-level cirrus clouds, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

NASA Technical Reports Server (NTRS)

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

2012-01-01

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

CloudSat Preps for Launch at Vandenberg Air Force Base, CA

NASA Technical Reports Server (NTRS)

2005-01-01

The CloudSat spacecraft sits encapsulated within its Boeing Delta launch vehicle dual payload attach fitting at Vandenberg Air Force Base, Calif. CloudSat will share its ride to orbit late next month with NASA's CALIPSO spacecraft. The two spacecraft are designed to reveal the secrets of clouds and aerosols.

Study Pollution Impacts on Upper-Tropospheric Clouds with Aura, CloudSat, and CALIPSO Data

NASA Technical Reports Server (NTRS)

Wu, Dong

2007-01-01

This viewgraph presentation reviews the impact of pollution on clouds in the Upper Troposphere. Using the data from the Aura Microwave Limb Sounder (MLS), CloudSat, CALIPSO the presentation shows signatures of pollution impacts on clouds in the upper troposphere. The presentation demonstrates the complementary sensitivities of MLS , CloudSat and CALIPSO to upper tropospheric clouds. It also calls for careful analysis required to sort out microphysical changes from dynamical changes.

CloudSat Level 3 Gridded Products: Introduction and Application to Evaluation of the MERRA-2 Reanalysis

NASA Astrophysics Data System (ADS)

Haynes, J. M.; Miller, S. D.; Partain, P.

2016-12-01

CloudSat mission data are currently available to the science community in the form of granule-level, single-orbit Level 2 products. Although this is useful for process-level studies and investigation of individual radar profiles, it is less convenient for regional studies or investigations requiring that cloud properties be aggregated over long periods of time. This aggregation process is not necessary straight-forward: it must be tailored to the specific data product and scientific data contained therein, it requires large amounts of data transfer, and care must be taken to perform the aggregation only on statistically significant spatial and temporal scales. To make CloudSat data more accessible to the broader scientific community and in order to better preserve the environmental data record, a suite of Level 3 (L3), gridded data products are being developed by the CloudSat Data Processing Center (DPC). These products are being developed in four broad categories: (1) radiation budget, (2) radar reflectivity, (3) precipitation incidence and type, and (4) microphysics. L3 products will be generated on both standard (i.e. fixed resolution) grids, and dynamically with user-configurable grid spacing and timescales via an online user interface. An important distinction of the current L3 development is in its usage of dynamically configurable histograms, allowing for representation of the detailed, non-Gaussian characteristics of the data distribution. This work serves to both introduce these products to the wider scientific community and demonstrate their utility for model and reanalysis evaluation. Toward the latter goal, an analysis of the new Modern Era Retrospective-Analysis for Research and Applications version 2 (MERRA-2) cloud products is performed using a development version of the CloudSat L3 products. L3 products are used to evaluate near-global cloud fraction, optical depth, cloud liquid and ice water content, shortwave and longwave cloud radiative effects, and precipitation occurrence. These results are then contrasted against the corresponding MERRA-2 fields, and the differences are explored in terms of potential improvements and/or shortcomings in both the reanalysis and observational products.

A-Train Observations of Young Volcanic Eruption Clouds

NASA Astrophysics Data System (ADS)

Carn, S. A.; Prata, F.; Yang, K.; Rose, W. I.

2011-12-01

NASA's A-Train satellite constellation (including Aqua, CloudSat, CALIPSO, and Aura) has been flying in formation since 2006, providing unprecedented synergistic observations of numerous volcanic eruption clouds in various stages of development. Measurements made by A-Train sensors include total column SO2 by the Ozone Monitoring Instrument (OMI) on Aura, upper tropospheric and stratospheric (UTLS) SO2 column by the Atmospheric Infrared Sounder (AIRS) on Aqua and Microwave Limb Sounder (MLS) on Aura, ash mass loading from AIRS and the Moderate resolution Imaging Spectroradiometer (MODIS) on Aqua, UTLS HCl columns and ice water content (IWC) from MLS, aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard CALIPSO, and hydrometeor profiles from the Cloud Profiling Radar (CPR) on CloudSat. The active vertical profiling capability of CALIPSO, CloudSat and MLS sychronized with synoptic passive sensing of trace gases and aerosols by OMI, AIRS and MODIS provides a unique perspective on the structure and composition of volcanic clouds. A-Train observations during the first hours of atmospheric residence are particularly valuable, as the fallout, segregation and stratification of material in this period determines the concentration and altitude of constituents that remain to be advected downwind. This represents the eruption 'source term' essential for dispersion modeling, and hence for aviation hazard mitigation. In this presentation we show examples of A-Train data collected during recent eruptions including Chaitén (May 2008), Kasatochi (August 2008), Redoubt (March 2009), Eyjafjallajökull (April 2010) and Cordón Caulle (June 2011). We interpret the observations using the canonical three-stage view of volcanic cloud development [e.g., Rose et al., 2000] from initial rapid ash fallout to far-field dispersion of fine ash, gas and aerosol, and results from numerical modeling of volcanic plumes [e.g., Textor et al., 2003] and discuss the degree to which the observations validate existing theory and models. We also describe plans for advanced SO2 and ash retrieval algorithms that will exploit the synergy between UV and IR sensors in the A-Train for improved quantification of ash and SO2 loading by volcanic eruptions.

Comparison of convective clouds observed by spaceborne W-band radar and simulated by cloud-resolving atmospheric models

NASA Astrophysics Data System (ADS)

Dodson, Jason B.

Deep convective clouds (DCCs) play an important role in regulating global climate through vertical mass flux, vertical water transport, and radiation. For general circulation models (GCMs) to simulate the global climate realistically, they must simulate DCCs realistically. GCMs have traditionally used cumulus parameterizations (CPs). Much recent research has shown that multiple persistent unrealistic behaviors in GCMs are related to limitations of CPs. Two alternatives to CPs exist: the global cloud-resolving model (GCRM), and the multiscale modeling framework (MMF). Both can directly simulate the coarser features of DCCs because of their multi-kilometer horizontal resolutions, and can simulate large-scale meteorological processes more realistically than GCMs. However, the question of realistic behavior of simulated DCCs remains. How closely do simulated DCCs resemble observed DCCs? In this study I examine the behavior of DCCs in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and Superparameterized Community Atmospheric Model (SP-CAM), the latter with both single-moment and double-moment microphysics. I place particular emphasis on the relationship between cloud vertical structure and convective environment. I also emphasize the transition between shallow clouds and mature DCCs. The spatial domains used are the tropical oceans and the contiguous United States (CONUS), the latter of which produces frequent vigorous convection during the summer. CloudSat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the clouds form. The CloudSat cloud mask and radar reflectivity profiles for CONUS cumuliform clouds (defined as clouds with a base within the planetary boundary layer) during boreal summer are first averaged and compared. Both NICAM and SP-CAM greatly underestimate the vertical growth of cumuliform clouds. Then they are sorted by three large-scale environmental variables: total preciptable water (TPW), surface air temperature (SAT), and 500hPa vertical velocity (W500), representing the dynamical and thermodynamical environment in which the clouds form. The sorted CloudSat profiles are then compared with NICAM and SP-CAM profiles simulated with the Quickbeam CloudSat simulator. Both models have considerable difficulty representing the relationship of SAT and clouds over CONUS. For TPW and W500, shallow clouds transition to DCCs at higher values than observed. This may be an indication of the models' inability to represent the formation of DCCs in marginal convective environments. NICAM develops tall DCCs in highly favorable environments, but SP-CAM appears to be incapable of developing tall DCCs in almost any environment. The use of double moment microphysics in SP-CAM improves the frequency of deep clouds and their relationship with TPW, but not SAT. Both models underpredict radar reflectivity in the upper cloud of mature DCCs. SP-CAM with single moment microphysics has a particularly unrealistic DCC reflectivity profile, but with double moment microphysics it improves substantially. SP-CAM with double-moment microphysics unexpectedly appears to weaken DCC updraft strength as TPW increases, but otherwise both NICAM and SP-CAM represent the environment-versus-DCC relationships fairly realistically.

CloudSat Anomaly and Return to the A-Train: Lessons Learned for Satellite Constellations

NASA Technical Reports Server (NTRS)

Vane, Deborah

2015-01-01

In April 2011, CloudSat suffered a severe battery anomaly, leaving the space-craft in emergency mode without the ability to command or maneuver the spacecraft. Before the team was able to recover spacecraft operability, CloudSat passed close to the Aqua satellite in the A-Train and then exited the A-Train. A new mode of operations, termed Daylight Only Operations (DO-Op) mode was developed to enable CloudSat to resume science operations in an orbit under the A-Train by November 2011, and in July 2012 CloudSat re-entered the A-Train. This paper describes challenges and lessons-learned during the anomaly, the exit from the A-Train and the return to the A-Train. These lessons-learned may ap-ply to other current and future satellite constellations in Earth orbit.

Dichroic Filter for Separating W-Band and Ka-Band

NASA Technical Reports Server (NTRS)

Epp, Larry W.; Durden, Stephen L.; Jamnejad, Vahraz; Long, Ezra M.; Sosnowski, John B.; Higuera, Raymond J.; Chen, Jacqueline C.

2012-01-01

The proposed Aerosol/Cloud/Ecosystems (ACEs) mission development would advance cloud profiling radar from that used in CloudSat by adding a 35-GHz (Ka-band) channel to the 94-GHz (W-band) channel used in CloudSat. In order to illuminate a single antenna, and use CloudSat-like quasi-optical transmission lines, a spatial diplexer is needed to add the Ka-band channel. A dichroic filter separates Ka-band from W-band by employing advances in electrical discharge machining (EDM) and mode-matching analysis techniques developed and validated for designing dichroics for the Deep Space Network (DSN), to develop a preliminary design that both met the requirements of frequency separation and mechanical strength. First, a mechanical prototype was built using an approximately 102-micron-diameter EDM process, and tolerances of the hole dimensions, wall thickness, radius, and dichroic filter thickness measured. The prototype validated the manufacturing needed to design a dichroic filter for a higher-frequency usage than previously used in the DSN. The initial design was based on a Ka-band design, but thicker walls are required for mechanical rigidity than one obtains by simply scaling the Ka-band dichroic filter. The resulting trade of hole dimensions for mechanical rigidity (wall thickness) required electrical redesign of the hole dimensions. Updates to existing codes in the linear solver decreased the analysis time using mode-matching, enabling the electrical design to be realized quickly. This work is applicable to missions and instruments that seek to extend W-band cloud profiling measurements to other frequencies. By demonstrating a dichroic filter that passes W-band, but reflects a lower frequency, this opens up the development of instruments that both compare to and enhance CloudSat.

Zonal Aerosol Direct and Indirect Radiative Forcing using Combined CALIOP, CERES, CloudSat, and CERES Data

NASA Astrophysics Data System (ADS)

Miller, W. F.; Kato, S.; Rose, F. G.; Sun-Mack, S.

2009-12-01

Under the NASA Energy and Water Cycle System (NEWS) program, cloud and aerosol properties derived from CALIPSO, CloudSat, and MODIS data then matched to the CERES footprint are used for irradiance profile computations. Irradiance profiles are included in the publicly available product, CCCM. In addition to the MODIS and CALIPSO generated aerosol, aerosol optical thickness is calculated over ocean by processing MODIS radiance through the Stowe-Ignatov algorithm. The CERES cloud mask and properties algorithm are use with MODIS radiance to provide additional cloud information to accompany the actively sensed data. The passively sensed data is the only input to the standard CERES radiative flux products. The combined information is used as input to the NASA Langley Fu-Liou radiative transfer model to determine vertical profiles and Top of Atmosphere shortwave and longwave flux for pristine, all-sky, and aerosol conditions for the special data product. In this study, the three sources of aerosol optical thickness will be compared directly and their influence on the calculated and measured TOA fluxes. Earlier studies indicate that the largest uncertainty in estimating direct aerosol forcing using aerosol optical thickness derived from passive sensors is caused by cloud contamination. With collocated CALIPSO data, we are able to estimate frequency of occurrence of cloud contamination, effect on the aerosol optical thickness and direct radiative effect estimates.

CloudSat Safety Operations at Vandenberg AFB

NASA Technical Reports Server (NTRS)

Greenberg, Steve

2006-01-01

CloudSat safety operations at Vendenberg AFB is given. The topics include: 1) CloudSat Project Overview; 2) Vandenberg Ground Operations; 3) Delta II Launch Vehicle; 4) The A-Train; 5) System Safety Management; 6) CALIPSO Hazards Assessment; 7) CALIPSO Supplemental Safeguards; 8) Joint System Safety Operations; 9) Extended Stand-down; 10) Launch Delay Safety Concerns; and 11) Lessons Learned.

A 94 GHz RF Electronics Subsystem for the CloudSat Cloud Profiling Radar

NASA Technical Reports Server (NTRS)

LaBelle, Remi C.; Girard, Ralph; Arbery, Graham

2003-01-01

The CloudSat spacecraft, scheduled for launch in 2004, will carry the 94 GHz Cloud Profiling Radar (CPR) instrument. The design, assembly and test of the flight Radio Frequency Electronics Subsystem (RFES) for this instrument has been completed and is presented here. The RFES consists of an Upconverter (which includes an Exciter and two Drive Amplifiers (DA's)), a Receiver, and a Transmitter Calibrator assembly. Some key performance parameters of the RFES are as follows: dual 100 mW pulse-modulated drive outputs at 94 GHz, overall Receiver noise figure < 5.0 dB, a highly stable W-band noise source to provide knowledge accuracy of Receiver gain of < 0.4 dB over the 2 year mission life, and a W-band peak power detector to monitor the transmitter output power to within 0.5 dB over life. Some recent monolithic microwave integrated circuit (MMIC) designs were utilized which implement the DA's in 0.1 micron GaAs high electron-mobility transistor (HEMT) technology and the Receiver low-noise amplifier (LNA) in 0.1 micron InP HEMT technology.

Microphysical variability of Amazonian deep convective cores observed by CloudSat and simulated by a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Brant Dodson, J.; Taylor, Patrick C.; Branson, Mark

2018-05-01

Recently launched cloud observing satellites provide information about the vertical structure of deep convection and its microphysical characteristics. In this study, CloudSat reflectivity data is stratified by cloud type, and the contoured frequency by altitude diagrams reveal a double-arc structure in deep convective cores (DCCs) above 8 km. This suggests two distinct hydrometeor modes (snow versus hail/graupel) controlling variability in reflectivity profiles. The day-night contrast in the double arcs is about four times larger than the wet-dry season contrast. Using QuickBeam, the vertical reflectivity structure of DCCs is analyzed in two versions of the Superparameterized Community Atmospheric Model (SP-CAM) with single-moment (no graupel) and double-moment (with graupel) microphysics. Double-moment microphysics shows better agreement with observed reflectivity profiles; however, neither model variant captures the double-arc structure. Ultimately, the results show that simulating realistic DCC vertical structure and its variability requires accurate representation of ice microphysics, in particular the hail/graupel modes, though this alone is insufficient.

CloudSat Education Network: Partnerships for Outreach

NASA Astrophysics Data System (ADS)

TeBockhorst, D.

2014-12-01

CloudSat Education Network (CEN): Partnerships to improve the understanding of clouds in formal and informal settings. Since The CloudSat satellite launched in 2006 the Formal and Informal education programs for the mission have been focused on bringing an understanding about the mission science and the importance of clouds, climate & weather science. This has been done by creating and strengthening partnership and collaboration within scientific and educational communities around the country and the world. Because CloudSat was formally recognized as a Earth System Science Pathfinder campaign with the GLOBE program, the CEN developed a set of field protocols for student observations that augmented the GLOBE atmosphere protocols when there was a satellite overpass. This shared process between GLOBE & CloudSat resulted in the training & creation of CEN schools that are both GLOBE schools and CloudSat schools, and also produced three GLOBE partnerships that specialize in cloud science education and outreach. In addition, the CEN has developed productive relationships with other NASA missions and EPO teams. Specifically, in collaboration with the NASA CERES mission projects S'Cool and MyNASAData, we have co-presented at NSTA conferences and with schools participating in a NASA EPOESS-funded formal education project. This collaborative work has been a very real benefit to a wide variety of audiences needing to strengthen their understanding of clouds and their roles in the earth system, and we hope will serve as a model to future missions looking to involve the public in mission science.

Exploring and Visualizing A-Train Instrument Data

NASA Technical Reports Server (NTRS)

Kempler, S.; Leptoukh, G.; Berrick, S.; Stephens, G.; Winker, D.; Reinke, D.

2007-01-01

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Clouds in a Bottle: Qualitative and Quantiative Demonstrations for Cloud Formation in a Learning Environment

NASA Astrophysics Data System (ADS)

Ellis, T. D.

2015-12-01

The NASA CloudSat mission has been revealing the inner secrets of clouds since 2006 using its one-of-a-kind spaceborne cloud radar. During its mission, the CloudSat Education Network, consisting of schools in Asia, Europe, and North America, have been collecting data on Clouds when CloudSat passes overhead. The education team has spent many hours researching and presenting different methods for making clouds for demonstrations in formal and informal settings. In this presentation, we will present several variations on methods for doing the cloud in a bottle demonstration, including strengths and weaknesses for each, and a brief overview of the science involved in the various demonstrations.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

A Multi-Variable Approach to Diagnosing the Monthly Covariability of the Amazonian Radiative and Convective Diurnal Cycles

NASA Astrophysics Data System (ADS)

Dodson, J. B.; Taylor, P. C.

2016-12-01

The diurnal cycle of convection (CDC) greatly influences the water, radiative, and energy budgets in convectively active regions. For example, previous research of the Amazonian CDC has identified significant monthly covariability between the satellite-observed radiative and precipitation diurnal and multiple reanalysis-derived atmospheric state variables (ASVs) representing convective instability. However, disagreements between retrospective analysis products (reanalyses) over monthly ASV anomalies create significant uncertainty in the resulting covariability. Satellite observations of convective clouds can be used to characterize monthly anomalies in convective activity. CloudSat observes multiple properties of both deep convective cores and the associated anvils, and so is useful as an alternative to the use of reanalyses. CloudSat cannot observe the full diurnal cycle, but it can detect differences between daytime and nighttime convection. Initial efforts to use CloudSat data to characterize convective activity showed that the results are highly dependent on the choice of variable used to characterize the cloud. This is caused by a series of inverse relationships between convective frequency, cloud top height, radar reflectivity vertical profile, and other variables. A single, multi-variable index for convective activity based on CloudSat data may be useful to clarify the results. Principal component analysis (PCA) provides a method to create a multivariable index, where the first principal component (PC1) corresponds with convective instability. The time series of PC1 can then be used as a proxy for monthly variability in convective activity. The primary challenge presented involves determining the utility of PCA for creating a robust index for convective activity that accounts for the complex relationships of multiple convective cloud variables, and yields information about the interactions between convection, the convective environment, and radiation beyond the previous single-variable approaches. The choice of variables used to calculate PC1 may influence any results based on PC1, so it is necessary to test the sensitivity of the results to different variable combinations.

CloudSat system engineering: techniques that point to a future success

NASA Technical Reports Server (NTRS)

Basilio, R. R.; Boain, R. J.; Lam, T.

2002-01-01

Over the past three years the CloutSat Project, a NASA Earth System Science Pathfinder mission to provide from space the first global survey of cloud profiles and cloud physical properties, has implemented a successful project system engineering approach. Techniques learned through heuristic reasoning of past project events and professional experience were applied along with select methods recently touted to increase effectiveness without compromising effiency.

Intercomparison of vertical structure of storms revealed by ground-based (NMQ) and spaceborne radars (CloudSat-CPR and TRMM-PR).

PubMed

Fall, Veronica M; Cao, Qing; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.

Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ) and Spaceborne Radars (CloudSat-CPR and TRMM-PR)

PubMed Central

Fall, Veronica M.; Hong, Yang

2013-01-01

Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR) and Ku-band Precipitation Radar (PR), which are onboard NASA's CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE). This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ) system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors' type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR) reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts. PMID:24459424

A second look at the CloudSat/TRMM intersect data

NASA Astrophysics Data System (ADS)

Haddad, Z.; Kuo, K.; Smith, E. A.; Kiang, D.; Turk, F. J.

2010-12-01

The original objective motivating the creation of the CloudSat+TRMM intersect products (by E.A. Smith, K.-S. Kuo et al) was to provide new opportunities in research related to precipitating clouds. The data products consist of near-coincident CloudSat Cloud Profiling Radar calibrated 94-GHz reflectivity factors and detection flag, sampled every 240 m in elevation, and the TRMM Precipitation Radar calibrated 13.8-GHz reflectivity factors, attenuation-adjusted reflectivity factors and rain rate estimates, sampled every 250 m in elevation, in the TRMM beam whose footprint encompasses the CloudSat beam footprint. Because retrieving precipitation distributions from single-frequency radar measurements is a very under-constrained proposition, we decided to restrict our analyses to CloudSat data that were taken within 3 minutes of a TRMM pass. We ended up with over 5000 beams of nearly simultaneous observations of precipitation, and proceeded in two different ways: 1) we attempted to perform retrievals based on simultaneous radar reflectivity measurements at Ku and W bands. At low precipitation rates, the Ku-band radar does not detect much of the rain. At higher precipitation rates, the W-band radar incurs high attenuation, and this makes “Hitschfeld-Bordan” retrievals (from the top of the column down toward the surface) diverge because of numerical instability. The main question for this portion of the analysis was to determine if these two extremes are indeed extremes that still afford us a significant number of “in-between” cases, on which we can apply a careful dual-frequency retrieval algorithm; 2) we also attempted to quantify the ability of the Ku-band measurements to provide complementary information to the W-band estimates outside their overlap region, and vice versa. Specifically, instead of looking at the admittedly small vertical region where both radars detect precipitation and where their measurements are unambiguously related to the underlying physics (unaffected by multiple scattering), we considered the TRMM estimates in the rain below the freezing level, and tried to infer the joint behavior of the overlying CloudSat measurements above the freezing level as a function of the rain - and, conversely, we considered the vertical variability of the CloudSat estimates in the above-freezing region, and derived the joint behavior of the TRMM measurements in the rain as a function of the CloudSat estimates. The results are compiled in databases that should allow users of less-sensitive lower-frequency radars to infer some quantitative information about the storm structure above the precipitating core in the absence of higher-frequency measurements, just as it will allow users of too-sensitive higher-frequency radars to infer some quantitative information about the precipitation closer to the surface in the absence of lower-frequency measurements.

Behavior of predicted convective clouds and precipitation in the high-resolution Unified Model over the Indian summer monsoon region

NASA Astrophysics Data System (ADS)

Jayakumar, A.; Sethunadh, Jisesh; Rakhi, R.; Arulalan, T.; Mohandas, Saji; Iyengar, Gopal R.; Rajagopal, E. N.

2017-05-01

National Centre for Medium Range Weather Forecasting high-resolution regional convective-scale Unified Model with latest tropical science settings is used to evaluate vertical structure of cloud and precipitation over two prominent monsoon regions: Western Ghats (WG) and Monsoon Core Zone (MCZ). Model radar reflectivity generated using Cloud Feedback Model Intercomparison Project Observation Simulator Package along with CloudSat profiling radar reflectivity is sampled for an active synoptic situation based on a new method using Budyko's index of turbulence (BT). Regime classification based on BT-precipitation relationship is more predominant during the active monsoon period when convective-scale model's resolution increases from 4 km to 1.5 km. Model predicted precipitation and vertical distribution of hydrometeors are found to be generally in agreement with Global Precipitation Measurement products and BT-based CloudSat observation, respectively. Frequency of occurrence of radar reflectivity from model implies that the low-level clouds below freezing level is underestimated compared to the observations over both regions. In addition, high-level clouds in the model predictions are much lesser over WG than MCZ.

Evaluation of multi-layer cloud detection based on MODIS CO2-slicing algorithm with CALIPSO-CloudSat measurements.

NASA Astrophysics Data System (ADS)

Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.

2016-12-01

Knowledge of the vertical cloud distribution is important for a variety of climate and weather applications. The cloud overlapping variations greatly influence the atmospheric heating/cooling rates, with implications for the surface-troposphere radiative balance, global circulation and precipitation. Additionally, an accurate knowledge of the multi-layer cloud distribution in real-time can be used in applications such safety condition for aviation through storms and adverse weather conditions. In this study, we evaluate a multi-layered cloud algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with cloud properties determined from VIS, IR and NIR channels to locate high thin clouds over low-level clouds, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and CloudSat (Stephens et. al, 2002) (CLCS) derived cloud vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer cloud properties. We focus on 2 layer overlapping and 1-layer clouds identified by the active sensors and investigate how well these systems are identified by the MODIS multi-layer technique. The results show that for these multi-layered clouds identified by CLCS, the MCF correctly identifies about 83% of the cases as multi-layer. However, it is found that the upper CTH is underestimated by about 2.6±0.4 km, because the CO2-slicing technique is not as sensitive to the cloud physical top as the CLCS. The lower CTH agree better with differences found to be about 1.2±0.5 km. Another outstanding issue for the MCF approach is the large number of multi-layer false alarms that occur in single-layer conditions. References: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles, J. Geophys. Res., 115. Stephens, G. L., et al. (2002), The CloudSat mission and A-Train, Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., 2010: The CALIPSO Mission: A global 3D view of aerosols and clouds. Bull. Amer. Meteor. Soc., 91.

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Haynes, John M.; Jedlovec, Gary J.; Lapenta, William M.

2009-01-01

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Cloud and aerosol occurrences in the UTLS region across Pakistan during summer monsoon seasons using CALIPSO and CloudSat observations

NASA Astrophysics Data System (ADS)

Chishtie, Farrukh

2016-04-01

As part of the A-train NASA constellation, Coudsat and CALIPSO provide an unprecedented vertical observation of clouds and aerosols. Using observational data from both of these satellites, we conduct a multi-year analysis from 2006-2014, of the UTLS (Upper Troposphere and the Lower Stratosphere) region. We map out cloud and aerosol occurrences in this region across Pakistan, specifically around the summer monsoon season. Over the past five years, Pakistan has faced tremendous challenges due to massive flooding as well as earlier brief monsoon seasons of low precipitation and short drought periods. Hence, this motivates the present study towards understanding the deep convective and related dynamics in this season which can possibly influence cloud and aerosol transport in the region. Further, while global studies are conducted, the goal of this study is to conduct a detailed study of cloud, aerosols and their interplay, across Pakistan. Due to a dearth of ground observations, this study provides a dedicated focus on the UTLS domain. Vertical profiling satellites in this region are deemed important as there are no ground observations being done. This is important as both the properties and dynamics of clouds and aerosols have to be studied in a wider context in order to better understand the monsoon season and its onset in this region. With the CALIPSO Vertical Feature Mask (VFM), Total Attenuated Backscatter (TAB) and Depolarization Ratio (DR) as well as the combined CloudSat's 2B-GEOPROF-LIDAR (Radar-Lidar Cloud Geometrical Profile) and 2B-CLDCLASS-LIDAR (Radar-Lidar Cloud Classification) products, we find the presence of thin cirrus clouds in the UTLS region in the periods of June-September from the 2006-2014 period. There are marked differences in day observations as compared to night in both of these satellite retrievals, with the latter period finding more occurrences of clouds in the UTLS region. Dedicated CloudSat products 2B-CLDCLASS (cloud classification) and 2C-TAU (Cloud Optical Depth) further confirm the presence of sub-visual and thin cirrus clouds in the UTLS region, during the summer monsoon season. From CALIPSO observations, there is significant presence of aerosol layers before the onset of precipitation in the troposphere. This thickness ranges from 1-4 km, with increasing thickness observed the 2009-2014 period. Implications of these findings are detailed in this presentation.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2005-05-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

NASA missions CALIPSO and CloudSat partner with the GLOBE program to provide student opportunities for data collection to aid scientists researching climate change

NASA Astrophysics Data System (ADS)

Robinson, D. Q.; Maggi, B. H.; Krumm, D. K.

2004-12-01

NASA places great emphasis on developing partnerships with education communities, including collaborations with university scientists, K-16 science educators and students. Two universities contributing to this effort through their involvement with NASA satellite based research missions, CALIPSO and CloudSat, are Hampton University and Colorado State University. Both universities provide atmospheric research scientists for the missions and leadership for the Education and Outreach Programs developed for CALIPSO and CloudSat. These satellite-based research missions are co-manifested for launch during the spring 2004 and are included in the Afternoon Constellation also known as the "A-Train" satellite formation. The A-Train will consist of six missions flying in close proximity, providing combined detailed observations about the Earth's atmosphere allowing scientists to make better predictions related to climate change. CloudSat will use radar and provide a global survey of cloud properties to aid with improving cloud models and the accuracy of weather forecasts. CALIPSO will use Lidar to detect size and distribution of aerosols that will aid in improving our understanding of the role aerosols and clouds play in Earth's climate system. Each of the A-Train missions has a unique education and outreach program for students and teachers. Included in the CALIPSO and CloudSat education and outreach is a partnership with the GLOBE Program. GLOBE involves students worldwide in data collection and mission observations. The GLOBE program is a network of K-14 schools, science centers, after school programs, and environmental clubs from over 105 countries. Students participating in GLOBE collect scientific data according to precise protocols and enter the data into a central database allowing both scientists and students to utilize the information collected. The CALIPSO and CloudSat partnership with GLOBE involves the enlistment of student assistance worldwide for data collection that will be used by both missions. Students use the existing GLOBE protocols on aerosols and clouds to collect data as the satellites pass over their schools. CloudSat scientists will involve students by having them report visual observations related to cloud cover, cloud type and precipitation. This information will be compared to the CloudSat radar data to determine the accuracy of the satellite radar unit. CALIPSO will have students collect and report on aerosol measurements taken with a handheld sun photometer. These measurements will then be compared to those taken with the lidar riding on the satellite. Climate change and the effects aerosols have on climate are current topics in schools today. It now appears likely that anthropogenic aerosols resulting from industrial activities and agricultural burning are affecting weather and climate in some regions of the world. The data collected by students internationally for CALIPSO and CloudSat will allow them to better understand the impacts made by humans on Earth's atmosphere and how these impacts are global in scope. In return, scientists gain a valuable resource giving them ground-based data in more locations than would be possible using established weather stations and research laboratories. The partnership established by the CALIPSO and CloudSat missions with the GLOBE program will provide an opportunity to enrich earth science education in schools with a sustainable connection to NASA education.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

CloudSat Takes a 3D Slice of Hurricane Matthew

NASA Image and Video Library

2016-10-07

NASA's CloudSat flew east of Hurricane Matthew's center on Oct. 6 at 11:30 a.m. PDT (2:30 p.m. EDT), intersecting parts of Matthew's outer rain bands and revealing Matthew's anvil clouds (thick cirrus cloud cover), with cumulus and cumulonimbus clouds beneath (lower image). Reds/pinks are larger water/ice droplets. http://photojournal.jpl.nasa.gov/catalog/PIA21095

Status of High Latitude Precipitation Estimates from Observations and Reanalyses

NASA Technical Reports Server (NTRS)

Behrangi, Ali; Christensen, Matthew; Richardson, Mark; Lebsock, Matthew; Stephens, Graeme; Huffman, George J.; Bolvin, David T.; Adler, Robert F.; Gardner, Alex; Lambrigtsen, Bjorn H.;

W-band spaceborne radar observations of atmospheric river events

NASA Astrophysics Data System (ADS)

Matrosov, S. Y.

2010-12-01

While the main objective of the world first W-band radar aboard the CloudSat satellite is to provide vertically resolved information on clouds, it proved to be a valuable tool for observing precipitation. The CloudSat radar is generally able to resolve precipitating cloud systems in their vertical entirety. Although measurements from the liquid hydrometer layer containing rainfall are strongly attenuated, special retrieval approaches can be used to estimate rainfall parameters. These approaches are based on vertical gradients of observed radar reflectivity factor rather than on absolute estimates of reflectivity. Concurrent independent estimations of ice cloud parameters in the same vertical column allow characterization of precipitating systems and provide information on coupling between clouds and rainfall they produce. The potential of CloudSat for observations atmospheric river events affecting the West Coast of North America is evaluated. It is shown that spaceborne radar measurements can provide high resolution information on the height of the freezing level thus separating areas of rainfall and snowfall. CloudSat precipitation rate estimates complement information from the surface-based radars. Observations of atmospheric rivers at different locations above the ocean and during landfall help to understand evolutions of atmospheric rivers and their structures.

NASA CloudSat Captures Hurricane Daniel Transformation

NASA Image and Video Library

2006-07-25

Hurricane Daniel intensified between July 18 and July 23rd. NASA new CloudSat satellite was able to capture and confirm this transformation in its side-view images of Hurricane Daniel as seen in this series of images

Reconciling CloudSat and GPM Estimates of Falling Snow

NASA Technical Reports Server (NTRS)

Munchak, S. Joseph; Jackson, Gail Skofronick; Kulie, Mark; Wood, Norm; Miliani, Lisa

2017-01-01

Satellite-based estimates of falling snow have been provided by CloudSat (launched in 2006) and the Global Precipitation Measurement (GPM) core satellite (launched in 2014). The CloudSat estimates are derived from W-band radar measurements whereas the GPM estimates are derived from its scanning Ku- and Ka-band Dual-Frequency Precipitation Radar (DPR) and 13-channel microwave imager (GMI). Each platform has advantages and disadvantages: CloudSat has higher resolution (approximately 1.5 km) and much better sensitivity (-28 dBZ), but poorer sampling (nadir-only and daytime-only since 2011) and the reflectivity-snowfall (Z-S) relationship is poorly constrained with single-frequency measurements. Meanwhile, DPR suffers from relatively poor resolution (5 km) and sensitivity (approximately 13 dBZ), but has cross-track scanning capability to cover a 245-km swath. Additionally, where Ku and Ka measurements are available, the conversion of reflectivity to snowfall rate is better-constrained than with a single frequency.

StatisticAl Characteristics of Cloud over Beijing, China Obtained FRom Ka band Doppler Radar Observation

NASA Astrophysics Data System (ADS)

LIU, J.; Bi, Y.; Duan, S.; Lu, D.

2017-12-01

It is well-known that cloud characteristics, such as top and base heights and their layering structure of micro-physical parameters, spatial coverage and temporal duration are very important factors influencing both radiation budget and its vertical partitioning as well as hydrological cycle through precipitation data. Also, cloud structure and their statistical distribution and typical values will have respective characteristics with geographical and seasonal variation. Ka band radar is a powerful tool to obtain above parameters around the world, such as ARM cloud radar at the Oklahoma US, Since 2006, Cloudsat is one of NASA's A-Train satellite constellation, continuously observe the cloud structure with global coverage, but only twice a day it monitor clouds over same local site at same local time.By using IAP Ka band Doppler radar which has been operating continuously since early 2013 over the roof of IAP building in Beijing, we obtained the statistical characteristic of clouds, including cloud layering, cloud top and base heights, as well as the thickness of each cloud layer and their distribution, and were analyzed monthly and seasonal and diurnal variation, statistical analysis of cloud reflectivity profiles is also made. The analysis covers both non-precipitating clouds and precipitating clouds. Also, some preliminary comparison of the results with Cloudsat/Calipso products for same period and same area are made.

Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

NASA Astrophysics Data System (ADS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

2017-08-01

Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (<1 km) cloud occurrences in CCCM are larger over tropical oceans because the CCCM algorithm uses a more relaxed threshold of cloud-aerosol discrimination score for CALIPSO Vertical Feature Mask product. In contrast, midlevel (1-8 km) cloud occurrences in GEOPROF-LIDAR are larger than CCCM at high latitudes (>40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

NASA CloudSat Looks Hurricane Nichole in the Eye

NASA Image and Video Library

2016-10-14

NASA's CloudSat satellite completed an eye overpass of Hurricane Nicole on Oct. 12, 2016, at 10:55 a.m. PDT (17:55 UTC) as the storm was moving toward Bermuda. At the time the system had sustained winds of 109 miles per hour (95 knots), with a minimum pressure of 962 millibars. CloudSat viewed the system just as it was going through a period of intensification (from 98 miles per hour, or 85 knots, to 121 miles per hour (105 knots) during a 12-hour period. http://photojournal.jpl.nasa.gov/catalog/PIA21098

Seeking Augmented Information Content Concerning Diurnal Precipitation Achieved by Combining TRMM-PR and CloudSat-CPR Radar Data Sets

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Kuo, Kwo-Sen; Carty, Hezekiah

2008-01-01

The CloudSat satellite's Cloud Profiling Radar (CPR) is a highly sensitive 94 GHz (W-band) nadir viewing radar system flown in retrograde sun synchronous orbit useful for determining the vertical structure of cloud hydrometeors down to sensitivity of approx. -30 dBZ reflectivity factor. Given this sensitivity, it is possible to unambiguously measure precipitation rates in clouds over a spectrum extending from approx. 0.08 - 3.0 mm hr (sup -1) down to altitudes of 0.5 km with approx.0.25 km vertical binning. This enables an effective means to measure a great deal of the drizzle and light rain spectrum. However, because of its near-polar sunsynchronous orbit, CloudSat cannot sample the diurnal cycle of precipitation, nor with its nadir-only CPR view can it obtain a high duty cycle in sampling precipitation at fixed local times over fixed positions. On the other hand, the TRMM satellite, which is flown in a non-sunsynchronous 35-degree inclined orbit carrying the 13.8 GHz KU-band Precipitation Radar (PR) scanning through nadir over an approx. 225 km swath, can sample both the diurnal cycle and with a much improved duty cycle relative to CloudSat. Moreover, the PR and CPR have the same 0.25 km vertical binning capability. The PR's greatest shortcoming is its approx. +17 dBZ sensitivity, which eliminates the possibility of measuring rain rates below -0.3-0.5 mm hr(sup -1), which can involve rainfall accumulations of up to 50% of the total over some regions. This begs the question of whether by combining CPR and PR data sets, whether it is possible to obtain an augmented measurement of the diurnal precipitation cycle. By collecting complimentary datasets during CloudSat and TRMM satellite orbit crossings within a delta t = 45-min proximity window, it is possible to demonstrate that whenever TRMM detects a precipitation signal, the correlations along the vertical axis between the reflectivities acquired from the CPR and PR are in inverse proportion to the magnitude of the delta t proximity window. By taking advantage of these underlying correlations, it is possible to develop a functional which can be used to broaden the reflectivity spectrum, concomitantly the rain rate spectrum, of the PR measurements based on the inherently broader reflectivity spectrum of the CPR at the lower reflectivity end of the spectrum, concomitantly at lighter rain rates. With the functional in place, it is then possible to produce synthetic CloudSat precipitation imagery over the PR track and thus over the diurnal time period. These augmented data are then used to study the spectral-vertical diurnal properties of precipitation over oceanic regions observed by TRMM.

CloudSat Reflectivity Data Visualization Inside Hurricanes

NASA Technical Reports Server (NTRS)

Suzuki, Shigeru; Wright, John R.; Falcon, Pedro C.

2011-01-01

We have presented methods to rapidly produce visualization and outreach products from CloudSat data for science and the media These methods combine data from several sources in the product generation process In general, the process can be completely automatic, producing products and notifying potential users

Taking a 3-D Slice of Hurricane Maria's Cloud Structure

NASA Image and Video Library

2017-09-20

NASA's CloudSat satellite flew over Hurricane Maria on Sept. 17, 2017, at 1:23 p.m. EDT (17:23 UTC) as the storm had just strengthened into a hurricane in the Atlantic Ocean. Hurricane Maria contained estimated maximum sustained winds of 75 miles per hour (65 knots) and had a minimum barometric pressure of 986 millibars. CloudSat flew over Maria through the center of the rapidly intensifying storm, directly through an overshooting cloud top (a dome-shaped protrusion that shoots out of the top of the anvil cloud of a thunderstorm). CloudSat reveals the vertical extent of the overshooting cloud top, showing the estimated height of the cloud to be 11 miles (18 kilometers). Areas of high reflectivity with deep red and pink colors extend well above 9 miles (15 kilometers) in height, showing large amounts of water being drawn upward high into the atmosphere. A movie is available at https://photojournal.jpl.nasa.gov/catalog/PIA21961

Calibration of a 35-GHz Airborne Cloud Radar: Lessons Learned and Intercomparison with a 94-GHz Airborne Cloud Radar

NASA Astrophysics Data System (ADS)

Ewald, Florian; Gross, Silke; Hagen, Martin; Hirsch, Lutz; Delanoë, Julien

2017-04-01

Clouds play an important role in the climate system since they have a profound influence on Earth's radiation budget and the water cycle. Uncertainties associated with their spatial characteristics as well as their microphysics still introduce large uncertainties in climate change predictions. In recent years, our understanding of the inner workings of clouds has been greatly advanced by the deployment of cloud profiling microwave radars from ground as well as from space like CloudSat or the upcoming EarthCARE satellite mission. In order to validate and assess the limitations of these spaceborne missions, a well-calibrated, airborne cloud radar with known sensitivity to clouds is indispensable. Within this context, the German research aircraft HALO was equipped with the high-power (30kW peak power) cloud radar operating at 35 GHz and a high spectral resolution lidar (HSRL) system at 532 nm. During a number of flight experiments over Europe and over the tropical and extra-tropical North-Atlantic, several radar calibration efforts have been made using the ocean surface backscatter. Moreover, CloudSat underflights have been conducted to compare the radar reflectivity and measurement sensitivity between the air- and spaceborne instruments. Additionally, the influence of different radar wavelengths was explored with joint flights of HALO and the French Falcon 20 aircraft, which was equipped with the RASTA cloud radar at 94 GHz and a HSRL at 355 nm. In this presentation, we will give an overview of lessons learned from different calibration strategies using the ocean surface backscatter. Additional measurements of signal linearity and signal saturation will complement this characterization. Furthermore, we will focus on the coordinated airborne measurements regarding the different sensitivity for clouds at 35 GHz and 94 GHz. By using the highly sensitive lidar signals, we show if the high-power cloud radar at 35 GHz can be used to validate spaceborne and airborne measurements at 94 GHz and which differences are to be expected. Furthermore, the coordinated measurements are used to explore the reflectivity cut-offs of CloudSat and future spaceborne constellations and compare them to ground-based systems.

CloudSat Reflectivity Data Visualization Inside Hurricanes

NASA Technical Reports Server (NTRS)

Suzuki, Shigeru; Wright, John R.; Falcon, Pedro C.

2011-01-01

Animations and other outreach products have been created and released to the public quickly after the CloudSat spacecraft flew over hurricanes. The automated script scans through the CloudSat quicklook data to find significant atmospheric moisture content. Once such a region is found, data from multiple sources is combined to produce the data products and the animations. KMZ products are quickly generated from the quicklook data for viewing in Google Earth and other tools. Animations are also generated to show the atmospheric moisture data in context with the storm cloud imagery. Global images from GOES satellites are shown to give context. The visualization provides better understanding of the interior of the hurricane storm clouds, which is difficult to observe directly. The automated process creates the finished animation in the High Definition (HD) video format for quick release to the media and public.

Characteristics of tropical clouds using A-train information and their relationships with sea surface temperature

NASA Astrophysics Data System (ADS)

Behrangi, A.; Kubar, T. L.; Lambrigtsen, B.

2011-12-01

Different cloud types have substantially different characteristics in terms of radiative forcing and microphysical properties, both important components of Earth's climate system. Relationships between tropical cloud type characteristics and sea surface temperature (SST) using two-years of A-train data are investigated in this presentation. Stratocumulus clouds are the dominant cloud type over SSTs less than 301K, and in fact their fraction is strongly inversely related to SST. This is physically logical as both static stability and large-scale subsidence scale well with decreasing SST. At SSTs greater than 301K, high clouds are the most abundant cloud type. All cloud types (except nimbostratus and stratocumulus) become sharply more abundant for SSTs greater than a window between 299K and 300.5K, depending on cloud type. The fraction of high, deep convective, altostratus, and altocumulus clouds peak at an SST close to 303K, while cumulus clouds have a broad cloud fraction peak centered near 301K. Deep convective and other high cloud types decrease sharply above SSTs of 303K. While overall early morning clouds are 10% (4%) more frequent than afternoon clouds as indicated by CloudSat (lidar-radar), certain cloud types occur more frequently in the early afternoon, such as high clouds. We also show that a large amount of warm precipitation mainly from stratocumulus clouds is missed or significantly underestimated by the current suite of satellite-based global precipitation measuring sensors. However, the operational sensitivity of Cloudsat cloud profiling radar permits to capture significant fraction of light drizzle and warm rain.

A systematic risk management approach employed on the CloudSat project

NASA Technical Reports Server (NTRS)

Basilio, R. R.; Plourde, K. S.; Lam, T.

2000-01-01

The CloudSat Project has developed a simplified approach for fault tree analysis and probabilistic risk assessment. A system-level fault tree has been constructed to identify credible fault scenarios and failure modes leading up to a potential failure to meet the nominal mission success criteria.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

NASA Astrophysics Data System (ADS)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

Multi-Sensor Investigation of a Regional High-Arctic Cloudy Event

NASA Astrophysics Data System (ADS)

Ivanescu, L.; O'Neill, N. T.; Blanchet, J. P.; Baibakov, K.; Chaubey, J. P.; Perro, C. W.; Duck, T. J.

2014-12-01

A regional high-Arctic cloud event observed in March, 2011 at the PEARL Observatory, near the Eureka Weather Station (80°N, 86°W), was investigated with a view to better understanding cloud formation mechanisms during the Polar night. We analysed the temporal cloud evolution with a suite of nighttime, ground-based remote sensing (RS) instruments, supplemented by radiosonde profiles and surface weather measurements. The RS suite included Raman lidar, cloud radar, a star-photometer and microwave-radiometers. In order to estimate the spatial extent and vertical variability of the cloud mass, we employed satellite-based lidar (CALIPSO) and radar (CloudSat) profiles in the regional neighbourhood of Eureka (at a latitude of 80°N, Eureka benefits from a high frequency of CALIPSO and CloudSat overpasses). The ground-based and satellite-based observations provide quantitative measurements of extensive (bulk) properties (cloud and aerosol optical depths), and intensive (per particle properties) such as aerosol and cloud particle size as well as shape, density and aggregation phase of the cloud particulates. All observations were then compared with the upper atmosphere NCEP/NCAR reanalyses in order to understand better the synoptic context of the cloud mass dynamics as a function of key meteorological parameters such as upper air temperature and water vapor circulation. Preliminary results indicated the presence of a particular type of thin ice cloud (TIC-2) associated with a deep and stable atmospheric low. A classification into small and large ice crystal size (< 40 μm and > 40 μm, respectively), identifies the clouds as TIC-1 or TIC-2. This classification is hypothesized to be associated with the nature of the aerosols (non-anthropogenic versus anthropogenic) serving as ice nuclei in their formation. Such a distinction has important implications on the initiation of precipitation, removal rate of the cloud particles and, in consequence, the radiative forcing properties on a regional basis.

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Demek, Scott R.

2010-01-01

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Comparison of the MODIS Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2008-01-01

CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.

An Update on Oceanic Precipitation Rate and its Zonal Distribution in Light of Advanced Observations from Space

NASA Technical Reports Server (NTRS)

Behrangi, Ali; Stephens, Graeme; Adler, Robert F.; Huffman, George J.; Lambrigsten, Bjorn; Lebstock, Matthew

2014-01-01

This study contributes to the estimation of the global mean and zonal distribution of oceanic precipitation rate using complementary information from advanced precipitation measuring sensors and provides an independent reference to assess current precipitation products. Precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and CloudSat cloud profiling radar (CPR) were merged, as the two complementary sensors yield an unprecedented range of sensitivity to quantify rainfall from drizzle through the most intense rates. At higher latitudes, where TRMM PR does not exist, precipitation estimates from Aqua's Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) complemented CloudSat CPR to capture intense precipitation rates. The high sensitivity of CPR allows estimation of snow rate, an important type of precipitation at high latitudes, not directly observed in current merged precipitation products. Using the merged precipitation estimate from the CloudSat, TRMM, and Aqua platforms (this estimate is abbreviated to MCTA), the authors' estimate for 3-yr (2007-09) nearglobal (80degS-80degN) oceanic mean precipitation rate is approx. 2.94mm/day. This new estimate of mean global ocean precipitation is about 9% higher than that of the corresponding Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) value (2.68mm/day) and about 4% higher than that of the Global Precipitation Climatology Project (GPCP; 2.82mm/day). Furthermore, MCTA suggests distinct differences in the zonal distribution of precipitation rate from that depicted in GPCPand CMAP, especially in the Southern Hemisphere.

Evaluation of NCMRWF unified model vertical cloud structure with CloudSat over the Indian summer monsoon region

NASA Astrophysics Data System (ADS)

Jayakumar, A.; Mamgain, Ashu; Jisesh, A. S.; Mohandas, Saji; Rakhi, R.; Rajagopal, E. N.

2016-05-01

Representation of rainfall distribution and monsoon circulation in the high resolution versions of NCMRWF Unified model (NCUM-REG) for the short-range forecasting of extreme rainfall event is vastly dependent on the key factors such as vertical cloud distribution, convection and convection/cloud relationship in the model. Hence it is highly relevant to evaluate the vertical structure of cloud and precipitation of the model over the monsoon environment. In this regard, we utilized the synergy of the capabilities of CloudSat data for long observational period, by conditioning it for the synoptic situation of the model simulation period. Simulations were run at 4-km grid length with the convective parameterization effectively switched off and on. Since the sample of CloudSat overpasses through the monsoon domain is small, the aforementioned methodology may qualitatively evaluate the vertical cloud structure for the model simulation period. It is envisaged that the present study will open up the possibility of further improvement in the high resolution version of NCUM in the tropics for the Indian summer monsoon associated rainfall events.

Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

NASA Technical Reports Server (NTRS)

Hence, Deanna A.; Houze, Robert A.

2011-01-01

A global study of the vertical structures of the clouds of tropical mesoscale convective systems (MCSs) has been carried out with data from the CloudSat Cloud Profiling Radar. Tropical MCSs are found to be dominated by cloud-top heights greater than 10 km. Secondary cloud layers sometimes occur in MCSs, but outside their primary raining cores. The secondary layers have tops at 6 8 and 1 3 km. High-topped clouds extend outward from raining cores of MCSs to form anvil clouds. Closest to the raining cores, the anvils tend to have broader distributions of reflectivity at all levels, with the modal values at higher reflectivity in their lower levels. Portions of anvil clouds far away from the raining core are thin and have narrow frequency distributions of reflectivity at all levels with overall weaker values. This difference likely reflects ice particle fallout and therefore cloud age. Reflectivity histograms of MCS anvil clouds vary little across the tropics, except that (i) in continental MCS anvils, broader distributions of reflectivity occur at the uppermost levels in the portions closest to active raining areas; (ii) the frequency of occurrence of stronger reflectivity in the upper part of anvils decreases faster with increasing distance in continental MCSs; and (iii) narrower-peaked ridges are prominent in reflectivity histograms of thick anvil clouds close to the raining areas of connected MCSs (superclusters). These global results are consistent with observations at ground sites and aircraft data. They present a comprehensive test dataset for models aiming to simulate process-based upper-level cloud structure around the tropics.

Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

NASA Technical Reports Server (NTRS)

Yuan, J.; Houze, R. A., Jr.; Heymsfield, A.

2011-01-01

A global study of the vertical structures of the clouds of tropical mesoscale convective systems (MCSs) has been carried out with data from the CloudSat Cloud Profiling Radar. Tropical MCSs are found to be dominated by cloud-top heights greater than 10 km. Secondary cloud layers sometimes occur in MCSs, but outside their primary raining cores. The secondary layers have tops at 6--8 and 1--3 km. High-topped clouds extend outward from raining cores of MCSs to form anvil clouds. Closest to the raining cores, the anvils tend to have broader distributions of reflectivity at all levels, with the modal values at higher reflectivity in their lower levels. Portions of anvil clouds far away from the raining core are thin and have narrow frequency distributions of reflectivity at all levels with overall weaker values. This difference likely reflects ice particle fallout and therefore cloud age. Reflectivity histograms of MCS anvil clouds vary little across the tropics, except that (i) in continental MCS anvils, broader distributions of reflectivity occur at the uppermost levels in the portions closest to active raining areas; (ii) the frequency of occurrence of stronger reflectivity in the upper part of anvils decreases faster with increasing distance in continental MCSs; and (iii) narrower-peaked ridges are prominent in reflectivity histograms of thick anvil clouds close to the raining areas of connected MCSs (superclusters). These global results are consistent with observations at ground sites and aircraft data. They present a comprehensive test dataset for models aiming to simulate process-based upper-level cloud structure around the tropics.

Temporal variation of the cloud top height over the tropical Pacific observed by geostationary satellites

NASA Astrophysics Data System (ADS)

Nishi, N.; Hamada, A.

2012-12-01

Stratiform clouds (nimbostratus and cirriform clouds) in the upper troposphere accompanied with cumulonimbus activity cover large part of the tropical region and largely affect the radiation and water vapor budgets there. Recently new satellites (CloudSat and CALIPSO) can give us the information of cloud height and cloud ice amount even over the open ocean. However, their coverage is limited just below the satellite paths; it is difficult to capture the whole shape and to trace the lifecycle of each cloud system by using just these datasets. We made, as a complementary product, a dataset of cloud top height and visible optical thickness with one-hour resolution over the wide region, by using infrared split-window data of the geostationary satellites (AGU fall meeting 2011) and released on the internet (http://database.rish.kyoto-u.ac.jp/arch/ctop/). We made lookup tables for estimating cloud top height only with geostationary infrared observations by comparing them with the direct cloud observation by CloudSat (Hamada and Nishi, 2010, JAMC). We picked out the same-time observations by MTSAT and CloudSat and regressed the cloud top height observation of CloudSat back onto 11μm brightness temperature (Tb) and the difference between the 11μm Tb and 12μm Tb. We will call our estimated cloud top height as "CTOP" below. The area of our coverage is 85E-155W (MTSAT2) and 80E-160W(MTSAT1R), and 20S-20N. The accuracy of the estimation with the IR split-window observation is the best in the upper tropospheric height range. We analyzed the formation and maintenance of the cloud systems whose top height is in the upper troposphere with our CTOP analysis, CloudSat 2B-GEOPROF, and GSMaP (Global Satellite Mapping of Precipitation) precipitation data. Most of the upper tropospheric stratiform clouds have their cloud top within 13-15 km range. The cloud top height decreases slowly when dissipating but still has high value to the end. However, we sometimes observe that a little lower cloud top height (6-10 km) is kept within one-two days. A typical example is observed on 5 January 2011 in a dissipating cloud system with 1000-km scale. This cluster located between 0-10N just west of the International Date Line and moved westward with keeping relatively lower cloud top (6-10 km) over one day. This top height is lower than the ubiquitous upper-tropospheric stratiform clouds but higher than the so-called 'congestus cloud' whose top height is around 0C. CloudSat data show the presence of convective rainfall. It suggests that this cloud system continuously kept making new anvil clouds in a little lower height than usual. We examined the seasonal variation of the distribution of cloud systems with a little lower cloud top height (6-11 km) during 2010-11. The number of such cloud systems is not constant with seasons but frequently increased in some specific seasons. Over the equatorial ocean region (east of 150E), they were frequently observed during the northern winter.

Using CloudSat and the A-Train to Estimate Tropical Cyclone Intensity in the Western North Pacific

DTIC Science & Technology

2014-09-01

CloudSat System Data Flow (from Cooperative Institute for Research in the Atmosphere 2008...radar Department of Defense Data Processing Center European Centre for Medium-Range Weather Forecasts Earth observing system Earth observing... system data and information system Earth sciences systems pathfinder hierarchical data format moderate resolution imaging spectroradiometer moist

An assessment of the cloud signals simulated by NICAM using ISCCP, CALIPSO, and CloudSat satellite simulators

NASA Astrophysics Data System (ADS)

Kodama, C.; Noda, A. T.; Satoh, M.

2012-06-01

This study presents an assessment of three-dimensional structures of hydrometeors simulated by the NICAM, global nonhydrostatic atmospheric model without cumulus parameterization, using multiple satellite data sets. A satellite simulator package (COSP: the CFMIP Observation Simulator Package) is employed to consistently compare model output with ISCCP, CALIPSO, and CloudSat satellite observations. Special focus is placed on high thin clouds, which are not observable in the conventional ISCCP data set, but can be detected by the CALIPSO observations. For the control run, the NICAM simulation qualitatively captures the geographical distributions of the high, middle, and low clouds, even though the horizontal mesh spacing is as coarse as 14 km. The simulated low cloud is very close to that of the CALIPSO low cloud. Both the CloudSat observations and NICAM simulation show a boomerang-type pattern in the radar reflectivity-height histogram, suggesting that NICAM realistically simulates the deep cloud development process. A striking difference was found in the comparisons of high thin cirrus, showing overestimated cloud and higher cloud top in the model simulation. Several model sensitivity experiments are conducted with different cloud microphysical parameters to reduce the model-observation discrepancies in high thin cirrus. In addition, relationships among clouds, Hadley circulation, outgoing longwave radiation and precipitation are discussed through the sensitivity experiments.

KSC-05PD-1400

NASA Technical Reports Server (NTRS)

2005-01-01

KENNEDY SPACE CENTER, FLA. Inside the Astrotech Payload Processing Facility on Vandenberg Air Force Base in California, workers hold the Wide Field Camera that they will install on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft at right. CALIPSO will fly in combination with the CloudSat satellite to provide never-before-seen 3-D perspectives of how clouds and aerosols form, evolve, and affect weather and climate. CALIPSO and CloudSat will join three other satellites in orbit to enhance understanding of climate systems. The launch date for CALIPSO/CloudSat is no earlier than Aug. 22.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

NASA Technical Reports Server (NTRS)

Tselioudis, George; Rossow, William; Zhang, Yuanchong; Konsta, Dimitra

2013-01-01

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

Influence of multiple scattering on CloudSat measurements in snow: A model study

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Battaglia, Alessandro

2009-06-01

The effects of multiple scattering on larger precipitating hydrometers have an influence on measurements of the spaceborne W-band (94 GHz) CloudSat radar. This study presents initial quantitative estimates of these effects in “dry” snow using radiative transfer calculations for appropriate snowfall models. It is shown that these effects become significant (i.e., greater than approximately 1 dB) when snowfall radar reflectivity factors are greater than about 10-15 dBZ. Reflectivity enhancement due to multiple scattering can reach 4-5 dB in heavier stratiform snowfalls. Multiple scattering effects counteract signal attenuation, so the observed CloudSat reflectivity factors in snowfall could be relatively close to the values that would be observed in the case of single scattering and the absence of attenuation.

Partitioning CloudSat Ice Water Content for Comparison with Upper-Tropospheric Ice in Global Atmospheric Models

NASA Astrophysics Data System (ADS)

Chen, W. A.; Woods, C. P.; Li, J. F.; Waliser, D. E.; Chern, J.; Tao, W.; Jiang, J. H.; Tompkins, A. M.

2010-12-01

CloudSat provides important estimates of vertically resolved ice water content (IWC) on a global scale based on radar reflectivity. These estimates of IWC have proven beneficial in evaluating the representations of ice clouds in global models. An issue when performing model-data comparisons of IWC particularly germane to this investigation, is the question of which component(s) of the frozen water mass are represented by retrieval estimates and how they relate to what is represented in models. The present study developed and applied a new technique to partition CloudSat total IWC into small and large ice hydrometeors, based on the CloudSat-retrieved ice particle size distribution (PSD) parameters. The new method allows one to make relevant model-data comparisons and provides new insights into the model’s representation of atmospheric IWC. The partitioned CloudSat IWC suggests that the small ice particles contribute to 20-30% of the total IWC in the upper troposphere when a threshold size of 100 μm is used. Sensitivity measures with respect to the threshold size, the PSD parameters, and the retrieval algorithms are presented. The new dataset is compared to model estimates, pointing to areas for model improvement. Cloud ice analyses from the European Centre for Medium-Range Weather Forecasts model agree well with the small IWC from CloudSat. The finite-volume multi-scale modeling framework model underestimates total IWC at 147 and 215 hPa, while overestimating the fractional contribution from the small ice species. These results are discussed in terms of their applications to, and implications for, the evaluation of global atmospheric models, providing constraints on the representations of cloud feedback and precipitation in global models, which in turn can help reduce uncertainties associated with climate change projections. Figure 1. A sample lognormal ice number distribution (red curve), and the corresponding mass distribution (black curve). The dotted line represents the cutoff size for IWC partitioning (Dc = 100 µm as an example). The partial integrals of the mass distribution for particles smaller and larger than Dc correspond to IWC<100 (green area) and IWC>100 (blue area), respectively.

Quantifying the microphysical impacts of fire aerosols on clouds in Indonesia using remote sensing observations

NASA Astrophysics Data System (ADS)

Tosca, M. G.; Diner, D. J.; Garay, M. J.; Kalashnikova, O. V.

2012-12-01

Fire-emitted aerosols modify cloud and precipitation dynamics by acting as cloud condensation nuclei in what is known as the first and second aerosol indirect effect. The cloud response to the indirect effect varies regionally and is not well understood in the highly convective tropics. We analyzed nine years (2003-2011) of aerosol data from the Multi-angle Imaging SpectroRadiometer (MISR), and fire emissions data from the Global Fire Emissions Database, version 3 (GFED3) over southeastern tropical Asia (Indonesia), and identified scenes that contained both a high atmospheric aerosol burden and large surface fire emissions. We then collected scenes from the Cloud Profiling Radar (CPR) on board the CLOUDSAT satellite that corresponded both spatially and temporally to the high-burning scenes from MISR, and identified differences in convective cloud dynamics over areas with varying aerosol optical depths. Differences in overpass times (MISR in the morning, CLOUDSAT in the afternoon) improved our ability to infer that changes in cloud dynamics were a response to increased or decreased aerosol emissions. Our results extended conclusions from initial studies over the Amazon that used remote sensing techniques to identify cloud fraction reductions in high burning areas (Koren et al., 2004; Rosenfeld, 1999) References Koren, I., Y.J. Kaufman, L.A. Remer and J.V. Martins (2004), Measurement of the effect of Amazon smoke on inhibition of cloud formation, Science, 303, 1342-1345 Rosenfeld, D. (1999), TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall, Gephys. Res. Lett., 26, 3105.

A-Train Satellite Observations of Recent Explosive Eruptions in Iceland and Chile

NASA Astrophysics Data System (ADS)

Carn, S. A.; Yang, K.; Prata, A. J.

2012-04-01

The past few years have seen remarkable levels of explosive volcanic activity in Iceland and Chile, with four significant eruptions at Chaitén (May 2008), Eyjafjallajökull (April 2010), Grimsvötn (May 2011) and Cordón Caulle (June 2011 - ongoing). The tremendous disruption and economic impact of the Eyjafjallajökull eruption is well known, but each of these events had a significant impact on aviation, sometimes at great distances from the volcano. As of late 2011, volcanic ash from Cordón Caulle was still affecting airports in southern South America, highlighting the potential for extended disruption during long-lived eruptions. Serendipitously, this period of elevated volcanic activity has coincided with an era of unprecedented availability of satellite remote sensing data pertinent to volcanic cloud studies. In particular, NASA's A-Train satellite constellation (including the Aqua, CloudSat, CALIPSO, and Aura satellites) has been flying in formation since 2006, providing synergistic, multi- and hyper-spectral, passive and active observations. Measurements made by A-Train sensors include total column sulfur dioxide (SO2) by the Ozone Monitoring Instrument (OMI) on Aura, upper tropospheric and stratospheric (UTLS) SO2 column by the Atmospheric Infrared Sounder (AIRS) on Aqua and Microwave Limb Sounder (MLS) on Aura, ash mass loading from AIRS and the Moderate resolution Imaging Spectroradiometer (MODIS) on Aqua, UTLS HCl columns and ice water content (IWC) from MLS, aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard CALIPSO, and hydrometeor profiles from the Cloud Profiling Radar (CPR) on CloudSat. The active vertical profiling capability of CALIPSO, CloudSat and MLS sychronized with synoptic passive sensing of trace gases and aerosols by OMI, AIRS and MODIS provides a unique perspective on the structure and composition of volcanic clouds. A-Train observations during the first hours of atmospheric residence are particularly valuable, as the fallout, segregation and stratification of material in this period determines the concentration and altitude of constituents that remain to be advected downwind. This represents the eruption 'source term' essential for ash dispersion modeling, and hence for aviation hazard mitigation. In this presentation we show how A-Train data have improved our understanding of the composition, structure and dynamics of volcanic eruption clouds, using examples from the recent Icelandic and Chilean eruptions. These events span a range of compositions and eruptive styles, including highly silicic, SO2-poor eruptions (Chaitén and Cordón Caulle), magma-ice interaction (Eyjafjallajökull and Grimsvötn), stratospheric eruption columns (Chaitén, Grimsvötn), and persistent, weak tropospheric plumes (Eyjafjallajökull). In each case, satellite remote sensing played a crucial role in characterizing the eruption, monitoring variations in intensity and tracking the dispersion of volcanic cloud constituents. We also describe plans for advanced SO2 and ash retrieval algorithms that will exploit the synergy between UV and IR sensors in the A-Train for improved quantification of ash and SO2 loading by volcanic eruptions.

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

NASA Astrophysics Data System (ADS)

Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

2016-05-01

Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

Adventures in Private Cloud: Balancing Cost and Capability at the CloudSat Data Processing Center

NASA Astrophysics Data System (ADS)

Partain, P.; Finley, S.; Fluke, J.; Haynes, J. M.; Cronk, H. Q.; Miller, S. D.

2016-12-01

Since the beginning of the CloudSat Mission in 2006, The CloudSat Data Processing Center (DPC) at the Cooperative Institute for Research in the Atmosphere (CIRA) has been ingesting data from the satellite and other A-Train sensors, producing data products, and distributing them to researchers around the world. The computing infrastructure was specifically designed to fulfill the requirements as specified at the beginning of what nominally was a two-year mission. The environment consisted of servers dedicated to specific processing tasks in a rigid workflow to generate the required products. To the benefit of science and with credit to the mission engineers, CloudSat has lasted well beyond its planned lifetime and is still collecting data ten years later. Over that period requirements of the data processing system have greatly expanded and opportunities for providing value-added services have presented themselves. But while demands on the system have increased, the initial design allowed for very little expansion in terms of scalability and flexibility. The design did change to include virtual machine processing nodes and distributed workflows but infrastructure management was still a time consuming task when system modification was required to run new tests or implement new processes. To address the scalability, flexibility, and manageability of the system Cloud computing methods and technologies are now being employed. The use of a public cloud like Amazon Elastic Compute Cloud or Google Compute Engine was considered but, among other issues, data transfer and storage cost becomes a problem especially when demand fluctuates as a result of reprocessing and the introduction of new products and services. Instead, the existing system was converted to an on premises private Cloud using the OpenStack computing platform and Ceph software defined storage to reap the benefits of the Cloud computing paradigm. This work details the decisions that were made, the benefits that have been realized, the difficulties that were encountered and issues that still exist.

CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

NASA Technical Reports Server (NTRS)

Gong, J.; Wu, D. L.

2014-01-01

Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

Improving the Representation of Snow Crystal Properties within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.

2010-01-01

The assumptions of a single-moment microphysics scheme (NASA Goddard) were evaluated using a variety of surface, aircraft and radar data sets. Fixed distribution intercepts and snow bulk densities fail to represent the vertical variability and diversity of crystal populations for this event. Temperature-based equations have merit, but they can be adversely affected by complex temperature profiles that are inverted or isothermal. Column-based approaches can mitigate complex profiles of temperature but are restricted by the ability of the model to represent cloud depth. Spheres are insufficient for use in CloudSat reflectivity comparisons due to Mie resonance, but reasonable for Rayleigh scattering applications. Microphysics schemes will benefit from a greater range of snow crystal characteristics to accommodate naturally occurring diversity.

What does Reflection from Cloud Sides tell us about Vertical Distribution of Cloud Droplet Sizes?

NASA Technical Reports Server (NTRS)

Marshak, A.; Martins, J. V.; Zubko, V.; Kaufman, Y. J.

2006-01-01

Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from CloudSat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3-D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimentional(3-D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 microns) and one with liquid water efficient absorption of solar radiation (2.1 microns). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3-D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

What Does Reflection from Cloud Sides Tell Us About Vertical Distribution of Cloud Droplet Sizes?

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Martins, J. Vanderlei; Zubko, Victor; Kaufman, Yoram, J.

2005-01-01

Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from Cloudsat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimensional (3D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 micrometers) and one with liquid water efficient absorption of solar radiation (2.1 micrometers). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

Covariability in the Monthly Mean Convective and Radiative Diurnal Cycles in the Amazon

NASA Technical Reports Server (NTRS)

Dodson, Jason B.; Taylor, Patrick C.

2015-01-01

The diurnal cycle of convective clouds greatly influences the radiative energy balance in convectively active regions of Earth, through both direct presence, and the production of anvil and stratiform clouds. Previous studies show that the frequency and properties of convective clouds can vary on monthly timescales as a result of variability in the monthly mean atmospheric state. Furthermore, the radiative budget in convectively active regions also varies by up to 7 Wm-2 in convectively active regions. These facts suggest that convective clouds connect atmospheric state variability and radiation variability beyond clear sky effects alone. Previous research has identified monthly covariability between the diurnal cycle of CERES-observed top-of-atmosphere radiative fluxes and multiple atmospheric state variables from reanalysis over the Amazon region. ASVs that enhance (reduce) deep convection, such as CAPE (LTS), tend to shift the daily OLR and cloud albedo maxima earlier (later) in the day by 2-3 hr. We first test the analysis method using multiple reanalysis products for both the dry and wet seasons to further investigate the robustness of the preliminary results. We then use CloudSat data as an independent cloud observing system to further evaluate the relationships of cloud properties to variability in radiation and atmospheric states. While CERES can decompose OLR variability into clear sky and cloud effects, it cannot determine what variability in cloud properties lead to variability in the radiative cloud effects. Cloud frequency, cloud top height, and cloud microphysics all contribute to the cloud radiative effect, all of which are observable by CloudSat. In addition, CloudSat can also observe the presence and variability of deep convective cores responsible for the production of anvil clouds. We use these capabilities to determine the covariability of convective cloud properties and the radiative diurnal cycle.

Summertime Coincident Observations of Ice Water Path in the Visible/Near-IR, Radar, and Microwave Frequencies

NASA Technical Reports Server (NTRS)

Pittman, Jasna V.; Robertson, Franklin R.; Atkinson, Robert J.

2008-01-01

Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

2010-01-01

CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

Evaluation of NCAR CAM5 Simulated Marine Boundary Layer Cloud Properties Using a Combination of Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Song, H.; Wang, M.; Ghan, S. J.; Dong, X.

2016-12-01

he main objective of this study is to systematically evaluate the MBL cloud properties simulated in CAM5 family models using a combination of satellite-based CloudSat/MODIS observations and ground-based observations from the ARM Azores site, with a special focus on MBL cloud microphysics and warm rain process. First, we will present a global evaluation based on satellite observations and retrievals. We will compare global cloud properties (e.g., cloud fraction, cloud vertical structure, cloud CER, COT, and LWP, as well as drizzle frequency and intensity diagnosed using the CAM5-COSP instrumental simulators) simulated in the CAM5 models with the collocated CloudSat and MODIS observations. We will also present some preliminary results from a regional evaluation based mainly on ground observations from ARM Azores site. We will compare MBL cloud properties simulated in CAM5 models over the ARM Azores site with collocated satellite (MODIS and CloudSat) and ground-based observations from the ARM site.

What does reflection from cloud sides tell us about vertical distribution of cloud droplets?

NASA Technical Reports Server (NTRS)

Marshak, A.; Kaufman, Yoram; Martins, V.; Zubko, Victor

2006-01-01

In order to accurately measure the interaction of clouds with aerosols, we have to resolve the vertical distribution of cloud droplet sizes and determine the temperature of glaciation for clean and polluted clouds. Knowledge of the droplet vertical profile is also essential for understanding precipitation. So far, all existing satellites either measure cloud microphysics only at cloud top (e.g., MODIS) or give a vertical profile of precipitation sized droplets (e.g., Cloudsat). What if one measures cloud microphysical properties in the vertical by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides? This was the idea behind CLAIM-3D (A 3D - cloud aerosol interaction mission) recently proposed by NASA GSFC. This presentation will focus on the interpretation of the radiation reflected from cloud sides. In contrast to plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer will be used for interpreting the observed reflectances. As a proof of concept, we will show a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with prescribed microphysics. Instead of fixed values of the retrieved effective radii, the probability density functions of droplet size distributions will serve as possible retrievals.

Observations of aerosol-induced convective invigoration in the tropical east Atlantic

NASA Astrophysics Data System (ADS)

Storer, R. L.; van den Heever, S. C.; L'Ecuyer, T. S.

2014-04-01

Four years of CloudSat data have been analyzed over a region of the east Atlantic Ocean in order to examine the influence of aerosols on deep convection. The satellite data were combined with information about aerosols taken from the Global and Regional Earth-System Monitoring Using Satellite and In Situ Data model. Only those profiles fitting the definition of deep convective clouds were analyzed. Overall, the cloud center of gravity, cloud top, and rain top were all found to increase with increased aerosol loading. These effects were largely independent of the environment, and the differences between the cleanest and most polluted clouds sampled were found to be statistically significant. When examining an even smaller subset of deep convective clouds likely to be part of the convective core, similar trends were seen. These observations suggest that convective invigoration occurs with increased aerosol loading, leading to deeper, stronger storms in polluted environments.

Initial Results from CALIPSO

NASA Technical Reports Server (NTRS)

Winker, David M.; Pelon, Jacques; McCormick, M. Patrick

2006-01-01

CALIPSO will carry the first polarization lidar in orbit, along with infrared and visible passive imagers, and will fly in formation as part of the Afternoon Constellation (A-train). The acquisition of observations which are simultaneous and coincident with observations from other instruments of the A-train will allow numerous synergies to be realized from combining CALIPSO observations with observations from other platforms. In particular, cloud observations from the CALIPSO lidar and the CloudSat radar will complement each other, together encompassing the variety of clouds found in the atmosphere, from thin cirrus to deep convective clouds. CALIPSO has been developed within the framework of a collaboration between NASA and CNES and is currently scheduled to launch, along with the CloudSat satellite, in spring 2006. This paper will present an overview of the CALIPSO mission, including initial results.

Quantifying Uncertainties in Mass-Dimensional Relationships Through a Comparison Between CloudSat and SPartICus Reflectivity Factors

NASA Astrophysics Data System (ADS)

Mascio, J.; Mace, G. G.

2015-12-01

CloudSat and CALIPSO, two of the satellites in the A-Train constellation, use algorithms to calculate the scattering properties of small cloud particles, such as the T-matrix method. Ice clouds (i.e. cirrus) cause problems with these cloud property retrieval algorithms because of their variability in ice mass as a function of particle size. Assumptions regarding the microphysical properties, such as mass-dimensional (m-D) relationships, are often necessary in retrieval algorithms for simplification, but these assumptions create uncertainties of their own. Therefore, ice cloud property retrieval uncertainties can be substantial and are often not well known. To investigate these uncertainties, reflectivity factors measured by CloudSat are compared to those calculated from particle size distributions (PSDs) to which different m-D relationships are applied. These PSDs are from data collected in situ during three flights of the Small Particles in Cirrus (SPartICus) campaign. We find that no specific habit emerges as preferred and instead we conclude that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum and, therefore, cannot be categorized easily. To quantify the uncertainties in the mass-dimensional relationships, an optimal estimation inversion was run to retrieve the m-D relationship per SPartICus flight, as well as to calculate uncertainties of the m-D power law.

A Neural Network Approach to Infer Optical Depth of Thick Ice Clouds at Night

NASA Technical Reports Server (NTRS)

Minnis, P.; Hong, G.; Sun-Mack, S.; Chen, Yan; Smith, W. L., Jr.

2016-01-01

One of the roadblocks to continuously monitoring cloud properties is the tendency of clouds to become optically black at cloud optical depths (COD) of 6 or less. This constraint dramatically reduces the quantitative information content at night. A recent study found that because of their diffuse nature, ice clouds remain optically gray, to some extent, up to COD of 100 at certain wavelengths. Taking advantage of this weak dependency and the availability of COD retrievals from CloudSat, an artificial neural network algorithm was developed to estimate COD values up to 70 from common satellite imager infrared channels. The method was trained using matched 2007 CloudSat and Aqua MODIS data and is tested using similar data from 2008. The results show a significant improvement over the use of default values at night with high correlation. This paper summarizes the results and suggests paths for future improvement.

CloudSat Overflight of Hurricane Bud

NASA Image and Video Library

2006-07-13

The image at the top of figure 1 is from a geostationary imager. The colors relate to the temperature of the clouds. The higher the clouds, the lower the temperature. The highest, coldest clouds are located near the center of the hurricane.

CALIPSO Overview and Early Results

NASA Astrophysics Data System (ADS)

McCormick, M. P.

2008-05-01

The CALIPSO spacecraft was co-manifested with the CloudSat spacecraft and launched by a Boeing Delta~II rocket from Vandenberg Air Force Base, California on April~28,~2006. CALIPSO is the acronym for Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations. CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) is a three-channel lidar on board that uses a Nd:YAG laser emitting pulses at 1064 and 532~nm. The receiver uses a 1-meter diameter telescope and photomultipliers in the two 532~nm channels; one for parallel-polarized backscatter, and the other for perpendicular-polarized backscatter. The 1064~nm channel uses an APD for measuring the total backscatter at this wavelength. CALIPSO is in a near-circular sunsynchronous polar 705-km orbit with a 1:30~PM ascending node, and is flying in formation with CloudSat, Aura, Aqua and PARASOL. CALIPSO and CloudSat are flying 15~seconds apart in the formation. This talk will present an overview of the CALIPSO mission and details of CALIOP and the rest of the payload. It will show typical results from measurements of clouds, details on cirrus cloud statistics for the first year of data, a characterization of Polar Stratospheric Clouds over the Artic and Antarctic during local winters and early springs, and some general atmospheric events like hurricanes and aerosols from minor volcanic eruptions, desert dust events, and smoke from fires and their transport. The presentation will end with a look toward the future of spaceborne lidars.

Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

NASA Astrophysics Data System (ADS)

Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan; Rutan, David A.; Stephens, Graeme L.; Loeb, Norman G.; Minnis, Patrick; Wielicki, Bruce A.; Winker, David M.; Charlock, Thomas P.; Stackhouse, Paul W., Jr.; Xu, Kuan-Man; Collins, William D.

2011-10-01

One year of instantaneous top-of-atmosphere (TOA) and surface shortwave and longwave irradiances are computed using cloud and aerosol properties derived from instruments on the A-Train Constellation: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the CloudSat Cloud Profiling Radar (CPR), and the Aqua Moderate Resolution Imaging Spectrometer (MODIS). When modeled irradiances are compared with those computed with cloud properties derived from MODIS radiances by a Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm, the global and annual mean of modeled instantaneous TOA irradiances decreases by 12.5 W m-2 (5.0%) for reflected shortwave and 2.5 W m-2 (1.1%) for longwave irradiances. As a result, the global annual mean of instantaneous TOA irradiances agrees better with CERES-derived irradiances to within 0.5W m-2 (out of 237.8 W m-2) for reflected shortwave and 2.6W m-2 (out of 240.1 W m-2) for longwave irradiances. In addition, the global annual mean of instantaneous surface downward longwave irradiances increases by 3.6 W m-2 (1.0%) when CALIOP- and CPR-derived cloud properties are used. The global annual mean of instantaneous surface downward shortwave irradiances also increases by 8.6 W m-2 (1.6%), indicating that the net surface irradiance increases when CALIOP- and CPR-derived cloud properties are used. Increasing the surface downward longwave irradiance is caused by larger cloud fractions (the global annual mean by 0.11, 0.04 excluding clouds with optical thickness less than 0.3) and lower cloud base heights (the global annual mean by 1.6 km). The increase of the surface downward longwave irradiance in the Arctic exceeds 10 W m-2 (˜4%) in winter because CALIOP and CPR detect more clouds in comparison with the cloud detection by the CERES cloud algorithm during polar night. The global annual mean surface downward longwave irradiance of 345.4 W m-2 is estimated by combining the modeled instantaneous surface longwave irradiance computed with CALIOP and CPR cloud profiles with the global annual mean longwave irradiance from the CERES product (AVG), which includes the diurnal variation of the irradiance. The estimated bias error is -1.5 W m-2 and the uncertainty is 6.9 W m-2. The uncertainty is predominately caused by the near-surface temperature and column water vapor amount uncertainties.

Reassessing the effect of cloud type on Earth's energy balance

NASA Astrophysics Data System (ADS)

Hang, A.; L'Ecuyer, T.

2017-12-01

Cloud feedbacks depend critically on the characteristics of the clouds that change, their location and their environment. As a result, accurately predicting the impact of clouds on future climate requires a better understanding of individual cloud types and their spatial and temporal variability. This work revisits the problem of documenting the effects of distinct cloud regimes on Earth's radiation budget distinguishing cloud types according to their signatures in spaceborne active observations. Using CloudSat's multi-sensor radiative fluxes product that leverages high-resolution vertical cloud information from CloudSat, CALIPSO, and MODIS observations to provide the most accurate estimates of vertically-resolved radiative fluxes available to date, we estimate the global annual mean net cloud radiative effect at the top of the atmosphere to be -17.1 W m-2 (-44.2 W m-2 in the shortwave and 27.1 W m-2 in the longwave), slightly weaker than previous estimates from passive sensor observations. Multi-layered cloud systems, that are often misclassified using passive techniques but are ubiquitous in both hemispheres, contribute about -6.2 W m-2 of the net cooling effect, particularly at ITCZ and higher latitudes. Another unique aspect of this work is the ability of CloudSat and CALIPSO to detect cloud boundary information providing an improved capability to accurately discern the impact of cloud-type variations on surface radiation balance, a critical factor in modulating the disposition of excess energy in the climate system. The global annual net cloud radiative effect at the surface is estimated to be -24.8 W m-2 (-51.1 W m-2 in the shortwave and 26.3 W m-2 in the longwave), dominated by shortwave heating in multi-layered and stratocumulus clouds. Corresponding estimates of the effects of clouds on atmospheric heating suggest that clouds redistribute heat from poles to equator enhancing the general circulation.

ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yuying; Xie, Shaocheng

It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model outputmore » and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP wherever possible. The ARM simulator is written in Fortran 90, just as is the COSP. It is incorporated into COSP to facilitate use by the climate modeling community. In order to evaluate simulator output, the observational counterpart of the simulator output, radar reflectivity-height histograms (CFAD) is also generated from the ARM observations. This report includes an overview of the ARM cloud radar simulator VAP and the required simulator-oriented ARM radar data product (radarCFAD) for validating simulator output, as well as a user guide for operating the ARM radar simulator VAP.« less

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Correlations of oriented ice and precipitation in marine midlatitude low clouds using collocated CloudSat, CALIOP, and MODIS observations

NASA Astrophysics Data System (ADS)

Ross, Alexa; Holz, Robert E.; Ackerman, Steven A.

2017-08-01

In April 2006, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) launched aboard the CALIPSO satellite and into the A-Train constellation of satellites with its transmitter pointed near nadir. This proved problematic due to specular reflection from horizontally oriented ice crystals occurring more frequently than expected. Because the specular backscatter from oriented ice crystals has large attenuated backscatter and almost no depolarization, the standard lidar inversions cannot be applied. To mitigate this issue, the CALIOP transmitter was moved to 3° off nadir in November 2007. Though problematic for global CALIOP retrievals, the sensitivity to oriented ice during the first year of observations provides a unique data set to investigate scenes of this ice crystal signature. This study focuses on the CALIOP-oriented signature that occurs in midlatitude ocean regions whose cloud tops are relatively warm and low, existing below 6 km. A significant seasonal dependence is found in the Northern Hemisphere with up to 19% of clouds below 6 km yielding specular reflection by CALIOP during the colder months. In contrast, the Southern Hemisphere lacks such seasonal dependence and sees fewer oriented ice crystals. Using collocated CloudSat observations with both CALIOP and Moderate Resolution Imaging Spectroradiometer (MODIS), we investigate the correlations of the oriented signature with MODIS cloud properties. Comparing with CloudSat precipitation retrievals, we find that the oriented signature is strongly correlated with surface precipitation with 64% of CALIOP-oriented ice crystal cases precipitating compared to 40% for nonoriented cases.

Engaging observers to look at clouds from both sides: connecting NASA mission science with authentic STEM experiences

NASA Astrophysics Data System (ADS)

Chambers, L. H.; Taylor, J.; Ellis, T. D.; McCrea, S.; Rogerson, T. M.; Falcon, P.

2016-12-01

In 1997, NASA's Clouds and the Earth's Radiant Energy System (CERES) team began engaging K-12 schools as ground truth observers of clouds. CERES seeks to understand cloud effects on Earth's energy budget; thus accurate detection and characterization of clouds is key. While satellite remote sensing provides global information about clouds, it is limited in time and resolution. Ground observers, on the other hand, can observe clouds at any time of day (and sometimes night), and can see small and thin clouds that are challenging to detect from space. In 2006, two active sensing satellites, CloudSat and CALIPSO, were launched into the A-Train, which already contained 2 CERES instruments on the Aqua spacecraft. The CloudSat team also engaged K-12 schools to observe clouds, through The GLOBE Program, with a specialized observation protocol customized for the narrow radar swath. While providing valuable data for satellite assessment, these activities also engage participants in accessible, authentic science that gets people outdoors, helps them develop observation skills, and is friendly to all ages. The effort has evolved substantially since 1997, adopting new technology to provide a more compelling experience to citizen observers. Those who report within 15 minutes of the passage of a wide range of satellites (Terra, Aqua, CloudSat, CALIPSO, NPP, as well as a number of geostationary satellites) are sent a satellite image centered on their location and are invited to extend the experience beyond simple observation to include analysis of the two different viewpoints. Over the years these projects have collected large amounts of cloud observations from every continent and ocean basin on Earth. A number of studies have been conducted comparing the ground observations to the satellite results. This presentation will provide an overview of those results and also describe plans for a coordinated, thematic cloud observation and data analysis activity going forward.

NASA CloudSat Spots Beginning of Pakistan Floods

NASA Image and Video Library

2010-08-19

In late July 2010, flooding caused by heavy monsoon rains began in several regions of Pakistan. This image from NASA Aqua spacecraft reveals the bright white cloud tops from the cluster of thunderstorms.

KSC-06pd0755

NASA Image and Video Library

2006-04-28

VANDENBERG AIR FORCE BASE, CALIF. - CloudSat and CALIPSO ¯ Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations ¯ thunders skyward after launch at approximately 6:02 a.m. EDT atop a Boeing Delta II rocket. The two satellites will eventually circle approximately 438 miles above Earth in a sun-synchronous polar orbit, which means they will always cross the equator at the same local time. Their technologies will enable scientists to study how clouds and aerosols form, evolve and interact. CloudSat is managed by NASA's Jet Propulsion Laboratory, in Pasadena, Calif. JPL developed the radar instrument with hardware contributions from the Canadian Space Agency. CALIPSO is collaboration between NASA and France's Centre National d'Etudes Spatiales (CNES). Langley Research Center, in Hampton, Va., is leading the CALIPSO mission and providing overall project management, systems engineering, and payload mission operations. Photo credit: Boeing/Thom Baur

Detection of single and multilayer clouds in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan

2017-10-01

Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water cloud or thick cirrus contiguous with underlying layers of ice and water clouds is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total cloud visible optical depth, is trained to detect multilayer ice-over-water cloud systems as identified by matched April 2009 CloudSat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are identified and will be addressed in future versions of the MLANN.

Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

NASA Technical Reports Server (NTRS)

Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

2008-01-01

Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

An A-Train Climatology of Extratropical Cyclone Clouds

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike

2016-01-01

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

Reducing Errors in Satellite Simulated Views of Clouds with an Improved Parameterization of Unresolved Scales

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Marchand, R.; Ackerman, T. P.

2016-12-01

Satellite instrument simulators have emerged as a means to reduce errors in model evaluation by producing simulated or psuedo-retrievals from model fields, which account for limitations in the satellite retrieval process. Because of the mismatch in resolved scales between satellite retrievals and large-scale models, model cloud fields must first be downscaled to scales consistent with satellite retrievals. This downscaling is analogous to that required for model radiative transfer calculations. The assumption is often made in both model radiative transfer codes and satellite simulators that the unresolved clouds follow maximum-random overlap with horizontally homogeneous cloud condensate amounts. We examine errors in simulated MISR and CloudSat retrievals that arise due to these assumptions by applying the MISR and CloudSat simulators to cloud resolving model (CRM) output generated by the Super-parameterized Community Atmosphere Model (SP-CAM). Errors are quantified by comparing simulated retrievals performed directly on the CRM fields with those simulated by first averaging the CRM fields to approximately 2-degree resolution, applying a "subcolumn generator" to regenerate psuedo-resolved cloud and precipitation condensate fields, and then applying the MISR and CloudSat simulators on the regenerated condensate fields. We show that errors due to both assumptions of maximum-random overlap and homogeneous condensate are significant (relative to uncertainties in the observations and other simulator limitations). The treatment of precipitation is particularly problematic for CloudSat-simulated radar reflectivity. We introduce an improved subcolumn generator for use with the simulators, and show that these errors can be greatly reduced by replacing the maximum-random overlap assumption with the more realistic generalized overlap and incorporating a simple parameterization of subgrid-scale cloud and precipitation condensate heterogeneity. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. SAND2016-7485 A

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-located arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in lat/lon bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Hua, H.

2012-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within SciReduce a versatile set of python operators for data lookup, access, subsetting, co-registration, mining, fusion, and statistical analysis. All operators take in sets of geo-arrays and generate more arrays. Large, multi-year satellite and model datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of granules) can be compared or fused in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP or webification URLs, thereby minimizing the size of the stored input and intermediate datasets. A typical map function might assemble and quality control AIRS Level-2 water vapor profiles for a year of data in parallel, then a reduce function would average the profiles in bins (again, in parallel), and a final reduce would aggregate the climatology and write it to output files. We are using SciReduce to automate the production of multiple versions of a multi-year water vapor climatology (AIRS & MODIS), stratified by Cloudsat cloud classification, and compare it to models (ECMWF & MERRA reanalysis). We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing huge datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer.

Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Im, Eastwood; Tripoli, Gregory J.; Yang, Song

2008-01-01

First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.

Verification of NWP Cloud Properties using A-Train Satellite Observations

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Weeks, C.; Wolff, C.; Bullock, R.; Brown, B.

2011-12-01

Recently, the NCAR Model Evaluation Tools (MET) has been enhanced to incorporate satellite observations for the verification of Numerical Weather Prediction (NWP) cloud products. We have developed tools that match fields spatially (both in the vertical and horizontal dimensions) to compare NWP products with satellite observations. These matched fields provide diagnostic evaluation of cloud macro attributes such as vertical distribution of clouds, cloud top height, and the spatial and seasonal distribution of cloud fields. For this research study, we have focused on using CloudSat, CALIPSO, and MODIS observations to evaluate cloud fields for a variety of NWP fields and derived products. We have selected cases ranging from large, mid-latitude synoptic systems to well-organized tropical cyclones. For each case, we matched the observed cloud field with gridded model and/or derived product fields. CloudSat and CALIPSO observations and model fields were matched and compared in the vertical along the orbit track. MODIS data and model fields were matched and compared in the horizontal. We then use MET to compute the verification statistics to quantify the performance of the models in representing the cloud fields. In this presentation we will give a summary of our comparison and show verification results for both synoptic and tropical cyclone cases.

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

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

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky;

Convectively-driven cold layer and its influences on moisture in the UTLS

NASA Astrophysics Data System (ADS)

Kim, J.; Randel, W. J.; Birner, T.

2016-12-01

Characteristics of the cold anomaly in the tropical tropopause layer (TTL) that is commonly observed with deep convection are examined using CloudSat and Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) GPS radio occultation measurements. Deep convection is sampled based on the cloud top height (>17 km) from CloudSat 2B-CLDCLASS, and then temperature profiles from COSMIC are composited around the deep convection. The composite temperature shows anomalously warm troposphere (up to 14 km) and a significantly cold layer near the tropopause (at 16-18 km) in the regions of deep convection. Generally in the tropics, the cold layer has very large horizontal scale (2,000 - 6,000 km) compared to that of mesoscale convective cluster, and it lasts one or two weeks with minimum temperature anomaly of - 2K. The cold layer shows slight but clear eastward-tilted vertical structure in the deep tropics indicating a large-scale Kelvin wave response. Further analyses on circulation patterns suggest that the anomaly can be explained as a part of Gill-type response in the TTL to deep convective heating in the troposphere. Response of moisture to the cold layer is also examined in the upper troposphere and lower stratosphere using microwave limb sounder (MLS) measurements. The water vapor anomalies show coherent structures with the temperature and circulation anomalies. A clear dry anomaly is found in the cold layer and its outflow region, implying a large-scale dehydration process due to the convectively driven cold layer in the upper TTL.

Convectively Driven Tropopause-Level Cooling and Its Influences on Stratospheric Moisture

NASA Astrophysics Data System (ADS)

Kim, Joowan; Randel, William J.; Birner, Thomas

2018-01-01

Characteristics of the tropopause-level cooling associated with tropical deep convection are examined using CloudSat radar and Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) GPS radio occultation measurements. Extreme deep convection is sampled based on the cloud top height (>17 km) from CloudSat, and colocated temperature profiles from COSMIC are composited around the deep convection. Response of moisture to the tropopause-level cooling is also examined in the upper troposphere and lower stratosphere using microwave limb sounder measurements. The composite temperature shows an anomalous warming in the troposphere and a significant cooling near the tropopause (at 16-19 km) when deep convection occurs over the western Pacific, particularly during periods with active Madden-Julian Oscillation (MJO). The composite of the tropopause cooling has a large horizontal scale ( 6,000 km in longitude) with minimum temperature anomaly of -2 K, and it lasts more than 2 weeks with support of mesoscale convective clusters embedded within the envelope of the MJO. The water vapor anomalies show strong correlation with the temperature anomalies (i.e., dry anomaly in the cold anomaly), showing that the convectively driven tropopause cooling actively dehydrate the lower stratosphere in the western Pacific region. The moisture is also affected by anomalous Matsuno-Gill-type circulation associated with the cold anomaly, in which dry air spreads over a wide range in the tropical tropopause layer (TTL). These results suggest that convectively driven tropopause cooling and associated transient circulation play an important role in the large-scale dehydration process in the TTL.

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert A. Houze, Jr.

2013-11-13

We examined cloud radar data in monsoon climates, using cloud radars at Darwin in the Australian monsoon, on a ship in the Bay of Bengal in the South Asian monsoon, and at Niamey in the West African monsoon. We followed on with a more in-depth study of the continental MCSs over West Africa. We investigated whether the West African anvil clouds connected with squall line MCSs passing over the Niamey ARM site could be simulated in a numerical model by comparing the observed anvil clouds to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model at highmore » resolution using six different ice-phase microphysical schemes. We carried out further simulations with a cloud-resolving model forced by sounding network budgets over the Niamey region and over the northern Australian region. We have devoted some of the effort of this project to examining how well satellite data can determine the global breadth of the anvil cloud measurements obtained at the ARM ground sites. We next considered whether satellite data could be objectively analyzed to so that their large global measurement sets can be systematically related to the ARM measurements. Further differences were detailed between the land and ocean MCS anvil clouds by examining the interior structure of the anvils with the satellite-detected the CloudSat Cloud Profiling Radar (CPR). The satellite survey of anvil clouds in the Indo-Pacific region was continued to determine the role of MCSs in producing the cloud pattern associated with the MJO.« less

A-Train Observations of Deep Convective Storm Tops

NASA Technical Reports Server (NTRS)

Setvak, Martin; Bedka, Kristopher; Lindsey, Daniel T.; Sokol, Alois; Charvat, Zdenek; Stastka, Jindrich; Wang, Pao K.

2013-01-01

The paper highlights simultaneous observations of tops of deep convective clouds from several space-borne instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Aqua satellite, Cloud Profiling Radar (CPR) of the CloudSat satellite, and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flown on the CALIPSO satellite. These satellites share very close orbits, thus together with several other satellites they are referred to as the "A-Train" constellation. Though the primary responsibility of these satellites and their instrumentation is much broader than observations of fine-scale processes atop convective storms, in this study we document how data from the A-Train can contribute to a better understanding and interpretation of various storm-top features, such as overshooting tops, cold-U/V and cold ring features with their coupled embedded warm areas, above anvil ice plumes and jumping cirrus. The relationships between MODIS multi-spectral brightness temperature difference (BTD) fields and cloud top signatures observed by the CPR and CALIOP are also examined in detail to highlight the variability in BTD signals across convective storm events.

Cloud structure evolution of heavy rain events from the East-West Pacific Ocean: a combined global observation analysis

NASA Astrophysics Data System (ADS)

Sekaranom, A. B.; Nurjani, E.; Pujiastuti, I.

2018-04-01

Heavy rain events are often associated with flood hazards as one of the most devastating events across the globe. It is therefore essential to identify the evolution of heavy rainfall cloud structures, primarily from global satellite observation, as a tool to provide better disaster early warning systems. To identify the mechanism of heavy rainfall systems and its relationship with cloud development, especially over The Pacific Ocean, we aim to study the westward evolution of the convective systems over this area. Several datasets from Tropical Rainfall Measuring Mission (TRMM), CloudSat GEOPROF product, and ECMWF-reanalysis (ERA) interim were utilized to characterize the evolution. Geolocation and orbital time-lag analysis of the three different datasets for more than 8 years (2006-2014) could provide information related to the evolution of cloud structures associated with heavy rain events. In the first step, a heavy rainfall database was generated from TRMM. The CloudSat coordinate and time position were then matched with TRMM coordinate and time position. All of the processes were programatically conducted in fortran programming language. The result shows a transition between East and West Pacific ocean for TMI data.

Estimating effective particle size of tropical deep convective clouds with a look-up table method using satellite measurements of brightness temperature differences

NASA Astrophysics Data System (ADS)

Hong, Gang; Minnis, Patrick; Doelling, David; Ayers, J. Kirk; Sun-Mack, Szedung

2012-03-01

A method for estimating effective ice particle radius Re at the tops of tropical deep convective clouds (DCC) is developed on the basis of precomputed look-up tables (LUTs) of brightness temperature differences (BTDs) between the 3.7 and 11.0 μm bands. A combination of discrete ordinates radiative transfer and correlated k distribution programs, which account for the multiple scattering and monochromatic molecular absorption in the atmosphere, is utilized to compute the LUTs as functions of solar zenith angle, satellite zenith angle, relative azimuth angle, Re, cloud top temperature (CTT), and cloud visible optical thickness τ. The LUT-estimated DCC Re agrees well with the cloud retrievals of the Moderate Resolution Imaging Spectroradiometer (MODIS) for the NASA Clouds and Earth's Radiant Energy System with a correlation coefficient of 0.988 and differences of less than 10%. The LUTs are applied to 1 year of measurements taken from MODIS aboard Aqua in 2007 to estimate DCC Re and are compared to a similar quantity from CloudSat over the region bounded by 140°E, 180°E, 0°N, and 20°N in the Western Pacific Warm Pool. The estimated DCC Re values are mainly concentrated in the range of 25-45 μm and decrease with CTT. Matching the LUT-estimated Re with ice cloud Re retrieved by CloudSat, it is found that the ice cloud τ values from DCC top to the vertical location where LUT-estimated Re is located at the CloudSat-retrieved Re profile are mostly less than 2.5 with a mean value of about 1.3. Changes in the DCC τ can result in differences of less than 10% for Re estimated from LUTs. The LUTs of 0.65 μm bidirectional reflectance distribution function (BRDF) are built as functions of viewing geometry and column amount of ozone above upper troposphere. The 0.65 μm BRDF can eliminate some noncore portions of the DCCs detected using only 11 μm brightness temperature thresholds, which result in a mean difference of only 0.6 μm for DCC Re estimated from BTD LUTs.

New insights about cloud vertical structure from CloudSat and CALIPSO observations

NASA Astrophysics Data System (ADS)

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2017-09-01

Active cloud observations from A-Train's CloudSat and CALIPSO satellites offer new opportunities to examine the vertical structure of hydrometeor layers. We use the 2B-CLDCLASS-LIDAR merged CloudSat-CALIPSO product to examine global aspects of hydrometeor vertical stratification. We group the data into major cloud vertical structure (CVS) classes based on our interpretation of how clouds in three standard atmospheric layers overlap and provide their global frequency of occurrence. The two most frequent CVS classes are single-layer (per our definition) low and high clouds that represent 53% of cloudy skies, followed by high clouds overlying low clouds, and vertically extensive clouds that occupy near-contiguously a large portion of the troposphere. The prevalence of these configurations changes seasonally and geographically, between daytime and nighttime, and between continents and oceans. The radiative effects of the CVS classes reveal the major radiative warmers and coolers from the perspective of the planet as a whole, the surface, and the atmosphere. Single-layer low clouds dominate planetary and atmospheric cooling and thermal infrared surface warming. We also investigate the consistency between passive and active views of clouds by providing the CVS breakdowns of Moderate Resolution Imaging Spectroradiometer cloud regimes for spatiotemporally coincident MODIS-Aqua (also on the A-Train) and CloudSat-CALIPSO daytime observations. When the analysis is expanded for a more in-depth look at the most heterogeneous of the MODIS cloud regimes, it ultimately confirms previous interpretations of their makeup that did not have the benefit of collocated active observations.

Insights from a Regime Decomposition Approach on CERES and CloudSat-inferred Cloud Radiative Effects

NASA Astrophysics Data System (ADS)

Oreopoulos, L.; Cho, N.; Lee, D.

2015-12-01

Our knowledge of the Cloud Radiative Effect (CRE) not only at the Top-of-the-Atmosphere (TOA), but also (with the help of some modeling) at the surface (SFC) and within the atmospheric column (ATM) has been steadily growing in recent years. Not only do we have global values for these CREs, but we can now also plot global maps of their geographical distribution. The next step in our effort to advance our knowledge of CRE is to systematically assess the contributions of prevailing cloud systems to the global values. The presentation addresses this issue directly. We identify the world's prevailing cloud systems, which we call "Cloud Regimes" (CRs) via clustering analysis of MODIS (Aqua-Terra) daily joint histograms of Cloud Top Pressure and Cloud Optical Thickness (TAU) at 1 degree scales. We then composite CERES diurnal values of CRE (TOA, SFC, ATM) separately for each CR by averaging these values for each CR occurrence, and thus find the contribution of each CR to the global value of CRE. But we can do more. We can actually decompose vertical profiles of inferred instantaneous CRE from CloudSat/CALIPSO (2B-FLXHR-LIDAR product) by averaging over Aqua CR occurrences (since A-Train formation flying allows collocation). Such an analysis greatly enhances our understanding of the radiative importance of prevailing cloud mixtures at different atmospheric levels. We can, for example, in addition to examining whether the CERES findings on which CRs contribute to radiative cooling and warming of the atmospheric column are consistent with CloudSat, also gain insight on why and where exactly this happens from the shape of the full instantaneous CRE vertical profiles.

GSFC_20170504_2017-13985_015

NASA Image and Video Library

2017-05-04

Canadian Minister of Science, Honourable Kirsty Duncan and staff visited Goddard on May 4, 2017. They toured Hyperwall with talks on Terra, CloudSat, OSIRIS-REx and JWST then visited Robotic Operations Center.

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Evaluating cloudiness in an AGCM with Cloud Vertical Structure classes and their radiative effects

NASA Astrophysics Data System (ADS)

Lee, D.; Cho, N.; Oreopoulos, L.; Barahona, D.

2017-12-01

Clouds are recognized not only as the main modulator of Earth's Radiation Budget but also as the atmospheric constituent carrying the largest uncertainty in future climate projections. The presentation will showcase a new framework for evaluating clouds and their radiative effects in Atmospheric Global Climate Models (AGCMs) using Cloud Vertical Structure (CVS) classes. We take advantage of a new CVS reference dataset recently created from CloudSat's 2B-CLDCLASS-LIDAR product and which assigns observed cloud vertical configurations to nine simplified CVS classes based on cloud co-occurrence in three standard atmospheric layers. These CVS classes can also be emulated in GEOS-5 using the subcolumn cloud generator currently paired with the RRTMG radiation package as an implementation of the McICA scheme. Comparisons between the observed and modeled climatologies of the frequency of occurrence of the various CVS classes provide a new vantage point for assessing the realism of GEOS-5 clouds. Furthermore, a comparison between observed and modeled cloud radiative effects according to their CVS is also possible thanks to the availability of CloudSat's 2B-FLXHR-LIDAR product and our ability to composite radiative fluxes by CVS class - both in the observed and modeled realm. This latter effort enables an investigation of whether the contribution of the various CVS classes to the Earth's radiation budget is represented realistically in GEOS-5. Making this new pathway of cloud evaluation available to the community is a major step towards the improved representation of clouds in climate models.

Modeling Lidar Multiple Scattering

NASA Astrophysics Data System (ADS)

Sato, Kaori; Okamoto, Hajime; Ishimoto, Hiroshi

2016-06-01

A practical model to simulate multiply scattered lidar returns from inhomogeneous cloud layers are developed based on Backward Monte Carlo (BMC) simulations. The estimated time delay of the backscattered intensities returning from different vertical grids by the developed model agreed well with that directly obtained from BMC calculations. The method was applied to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data to improve the synergetic retrieval of cloud microphysics with CloudSat radar data at optically thick cloud grids. Preliminary results for retrieving mass fraction of co-existing cloud particles and drizzle size particles within lowlevel clouds are demonstrated.

GSFC_20170504_2017-13985_005

NASA Image and Video Library

2017-05-04

Canadian Minister of Science Honourable Kirsty Duncan and staff visited Goddard on May 4, 2017. They toured Hyperwall with talks on Terra, CloudSat, OSIRIS-Rex and JWST and had overview of Robotic Operations Center.

GSFC_20170504_2017-13985_029

NASA Image and Video Library

2017-05-04

Canadian Minister of Science Honourable Kirsty Duncan and staff visited Goddard on May 4, 2017. They toured Hyperwall with talks on Terra, CloudSat, OSIRIS-REx and JWST and had an overview of Robotic Operations Center.

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

NASA Technical Reports Server (NTRS)

Kempler, Steven; Stephens, Graeme; Winkler, Dave; Leptoukh, Greg; Reinke, Don; Smith, Peter

2006-01-01

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

NASA Astrophysics Data System (ADS)

Kempler, S.; Stephens, G.; Winker, D.; Leptoukh, G.; Reinke, D.; Smith, P.; Savtchenko, A.; Kummerer, R.; Mao, J.

2006-12-01

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the A-Train. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

NASA Astrophysics Data System (ADS)

Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

2017-12-01

Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

Differential absorption radar techniques: water vapor retrievals

NASA Astrophysics Data System (ADS)

Millán, Luis; Lebsock, Matthew; Livesey, Nathaniel; Tanelli, Simone

2016-06-01

Two radar pulses sent at different frequencies near the 183 GHz water vapor line can be used to determine total column water vapor and water vapor profiles (within clouds or precipitation) exploiting the differential absorption on and off the line. We assess these water vapor measurements by applying a radar instrument simulator to CloudSat pixels and then running end-to-end retrieval simulations. These end-to-end retrievals enable us to fully characterize not only the expected precision but also their potential biases, allowing us to select radar tones that maximize the water vapor signal minimizing potential errors due to spectral variations in the target extinction properties. A hypothetical CloudSat-like instrument with 500 m by ˜ 1 km vertical and horizontal resolution and a minimum detectable signal and radar precision of -30 and 0.16 dBZ, respectively, can estimate total column water vapor with an expected precision of around 0.03 cm, with potential biases smaller than 0.26 cm most of the time, even under rainy conditions. The expected precision for water vapor profiles was found to be around 89 % on average, with potential biases smaller than 77 % most of the time when the profile is being retrieved close to surface but smaller than 38 % above 3 km. By using either horizontal or vertical averaging, the precision will improve vastly, with the measurements still retaining a considerably high vertical and/or horizontal resolution.

A Sample of What We Have Learned from A-Train Cloud Measurements

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Vasilkov, Alexander; Ziemke, Jerry; Chandra, Sushil; Spurr, Robert; Bhartia, P. K.; Krotkov, Nick; Sneep, Maarten; Menzel, Paul; Platnick, Steve;

Assessment of the NPOESS/VIIRS Nighttime Infrared Cloud Optical Properties Algorithms

NASA Astrophysics Data System (ADS)

Wong, E.; Ou, S. C.

2008-12-01

In this paper we will describe two NPOESS VIIRS IR algorithms used to retrieve microphysical properties for water and ice clouds during nighttime conditions. Both algorithms employ four VIIRS IR channels: M12 (3.7 μm), M14 (8.55 μm), M15 (10.7 μm) and M16 (12 μm). The physical basis for the two algorithms is similar in that while the Cloud Top Temperature (CTT) is derived from M14 and M16 for ice clouds the Cloud Optical Thickness (COT) and Cloud Effective Particle Size (CEPS) are derived from M12 and M15. The two algorithms depart in the different radiative transfer parameterization equations used for ice and water clouds. Both the VIIRS nighttime IR algorithms and the CERES split-window method employ the 3.7 μm and 10.7 μm bands for cloud optical properties retrievals, apparently based on similar physical principles but with different implementations. It is reasonable to expect that the VIIRS and CERES IR algorithms produce comparable performance and similar limitations. To demonstrate the VIIRS nighttime IR algorithm performance, we will select a number of test cases using NASA MODIS L1b radiance products as proxy input data for VIIRS. The VIIRS retrieved COT and CEPS will then be compared to cloud products available from the MODIS, NASA CALIPSO, CloudSat and CERES sensors. For the MODIS product, the nighttime cloud emissivity will serve as an indirect comparison to VIIRS COT. For the CALIPSO and CloudSat products, the layered COT will be used for direct comparison. Finally, the CERES products will provide direct comparison with COT as well as CEPS. This study can only provide a qualitative assessment of the VIIRS IR algorithms due to the large uncertainties in these cloud products.

Evaluation of the Cloud Fields in the UK Met Office HadGEM3-UKCA Model Using the CCCM Satellite Data Product to Advance Our Understanding of the Influence of Clouds on Tropospheric Composition and Chemistry

NASA Technical Reports Server (NTRS)

Varma, Sunil; Voulgarakis, Apostolos; Liu, Hongyu; Crawford, James H.; White, James

2016-01-01

To determine the role of clouds in driving inter-annual and inter-seasonal variability of trace gases in the troposphere and lower stratosphere with a particular focus on the importance of cloud modification of photolysis. To evaluate the cloud fields and their vertical distribution in the HadGEM3 model utilizing CCCM, a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center.

Cloudsat tropical cyclone database

NASA Astrophysics Data System (ADS)

Tourville, Natalie D.

CloudSat (CS), the first 94 GHz spaceborne cloud profiling radar (CPR), launched in 2006 to study the vertical distribution of clouds. Not only are CS observations revealing inner vertical cloud details of water and ice globally but CS overpasses of tropical cyclones (TC's) are providing a new and exciting opportunity to study the vertical structure of these storm systems. CS TC observations are providing first time vertical views of TC's and demonstrate a unique way to observe TC structure remotely from space. Since December 2009, CS has intersected every globally named TC (within 1000 km of storm center) for a total of 5,278 unique overpasses of tropical systems (disturbance, tropical depression, tropical storm and hurricane/typhoon/cyclone (HTC)). In conjunction with the Naval Research Laboratory (NRL), each CS TC overpass is processed into a data file containing observational data from the afternoon constellation of satellites (A-TRAIN), Navy's Operational Global Atmospheric Prediction System Model (NOGAPS), European Center for Medium range Weather Forecasting (ECMWF) model and best track storm data. This study will describe the components and statistics of the CS TC database, present case studies of CS TC overpasses with complementary A-TRAIN observations and compare average reflectivity stratifications of TC's across different atmospheric regimes (wind shear, SST, latitude, maximum wind speed and basin). Average reflectivity stratifications reveal that characteristics in each basin vary from year to year and are dependent upon eye overpasses of HTC strength storms and ENSO phase. West Pacific (WPAC) basin storms are generally larger in size (horizontally and vertically) and have greater values of reflectivity at a predefined height than all other basins. Storm structure at higher latitudes expands horizontally. Higher vertical wind shear (≥ 9.5 m/s) reduces cloud top height (CTH) and the intensity of precipitation cores, especially in HTC strength storms. Average zero and ten dBZ height thresholds confirm WPAC storms loft precipitation sized particles higher into the atmosphere than in other basins. Two CS eye overpasses (32 hours apart) of a weakening Typhoon Nida in 2009 reveal the collapse of precipitation cores, warm core anomaly and upper tropospheric ice water content (IWC) under steady moderate shear conditions.

Tropical cloud and precipitation regimes as seen from near-simultaneous TRMM, CloudSat, and CALIPSO observations and comparison with ISCCP

NASA Astrophysics Data System (ADS)

Luo, Zhengzhao Johnny; Anderson, Ricardo C.; Rossow, William B.; Takahashi, Hanii

2017-06-01

Although Tropical Rainfall Measuring Mission (TRMM) and CloudSat/CALIPSO fly in different orbits, they frequently cross each other so that for the period between 2006 and 2010, a total of 15,986 intersect lines occurred within 20 min of each other from 30°S to 30°N, providing a rare opportunity to study tropical cloud and precipitation regimes and their internal vertical structure from near-simultaneous measurements by these active sensors. A k-means cluster analysis of TRMM and CloudSat matchups identifies three tropical cloud and precipitation regimes: the first two regimes correspond to, respectively, organized deep convection with heavy rain and cirrus anvils with moderate rain; the third regime is a convectively suppressed regime that can be further divided into three subregimes, which correspond to, respectively, stratocumulus clouds with drizzle, cirrus overlying low clouds, and nonprecipitating cumulus. Inclusion of CALIPSO data adds to the dynamic range of cloud properties and identifies one more cluster; subcluster analysis further identifies a thin, midlevel cloud regime associated with tropical mountain ranges. The radar-lidar cloud regimes are compared with the International Satellite Cloud Climatology Project (ISCCP) weather states (WSs) for the extended tropics. Focus is placed on the four convectively active WSs, namely, WS1-WS4. ISCCP WS1 and WS2 are found to be counterparts of Regime 1 and Regime 2 in radar-lidar observations, respectively. ISCCP WS3 and WS4, which are mainly isolated convection and broken, detached cirrus, do not have a strong association with any individual radar and lidar regimes, a likely effect of the different sampling strategies between ISCCP and active sensors and patchy cloudiness of these WSs.

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

NASA Technical Reports Server (NTRS)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Major Characteristics of Southern Ocean Cloud Regimes and Their Effects on the Energy Budget

NASA Technical Reports Server (NTRS)

Haynes, John M.; Jakob, Christian; Rossow, William B.; Tselioudis, George; Brown, Josephine

2011-01-01

Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79%of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

2010-01-01

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Optically thin ice clouds in Arctic : Formation processes

NASA Astrophysics Data System (ADS)

Jouan, C.; Girard, E.; Pelon, J.; Blanchet, J.; Wobrock, W.; Gultepe, I.; Gayet, J.; Delanoë, J.; Mioche, G.; Adam de Villiers, R.

2010-12-01

Arctic ice cloud formation during winter is poorly understood mainly due to lack of observations and the remoteness of this region. Their influence on Northern Hemisphere weather and climate is of paramount importance, and the modification of their properties, linked to aerosol-cloud interaction processes, needs to be better understood. Large concentration of aerosols in the Arctic during winter is associated to long-range transport of anthropogenic aerosols from the mid-latitudes to the Arctic. Observations show that sulphuric acid coats most of these aerosols. Laboratory and in-situ measurements show that at cold temperature (<-30°C), acidic coating lowers the freezing point and deactivates ice nuclei (IN). Therefore, the IN concentration is reduced in these regions and there is less competition for the same available moisture. As a result, large ice crystals form in relatively small concentrations. It is hypothesized that the observed low concentration of large ice crystals in thin ice clouds is linked to the acidification of aerosols. Extensive measurements from ground-based sites and satellite remote sensing (CloudSat and CALIPSO) reveal the existence of two types of extended optically thin ice clouds (TICs) in the Arctic during the polar night and early spring. The first type (TIC-1) is seen only by the lidar, but not the radar, and is found in pristine environment whereas the second type (TIC-2) is detected by both sensors, and is associated with high concentration of aerosols, possibly anthropogenic. TIC-2 is characterized by a low concentration of ice crystals that are large enough to precipitate. To further investigate the interactions between TICs clouds and aerosols, in-situ, airborne and satellite measurements of specific cases observed during the POLARCAT and ISDAC field experiments are analyzed. These two field campaigns took place respectively over the North Slope of Alaska and Northern part of Sweden in April 2008. Analysis of cloud type can be done from these observations, and a first classification has been performed. Results are then compared to satellite data analysis. The new retrieval scheme of Delanoë and Hogan, which combines CloudSat radar and CALIPSO lidar measurements, is used to recover profiles of the properties of ice clouds such as the visible extinction coefficient, the ice water content and the effective radius of ice crystals. Comparisons with in situ airborne measurements allow to validate this retrieval method, and thus the clouds and aerosols properties, for selected cases whereflights are coordinated with the satellite overpasses. A comparison of combined CloudSat/CALIPSO microphysical properties retrievals with airborne ice clouds measurements will be presented. The Lagrangian Particle Dispersion Model FLEXPART is use to study the origin of observed air masses, to be linked with pollution sources.

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

NASA Astrophysics Data System (ADS)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-01

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200 % for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASC measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18 % difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36 % for the individual events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122 % for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. More accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.

Cloud ice: A climate model challenge with signs and expectations of progress

NASA Astrophysics Data System (ADS)

Waliser, Duane E.; Li, Jui-Lin F.; Woods, Christopher P.; Austin, Richard T.; Bacmeister, Julio; Chern, Jiundar; Del Genio, Anthony; Jiang, Jonathan H.; Kuang, Zhiming; Meng, Huan; Minnis, Patrick; Platnick, Steve; Rossow, William B.; Stephens, Graeme L.; Sun-Mack, Szedung; Tao, Wei-Kuo; Tompkins, Adrian M.; Vane, Deborah G.; Walker, Christopher; Wu, Dong

2009-04-01

Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their "cloud" ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of remaining questions and suggestions for pathways forward.

An Observationally-Based Evaluation of Cloud Ice and Liquid Water in CMIP3 and CMIP5 GCMs and Contemporary Reanalyses Using Contemporary Satellite Data (Invited)

NASA Astrophysics Data System (ADS)

Li, J. F.; Waliser, D. E.; Chen, W.; Deng, M.; Lebsock, M. D.; Stephens, G. L.; Guan, B.; Christensen, M.; Teixeira, J.

2013-12-01

Representing clouds and cloud climate feedbacks in global climate models (GCMs) remains a pressing challenge to reduce and quantify uncertainties associated with climate change projection. Vertical structures of clouds simulated by present-day models have not been extensively examined using vertically-resolved cloud hydrometers such as cloud ice water (CIW) content and cloud liquid water (CLW) content. The gap in available observations for cloud mass was clearly evident from the wide disparity in the CIW path [Waliser et al., 2009] and CLW path [Li et al., 2008;2011] values exhibited in the CMIP3 GCMs. We present an observationally-based evaluation of the CIW and CLW of present-day GCMs, notably 20th century CMIP5 simulations, and compare these results to the CMIP3 and two recent reanalyses (ECMWF and MERRA). We use three different CloudSat+CALIPSO CIW products as well as three different observation CLW products, CloudSat, MODIS and AMSRE and their combined product for CLW with methods to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate with uncertainty can be obtained for model evaluations. Note, considering the CloudSat's limitations of CLW retrievals due to contamination from the precipitation and from radar clutter near the surface, an alternative CLW is synergistically constructed using MODIS CLW and CloudSat CLW. The results show that for annual mean CIW path, there are factors of 2-10 in the differences between observations and models for a majority of the GCMs and for a number of regions. Based on a number of metrics, the ensemble behavior of CMIP5 has improved considerably relative to CMIP3 (~ 50%), although neither the CMIP5 ensemble mean nor any individual model performs particularly well, and there are still a number of models that exhibit very large biases despite the availability of relevant observations. For CLW, most of the CMIP3/CMIP5 annual mean CLW path values are overestimated by factors of 2-10 compared to observations globally. For the vertical structure of CIW/CLW content, significant systematic biases are found with many models biased significantly. Based on the Taylor diagram, the ensemble performance of CMIP5 CLW path simulation shows little or no improvement relative to CMIP3. The implications of these results on model representations of the earth radiation balance are discussed, along with caveats and uncertainties associated with the observational estimates, model and observation representations of the precipitating and cloudy ice components, relevant physical processes and parameterizations.

Features of clouds and convection during the pre- and post-onset periods of the Asian summer monsoon

NASA Astrophysics Data System (ADS)

Wang, Yi; Wang, Chenghai

2016-02-01

The statistical characteristics of the vertical structure of clouds in the Asian summer monsoon region are investigated using two CloudSat standard products (Geometrical Profiling Product (GEOPROF) and GEOPROF-lidar) during the pre- and post-onset periods of the Asian summer monsoon, from April to August in 2007-2010. The characteristics of the vertical structure of clouds are analyzed and compared for different underlying surfaces in four subregions during this period. Also analyzed are the evolution of precipitation and hydrometeors with the northward advance of the Asian summer monsoon, and different hydrometeor characteristics attributed to the underlying surface features. The results indicate that the vertical cloud amounts increase significantly after the summer monsoon onset; this increase occurs first in the upper troposphere and then at lower altitudes over tropical regions (South Asian and tropical Northwest Pacific regions). The heights of the cloud top ascend, and the vertical height between the top and the base of the whole cloud increases. Single-layer (SL) and double-layer (DL) hydrometeors contribute over half and one third of the cloudiness in these 5 months (April to August), respectively. The multilayer frequencies increase in four different regions, and cloud layer depths (CLD) increase after the summer monsoon onset. These changes are stronger in tropical regions than in subtropical regions, while the vertical distance between cloud layers (VDCL) deceases in tropical regions and increases in subtropical regions.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

4-D cloud properties from passive satellite data and applications to resolve the flight icing threat to aircraft

NASA Astrophysics Data System (ADS)

Smith, William L., Jr.

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This thesis develops new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft in a wide range of cloud conditions. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS, the satellite icing detection and intensity accuracies are found to be about 90% and 70%, respectively. Mean differences between the imager IWC retrievals with those from CloudSat and Calipso are less than 30%. This level of closure in the cloud water budget can only be achieved by correcting for errors in the imager retrievals due to the simplifying but poor assumption that deep optically thick clouds are single-phase and vertically homogeneous. When applied to geostationary satellite data, the profiling method provides a real-time characterization of clouds in 4-D. This research should improve the utility of satellite imager data for quantitatively diagnosing and predicting clouds and their effects in weather and climate applications.

Are ship tracks useful analogs for studying the aerosol indirect effect?

NASA Astrophysics Data System (ADS)

Christensen, M.; Toll, V.; Stephens, G. L.

2017-12-01

Vessels transiting the ocean sometimes leave their mark on the clouds - leaving behind reflective cloud lines, known as ship tracks. Ship tracks have been looked upon by some as a possible Rosetta Stone connecting the effects of changing aerosol over the ocean and cloud albedo effects on climate (Porch et al. 1990, Atmos. Enviorn., 1051-1059). In this research, we establish whether ship tracks, and volcano tracks - a natural analog, can be used to relate these cloud-scale perturbations to the aerosol effects occurring at larger regional-scales. Two databases containing over 1,500 ship and 900 volcano tracks, all carefully hand-selected from satellite imagery, are utilized; showing that ship tracks exhibit very similar cloud albedo effect responses to that of volcano tracks. For comparison, our global dataset utilises over 7 million CloudSat profiles consisting of single-layer marine warm cloud in which the retrievals are co-located with the MODerate Imaging Spectroradiometer (MODIS) product so that statistical relationships between aerosol and cloud can be computed over 4x4 degree regions. All datasets show the same key physical processes that govern the cloud-aerosol indirect effect, namely, the strong negative responses in cloud droplet size and the bidirectional responses in liquid water path and cloud albedo depending on the meteorological conditions. Finally, this analysis is extended to a comparison against several general circulation models where it is suggested that key processes such as cloud-top entrainment and evaporation that regulates against strong liquid water path responses are likely underrepresented in most models.

Maintenance Downtime May 8 - 11, 2015

Atmospheric Science Data Center

2015-05-06

... The ASDC will experience a partial outage to move from old storage to new storage. ANGe ingest will be paused and production processing on ... any inconvenience this may cause.   The following data providers will be impacted: AFWA-MESH16 CloudSat FLASH GHRC NCEP ...

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

PubMed

Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E

2015-05-16

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

PubMed Central

Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

2015-01-01

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study. PMID:27656330

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Lee, Dongmin; Norris, Peter; Yuan, Tianle

2011-01-01

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Advances in Understanding the Role of Frozen Precipitation in High Latitude Hydrology

NASA Astrophysics Data System (ADS)

L'Ecuyer, T. S.; Wood, N.; Smalley, M.; McIlhattan, E.; Kulie, M.

2017-12-01

Satellite-based millimeter wavelength radar observations provide a unique perspective on the global character of frozen precipitation that has been difficult to detect using conventional spaceborne precipitation sensors. This presentation will describe the methodology underpinning the ten-year CloudSat global snowfall product and discuss the results of a number of complementary approaches that have been adopted to quantify its uncertainties. These datasets are shedding new light on the distribution, character, and impacts of frozen precipitation on high latitude hydrology. Inferred regional snowfall accumulations, for example, provide valuable constraints on projected changes in precipitation and mass balance on the Antarctic ice sheet in climate models. When placed in the broader context of complementary observations from other A-Train sensors, instantaneous snowfall estimates also hint at the large-scale processes that influence snow formation including air-sea interactions associated with cold-air outbreaks, lake-effect snows, and orographic enhancement. Simultaneous CloudSat and CALIPSO observations further emphasize the important role snowfall plays in the lifetime of super-cooled liquid containing clouds in the Arctic and highlight a model deficiency with important implications for surface energy and mass balance on the Greenland ice sheet.

Satellite-Derived Tropical Cyclone Intensities And Structure Change (TCS-08)

DTIC Science & Technology

2009-09-30

eyewall details are available from the NRL P-3 Eldora radar and from the CloudSat cloud radar that infrequently samples TC inner core structure...18. Black, P., and J. Hawkins, 2009: Overview of the WC-130J storm-scale observations during T- PARC /TCS-08, Third THORPEX International Science...satellite data and products for mission support and science applications in T- PARC , Third THORPEX International Science Symposium, Monterey, CA

End-of-Mission Planning Challenges for a Satellite in a Constellation

NASA Technical Reports Server (NTRS)

Boain, Ronald J.

2013-01-01

At the end of a mission, satellites embedded in a constellation must first perform propulsive maneuvers to safely exit the constellation before they can begin with the usual end-of-mission activities: deorbit, passivation, and decommissioning. The target orbit for these exit maneuvers must be sufficiently below the remaining constellation satellites such that, once achieved, there is no longer risk of close conjunctions. Yet, the exit maneuvers must be done based on the spacecraft's state of health and operational capability when the decision to end the mission is made. This paper focuses on the recently developed exit strategy for the CloudSat mission to highlight problems and issues, which forced the discarding of CloudSat's original EoM Plan and its replacement with a new plan consistent with changes to the spacecraft's original operational mode. The analyses behind and decisions made in formulating this new exit strategy will be of interest to other missions in a constellation currently preparing to update their End-of-Mission Plan.

Satellite-Observed Vertical Structures of Clouds over the Amazon Basin

NASA Astrophysics Data System (ADS)

Wu, M.; Lee, J. E.

2017-12-01

The long wet season of the Amazon basin currently plays a critical role in the terrestrial ecosystem, regulating carbon balance and supporting high biodiversity. It has been argued that the land surface processes are important in maintaining high precipitation; yet, how the land-atmosphere interactions modulate the atmospheric processes are not completely understood. As a first step toward solving this problem, here we examine the vertical structures of clouds and the thermodynamics of the atmosphere over the entire basin at the different time of the year. We combine the vertical distribution of cloud water content from CloudSat, and the atmospheric thermodynamic conditions from the ECMWF ERA-interim reanalysis to compare and contrast the atmospheric condition at different time of the year-the wet, dry, and dry-to-wet transition seasons-and in different regions-ever-wet evergreen broadleaf forests, wet evergreen broadleaf forests with a dry season, and dry wooded grasslands/woodlands-following water stress gradient. In the ever-wet and wet regions, a large amount of cloud ice water is present in the upper atmosphere (above 11km) and convective available potential energy (CAPE) is high during the transition season, supporting the claim that the convective activity is strongest during the transition season. In the dry region, there are more cloud water above 8km over woodlands than over wooded grasslands during the dry and transition seasons, indicating the influence of the land cover. We also classified our data following the large-scale circulation pattern, and the CloudSat data support more deep convective activities in the wet and dry regions when the wind blows from the east during the wet and transition seasons. As a next step, we will focus more on linking the cloud structure to the large-scale circulation and surface processes.

Polar cloud observatory at Ny-Ålesund in GRENE Arctic Climate Change Research Project

NASA Astrophysics Data System (ADS)

Yamanouchi, Takashi; Takano, Toshiaki; Shiobara, Masataka; Okamoto, Hajime; Koike, Makoto; Ukita, Jinro

2016-04-01

Cloud is one of the main processes in the climate system and especially a large feed back agent for Arctic warming amplification (Yoshimori et al., 2014). From this reason, observation of polar cloud has been emphasized and 95 GHz cloud profiling radar in high precision was established at Ny-Ålesund, Svalbard in 2013 as one of the basic infrastructure in the GRENE (Green Network of Excellence Program) Arctic Climate Change Research Project. The radar, "FALCON-A", is a FM-CW (frequency modulated continuous wave) Doppler radar, developed for Arctic use by Chiba University (PI: T. Takano) in 2012, following its prototype, "FALCON-1" which was developed in 2006 (Takano et al., 2010). The specifications of the radar are, central frequency: 94.84 GHz; antenna power: 1 W; observation height: up to 15 km; range resolution: 48 m; beam width: 0.2 degree (15 m at 5 km); Doppler width: 3.2 m/s; time interval: 10 sec, and capable of archiving high sensitivity and high spatial and time resolution. An FM-CW type radar realizes similar sensitivity with much smaller parabolic antennas separated 1.4 m from each other used for transmitting and receiving the wave. Polarized Micro-Pulse Lidar (PMPL, Sigma Space MPL-4B-IDS), which is capable to measure the backscatter and depolarization ratio, has also been deployed to Ny-Ålesund in March 2012, and now operated to perform collocated measurements with FALCON-A. Simultaneous measurement data from collocated PMPL and FALCON-A are available for synergetic analyses of cloud microphysics. Cloud mycrophysics, such as effective radius of ice particles and ice water content, are obtained from the analysis based on algorithm, which is modified for ground-based measurements from Okamoto's retrieval algorithm for satellite based cloud profiling radar and lidar (CloudSat and CALIPSO; Okamoto et al., 2010). Results of two years will be shown in the presentation. Calibration is a point to derive radar reflectivity (dBZ) from original intensity data. Degradation of transmission power was monitored and sensitivity of receiving system was derived with estimating antenna gain by using radio wave absorber and considering antenna geometry of two antenna system. In order to estimate final results, altitude dependent detection limit curve was also calculated. Original intensity data in real time and calibrated radar reflectivity data are archived on "Arctic Data archive System (ADS)". Other collocated observations were made with fog monitor (particle size distribution), MPS (particle image) for continuous measurements at Zeppelin Mountain, 450 m height a. s. l., and tethered balloon for intense observing period. From these measurements together with aerosol and meteorological monitoring made by collaborating institutes (Stockholm University, University of Florence, AWI, NILU, NCAR and NPI) microphysics of low level cloud and aerosol-cloud interactions are discussed. Ground based remote sensors provide a powerful validation for satellite cloud observations. Radar reflectivity (dBZ) by FALCON-A was compared with that by CPR on CloudSAT during several overpasses around Ny-Ålesund, and though some difference due to the different vertical resolution was seen, overall agreement was confirmed. We are planning to establish Ny-Ålesund observatory as the super site for validation for EarthCARE (JAXA-ESA) mission.

Assessing cloud radiative effects on tropospheric photolysis rates and key oxidants during aircraft campaigns using satellite cloud observations and a global chemical transport model

NASA Astrophysics Data System (ADS)

Zhang, B.; Liu, H.; Crawford, J. H.; Chen, G.; Voulgarakis, A.; Fairlie, T. D.; Duncan, B. N.; Ham, S. H.; Kato, S.; Payer Sulprizio, M.; Yantosca, R.

2017-12-01

Clouds affect tropospheric photochemistry through modifying solar radiation that determines photolysis rates. Observational and modeling studies have indicated that photolysis rates are enhanced above and in the upper portion of cloud layers and are reduced below optically thick clouds due to their dominant backscattering effect. However, large uncertainties exist in the representation of cloud spatiotemporal (especially vertical) distributions in global models, which makes understanding of cloud radiative effects on tropospheric chemistry challenging. Our previous study using a global 3-D chemical transport model (GEOS-Chem) driven by various meteorological data sets showed that the radiative effects of clouds on photochemistry are more sensitive to the differences in the vertical distribution of clouds than to those in the magnitude of column cloud optical depths. In this work, we evaluate monthly mean cloud optical properties and distributions in the MERRA-2 reanalysis with those in C3M, a 3-D cloud data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, CloudSat, CALIPSO, and MODIS) observations. We conduct tropospheric chemistry simulations for the periods of several aircraft campaigns, including ARCTAS (April, June-July, 2008), DC3 (May-June, 2012), and SEAC4RS (August-September, 2013) with GEOS-Chem driven by MERRA-2. We compare model simulations with and without constraints of cloud optical properties and distributions from C3M, and evaluate model photolysis rates (J[O1D] and J[NO2]) and key oxidants (e.g., OH and ozone) with aircraft profile measurements. We will assess whether the constraints provided by C3M improve model simulations of photolysis rates and oxidants as well as their variabilities.

Ice Cloud Properties And Their Radiative Effects: Global Observations And Modeling

NASA Astrophysics Data System (ADS)

Hong, Yulan

Ice clouds are crucial to the Earth's radiation balance. They cool the Earth-atmosphere system by reflecting solar radiation back to space and warm it by blocking outgoing thermal radiation. However, there is a lack of an observation-based climatology of ice cloud properties and their radiative effects. Two active sensors, the CloudSat radar and the CALIPSO lidar, for the first time provide vertically resolved ice cloud data on a global scale. Using synergistic signals of these two sensors, it is possible to obtain both optically thin and thick ice clouds as the radar excels in probing thick clouds while the lidar is better to detect the thin ones. First, based on the CloudSat radar and CALIPSO lidar measurements, we have derived a climatology of ice cloud properties. Ice clouds cover around 50% of the Earth surface, and their global-mean optical depth, ice water path, and effective radius are approximately 2 (unitless), 109 g m. {-2} and 48 \\mum, respectively. Ice cloud occurrence frequency not only depends on regions and seasons, but also on the types of ice clouds as defined by optical depth (tau) values. Optically thin ice clouds (tau < 3) are most frequently observed in the tropics around 15 km and in the midlatitudes below 5 km, while the thicker clouds (tau > 3) occur frequently in the tropical convective areas and along the midlatitude storm tracks. Using ice retrievals derived from combined radar-lidar measurements, we conducted radiative transfer modeling to study ice cloud radiative effects. The combined effects of ice clouds warm the earth-atmosphere system by approximately 5 W m-2, contributed by a longwave warming effect of about 21.8 W m-2 and a shortwave cooling effect of approximately -16.7 W m-2. Seasonal variations of ice cloud radiative effects are evident in the midlatitudes where the net effect changes from warming during winter to cooling during summer, and the net warming effect occurs year-round in the tropics (˜ 10 W m-2). Ice cloud optical depth is shown to be an important factor in determining the sign and magnitude of the net radiative effect. On a global average, ice clouds with tau ≤ 4.6 display a warming effect with the largest contributions from those with tau ˜ 1.0. Optically thin and high ice clouds cause strong heating in the tropical upper troposphere, while outside the tropics, mixed-phase clouds cause strong cooling at lower altitudes (> 5 km). In addition, ice clouds occurring with liquid clouds in the same profile account for about 30%$of all observations. These liquid clouds reduce longwave heating rates in ice cloud layers by 0-1 K/day depending on the values of ice cloud optical depth and regions. This research for the first time provides a clear picture on the global distribution of ice clouds with a wide range of optical depth. Through radiative transfer modeling, we have gained better knowledge on ice cloud radiative effects and their dependence on ice cloud properties. These results not only improve our understanding of the interaction between clouds and climate, but also provide observational basis to evaluate climate models.

The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.

Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less

Characterization of snowfall properties at high-latitude sites through use of a combined Multi-Angle Snow Camera (MASC) and radar approach

NASA Astrophysics Data System (ADS)

Cooper, S.; Wood, N.; Garrett, T. J.; L'Ecuyer, T. S.; Pettersen, C.

2016-12-01

Estimates of snowfall rate derived from radar reflectivities alone are non-unique, as different combinations of snowfall rates and snowflake microphysical properties can conspire to produce nearly identical radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200% for individual events. Here, we use observations of snowflake particle size distribution, fallspeed, and habit from the Multi-Angle Snow Camera (MASC) to constrain estimates of snowfall derived from radar reflectivities. MASC measurements of microphysical properties and uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Initial results focus on the MASC and Ka-band Zenith Radar (KaZR) measurements at the ARM NSA Barrow Climate Facility site. Use of MASC fallspeed, MASC PSD, and a CloudSat particle model as base assumptions resulted in retrieved total accumulations with a -17% difference relative to nearby National Weather Service observations averaged over five snow events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -63% to + 86% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fallspeed and habit, suggesting that MASC measurements may provide a path forward in reducing the non-uniqueness of the snowfall retrieval problem. Preliminary results also will be presented for the deployment of the MASC, MicroRain Radar (MRR), and Precipitation Imaging Package (PIP) to Haukeliseter, Norway during winter season 2016-17. These instruments will then be deployed to northern Sweden for winter 2017-18. It is hoped more accurate knowledge of snowfall properties dependent upon location and meteorological conditions will be useful for both weather and climate applications.

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE PAGES

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-20

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

NASA Astrophysics Data System (ADS)

Greenwald, Thomas J.; Bennartz, Ralf; Lebsock, Matthew; Teixeira, João.

2018-04-01

The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9-year record of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E): clear-sky bias, cloud-rain partition (CRP) bias, cloud-fraction-dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR-E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud-Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud-fraction-dependent bias was found to be a combination of the CRP bias, an in-cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in-cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias-corrected AMSR-E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible-infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations.

Cloud-Radiative Driving of the Madden-Julian Oscillation as Seen by the A-Train

NASA Technical Reports Server (NTRS)

Del Genio, Anthony; Chen, Yonghua

2015-01-01

Cloud and water vapor radiative heating anomalies associated with convection may be an effective source of moist static energy driving the Madden-Julian Oscillation (MJO). In this paper five years of radiative heating profiles derived from CloudSat radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data are analyzed to document radiative heating anomalies during the MJO. Atmospheric shortwave absorption and surface longwave radiation anomalies are of opposite sign and 10-20% as large as top-of-atmosphere outgoing longwave radiation (OLR) anomalies, confirming that OLR provides a useful estimate of the total column radiative heating anomaly. Positive anomalies generally peak about one week before the MJO peak and are smallest over the Indian Ocean. Anomalies over the Maritime Continent are strongest, and coincident with the MJO peak. Shortwave heating profile anomalies are about half as large as longwave anomalies in the active region of the MJO but generally of opposite sign; thus shortwave heating damps the longwave destabilization of the lower troposphere. The exception is the onset phase of the MJO, where shortwave and longwave heating anomalies due to thin cirrus are both positive in the upper troposphere and exert a stabilizing influence. Specific humidity anomalies in the middle troposphere reach 0.5 g kg(exp. -1), but the associated clear sky heating anomaly is very small. Radiative enhancement of column moist static energy becomes significant about 10 days before the MJO peak, when precipitation anomalies are still increasing, and then remains high after the MJO peak after precipitation has begun to decline.

Optically thin ice clouds in Arctic; Formation processes

NASA Astrophysics Data System (ADS)

Jouan, Caroline; Pelon, Jacques; Girard, Eric; Blanchet, Jean-Pierre; Wobrock, Wolfram; Gayet, Jean-Franćois; Schwarzenböck, Alfons; Gultepe, Ismail; Delanoë, Julien; Mioche, Guillaume

2010-05-01

Arctic ice cloud formation during winter is poorly understood mainly due to lack of observations and the remoteness of this region. Yet, their influence on Northern Hemisphere weather and climate is of paramount importance, and the modification of their properties, linked to aerosol-cloud interaction processes, needs to be better understood. Large concentration of aerosols in the Arctic during winter is associated to long-range transport of anthropogenic aerosols from the mid-latitudes to the Arctic. Observations show that sulphuric acid coats most of these aerosols. Laboratory and in-situ measurements show that at cold temperature (< -30°C), acidic coating lowers the freezing point and deactivates ice nuclei (IN). Therefore, the IN concentration is reduced in these regions and there is less competition for the same available moisture. As a result, large ice crystals form in relatively small concentrations. It is hypothesized that the observed low concentration of large ice crystals in thin ice clouds is linked to the acidification of aerosols. To check this, it is necessary to analyse cloud properties in the Arctic. Extensive measurements from ground-based sites and satellite remote sensing (CloudSat and CALIPSO) reveal the existence of two types of extended optically thin ice clouds (TICs) in the Arctic during the polar night and early spring. The first type (TIC-1) is seen only by the lidar, but not the radar, and is found in pristine environment whereas the second type (TIC-2) is detected by both sensors, and is associated with high concentration of aerosols, possibly anthropogenic. TIC-2 is characterized by a low concentration of ice crystals that are large enough to precipitate. To further investigate the interactions between TICs clouds and aerosols, in-situ, airborne and satellite measurements of specific cases observed during the POLARCAT and ISDAC field experiments are analyzed. These two field campaigns took place respectively over the North Slope of Alaska and Northern part of Sweden in April 2008. The airborne microphysical instruments include a complete set of dynamic, thermodynamic, radiation, aerosol and microphysical sensors such as the Polar Nephelometer probe, the Cloud Particle Imager probe (CPI) and standard PMS probes: 2D-C, 2D-P, FSSP. Analysis of cloud type can be done from these observations, and a first classification has been performed. Results are then compared to satellite data analysis. The new retrieval scheme of Delanoë and Hogan, which combines CloudSat radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements, is used to recover profiles of the properties of ice clouds such as the visible extinction coefficient, the ice water content and the effective radius of ice crystals. Comparisons with in situ airborne measurements allow to validate this retrieval method, and thus the clouds and aerosols properties, for selected cases where flights are coordinated with the satellite overpasses. A comparison of combined CloudSat/CALIPSO microphysical properties retrievals with airborne ice clouds measurements will be presented. The Lagrangian Particle Dispersion Model (LPDM) FLEXPART is use to study the origin of observed air masses, to be linked with pollution sources.

Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity based on water cloud simulations using a spectral-bin microphysics cloud model

NASA Astrophysics Data System (ADS)

Matsui, T. N.; Suzuki, K.; Nakajima, T. Y.; Matsumae, Y.

2011-12-01

Clouds play an import role in energy balance and climate changes of the Earth. IPCC AR4, however, pointed out that cloud feedback is still the large source of uncertainty in climate estimates. In the recent decade, the new satellites with the active instruments (e.g. Cloudsat) represented a new epoch in earth observations. The active remote sensing is powerful for illustrating the vertical structures of clouds, but the passive remote sensing from satellite images also contribute to better understating of cloud system. For instance, Nakajima et al. (2010a) and Suzuki et al. (2010) illustrated transition of cloud growth, from cloud droplet to drizzle to rain, using the combine analysis of the cloud droplet size retrieved from passive images (MODIS) and the reflectivity profiles from Cloudsat. Furthermore, EarthCARE that is a new satellite launched years later is composed of not only the active but also passive instruments for the combined analysis. On the other hands, the methods to retrieve the advanced information of cloud properties are also required because many imagers have been operated and are now planned (e.g. GCOM-C/SGLI), and have the advantages such as wide observation width and more observation channels. Cloud droplet effective radius (CDR) and cloud optical thickness (COT) can be retrieved using a non-water-absorbing band (e.g. 0.86μm) and a water-absorbing band (1.6, 2.1, 3.7μm) of imagers under the assumptions such as the log-normal droplet size distribution and the plane-parallel cloud structure. However, the differences between three retrieved CDRs using 1.6, 2.1 or 3.7μm (R16, R21 and R37) are found in the satellite observations. Several studies pointed out that vertical/horizontal inhomogeneity of cloud structure, difference of penetration depth of water-absorbing bands, multi-modal droplet distribution and/or 3-D radiative transfer effect cause the CDR differences. In other words, the advanced information of clouds may lie hidden in the differences. Nakajima et al. (2010b) investigated the impact of the differences sensitivities to particle size and the penetration depth in an attempt to explain the CDR differences found in by using a simple two-layer cloud model with the bi-modal size distribution functions. Their results showed the sensitivity differences between 1.6, 2.1 and 3.7μm bands to droplet sizes and their vertical stratification. In this study, we further investigate the impact of the vertical inhomogeneity structure including the drizzle by using a spectral-bin microphysics cloud model. We apply the 1-D radiative transfer computation to the numerical cloud fields generated by the cloud model, and retrieve the CDRs from the reflectances thus simulated at each band. We then compare the statistics of these retrieved CDRs with the CDRs obtained from MODIS observations and derive the sensitivity functions of the retrieved CDRs to the particle size and the optical depth from the sets of the droplet distribution functions predicted by the model and the retrieved CDRs. This study is an attempt to interpret the CDR differences in terms of the cloud vertical structure and the cloud particle growth processes.

Validation of VIIRS Cloud Base Heights at Night Using Ground and Satellite Measurements over Alaska

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Seaman, C.; Forsythe, J. M.; Brummer, R.; Lindsey, D. T.; Walther, A.; Heidinger, A. K.; Li, Y.

2016-12-01

Knowledge of Cloud Base Height (CBH) is critical to describing cloud radiative feedbacks in numerical models and is of practical significance to aviation communities. We have developed a new CBH algorithm constrained by Cloud Top Height (CTH) and Cloud Water Path (CWP) by performing a statistical analysis of A-Train satellite data. It includes an extinction-based method for thin cirrus. In the algorithm, cloud geometric thickness is derived with upstream CTH and CWP input and subtracted from CTH to generate the topmost layer CBH. The CBH information is a key parameter for an improved Cloud Cover/Layers product. The algorithm has been applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP spacecraft. Nighttime cloud optical properties for CWP are retrieved from the nighttime lunar cloud optical and microphysical properties (NLCOMP) algorithm based on a lunar reflectance model for the VIIRS Day/Night Band (DNB) measuring nighttime visible light such as moonlight. The DNB has innovative capabilities to fill the polar winter and nighttime gap of cloud observations which has been an important shortfall from conventional radiometers. The CBH products have been intensively evaluated against CloudSat data. The results showed the new algorithm yields significantly improved performance over the original VIIRS CBH algorithm. However, since CloudSat is now operational during daytime only due to a battery anomaly, the nighttime performance has not been fully assessed. This presentation will show our approach to assess the performance of the CBH algorithm at night. VIIRS CBHs are retrieved over the Alaska region from October 2015 to April 2016 using the Clouds from AVHRR Extended (CLAVR-x) processing system. Ground-based measurements from ceilometer and micropulse lidar at the Atmospheric Radiation Measurement (ARM) site on the North Slope of Alaska are used for the analysis. Local weather conditions are checked using temperature and precipitation observations at the site. CALIPSO data with near-simultaneous colocation are added for multi-layered cloud cases which may have high clouds aloft beyond the ground measurements. Multi-month statistics of performance and case studies will be shown. Additional efforts for algorithm refinements will be also discussed.

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Li, Jiming; Lv, Qiaoyi; Jian, Bida; Zhang, Min; Zhao, Chuanfeng; Fu, Qiang; Kawamoto, Kazuaki; Zhang, Hua

2018-05-01

Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007-2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.

Estimating surface longwave radiative fluxes from satellites utilizing artificial neural networks

NASA Astrophysics Data System (ADS)

Nussbaumer, Eric A.; Pinker, Rachel T.

2012-04-01

A novel approach for calculating downwelling surface longwave (DSLW) radiation under all sky conditions is presented. The DSLW model (hereafter, DSLW/UMD v2) similarly to its predecessor, DSLW/UMD v1, is driven with a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 cloud parameters and information from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim model. To compute the clear sky component of DSLW a two layer feed-forward artificial neural network with sigmoid hidden neurons and linear output neurons is implemented; it is trained with simulations derived from runs of the Rapid Radiative Transfer Model (RRTM). When computing the cloud contribution to DSLW, the cloud base temperature is estimated by using an independent artificial neural network approach of similar architecture as previously mentioned, and parameterizations. The cloud base temperature neural network is trained using spatially and temporally co-located MODIS and CloudSat Cloud Profiling Radar (CPR) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. Daily average estimates of DSLW from 2003 to 2009 are compared against ground measurements from the Baseline Surface Radiation Network (BSRN) giving an overall correlation coefficient of 0.98, root mean square error (rmse) of 15.84 W m-2, and a bias of -0.39 W m-2. This is an improvement over an earlier version of the model (DSLW/UMD v1) which for the same time period has an overall correlation coefficient 0.97 rmse of 17.27 W m-2, and bias of 0.73 W m-2.

Cloud Ice: A Climate Model Challenge With Signs and Expectations of Progress

NASA Astrophysics Data System (ADS)

Li, F.; Waliser, D.; Bacmeister, J.; Chern, J.; Del Genio, T.; Jiang, J.; Kharitondov, M.; Liou, K.; Meng, H.; Minnis, P.; Rossow, B.; Stephens, G.; Sun-Mack, S.; Tao, W.; Vane, D.; Woods, C.; Tompkins, A.; Wu, D.

2007-12-01

Global climate models (GCMs), including those assessed in the IPCC AR4, exhibit considerable disagreement in the amount of cloud ice - both in terms of the annual global mean as well as their spatial variability. Global measurements of cloud ice have been difficult due to the challenges involved in remotely sensing ice water content (IWC) and its vertical profile - including complications associated with multi-level clouds, mixed-phases and multiple hydrometer types, the uncertainty in classifying ice particle size and shape for remote retrievals, and the relatively small time and space scales associated with deep convection. Together, these measurement difficulties make it a challenge to characterize and understand the mechanisms of ice cloud formation and dissipation. Fortunately, there are new observational resources recently established that can be expected to lead to considerable reduction in the observational uncertainties of cloud ice, and in turn improve the fidelity of model representations. Specifically, these include the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite, and the CloudSat and Calipso satellite missions, all of which fly in formation in what is referred to as the A-Train. Based on radar and limb-sounding techniques, these new satellite measurements provide a considerable leap forward in terms of the information gathered regarding upper-tropospheric cloud IWC as well as other macrophysical and microphysical properties. In this presentation, we describe the current state of GCM representations of cloud ice and their associated uncertainties, the nature of the new observational resources for constraining cloud ice values in GCMs, the challenges in making model-data comparisons with these data resources, and prospects for near-term improvements in model representations.

Cloud and aerosol studies using combined CPL and MAS data

NASA Astrophysics Data System (ADS)

Vaughan, Mark A.; Rodier, Sharon; Hu, Yongxiang; McGill, Matthew J.; Holz, Robert E.

2004-11-01

Current uncertainties in the role of aerosols and clouds in the Earth's climate system limit our abilities to model the climate system and predict climate change. These limitations are due primarily to difficulties of adequately measuring aerosols and clouds on a global scale. The A-train satellites (Aqua, CALIPSO, CloudSat, PARASOL, and Aura) will provide an unprecedented opportunity to address these uncertainties. The various active and passive sensors of the A-train will use a variety of measurement techniques to provide comprehensive observations of the multi-dimensional properties of clouds and aerosols. However, to fully achieve the potential of this ensemble requires a robust data analysis framework to optimally and efficiently map these individual measurements into a comprehensive set of cloud and aerosol physical properties. In this work we introduce the Multi-Instrument Data Analysis and Synthesis (MIDAS) project, whose goal is to develop a suite of physically sound and computationally efficient algorithms that will combine active and passive remote sensing data in order to produce improved assessments of aerosol and cloud radiative and microphysical properties. These algorithms include (a) the development of an intelligent feature detection algorithm that combines inputs from both active and passive sensors, and (b) identifying recognizable multi-instrument signatures related to aerosol and cloud type derived from clusters of image pixels and the associated vertical profile information. Classification of these signatures will lead to the automated identification of aerosol and cloud types. Testing of these new algorithms is done using currently existing and readily available active and passive measurements from the Cloud Physics Lidar and the MODIS Airborne Simulator, which simulate, respectively, the CALIPSO and MODIS A-train instruments.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

Global Variability of Mesoscale Convective System Anvil Structure from A-Train Satellite Data

NASA Technical Reports Server (NTRS)

Yuan, Jian; Houze, Robert A.

2010-01-01

Mesoscale convective systems (MCSs) in the tropics produce extensive anvil clouds, which significantly affect the transfer of radiation. This study develops an objective method to identify MCSs and their anvils by combining data from three A-train satellite instruments: Moderate Resolution Imaging Spectroradiometer (MODIS) for cloud-top size and coldness, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) for rain area size and intensity, and CloudSat for horizontal and vertical dimensions of anvils. The authors distinguish three types of MCSs: small and large separated MCSs and connected MCSs. The latter are MCSs sharing a contiguous rain area. Mapping of the objectively identified MCSs shows patterns of MCSs that are consistent with previous studies of tropical convection, with separated MCSs dominant over Africa and the Amazon regions and connected MCSs favored over the warm pool of the Indian and west Pacific Oceans. By separating the anvil from the raining regions of MCSs, this study leads to quantitative global maps of anvil coverage. These maps are consistent with the MCS analysis, and they lay the foundation for estimating the global radiative effects of anvil clouds. CloudSat radar data show that the modal thickness of MCS anvils is about 4-5 km. Anvils are mostly confined to within 1.5-2 times the equivalent radii of the primary rain areas of the MCSs. Over the warm pool, they may extend out to about 5 times the rain area radii. The warm ocean MCSs tend to have thicker non-raining and lightly raining anvils near the edges

Outcome of the third cloud retrieval evaluation workshop

NASA Astrophysics Data System (ADS)

Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

2013-05-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement, cloud physical properties, and cloud climatologies. We present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize actions defined to tailor CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention is given to increase the traceability and uniformity of different longterm and homogeneous records of cloud parameters.

An Uncertainty Data Set for Passive Microwave Satellite Observations of Warm Cloud Liquid Water Path

PubMed Central

Bennartz, Ralf; Lebsock, Matthew; Teixeira, João

2018-01-01

Abstract The first extended comprehensive data set of the retrieval uncertainties in passive microwave observations of cloud liquid water path (CLWP) for warm oceanic clouds has been created for practical use in climate applications. Four major sources of systematic errors were considered over the 9‐year record of the Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E): clear‐sky bias, cloud‐rain partition (CRP) bias, cloud‐fraction‐dependent bias, and cloud temperature bias. Errors were estimated using a unique merged AMSR‐E/Moderate resolution Imaging Spectroradiometer Level 2 data set as well as observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization and the CloudSat Cloud Profiling Radar. To quantify the CRP bias more accurately, a new parameterization was developed to improve the inference of CLWP in warm rain. The cloud‐fraction‐dependent bias was found to be a combination of the CRP bias, an in‐cloud bias, and an adjacent precipitation bias. Globally, the mean net bias was 0.012 kg/m2, dominated by the CRP and in‐cloud biases, but with considerable regional and seasonal variation. Good qualitative agreement between a bias‐corrected AMSR‐E CLWP climatology and ship observations in the Northeast Pacific suggests that the bias estimates are reasonable. However, a possible underestimation of the net bias in certain conditions may be due in part to the crude method used in classifying precipitation, underscoring the need for an independent method of detecting rain in warm clouds. This study demonstrates the importance of combining visible‐infrared imager data and passive microwave CLWP observations for estimating uncertainties and improving the accuracy of these observations. PMID:29938146

Aerosol Microphysical Effects on Cloud Fraction over the Nighttime Arctic Ocean

NASA Astrophysics Data System (ADS)

Zamora, L. M.; Kahn, R. A.; Stohl, A.; Eckhardt, S.

2017-12-01

Cloud fraction is a key component affecting the surface energy balance in the Arctic. Aerosol microphysical processes can affect cloud fraction, for example through cloud lifetime effects. However, the importance of aerosol impacts on cloud fraction is not well constrained on a regional scale at high latitudes. Here we discuss a new method for identifying and comparing clean and aerosol-influenced cloud characteristics using a combination of multi-year remote sensing data (CALIPSO, CloudSat) and the FLEXPART aerosol model. We use this method to investigate a variety of aerosol microphysical impacts on nighttime Arctic Ocean clouds on regional and local scales. We observe differences in factors that can impact cloud lifetime, including cloud thickness and phase, within a subset of clean vs. polluted clouds. We will also discuss cumulative cloud fraction differences in clean and non-clean environments, as well as their likely impact on longwave cloud radiative effects at the Arctic Ocean surface during polar night.

Combining In-situ Measurements, Passive Satellite Imagery, and Active Radar Retrievals for the Detection of High Ice Water Content

NASA Astrophysics Data System (ADS)

Yost, C. R.; Minnis, P.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Spangenberg, D.; Strapp, J. W.; Delanoë, J.; Protat, A.

2016-12-01

At least one hundred jet engine power loss events since the 1990s have been attributed to the phenomenon known as ice crystal icing (ICI). Ingestion of high concentrations of ice particles into aircraft engines is thought to cause these events, but it is clear that the use of current on-board weather radar systems alone is insufficient for detecting conditions that might cause ICI. Passive radiometers in geostationary orbit are valuable for monitoring systems that produce high ice water content (HIWC) and will play an important role in nowcasting, but are incapable of making vertically resolved measurements of ice particle concentration, i.e., ice water content (IWC). Combined radar, lidar, and in-situ measurements are essential for developing a skilled satellite-based HIWC nowcasting technique. The High Altitude Ice Crystals - High Ice Water Content (HAIC-HIWC) field campaigns in Darwin, Australia, and Cayenne, French Guiana, have produced a valuable dataset of in-situ total water content (TWC) measurements with which to study conditions that produce HIWC. The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) was used to derive cloud physical and optical properties such cloud top height, temperature, optical depth, and ice water path from multi-spectral satellite imagery acquired throughout the HAIC-HIWC campaigns. These cloud properties were collocated with the in-situ TWC measurements in order to characterize cloud properties in the vicinity of HIWC. Additionally, a database of satellite-derived overshooting cloud top (OT) detections was used to identify TWC measurements in close proximity to convective cores likely producing large concentrations of ice crystals. Certain cloud properties show some sensitivity to increasing TWC and a multivariate probabilistic indicator of HIWC was developed from these datasets. This paper describes the algorithm development and demonstrates the HIWC indicator with imagery from the HAIC-HIWC campaigns. Vertically resolved IWC retrievals from active sensors such as the Cloud Profiling Radar (CPR) on CloudSat and the Doppler Radar System Airborne (RASTA) provide IWC profiles with which to validate and potentially enhance the satellite-based HIWC indicator.

Study on Diagnosing Three Dimensional Cloud Region

NASA Astrophysics Data System (ADS)

Cai, M., Jr.; Zhou, Y., Sr.

2017-12-01

Cloud mask and relative humidity (RH) provided by Cloudsat products from 2007 to 2008 are statistical analyzed to get RH Threshold between cloud and clear sky and its variation with height. A diagnosis method is proposed based on reanalysis data and applied to three-dimensional cloud field diagnosis of a real case. Diagnostic cloud field was compared to satellite, radar and other cloud precipitation observation. Main results are as follows. 1.Cloud region where cloud mask is bigger than 20 has a good space and time corresponding to the high value relative humidity region, which is provide by ECWMF AUX product. Statistical analysis of the RH frequency distribution within and outside cloud indicated that, distribution of RH in cloud at different height range shows single peak type, and the peak is near a RH value of 100%. Local atmospheric environment affects the RH distribution outside cloud, which leads to TH distribution vary in different region or different height. 2. RH threshold and its vertical distribution used for cloud diagnostic was analyzed from Threat Score method. The method is applied to a three dimension cloud diagnosis case study based on NCEP reanalysis data and th diagnostic cloud field is compared to satellite, radar and cloud precipitation observation on ground. It is found that, RH gradient is very big around cloud region and diagnosed cloud area by RH threshold method is relatively stable. Diagnostic cloud area has a good corresponding to updraft region. The cloud and clear sky distribution corresponds to satellite the TBB observations overall. Diagnostic cloud depth, or sum cloud layers distribution consists with optical thickness and precipitation on ground better. The cloud vertical profile reveals the relation between cloud vertical structure and weather system clearly. Diagnostic cloud distribution correspond to cloud observations on ground very well. 3. The method is improved by changing the vertical interval from altitude to temperature. The result shows that, the five factors , including TS score for clear sky, empty forecast, missed forecast, and especially TS score for cloud region and the accurate rate increased obviously. So, the RH threshold and its vertical distribution with temperature is better than with altitude. More tests and comparision should be done to assess the diagnosis method.

Variability of Oceanic Mesoscale Convective System Vertical Structures Observed by CloudSat in Indo-Pacific Regions Associated with the Madden-Julian Oscillation

NASA Astrophysics Data System (ADS)

Yuan, J.

2016-12-01

Vertical structures of mesoscale convective systems (MCSs) during the Madden-Julian-Oscillation (MJO) are investigated using 2006-2011 CloudSat radar measurements for Indo-Pacific oceanic areas. In active phases of the MJO relatively more large MCSs and connected MCSs occur. The frequency of occurrence of connected MCSs peaks in the onset phase, a phase earlier than separated MCSs. Compared to separated MCSs, connected MCSs in all sizes have weaker reflectivity above 8 km in their deep precipitating portions and thick anvil clouds closely linked to them, suggesting more "stratiform" physics associated with them. Separated MCSs and connected MCSs together produce relatively the least anvil clouds in the onset phase while their deep precipitating portions show stronger/weaker reflectivity above 8 km before/after the onset phase. Thus after the onset phase of the MJO, MCSs shift toward more "convective" organization because separated MCSs maximize after the onset, while their internal structures appear more "stratiform" because internally they have weaker reflectivity above 8km. Connected MCSs coincide with a more humid middle troposphere spatially, even at the same places a few days before they occur. Middle-tropospheric moistening peaks in the onset phase. Moistening of the free troposphere around deep convective systems shows relatively stronger moistening/drying below the 700 hPa before/after the onset phase compared to domain-mean averages. Lower-topped clouds occur most frequently around CMCSs and in active phases, consistent with the presence of a moister free troposphere. Coexistence of these phenomena suggests that the role of middle troposphere moisture in the formation of CMCSs needs to be better understood.

Variability of oceanic deep convective system vertical structures observed by CloudSat in Indo-Pacific regions associated with the Madden-Julian oscillation

NASA Astrophysics Data System (ADS)

Yuan, Jian

2016-09-01

Vertical structures of deep convective systems during the Madden-Julian oscillation (MJO) are investigated using CloudSat radar measurements in Indo-Pacific oceanic areas. In active phases of the MJO, relatively more large systems and connected mesoscale convective systems (CMCSs) occur. The occurrence frequency of CMCSs peaks in the onset phase, a phase earlier than separated mesoscale convective systems (SMCSs). Compared with SMCSs, CMCSs of all sizes have weaker reflectivity above 8 km in their deep precipitating portions and thick anvil clouds closely linked to them, suggesting more "stratiform" physics associated with them. SMCSs and CMCSs together produce relatively the least anvil clouds in the onset phase, while their deep precipitating portions show stronger/weaker reflectivity above 8 km before/after the onset phase. Thus, after the onset phase of the MJO, mesoscale convective systems shift toward a more "convective" organization because SMCSs maximize after the onset, while their internal structures appear more stratiform because internally they have weaker reflectivity above 8 km. CMCSs coincide with a more humid middle troposphere spatially, even at the same locations a few days before they occur. Middle-tropospheric moistening peaks in the onset phase. Moistening of the free troposphere around deep convective systems shows relatively stronger moistening/drying below 700 hPa before/after the onset phase than domain-mean averages. Low-topped clouds occur most frequently around CMCSs and in active phases, consistent with the presence of a moister free troposphere. Coexistence of these phenomena suggests that the role of middle troposphere moisture in the formation of CMCSs should be better understood.

Re-evaluating the Cloud Lifetime Effect: Does Precipitation Suppression Always Lead to an Increased Cloud Extent in Warm Clouds?

NASA Astrophysics Data System (ADS)

Douglas, A.; L'Ecuyer, T.

2017-12-01

Aerosol influences on cloud lifetime remain a poorly understood pathway of aerosol-cloud-radiation interaction with large margins of error according to the fifth IPCC report. Increases in cloud lifetime are attributed to changes in cloud extent due to the suppression of precipitation by increased aerosol concentrations. The dependence of changes in cloud fraction and probability of precipitation on aerosol perturbations for controlled cloud regimes will be investigated using A-Train measurements. CloudSat, MODIS, and AMSR-E measurements from 2006 to 2010 are sorted into regimes established using stability to describe local meteorology, and relative humidity and liquid water path to describe cloud morphology. Holding the thermodynamic and meteorological environments constant allows variations in precipitation and cloud extent owing to regime-specific cloud lifetime effects to be attributed to aerosol perturbations. The relationship between precipitation suppression, cloud extent, and liquid water path will be analyzed. The cloud lifetime effect will be constrained using regimes in the hopes of improving our understanding of precipitation-aerosol interactions.

Monthly Covariability of Amazonian Convective Cloud Properties and Radiative Diurnal Cycle

NASA Technical Reports Server (NTRS)

Dodson, J. Brant; Taylor, Patrick C.

2016-01-01

The diurnal cycle of convective clouds greatly influences the top-of-atmosphere radiative energy balance in convectively active regions of Earth, through both direct presence and the production of anvil and stratiform clouds. CloudSat and CERES data are used to further examine these connections by determining the sensitivity of monthly anomalies in the radiative diurnal cycle to monthly anomalies in multiple cloud variables. During months with positive anomalies in convective frequency, the longwave diurnal cycle is shifted and skewed earlier in the day by the increased longwave cloud forcing during the afternoon from mature deep convective cores and associated anvils. This is consistent with previous studies using reanalysis data to characterize anomalous convective instability. Contrary to this, months with positive anomalies in convective cloud top height (commonly associated with more intense convection) shifts the longwave diurnal cycle later in the day. The contrary results are likely an effect of the inverse relationships between cloud top height and frequency. The albedo diurnal cycle yields inconsistent results when using different cloud variables.

Outcome of the Third Cloud Retrieval Evaluation Workshop

NASA Astrophysics Data System (ADS)

Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

2012-04-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement; cloud physical properties, and cloud climatologies. We will present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize the actions defined to tailor the CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention will be given to increase the traceability and uniformity of different long-term and homogeneous records of cloud parameters.

CIRA: Cooperative Institute for Research in the Atmosphere Newsletter, Volume 28, Fall 2007

NASA Technical Reports Server (NTRS)

McInnis-Efaw, Mary (Editor); Leinen, Laura (Editor)

2007-01-01

The articles in this issue of the Cooperative Institute for Research in the Atmosphere (CIRA) Newsletter are: "Unmanned Aerial Systems: An Overview of NOAA's Unmanned Aircraft System Program," "International Activities: Weather Briefings and Training Via the Internet," "Cloudsat's One-Year Anniversary: An Abundance of Exciting New Cloud Observations," and "The Migration of NCAR'S Auto-Nowcaster into NWS AWIPS."

Development of Spaceborne Radar Simulator by NICT and JAXA using JMA Cloud-resolving Model

NASA Astrophysics Data System (ADS)

Kubota, T.; Eito, H.; Aonashi, K.; Hashimoto, A.; Iguchi, T.; Hanado, H.; Shimizu, S.; Yoshida, N.; Oki, R.

2009-12-01

We are developing synthetic spaceborne radar data toward a simulation of the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core-satellite. Our purposes are a production of test-bed data for higher level DPR algorithm developers, in addition to a diagnosis of a cloud resolving model (CRM). To make the synthetic data, we utilize the CRM by the Japan Meteorological Agency (JMA-NHM) (Ikawa and Saito 1991, Saito et al. 2006, 2007), and the spaceborne radar simulation algorithm by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) named as the Integrated Satellite Observation Simulator for Radar (ISOSIM-Radar). The ISOSIM-Radar simulates received power data in a field of view of the spaceborne radar with consideration to a scan angle of the radar (Oouchi et al. 2002, Kubota et al. 2009). The received power data are computed with gaseous and hydrometeor attenuations taken into account. The backscattering and extinction coefficients are calculated assuming the Mie approximation for all species. The dielectric constants for solid particles are computed by the Maxwell-Garnett model (Bohren and Battan 1982). Drop size distributions are treated in accordance with those of the JMA-NHM. We assume a spherical sea surface, a Gaussian antenna pattern, and 49 antenna beam directions for scan angles from -17 to 17 deg. in the PR. In this study, we report the diagnosis of the JMA-NHM with reference to the TRMM Precipitation Radar (PR) and CloudSat Cloud Profiling Radar (CPR) using the ISOSIM-Radar from the view of comparisons in cloud microphysics schemes of the JMA-NHM. We tested three kinds of explicit bulk microphysics schemes based on Lin et al. (1983), that is, three-ice 1-moment scheme, three-ice 2-moment scheme (Eito and Aonashi 2009), and newly developed four-ice full 2-moment scheme (Hashimoto 2008). The hydrometeor species considered here are rain, graupel, snow, cloud water, cloud ice and hail (4-ice scheme only). We examined a case of an intersection with the TRMM PR and the CloudSat CPR on 6th April 2008 over sea surface in the south of Kyushu Island of Japan. In this work, observed rainfall systems are simulated with one-way double nested domains having horizontal grid sizes of 5 km (outer) and 2 km (inner). Data used here are from the inner domain only. Results of the PR indicated better performances of 2-moment bulk schemes. It suggests that prognostic number concentrations of frozen hydrometeors are more effective in high altitudes and constant number concentrations can lead to the overestimation of the snow there. For three-ice schemes, simulated received power data overestimated above freezing levels with reference to the observed data. In contrast, the overestimation of frozen particles was heavily reduced for the four-ice scheme.

Interpretation of Aura satellite observations of CO and aerosol index related to the December 2006 Australia fires

NASA Astrophysics Data System (ADS)

Luo, M.; Boxe, C.; Jiang, J.; Nassar, R.; Livesey, N.

2009-11-01

Enhanced Carbon Monoxide (CO) in the upper troposphere (UT) is shown by collocated Tropospheric Emission Spectrometer (TES) and Microwave Limb Sounder (MLS) measurements near and down-wind from the known wildfire region of SE Australia from 12-19 December 2006. Enhanced UV aerosol index (AI) derived from Ozone Monitoring Instrument (OMI) measurements correlate with these high CO concentrations. HYSPLIT model back trajectories trace selected air parcels to the SE Australia fire region as their initial location, where TES observes enhanced CO in the upper and lower troposphere. Simultaneously, they show a lack of vertical advection along their tracks. TES retrieved CO vertical profiles in the higher and lower southern latitudes are examined together with the averaging kernels and show that TES CO retrievals are most sensitive at approximately 300-400 hPa. The enhanced CO observed by TES at the upper (215 hPa) and lower (681 hPa) troposphere are, therefore, influenced by mid-tropospheric CO. GEOS-Chem model simulations with an 8-day emission inventory, as the wildfire source over Australia, are sampled to the TES/MLS observation times and locations. These simulations only show CO enhancements in the lower troposphere near and down-wind from the wildfire region of SE Australia with drastic underestimates of UT CO. Although CloudSat along-track ice-water content curtains are examined to see whether possible vertical convection events can explain the high UT CO values, sparse observations of collocated Aura CO and CloudSat along-track ice-water content measurements for the single event precludes any conclusive correlation. Vertical convection that uplift fire-induced CO (i.e. most notably referred to as pyro-cumulonimbus, pyroCb) may provide an explanation for the incongruence between these simulations and the TES/MLS observations of enhanced CO in the UT. Future GEOS-Chem simulations are needed to validate this conjecture as the the PyroCb mechanism is currently not incorporated in GEOS-Chem.

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2015-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be executed "near" the multi-sensor data. Decade-long, multi-sensor studies can be performed without pre-staging data, with the researcher paying only his own Cloud compute bill.

Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

NASA Astrophysics Data System (ADS)

Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

2011-12-01

The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0.74), while CERES-MODIS derived values are much lower (0.60). CERES-MODIS derived cloud effective height (2.7 km) falls between the CloudSat/CALIPSO derived cloud base (0.6 km) and top (6.4 km) and the ARM ceilometers and MMCR derived cloud base (0.9 km) and radar derived cloud top (5.8 km). When extended to the entire Arctic, although the CERES-MODIS and Cloudsat/CALIPSO derived annual mean CFs agree within a few percents, there are significant differences over several regions, and the maximum cloud heights derived from CloudSat/CALIPSO (13.4 km) and CERES-MODIS (10.7 km) show the largest disagreement during early spring.

A satellite observation test bed for cloud parameterization development

NASA Astrophysics Data System (ADS)

Lebsock, M. D.; Suselj, K.

2015-12-01

We present an observational test-bed of cloud and precipitation properties derived from CloudSat, CALIPSO, and the the A-Train. The focus of the test-bed is on marine boundary layer clouds including stratocumulus and cumulus and the transition between these cloud regimes. Test-bed properties include the cloud cover and three dimensional cloud fraction along with the cloud water path and precipitation water content, and associated radiative fluxes. We also include the subgrid scale distribution of cloud and precipitation, and radiaitive quantities, which must be diagnosed by a model parameterization. The test-bed further includes meterological variables from the Modern Era Retrospective-analysis for Research and Applications (MERRA). MERRA variables provide the initialization and forcing datasets to run a parameterization in Single Column Model (SCM) mode. We show comparisons of an Eddy-Diffusivity/Mass-FLux (EDMF) parameterization coupled to micorphsycis and macrophysics packages run in SCM mode with observed clouds. Comparsions are performed regionally in areas of climatological subsidence as well stratified by dynamical and thermodynamical variables. Comparisons demonstrate the ability of the EDMF model to capture the observed transitions between subtropical stratocumulus and cumulus cloud regimes.

"Analysis of the multi-layered cloud radiative effects at the surface using A-train data"

NASA Astrophysics Data System (ADS)

Viudez-Mora, A.; Smith, W. L., Jr.; Kato, S.

2017-12-01

Clouds cover about 74% of the planet and they are an important part of the climate system and strongly influence the surface energy budget. The cloud vertical distribution has important implications in the atmospheric heating and cooling rates. Based on observations by active sensors in the A-train satellite constellation, CALIPSO [Winker et. al, 2010] and CloudSat [Stephens et. al, 2002], more than 1/3 of all clouds are multi-layered. Detection and retrieval of multi-layer cloud physical properties are needed in understanding their effects on the surface radiation budget. This study examines the sensitivity of surface irradiances to cloud properties derived from satellite sensors. Surface irradiances were computed in two different ways, one using cloud properties solely from MODerate resolution Imaging Spectroradiometer (MODIS), and the other using MODIS data supplemented with CALIPSO and CloudSat (hereafter CLCS) cloud vertical structure information [Kato et. al, 2010]. Results reveal that incorporating more precise and realistic cloud properties from CLCS into radiative transfer calculations yields improved estimates of cloud radiative effects (CRE) at the surface (CREsfc). The calculations using only MODIS cloud properties, comparisons of the computed CREsfc for 2-layer (2L) overcast CERES footprints, CLCS reduces the SW CRE by 1.5±26.7 Wm-2, increases the LW CRE by 4.1±12.7 Wm-2, and increases the net CREsfc by 0.9±46.7 Wm-2. In a subsequent analysis, we classified up to 6 different combinations of multi-layered clouds depending on the cloud top height as: High-high (HH), high-middle (HM), high-low (HL), middle-middle (MM), middle-low (ML) and low-low (LL). The 3 most frequent 2L cloud systems were: HL (56.1%), HM (22.3%) and HH (12.1%). For these cases, the computed CREsfc estimated using CLCS data presented the most significant differences when compared using only MODIS data. For example, the differences for the SW and Net CRE in the case HH was 12.3±47.3 Wm-2 and 16.0±48.45 Wm-2, respectively. For the case of HM, the LW CRE difference was -9.9±14.0 Wm-2. Kato, S., et al. (2010), J. Geophys. Res., 115. Stephens, G. L., et al. (2002), Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., (2010),Bull. Amer. Meteor. Soc., 91.

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hua; Zhang, Zhibo; Ma, Po-Lun

This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less

Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

NASA Astrophysics Data System (ADS)

Mascio, Jeana; Mace, Gerald G.

2017-02-01

Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

Estimating Precipitation Susceptibility in Warm Marine Clouds Using Multi-sensor Aerosol and Cloud Products from A-Train Satellites

NASA Astrophysics Data System (ADS)

Bai, H.; Gong, C.; Wang, M.; Zhang, Z.

2017-12-01

Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol-cloud interactions and constraining aerosol indirect effects. However, large discrepancies exist in the previous satellite estimates of precipitation susceptibility. In this paper, multi-sensor aerosol and cloud products, including those from CALIPSO, CloudSat, MODIS, and AMSR-E from June 2006 to April 2011 are analyzed to estimate precipitation susceptibility (including precipitation frequency susceptibility SPOP, precipitation intensity susceptibility SI, and precipitation rate susceptibility SR) in warm marine clouds. Our results show that SPOP demonstrates relatively robust features throughout independent LWP products and diverse rain products. In contrast, the behaviors of SI are more subject to LWP or rain products. Our results further show that SPOP strongly depends on atmospherics stability, with larger value under more stable environment. Precipitation susceptibility calculated with respect to cloud droplet number concentration (CDNC) is generally much larger than that estimated with respect to aerosol index (AI), which results from the weak dependency of CDNC on AI.

The evaluation and development of the Met Office Unified Model using surface and space borne radar.

NASA Astrophysics Data System (ADS)

Petch, J.

2012-12-01

The Met Office Unified Model is used for the prediction of weather and climate on time scales of hours through to centuries. Therefore, the parametrizations in that model need to work on weather and climate timescale, and with grid-lengths from hundres of meters through to several hundred kilometres. Focusing on the development of the cloud and radiation schemes I will discuss how we are using ground-based remote-sensing observations from Chilbolton (England) and a combination of Cloudsat and Calipso data to evaluate and improve the performance of the model. I will show how the prediction of the clouds has improved since the AR5 version of the model and how we have developed an improved cloud generator to rebresent the sub-grid variability of clouds for radiative transfer.

A-Train Data Depot: Integrating and Visualizing Atmospheric Measurements Along the A-Train Tracks

NASA Technical Reports Server (NTRS)

Kempler, Steven; Stephens, Graeme; Winker, Dave; Leptoukh, Greg; Reinke, Don; Smith, Peter

2006-01-01

The succession of US and international satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot, to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The A-Train Data Depot (ATDD) will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth s Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archwing for fast data access, and Cooperative Institute for Research in the Atmosphere (CRA) data co-registration tools. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be discussed. The project s resulting visualizations and analysis illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Observed linkages between the northern annular mode/North Atlantic Oscillation, cloud incidence, and cloud radiative forcing

NASA Astrophysics Data System (ADS)

Li, Ying; Thompson, David W. J.; Huang, Yi; Zhang, Minghong

2014-03-01

The signature of the northern annular mode/North Atlantic Oscillation (NAM/NAO) in the vertical and horizontal distribution of tropospheric cloudiness is investigated in CloudSat and CALIPSO data from June 2006 to April 2011. During the Northern Hemisphere winter, the positive polarity of the NAM/NAO is marked by increases in zonally averaged cloud incidence north of ~60°N, decreases between ~25 and 50°N, and increases in the subtropics. The tripolar-like anomalies in cloud incidence associated with the NAM/NAO are largest over the North Atlantic Ocean basin/Middle East and are physically consistent with the NAM/NAO-related anomalies in vertical motion. Importantly, the NAM/NAO-related anomalies in tropospheric cloud incidence lead to significant top of atmosphere cloud radiative forcing anomalies that are comparable in amplitude to those associated with the NAM/NAO-related temperature anomalies. The results provide observational evidence that the most prominent pattern of Northern Hemisphere climate variability is significantly linked to variations in cloud radiative forcing. Implications for two-way feedback between extratropical dynamics and cloud radiative forcing are discussed.

GCSS/WGNE Pacific Cross-section Intercomparison: Tropical and Subtropical Cloud Transitions

NASA Astrophysics Data System (ADS)

Teixeira, J.

2008-12-01

In this presentation I will discuss the role of the GEWEX Cloud Systems Study (GCSS) working groups in paving the way for substantial improvements in cloud parameterization in weather and climate models. The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI) is an extension of GCSS and is a different type of model evaluation where climate models are analyzed along a Pacific Ocean transect from California to the equator. This approach aims at complementing the more traditional efforts in GCSS by providing a simple framework for the evaluation of models that encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. Currently twenty four climate and weather prediction models are participating in GPCI. We will present results of the comparison between models and recent satellite data. In particular, we will explore in detail the potential of the Atmospheric Infrared Sounder (AIRS) and CloudSat data for the evaluation of the representation of clouds and convection in climate models.

A multi-sensor approach to the retrieval and model validation of global cloudiness

NASA Astrophysics Data System (ADS)

Miller, Steven D.

2000-11-01

The ephemeral clouds have represented a daunting challenge to the atmospheric modeling community from the very beginning. Our inability to resolve them by means of traditional passive sensors to the level of detail required for characterizing their complicated role in the climate feedback system has lead us to explore other resources at our disposal. This research seeks to illustrate and, where applicable, quantify the ways in which active (e.g., radar and lidar) remote sensing devices on existing and proposed platforms can serve to improve our current understanding of cloud and cloud processes in terms of (1)their role in the improvement of cloud property retrievals and (2)their application to the validation/development of clouds in numerical weather prediction models. A new retrieval technique which employs active sensors to constrain cloud boundaries in the vertical is shown to decrease the parameter uncertainties with respect to traditional passive methods in excess of 20% for effective particle radius, and 10-20% for optical depth when considering night-time retrievals of cirrus. These results are brought together with detailed cloud profile sampling from the Lidar In-space Technology Experiment (LITE) to conduct the first global-scale active sensor validation of ECMWF short-range forecasts. The comparisons display remarkable agreement in cloud spatial distribution. A weighted statistical analysis yields hit rates between 75-90%, threat scores 45-75%, probabilities of detection ~80%, and false alarm rates 10-45%. The results suggest that, given the level of realism displayed currently by the ECMWF prognostic cloud scheme forecasts, the reanalysis data may be considered as a new resource for global cloud information. A practical application of these findings has been outlined in the context of defining Cloud-Sat instrument requirements based on virtual orbital observations created from ECMWF global cloud distributions of liquid and ice water contents. This research gives cause for new hope in capturing the complex radiative, convective, and dynamical feedback mechanisms associated with clouds in the climate feedback system. Further, it appeals to the need for an improved collaborative rapport between the now largely disjoint modeling and measurement communities.

A new retrieval method for the ice water content of cirrus using data from the CloudSat and CALIPSO

NASA Astrophysics Data System (ADS)

Pan, Honglin; Bu, Lingbing; Kumar, K. Raghavendra; Gao, Haiyang; Huang, Xingyou; Zhang, Wentao

2017-08-01

The CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) are the members of satellite observation system of A-train to achieve the quasi-synchronization observation on the same orbit. With the help of active (CALIOP and CPR) and passive payloads from these two satellites, respectively, unprecedented detailed information of microphysical properties of ice cloud can be retrieved. The ice water content (IWC) is regarded as one of the most important microphysical characteristics of cirrus for its prominent role in cloud radiative forcing. In this paper, we proposed a new joint (Combination) retrieval method using the full advantages of different well established retrieval methods, namely the LIDAR method (for the region Lidar-only), the MWCR method (for the region Radar-only), and Wang method (for the region Lidar-Radar) proposed by Wang et al. (2002). In retrieval of cirrus IWC, empirical formulas of the exponential type were used for both thinner cirrus (detected by Lidar-only), thicker cirrus (detected by radar-only), and the part of cirrus detected by both, respectively. In the present study, the comparison of various methods verified that our proposed new joint method is more comprehensive, rational and reliable. Further, the retrieval information of cirrus is complete and accurate for the region that Lidar cannot penetrate and Radar is insensitive. On the whole, the retrieval results of IWC showed certain differences retrieved from the joint method, Ca&Cl, and ICARE which can be interpreted from the different hypothesis of microphysical characteristics and parameters used in the retrieval method. In addition, our joint method only uses the extinction coefficient and the radar reflectivity factor to calculate the IWC, which is simpler and reduces to some extent the accumulative error. In future studies, we will not only compare the value of IWC but also explore the detailed macrophysical and microphysical characteristics of cirrus.

Evaluation of Cloud Microphysics Simulated using a Meso-Scale Model Coupled with a Spectral Bin Microphysical Scheme through Comparison with Observation Data by Ship-Borne Doppler and Space-Borne W-Band Radars

NASA Technical Reports Server (NTRS)

Iguchi, T.; Nakajima, T.; Khain, A. P.; Saito, K.; Takemura, T.; Okamoto, H.; Nishizawa, T.; Tao, W.-K.

2012-01-01

Equivalent radar reflectivity factors (Ze) measured by W-band radars are directly compared with the corresponding values calculated from a three-dimensional non-hydrostatic meso-scale model coupled with a spectral-bin-microphysical (SBM) scheme for cloud. Three case studies are the objects of this research: one targets a part of ship-borne observation using 95 GHz Doppler radar over the Pacific Ocean near Japan in May 2001; other two are aimed at two short segments of space-borne observation by the cloud profiling radar on CloudSat in November 2006. The numerical weather prediction (NWP) simulations reproduce general features of vertical structures of Ze and Doppler velocity. A main problem in the reproducibility is an overestimation of Ze in ice cloud layers. A frequency analysis shows a strong correlation between ice water contents (IWC) and Ze in the simulation; this characteristic is similar to those shown in prior on-site studies. From comparing with the empirical correlations by the prior studies, the simulated Ze is overestimated than the corresponding values in the studies at the same IWC. Whereas the comparison of Doppler velocities suggests that large-size snowflakes are necessary for producing large velocities under the freezing level and hence rules out the possibility that an overestimation of snow size causes the overestimation of Ze. Based on the results of several sensitivity tests, we conclude that the source of the overestimation is a bias in the microphysical calculation of Ze or an overestimation of IWC. To identify the source of the problems needs further validation research with other follow-up observations.

NASA'S Earth Science Enterprise Embraces Active Laser Remote Sensing from Space

NASA Technical Reports Server (NTRS)

Luther, Michael R.; Paules, Granville E., III

1999-01-01

Several objectives of NASA's Earth Science Enterprise are accomplished, and in some cases, uniquely enabled by the advantages of earth-orbiting active lidar (laser radar) sensors. With lidar, the photons that provide the excitation illumination for the desired measurement are both controlled and well known. The controlled characteristics include when and where the illumination occurs, the wavelength, bandwidth, pulse length, and polarization. These advantages translate into high signal levels, excellent spatial resolution, and independence from time of day and the sun's position. As the lidar technology has rapidly matured, ESE scientific endeavors have begun to use lidar sensors over the last 10 years. Several more lidar sensors are approved for future flight. The applications include both altimetry (rangefinding) and profiling. Hybrid missions, such as the approved Geoscience Laser Altimeter System (GLAS) sensor to fly on the ICESat mission, will do both at the same time. Profiling applications encompass aerosol, cloud, wind, and molecular concentration measurements. Recent selection of the PICASSO Earth System Science Pathfinder mission and the complementary CLOUDSAT radar-based mission, both flying in formation with the EOS PM mission, will fully exploit the capabilities of multiple sensor systems to accomplish critical science needs requiring such profiling. To round out the briefing a review of past and planned ESE missions will be presented.

Spatial correlation of hydrometeor occurrence, reflectivity, and rain rate from CloudSat

NASA Astrophysics Data System (ADS)

Marchand, Roger

2012-03-01

This paper examines the along-track vertical and horizontal structure of hydrometeor occurrence, reflectivity, and column rain rate derived from CloudSat. The analysis assumes hydrometeors statistics in a given region are horizontally invariant, with the probability of hydrometeor co-occurrence obtained simply by determining the relative frequency at which hydrometeors can be found at two points (which may be at different altitudes and offset by a horizontal distance, Δx). A correlation function is introduced (gamma correlation) that normalizes hydrometeor co-occurrence values to the range of 1 to -1, with a value of 0 meaning uncorrelated in the usual sense. This correlation function is a generalization of the alpha overlap parameter that has been used in recent studies to describe the overlap between cloud (or hydrometeor) layers. Examples of joint histograms of reflectivity at two points are also examined. The analysis shows that the traditional linear (or Pearson) correlation coefficient provides a useful one-to-one measure of the strength of the relationship between hydrometeor reflectivity at two points in the horizontal (that is, two points at the same altitude). While also potentially useful in the vertical direction, the relationship between reflectivity values at different altitudes is not as well described by the linear correlation coefficient. The decrease in correlation of hydrometeor occurrence and reflectivity with horizontal distance, as well as precipitation occurrence and column rain rate, can be reasonably well fit with a simple two-parameter exponential model. In this paper, the North Pacific and tropical western Pacific are examined in detail, as is the zonal dependence.

Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

NASA Astrophysics Data System (ADS)

Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.

2013-12-01

Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.

Aerosol Direct Radiative Effects and Heating in the New Era of Active Satellite Observations

NASA Astrophysics Data System (ADS)

Matus, Alexander V.

Atmospheric aerosols impact the global energy budget by scattering and absorbing solar radiation. Despite their impacts, aerosols remain a significant source of uncertainty in our ability to predict future climate. Multi-sensor observations from the A-Train satellite constellation provide valuable observational constraints necessary to reduce uncertainties in model simulations of aerosol direct effects. This study will discuss recent efforts to quantify aerosol direct effects globally and regionally using CloudSat's radiative fluxes and heating rates product. Improving upon previous techniques, this approach leverages the capability of CloudSat and CALIPSO to retrieve vertically resolved estimates of cloud and aerosol properties critical for accurately evaluating the radiative impacts of aerosols. We estimate the global annual mean aerosol direct effect to be -1.9 +/- 0.6 W/m2, which is in better agreement with previously published estimates from global models than previous satellite-based estimates. Detailed comparisons against a fully coupled simulation of the Community Earth System Model, however, reveal that this agreement on the global annual mean masks large regional discrepancies between modeled and observed estimates of aerosol direct effects related to model biases in cloud cover. A low bias in stratocumulus cloud cover over the southeastern Pacific Ocean, for example, leads to an overestimate of the radiative effects of marine aerosols. Stratocumulus clouds over the southeastern Atlantic Ocean can enhance aerosol absorption by 50% allowing aerosol layers to remain self-lofted in an area of subsidence. Aerosol heating is found to peak at 0.6 +/- 0.3 K/day an altitude of 4 km in September when biomass burning reaches a maximum. Finally, the contributions of observed aerosols components are evaluated to estimate the direct radiative forcing of anthropogenic aerosols. Aerosol forcing is computed using satellite-based radiative kernels that describe the sensitivity of shortwave fluxes in response to aerosol optical depth. The direct radiative forcing is estimated to be -0.21 W/m2 with the largest contributions from pollution that is partially offset by a positive forcing from smoke aerosols. The results from these analyses provide new benchmarks on the global radiative effects of aerosols and offer new insights for improving future assessments.

3D Online Visualization and Synergy of NASA A-Train Data Using Google Earth

NASA Technical Reports Server (NTRS)

Chen, Aijun; Kempler, Steven; Leptoukh, Gregory; Smith, Peter

2010-01-01

This poster presentation reviews the use of Google Earth to assist in three dimensional online visualization of NASA Earth science and geospatial data. The NASA A-Train satellite constellation is a succession of seven sun-synchronous orbit satellites: (1) OCO-2 (Orbiting Carbon Observatory) (will launch in Feb. 2013), (2) GCOM-W1 (Global Change Observation Mission), (3) Aqua, (4) CloudSat, (5) CALIPSO (Cloud-Aerosol Lidar & Infrared Pathfinder Satellite Observations), (6) Glory, (7) Aura. The A-Train makes possible synergy of information from multiple resources, so more information about earth condition is obtained from the combined observations than would be possible from the sum of the observations taken independently

Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, Brian; Manipon, Gerald; Hua, Hook; Fetzer, Eric

2014-05-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map-reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in a hybrid Cloud (private eucalyptus & public Amazon). Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept and prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed "near" the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be perform

Impact of convection on stratospheric humidity and upper tropospheric clouds

NASA Astrophysics Data System (ADS)

Ueyama, R.; Schoeberl, M. R.; Jensen, E. J.; Pfister, L.; Avery, M. A.

2017-12-01

The role of convection on stratospheric water vapor and upper tropospheric cloud fraction is investigated using two sets of complementary transport and microphysical models driven by MERRA-2 and ERA-Interim meteorological analyses: (1) computationally efficient ensembles of forward trajectories with simplified cloud microphysics, and (2) one-dimensional simulations with detailed microphysics along back trajectories. Convective influence along the trajectories is diagnosed based on TRMM/GPM rainfall products and geostationary infrared satellite cloud-top measurements, with convective cloud-top height adjusted to match the CloudSat, CALIPSO, and CATS measurements. We evaluate and constrain the model results by comparison with satellite observations (e.g., Aura MLS, CALIPSO CALIOP) and high-altitude aircraft campaigns (e.g., ATTREX, POSIDON). Convection moistens the lower stratosphere by approximately 10-15% and increases the cloud fraction in the upper troposphere by 35-50%. Convective moistening is dominated by the saturating effect of parcels; convectively-lofted ice has a negligible impact on lower stratospheric humidity. We also find that the highest convective clouds have a disproportionately large impact on stratospheric water vapor because stratospheric relative humidity is low. Implications of these model results on the role of convection on present and future climate will be discussed.

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

NASA Astrophysics Data System (ADS)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

The 94 GHz Cloud Radar System on a NASA ER-2 Aircraft

NASA Technical Reports Server (NTRS)

Li, Lihua; Heymsfield, Gerald M.; Racette, Paul E.; Tian, Lin; Zenker, Ed

2003-01-01

The 94-GHz (W-band) Cloud Radar System (CRS) has been developed and flown on a NASA ER-2 high-altitude (20 km) aircraft. The CRS is a fully coherent, polarimeteric Doppler radar that is capable of detecting clouds and precipitation from the surface up to the aircraft altitude in the lower stratosphere. The radar is especially well suited for cirrus cloud studies because of its high sensitivity and fine spatial resolution. This paper describes the CRS motivation, instrument design, specifications, calibration, and preliminary data &om NASA s Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE) field campaign. The unique combination of CRS with other sensors on the ER-2 provides an unprecedented opportunity to study cloud radiative effects on the global energy budget. CRS observations are being used to improve our knowledge of atmospheric scattering and attenuation characteristics at 94 GHz, and to provide datasets for algorithm implementation and validation for the upcoming NASA CloudSat mission that will use a 94-GHz spaceborne cloud radar to provide the first direct global survey of the vertical structure of cloud systems.

Ice particle production in mid-level stratiform mixed-phase clouds observed with collocated A-Train measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Damao; Wang, Zhien; Kollias, Pavlos

In this study, collocated A-Train CloudSat radar and CALIPSO lidar measurements between 2006 and 2010 are analyzed to study primary ice particle production characteristics in mid-level stratiform mixed-phase clouds on a global scale. For similar clouds in terms of cloud top temperature and liquid water path, Northern Hemisphere latitude bands have layer-maximum radar reflectivity (ZL) that is ~1 to 8 dBZ larger than their counterparts in the Southern Hemisphere. The systematically larger ZL under similar cloud conditions suggests larger ice number concentrations in mid-level stratiform mixed-phase clouds over the Northern Hemisphere, which is possibly related to higher background aerosol loadings.more » Furthermore, we show that springtime northern mid- and high latitudes have ZL that is larger by up to 6 dBZ (a factor of 4 higher ice number concentration) than other seasons, which might be related to more dust events that provide effective ice nucleating particles. Our study suggests that aerosol-dependent ice number concentration parameterizations are required in climate models to improve mixed-phase cloud simulations, especially over the Northern Hemisphere.« less

Ice particle production in mid-level stratiform mixed-phase clouds observed with collocated A-Train measurements

DOE PAGES

Zhang, Damao; Wang, Zhien; Kollias, Pavlos; ...

2018-03-28

In this study, collocated A-Train CloudSat radar and CALIPSO lidar measurements between 2006 and 2010 are analyzed to study primary ice particle production characteristics in mid-level stratiform mixed-phase clouds on a global scale. For similar clouds in terms of cloud top temperature and liquid water path, Northern Hemisphere latitude bands have layer-maximum radar reflectivity (ZL) that is ~1 to 8 dBZ larger than their counterparts in the Southern Hemisphere. The systematically larger ZL under similar cloud conditions suggests larger ice number concentrations in mid-level stratiform mixed-phase clouds over the Northern Hemisphere, which is possibly related to higher background aerosol loadings.more » Furthermore, we show that springtime northern mid- and high latitudes have ZL that is larger by up to 6 dBZ (a factor of 4 higher ice number concentration) than other seasons, which might be related to more dust events that provide effective ice nucleating particles. Our study suggests that aerosol-dependent ice number concentration parameterizations are required in climate models to improve mixed-phase cloud simulations, especially over the Northern Hemisphere.« less

Multi-sensor quantification of aerosol-induced variability in warm clouds over eastern China

NASA Astrophysics Data System (ADS)

Wang, Fu; Guo, Jianping; Zhang, Jiahua; Huang, Jingfeng; Min, Min; Chen, Tianmeng; Liu, Huan; Deng, Minjun; Li, Xiaowen

2015-07-01

Aerosol-cloud (AC) interactions remain uncharacterized due to difficulties in obtaining accurate aerosol and cloud observations. In this study, we quantified the aerosol indirect effects (AIE) on warm clouds over Eastern China based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO, and CPR/CLOUDSAT between June 2006 and December 2010. The seasonality of aerosols from ground-based PM10 (aerosol particles with diameter of 10 μm or less) significantly differed from that estimated using MODIS aerosol optical depth (AOD). This result was supported by the lower level frequency profile of aerosol occurrence from CALIOP, indicative of the significant role of CALIOP in the AC interaction. To focus on warm clouds, cloud layers with base (top) altitudes above 7 (10) km were excluded. The combination of CALIOP and CPR was applied to determine the exact position of warm clouds relative to aerosols out of the following six scenarios in terms of AC mixing states: 1) aerosol only (AO); 2) cloud only (CO); 3) single aerosol layer-single cloud layer (SASC); 4) single aerosol layer-double cloud layers (SADC); 5) double aerosol layers - single cloud layer (DASC); and 6) others. The cases with vertical distance between aerosol and cloud layer less (more) than 100 m (700 m) were marked mixed (separated), and the rest as uncertain. Results showed that only 8.95% (7.53%) belonged to the mixed (separated and uncertain) state among all of the collocated AC overlapping cases, including SASC, SADC, and DASC. Under mixed conditions, the cloud droplet effective radius (CDR) decreased with increasing AOD at moderate aerosol loading (AOD<0.4), and then became saturated at an AOD of around 0.5, followed by an increase in CDR with increasing AOD, known as boomerang shape. Under separated conditions, no apparent changes in CDR with AOD were observed. We categorized the AC dataset into summer- and winter-season subsets to determine how the boomerang shape varied with season. The response of CDR to AOD in summer exhibited similar but much more deepened boomerang shape, as compared with the all year round case. In contrast, CDR in winter did not follow the boomerang shape for its continued decreasing with increasing AOD, even after the saturation zone (AOD around 0.5) of a cloud droplet.

Use of coincident radar and radiometer observations from GPM, ATMS, and CloudSat for global spaceborne snowfall observation assessment

NASA Astrophysics Data System (ADS)

Panegrossi, Giulia; Casella, Daniele; Sanò, Paolo; Cinzia Marra, Anna; Dietrich, Stefano; Johnson, Benjamin T.; Kulie, Mark S.

2017-04-01

Snowfall is the main component of the global precipitation amount at mid and high latitudes, and improvement of global spaceborne snowfall quantitative estimation is one of the main goals of the Global Precipitation Measurement (GPM) mission. Advancements in snowfall detection and retrieval accuracy at mid-high latitudes are expected from both instruments on board the GPM Core Observatory (GPM-CO): the GMI, the most advanced conical precipitation radiometer with respect to both channel assortment and spatial resolution; and the Dual-frequency Precipitation Radar (DPR) (Ka and Ku band). Moreover, snowfall monitoring is now possible by exploiting the high frequency channels (i.e. >100 GHz) available from most of the microwave radiometers in the GPM constellation providing good temporal coverage at mid-high latitudes (hourly or less). Among these, the Advanced Technology Microwave Sounder (ATMS) onboard Suomi-NPP is the most advanced polar-orbiting cross track radiometer with 5 channels in the 183 GHz oxygen absorption band. Finally, CloudSat carries the W-band Cloud Profiling Radar (CPR) that has collected data since its launch in 2006. While CPR was primarily designed as a cloud remote sensing mission, its high-latitude coverage (up to 82° latitude) and high radar sensitivity ( -28 dBZ) make it very suitable for snowfall-related research. In this work a number of global datasets made of coincident observations of snowfall producing clouds from the spaceborne radars DPR and CPR and from the most advanced radiometers available (GMI and ATMS) have been created and analyzed. We will show the results of a study where CPR is used to: 1) assess snowfall detection and estimate capabilities of DPR; 2) analyze snowfall signatures in the high frequency channels of the passive microwave radiometers in relation to fundamental environmental conditions. We have estimated that DPR misses a very large fraction of snowfall precipitation (more than 90% of the events and around 70% of the precipitating snowfall mass), mostly because of sensitivity limits of the DPR and secondly because of the effect of side lobe clutter. We will show that improved DPR detection capabilities (> 50%) of the snowfall mass can be achieved by optimally combining Ku-band and Ka-band measured reflectivity and exploiting the weak signals related to snowfall. ATMS-CPR, GMI-CPR, and GMI-DPR coincident observations have been analyzed in order to study the multichannel brightness temperature signal related to snowfall. The main results of this study show that the high frequency channels (and the 183 GHz band channels in particular) can be successfully used to identify snowfall, but results depend strongly on proper identification of surface background and proper estimation of integrated water vapor content. In this context a new algorithm for surface classification using primarily ATMS (and GMI) low frequency channels, and identifying different snow-covered land surfaces and ice or broken-ice over ocean, is proposed and will be presented.

Impact of Assimilated and Interactive Aerosol on Tropical Cyclogenesis

NASA Technical Reports Server (NTRS)

Reale, O.; Lau, K. M.; daSilva, A.; Matsui, T.

2014-01-01

This article investigates the impact 3 of Saharan dust on the development of tropical cyclones in the Atlantic. A global data assimilation and forecast system, the NASA GEOS-5, is used to assimilate all satellite and conventional data sets used operationally for numerical weather prediction. In addition, this new GEOS-5 version includes assimilation of aerosol optical depth from the Moderate Resolution Imaging Spectroradiometer (MODIS). The analysis so obtained comprises atmospheric quantities and a realistic 3-d aerosol and cloud distribution, consistent with the meteorology and validated against Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data. These improved analyses are used to initialize GEOS-5 forecasts, explicitly accounting for aerosol direct radiative effects and their impact on the atmospheric dynamics. Parallel simulations with/without aerosol radiative effects show that effects of dust on static stability increase with time, becoming highly significant after day 5 and producing an environment less favorable to tropical cyclogenesis.

Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E.

2013-05-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically "sharded" by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept/prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed "near" the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be performed in an efficient way, with the researcher paying only his own Cloud compute bill.; Figure 1 -- Architecture.

Large-Scale, Parallel, Multi-Sensor Atmospheric Data Fusion Using Cloud Computing

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

2013-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the 'A-Train' platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration analyses of important climate variables presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (MERRA), stratify the comparisons using a classification of the 'cloud scenes' from CloudSat, and repeat the entire analysis over 10 years of data. To efficiently assemble such datasets, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. However, these problems are Data Intensive computing so the data transfer times and storage costs (for caching) are key issues. SciReduce is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Figure 1 shows the architecture of the full computational system, with SciReduce at the core. Multi-year datasets are automatically 'sharded' by time and space across a cluster of nodes so that years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the cached input and intermediate datasets. We are using SciReduce to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a NASA MEASURES grant. We will present the architecture of SciReduce, describe the achieved 'clock time' speedups in fusing datasets on our own compute nodes and in the public Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. We will also present a concept/prototype for staging NASA's A-Train Atmospheric datasets (Levels 2 & 3) in the Amazon Cloud so that any number of compute jobs can be executed 'near' the multi-sensor data. Given such a system, multi-sensor climate studies over 10-20 years of data could be performed in an efficient way, with the researcher paying only his own Cloud compute bill. SciReduce Architecture

A CloudSat-CALIPSO View of Cloud and Precipitation Properties Across Cold Fronts over the Global Oceans

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

2015-01-01

The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the post frontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime post frontal precipitation.

The Atmospheric Infrared Sounder Version 6 Cloud Products

NASA Technical Reports Server (NTRS)

Kahn, B. H.; Irion, F. W.; Dang, V. T.; Manning, E. M.; Nasiri, S. L.; Naud, C. M.; Blaisdell, J. M.; Schreier, M. M..; Yue, Q.; Bowman, K. W.;

Measurements of Ocean Surface Scattering Using an Airborne 94-GHz Cloud Radar: Implication for Calibration of Airborne and Spaceborne W-band Radars

NASA Technical Reports Server (NTRS)

Li, Li-Hua; Heymsfield, Gerald M.; Tian, Lin; Racette, Paul E.

2004-01-01

Scattering properties of the Ocean surface have been widely used as a calibration reference for airborne and spaceborne microwave sensors. However, at millimeter-wave frequencies, the ocean surface backscattering mechanism is still not well understood, in part, due to the lack of experimental measurements. During the Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE), measurements of ocean surface backscattering were made using a 94-GHz (W-band) cloud radar onboard a NASA ER-2 high-altitude aircraft. The measurement set includes the normalized Ocean surface cross section over a range of the incidence angles under a variety of wind conditions. Analysis of the radar measurements shows good agreement with a quasi-specular scattering model. This unprecedented dataset enhances our knowledge about the Ocean surface scattering mechanism at 94 GHz. The results of this work support the proposition of using the Ocean surface as a calibration reference for airborne millimeter-wave cloud radars and for the ongoing NASA CloudSat mission, which will use a 94-GHz spaceborne cloud radar for global cloud measurements.

Sources and Variability of Aerosols and Aerosol-Cloud Interactions in the Arctic

NASA Astrophysics Data System (ADS)

Liu, H.; Zhang, B.; Taylor, P. C.; Moore, R.; Barahona, D.; Fairlie, T. D.; Chen, G.; Ham, S. H.; Kato, S.

2017-12-01

Arctic sea ice in recent decades has significantly declined. This requires understanding of the Arctic surface energy balance, of which clouds are a major driver. However, the mechanisms for the formation and evolution of clouds in the Arctic and the roles of aerosols therein are highly uncertain. Here we conduct data analysis and global model simulations to examine the sources and variability of aerosols and aerosol-cloud interactions in the Arctic. We use the MERRA-2 reanalysis data (2006-present) from the NASA Global Modeling and Assimilation Office (GMAO) to (1) quantify contributions of different aerosol types to the aerosol budget and aerosol optical depths in the Arctic, (2) ­examine aerosol distributions and variability and diagnose the major pathways for mid-latitude pollution transport to the Arctic, including their seasonal and interannual variability, and (3) characterize the distribution and variability of clouds (cloud optical depth, cloud fraction, cloud liquid and ice water path, cloud top height) in the Arctic. We compare MERRA-2 aerosol and cloud properties with those from C3M, a 3-D aerosol and cloud data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, CloudSat, CALIPSO, and MODIS) observations. We also conduct perturbation experiments using the NASA GEOS-5 chemistry-climate model (with GOCART aerosol module coupled with two-moment cloud microphysics), and discuss the roles of various types of aerosols in the formation and evolution of clouds in the Arctic.

3D Visualization of near real-time remote-sensing observation for hurricanes field campaign using Google Earth API

NASA Astrophysics Data System (ADS)

Li, P.; Turk, J.; Vu, Q.; Knosp, B.; Hristova-Veleva, S. M.; Lambrigtsen, B.; Poulsen, W. L.; Licata, S.

2009-12-01

NASA is planning a new field experiment, the Genesis and Rapid Intensification Processes (GRIP), in the summer of 2010 to better understand how tropical storms form and develop into major hurricanes. The DC-8 aircraft and the Global Hawk Unmanned Airborne System (UAS) will be deployed loaded with instruments for measurements including lightning, temperature, 3D wind, precipitation, liquid and ice water contents, aerosol and cloud profiles. During the field campaign, both the spaceborne and the airborne observations will be collected in real-time and integrated with the hurricane forecast models. This observation-model integration will help the campaign achieve its science goals by allowing team members to effectively plan the mission with current forecasts. To support the GRIP experiment, JPL developed a website for interactive visualization of all related remote-sensing observations in the GRIP’s geographical domain using the new Google Earth API. All the observations are collected in near real-time (NRT) with 2 to 5 hour latency. The observations include a 1KM blended Sea Surface Temperature (SST) map from GHRSST L2P products; 6-hour composite images of GOES IR; stability indices, temperature and vapor profiles from AIRS and AMSU-B; microwave brightness temperature and rain index maps from AMSR-E, SSMI and TRMM-TMI; ocean surface wind vectors, vorticity and divergence of the wind from QuikSCAT; the 3D precipitation structure from TRMM-PR and vertical profiles of cloud and precipitation from CloudSAT. All the NRT observations are collected from the data centers and science facilities at NASA and NOAA, subsetted, re-projected, and composited into hourly or daily data products depending on the frequency of the observation. The data products are then displayed on the 3D Google Earth plug-in at the JPL Tropical Cyclone Information System (TCIS) website. The data products offered by the TCIS in the Google Earth display include image overlays, wind vectors, clickable placemarks with vertical profiles for temperature and water vapors and curtain plots along the satellite tracks. Multiple products can be overlaid with individual adjustable opacity control. The time sequence visualization is supported by calendar and Google Earth time animation. The work described here was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

A-Train Data Depot (ATDD)

NASA Technical Reports Server (NTRS)

Smith, Peter M.; Kempler, Steven; Leptoukh, Gregory; Savtchenko, Andrey; Kummerer, Robert; Gopolan, Arun

2008-01-01

ATDD is a web based tool which provides collocated data and display products for a number of A-train instruments Cloudsat, Calipso, OMI, AIRS, MODIS, MLS, POLDER-3, and ECWMF model data. Products provided include Clouds, Aerosols, Water Vapor, Temperatures and trace gases. All input data is online and in HDF4, HDF5 format. Display products include curtain images, horizontal strips, line plot overlays, and GE kmz files. Sample products are shown for two type of events. Hurricane event, Norbert, Oct 8, 2008 and a dust storm event over the Arabian Sea, Nov 13-14, 2008.

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

Clouds vertical properties over the Northern Hemisphere monsoon regions from CloudSat-CALIPSO measurements

NASA Astrophysics Data System (ADS)

Das, Subrata Kumar; Golhait, R. B.; Uma, K. N.

2017-01-01

The CloudSat spaceborne radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-borne lidar measurements, provide opportunities to understand the intriguing behavior of the vertical structure of monsoon clouds. The combined CloudSat-CALIPSO data products have been used for the summer season (June-August) of 2006-2010 to present the statistics of cloud macrophysical (such as cloud occurrence frequency, distribution of cloud top and base heights, geometrical thickness and cloud types base on occurrence height), and microphysical (such as ice water content, ice water path, and ice effective radius) properties of the Northern Hemisphere (NH) monsoon region. The monsoon regions considered in this work are the North American (NAM), North African (NAF), Indian (IND), East Asian (EAS), and Western North Pacific (WNP). The total cloud fraction over the IND (mostly multiple-layered cloud) appeared to be more frequent as compared to the other monsoon regions. Three distinctive modes of cloud top height distribution are observed over all the monsoon regions. The high-level cloud fraction is comparatively high over the WNP and IND. The ice water content and ice water path over the IND are maximum compared to the other monsoon regions. We found that the ice water content has little variations over the NAM, NAF, IND, and WNP as compared to their macrophysical properties and thus give an impression that the regional differences in dynamics and thermodynamics properties primarily cause changes in the cloud frequency or coverage and only secondary in the cloud ice properties. The background atmospheric dynamics using wind and relative humidity from the ERA-Interim reanalysis data have also been investigated which helps in understanding the variability of the cloud properties over the different monsoon regions.

The CREW intercomparison of SEVIRI cloud retrievals

NASA Astrophysics Data System (ADS)

Hamann, U.; Walther, A.; Bennartz, R.; Thoss, A.; Meirink, J. M.; Roebeling, R.

2012-12-01

About 70% of the earth's surface is covered with clouds. They strongly influence the radiation balance and the water cycle of the earth. Hence the detailed monitoring of cloud properties - such as cloud fraction, cloud top temperature, cloud particle size, and cloud water path - is important to understand the role of clouds in the weather and the climate system. The remote sensing with passive sensors is an essential mean for the global observation of the cloud parameters, but is nevertheless challenging. This presentation focuses on the inter-comparison and validation of cloud physical properties retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard METEOSAT. For this study we use retrievals from 12 state-of-art algorithms (Eumetsat, KNMI, NASA Langley, NASA Goddard, University Madison/Wisconsin, DWD, DLR, Meteo-France, KMI, FU Berlin, UK MetOffice) that are made available through the common database of the CREW (Cloud Retrieval Evaluation Working) group. Cloud detection, cloud top phase, height, and temperature, as well as optical properties and water path are validated with CLOUDSAT, CALIPSO, MISR, and AMSR-E measurements. Special emphasis is given to challenging retrieval conditions. Semi-transparent clouds over the earth's surface or another cloud layer modify the measured brightness temperature and increase the retrieval uncertainty. The consideration of the three-dimensional radiative effects is especially important for large viewing angles and broken cloud fields. Aerosols might be misclassified as cloud and may increase the retrieval uncertainty, too. Due to the availability of the high number of sophisticated retrieval datasets, the advantages of different retrieval approaches can be examined and suggestions for future retrieval developments can be made. We like to thank Eumetsat for sponsoring the CREW project including this work.nstitutes that participate in the CREW project.

WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations

NASA Technical Reports Server (NTRS)

Shi, J. J.; Tao, W.-K.; Matsui, T.; Cifelli, R.; Huo, A.; Lang, S.; Tokay, A.; Peters-Lidard, C.; Jackson, G.; Rutledge, S.;

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Xing, Z.; Fetzer, E.

2008-12-01

NASA's Earth Observing System (EOS) is the world's most ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the A-Train platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the cloud scenes from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time matchups between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, and assemble merged datasets for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, and perform pairwise instrument matchups for A-Train datasets. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

Assembling Large, Multi-Sensor Climate Datasets Using the SciFlo Grid Workflow System

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Xing, Z.; Fetzer, E.

2009-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To meet these large-scale challenges, we are utilizing a Grid computing and dataflow framework, named SciFlo, in which we are deploying a set of versatile and reusable operators for data query, access, subsetting, co-registration, mining, fusion, and advanced statistical analysis. SciFlo is a semantically-enabled ("smart") Grid Workflow system that ties together a peer-to-peer network of computers into an efficient engine for distributed computation. The SciFlo workflow engine enables scientists to do multi-instrument Earth Science by assembling remotely-invokable Web Services (SOAP or http GET URLs), native executables, command-line scripts, and Python codes into a distributed computing flow. A scientist visually authors the graph of operation in the VizFlow GUI, or uses a text editor to modify the simple XML workflow documents. The SciFlo client & server engines optimize the execution of such distributed workflows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The engine transparently moves data to the operators, and moves operators to the data (on the dozen trusted SciFlo nodes). SciFlo also deploys a variety of Data Grid services to: query datasets in space and time, locate & retrieve on-line data granules, provide on-the-fly variable and spatial subsetting, perform pairwise instrument matchups for A-Train datasets, and compute fused products. These services are combined into efficient workflows to assemble the desired large-scale, merged climate datasets. SciFlo is currently being applied in several large climate studies: comparisons of aerosol optical depth between MODIS, MISR, AERONET ground network, and U. Michigan's IMPACT aerosol transport model; characterization of long-term biases in microwave and infrared instruments (AIRS, MLS) by comparisons to GPS temperature retrievals accurate to 0.1 degrees Kelvin; and construction of a decade-long, multi-sensor water vapor climatology stratified by classified cloud scene by bringing together datasets from AIRS/AMSU, AMSR-E, MLS, MODIS, and CloudSat (NASA MEASUREs grant, Fetzer PI). The presentation will discuss the SciFlo technologies, their application in these distributed workflows, and the many challenges encountered in assembling and analyzing these massive datasets.

MODIS Microphysical Regimes for Examining Apparent Aerosol Effects on Clouds and Precipitation

NASA Astrophysics Data System (ADS)

Oreopoulos, L.; Cho, N.; Lee, D.; Kato, S.; Lebsock, M. D.; Yuan, T.; Huffman, G. J.

2014-12-01

We use a 10-year record of MODIS Terra and Aqua Level-3 joint histograms of cloud optical thickness (COT) and cloud effective radius (CER) to derive so-called cloud microphysical regimes by means of clustering analysis. The regimes reveal the dominant modes of COT and CER co-variations around the globe for both liquid and ice phases. The clustering analysis is capable of separating regimes so that each is dominated by one of the two water phases and can be associated with previously derived "dynamical" regimes. The microphysical regimes serve as an appropriate basis to study possible effects of aerosols on cloud microphysical changes and precipitation. To this end, we employ MODIS aerosol loading measurements either in terms of aerosol index or aerosol optical depth and spatiotemporally matched precipitation (from either GPCP, TRMM or CloudSat) to examine intra-regime variability, regime transitions from morning (Terra) to afternoon (Aqua), and regime precipitation characteristics for locally low, average, and high aerosol loadings. Breakdowns by ocean/land and geographical zone (e.g., tropics vs. midlatitudes) are essential for physical interpretation of the results. The analysis conducted so far reveals notable differences in apparent characteristics of low- and high-cloud dominated microphysical regimes when in different aerosol environments. The presentation will attempt to examine whether the picture painted by our work is consistent with prevailing expectations, rooted to either modeling or prior observational studies, on how clouds and precipitation respond to distinct aerosol environments.

Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

NASA Astrophysics Data System (ADS)

Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

2017-04-01

The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

Estimating precipitation susceptibility in warm marine clouds using multi-sensor aerosol and cloud products from A-Train satellites

NASA Astrophysics Data System (ADS)

Bai, Heming; Gong, Cheng; Wang, Minghuai; Zhang, Zhibo; L'Ecuyer, Tristan

2018-02-01

Precipitation susceptibility to aerosol perturbation plays a key role in understanding aerosol-cloud interactions and constraining aerosol indirect effects. However, large discrepancies exist in the previous satellite estimates of precipitation susceptibility. In this paper, multi-sensor aerosol and cloud products, including those from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) from June 2006 to April 2011 are analyzed to estimate precipitation frequency susceptibility SPOP, precipitation intensity susceptibility SI, and precipitation rate susceptibility SR in warm marine clouds. We find that SPOP strongly depends on atmospheric stability, with larger values under more stable environments. Our results show that precipitation susceptibility for drizzle (with a -15 dBZ rainfall threshold) is significantly different than that for rain (with a 0 dBZ rainfall threshold). Onset of drizzle is not as readily suppressed in warm clouds as rainfall while precipitation intensity susceptibility is generally smaller for rain than for drizzle. We find that SPOP derived with respect to aerosol index (AI) is about one-third of SPOP derived with respect to cloud droplet number concentration (CDNC). Overall, SPOP demonstrates relatively robust features throughout independent liquid water path (LWP) products and diverse rain products. In contrast, the behaviors of SI and SR are subject to LWP or rain products used to derive them. Recommendations are further made for how to better use these metrics to quantify aerosol-cloud-precipitation interactions in observations and models.

The MJO Transition from Shallow to Deep Convection in CloudSat/CALIPSO Data and GISS GCM Simulations

NASA Technical Reports Server (NTRS)

DelGenio, Anthony G.; Chen, Yonghua; Kim, Daehyun; Yao, Mao-Sung

2013-01-01

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden-Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10MJO events show the following anticipatedMJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for EarthObserving System (EOS) (AMSR-E) columnwater vapor (CWV) increases by;5 mmduring the shallow- deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between;46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow-deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV. 1.

Clouds enhance Greenland ice sheet mass loss

NASA Astrophysics Data System (ADS)

Van Tricht, Kristof; Gorodetskaya, Irina V.; L'Ecuyer, Tristan; Lenaerts, Jan T. M.; Lhermitte, Stef; Noel, Brice; Turner, David D.; van den Broeke, Michiel R.; van Lipzig, Nicole P. M.

2015-04-01

Clouds have a profound influence on both the Arctic and global climate, while they still represent one of the key uncertainties in climate models, limiting the fidelity of future climate projections. The potentially important role of thin liquid-containing clouds over Greenland in enhancing ice sheet melt has recently gained interest, yet current research is spatially and temporally limited, focusing on particular events, and their large scale impact on the surface mass balance remains unknown. We used a combination of satellite remote sensing (CloudSat - CALIPSO), ground-based observations and climate model (RACMO) data to show that liquid-containing clouds warm the Greenland ice sheet 94% of the time. High surface reflectivity (albedo) for shortwave radiation reduces the cloud shortwave cooling effect on the absorbed fluxes, while not influencing the absorption of longwave radiation. Cloud warming over the ice sheet therefore dominates year-round. Only when albedo values drop below ~0.6 in the coastal areas during summer, the cooling effect starts to overcome the warming effect. The year-round excess of energy due to the presence of liquid-containing clouds has an extensive influence on the mass balance of the ice sheet. Simulations using the SNOWPACK snow model showed not only a strong influence of these liquid-containing clouds on melt increase, but also on the increased sublimation mass loss. Simulations with the Community Earth System Climate Model for the end of the 21st century (2080-2099) show that Greenland clouds contain more liquid water path and less ice water path. This implies that cloud radiative forcing will be further enhanced in the future. Our results therefore urge the need for improving cloud microphysics in climate models, to improve future projections of ice sheet mass balance and global sea level rise.

The EarthCARE Simulator (Invited)

NASA Astrophysics Data System (ADS)

Donovan, D. P.; van Zadellhoff, G.; Lajas, D.; Eisinger, M.; Franco, R.

2009-12-01

In recent years, the value of multisensor remote sensing techniques applied to cloud, aerosol, radiation and precipitation studies has become clear. For example, combinations of instruments including lidars and/or radars have proved very useful for profile retrievals of cloud macrophysical and microphysical properties. This is amply illustrated by various results from the ARM (and similar) sites as well as from results derived using the Cloudsat/CALIPSO/A-train combination of instruments. The Earth Clouds Aerosol and Radiation Explorer (EarthCARE) mission is a combined ESA/JAXA mission scheduled for launch in 2013 and has been designed with sensor-synergy playing a driving role in its scientific applications. The EarthCARE mission consists of a cloud profiling Doppler radar, a high-spectral-resolution lidar, a cloud/aerosol imager and a three-view broadband radiometer. As part of the mission development process, a detailed end-to-end multisensor simulation system has been developed. The EarthCARE Simulator (ECSIM) consists of a modular general framework populated by various models. The models within ECSIM are grouped according to the following scheme: 1) Scene creation models (3D atmospheric scene definition) 2) Orbit models (orbit and orientation of the platform as it overflies the scene) 3) Forward models (calculate the signal impinging on the telescope/antenna of the instrument(s) in question) 4) Instrument models (calculate the instrument response to the signals calculated by the Forward models) 5) Retrieval models (invert the instrument signals to recover relevant geophysical information) Within the default ECSIM models crude instrument specific parameterizations (i.e. empirically based Z vs IWC relationships) are avoided. Instead, the radiative transfer forward models are kept as separate as possible from the instrument models. In order to accomplish this, the atmospheric scenes are specified in high detail (i.e. bin resolved cloud size distribution are stored) and the relevant wavelength dependent optical properties are stored in a separate database. This helps insure that all the instruments involved in the simulation are treated in a consistent fashion and that the physical relationships between the various measurements are realistically captured (something that using instrument specific parameterizations relationships can not guarantee). As a consequence, ECSIM's modular structure makes it straightforward to add new instruments (thus expanding ECSIM beyond the EarthCARE instrument suite) and also makes ECSIM well-suited for physically based retrieval algorithm development. In this talk, we will introduce ECSIM and emphasize the philosophy behind its design. We will also give a brief overview on the various default models. Finally, we will present several examples of how ECSIM can and is being used for purposes ranging from general radiative transfer calculations to instrument performance estimation and synergistic algorithm development and characterization.

Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds

DOE PAGES

Kuo, Chia-Pang; Yang, Ping; Huang, Xianglei; ...

2017-12-13

General circulation models (GCMs) are extensively used to estimate the influence of clouds on the global energy budget and other aspects of climate. Because radiative transfer computations involved in GCMs are costly, it is typical to consider only absorption but not scattering by clouds in longwave (LW) spectral bands. In this study, the flux and heating rate biases due to neglecting the scattering of LW radiation by clouds are quantified by using advanced cloud optical property models, and satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth's Radiant Energy System (CERES), and Moderatemore » Resolution Imaging Spectrometer (MODIS) merged products (CCCM). From the products, information about the atmosphere and clouds (microphysical and buck optical properties, and top and base heights) is used to simulate fluxes and heating rates. One-year global simulations for 2010 show that the LW scattering decreases top-of-atmosphere (TOA) upward flux and increases surface downward flux by 2.6 and 1.2 W/m 2, respectively, or approximately 10% and 5% of the TOA and surface LW cloud radiative effect, respectively. Regional TOA upward flux biases are as much as 5% of global averaged outgoing longwave radiation (OLR). LW scattering causes approximately 0.018 K/d cooling at the tropopause and about 0.028 K/d heating at the surface. Furthermore, over 40% of the total OLR bias for ice clouds is observed in 350–500 cm -1. Overall, the radiative effects associated with neglecting LW scattering are comparable to the counterpart due to doubling atmospheric CO 2 under clear-sky conditions.« less

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Protat, Alain; Young, Stuart; McFarlane, Sally A.

2014-02-01

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar-lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (due to limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar - Cloud-Aerosol Lidar withmore » Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2 km height, due to instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar-lidar instruments and RT calculations are also found above 10 km (up to 0.35 Kday-1 for the shortwave and 0.8 Kday-1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud-radiation interactions in large-scale models and limitations of each set of instrumentation should be considered when interpreting model-observations differences.« less

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

NASA Astrophysics Data System (ADS)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

The NASA CloudSat/GPM Light Precipitation Validation Experiment (LPVEx)

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; L'Ecuyer, Tristan; Moisseev, Dmitri

2011-01-01

Ground-based measurements of cool-season precipitation at mid and high latitudes (e.g., above 45 deg N/S) suggest that a significant fraction of the total precipitation volume falls in the form of light rain, i.e., at rates less than or equal to a few mm/h. These cool-season light rainfall events often originate in situations of a low-altitude (e.g., lower than 2 km) melting level and pose a significant challenge to the fidelity of all satellite-based precipitation measurements, especially those relying on the use of multifrequency passive microwave (PMW) radiometers. As a result, significant disagreements exist between satellite estimates of rainfall accumulation poleward of 45 deg. Ongoing efforts to develop, improve, and ultimately evaluate physically-based algorithms designed to detect and accurately quantify high latitude rainfall, however, suffer from a general lack of detailed, observationally-based ground validation datasets. These datasets serve as a physically consistent framework from which to test and refine algorithm assumptions, and as a means to build the library of algorithm retrieval databases in higher latitude cold-season light precipitation regimes. These databases are especially relevant to NASA's CloudSat and Global Precipitation Measurement (GPM) ground validation programs that are collecting high-latitude precipitation measurements in meteorological systems associated with frequent coolseason light precipitation events. In an effort to improve the inventory of cool-season high-latitude light precipitation databases and advance the physical process assumptions made in satellite-based precipitation retrieval algorithm development, the CloudSat and GPM mission ground validation programs collaborated with the Finnish Meteorological Institute (FMI), the University of Helsinki (UH), and Environment Canada (EC) to conduct the Light Precipitation Validation Experiment (LPVEx). The LPVEx field campaign was designed to make detailed measurements of cool-season light precipitation by leveraging existing infrastructure in the Helsinki Precipitation Testbed. LPVEx was conducted during the months of September--October, 2010 and featured coordinated ground and airborne remote sensing components designed to observe and quantify the precipitation physics associated with light rain in low-altitude melting layer environments over the Gulf of Finland and neighboring land mass surrounding Helsinki, Finland.

The Influence of Sea Ice on Arctic Low Cloud Properties and Radiative Effects

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.

2015-01-01

The Arctic is one of the most climatically sensitive regions of the Earth. Climate models robustly project the Arctic to warm 2-3 times faster than the global mean surface temperature, termed polar warming amplification (PWA), but also display the widest range of surface temperature projections in this region. The response of the Arctic to increased CO2 modulates the response in tropical and extra-tropical regions through teleconnections in the atmospheric circulation. An increased frequency of extreme precipitation events in the northern mid-latitudes, for example, has been linked to the change in the background equator-to-pole temperature gradient implied by PWA. Understanding the Arctic climate system is therefore important for predicting global climate change. The ice albedo feedback is the primary mechanism driving PWA, however cloud and dynamical feedbacks significantly contribute. These feedback mechanisms, however, do not operate independently. How do clouds respond to variations in sea ice? This critical question is addressed by combining sea ice, cloud, and radiation observations from satellites, including CERES, CloudSAT, CALIPSO, MODIS, and microwave radiometers, to investigate sea ice-cloud interactions at the interannual timescale in the Arctic. Cloud characteristics are strongly tied to the atmospheric dynamic and thermodynamic state. Therefore, the sensitivity of Arctic cloud characteristics, vertical distribution and optical properties, to sea ice anomalies is computed within atmospheric dynamic and thermodynamic regimes. Results indicate that the cloud response to changes in sea ice concentration differs significantly between atmospheric state regimes. This suggests that (1) the atmospheric dynamic and thermodynamic characteristics and (2) the characteristics of the marginal ice zone are important for determining the seasonal forcing by cloud on sea ice variability.

Using the C3M Satellite Data Product to Evaluate and Constrain the Cloud Fields in the HadGEM3-UKCA Model with an Aim to Enhance Understanding of the Effects of Clouds on Atmospheric Composition via Photolysis

NASA Astrophysics Data System (ADS)

Varma, S.; Voulgarakis, A.; Liu, H.; Crawford, J. H.; Zhang, B.

2017-12-01

What drives the variability of trace gases in the troposphere is not well understood, as is the role of clouds in modulating this variability via radiative, transport, deposition, heterogeneous chemistry, and lightning effects that are associated with them. Accurately simulating tropospheric composition and its variability is of utmost importance as both could have a significant effect on the region's temperature and circulation, as well as on surface climate and the amount of UV radiation in the troposphere. In this presentation, we will examine how clouds can influence tropospheric and lower stratospheric composition through modifying solar radiation leading to changes in the local actinic flux and subsequently to photolysis, a key driver of chemistry. We will utilize C3M (a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center to evaluate the cloud fields and their vertical distribution in the HadGEM3-UKCA model developed by the Natural Environment Research Council (NERC, UK) and the Met Office. This evaluation will involve 1) comparing the effective cloud optical depth (ECOD) as calculated from C3M and the model using the approximate random overlap method, 2) applying 3-D scaling factors from C3M to the model's ECOD and analyzing the changes this makes to the model's cloud fields, and 3) running the scaled model and analyzing the impacts of this cloud field adjustment on the model's estimates of photolysis rates and key tropospheric oxidants such as ozone and OH.

Diagnosing Warm Frontal Cloud Formation in a GCM: A Novel Approach Using Conditional Subsetting

NASA Technical Reports Server (NTRS)

Booth, James F.; Naud, Catherine M.; DelGenio, Anthony D.

2013-01-01

This study analyzes characteristics of clouds and vertical motion across extratropical cyclone warm fronts in the NASA Goddard Institute for Space Studies general circulation model. The validity of the modeled clouds is assessed using a combination of satellite observations from CloudSat, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. The analysis focuses on developing cyclones, to test the model's ability to generate their initial structure. To begin, the extratropical cyclones and their warm fronts are objectively identified and cyclone-local fields are mapped into a vertical transect centered on the surface warm front. To further isolate specific physics, the cyclones are separated using conditional subsetting based on additional cyclone-local variables, and the differences between the subset means are analyzed. Conditional subsets are created based on 1) the transect clouds and 2) vertical motion; 3) the strength of the temperature gradient along the warm front, as well as the storm-local 4) wind speed and 5) precipitable water (PW). The analysis shows that the model does not generate enough frontal cloud, especially at low altitude. The subsetting results reveal that, compared to the observations, the model exhibits a decoupling between cloud formation at high and low altitudes across warm fronts and a weak sensitivity to moisture. These issues are caused in part by the parameterized convection and assumptions in the stratiform cloud scheme that are valid in the subtropics. On the other hand, the model generates proper covariability of low-altitude vertical motion and cloud at the warm front and a joint dependence of cloudiness on wind and PW.

The Earthcare Cloud Profiling Radar, its PFM development status (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nakatsuka, Hirotaka; Tomita, Eichi; Aida, Yoshihisa; Seki, Yoshihiro; Okada, Kazuyuki; Maruyama, Kenta; Ishii, Yasuyuki; Tomiyama, Nobuhiro; Ohno, Yuichi; Horie, Hiroaki; Sato, Kenji

2016-10-01

The Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is joint mission between Europe and Japan for the launch year of 2018. Mission objective is to improve scientific understanding of cloud-aerosol-radiation interactions that is one of the biggest uncertain factors for numerical climate and weather predictions. The EarthCARE spacecraft equips four instruments such as an ultra violet lidar (ATLID), a cloud profiling radar (CPR), a broadband radiometer (BBR), and a multi-spectral imager (MSI) and perform complete synergy observation to observe aerosols, clouds and their interactions simultaneously from the orbit. Japan Aerospace Exploration Agency (JAXA) is responsible for development of the CPR in this EarthCARE mission and the CPR will be the first space-borne W-band Doppler radar. The CPR is defined with minimum radar sensitivity of -35dBz (6dB better than current space-borne cloud radar, i.e. CloudSat, NASA), radiometric accuracy of 2.7 dB, and Doppler velocity measurement accuracy of less than 1.3 m/s. These specifications require highly accurate pointing technique in orbit and high power source with large antenna dish. JAXA and National Institute of Information and Communications Technology (NICT) have been jointly developed this CPR to meet these strict requirements so far and then achieved the development such as new CFRP flex-core structure, long life extended interaction klystron, low loss quasi optical feed technique, and so on. Through these development successes, CPR development phase has been progressed to critical design phase. In addition, new ground calibration technique is also being progressed for launch of EarthCARE/CPR. The unique feature of EarthCARE CPR is vertical Doppler velocity measurement capability. Vertical Doppler velocity measurement is very attractive function from the science point of view, because vertical motions of cloud particles are related with cloud microphysics and dynamics. However, from engineering point of view, Doppler measurement from satellite is quite challenging Technology. In order to maintain and ensure the CPR performance, several types of calibration data will be obtained by CPR. Overall performance of CPR is checked by Active Radar Calibrator (ARC) equipped on the ground (CPR in External Calibration mode). ARC is used to check the CPR transmitter performance (ARC in receiver mode) and receiver performance (ARC in transmitter mode) as well as overall performance (ARC in transponder mode with delay to avoid the contamination with ground echo). In Japan, the instrument industrial Critical Design Review of the CPR was completed in 2013 and it was also complemented by an Interface and Mission aspects CPR CDR, involving ESA and the EarthCARE Prime, that was completed successfully in 2015. The CPR Proto-Flight Model is currently being tested with almost completion of Proto-Flight Model integration. After handed-over to ESA planned for the beginning of 2017, the CPR will be installed onto the EarthCARE satellite with the other instruments. After that the CPR will be tested, transported to Guiana Space Center in Kourou, French Guiana and launched by a Soyuz launcher in 2018. This presentation will show the summary of the latest CPR design and CPR PFM testing status.

Satellite Data Analysis of Impact of Anthropogenic Air Pollution on Ice Clouds

NASA Astrophysics Data System (ADS)

Gu, Y.; Liou, K. N.; Zhao, B.; Jiang, J. H.; Su, H.

2017-12-01

Despite numerous studies about the impact of aerosols on ice clouds, the role of anthropogenic aerosols in ice processes, especially over pollution regions, remains unclear and controversial, and has not been considered in a regional model. The objective of this study is to improve our understanding of the ice process associated with anthropogenic aerosols, and provide a comprehensive assessment of the contribution of anthropogenic aerosols to ice nucleation, ice cloud properties, and the consequent regional radiative forcing. As the first attempt, we evaluate the effects of different aerosol types (mineral dust, air pollution, polluted dust, and smoke) on ice cloud micro- and macro-physical properties using satellite data. We identify cases with collocated CloudSat, CALIPSO, and Aqua observations of vertically resolved aerosol and cloud properties, and process these observations into the same spatial resolution. The CALIPSO's aerosol classification algorithm determines aerosol layers as one of six defined aerosol types by taking into account the lidar depolarization ratio, integrated attenuated backscattering, surface type, and layer elevation. We categorize the cases identified above according to aerosol types, collect relevant aerosol and ice cloud variables, and determine the correlation between column/layer AOD and ice cloud properties for each aerosol type. Specifically, we investigate the correlation between aerosol loading (indicated by the column AOD and layer AOD) and ice cloud microphysical properties (ice water content, ice crystal number concentration, and ice crystal effective radius) and macro-physical properties (ice water path, ice cloud fraction, cloud top temperature, and cloud thickness). By comparing the responses of ice cloud properties to aerosol loadings for different aerosol types, we infer the role of different aerosol types in ice nucleation and the evolution of ice clouds. Our preliminary study shows that changes in the ice crystal effective radius with respect to AOD over Eastern Asia for the aerosol types of polluted continental and mineral dust look similar, implying that both air pollution and mineral dust could affect the microphysical properties of ice clouds.

Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

2016-05-01

Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

The potential influence of multiple scattering on longwave flux and heating rate simulations with clouds

NASA Astrophysics Data System (ADS)

Kuo, C. P.; Yang, P.; Huang, X.; Feldman, D.; Flanner, M.; Kuo, C.; Mlawer, E. J.

2017-12-01

Clouds, which cover approximately 67% of the globe, serve as one of the major modulators in adjusting radiative energy on the Earth. Since rigorous radiative transfer computations including multiple scattering are costly, only absorption is considered in the longwave spectral bands in the radiation sub-models of the general circulation models (GCMs). Quantification of the effect of ignoring longwave scattering for flux and heating rate simulations is performed by using the GCM version of the Longwave Rapid Radiative Transfer Model (RRTMG_LW) with an implementation with the 16-stream Discrete Ordinates Radiative Transfer (DISORT) Program for a Multi-Layered Plane-Parallel Medium in conjunction with the 2010 CCCM products that merge satellite observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the CloudSat, the Clouds and the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectrometer (MODIS). One-year global simulations show that neglecting longwave scattering overestimates upward flux at the top of the atmosphere (TOA) and underestimates downward flux at the surface by approximately 2.63 and 1.15 W/m2, respectively. Furthermore, when longwave scattering is included in the simulations, the tropopause is cooled by approximately 0.018 K/day and the surface is heated by approximately 0.028 K/day. As a result, the radiative effects of ignoring longwave scattering and doubling CO2 are comparable in magnitude.

A-Train Education Activities: Partnerships to Engage Citizens with Atmospheric Science

NASA Astrophysics Data System (ADS)

Ellis, T. D.; Taylor, J.; Chambers, L. H.; Graham, S.; Butcher, G. J.

2016-12-01

Since the launch of Aqua in 2002, the A-Train satellites have been at the forefront of observing Earth's atmosphere using the wide variety of instruments on the spacecraft in the formation. Similarly, the A-Train missions have also taken a variety of perspectives on engaging the general public with NASA science. These approaches have included a range of formal education partnerships featuring the GLOBE program (including a cloud observation network through CloudSat, several initiatives to understand and measure aerosols, and development of a new elementary story book), unique citizen-science activities such as Students' Cloud Observations On Line (S'COOL), connections with the PBS Kids SciGirls program, and much more. An education component was also featured at the first A-Train symposium in New Orleans, engaging local educators to learn about the many education resources available from the A-Train missions. Increasingly, the mission education teams have been working together to drive home thematic science content, such as the roles of clouds in our climate system and regular measurements of Earth's radiant energy balance. This paper describes the evolution of A-Train education efforts over the past decade, highlights key achievements, and presents information on new initiatives to continue to engage the public with A-Train science.

Analysis of geostationary satellite-derived cloud parameters associated with environments with high ice water content

NASA Astrophysics Data System (ADS)

de Laat, Adrianus; Defer, Eric; Delanoë, Julien; Dezitter, Fabien; Gounou, Amanda; Grandin, Alice; Guignard, Anthony; Fokke Meirink, Jan; Moisselin, Jean-Marc; Parol, Frédéric

2017-04-01

We present an evaluation of the ability of passive broadband geostationary satellite measurements to detect high ice water content (IWC > 1 g m-3) as part of the European High Altitude Ice Crystals (HAIC) project for detection of upper-atmospheric high IWC, which can be a hazard for aviation. We developed a high IWC mask based on measurements of cloud properties using the Cloud Physical Properties (CPP) algorithm applied to the geostationary Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Evaluation of the high IWC mask with satellite measurements of active remote sensors of cloud properties (CLOUDSAT/CALIPSO combined in the DARDAR (raDAR-liDAR) product) reveals that the high IWC mask is capable of detecting high IWC values > 1 g m-3 in the DARDAR profiles with a probability of detection of 60-80 %. The best CPP predictors of high IWC were the condensed water path, cloud optical thickness, cloud phase, and cloud top height. The evaluation of the high IWC mask against DARDAR provided indications that the MSG-CPP high IWC mask is more sensitive to cloud ice or cloud water in the upper part of the cloud, which is relevant for aviation purposes. Biases in the CPP results were also identified, in particular a solar zenith angle (SZA) dependence that reduces the performance of the high IWC mask for SZAs > 60°. Verification statistics show that for the detection of high IWC a trade-off has to be made between better detection of high IWC scenes and more false detections, i.e., scenes identified by the high IWC mask that do not contain IWC > 1 g m-3. However, the large majority of these detections still contain IWC values between 0.1 and 1 g m-3. Comparison of the high IWC mask against results from the Rapidly Developing Thunderstorm (RDT) algorithm applied to the same geostationary SEVIRI data showed that there are similarities and differences with the high IWC mask: the RDT algorithm is very capable of detecting young/new convective cells and areas, whereas the high IWC mask appears to be better capable of detecting more mature and ageing convection as well as cirrus remnants. The lack of detailed understanding of what causes aviation hazards related to high IWC, as well as the lack of clearly defined user requirements, hampers further tuning of the high IWC mask. Future evaluation of the high IWC mask against field campaign data, as well as obtaining user feedback and user requirements from the aviation industry, should provide more information on the performance of the MSG-CPP high IWC mask and contribute to improving the practical use of the high IWC mask.

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

NASA Technical Reports Server (NTRS)

Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.;

The Global Character of the Flux of Downward Longwave Radiation

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.; Wild, Martin; Stackhouse, Paul W., Jr.; L'Ecuyer, Tristan; Kato, Seiji; Henderson, David S.

2012-01-01

Four different types of estimates of the surface downwelling longwave radiative flux (DLR) are reviewed. One group of estimates synthesizes global cloud, aerosol, and other information in a radiation model that is used to calculate fluxes. Because these synthesis fluxes have been assessed against observations, the global-mean values of these fluxes are deemed to be the most credible of the four different categories reviewed. The global, annual mean DLR lies between approximately 344 and 350 W/sq m with an error of approximately +/-10 W/sq m that arises mostly from the uncertainty in atmospheric state that governs the estimation of the clear-sky emission. The authors conclude that the DLR derived from global climate models are biased low by approximately 10 W/sq m and even larger differences are found with respect to reanalysis climate data. The DLR inferred from a surface energy balance closure is also substantially smaller that the range found from synthesis products suggesting that current depictions of surface energy balance also require revision. The effect of clouds on the DLR, largely facilitated by the new cloud base information from the CloudSat radar, is estimated to lie in the range from 24 to 34 W/sq m for the global cloud radiative effect (all-sky minus clear-sky DLR). This effect is strongly modulated by the underlying water vapor that gives rise to a maximum sensitivity of the DLR to cloud occurring in the colder drier regions of the planet. The bottom of atmosphere (BOA) cloud effect directly contrast the effect of clouds on the top of atmosphere (TOA) fluxes that is maximum in regions of deepest and coldest clouds in the moist tropics.

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

NASA Technical Reports Server (NTRS)

Pfister, Leonhard; Ueyama, Rei; Jensen, Eric; Schoeberl, Mark

2017-01-01

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

Cloud vertical structure, precipitation, and cloud radiative effects over Tibetan Plateau

NASA Astrophysics Data System (ADS)

Liu, Y.; Yan, Y.; Lu, J.

2017-12-01

The vertical structure of clouds and its connection with precipitation and cloud radiative effects (CRE) over the Tibetan Plateau (TP) are analyzed and compared with its neighboring land and tropical oceans based on CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) products and the Tropical Rainfall Measuring Mission (TRMM) precipitation data. Unique characteristics of cloud vertical structure and CRE over the TP are found. The cloud amount shows seasonal variation over the TP, which presents a single peak (located in 7-11 km) during January to April and two peaks (located in 5-8 km and 11-17 km separately) after mid-June, and then resumes to one peak (located in 5-10 km) after mid-August. Topography-induced restriction on moisture supply leads to a compression effect on clouds, i.e., the reduction in both cloud thickness and number of cloud layers, over the TP. The topography-induced compression effect is also shown in the range in the variation of cloud thickness and cloud-top height corresponding to different precipitation intensity, which is much smaller over the TP than its neighboring regions. In summer, cloud ice particles over the TP are mostly located at lower altitude (5-10 km) with richer variety of sizes and aggregation in no rain conditions compared to other regions. Ice water content becomes abundant and the number concentration tends to be dense at higher levels when precipitation is enhanced. The longwave CRE in the atmosphere over the TP is a net cooling effect. The vertical structure of CRE over the TP is unique compared to other regions: there exists a strong cooling layer of net CRE at the altitude of 8 km, from June to the beginning of October; the net radiative heating layer above the surface is shallower but stronger underneath 7 km and with a stronger seasonal variation over the TP.

A CloudSat Perspective of the Atmospheric Water Cycle and Precipitation: Recent Progress and Grand Challenges

NASA Technical Reports Server (NTRS)

Stephens, Graeme L.; Im, Eastwood; Vane, Deborah

2012-01-01

Summary Global - mean precipitation - is controlled by Earth's energy balance and is a quantifiable consequence of the water vapor feedback. Predictability rests on the degree to which the water vapor feedback is predictable. Regional scale - to a significant extent, changes are shaped by atmospheric circulation changes but we do not know the extent to which regional scale changes are predictable. The impacts of changes to atmospheric circulation on regional scale water cycle changes can be dramatic. Process - scale - significant biases to the CHARACTER of precipitation (frequency and intensity) is related to how the precipitation process is parameterized in models. Aerosol - We still do not know the extent to which the water cycle is influenced by aerosol but anecdotal evidence is building. The character of precipitation is affected by the way aerosol influence clouds and thus affects the forcing of the climate system through the albedo effect. Observations - we still have a way to go and need to approach the problem in a more integrated way (tie clouds, aerosol and precipitation together and then link to soil moisture, etc). Globally our capabilities seriously lag behind the science and model development.

Characterization of Arctic ice cloud properties observed during ISDAC

NASA Astrophysics Data System (ADS)

Jouan, Caroline; Girard, Eric; Pelon, Jacques; Gultepe, Ismail; Delanoë, Julien; Blanchet, Jean-Pierre

2012-12-01

Extensive measurements from ground-based sites and satellite remote sensing (CloudSat and CALIPSO) reveal the existence of two types of ice clouds (TICs) in the Arctic during the polar night and early spring. The first type (TIC-2A), being topped by a cover of nonprecipitating very small (radar unseen) ice crystals (TIC-1), is found more frequently in pristine environment, whereas the second type (TIC-2B), detected by both sensors, is associated preferentially with a high concentration of aerosols. To further investigate the microphysical properties of TIC-1/2A and TIC-2B, airborne in situ and satellite measurements of specific cases observed during Indirect and Semi-Direct Aerosol Campaign (ISDAC) have been analyzed. For the first time, Arctic TIC-1/2A and TIC-2B microstructures are compared using in situ cloud observations. Results show that the differences between them are confined in the upper part of the clouds where ice nucleation occurs. TIC-2B clouds are characterized by fewer (by more than 1 order of magnitude) and larger (by a factor of 2 to 3) ice crystals and a larger ice supersaturation (of 15-20%) compared to TIC-1/2A. Ice crystal growth in TIC-2B clouds seems explosive, whereas it seems more gradual in TIC-1/2A. It is hypothesized that these differences are linked to the number concentration and the chemical composition of aerosols. The ice crystal growth rate in very cold conditions impinges on the precipitation efficiency, dehydration and radiation balance. These results represent an essential and important first step to relate previous modeling, remote sensing and laboratory studies with TICs cloud in situ observations.

The NASA Decadal Survey Aerosol, Cloud, Ecosystems Mission

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Bontempi, Paula; Maring, Hal

2011-01-01

In 2007, the National Academy of Sciences delivered a Decadal Survey (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond) for NASA, NOAA, and USGS, which is a prioritization of future satellite Earth observations. The recommendations included 15 missions (13 for NASA, two for NOAA), which were prioritized into three groups or tiers. One of the second tier missions is the Aerosol, Cloud, (ocean) Ecosystems (ACE) mission, which focuses on climate forcing, cloud and aerosol properties and interactions, and ocean ecology, carbon cycle science, and fluxes. The baseline instruments recommended for ACE are a cloud radar, an aerosol/cloud lidar, an aerosol/cloud polarimeter, and an ocean radiometer. The instrumental heritage for these measurements are derived from the Cloudsat, CALIPSO, Glory, SeaWiFS and Aqua (MODIS) missions. In 2008, NASA HQ, lead by Hal Maring and Paula Bontempi, organized an interdisciplinary science working group to help formulate the ACE mission by refining the science objectives and approaches, identifying measurement (satellite and field) and mission (e.g., orbit, data processing) requirements, technology requirements, and mission costs. Originally, the disciplines included the cloud, aerosol, and ocean biogeochemistry communities. Subsequently, an ocean-aerosol interaction science working group was formed to ensure the mission addresses the broadest range of science questions possible given the baseline measurements, The ACE mission is a unique opportunity for ocean scientists to work closely with the aerosol and cloud communities. The science working groups are collaborating on science objectives and are defining joint field studies and modeling activities. The presentation will outline the present status of the ACE mission, the science questions each discipline has defined, the measurement requirements identified to date, the current ACE schedule, and future opportunities for broader community participation.

Aerosol Indirect Effect on Warm Clouds over Eastern China Using Combined CALIOP and MODIS Observations

NASA Astrophysics Data System (ADS)

Guo, Jianping; Wang, Fu; Huang, Jingfeng; Li, Xiaowen

2015-04-01

Aerosol, one of key components of the climate system, is highly variable, both temporally and spatially. It often exerts great influences on the cloud-precipitation chain processes by serving as CCN/IN, altering cloud microphysics and its life cycle. Yet, the aerosol indirect effect on clouds remains largely unknown, because the initial changes in clouds due to aerosols may be enhanced or dampened by such feedback processes as modified cloud dynamics, or evaporation of the smaller droplets due to the competition for water vapor. In this study, we attempted to quantify the aerosol effects on warm cloud over eastern China, based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO and CPR/CLOUDSAT during the period 2006 to 2010. The seasonality of aerosol from ground-based PM10 is quite different from that estimated from MODIS AOD. This result is corroborated by lower level profile of aerosol occurrence frequency from CALIOP, indicating the significant role CALIOP could play in aerosol-cloud interaction. The combined use of CALIOP and CPR facilitate the process to exactly determine the (vertical) position of warm cloud relative to aerosol, out of six scenarios in terms of aerosol-cloud mixing status in terms of aerosol-cloud mixing status, which shows as follows: AO (Aerosol only), CO (Cloud only), SASC (Single aerosol-single cloud), SADC (single aerosol-double cloud), DASC (double aerosol-single cloud), and others. Results shows that about 54% of all the cases belong to mixed status, among all the collocated aerosol-cloud cases. Under mixed condition, a boomerang shape is observed, i.e., reduced cloud droplet radius (CDR) is associated with increasing aerosol at moderate aerosol pollution (AOD<0.4), becoming saturated at AOD of 0.5, followed by an increase in CDR with aerosol. In contrast, there is no such boomerang shape found for (aerosol-cloud) separated cases. We categorize dataset into warm-season and cold-season subsets to figure out how the boomerang shape varies with season. For moderate aerosol loading (AOD<0.4), the effect on the droplet size for the "Mixed" cases is greater during cold season (denoted by a large slope), as compared with that during warm season. It is likely associated with an increase in the emission of light absorbing aerosol like smoke (black carbon), mainly caused by coal-fired heating during the cold season in China. As expected, the sensitivity of CDR to AOD is much weaker for "Separated" cases, irrespective of warm or cold seasons, indicating no real aerosol indirect effect occurring in this case. In contrast, for heavy aerosol loading (AOD>0.4), an increasing CDR with AOD can be seen in "Mixed" scenario during the warm season. Conversely, a closer look at the responses of CDR during the cold season shows that CDR decreases with AOD, although the strength is not much large. Therefore, we argue that cloud droplet size decreases with aerosol loading during cold season, irrespective of moderate or heavy atmospheric pollution. Finally, we discuss the possible factors that may influence the aerosol indirect effects on warm clouds investigated here. For instance, aerosol-cloud interaction conundrum might be affected by aerosol humidification, which is the case for MODIS AOD during warm seasons. But this issue can be partly overcome by categorizing dataset into warm-season and cold-season subsets, representing different ambient humidity condition in the atmosphere. The different boomerang shapes observed during various seasons, particularly after transition zone due to droplet saturation effect, have great implications for climate forcing by aerosol in eastern China.

Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

2016-12-01

Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of representations of large-scale moisture transport, cloud microphysics, ice nucleation, and cumulus detrainment in order to improve the mixed-phase transition in GCMs.

Perspectives of Future Satellite Observations for Studying Aerosol-Cloud Interactions

NASA Astrophysics Data System (ADS)

Vane, D. G.; Stephens, G. L.

2008-12-01

There are many studies that examine the effects of aerosol on clouds and the consequence of these effects for climate. Much of the focus of these interactions revolve around two types of indirect effects. Using the A- Train as a resource for studying these interactions as a way of defining the requirements for future new missions, we find that the sensitivity of the cloud albedo, as observed by CERES, to aerosol varies according to these various conditions and does not simply correlate with decreased particle size as is typically assumed. It is clear that these effects require more in-depth information about cloud water path, and the occurrence and amount of precipitation and the environmental conditions in which the interactions take place. Information about the motions in clouds, the depths of clouds and more resolved microphysical details on cloud and drizzle are essential to study these effects. Perhaps more important than indirect effects on cloud albedo are the possible effects of aerosol on precipitation. There is much speculation about such influences and the A-Train observations are beginning to reveal much insight on such effects. These observations appear to suggest that the effects on shallow clouds is to delay precipitation production and reduce rainfall as has been speculated. The effects of aerosol on the precipitation falling from deep convection is less clear and more difficult to observe, although many model studies consistently suggest that the effects might be even more pronounced than on shallow convection through, among other mechanisms, the invigoration of storms via freezing of elevated water contents in updrafts. Such studies are now clearly pointing to the need to define the water contents and microphysics of hydrometeors in convective updrafts. This talk draws on these results as a way of framing the definition of the cloud-aerosol and precipitation component of the ACE mission of the decadal survey. This mission represents the follow-on to CloudSat and CALIPSO and notional measurement needs will be discussed.

Analysis of clouds and precipitation during Baiu period over the East China Sea with cloud database CTOP and precipitation database GSMaP

NASA Astrophysics Data System (ADS)

Nishi, N.; Hamada, A.; Hirose, H.; Hotta, S.; Suzuki, J.

2016-12-01

We have made a quantitative research of the clouds and precipitation during Baiu: the rainy season within the East Asia, using recent satellite observation datasets. As the precipitation dataset, we utilized the Global Satellite Mapping of Precipitation (GSMaP), whose primary source is passive microwave observations. As the cloud dataset, we used our original database CTOP, in which the cloud top height and optical depth are estimated only with the infrared split-window channels of the geostationary satellites. Lookup tables are made by training the infrared observations with the direct cloud observation by CloudSat and CALIPSO. This technique was originally developed only for the tropics but we extended it to the mid-latitude by estimating temperature at the cloud top instead of the height. We analyzed the properties of northward shift of the Baiu precipitation zone over the East China Sea. Abrupt northward shift in mid-June has already been reported. We showed here that the abrupt shift is limited to the western half of the East China Sea. We also analyzed the zonal difference of the precipitation amount in the East China Sea. In the central latitudinal range (30-33N), the amount is larger in the eastern part of the sea. There is no significant zonal contrast in both the activity of the low pressure and the front, while the sea surface temperature in the eastern part is slightly larger than in the western part. The zonal gradient is much smaller than that in the southern region near the Kuroshio Current, but may possibly affect the zonal contrast of the precipitation. By using CTOP cloud top data, we also calculated the occurrence ratio of the cloud with various thresholds of the top height. The ratio of clouds with the tops higher than 12 km in the East China Sea is clearly lower than those over the Continental area and the main Japanese islands.

Evaluation of the cloud fields in the UK Met Office HadGEM3-UKCA model using the CCCM satellite data product to advance our understanding of the influence of clouds on tropospheric composition and chemistry

NASA Astrophysics Data System (ADS)

Varma, S.; Voulgarakis, A.; Liu, H.; Crawford, J. H.

2016-12-01

What drives the variability of trace gases and aerosols in the troposphere is not well understood, as is the role of clouds in modulating this variability via radiative, transport, deposition, and lightning effects that are associated with them. Such uncertainties are expected to be of particular importance in the tropical troposphere, a region that receives significant surface emissions and moisture via deep convection and upwelling, and experiences large amounts of lightning production of nitrogen oxides (NOx). Accurately simulating tropospheric composition and its variability is of utmost importance as both could have a significant effect on the region's temperature and circulation, as well as on surface climate and the amount of UV radiation in the troposphere. In this presentation, we will examine the key cloud processes which are expected to have an influence on tropospheric composition with a specific focus on their roles in modifying solar radiation and photolysis rates of trace gases through the backscattering of shortwave radiation. We will pay particular attention to the UT/LS which is less well understood and where clouds could have a significant impact due to backscattering. We will also utilize CCCM (a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center to evaluate the cloud fields and their vertical distribution in the HadGEM3-UKCA model and to adjust the cloud fields where appropriate. This evaluation will initially involve the comparison of effective cloud optical depth (ECOD) as calculated from CCCM and HadGEM3-UKCA using the approximate random overlap approximation followed by the application of 3-D scaling factors to the model's ECOD. We will then examine the impacts of the cloud field adjustment on tropospheric chemistry, with a focus on oxidants in the UT/LS.

Observational Analysis of Cloud and Precipitation in Midlatitude Cyclones: Northern Versus Southern Hemisphere Warm Fronts

NASA Technical Reports Server (NTRS)

Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.

2012-01-01

Extratropical cyclones are responsible for most of the precipitation and wind damage in the midlatitudes during the cold season, but there are still uncertainties on how they will change in a warming climate. An ubiquitous problem amongst General Circulation Models (GCMs) is a lack of cloudiness over the southern oceans that may be in part caused by a lack of clouds in cyclones. We analyze CloudSat, CALIPSO and AMSR-E observations for 3 austral and boreal cold seasons and composite cloud frequency of occurrence and precipitation at the warm fronts for northern and southern hemisphere oceanic cyclones. We find that cloud frequency of occurrence and precipitation rate are similar in the early stage of the cyclone life cycle in both northern and southern hemispheres. As cyclones evolve and reach their mature stage, cloudiness and precipitation at the warm front increase in the northern hemisphere but decrease in the southern hemisphere. This is partly caused by lower amounts of precipitable water being available to southern hemisphere cyclones, and smaller increases in wind speed as the cyclones evolve. Southern hemisphere cloud occurrence at the warm front is found to be more sensitive to the amount of moisture in the warm sector than to wind speeds. This suggests that cloudiness in southern hemisphere storms may be more susceptible to changes in atmospheric water vapor content, and thus to changes in surface temperature than their northern hemisphere counterparts. These differences between northern and southern hemisphere cyclones are statistically robust, indicating A-Train-based analyses as useful tools for evaluation of GCMs in the next IPCC report.

Uncertainty Estimate of Surface Irradiances Computed with MODIS-, CALIPSO-, and CloudSat-Derived Cloud and Aerosol Properties

NASA Astrophysics Data System (ADS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan

2012-07-01

Differences of modeled surface upward and downward longwave and shortwave irradiances are calculated using modeled irradiance computed with active sensor-derived and passive sensor-derived cloud and aerosol properties. The irradiance differences are calculated for various temporal and spatial scales, monthly gridded, monthly zonal, monthly global, and annual global. Using the irradiance differences, the uncertainty of surface irradiances is estimated. The uncertainty (1σ) of the annual global surface downward longwave and shortwave is, respectively, 7 W m-2 (out of 345 W m-2) and 4 W m-2 (out of 192 W m-2), after known bias errors are removed. Similarly, the uncertainty of the annual global surface upward longwave and shortwave is, respectively, 3 W m-2 (out of 398 W m-2) and 3 W m-2 (out of 23 W m-2). The uncertainty is for modeled irradiances computed using cloud properties derived from imagers on a sun-synchronous orbit that covers the globe every day (e.g., moderate-resolution imaging spectrometer) or modeled irradiances computed for nadir view only active sensors on a sun-synchronous orbit such as Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation and CloudSat. If we assume that longwave and shortwave uncertainties are independent of each other, but up- and downward components are correlated with each other, the uncertainty in global annual mean net surface irradiance is 12 W m-2. One-sigma uncertainty bounds of the satellite-based net surface irradiance are 106 W m-2 and 130 W m-2.

A Decade of Volcanic Observations from Aura and the A-Train

NASA Technical Reports Server (NTRS)

Carn, Simon A.; Krotkov, Nickolay Anatoly; Yang, Kai; Krueger, Arlin J.; Hughes, Eric J.; Wang, Jun; Flower, Verity; Telling, Jennifer

2014-01-01

Aura observations have made many seminal contributions to volcanology. Prior to the Aura launch, satellite observations of volcanic degassing (e.g., from TOMS) were mostly restricted to large eruptions. However, the vast majority of volcanic gases are released during quiescent 'passive' degassing between eruptions. The improved sensitivity of Aura OMI permitted the first daily, space-borne measurements of passive volcanic SO2 degassing, providing improved constraints on the source locations and magnitude of global SO2 emissions for input to atmospheric chemistry and climate models. As a result of this unique sensitivity to volcanic activity, OMI data were also the first satellite SO2 measurements to be routinely used for volcano monitoring at several volcano observatories worldwide. Furthermore, the Aura OMI SO2 data also offer unprecedented sensitivity to volcanic clouds in the UTLS, elucidating the transport, fate and lifetime of volcanic SO2 and providing critical input to aviation hazard mitigation efforts. Another major advance has been the improved vertical resolution of volcanic clouds made possible by synergy between Aura and other A-Train instruments (e.g., AIRS, CALIPSO, CloudSat), advanced UV SO2 altitude retrievals, and inverse trajectory modeling of detailed SO2 cloud maps. This altitude information is crucial for climate models and aviation hazards. We will review some of the highlights of a decade of Aura observations of volcanic activity and look ahead to the future of volcanic observations from space.

Improving Satellite-Based Snowfall Estimation: A New Method for Classifying Precipitation Phase and Estimating Snowfall Rate

NASA Astrophysics Data System (ADS)

Sims, Elizabeth M.

In order to study the impact of climate change on the Earth's hydrologic cycle, global information about snowfall is needed. To achieve global measurements of snowfall over both land and ocean, satellites are necessary. While satellites provide the best option for making measurements on a global scale, the task of estimating snowfall rate from these measurements is a complex problem. Satellite-based radar, for example, measures effective radar reflectivity, Ze, which can be converted to snowfall rate, S, via a Ze-S relation. Choosing the appropriate Ze-S relation to apply is a complicated problem, however, because quantities such as particle shape, size distribution, and terminal velocity are often unknown, and these quantities directly affect the Ze-S relation. Additionally, it is important to correctly classify the phase of precipitation. A misclassification can result in order-of-magnitude errors in the estimated precipitation rate. Using global ground-based observations over multiple years, the influence of different geophysical parameters on precipitation phase is investigated, with the goal of obtaining an improved method for determining precipitation phase. The parameters studied are near-surface air temperature, atmospheric moisture, low-level vertical temperature lapse rate, surface skin temperature, surface pressure, and land cover type. To combine the effects of temperature and moisture, wet-bulb temperature, instead of air temperature, is used as a key parameter for separating solid and liquid precipitation. Results show that in addition to wet-bulb temperature, vertical temperature lapse rate also affects the precipitation phase. For example, at a near-surface wet-bulb temperature of 0°C, a lapse rate of 6°C km-1 results in an 86 percent conditional probability of solid precipitation, while a lapse rate of -2°C km-1 results in a 45 percent probability. For near-surface wet-bulb temperatures less than 0°C, skin temperature affects precipitation phase, although the effect appears to be minor. Results also show that surface pressure appears to influence precipitation phase in some cases, however, this dependence is not clear on a global scale. Land cover type does not appear to affect precipitation phase. Based on these findings, a parameterization scheme has been developed that accepts available meteorological data as input, and returns the conditional probability of solid precipitation. Ze-S relations for various particle shapes, size distributions, and terminal velocities have been developed as part of this research. These Ze-S relations have been applied to radar reflectivity data from the CloudSat Cloud Profiling Radar to calculate the annual mean snowfall rate. The calculated snowfall rates are then compared to surface observations of snowfall. An effort to determine which particle shape best represents the type of snow falling in various locations across the United States has been made. An optimized Ze-S relation has been developed, which combines multiple Ze-S relations in order to minimize error when compared to the surface snowfall observations. Additionally, the resulting surface snowfall rate is compared with the CloudSat standard product for snowfall rate.

Atmosphere Kits: Hands-On Learning Activities with a Foundation in NASA Earth Science Missions.

NASA Astrophysics Data System (ADS)

Teige, V.; McCrea, S.; Damadeo, K.; Taylor, J.; Lewis, P. M., Jr.; Chambers, L. H.

2016-12-01

The Science Directorate (SD) at NASA Langley Research Center provides many opportunities to involve students, faculty, researchers, and the citizen science community in real world science. The SD Education Team collaborates with the education community to bring authentic Earth science practices and real-world data into the classroom, provide the public with unique NASA experiences, engaging activities, and advanced technology, and provide products developed and reviewed by science and education experts. Our goals include inspiring the next generation of Science, Technology, Engineering and Mathematics (STEM) professionals and improving STEM literacy by providing innovative participation pathways for educators, students, and the public. The SD Education Team has developed Atmosphere activity kits featuring cloud and aerosol learning activities with a foundation in NASA Earth Science Missions, the Next Generation Science Standards, and The GLOBE Program's Elementary Storybooks. Through cloud kit activities, students will learn how to make estimates from observations and how to categorize and classify specific cloud properties, including cloud height, cloud cover, and basic cloud types. The purpose of the aerosol kit is to introduce students to aerosols and how they can affect the colors we see in the sky. Students will engage in active observation and reporting, explore properties of light, and model the effects of changing amounts/sizes or aerosols on sky color and visibility. Learning activity extensions include participation in ground data collection of environmental conditions and comparison and analysis to related NASA data sets, including but not limited to CERES, CALIPSO, CloudSat, and SAGE III on ISS. This presentation will provide an overview of multiple K-6 NASA Earth Science hands-on activities and free resources will be available.

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

NASA Astrophysics Data System (ADS)

Liu, Yuqin; de Leeuw, Gerrit; Kerminen, Veli-Matti; Zhang, Jiahua; Zhou, Putian; Nie, Wei; Qi, Ximeng; Hong, Juan; Wang, Yonghong; Ding, Aijun; Guo, Huadong; Krüger, Olaf; Kulmala, Markku; Petäjä, Tuukka

2017-05-01

Aerosol effects on low warm clouds over the Yangtze River Delta (YRD, eastern China) are examined using co-located MODIS, CALIOP and CloudSat observations. By taking the vertical locations of aerosol and cloud layers into account, we use simultaneously observed aerosol and cloud data to investigate relationships between cloud properties and the amount of aerosol particles (using aerosol optical depth, AOD, as a proxy). Also, we investigate the impact of aerosol types on the variation of cloud properties with AOD. Finally, we explore how meteorological conditions affect these relationships using ERA-Interim reanalysis data. This study shows that the relation between cloud properties and AOD depends on the aerosol abundance, with a different behaviour for low and high AOD (i.e. AOD < 0.35 and AOD > 0.35). This applies to cloud droplet effective radius (CDR) and cloud fraction (CF), but not to cloud optical thickness (COT) and cloud top pressure (CTP). COT is found to decrease when AOD increases, which may be due to radiative effects and retrieval artefacts caused by absorbing aerosol. Conversely, CTP tends to increase with elevated AOD, indicating that the aerosol is not always prone to expand the vertical extension. It also shows that the COT-CDR and CWP (cloud liquid water path)-CDR relationships are not unique, but affected by atmospheric aerosol loading. Furthermore, separation of cases with either polluted dust or smoke aerosol shows that aerosol-cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust, which is ascribed to the higher absorption efficiency of smoke than dust. The variation of cloud properties with AOD is analysed for various relative humidity and boundary layer thermodynamic and dynamic conditions, showing that high relative humidity favours larger cloud droplet particles and increases cloud formation, irrespective of vertical or horizontal level. Stable atmospheric conditions enhance cloud cover horizontally. However, unstable atmospheric conditions favour thicker and higher clouds. Dynamically, upward motion of air parcels can also facilitate the formation of thicker and higher clouds. Overall, the present study provides an understanding of the impact of aerosols on cloud properties over the YRD. In addition to the amount of aerosol particles (or AOD), evidence is provided that aerosol types and ambient environmental conditions need to be considered to understand the observed relationships between cloud properties and AOD.

Computation of Solar Radiative Fluxes by 1D and 3D Methods Using Cloudy Atmospheres Inferred from A-train Satellite Data

NASA Technical Reports Server (NTRS)

Barker, Howard W.; Kato, Serji; Wehr, T.

2012-01-01

The main point of this study was to use realistic representations of cloudy atmospheres to assess errors in solar flux estimates associated with 1D radiative transfer models. A scene construction algorithm, developed for the EarthCARE satellite mission, was applied to CloudSat, CALIPSO, and MODIS satellite data thus producing 3D cloudy atmospheres measuring 60 km wide by 13,000 km long at 1 km grid-spacing. Broadband solar fluxes and radiances for each (1 km)2 column where then produced by a Monte Carlo photon transfer model run in both full 3D and independent column approximation mode (i.e., a 1D model).

The Afternoon Constellation: A Formation of Earth Observing Systems for the Atmosphere and Hydrosphere

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.

2002-01-01

Two of the large EOS observatories, Aqua (formerly EOS-PM) and Aura (formerly EOS-CHEM) will fly is nearly the same inclination with 1:30 PM -15 min ascending node equatorial crossing times. Between Aura and Aqua a series of smaller satellites will be stationed: Cloudsat, CALYPSO (formerly PICASSO-CENA), and PARASOL. This constellation of low earth orbit satellites will provide an unprecedented opportunity to make near simultaneous atmospheric cloud and aerosol observations. This paper will provide details of the science opportunity and describe the sensor types for the afternoon constellation. This constellation by accretion provides a prototype for the Earth Science Vision sensor web and represent the building books for a future web structure.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guosheng

2013-03-15

Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term ofmore » condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMs cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10° (latitude) x 10° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.« less

The Characteristics of Ice Cloud Properties in China Derived from DARDAR data

NASA Astrophysics Data System (ADS)

Lin, T.; Zheng, Y.

2017-12-01

Ice clouds play an important role in modulating the Earth radiation budget and global hydrological cycle.Thus,study the properties of ice clouds has the vital significance on the interaction between the atmospheric models,cloud,radiation and climate .The world has explore the combination of two or several kinds of sensor data to solve the complementary strengths and error reduction to improve accuracy of ice cloud at the present , but for China ,has be lack of research on combination sensor data to analysis properties of ice cloud.To reach a wider range of ice cloud, a combination of the CloudSat radar and the CALIPSO lidar is used to derive ice cloud properties. These products include the radar/lidar product (DARDAR) developed at the University of Reading.The China probability distribution of ice cloud occurrence frequency, ice water path, ice water content and ice cloud effective radius were presented based on DARDAR data from 2012 to 2016,the distribution and vertical sturctures was discussed.The results indicate that the ice cloud occurrence frequency distribution takes on ascend trend in the last 4 years and has obvious seasonal variation, the high concentration area in the northeastern part of the Tibetan Plateau,ice cloud occurrence frequency is relatively high in northwest area.the increased of ice cloud occurrence frequency play an integral role of the climate warming in these four years; the general trend for the ice water path is southeast area bigger than northwest area, in winter the IWP is the smallest, biggest in summer; the IWC is the biggest in summer, and the vertical height distribution higher than other seasons; ice cloud effective radius and ice water content had similar trend..There were slight declines in ice cloud effective radius with increase height of China,in the summer ice effective radius is generally larger.The ice cloud impact Earth radiation via their albedo an greenhouse effects, that is, cooling the Earth by reflecting solar incident radiation and at the same time.Thus,thorough research of the characteristics of ice cloud properties can explain the complicated relationship between ice cloud and global warming,and this kind of data analysis can comprehend the climate effect of mainland China .

How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

2014-12-01

The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at least one or more potential reasons mentioned above. Collocated radar reflectivity observations from CloudSat suggest that the remaining 20% are unlikely to be retrieval artifacts, but reflection of true cloud microphysics, i.e., the true is either truly very small or very large.

McIDAS-V: Advanced Visualization for 3D Remote Sensing Data

NASA Astrophysics Data System (ADS)

Rink, T.; Achtor, T. H.

2010-12-01

McIDAS-V is a Java-based, open-source, freely available software package for analysis and visualization of geophysical data. Its advanced capabilities provide very interactive 4-D displays, including 3D volumetric rendering and fast sub-manifold slicing, linked to an abstract mathematical data model with built-in metadata for units, coordinate system transforms and sampling topology. A Jython interface provides user defined analysis and computation in terms of the internal data model. These powerful capabilities to integrate data, analysis and visualization are being applied to hyper-spectral sounding retrievals, eg. AIRS and IASI, of moisture and cloud density to interrogate and analyze their 3D structure, as well as, validate with instruments such as CALIPSO, CloudSat and MODIS. The object oriented framework design allows for specialized extensions for novel displays and new sources of data. Community defined CF-conventions for gridded data are understood by the software, and can be immediately imported into the application. This presentation will show examples how McIDAS-V is used in 3-dimensional data analysis, display and evaluation.

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Bacmeister, Julio; Bosilovich, Michael; Pittman, Jasna

2007-01-01

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

The Earth Science Afternoon Constellation Contingency Procedures

NASA Technical Reports Server (NTRS)

Case, Warren F.; Richon, Karen

2005-01-01

The Earth Science Afternoon Constellation comprises NASA missions Aqua, Aura, CloudSat and the Orbiting Carbon Observatory (OCO), the joint NASA/CNES mission CALIPSO and the CNES mission PARASOL. Both NASA and CNES offices are responsible for ensuring that contingency plans or other arrangements exist to cope with contingencies within their respective jurisdictions until the conclusion of all Afternoon Constellation operations. The Mission Operations Working Group, comprised of members from each of the missions, has developed the high-level procedures for maintaining the safety of this constellation. Each contingency situation requires detailed analyses before any decisions are made. This paper describes these procedures, and includes defining what constitutes a contingency situation, the pertinent parameters involved in the contingency analysis and guidelines for the actions required, based on the results of the contingency analyses.

Climatology and Impact of Convection on the Tropical Tropopause Layer

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Pittman, Jasna

2007-01-01

Water vapor plays an important role in controlling the radiative balance and the chemical composition of the Tropical Tropopause Layer (TTL). Mechanisms ranging from slow transport and dehydration under thermodynamic equilibrium conditions to fast transport in convection have been proposed as regulators of the amount of water vapor in this layer. However,.details of these mechanisms and their relative importance remain poorly understood, The recently completed Tropical Composition, Cloud, and Climate Coupling (TC4) campaign had the opportunity to sample the.TTL over the Eastern Tropical Pacific using ground-based, airborne, and spaceborne instruments. The main goal of this study is to provide the climatological context for this campaign of deep and overshooting convective activity using various satellite observations collected during the summertime. We use the Microwave Humidity Sensor (MRS) aboard the NOAA-18 satellite to investigate the horizontal extent.and the frequency of convection reaching and penetrating into the TTL. We use the Moderate Resolution I1l1aging Spectroradiometer (MODIS) aboard the Aqua satellite to investigate the frequency distribution of daytime cirrus clouds. We use the Tropical Rainfall Measuring Mission(TRMM) and CloudSat to investigate the vertical structure and distribution of hydrometeors in the convective cells, In addition to cloud measurements; we investigate the impact that convection has on the concentration of radiatively important gases such as water vapor and ozone in the TTL by examining satellite measurement obtained from the Microwave Limb Sounder(MLS) aboard the Aura satellite.

Cloud evaluation using satellite simulators and cloud changes for global nonhydrostatic simulations with NICAM

NASA Astrophysics Data System (ADS)

Satoh, M.; Noda, A. T.; Kodama, C.; Yamada, Y.; Hashino, T.

2012-12-01

Global cloud distributions and properties simulated by the global nonhydrostatic model, NICAM (Nonhydrostatic Icosahedral Atmospheric Model), are evaluated and their future changes are discussed. First, we evaluated the simulated cloud properties produced by a case study of the 3.5km mesh experiment of NICAM using the satellite simulator package (the Joint-simulator) with cloud microphysics oriented approach (Hashino et al. 2012). Then, we analyzed future cloud changes using various sets of simulations under the present and the future global warming conditions. The results show that the zonal averaged ice water path (IWP) generally decreases or marginally unchanged in the tropics, while IWP in the extra-tropics increases. The upper cloud fraction increases both in the tropics and in the extra-tropics in general. We further analyzed contributions of cloud systems such as cloud clusters, tropical cyclones (TCs), and storm-tracks to these changes. Probability distribution of the larger cloud clusters decreases, while that of the smaller ones increases, consistent with the decrease in the number of tropical cyclones in the future climate. Average liquid water path (LWP) and IWP associated with each tropical cyclone are diagnosed, and it is found that both the associated LWP and IWP increase under the warmer condition. Even though, since the number of the intensive cloud systems decrease, the average IWP decreases. It should be remarked that the change in TC tracks largely contribute to the change in the horizontal distribution of clouds. The NICAM simulations also show that the storm-tracks shift poleward, and the storms become less frequent and stronger in the extra-tropics, similar to the results of other general circulation models. Both LWP and IWP associated with the storms also increase in the warmer climate in the NICAM simulations. This results in increase in the upper clouds under the warmer climate condition, as described by Miura et al. (2005). References: Hashino, T., Satoh, M., Hagihara, Y., Kubota, T., Matsui, T., Nasuno, T., and Okamoto, H. (2012), Evaluating Global Cloud Distribution and Microphysics from the NICAM against CloudSat and CALIPSO, J. Geophys. Res., submitted. Miura, H., Tomita,H., Nasuno,T., Iga, S., Satoh,M., and Matsuno, T. (2005), A climate sensitivity test using a global cloud resolving model under an aqua planet condition, Geophys. Res. Lett., 32, L19717, doi:10.1029/2005GL023672.

The cloud-radiative processes and its modulation by sea-ice cover and stability as derived from a merged C3M Data product.

NASA Astrophysics Data System (ADS)

Nag, B.

2016-12-01

The polar regions of the world constitute an important sector in the global energy balance. Among other effects responsible for the change in the sea-ice cover like ocean circulation and ice-albedo feedback, the cloud-radiation feedback also plays a vital role in modulation of the Arctic environment. However the annual cycle of the clouds is very poorly represented in current global circulation models. This study aims to take advantage of a merged C3M data (CALIPSO, CloudSat, CERES, and MODIS) product from the NASA's A-Train Series to explore the sea-ice and atmospheric conditions in the Arctic on a spatial coverage spanning 70N to 80N. This study is aimed at the interactions or the feedbacks processes among sea-ice, clouds and the atmosphere. Using a composite approach based on a classification due to surface type, it is found that limitation of the water vapour influx from the surface due to change in phase at the surface featuring open oceans or marginal sea-ice cover to complete sea-ice cover is a major determinant in the modulation of the atmospheric moisture and its impacts. The impact of the cloud-radiative effects in the Arctic is found to vary with sea-ice cover and seasonally. The effect of the marginal sea-ice cover becomes more and more pronounced in the winter. The seasonal variation of the dependence of the atmospheric moisture on the surface and the subsequent feedback effects is controlled by the atmospheric stability measured as a difference between the potential temperature at the surface and the 700hPa level. It is found that a stronger stability cover in the winter is responsible for the longwave cloud radiative feedback in winter which is missing during the summer. A regional analysis of the same suggests that most of the depiction of the variations observed is contributed from the North Atlantic region.

Evaluating the Performance of Single and Double Moment Microphysics Schemes During a Synoptic-Scale Snowfall Event

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.

2011-01-01

Increases in computing resources have allowed for the utilization of high-resolution weather forecast models capable of resolving cloud microphysical and precipitation processes among varying numbers of hydrometeor categories. Several microphysics schemes are currently available within the Weather Research and Forecasting (WRF) model, ranging from single-moment predictions of precipitation content to double-moment predictions that include a prediction of particle number concentrations. Each scheme incorporates several assumptions related to the size distribution, shape, and fall speed relationships of ice crystals in order to simulate cold-cloud processes and resulting precipitation. Field campaign data offer a means of evaluating the assumptions present within each scheme. The Canadian CloudSat/CALIPSO Validation Project (C3VP) represented collaboration among the CloudSat, CALIPSO, and NASA Global Precipitation Measurement mission communities, to observe cold season precipitation processes relevant to forecast model evaluation and the eventual development of satellite retrievals of cloud properties and precipitation rates. During the C3VP campaign, widespread snowfall occurred on 22 January 2007, sampled by aircraft and surface instrumentation that provided particle size distributions, ice water content, and fall speed estimations along with traditional surface measurements of temperature and precipitation. In this study, four single-moment and two double-moment microphysics schemes were utilized to generate hypothetical WRF forecasts of the event, with C3VP data used in evaluation of their varying assumptions. Schemes that incorporate flexibility in size distribution parameters and density assumptions are shown to be preferable to fixed constants, and that a double-moment representation of the snow category may be beneficial when representing the effects of aggregation. These results may guide forecast centers in optimal configurations of their forecast models for winter weather and identify best practices present within these various schemes.

Investigating the influence of volcanic sulfate aerosol on cloud properties Along A-Train tracks

NASA Astrophysics Data System (ADS)

Mace, G. G.

2017-12-01

Marine boundary layer (MBL) clouds are central actors in the climate system given their extensive coverage on the Earth's surface, their 1-way influence on the radiative balance (cooling), and their intimate coupling between air motions, anthropogenic and natural aerosol sources, and processes within the upper ocean mixed layer. Knowledge of how MBL shallow cumulus clouds respond to changes in aerosol is central to understanding how MBL clouds modulate the climate system. A frequent approach to investigating how sulfate aerosol influences MBL clouds has been to examine sulfate plumes extending downstream of active island volcanoes. This approach is challenging due to modification of the air motions in the plumes downstream of islands and due to the tendency of most researchers to examine only level-2 retrievals ignoring the actual data collected by sensors such as MODIS. Past studies have concluded that sulfate aerosols have large effects consistent with the 1st aerosol indirect effect (AIE). We reason that if such effects are as large as suggested in level-2 retrievals then evidence should also be present in the raw MODIS reflectance data as well as other data sources. In this paper we will build on our recently published work where we tested that hypothesis from data collected near Mount Kilauea during a 3-year period. Separating data into aerosol optical depth (A) quartiles, we found little support for a large 1st AIE response. We did find an unambiguous increase in sub 1km-scale cloud fraction with A. This increase in sub 1 km cloud fraction was entirely consistent with increased reflectance with increasing A that is used, via the level 2 retrievals, to argue for a large AIE response of MBL clouds. While the 1-km pixels became unambiguously brighter, that brightening was due to increased sub 1 km cloud fraction and not necessarily due to changes in pixel-level cloud microphysics. We also found that MBL cloud top heights increase as do surface wind speeds as aerosol increases while the radar reflectivity from CloudSat does not change implying that increased aerosols may have caused invigoration of the MBL clouds with little effect on precipitation. We have since expanded upon this initial analysis by exmaining data near other volcanic islands. These expanded results support our initial findings.

Support for the Harvard University Water Vapor and Total Water Instruments for the 2004 NASA WB57 Middle Latitude Cirrus Experiment

NASA Technical Reports Server (NTRS)

Anderson, James G.

2005-01-01

In order to improve our understanding of the role clouds play in the climate system, NASA is investing considerable effort in characterizing clouds with instruments ranging from passive remote sensors on board the EOS platforms, to the forthcoming active remote sensors on Cloudsat and Calipso. These missions, when taken together, have the capacity to advance our understanding of the coupling between various components of the hydrologic cycle and the atmospheric circulation, and hold the additional potential of leading to significant improvements in the characterization of cloud feedbacks in global models. This is especially true considering that several of these platforms will be flown in an identical orbit within several minutes of one another-a constellation of satellites known as the A-Train. The algorithms that are being implemented and developed to convert these new data streams from radiance and reflectivity measurements into geophysical parameters invariably rely on some set of simplifymg assumptions and empirical constants. Uncertainties in these relationships lead to poorly understood random and systematic errors in the retrieved properties. This lack of understanding introduces ambiguity in interpreting the data and in using the global data sets for their intended purposes. In light of this, a series of flights with the W57F was proposed to address certain specific issues related to the basic properties of mid latitude cirrus clouds: the NASA WE357 Middle Latitude Cirrus Experiment ("MidCiX"). The science questions addressed are: 1) Can cloud property retrieval algorithms developed for A-Train active and passive remote sensing measurements accurately characterize the microphysical properties of synoptic and convectively generated cirrus cloud systems? 2) What are the relationships between the cirrus particle mass, projected area, and particle size spectrum in various genre of cirrus clouds? 3) Does the present compliment of state of the art in situ cloud probes provide the level of precision and accuracy needed to develop and validate algorithms and to contribute to our understanding of the characteristics and microphysical processes operating in cirrus clouds?

A New Understanding for the Rain Rate retrieval of Attenuating Radars Measurement

NASA Astrophysics Data System (ADS)

Koner, P.; Battaglia, A.; Simmer, C.

2009-04-01

The retrieval of rain rate from the attenuated radar (e.g. Cloud Profiling Radar on board of CloudSAT in orbit since June 2006) is a challenging problem. ĹEcuyer and Stephens [1] underlined this difficulty (for rain rates larger than 1.5 mm/h) and suggested the need of additional information (like path-integrated attenuations (PIA) derived from surface reference techniques or precipitation water path estimated from co-located passive microwave radiometer) to constrain the retrieval. It is generally discussed based on the optimal estimation theory that there are no solutions without constraining the problem in a case of visible attenuation because there is no enough information content to solve the problem. However, when the problem is constrained by the additional measurement of PIA, there is a reasonable solution. This raises the spontaneous question: Is all information enclosed in this additional measurement? This also contradicts with the information theory because one measurement can introduce only one degree of freedom in the retrieval. Why is one degree of freedom so important in the above problem? This question cannot be explained using the estimation and information theories of OEM. On the other hand, Koner and Drummond [2] argued that the OEM is basically a regularization method, where a-priori covariance is used as a stabilizer and the regularization strength is determined by the choices of the a-priori and error covariance matrices. The regularization is required for the reduction of the condition number of Jacobian, which drives the noise injection from the measurement and inversion spaces to the state space in an ill-posed inversion. In this work, the above mentioned question will be discussed based on the regularization theory, error mitigation and eigenvalue mathematics. References 1. L'Ecuyer TS and Stephens G. An estimation based precipitation retrieval algorithm for attenuating radar. J. Appl. Met., 2002, 41, 272-85. 2. Koner PK, Drummond JR. A comparison of regularization techniques for atmospheric trace gases retrievals. JQSRT 2008; 109:514-26.

An Integrated Retrieval Framework for AMSR2: Implications for Light Precipitation and Sea Ice Edge Detectability

NASA Astrophysics Data System (ADS)

Duncan, D.; Kummerow, C. D.; Meier, W.

2016-12-01

Over the lifetime of AMSR-E, operational retrieval algorithms were developed and run for precipitation, ocean suite (SST, wind speed, cloud liquid water path, and column water vapor over ocean), sea ice, snow water equivalent, and soil moisture. With a separate algorithm for each group, the retrievals were never interactive or integrated in any way despite many co-sensitivities. AMSR2, the follow-on mission to AMSR-E, retrieves the same parameters at a slightly higher spatial resolution. We have combined the operational algorithms for AMSR2 in a way that facilitates sharing information between the retrievals. Difficulties that arose were mainly related to calibration, spatial resolution, coastlines, and order of processing. The integration of all algorithms for AMSR2 has numerous benefits, including better detection of light precipitation and sea ice, fewer screened out pixels, and better quality flags. Integrating the algorithms opens up avenues for investigating the limits of detectability for precipitation from a passive microwave radiometer and the impact of spatial resolution on sea ice edge detection; these are investigated using CloudSat and MODIS coincident observations from the A-Train constellation.

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

NASA Technical Reports Server (NTRS)

Hodges, D. B.

1976-01-01

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

NASA's Potential Contributions to Avalanche Forecasting Using Active and Passive Microwave Measurements

NASA Technical Reports Server (NTRS)

Blonski, Slawomir

2007-01-01

This Candidate Solution is based on using active and passive microwave measurements acquired from NASA satellites to improve USDA (U.S. Department of Agriculture) Forest Service forecasting of avalanche danger. Regional Avalanche Centers prepare avalanche forecasts using ground measurements of snowpack and mountain weather conditions. In this Solution, range of the in situ observations is extended by adding remote sensing measurements of snow depth, snow water equivalent, and snowfall rate acquired by satellite missions that include Aqua, CloudSat, future GPM (Global Precipitation Measurement), and the proposed SCLP (Snow and Cold Land Processes). Measurements of snowpack conditions and time evolution are improved by combining the in situ and satellite observations with a snow model. Recurring snow observations from NASA satellites increase accuracy of avalanche forecasting, which helps the public and the managers of public facilities make better avalanche safety decisions.

Performance of greenhouse gas profiling by infrared-laser and microwave occultation in cloudy air

NASA Astrophysics Data System (ADS)

Proschek, V.; Kirchengast, G.; Emde, C.; Schweitzer, S.

2012-12-01

ACCURATE is a proposed future satellite mission enabling simultaneous measurements of greenhouse gases (GHGs), wind and thermodynamic variables from Low Earth Orbit (LEO). The measurement principle is a combination of LEO-LEO infrared-laser occultation (LIO) and microwave occultation (LMO), the LMIO method, where the LIO signals are very sensitive to clouds. The GHG retrieval will therefore be strongly influenced by clouds in parts of the troposphere. The IR-laser signals, at wavelengths within 2--2.5μ m, are chosen to measure six GHGs (H2O, CO2, CH4, N2O, O3, CO; incl.~key isotopes 13CO2, C18OO, HDO). The LMO signals enable to co-measure the thermodynamic variables. In this presentation we introduce the algorithm to retrieve GHG profiles under cloudy-air conditions by using quasi-realistic forward simulations, including also influence of Rayleigh scattering, scintillations and aerosols. Data from CALIPSO--Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations--with highest vertical resolution of about 60 m and horizontal resolution of about 330 m were used for simulation of clouds. The IR-laser signals consist for each GHG of a GHG-sensitive and a close-by reference signal. The key process, ``differencing'' of these two signals, removes the atmospheric ``broadband'' effects, resulting in a pure GHG transmission profile. Very thin ice clouds, like sub-visible cirrus, are fairly transparent to the IR-laser signals, thicker and liquid water clouds block the signals. The reference signal is used to produce a cloud layering profile from zero to blocking clouds and is smoothed in a preprocess to suppress scintillations. Sufficiently small gaps, of width <2 km in the cloud layering profile, are found to enable a decent retrieval of entire GHG profiles over the UTLS under broken cloudiness and are therefore bridged by interpolation. Otherwise in case of essentially continuous cloudiness the profiles are found to terminate at cloud top level. The accuracy of retrieved GHG profiles is found better than 1% to 4% for single profiles in the UTLS region outside clouds and through broken cloudiness, and the profiles are essentially unbiased. Cloud gap-interpolation increases the tropospheric penetration of GHG profiles for scientific applications. The associated cloud layering profile provides quality-control information on cloud gap-interpolations, if they occured, and on cloud-top altitude for cloud blocking cases. The LMIO technique shows promising prospects for GHG monitoring even under cloudy-air conditions.

Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

2003-01-01

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Anvil Clouds of Tropical Mesoscale Convective Systems in Monsoon Regions

NASA Technical Reports Server (NTRS)

Cetrone, J.; Houze, R. A., Jr.

2009-01-01

The anvil clouds of tropical mesoscale convective systems (MCSs) in West Africa, the Maritime Continent and the Bay of Bengal have been examined with TRMM and CloudSat satellite data and ARM ground-based radar observations. The anvils spreading out from the precipitating cores of MCSs are subdivided into thick, medium and thin portions. The thick portions of anvils show distinct differences from one climatological regime to another. In their upper portions, the thick anvils of West Africa MCSs have a broad, flat histogram of reflectivity, and a maximum of reflectivity in their lower portions. The reflectivity histogram of the Bay of Bengal thick anvils has a sharply peaked distribution of reflectivity at all altitudes with modal values that increase monotonically downward. The reflectivity histogram of the Maritime Continent thick anvils is intermediate between that of the West Africa and Bay of Bengal anvils, consistent with the fact this region comprises a mix of land and ocean influences. It is suggested that the difference between the statistics of the continental and oceanic anvils is related to some combination of two factors: (1) the West African anvils tend to be closely tied to the convective regions of MCSs while the oceanic anvils are more likely to be extending outward from large stratiform precipitation areas of MCSs, and (2) the West African MCSs result from greater buoyancy, so that the convective cells are more likely to produce graupel particles and detrain them into anvils

Synopsis of TC4 Missions and Meteorology

NASA Astrophysics Data System (ADS)

Starr, D.; Pfister, L.; Selkirk, H.; Nguyen, L.

2007-12-01

The TC4 (Tropical Composition, Clouds and Climate Coupling) Experiment conducted 26 aircraft sorties on 13 flight days from July 17 to August 8, 2007 (23 days). Quality science observations were also obtained during the transit flights to/from from San Jose, Costa Rica, where the mission was based. On 9 days, coordinated aircraft missions were flown with the NASA ER-2 and DC-8, and with the NASA WB-57 on 3 occasions (and transit flights). The ER-2 served as an A-Train simulator (MODIS, CloudSat, CALIPSO, AIRS/TES, partial AMSR-E) while the WB-57 provided in-situ measurements of upper tropospheric cloud particles, aerosols and trace gases. The DC-8 provided both in-situ and remote sensing measurements, where the latter were focused on Aura validation, and also including a down-looking scanning precipitation radar (TRMM PR simulator). This paper will provide a synopsis of the science observations that were obtained, as regards the clouds and cloud systems sampled, from a meteorological perspective. A diversity of clouds were sampled and the meteorology proved more interesting than expected, at least to this author. Upper tropospheric cirrus outflows were sampled from a number of convective cloud systems including ITCZ-type systems as well as systems close to and affected by land. The low level inflows to these systems were also sampled in some cases (DC-8) and missions were flown to sample stratocumulus clouds over the Pacific Ocean exploiting the unique instrumentation on the DC-8 to add to the knowledge of these clouds which are so important to the Earth radiation budget. Measurements were made in the tropical Tropopause Transition Layer (TTL) by the WB-57. Upper tropospheric clouds and TTL properties and processes were central TC4 objectives. Excellent data were also obtained on the fate of the Saharan Air Layer and its aerosols over the Caribbean and Central America, as well as samples of plumes from volcanoes in Ecuador and Columbia and biogenic emissions over Columbia and the Pacific Ocean. Satellite observations, including those from various A-Train sensors, were used in planning the missions which were, in many cases, coordinated, at least in part, with satellite overpasses, especially Aura and other A-Train sensors (DC-8) and Terra.

Analysis of actinic flux profiles measured from an ozonesonde balloon

NASA Astrophysics Data System (ADS)

Wang, P.; Allaart, M.; Knap, W. H.; Stammes, P.

2015-04-01

A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling-Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

NASA Astrophysics Data System (ADS)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

2013-01-01

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds.

PubMed

Miller, Daniel J; Zhang, Zhibo; Ackerman, Andrew S; Platnick, Steven; Baum, Bryan A

2016-04-27

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness ( τ ) and effective radius ( r e ) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5-10 g/m 2 . In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic r e profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques.

The impact of cloud vertical profile on liquid water path retrieval based on the bispectral method: A theoretical study based on large-eddy simulations of shallow marine boundary layer clouds

PubMed Central

Miller, Daniel J.; Zhang, Zhibo; Ackerman, Andrew S.; Platnick, Steven; Baum, Bryan A.

2018-01-01

Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness (τ) and effective radius (re) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS-like satellite retrievals, which in turn are compared directly to the large-eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5–10 g/m2. In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic re profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques. PMID:29637042

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

NASA Technical Reports Server (NTRS)

Stanfield, Ryan E.; Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Del Genio, Anthony D.; Minnia, Patrick; Jiang, Jonathan H.

2014-01-01

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

Cloud properties and bulk microphysical properties of semi-transparent cirrus from IR Sounders

NASA Astrophysics Data System (ADS)

Stubenrauch, Claudia; Feofilov, Artem; Armante, Raymond; Guignard, Anthony

2013-04-01

Satellite observations provide a continuous survey of the atmosphere over the whole globe. IR sounders have been observing our planet since 1979. The spectral resolution has improved from TIROS-N Operational Vertical Sounders (TOVS) to the Atmospheric InfraRed Sounder (AIRS), and to the InfraRed Atmospheric Sounding Interferometer (IASI); resolution within the CO2 absorption band makes these passive sounders most sensitive to semi-transparent cirrus (about 30% of all clouds), day and night. The LMD cloud property retrieval method developed for TOVS, has been adapted to the second generation of IR sounders like AIRS and, recently, IASI. It is based on a weighted χ2 method using different channels within the 15 micron CO2 absorption band. Once the cloud physical properties (cloud pressure and IR emissivity) are retrieved, cirrus bulk microphysical properties (De and IWP) are determined from spectral emissivity differences between 8 and 12 μm. The emissivities are determined using the retrieved cloud pressure and are then compared to those simulated by the radiative transfer model. For IASI, we use the latest version of the radiative transfer model 4A (http://4aop.noveltis.com), which has been coupled with the DISORT algorithm to take into account multiple scattering of ice crystals. The code incorporates single scattering properties of column-like or aggregate-like ice crystals provided by MetOffice (Baran et al. (2001); Baran and Francis (2004)). The synergy of AIRS and two active instruments of the A-Train (lidar and radar of the CALIPSO and CloudSat missions), which provide accurate information on vertical cloud structure, allowed the evaluation of cloud properties retrieved by the weighted χ2 method. We present first results for cloud properties obtained with IASI/ Metop-A and compare them with those of AIRS and other cloud climatologies having participated in the GEWEX cloud assessment. The combination of IASI observations at 9:30 AM and 9:30 PM complement the AIRS observations at 1:30 AM and 1:30 PM local time, giving information on the diurnal cycle of clouds. References: Baran, A.J. and Francis, P.N. and Havemann, S. and Yang, P: A study of the absorption and extinction properties of hexagonal ice columns and plates in random and preferred orientation, using exact T-matrix theory and aircraft observations of cirrus, J. Quant. Spectrosc. Ra., 70, 505-518, 2001 Baran, A. J. and Francis, P. N.: On the radiative properties of cirrus cloud at solar and thermal wavelengths:A test of model consistency using high-resolution airborne radiance measurements, Q. J. Roy. Meteor. Soc.,130, 763-778, 2004.

Retrieving Atmospheric Profiles Data in the Presence of Clouds from Hyperspectral Remote Sensing Data

NASA Technical Reports Server (NTRS)

Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.;

Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations

NASA Astrophysics Data System (ADS)

Watson-Parris, Duncan; Schutgens, Nick; Cook, Nicholas; Kipling, Zak; Kershaw, Philip; Gryspeerdt, Edward; Lawrence, Bryan; Stier, Philip

2016-09-01

The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field.

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

NASA Technical Reports Server (NTRS)

Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

2016-01-01

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Aerosol impacts on deep convective storms in the tropics: A combination of modeling and observations

NASA Astrophysics Data System (ADS)

Storer, Rachel Lynn

It is widely accepted that increasing the number of aerosols available to act as cloud condensation nuclei (CCN) will have significant effects on cloud properties, both microphysical and dynamical. This work focuses on the impacts of aerosols on deep convective clouds (DCCs), which experience more complicated responses than warm clouds due to their strong dynamical forcing and the presence of ice processes. Several previous studies have seen that DCCs may be invigorated by increasing aerosols, though this is not the case in all scenarios. The precipitation response to increased aerosol concentrations is also mixed. Often precipitation is thought to decrease due to a less efficient warm rain process in polluted clouds, yet convective invigoration would lead to an overall increase in surface precipitation. In this work, modeling and observations are both used in order to enhance our understanding regarding the effects of aerosols on DCCs. Specifically, the area investigated is the tropical East Atlantic, where dust from the coast of Africa frequently is available to interact with convective storms over the ocean. The first study investigates the effects of aerosols on tropical DCCs through the use of numerical modeling. A series of large-scale, two-dimensional cloud-resolving model simulations was completed, differing only in the concentration of aerosols available to act as CCN. Polluted simulations contained more deep convective clouds, wider storms, higher cloud tops and more convective precipitation across the entire domain. Differences in the warm cloud microphysical processes were largely consistent with aerosol indirect theory, and the average precipitation produced in each DCC column decreased with increasing aerosol concentration. A detailed microphysical budget analysis showed that the reduction in collision and coalescence largely dominated the trend in surface precipitation; however the production of rain through the melting of ice, though it also decreased, became more important as the aerosol concentration increased. The DCCs in polluted simulations contained more frequent, stronger updrafts and downdrafts, but the average updraft speed decreased with increasing aerosols in DCCs above 6 km. An examination of the buoyancy term of the vertical velocity equation demonstrates that the drag associated with condensate loading is an important factor in determining the average updraft strength. The largest contributions to latent heating in DCCs were cloud nucleation and vapor deposition onto water and ice, but changes in latent heating were, on average, an order of magnitude smaller than those in the condensate loading term. It is suggested that the average updraft is largely influenced by condensate loading in the more extensive stratiform regions of the polluted storms, while invigoration in the convective core leads to stronger updrafts and higher cloud tops. The goal of the second study was to examine observational data for evidence that would support the findings of the modeling work. In order to do this, four years of CloudSat data were analyzed over a region of the East Atlantic, chosen for the similarity (in meteorology and the presence of aerosols) to the modeling study. The satellite data were combined with information about aerosols taken from the output of a global transport model, and only those profiles fitting the definition of deep convective clouds were analyzed. Overall, the cloud center of gravity, cloud top, rain top, and ice water path were all found to increase with increased aerosol loading. These findings are in agreement with what was found in the modeling work, and are suggestive of convective invigoration with increased aerosols. In order to separate environmental effects from that due to aerosols, the data were sorted by environmental convective available potential energy (CAPE) and lower tropospheric static stability (LTSS). The aerosol effects were found to be largely independent of the environment. A simple statistical test suggests that the difference between the cleanest and most polluted clouds sampled are significant, lending credence to the hypothesis of convective invigoration. This is the first time evidence of deep convective invigoration has been demonstrated within a large region and over a long time period, and it is quite promising that there are many similarities between the modeling and observational results.

Intercomparison of spaceborne precipitation radars and its applications in examining precipitation-topography relationships in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, G.; Gao, J.; Long, D.

2017-12-01

Precipitation is one of the most important components in the water and energy cycles. Spaceborne radars are considered the most direct technology for observing precipitation from space since 1998. This study compares and evaluates the only three existing spaceborne precipitation radars, i.e., the Ku-band precipitation radar (TRMM PR), the W-band Cloud Profiling Radar (CloudSat CPR), and the Ku/Ka-band Dual-frequency Precipitation Radar (GPM DPR). In addition, TRMM PR and GPM DPR are evaluated against hourly rain gauge data in Mainland China. The Tibetan Plateau (TP) is known as the Earth's third pole where precipitation is affected profoundly by topography. However, ground gauges are extremely sparse in the TP, and spaceborne radars can provide valuable data with relatively high accuracy. The relationships between precipitation and topography over the TP are investigated using 17-year TRMM PR data and 2-year GPM DPR data, in combination with rain gauge data. Results indicate that: (1) DPR and PR agree with each other and correlate very well with gauges in Mainland China. DPR improves light precipitation detectability significantly compared with PR. However, DPR high sensitivity scans (HS) deviates from DPR normal and matched scans (NS and MS) and PR in the comparison based on global coincident events and rain gauges in China; (2) CPR outperforms the other two radars in terms of light precipitation detection. In terms of global snowfall estimation, DPR and CPR show very different global snowfall distributions originating from different frequencies, retrieval algorithms, and sampling characteristics; and (3) Precipitation generally decreases exponentially with increasing elevation in the TP. The precipitation-topography relationships are regressed using exponential fitting in seventeen river basins in the TP with good coefficients of determination. Due to the short time span of GPM DPR, the relationships based on GPM DPR data are less robust than those derived from TRMM PR data. The Level-3 precipitation products, i.e., GPM IMERG and GSMaP, can reproduce the general pattern on how precipitation varies with elevation but misrepresent some important details.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

Comparing the cloud vertical structure derived from several methods based on measured atmospheric profiles and active surface measurements

NASA Astrophysics Data System (ADS)

Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.

2013-06-01

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds in a changing climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 125 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The overall agreement for the methods ranges between 44-88%; four methods produce total agreements around 85%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, which could be useful in atmospheric modeling. The total agreement, even when using low resolution profiles, can be improved up to 91% if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

Nighttime lidar water vapor mixing ratio profiling over Warsaw - impact of the relative humidity profile on cloud formation

NASA Astrophysics Data System (ADS)

Costa Surós, Montserrat; Stachlewska, Iwona S.

2016-04-01

A long-term study, assessing ground-based remote Raman lidar versus in-situ radiosounding has been conducted with the aim of improving the knowledge on the water content vertical profile through the atmosphere, and thus the conditions for cloud formation processes. Water vapor mixing ratio (WVMR) and relative humidity (RH) profiles were retrieved from ADR Lidar (PollyXT-type, EARLINET site in Warsaw). So far, more than 100 nighttime profiles averaged over 1h around midnight from July 2013 to December 2015 have been investigated. Data were evaluated with molecular extinctions calculated using two approximations: the US62 standard atmosphere and the radiosounding launched in Legionowo (12374). The calibration factor CH2O for lidar retrievals was obtained for each profile using the regression method and the profile method to determine the best calibration factor approximation to be used in the final WVMR and RH calculation. Thus, statistically representative results for comparisons between lidar WVMR median profiles obtained by calibrating using radiosounding profiles and using atmospheric synthetic profiles, all of them with the best calibration factor, will be presented. Finally, in order to constrain the conditions of cloud formation in function of the RH profile, the COS14 algorithm, capable of deriving cloud bases and tops by applying thresholds to the RH profiles, was applied to find the cloud vertical structure (CVS). The algorithm was former applied to radiosounding profiles at SGP-ARM site and tested against the CVS obtained from the Active Remote Sensing of Clouds (ARSCL) data. Similarly, it was applied for lidar measurements at the Warsaw measurement site.

Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast

NASA Astrophysics Data System (ADS)

Masselink, Thomas; Schluessel, P.

1995-12-01

Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.

Derivation of Cloud Heating Rate Profiles using observations of Mixed-Phase Arctic Clouds: Impacts of Solar Zenith Angle

NASA Astrophysics Data System (ADS)

Zhang, G.; McFarquhar, G.; Poellot, M.; Verlinde, J.; Heymsfield, A.; Kok, G.

2005-12-01

Arctic stratus clouds play an important role in the energy balance of the Arctic region. Previous studies have suggested that Arctic stratus persist due to a balance among cloud top radiation cooling, latent heating, ice crystal fall out and large scale forcing. In this study, radiative heating profiles through Arctic stratus are computed using cloud, surface and thermodynamic observations obtained during the Mixed-Phase Arctic Cloud Experiment (M-PACE) as input to the radiative transfer model STREAMER. In particular, microphysical and macrophycial cloud properties such as phase, water content, effective particle size, particle shape, cloud height and cloud thickness were derived using data collected by in-situ sensors on the University of North Dakota (UND) Citation and ground-based remote sensors at Barrow and Oliktok Point. Temperature profiles were derived from radiosonde launches and a fresh snow surface was assumed. One series of sensitivity studies explored the dependence of the heating profile on the solar zenith angle. For smaller solar zenith angles, more incoming solar radiation is received at cloud top acting to counterbalance infrared cooling. As solar zenith angle in the Arctic is large compared to low latitudes, a large solar zenith angle may contribute to the longevity of these clouds.

Normalized vertical ice mass flux profiles from vertically pointing 8-mm-wavelength Doppler radar

NASA Technical Reports Server (NTRS)

Orr, Brad W.; Kropfli, Robert A.

1993-01-01

During the FIRE 2 (First International Satellite Cloud Climatology Project Regional Experiment) project, NOAA's Wave Propagation Laboratory (WPL) operated its 8-mm wavelength Doppler radar extensively in the vertically pointing mode. This allowed for the calculation of a number of important cirrus cloud parameters, including cloud boundary statistics, cloud particle characteristic sizes and concentrations, and ice mass content (imc). The flux of imc, or, alternatively, ice mass flux (imf), is also an important parameter of a cirrus cloud system. Ice mass flux is important in the vertical redistribution of water substance and thus, in part, determines the cloud evolution. It is important for the development of cloud parameterizations to be able to define the essential physical characteristics of large populations of clouds in the simplest possible way. One method would be to normalize profiles of observed cloud properties, such as those mentioned above, in ways similar to those used in the convective boundary layer. The height then scales from 0.0 at cloud base to 1.0 at cloud top, and the measured cloud parameter scales by its maximum value so that all normalized profiles have 1.0 as their maximum value. The goal is that there will be a 'universal' shape to profiles of the normalized data. This idea was applied to estimates of imf calculated from data obtained by the WPL cloud radar during FIRE II. Other quantities such as median particle diameter, concentration, and ice mass content can also be estimated with this radar, and we expect to also examine normalized profiles of these quantities in time for the 1993 FIRE II meeting.

Parameterization of cloud lidar backscattering profiles by means of asymmetrical Gaussians

NASA Astrophysics Data System (ADS)

del Guasta, Massimo; Morandi, Marco; Stefanutti, Leopoldo

1995-06-01

A fitting procedure for cloud lidar data processing is shown that is based on the computation of the first three moments of the vertical-backscattering (or -extinction) profile. Single-peak clouds or single cloud layers are approximated to asymmetrical Gaussians. The algorithm is particularly stable with respect to noise and processing errors, and it is much faster than the equivalent least-squares approach. Multilayer clouds can easily be treated as a sum of single asymmetrical Gaussian peaks. The method is suitable for cloud-shape parametrization in noisy lidar signatures (like those expected from satellite lidars). It also permits an improvement of cloud radiative-property computations that are based on huge lidar data sets for which storage and careful examination of single lidar profiles can't be carried out.

Comparing the cloud vertical structure derived from several methods based on radiosonde profiles and ground-based remote sensing measurements

NASA Astrophysics Data System (ADS)

Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.

2014-08-01

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, are important characteristics in order to describe the impact of clouds on climate. In this work, several methods for estimating the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering the number and position of cloud layers, with a ground-based system that is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ in the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study, these methods are applied to 193 radiosonde profiles acquired at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site during all seasons of the year 2009 and endorsed by Geostationary Operational Environmental Satellite (GOES) images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e., when the whole CVS is estimated correctly) for the methods ranges between 26 and 64%; the methods show additional approximate agreement (i.e., when at least one cloud layer is assessed correctly) from 15 to 41%. Further tests and improvements are applied to one of these methods. In addition, we attempt to make this method suitable for low-resolution vertical profiles, like those from the outputs of reanalysis methods or from the World Meteorological Organization's (WMO) Global Telecommunication System. The perfect agreement, even when using low-resolution profiles, can be improved by up to 67% (plus 25% of the approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

Comparing the cloud vertical structure derived from several methods based on measured atmospheric profiles and active surface measurements

NASA Astrophysics Data System (ADS)

Costa-Surós, M.; Calbó, J.; González, J. A.; Long, C. N.

2014-04-01

The cloud vertical distribution and especially the cloud base height, which is linked to cloud type, is an important characteristic in order to describe the impact of clouds on climate. In this work several methods to estimate the cloud vertical structure (CVS) based on atmospheric sounding profiles are compared, considering number and position of cloud layers, with a ground based system which is taken as a reference: the Active Remote Sensing of Clouds (ARSCL). All methods establish some conditions on the relative humidity, and differ on the use of other variables, the thresholds applied, or the vertical resolution of the profile. In this study these methods are applied to 193 radiosonde profiles acquired at the ARM Southern Great Plains site during all seasons of year 2009 and endorsed by GOES images, to confirm that the cloudiness conditions are homogeneous enough across their trajectory. The perfect agreement (i.e. when the whole CVS is correctly estimated) for the methods ranges between 26-64%; the methods show additional approximate agreement (i.e. when at least one cloud layer is correctly assessed) from 15-41%. Further tests and improvements are applied on one of these methods. In addition, we attempt to make this method suitable for low resolution vertical profiles, like those from the outputs of reanalysis methods or from the WMO's Global Telecommunication System. The perfect agreement, even when using low resolution profiles, can be improved up to 67% (plus 25% of approximate agreement) if the thresholds for a moist layer to become a cloud layer are modified to minimize false negatives with the current data set, thus improving overall agreement.

Climate Variability during the TRMM Era: Relationships between TRMM Precipitation and Upper-Tropospheric Hydrometeors

NASA Technical Reports Server (NTRS)

Robertson, Franklin

2008-01-01

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In out analysis we are examining the question of 'What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS'. This will allow us to pursue fundamental issues of precipitation, efficiency, maintenance of upper-troposheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

Relationships Between TRMM Precipitation and Upper-Tropospheric Hydrometeors as Seen From AMSU-B/MHS and A-Train Sensors

NASA Technical Reports Server (NTRS)

Robertson, Franklin; Pittman, Jasna; Atkinson, Robert

2008-01-01

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In our analysis we are examining the question of "What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS". This will allow us to pursue fundamental issues of precipitation efficiency, maintenance of upper-tropospheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

Profiling of Atmospheric Water Vapor from the SSM/T-2 Radiometric Measurements

NASA Technical Reports Server (NTRS)

Wang, J. R.

2000-01-01

An advantage of using the millimeter-wave measurements for water vapor profiling is the ability to probe beyond a moderate cloud cover. Such a capability has been demonstrated from an airborne MIR (Millimeter-wave Imaging Radiometer) flight over the Pacific Ocean during an intense observation period of TOGA/COARE (Tropical Ocean Global Atmosphere/ Couple Ocean Atmospheric Response Experiment) in early 1993. A Cloud Lidar System (CLS) and MODIS Airborne Simulator (MAS) were on board the same aircraft to identify the presence of clouds and cloud type. The retrieval algorithm not only provides output of a water vapor profile, but also the cloud liquid water and approximate cloud altitude required to satisfy convergence of the retrieval. The validity of these cloud parameters has not been verified previously. In this document, these cloud parameters are compared with those derived from concurrent measurements from the CLS and AMPR (Advanced Microwave Precipitation Radiometer).

Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

NASA Astrophysics Data System (ADS)

MacDonald, Alexander B.; Dadashazar, Hossein; Chuang, Patrick Y.; Crosbie, Ewan; Wang, Hailong; Wang, Zhen; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.; Sorooshian, Armin

2018-04-01

This study uses airborne cloud water composition measurements to characterize the vertical structure of air-equivalent mass concentrations of water-soluble species in marine stratocumulus clouds off the California coast. A total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water-soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in-cloud altitude for particulate species directly emitted from sources below cloud without in-cloud sources (e.g., Cl- and Na+), (ii) an increase of concentration with in-cloud altitude (e.g., NO2- and formate), and (iii) species exhibiting a peak in concentration in the middle of cloud (e.g., non-sea-salt SO42-, NO3-, and organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed.

Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, Alexander B.; Dadashazar, Hossein; Chuang, Patrick Y.

This study uses airborne cloud water composition measurements to characterize the vertical structure of air-equivalent mass concentrations of water-soluble species in marine stratocumulus clouds off the California coast. A total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water-soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in-cloud altitude for particulate species directly emitted from sources below cloud without in-cloud sources (e.g., Cl-, Na+); (ii) an increase of concentration with in-cloud altitude (e.g., NO2-, formate); and (iii) species exhibiting a peakmore » in concentration in the middle of cloud (e.g., non-sea salt SO42-, NO3-, organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed.« less

Extinction-to-Backscatter Ratios of Lofted Aerosol Layers Observed During the First Three Months of CALIPSO Measurements

NASA Technical Reports Server (NTRS)

Omar, Ali H.; Vaughan, Mark A.; Liu, Zhaoyan; Hu, Yongxiang; Reagan, John A.; Winker, David M.

2007-01-01

Case studies from the first three months of the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) measurements of lofted aerosol layers are analyzed using transmittance [Young, 1995] and two-wavelength algorithms [Vaughan et al., 2004] to determine the aerosol extinction-to-backscatter ratios at 532 and 1064 nm. The transmittance method requires clear air below the layer so that the transmittance through the layer can be determined. Suitable scenes are selected from the browse images and clear air below features is identified by low 532 nm backscatter signal and confirmed by low depolarization and color ratios. The transmittance and two-wavelength techniques are applied to a number of lofted layers and the extinction-to-backscatter ratios are compared with values obtained from the CALIPSO aerosol models [Omar et al., 2004]. The results obtained from these studies are used to adjust the aerosol models and develop observations based extinction-to-backscatter ratio look-up tables and phase functions. Values obtained by these techniques are compared to Sa determinations using other independent methods with a goal of developing probability distribution functions of aerosol type-specific extinction to backscatter ratios. In particular, the results are compared to values determined directly by the High Spectral Resolution Lidar (HSRL) during the CALIPSO CloudSat Validation Experiments (CCVEX) and Sa determined by the application of the two-wavelength lidar Constrained Ratio Aerosol Model-fit (CRAM) retrieval approach [Cattrall et al., 2005; Reagan et al., 2004] to the HSRL data. The results are also compared to values derived using the empirical relationship between the multiple-scattering fraction and the linear depolarization ratio by using Monte Carlo simulations of water clouds [Hu et al., 2006].

A multi-sensor study of the impact of ground-based glaciogenic seeding on clouds and precipitation over mountains in Wyoming. Part I: Project description

NASA Astrophysics Data System (ADS)

Pokharel, Binod; Geerts, Bart

2016-12-01

The AgI Seeding Cloud Impact Investigation (ASCII) campaign was conducted in early 2012 and 2013 over two mountain ranges in southern Wyoming to examine the impact of ground-based glaciogenic seeding on snow growth in winter orographic clouds. The campaign was supported by a network of ground-based instruments, including microwave radiometers, two profiling Ka-band Micro-Rain Radars (MRRs), a Doppler on Wheels (DOW) X-band radar, and a Parsivel disdrometer. The University of Wyoming King Air operated the profiling Wyoming Cloud Radar, the Wyoming Cloud Lidar, and in situ cloud and precipitation particle probes. The characteristics of the orographic clouds, flow field, and upstream stability profiles in 27 intensive observation periods (IOPs) are described here. A composite analysis of the impact of seeding on snow growth is presented in Part II of this study (Pokharel et al., 2017).

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

NASA Astrophysics Data System (ADS)

DeSouza-Machado, Sergio; Larrabee Strow, L.; Tangborn, Andrew; Huang, Xianglei; Chen, Xiuhong; Liu, Xu; Wu, Wan; Yang, Qiguang

2018-01-01

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2-4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper.

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

NASA Technical Reports Server (NTRS)

Smith, Cosmo

2011-01-01

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

The evaluation of GCMs and a new cloud parameterisation using satellite and in-situ data as part of a Climate Process Team

NASA Astrophysics Data System (ADS)

Grosvenor, D. P.; Wood, R.

2012-12-01

As part of one of the Climate Process Teams (CPTs) we have been testing the implementation of a new cloud parameterization into the CAM5 and AM3 GCMs. The CLUBB parameterization replaces all but the deep convection cloud scheme and uses an innovative PDF based approach to diagnose cloud water content and turbulence. We have evaluated the base models and the CLUBB parameterization in the SE Pacific stratocumulus region using a suite of satellite observation metrics including: Liquid Water Path (LWP) measurements from AMSRE; cloud fractions from CloudSat/CALIPSO; droplet concentrations (Nd) and Cloud Top Temperatures from MODIS; CloudSat precipitation; and relationships between Estimated Inversion Strength (calculated from AMSRE SSTs, Cloud Top Temperatures from MODIS and ECMWF re-analysis fields) and cloud fraction. This region has the advantage of an abundance of in-situ aircraft observations taken during the VOCALS campaign, which is facilitating the diagnosis of the model problems highlighted by the model evaluation. This data has also been recently used to demonstrate the reliability of MODIS Nd estimates. The satellite data needs to be filtered to ensure accurate retrievals and we have been careful to apply the same screenings to the model fields. For example, scenes with high cloud fractions and with output times near to the satellite overpass times can be extracted from the model for a fair comparison with MODIS Nd estimates. To facilitate this we have been supplied with instantaneous model output since screening would not be possible based on time averaged data. We also have COSP satellite simulator output, which allows a fairer comparison between satellite and model. For example, COSP cloud fraction is based upon the detection threshold of the satellite instrument in question. These COSP fields are also used for the model output filtering just described. The results have revealed problems with both the base models and the versions with the CLUBB parameterization. The CAM5 model produces realistic near-coast cloud cover, but too little further west in the stratocumulus to cumulus regions. The implementation of CLUBB has vastly improved this situation with cloud cover that is very similar to that observed. CLUBB also improves the Nd field in CAM5 by producing realistic near-coast increases and by removing high Nd values associated with the detrainment of droplets by cumulus clouds. AM3 has a lack of stratocumulus cloud near the South American coast and has much lower droplet concentrations than observed. VOCALS measurements showed that sulfate mass loadings were generally too high in both base models, whereas CCN concentrations were too low. This suggests a problem with the mass distribution partitioning of sulfate that is being investigated. Diurnal and seasonal comparisons have been very illuminating. CLUBB produces very little diurnal variation in LWP, but large variations in precipitation rates. This is likely to point to problems that are now being addressed by the modeling part of the CPT team, creating an iterative workflow process between the model developers and the model testers, which should facilitate efficient parameterization improvement. We will report on the latest developments of this process.

Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

NASA Technical Reports Server (NTRS)

Titlow, James; Baum, Bryan A.

1993-01-01

Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.

SAGE II

Atmospheric Science Data Center

2016-02-16

... the spatial distributions of stratospheric aerosols, ozone, nitrogen dioxide, water vapor and cloud occurrence by mapping vertical profiles ... Clouds Clouds in a Clear Sky Clouds in the Balance Stars Clouds Crops Volcanoes and Climate Change ...

Optical property retrievals of subvisual cirrus clouds from OSIRIS limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2012-08-01

We present a technique for retrieving the optical properties of subvisual cirrus clouds detected by OSIRIS, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Optical properties from an in-situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is demonstrated that the retrieved extinction profile models accurately the measured in-cloud radiances from OSIRIS. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Climate Simulations from Super-parameterized and Conventional General Circulation Models with a Third-order Turbulence Closure

NASA Astrophysics Data System (ADS)

Xu, Kuan-Man; Cheng, Anning

2014-05-01

A high-resolution cloud-resolving model (CRM) embedded in a general circulation model (GCM) is an attractive alternative for climate modeling because it replaces all traditional cloud parameterizations and explicitly simulates cloud physical processes in each grid column of the GCM. Such an approach is called "Multiscale Modeling Framework." MMF still needs to parameterize the subgrid-scale (SGS) processes associated with clouds and large turbulent eddies because circulations associated with planetary boundary layer (PBL) and in-cloud turbulence are unresolved by CRMs with horizontal grid sizes on the order of a few kilometers. A third-order turbulence closure (IPHOC) has been implemented in the CRM component of the super-parameterized Community Atmosphere Model (SPCAM). IPHOC is used to predict (or diagnose) fractional cloudiness and the variability of temperature and water vapor at scales that are not resolved on the CRM's grid. This model has produced promised results, especially for low-level cloud climatology, seasonal variations and diurnal variations (Cheng and Xu 2011, 2013a, b; Xu and Cheng 2013a, b). Because of the enormous computational cost of SPCAM-IPHOC, which is 400 times of a conventional CAM, we decided to bypass the CRM and implement the IPHOC directly to CAM version 5 (CAM5). IPHOC replaces the PBL/stratocumulus, shallow convection, and cloud macrophysics parameterizations in CAM5. Since there are large discrepancies in the spatial and temporal scales between CRM and CAM5, IPHOC used in CAM5 has to be modified from that used in SPCAM. In particular, we diagnose all second- and third-order moments except for the fluxes. These prognostic and diagnostic moments are used to select a double-Gaussian probability density function to describe the SGS variability. We also incorporate a diagnostic PBL height parameterization to represent the strong inversion above PBL. The goal of this study is to compare the simulation of the climatology from these three models (CAM5, CAM5-IPHOC and SPCAM-IPHOC), with emphasis on low-level clouds and precipitation. Detailed comparisons of scatter diagrams among the monthly-mean low-level cloudiness, PBL height, surface relative humidity and lower tropospheric stability (LTS) reveal the relative strengths and weaknesses for five coastal low-cloud regions among the three models. Observations from CloudSat and CALIPSO and ECMWF Interim reanalysis are used as the truths for the comparisons. We found that the standard CAM5 underestimates cloudiness and produces small cloud fractions at low PBL heights that contradict with observations. CAM5-IPHOC tends to overestimate low clouds but the ranges of LTS and PBL height variations are most realistic. SPCAM-IPHOC seems to produce most realistic results with relatively consistent results from one region to another. Further comparisons with other atmospheric environmental variables will be helpful to reveal the causes of model deficiencies so that SPCAM-IPHOC results will provide guidance to the other two models.

Thermodynamic and cloud parameter retrieval using infrared spectral data

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.

2005-01-01

High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

SACR ADVance 3-D Cartesian Cloud Cover (SACR-ADV-3D3C) product

DOE Data Explorer

Meng Wang, Tami Toto, Eugene Clothiaux, Katia Lamer, Mariko Oue

2017-03-08

SACR-ADV-3D3C remaps the outputs of SACRCORR for cross-wind range-height indicator (CW-RHI) scans to a Cartesian grid and reports reflectivity CFAD and best estimate domain averaged cloud fraction. The final output is a single NetCDF file containing all aforementioned corrected radar moments remapped on a 3-D Cartesian grid, the SACR reflectivity CFAD, a profile of best estimate cloud fraction, a profile of maximum observable x-domain size (xmax), a profile time to horizontal distance estimate and a profile of minimum observable reflectivity (dBZmin).

Lidar characterizations of atmospheric aerosols and clouds

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Burton, S. P.

2017-12-01

Knowledge of the vertical profile, composition, concentration, and size distribution of aerosols is required to quantify the impacts of aerosols on human health, global and regional climate, clouds and precipitation. In particular, radiative forcing due to anthropogenic aerosols is the most uncertain part of anthropogenic radiative forcing, with aerosol-cloud interactions (ACI) as the largest source of uncertainty in current estimates of global radiative forcing. Improving aerosol transport model predictions of the vertical profile of aerosol optical and microphysical characteristics is crucial for improving assessments of aerosol radiative forcing. Understanding how aerosols and clouds interact is essential for investigating the aerosol indirect effect and ACI. Through its ability to provide vertical profiles of aerosol and cloud distributions as well as important information regarding the optical and physical properties of aerosols and clouds, lidar is a crucial tool for addressing these science questions. This presentation describes how surface, airborne, and satellite lidar measurements have been used to address these questions, and in particular how High Spectral Resolution Lidar (HSRL) measurements provide profiles of aerosol properties (backscatter, extinction, depolarization, concentration, size) important for characterizing radiative forcing. By providing a direct measurement of aerosol extinction, HSRL provides more accurate aerosol measurement profiles and more accurate constraints for models than standard retrievals from elastic backscatter lidar, which loses accuracy and precision at lower altitudes due to attenuation from overlying layers. Information regarding particle size and abundance from advanced lidar retrievals provides better proxies for cloud-condensation-nuclei (CCN), which are required for assessing aerosol-cloud interactions. When combined with data from other sensors, advanced lidar measurements can provide information on aerosol and cloud properties for addressing both direct and indirect radiative forcing.

Jupiter's Deep Cloud Structure Revealed Using Keck Observations of Spectrally Resolved Line Shapes

NASA Technical Reports Server (NTRS)

Bjoraker, G. L.; Wong, M.H.; de Pater, I.; Adamkovics, M.

2015-01-01

Technique: We present a method to determine the pressure at which significant cloud opacity is present between 2 and 6 bars on Jupiter. We use: a) the strength of a Fraunhofer absorption line in a zone to determine the ratio of reflected sunlight to thermal emission, and b) pressure- broadened line profiles of deuterated methane (CH3D) at 4.66 meters to determine the location of clouds. We use radiative transfer models to constrain the altitude region of both the solar and thermal components of Jupiter's 5-meter spectrum. Results: For nearly all latitudes on Jupiter the thermal component is large enough to constrain the deep cloud structure even when upper clouds are present. We find that Hot Spots, belts, and high latitudes have broader line profiles than do zones. Radiative transfer models show that Hot Spots in the North and South Equatorial Belts (NEB, SEB) typically do not have opaque clouds at pressures greater than 2 bars. The South Tropical Zone (STZ) at 32 degrees South has an opaque cloud top between 4 and 5 bars. From thermochemical models this must be a water cloud. We measured the variation of the equivalent width of CH3D with latitude for comparison with Jupiter's belt-zone structure. We also constrained the vertical profile of H2O in an SEB Hot Spot and in the STZ. The Hot Spot is very dry for a probability less than 4.5 bars and then follows the H2O profile observed by the Galileo Probe. The STZ has a saturated H2O profile above its cloud top between 4 and 5 bars.

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2013-01-01

We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Radiative Heating of the ISCCP Upper Level Cloud Regimes and its Impact on the Large-scale Tropical Circulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Wei; Schumacher, Courtney; McFarlane, Sally A.

2013-01-31

Radiative heating profiles of the International Satellite Cloud Climatology Project (ISCCP) cloud regimes (or weather states) were estimated by matching ISCCP observations with radiative properties derived from cloud radar and lidar measurements from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) sites at Manus, Papua New Guinea, and Darwin, Australia. Focus was placed on the ISCCP cloud regimes containing the majority of upper level clouds in the tropics, i.e., mesoscale convective systems (MCSs), deep cumulonimbus with cirrus, mixed shallow and deep convection, and thin cirrus. At upper levels, these regimes have average maximum cloud occurrences ranging from 30% tomore » 55% near 12 km with variations depending on the location and cloud regime. The resulting radiative heating profiles have maxima of approximately 1 K/day near 12 km, with equal heating contributions from the longwave and shortwave components. Upper level minima occur near 15 km, with the MCS regime showing the strongest cooling of 0.2 K/day and the thin cirrus showing no cooling. The gradient of upper level heating ranges from 0.2 to 0.4 K/(day∙km), with the most convectively active regimes (i.e., MCSs and deep cumulonimbus with cirrus) having the largest gradient. When the above heating profiles were applied to the 25-year ISCCP data set, the tropics-wide average profile has a radiative heating maximum of 0.45Kday-1 near 250 hPa. Column-integrated radiative heating of upper level cloud accounts for about 20% of the latent heating estimated by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The ISCCP radiative heating of tropical upper level cloud only slightly modifies the response of an idealized primitive equation model forced with the tropics-wide TRMM PR latent heating, which suggests that the impact of upper level cloud is more important to large-scale tropical circulation variations because of convective feedbacks rather than direct forcing by the cloud radiative heating profiles. However, the height of the radiative heating maxima and gradient of the heating profiles are important to determine the sign and patterns of the horizontal circulation anomaly driven by radiative heating at upper levels.« less

NASA's Genesis and Rapid Intensification Processes (GRIP) Field Experiment

NASA Technical Reports Server (NTRS)

Braun, Scott A.; Kakar, Ramesh; Zipser, Edward; Heymsfield, Gerald; Albers, Cerese; Brown, Shannon; Durden, Stephen; Guimond, Stephen; Halverson, Jeffery; Heymsfield, Andrew;

Where is the level of neutral buoyancy for deep convection?

NASA Astrophysics Data System (ADS)

Takahashi, Hanii; Luo, Zhengzhao

2012-08-01

This study revisits an old concept in meteorology - level of neutral buoyancy (LNB). The classic definition of LNB is derived from the parcel theory and can be estimated from the ambient sounding (LNB_sounding) without having to observe any actual convective cloud development. In reality, however, convection interacts with the environment in complicated ways; it will eventually manage to find its own effective LNB and manifests it through detraining masses and developing anvils (LNB_observation). This study conducts a near-global survey of LNB_observation for tropical deep convection using CloudSat data and makes comparison with the corresponding LNB_sounding. The principal findings are as follows: First, although LNB_sounding provides a reasonable upper bound for convective development, correlation between LNB_sounding and LNB_observation is low suggesting that ambient sounding contains limited information for accurately predicting the actual LNB. Second, maximum mass outflow is located more than 3 km lower than LNB_sounding. Hence, from convective transport perspective, LNB_sounding is a significant overestimate of the “destination” height level of the detrained mass. Third, LNB_observation is consistently higher over land than over ocean, although LNB_sounding is similar between land and ocean. This difference is likely related to the contrasts in convective strength and environment between land and ocean. Finally, we estimate the bulk entrainment rates associated with the observed deep convection, which can serve as an observational basis for adjusting GCM cumulus parameterization.

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kollias, Pavlos

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

Development of High Altitude UAV Weather Radars for Hurricane Research

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald; Li, Li-Hua

2005-01-01

A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.

Cloud Detection Using Measured and Modeled State Parameters

NASA Technical Reports Server (NTRS)

Yi, Y.; Minnis, P.; Huang, J.; Ayers, J. K.; Doelling, D. R.; Khaiyer, M. M.; Nordeen, M. L.

2004-01-01

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

A simple biota removal algorithm for 35 GHz cloud radar measurements

NASA Astrophysics Data System (ADS)

Kalapureddy, Madhu Chandra R.; Sukanya, Patra; Das, Subrata K.; Deshpande, Sachin M.; Pandithurai, Govindan; Pazamany, Andrew L.; Ambuj K., Jha; Chakravarty, Kaustav; Kalekar, Prasad; Krishna Devisetty, Hari; Annam, Sreenivas

2018-03-01

Cloud radar reflectivity profiles can be an important measurement for the investigation of cloud vertical structure (CVS). However, extracting intended meteorological cloud content from the measurement often demands an effective technique or algorithm that can reduce error and observational uncertainties in the recorded data. In this work, a technique is proposed to identify and separate cloud and non-hydrometeor echoes using the radar Doppler spectral moments profile measurements. The point and volume target-based theoretical radar sensitivity curves are used for removing the receiver noise floor and identified radar echoes are scrutinized according to the signal decorrelation period. Here, it is hypothesized that cloud echoes are observed to be temporally more coherent and homogenous and have a longer correlation period than biota. That can be checked statistically using ˜ 4 s sliding mean and standard deviation value of reflectivity profiles. The above step helps in screen out clouds critically by filtering out the biota. The final important step strives for the retrieval of cloud height. The proposed algorithm potentially identifies cloud height solely through the systematic characterization of Z variability using the local atmospheric vertical structure knowledge besides to the theoretical, statistical and echo tracing tools. Thus, characterization of high-resolution cloud radar reflectivity profile measurements has been done with the theoretical echo sensitivity curves and observed echo statistics for the true cloud height tracking (TEST). TEST showed superior performance in screening out clouds and filtering out isolated insects. TEST constrained with polarimetric measurements was found to be more promising under high-density biota whereas TEST combined with linear depolarization ratio and spectral width perform potentially to filter out biota within the highly turbulent shallow cumulus clouds in the convective boundary layer (CBL). This TEST technique is promisingly simple in realization but powerful in performance due to the flexibility in constraining, identifying and filtering out the biota and screening out the true cloud content, especially the CBL clouds. Therefore, the TEST algorithm is superior for screening out the low-level clouds that are strongly linked to the rainmaking mechanism associated with the Indian Summer Monsoon region's CVS.

Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

NASA Technical Reports Server (NTRS)

Sinclair, Kenneth; Van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; Mcgill, Matthew

2017-01-01

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

Estimation of Cloud Fraction Profile in Shallow Convection Using a Scanning Cloud Radar

DOE PAGES

Oue, Mariko; Kollias, Pavlos; North, Kirk W.; ...

2016-10-18

Large spatial heterogeneities in shallow convection result in uncertainties in estimations of domain-averaged cloud fraction profiles (CFP). This issue is addressed using large eddy simulations of shallow convection over land coupled with a radar simulator. Results indicate that zenith profiling observations are inadequate to provide reliable CFP estimates. Use of Scanning Cloud Radar (SCR), performing a sequence of cross-wind horizon-to-horizon scans, is not straightforward due to the strong dependence of radar sensitivity to target distance. An objective method for estimating domain-averaged CFP is proposed that uses observed statistics of SCR hydrometeor detection with height to estimate optimum sampling regions. Thismore » method shows good agreement with the model CFP. Results indicate that CFP estimates require more than 35 min of SCR scans to converge on the model domain average. Lastly, the proposed technique is expected to improve our ability to compare model output with cloud radar observations in shallow cumulus cloud conditions.« less

Tropical High Cloud Fraction Controlled by Cloud Lifetime Rather Than Clear-sky Convergence

NASA Astrophysics Data System (ADS)

Seeley, J.; Jeevanjee, N.; Romps, D. M.

2016-12-01

Observations and simulations show a peak in cloud fraction below the tropopause. This peak is usually attributed to a roughly co-located peak in radiatively-driven clear-sky convergence, which is presumed to force convective detrainment and thus promote large cloud fraction. Using simulations of radiative-convective equilibrium forced by various radiative cooling profiles, we refute this mechanism by showing that an upper-tropospheric peak in cloud fraction persists even in simulations with no peak in clear-sky convergence. Instead, cloud fraction profiles seem to be controlled by cloud lifetimes — i.e., how long it takes for clouds to dissipate after they have detrained. A simple model of cloud evaporation shows that the small saturation deficit in the upper troposphere greatly extends cloud lifetimes there, while the large saturation deficit in the lower troposphere causes condensate to evaporate quickly. Since cloud mass flux must go to zero at the tropopause, a peak in cloud fraction emerges at a "sweet spot" below the tropopause where cloud lifetimes are long and there is still sufficient mass flux to be detrained.

The Effect of Clouds on Water Vapor Profiling from the Millimeter-Wave Radiometric Measurements

NASA Technical Reports Server (NTRS)

Wang, J. R.; Spinhirne, J. D.; Racette, P.; Chang, L. A.; Hart, W.

1997-01-01

Simultaneous measurements with the millimeter-wave imaging radiometer (MIR), cloud lidar system (CLS), and the MODIS airborne simulator (MAS) were made aboard the NASA ER-2 aircraft over the western Pacific Ocean on 17-18 January 1993. These measurements were used to study the effects of clouds on water vapor profile retrievals based on millimeter-wave radiometer measurements. The CLS backscatter measurements (at 0.532 and 1.064 am) provided information on the heights and a detailed structure of cloud layers; the types of clouds could be positively identified. All 12 MAS channels (0.6-13 Am) essentially respond to all types of clouds, while the six MIR channels (89-220 GHz) show little sensitivity to cirrus clouds. The radiances from the 12-/Am and 0.875-gm channels of the MAS and the 89-GHz channel of the MIR were used to gauge the performance of the retrieval of water vapor profiles from the MIR observations under cloudy conditions. It was found that, for cirrus and absorptive (liquid) clouds, better than 80% of the retrieval was convergent when one of the three criteria was satisfied; that is, the radiance at 0.875 Am is less than 100 W/cm.sr, or the brightness at 12 Am is greater than 260 K, or brightness at 89 GHz is less than 270 K (equivalent to cloud liquid water of less than 0.04 g/cm). The range of these radiances for convergent retrieval increases markedly when the condition for convergent retrieval was somewhat relaxed. The algorithm of water vapor profiling from the MIR measurements could not perform adequately over the areas of storm-related clouds that scatter radiation at millimeter wavelengths.

What are the associated parameters and temporal coverage?

Atmospheric Science Data Center

2014-12-08

... Extinction Coefficient, Cloud Vertical Profile, Radar-only Liquid Water Content, Radar-only Liquid Ice Content, Vertical Flux Profile, ... ISCCP-D2like Cloud fraction, Effective Pressure, Temperature, optical depth, IWP/LWP, particle size, IR Emissivity in ...

Vector velocity profiles of the solar wind within expanding magnetic clouds at 1 AU: Some surprises

NASA Astrophysics Data System (ADS)

Wu, C.; Lepping, R. P.; Berdichevsky, D.; Ferguson, T.; Lazarus, A. J.

2002-12-01

We investigated the average vector velocity profile of 36 carefully chosen WIND interplanetary magnetic clouds occurring over about a 7 year period since spacecraft launch, to see if a differential pattern of solar wind flow exists. Particular cases were chosen of clouds whose axes were generally within 45 degrees of the ecliptic plane and of relatively well determined characteristics obtained from cloud-parameter (cylindrically symmetric force free) fitting. This study was motivated by the desire to understand the manner in which magnetic clouds expand, a well know phenomenon revealed by most cloud speed-profiles at 1 AU. One unexpected and major result was that, even though cloud expansion was confirmed, it was primarily along the Xgse axis; i.e., neither the Ygse or Zgse velocity components reveal any noteworthy pattern. After splitting the full set of clouds into a north-passing set (spacecraft passing above the cloud, where Nn = 21) and south-passing set (Ns = 15), to study the plasma expansion of the clouds with respect to the position of the observer, it was seen that the Xgse component of velocity differs for these two sets in a rather uniform and measurable way for most of the average cloud's extent. This does not appear to be the case for the Ygse or Zgse velocity components where little measurable differences exists, and clearly no pattern, across the average cloud between the north and south positions. It is not clear why such a remarkably non-axisymmetric plasma flow pattern within the "average magnetic cloud" at 1 AU should exist. The study continues from the perspective of magnetic cloud coordinate representation. ~ ~ ~

A study of the 3D radiative transfer effect in cloudy atmospheres

NASA Astrophysics Data System (ADS)

Okata, M.; Teruyuki, N.; Suzuki, K.

2015-12-01

Evaluation of the effect of clouds in the atmosphere is a significant problem in the Earth's radiation budget study with their large uncertainties of microphysics and the optical properties. In this situation, we still need more investigations of 3D cloud radiative transer problems using not only models but also satellite observational data.For this purpose, we have developed a 3D-Monte-Carlo radiative transfer code that is implemented with various functions compatible with the OpenCLASTR R-Star radiation code for radiance and flux computation, i.e. forward and backward tracing routines, non-linear k-distribution parameterization (Sekiguchi and Nakajima, 2008) for broad band solar flux calculation, and DM-method for flux and TMS-method for upward radiance (Nakajima and Tnaka 1998). We also developed a Minimum cloud Information Deviation Profiling Method (MIDPM) as a method for a construction of 3D cloud field with MODIS/AQUA and CPR/CloudSat data. We then selected a best-matched radar reflectivity factor profile from the library for each of off-nadir pixels of MODIS where CPR profile is not available, by minimizing the deviation between library MODIS parameters and those at the pixel. In this study, we have used three cloud microphysical parameters as key parameters for the MIDPM, i.e. effective particle radius, cloud optical thickness and top of cloud temperature, and estimated 3D cloud radiation budget. We examined the discrepancies between satellite observed and mode-simulated radiances and three cloud microphysical parameter's pattern for studying the effects of cloud optical and microphysical properties on the radiation budget of the cloud-laden atmospheres.

Winter Far InfraRed Measurements in the High Arctic

NASA Astrophysics Data System (ADS)

S Pelletier, L.; Libois, Q.; Laurence, C.; Blanchet, J. P.

2017-12-01

During the polar night the majority of earth emission to space occurs in the Far InfraRed (FIR) (l>15mm). Below 10 mm of column integrated water vapour (WV) the atmosphere becomes partially transparent in this spectral range, extending the atmospheric window to longer wavelength. Small variations of WV content can thus lead to strong variations of the transmittance of the atmosphere, impacting its cooling rate and the water vapor greenhouse effect. This is especially true in the Arctic since more than 50% of atmospheric cooling occurs in the FIR. Furthermore, remote sensing observations from CALIPSO and CloudSat satellites over the Arctic have enlighten the ubiquity of optically thin ice clouds (TIC). Those clouds act as effective radiators through the whole troposphere and their formation process is still poorly understood. Theoretical work has shown the added value of FIR measurements for WV and TIC optical properties retrieval. Even so there is currently no spaceborne instrument performing spectrally resolved measurements in the FIR. The TICFIRE (Thin ice cloud in the far infrared experiment) satellite project aims to fill this gap. Here we present the results of the first ground experiments using a breadboard of the satellite, the Far InfraRed Radiometer (FIRR). It measured downwelling radiance at Eureka, NU (79°59'20″N 085°56'27″W) from 25/02/2016 to 31/05/2016. The FIRR uses an array of uncooled microbolometers to measure radiance in 9 spectral channels spanning from 8 - 50 μm. The emission of the atmosphere in this spectral region is extremely sensitive to its WV content and the effective diameter of TIC ice crystals. By comparing these measurements with the E-AERI, a Fourier transform interferometer which serves as a reference, and a radiative transfers model , we aim to assess the radiative accuracy of this new technology as well as its sensitivity to the state of the atmosphere. Results shows that the in situ radiometric accuracy of the FIRR matches laboratory performances (noise below 0.02 Wm-2sr-1). This paves the way for the development of TIC properties retrieval from ground measurements.

The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)

NASA Astrophysics Data System (ADS)

Chepfer, H.; Bony, S.; Winker, D.; Cesana, G.; Dufresne, J. L.; Minnis, P.; Stubenrauch, C. J.; Zeng, S.

2010-01-01

This article presents the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, Cloud-Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January-March 2007-2008 and June-August 2006-2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low-level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high-level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low-level and middle-level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate-Resolution Imaging Spectroradiometer-Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS-Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.

Horizontal Variability of Water and Its Relationship to Cloud Fraction near the Tropical Tropopause: Using Aircraft Observations of Water Vapor to Improve the Representation of Grid-scale Cloud Formation in GEOS-5

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Molod, Andrea M.

2014-01-01

Large-scale models such as GEOS-5 typically calculate grid-scale fractional cloudiness through a PDF parameterization of the sub-gridscale distribution of specific humidity. The GEOS-5 moisture routine uses a simple rectangular PDF varying in height that follows a tanh profile. While below 10 km this profile is informed by moisture information from the AIRS instrument, there is relatively little empirical basis for the profile above that level. ATTREX provides an opportunity to refine the profile using estimates of the horizontal variability of measurements of water vapor, total water and ice particles from the Global Hawk aircraft at or near the tropopause. These measurements will be compared with estimates of large-scale cloud fraction from CALIPSO and lidar retrievals from the CPL on the aircraft. We will use the variability measurements to perform studies of the sensitivity of the GEOS-5 cloud-fraction to various modifications to the PDF shape and to its vertical profile.

A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

NASA Technical Reports Server (NTRS)

Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

2011-01-01

This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

Production of Lightning NO(x) and its Vertical Distribution Calculated from 3-D Cloud-scale Chemical Transport Model Simulations

NASA Technical Reports Server (NTRS)

Ott, Lesley; Pickering, Kenneth; Stenchikov, Georgiy; Allen, Dale; DeCaria, Alex; Ridley, Brian; Lin, Ruei-Fong; Lang, Steve; Tao, Wei-Kuo

2009-01-01

A 3-D cloud scale chemical transport model that includes a parameterized source of lightning NO(x), based on observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P(sub IC) and cloud-to-ground (P(sub CG)) flash is estimated by assuming various values of P(sub IC) and P(sub CG) for each storm and determining which production scenario yields NO(x) mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P(sub CG) value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P(sub IC) may be nearly equal to P(sub CG), which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO(x), after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO(x), remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a "C-shaped" profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO(x) mass may place too much mass neat the surface and too little in the middle troposphere.

Cloud and Radiation Mission with Active and Passive Sensing from the Space Station

NASA Technical Reports Server (NTRS)

Spinhirne, James D.

1998-01-01

A cloud and aerosol radiative forcing and physical process study involving active laser and radar profiling with a combination of passive radiometric sounders and imagers would use the space station as an observation platform. The objectives are to observe the full three dimensional cloud and aerosol structure and the associated physical parameters leading to a complete measurement of radiation forcing processes. The instruments would include specialized radar and lidar for cloud and aerosol profiling, visible, infrared and microwave imaging radiometers with comprehensive channels for cloud and aerosol observation and specialized sounders. The low altitude,. available power and servicing capability of the space station are significant advantages for the active sensors and multiple passive instruments.

Lidar measurements of boundary layers, aerosol scattering and clouds during project FIFE

NASA Technical Reports Server (NTRS)

Eloranta, Edwin W. (Principal Investigator)

1995-01-01

A detailed account of progress achieved under this grant funding is contained in five journal papers. The titles of these papers are: The calculation of area-averaged vertical profiles of the horizontal wind velocity using volume imaging lidar data; Volume imaging lidar observation of the convective structure surrounding the flight path of an instrumented aircraft; Convective boundary layer mean depths, cloud base altitudes, cloud top altitudes, cloud coverages, and cloud shadows obtained from Volume Imaging Lidar data; An accuracy analysis of the wind profiles calculated from Volume Imaging Lidar data; and Calculation of divergence and vertical motion from volume-imaging lidar data. Copies of these papers form the body of this report.

Observed Aerosol Influence on Ice Water Content of Arctic Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Norgren, M.; de Boer, G.; Shupe, M.

2016-12-01

The response of ice water content (IWC) in Arctic mixed-phase stratocumulus to atmospheric aerosols is observed. IWC retrievals from ground based radars operated by the Atmospheric Radiation Measurement (ARM) program in Barrow, Alaska are used to construct composite profiles of cloud IWC from a 9-year radar record starting in January of 2000. The IWC profiles for high (polluted) and low (clean) aerosol loadings are compared. Generally, we find that clean clouds exhibit statistically significant higher levels of IWC than do polluted clouds by a factor of 2-4 at cloud base. For springtime clouds, with a maximum relative humidity with respect to ice (RHI) above 110% in the cloud layer, the IWC at cloud base was a factor of 3.25 times higher in clean clouds than it was in polluted clouds. We infer that the aerosol loading of the cloud environment alters the liquid drop size distribution within the cloud, with larger drops being more frequent in clean clouds. Larger cloud drops promote riming within the cloud layer, which is one explanation for the higher IWC levels in clean clouds. The drop size distribution may also be a significant control of ice nucleation events within mixed-phase clouds. Whether the high IWC levels in clean clouds are due to increased riming or nucleation events is unclear at this time.

The Cloud-Aerosol Transport System (CATS): a New Lidar for Aerosol and Cloud Profiling from the International Space Station

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; McGill, Matthew J.; Yorks, John E.; Hlavka, Dennis L.; Hart, William D.; Palm, Stephen P.; Colarco, Peter R.

2011-01-01

Spaceborne lidar profiling of aerosol and cloud layers has been successfully implemented during a number of prior missions, including LITE, ICESat, and CALIPSO. Each successive mission has added increased capability and further expanded the role of these unique measurements in wide variety of applications ranging from climate, to air quality, to special event monitoring (ie, volcanic plumes). Many researchers have come to rely on the availability of profile data from CALIPSO, especially data coincident with measurements from other A-Train sensors. The CALIOP lidar on CALIPSO continues to operate well as it enters its fifth year of operations. However, active instruments have more limited lifetimes than their passive counterparts, and we are faced with a potential gap in lidar profiling from space if the CALIOP lidar fails before a new mission is operational. The ATLID lidar on EarthCARE is not expected to launch until 2015 or later, and the lidar component of NASA's proposed Aerosols, Clouds, and Ecosystems (ACE) mission would not be until after 2020. Here we present a new aerosol and cloud lidar that was recently selected to provide profiling data from the International Space Station (ISS) starting in 2013. The Cloud-Aerosol Transport System (CATS) is a three wavelength (1064, 532, 355 nm) elastic backscatter lidar with HSRL capability at 532 nm. Depolarization measurements will be made at all wavelengths. The primary objective of CATS is to continue the CALIPSO aerosol and cloud profile data record, ideally with overlap between both missions and EarthCARE. In addition, the near real time data capability of the ISS will enable CATS to support operational applications such as air quality and special event monitoring. The HSRL channel will provide a demonstration of technology and a data testbed for direct extinction retrievals in support of ACE mission development. An overview of the instrument and mission will be provided, along with a summary of the science objectives and simulated data.

Trans-Pacific transport of Asian dust: the CESM model analysis and comparison with satellite observations

NASA Astrophysics Data System (ADS)

Wu, M.; Liu, X.; Luo, T.; Wang, Z.; Yang, K.; Wu, C.; Wang, H.; Zhang, K.

2017-12-01

Mineral dust plays an important role in the Earth's climate system due to its effects on radiation budgets, clouds, chemistry and biosphere. However, modeled dust aerosol is not well constrained and large uncertainties exist in modeled dust lifecycles. We evaluate dust spatial distributions in the Community Earth System Model (CESM) with new dust extinction retrievals (Luo et al., 2015a, b) based on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and CloudSat measurement, with special focus on the Asian dust transport across the Pacific. It is shown that the default CESM underestimates the dust extinction over the Pacific by 1-2 order of magnitude. Especially, the model fails to capture the observed high values of dust extinction occurring from 850 to 500 hPa across the North Pacific (20°N-50°N). Modeled dust optical depth (DOD) decreases faster across the Pacific compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR) observations. Sensitivity experiments with altered emission, vertical transport and deposition schemes have been conducted to identify the key process impacting dust transport. For that purpose, two new dust emission schemes by Kok et al. (2014a, b) and Ginoux et al. (2001), a new dry deposition scheme by Petroff and Zhang (2010) are implemented to the CESM. In addition, a new unified scheme for convective transport and wet removal of aerosols (Wang et al., 2013) is implemented to the same version of CESM to examine the influence of convective transport and wet deposition on dust transport. It is found that changes in wet scavenging and convective transport can strongly impact dust transport over the Pacific compared to changes in other processes. One of the new emission schemes further decreases the dust extinction across the Pacific. Dust extinction across the Pacific slightly increases when dry deposition velocity for fine particles is reduced.

Ortho-para-hydrogen equilibration on Jupiter

NASA Technical Reports Server (NTRS)

Carlson, Barbara E.; Lacis, Andrew A.; Rossow, William B.

1992-01-01

Voyager IRIS observations reveal that the Jovian para-hydrogen fraction is not in thermodynamic equilibrium near the NH3 cloud top, implying that a vertical gradient exists between the high-temperature equilibrium value of 0.25 at depth and the cloud top values. The height-dependent para-hydrogen profile is obtained using an anisotropic multiple-scattering radiative transfer model. A vertical correlation is found to exist between the location of the para-hydrogen gradient and the NH3 cloud, strongly suggesting that paramagnetic conversion on NH3 cloud particle surfaces is the dominant equilibration mechanism. Below the NH3 cloud layer, the para fraction is constant with depth and equal to the high-temperature equilibrium value of 0.25. The degree of cloud-top equilibration appears to depend on the optical depth of the NH3 cloud layer. Belt-zone variations in the para-hydrogen profile seem to be due to differences in the strength of the vertical mixing.

Negative Aerosol-Cloud re Relationship From Aircraft Observations Over Hebei, China

NASA Astrophysics Data System (ADS)

Zhao, Chuanfeng; Qiu, Yanmei; Dong, Xiaobo; Wang, Zhien; Peng, Yiran; Li, Baodong; Wu, Zhihui; Wang, Yang

2018-01-01

Using six flights observations in September 2015 over Hebei, China, this study shows a robust negative aerosol-cloud droplet effective radius (re) relationship for liquid clouds, which is different from previous studies that found positive aerosol-cloud re relationship over East China using satellite observations. A total of 27 cloud samples was analyzed with the classification of clean and polluted conditions using lower and upper 1/3 aerosol concentration at 200 m below the cloud bases. By normalizing the profiles of cloud droplet re, we found significant smaller values under polluted than under clean condition at most heights. Moreover, the averaged profiles of cloud liquid water content (LWC) show larger values under polluted than clean conditions, indicating even stronger negative aerosol-cloud re relationship if LWC is kept constant. The droplet size distributions further demonstrate that more droplets concentrate within smaller size ranges under polluted conditions. Quantitatively, the aerosol-cloud interaction is found around 0.10-0.19 for the study region.

Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States

NASA Astrophysics Data System (ADS)

Igel, M.; Biello, J. A.

2017-12-01

Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.

Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Olson, William S.

2003-01-01

A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.

Evaluating cloud retrieval algorithms with the ARM BBHRP framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mlawer,E.; Dunn,M.; Mlawer, E.

2008-03-10

Climate and weather prediction models require accurate calculations of vertical profiles of radiative heating. Although heating rate calculations cannot be directly validated due to the lack of corresponding observations, surface and top-of-atmosphere measurements can indirectly establish the quality of computed heating rates through validation of the calculated irradiances at the atmospheric boundaries. The ARM Broadband Heating Rate Profile (BBHRP) project, a collaboration of all the working groups in the program, was designed with these heating rate validations as a key objective. Given the large dependence of radiative heating rates on cloud properties, a critical component of BBHRP radiative closure analysesmore » has been the evaluation of cloud microphysical retrieval algorithms. This evaluation is an important step in establishing the necessary confidence in the continuous profiles of computed radiative heating rates produced by BBHRP at the ARM Climate Research Facility (ACRF) sites that are needed for modeling studies. This poster details the continued effort to evaluate cloud property retrieval algorithms within the BBHRP framework, a key focus of the project this year. A requirement for the computation of accurate heating rate profiles is a robust cloud microphysical product that captures the occurrence, height, and phase of clouds above each ACRF site. Various approaches to retrieve the microphysical properties of liquid, ice, and mixed-phase clouds have been processed in BBHRP for the ACRF Southern Great Plains (SGP) and the North Slope of Alaska (NSA) sites. These retrieval methods span a range of assumptions concerning the parameterization of cloud location, particle density, size, shape, and involve different measurement sources. We will present the radiative closure results from several different retrieval approaches for the SGP site, including those from Microbase, the current 'reference' retrieval approach in BBHRP. At the NSA, mixed-phase clouds and cloud with a low optical depth are prevalent; the radiative closure studies using Microbase demonstrated significant residuals. As an alternative to Microbase at NSA, the Shupe-Turner cloud property retrieval algorithm, aimed at improving the partitioning of cloud phase and incorporating more constrained, conditional microphysics retrievals, also has been evaluated using the BBHRP data set.« less

Simultaneous and synergistic profiling of cloud and drizzle properties using ground-based observations

NASA Astrophysics Data System (ADS)

Rusli, Stephanie P.; Donovan, David P.; Russchenberg, Herman W. J.

2017-12-01

Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water cloud properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the clouds. So far, there has been no published work that utilizes Z to identify the presence of drizzle above the cloud base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the cloud and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the cloud base, and microwave brightness temperatures. Fast physical forward models coupled to cloud and drizzle structure parameterization are used in an optimal-estimation-type framework in order to retrieve the best estimate for the cloud and drizzle property profiles. The cloud retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the cloud properties can be retrieved within 5 % of the mean truth. The full cloud-drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the cloud properties, the drizzle properties below the cloud base, or the drizzle fraction within the cloud. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived using the three independent methods.

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, WIlliam L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

If Frisch is true - impacts of varying beam width, resolution, frequency combinations and beam overlap when retrieving liquid water content profiles

NASA Astrophysics Data System (ADS)

Küchler, N.; Kneifel, S.; Kollias, P.; Loehnert, U.

2017-12-01

Cumulus and stratocumulus clouds strongly affect the Earth's radiation budget and are a major uncertainty source in weather and climate prediction models. To improve and evaluate models, a comprehensive understanding of cloud processes is necessary and references are needed. Therefore active and passive microwave remote sensing of clouds can be used to derive cloud properties such as liquid water path and liquid water content (LWC), which can serve as a reference for model evaluation. However, both the measurements and the assumptions when retrieving physical quantities from the measurements involve uncertainty sources. Frisch et al. (1998) combined radar and radiometer observations to derive LWC profiles. Assuming their assumptions are correct, there will be still uncertainties regarding the measurement setup. We investigate how varying beam width, temporal and vertical resolutions, frequency combinations, and beam overlap of and between the two instruments influence the retrieval of LWC profiles. Especially, we discuss the benefit of combining vertically, high resolved radar and radiometer measurements using the same antenna, i.e. having ideal beam overlap. Frisch, A. S., G. Feingold, C. W. Fairall, T. Uttal, and J. B. Snider, 1998: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles. J. Geophys. Res.: Atmos., 103 (18), 23 195-23 197, doi:0148-0227/98/98JD-01827509.00.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Hemispheric aerosol vertical profiles: anthropogenic impacts on optical depth and cloud nuclei.

PubMed

Clarke, Antony; Kapustin, Vladimir

2010-09-17

Understanding the effect of anthropogenic combustion upon aerosol optical depth (AOD), clouds, and their radiative forcing requires regionally representative aerosol profiles. In this work, we examine more than 1000 vertical profiles from 11 major airborne campaigns in the Pacific hemisphere and confirm that regional enhancements in aerosol light scattering, mass, and number are associated with carbon monoxide from combustion and can exceed values in unperturbed regions by more than one order of magnitude. Related regional increases in a proxy for cloud condensation nuclei (CCN) and AOD imply that direct and indirect aerosol radiative effects are coupled issues linked globally to aged combustion. These profiles constrain the influence of combustion on regional AOD and CCN suitable for challenging climate model performance and informing satellite retrievals.

915-MHz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, M.; Bartholomew, M. J.; Giangrande, S.

When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to hours) variability through scattering and reflection of incoming solar radiation. Providing estimates of this short-term variability is important for determining and regulating the output from large solar arrays as they connect with the larger power infrastructure. In support of the installation of a 37-MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study of the impacts of clouds onmore » the output of the solar array has been undertaken. The study emphasis is on predicting the change in surface solar radiation resulting from the observed/forecast cloud field on a 5-minute time scale. At these time scales, advection of cloud elements over the solar array is of particular importance. As part of the BNL Aerosol Life Cycle Intensive Operational Period (IOP), a 915-MHz Radar Wind Profiler (RWP) was deployed to determine the profile of low-level horizontal winds and the depth of the planetary boundary layer. The initial deployment mission of the 915-MHz RWP for cloud forecasting has been expanded the deployment to provide horizontal wind measurements for estimating and constraining cloud advection speeds. A secondary focus is on the observation of dynamics and microphysics of precipitation during cold season/winter storms on Long Island. In total, the profiler was deployed at BNL for 1 year from May 2011 through May 2012.« less

915-Mhz Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, M.; Bartholomew, M. J.; Giangrande, S.

When considering the amount of shortwave radiation incident on a photovoltaic solar array and, therefore, the amount and stability of the energy output from the system, clouds represent the greatest source of short-term (i.e., scale of minutes to hours) variability through scattering and reflection of incoming solar radiation. Providing estimates of this short-term variability is important for determining and regulating the output from large solar arrays as they connect with the larger power infrastructure. In support of the installation of a 37-MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study of the impacts of clouds onmore » the output of the solar array has been undertaken. The study emphasis is on predicting the change in surface solar radiation resulting from the observed/forecast cloud field on a 5-minute time scale. At these time scales, advection of cloud elements over the solar array is of particular importance. As part of the BNL Aerosol Life Cycle Intensive Operational Period (IOP), a 915-MHz Radar Wind Profiler (RWP) was deployed to determine the profile of low-level horizontal winds and the depth of the planetary boundary layer. The initial deployment mission of the 915-MHz RWP for cloud forecasting has been expanded the deployment to provide horizontal wind measurements for estimating and constraining cloud advection speeds. A secondary focus is on the observation of dynamics and microphysics of precipitation during cold season/winter storms on Long Island. In total, the profiler was deployed at BNL for 1 year from May 2011 through May 2012.« less

Effect of Convection on the Tropical Tropopause Layer over the Tropical Americas

NASA Technical Reports Server (NTRS)

Pittman, Jasna; Robertson, Franklin

2007-01-01

Water vapor and ozone are the most important gases that regulate the radiative balance of the Tropical Tropopause Layer (TTL). Their radiative contribution dictates the height within the TTL and the rate at which air either ascends into the tropical stratosphere or subsides back to the tropical troposphere. The details of the mechanisms that control their concentration, however, are poorly understood. One of such mechanisms is convection that reaches into the TTL. ill this study, we will present evidence from space-borne observations of the impact that convection has on water vapor, ozone, and temperature in the TTL over the Tropical Americas where deep and overshooting convection have the highest frequency of occurrence in the tropics. We explore the effect of convective systems such as hurricanes during the 2005 season using the Microwave Limb Sounder (MLS) on Aura version 1.5 data and more recent tropical systems using the newly released version 2 data with higher vertical resolution. ill order to provide the horizontal extent and the vertical structure of the convective systems, we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua, the Microwave Humidity Sensor (MHS) on NOAA18, and CloudSat when available.

Cloud Properties and Radiative Heating Rates for TWP

DOE Data Explorer

Comstock, Jennifer

2013-11-07

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Impact of Arctic sea-ice retreat on the recent change in cloud-base height during autumn

NASA Astrophysics Data System (ADS)

Sato, K.; Inoue, J.; Kodama, Y.; Overland, J. E.

2012-12-01

Cloud-base observations over the ice-free Chukchi and Beaufort Seas in autumn were conducted using a shipboard ceilometer and radiosondes during the 1999-2010 cruises of the Japanese R/V Mirai. To understand the recent change in cloud base height over the Arctic Ocean, these cloud-base height data were compared with the observation data under ice-covered situation during SHEBA (the Surface Heat Budget of the Arctic Ocean project in 1998). Our ice-free results showed a 30 % decrease (increase) in the frequency of low clouds with a ceiling below (above) 500 m. Temperature profiles revealed that the boundary layer was well developed over the ice-free ocean in the 2000s, whereas a stable layer dominated during the ice-covered period in 1998. The change in surface boundary conditions likely resulted in the difference in cloud-base height, although it had little impact on air temperatures in the mid- and upper troposphere. Data from the 2010 R/V Mirai cruise were investigated in detail in terms of air-sea temperature difference. This suggests that stratus cloud over the sea ice has been replaced as stratocumulus clouds with low cloud fraction due to the decrease in static stability induced by the sea-ice retreat. The relationship between cloud-base height and air-sea temperature difference (SST-Ts) was analyzed in detail using special section data during 2010 cruise data. Stratus clouds near the sea surface were predominant under a warm advection situation, whereas stratocumulus clouds with a cloud-free layer were significant under a cold advection situation. The threshold temperature difference between sea surface and air temperatures for distinguishing the dominant cloud types was 3 K. Anomalous upward turbulent heat fluxes associated with the sea-ice retreat have likely contributed to warming of the lower troposphere. Frequency distribution of the cloud-base height (km) detected by a ceilometer/lidar (black bars) and radiosondes (gray bars), and profiles of potential temperature (K) for (a) ice-free cases (R/V Mirai during September) and (b) ice-covered case (SHEBA during September 1998). (c) Vertical profiles of air temperature from 1000 hPa to 150 hPa (solid lines: observations north of 75°N, and dashed lines: the ERA-Interim reanalysis over 75-82.5°N, 150-170°W). Green, blue, and red lines denote profiles derived from observations by NP stations (the 1980s), SHEBA (1998), and the R/V Mirai (the 2000s), respectively. (d) Temperature trend calculated by the ERA-Interim reanalysis over the area.

The rationale and suggested approaches for research geosynchronous satellite measurements for severe storm and mesoscale investigations

NASA Technical Reports Server (NTRS)

Shenk, W. E.; Adler, R. F.; Chesters, D.; Susskind, J.; Uccellini, L.

1984-01-01

The measurements from current and planned geosynchronous satellites provide quantitative estimates of temperature and moisture profiles, surface temperature, wind, cloud properties, and precipitation. A number of significant observation characteristics remain, they include: (1) temperature and moisture profiles in cloudy areas; (2) high vertical profile resolution; (3) definitive precipitation area mapping and precipitation rate estimates on the convective cloud scale; (4) winds from low level cloud motions at night; (5) the determination of convective cloud structure; and (6) high resolution surface temperature determination. Four major new observing capabilities are proposed to overcome these deficiencies: a microwave sounder/imager, a high resolution visible and infrared imager, a high spectral resolution infrared sounder, and a total ozone mapper. It is suggested that the four sensors are flown together and used to support major mesoscale and short range forecasting field experiments.

Tropical Cloud Properties and Radiative Heating Profiles

DOE Data Explorer

Mather, James

2008-01-15

We have generated a suite of products that includes merged soundings, cloud microphysics, and radiative fluxes and heating profiles. The cloud microphysics is strongly based on the ARM Microbase value added product (Miller et al., 2003). We have made a few changes to the microbase parameterizations to address issues we observed in our initial analysis of the tropical data. The merged sounding product is not directly related to the product developed by ARM but is similar in that it uses the microwave radiometer to scale the radiosonde column water vapor. The radiative fluxes also differ from the ARM BBHRP (Broadband Heating Rate Profile) product in terms of the radiative transfer model and the sampling interval.

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

NASA Technical Reports Server (NTRS)

Weisz, Elisabeth; Li, Jun; Li, Jinlong; Zhou, Daniel K.; Huang, Hung-Lung; Goldberg, Mitchell D.; Yang, Ping

2007-01-01

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Combined Lidar-Radar Remote Sensing: Initial Results from CRYSTAL-FACE and Implications for Future Spaceflight Missions

NASA Technical Reports Server (NTRS)

McGill, Matthew J.; Li, Li-Hua; Hart, William D.; Heymsfield, Gerald M.; Hlavka, Dennis L.; Vaughan, Mark A.; Winker, David M.

2003-01-01

In the near future NASA plans to fly satellites carrying a multi-wavelength backscatter lidar and a 94-GHz cloud profiling radar in formation to provide complete global profiling of cloud and aerosol properties. The CRYSTAL-FACE field campaign, conducted during July 2002, provided the first high-altitude colocated measurements from lidar and cloud profiling radar to simulate these spaceborne sensors. The lidar and radar provide complementary measurements with varying degrees of measurement overlap. This paper presents initial results of the combined airborne lidar-radar measurements during CRYSTAL-FACE. The overlap of instrument sensitivity is presented, within the context of particular CRYSTAL-FACE conditions. Results are presented to quantify the portion of atmospheric profiles sensed independently by each instrument and the portion sensed simultaneously by the two instruments.

Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling

DOE PAGES

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan; ...

2016-03-09

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

Design of relative motion and attitude profiles for three-dimensional resident space object imaging with a laser rangefinder

NASA Astrophysics Data System (ADS)

Nayak, M.; Beck, J.; Udrea, B.

This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized; the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative “ metric” that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud densit- , therefore they are utilized to compare the quality of point clouds generated by various attitude and waypoint command profiles. The RSO model incorporates diverse irregular protruding shapes, such as open sensor covers, instrument pods and solar arrays, to test the limits of the algorithms. This analysis is used to mathematically prove that point clouds generated by a single-beam LRF can achieve sufficient edge recognition accuracy for SSA applications, with meaningful shape information extractable even from sparse point clouds. For all command profiles, reconstruction of RSO shapes from the point clouds generated with the proposed method are compared to the truth model and conclusions are drawn regarding their fidelity.

Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

NASA Technical Reports Server (NTRS)

Hlavka, Dennis; Tian, Lin; Hart, William; Li, Lihua; McGill, Matthew; Heymsfield, Gerald

2009-01-01

Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy profiles occurring 94 percent of the time during the ER-2 flights. One to three cloud layers were common, with the average calculated at 2.03 layers per profile. The upper troposphere had a cloud frequency generally over 30%, reaching 42 percent near 13 km during the study. There were regional differences. The Caribbean was much clearer than the Pacific regions. Land had a much higher frequency of high clouds than ocean areas. One region just south and west of Panama had a high probability of clouds below 15 km altitude with the frequency never dropping below 25% and reaching a maximum of 60% at 11-13 km altitude. These cloud statistics will help characterize the cloud volume for TC4 scientists as they try to understand the complexities of the tropical atmosphere.

The Cloud-Aerosol Transport System (CATS): A New Lidar for Aerosol and Cloud Profiling from the International Space Station

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; McGill, Mathew J.; Yorks. John E.; Hlavka, Dennis L.; Hart, William D.; Palm, Stephen P.; Colarco, Peter R.

2012-01-01

Spaceborne lidar profiling of aerosol and cloud layers has been successfully implemented during a number of prior missions, including LITE, ICESat, and CALIPSO. Each successive mission has added increased capability and further expanded the role of these unique measurements in wide variety of applications ranging from climate, to air quality, to special event monitoring (ie, volcanic plumes). Many researchers have come to rely on the availability of profile data from CALIPSO, especially data coincident with measurements from other A-Train sensors. The CALIOP lidar on CALIPSO continues to operate well as it enters its fifth year of operations. However, active instruments have more limited lifetimes than their passive counterparts, and we are faced with a potential gap in lidar profiling from space if the CALIOP lidar fails before a new mission is operational. The ATLID lidar on EarthCARE is not expected to launch until 2015 or later, and the lidar component of NASA's proposed Aerosols, Clouds, and Ecosystems (ACE) mission would not be until after 2020. Here we present a new aerosol and cloud lidar that was recently selected to provide profiling data from the International Space Station (ISS) starting in 2013. The Cloud-Aerosol Transport System (CATS) is a three wavelength (1064,532,355 nm) elastic backscatter lidar with HSRL capability at 532 nm. Depolarization measurements will be made at all wavelengths. The primary objective of CATS is to continue the CALIPSO aerosol and cloud profile data record, ideally with overlap between both missions and EarthCARE. In addition, the near real time (NRT) data capability ofthe ISS will enable CATS to support operational applications such as aerosol and air quality forecasting and special event monitoring. The HSRL channel will provide a demonstration of technology and a data testbed for direct extinction retrievals in support of ACE mission development. An overview of the instrument and mission will be provided, along with a summary of the science objectives and simulated data. Input from the ICAP community is desired to help plan our NRT mission goals and interactions with ICAP forecasters.

Assessment of 3D cloud radiative transfer effects applied to collocated A-Train data

NASA Astrophysics Data System (ADS)

Okata, M.; Nakajima, T.; Suzuki, K.; Toshiro, I.; Nakajima, T. Y.; Okamoto, H.

2017-12-01

This study investigates broadband radiative fluxes in the 3D cloud-laden atmospheres using a 3D radiative transfer (RT) model, MCstar, and the collocated A-Train cloud data. The 3D extinction coefficients are constructed by a newly devised Minimum cloud Information Deviation Profiling Method (MIDPM) that extrapolates CPR radar profiles at nadir into off-nadir regions within MODIS swath based on collocated information of MODIS-derived cloud properties and radar reflectivity profiles. The method is applied to low level maritime water clouds, for which the 3D-RT simulations are performed. The radiative fluxes thus simulated are compared to those obtained from CERES as a way to validate the MIDPM-constructed clouds and our 3D-RT simulations. The results show that the simulated SW flux agrees with CERES values within 8 - 50 Wm-2. One of the large biases occurred by cyclic boundary condition that was required to pose into our computational domain limited to 20km by 20km with 1km resolution. Another source of the bias also arises from the 1D assumption for cloud property retrievals particularly for thin clouds, which tend to be affected by spatial heterogeneity leading to overestimate of the cloud optical thickness. These 3D-RT simulations also serve to address another objective of this study, i.e. to characterize the "observed" specific 3D-RT effects by the cloud morphology. We extend the computational domain to 100km by 100km for this purpose. The 3D-RT effects are characterized by errors of existing 1D approximations to 3D radiation field. The errors are investigated in terms of their dependence on solar zenith angle (SZA) for the satellite-constructed real cloud cases, and we define two indices from the error tendencies. According to the indices, the 3D-RT effects are classified into three types which correspond to different simple three morphologies types, i.e. isolated cloud type, upper cloud-roughened type and lower cloud-roughened type. These 3D-RT effects linked to cloud morphologies are also visualized in the form of the RGB composite maps constructed from MODIS/Aqua three channels, which show cloud optical thickness and cloud height information. Such a classification offers a novel insight into 3D-RT effect in a manner that directly relates to cloud morphology.

Autonomous, Full-Time Cloud Profiling at Arm Sites with Micro Pulse Lidar

NASA Technical Reports Server (NTRS)

Spinhirne, James D.; Campbell, James R.; Hlavka, Dennis L.; Scott, V. Stanley; Flynn, Connor J.

2000-01-01

Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Atmospheric, Cloud, and Surface Parameters Retrieved from Satellite Ultra-spectral Infrared Sounder Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Yang, Ping; Schluessel, Peter; Strow, Larrabee

2007-01-01

An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. This retrieval algorithm is applied to the MetOp satellite Infrared Atmospheric Sounding Interferometer (IASI) launched on October 19, 2006. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI measurements are obtained and presented.

Liquid water content variation with altitude in clouds over Europe

NASA Astrophysics Data System (ADS)

Andreea, Boscornea; Sabina, Stefan

2013-04-01

Cloud water content is one of the most fundamental measurements in cloud physics. Knowledge of the vertical variability of cloud microphysical characteristics is important for a variety of reasons. The profile of liquid water content (LWC) partially governs the radiative transfer for cloudy atmospheres, LWC profiles improves our understanding of processes acting to form and maintain cloud systems and may lead to improvements in the representation of clouds in numerical models. Presently, in situ airborne measurements provide the most accurate information about cloud microphysical characteristics. This information can be used for verification of both numerical models and cloud remote sensing techniques. The aim of this paper was to analyze the liquid water content (LWC) measurements in clouds, in time of the aircraft flights. The aircraft and its platform ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research is property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania. The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - Cloud, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 m). The processed and analyzed measurements are acquired during 4 flights from Romania (Bucharest, 44°25'57″N 26°06'14″E) to Germany (Berlin 52°30'2″N 13°23'56″E) above the same region of Europe. The flight path was starting from Bucharest to the western part of Romania above Hungary, Austria at a cruse altitude between 6000-8500 m, and after 5 hours reaching Berlin. In total we acquired data during approximately 20 flight hours and we presented the vertical and horizontal LWC variations for different cloud types. The LWC values are similar for each type of cloud to values from literature. The vertical LWC profiles in the atmosphere measured during takeoff and landing of the aircraft have shown their dependence of the meteorological parameters.

G-band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-01-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud-scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G-band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G-band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

G band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-06-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

Depolarization Lidar Determination Of Cloud-Base Microphysical Properties

NASA Astrophysics Data System (ADS)

Donovan, D. P.; Klein Baltink, H.; Henzing, J. S.; de Roode, S.; Siebesma, A. P.

2016-06-01

The links between multiple-scattering induced depolarization and cloud microphysical properties (e.g. cloud particle number density, effective radius, water content) have long been recognised. Previous efforts to use depolarization information in a quantitative manner to retrieve cloud microphysical cloud properties have also been undertaken but with limited scope and, arguably, success. In this work we present a retrieval procedure applicable to liquid stratus clouds with (quasi-)linear LWC profiles and (quasi-)constant number density profiles in the cloud-base region. This set of assumptions allows us to employ a fast and robust inversion procedure based on a lookup-table approach applied to extensive lidar Monte-Carlo multiple-scattering calculations. An example validation case is presented where the results of the inversion procedure are compared with simultaneous cloud radar observations. In non-drizzling conditions it was found, in general, that the lidar- only inversion results can be used to predict the radar reflectivity within the radar calibration uncertainty (2-3 dBZ). Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud base number considerations are also presented. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.

Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

DTIC Science & Technology

2013-09-30

Cover in the Beaufort and Chukchi Seas Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys Axel...how changes in sea ice and sea surface conditions in the SIZ affect changes in cloud properties and cover . • Determine the role additional atmospheric...REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Atmospheric Profiles, Clouds, and the Evolution of Sea Ice Cover in the

Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships

NASA Astrophysics Data System (ADS)

Christensen, Matthew Wells

Multiple sensors flying in the A-train constellation of satellites were used to determine the extent to which aerosol plumes from ships passing below marine stratocumulus alter the microphysical and macrophysical properties of the clouds. Aerosol plumes generated by ships sometimes influence cloud microphysical properties (effective radius) and, to a largely undetermined extent, cloud macrophysical properties (liquid water path, coverage, depth, precipitation, and longevity). Aerosol indirect effects were brought into focus, using observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the 94-GHZ radar onboard CloudSat. To assess local cloud scale responses to aerosol, the locations of over one thousand ship tracks coinciding with the radar were meticulously logged by hand from the Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. MODIS imagery was used to distinguish ship tracks that were embedded in closed, open, and unclassifiable mesoscale cellular cloud structures. The impact of aerosol on the microphysical cloud properties in both the closed and open cell regimes were consistent with the changes predicted by the Twomey hypothesis. For the macrophysical changes, differences in the sign and magnitude of these properties were observed between cloud regimes. The results demonstrate that the spatial extent of rainfall (rain cover fraction) and intensity decrease in the clouds contaminated by the ship plume compared to the ambient pristine clouds. Although reductions of precipitation were common amongst the clouds with detectable rainfall (72% of cases), a substantial fraction of ship tracks (28% of cases) exhibited the opposite response. The sign and strength of the response was tied to the type of stratocumulus (e.g., closed vs open cells), depth of the boundary layer, and humidity in the free-troposphere. When closed cellular clouds were identified, liquid water path, drizzle rate, and rain cover fraction (an average relative decrease of 61%) was significantly smaller in the ship-contaminated clouds. Differences in drizzle rate resulted primarily from the reductions in rain cover fraction (i.e., fewer pixels were identified with rain in the clouds polluted by the ship). The opposite occurred in the open cell regime. Ship plumes ingested into this regime resulted in significantly deeper and brighter clouds with higher liquid water amounts and rain rates. Enhanced rain rates (average relative increase of 89%) were primarily due to the changes in intensity (i.e., rain rates on the 1.1 km pixel scale were higher in the ship contaminated clouds) and, to a lesser extent, rain cover fraction. One implication for these differences is that the local aerosol indirect radiative forcing was more than five times larger for ship tracks observed in the open cell regime (-59 W m-2) compared to those identified in the closed cell regime (-12 W m -2). The results presented here underline the need to consider the mesoscale structure of stratocumulus when examining the cloud dynamic response to changes in aerosol concentration. In the final part of the dissertation, the focus shifted to the climate scale to examine the impact of shipping on the Earth's radiation budget. Two studies were employed, in the first; changes to the radiative properties of boundary layer clouds (i.e., cloud top heights less than 3 km) were examined in response to the substantial decreases in ship traffic that resulted from the recent world economic recession in 2008. Differences in the annually averaged droplet effective radius and top of atmosphere outgoing shortwave radiative flux between 2007 and 2009 did not manifest as a clear response in the climate system and, was probably masked either due to competing aerosol cloud feedbacks or by interannual climate variability. In the second study, a method was developed to estimate the radiative forcing from shipping by convolving lanes of densely populated ships onto the global distributions of closed and open cell stratocumulus clouds. Closed cells were observed more than twice as often as open cells. Despite the smaller abundance of open cells, a significant portion of the radiaitve forcing from shipping was claimed by this regime. On the whole, the global radiative forcing from ship tracks was small (approximately -0.45 mW m-2) compared to the radiative forcing associated with the atmospheric buildup of anthropogenic CO2.

Advanced multi-frequency radar: Design, preliminary measurements and particle size distribution retrieval

NASA Astrophysics Data System (ADS)

Majurec, Ninoslav

In the spring of 2001 the Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts began the development of an advanced Multi-Frequency Radar (AMFR) system for studying clouds and precipitation. This mobile radar was designed to consist of three polarimetric Doppler subsystems operating at Ku-band (13.4 GHz), Ka-band (35.6 GHz) and W-band (94.92 GHz). This combination of frequency bands allows a measurement of a wide range of atmospheric targets ranging from weakly reflecting clouds to strong precipitation. The antenna beamwidths at each frequency were intentionally matched, ensuring consistent sampling volume. Multi-frequency radar remote sensing techniques are not widely used because few multi-frequency radars are available to the science community. One exception is the 33 GHz/95 GHz UMass Cloud Profiling Radar System (CPRS), which AMFR is intended to replace. AMFR's multi-parameter capabilities are designed for characterizing the complex microphysics of layer clouds and precipitation processes in winter storms. AMFR will also play an important role in developing algorithms and validating measurements for an upcoming generation of space-borne radars. The frequency bands selected for AMFR match those of several sensors that have been deployed or are under development. These include the Japanese Aerospace Exploration Agencies (JAXA's) Tropical Rainfall Measuring Mission (TRMM) satellite Ku-band (13 GHz) radar, the CloudSat W-band (95 GHz) radar, and the Global Precipitation Mission (GPM) satellite radars at Ku-band and Ka-band. This dissertation describes the AMFR hardware design and development. Compared to CPRS, the addition of one extra frequency band (Ku) will extend AMFR's measurement capabilities towards the larger particle sizes (precipitation). AMFR's design is based around high-power klystron amplifiers. This ensures complete coherency (CPRS uses magnetrons and coherent-on-receive technique). The partial loss in sensitivity due to lower output power of klystron amplifiers (comparing to magnetrons) is compensated by use of pulse compression (linear FM). The problem of range sidelobes (pulse compression artifacts) has been solved by using appropriate windowing functions in the receiver. Satisfactory sidelobe suppression level of 45 dB has been demonstrated in the lab. The currently best achievable range resolution of the AMFR system is 30 m (corresponds to 5 MHz receiver BW, set by the sampling rate of the Analog-to-Digital card). During the design stage, various polarization schemes have been investigated. The polarization scheme analysis showed the switching polarization scheme to be the best suited for the AMFR system. The AMFR subsystems were partially finished in the winter of 2005. Some preliminary tests were conducted in January 2006. Antenna platform was fabricated in summer 2006. The final assembly took place in the fall of 2006. Early results are presented in the dissertation. These results were helpful in revealing of certain problems in the radar system (i.e. immediate processing computer synchronization) that needed to be addressed during system development. Stratiform rain event occurred on December 18 2006 has been analyzed in detail. A number of commonly used theoretical particle size distributions is presented. Furthermore, it is shown that a fully calibrated multi-frequency radar system has capability of separating scattering and attenuation effects. This was accomplished by fitting the theoretical models into the measured data. An alternative method of estimating rain rate that relies on the dual wavelength ratios is also presented. Although not as powerful as theoretical model fitting, it has its merits for off-zenith observations. During January 2007, AMFR system participated in the C3VP experiment (Canadian CloudSat/CALIPSO Validation Project) in south Ontario, Canada. Some of the data obtained during C3VP experiment has been analyzed and presented. Analysis of these two weather events resulted in the development of the initial multi-frequency particle size distribution retrieval algorithm.

Aircraft profile measurements of 18O/16O and D/H isotope ratios of cloud condensate and water vapor constrain precipitation efficiency and entrainment rates in tropical clouds

NASA Astrophysics Data System (ADS)

Noone, D. C.; Raudzens Bailey, A.; Toohey, D. W.; Twohy, C. H.; Heymsfield, A.; Rella, C.; Van Pelt, A. D.

2011-12-01

Convective clouds play a significant role in the moisture and heat balance of the tropics. The dynamics of organized and isolated convection are a function of the background thermodynamic profile and wind shear, buoyancy sources near the surface and the latent heating inside convective updrafts. The stable oxygen and hydrogen isotope ratios in water vapor and condensate can be used to identify dominant moisture exchanges and aspects of the cloud microphysics that are otherwise difficult to observe. Both the precipitation efficiency and the dilution of cloud updrafts by entrainment can be estimated since the isotopic composition outside the plume is distinct from inside. Measurements of the 18O/16O and D/H isotope ratios were made in July 2011 on 13 research flights of the NCAR C130 aircraft during the ICE-T (Ice in Clouds Experiment - Tropical) field campaign near St Croix. Measurements were made using an instrument based on the Picarro Wave-Length Scanning Cavity Ring Down platform that includes a number of optical, hardware and software modifications to allow measurements to be made at 5 Hz for deployment on aircraft. The measurement system was optimized to make precise measurements of the isotope ratio of liquid and ice cloud condensate by coupling the gas analyzer to the NCAR Counter flow Virtual Impactor inlet. The inlet system provides a particle enhancement while rejecting vapor. Sample air is vigorously heated before flowing into the gas phase analyzer. We present statistics that demonstrate the performance and calibration of the instrument. Measured profiles show that environmental air exhibits significant layering showing controls from boundary layer processes, large scale horizontal advection and regional subsidence. Condensate in clouds is consistent with generally low precipitation efficiency, although there is significant variability in the isotope ratios suggesting heterogeneity within plumes and the stochastic nature of detrainment processes. Entrainment of air into the plume is seen as evaporation of condensate. In the plume between about -7 and -12C, the ice condensate fraction increases with height, and the isotope ratios are used to discern ice formation from deposition from ice formed from in situ freezing of cloud liquid. The observed profiles demonstrate a new capacity for cloud process studies and provide new insight into the water budget of clouds.

Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and column cloud liquid water amounts

NASA Technical Reports Server (NTRS)

Wu, Xiaohua; Diak, George R.; Hayden, Cristopher M.; Young, John A.

1995-01-01

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

Technology Development for 3-D Wide Swath Imaging Supporting ACE

NASA Technical Reports Server (NTRS)

Racette, Paul; Heymsfield, Gerry; Li, Lihua; Mclinden, Matthew; Park, Richard; Cooley, Michael; Stenger, Pete; Hand, Thomas

2014-01-01

The National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) aims to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack in understanding of aerosol-cloud interactions. As part of the mission instrument suite, a dual-frequency radar comprised of a fixed-beam 94 gigahertz (W-band) radar and a wide-swath 35 gigahertz (Ka-band) imaging radar has been recommended by the ACE Science Working Group.In our 2010 Instrument Incubator Program project, we've developed a radar architecture that addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (100 kilometers) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflectorreflectarray and b) a Ka-band Active Electronically Scanned Array (AESA) feed module. The dual-band antenna is comprised of a primary cylindrical reflectorreflectarray surface illuminated by a point-focus W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat); the Ka-band AESA line feed provides wide-swath across-track scanning. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost, as compared to a two aperture approach. Four objectives were addressed in our project. The first entailed developing the tools for the analysis and design of reflectarray antennas, assessment of candidate reflectarray elements, and validation using test coupons. The second objective was to develop a full-scale aperture design utilizing the reflectarray surface and to detail specific requirements and trades for the Ka-band AESA line feed. As part of the third objective a subscale antenna, similar to the full-scale aperture design, was developed, integrated, and flown with the Cloud Radar System during the 2014 Integrated Precipitation and Hydrology Experiment. The fourth and ongoing objective entails developing a GaN MMIC (Gallium Nitride Monolithic Microwave Integrated Circuits) power amplifier for use in the Ka-band AESA. An overview of the progress made on this project and a look ahead at the 2013 IIP (Instrument Incubator Program) award selection will be presented.

Transitioning ISR architecture into the cloud

NASA Astrophysics Data System (ADS)

Lash, Thomas D.

2012-06-01

Emerging cloud computing platforms offer an ideal opportunity for Intelligence, Surveillance, and Reconnaissance (ISR) intelligence analysis. Cloud computing platforms help overcome challenges and limitations of traditional ISR architectures. Modern ISR architectures can benefit from examining commercial cloud applications, especially as they relate to user experience, usage profiling, and transformational business models. This paper outlines legacy ISR architectures and their limitations, presents an overview of cloud technologies and their applications to the ISR intelligence mission, and presents an idealized ISR architecture implemented with cloud computing.

Isolating the Liquid Cloud Response to Recent Arctic Sea Ice Variability Using Spaceborne Lidar Observations

NASA Astrophysics Data System (ADS)

Morrison, A. L.; Kay, J. E.; Chepfer, H.; Guzman, R.; Yettella, V.

2018-01-01

While the radiative influence of clouds on Arctic sea ice is known, the influence of sea ice cover on Arctic clouds is challenging to detect, separate from atmospheric circulation, and attribute to human activities. Providing observational constraints on the two-way relationship between sea ice cover and Arctic clouds is important for predicting the rate of future sea ice loss. Here we use 8 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations from 2008 to 2015 to analyze Arctic cloud profiles over sea ice and over open water. Using a novel surface mask to restrict our analysis to where sea ice concentration varies, we isolate the influence of sea ice cover on Arctic Ocean clouds. The study focuses on clouds containing liquid water because liquid-containing clouds are the most important cloud type for radiative fluxes and therefore for sea ice melt and growth. Summer is the only season with no observed cloud response to sea ice cover variability: liquid cloud profiles are nearly identical over sea ice and over open water. These results suggest that shortwave summer cloud feedbacks do not slow long-term summer sea ice loss. In contrast, more liquid clouds are observed over open water than over sea ice in the winter, spring, and fall in the 8 year mean and in each individual year. Observed fall sea ice loss cannot be explained by natural variability alone, which suggests that observed increases in fall Arctic cloud cover over newly open water are linked to human activities.

Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

NASA Technical Reports Server (NTRS)

Martins, J. V.; Marshak, A.; Remer, L. A.; Rosenfeld, D.; Kaufman, Y. J.; Fernandez-Borda, R.; Koren, I.; Correia, A. L.; Zubko, V.; Artaxo, P.

2011-01-01

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

multi-dimensional Cloud-aERosol Exploratory Study using RPAS (mCERES): Bottom-up and top-down closure of aerosol-cloud interactions

NASA Astrophysics Data System (ADS)

Roberts, Greg; Calmer, Radiance; Sanchez, Kevin; Cayez, Grégoire; Nicoll, Kerianne; Hashimshoni, Eyal; Rosenfeld, Daniel; Ansmann, Albert; Sciare, Jean; Ovadneite, Jurgita; Bronz, Murat; Hattenberger, Gautier; Preissler, Jana; Buehl, Johannes; Ceburnis, Darius; O'Dowd, Colin

2016-04-01

Clouds are omnipresent in earth's atmosphere and constitute an important role in regulating the radiative budget of the planet. However, the response of clouds to climate change remains uncertain, in particular, with respect to aerosol-cloud interactions and feedback mechanisms between the biosphere and atmosphere. Aerosol-cloud interactions and their feedbacks are the main themes of the European project FP7 BACCHUS (Impact of Biogenic versus Anthropogenic Emissions on Clouds and Climate: towards a Holistic Understanding). The National Center for Meteorological Research (CNRM-GAME, Toulouse, France) conducted airborne experiments in Cyprus and Ireland in March and August 2015 respectively to link ground-based and satellite observations. Multiple RPAS (remotely piloted aircraft systems) were instrumented for a specific scientific focus to characterize the vertical distribution of aerosol, cloud microphysical properties, radiative fluxes, 3D wind vectors and meteorological state parameters. Flights below and within clouds were coordinated with satellite overpasses to perform 'top-down' closure of cloud micro-physical properties. Measurements of cloud condensation nuclei spectra at the ground-based site have been used to determine cloud microphyical properties using wind vectors and meteorological parameters measured by the RPAS at cloud base. These derived cloud properties have been validated by in-situ RPAS measurements in the cloud and compared to those derived by the Suomi-NPP satellite. In addition, RPAS profiles in Cyprus observed the layers of dust originating from the Arabian Peninsula and the Sahara Desert. These profiles generally show a well-mixed boundary layer and compare well with ground-based LIDAR observations.

Narrow-line region kinematics in Seyfert nuclei

NASA Astrophysics Data System (ADS)

Moore, David J.

1994-01-01

We present results of a study of narrow-line region (NLR) kinematics in Seyfert nuclei. This study has involved extensive modeling which includes collimated emission, radially dependent rotation and turbulence, explicit photoionization calculations, realistic treatments of both internal and external obscuration, and allows for gradients in the electron density and the radial velocity of clouds throughout the NLR. Line profiles of (O II) lambda 3727, (Ne III) lambda 3869, (O III) lambda 5007, (Fe VII) lambda 6087, (Fe X) lambda 6374, (O I) lambda 6300, H alpha lambda 6563, and (S II) lambda 6731 are calculated for a wide range of physical conditions throughout the NLR. The model profiles are compared with line profiles derived from data taken with the Mount Palomar 5 m Hale Telescope as well as from profiles taken from the literature. The scenario in agreement with the largest of observational considerations consists of clouds which are accelerating outward with v varies as square root of r (i.e., constant force) and ne varies as 1/r2. The cloud start out at the inner NLR radium with ne approximately equal to 106/cu cm and with a very large column density (1023 - 10(exp 24/sq cm). These clouds are uniformly accelerated from a few tens of km/sec to approximately less than 1,000 km/sec. When the clouds reached the outer NLR radius, they have ne approximately greater than 102/cu cm and a column density of 1021-1022/sq cm. The clouds maintain an ionization parameter of about 0.3 throughout the NLR.

3D Cloud Field Prediction using A-Train Data and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Johnson, C. L.

2017-12-01

Validation of cloud process parameterizations used in global climate models (GCMs) would greatly benefit from observed 3D cloud fields at the size comparable to that of a GCM grid cell. For the highest resolution simulations, surface grid cells are on the order of 100 km by 100 km. CloudSat/CALIPSO data provides 1 km width of detailed vertical cloud fraction profile (CFP) and liquid and ice water content (LWC/IWC). This work utilizes four machine learning algorithms to create nonlinear regressions of CFP, LWC, and IWC data using radiances, surface type and location of measurement as predictors and applies the regression equations to off-track locations generating 3D cloud fields for 100 km by 100 km domains. The CERES-CloudSat-CALIPSO-MODIS (C3M) merged data set for February 2007 is used. Support Vector Machines, Artificial Neural Networks, Gaussian Processes and Decision Trees are trained on 1000 km of continuous C3M data. Accuracy is computed using existing vertical profiles that are excluded from the training data and occur within 100 km of the training data. Accuracy of the four algorithms is compared. Average accuracy for one day of predicted data is 86% for the most successful algorithm. The methodology for training the algorithms, determining valid prediction regions and applying the equations off-track is discussed. Predicted 3D cloud fields are provided as inputs to the Ed4 NASA LaRC Fu-Liou radiative transfer code and resulting TOA radiances compared to observed CERES/MODIS radiances. Differences in computed radiances using predicted profiles and observed radiances are compared.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

Searching for Dark Matter Annihilation in the Smith High-Velocity Cloud

NASA Technical Reports Server (NTRS)

Drlica-Wagner, Alex; Gomez-Vargas, German A.; Hewitt, John W.; Linden, Tim; Tibaldo, Luigi

2014-01-01

Recent observations suggest that some high-velocity clouds may be confined by massive dark matter halos. In particular, the proximity and proposed dark matter content of the Smith Cloud make it a tempting target for the indirect detection of dark matter annihilation. We argue that the Smith Cloud may be a better target than some Milky Way dwarf spheroidal satellite galaxies and use gamma-ray observations from the Fermi Large Area Telescope to search for a dark matter annihilation signal. No significant gamma-ray excess is found coincident with the Smith Cloud, and we set strong limits on the dark matter annihilation cross section assuming a spatially extended dark matter profile consistent with dynamical modeling of the Smith Cloud. Notably, these limits exclude the canonical thermal relic cross section (approximately 3 x 10 (sup -26) cubic centimeters per second) for dark matter masses less than or approximately 30 gigaelectronvolts annihilating via the B/B- bar oscillation or tau/antitau channels for certain assumptions of the dark matter density profile; however, uncertainties in the dark matter content of the Smith Cloud may significantly weaken these constraints.

Searching For Dark Matter Annihilation In The Smith High-Velocity Cloud

DOE PAGES

Drlica-Wagner, Alex; Gómez-Vargas, Germán A.; Hewitt, John W.; ...

2014-06-27

Recent observations suggest that some high-velocity clouds may be confined by massive dark matter halos. In particular, the proximity and proposed dark matter content of the Smith Cloud make it a tempting target for the indirect detection of dark matter annihilation. We argue that the Smith Cloud may be a better target than some Milky Way dwarf spheroidal satellite galaxies and use γ-ray observations from the Fermi Large Area Telescope to search for a dark matter annihilation signal. No significant γ-ray excess is found coincident with the Smith Cloud, and we set strong limits on the dark matter annihilation crossmore » section assuming a spatially extended dark matter profile consistent with dynamical modeling of the Smith Cloud. Notably, these limits exclude the canonical thermal relic cross section (~3 × 10 -26 cm3 s -1) for dark matter masses . 30 GeV annihilating via the b¯b or τ⁺τ⁻ channels for certain assumptions of the dark matter density profile; however, uncertainties in the dark matter content of the Smith Cloud may significantly weaken these constraints.« less

Using CATS Near-Real-time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; da Silva, A. M.; Mcgill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5 days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

Using CATS Near-Real-Time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; Da Silva, A. M.; McGill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects

NASA Astrophysics Data System (ADS)

Gu, B.; Yang, P.; Kuo, C. P.; Mlawer, E. J.

2017-12-01

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects Boyan Gu1, Ping Yang1, Chia-Pang Kuo1, Eli J. Mlawer2 Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA Atmospheric and Environmental Research (AER), Lexington, MA 02421, USA Ice clouds play an important role in climate system, especially in the Earth's radiation balance and hydrological cycle. However, the representation of ice cloud radiative effects (CRE) remains significant uncertainty, because scattering properties of ice clouds are not well considered in general circulation models (GCM). We analyze the strengths and weakness of the Rapid Radiative Transfer Model for GCM Applications (RRTMG) and Fu-Liou Radiative Transfer Model (RTM) against rigorous LBLRTM-DISORT (a combination of Line-By-Line Radiative Transfer Model and Discrete Ordinate Radiative Transfer Model) calculations and CERES (Clouds and the Earth's Radiant Energy System) flux observations. In total, 6 US standard atmospheric profiles and 42 atmospheric profiles from Atmospheric and Environmental Research (AER) Company are used to evaluate the RRTMG and Fu-Liou RTM by LBLRTM-DISORT calculations from 0 to 3250 cm-1. Ice cloud radiative effect simulations with RRTMG and Fu-Liou RTM are initialized using the ice cloud properties from MODIS collection-6 products. Simulations of single layer ice cloud CRE by RRTMG and LBLRTM-DISORT show that RRTMG, neglecting scattering, overestimates the TOA flux by about 0-15 W/m2 depending on the cloud particle size and optical depth, and the most significant overestimation occurs when the particle effective radius is small (around 10 μm) and the cloud optical depth is intermediate (about 1-10). The overestimation reduces significantly when the similarity rule is applied to RRTMG. We combine ice cloud properties from MODIS Collection-6 and atmospheric profiles from the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) reanalysis to simulate ice cloud CRE, which is compared with CERES observations.

Constraints on the Profiles of Total Water PDF in AGCMs from AIRS and a High-Resolution Model

NASA Technical Reports Server (NTRS)

Molod, Andrea

2012-01-01

Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the RH01 diagnostic, which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.

Subtropical Low Cloud Responses to Central and Eastern Pacific El Nino Events

NASA Astrophysics Data System (ADS)

Rapp, A. D.; Bennartz, R.; Jiang, J. H.; Kato, S.; Olson, W. S.; Pinker, R. T.; Su, H.; Taylor, P. C.

2014-12-01

The eastern Pacific El Niño event in 2006-2007 and the central Pacific El Niño event during 2009-2010 exhibit opposite responses in the top of atmosphere (TOA) cloud radiative effects. These responses are driven by differences in large-scale circulation that result in significant low cloud anomalies in the subtropical southeastern Pacific. Both the vertical profile of cloud fraction and cloud water content are reduced during the eastern Pacific El Niño; however, the shift in the distribution of cloud characteristics and the physical processes underlying these changes need further analysis. The NASA Energy and Water Cycle Study (NEWS) Clouds and Radiation Working Group will use a synthesis of NEWS data products, A-Train satellite measurements, reanalysis, and modeling approaches to further explore the differences in the low cloud response to changes in the large-scale forcing, as well as try to understand the physical mechanism driving the observed changes in the low clouds for the 2006/07 and 2009/10 distinct El Niño events. The distributions of cloud macrophysical, microphysical, and radiative properties over the southeast Pacific will first be compared for these two events using a combination of MODIS, CloudSat/CALIPSO, and CERES data. Satellite and reanalysis estimates of changes in the vertical temperature and moisture profiles, lower tropospheric stability, winds, and surface heat fluxes are then used to identify the drivers for observed differences in the clouds and TOA radiative effects.

Overview of MPLNET Version 3 Cloud Detection

NASA Technical Reports Server (NTRS)

Lewis, Jasper R.; Campbell, James; Welton, Ellsworth J.; Stewart, Sebastian A.; Haftings, Phillip

2016-01-01

The National Aeronautics and Space Administration Micro Pulse Lidar Network, version 3, cloud detection algorithm is described and differences relative to the previous version are highlighted. Clouds are identified from normalized level 1 signal profiles using two complementary methods. The first method considers vertical signal derivatives for detecting low-level clouds. The second method, which detects high-level clouds like cirrus, is based on signal uncertainties necessitated by the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multitemporal averaging scheme is used to improve cloud detection under conditions of a weak signal-to-noise ratio. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, Maryland) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5 km, above MSL), which increase in occurrence by over 5%. There is also an increase in the detection of multilayered cloud profiles from 9% to 19%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which the cirrus cloud optical depth could be reliably estimated occurs between 0.5 and 0.8. A comparison using collocated CALIPSO measurements at the Goddard Space Flight Center and Singapore Micro Pulse Lidar Network (MPLNET) sites indicates improvements in cloud occurrence frequencies and layer heights.

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Di Natale, Gianluca; Palchetti, Luca; Bianchini, Giovanni; Del Guasta, Massimo

2017-03-01

The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared - Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230-980 cm-1 spectral band. To simulate atmospheric radiative transfer, the Line-By-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the single-scattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg-Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

NASA Astrophysics Data System (ADS)

Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the vertical distribution of particle sizes, which allow reconstructing the profile of reff close to the cloud top. The comparison between retrieved and in situ reff yields a normalized mean absolute deviation, which ranges between 1.5 and 10.3 %, and a robust correlation coefficient of 0.82.

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

DTIC Science & Technology

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

DOE PAGES

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mechem, David B.; Giangrande, Scott E.

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

NASA Astrophysics Data System (ADS)

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large-eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time-varying three-dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

NASA Astrophysics Data System (ADS)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.

The dependence of entrainment and drizzle in marine stratiform clouds on biomass burning aerosols derived from stable isotope and thermodynamic profiles

NASA Astrophysics Data System (ADS)

Henze, D.; Noone, D.

2017-12-01

A third of the world's biomass burning aerosol (BBA) particles are generated in southern Africa, and these particles are swept into the midlevel troposphere over the southeast Atlantic Ocean. The presence of these aerosols over the marine environment of the south east Atlantic offers a unique natural laboratory for studying aerosol effects on climate, and specifically a modification to the hydrologic cycle and microphysical characteristics of clouds. Different rates of condensation with high aerosol numbers change the precipitation rates in drizzling stratiform clouds, while the mixing of aerosols into the cloud layer is synonymous with entrainment from above cloud top near the top of the subtropical inversion. To better understanding the magnitude of the aerosol influence on southeast Atlantic boundary layer clouds we analyze the cloud-top entrainment and drizzle as a function of aerosol loading to determine the impact of BBA. Entrainment was determined from mixing line analysis based on profile measurements of moist static energy, total water, and the two most common heavy isotopes of water - HDO and H218O. Data was collected on the P-3 Orion aircraft during the NASA 2017 ORACLES campaign. Using these measurements, a box model was constructed using the combined conservation laws associated with all four of these quantities to estimate the entrainment and rainout of cloud liquid. The population of profiles sampled by the aircraft over the course of the 30 day mission spans varying concentrations of BBA. Initial plots of the water isotope mixing lines show where and to what degree the BBA air mass has mixed into the boundary layer air mass from above. This is demonstrated by the fact that the mixing end-members are the same for the different areas sampled, but the rate at which the various mixing lines are traversed as a function of altitude varies. Further, the mixing lines as a function of height traverse back and forth between end members multiple times over one profile. This suggests that air masses are mixing by `layering' into each other, and helps us to better represent entrainment in our box model. Meanwhile, isotope ratios measured below vs above the cloud layer show that the air above the clouds is depleted of heavy water isotopes in comparison to below - the degree of depletion could correspond to drizzle amount.

Preliminary Results from the First Deployment of a Tethered-Balloon Cloud Particle Imager Instrument Package in Arctic Stratus Clouds at Ny-Alesund

NASA Astrophysics Data System (ADS)

Lawson, P.; Stamnes, K.; Stamnes, J.; Zmarzly, P.; O'Connor, D.; Koskulics, J.; Hamre, B.

2008-12-01

A tethered balloon system specifically designed to collect microphysical data in mixed-phase clouds was deployed in Arctic stratus clouds during May 2008 near Ny-Alesund, Svalbard, at 79 degrees North Latitude. This is the first time a tethered balloon system with a cloud particle imager (CPI) that records high-resolution digital images of cloud drops and ice particles has been operated in cloud. The custom tether supplies electrical power to the instrument package, which in addition to the CPI houses a 4-pi short-wavelength radiometer and a met package that measures temperature, humidity, pressure, GPS position, wind speed and direction. The instrument package was profiled vertically through cloud up to altitudes of 1.6 km. Since power was supplied to the instrument package from the ground, it was possible to keep the balloon package aloft for extended periods of time, up to 9 hours at Ny- Ålesund, which was limited only by crew fatigue. CPI images of cloud drops and the sizes, shapes and degree of riming of ice particles are shown throughout vertical profiles of Arctic stratus clouds. The images show large regions of mixed-phase cloud from -8 to -2 C. The predominant ice crystal habits in these regions are needles and aggregates of needles. The amount of ice in the mixed-phase clouds varied considerably and did not appear to be a function of temperature. On some occasions, ice was observed near cloud base at -2 C with supercooled cloud above to - 8 C that was devoid of ice. Measurements of shortwave radiation are also presented. Correlations between particle distributions and radiative measurements will be analyzed to determine the effect of these Arctic stratus clouds on radiative forcing.

An Analysis of Water Line Profiles in Star Formation Regions Observed by SWAS

NASA Technical Reports Server (NTRS)

Ashby, Matthew L. N.; Bergin, Edwin A.; Plume, Rene; Carpenter, John M.; Neufeld, David A.; Chin, Gordon; Erickson, Neal R.; Goldsmith, Paul F.; Harwit, Martin; Howe, J. E.

2000-01-01

We present spectral line profiles for the 557 GHz 1(sub 1,0) yields 1(sub 0,1) ground-state rotational transition of ortho-H2(16)O for 18 galactic star formation regions observed by SWAS. 2 Water is unambiguously detected in every source. The line profiles exhibit a wide variety of shapes, including single-peaked spectra and self-reversed profiles. We interpret these profiles using a Monte Carlo code to model the radiative transport. The observed variations in the line profiles can be explained by variations in the relative strengths of the bulk flow and small-scale turbulent motions within the clouds. Bulk flow (infall, outflow) must be present in some cloud cores, and in certain cases this bulk flow dominates the turbulent motions.

CATS Cloud and Aerosol Level 2 Heritage Edition Data Products.

NASA Astrophysics Data System (ADS)

Rodier, S. D.; Vaughan, M.; Yorks, J. E.; Palm, S. P.; Selmer, P. A.; Hlavka, D. L.; McGill, M. J.; Trepte, C. R.

2017-12-01

The Cloud-Aerosol Transport System (CATS) instrument was developed at NASA's Goddard Space Flight Center (GSFC) and deployed to the International Space Station (ISS) in January 2015. The CATS elastic backscatter lidars have been operating continuously in one of two science modes since February 2015. One of the primary science objectives of CATS is to continue the CALIPSO aerosol and cloud profile data record to provide continuity of lidar climate observations during the transition from CALIPSO to EarthCARE. To accomplish this, the CATS project at NASA's Goddard Space Flight Center (GSFC) and the CALIPSO project at NASA's Langley Research Center (LaRC) closely collaborated to develop and deliver a full suite of CALIPSO-like level 2 data products using the latest version of the CALIPSO level 2 Version 4 algorithms for the CATS data acquired while operating in science mode 1 (Multi-beam backscatter detection at 1064 and 532 nm, with depolarization measurement at both wavelengths). In this work, we present the current status of the CATS Heritage (i.e. CALIPSO-like) level 2 data products derived from the recent released CATS Level 1B V2-08 data. Extensive comparisons are performed between the three data sets (CALIPSO V4.10 Level 2, CATS Level 2 Operational V2-00 and CATS Heritage V1.00) for cloud and aerosol measurements (e.g., cloud-top height cloud-phase, cloud-layer occurrence frequency and cloud-aerosol discrimination) along the ISS path. In addition, global comparisons (between 52°S and 52°N) of aerosol extinction profiles derived from the CATS Level 2 Operational products and CALIOP V4 Level 2 products are presented. Comparisons of aerosol optical depths retrieved from active sensors (CATS and CALIOP) and passive sensors (MODIS) will provide context for the extinction profile comparisons.

Domain-averaged, Shallow Precipitation Measurements During the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)

NASA Astrophysics Data System (ADS)

Lamer, K.; Luke, E. P.; Kollias, P.; Oue, M.; Wang, J.

2017-12-01

The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates a fixed observatory in the Eastern North Atlantic (ENA) on Graciosa Island in the Azores. Straddling the tropics and extratropics, the Azores receive air transported from North America, the Arctic and sometimes Europe. At the ARM ENA site, marine boundary layer clouds are frequently observed all year round. Estimates of drizzle mass flux from the surface to cloud base height are documented using a combination of high sensitivity profiling 35-GHz radar and ceilometer observations. Three years of drizzle mass flux retrievals reveal that statistically, directly over the ENA site, marine boundary layer cloud drizzle rates tend to be weak with few heavy drizzle events. In the summer of 2017, this site hosted the first phase of the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign, which is motivated by the need for comprehensive in situ characterization of boundary layer structure, low clouds and aerosols. During this phase, the 35-GHz scanning ARM cloud radar was operated as a surveillance radar, providing regional context for the profiling observations. While less sensitive, the scanning radar measurements document a larger number of heavier drizzle events and provide domain-representative estimates of shallow precipitation. A best estimate, domain averaged, shallow precipitation rate for the region around the ARM ENA site is presented. The methodology optimally combines the ability of the profiling observations to detect the weak but frequently occurring drizzle events with the scanning cloud radar's ability to capture the less frequent heavier drizzle events. The technique is also evaluated using high resolution model output and a sophisticated forward radar operator.

Latitudinal Variations In Vertical Cloud Structure Of Jupiter As Determined By Ground- based Observation With Multispectral Imaging

NASA Astrophysics Data System (ADS)

Sato, T.; Kasaba, Y.; Takahashi, Y.; Murata, I.; Uno, T.; Tokimasa, N.; Sakamoto, M.

2008-12-01

We conducted ground-based observation of Jupiter with the liquid crystal tunable filter (LCTF) and EM-CCD camera in two methane absorption bands (700-757nm, 872-950nm at 3 nm step: total of 47 wavelengths) to derive detailed Jupiter's vertical cloud structure. The 2-meter reflector telescope at Nishi-Harima astronomical observatory in Japan was used for our observation on 26-30 May, 2008. After a series of image processing (composition of high quality images in each wavelength and geometry calibration), we converted observed intensity to absolute reflectivity at each pixel using standard star. As a result, we acquired Jupiter's data cubes with high-spatial resolution (about 1") and narrow band imaging (typically 7nm) in each methane absorption band by superimposing 30 Jupiter's images obtained in short exposure time (50 ms per one image). These data sets enable us to probe different altitudes of Jupiter from 100 mbar down to 1bar level with higher vertical resolution than using convectional interference filters. To interpret observed center-limb profiles, we developed radiative transfer code based on layer adding doubling algorithm to treat multiple scattering of solar light theoretically and extracted information on aerosol altitudes and optical properties using two-cloud model. First, we fit 5 different profiles simultaneously in continuum data (745-757 nm) to retrieve information on optical thickness of haze and single scattering albedo of cloud. Second, we fit 15 different profiles around 727nm methane absorption band and 13 different profiles around 890 nm methane absorption band to retrieve information on the aerosol altitude location and optical thickness of cloud. In this presentation, we present the results of these modeling simulations and discuss the latitudinal variations of Jupiter's vertical cloud structure.

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

NASA Astrophysics Data System (ADS)

Beck, Alexander; Henneberger, Jan; Schöpfer, Sarah; Fugal, Jacob; Lohmann, Ulrike

2017-02-01

In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s-1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

Fast Longwave and Shortwave Radiative Fluxes (FLASHFlux) From CERES and MODIS Measurements

NASA Astrophysics Data System (ADS)

Stackhouse, Paul; Gupta, Shashi; Kratz, David; Geier, Erika; Edwards, Anne; Wilber, Anne

The Clouds and the Earth's Radiant Energy System (CERES) project is currently producing highly accurate surface and top-of-atmosphere (TOA) radiation budget datasets from measurements taken by CERES broadband radiometers and a subset of imaging channels on the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument operating onboard Terra and Aqua satellites. The primary objective of CERES is to produce highly accurate and stable time-series datasets of radiation budget parameters to meet the needs of climate change research. Accomplishing such accuracy and stability requires monitoring the calibration and stability of the instruments, maintaining constancy of processing algorithms and meteorological inputs, and extensively validating the products against independent measurements. Such stringent requirements inevitably delay the release of products to the user community by as much as six months to a year. While such delays are inconsequential for climate research, other applications like short-term and seasonal predictions, agricultural and solar energy research, ocean and atmosphere assimilation, and field experiment support could greatly benefit if CERES products were available quickly after satellite measurements. To meet the needs of the latter class of applications, FLASHFlux was developed and is being implemented at the NASA/LaRC. FLASHFlux produces reliable surface and TOA radiative parameters within a one week of satellite observations using CERES "quicklook" data stream and fast surface flux algorithms. Cloud properties used in flux computation are derived concurrently using MODIS channel radiances. In the process, a modest degree of accuracy is sacrificed in the interest of speed. All fluxes are derived initially on a CERES footprint basis. Daily average fluxes are then derived on a 1° x1° grid in the next stage of processing. To date, FLASHFlux datasets have been used in operational processing of CloudSat data, in support of a field experiment, and for the S'COOL education outreach program. In this presentation, examples will be presented of footprint level and gridded/daily averaged fluxes and their validation. FLASHFlux datasets are available to the science community at the LaRC Atmospheric Sciences Data Center (ASDC) at: eosweb.larc.nasa.gov/PRODOCS/flashflux/table flashflux.html.

Observations of high droplet number concentrations in Southern Ocean boundary layer clouds

NASA Astrophysics Data System (ADS)

Chubb, T.; Huang, Y.; Jensen, J.; Campos, T.; Siems, S.; Manton, M.

2015-09-01

Data from the standard cloud physics payload during the NSF/NCAR High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) campaigns provide a snapshot of unusual wintertime microphysical conditions in the boundary layer over the Southern Ocean. On 29 June 2011, the HIAPER sampled the boundary layer in a region of pre-frontal warm air advection between 58 and 48° S to the south of Tasmania. Cloud droplet number concentrations were consistent with climatological values in the northernmost profiles but were exceptionally high for wintertime in the Southern Ocean at 100-200 cm-3 in the southernmost profiles. Sub-micron (0.0625 m s-1) were most likely responsible for production of sea spray aerosol which influenced the microphysical properties of the boundary layer clouds. The smaller size and higher number concentration of cloud droplets is inferred to increase the albedo of these clouds, and these conditions occur regularly, and are expected to increase in frequency, over windy parts of the Southern Ocean.

Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

NASA Technical Reports Server (NTRS)

Wang, Zhien; Heymsfield, Gerald M.; Li, Lihua; Heymsfield, Andrew J.

2005-01-01

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

The Radiative Effects of Martian Water Ice Clouds on the Local Atmospheric Temperature Profile

NASA Technical Reports Server (NTRS)

Colaprete, Anthony; Toon, Owen B.

2000-01-01

Mars Pathfinder made numerous discoveries, one of which was a deep temperature inversion that extended from about 15 km down to 8 km above the surface. It has been suggested by Haberle et al. (1999. J. Geophys. Res. 104, 8957-8974.) that radiative cooling by a water ice cloud may generate such an inversion. Clouds can strongly affect the local air temperature due to their ability to radiate efficiently in the infrared and due to the low air mass of the martian atmosphere, which allows the temperature to change during the relatively short lifetime of a cloud. We utilize a time-dependent microphysical aerosol model coupled to a radiative--convective model to explore the effects water ice clouds have on the local martian temperature profile. We constrain the dust and water vapor abundance using data from the Viking Missions and Mars Pathfinder. Water t ice clouds with visible optical depths of r > 0.1 form readily in these simulations. These clouds alter the local air temperature directly, through infrared cooling, and indirectly, by redistributing atmospheric dust. With this model we are able to reproduce the temperature inversions observed by Mars Pathfinder and Mars Global t Surveyor 2000 Academic Press

Aerosol effect on the evolution of the thermodynamic properties of warm convective cloud fields

PubMed Central

Dagan, Guy; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven H.

2016-01-01

Convective cloud formation and evolution strongly depend on environmental temperature and humidity profiles. The forming clouds change the profiles that created them by redistributing heat and moisture. Here we show that the evolution of the field’s thermodynamic properties depends heavily on the concentration of aerosol, liquid or solid particles suspended in the atmosphere. Under polluted conditions, rain formation is suppressed and the non-precipitating clouds act to warm the lower part of the cloudy layer (where there is net condensation) and cool and moisten the upper part of the cloudy layer (where there is net evaporation), thereby destabilizing the layer. Under clean conditions, precipitation causes net warming of the cloudy layer and net cooling of the sub-cloud layer (driven by rain evaporation), which together act to stabilize the atmosphere with time. Previous studies have examined different aspects of the effects of clouds on their environment. Here, we offer a complete analysis of the cloudy atmosphere, spanning the aerosol effect from instability-consumption to enhancement, below, inside and above warm clouds, showing the temporal evolution of the effects. We propose a direct measure for the magnitude and sign of the aerosol effect on thermodynamic instability. PMID:27929097

Aerosol effect on the evolution of the thermodynamic properties of warm convective cloud fields.

PubMed

Dagan, Guy; Koren, Ilan; Altaratz, Orit; Heiblum, Reuven H

2016-12-08

Convective cloud formation and evolution strongly depend on environmental temperature and humidity profiles. The forming clouds change the profiles that created them by redistributing heat and moisture. Here we show that the evolution of the field's thermodynamic properties depends heavily on the concentration of aerosol, liquid or solid particles suspended in the atmosphere. Under polluted conditions, rain formation is suppressed and the non-precipitating clouds act to warm the lower part of the cloudy layer (where there is net condensation) and cool and moisten the upper part of the cloudy layer (where there is net evaporation), thereby destabilizing the layer. Under clean conditions, precipitation causes net warming of the cloudy layer and net cooling of the sub-cloud layer (driven by rain evaporation), which together act to stabilize the atmosphere with time. Previous studies have examined different aspects of the effects of clouds on their environment. Here, we offer a complete analysis of the cloudy atmosphere, spanning the aerosol effect from instability-consumption to enhancement, below, inside and above warm clouds, showing the temporal evolution of the effects. We propose a direct measure for the magnitude and sign of the aerosol effect on thermodynamic instability.

Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenfeld, Daniel

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which ismore » the same as CCN(S). Developing and validating this methodology was possible thanks to the ASR/ARM measurements of CCN and vertical updraft profiles. Validation against ground-based CCN instruments at the ARM sites in Oklahoma, Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25º restricts the satellite coverage to ~25% of the world area in a single day. This methodology will likely allow overcoming the challenge of quantifying the aerosol indirect effect and facilitate a substantial reduction of the uncertainty in anthropogenic climate forcing.« less

Lightning Nitrogen Oxides (LNOx) Vertical Profile Quantification and 10 Year Trend Analysis using Ozone Monitoring Instrument (OMI) Satellite Measurements, Air Quality Station (AQS) Surface Measurements, The National Lightning Detection Network (NLDN), and Simulated by Cloud Resolving Chemical Transport Model (REAM Cloud)

NASA Astrophysics Data System (ADS)

Smeltzer, C. D.; Wang, Y.; Koshak, W. J.

2014-12-01

Vertical profiles and emission lifetimes of lightning nitrogen oxides (LNOx) are derived using the Ozone Monitoring Instrument (OMI). Approximately 200 million flashes, over a 10 year climate period, from the United States National Lighting Detection Network (NLDN), are aggregated with OMI cloud top height to determine the vertical LNOx structure. LNOx lifetime is determined as function of LNOx signal in a 36 kilometer vertical column from the time of the last known flash to depletion of the LNOx signal. Environmental Protection Agency (EPA) Air Quality Station (AQS) surface data further support these results by demonstrating as much as a 200% increase in surface level NO2 during strong thunderstorm events and a lag as long as 5 to 8 hours from the lightning event to the peak surface event, indicating a evolutional process. Analysis of cloud resolving chemical transport model (REAM Cloud) demonstrates that C-shaped LNOx profiles, which agree with OMI vertical profile observations, evolve due to micro-scale convective meteorology given inverted C-shaped LNOx emission profiles as determined from lightning radio telemetry. It is shown, both in simulations and in observations, that the extent to which the LNOx vertical distribution is C-shaped and the lifetime of LNOx is proportional to the shear-strength of the thunderstorm. Micro-scale convective meteorology is not adequately parameterized in global scale and regional scale chemical transport models (CTM). Therefore, these larger scale CTMs ought to use a C-shape emissions profile to best reproduce observations until convective parameterizations are updated. These findings are used to simulate decadal LNOx and lightning ozone climatology over the Continental United States (CONUS) from 2004-2014.

Earlinet validation of CATS L2 product

NASA Astrophysics Data System (ADS)

Proestakis, Emmanouil; Amiridis, Vassilis; Kottas, Michael; Marinou, Eleni; Binietoglou, Ioannis; Ansmann, Albert; Wandinger, Ulla; Yorks, John; Nowottnick, Edward; Makhmudov, Abduvosit; Papayannis, Alexandros; Pietruczuk, Aleksander; Gialitaki, Anna; Apituley, Arnoud; Muñoz-Porcar, Constantino; Bortoli, Daniele; Dionisi, Davide; Althausen, Dietrich; Mamali, Dimitra; Balis, Dimitris; Nicolae, Doina; Tetoni, Eleni; Luigi Liberti, Gian; Baars, Holger; Stachlewska, Iwona S.; Voudouri, Kalliopi-Artemis; Mona, Lucia; Mylonaki, Maria; Rita Perrone, Maria; João Costa, Maria; Sicard, Michael; Papagiannopoulos, Nikolaos; Siomos, Nikolaos; Burlizzi, Pasquale; Engelmann, Ronny; Abdullaev, Sabur F.; Hofer, Julian; Pappalardo, Gelsomina

2018-04-01

The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.

The Microwave Properties of Simulated Melting Precipitation Particles: Sensitivity to Initial Melting

NASA Technical Reports Server (NTRS)

Johnson, B. T.; Olson, W. S.; Skofronick-Jackson, G.

2016-01-01

A simplified approach is presented for assessing the microwave response to the initial melting of realistically shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM), a heuristic melting simulation for ice-phase precipitation particles of any shape or size (SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass), and (2) the computation of the single-particle microwave scattering and extinction properties of these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, and 94.0GHz for radar applications and 89, 165.0, and 183.31GHz for radiometer applications. These selected frequencies are consistent with current microwave remote-sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

Fast Longwave and Shortwave Radiative Flux (FLASHFlux) Products from CERES and MODIS Measurements

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Kratz, David P.; McGarragh, Greg R.; Gupta, Shashi K.; Geier, Erika B.

2006-01-01

The Clouds and the Earth s Radiant Energy Systems (CERES) project is currently producing world-class climatological data products derived from measurements taken aboard the Terra and Aqua spacecrafts (Wielicki et al., 1996). While of exceptional fidelity, these data products require a considerable amount of processing to assure quality and verify accuracy and precision. Obtaining such high quality assurance, however, means that the CERES data is typically released more than six months after the acquisition of the initial measurements. For climate studies, such delays are of little consequence, especially considering the improved quality of the released data products. There are, however, many uses for the CERES data products on a near real-time basis. These include: CERES instrument calibration and subsystem quality checks, CLOUDSAT operations, seasonal predictions, agricultural and ocean assimilations, support of field campaigns, and outreach programs such as S'Cool. The FLASHflux project was envisioned as a conduit whereby CERES data could be provided to the community within a week of the initial measurements, with the trade-off that some degree of fidelity would be exacted to gain speed. In this paper, we will report on some very encouraging initial results from the FLASHflux project in which we compared the FLASHflux instantaneous surface fluxes to the CERES surface-only flux algorithm data products.

Propagation of a Toroidal Magnetic Cloud through the Inner Heliosphere

NASA Astrophysics Data System (ADS)

Romashets, Eugene; Vandas, Marek

2003-09-01

An analytical solution for a potential magnetic field with arbitrary intensity around a toroidal magnetic cloud has been found. The background external field may have a gradient. The solution is used for calculation of magnetic cloud propagation. Obtained velocity profiles show a good agreement with in situ observations near the Earth's orbit.

A Decade of Global Lidar Cloud and Aerosol Profiling

NASA Astrophysics Data System (ADS)

Winker, D. M.

2016-12-01

The CALIPSO satellite was developed as a collaboration between NASA and CNES with the objective of globally profiling aerosols and clouds for the first time. Launched in April 2006, CALIPSO has now flown for a decade as part of the A-train satellite constellation, producing an unprecedented 3D observational record and more than a thousand publications to date. Originally planned as a three-year mission, the unanticipated duration of the CALIPSO mission has allowed the characterization of seasonal and interannual variability of aerosols and clouds. This presentation will discuss highlights among the scientific findings from CALIPSO, including contributions to our understanding of Earth's climate and climate change.

Rayleigh beacon for measuring the surface profile of a radio telescope.

PubMed

Padin, S

2014-12-01

Millimeter-wavelength Rayleigh scattering from water droplets in a cloud is proposed as a means of generating a bright beacon for measuring the surface profile of a radio telescope. A λ=3  mm transmitter, with an output power of a few watts, illuminating a stratiform cloud, can generate a beacon with the same flux as Mars in 10 GHz bandwidth, but the beacon has a narrow line width, so it is extremely bright. The key advantage of the beacon is that it can be used at any time, and positioned anywhere in the sky, as long as there are clouds.

GEOMETRY-INDEPENDENT DETERMINATION OF RADIAL DENSITY DISTRIBUTIONS IN MOLECULAR CLOUD CORES AND OTHER ASTRONOMICAL OBJECTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krčo, Marko; Goldsmith, Paul F., E-mail: marko@astro.cornell.edu

2016-05-01

We present a geometry-independent method for determining the shapes of radial volume density profiles of astronomical objects whose geometries are unknown, based on a single column density map. Such profiles are often critical to understand the physics and chemistry of molecular cloud cores, in which star formation takes place. The method presented here does not assume any geometry for the object being studied, thus removing a significant source of bias. Instead, it exploits contour self-similarity in column density maps, which appears to be common in data for astronomical objects. Our method may be applied to many types of astronomical objectsmore » and observable quantities so long as they satisfy a limited set of conditions, which we describe in detail. We derive the method analytically, test it numerically, and illustrate its utility using 2MASS-derived dust extinction in molecular cloud cores. While not having made an extensive comparison of different density profiles, we find that the overall radial density distribution within molecular cloud cores is adequately described by an attenuated power law.« less

Scanning Cloud Radar Observations at the ARM sites

NASA Astrophysics Data System (ADS)

Kollias, P.; Clothiaux, E. E.; Shupe, M.; Widener, K.; Bharadwaj, N.; Miller, M. A.; Verlinde, H.; Luke, E. P.; Johnson, K. L.; Jo, I.; Tatarevic, A.; Lamer, K.

2012-12-01

Recently, the DOE Atmospheric Radiation Measurement (ARM) program upgraded its fixed and mobile facilities with the acquisition of state-of-the-art scanning, dual-wavelength, polarimetric, Doppler cloud radars. The scanning ARM cloud radars (SACR's) are the most expensive and significant radar systems at all ARM sites and eight SACR systems will be operational at ARM sites by the end of 2013. The SACR's are the primary instruments for the detection of 3D cloud properties (boundaries, volume cloud fractional coverage, liquid water content, dynamics, etc.) beyond the soda-straw (profiling) limited view. Having scanning capabilities with two frequencies and polarization allows more accurate probing of a variety of cloud systems (e.g., drizzle and shallow, warm rain), better correction for attenuation, use of attenuation for liquid water content retrievals, and polarimetric and dual-wavelength ratio characterization of non-spherical particles for improved ice crystal habit identification. Examples of SACR observations from four ARM sites are presented here: the fixed sites at Southern Great Plains (SGP) and North Slope of Alaska (NSA), and the mobile facility deployments at Graciosa Island, Azores and Cape Cod, Massachusetts. The 3D cloud structure is investigated both at the macro-scale (20-50 km) and cloud-scale (100-500 m). Doppler velocity measurements are corrected for velocity folding and are used either to describe the in-cloud horizontal wind profile or the 3D vertical air motions.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

3.6 cm signal attenuation in Venus' lower and middle atmosphere observed by the Radio Science experiment VeRa onboard Venus Express

NASA Astrophysics Data System (ADS)

Oschlisniok, J.; Tellmann, S.; Pätzold, M.; Häusler, B.; Andert, T.; Bird, M.; Remus, S.

2012-09-01

The planet Venus is shrouded within a roughly 20 km thick cloud layer, which extends from the lower to the middle atmosphere (ca. 50 - 70 km). While the clouds are mostly composed of sulfuric acid droplets, a haze layer of sulfuric acid vapor exists below the clouds. Within the cloud and the sub - cloud region Radio signal strength variations (intensity scintillations) caused by atmospheric waves and a decrease in the signal intensity caused by absorption by H2SO4 are observed by radio occultation experiments. The Venus Express spacecraft is orbiting Venus since 2006. The Radio Science Experiment VeRa probes the atmosphere with radio signals at 3.6 cm (XBand) and 13 cm (S-Band) wavelengths. The disturbance of the radio signal intensity is used to investigate the cloud region with respect to atmospheric waves. The absorption of the signal is used to determine the abundance of H2SO4 near the cloud base. This way a detailed study of the H2SO4 abundance within the cloud and sub - cloud region is possible. Results from the intensity scintillations within the cloud deck are presented and compared with gravity wave studies based on temperature variations inferred from VeRa soundings. Vertical absorptivity profiles and resulting sulfuric acid vapor profiles are presented and compared with previous missions. A distinct latitudinal dependence and a southern northern symmetry are clearly visible.

Precipitating Condensation Clouds in Substellar Atmospheres

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Marley, Mark S.; Gore, Warren J. (Technical Monitor)

2000-01-01

We present a method to calculate vertical profiles of particle size distributions in condensation clouds of giant planets and brown dwarfs. The method assumes a balance between turbulent diffusion and precipitation in horizontally uniform cloud decks. Calculations for the Jovian ammonia cloud are compared with previous methods. An adjustable parameter describing the efficiency of precipitation allows the new model to span the range of predictions from previous models. Calculations for the Jovian ammonia cloud are found to be consistent with observational constraints. Example calculations are provided for water, silicate, and iron clouds on brown dwarfs and on a cool extrasolar giant planet.

Precipitation from the GPM Microwave Imager and Constellation Radiometers

NASA Astrophysics Data System (ADS)

Kummerow, Christian; Randel, David; Kirstetter, Pierre-Emmanuel; Kulie, Mark; Wang, Nai-Yu

2014-05-01

Satellite precipitation retrievals from microwave sensors are fundamentally underconstrained requiring either implicit or explicit a-priori information to constrain solutions. The radiometer algorithm designed for the GPM core and constellation satellites makes this a-priori information explicit in the form of a database of possible rain structures from the GPM core satellite and a Bayesian retrieval scheme. The a-priori database will eventually come from the GPM core satellite's combined radar/radiometer retrieval algorithm. That product is physically constrained to ensure radiometric consistency between the radars and radiometers and is thus ideally suited to create the a-priori databases for all radiometers in the GPM constellation. Until a robust product exists, however, the a-priori databases are being generated from the combination of existing sources over land and oceans. Over oceans, the Day-1 GPM radiometer algorithm uses the TRMM PR/TMI physically derived hydrometer profiles that are available from the tropics through sea surface temperatures of approximately 285K. For colder sea surface temperatures, the existing profiles are used with lower hydrometeor layers removed to correspond to colder conditions. While not ideal, the results appear to be reasonable placeholders until the full GPM database can be constructed. It is more difficult to construct physically consistent profiles over land due to ambiguities in surface emissivities as well as details of the ice scattering that dominates brightness temperature signatures over land. Over land, the a-priori databases have therefore been constructed by matching satellite overpasses to surface radar data derived from the WSR-88 network over the continental United States through the National Mosaic and Multi-Sensor QPE (NMQ) initiative. Databases are generated as a function of land type (4 categories of increasing vegetation cover as well as 4 categories of increasing snow depth), land surface temperature and total precipitable water. One year of coincident observations, generating 20 and 80 million database entries, depending upon the sensor, are used in the retrieval algorithm. The remaining areas such as sea ice and high latitude coastal zones are filled with a combination of CloudSat and AMSR-E plus MHS observations together with a model to create the equivalent databases for other radiometers in the constellation. The most noteworthy result from the Day-1 algorithm is the quality of the land products when compared to existing products. Unlike previous versions of land algorithms that depended upon complex screening routines to decide if pixels were precipitating or not, the current scheme is free of conditional rain statements and appears to produce rain rate with much greater fidelity than previous schemes. There results will be shown.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2017-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2016-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

Probing a dusty magnetized plasma with self-excited dust-density waves

NASA Astrophysics Data System (ADS)

Tadsen, Benjamin; Greiner, Franko; Piel, Alexander

2018-03-01

A cloud of nanodust particles is created in a reactive argon-acetylene plasma. It is then transformed into a dusty magnetized argon plasma. Plasma parameters are obtained with the dust-density wave diagnostic introduced by Tadsen et al. [Phys. Plasmas 22, 113701 (2015), 10.1063/1.4934927]. A change from an open to a cylindrically enclosed nanodust cloud, which was observed earlier, can now be explained by a stronger electric confinement if a vertical magnetic field is present. Using two-dimensional extinction measurements and the inverse Abel transform to determine the dust density, a redistribution of the dust with increasing magnetic induction is found. The dust-density profile changes from being peaked around the central void to being peaked at an outer torus ring resulting in a hollow profile. As the plasma parameters cannot explain this behavior, we propose a rotation of the nanodust cloud in the magnetized plasma as the origin of the modified profile.

Using Space Lidar Observations to Decompose Longwave Cloud Radiative Effect Variations Over the Last Decade

NASA Astrophysics Data System (ADS)

Vaillant de Guélis, Thibault; Chepfer, Hélène; Noel, Vincent; Guzman, Rodrigo; Winker, David M.; Plougonven, Riwal

2017-12-01

Measurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Aerosol and Cloud Interaction Observed From High Spectral Resolution Lidar Data

NASA Technical Reports Server (NTRS)

Su, Wenying; Schuster, Gregory L.; Loeb, Norman G.; Rogers, Raymond R.; Ferrare, Richard A.; Hostetler, Chris A.; Hair, Johnathan W.; Obland, Michael D.

2008-01-01

Recent studies utilizing satellite retrievals have shown a strong correlation between aerosol optical depth (AOD) and cloud cover. However, these retrievals from passive sensors are subject to many limitations, including cloud adjacency (or 3D) effects, possible cloud contamination, uncertainty in the AOD retrieval. Some of these limitations do not exist in High Spectral Resolution Lidar (HSRL) observations; for instance, HSRL observations are not a ected by cloud adjacency effects, are less prone to cloud contamination, and offer accurate aerosol property measurements (backscatter coefficient, extinction coefficient, lidar ratio, backscatter Angstrom exponent,and aerosol optical depth) at a neospatial resolution (less than 100 m) in the vicinity of clouds. Hence, the HSRL provides an important dataset for studying aerosol and cloud interaction. In this study, we statistically analyze aircraft-based HSRL profiles according to their distance from the nearest cloud, assuring that all profile comparisons are subject to the same large-scale meteorological conditions. Our results indicate that AODs from HSRL are about 17% higher in the proximity of clouds (approximately 100 m) than far away from clouds (4.5 km), which is much smaller than the reported cloud 3D effect on AOD retrievals. The backscatter and extinction coefficients also systematically increase in the vicinity of clouds, which can be explained by aerosol swelling in the high relative humidity (RH) environment and/or aerosol growth through in cloud processing (albeit not conclusively). On the other hand, we do not observe a systematic trend in lidar ratio; we hypothesize that this is caused by the opposite effects of aerosol swelling and aerosol in-cloud processing on the lidar ratio. Finally, the observed backscatter Angstrom exponent (BAE) does not show a consistent trend because of the complicated relationship between BAE and RH. We demonstrate that BAE should not be used as a surrogate for Angstrom exponent, especially at high RH.

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhien

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentrationmore » retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).« less

Vertical structure of tropospheric winds on gas giants

NASA Astrophysics Data System (ADS)

Scott, R. K.; Dunkerton, T. J.

2017-04-01

Zonal mean zonal velocity profiles from cloud-tracking observations on Jupiter and Saturn are used to infer latitudinal variations of potential temperature consistent with a shear stable potential vorticity distribution. Immediately below the cloud tops, density stratification is weaker on the poleward and stronger on the equatorward flanks of midlatitude jets, while at greater depth the opposite relation holds. Thermal wind balance then yields the associated vertical shears of midlatitude jets in an altitude range bounded above by the cloud tops and bounded below by the level where the latitudinal gradient of static stability changes sign. The inferred vertical shear below the cloud tops is consistent with existing thermal profiling of the upper troposphere. The sense of the associated mean meridional circulation in the upper troposphere is discussed, and expected magnitudes are given based on existing estimates of the radiative timescale on each planet.

Boundary-layer cumulus over heterogeneous landscapes: A subgrid GCM parameterization. Final report, December 1991--November 1995

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stull, R.B.; Tripoli, G.

1996-01-08

The authors developed single-column parameterizations for subgrid boundary-layer cumulus clouds. These give cloud onset time, cloud coverage, and ensemble distributions of cloud-base altitudes, cloud-top altitudes, cloud thickness, and the characteristics of cloudy and clear updrafts. They tested and refined the parameterizations against archived data from Spring and Summer 1994 and 1995 intensive operation periods (IOPs) at the Southern Great Plains (SGP) ARM CART site near Lamont, Oklahoma. The authors also found that: cloud-base altitudes are not uniform over a heterogeneous surface; tops of some cumulus clouds can be below the base-altitudes of other cumulus clouds; there is an overlap regionmore » near cloud base where clear and cloudy updrafts exist simultaneously; and the lognormal distribution of cloud sizes scales to the JFD of surface layer air and to the shape of the temperature profile above the boundary layer.« less

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

NASA Astrophysics Data System (ADS)

McLoughlin, Leigh

Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physically-based simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation..

NASA Goddard Giovanni Support for YOTC

NASA Technical Reports Server (NTRS)

Ostrenga, Dana; Leptoukh, Gregory; Waliser, Duane

2010-01-01

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Impact of aerosol intrusions on sea-ice melting rates and the structure Arctic boundary layer clouds

NASA Astrophysics Data System (ADS)

Cotton, W.; Carrio, G.; Jiang, H.

2003-04-01

The Los Alamos National Laboratory sea-ice model (LANL CICE) was implemented into the real-time and research versions of the Colorado State University-Regional Atmospheric Modeling System (RAMS@CSU). The original version of CICE was modified in its structure to allow module communication in an interactive multigrid framework. In addition, some improvements have been made in the routines involved in the coupling, among them, the inclusion of iterative methods that consider variable roughness lengths for snow-covered ice thickness categories. This version of the model also includes more complex microphysics that considers the nucleation of cloud droplets, allowing the prediction of mixing ratios and number concentrations for all condensed water species. The real-time version of RAMS@CSU automatically processes the NASA Team SSMI F13 25km sea-ice coverage data; the data are objectively analyzed and mapped to the model grid configuration. We performed two types of cloud resolving simulations to assess the impact of the entrainment of aerosols from above the inversion on Arctic boundary layer clouds. The first series of numerical experiments corresponds to a case observed on May 4 1998 during the FIRE-ACE/SHEBA field experiment. Results indicate a significant impact on the microstructure of the simulated clouds. When assuming polluted initial profiles above the inversion, the liquid water fraction of the cloud monotonically decreases, the total condensate paths increases and downward IR tends to increase due to a significant increase in the ice water path. The second set of cloud resolving simulations focused on the evaluation of the potential effect of aerosol concentration above the inversion on melting rates during spring-summer period. For these multi-month simulations, the IFN and CCN profiles were also initialized assuming the 4 May profiles as benchmarks. Results suggest that increasing the aerosol concentrations above the boundary layer increases sea-ice melting rates when mixed phase clouds are present.

Spatial and Temporal Inter-Relationships Between Anomalies of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

NASA Technical Reports Server (NTRS)

Susskind, Joel

2008-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, percent cloud cover and cloud top pressure, and OLR. Near real time products, stating with September 2002, have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. Results in this paper included products through April 2008. The time period studied is marked by a substantial warming trend of Northern Hemisphere Extropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, are shown below, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. The ability to match this data represents a good test of a model's response to El Nino.

Determination of precipitation profiles from airborne passive microwave radiometric measurements

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.

1991-01-01

This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.

Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

NASA Astrophysics Data System (ADS)

Kalesse, H.; Luke, E. P.; Seifert, P.

2017-12-01

The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

Macrophysical Properties of Tropical Cirrus Clouds from the CALIPSO Satellite and from Ground-based Micropulse and Raman Lidars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsen, Tyler J.; Fu, Qiang; Comstock, Jennifer M.

2013-08-27

Lidar observations of cirrus cloud macrophysical properties over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Darwin, Australia site are compared from the Cloud-Aerosol Lidar and In- frared Pathfinder Satellite Observation (CALIPSO) satellite, the ground-based ARM micropulse lidar (MPL), and the ARM Raman lidar (RL). Comparisons are made using the subset of profiles where the lidar beam is not fully attenuated. Daytime measurements using the RL are shown to be relatively unaffected by the solar background and are therefore suited for checking the validity of diurnal cycles. RL and CALIPSO cloud fraction profiles show good agreement while themore » MPL detects significantly less cirrus, particularly during the daytime. Both MPL and CALIPSO observations show that cirrus clouds occur less frequently during the day than at night at all altitudes. In contrast, the RL diurnal cy- cle is significantly different than zero only below about 11 km; where it is the opposite sign (i.e. more clouds during the daytime). For cirrus geomet- rical thickness, the MPL and CALIPSO observations agree well and both datasets have signficantly thinner clouds during the daytime than the RL. From the examination of hourly MPL and RL cirrus cloud thickness and through the application of daytime detection limits to all CALIPSO data we find that the decreased MPL and CALIPSO cloud thickness during the daytime is very likely a result of increased daytime noise. This study highlights the vast im- provement the RL provides (compared to the MPL) in the ARM program's ability to observe tropical cirrus clouds as well as a valuable ground-based lidar dataset for the validation of CALIPSO observations and to help im- prove our understanding of tropical cirrus clouds.« less

Earth cloud, aerosol, and radiation explorer optical payload development status

NASA Astrophysics Data System (ADS)

Hélière, A.; Wallace, K.; Pereira do Carmo, J.; Lefebvre, A.

2017-09-01

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are co-operating to develop as part of ESA's Living Planet Programme, the third Earth Explorer Core Mission, EarthCARE, with the ojective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth's atmosphere. EarthCARE payload consists of two active and two passive instruments: an ATmospheric LIDar (ATLID), a Cloud Profiling Radar (CPR), a Multi-Spectral Imager (MSI) and a Broad-Band Radiometer (BBR). The four instruments data are processed individually and in a synergetic manner to produce a large range of products, which include vertical profiles of aerosols, liquid water and ice, observations of cloud distribution and vertical motion within clouds, and will allow the retrieval of profiles of atmospheric radiative heating and cooling. MSI is a compact instrument with a 150 km swath providing 500 m pixel data in seven channels, whose retrieved data will give context to the active instrument measurements, as well as providing cloud and aerosol information. BBR measures reflected solar and emitted thermal radiation from the scene. Operating in the UV range at 355 nm, ATLID provides atmospheric echoes from ground to an altitude of 40 km. Thanks to a high spectral resolution filtering, the lidar is able to separate the relative contribution of aerosol and molecular scattering, which gives access to aerosol optical depth. Co-polarised and cross-polarised components of the Mie scattering contribution are measured on dedicated channels. This paper will provide a description of the optical payload implementation, the design and characterisation of the instruments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew R. Kumjian; Giangrande, Scott E.; Mishra, Subashree

Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation, riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. Furthermore, the Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity.

Study of wind retrieval from space-borne infrared coherent lidar in cloudy atmosphere.

NASA Astrophysics Data System (ADS)

Baron, Philippe; Ishii, Shoken; Mizutani, Kohei; Okamoto, Kozo; Ochiai, Satoshi

2015-04-01

Future spaceborne tropospheric wind missions using infrared coherent lidar are currently being studied in Japan and in the United States [1,2]. The line-of-sight wind velocity is retrieved from the Doppler shift frequency of the signal returned by aerosol particles. However a large percentage (70-80%) of the measured single-shot intensity profiles are expected to be contaminated by clouds [3]. A large number of cloud contaminated profiles (>40%) will be characterized by a cloud-top signal intensity stronger than the aerosol signal by a factor of one order of magnitude, and by a strong attenuation of the signal backscattered from below the clouds. Profiles including more than one cloud layer are also expected. This work is a simulation study dealing with the impacts of clouds on wind retrieval. We focus on the three following points: 1) definition of an algorithm for optimizing the wind retrieval from the cloud-top signal, 2) assessment of the clouds impact on the measurement performance and, 3) definition of a method for averaging the measurements before the retrieval. The retrieval simulations are conducted considering the instrumental characteristics selected for the Japanese study: wavelength at 2 µm, PRF of 30 Hz, pulse power of 0.125 mJ and platform altitude between 200-400 km. Liquid and ice clouds are considered. The analysis uses data from atmospheric models and statistics of cloud effects derived from CALIPSO measurements such as in [3]. A special focus is put on the average method of the measurements before retrieval. Good retrievals in the mid-upper troposphere implie the average of measured single-range power spectra over large horizontal (100 km) and vertical (1 km) ranges. Large differences of signal intensities due to the presence of clouds and the clouds non-uniform distribution have to be taken into account when averaging the data to optimize the measurement performances. References: [1] S. Ishii, T. Iwasaki, M. Sato, R. Oki, K. Okamoto, T. Ishibashi, P. Baron, and T. Nishizawa: Future Doppler lidar wind measurement from space in Japan, Proc. of SPIE Vol. 8529, 2012 [2] D. Wu, J. Tang, Z. Liu, and Y. Hu: Simulation of coherent doppler wind lidar measurement from space based on CALIPSO lidar global aerosol observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 122(0), 79-86, 2013 [3] G.D Emmitt: CFLOS and cloud statistics from satellite and their impact on future space-based Doppler Wind Lidar development. Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, 2008

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.

2008-01-01

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have 0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

Temporal Variability and Latitudinal Jets in Venus's Zonal Wind Profiles

NASA Astrophysics Data System (ADS)

Young, Eliot F.; Bullock, M. A.; Tavenner, T.; Coyote, S.; Murphy, J. R.

2008-09-01

We have observed Venus's night hemisphere from NASA's IRTF (Infrared Telescope Facility) during each inferior conjunction since 2001 to quantify the motion of features in Venus's lower and middle cloud decks. We now present latitudinal profiles from 11 nights, obtained in May and July 2004, February 2006 and September 2007. In about 7 of the 11 nights there are zonal jets near 45N and/or -50S, with speed differentials of 5 to 15 m/s relative to the adjacent equatorward latitude bands. These jets may be evidence of episodic Hadley cell-type circulation. About half of the nights show relatively constant velocity profiles between the latitudes of 50N to 50S, suggesting that considerable mixing is taking place between latitudes. Our most remarkable result is the temporal variability in the median zonal speeds from day to day. For example, the median velocity near the equator increases from 53 to 65 m/s over the period from July 11 - 13, 2004, and increases from 65 to 82 m/s over the period from Sept. 9 - 11, 2007. These velocity changes are too great to be due to the tracking of clouds that are in the middle vs. lower cloud deck, nor can they be caused by clouds that occupy different altitudes; a velocity variation of 25% corresponds to an altitude difference of 15 km, based on vertical profiles of zonal windspeeds from tracking of Pioneer Venus and Venera descent probes. Fifteen km is greater than the expected variation in either cloud base. VIRTIS observations of Venus's southern hemisphere were also obtained in September 2007 and should be able to corroborate or contradict the observed variations. This work was supported by NASA's Planetary Astronomy and Atmospheres programs.

An efficient routine for infrared radiative transfer in a cloudy atmosphere

NASA Technical Reports Server (NTRS)

Chou, M. D.; Kouvaris, L.

1981-01-01

A FORTRAN program that calculates the atmospheric cooling rate and infrared fluxes for partly cloudy atmospheres is documented. The IR fluxes in the water bands and the 9.6 and 15 micron bands are calculated at 15 levels ranging from 1.39 mb to the surface. The program is generalized to accept any arbitrary atmospheric temperature and humidity profiles and clouds as input and return the cooling rate and fluxes as output. Sample calculations for various atmospheric profiles and cloud situations are demonstrated.

An Algorithm for the Vertical Structure of Aerosol Extinction in the Lowest Kilometer of the Atmosphere: Rev. 1

DTIC Science & Technology

2017-11-01

inversion layer, or the well-mixed boundary layer. In such cases a low cloud ceiling is not present. In all instances the atmospheric extinction profiles...height, radiation fog depth, or the inversion layer height. The visibility regions and several representative vertical profiles of extinction are...the coefficient B can be found by B = ln(D/A) . (2) The coefficient B is sometimes a function of the cloud ceiling height, the inversion layer height

The abundance and distribution of water vapor in the Jovian troposphere as inferred from Voyager IRIS observations

NASA Technical Reports Server (NTRS)

Carlson, Barbara E.; Lacis, Andrew A.; Rossow, William B.

1992-01-01

The Voyager IRIS spectra of the Jovian North Equatorial Belt (NEB) hot spots are reanalyzed using a radiative transfer model which includes the full effects of anisotropic multiple scattering by clouds. The atmospheric model includes the three thermochemically predicted cloud layers, NH3, NH4SH, and H2O. Spectrally dependent cloud extinction is modeled using Mie theory and the refractive indices of NH3 ice, NH4SH ice, water, and H2O ice. The upper tropospheric temperature profile, gas abundances, height-dependent parahydrogen profile, and vertical distribution of NH3 cloud opacity are retrieved from an analysis of the far-infrared (180-1200/cm) IRIS observations. With these properties constrained, the 5-micron (1800-2300/cm) observations are analyzed to determine the atmospheric and cloud structure of the deeper atmosphere (P of greater than 1.5 bars). The results show that the abundance of water is at least 1.5 times solar with 2 times solar (0.00276 mixing ratio relative to H2) providing the best-fit to the Voyager IRIS hot spot observations.

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

NASA Astrophysics Data System (ADS)

Winker, David; Chepfer, Helene; Noel, Vincent; Cai, Xia

2017-11-01

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Extending 3D Near-Cloud Corrections from Shorter to Longer Wavelengths

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Evans, K. Frank; Varnai, Tamas; Guoyong, Wen

2014-01-01

Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

CATS Data and Information Page

Atmospheric Science Data Center

2018-02-26

... of atmospheric aerosols and clouds from the International Space Station (ISS).   CATS will provide vertical profiles at three ... (day-to-night) changes in cloud and aerosol effects from space by observing the same spot on Earth at different times each day.   ...

Satellite Analyses of Cirrus Cloud Properties During the FIRE Phase 2 Cirrus Intensive Field Observations over Kansas

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Young, David F.; Heck, Patrick W.; Liou, Kuo-Nan; Takano, Yoshihide

1992-01-01

The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances.

The July 2016 Study of the water VApour in the polar AtmosPhere (SVAAP) campaign at Thule, Greenland: surface radiation budget and role of clouds

NASA Astrophysics Data System (ADS)

Meloni, Daniela; Di Iorio, Tatiana; di Sarra, Alcide; Iaccarino, Antonio; Pace, Giandomenico; Mevi, Gabriele; Muscari, Giovanni; Cacciani, Marco; Gröbner, Julian

2017-04-01

The Study of the water VApour in the polar AtmosPhere (SVAAP) project, funded by the Italian Programme for Antarctic Research, is aimed at investigating the surface radiation budget (SRB), the variability of atmospheric water vapour, and the long-term variations in stratospheric composition and structure at Thule, Greenland, in the framework of the international Network for Detection of Atmospheric Composition Change (NDACC). Thule High Arctic Atmospheric Observatory (THAAO, 76.5° N, 68.8° W) is devoted to study climate change and has been operational since 1990, with the contribution of different international institutions: DMI, NCAR, ENEA, INGV, Universities of Roma and Firenze (http://www.thuleatmos-it.it). As part of SVAAP an intensive field campaign was held at Thule from 5 to 28 July 2016. The campaign was also aimed at supporting the installation of VESPA-22, a new microwave radiometer for water vapour profiling in the upper atmosphere and integrated water vapour (IWV), and offered the possibility to study the cloud physical and optical properties and their impact on the SRB. Measurements of downward shortwave (SW) and longwave (LW) irradiance were already available since 2009. Additional observations were added to obtain the SRB and to characterize the atmospheric state: upward SW and LW irradiance, upwelling and downwelling photosynthetically active radiation (PAR), downward irradiance in the 8-14 µm infrared window, temperature and relative humidity tropospheric profiles, IWV, liquid water path (LWP), lidar tropospheric backscattering profiles, sky brightness temperature (BT) in the 9.6-11.5 µm spectral range, visible and infrared sky images, surface meteorological parameters. Moreover, 23 radiosonde were launched during the campaign. Data from the period 14-28 July are presented in this study. The first part of the campaign was characterized by stable cloud-free conditions, while alternation of cloudy and cloud-free sky occurred after 18 July. The time evolution of SW and LW SRB, surface albedo, and derived cloud parameters, such as cloud optical thickness and effective radius, are presented and discussed. Thickest clouds reached visible optical depths of about 200, and values of LWP of about 0.4 kg/m2. While the SW SRB is always positive during the measurement campaign, the LW SRB is negative under cloud-free conditions (own to -100 W/m2 at noon), becoming positive (up to +50 W/m2) during cloudy periods. The total (SW+LW) SRB is positive and its variability is dominated by the SW irradiance. Clouds induce a reduction of the SRB compared to the cloud-free periods, thanks to the dominant SW effect. The LW component offsets about 20% of the SW at noon in clear sky, and contributes up to 50% of the total SRB in thick cloud conditions. The availability of the cloud physical and optical properties and the atmospheric vertical profiles allow to study in details the SW and LW cloud radiative effect by means of radiative transfer simulations performed with MODTRAN6.0 model.

The Effect of Cumulus Cloud Field Anisotropy on Domain-Averaged Solar Fluxes and Atmospheric Heating Rates

NASA Technical Reports Server (NTRS)

Hinkelman, Laura M.; Evans, K. Franklin; Clothiaux, Eugene E.; Ackerman, Thomas P.; Stackhouse, Paul W., Jr.

2006-01-01

Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce twenty three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-average transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction, i.e., the cloud fraction when the field is projected on a surface perpendicular to the direction of the incident solar beam.

Processes that generate and deplete liquid water and snow in thin midlevel mixed-phase clouds

NASA Astrophysics Data System (ADS)

Smith, Adam J.; Larson, Vincent E.; Niu, Jianguo; Kankiewicz, J. Adam; Carey, Lawrence D.

2009-06-01

This paper uses a numerical model to investigate microphysical, radiative, and dynamical processes in mixed-phase altostratocumulus clouds. Three cloud cases are chosen for study, each of which was observed by aircraft during the fifth or ninth Complex Layered Cloud Experiment (CLEX). These three clouds are numerically modeled using large-eddy simulation (LES). The observed and modeled clouds consist of a mixed-phase layer with a quasi-adiabatic profile of liquid, and a virga layer below that consists of snow. A budget of cloud (liquid) water mixing ratio is constructed from the simulations. It shows that large-scale ascent/descent, radiative cooling/heating, turbulent transport, and microphysical processes are all significant. Liquid is depleted indirectly via depositional growth of snow (the Bergeron-Findeisen process). This process is more influential than depletion of liquid via accretional growth of snow. Also constructed is a budget of snow mixing ratio, which turns out to be somewhat simpler. It shows that snow grows by deposition in and below the liquid (mixed-phase) layer, and sublimates in the remainder of the virga region below. The deposition and sublimation are balanced primarily by sedimentation, which transports the snow from the growth region to the sublimation region below. In our three clouds, the vertical extent of the virga layer is influenced more by the profile of saturation ratio below the liquid (mixed-phase) layer than by the mixing ratio of snow at the top of the virga layer.

The relationship between interannual and long-term cloud feedbacks

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.; ...

2015-12-11

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« less

On the dominant impact of vertical moisture gradient on mesoscale cloud cellular organization of stratocumulus

NASA Astrophysics Data System (ADS)

Zhou, X.; Ackerman, A. S.; Fridlind, A. M.; Kollias, P.

2016-12-01

Large-eddy simulations are performed to study the mechanisms of stratocumulus organization. Precipitation tends to increase horizontal cloud scales, but is not required for cloud mesoscale organization. A study of the terms in the prognostic equation for total water mixing ratio variance shows the critical impact of vertical moisture gradient on cloud scale. For precipitating clouds, the organization originates from the negative moisture gradient in the boundary layer resulting from evaporation of precipitation. This hypothesis is supported by simulations in which thermodynamics profiles are nudged to their initial well-mixed state, which reduces cloud scales. Cold pools effect are surprisingly found to respond to rather than determine the cloud mesoscale variability. For non-precipitating clouds, organization results from turbulent transport of moisture variance originating primarily from cloud top, where dry air is entrained into the boundary layer through convection driven by cloud top longwave (LW) cooling. Both LW cooling and a moisture gradient above cloud top are essential for the growth of mesoscale fluctuations.

Atmospheric Soundings from AIRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert

2004-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correlation coefficients and the prediction of location and intensity of cyclones.

Current results from AlRS/AMSU/HSB

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert; Barnet, Christopher; Blaisdell, Jon; Iredell, Lena; Bri, Genia; Jusem, Juan Carlos; Keita, Fricky; Kouvaris, Louis; Molnar, Gyula

2004-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correction coefficients and the prediction of location and intensity of cyclones.

SeReNA Project: studying aerosol interactions with cloud microphysics in the Amazon Basin

NASA Astrophysics Data System (ADS)

Correia, A. L.; Catandi, P. B.; Frigeri, F. F.; Ferreira, W. C.; Martins, J.; Artaxo, P.

2012-12-01

Cloud microphysics and its interaction with aerosols is a key atmospheric process for weather and climate. Interactions between clouds and aerosols can impact Earth's radiative balance, its hydrological and energetic cycles, and are responsible for a large fraction of the uncertainty in climatic models. On a planetary scale, the Amazon Basin is one of the most significant land sources of moisture and latent heat energy. Moreover, every year this region undergoes mearked seasonal shifts in its atmospheric state, transitioning from clean to heavily polluted conditions due to the occurrence of seasonal biomass burning fires, that emit large amounts of smoke to the atmosphere. These conditions make the Amazon Basin a special place to study aerosol-cloud interactions. The SeReNA Project ("Remote sensing of clouds and their interaction with aerosols", from the acronym in Portuguese, @SerenaProject on Twitter) is an ongoing effort to experimentally investigate the impact of aerosols upon cloud microphysics in Amazonia. Vertical profiles of droplet effective radius of water and ice particles, in single convective clouds, can be derived from measurements of the emerging radiation on cloud sides. Aerosol optical depth, cloud top properties, and meteorological parameters retrieved from satellites will be correlated with microphysical properties derived for single clouds. Maps of cloud brightness temperature will allow building temperature vs. effective radius profiles for hydrometeors in single clouds. Figure 1 shows an example extracted from Martins et al. (2011), illustrating a proof-of-concept for the kind of result expected within the framework for the SeReNA Project. The results to be obtained will help foster the quantitative knowledge about interactions between aerosols and clouds in a microphysical level. These interactions are a fundamental process in the context of global climatic changes, they are key to understanding basic processes within clouds and how aerosols can influence them. Reference: Martins et al. (2011) ACP, v.11, p.9485-9501. Available at: http://bit.ly/martinspaper Figure 1. Brightness temperature (left panel) and thermodynamic phase (right) of hydrometeors in the convective cloud shown in the middle panel. Extracted from Martins et al. (2011).

First X-ray Statistical Tests for Clumpy-Torus Models: Constraints from RXTEmonitoring of Seyfert AGN

NASA Astrophysics Data System (ADS)

Markowitz, Alex; Krumpe, Mirko; Nikutta, R.

2016-06-01

In two papers (Markowitz, Krumpe, & Nikutta 2014, and Nikutta et al., in prep.), we derive the first X-ray statistical constraints for clumpy-torus models in Seyfert AGN by quantifying multi-timescale variability in line of-sight X-ray absorbing gas as a function of optical classification.We systematically search for discrete absorption events in the vast archive of RXTE monitoring of 55 nearby type Is and Compton-thin type IIs. We are sensitive to discrete absorption events due to clouds of full-covering, neutral/mildly ionized gas transiting the line of sight. Our results apply to both dusty and non-dusty clumpy media, and probe model parameter space complementary to that for eclipses observed with XMM-Newton, Suzaku, and Chandra.We detect twelve eclipse events in eight Seyferts, roughly tripling the number previously published from this archive. Event durations span hours to years. Most of our detected clouds are Compton-thin, and most clouds' distances from the black hole are inferred to be commensurate with the outer portions of the BLR or the inner regions of infrared-emitting dusty tori.We present the density profiles of the highest-quality eclipse events; the column density profile for an eclipsing cloud in NGC 3783 is doubly spiked, possibly indicating a cloud that is being tidallysheared. We discuss implications for cloud distributions in the context of clumpy-torus models. We calculate eclipse probabilities for orientation-dependent Type I/II unification schemes.We present constraints on cloud sizes, stability, and radial distribution. We infer that clouds' small angular sizes as seen from the SMBH imply 107 clouds required across the BLR + torus. Cloud size is roughly proportional to distance from the black hole, hinting at the formation processes (e.g., disk fragmentation). All observed clouds are sub-critical with respect to tidal disruption; self-gravity alone cannot contain them. External forces, such as magnetic fields or ambient pressure, are needed to contain them; otherwise, clouds must be short-lived.

Role of mixed precipitating cloud systems on the typhoon rainfall

NASA Astrophysics Data System (ADS)

Pan, C. J.; Krishna Reddy, K.; Lai, H. C.; Yang, S. S.

2010-01-01

L-band wind profiler data are utilized to diagnose the vertical structure of the typhoon precipitating cloud systems in Taiwan. For several typhoons, a pronounced bright band (BB) around 5 km is commonly observed from the observation. Since strong convection within typhoon circulation may disturb and/or disrupt the melting layer, the BB shall not appear persistently. Hence, an understanding of the vertical structure of the BB region is important because it holds extensive hydrometeors information on the type of precipitation and its variability. Wind profiler observational results suggest that the mixture of convective and stratiform (embedded type) clouds are mostly associated with typhoons. In the case of one typhoon, BB is appeared around 5.5 km with embedded precipitation and also BB height of 1 km higher than ordinary showery precipitation. This is evident from the long-term observations of wind profiler and Tropical Rainfall Measuring Mission. The Doppler velocity profiles show hydrometers (ice/snow) at 6 km but liquid below 5 km for typhoons and 4 km for showery precipitation. In the BB region the melting particles accelerations of 5.8 ms-1 km-1 and 3.2 ms-1 km-1 are observed for typhoon and showery precipitation, respectively.

Shapes of star-gas waves in spiral galaxies

NASA Technical Reports Server (NTRS)

Lubow, Stephen H.

1988-01-01

Density-wave profile shapes are influenced by several effects. By solving viscous fluid equations, the nonlinear effects of the gas and its gravitational interaction with the stars can be analyzed. The stars are treated through a linear theory developed by Lin and coworkers. Short wavelength gravitational forces are important in determining the gas density profile shape. With the inclusion of disk finite thickness effects, the gas gravitational field remains important, but is significantly reduced at short wavelengths. Softening of the gas equation of state results in an enhanced response and a smoothing of the gas density profile. A Newtonian stress relation is marginally acceptable for HI gas clouds, but not acceptable for giant molecular clouds.

Constraints from Airborne (210)Pb Observations on Aerosol Scavenging and Lifetime in a Global Chemical Transport Model

NASA Technical Reports Server (NTRS)

Zhang, Bo; Liu, Hongyu; Crawford, James H.; Fairlie, Duncan T.; Chen, Gao; Dibb, Jack E.; Shah, Viral; Sulprizio, Melissa P.; Yantosca, Robert M.

2016-01-01

Lead-210 distribution and lifetime in the atmosphere are not sensitive to ice in-cloud scavenging in convective updraft. Ice in-cloud scavenging in stratiform clouds reduce tropospheric (210)Pb lifetime by approximately 1 day and results in better agreements with observed surface observations and aircraft measured profiles. However, the process results in significant underestimate of (210)Pb in UT/LS.

Improved simulation of aerosol, cloud, and density measurements by shuttle lidar

NASA Technical Reports Server (NTRS)

Russell, P. B.; Morley, B. M.; Livingston, J. M.; Grams, G. W.; Patterson, E. W.

1981-01-01

Data retrievals are simulated for a Nd:YAG lidar suitable for early flight on the space shuttle. Maximum assumed vertical and horizontal resolutions are 0.1 and 100 km, respectively, in the boundary layer, increasing to 2 and 2000 km in the mesosphere. Aerosol and cloud retrievals are simulated using 1.06 and 0.53 microns wavelengths independently. Error sources include signal measurement, conventional density information, atmospheric transmission, and lidar calibration. By day, tenuous clouds and Saharan and boundary layer aerosols are retrieved at both wavelengths. By night, these constituents are retrieved, plus upper tropospheric, stratospheric, and mesospheric aerosols and noctilucent clouds. Density, temperature, and improved aerosol and cloud retrievals are simulated by combining signals at 0.35, 1.06, and 0.53 microns. Particlate contamination limits the technique to the cloud free upper troposphere and above. Error bars automatically show effect of this contamination, as well as errors in absolute density nonmalization, reference temperature or pressure, and the sources listed above. For nonvolcanic conditions, relative density profiles have rms errors of 0.54 to 2% in the upper troposphere and stratosphere. Temperature profiles have rms errors of 1.2 to 2.5 K and can define the tropopause to 0.5 km and higher wave structures to 1 or 2 km.