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NASA NTRS2023

An ALMA Glimpse of Dense Molecular Filaments Associated with High-mass Protostellar Systems in the Large Magellanic Cloud

Recent millimeter/submillimeter facilities have revealed the physical properties of filamentary molecular clouds in relation to high-mass star formation. A uniform survey of the nearest, face-on star-forming galaxy, the Large Magellanic Cloud (LMC), complements the Galactic knowledge. We present ALMA survey data with a spatial resolution of ∼0.1 pc in the 0.87 mm continuum and HCO+ (4–3) emission toward 30 protostellar objects with luminosities of 104–105.5L⊙ in the LMC. The spatial distributions of the HCO+ (4–3) line and thermal dust emission are well correlated, indicating that the line effectively traces dense, filamentary gas with an H2 volume density of ≳105 cm−3 and a line mass of ∼103–104M⊙ pc−1. Furthermore, we obtain an increase in the velocity line widths of filamentary clouds, which follows a power-law dependence on their H2 column densities with an exponent of ∼0.5. This trend is consistent with observations toward filamentary clouds in nearby star-forming regions within ≲1 kpc from us and suggests enhanced internal turbulence within the filaments due to surrounding gas accretion. Among the 30 sources, we find that 14 are associated with hub-filamentary structures, and these complex structures predominantly appear in protostellar luminosities exceeding ∼5 × 104L⊙. The hub-filament systems tend to appear in the latest stages of their natal cloud evolution, often linked to prominent H II regions and numerous stellar clusters. Our preliminary statistics suggest that the massive filaments accompanied by hub-type complex features may be a necessary intermediate product in forming extremely luminous high-mass stellar systems capable of ultimately dispersing the parent cloud.

Marta M Sewilo↗

NASA NTRS1999

CERES: The Next Generation of Earth Radiation Budget Measurements

NASA's Earth Observing System (EOS) is part of an international program for studying the Earth from space using a multiple-instrument, multiple-satellite approach. The Clouds and the Earth's Radiant Energy System (CERES) experiment is designed to monitor changes in the Earth s radiant energy system and cloud systems and to provide these data with sufficient simultaneity and accuracy to examine critical cloud/climate feedback mechanisms which may play a major role in determining future changes in the climate system. The first EOS satellite (Terra), scheduled for launch this year, and the EOS-PM satellite, to be launched in late 2000, will each carry two CERES instruments. The first CERES instrument was launched in 1997 on the Tropical Rainfall Measuring Mission (TRMM) satellite. The CERES TRMM data show excellent instrument stability and a factor of 2 to 3 less error than previous Earth radiation budget missions. The first CERES data products have been validated and archived. The data consist of instantaneous longwave and shortwave broadband radiances, top-of-atmosphere fluxes, scene types, and time and space averaged fluxes and albedo. A later data product will combine CERES radiances and high- resolution imager data to produce cloud properties and fluxes throughout the atmosphere and at the surface.

Gibson, Gary G.↗

DOE OSTI2022

Polar Cloud Microphysics and Surface Energy Budget from AWARE (Final Technical Report)

This was a collaborative project between the Scripps Institution of Oceanography at the University of California San Diego (SIO), Byrd Polar and Climate Research Center at The Ohio State University (BPCRC), The Department of Meteorology and Atmospheric Science at The Pennsylvania State University (Penn State), and Brookhaven National Laboratory (BNL). The project’s over-arching objectives involved maximizing the scientific potential of the ARM West Antarctic Radiation Experiment (AWARE) data set, in two respects: (1) application of polar-optimized climate models to test the most current and comprehensive cloud microphysical parameterizations; and (2) analysis of the most advanced ARM Mobile Facility sensors (e.g., cloud radar, spectroradiometer, and aerosol observing system data) to advance understanding of Antarctic cloud microphysical and radiative properties, particularly on a climatological basis with emphasis on contrasts with the high Arctic. The team’s efforts have resulted in 16 peer-review publications, in addition to an overview of the AWARE campaign in the Bulletin of the American Meteorological Society. Our emphasis throughout this program was to go beyond the traditional “case study” approach to model evaluation, in which a “classical” or otherwise well-characterized surface-atmosphere-cloud system of short duration is simulated by several climate models. Instead, we attempted analysis of longer time series in the AWARE data, both climatologically and with models. We have numerous successful results from both AWARE locations: The main AMF-2 deployment at McMurdo Station on Ross Island (13 months duration), and the extended facility at the West Antarctic Ice Sheet (WAIS) Divide Ice Camp (40 days during austral summer 2015-16).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1986

Inversion of 2 wavelength Lidar data for cloud properties

The inversion of the lidar equation to derive quantitative properties of the atmosphere has continued to present considerable difficulty. The results of a study in which Klett's procedure was utilized for the analysis of cloud backscatter measurements made simulataneously at two ruby lidar wavelengths (694nm,347nmm) are presented. With one lidar system a cloud is probed at the two wavelength and the backscatter measured simulataneously by separate receivers. As a result two sigma profiles which should differ only because the wavlength dependence of the scattering. Experimental data presented to demonstrate the effects and the implications of the applications of the inversion method will be discussed.

Pal, S. R.↗

NASA NTRSDate not supplied

NASA's Implementation of Cloud Services for Human Space Flight

Cloud is a tried-and-true technology used throughout United States government agencies, including the National Aeronautics and Space Administration (NASA). With reliable results and infrequent downtimes, cloud allows for secure remote access, customizability, and streamlined monitoring options, creating an environment for better data integrity and availability. As NASA increasingly migrates functions to the cloud, the Space Communications and Navigation Program (SCaN) program has been investigating how this capability can be leveraged to provide communication services to its users and customers. Currently, missions such as NASA-ISRO Synthetic Aperture Radar (NISAR), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and Roman Space Telescope (RST) are planned to incorporate cloud into their data delivery architecture. However, SCaN is looking to expand further. This conversion to using cloud services allows for greater availability of mission data for both robotic and human space flight (HSF)missions. The SCaN program and the Near Space Network (NSN) are working to consolidate resources and create a cloud environment suitable for the entirety of the SCaN program network architecture. SCaN is in the process of finalizing its cloud architecture and soon will be implementing cloud services. The new services used will adhere to federal regulations including Federal Risk and Authorization Management Program (FedRAMP), which is built upon National Institute of Standards and Technology (NIST)documentation. While keeping in mind these security requirements, an auxiliary objective of the cloud integration is to ensure the most cost-efficient solution; providing a scalable, robust and resilient system. Using cloud services, NASA will gain access to better centralized monitoring and management features, along with customizable services on a pay-per-use plan. With the ever-growing NASA mission data volume needs, maintaining ample storage space is another major constraint. Processing and storing such large amounts of data, on the order of terabytes a day, requires dynamic processing capability which is inherently a strength of cloud computing. By routing this data from ground stations through the cloud, there will be greater ease of access for both SCaN and the user community. Artificial intelligence and other built-in cloud functions can also enhance efficiency, improving data processing time. Thereby also allowing for better data availability. As we look to the future of cloud services, NASA will continue to leverage capabilities that will benefit NASA’s ability to provide cost-effective communication services. This paper further outlines the evolution of cloud use by SCaN in the context of Human Space Flight.

cloud storage↗

NASA NTRS2003

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite: Methodology - Part 1

Clouds and the Earth s Radiant Energy System (CERES) investigates the critical role that clouds and aerosols play in modulating the radiative energy flow within the Earth-atmosphere system. CERES builds upon the foundation laid by previous missions, such as the Earth Radiation Budget Experiment, to provide highly accurate top-of-atmosphere (TOA) radiative fluxes together with coincident cloud and aerosol properties inferred from high-resolution imager measurements. This paper describes the method used to construct empirical angular distribution models (ADMs) for estimating shortwave, longwave, and window TOA radiative fluxes from CERES radiance measurements on board the Tropical Rainfall Measuring Mission satellite. To construct the ADMs, multiangle CERES measurements are combined with coincident high-resolution Visible Infrared Scanner measurements and meteorological parameters from the European Centre for Medium-Range Weather Forecasts data assimilation product. The ADMs are stratified by scene types defined by parameters that have a strong influence on the angular dependence of Earth's radiation field at the TOA. Examples of how the new CERES ADMs depend upon the imager-based parameters are provided together with comparisons with existing models.

Loeb, N. G.↗

NASA NTRS2004

Objective Lightning Forecasting at Kennedy Space Center/Cape Canaveral Air Force Station using Cloud-to-Ground Lightning Surveillance System Data

The 45th Weather Squadron (45 WS) forecasters at Cape Canaveral Air Force Station (CCAFS) in Florida include a probability of thunderstorm occurrence in their daily morning briefings. This information is used by personnel involved in determining the possibility of violating Launch Commit Criteria, evaluating Flight Rules for the Space Shuttle, and daily planning for ground operation activities on Kennedy Space Center (KSC)/CCAFS. Much of the current lightning probability forecast is based on a subjective analysis of model and observational data. The forecasters requested that a lightning probability forecast tool based on statistical analysis of historical warm-season (May - September) data be developed in order to increase the objectivity of the daily thunderstorm probability forecast. The tool is a set of statistical lightning forecast equations that provide a lightning occurrence probability for the day by 1100 UTC (0700 EDT) during the warm season. This study used 15 years (1989-2003) of warm season data to develop the objective forecast equations. The local CCAFS 1000 UTC sounding was used to calculate stability parameters for equation predictors. The Cloud-to-Ground Lightning Surveillance System (CGLSS) data were used to determine lightning occurrence for each day. The CGLSS data have been found to be more reliable indicators of lightning in the area than surface observations through local informal analyses. This work was based on the results from two earlier research projects. Everitt (1999) used surface observations and rawinsonde data to develop logistic regression equations that forecast the daily thunderstorm probability at CCAFS. The Everitt (1999) equations showed an improvement in skill over the Neumann-Pfeffer thunderstorm index (Neumann 1971), which uses multiple linear regression, and also persistence and climatology forecasts. Lericos et al. (2002) developed lightning distributions over the Florida peninsula based on specific flow regimes. The flow regimes were inferred from the average wind direction in the 1000-700 mb layer at Miami (MIA), Tampa (TBW), and Jacksonville (JAX), Florida, and the lightning data were from the National Lightning Detection Network. The results suggested that the daily flow regime may be an important predictor of lightning occurrence on KSC/CCAFS.

Lambert, Winifred↗

NASA NTRS1982

Cloud cover from high-resolution scanner data - Detecting and allowing for partially filled fields of view

A new technique is presented for obtaining cloud cover and determining clear sky radiances using high-resolution IR scanner data. The technique, which can be automated, employs the spatial structure of the IR radiance field to identify radiances associated with fields of view that are either free of clouds or completely covered by clouds drawn from one or more distinct layers. The approach is particularly well-suited for determining clear sky radiances over oceans from which sea surface temperatures may be derived. In addition, for single-layered systems, the cloud cover fraction for a given region may be obtained from the clear sky radiance, the completely cloud-covered radiance, and the mean radiance for the region. For such systems the separation of completely covered from partially covered fields of view makes it possible to estimate the errors associated with commonly used threshold techniques for determining cloud cover.

Coakley, J. A., Jr.↗

NASA NTRS2007

Comparison of the KSC-ER Cloud-to-Ground Lightning Surveillance System (CGLSS) and the U.S. National Lightning Detection Network(TradeMark)(NLDN)

The NASA Kennedy Space Center (KSC) and Air Force Eastern Range (ER) use data from two cloud-to-ground lightning detection networks, CGLSS and NLDN, during ground and launch operations at the KSC-ER. For these applications, it is very important to understand the location accuracy and detection efficiency of each network near the KSC-ER. If a cloud-to-ground (CG) lightning strike is missed or mis-located by even a small amount, the result could have significant safety implications, require expensive retests, or create unnecessary delays or scrubs in launches. Therefore, it is important to understand the performance of each lightning detection system in considerable detail. To evaluate recent upgrades in the CGLSS sensors in 2000 and the entire NLDN in 2002- 2003, we have compared. measurements provided by these independent networks in the summers of 2005 and 2006. Our analyses have focused on the fraction of first strokes reported individually and in-common by each network (flash detection efficiency), the spatial separation between the strike points reported by both networks (relative location accuracy), and the values of the estimated peak current, Ip, reported by each network. The results within 100 km of the KSC-ER show that the networks produce very similar values of Ip (except for a small scaling difference) and that the relative location accuracy is consistent with model estimates that give median values of 200-300m for the CGLSS and 600-700m for the NLDN in the region of the KSC-ER. Because of differences in the network geometries and sensor gains, the NLDN does not report 10-20% of the flashes that have a low Ip (2 kA < |Ip| < 16 kA), both networks report 99 % of the flashes that have intermediate values of Ip (16< |Ip| < 50 kA), and the CGLSS fails to report 20-30% of the high-current events (|Ip| >=0 kA).

Ward, Jennifer G.↗

NASA NTRS2000

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

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).

Wang, J. R.↗

NASA NTRS1991

An interactive system for analysis of global cloud imagery

Synoptic images of the global cloud pattern composited from six contemporaneous satellites provide an unprecedented view of the global cloud field. Having horizontal resolution of about 0.5 deg and temporal resolution of 3 h, the global cloud imagery (GCI) resolves most of the variability of organized convection, including several harmonics of the diurnal cycle. Although the GCI has these attractive features, the dense and 3D nature of that data make it a formidable volume of information to treat in a practical and efficient manner. An interactive image-analysis system (IAS) has been developed to investigate the space-time variability of global cloud behavior. In the IAS, data, hardware, and software are integrated into a single system providing a variety of space-time covariance analyses in a menu-driven format. Owing to its customized architecture and certain homogeneous properties of the GCI, the IAS calculates such quantities effectively. Many covariance statistics are derived from 3D data with interactive speed, allowing the user to interrogate the archive iteratively in a single session. The 3D nature of those analyses and the speed with which they are performed distinguish the IAS from conventional image processing of 2D data.

Woodberry, Karen↗

NASA NTRS2018

Compact Mid-Wave Imaging System (CMIS) for Retrieval of Cloud Motion Vectors and Cloud Geometric Heights

The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is developing a compact, light-weight, and low power midwave-infrared (MWIR) imager called the Compact Midwave Imaging Sensor (CMIS), under the support of the NASA Earth Science Technology Office Instrument Incubator Program. The goal of this CMIS instrument development and demonstration project is to increase the technical readiness of CMIS, a multi-spectral sensor capable of retrieving 3D winds and cloud heights 24/7, for a space mission. The CMIS instrument employs an advanced MWIR detector that requires less cooling than traditional technologies and thus permits a compact, low-power design, which enables accommodation on small spacecraft such as CubeSats. CMIS provides the critical midwave component of a multi-spectral sensor suite that includes a high-resolution Day-Night Band and a longwave infrared (LWIR) imager to provide global cloud characterization and theater weather imagery. In this presentation, an overview of the CMIS project, including the high-level sensor design, the concept of operations, and measurement capability will be presented. System performance for a variety of different scenes generated by a cloud resolving model (CRM) will also be discussed.

midwave↗

NASA NTRS1985

Remote sensing of atmospheric and surface parameters from HIRS2/MSU on TIROS-N

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system was developed, involving the simultaneous analysis of sounding data, for determining atmospheric and surface conditions that are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of clouds, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, cloud amounts, cloudtop heights and temperatures, and albedo. The characteristics of the atmospheric and surface parameters derived from the GLAS Physical Retrieval System are reviewed, results for the FGGE year are presented and, whenever possible, compared with other measurements of the same fields. Some of the model-derived diagnostic fields available from the GLAS Analysis/Forecast System are also discussed. These fields may lead to more accurate determination of the source terms of the atmospheric heat and moisture budgets.

Susskind, J.↗

DOE OSTI2021

The response of the Amazon ecosystem to the photosynthetically active radiation fields: integrating impacts of biomass burning aerosol and clouds in the NASA GEOS Earth system model

The Amazon experiences fires every year, and the resulting biomass burning aerosols, together with cloud particles, influence the penetration of sunlight through the atmosphere, increasing the ratio of diffuse to direct photosynthetically active radiation (PAR) reaching the vegetation canopy and thereby potentially increasing ecosystem productivity. In this study, we use the NASA Goddard Earth Observing System (GEOS) model with coupled aerosol, cloud, radiation, and ecosystem modules to investigate the impact of Amazon biomass burning aerosols on ecosystem productivity, as well as the role of the Amazon's clouds in tempering this impact. The study focuses on a 7-year period (2010–2016) during which the Amazon experienced a variety of dynamic environments (e.g., La Niña, normal years, and El Niño). The direct radiative impact of biomass burning aerosols on ecosystem productivity – called here the aerosol diffuse radiation fertilization effect – is found to increase Amazonian gross primary production (GPP) by 2.6 % via a 3.8 % increase in diffuse PAR (DFPAR) despite a 5.4 % decrease in direct PAR (DRPAR) on multiyear average during burning seasons. On a monthly basis, this increase in GPP can be as large as 9.9 % (occurring in August 2010). Consequently, the net primary production (NPP) in the Amazon is increased by 1.5 %, or ~92 Tg C yr -1 – equivalent to ~37 % of the average carbon lost due to Amazon fires over the 7 years considered. Clouds, however, strongly regulate the effectiveness of the aerosol diffuse radiation fertilization effect. The efficiency of this fertilization effect is the highest in cloud-free conditions and linearly decreases with increasing cloud amount until the cloud fraction reaches ~0.8, at which point the aerosol-influenced light changes from being a stimulator to an inhibitor of plant growth. Nevertheless, interannual changes in the overall strength of the aerosol diffuse radiation fertilization effect are primarily controlled by the large interannual changes in biomass burning aerosols rather than by changes in cloudiness during the studied period.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

The Response of the Amazon Ecosystem to the Photosynthetically Active Radiation Fields: Integrating Impacts of Biomass Burning Aerosol and Clouds in the NASA GEOS Earth System Model

The Amazon experiences fires every year, and the resulting biomass burning aerosols, together with cloud particles, influence the penetration of sunlight through the atmosphere, increasing the ratio of diffuse to direct photosynthetically active radiation (PAR) reaching the vegetation canopy and thereby potentially increasing ecosystem productivity. In this study, we use the NASA Goddard Earth Observing System (GEOS) model with coupled aerosol, cloud, radiation, and ecosystem modules to investigate the impact of Amazon biomass burning aerosols on ecosystem productivity, as well as the role of the Amazon’s clouds in tempering this impact. The study focuses on a seven-year period (2010-2016) during which the Amazon experienced a variety of dynamic environments (e.g., La Niña, normal years, and El Niño). The direct radiative impact of biomass burning aerosols on ecosystem productivity—called here the aerosol diffuse radiation fertilization effect —is found to increase Amazonian Gross Primary Production (GPP) by 2.6% via a 3.8% increase in diffuse PAR (DFPAR) despite a 5.4% decrease in direct PAR (DRPAR) on multiyear average during burning seasons. On a monthly basis, this increase in GPP can be as large as 9.9% (occurring in August 2010). Consequently, the net primary production (NPP) in Amazon is increased by 1.5%, or ~92 Tg C a-1– equivalent to ~37% of the average carbon lost due to Amazon fires over the seven years considered. Clouds, however, strongly regulate the effectiveness of the aerosol diffuse radiation fertilization effect. The efficiency of this fertilization effect is the highest in cloud-free conditions and linearly decreases with increasing cloud amount until the cloud fraction reaches ~0.8, at which point the aerosol-influenced light changes from being a stimulator to an inhibitor of plant growth. Nevertheless, interannual changes in the overall strength of the aerosol diffuse radiation fertilization effect are primarily controlled by the large interannual changes in biomass burning aerosols rather than by changes in cloudiness during the studied period.

biomass burning aerosols on ecosystem productivity↗

NASA NTRS2012

A Statistics-Based Material Property Analysis to Support TPS Characterization

Accurate characterization of entry capsule heat shield material properties is a critical component in modeling and simulating Thermal Protection System (TPS) response in a prescribed aerothermal environment. The thermal decomposition of the TPS material during the pyrolysis and charring processes is poorly characterized and typically results in large uncertainties in material properties as inputs for ablation models. These material property uncertainties contribute to large design margins on flight systems and cloud re- construction efforts for data collected during flight and ground testing, making revision to existing models for entry systems more challenging. The analysis presented in this work quantifies how material property uncertainties propagate through an ablation model and guides an experimental test regimen aimed at reducing these uncertainties and characterizing the dependencies between properties in the virgin and charred states for a Phenolic Impregnated Carbon Ablator (PICA) based TPS. A sensitivity analysis identifies how the high-fidelity model behaves in the expected flight environment, while a Monte Carlo based uncertainty propagation strategy is used to quantify the expected spread in the in-depth temperature response of the TPS. An examination of how perturbations to the input probability density functions affect output temperature statistics is accomplished using a Kriging response surface of the high-fidelity model. Simulations are based on capsule configuration and aerothermal environments expected during the Mars Science Laboratory (MSL) entry sequence. We identify and rank primary sources of uncertainty from material properties in a flight-relevant environment, show the dependence on spatial orientation and in-depth location on those uncertainty contributors, and quantify how sensitive the expected results are.

Copeland, Sean R.↗

NASA NTRS2015

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Kato, Seiji↗

NASA NTRSDate not supplied

Evaluating Subgrid-Scale Properties of Low Clouds over the Beaufort Sea in Arctic System Reanalysis using ARISE Airborne In Situ Observations

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. To better understand the magnitude and possible causes of this problem, we analyze the disagreements between the Arctic System Reanalysis version 2 (ASR) and data taken during the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign conducted over the Beaufort Sea. Previous analysis of grid scale-averaged meteorological variables revealed a lack of cloud water produced in ASR, related to warm/dry biases, a failure to produce sufficient cloud water in conditions that are observed to be favorable for large cloud water values, and sampling issues with the ARISE flight paths. However, ARISE collected meteorological observations at one second intervals, offering spatial data resolution comparable to the subgrid scale of ASR. Subgrid scale properties and processes must be parameterized in conventional atmospheric models and reanalyses such as ASR, and often rely on assumed distributions of meteorological variables about the grid box mean state. To enable an examination of the realism of ASR’s subgrid scale properties, we use high resolution data from ARISE determine the “subgrid scale” distributions of cloud water and thermodynamic variables in the real atmosphere. Preliminary results show that the subgrid scale distribution of thermodynamic variables about the grid scale mean resembles the triangular distribution assumed in many bulk microphysical parameterization schemes, but also with tails resembling Gaussian distributions. The main goal is to understand the partitioning of the total available atmospheric water into water vapor and cloud water. Models typically covert some percentage of total water in a grid box to cloud water based on the estimated amount of supersaturation from the assumed vapor distribution. The ARISE measurements can reveal the relationship between subgrid scale supersaturation and the partition between cloud water and water vapor.

Jason Brant Dodson↗