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NASA NTRSDate not supplied

A Newly Developing Community-Oriented Data System from NASA GES DISC

Data services are essential to facilitate data access and to aid efficiency of conducting research and application activities. With emerging technologies such as cloud computing and AI/ML (Artificial Intelligence/Machine Learning) leading the pace of the data world, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), home to the permanent archive for multidisciplinary Earth Observation (EO) geospatial data to study atmospheric composition, weather and climate variability, and water and energy cycles is no exception.Interfacing directly with users as part of data center work, we understand the challenges for the required time and effort to discover, visualize, and analyze large varieties and quantities of Earth Observation information for research, monitoring, and decision-making, largely due to the existing data and information systems aim to support experienced users, but has been proved difficult for non-earth scientists and new users that are unfamiliar with the variety of formats and structures in which data, metadata, and information are stored, as well as the required methods to use them. To address these challenges, I will update our latest activities with regard to water-and energy-related products and community-oriented and user-friendly services at the GES DISC, including our plans for the emerging technologies.

Jennifer Wei↗
NASA NTRS2002

The International Intercomparison of 3-Dimensional Radiation Codes

I3RC (International Intercomparison of 3-dimensional Radiation Codes) has as its primary goal to compare a wide variety of three-dimensional (3D) radiative transfer methods applied to Earth's atmosphere, with a few selected cloud fields as input, and a few selected radiative quantities as output. Phases 1 and 2 are now complete, and participants represented institutions in Canada, France, Germany, Russia, the United Kingdom, and the USA, who met for two workshops in Tucson, Arizona USA, and compared results from 5 cloud fields of varying complexity, beginning with simplified atmosphere and surface, and proceeding to more realistic cases. Phase 3 is now underway, focusing on improvement and sharing of 3D radiation code, aided by working groups on "Approximations" and "Open Source". The "Approximations" group has so far focused on diffusive approximate methods in an attempt to gain advantages in execution time, and also to advance the understanding of 3D radiation processes. The "Open Source" subgroup is developing a Monte Carlo radiative transfer toolkit that makes state-of-the-art techniques available to a wide range of users. Activities of both subgroups are further explained at the I3RC website http://i3rc.gsfc.nasa.gov. Participants in 13RC are forming a 3D Working Group under the auspices of the International Radiation Commission, and will meet for this and related activities at a workshop in Tucson in November 2002.

Cahalan, R. F.↗
NASA NTRS1994

Observations of lower-stratospheric ClONO2, HNO3, and aerosol by the UARS CLAES experiment between January 1992 and April 1993

This paper discusses simultaneous measurements of stratospheric ClONO2, HNO3, temperature, and aerosol extinction coefficient by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on the NASA Upper Atmosphere Research Satellite (UARS), obtained over the period 9 January 1992 through 23 April 1993. The discussion concentrates on the stratosphere region near 21 km of particular interest to heterogeneously driven ozone depletion. For periods between 12 June and 1 September 1992 at latitudes poleward of about 60 deg S, when temperatures were below type I polar stratospheric cloud (PSC) formation thresholds throughout the lower stratosphere, CLAES observed high levels of PSCs coincident with highly depleted fields of both HNO3 and ClONO2. By 17 September, the incidence of PSCs had greatly diminished in the lower stratosphere, but both CLONO2 and HNO3 remained highly depleted. These observations are consistent with the removal of gaseous HNO3 through the formation of nitric acid trihydrate (NAT) particles and the removal of ClONO2 through heterogeneous reactions on the particle surfaces. They also suggest substantial denitrification of the lower Antarctic vortex through sedimentation of PSC particles. In the Northern Hemisphere winter of 1992/93 far fewer PSCs were observed in the Arctic lower-stratosphere vortex, which had shorter periods and more localized regions of cold temperatures. Both HNO3 and ClONO2 maintained much higher levels inside the Arctic vortex than seen in the Antarctic throughout the winter/spring period. Following 28 February 1993 when Arctic vortex temperatures rose above 195 K, ClONO2 was observed in large quantities (greater than 2.1 ppbv near 21 km) inside the vortex. The persistence of relatively high levels of HNO3 inside the Arctic spring vortex compared with the low levels seen in the Antarctic spring vortex suggest a much lower level of denitrification in the Arctic.

Roche, A. E.↗
NASA NTRS2010

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

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-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. 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 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗
NASA NTRS1993

Possible solutions to the problem of channel formation on early Mars

A warm climate on early Mars would provide a natural, although not unique, explanation for the presence of fluvial networks on the ancient, heavily cratered terrains. Explaining how the climate could have been kept warm, however, is not easy. The idea that the global average surface temperature, T(sub s), could have been kept warm by a dense, CO2 atmosphere supplied by volcanism or impacts is no longer viable. It was shown that CO2 cloud formation should have kept T(sub s) well below freezing until approximately 2 b.y. ago, when the Sun had brightened to at least 86 percent of its present value. Warm equatorial regions on an otherwise cold planet seem unlikely because atmospheric CO2 would probably condense out at the poles. Warming by impact-produced dust in the atmosphere seems unlikely because the amount of warming expected for silicate dust particles is relatively small. Greenhouse warming by high altitude CO2 ice clouds seems unlikely because such are poor absorbers of infrared radiation at most wavelengths. Warming by atmospheric NH3 seems unlikely because NH3 is readily photodissociated and because N may have been in short supply as consequence of impact erosion and the high solubility of NH3. A brighter, mass-losing young Sun seems unlikely because stellar winds of the required strength were not observed on other solar-type stars. In short, most of the explanations for a warm Martian paleoclimate that were proposed in the past seem unlikely. One possibility that seems feasible from radiative/photochemical standpoint is that CH4 and associated hydrocarbon gases and particles contributed substantially to the greenhouse effect on early Mars. Methane is photochemically more stable than NH3 and the gases and particles that can be formed from it are all good absorbers of infrared radiation. The idea of a CH4-rich Martian paleoatmosphere was suggested a long time ago but has fallen out of favor because of perceived difficulties in maintaining a CH4-rich atmosphere. In particular, it is not obvious where the CH4 might come from, since volcanic gases (on Earth, at least) contain very little CH4. This difficulty could be largely overcome if early Mars was inhabited by microorganisms. Then, methanogenic bacteria living in sediments could presumably have supplied CH4 to the atmosphere in copious quantities.

Kasting, J. F.↗
NASA NTRS2024

Enhancing Consistency of Microphysical Properties of Precipitation Across the Melting Layer in the Dual-Frequency Precipitation Radar Data

Stratiform rain and the overlying ice play crucial roles in Earth's climate system. From a microphysics standpoint, water mass flux primarily depends on two variables: particles' concentration and their mass. The Dual-frequency Precipitation Radar (DPR) on the Global Precipitation Measurement mission core satellite is a spaceborne instrument capable of estimating these two quantities through dual-wavelength measurements. In this study, we evaluate bulk statistics on the ice particle properties derived from dual-wavelength radar data in relation to the properties of rain underneath. Specifically, we focus on DPR observations over stratiform precipitation, characterized by columns exhibiting a prominent bright band, where the melting layer can be easily detected. Our analysis reveals a large increase in the retrieved mass flux as we transition from the ice to the rain phase in the official DPR product. This observation is in disagreement with our expectation that mass flux should remain relatively stable across the bright band in cold-rain conditions. To address these discrepancies, we propose an alternative retrieval algorithm that ensures a gradual transition of Dm (mean mass-weighted particle melted-equivalent diameter) and the precipitation rate across the melting zone. This approach also helps in estimating bulk ice density above the melting level. These findings demonstrate that DPR observations can not only quantify ice particle content and their size above stratiform rain regions but also estimate bulk density, provided uniform conditions that minimize uncertainties related to partial beam filling.

radar measurements from space↗
NASA NTRS1999

Remote Sensing of Rain

The first problem addressed concerns passive-microwave rain retrievals. Most current approaches start by building off-line a cloud-model-derived database. Given data, the retrieval algorithms search the database for the microwave temperatures "closest" to the observed data, then after some fine-tuning (performed in different ways by different implementations) the rain is estimated to be that which corresponds to the selected (and fine-tuned) set of database temperatures. These approaches have three drawbacks: they cannot properly take into account the ambiguities which arise from the fact that several rain scenarios can produce the same observed temperatures; they are quite inefficient since they require manipulating a large database along with often complex "fine-tuning" procedures; and they cannot refine their estimates if additional data is available. This past year we have derived closed formulae relating observed microwave brightness temperatures, T(sub b), and the underlying rain rates, R: average T(sub b) =f (rain) and average rain = g (T(sub b)), along with the corresponding covariance matrices. These results are sufficient to describe the conditional probabilities p(R/T(sub b)) and p(T(sub b)/R) to second order. Progress has also been made towards deriving a robust description of the rain drop size distribution (DSD). The widespread approach consisting in parameterizing the DSD as a gamma-distribution in terms of the drop diameter D suffers from the facts that, in reality, the DSD is not a smooth function of D and that the largely arbitrary Gamma model imposes unintended behavior, which has implications on any quantities derived from the DSD model. We have therefore developed a non-parametric yet practical description of the DSD, which is particularly well-suited for use in remote-sensing applications. The diagram on the left shows a comparison between an actual DSD sample and the truncated non-parametric representation. One figure shows the relation between radar reflectivity and rain rate derived using this representation. Validation of the Tropical Rainfall Measuring Mission (TRMM) radar-radiometer combined R and DSD algorithm is underway. This algorithm was designed to make optimal use of the instantaneous reflectivity profiles measured by the TRMM radar and the microwave brightness temperatures measured by the TRMM passive radiometer. So far, it appears to be the most reliable TRMM rain algorithm.

Haddad, Ziad S.↗
NASA NTRS2011

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS2012

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Roman, Miguel O.↗
NASA NTRS2012

Transformation of Graphitic and Amorphous Carbon Dust to Complex Organic Molecules in a Massive Carbon Cycle in Protostellar Nebulae

More than 95% of silicate minerals and other oxides found in meteorites were melted, or vaporized and recondensed in the Solar Nebula prior to their incorporation into meteorite parent bodies. Gravitational accretion energy and heating via radioactive decay further transformed oxide minerals accreted into planetesimals. In such an oxygen-rich environment the carbonaceous dust that fell into the nebula as an intimate mixture with oxide grains should have been almost completely converted to CO. While some pre-collapse, molecular-cloud carbonaceous dust does survive, much in the same manner as do pre-solar oxide grains, such materials constitute only a few percent of meteoritic carbon and are clearly distinguished by elevated D/H, N-15/N-16, C-13/C-12 ratios or noble gas patterns. Carbonaceous Dust in Meteorites: We argue that nearly all of the carbon in meteorites was synthesized in the Solar Nebula from CO and that this CO was generated by the reaction of carbonaceous dust with solid oxides, water or OH. It is probable that some fraction of carbonaceous dust that is newly synthesized in the Solar Nebula is also converted back into CO by additional thermal processing. CO processing might occur on grains in the outer nebula through irradiation of CO-containing ice coatings or in the inner nebula via Fischer-Tropsch type (FTT) reactions on grain surfaces. Large-scale transport of both gaseous reaction products and dust from the inner nebula out to regions where comets formed would spread newly formed carbonaceous materials throughout the solar nebula. Formation of Organic Carbon: Carbon dust in the ISM might easily be described as inorganic graphite or amorphous carbon, with relatively low structural abundances of H, N, O and S . Products of FTT reactions or organics produced via irradiation of icy grains contain abundant aromatic and aliphatic hydrocarbons. aldehydes, keytones, acids, amines and amides.. The net result of the massive nebular carbon cycle is to convert relatively inert carbonaceous dust from the ISM into the vital organic precursors to life such as amino acids and sugars intimately mixed with dust and ice in primitive planetesimals. Since the number of carbon atoms entering the Solar Nebula as dust exceeds the number of atoms entering the nebula as oxide grains. the formation of large quantities of complex organic molecules may represent the largest single chemical cycle in the nebula.

Nuth, Joseph A., III↗
NASA NTRS1992

Validating a large geophysical data set: Experiences with satellite-derived cloud parameters

We are validating the global cloud parameters derived from the satellite-borne HIRS2 and MSU atmospheric sounding instrument measurements, and are using the analysis of these data as one prototype for studying large geophysical data sets in general. The HIRS2/MSU data set contains a total of 40 physical parameters, filling 25 MB/day; raw HIRS2/MSU data are available for a period exceeding 10 years. Validation involves developing a quantitative sense for the physical meaning of the derived parameters over the range of environmental conditions sampled. This is accomplished by comparing the spatial and temporal distributions of the derived quantities with similar measurements made using other techniques, and with model results. The data handling needed for this work is possible only with the help of a suite of interactive graphical and numerical analysis tools. Level 3 (gridded) data is the common form in which large data sets of this type are distributed for scientific analysis. We find that Level 3 data is inadequate for the data comparisons required for validation. Level 2 data (individual measurements in geophysical units) is needed. A sampling problem arises when individual measurements, which are not uniformly distributed in space or time, are used for the comparisons. Standard 'interpolation' methods involve fitting the measurements for each data set to surfaces, which are then compared. We are experimenting with formal criteria for selecting geographical regions, based upon the spatial frequency and variability of measurements, that allow us to quantify the uncertainty due to sampling. As part of this project, we are also dealing with ways to keep track of constraints placed on the output by assumptions made in the computer code. The need to work with Level 2 data introduces a number of other data handling issues, such as accessing data files across machine types, meeting large data storage requirements, accessing other validated data sets, processing speed and throughput for interactive graphical work, and problems relating to graphical interfaces.

Kahn, Ralph↗
NASA NTRSDate not supplied

Quantitative Highlights of 20 years Aqua Data Archive and Data Usage

NASA’s Aqua satellite carries six Earth-observing instruments Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Advanced Microwave Sounding Unit (AMSU), Clouds and the Earth’s Radiant Energy System (CERES), Humidity Sounder for Brazil (HSB) and Moderate Resolution Imaging Spectroradiometer (MODIS). Currently only four of six instruments are collecting data, two instruments that stopped transmitting data are AMSR-E that suffered a major anomaly in October 2011 and was powered off in March 2016 while as HSB failed in February 2003. NASA’s Earth Science Data and Information System (ESDIS) Project makes these data, along with derived products, available to worldwide data users. Since the launch of Aqua on May 4, 2002, more than 10,000 data products have been archived and distributed by NASA-funded Distributed Active Archive Centers (DAACs) that are part of NASA’s Earth Observing System Data and Information System (EOSDIS). At the end of the 2021 Fiscal Year with over 100,000 orbits data, about 1,000 Aqua data products constituted almost 16.5 % of the entire EOSDIS data archive volume (8.6 PB out of approximately 55.2 PB), and 7.5 PB of Aqua data were distributed to over half-a-million public users worldwide. By categorizing the Aqua data products and their distribution, we can get a quantitative assessment of Aqua data usage. NASA’s ESDIS Project has collected archive, distribution, and user information from EOSDIS data users since February 2000. These metrics are available through the ESDIS Metrics System (EMS). EMS information is stored in a relational database from which quantitative metrics of Aqua data use can be retrieved and analyzed. The purposes of this study are to: 1) perform a comprehensive investigation of the 20-year trend in the archive and distribution of Aqua data products; 2) identify and characterize data product usage over the last 20 years; and 3) identify and characterize the global user community for these data. In addition to revealing how Aqua data use has evolved over time, the results of this study provide insights on identifying the various user communities for different kinds of Earth science data products. Also, because of the enormous quantity of data handled by EOSDIS DAACs, the study provides guidance of the requirements for future data systems that will be needed to effectively and efficiently handle the ever-increasing amounts of Earth science data produced by future (and ongoing) Earth science missions.

Lalit Wanchoo↗
NASA NTRS1998

The Role of Grain Surface Reactions in the Chemistry of Star Forming Regions

The importance of reactions at the surfaces of dust grains has long been recognized to be one of the two main chemical processes that form molecules in cold, dark interstellar clouds where simple, saturated (fully-hydrogenated) molecules such as H2 water, methanol, H2CO, H2S, ammonia and CH4 are present in quantities far too high to be consistent with their extremely low gas phase formation rates. In cold dark regions of interstellar space, dust grains provide a substrate onto which gas-phase species can accrete and react. Grains provide a "third body" or a sink for the energy released in the exothermic reactions that form chemical bonds. In essence, the surfaces of dust grains open up alternative reaction pathways to form observed molecules whose abundances cannot be explained with gas-phase chemistry alone. This concept is taken one step further in this work: instead of merely acting as a substrate onto which radicals and molecules may physically adsorb, some grains may actively participate in the reaction itself, forming chemical bonds with the accreting species. Until recently, surface chemical reactions had not been thought to be important in warm circumstellar media because adspecies rapidly desorb from grains at very low temperatures; thus, the residence times of molecules and radicals on the surface of grains at all but the lowest temperatures are far too short to allow these reactions to occur. However, if the adspecies could adsorb more strongly, via a true chemical bond with surfaces of some dust grains, then grain surface reactions will play an important role in warm circumstellar regions as well. In this work, the surface-catalyzed reaction CO + 3 H2 yields CH4 + H2O is studied in the context that it may be very effective at converting the inorganic molecule CO into the simplest organic compound, methane. H2 and CO are the most abundant molecules in space, and the reaction converting them to methane, while kinetically inhibited in the gas phase under most astrophysical conditions, is catalyzed by iron, an abundant constituent of interstellar dust. At temperatures between 600 and 1000 K, which occur in the outflows from red giants and near luminous young stars, this reaction readily proceeds in the presence of an iron catalyst. Iron is one of the more abundant elements composing interstellar dust. Its abundance relative to hydrogen is almost that of silicon, and both of these heavy elements are primarily locked up in dust at all but the hottest regions of interstellar space.

Kress, M. E.↗
DOE OSTI2026

Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)

Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.

Silber, Israel [Pacific Northwest National Laborat↗
NASA NTRS2022

The Earth Model Column Collaboratory (EMC2) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Earth Model Column Collaboratory↗