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NASA NTRS2011

Accelerating Climate and Weather Simulations through Hybrid Computing

Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

hybrid computing↗

NASA NTRS2020

Process for Detecting Strong Convection Using an Airborne, Doppler, Weather Radar

This document presents a methodology for producing a measure of the convective wind field ahead of an aircraft using a modern, airborne, Doppler, weather radar. The processes and hardware requirements are consistent with the capabilities found in modern commercial weather radars commonly in use on commercial transport aircraft. The fundamental process is developed as well as results from ground and flight testing are described. This application appears sufficiently mature to allow its use in future NASA flight campaigns that will search for convective cells. If this application continues to perform successfully, it will be recommended to avionics manufacturing colleagues for inclusion into future commercial, airborne, Doppler, weather radars to aide pilots with flight operations and further enhance aviation safety.

Steven D. Harrah↗

NASA NTRS1998

Efficient Third Harmonic Generation for Wind Lidar Applications

The characterization of atmospheric winds on a global basis is a key parameter required for accurate weather prediction. The use of a space based lidar system for remote measurement of wind speed would provide detailed and highly accurate data for future weather prediction models. This paper reports the demonstration of efficient third harmonic conversion of a 1 micrometer laser to provide an ultraviolet (UV) source suitable for a wind lidar system based on atmospheric molecular scattering. Although infrared based lidars using aerosol scattering have been demonstrated to provide accurate wind measurement, a UV based system using molecular or Rayleigh scattering will provide accurate global wind measurements, even in those areas of the atmosphere where the aerosol density is too low to yield good infrared backscatter signals. The overall objective of this work is to demonstrate the maturity of the laser technology and its suitability for a near term flight aboard the space shuttle. The laser source is based on diode-pumped solid-state laser technology which has been extensively demonstrated at TRW in a variety of programs and internal development efforts. The pump laser used for the third harmonic demonstration is a breadboard system, designated the Laser for Risk Reduction Experiments (LARRE), which has been operating regularly for over 5 years. The laser technology has been further refined in an engineering model designated as the Compact Advanced Pulsed Solid-State Laser (CAPSSL), in which the laser head was packaged into an 8 x 8 x 18 inch volume with a weight of approximately 61 pounds. The CAPSSL system is a ruggedized configuration suitable for typical military applications. The LARRE and CAPSSL systems are based on Nd:YAG with an output wavelength of 1064 nm. The current work proves the viability of converting the Nd:YAG fundamental to the third harmonic wavelength at 355 nm for use in a direct detection wind lidar based on atmospheric Rayleigh scattering.

Mordaunt, David W.↗

NASA NTRS2013

Lessons from 18 Years of Hyperspectral Infrared Sounder Data

By the end of 2013 NASA and EUMETSAT will have accumulated more than 11 years of AIRS, 6 years of IASI and one year of CrIS data. All three instruments were nominally specified to support the NWC for short term weather forecasting with a five year lifetime, but continue to exceed the accuracy requirement needed for weather forecasting alone. This allows use of their data for a much broader range of applications, including the calibration of broad-band instruments in space and climate research. We illustrate calibration aspects with examples from AIRS, IASI and CrIS using spatially uniform clear conditions, simultaneous nadir overpasses and random nadir samples. The differences between AIRS, IASI and CrIS for the purpose of weather forecasting are small and we expect that the excellent forecast impact demonstrated by the combination of AIRS and IASI will be continued by the combination of CrIS and IASI. Clear data are useful for calibration, but contain no climate signal. The analysis of random nadir samples from AIRS and CrIS identifies larger biases for observation of extreme conditions, represented by 1% and 99%tile data than for non-extreme observations. This is relevant for climate analysis. Resolution of these differences require further work, since they can complicate the continuation of trends established by AIRS with CrIS data, at least for extrema. The unequaled stability of the AIRS data allows us to evaluate trends using random nadir sampled data. We see an increasing frequency in severe storms over land, a decreasing frequency over ocean. The 11 years of AIRS data are too short to tell if these trends are significant from a climate change viewpoint, or if they are parts of multi-decadal oscillations.

CRIS↗

NASA NTRSDate not supplied

From NASA's EOS to ESO: Advancing Applications of the Future Atmosphere Observing (AOS) Mission

The NASA Earth System Observatory (ESO) Atmosphere Observing System (AOS) is being designed to explore the fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. A fundamental component of the AOS mission is ensuring that applications for economic and societal benefit are considered to the greatest extent possible in mission design. As a result, the AOS Applications Impact Team (AIT) was formed to address this objective. The overarching goal of the AIT is to help improve capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data become available. A critical component of preparing future users of AOS mission data is building on the successes of applications of NASA’s existing Earth Observing System (EOS), A-Train, and sub-orbital campaigns with the goal of advancing current mission applications activities and preparing for innovative AOS mission observations. NASA’s GPM mission forms a framework to enhance AOS precipitation applications while AOS health and air quality applications benefit from the heritage of CALIPSO and MODIS. Additionally, AOS will likely benefit from current and future missions such as TROPICS, MAIA, TEMPO, and PACE which launch before AOS. Additionally, current sub-orbital field campaigns, such as NASA IMPACTS and ACTIVATE, provide rich data sources to highlight future AOS capabilities. Engaging with existing missions and sub-orbital field campaigns helps to identify and understand data needs, gaps, and opportunities for current and future stakeholders, determine what data products are of highest value and use, and connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS AIT activities, initiatives, and the AOS Applications Seminar Series to highlight how existing EOS, A-Train, and sub-orbital missions can play a critical role in advancing AOS applications prior to launch.

Emily B. Berndt↗

NASA NTRS2018

Urban Air Mobility (UAM) Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5% of the total available market, or $2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized. The barriers and challenges we characterized in this study can be stratified according to their applicability or potential mitigation through technology as well as market maturity (Figure 1). In the near term, high cost of service will be a key economic challenge. We found potential for significant reduction in service cost through increased vehicle and component efficiency, and automation in a more mature market scenario. Weather conditions also pose a challenge to the UAM market, though there is potential for mitigation of some of these impacts through technology such as sensors enabling operations in low visibility. However, even in a mature market with advanced technology, disruptions are still likely to occur due to weather events such as thunderstorms and strong winds. High density operations will likely stress the current Air Traffic Management (ATM) system in the near term, but technology and new initiatives such as the Air Traffic Management -eXploration project (ATM-X) will enable safe and efficient integration of UAM into the National Airspace System (NAS). Current battery technology creates a barrier in the near term, especially for the Air Ambulance market, as battery weight and extensive recharging times would be needed for these operations. Advancements in battery technology, as well as use of hybrid VTOLs, could significantly reduce this barrier in the longer term. As UAM emerges as a viable mode of transportation in the near term, adverse energy and environmental impacts, particularly noise, may impact community acceptance and potentially persist as the market matures into larger-scale operations. For non-technology related challenges, we found that infrastructure constraints will create a significant barrier to UAM in the near term but could be addressed in the longer term through development and expansion of vertiports. Competition from existing modes of transportation such as ride-sharing (e.g., Lyft, Uber) and ground taxi’s pose a key barrier to UAM in the short term, which will likely evolve into competition from other emerging technologies such as autonomous cars and electric trains in the longer term. Weather events will influence other components of the operation such as passenger comfort (e.g., extreme temperatures, turbulence) and infrastructure (e.g., winter weather causing cracks and degradation in vertiports). There is also potential for these impacts to be heightened in the longer term from the increased frequency of adverse weather such as thunderstorms due to changing climatic conditions. We also found that the public has strong concerns about safety as a passenger in a piloted UAM, including “lasing” of pilots, unruly passengers, and sabotage. They would prefer that all passengers pass through a security screening process before boarding a vehicle. They would also prefer to use UAM for longer regional trips, such as flying from Washington, DC to Baltimore, MD or San Diego, CA to Los Angeles, CA. A longer term automated UAM vehicle market will face challenges due to public apprehension about automation and unmanned operations, and a preference to fly with passengers they know in an autonomous (unmanned) operational scenario.

Rohit Goyal↗

NASA NTRS2011

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Putnam, Williama↗

NASA NTRS2024

Quantification of Uncertainty and Risk Sensitivity for Safety of Emerging Operations

The growing need to develop and deploy small unmanned aerial vehicles (sUAVs) for various applications in the airspace necessitates reliable tools to accurately predict the flight trajectories of the sUAVs. The knowledge of the predicted trajectories help decision makers anticipate potential conflict, assess the risk, and take appropriate risk mitigation actions. In addition, uncertainties in vehicle models, weather, and controller action further highlights the need for reliable prediction tools. In this project, the application of mixed sparse grid-based quadrature and generalized polynomial chaos(gPC) expansion method for uncertainty quantification and collision assessment in air traffic consisting of fixed-wing small unmanned aerial vehicles (sUAV) was studied. From the results obtained, it can be concluded that this provides a reliable framework to carry out quantitative conflict assessment in an unmanned air traffic, which when employed, can improve the functionalities of the unmanned traffic management system. It was observed that the results from the gPC expansion framework developed in the project can be utilized to conduct rapid probabilistic collision assessment for near real-time unmanned traffic management in the airspace. From the vehicle models, position updates, and wind-field data, a priori gPC based 3-σcon-fidence ellipses can provide estimates of potential conflict at some future instants. The computational costs scaled linearly when the uncertain inputs were fewer. Further, the largest allowable distribution of para-metric uncertainties that leads to the smallest risk of collision in traffic of small unmanned aerial vehicles could be calculated. The time of closest approach between two sUAVs can be established paving way for development of proactive mitigation strategies. The separation between the sUAVs was found to be most significantly affected by uncertainties in the maximum available thrusts, zero-lift drag coefficients, and wing planform areas of the sUAVs. The study of uncertain wind-fields indicated that a heterogeneous traffic mix resulted in an increased probability of conflict. Increased measurement update rate reduced the uncertain-ties in the trajectories of the vehicles, further reducing the probability of conflict but rapid updates of all vehicles in the airspace poses a stringent communication limitation. The gPC framework also provided the means to analyze vehicle impact (crash region) due to loss of control resulting from actuator failure in sUAS traffic, essentially to predict impact and crash zones for representative vehicles. The predicted regions when compared with non-participant density, provides a means to develop an early mitigation strategy, should the sUAV detect an imminent actuator failure.

Rajnish Bhusal↗

NASA NTRS2010

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗

NASA NTRS1974

An evaluation of SAO sites for laser operations

Operational criteria are provided for the selection of laser tracking sites for the Earth and Ocean Physics Applications Program. A compilation of data is given concerning the effect of weather conditions on laser and Baker-Nunn camera operations. These data have been gathered from the Smithsonian astrophysical observing station sites occupied since the inception of the satellite tracking program. Also given is a brief description of each site, including its characteristic weather conditions, comments on communications and logistics, and a summary of the terms of agreement under which the station is or was operated.

Thorp, J. M.↗

NASA NTRS1985

Automatic Erection System for Antenna Masts

A telescoping mast does not require the payout of guy wires under tension. Erection system is built into stack of telescoping mast elements and is thereby protected from the weather. Concept is based on a telescoping tube mast, it is also applicable to an open truss with only minor modifications.

Dotson, R. D.↗

NASA NTRS1994

Infrared Detectors Reach New Lengths

Infrared detectors operating from mid IR wavelengths to very long wavelength IR are of great interest for a variety of ground based and space based applications such as night vision, early warning systems, navigation, flight control systems, weather monitoring, and astronomy.

infrared detectors↗

NASA NTRS2011

Spray-On Foam Insulations for Launch Vehicle Cryogenic Tanks

Spray-on foam insulation (SOFI) has been developed for use on the cryogenic tanks of space launch vehicles beginning in the 1960s with the Apollo program. The use of SOFI was further developed for the Space Shuttle program. The External Tank (ET) of the Space Shuttle, consisting of a forward liquid oxygen tank in line with an aft liquid hydrogen tank, requires thermal insulation over its outer surface to prevent ice formation and avoid in-flight damage to the ceramic tile thermal protection system on the adjacent Orbiter. The insulation also provides system control and stability with throughout the lengthy process of cooldown, loading, and replenishing the tank. There are two main types of SOFI used on the ET: acreage (with the rind) and closeout (machined surface). The thermal performance of the seemingly simple SOFI system is a complex of many variables starting with the large temperature difference of from 200 to 260 K through the typical 25-mm thickness. Environmental factors include air temperature and humidity, wind speed, solar exposure, and aging or weathering history. Additional factors include manufacturing details, launch processing operations, and number of cryogenic thermal cycles. The study of the cryogenic thermal performance of SOFI under large temperature differentials is the subject of this article. The amount of moisture taken into the foam during the cold soak phase, termed Cryogenic Moisture Uptake, must also be considered. The heat leakage rates through these foams were measured under representative conditions using laboratory standard liquid nitrogen boiloff apparatus. Test articles included baseline, aged, and weathered specimens. Testing was performed over the entire pressure range from high vacuum to ambient pressure. Values for apparent thermal conductivity and heat flux were calculated and compared with prior data. As the prior data of record was obtained for small temperature differentials on non-weathered foams, analysis of the different methods is provided. Recent advancements and applications of SOFI systems on future launch vehicles and spacecraft are also addressed.

Fesmire, J. E.↗

NASA NTRS2020

Ensemble Methodologies for Astronaut Cancer Risk Assessment in the face of Large Uncertainties

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

space radiation↗

NASA NTRSDate not supplied

Ensemble Cancer Risk Model for Astronaut Risk Assessment

Lisa C Simonsen↗

NASA NTRS2021

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Daniel Pérez-Ramírez↗

NASA NTRSDate not supplied

Exploring the Elevated Water Vapor Signal Associated With the Free Tropospheric Biomass Burning Plume Over the Southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol–cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume–vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ∼5–6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (∼6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

Kristina Pistone↗

NASA NTRS2022

An Overview of ARTMIP’s Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and their Associated Precipitation

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

ARTMIP↗