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DOE OSTI2022

The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary-layer structure, aerosol, cloud and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary-layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Pan-tropical daily L-band microwave land surface emissivity retrieval from GNSS-R observations

The uncertainties in microwave land surface emissivity (MLSE) measurements have long limited the use of spaceborne microwave radiometer data. As an emerging observation method, Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated great potential in several land and ocean applications. In this study, a method for obtaining daily MLSE dataset in the pan-tropical region from Cyclone GNSS (CYGNSS) observations is presented and evaluated. The CYGNSS observations are first aggregated into the Equal-Area-Scalable-Earth (EASE) 2.0 36 km grid by a combined weight function of distance, time, and signal-to-noise ratio variance. Then, the method employs a pixel-by-pixel regression algorithm to conduct the daily MLSE retrieval using reference emissivity derived from the Soil Moisture Active Passive (SMAP) brightness temperature. The CYGNSS MLSE shows good agreement with SMAP MLSE, delivering an overall root-mean-square error (RMSE) of 0.022 and 0.017 for horizontal and vertical polarization, respectively, during the training set spanning the whole year of 2018. Furthermore, on the test set from January 2019 to May 2019, the RMSE values amounted to 0.030 and 0.023 for horizontal and vertical polarization, respectively. Temperature records from the International Soil Moisture Network are employed to calculate the emissivity and for in-situ validation, which yield an RMSE of 0.034 and 0.026 for the two polarizations, respectively. The proposed algorithm provides an encouraging approach to obtain accurate daily MLSE dataset for microwave remote sensing. Compared to the SMAP MLSE, the CYGNSS MLSE has a remarkable improvement of 86% in temporal resolution, greatly complementing the existing microwave emissivity datasets.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases

The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within +/-0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

retrieval algorithm↗

NASA NTRS2019

Picture this SELFI: Submillimeter Enceladus Life Fundamentals Instrument

The Submillimeter Enceladus Life Fundamentals Instrument (SELFI) is a passive remote sensing submillimeter heterodyne spectrometer being developed at NASA GSFC under NASA's Maturation of Instruments for Solar System Exploration (MatISSE) program. SELFI will advance submillimeter receiver technology by 1) investigating the chemical and isotopic compositions and corresponding densities of Enceladus' plume material, their vertical thermal structures, and the transport mechanisms within the plumes, and 2) characterizing the source regions from which the plumes emerge. The Enceladus plumes are important in the context of life and habitability of its subsurface ocean environment. SELFI remote sensing measurements will 1) measure the spatial and temporal variabilities in the plume chemical compositions, 2) provide insight in to Enceladus' subsurface ocean environment by monitoring H2O, HDO, d18O, and d17O, 3) constrain the oxidation state of the subsurface ocean using H2O2 and O3, and 4) utilize the SO2 and H2S spectral signatures to constrain the impact arising from both the sea-floor volcanoes and pre-biotic molecules. Moreover, the detection of the remaining molecular species (14 in total) is vital to improving the current state of knowledge of Enceladus' subsurface ocean habitability this also permits us to explore the chemical alteration processes arising from primordial volatiles that have been observed in comets. Lastly, SELFI's continuum observations enable the correlation between observed variations in plume activity with surface temperatures.SELFI is currently being developed under a technology maturation program that will advance the RF-to-digital electronics of a submillimeter-wave heterodyne spectrometer to simultaneously observe fourteen molecular species with resonances between 530 GHz and 600 GHz. SELFI will have fine radiometric resolution, high spectral resolution (resolving power R > 106), multiple continuum channels and a high dynamical range, necessary to map Enceladus across its 30 K to 250 K temperature range. Under the MatISSE program, SELFI will advance from TRL 4 to 6 four key technologies of the RF-to-digital subsystem, which are: 1) the RF low noise amplifier design; 2) the single-sideband (SSB) mixer and local oscillator; 3) the IF assembly down-converter that maps the fourteen species to 2 x 500 MHz bandwidth; and 4) the digital spectrometer electronics.

Racette, Paul↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

DOE OSTI2021

Comparison of Observations and Predictions of Daytime Planetary-Boundary-Layer Heights and Surface Meteorological Variables in the Columbia River Gorge and Basin During the Second Wind Forecast Improvement Project

The second Wind Forecast Improvement Project (WFIP2) is an 18-month field campaign in the Pacific Northwest U.S.A., whose goal is to improve the accuracy of numerical-weather-prediction forecasts in complex terrain. The WFIP2 campaign involved the deployment of a large suite of in situ and remote sensing instrumentation, including eight 915-MHz wind-profiling radars, and surface meteorological stations. The evolution and annual variability of the daytime convective planetary-boundary-layer (PBL) height is investigated using the wind-profiling radars. Three models with different horizontal grid spacing are evaluated: the Rapid Refresh, the High-Resolution Rapid Refresh, and its nested version. The results are used to assess errors in the prediction of PBL height within the experimental and control versions of the models, with the experimental versions including changes and additions to the model parametrizations developed during the field campaign, and the control version using the parametrizations present in the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction operational version of the models at the start of the project. Results show that the high-resolution models outperform the low-resolution versions, the experimental versions perform better compared with the control versions, model PBL height estimations are more accurate on cloud-free days, and model estimates of the PBL height growth rate are more accurate than model estimates of the rate of decay. Finally, using surface sensors, we assess surface meteorological variables, finding improved surface irradiance and, to a lesser extent, improved 2-m temperature in the experimental version of the model.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Toward P-Band Passive Microwave Sensing of Soil Moisture

Currently, near-surface soil moisture at a global scale is being provided using National Aeronautics and Space Administration’s (NASA’s) Soil Moisture Active Passive (SMAP) and European Space Agency’s (ESA’s) Soil Moisture and Ocean Salinity (SMOS) satellites, both of which utilize L-band (1.4 GHz; 21 cm wavelength ) passive microwave remote sensing techniques. However, a fundamental limitation of this technology is that the water content can only be measured for approximately the top 5-cm layer of soil moisture, and only over low-to-moderate vegetation covered areas in order to meet the 0.04 m3/m3 target accuracy, limiting its applicability. Consequently, a longer wavelength radiometer is being explored as a potential solution for measuring soil moisture in a deeper surface layer of soil and under denser vegetation. It is expected that P-band ( wavelength of 40 cm and frequency of 750 MHz) could potentially provide soil moisture information for the top 10-cm layer of soil, being one-tenth to one-quarter of the wavelength. In addition, P-band is expected to have higher soil moisture retrieval accuracy due to its reduced sensitivity to vegetation water content and surface roughness. To demonstrate the potential of P-band passive microwave soil moisture remote sensing, a short-term airborne field experiment was conducted over a center pivot irrigated farm at Cressy in Tasmania, Australia, in January 2017. First results showing a comparison of airborne P-band brightness temperature observations against airborne L-band brightness temperature observations and ground soil moisture measurements are presented. The P-band brightness temperature was found to have a similar but stronger response to soil moisture compared to L-band.

Nan Ye↗

DOE OSTI2025

Best estimate of the planetary boundary layer height from multiple remote sensing measurements

Remote sensing measurements have been widely used to estimate the planetary boundary layer height (PBLHT). Each remote sensing approach offers unique strengths and faces different limitations. In this study, we use machine learning (ML) methods to produce a best-estimate PBLHT (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. Three ML models – random forest (RF) classifier, RF regressor, and light gradient-boosting machine (LightGBM) – were trained on a dataset from 2017 to 2023 that included radiosonde, various remote sensing PBLHT estimates, and atmospheric meteorological conditions. Evaluations indicated that PBLHT-BE-ML from all three models improved alignment with the PBLHT derived from radiosonde data (PBLHT-SONDE), with LightGBM demonstrating the highest accuracy under both stable and unstable boundary layer conditions. Feature analysis revealed that the most influential input features at the SGP site were the PBLHT estimates derived from (a) potential temperature profiles retrieved using Raman lidar (RL) and atmospheric emitted radiance interferometer (AERI) measurements (PBLHT-THERMO), (b) vertical velocity variance profiles from Doppler lidar (PBLHT-DL), and (c) aerosol backscatter profiles from micropulse lidar (PBLHT-MPL). The trained models were then used to predict PBLHT-BE-ML at a temporal resolution of 10 min, effectively capturing the diurnal evolution of PBLHT and its significant seasonal variations, with the largest diurnal variation observed over summer at the SGP site. We applied these trained models to data from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) field campaign (EPC), where the PBLHT-BE-ML, particularly with the LightGBM model, demonstrated improved accuracy against PBLHT-SONDE. Analyses of model performance at both the SGP and EPC sites suggest that expanding the training dataset to include various surface types, such as ocean and ice-covered areas, could further enhance ML model performance for PBLHT estimation across varied geographic regions.

Zhang, Damao [Pacific Northwest National Laborator↗

DOE OSTI2026

Observed Temperature and Moisture Advection Characteristics in the Southern Great Plains

Until recently, advection profiles in the planetary boundary layer have been difficult to quantify from observations. As a result, not much is known about its basic characteristics, like magnitude and diurnal cycles, or how these differ as a function of large-scale environments. Here, to provide insight into advective characteristics, a Green’s Theorem–based method for calculating profiles of advection in the lowest 3 km from an array of ground-based thermodynamic and kinematic profiling instruments has been applied to 2 years of observations from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observing site. Since advection largely depends on synoptic-scale forcing, a self-organizing map (SOM) was used to classify days based on mean sea level pressure analyses; from that, the diurnal evolution of vertical profiles of advection for different synoptic environments was quantified. The overall mean magnitude of the potential temperature advection is approximately ±3 K h −1 , while the moisture advection is approximately ±1.5 g kg −1 h −1 , with substantial variability in the sign and magnitude of the advective tendencies at different heights and throughout the diurnal cycle. Advection magnitude is strongly connected to the strength of synoptic-scale forcing, which varies depending on the time of year. Variability in advection is larger for potential temperature than it is for moisture, and strongly forced environments, like midlatitude cyclones, feature greater variability in the advection magnitude than weakly forced or quiescent environments.

advection↗

NASA NTRS2021

Second Time-Resolved Observations of Precipitation Structure and Storm Intensity With a Constellation of Smallsats (TROPICS) Mission Applications Workshop

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of state-of-the-science observing platforms that will measure temperature and humidity soundings and precipitation with spatial resolution comparable to current operational passive microwave (PMW) sounders but with unprecedented temporal resolution (Mission Website).1 TROPICS is a cost-capped ($30.2 million), Venture-class mission funded by the NASA Earth Science Division (ESD) and led by Principal Investigator Dr. William Blackwell from the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). The mission consists of a constellation of six, three-unit (3U) CubeSats (approximately 10×10×34 cm), each hosting a 12-channel PMW spectrometer based on the Micro-sized Microwave Atmospheric Satellite-2 (MicroMAS-2) developed at MIT LL, but with a substantially improved design. TROPICS will provide imagery near 91 and 205 GHz, temperature sounding near 118 GHz, and moisture sounding near 183 GHz. Spatial resolution at nadir will be around 27 km for temperature and 17 km for moisture and precipitation with a swath width of approximately 2,000 km from a 550-km orbit altitude. Both the spatial resolution and swath width are similar to the Advanced Technology Microwave Sounder (ATMS) that is being flown as part of the Suomi National Polar-orbiting Partnership (SNPP) and National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS). In addition, TROPICS meets many of the requirements outlined in the 2007 Decadal Survey for the Precision and All-Weather Tempera-ture and Humidity (PATH) mission, which was originally envisioned as a microwave instrument in geostationary orbit. TROPICS enables temporal resolution approaching that of geostationary orbit but at a much lower cost, demonstrating a technology that could impact the design of future Earth-observing missions. The satellites for the TROPICS mission were delivered to NASA in 2019 for launches planned in the 2021–2022 timeframe. The primary mission objective of TROPICS is to relate temperature, humidity, and precipitation structure to the evolution of tropical cyclone (TC) intensity.

remote sensing↗

DOE OSTI2019

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part I: Maritime Conditions

Zheng and Rosenfeld found linear relationships between the convective updrafts and cloud-base height z b using ground-based observations over both land and ocean. The empirical relationships allow for a novel satellite remote sensing technique of inferring the cloud-base updrafts and cloud condensation nuclei concentration, both of which are important for understanding aerosol–cloud–climate interactions but have been notoriously difficult to retrieve from space. In Part I of a two-part study, a theoretical framework is established for understanding this empirical relationship over the ocean. Part II deals with continental cumulus clouds. Using the bulk concept of mixed-layer (ML) model for shallow cumulus, I found that this relationship arises from the conservation law of energetics that requires the radiative flux divergence of an ML to balance surface buoyancy flux. Given a certain ML radiative cooling rate per unit mass Q, a deeper ML (higher z b ) undergoes more radiative cooling and requires stronger surface buoyancy flux to balance it, leading to stronger updrafts. The rate with which the updrafts vary with z b is modulated by Q. The cooling rate Q manifests strong resilience to external large-scale forcing that spans a wide range of climatology, allowing the slope of the updrafts– z b relationship to remain nearly invariant. This causes the relationship to manifest linearity. The physical mechanism underlying the resilience of Q to large-scale forcing, such as free-tropospheric moisture and sea surface temperature, is investigated through the lens of the radiative transfer theory (two-stream Schwarzschild equations) and an ML model for shallow cumulus.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Robertson, F. R.↗

NASA NTRS2003

A Climatology of Tropospheric CO over the Central and Southeastern United States and the Southwestern Pacific Ocean Derived from Space, Air, and Ground-based Infrared Interferometer Spectra

This final report summarizes all research activities and publications undertaken as part of NASA Atmospheric Chemistry and Modeling Analysis Program (ACMAP) Grant NAG-1-2022, 'A Climatology of Tropospheric CO over the Central and Southeastern United States and the Southwestern Pacific Ocean Derived from Space, Air, and Ground-based Infrared Interferometer Spectra'. Major project accomplishments include: (1) analysis of more than 300,000 AERI spectra from the ARM SGP site yielding a 5-year (1998-2002) timeseries of CO retrievals from the Lamont, OK AERI; (2) development of a prototype CO profile retrieval algorithm for AERI spectra; (3) validation and publication of the first CO retrievals from the Scanning High-resolution Interferometer Sounder (SHIS); and (4) development of a prototype AERI tropospheric O3 retrieval algorithm. Compilation and publication of the 5-year Lamont, OK timeseries is underway including a new collaboration with scientists at the Lawrence Berkeley National Laboratory. Public access to this data will be provided upon article submission. A comprehensive CO analysis of the archive of HIS spectra of remains as the only originally proposed activity with little progress. The greatest challenge faced in this project was motivating the University of Wisconsin Co-Investigators to deliver their archived HIS and AERIOO data along with the requisite temperature and water vapor profiles in a timely manner. Part of the supplied HIS dataset from ASHOE may be analyzed as part of a Master s Thesis under a separate project. Our success with the SAFARI 2000 SHIS CO analysis demonstrates the utility of such aircraft remote sensing data given the proper support from the instrument investigators. In addition to the PI and Co-I s, personnel involved in this CO climatology project include one Post Doctoral Fellow, one Research Scientist, two graduate students, and two undergraduate students. A total of fifteen presentations regarding research related to this project were delivered at eleven different scientific meetings. Thus far, three publications have resulted from this project with another five in preparation. No subject inventions resulted from this research project.

McMillian, W. Wallace↗

NASA NTRSDate not supplied

Analysis of CO Transport from Australia Fires and Its Impact to Ozone, Water Vapor and Clouds Using CrIS Single-Field-of-View Sounder Products and Other Remote Sensing and MERRA-2 Reanalysis Data

Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles, and the long-range transport of the smoke plumes poses great impact to climate change, such as altering the Antarctic ozone (O3) hole. Spaceborne observations from satellites have been proven successful in monitoring CO from wildfires in the past decade and can be used to examine the associated CO transport. The primary remote sensing data used in this study is the Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from the Cross-track Infrared Sounder (CrIS) on SNPP, a new product that will be generated at NASA and released to the public in a few months. SiFSAP has a high spatial resolution of ~14 km and includes atmospheric profiles of temperature, water vapor, CO, O3, as well as cloud products, and as the SiFSAP algorithm performs both day- and night-time retrievals, it provides an additional observation for night-time in comparison to the day-time-only solar polar satellite instruments such as MOPPIT, OMPS, and TROPOMI. Most recent significant improvements in the quality of this product plus its good spatial resolution (better than most global weather and climate models) enable us to conduct process-oriented analysis of CO transport, and the variation of water vapor, O3 and clouds (optical depth, effective radius and cloud height) within and around the fire plumes. The wind fields from MERRA-2 reanalysis will be used to help characterize the transport. Other remote sensing data, such as CO from AIRS, MOPPIT and TROPOMI, O3 from OMPS and TROPOMI, as well as the UV aerosol index from OMI and OMPS, will be used and compared with SiFSAP sounder products. Cross-validation of CO and O3 from these different sensors with the corresponding MERRA-2 products will also be carried out. Along the plume transport path, some enhancement of O3 and correlation between fire aerosol, cloud optical depth and water vapor have been found but need further investigation. Using the transport of fire plumes over the Southern Pacific Ocean as a unique testbed, this study will demonstrate the trace species monitoring capability of current satellite observations, in particular, for CO and O3, and hopefully, it will provide some insight on the impacts on fire emissions on air quality and climate.

Xiaozhen (Shawn) Xiong↗

DOE OSTI2025

Relative Contributions of Surface Parcel and Atmospheric Environment to Convective Potential during Interstorm Periods

Convective instability is affected by both surface heat fluxes into near-surface air parcels and the atmospheric profile encountered as these air parcels are lifted aloft. In this study, we investigate the evolution of buoyancy experienced by surface-based parcels, taking interstorm soil moisture drydowns as fundamental time periods. We use profile observations of atmospheric temperature and humidity from ground-based passive remote sensing and in situ observations available at the U.S. Department of Energy Atmospheric Radiation Measurement Southern Great Plains site in Oklahoma, United States, and examine drydown events during the warm seasons from 2017 to 2022. Results reveal new insights on the emergence and growth of convective available potential energy (CAPE) during drydowns. We observe that the peak convective potential appears in the afternoon and grows in the midtroposphere (68% of 66 drydown events), with the largest CAPE values toward the end of the drydown event. We also find that the near-surface parcel contributes more to the evolution of CAPE than the atmospheric environment (86% of drydown events). These findings highlight the importance of surface heat fluxes and moisture availability from surface-based parcels in modulating the evolution of atmospheric conditions favorable for convection, underscoring the interplay between surface processes and atmospheric dynamics in driving convective instability.

Atmosphere-land interaction↗

NASA NTRS2012

Onboard Science and Applications Algorithm for Hyperspectral Data Reduction

An onboard processing mission concept is under development for a possible Direct Broadcast capability for the HyspIRI mission, a Hyperspectral remote sensing mission under consideration for launch in the next decade. The concept would intelligently spectrally and spatially subsample the data as well as generate science products onboard to enable return of key rapid response science and applications information despite limited downlink bandwidth. This rapid data delivery concept focuses on wildfires and volcanoes as primary applications, but also has applications to vegetation, coastal flooding, dust, and snow/ice applications. Operationally, the HyspIRI team would define a set of spatial regions of interest where specific algorithms would be executed. For example, known coastal areas would have certain products or bands downlinked, ocean areas might have other bands downlinked, and during fire seasons other areas would be processed for active fire detections. Ground operations would automatically generate the mission plans specifying the highest priority tasks executable within onboard computation, setup, and data downlink constraints. The spectral bands of the TIR (thermal infrared) instrument can accurately detect the thermal signature of fires and send down alerts, as well as the thermal and VSWIR (visible to short-wave infrared) data corresponding to the active fires. Active volcanism also produces a distinctive thermal signature that can be detected onboard to enable spatial subsampling. Onboard algorithms and ground-based algorithms suitable for onboard deployment are mature. On HyspIRI, the algorithm would perform a table-driven temperature inversion from several spectral TIR bands, and then trigger downlink of the entire spectrum for each of the hot pixels identified. Ocean and coastal applications include sea surface temperature (using a small spectral subset of TIR data, but requiring considerable ancillary data), and ocean color applications to track biological activity such as harmful algal blooms. Measuring surface water extent to track flooding is another rapid response product leveraging VSWIR spectral information.

Chien, Steve A.↗

NASA NTRS2004

High Spectral Resolution MODIS Algorithms for Ocean Chlorophyll in Case II Waters

The Case 2 chlorophyll a algorithm is based on a semi-analytical, bio-optical model of remote sensing reflectance, R(sub rs)(lambda), where R(sub rs)(lambda) is defined as the water-leaving radiance, L(sub w)(lambda), divided by the downwelling irradiance just above the sea surface, E(sub d)(lambda,0(+)). The R(sub rs)(lambda) model (Section 3) has two free variables, the absorption coefficient due to phytoplankton at 675 nm, a(sub phi)(675), and the absorption coefficient due to colored dissolved organic matter (CDOM) or gelbstoff at 400 nm, a(sub g)(400). The R(rs) model has several parameters that are fixed or can be specified based on the region and season of the MODIS scene. These control the spectral shapes of the optical constituents of the model. R(sub rs)(lambda(sub i)) values from the MODIS data processing system are placed into the model, the model is inverted, and a(sub phi)(675), a(sub g)(400) (MOD24), and chlorophyll a (MOD21, Chlor_a_3) are computed. Algorithm development is initially focused on tropical, subtropical, and summer temperate environments, and the model is parameterized in Section 4 for three different bio-optical domains: (1) high ratios of photoprotective pigments to chlorophyll and low self-shading, which for brevity, we designate as 'unpackaged'; (2) low ratios and high self-shading, which we designate as 'packaged'; and (3) a transitional or global-average type. These domains can be identified from space by comparing sea-surface temperature to nitrogen-depletion temperatures for each domain (Section 5). Algorithm errors of more than 45% are reduced to errors of less than 30% with this approach, with the greatest effect occurring at the eastern and polar boundaries of the basins. Section 6 provides an expansion of bio-optical domains into high-latitude waters. The 'fully packaged' pigment domain is introduced in this section along with a revised strategy for implementing these variable packaging domains. Chlor_a_3 values derived semi-analytically and Chlor_a_2 values derived empirically using the O Reilly et al. OC3M algorithm from MODIS Terra radiances are compared to field chlorophyll-a concentrations in Sections 7 and 8.

Carder, Kendall L.↗