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NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) in the Goddard Earth Observing System (GEOS), which is used for weather, climate, and air quality forecasts and producing reanalysis datasets, it is necessary to validate the observing system in JEDI. NASA’s Global Modeling and Assimilation Office (GMAO), with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) and adding all the necessary features to replicate existing capability. Various satellite and conventional observations are assimilated by the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures including the GEOS all-sky microwave radiance assimilation framework to assimilate those observation in UFO. Robust tests are conducted to ensure correct configurations of observational data bias correction (BC), quality control (QC), and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations is reported in this presentation.

Jianjun Jin↗

NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).

Brett Raczka↗

NASA NTRSDate not supplied

Models, In situ, and Remote sensing of Aerosols (MIRA)

There is a natural partitioning of scientific interest amongst three specialties of aerosol research: modeling, in situ measurements, and remote sensing. The community sees enhanced measurement capabilities when these groups interact, and this strengthens the overall scientific impact on climate and air quality. The Models, In situ, and Remote sensing of Aerosols (MIRA) working group connects members of the different aerosol communities through collaborative projects. What is MIRA? MIRA is a forum that fosters international collaborations amongst the aerosol specialties. MIRA is also a collection of interdisciplinary projects with clear goals that are pursued by small working groups. Finally, MIRA projects are generally characterized by requests for additional scientific data (both observational and modeled). Why? The purpose of MIRA is to contextualize both observations and model results through the encouragement of holistic projects and collaborations. How does MIRA differ from other projects? MIRA focuses on interdisciplinarity to improve measurements and their utility, so MIRA complements the activities of other groups. For example, ensemble model runs of AeroCom could be used in a MIRA project with greater robustness than a similar effort that uses single-model analyses. We present a description of MIRA and brief descriptions of some of the current MIRA topics, which include Satellite-Assisted Particulate Matter (SAPM), Mapping of Aerosol lidar ratios for CALIPSO (MAC), Tables of Aerosol Optics (TAO), and the Harmonization of aerosol Assimilation Models and Retrievals (HAMR). Finally, we discuss the immediate science goals and organization of MIRA. See https://science.larc.nasa.gov/mira-wg/ for more information.

Travis Toth↗

NASA NTRSDate not supplied

The Transition of Satellite Observations Assimilated in GEOS to JEDI

The Goddard Earth Observing System (GEOS) is used by NASA’s Global Modeling and Assimilation Office (GMAO) to produce weather, climate, and air quality forecasts and reanalysis datasets. In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) system into GEOS it is necessary to provide a validated set of input observations in JEDI. The GMAO, in collaboration with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) in JEDI and adding all the necessary features to replicate the existing capability of the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures to assimilate the vast array of satellite and conventional observations assimilated in GEOS, including the GEOS all-sky microwave radiance assimilation framework to assimilate those observations in the UFO. Robust tests have been conducted to ensure correct configurations of observational data bias correction, quality control, and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations will be reported in this presentation.

Jianjun Jin↗

NASA NTRSDate not supplied

Satellite Data Assimilation in the GEOS Atmospheric Data Assimilation System

Jianjun Jin↗

NASA NTRSDate not supplied

All-sky Microwave Radiance Assimilation in The GEOS Atmospheric Reanalysis for The Early 21st Century (GEOS-21C)

The Goddard Earth Observing System (GEOS) is used for weather, climate, and air quality forecasts and producing reanalysis datasets. Its atmospheric data assimilation system (ADAS) is a hybrid–4DEnVar system. Various satellite radiance, atmospheric motion vector (winds), aircraft, and convectional data are assimilated by this system to produce global atmospheric states. Satellite data assimilation within GEOS ADAS is enhanced by considering correlated observational errors among infrared radiance observations and assimilating new microwave radiance data in all-sky conditions since the release of the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). These new microwave radiance data include brightness temperature measurements made by the Global Precipitation Mission (GPM) microwave imager (GMI) and Advanced Microwave Scanning Radiometer 2 / Global Change Observation Mission 1st – Water (AMSR2/GCOM-W). Historical microwave radiance data made by various Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) aboard the Aqua satellite are tested within the all-sky microwave radiance assimilation framework in the preparation of the GEOS enhanced Atmospheric Reanalysis for the early 21st century (GEOS-21C). Assimilation of these data in all-sky conditions enhances use of other satellite data and improves GEOS analysis and forecast. In this talk, we will present the procedures of to assimilate microwave radiance data in all-sky conditions and their impact on atmospheric analysis in the preparation of GEOS-21C.

Jianjun Jin↗

NASA NTRSDate not supplied

CALIGOLA: A New Multidisciplinary Spaceborne Lidar Mission (Cloud Aerosol Lidar for Global scale Observations of the ocean-Land-Atmosphere system)

Spaceborne lidars provide unique and valuable insight into the vertical structure of clouds and aerosols over the globe as well as insight into their microphysical and optical properties. Over the past two decades, lidar observations from CALIPSO, ICESAT-2 and CATS fundamentally advanced our understanding of the roles of clouds and aerosols play in weather, climate and air quality. The measurement records further served as important references for validating and improving retrieval algorithms of cloud/aerosol properties from operational weather satellites. A more recent development is the emerging awareness on how spaceborne lidar profile observations can also enhance knowledge of Earth’s coupled atmosphere-ocean-land system. Here we report on a new and powerful spaceborne lidar mission concept known as CALIGOLA (Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System). The mission is multidisciplinary and will provide new insights into atmospheric processes with advance measurement capabilities beyond CALIPSO and the recently launched EarthCARE mission. CALIGOLA will further provide the first profiling of the world’s oceans to reveal unprecedented observations on the health and productivity of marine biology (phytoplankton and zooplankton) as well as provide unique observations of surface vegetation, ice, and snow. The mission will feature an innovative three-wavelength lidar, that will simultaneously acquire elastic backscatter, Raman, and fluorescence measurements, with polarization sensitivity on the elastic channels. The instrument is further designed with greater sensitivity than CALIOP and with vertical resolution on the order of a few meters near the surface. The mission is planned for launch early next decade and is baselined to fly in a polar orbit that is compatible with the previous A-Train constellation to extend the long-term measurement record. CALIGOLA is being developed through a partnership between Agenzia Spaziale Italiana (ASI) and National Aeronautics and Space Administration (NASA).

Lidar Aerosols Clouds Ocean Biology↗

NASA NTRSDate not supplied

Towards Assimilation of Satellite Derived Aerosol Optical Centroid Height in the NASA’s Goddard Earth Observing System (GEOS) Model: Case Studies

Aerosol vertical distribution plays an important role in determining aerosol effects on the weather, climate and air quality, but is one of the largest uncertainties in current global chemistry transport models. Operational datasets of global aerosol vertical distribution from observational sources that could constrain models are not adequate.

Santiago Gasso↗

DOE OSTI2023

Reliability and Decarbonization Resource Adequacy and Resilience

The Electric Power Transformation: 2023 MEGA Symposium has a focus on the transition of the energy generation industry to cleaner and climate resilient electric power that can remain cost-effective and reliable. Electric power energy issues abound as the world and the industry address environmental policy challenges—climate change, air quality, waste and water policy, environmental justice, and Environmental Social Governance —and various technology issues related to energy production and delivery, including the latest cutting-edge options. This presentation discusses reliability and decarbonization of the power sector with a focus on resource adequacy and resilience.

Balash, Peter↗

NASA NTRS1997

The Climate Signal in Regional Moisture Fluxes: A Comparison of Three Global Data Assimilation Products

This study assesses the quality of estimates of climate variability in moisture flux and convergence from three assimilated data sets: two are reanalysis products generated at the Goddard Data Assimilation Office (DAO) and the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEPJNCAR), and the third consists of the operational analyses generated at the European Center for Medium Range Forecasts (ECMWF). The regions under study (the United States Great Plains, the Indian monsoon region, and Argentina east of the Andes) are characterized by frequent low level jets (LLJs) and other interannual low level wind variations tied to the large-scale flow. While the emphasis is on the reanalysis products, the comparison with the operational product is provided to help assess the improvements gained from a fixed analysis system. All three analyses capture the main moisture flux anomalies associated with selected extreme climate (drought and flood) events during the period 1985-93. The correspondence is strongest over the Great Plains and weakest over the Indian monsoon region reflecting differences in the observational coverage. For the reanalysis products, the uncertainties in the lower tropospheric winds is by far the dominant source of the discrepancies in the moisture flux anomalies in the middle latitude regions. Only in the Indian Monsoon region, where interannual variability in the low level winds is comparatively small, does the moisture bias play a substantial role. In contrast, the comparisons with the operational product show differences in moisture which are comparable torhe differences in the wind in all three regions. Compared with the fluxes, the anomalous moisture convergences show substantially larger differences among the three products. The best agreement occurs over the Great Plains region where all three products show vertically-integrated moisture convergence during the floods and divergence during the drought with differences in magnitude of about 25%. The reanalysis products, in particular, show good agreement in depicting the different roles of the mean flow and transients during the flood and drought periods. Differences between the three products in the other two regions exceed 100% reflecting differences in the low level jets and the large scale circulation patterns. The operational product tends to have locally larger amplitude convergence fields which average out in area-mean budgets: this appears to be at least in part due to errors in the surface pressure fields and aliasing from the higher resolution of the original ECMWF fields. On average, the reanalysis products show higher coherence with each other than with the operational product in the estimates of interannual variability. This result is less clear in the Indian monsoon region where differences in the input observations appears to be an important factor. The agreement in the anomalous convergence patterns is, however, still rather poor even over relatively data dense regions such as the United States Great Plains. These differences are attributed to deficiencies in the assimilating GCM's representations of the planetary boundary layer and orography, and a global observing system incapable of resolving the highly confined low level winds associated with the climate anomalies.

Min, Wei↗

NASA NTRS2015

Reforestation and Crop Land Conversion Impacts on Future Regional Air Quality in the Southeastern U.S.

Land in the southeastern U.S. is expected to change, e.g., given the potential demand to develop forest-to-fuel technologies or, conversely, cropification of current forests to increase food production. Possible future PM(sub 2.5) and O3 air quality for two land use/land cover change (LULCC) scenarios, reforestation and cropland conversion, are compared to a reference case scenario for the year 2050 using the Weather Research and Forecasting (WRF) and Community Multi-scale Air Quality (CMAQ) models. Changes in air quality driven by changes in climate, deposition and emissions relating to the LULCC are investigated. Reforestation in the Southeast tends to decrease the ambient O3mixing ratio while slightly increasing summertime PM(sub 2.5) in the Southeastern U.S. Results of a climate and deposition (CD) sensitivity simulation are provided for the two alternative LULCC scenarios to isolate the impact of changing climate and deposition on PM(sub 2.5) and O3 air quality. The sensitivity results indicate that deposition and emissions changes associated with reforestation impact O3 and PM(sub 2.5concentrations as much as, and in most cases more than, changes in meteorology. Conversion of forest to cropland in the Southeast, on the other hand, tends to increase O3and increase PM(sub 2.5) year-round. Cropland conversion leads to increased NOX emissions and increases in the 4th highest maximum daily 8-h O3(MDA8) of the year by up to 10 ppb despite the tendency for increased deposition and decreased temperature to reduce the MDA8 mixing ratio. The results of this study show that O3and aerosol concentrations are sensitive to reforestation and cropland conversion in the Southeast and these land use changes should be considered in air quality management plans. Further, they show the sensitivity of such calculations to land cover properties.

deposition↗

NASA NTRS2020

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

DOE OSTI2023

Mechanical Ventilation and Indoor Air Quality in Recently Constructed U.S. Homes in Marine and Cold-Dry Climates Data from Building America Project

Data were collected to characterize whole-house mechanical ventilation (WHMV) and indoor air quality (IAQ) in 55 homes in the Marine climate of Oregon and Cold-Dry climate of Colorado in the U.S. Sixteen homes were monitored for two weeks, with and without WHMV operating. Ventilation airflows; airtightness; time-resolved CO2, PM2.5 and radon; and time-integrated NO2, NOX and formaldehyde were measured. Participants provided information about IAQ-impacting activities, perceptions and ventilation use. All homes had operational cooktop ventilation and bathroom exhaust. Thirty homes had equipment that could meet the ASHRAE 62.2-2010 standard with continuous or controlled runtime and 34 had some WHMV operating as found. Thirty-five of 46 participants with WHMV reported they did not know how to operate it, and only half of the systems were properly labeled. Two-week homes had lower formaldehyde, radon, CO2, and NO (NOX-NO2) when operated with WHMV; and also had faster PM2.5 decays following indoor emission events. Overall IAQ satisfaction was similar in Oregon and Colorado, but more Colorado participants (19 vs. 3%) felt their IAQ could be improved and more reported dryness as a problem (58 vs. 14%). The collected data indicate that there are benefits of operating WHMV, even when continuous use may not be needed because outdoor pollutant concentrations are low and indoor sources do not present substantial challenges.

air quality↗

NASA NTRS1994

Quality control concept and recent developments of the light climatic observatory at Arosa: Ozone measuring station of the Swiss Meteorological Institute (LKO)

Total ozone observations of two Dobson instruments (D15 and D101, C- and AD wavelength pair observations) and of two Brewer instruments (Br40 and Br72) are currently performed at the LKO at Arosa. A quality control concept is presented in order to make best use of the large number of quasi-simultaneous measurements. The longest ozone series of the world is mainly based on the measurements of the Dobson instrument D15 (wavelength pair C). Since the last years D15 has suffered from instrumental problems. The transformation of the longterm series to the measurements of D101(AD) is described.

Hoegger, Bruno↗

NASA NTRS2012

JPL's Role in Advancing Earth System Science to Meet the Challenges of Climate and Environmental Change

Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Earth observations↗

DOE OSTI2021

Pathways of China's PM 2.5 air quality 2015–2060 in the context of carbon neutrality

Clean air policies in China have substantially reduced particulate matter (PM 2.5 ) air pollution in recent years, primarily by curbing end-of-pipe emissions. However, reaching the level of the World Health Organization (WHO) guidelines may instead depend upon the air quality co-benefits of ambitious climate action. Here, we assess pathways of Chinese PM 2.5 air quality from 2015 to 2060 under a combination of scenarios that link global and Chinese climate mitigation pathways (i.e. global 2°C- and 1.5°C-pathways, National Determined Contributions (NDC) pledges and carbon neutrality goals) to local clean air policies. We find that China can achieve both its near-term climate goals (peak emissions) and PM 2.5 air quality annual standard (35 μg/m3) by 2030 by fulfilling its NDC pledges and continuing air pollution control policies. However, the benefits of end-of-pipe control reductions are mostly exhausted by 2030, and reducing PM 2.5 exposure of the majority of the Chinese population to below 10 μg/m 3 by 2060 will likely require more ambitious climate mitigation efforts such as China's carbon neutrality goals and global 1.5°C-pathways. Our results thus highlight that China's carbon neutrality goals will play a critical role in reducing air pollution exposure to the level of the WHO guidelines and protecting public health.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗

NASA NTRS1990

Solar Activity and the Sea-surface Temperature Record-evidence of a Long-period Variation in Solar Total Irradiance

There have been many suggestions over the years of a connection between solar activity and the Earth's climate on time scales long compared to the 11-year sunspot cycle. They have remained little more than suggestions largely because of the major uncertainties in the climate record itself, and the difficulty in trying to compile a global average from an assembly of measurements that are uneven in both quality and distribution. Different climate time response to solar activity, some suggesting a positive correlation, some a negative correlation, and some no correlation at all. The only excuse for making yet another such suggestion is that much effort has been devoted in recent years to compiling climate records for the past century or more that are internally consistent and believable, and that a decadal-scale record of solar total irradiance is emerging from spacecraft measurements, and can be used to set limits on the variation that is likely to have occurred on these time scales. The work described here was originally inspired by the observation that the time series of globally averaged sea-surface temperatures over the past 120 years or so, as compiled by the British Meteorological Office group (Folland and Kates, 1984), bore a resonable similarity to the long-term average sunspot number, which is an indicator of the secular variability of solar activity. The two time series are shown where the sunspot number is shown as the 135-month running mean, and the SST variation is shown as the departure from an arbitrary average value. The simplest explanation of the similarity, if one accepts it as other than coincidental, is that the sun's luminosity may have been varying more or less in step with the level of solar activity, or in other words that there is a close coupling between the sun's magnetic condition and its radiative output on time scales longer than the 11-year cycle. Such an idea is not new, and in fact the time series shown can be regarded as a modern extension of the proposal put forward by Eddy (1977) to explain the covariance between various global climate indicators and solar activity as revealed by the C-14 record over the past millenium.

Reid, George C.↗