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At least 235 records · Page 13
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NASA NTRS1992

Multiple dataset water-quality analyses in the vicinity of an ocean wastewater plume

The White's Point ocean outfall is the method of disposal for approximately 374 million gallons of treated wastewater per day from Los Angeles County. The photosynthetic characteristics and particle distributions have well-defined properties that can be exploited to yield information on transport of the plume, mixing dynamics, and resuspension of bottom sediments during periods of bottom current velocity in excess of ca. 0.1 m/s. This plume of particles serves as a conservative tracer, which was studied using a number of sampling platforms and strategies, including underway sawtooth, or 'tow-yo' sampling, moored arrays of instruments, stationary profiling, and now for the first time with remotely-sensed multispectral color imagery. Research in this area previously focused on examination of the plume as it relates to the local current field and transport of particles, and on the resuspension of bottom sediments during periods of increased currents. In addition, Wu et al elucidated techniques for separating the particle signal into photosynthetic and nonphotosynthetic components, based on the beam attenuation to chlorophyll fluorescence ratio. High-frequency time series measurements of the current field and bio-optical characteristics at a site close to the waste diffusers were also collected. These are being analyzed for the spectral characteristics of the longer-timescale variability, in order to predict particle transport through simple meteorological measurements. With the advent of high spectral and spatial resolution imaging spectrometers such as AVIRIS, it is now possible to construct causal relationships between particle distributions and signature of the upwelled radiance from the surface. The availability of a constant and well-characterized source of material lends itself well to models which predict upwelled radiance from the surface. The availability of a constant and well-characterized source of material lends itself well to models which predict upwelled light as a function of particle distributions, photosynthetic pigments, colored dissolved organic material, and detrital and degradation products of photosynthesis. In addition, the spatial coverage provided by the tow-yo sampling device, combined with the profile measurements of the light field, should facilitate the best inverse modeling attempts possible thus far.

Hamilton, Michael↗
NASA NTRS2004

[Analysis of Multiplatform CO (Carbon Monoxide) Measurements During Trace-P Mission]

Carbon monoxide is considered mission critical (TRACE-P NRA) because it is one of the gases involved in controlling the oxidizing power of the atmosphere and, as a tracer gas, is valuable in interpreting mission data sets. Carbon monoxide exhibits interannual differences, suggesting relatively short-term imbalances in sources and sinks. Sources of CO are dominated by fossil fuel combustion, biomass burning, and the photochemical oxidation of CH4 and nonmethane hydrocarbons while reaction with OH is believed to be the major sink for atmospheric CO, with additional losses due to soil uptake. Uncertainties in the magnitude and distribution of both sources and sinks remain fairly large however, and additional data are required to refine the global budget. Seasonal changes and a northern hemispheric latitudinal gradient have been described for a variety of Pacific basin sites through long-term monitoring of surface background levels. Latitudinal variations have also recently been described at upper tropospheric altitudes over a multi-year period by. TRACE-P will provide an aircraft survey of CO over the northern Pacific in the northern spring when CO concentrations are at their seasonal maximum in the northern hemisphere (NH) and at their seasonal minimum in the southern hemisphere (SH). Previous GTE missions, Le., PEM West-B and PEM Tropics-B, ground-based, and satellite observations (MAPS, April 1994) give us a general picture of the distribution of CO over the northern Pacific during this season. Based on these measurements, background CO levels over remote ocean areas are anticipated to be in the range of 110 - 180 ppbv, while those closer to the Asian continent may rise as high as 600 ppbv. These measurements also reveal high spatial variability (both horizontal and vertical) as well as temporal variations in CO over the area planned for the TRACE-P mission. This variability is a result of multiple CO sources, the meteorological complexity of transport processes, and the photochemical aging of air masses. The influence of biomass burning in the southern Pacific should be relatively small since the mission coincides with the southern tropical wet season when agricultural burning is at its seasonal low. The proposed CO measurements taken during TRACE-P should therefore largely be a function of the impact of various NH sources, primarily Asian and predominantly fossil fuel combustion and biomass burning. These processes are also major sources of many other atmospheric pollutants, consequently making accurate and precise CO measurements is one of the highest TRACE-P priorities [TRACE-P NRA]. The TRACE-P mission emphasizes the dual objectives of assessing the magnitude of the transport of chemically and radiatively important gases such as CO from Asia to the western Pacific, and determining how emissions change and are modified during this transport.

Pougatchev, Nikita S.↗
NASA NTRS2016

Large Gain in Air Quality Compared to an Alternative Anthropogenic Emissions Scenario

During the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistrytransport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the yearto- year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy.

Law (Jurisprudence)↗
NASA NTRS2020

Constraining Fossil Fuel CO2 Emissions from Urban Area Using OCO-2 Observations of Total Column CO2

Satellite observations of the total column dry-air CO2(XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals to optimize whole-city emissions, using a Bayesian inversion system and high-resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: “plume city” located in relatively flat terrain, represented by Riyadh and Cairo; “basin city” located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least number of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 5, 8, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.

Xinxin Ye↗
NASA NTRS2020

Ensemble-Based Deep Learning for Estimating PM2.5 over California with Multisource Big Data Including Wildfire Smoke

Estimating PM2.5 concentrations and their prediction uncertainties at a high spatiotemporal resolution is important for air pollution health effect studies. This is particularly challenging for California, which has high variability in natural (e.g. wildfires, dust) and anthropogenic emissions, meteorology, topography (e.g. desert surfaces, mountains, snow cover) and land use.

air quality↗
NASA NTRS2021

PRELIMINARY MODEL FOR SOIL MOISTURE RETRIEVAL USING P-BAND RADIOMETER OBSERVATIONS

Soil Moisture is an important geophysical variable that needs reliable quantification for applications in hydrology, meteorology and agriculture. L-band radiometry has proved to be one of the best methods in soil moisture estimation using microwave signals. However, they provide measurements that correspond to a shallow depth of 5 cm and are also affected by the presence of overlaying vegetation and roughness. In contrast, P-band radiometry is expected to provide moisture information on a deeper layer of soil. Moreover, these lower frequency measurements are expected to be less affected by soil roughness and vegetation contributions. Consequently, this pilot study uses the Polarimetric P-band Multi beam Radiometer(PPMR) at 740 MHz to evaluate the response of theP-band radiometer over a realistic range of surface condition sat the field scale. A preliminary framework of P-band MicrowaveEmission of theBiosphere (P-MEB) has been developed as a forward model that simulates brightness temperature from soil moisture and other ancillary data collected from the field. This paper presents the model for the bare soil condition observed during June 2018 to August 2018. The results show that H-polarized PPMR data has better correlation to the soil moisture over a depth of 10 cm than the V-polarized PPMR data. A model is under improvement by incorporating a more suitable effective temperature formulation.

Edward J Kim↗
NASA NTRSDate not supplied

The Influence of Sea ice on Arctic Cloud Properties: What Can We Learn by Applying a In Situ Observational Strategy to Satellite Data?

Sea ice is declining because of anthropogenic climate change. This change alters many aspects of the Arctic climate system, including the way that the surface and atmosphere interact. Atmosphere-surface coupling processes represent an important cloud feedback mechanism that can alter the Arctic surface energy budget. For the Arctic, it has been hypothesized that a reduction in sea ice cover could lead to an increase in clouds. If this process were to occur as originally hypothesized, sea ice loss in all seasons would lead to an increase in clouds. Recent observational studies find a cloud response to sea ice loss in non-summer months and no cloud response in summer months. However, previous studies rely on inter-annual variability and reanalysis to control for the influence of meteorology, reducing the confidence in the resulting conclusions. We adopt a phenomenological, event-based approach that does not need to use meteorological reanalysis. The approach analyzes cloud properties derived from CALIPSO-CloudSat over sea ice and adjacent ice-free footprints by compositing individual satellite ground tracks that cross the Arctic sea ice edge. The underlying assumption, which we verify, is that footprints that are close to each other in space and time experience similar large-scale meteorological conditions. Our results show larger cloud fraction and more cloud liquid water over ice-free than over sea ice footprints and provide additional evidence for a seasonal dependence of cloud-sea ice coupling that is in line with previous work. We find a different result where the maximum cloud property differences between sea ice and ice-free ocean occurs in spring, not fall as earlier studies suggest. We argue that these cloud differences between sea ice and ice-free ocean are primarily caused by the influence of the surface type on the thermodynamic stability of the lower troposphere and not principally from an increase in surface evaporation. In addition, we explore the sensitivity of these results to marginal ice zone width, season, Atlantic vs. Pacific sector, and the cloud property dependence on the distance from the sea ice edge. Overall, our results provide further evidence that cloud-sea ice coupling processes are not offsetting the observed surface energy budget perturbation due to sea ice loss in summer; thus, the cloud response to declining sea ice appears to contribute to amplified Arctic warming.

Patrick C Taylor↗
NASA NTRSDate not supplied

Seasonal and Dayurnal Planetary Albedo Variability from Six Years of DSCOVR EPIC Data

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar radiation from the Lissajous orbital position near the Lagrangian L1 point provide continuous monitoring of the Earth’s sunlit hemisphere. CERES-based angle models were used to convert the near-hourly reflected radiances of the EPIC images into a climate-style planetary albedo data-point over the sunlit hemisphere. Integration over the sunlit hemispheres averages out the meteorological weather noise, but retains the seasonal and planetary-scale variability. As the Earth rotates, this generates variations in the Earth’s planetary albedo that are precisely aligned in longitude, which constitutes the dayurnal cycle. This dayurnal variability in the planetary albedo arises from planetary-scale changes in cloud radiative properties that can be directly compared to similarly sampled climate GCM output data. Six years of EPIC data have been analyzed, showing characteristic patterns in the seasonal and dayurnal variability of the Earth’s planetary albedo. Much of the seasonal change in planetary albedo is associated with the changing DSCOVR viewing geometry and the change in solar declination. But throughout the year, the highest planetary albedos are observed over the Central Asia (Iraq) longitude, while the lowest planetary albedos occur over the Central Pacific longitude. For these longitudes, the relative seasonal changes in the planetary albedo are slowly varying and anti-correlated. Dayurnal amplitude maxima tend to occur during the July-September timeframe, with April-May and December exhibit distinct minima in the dayurnal amplitude. West Africa and the West Pacific longitudes likewise exhibit anti-correlated seasonal variability, while they also undergo anti-correlated short period oscillations. On the other hand, in nearby longitudes, there are short period spikes in planetary albedo of a few-days duration, as well as longer period oscillations that may range from a week to several months, that generally tend to be correlated.

Planetary Albedo↗
NASA NTRSDate not supplied

Simultaneous lidar profiling of water vapor, aerosol, and wind over the eastern Pacific and implications for observational challenges on clouds, circulation, and climate sensitivity

Moist convective processes and related circulations are key components of the Earth’s climate system. Improving our understanding of moisture and cloud processes over oceans is especially challenging due to observational limitations, but also important due to the large radiative effects of cloud over ocean as well as the ties to local and global-scale circulations. A unique dataset for addressing these topics was collected over 5 flights with the NASA HALO (water vapor DIAL and aerosol HSRL) and DAWN (Doppler wind) lidar systems onboard the NASA DC-8 aircraft during the spring 2019 ADM-Aeolus Cal/Val test flight campaign. High-resolution water vapor, aerosol/cloud, and wind profiles were simultaneously collected and complimented with in situ high-resolution dropsonde measurements of temperature, relative humidity, and wind profiles. Airborne lidar measurements of these key variables captured both large-scale spatial variability across different cloud and atmospheric conditions as well as finer features, providing insight into processes from large-scale circulations down to aerosol/cloud interactions. The 5 flights spanned the northeast Pacific and southwest U.S. from 6 N to 52 N and 112 W to 157 W and captured several features of interest including moist layers from the ascending region of the Hadley circulation, very dry layers above midlatitude marine stratocumulus and cloud-free planetary boundary layers, and cloud top height and spatial variability. High covariance of aerosol and water vapor in the free troposphere was also observed for the first time. Preliminary analysis of these data sets will be presented as they apply to clouds and circulations, supplemented by model reanalysis to inform how regional water vapor structure and large-scale motion may contribute to observed shallow cloud formations and other meteorological processes that underpin our current understanding of how these state variables couple to impact the Earth’s weather and climate systems. The potential of complementary measurements in future field campaigns will also be mentioned.

Brian James Carroll↗
NASA NTRS2000

Mid-Latitude Atmospheric Variability Between 20-60 KM from Rocketsonde Measurements

The information obtained from deployment of instrumented meteorological rockets provides middle atmospheric data in a region that is difficult to measure by other means. In the last two decades, in-situ measurements of the middle atmosphere have become less frequent and only originate from a handful of locations. However, the value of these measurements continues to be proven through the validation of remote sensing techniques, support of other payloads sampling the region, and as importantly, the continued study of the rocket datasets with the details and trends that they hold. Wallops Island (37.8 N, 75.5 W) has one of the longest meteorological rocket data records available with relatively few system changes. Two particular periods from this record are studied: (1) January/February and (2) July/August, 1977. Both data sets consist of Super-Loki meteorological rockets with a Datasonde and Starute payload, which yield temperature and wind profiles. The January/February set consists of almost daily launches with days with multiple launches interspersed through January. In the July/August set, rockets were launched for thirty consecutive days at nearly the same time daily from Wallops Island. This campaign was immediately followed by sets of multiple launches with up to six launches per day separated by hours and in some cases minutes. The unique nature of the data allows a detailed examination of the atmosphere's short-term variability. These results are compared to the current views of middle atmospheric dynamics and turbulence from altitudes in the range of 20-60 km.

Schauer, A. G.↗
NASA NTRS1984

Variational objective analyses for cyclone studies

The basic analysis equations, i.e., the two horizontal momentum equations, the hydrostatic equation, and the integrated continuity equation were derived for the nonlinear vertical coordinate, nondimensionalized, and expressed in finite differences on a staggered grid. Special care was taken to transform the hydrostatic equation and the pressure gradient terms of the horizontal momentum equations to nearly eliminate truncation error over steeply sloping terrain. This formulation also eliminated explicit reference to orographically induced variations in the thermodynamic variables so that the variational adjustments are on the scale of the meteorological perturbations. The analysis equations were subjected to the Euler-Lagrange operations as expressed for finite differences and an additional set of five partial differential equations was derived, bringing to nine the number of equations in Model I. Higher order terms, terms containing observed quantities, and terms containing none of the variables to be adjusted were grouped into forcing functions and the equations were solved for the zero order terms. Zero order variables were eliminated between these equations and there resulted two diagnostic equations which take the form of general linear second order partial differential equations with nonconstant coefficients.

Achtemeier, G. L.↗
NASA NTRS2014

Peru Water Resources: Integrating NASA Earth Observations into Water Resource Planning and Management in Perus La Libertad Region

Developing countries often struggle with providing water security and sanitation services to their populations. An important aspect of improving security and sanitation is developing a comprehensive understanding of the country's water budget. Water For People, a non-profit organization dedicated to providing clean drinking water, is working with the Peruvian government to develop a water budget for the La Libertad region of Peru which includes the creation of an extensive watershed management plan. Currently, the data archive of the necessary variables to create the water management plan is extremely limited. Implementing NASA Earth observations has bolstered the dataset being used by Water For People, and the METRIC (Mapping EvapoTranspiration at High Resolution and Internalized Calibration) model has allowed for the estimation of the evapotranspiration values for the region. Landsat 8 imagery and the DEM (Digital Elevation Model) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor onboard Terra were used to derive the land cover information, and were used in conjunction with local weather data of Cascas from Peru's National Meteorological and Hydrological Service (SENAMHI). Python was used to combine input variables and METRIC model calculations to approximate the evapotranspiration values for the Ochape sub-basin of the Chicama River watershed. Once calculated, the evapotranspiration values and methodology were shared Water For People to help supplement their decision support tools in the La Libertad region of Peru and potentially apply the methodology in other areas of need.

Padgett-Vasquez, Steve↗
NASA NTRSDate not supplied

Maintaining the Continuity of the Global Climate Data Record of Lightning from Space

Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.

Timothy Lang↗
NASA NTRSDate not supplied

Use of Aerosol Observations From Aircraft in Satellite Remote Sensing and Modelling Comparisons

Aerosol extensive and intensive properties vary throughout the world and remain one of the largest uncertainties in determining future climate both because of difficulties in their measurement and their modelled behaviors. Here we highlight the contributions of airborne sampling by the sunphotometer 4STAR (Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) from two different parts of the world; Korean peninsula and region during the KORUS-AQ experiment (KORean-US Air Quality in May-June 2016) and over the South East Atlantic during ORACLES (ObseRvations of CLouds above Aerosols and their intEractionS in August-September-October 2016, 2017, and 2018) field campaign. The high temporal and spatial resolution, afforded by airborne sampling during KORUS-AQ, are used to determine the variability of aerosol intensive and extensive properties, which is a metric than can be compared in between multiple different observations and models, even over varying surfaces and spanning multiple different aerosol emission sources. We show the consistency over spatial scales of the AOD (Aerosol Optical Depth), and the aerosol intensive properties (Angstrom exponent - AE, fine mode fraction - FMF) observed by 4STAR, GOCI (Geostationary Ocean Color Imager Yonsei aerosol retrieval v2), MERRA-2 reanalysis (Modern-Era Retrospective Analysis for Research and Applications, v2), and from airborne in situ aerosol optical measurements by LARGE (NASA Langley Aerosol Research Group Experiment). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km and is dependent on the prevailing meteorological conditions. AE and FMF are found to be more spatially variable than AOD during all of KORUS-AQ, even when accounting for potential sampling biases. This may indicate that microphysical processes like aerosol particle formation, growth, and coagulation impact the dominant aerosol size at shorter scales than their combined effect on the aerosol optical depth by the aerosol emission, transport, and removal. Averaging between measurements and model, the distance at which the correlation to itself is reduced by 15% is 65 km for AOD, and 22.7 km for AE. Vertically resolved measurement from an aircraft enable the direct measurements of aerosols overlying clouds. When aerosol overlie bright clouds, their radiative impact on the incident light can be either positive or negative. This difference in radiative impact promotes difficulties in remote sensing aerosol properties, which have shown biases in AOD retrievals when clouds are underneath. The AOD above clouds measured by 4STAR during ORACLES are used to build and improve upon the current Near-Real-Time MODACAERO algorithm for above cloud AOD from MODIS, into a continuity product for NASA EOS/SNPP/JPSS.

Aerosol↗
NASA NTRS2017

Stratospheric Instrusion Catalog: A 10-Year Compilation of Events Identified by using TRACK with NASA's MERRA-2 Reanalysis

Stratospheric intrusions "the introduction of ozone-rich stratospheric air into the troposphere" have been linked with surface ozone air quality exceedances, especially at the high elevations in the western USA in springtime. However, the impact of stratospheric intrusions in the remaining seasons and over the rest of the USA is less clear. A new approach to the study of stratospheric intrusions uses NASA's Goddard Earth Observing System Model (GEOS) model and assimilation products with an objective feature tracking algorithm to investigate the atmospheric dynamics that generate stratospheric intrusions and the different mechanisms through which stratospheric intrusions may influence tropospheric chemistry and surface air quality seasonally over both the western and the eastern USA. A catalog of stratospheric intrusions identified in the MERRA-2 reanalysis was produced for the period 2004-2015 and validated against surface ozone observations (focusing on those which exceed the national air quality standard) and a recent data set of stratospheric intrusion-influenced air quality exceedance flags from the US Environmental Protection Agency (EPA). Considering not all ozone exceedances have been flagged by the EPA, a collection of stratospheric intrusions can support air quality agencies for more rapid identification of the impact of stratospheric air on surface ozone and demonstrates that future operational analyses may aid in forecasting such events. An analysis of the spatiotemporal variability of stratospheric intrusions over the continental US was performed, and while the spring over the western USA does exhibit the largest number of stratospheric intrusions affecting the lower troposphere, the number of intrusions in the remaining seasons and over the eastern USA is sizable. By focusing on the major modes of variability that influence weather in the USA, such as the Pacific North American (PNA) teleconnection index, predicative meteorological patterns associated with stratospheric intrusions and their regional effects on tropospheric ozone were identified. Improved understanding of the connections between large-scale climate variability and local-scale dynamically-driven air quality events may support improved seasonal prediction of such events.

PN↗
NASA NTRS2022

Unique Observational Constraints on the Seasonal and Longitudinal Variability of the Earth’s Planetary Albedo and Cloud Distribution Inferred From EPIC Measurements

Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.

DSCOVR↗
NASA NTRS2019

The Effects of a 1998 Observing System Change on MERRA-2-Based Ozone Profile Simulations

Model simulations of ozone (O3) driven by meteorological reanalyses are useful for filling observational gaps and interpreting observed O3 variability and trends. However, the transport circulation of reanalysis products is impacted by changes to the observing system (the data assimilated into the reanalyses). We examine the impacts of these changes on simulated O3 from two models, Global Modeling Initiative (GMI) Chemistry Transport Model (GMI CTM) and Modern‐Era Retrospective Analysis for Research Applications version 2 (MERRA‐2) GMI Replay (M2 GMI Replay) simulation, using observations from global ozonesondes (>50,000 profiles) and satellites from 1980 to 2016. Both models are constrained by meteorology from the NASA MERRA‐2 reanalysis, and both use versions of NASA's GMI chemical mechanism. We focus on an observing system change affecting simulated O3 after 1998, associated with the assimilation of temperature and humidity data from new microwave profiling satellites. A large post‐1998 O3 increase, mainly confined to 15–20‐km altitude, of ~10 Dobson units (DU) in midlatitudes occurs in the GMI CTM, worsening the bias compared to observations. In contrast, an increase in M2 GMI Replay simulation O3 of ~10 DU is observed only near −60° latitude, reducing the bias compared to observations. The GMI CTM O3 high biases display a Quasi‐Biennial Oscillation (QBO)‐like periodicity that result from excessive transport from the tropical stratosphere to the midlatitude lower stratosphere during the QBO westerly phase. We quantify O3 discontinuities caused by MERRA‐2 observing system changes and demonstrate how the MERRA‐2 Global Modeling Initiative Replay simulation dampens the effects of these changes and QBO‐driven artifacts on simulated lower stratospheric and total O3. We caution against using simulations driven by a reanalysis to derive multidecadal O3 trends, especially prior to 1998.

Replay↗
NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗