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NASA NTRS2003

Aerosol Absorption in the Atmosphere: Perspectives from Global Model, Ground-Based Measurements, and Field Observations

Aerosol absorption in the atmosphere poses a major uncertainty in assessing the aerosol climate effects. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, and our limited knowledge of aerosol mixing state and optical properties. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt. We compare the model calculated total aerosol optical thickness, extinction, and absorption with those quantities from the ground-based sun photometer measurements from AERONET at several different wavelengths and the field observations from ACE-Asia. We will examine what are the most sensitive factors in determining the aerosol absorption, and the consequences of assessing the aerosol radiative forcing and atmospheric heating associated with those factors.

Chin, Mian↗

NASA NTRS2003

Aerosol Absorption in the Atmosphere: Perspectives from Global Model, Ground-Based Measurements, and Field Observations

Chin, Mian↗

NASA NTRS2016

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

snow↗

NASA NTRS2018

A Global Spatially Contiguous Solar-Induced Fluorescence (CSIF) Dataset Using Neural Networks

Satellite-retrieved solar-induced chlorophyll fluorescence (SIF) has shown great potential to monitor the photosynthetic activity of terrestrial ecosystems. However, several issues, including low spatial and temporal resolution of the gridded datasets and high uncertainty of the individual retrievals, limit the applications of SIF. In addition, inconsistency in measurement footprints also hinders the direct comparison between gross primary production (GPP) from eddy covariance (EC) flux towers and satellite-retrieved SIF. In this study, by training a neural network (NN) with surface reflectance from the MODerate-resolution Imaging Spectroradiometer (MODIS) and SIF from Orbiting Carbon Observatory-2 (OCO-2), we generated two global spatially contiguous SIF (CSIF) datasets at moderate spatiotemporal (0.05° 4-day) resolutions during the MODIS era, one for clear-sky conditions (2000–2017) and the other one in all-sky conditions (2000–2016). The clear-sky instantaneous CSIF (CSIF(sub clear-inst)) shows high accuracy against the clear-sky OCO-2 SIF and little bias across biome types. The all-sky daily average CSIF (CSIF(sub all-daily)) dataset exhibits strong spatial, seasonal and interannual dynamics that are consistent with daily SIF from OCO-2 and the Global Ozone Monitoring Experiment-2 (GOME-2). An increasing trend (0.39 %) of annual average CSIFall-daily is also found, confirming the greening of Earth in most regions. Since the difference between satellite-observed SIF and CSIF is mostly caused by the environmental down-regulation on SIF(sub yield), the ratio between OCO-2 SIF and CSIF(sub clear-inst) can be an effective indicator of drought stress that is more sensitive than the normalized difference vegetation index and enhanced vegetation index. By comparing CSIF(sub all-daily) with GPP estimates from 40 EC flux towers across the globe, we find a large cross-site variation (c.v. = 0.36) of the GPP–SIF relationship with the highest regression slopes for evergreen needleleaf forest. However, the cross-biome variation is relatively limited (c.v. = 0.15). These two contiguous SIF datasets and the derived GPP–SIF relationship enable a better understanding of the spatial and temporal variations of the GPP across biomes and climate.

Zhang, Yao↗

NASA NTRS2013

A Single-column Model Ensemble Approach Applied to the TWP-ICE Experiment

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

numerical weather forecasting↗

NASA NTRS1989

Nonscanning climate sensor study

The Nonscanning Climate Sensor represents a new instrument for climate research and global monitoring of the earth radiation budget. It contains a mosaic of array of detectors which measures the outgoing radiation of the earth in all directions without the need for mechanical scanning. The goal is to eliminate all moving parts and obtain highly calibrated measurements for up to one solar cycle (11 years) without being susceptible to mechanical failure. Over set intervals of time, the angular measurements are integrated up to produce total reflected and emitted flux values from each target area on the Earth. To achieve the require sensitivity while maintaining a flat spectral response, an improved dual cavity detector with digital control loop was developed. The detector is self calibrating to maintain high precision over the life of the instrument. Prototype detectors and a complete set of electronics with a microprocessor controller were fabricated and tested. Measurements show that the new detectors are more than an order of magnitude more sensitive than previous versions.

Hoffman, James W.↗

NASA NTRS2015

Development of Double and Triple-Pulsed 2-micron IPDA Lidars for Column CO2 Measurements

Carbon dioxide (CO2) is an important greenhouse gas that significantly contributes to the carbon cycle and globalradiation budget on Earth. CO2 role on Earth’s climate is complicated due to different interactions with various climatecomponents that include the atmosphere, the biosphere and the hydrosphere. Although extensive worldwide efforts formonitoring atmospheric CO2 through various techniques, including in-situ and passive sensors, are taking place highuncertainties exist in quantifying CO2 sources and sinks. These uncertainties are mainly due to insufficient spatial andtemporal mapping of the gas. Therefore it is required to have more rapid and accurate CO2 monitoring with higheruniform coverage and higher resolution. CO2 DIAL operating in the 2-μm band offer better near-surface CO2measurement sensitivity due to the intrinsically stronger absorption lines. For more than 15 years, NASA LangleyResearch Center (LaRC) contributed in developing several 2-m CO2 DIAL systems and technologies. This paperfocuses on the current development of the airborne double-pulsed and triple-pulsed 2-m CO2 integrated pathdifferential absorption (IPDA) lidar system at NASA LaRC. This includes the IPDA system development andintegration. Results from ground and airborne CO2 IPDA testing will be presented. The potential of scaling suchtechnology to a space mission will be addressed.

Singh, Upendra N.↗

NASA NTRS2023

The Planetary Protection Strategy of Mars Sample Return’s Earth Return Orbiter Mission

The Mars Sample Return campaign aims to use three flight missions and one ground element to safely bring rock cores, regolith and atmospheric samples from the surface of Mars to Earth to answer key questions about the geologic and climate history of Mars, including the potential for ancient life. Since its landing in Jezero Crater in 2021, the first mission, NASA’s Mars 2020, has collected a number of samples on the crater floor and on the delta using the Perseverance rover. Subsequent missions would recover the sealed sample tubes, launch them into Mars orbit, and transport them back to Earth. The ground element would be a high-containment facility that would isolate and protect the samples during initial sample characterization, which would include sample safety assessments and time-sensitive scientific investigations. These elements are currently in the planning and design stages of development, and represent an international effort of NASA, the European Space Agency (ESA), and many industry partners. The work presented here provides an overview of the planetary protection strategy of the third flight mission, the ESA-led Earth Return Orbiter (ERO), which hosts the NASA-provided Capture, Containment, and Return System (CCRS). ERO-CCRS would capture the container with up to 30 sealed tubes previously put in Martian orbit, contain them in redundant containers to ensure that no potentially hazardous Mars particles are released, and return them to Earth through an entry vehicle. Both NASA and ESA policies comply with the United Nations’ Outer Space Treaty by planning to protect Earth’s biosphere from any potential adverse effects from material returned from solar system bodies beyond the Earth-Moon system. In the conduct of Mars Sample Return, the two agencies have agreed to apply approaches consistent with their own planetary protection standards to the campaign elements each provides.

Mars Sample Return↗

NASA NTRSDate not supplied

The Planetary Protection Strategy of Mars Sample Return Earth Return Orbiter Mission

The Mars Sample Return campaign aims to use three flight missions and one ground element to safely bring rock cores, regolith and atmospheric samples from the surface of Mars to Earth to answer key questions about the geologic and climate history of Mars, including the potential for ancient life. Since its landing in Jezero Crater in 2021, the first mission, NASA’s Mars 2020, has collected a number of samples on the crater floor and on the delta using the Perseverance rover. Subsequent missions would recover the sealed sample tubes, launch them into Mars orbit, and transport them back to Earth. The ground element would be a high-containment facility that would isolate and protect the samples during initial sample characterization, which would include sample safety assessments and time-sensitive scientific investigations. These elements are currently in the planning and design stages of development, and represent an international effort of NASA, the European Space Agency (ESA), and many industry partners. The work presented here provides an overview of the Planetary Protection strategy of the third flight mission, the ESA-led Earth Return Orbiter (ERO), which hosts the NASA-provided Capture, Containment, and Return System (CCRS). ERO-CCRS would detect and capture the container with up to 30 sealed tubes previously put in Martian orbit, contain them in redundant containers to ensure that no potentially hazardous Mars particles are released, and return them to Earth through an entry vehicle. Both NASA and ESA policies comply with the United Nations’ Outer Space Treaty by planning to protect Earth’s biosphere from any potential adverse effects from material returned from solar system bodies beyond the Earth-Moon system. In the conduct of Mars Sample Return, the two agencies have mutually agreed to apply approaches consistent with their own planetary protection standards to the campaign elements they each provides.

mars sample return↗

NASA NTRS2024

The Planetary Protection Strategy of Mars Sample Return’s Earth Return Orbiter Mission

The Mars Sample Return campaign aims to use three flight missions and one ground element to safely bring rock cores, regolith and atmospheric samples from the surface of Mars to Earth to answer key questions about the geologic and climate history of Mars, including the potential for ancient life. Since its landing in Jezero Crater in 2021, the first mission, NASA’s Mars 2020, has collected a number of samples on the crater floor and on the delta using the Perseverance rover. Subsequent missions would recover the sealed sample tubes, launch them into Mars orbit, and transport them back to Earth. The ground element would be a high-containment facility that would isolate and protect the samples during initial sample characterization, which would include sample safety assessments and time-sensitive scientific investigations. These elements are currently in the planning and design stages of development, and represent an international effort of NASA, the European Space Agency (ESA), and many industry partners. The work presented here provides an overview of the planetary protection strategy of the third flight mission, the ESA-led Earth Return Orbiter, which hosts the NASA-provided Capture, Containment, and Return System. The orbiter would detect and capture the container with up to 30 sealed tubes previously put in Martian orbit, contain them in redundant containers to ensure that no potentially hazardous Mars particles are released, and return them to Earth through an entry vehicle. Both NASA and ESA policies comply with the United Nations’ Outer Space Treaty by planning to protect Earth’s biosphere from any potential adverse effects from material returned from solar system bodies beyond the Earth-Moon system. In the conduct of Mars Sample Return, the two agencies have mutually agreed to apply approaches consistent with their own planetary protection standards to the campaign elements they each provide.

Mars Sample Return↗

NASA NTRS1991

Nonlinear dynamics of global atmospheric and Earth-system processes

General Circulation Model (GCM) studies of the atmospheric response to change boundary conditions are discussed. Results are reported on an extensive series of numerical studies based on the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM) general circulation model. In these studies the authors determined the response to systematic changes in atmospheric CO2 ranging from 100 to 1000 ppm; to changes in the prescribed sea surface temperature (SST) in the Gulf of Mexico, such as occurred during the deglaciation phase of the last ice age; to changes in soil moisture over North America; and to changes in sea ice extent in the Southern Hemisphere. Study results show that the response of surface temperature and other variables is nearly logarithmic, with lower levels of CO2 implying greater sensitivity of the atmospheric state to changes in CO2. It was found that the surface temperature of the Gulf of Mexico exerts considerable control over the storm track and behavior of storm systems over the North Atlantic through its influence on evaporation and the source of latent heat. It was found that reductions in soil moisture can play a significant role in amplifying and maintaining North American drought, particularly when a negative soil moisture anomaly prevails late in the spring.

Saltzman, Barry↗

NASA NTRS2014

Uncertainty Analysis for the Miniaturized Laser Heterodyne Radiometer (mini-LHR)

Presented here is a sensitivity analysis for the miniaturized laser heterodyne radiometer (mini-LHR). This passive, ground-based instrument measures carbon dioxide (CO2) in the atmospheric column and has been under development at NASA/GSFC since 2009. The goal of this development is to produce a low-cost, easily-deployable instrument that can extend current ground measurement networks in order to (1) validate column satellite observations, (2) provide coverage in regions of limited satellite observations, (3) target regions of interest such as thawing permafrost, and (4) support the continuity of a long-term climate record. In this paper an uncertainty analysis of the instrument performance is presented and compared with results from three sets of field measurements. The signal-to-noise ratio (SNR) and corresponding uncertainty for a single scan are calculated to be 329.4+/-1.3 by deploying error propagation through the equation governing the SNR. Reported is an absorbance noise of 0.0024 for 6 averaged scans of field data, for an instrument precision of approximately 0.2 ppmv for CO2.

carbon dioxide (CO2)↗

NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗

NASA NTRS1974

Our contaminated atmosphere: The danger of climate change, phases 1 and 2

The effects of increased concentrations of atmospheric particulate matter on average surface temperature and on the components of the earth's radiation budget are studied. An atmospheric model which couples particulate loading to surface temperature and to changes in the earth's radiation budget was used. A determination of the feasibility of using satellites to monitor the effect of increased atmospheric particulate concentrations is performed. It was found that: (1) a change in man-made particulate loading of a factor of 4 is sufficient to initiate an ice age; (2) variations in the global and hemispheric weighted averages of surface temperature, reflected radiant fluz and emitted radiant flux are nonlinear functions of particulate loading; and (3) a black satellite sphere meets the requirement of night time measurement sensitivity, but not the required day time sensitivity. A nonblack, spherical radiometer whose external optical properties are sensitive to either the reflected radiant fluz or the emitted radiant flux meets the observational sensitivity requirements.

Cimorelli, A. J.↗

NASA NTRS2002

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Shepherd, J. Marshall↗

NASA NTRS2014

Comparison of Climatological Planetary Boundary Layer Depth Estimates Using the GEOS-5 AGCM

Planetary boundary layer (PBL) processes, including those influencing the PBL depth, control many aspects of weather and climate and accurate models of these processes are important for forecasting changes in the future. However, evaluation of model estimates of PBL depth are difficult because no consensus on PBL depth definition currently exists and various methods for estimating this parameter can give results that differ by hundreds of meters or more. In order to facilitate comparisons between the Goddard Earth Observation System (GEOS-5) and other modeling and observational systems, seven PBL depth estimation methods are used to produce PBL depth climatologies and are evaluated and compared here. All seven methods evaluate the same atmosphere so all differences are related solely to the definition chosen. These methods depend on the scalar diffusivity, bulk and local Richardson numbers, and the diagnosed horizontal turbulent kinetic energy (TKE). Results are aggregated by climate class in order to allow broad generalizations. The various PBL depth estimations give similar midday results with some exceptions. One method based on horizontal turbulent kinetic energy produces deeper PBL depths in the winter associated with winter storms. In warm, moist conditions, the method based on a bulk Richardson number gives results that are shallower than those given by the methods based on the scalar diffusivity. The impact of turbulence driven by radiative cooling at cloud top is most significant during the evening transition and along several regions across the oceans and methods sensitive to this cooling produce deeper PBL depths where it is most active. Additionally, Richardson number-based methods collapse better at night than methods that depend on the scalar diffusivity. This feature potentially affects tracer transport.

Planetary Boundary Layer Depth↗

NASA NTRS2022

Remote sensing-based vegetation and soil moisture constraints reduce irrigation estimation uncertainty

Understanding the human water footprint and its impact on the hydrological cycle is essential to inform water management under climate change. Despite efforts in estimating irrigation water withdrawals in earth system models, uncertainties and discrepancies exist within and across modeling systems conditioned by model structure, irrigation parameterization, and the choice of input datasets. Achieving model reliability could be much more challenging for data-sparse regions, given limited access to ground truth for parameterization and validation. Here, we demonstrate the potential of utilizing remotely sensed vegetation and soil moisture observations in constraining irrigation estimation in the Noah-MP land surface model. Results indicate that the two constraints together can effectively reduce model sensitivity to the choice of irrigation parameterization by 7%–43%. It also improves the characterization of the spatial patterns of irrigation and its impact on evapotranspiration and surface soil moisture by correcting for vegetation conditions and irrigation timing. This study highlights the importance of utilizing remotely sensed soil moisture and vegetation measurements in detecting irrigation signals and correcting for vegetation growth. Integrating the two remote sensing datasets into the model provides an effective and less feature engineered approach to constraining the uncertainty of irrigation modeling. Such strategies can be potentially transferred to other modeling systems and applied to regions across the globe.

Wanshu Nie↗

NASA NTRS2020

The case for a multi-channel polarization sensitive LIDAR for investigation of insolation-driven ices and atmospheres

All LIDAR instruments are not the same, and advancement of LIDAR technology requires an ongoing interest and demand from the community to foster further development of the required components. The purpose of this white paper is to make the decadal survey panel aware of the need for further technical development, and the potential payoff of investing experimental time, money and thought into the next generation of LIDARs. Technologies for development: We advocate for future development of LIDAR technologies to measure the polarization state of the reflected light at selected multiple wavelengths, chosen according to the species of interest (e.g., H2O and CO2 in the Martian setting).Key scientific questions: In the coming decade, dollars spent on these LIDAR technologies will go towards addressing key climate questions on Mars and other rocky bodies, particularly those with seasonally changing (i.e. insolation driven) plumes of multiple icy volatiles such as Mars, Enceladus, Triton, or Pluto, and insolation-driven dust lifting, such as cometary bodies and the Moon. We will show from examining past Martian and terrestrial lidars that orbital and landed LIDARs can be effective for producing new insights into insolation-driven processes in current planetary climate on several bodies, beyond that available to our current fleet of largely passive instruments on planetary missions

Adrian Jon Brown↗