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NASA NTRSDate not supplied

Continuing Global SO2 Data Record from OMI and SNPP/OMPS to JPSS-1/NOAA-20/OMPS

Since 2004, the Ozone Monitoring Instrument (OMI) aboard NASA's Earth Observing System (EOS) Aura spacecraft has been providing global observations that help to constrain the sources, transport, and environmental impacts of anthropogonic and volcanic SO2. The OMI SO2 data record is now being continued with the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP)/Ozone Mapping and Profiler Suite (OMPS) launched in 2011. Both OMI and SNPP/OMPS SO2 products are produced with the Goddard principal component analysis (PCA) based spectral fitting algorithm. This data-driven technique inherently accounts for various instrumental factors and geophysical interferences, leading to high-quality, consistent SO2 retrievals between OMI and SNPP/OMPS, despite coarser spectral (~0.5 nm vs. ~1 nm) and spatial (13  24 km2 vs. 50  50 km2 at nadir) resolution for the latter. In this presentation, we describe our effort to continue the long-term SO2 climate data record using measurements from the Joint Polar Satellite System (JPSS)-1/NOAA-20 (N20)/OMPS. Launched in 2017, the N20/OMPS is a follow-on for SNPP/OMPS but features a spatial resolution (17  13 km2) that is comparable with OMI. We will discuss our progress implementing the PCA SO2 algorithm with N20/OMPS, especially algorithmic improvements to further reduce retrieval noise and bias for large volcanic eruptions. We will present examples for both continuously emitting sources (e.g., power plants in India and oil/gas fields in the Middle East) and volcanic eruptions (e.g., Raikoke in 2019). We will also compare N20/OMPS SO2 retrievals with OMI and SNPP/OMPS, as well as other instruments such as the ESA Copernicus Sentinel-5 Precursor (S5P)/TROPOspheric Monitoring Instrument (TROPOMI). To assess the ability of N20/OMPS to monitor and quantify SO2 sources, we will run the level 2 retrievals through a top-down emission algorithm to estimate the SO2 emission strengths for a number of point sources. Finally, we will outline our plan for further algorithm refinement and public data release.

SO2↗
NASA NTRS2013

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.

Climate Models↗
NASA NTRS2001

Ultra-Efficient Engine Technology (UEET) Program

The Ultra-Efficient Engine Technology (UEET) Program includes seven key projects that work with industry to develop and hand off revolutionary propulsion technologies that will enable future-generation vehicles over a wide range of flight speeds. A new program office, the Ultra-Efficient Engine Technology (UEET) Program Office, was formed at the NASA Glenn Research Center to manage an important National propulsion program for NASA. The Glenn-managed UEET Program, which began on October 1, 1999, includes participation from three other NASA centers (Ames, Goddard, and Langley), as well as five engine companies (GE Aircraft Engines, Pratt & Whitney, Honeywell, Allison/Rolls Royce, and Williams International) and two airplane manufacturers (the Boeing Company and Lockheed Martin Corporation). This 6-year, nearly $300 million program will address local air-quality concerns by developing technologies to significantly reduce nitrogen oxide (NOx) emissions. In addition, it will provide critical propulsion technologies to dramatically increase performance as measured in fuel burn reduction that will enable reductions of carbon dioxide (CO2) emissions. This is necessary to address the potential climate impact of long-term aviation growth.

Manthey, Lori A.↗
NASA NTRS2012

Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm

AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,

Susskind, Joel↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗
NASA NTRS2020

Evaluation of Stratospheric Intrusions and Biomass Burning Plumes on the Vertical Distribution of Tropospheric Ozone Over the Midwestern U.S.

Naturally occurring ozone rich Stratosphere-to-Troposphere Transport (STT) intrusions and biomass burning plumes reaching the surface can contribute to exceedances of the U.S. National Ambient Air Quality Standards (NAAQS) for ground-level ozone (70 ppbv implemented in 2015). In addition, fires can inject significant pollution into the free troposphere where it can be transported long distances. The combined air quality impacts from these sources on ozone has only been analyzed in a few case studies for the Midwest U.S. Here we study ozone impacts in a major Midwestern city, for the first time in St. Louis, Missouri, using a series of ozonesonde profiles taken during the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) field campaign in August-September 2013. All ozonesondes showed some enhancements above the background profile levels (~55 ppbv) throughout each tropospheric column. Two models were used to estimate and quantify ozone origins within the columns. A chemical transport model identified enhancements from STT equivalent to 10to15 ppbv over the background with a 10 to15% contribution overall to the column. Two FLEXPART-WRF simulations, one with smoke in the boundary layer and the other with smoke above, identified enhancements from biomass burning equivalent to 10to 80 ppbv. Overall, the total biomass burning contribution is 15to 30% of the total column. Five ozonesondes showed signatures of mixed biomass burning plumes and STT intrusions. During this study period, biomass burning in the western U.S. contributed 70% to ozone enhancements in the total column compared to 3% from the central U.S and 27% from other areas.

National Ambient Air Quality Standards for ground‐↗
NASA NTRS1994

Observations of water vapor by ground-based microwave radiometers and Raman lidar

In November to December 1991, a substantial number of remote sensors and in situ instruments were operated together in Coffeyville, Kansas, during the climate experiment First ISCCP Regional Experiment Phase 2 (FIRE 2). Includede in the suite of instruments were (1) the NOAA Environmental Technology Laboratory (ETL) three-channel microwave radiometer, (2) the NASA GSFC Raman lidar, (3) ETL radio acoustic sounding system (RASS), and (4) frequent, research-quality radiosondes. The Raman lidar operated only at night and the focus of this portion of the experiment concentrated on clear conditions. The lidar data, together with frequent radiosondes and measurements of temperature profiles (every 15 min) by RASS allowed profiles of temperature and absolute humidity to be estimated every minute. We compared 20 min measurements of brightness temperature (T(sub b) with calculations of T(sub b) that were based on the Liebe and Layton (1987) and Liebe et al. (1993) microwave propagation models, as well as the Waters (1976) model. The comparisons showed the best agreement at 20.6 GHz with the Waters model, with the Liebe et al. (1993) model being best at 31.65 GHz. The results at 90 GHz gave about equal success with the Liebe and Layton (1987) and Liebe et al. (1993) models. Comparisons of precipitable water vapor derived independently from the two instruments also showed excellent agreement, even for averages as short as 2 min. The rms difference between Raman and radiometric determinations of precipitable water vapor was 0.03 cm which is roughly 2%. The experiments clearly demonstrate the potential of simultaneous operation of radiometers and Raman lidars for fundamental physical studies of water vapor.

Han, Yong↗
NASA NTRS2010

Using Remote Sensing Data to Evaluate Habitat Loss in the Mobile, Galveston, and Tampa Bay Watersheds

The Gulf of Mexico has experienced dramatic wetland habitat area losses over the last two centuries. These losses not only damage species diversity, but contribute to water quality, flood control, and aspects of the Gulf coast economy. Overall wetland losses since the 1950s were examined using land cover/land use (LCLU) change analysis in three Gulf coast watershed regions: Mobile Bay, Galveston Bay, and Tampa Bay. Two primary causes of this loss, LCLU change and climate change, were then assessed using LCLU maps, U.S. census population data, and available current and historical climate data from NOAA. Sea level rise, precipitation, and temperature effects were addressed, with emphasis on analysis of the effects of sea level rise on salt marsh degradation. Ecological impacts of wetland loss, including fishery depletion, eutrophication, and hypoxia were addressed using existing literature and data available from NOAA. These ecological consequences in turn have had an affect on the Gulf coast economy, which was analyzed using fishery data and addressing public health impacts of changes in the environment caused by wetland habitat loss. While recent federal and state efforts to reduce wetland habitat loss have been relatively successful, this study implies a need for more aggressive action in the Gulf coast area, as the effects of wetland loss reach far beyond individual wetland systems themselves to the Gulf of Mexico as a whole.

Steffen, Morgan↗
NASA NTRS2010

Assessment of NPP VIIRS Ocean Color Data Products: Hope and Risk

For several years, the NASA/Goddard Space Flight Center (GSFC) NPP VIIRS Ocean Science Team (VOST) provided substantial scientific input to the NPP project regarding the use of Visible Infrared Imaging Radiometer Suite (VIIRS) to create science quality ocean color data products. This work has culminated into an assessment of the NPP project and the VIIRS instrument's capability to produce science quality Ocean Color data products. The VOST concluded that many characteristics were similar to earlier instruments, including SeaWiFS or MODIS Aqua. Though instrument performance and calibration risks do exist, it was concluded that programmatic and algorithm issues dominate concerns. Keywords: NPP, VIIRS, Ocean Color, satellite remote sensing, climate data record.

Turpie, Kevin R.↗
NASA NTRS2008

How Does Mediterranean Basin's Atmosphere Become Weak Moisture Source During Negative Phase of NAO: Use of AIRS, AMSR, TOVS, & TRMM Satellite Datasets Over Last Two NAO Cycles to Examine Governing Controls on E-P

The Mediterranean Sea is a noted 'concentration" basin in that it almost continuously exhibits positive evaporation minus precipitation (E - P ) properties -- throughout the four seasons and from one year to the next. Nonetheless, according to the ECMWF Era-40 48-year (1958-2005) climate reanalysis dataset, for various phases of the North Atlantic Oscillation (NAO) when the pressure gradient between Portugal and Iceland becomes either very relaxed (large negative NAO-Index) or in transition (small positive or negative NAO-Index), the atmospheric moisture source properties of the basin become weak, at times even reversed for several months (i.e., negative E - P). This behavior poses numerous questions concerning how and why these events occur. Moreover, it begs the question of what it would take for the basin to reach its tipping point in which P would exceed E throughout the rainy season (some six months) on an annually persistent basis -- and the sea would possibly transform to a recurring "dilution" basin. This talk investigates these questions by: (1) establishing over a period from 1979 to present, based on detailed analyses of satellite retrieval products from a combination of NASA-AQUA, NOAA-LEO, NASA/JAXA Scatterometer, and NASA-TRMM platforms, plus additional specialized satellite data products and ancillary meteorological datasets, the actual observation-based behavior of E - P, (2) diagnosing the salient physical and meteorological mechanisms that lead to the weaker E - P events during the analysis period, partly based on analyzing surface and upper air data at discrete stations in the western and eastern Mediterranean -- while at the same time evaluating the quality of the ERA-40 data over this same time period, (3) conducting GCM and high-resolution regional modeling experiments to determine if perturbed but realistic meteorological background conditions could maintain Mediterranean as a "dilution" basin through the October to March rainy season on annually recurring basis, and (4) investigating how such conditions might modify important internal and external climatic processes known to be closely related to the dynamical, thermal, and hydrological properties of the basin (e.g., drought frequency over Iberian peninsula, rainfall accumulation within Sahel, alteration of Levantine branch of east-west aligned open thermohaline cell, and modification of warm-salty intermediate flow through Gibraltar straight into North Atlantic).

Smith, Eric A.↗
NASA NTRS2013

Results from CrIS-ATMS Obtained Using the AIRS Science Team Retrieval Methodology

AIRS was launched on EOS Aqua in May 2002, together with AMSU-A and HSB (which subsequently failed early in the mission), to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS/AMSU had two primary objectives. The first objective was to provide real-time data products available for use by the operational Numerical Weather Prediction Centers in a data assimilation mode to improve the skill of their subsequent forecasts. The second objective was to provide accurate unbiased sounding products with good spatial coverage that are used to generate stable multi-year climate data sets to study the earth's interannual variability, climate processes, and possibly long-term trends. AIRS/AMSU data for all time periods are now being processed using the state of the art AIRS Science Team Version-6 retrieval methodology. The Suomi-NPP mission was launched in October 2011 as part of a sequence of Low Earth Orbiting satellite missions under the "Joint Polar Satellite System" (JPSS). NPP carries CrIS and ATMS, which are advanced infra-red and microwave atmospheric sounders that were designed as follow-ons to the AIRS and AMSU instruments. The main objective of this work is to assess whether CrIS/ATMS will be an adequate replacement for AIRS/AMSU from the perspective of the generation of accurate and consistent long term climate data records, or if improved instruments should be developed for future flight. It is critical for CrIS/ATMS to be processed using an algorithm similar to, or at least comparable to, AIRS Version-6 before such an assessment can be made. We have been conducting research to optimize products derived from CrIS/ATMS observations using a scientific approach analogous to the AIRS Version-6 retrieval algorithm. Our latest research uses Version-5.70 of the CrIS/ATMS retrieval algorithm, which is otherwise analogous to AIRS Version-6, but does not yet contain the benefit of use of a Neural-Net first guess start-up system which significantly improved results of AIRS Version-6. Version-5.70 CrIS/ATMS temperature profile and surface skin temperature retrievals are of very good quality, and are better than AIRS Version-5 retrievals, but are still significantly poorer than those of AIRS Version-6. CrIS/ATMS retrievals should improve when a Neural-Net start-up system is ready for use. We also examined CrIS/ATMS retrievals generated by NOAA using their NUCAPS retrieval algorithm, which is based on earlier versions of the AIRS Science Team retrieval algorithms. We show that the NUCAPS algorithm as currently configured is not well suited for climate monitoring purposes.

CrIS↗
NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗
NASA NTRS2004

PhyLM: A Mission Design Concept for an Optical/Lidar Instrument to Measure Ocean Productivity and Aerosols from Space

The Physiology Lidar-Multispectral Mission (PhyLM) is intended to explore the complex ecosystems of our global oceans. New "inversion" methods and improved understanding of marine optics have opened the door to quantifying a range of critical ocean properties. This new information could revolutionize our understanding of global ocean processes, such as phytoplankton growth, harmful algal blooms, carbon fluxes between major pools and the productivity equation. The new science requires new measurements not addressed by currently planned space missions. PhyLM will combine active and advanced passive remote sensing technologies to quantify standing stocks and fluxes of climate-critical components of the Ocean carbon cycle to meet these science providing multispectral bands from the far UV through the near infrared (340 - 1250 nm) at a ground resolution of 250 m. Improved detectors, filters, mirrors, digitization and focal plane design will offer an overall higher-quality data product. The unprecedented accuracy and precision of the absolute water-leaving radiances will support inversion- based quantification of an expanded set of ocean carbon cycle components. The dual- wavelength (532 & 1064 nm) Nd:Yag Lidar will enhance the accuracy and precision of the passive data by providing aerosol profiles for atmospheric correction and coincident active measurements of backscattering. The Lidar will also examine dark-side fluorescence as an additional approach to quantifying phytoplankton biomass in highly productive regions.

Gervin, Janette C.↗
NASA NTRS2015

Modelling Freshwater Resources at the Global Scale: Challenges and Prospects

Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater-surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyper resolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy.

Global hydrological model↗
NASA NTRS2024

Modeling Impacts of Dust Mineralogy on Fast Climate Response

Mineralogical composition drives dust impacts on Earth's climate systems. However, most climate models still use homogeneous dust, without accounting for the temporal and spatial variation in mineralogy. To quantify the radiative impact of resolving dust mineralogy on Earth's climate, we implement and simulate the distribution of dust minerals (i.e., illite, kaolinite, smectite, hematite, calcite, feldspar, quartz, and gypsum) from Claquin et al. (1999) (C1999) and activate their interaction with radiation in the GFDL AM4.0 model. Resolving mineralogy reduces dust absorption compared to the homogeneous dust used in the standard GFDL AM4.0 model that assumes a globally uniform hematite volume content of 2.7 % (HD27). The reduction in dust absorption results in improved agreement with observation-based single-scattering albedo (SSA), radiative fluxes from CERES (the Clouds and the Earth's Radiant Energy System), and land surface temperature from the CRU (Climatic Research Unit) compared to the baseline HD27 model version. It also results in distinct radiative impacts on Earth's climate over North Africa. Over the 19-year (from 2001 to 2019) modeled period during JJA (June–July–August), the reduction in dust absorption in AM4.0 leads to a reduction of over 50 % in net downward radiation across the Sahara and approximately 20 % over the Sahel at the top of the atmosphere (TOA) compared to the baseline HD27 model version. The reduced dust absorption weakens the atmospheric warming effect of dust aerosols and leads to an alteration in land surface temperature, resulting in a decrease of 0.66 K over the Sahara and an increase of 0.7 K over the Sahel. The less warming in the atmosphere suppresses ascent and weakens the monsoon inflow from the Gulf of Guinea. This brings less moisture to the Sahel, which combined with decreased ascent induces a reduction of precipitation. To isolate the effect of reduced absorption compared to resolving spatial and temporal mineralogy, we carry out a simulation where the hematite volume content of homogeneous dust is reduced from 2.7 % to 0.9 % (HD09). The dust absorption (e.g., single-scattering albedo) of HD09 is comparable to that of the mineralogically speciated model on a global mean scale, albeit with a lower spatial variation that arises solely from particle size. Comparison of the two models indicates that the spatial inhomogeneity in dust absorption resulting from resolving mineralogy does not have significant impacts on Earth's radiation and climate, provided there is a similar level of dust absorption on a global mean scale before and after resolving dust mineralogy. However, uncertainties related to emission and distribution of minerals may blur the advantages of resolving minerals to study their impact on radiation, cloud properties, ocean biogeochemistry, air quality, and photochemistry. On the other hand, lumping together clay minerals (i.e., illite, kaolinite, and smectite), but excluding externally mixed hematite and gypsum, appears to provide both computational efficiency and relative accuracy. Nevertheless, for specific research, it may be necessary to fully resolve mineralogy to achieve accuracy.

Soil dust↗
NASA NTRS2020

AMPR CAMP2Ex Calibrated and Quality-Controlled Dataset Level 2B, Revision B

Data were acquired by the Advanced Microwave Precipitation Radiometer (AMPR) during the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign in August-October of 2019. These files include the Level 2B calibrated, corrected, and geo-referenced brightness temperature for the four AMPR-observed frequencies (10, 19, 37, 85 GHz). These data are archived in a self-describing, Climate and Forecasting (CF) 1.6-compliant Version 4 Network Common Data Format (netCDF4) format.Python software has been developed for reading, plotting, and providing some additional analysis capabilities. This software is available from: https://github.com/nasa/pyampr.The AMPR instrument is explained in more detail here: https://weather.msfc.nasa.gov/ampr/.These data have been determined to be viable for publishable scientific research, and alsoshould be useful for generating quicklooks or understanding what happened during a flight. Note: AMPRis not expected to provide useful data during significant aircraft maneuvers

Timothy Lang↗
NASA NTRS2004

Means, Variability and Trends of Precipitation in the Global Climate as Determined by the 25-year GEWEWGPCP Data Set

The Global Precipitation Climatology Project (GPCP) 25-year precipitation data set is used as a basis to evaluate the mean state, variability and trends (or inter-decadal changes) of global and regional scales of precipitation. The uncertainties of these characteristics of the data set are evaluated by examination of other, parallel data sets and examination of shorter periods with higher quality data (e.g., TRMM). The global and regional means are assessed for uncertainty by comparing with other satellite and gauge data sets, both globally and regionally. The GPCP global mean of 2.6 mdday is divided into values of ocean and land and major latitude bands (Tropics, mid-latitudes, etc.). Seasonal variations globally and by region are shown and uncertainties estimated. The variability of precipitation year-to-year is shown to be related to ENS0 variations and volcanoes and is evaluated in relation to the overall lack of a significant global trend. The GPCP data set necessarily has a heterogeneous time series of input data sources, so part of the assessment described above is to test the initial results for potential influence by major data boundaries in the record.

Adler, R. F.↗
NASA NTRS2001

Merging Ocean Color Data from Multiple Missions

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, the National Aeronautics and Space Administration (NASA) and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data. Seven of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance) and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans. Any individual ocean color mission is limited in ocean coverage due to sun glint and clouds. For example, one of the first proposed missions, the SeaWiFS, can provide about 45% coverage of the global ocean in four days and only about 15% in one day.

Gregg, Watson W.↗