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At least 217 records · Page 12

Global distributions of upper tropospheric relative humidity derived from SAGE II observations

The global distributions of upper tropospheric relative humidity derived from the archived SAGE II water vapor data set are presented. For both summer and winter months, vertical profiles of zonal mean relative humidity are derived for each of the six 20-deg latitude bands covering 60 deg N - 60 deg S. Some examples of global maps of upper tropospheric relative humidity are shown to illustrate the relationship between moist areas and convective activity.

Chiou, E. W.↗

Comparisons of downwelling radiation to model predictions based on groundbased measurements during FIRE 1991

Surface radiation measurements and simultaneous ground-based measurements of the atmosphere during the FIRE'91 cirrus field experiment provided an opportunity to identify crucial measurements and parameterization deficiencies in current cloud-radiation models. Comparisons between measured and calculated broadband surface fluxes with only a small data subset already reveal these needs: accurate humidity and aerosol vertical profiles for clear cases, accurate vertical extinction profiles and dimensions for clouds, and understanding of the (solar) scattering properties of cirrus.

Kinne, S.↗

Surface Turbulent Fluxes Over Pack Ice Inferred from TOVS Observations

A one-dimensional, atmospheric boundary layer model is coupled to a thermodynamic ice model to estimate the surface turbulent fluxes over thick sea ice. The principal forcing parameters in this time-dependent model are the air temperature, humidity, and wind speed at a specified level (either at 2 m or at 850 mb) and the downwelling surface radiative fluxes. The free parameters. are the air temperature, humidity, and wind speed profiles below the specified level, the surface skin temperature, the ice temperature profile, and the surface turbulent fluxes. The goal is to determine how well we can estimate the turbulent surface heat and momentum fluxes using forcing parameters from atmospheric temperatures and radiative fluxes retrieved from the TIROS-N Operational Vertical Sounder (TOVS) data. Meteorological observations from the Lead Experiment (LeadEx, April 1992) ice camp are used to validate turbulent fluxes computed with the surface observations and the results are used to compare with estimates based on radio-sonde observations or with estimates based on TOVS data. We find that the TOVS-based estimates of the stress are significantly more accurate than those found with a constant geostrophic drag coefficient, with a root-mean-square error about half as large. This improvement is due to stratification effects included in the boundary layer model. The errors in the sensible heat flux estimates, however, are large compared to the small mean values observed during the field experiment.

Lindsay, R. W.↗

Cloud Forcing and the Earth's Radiation Budget: New Ideas and New Observations

1. NEW PERSPECTIVES ON CLOUD-RADIATIVE FORCING. When the Earth Radiation Budget Experiment (ERBE) produced the first measurements of cloud-radiative forcing, the climate community interpreted the results from a context in which the atmosphere was a single column, strongly coupled to the Earth's surface. 2. NEW PERSPECTIVES ON CLOUD-RADIATION OBSERVATIONS. The climate community is also on the verge of adding a new dimension to its observational capability. In classic thinking about atmospheric circulation and climate, surface pressure was a readily available quantity. As meteorology developed, it was possible to develop quantitative predictions of future weather by bringing together a network of surface pressure observations and then of profiles of temperature and humidity obtained from balloons. 3. ON COMBINING OBSERVATIONS AND THE - ORY. With this new capability, it is natural to seek recognizable features in the observations we make of the Earth. There are techniques we can use to group the remotely sensed data in the individual footprints into objects that we can track. We will present one such image-processing application to radiation budget data, showing how we can interpret the radiation budget data in terms of cloud systems that are organized into systematic patterns of behavior - an ecosystem-like view of cloud behavior.

Barkstrom, Bruce R.↗

Satellite Validation: A Project to Create a Data-Logging System to Monitor Lake Tahoe

Flying aboard the satellite Terra, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an imaging instrument used to acquire detailed maps of Earth's surface temperature, elevation, emissivity, and reflectance. An automated site consisting of four buoys was established 6 years ago at Lake Tahoe for the validation of ASTERS thermal infrared data. Using Campbell CR23X Dataloggers, a replacement system to be deployed on a buoy was designed and constructed for the measurement of the lake's temperature profile, surrounding air temperature, humidity, wind direction and speed, net radiation, and surface skin temperature. Each Campbell Datalogger has been programmed to control, power, and monitor 14 different temperature sensors, a JPL-built radiometer, and an RM Young 32500 meteorological station. The logger communicates with the radiometer and meteorological station through a Campbell SDM-SIO4 RS232 serial interface, sending polling commands, and receiving filtered data back from the sensors. This data is then cataloged and sent back across a cellular modem network every hour to JPL. Each instrument is wired via a panel constructed with 18 individual plugs that allow for simple installation and expansion. Data sent back from the system are analyzed at JPL, where they are used to calibrate ASTER data.

Roy, Rudy A.↗

March 2003 EOS Aqua AMSR-E Arctic Sea Ice Field Campaign

An overview of the March 2003 coordinated sea ice field campaign in the Alaskan Arctic is presented with reference to the papers in this special section. This campaign is part of the program to validate the Aqua Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice products. Standard AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The validation program consists of three elements, namely: 1) satellite data comparisons; 2) coordinated satellite/aircraft surface measurements; and 3) modeling and sensitivity analyses. Landsat-7 and RADARSAT observations were used in comparative studies with the retrieved AMSR-E sea ice concentrations. The aircraft sensors provided high-resolution microwave imagery of the surface, atmospheric profiles of temperature and humidity, and digital records of sea ice conditions. When combined with in situ measurements, aircraft data were used to validate the AMSR-E sea ice temperature and snow-depth products. The modeling studies helped interpret the field-data comparisons, provided insight on the limitations of the AMSR-E sea ice algorithms, and suggested potential improvements to the AMSR-E retrieval algorithms.

Cavalieri, Donald J.↗

Percentage Contributions from Atmospheric and Surface Features to Computed Brightness Temperatures

Over the past few years, there has become an increasing interest in the use of millimeter-wave (mm-wave) and sub-millimeter-wave (submm-wave) radiometer observations to investigate the properties of ice particles in clouds. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. One methodology used since the 1960's to discern the relationship between the physical state observed and the brightness temperature (TB) is through the temperature weighting function profile. In this research, the temperature weighting function concept is exploited to analyze the sensitivity of various characteristics of the cloud profile, such as relative humidity, ice water path, liquid water path, and surface emissivity. In our numerical analysis, we compute the contribution (in Kelvin) from each of these cloud and surface characteristics, so that the sum of these various parts equals the computed TB. Furthermore, the percentage contribution from each of these characteristics is assessed. There is some intermingling/contamination of the contributions from various components due to the integrated nature of passive observations and the absorption and scattering between the vertical layers, but all in all the knowledge gained is useful. This investigation probes the sensitivity over several cloud classifications, such as cirrus, blizzards, light snow, anvil clouds, and heavy rain. The focus is on mm-wave and submm-wave frequencies, however discussions of the effects of cloud variations to frequencies as low as 10 GHz and up to 874 GHz will also be presented. The results show that nearly 60% of the TB value at 89 GHz comes from the earth's surface for even the heaviest blizzard snow rates. On the other hand, a significant percentage of the TB value comes from the snow in the cloud for 166, and 183 plus or minus 7 GHz for the heavy and medium snow rates. For submm-wave channels, there is no contribution from the surface because these channels cannot probe through clouds, nor normal water vapor amounts in clear air regions. This work is extremely valuable in physically-based retrieval algorithm development research.

Gail Skofronick-Jackson↗

GRAS NRT Precise Orbit Determination: Operational Experience

EUMETSAT launched the meteorological satellite MetOp-A in October 2006; it is the first of the three satellites that constitute the EUMETSAT Polar System (EPS) space segment. This satellite carries a challenging and innovative instrument, the GNSS Receiver for Atmospheric Sounding (GRAS). The goal of the GRAS instrument is to support the production of atmospheric profiles of temperature and humidity with high accuracy, in an operational context, based on the bending of the GPS signals traversing the atmosphere during the so-called occultation periods. One of the key aspects associated to the data processing of the GRAS instrument is the necessity to describe the satellite motion and GPS receiver clock behaviour with high accuracy and within very strict timeliness limitations. In addition to these severe requirements, the GRAS Product Processing Facility (PPF) must be integrated in the EPS core ground segment, which introduces additional complexity from the data integration and operational procedure points of view. This paper sets out the rationale for algorithm selection and the conclusions from operational experience. It describes in detail the rationale and conclusions derived from the selection and implementation of the algorithms leading to the final orbit determination requirements (0.1 mm/s in velocity and 1 ns in receiver clock error at 1 Hz). Then it describes the operational approach and extracts the ideas and conclusions derived from the operational experience.

MartinezFadrique, Francisco M.↗

Assessing Uncertainties of a Geophysical Approach to Estimate Surface Fine Particulate Matter Distributions from Satellite-Observed Aerosol Optical Depth

Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2(exp) resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2(exp) horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3(exp) in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3(exp). Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.

aerosol optical depth↗

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

Assimilation of microwave satellite observations over the rainbands of tropical cyclones

The potential of microwave observations in improving the weather forecasts is limited by the accuracy of all-sky radiative transfer calculations. We introduce a novel Bayesian MonteCarlo technique to improve the assimilation of microwave observations over the rainbands of tropical cyclones. The BMCI technique eliminates the need for a forward model in the data assimilation system. The technique includes three steps, (i) generating a comprehensive dataset using in-situ cloud measurements and atmospheric profiles, (ii) generating synthetic ATMS observations from the training dataset, and (iii) using real observations to estimate the geophysical variables over the rainbands of tropical cyclones. The retrieved profiles of temperature, relative humidity, and cloud water content as well assurface information such as SST were then assimilated into the model. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns.

Monte Carlo↗

NASA Surface Radiation Budget Project: A Look Back and A Look Forward

The NASA Langley Surface Radiation Budget (SRB) project, historically associated with GEWEX, has provided estimates of surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology Project (ISCCP) cloud properties and radiances as primary input. The first release was in 1995 (Whitlock et al., 1995) at daily 2.5° resolution. Subsequent releases have improved physics, temporal and spatial resolution, as well as increasing the total length of the time series. Release 4 in 2019 (Kummerow et al., 2019) is on a 1° nested grid, with temporal resolutions from 3-hourly to daily and monthly. It originally spanned from July 1983 to December 2017 and has since been extended through 2019. Release 4 uses the ISCCP H series of data, a complete reprocessing which retains more pixels than the previous D series, used in prior SRB versions. SRB data has been used extensively by a wide range of customers, including but not limited to the solar energy community, climate modelers, architects, oceanographers, and the agricultural community. It is an especial feature of SRB that global radiation budget data are available from the 1983 through 2000 period, which is prior to CERES providing alternate data, and then 2000 through near present to provide overlap coverage. Here we use the 36.5 year record of SRB Release 4 to examine the changes in shortwave and longwave fluxes over the period, including the changes in different regions of the globe. We examine energy budget features such as hemispheric symmetry and implied meridional transport of energy. We look at the variability of these features prior to and during the CERES period and compare to later products. We also look at Release 5, currently under development. This version will provide 0.5° resolution. In addition to surface and TOA radiative fluxes it will include fluxes at several atmospheric layers, and some spectral features beyond the broadband shortwave and longwave fluxes in Release 4 and prior. The shortwave algorithm is undergoing a complete change from the Pinker-Laszlo algorithm. Shortwave fluxes will now be calculated from a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). Input datasets are being improved, including surface properties, atmospheric profiles of temperature and humidity, aerosols, and total solar irradiance. Preliminary results from Release 5 and comparisons to Release 4 will be shown.

Earth Radiation Budget↗

Exploring and Visualizing A-Train Instrument Data

The succession of US and international satellites that follow each other in close succession, known as the A-Train, affords an opportunity to atmospheric researchers that no single platform could provide: Increasing the number of observations at any given geographic location.. . a more complete "virtual science platform". However, vertically and horizontally, co-registering and regridding datasets from independently developed missions, Aqua, Calipso, Cloudsat, Parasol, and Aura, so that they can be inter-compared can be daunting to some, and may be repeated by many. Scientists will individually spend much of their time and resources acquiring A-Train datasets of interest residing at various locations, developing algorithms to match up and graph datasets along the A-Train track, and search through large amounts of data for areas and/or phenomena of interest. The aggregate amount of effort that can be expended on repeating pre-science tasks could climb into the tens of millions of dollars. The goal of the A-Train Data Depot (ATDD) is to enable free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) is accomplished by through the ATDDs Giovanni data analysis and visualization tool. Giovanni brings together data from Aqua (MODIS, AIRS, AMSR-E), Cloudsat (cloud profiling radar) and Calipso (CALIOP, IIR), as well as the Aura (OMI, MLS, HIRDLS, TES) to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. This easy to learn and use exploration tool will allow users to create vertical profiles of any desired A-Train dataset, for any given time of choice. This presentation shows the power of Giovanni by describing and illustrating how this tool facilitates and aids A-Train science and research. A web based display system Giovanni provides users with the capability of creating co-located profile images of temperature and humidity data from the MODIS, MLS and AIRS instruments for a user specified time and spatial area. In addition, Cloud and Aerosol profiles may also be displayed for the Cloudsat and Caliop instruments. The ability to modify horizontal and vertical axis range, data range and dynamic color range is also provided. Two dimensional strip plots of MODIS, AIRS, OM1 and POLDER parameters, co-located along the Cloudsat reference track, can also be plotted along with the Cloudsat cloud profiling data. Center swath pixels for the same parameters can also be shown as line plots overlaying the Cloudsat or Calipso profile images. Images and subsetted data produced in each analysis run may be downloaded. Users truly can explore and discover data specific to their needs prior to ever transferring data to their analysis tools.

Kempler, S.↗

Retrieval of surface heat and moisture fluxes from slow-launched radiosondes

A feasibility experiment to determine whether the Bowden ratio (and indirectly moisture fluxes and surface heat) can be reasonably and accurately derived from thermodynamic measurements obtained from balloon-launched radiosondes is presented. This experiment was conducted during July 1988 in Tallahassee, Florida using an airsonde system and a surface radiation and energy budget station. The airsonde system consists of a balloon-launched airsonde, which measures vertical profiles of atmospheric pressure, relative humidity, temperature, and an automatic data acquisition system, which receives and records sensor output from the airsonde package. Intercomparisons were made between Bowen ratios derived from the airsonde profiles and the Bowen ratios measured directly by the energy budget station and the surface radiation.

Smith, Eric A.↗

Springtime SEA Air Is Consistently Both Smoky and Humid, but This Relationship (and Its Radiative Effects) Varies Spatially and Seasonally

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. A previous study discussed the spatial characteristics of the water vapor-BB plume observations in the September 2016 flight data and their degree of agreement with several atmospheric reanalyses and models. In the present work, we first discuss atmospheric chemistry, structure, and aerosol results from all three ORACLES deployments to place these results in a broader seasonal context. Despite the differing locations and season of each deployment, we show that there continues to be good agreement between the airborne ORACLES dataset and large-scale reanalyses, specifically the ECMWF ERA5 and CAMS reanalyses. Other reanalyses (specifically NASA's MERRA-2) preserved the observed correlation between meteorology and biomass burning conditions, but, as was seen for 2016, was frequently displaced spatially relative to the observations. The CAMS reanalysis performs better with water vapor than with CO. Results comparing CAMS column AOD to the field measurements show slight overestimates, consistent with previous analysis, but the good relationship observed between AOD and inlet-based aerosol extinction demonstrates this metric's utility to broader studies. The good ERA5/CAMS/ORACLES agreement allows us to next examine the multi-year seasonal patterns and trends beyond the three ORACLES deployment periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalysis, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. This classification will allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗

The Seasonal Evolution of Atmospheric Vertical Structure of Smoke and Humidity Over the Southeast Atlantic Biomass Burning Region

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region; this correlation is persistent through the biomass burning season, although varying through the course of the season. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. We use the ORACLES observations to assess this smoke-vapor relationship. First, we discuss the good agreement between the airborne ORACLES dataset and the ECMWF ERA5 and CAMS reanalyses, as well as results from NASA’s MERRA-2, as seen over the three deployment years. We then use the reanalyses to develop a framework in which to understand more broadly the radiative and dynamical interactions between the elevated smoke and water vapor over the SEA through the biomass burning season, beyond the three ORACLES observation periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalyses, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. The radiative heating of both aerosol and water vapor has potential to influence the cloud-top entrainment and atmospheric turbulence, thus modifying the underlying stratocumulus cloud properties. We next discuss how these smoke-humidity variations influence both the low-cloud fraction (as observed by MODIS and VIIRS, and output by ERA5) and the boundary layer height in the region. This classification will ultimately allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗

Comparison of Water Vapor Measurements by Airborne Sun Photometer and Near-Coincident in Situ and Satellite Sensors during INTEX/ITCT 2004

We have retrieved columnar water vapor (CWV) from measurements acquired by the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS-14) during 19 Jetstream 31 (J31) flights over the Gulf of Maine in summer 2004 in support of the Intercontinental Chemical Transport Experiment (INTEX)/Intercontinental Transport and Chemical Transformation (ITCT) experiments. In this paper we compare AATS-14 water vapor retrievals during aircraft vertical profiles with measurements by an onboard Vaisala HMP243 humidity sensor and by ship radiosondes and with water vapor profiles retrieved from AIRS measurements during eight Aqua overpasses. We also compare AATS CWV and MODIS infrared CWV retrievals during five Aqua and five Terra overpasses. For 35 J31 vertical profiles, mean (bias) and RMS AATS-minus-Vaisala layer-integrated water vapor (LWV) differences are -7.1 percent and 8.8 percent, respectively. For 22 aircraft profiles within 1 hour and 130 km of radiosonde soundings, AATS-minus-sonde bias and RMS LWV differences are -5.4 percent and 10.7 percent, respectively, and corresponding J31 Vaisala-minus-sonde differences are 2.3 percent and 8.4 percent, respectively. AIRS LWV retrievals within 80 lan of J31 profiles yield lower bias and RMS differences compared to AATS or Vaisala retrievals than do AIRS retrievals within 150 km of the J31. In particular, for AIRS-minus-AATS LWV differences, the bias decreases from 8.8 percent to 5.8 percent, and the RMS difference decreases from 2 1.5 percent to 16.4 percent. Comparison of vertically resolved AIRS water vapor retrievals (LWVA) to AATS values in fixed pressure layers yields biases of -2 percent to +6 percent and RMS differences of -20 percent below 700 hPa. Variability and magnitude of these differences increase significantly above 700 hPa. MODIS IR retrievals of CWV in 205 grid cells (5 x 5 km at nadir) are biased wet by 10.4 percent compared to AATS over-ocean near-surface retrievals. The MODIS-Aqua subset (79 grid cells) exhibits a wet bias of 5.1 percent, and the MODIS-Terra subset (126 grid cells) yields a wet bias of 13.2 percent.

Livingston, J.↗

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↗