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Atmospheric Ionization by Solar Particles Detected by Nitrate Measurements in Antarctic Snow. FY91 AASERT

The odd nitrogen source strengths associated with Solar Proton Events (SPEs), Galactic Cosmic Rays (GCRs), and the oxidation of nitrous oxide in the Earth's middle atmosphere from 1974 through 1993 have been compared globally, at middle and lower latitudes (less than 50 deg), and polar regions (greater than 50 deg) with a two-dimensional (2-D) photochemical transport model. As discovered previously, the oxidation of nitrous oxide dominates the global odd nitrogen source while GCRs and SPEs are significant at polar latitudes. The horizontal transport of odd nitrogen, produced by the oxidation of nitrous oxide at latitudes < 50 deg, was found to be the dominant source of odd nitrogen in the polar regions with GCRs contributing substantially during the entire solar cycle. The source of odd nitrogen from SPEs was more sporadic; however, contributions during several years (mostly near solar maximum) were significant in the polar middle atmosphere.

Vitt, Francis M.↗

OGLE-2015-BLG-1670Lb: A Cold Neptune beyond the Snow Line in the Provisional WFIRST Microlensing Survey Field

We present the analysis of the microlensing event OGLE-2015-BLG-1670, detected in a high-extinction field very close to the Galactic plane. Due to the dust extinction along the line of sight, this event was too faint to be detected before it reached the peak of magnification. The microlensing light-curve models indicate a high-magnification event with a maximum of A(max)≳ 200, very sensitive to planetary deviations. An anomaly in the light curve has been densely observed by the microlensing surveys MOA, KMTNet, and OGLE. From the light-curve modeling, we find a planetary anomaly characterized by a planet-to-host mass ratio, q=(1.00 (sup+0.18, sub -0.16) x 10(exp -4), at the peak recently identified in the mass-ratio function of microlensing planets. Thus, this event is interesting to include in future statistical studies about planet demography. We have explored the possible degeneracies and find two competing planetary models resulting from the s ↔ 1/s degeneracy. However, because the projected separation is very close to s = 1, the physical implications for the planet for the two solutions are quite similar, except for the value of s. By combining the light-curve parameters with a Galactic model, we have estimated the planet mass M(2)=17.9(sup +9.6,sub-8.8)M(ꚛ) and the lens distance D(L) = 6.7(sup +1.0, sub -1.3) kpc, corresponding to a Neptune-mass planet close to the Galactic bulge. Such events with a low absolute latitude (|b| ≈1ᵒ.1) are subject to both high extinction and more uncertain source distances, two factors that may affect the mass measurements in the provisional Wide Field Infrared Survey Telescope fields. More events are needed to investigate the potential trade-off between the higher lensing rate and the difficulty in measuring masses in these low-latitude fields.

Clément Ranc↗

Meteoric 10Be Flux Calibration Data for the East River Watershed, Colorado, USA

This data package contains tabular and geospatial data used to quantify and model meteoric beryllium-10 fluxes in the East River watershed, Colorado, USA. The tabular component includes calibration-site data from five glacial moraine sites and includes environmental variables used to evaluate spatial controls on meteoric 10Be delivery, including elevation, mean annual precipitation (MAP), mean snow depth, and mean snow water equivalent (SWE). These site-level data were used to compare observed fluxes with environmental gradients across the watershed and to evaluate the effects of erosion correction on flux estimates. The package also includes supporting slope and curvature values used to assess topographic inputs to the erosion analysis. A second component of the data package contains updated manuscript tables and regression outputs used to summarize the relationships between meteoric 10Be flux and environmental predictors. These tables include meteoric 10Be sample information and AMS results, site-level environmental values, site-level meteoric 10Be inventory and flux values, watershed-averaged predicted fluxes, soil bulk density measurements, fine-fraction values, soil pH measurements, and regression statistics including slope, intercept, coefficient of determination, and p-value. The regression products include both standard linear regressions and regressions in which the intercept is constrained to pass through zero, and they support the analyses presented in the companion manuscript. Together, these tabular files provide the numerical basis for the manuscript tables and the regression-based interpretation of meteoric 10Be flux variability in a snow-dominated mountain watershed. The geospatial component of the package consists of GeoTIFF raster files used to generate the map products presented in Figures 2 and 6 of the companion manuscript. These rasters represent watershed-scale spatial layers for environmental variables and regression-based predictions of meteoric 10Be flux. This dataset contains comma-separated values files (.csv), Microsoft Excel files (.xlsx), GeoTIFF raster files (.tif), and upporting metadata files, including CSV data dictionaries and readme text files (.csv, .txt). The tabular files can be opened with standard spreadsheet software, and the raster files can be viewed and analyzed in GIS software such as ArcGIS Pro or QGIS. Together, these files document the numerical and spatial datasets used to calibrate and predict meteoric 10Be delivery in the East River watershed.

East River↗

Effects of surface anomalies on certain model generated meteorological histories

The Mintz-Arakawa 2-level general circulation model has been used in a series of experiments to compute the response of the model atmosphere to: (1) a positive sea surface temperature anomaly in the North Pacific Ocean in summer and in winter, (2) an identical anomaly in the South Pacific Ocean in the Southern Hemisphere winter, and (3) anomalous northward and southward displacements of the Northern Hemisphere snow line over the continents. In each case computations were carried out for 90 forecast days. Results are shown in terms of the differences between anomaly and control histories. Time series of certain regional response indices, including area-average sea level pressure and 600 mb circulation indices, as well as 30-day mean sea level pressure maps are used in the analysis. Of particular interest is the evidence of significant interhemisphere influence.

Spar, J.↗

Landsat - What is operational in water resources

Applications of Landsat data in hydrology and water quality measurement were examined to determine which applications are operational. In hydrology, the principal applications have been surface water inventory, and land cover analysis for (1) runoff modeling and (2) abatement planning for non-point pollution and erosion. In water quality measurement, the principal applications have been: (1) trophic state assessment, and (2) measurement of turbidity and suspended sediment. The following applications were found to be operational: mapping of surface water, snow cover, and land cover (USGS Level 1) for watershed applications; measurement of turbidity, Secchi disk depth, suspended sediment concentration, and water depth.

Middleton, E. M.↗

LANDSAT-D investigations in snow hydrology

Thematic mapper data for the southern Sierra Nevada area were registered to digital topographic data and compared to LANDSAT MSS and NOAA-7 AVHRR data of snow covered areas in order to determine the errors associated with using coarser resolution and to qualify the information lost when high resolution data are not available. Both the zenith and the azimuth variations in the radiative field are considered in an atmospheric radiative transfer model which deals with a plane parallel structured atmosphere composed of different layers, each assumed to be homogeneous in composition and to have a linear in tau temperature profile. Astronomical parameters for each layer are Earth-Sun distance and solar flux at the top of the atmosphere. Atmospheric parameters include pressure temperature, chemical composition of the air molecules, and the composition and size of the aerosol, water droplets, and ice crystals. Outputs of the model are the monochromatic radiance and irradiance at each level. The use of the model in atmospheric correction of remotely sensed data is discussed.

Dozier, J.↗

Atmospheric model development

Spectral albedo measurements from the LANDSAT-4/5 thematic mappers require that spacecraft upwelling radiances be corrected for atmospheric absorption and scattering and for local surface illumination. A two-stream model is developed, with a lower boundary condition that varies with incidence angle. The TM data must be registered to digital terrain data. Reflectance from points in shadows can be used to estimate optical depth. The primary application is determination of the spectral albedo of snow. The TM is better-suited for this purpose than the MSS because of its larger dynamic range.

Source record↗

Reflectance measurements from Landsat Thematic Mapper over rugged terrain

Spectral albedo measurements from the Landsat-4/5 Thematic Mapper require that spacecraft upwelling radiances be corrected for atmospheric absorption and scattering and for local surface illumination. A two-stream model is developed, with a lower boundary condition that varies with incidence angle. TM data must be registered to digital terrain data. Reflectance from points in shadows can be used to estimate optical depth. The primary application here is determination of the spectral albedo of snow. The TM is better-suited for this purpose than the MSS because of its larger dynamic range.

Dozier, J.↗

Microwave backscatter coefficients of artificially grown first-year sea ice

The radar backscattering coefficient of simulated first year sea ice was measured at 5.2, 9.6, 13.6, and 16.6 GHz, using a dual-antenna FM-CW scatterometer. The measurements were corrected for antenna separation and beamwidth, to obtain true values of scattering coefficient. Above 15 deg, snow-covered and rough gray ice have similar angular responses, while the decrease in scattering coefficient with incidence angle is more rapid for smoother surfaces. True scattering coefficients and surface roughness data estimated with an antenna-beamwidth correction based on a physical-optics model give values close to those measured.

Xue, D.↗

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

MAIAC AO↗

Simulating Microwave and Radar Signals in Severe Weather Conditions

The development of radiative transfer simulators for radar and microwave signals, spanning a range of frequencies from 10 to 800 GHz, is paramount for enhancing weather forecasting accuracy, particularly for severe weather events. These tools facilitate the assimilation of microwave and radar observations into numerical weather prediction models, thereby improving accuracy of weather forecasts. Additionally, they directly simulate radar signals crucial for autonomous vehicle operation, with frequencies commonly used in radar systems such as 24, 74, 77, and 79 GHz. However, these frequencies are susceptible to weather phenomena like severe rain and snow, which can significantly impact vehicle safety and performance. These simulation tools, including radiative transfer simulators, serve a dual purpose. Firstly, they enhance forecasts for severe weather events, contributing to autonomous vehicle safety by providing early warnings and risk assessments. Secondly, they enable the direct simulation of radar signals in autonomous vehicle driving systems, allowing researchers and engineers to evaluate radar system performance under various weather conditions. In addition to the radar signal simulator, this abstract discusses the incorporation of advanced scattering properties developed using the discrete dipole approximation (DDA). The DDA technique enhances scattering calculations for frozen hydrometeors at microwave frequencies, thereby improving the accuracy of radar signal simulations and enabling more accurate assessments of radar system performance in adverse weather conditions. In summary, this abstract explores the development and utilization of comprehensive simulation tools, emphasizing their significance in simulating microwave and radar signals and improving weather forecasts. Special attention is given to the simulation of radar signals at critical frequencies for autonomous vehicle sensing and navigation, addressing challenges posed by severe weather phenomena and their effects on signal propagation and detection

Isaac Moradi↗

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

Spangenberg, Douglas A.↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗

The Role of Aerosols on Precipitation Processes

Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗

Climate Quality Broadband and Narrowband Solar Reflected Radiance Calibration Between Sensors in Orbit

vAs the potential impacts of global climate change become more clear [1], the need to determine the accuracy of climate prediction over decade-to-century time scales has become an urgent and critical challenge. The most critical tests of climate model predictions will occur using observations of decadal changes in climate forcing, response, and feedback variables. Many of these key climate variables are observed by remotely sensing the global distribution of reflected solar spectral and broadband radiance. These "reflected solar" variables include aerosols, clouds, radiative fluxes, snow, ice, vegetation, ocean color, and land cover. Achieving sufficient satellite instrument accuracy, stability, and overlap to rigorously observe decadal change signals has proven very difficult in most cases and has not yet been achieved in others [2]. One of the earliest efforts to make climate quality observations was for Earth Radiation Budget: Nimbus 6/7 in the late 1970s, ERBE in the 1980s/90s, and CERES in 2000s are examples of the most complete global records. The recent CERES data products have carried out the most extensive intercomparisons because if the need to merge data from up to 11 instruments (CERES, MODIS, geostationary imagers) on 7 spacecraft (Terra, Aqua, and 5 geostationary) for any given month. In order to achieve climate calibration for cloud feedbacks, the radiative effect of clear-sky, all-sky, and cloud radiative effect must all be made with very high stability and accuracy. For shortwave solar reflected flux, even the 1% CERES broadband absolute accuracy (1-sigma confidence bound) is not sufficient to allow gaps in the radiation record for decadal climate change. Typical absolute accuracy for the best narrowband sensors like SeaWiFS, MISR, and MODIS range from 2 to 4% (1-sigma). IPCC greenhouse gas radiative forcing is approx. 0.6 W/sq m per decade or 0.6% of the global mean shortwave reflected flux, so that a 50% cloud feedback would change the global reflected flux by approx. 0.3 W/sq m or 0.3% per decade in broadband SW calibration change. Recent results comparing CERES reflected flux changes with MODIS, MISR, and SeaWiFS narrowband changes concluded that only SeaWiFS and CERES were approaching sufficient stability in calibration for decadal climate change [3]. Results using deep convective clouds in the optically thick limit as a stability target may prove very effective for improving past data sets like ISCCP. Results for intercalibration of geostationary imagers to CERES using an entire month of regional nearly coincident data demonstrates new approaches to constraining the calibration of current geostationary imagers. The new Decadal Survey Mission CLARREO is examining future approaches to a "NIST-in-Orbit" approach of very high absolute accuracy reference radiometers that cover the full solar and infrared spectrum at high spectral resolution but at low spatial resolution. Sampling studies have shown that a precessing CLARREO mission could calibrate other geo and leo reflected solar radiation and thermal infrared sensors.

Wielicki, Bruce A.↗

Evaluation of Cloud Microphysics in JMA-NHM Simulations Using Bin or Bulk Microphysical Schemes through Comparison with Cloud Radar Observations

Numerical weather prediction (NWP) simulations using the Japan Meteorological Agency NonhydrostaticModel (JMA-NHM) are conducted for three precipitation events observed by shipborne or spaceborneW-band cloud radars. Spectral bin and single-moment bulk cloud microphysics schemes are employed separatelyfor an intercomparative study. A radar product simulator that is compatible with both microphysicsschemes is developed to enable a direct comparison between simulation and observation with respect to theequivalent radar reflectivity factor Ze, Doppler velocity (DV), and path-integrated attenuation (PIA). Ingeneral, the bin model simulation shows better agreement with the observed data than the bulk modelsimulation. The correction of the terminal fall velocities of snowflakes using those of hail further improves theresult of the bin model simulation. The results indicate that there are substantial uncertainties in the masssizeand sizeterminal fall velocity relations of snowflakes or in the calculation of terminal fall velocity of snowaloft. For the bulk microphysics, the overestimation of Ze is observed as a result of a significant predominanceof snow over cloud ice due to substantial deposition growth directly to snow. The DV comparison shows thata correction for the fall velocity of hydrometeors considering a change of particle size should be introducedeven in single-moment bulk cloud microphysics.

cloud radar↗