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At least 145 records · Page 8

July 2018 Mid-Atlantic Atmospheric River and Extreme Precipitation Event Captured by MERRA-2

Despite starting off the month with hardly any precipitation, July 2018 turned out to be one of the wettest on record in the Baltimore/Washington D.C. area. Daily rainfall records were demolished as an entire month's worth of precipitation fell in a matter of days and flash flood warnings covered the region. Beginning on July 21, 2018, an atmospheric river, or a narrow stream of enhanced water vapor transport, positioned itself over the region, bringing gray skies and precipitation for days. This was captured by GMAO's Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and given the nearly 40-year record of MERRA-2, can be placed in the context of past events and the overall climate for the region during July. Not only was the multi-day rainfall out of character, but large-scale features throughout July differed from climatology and there were even bigger differences in the state of the atmosphere between the first and second halves of July 2018.

Collow, Allie↗

An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO 2 , ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm 2 for the ARMP and 0.26 g/cm 2 for the AERONET datasets, with bias of 0.072 g/cm 2 and 0.096 g/cm 2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales.

54 ENVIRONMENTAL SCIENCES↗

Observational Evidence that Soil Moisture Variations Affect Precipitation

Land-atmosphere feedback, by which precipitation-induced soil moisture anomalies affect subsequent precipitation, may be an important element of Earth's climate system, but its very existence has never been demonstrated conclusively at regional to continental scales. Evidence for the feedback is sought in a 50-year observational precipitation dataset covering the United States. The precipitation variance and autocorrelation fields are characterized by features that agree (in structure, though not in magnitude) with those produced by an atmospheric general circulation model (AGCM). Because the model-generated features are known to result from land-atmosphere feedback alone, the observed features are highly suggestive of the existence of feedback in nature.

Koster, Randal D.↗

Establishing the Global Fresh Water Sensor Web

This paper presents an approach to measuring the major components of the water cycle from space using the concept of a sensor-web of satellites that are linked to a data assimilation system. This topic is of increasing importance, due to the need for fresh water to support the growing human population, coupled with climate variability and change. The net effect is that water is an increasingly valuable commodity. The distribution of fresh water is highly uneven over the Earth, with both strong latitudinal distributions due to the atmospheric general circulation, and even larger variability due to landforms and the interaction of land with global weather systems. The annual global fresh water budget is largely a balance between evaporation, atmospheric transport, precipitation and runoff. Although the available volume of fresh water on land is small, the short residence time of water in these fresh water reservoirs causes the flux of fresh water - through evaporation, atmospheric transport, precipitation and runoff - to be large. With a total atmospheric water store of approx. 13 x 10(exp 12)cu m, and an annual flux of approx. 460 x 10(exp 12)cu m/y, the mean atmospheric residence time of water is approx. 10 days. River residence times are similar, biological are approx. 1 week, soil moisture is approx. 2 months, and lakes and aquifers are highly variable, extending from weeks to years. The hypothesized potential for redistribution and acceleration of the global hydrological cycle is therefore of concern. This hypothesized speed-up - thought to be associated with global warming - adds to the pressure placed upon water resources by the burgeoning human population, the variability of weather and climate, and concerns about anthropogenic impacts on global fresh water availability.

Hildebrand, Peter H.↗

Meteorological, reference evapotranspiration and estimated transpiration data, July 2020-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.

54 ENVIRONMENTAL SCIENCES↗

Middle atmospheric electrodynamic modification by particle precipitation at the South Atlantic magnetic anomaly

Evidence for a localized middle atmospheric electrodynamic modification at low latitudes (southern Brazilian coast) of the South Atlantic Magnetic Anomaly (SAMA), in association with enhanced geomagnetic activity, are presented in a unified way combining recent observational efforts and related numerical studies. They involve a distortion effect in the fair weather electric field at balloon altitudes. This effect is attributed to a local intensification of energetic electron precipitation through a related middle atmospheric ionization enhancement and is elucidated by numeric simulation. From the electric field measurements and the numeric simulation, the intensification of precipitation is considered to occur in fairly narrow regions at the observed low L values (around L = 1.13) of the SAMA, with horizontal extensions of the order of a few hundred kilometers. A physical mechanism that could be responsible for this sort of intensification is suggested. Furthermore, a comparison of the phenomenon of middle atmospheric electrodynamic modification at the SAMA with a similar one at auroral latitudes, in response to enhanced solar and geomagnetic activity, is also given.

Gonzalez, W. D.↗

Micro Rain Radar Pro Data at the Argonne Testbed for Multiscale Observational Science obtained during the CROCUS Urban Integrated Field Laboratory

The Micro Rain Radar Pro (MRR-PRO) is a vertically pointing Ka-band Doppler radar designed to capture the fine-scale structure and evolution of precipitation. By recording the full Doppler spectrum at high temporal and spatial resolution, the MRR-PRO provides insight into both hydrometeor fall velocities and precipitation microphysics. From these spectra, key moments—reflectivity, mean Doppler velocity, spectral width, and rainfall rate—are derived and stored alongside the raw spectral data in CF/Radial 1.4-compliant files. Deployed at the Argonne Testbed for Multiscale Observational Studies (ATMOS) since November 2024, the MRR-PRO delivers vertical profiles at 70 m range resolution extending up to 4.5 km above ground level. These observations enable detailed analyses of precipitation type, intensity, and vertical structure, supporting process-level studies of cloud and precipitation dynamics in diverse weather regimes.

54 ENVIRONMENTAL SCIENCES↗

Seasonal Precipitation Classification during Surface Atmosphere Integrated Field Laboratory Campaign

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, conducted from September 2021 to June 2023 in Crested Butte, Colorado, aimed to characterize precipitation processes in the Upper Colorado River Basin (UCRB). This increased observations of snowfall accumulation in this hydrologically significant watershed would be useful for quantitative precipitation estimates (QPE). Therefore, the Surface Quantitative Precipitation Estimate (SQUIRE) product was developed using the ARM-supported Colorado State University (CSU) X-band Precipitation Radar. Although SQUIRE will be only released for snowfall, by categorizing precipitation types, users can effectively utilize relevant datasets under diverse meteorological conditions. Moreover, the dataset facilitates validation of the QPE product and the analysis of seasonal variations in precipitation types at the surface. Hydrometeors classes are organized based on their phase and physical characteristics mapping the CSU (both winter Summer) and Py-ART classifications into four groups. 1. Liquid Precipitation: includs drizzle, rain, and large raindrops. 2. Frozen Snow and Ice : Pure Snow, combining ice crystals, aggregates, and vertically oriented ice structures. 3. Dense and Large frozen hydrometeors: including low- and high-density graupel and dry hail. 4.Melting: Wet Snow and Melting Hail, hydrometeors exhibiting both liquid and frozen characteristics.

54 ENVIRONMENTAL SCIENCES↗

Scripts and raw/processed precipitation NRCS network data, Upper Colorado, 2008-2017

This data package consists of scripts and data that were used to generate all the results and figures for Mital et al., 2020 (https://doi.org/10.3389/frwa.2020.00020). The purpose of the study was to develop a new algorithm to impute (or gap-fill) missing daily precipitation data. Study area was the Upper Colorado Water Resources Region (UCWRR), over a time period of 2008-2017. In terms of data, the package consists of raw precipitation measurements from Natural Resources Conservation Service (NRCS) network. These raw measurements are compiled into a single csv file (NRCS_dates_2008_2017.csv). The corresponding metadata are compiled in Metadata_processed.csv. The package also consists of outputs generated during Baseline and Sequential imputation runs as documented in Mital et al., 2020. Scripts used to generate all the results and figures for Mital et al., 2020 are also uploaded. A readme file documenting the layout of the data archive is also uploaded, and a KML file shows the geographic range for the data.

54 ENVIRONMENTAL SCIENCES↗

Downscaled precipitation and mean air temperature datasets; East-Taylor subbasin; 2008-2019; daily temporal resolution; 400 m spatial resolution

This dataset provides gridded meteorological forcing data (specifically, daily precipitation and daily mean air temperature). The dataset has been generated by downscaling the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset from a spatial resolution of 800 m to 400 m. The time period is 2008-2019, and the mapped area is East Taylor subbasin in Upper Colorado. The data are in the form of NetCDF files, arranged by year. Compared to the PRISM dataset, the dates of the downscaled dataset are shifted backwards by one (e.g., downscaled data for May 25 corresponds to PRISM data for May 26). This temporal shifting makes the meteorological forcing correspond more closely to the prescribed date. The NetCDF format is a standard raster format that can be read using any Geographic Information System (GIS) software; plenty of modules exist in popular scripting languages (such as Python, R and Matlab) that can also be used to read NetCDF files.East_Taylor_Tavg_PRISM400 corresponds to mean air temperature.East_Taylor_Precip_PRISM400.zip corresponds to precipitation.The proprietary PRISM data (800 m resolution) were purchased with funding from the Watershed Function Scientific Focus Area supported by U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award no. DE-AC02-05CH11231.Dataset update on March 9, 2022:Uploaded new data files that are identical to the earlier files but are now in the NetCDF format, arranged by year. Earlier, the files were in the GeoTiff format, arranged by date.

54 ENVIRONMENTAL SCIENCES↗

CROCUS Weather Data at Argonne National Laboratory Prairie Site

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a prairie field site at Argonne National Laboratory in Lemont, Illinois. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. The data is aggregated into daily frequency to make it easier to process multiple days, and compress the higher-resolution fields. Each file contains one day's worth of data (24 hours, starting at 0000 UTC). File naming convention includes the project (CROCUS), location (atmos), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗

CROCUS Weather Data at University of Illinois - Chicago Tower

Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. These measurements are collected at the University of Illinois in Chicago, Illinois, on the meteorological tower near the greenhouse on campus. Data is available in the netCDF data format, we encourage data users review documentation through Project Pythia to understand how to work with netCDF data https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html. File naming convention includes the project (CROCUS), location (UIC), data level (raw, a1), date (year, month, day), and hour (0000).

54 ENVIRONMENTAL SCIENCES↗

A CloudSat Perspective of the Atmospheric Water Cycle and Precipitation: Recent Progress and Grand Challenges

Summary Global - mean precipitation - is controlled by Earth's energy balance and is a quantifiable consequence of the water vapor feedback. Predictability rests on the degree to which the water vapor feedback is predictable. Regional scale - to a significant extent, changes are shaped by atmospheric circulation changes but we do not know the extent to which regional scale changes are predictable. The impacts of changes to atmospheric circulation on regional scale water cycle changes can be dramatic. Process - scale - significant biases to the CHARACTER of precipitation (frequency and intensity) is related to how the precipitation process is parameterized in models. Aerosol - We still do not know the extent to which the water cycle is influenced by aerosol but anecdotal evidence is building. The character of precipitation is affected by the way aerosol influence clouds and thus affects the forcing of the climate system through the albedo effect. Observations - we still have a way to go and need to approach the problem in a more integrated way (tie clouds, aerosol and precipitation together and then link to soil moisture, etc). Globally our capabilities seriously lag behind the science and model development.

terrestrial water cycles↗

The precipitation of energetic heavy ions into the upper atmosphere of Jupiter

Evidence for auroral particle precipitation at Jupiter was provided by the ultraviolet spectrometers on board the Voyager 1 and 2 spacecraft and by the International Ultraviolet Explorer. Magnetospheric measurements made by instruments on board the Voyager spacecraft indicate that energetic sulfur and oxygen ions are precipitating into the upper atmosphere of Jupiter. A theoretical model describing the interaction of precipitating oxygen with the Jovian atmosphere was constructed. The auroral energy is deposited in the atmosphere by means of ionization, excitation, and dissociation and heating of the atmospheric gas. Energetic ion precipitation and electron precipitation are shown to have similar effects on the atmosphere and ionosphere of Jupiter.

Horanyi, M.↗

NASA’s Atmosphere Observing System (AOS), From A Precipitation Perspective

NASA is developing the Atmosphere Observing System (AOS) mission as part of its Earth System Observatory (ESO) in response to priorities identified in the 2017 Earth Science Decadal Survey. AOS addresses the Decadal Survey’s call for missions measuring the targeted observables “clouds, convection, and precipitation”; “aerosol and cloud radiative properties”, and “aerosol vertical profiles”. AOS is currently in Phase A, the concept and technology development phase, with plans for satellite launches in the late 2020’s and early 2030’s, and suborbital measurements to include field campaigns after those satellite launches. Key precipitation-related instrumentation includes Doppler radars capable of measuring clouds and precipitation, and passive microwave radiometers with channels between 89-700 GHz. Other instrumentation includes dual-wavelength backscatter lidars, a multi-wavelength and multi-angle polarimeter, a far infrared imaging radiometer, and aerosol and moisture limb sounders that will contribute to studies of coupled aerosol-cloud-precipitation processes. From the perspective of precipitation science, a Ku-band Doppler radar in a 55° inclined orbit provided by JAXA will continue the heritage of precipitation radar measurements made by the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM), while adding information about Doppler-derived particle vertical motions. With assumptions about particle terminal velocities, the Doppler measurements will enable estimates of the vertical air motion in storms. A higher frequency (W and/or Ka band) radar on a satellite in a polar sun-synchronous orbit will add similar information with greater sensitivity to clouds and to light precipitation. Passive microwave radiometers for AOS will be less capable than those from TRMM and GPM from a precipitation-measurement perspective, but more capable of adding information about cloud processes. Synergies among these and other instruments are expected to advance process-level understanding of aerosols, clouds, and precipitation.

Daniel J Cecil↗

Biases in Total Precipitable Water Vapor Climatologies from Atmospheric Infrared Sounder and Advanced Microwave Scanning Radiometer

We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.

Atmospheric Infrared Sounder (AIRS)↗

Electrostatic Precipitation for Cleaning Mars Atmospheric ISRU Intakes

Future Mars ISRU atmospheric intakes are estimated to ingest several hundred grams of dust over their lifetime. The Electrostatics and Surface Physics Laboratory at NASA's Kennedy Space Center is developing a dust removal system based on a mature terrestrial technology - electrostatic precipitation. In this technology, a high voltage and grounded collection electrode create a corona discharge which charges particles in a dust-laden flow. The resulting electric field between the high voltage and collection electrodes drive the charged particles toward the collection electrode. This paper presents the design of the electrostatic precipitator and preliminary results.

Precipitator↗