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DOE OSTI2021

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Further, comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Improving GCM Representation of Convective Cloud Microphysics by Using ARM Raman Lidar and Cloud Radar Observations

The overall objective of this Department of Energy (DOE) Atmospheric System Research (ASR) funded project is to improve the representation of convective cloud microphysics in global climate models (GCMs) and check it by comparing the model simulations with observations. We have derived the cloud ice water content by synthesizing ARM Raman lidar (RL) and cloud radar observations at the Atmospheric Radiation Measurement (ARM) sites. Noting that the simulated anvil clouds in terms of their macro- and micro-physical properties are sensitive to the parameterization of convective microphysical processes, observed ice water content in anvil clouds provides a useful constraint on these parameterizations. We have improved the convective microphysics parameterization scheme by (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. We have examined the impact of improved convective cloud microphysics parameterization on the simulated global climate from GCM simulations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

terminal velocity↗

DOE OSTI2022

Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States

Despite the close linkage between extreme floods and snowmelt, particularly through rain-on-snow (ROS), hydrologic infrastructure is mostly designed based on standard precipitation Intensity-Duration-Frequency curves (PREC-IDF) that neglect snow processes in runoff generation. For snow-dominated regions, such simplification could result in substantial errors in estimating extreme events and infrastructure design risk. To address this long-standing problem, we applied the Next Generation IDF (NG-IDF) technique to estimate design basis extreme events for different durations and return periods in the conterminous United States (CONUS) to distinctly represent the contribution of rain, snowmelt, and ROS events to the amount of water reaching the land surface. A suite of datasets were developed to characterize the magnitude, trend, seasonality, and dominant mechanism of extreme events for over 200,000 locations. Infrastructure design risk associated with the use of PREC-IDF was estimated. Accuracy of the model simulations used in the analyses was confirmed by long-term snow data at over 200 Snowpack Telemetry stations. The presented spatially continuous datasets are readily usable and instrumental for supporting site-specific infrastructure design.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Impacts of aerosol size-dependent below-cloud scavenging on tropospheric aerosol in the NASA GEOS model

Wet deposition is the major sink for a suite of tropospheric aerosols, and thus largely affects the global distribution and lifetime of aerosols as well as the formation of clouds in the atmosphere. In this study, we implement the aerosol size-dependent below-cloud scavenging (BCS; washout) parameterization of Croft et al. (Atmos. Chem. Phys., 2009; hereafter referred to as C09) in the GOCART bulk aerosol scheme coupled with the NASA Goddard Earth Observing System (GEOS) model, and evaluate the simulated tropospheric aerosols against surface, airborne, and satellite observations. The current below-cloud scavenging in GOCART employs a first-order removal function with a constant scavenging coefficient that is independent of aerosol sizes and precipitation fluxes. The C09 BCS parameterization instead calculates aerosol below-cloud scavenging coefficients based on a size-dependent collision efficiency between aerosol particles and raindrops (or snow crystals). A look-up table of compiled collision efficiencies provides scavenging coefficients for sixty aerosol sizes and nine rain flux rates. We determine instantaneous coefficients according to the C09 BCS look-up table, precipitation fluxes, and a log-normal size distribution of aerosols. The implemented BCS parameterization tends to result in a large diversity of scavenging coefficient values with higher magnitudes, leading to more efficient scavenging. The model-simulated global mean tropospheric Pb-210 aerosol lifetime decreases from 7.4 days to 5.8 days. The separate consideration of rain and snow conditions in the scavenging coefficient lookup table leads to a bi-mode distribution of scavenging coefficients. These changes also cause increased mass fractions of smaller aerosols compared to the current simulation. We examine the impacts of the C09 BCS parameterization on the simulated aerosol vertical profiles, tropospheric lifetimes, and deposition fluxes through comparisons with NASA aircraft measurements (ATom), surface observations of aerosol concentrations (IMPROVE) and wet deposition fluxes (NADP and APQMP), and MODIS aerosol optical depth (AOD) retrievals.

Aerosols↗

DOE OSTI2022

Variability of Snow and Rainfall Partitioning Into Evapotranspiration and Summer Runoff Across Nine Mountainous Catchments

Abstract Understanding the partitioning of snow and rain contributing to either catchment streamflow or evapotranspiration (ET) is of critical relevance for water management in response to climate change. To investigate this partitioning, we use endmember splitting and mixing analyses based on stable isotope ( 18 O) data from nine headwater catchments in the East River, Colorado. Our results show that one third of the snow partitions to ET and 13% of the snowmelt sustains summer streamflow. Only 8% of the rainfall contributes to the summer streamflow, because most of the rain (67%) partitions to ET. The spatial variability of precipitation partitioning is mainly driven by aspect and tree cover across the sub‐catchments. Catchments with higher tree cover have a higher share of snow becoming ET, resulting in less snow in summer streamflow. Summer streamflow did not contain more rain with higher rainfall sums, but more rain was taken up in ET.

58 GEOSCIENCES↗

NASA NTRS2017

Contribution of Lake-Effect Snow to the Catskill Mountains Snowpack

Meltwater from snow that falls in the Catskill Mountains in southern New York contributes to reservoirs that supply drinking water to approximately nine million people in New York City. Using the NOAA National Ice Centers Interactive Multisensor Snow and Ice Mapping System (IMS) 4km snow maps, we have identified at least 32 lake-effect (LE) storms emanating from Lake Erie andor Lake Ontario that deposited snow in the CatskillDelaware Watershed in the Catskill Mountains of southern New York State between 2004 and 2017. This represents a large underestimate of the contribution of LE snow to the Catskills snowpack because many of the LE snowstorms are not visible in the IMS snow maps when they travel over snow-covered terrain. Most of the LE snowstorms that we identified originate from Lake Ontario but quite a few originate from both Erie and Ontario, and a few from Lake Erie alone. Using satellite, meteorological and reanalysis data we identify conditions that contributed to LE snowfall in the Catskills. Clear skies following some of the storms permitted measurement of the extent of snow cover in the watershed using multiple satellite sensors. IMS maps tend to overestimate the extent of snow compared to MODerate resolution Imaging Spectroradiometer (MODIS) and Landsat-derived snow-cover extent maps. Using this combination of satellite and meteorological data, we can begin to quantify the important contribution of LE snow to the Catskills Mountain snowpack. Changes that are predicted in LE snowfall from the Great Lakes could impact the distribution of rain vs snow in the Catskills which may affect future reservoir operations in the NYC Water Supply System.

Lake Ontario↗

DOE OSTI2020

Hydrologic Model Files (PRMS) for Historical Conditions in the East River Watershed, Colorado between 1987-2019

The data package contains model input and output file for the East River watershed (85 km2) located in the headwaters of the Colorado River. The model is the U.S. Geological Survey (USGS) Precipitation-Modeling Runoff System (PRMS) for the historical, or baseline, condition (1987-2019) to assess the efficiency of summer monsoon rains to generate streamflow. The finite difference grid resolution is 100 m with elevations resampled from the USGS National Elevation Dataset. LANDFIRE raster data is used to derive parameters of dominant cover type, summer and winter cover density, canopy interception characteristics for snow and rain and transmission coefficient for shortwave radiation. Climate forcing uses minimum and maximum daily temperature lapse rates defined by the two Snow Telemetry (SNOTEL) stations located in the vicinity of the East River adjusted for aspect. Schofield SNOTEL snowfall is spatially distributed using LiDAR derived snow depth observations from the Airborne Snow Observatory (ASO) flown 4 April 2016. Snow depths are converted to snow water equivalent based on ground surveys and density modeling. Rainfall is spatially distributed using the monthly Parameter-elevation Relationships on Independent Slopes Model 30-year monthly averages. Simulated solar radiation is calibrated to match weather station observations. Model verification of snow water equivalent (SWE) accumulation and ablation relies on the 2018 and 2019 ASO maps and weather station snow depth. The data package contains model input files in text format, model documentation in pfd and a readme.txt file to help users understand the file structure to run the program.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Atmospheric transport of pollutants from North America to the North Atlantic Ocean

Ground-based measurements strongly support the hypothesis that pollutant materials of anthropogenic origin are being transported over long distances in the midtroposphere and are a significant source of acid rain, acid snow, trace metal deposition, ozone and visibility-reducing aerosols in remote oceanic and polar regions of the Norhern Hemisphere. Atmospheric sulphur budget calculations and studies of acid rain on Bermuda indicate that a large fraction of pollutant materials emitted into the atmosphere in eastern North America are advected eastwards over the North Atlantic Ocean. The first direct airborne measurements of the vertical distribution of tropospheric aerosols over the western North Atlantic is reported here. A newly developed airborne differential adsorption lidar system was used to obtain continuous, remotely sensed aerosol distributions along its flight path. The data document two episodes of long-distance transport of pollutant materials from North America over the North Atlantic Ocean.

Harriss, R. C.↗

NASA NTRS2021

Assessing the Impact of Light/Shallow Precipitation Retrievals from Satellite-Based Observations Using Surface Radar and Micro Rain Radar Observations

The accurate representation of precipitation across the Earth’s surface is crucial to furthering our knowledge and understanding of the Earth System and its component processes. Precipitation poses a number of challenges, particularly due to the variability of precipitation over time and space and whether it falls as snow or rain. While conventional measures of precipitation are reasonably good at the location of their measurement, their distribution across the Earth’s surface is uneven with some regions having no surface measurements. Spaceborne sensors have the capability of providing regular observations across the Earth’s surface that can provide estimates of precipitation. However, the estimation of precipitation from satellite observations is not necessarily straightforward. Visible and/or infrared techniques rely upon imprecise cloud-top to surface precipitation relationships, while the sensitivity of passive microwave techniques to different precipitation types is not consistent. Active microwave (radar) observations provide the most direct satellite measurements of precipitation but cannot provide estimates close to the surface and are generally not sufficiently sensitive to resolve light precipitation. This is particularly problematic at mid to high latitudes, where light and/or shallow precipitation dominates. This paper compares measurements made by ground-based weather radars, Micro Rain Radars and the spaceborne Dual-frequency Precipitation Radar to study both light precipitation intensity and shallow precipitation occurrence and to assess their impact on satellites retrievals of precipitation at the mid to high latitudes.

light precipitation↗

DOE OSTI2025

Controls From Above and Below: Snow, Soil, and Steepness Drive Diverging Trends of Subsurface Water and Streamflow Dynamics

ABSTRACT The importance of subsurface water dynamics, such as water storage and flow partitioning, is well recognised. Yet, our understanding of their drivers and links to streamflow generation has remained elusive, especially in small headwater streams that are often data‐limited but crucial for downstream water quantity and quality. Large‐scale analyses have focused on streamflow characteristics across rivers with varying drainage areas, often overlooking the subsurface water dynamics that shape streamflow behaviour. Here we ask the question: What are the climate and landscape characteristics that regulate subsurface dynamic storage, flow path partitioning, and dynamics of streamflow generation in headwater streams? To answer this question, we used streamflow data and a widely‐used hydrological model (HBV) for 15 headwater catchments across the contiguous United States. Results show that climate characteristics such as aridity and precipitation phase (snow or rain) and land attributes such as topography and soil texture are key drivers of streamflow generation dynamics. In particular, steeper slopes generally promoted more streamflow, regardless of aridity. Streams in flat, rainy sites (< 30% precipitation as snow) with finer soils exhibited flashier regimes than those in snowy sites (> 30% precipitation as snow) or sites with coarse soils and deeper flow paths. In snowy sites, less weathered, thinner soils promoted shallower flow paths such that discharge was more sensitive to changes in storage, but snow dampened streamflow flashiness overall. Results here indicate that land characteristics such as steepness and soil texture modify subsurface water storage and shallow and deep flow partitioning, ultimately regulating streamflow response to climate forcing. As climate change increases uncertainty in water availability, understanding the interacting climate and landscape features that regulate streamflow will be essential to predict hydrological shifts in headwater catchments and improve water resources management.

Kerins, Devon [Department of Civil and Environment↗

NASA NTRS2019

Assimilation of GPM Retrieved Surface Meteorology Variables with ICE-POP Case Studies

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM has a broad global coverage ~70°S – 70°N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall.

GPM retrieval product↗

NASA NTRS2017

Chapter 7: Precipitation Change in the United States

Annual precipitation has decreased in much of the West, Southwest, and Southeast and increased in most of the Northern and Southern Plains, Midwest, and Northeast. A national average increase of 4% in annual precipitation since 1901 is mostly a result of large increases in the fall season. Heavy precipitation events in most parts of the United States have increased in both intensity and frequency since 1901. There are important regional differences in trends, with the largest increases occurring in the northeastern United States. In particular, mesoscale convective systems (organized clusters of thunderstorms)-the main mechanism for warm season precipitation in the central part of the United States-have increased in occurrence and precipitation amounts since 1979. The frequency and intensity of heavy precipitation events are projected to continue to increase over the 21st century (high confidence). Mesoscale convective systems in the central United States are expected to continue to increase in number and intensity in the future. There are, however, important regional and seasonal differences in projected changes in total precipitation: the northern United States, including Alaska, is projected to receive more precipitation in the winter and spring, and parts of the southwestern United States are projected to receive less precipitation in the winter and spring. Northern Hemisphere spring snow cover extent, North America maximum snow depth, snow water equivalent in the western United States, and extreme snowfall years in the southern and western United States have all declined, while extreme snowfall years in parts of the northern United States have increased. Projections indicate large declines in snowpack in the western United States and shifts to more precipitation falling as rain than snow in the cold season in many parts of the central and eastern United States.

Easterling, D. R.↗

DOE OSTI2022

Southern Ocean Precipitation Characteristics Observed From CloudSat and Ground Instrumentation During the Macquarie Island Cloud & Radiation Experiment (MICRE): April 2016 to March 2017

A 1-year blended surface precipitation data set using Parsivel disdrometer, surface W-band radar, and tipping bucket measurements is produced for the Macquarie Island Cloud and Radiation Experiment (MICRE) and compared with retrievals from CloudSat (spaceborne 94 GHz radar). Surface precipitation was observed 44% ± 4% of the time between April 2016 and March 2017. Precipitation composed primarily of small particles (diameter <1 mm) occurred about 36% ± 2% of the time, constituting 10% of total accumulation. Remaining precipitation contained enough large particles such that the disdrometer could be used to identify the precipitation type as rain, ice, snow or wet snow. Seasonal and annual statistics on frequency of occurrence and accumulation for each precipitation type observed during MICRE are presented. Most ice and mixed phase precipitation was shallow, originating at a height of 3 km or lower, and occurred most often when Macquarie Island was to the northwest of the nearest cyclonic low-pressure center. In contrast, rain was more often deep and occurred most frequently when the island was to the southeast of cyclonic lows. A weak diurnal cycle in frequency and mean rate was present with a minimum between 12:00 and 14:00 local time and maximum between 03:00 and 06:00 local time. The CloudSat 2C-Precip-Column product missed the lightest precipitation (because the near-surface reflectivity is <-15 dBZ) and overestimated total liquid precipitation and occurrence of mixed phase precipitation, but captured reasonably well the distribution of rain rates for rates >0.5 mm/hr.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

Tracking the Impacts of Precipitation Phase Changes Through the Hydrologic Cycle in Snowy Regions: From Precipitation to Reservoir Storage

Cool season precipitation plays a critical role in regional water resource management in the western United States. Throughout the twenty-first century, regional precipitation will be impacted by rising temperatures and changing circulation patterns. Changes to precipitation magnitude remain challenging to project; however, precipitation phase is largely dependent on temperature, and temperature predictions from global climate models are generally in agreement. To understand the implications of this dependence, we investigate projected patterns in changing precipitation phase for mountain areas of the western United States over the twenty-first century and how shifts from snow to rain may impact runoff. We downscale two bias-corrected global climate models for historical and end-century decades with the Weather Research and Forecasting (WRF) regional climate model to estimate precipitation phase and spatial patterns at high spatial resolution (9 km). For future decades, we use the RCP 8.5 scenario, which may be considered a very high baseline emissions scenario to quantify snow season differences over major mountain chains in the western U.S. Under this scenario, the average annual snowfall fraction over the Sierra Nevada decreases by >45% by the end of the century. In contrast, for the colder Rocky Mountains, the snowfall fraction decreases by 29%. Streamflow peaks in basins draining the Sierra Nevada are projected to arrive nearly a month earlier by the end of the century. By coupling WRF with a water resources model, we estimate that California reservoirs will shift towards earlier maximum storage by 1–2 months, suggesting that water management strategies will need to adapt to changes in streamflow magnitude and timing.

Melissa L. Wrzesien↗

NASA NTRS2018

Impact of GPM Rainrate Data Assimilation on Simulation of Hurricane Harvey (2017)

Built upon Tropical Rainfall Measuring Mission (TRMM) legacy for next-generation global observation of rain and snow. The GPM was launched in February 2014 with Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) onboard. The GPM has a broad global coverage approximately 70deg S -70deg N with a swath of 245/125-km for the Ka (35.5 GHz)/Ku (13.6 GHz) band radar, and 850-km for the 13-channel GMI. GPM also features better retrievals for heavy, moderate, and light rain and snowfall To develop methodology to assimilate GPM surface precipitation data with Grid-point Statistical Interpolation (GSI) data assimilation system and WRF ARW model To investigate the potential and the value of utilizing GPM observation into NWP for operational environment The GPM rain rate data has been successfully assimilated using the GSI rain data assimilation package. Impacts of rain rate data have been found in temperature and moisture fields of initial conditions. 2.Assimilation of either GPM IMERG or GPROF rain product produces significant improvement in precipitation amount and structure for Hurricane Harvey (2017) forecast. Since IMERG data is available half-hourly, further forecast improvement is expected with continuous assimilation of IMERG data

Precipitation↗

DOE OSTI2021

Future Changes in Snowpack, Snowmelt, and Runoff Potential Extremes Over North America

Snowpack and snowmelt-driven extreme events (e.g., floods) have large societal consequences including infrastructure failures. However, it is not well understood how projected changes in the snow-related extremes differ across North America. Using dynamically downscaled regional climate model (RCM) simulations, we found that the magnitudes of extreme snow water equivalent, snowmelt, and runoff potential (RP; snowmelt plus precipitation) decrease by 72%, 73%, and 45%, respectively, over the continental United States and southern Canada but increase by up to 8%, 53%, and 41% in Alaska and northern Canada by the late 21st century. In California and the Pacific Northwest, there is a notable increase in extreme RP by 21% contrary to a decrease in snowmelt by 31% by the late century. These regions could be vulnerable to larger rain-on-snow floods in a warmer climate. Regions with a large variability among RCM ensembles are identified, which require further investigation to reduce the regional uncertainties.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Future Changes in Snowpack, Snowmelt, and Runoff Potential Extremes Over North America

Eunsang Cho↗