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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Performance of New Near-Real-Time PERSIANN Product (PDIR-Now) for Atmospheric River Events over the Russian River Basin, California

Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for water management and early warning systems of flooding and landslides over these regions. At the same time, high-quality near-real-time measurements of AR precipitation remain challenging due to the complex topographic features of land surface and meteorological conditions of the region: specifically, orographic features occlude radar measurements while infrared-based algorithms face challenges, differentiating between both cold brightband (BB) precipitation and the warmer nonbrightband (NBB) precipitation. It should be noted that the latter precipitation is characterized by greater orographic enhancement. In this study, we evaluate the performance of a recently developed near-real-time satellite precipitation algorithm: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate-Now (PDIR-Now). This model is primarily dependent on infrared information from geostationary satellites as input; consequently, PDIR-Now has the advantage of short data latency, 15–60-min delay between observation to precipitation product delivery. The performance of PDIR-Now is analyzed with a focus on AR-related events for cases dominated by NBB and BB precipitation over the Russian River basin. In our investigations, we utilize S-band (3-GHz) precipitation profilers with Joss/Parsivel disdrometer measurements at the Middletown and Santa Rosa stations to classify BB and NBB precipitation events. In general, our analysis shows that PDIR-Now is more skillful in retrieving precipitation rates over both BB and NBB events across the topologically complex study area as compared to PERSIANN-Cloud Classification System (CCS). Also, we discuss the performance of well-known operational near-real-time precipitation products from 2017 to 2019. Conventional categorical and volumetric categorical indices, as well as continuous statistical metrics, are used to show the differences between various high-resolution precipitation products such as Multi-Radar Multi-Sensor (MRMS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Effect of Niobium on the Secondary Precipitates and Tempering Resistance of Spray-Formed M3:2 High-Speed Steel

The precipitation of secondary carbides in spray-formed M3:2 high-speed steels with or without 2% niobium (Nb) addition during overtempering at 600 °C was characterized, and the carbides were identified in detail using transmission electron microscopy. Strengthening in the peak-hardened state is due to coherent precipitates of types MC and M{sub 2}C. During overtempering, the hardness of M3:2 steel greatly decreases due to M{sub 2}C coarsening with the precipitation of M{sub 3}C carbide, whereas the very fine and dense nature of the M{sub 2}C precipitates is responsible for the remarkable long-time strength exhibited by the Nb-containing steel. The MC precipitates, however, are fairly stable. The addition of Nb results in substantial dissolution of Mo and Cr into the matrix prior to tempering, which refines the secondary M{sub 2}C precipitate dispersion and delays overaging reactions; therefore, superior tempering resistance can be obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Thermodynamic versus Dynamic Controls on Extreme Precipitation in a Warming Climate from the Community Earth System Model Large Ensemble

The moisture budget is evaluated as a function of the probability distribution of precipitation for the end of the twentieth century and projected end of the twenty-first century in the Community Earth System Model Large Ensemble. For a given precipitation percentile, a conditional moisture budget equation relates precipitation minus evaporation ( P − E) to vertical moisture transport, horizontal moisture advection, and moisture storage. At high percentiles, moisture advection and moisture storage cancel and evaporation is negligible, so that precipitation is approximately equal to vertical moisture transport, and likewise for projected changes. Therefore, projected changes to extreme precipitation are approximately equal to the sum of thermodynamic and dynamic tendencies, representing changes to the vertical profiles of moisture content and mass convergence, respectively. The thermodynamic tendency is uniform across percentiles and regions as an intensification of the hydrological cycle, but the dynamic tendency is more complex. For extreme events, per degree of warming, in the mid-to-high latitudes the dynamic tendency is small, so that precipitation approximately scales by the Clausius–Clapeyron 7% K −1 increase. In the subtropics, a drying tendency originating from dynamics offsets the thermodynamic wetting tendency, with the net effect on precipitation varying among regions. The effect of this dynamic drying decreases with increasing percentile. In the deep tropics, a positive dynamic tendency occurs with magnitude similar to or greater than the positive thermodynamic tendency, resulting in generally a 10%–15% K −1 precipitation increase, and with a >25% K −1 increase over the tropical east Pacific. This reinforcing dynamical tendency increases rapidly for high percentiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of the mid-latitude zonal circulation on dynamic mechanism of anomalous precipitation over China in summer 2021

China was hit by extreme precipitation in July and August of 2021 along with significant monthly variation. The positive precipitation anomalies observed in July were mainly located in eastern China, but these anomalies shifted to the middle and lower reaches of the Yangtze River (MLYR) in August. In this study, we investigated the July and August precipitation anomaly dynamics based on the three-pattern decomposition of global atmospheric circulation (3P-DGAC) method. The results showed that the mid-latitude zonal circulation played a dominant role in July 2021, causing anomalous positive relative vorticity advection over the center of the positive precipitation anomalies, thus providing strong convective activity for the anomalous precipitation. Nevertheless, the August anomalies could be better explained from a climate perspective. The anomalous relative vorticity distribution patterns recorded in August were often accompanied by extreme precipitation in the MLYR, and the negative relative vorticity anomalies identified in Northeast Asia also played a crucial role. In conclusion, the mechanisms of precipitation anomalies in July and August 2021 were almost completely disparate. In this study, we emphasized the role of the mid-latitude zonal circulation in extreme precipitation events, and suggested that the impact of mid-latitude zonal circulation will be further accentuated under global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Analyzing urban ecosystem variation in the City of Dongguan: A stepwise cluster modeling approach

Highlights: • A stepwise cluster modeling approach is proposed for urban ecosystem simulation. • Nonlinear relationship is established among NDVI and multiple drivers. • Vegetation conditions get better gradually from the north to the south of Dongguan. • Ecosystem in the east of Dongguan is sensitive to growth of economy and population. In this study, a stepwise cluster modeling approach (SCMA) is developed for analyzing urban ecosystem variation via Normalized Difference Vegetation Index (NDVI). NDVI is an indicator of vegetation growth and coverage and useful in reflecting urban ecosystem. SCMA is established on a cluster tree that can characterize the complex relationship between independent and dependent variables. SCMA is applied to the City of Dongguan for simulating the urban NDVI and identifying associated drivers of human activity, topography and meteorology without specific functions. Results show that SCMA performances better than conventional statistical methods, illustrating the ability of SCMA in capturing the complex and nonlinear features of urban ecosystem. Results disclose that human activities play negative effects on NDVI due to the destruction of green space for pursuing more space for buildings. NDVI reduces gradually from the south part to the north part of Dongguan due to increased gross domestic product and population density, indicating that the ecosystem in Dongguan is better in the south part. NDVI in the northeast part (dominated by agriculture) is sensitive to the growth of economy and population. More attention should be paid to this part for sustainable development, such as increasing afforestation, planting grass and constructing parks. Precipitation has a positive effect on NDVI due to the promotion of soil moisture that is beneficial to plants’ growth. Awareness of these complexities is helpful for sustainable development of urban ecosystem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Correlation Between Structure and Properties of Low-Carbon Cu-Ni-Mo-Ti-Nb Ultrahigh-Strength Steel

Low-carbon Cu-Ni-Mo-Ti-Nb steel having more than 1700 MPa tensile strength and good low-temperature impact toughness was successfully designed and processed for automobile, defence and structural applications. The steel was thermomechanical controlled processed at a different finish rolling temperatures (750-850 °C) and cooled at two different conditions: air cooling and water quenching. Evolutions of microstructure and precipitates were thoroughly characterised to understand the effect of different factors, such as steel composition, finish rolling temperature and cooling rate on the mechanical properties. The results indicate that the steel processed at 750 °C finish rolling temperature (FRT) followed by water quenching has exhibited superior tensile properties with a yield strength of 1034-1449 MPa, the tensile strength of 1598-1726 MPa and total elongation of 10-13%. Such an ultrahigh-strength level is primarily attributed to the combined effect of lower bainite dominated microstructure along with precipitation hardening. The satisfactory low-temperature toughness is promoted by low finish rolling temperature and higher amount of misorientation offered by the boundaries within the lower bainite.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Microbial Activity and Precipitation at Solution-Solution Mixing Zones in Porous Media -- Subsurface Biogeochemical Research

The goal for this research was to understand how best to add compounds to receptive microbial communities in porous media in order to achieve optimal calcite precipitation in a volumetrically significant space and to understand the physiological health of the cells that are responsible for the calcite precipitation. The specific objectives were to: (1) develop better tools for visually examining biofilms in porous media and calcium carbonate precipitation being mediated by microbes in porous media, and (2) demonstrate the effectiveness of using that tool within a flow cell model system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Investigations of segregation phenomena in highly strained Mn-doped Ge wetting layers and Ge quantum dots embedded in silicon

In this Letter, we investigate manganese diffusion and the formation of Mn precipitates in highly strained, few monolayer thick, Mn-doped Ge wetting layers and nanometric size Ge quantum dot heterostructures embedded in silicon. We show that in this Ge(Mn)/Si system manganese always precipitates and that the size and the position of Mn clusters (precipitates) depend on the growth temperature. At high growth temperature, manganese strongly diffuses from germanium to silicon, whereas decreasing the growth temperature reduces the manganese diffusion. In the germanium quantum dots layers, Mn precipitates are detected, not only in partially relaxed quantum dots but also in fully strained germanium wetting layers between the dots.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Survival of Snow in the Melting Layer: Relative Humidity Influence

This study quantifies how far snow can fall into the melting layer (ML) before all snow has melted by examining a combination of in-situ observations from aircraft measurements in Lagrangian spiral descents from above through the ML and descents and ascents into the ML, as well as an extensive database of NOAA surface observer reports during the past 50 years. The airborne data contain information on the particle phase (solid, mixed, or liquid), population size distributions and shapes, along with temperature, relative humidity, and vertical velocity. A wide range of temperatures and ambient relative humidities are used for both the airborne and ground-based data. It is shown that an ice bulb temperature of 0°C, together with the air temperature and pressure (altitude), are good first order predictors of the highest temperature snowflakes can survive in the melting layer before completely melting. Particle size is also important, as is whether the particles are graupel or hail. If the relative humidity is too low, the particles will sublimate completely as they fall into the melting layer. Snow as warm as +7°C is observed from aircraft measurements and surface observations. Snow pellets survive to even warmer temperatures. Relationships are developed to represent the primary findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) Field Campaign Report

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) field campaign contributes to CalWater 2015, a multi-agency field campaign that aims to improve understanding of atmospheric rivers and aerosol sources and transport that influence cloud and precipitation processes. The ultimate goal is to reduce uncertainties in weather predictions and climate projections of droughts and floods in California. With the DOE G-1 aircraft and ARM Mobile Facility 2 (AMF2) well equipped for making aerosol and cloud measurements, ACAPEX focuses specifically on understanding how aerosols from local pollution and long-range transport affect the amount and phase of precipitation associated with atmospheric rivers. ACAPEX took place between January 12, 2015 and March 8, 2015 as part of CalWater 2015, which included four aircraft (DOE G-1, National Oceanic and Atmospheric Administration [NOAA] G-IV and P-3, and National Aeronautics and Space Administration [NASA] ER-2), the NOAA research ship Ron Brown, carrying onboard the AMF2, National Science Foundation (NSF)-sponsored aerosol and precipitation measurements at Bodega Bay, and the California Department of Water Resources extreme precipitation network.

aerosol transport↗
DOE OSTI2022

Predicting spring green-up across diverse North American grasslands

Vegetation phenology influences many ecosystem and climate processes, such as carbon uptake and energy and water cycles. Thus, understanding drivers of vegetation phenology is crucial for predicting current and future impacts of climate change on ecological systems. Existing models can accurately predict the date of spring green-up in temperate forests but tend to perform poorly in grassland systems. We hypothesize this is because most do not incorporate water availability, a primary limiting factor for grassland plants. In this study, we used long-term datasets of digital imagery from the PhenoCam Network of 43 diverse North American grassland sites (195 site-years) to test existing spring phenology models, as well as develop several new models that incorporate precipitation or soil moisture (53 models). As a result, most of the new models performed substantially better, with the best model requiring sufficient accumulated precipitation followed by warm temperatures to trigger spring onset (root mean square error, RMSE, between predicted and observed dates = 16.0 days). Importantly, the best model performed well across all grassland types using a single set of parameters, from temperate to arid grasslands. Since plants are adapted to their local climates, model performance was further improved when parameters were independently optimized for four separate climate regions (RMSE = 10.4 days). Therefore, both sufficient precipitation and temperature are required for grassland green-up, but optimal thresholds vary by region. Running the top model with projected climate data (representative concentration pathway 8.5) suggests that, depending on the climate region, spring onset will occur up to 12 days earlier within 100 years in temperature-limited sites, but the trend is unclear for precipitation-limited sites (3.5 ± 8.0 days later). This new phenology model improves our ability to understand and predict grassland dynamics, with implications for both current and future ecosystem processes related to carbon and water cycling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

The GPM GV Program

We present a detailed overview of the structure and activities associated with the NASA-led ground validation component of the NASA-JAXA Global Precipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA’s GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA’s GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA’s Level-1 science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated Multi-satellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the U.S.) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

Radar↗
DOE OSTI2020

Ice Nucleating Particles, Aerosols and Clouds over the Higher Latitude Southern Ocean

Improved understanding of aerosol-cloud-precipitation interactions is a key goal of the DOE-ASR program. Ice Nucleating Particles (INPs) are rare aerosol particles that trigger ice formation in clouds. By doing so they may initiate precipitation in clouds, and this impacts cloud lifetime. Nowhere may the role of INPs be manifested so dramatically as in the Southern Ocean (SO). This vast region was the focus of the DOE-ARM MARCUS (Measurement of Aerosols, Radiation and CloUds over the Southern Oceans) and MICRE (Macquarie Island Cloud and Radiation Experiment) campaigns. In the SO, a deficit of INPs has been a leading hypothesis for why liquid clouds persist, which underlays the bias of global climate models in predicting excess shortwave radiation reaching the ocean surface between 55°S and Antarctica. In this study, we used the 6-month acquisition of INP data on four MARCUS cruises from Hobart, Tasmania, to Antarctica, and the single-location full annual INP cycle observed in MICRE, to gain a holistic, quantitative picture of the INP number concentrations as a function of temperature and their variability over SO latitudes from 43°S to Antarctica. Augmenting initial processing of filter collections of aerosol particles during MARCUS and MICRE, additional freezing studies following thermal treatment (to removes INPs associated with microbes) and peroxide treatment (to remove all organics), as well as ionic chemistry and total organic carbon analysis, were applied to samples to improve time and space resolution, and differentiate marine from terrestrial contributions. We also performed Next Generation Sequencing to determine that bacterial composition can tag periods of enhanced and degraded marine organic INPs and the relative lack of occurrence of land-sourced bio-particles. Through these and other analyses, INP data were categorized into representative source types (e.g., marine versus terrestrially-influenced). The products of our analyses are being used to parameterize ice formation for use in numerical modeling studies to determine if, and when, ocean-derived INPs control the microphysical composition and radiative balance of SO clouds in a manner not presently captured by global models. The specific objectives and approaches proposed were largely accomplished, including: 1) Additional and value-added chemical and biological analyses of archived samples of aerosols were completed to categorize and quantify INP types and concentrations over the SO. 2) Analyses were completed to place INP data in meteorological and aerosol context. 3) Sea spray aerosol INPs were demonstrated to dominate the SO region in all but episodic events. 4) New parameterizations for INP sources relevant to the SO were constructed. 5) Collaborative modeling studies demonstrating the crucial role of INPs in determining cloud radiative and precipitation properties were conducted with MARCUS and MICRE partners. Collaborative publication submissions in this regard ensued within the two year study. This work will advance the science of interactions of aerosols, clouds and precipitation, to improve their representation in regional and global climate models. Results have informed representation of primary ice crystal nucleation, give inference to the role of secondary processes, and improve investigations of aerosol influences on clouds via ice nucleation over SO high latitudes and similar vast ocean regions. Application will improve representation of such interactions for clouds in both regional and global climate models. The data base and analyses methods applied will continue to serve research studies in the future.

58 GEOSCIENCES↗
DOE OSTI2020

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗