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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Approximate Co-Location of Precipitation and Low-Level Westerlies in Tropical Monthly Means

In summer monsoon regions the monthly mean precipitation regions coincide approximately well with regions of westerlies at low-levels. An included chart shows a 15-year (1979-1993) mean August 850 hPa zonal wind from NCEP/NCAR reanalysis dataset and Xie-Arkin precipitation. It shows a region of westerlies covering most of Northern Indian Ocean and extending to northwestern Pacific. This region coincides well with the region with precipitation greater than 6 mm/day. Obviously the coincidence is not exact; the region of larges; zonal wind in the Arabian Sea is in a region of relatively low precipitation and is far from the region of maximum precipitation in Bay of Bengal. Also, in a zonally averaged sense between 40E and 140E, the latitude of maximum precipitation is slightly higher than that of the maximum zonal wind. Low-level westerlies are also found in regions west of Central America and in western Africa north of the equator. These regions are also closely associated with precipitation centers. Across equator from these westerlies regions there are regions of strong easterlies. Also, on their poleward side the westerly regions are flanked by weaker easterly regions. In February, similar observation can be found in the Australian monsoon area and in South America monsoon region; again the regions of westerlies coincide well with regions of maximum precipitation. As in the northern hemisphere, the maximum precipitation is found to the cast of the maximum zonal wind. The two maxima lie almost at the same latitude with that of the westerlies slightly closer to the equator. In the non-monsoon seasons the low- level westerlies can also be found in the tropical precipitation regions, the longitudinal range of the westerlies is undiminished and the speed of the westerlies is not much weaker than that found in February. The interpretation of these observational facts is the goal of this investigation. The approach taken is numerical simulation with the Goddard Earth Observation Systems atmospheric general circulation model, and its aqua-planet version, combined with theoretical arguments.

Choa, Winston C.↗
NASA NTRS2000

The Evolution of Tropical Precipitation Patterns During ENSO Events Using 21+ Years of GPCP Merged Data

The ENSO phenomenon is characterized by fluctuations in the climate system of the tropical Pacific. Quantifying changes in the precipitation component of this system is important in understanding the distribution of heating in the atmosphere which drives the large-scale circulation and affects the weather patterns in the mid-latitudes. Monitoring precipitation anomalies in the Pacific is also an important component for tracking the evolution of ENSO. The most timely and complete observations of the earth come from satellite instruments. In this study, the state of the art satellite-gauge merged monthly precipitation data set from the Global Precipitation Climatology Project (GPCP) is used to depict tropical rainfall patterns during ENSO events over the past two decades and quantify these patterns using indices. This analysis will be complemented by daily precipitation data which can resolve the Madden-Julian Oscillation and westerly wind burst events. The 1997-98 El Nino and 1998-2000 La Nina were the best observed ENSO cycle in the historic record. Prior to the El Nino (in terms of anomalous warming of the east Pacific) dry anomalies over the Maritime Continent were observed in February 1997 as a westerly wind burst advected convection to the east. The largest SST anomalies occurred around November-December 1997, which were followed by the largest precipitation anomalies in the beginning of 1998. The largest precipitation departures from normal were not colocated with the SST anomalies, but were further west, In the spring of 1998 negative precipitation anomalies to the north of the equator intensified, signaling the mature phase of the El Nino. A rapid increase in the precipitation-based La Nina index from December-January 1998 to March-April 1998 signaled the coming La Nina. The 1982-1983 El Nino was comparable in strength (according to several indices) and the precipitation patterns evolved in a similar fashion. For the 1998-2000 La Nina, the coldest anomalies, were confined to the central equatorial Pacific, while the driest anomalies were found in the west Pacific,

Curtis, Scott↗
NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗
NASA NTRS2007

Influences of Local Sea-Surface Temperatures and Large-scale Dynamics on Monthly Precipitation Inferred from Two 10-year GCM-Simulations

Two parallel sets of 10-year long: January 1, 1982 to December 31, 1991, simulations were made with the finite volume General Circulation Model (fvGCM) in which the model integrations were forced with prescribed sea-surface temperature fields (SSTs) available as two separate SST-datasets. One dataset contained naturally varying monthly SSTs for the chosen period, and the oth& had the 12-monthly mean SSTs for the same period. Plots of evaporation, precipitation, and atmosphere-column moisture convergence, binned by l C SST intervals show that except for the tropics, the precipitation is more strongly constrained by large-scale dynamics as opposed to local SST. Binning data by SST naturally provided an ensemble average of data contributed from disparate locations with same SST; such averages could be expected to mitigate all location related influences. However, the plots revealed: i) evaporation, vertical velocity, and precipitation are very robust and remarkably similar for each of the two simulations and even for the data from 1987-ENSO-year simulation; ii) while the evaporation increased monotonically with SST up to about 27 C, the precipitation did not; iii) precipitation correlated much better with the column vertical velocity as opposed to SST suggesting that the influence of dynamical circulation including non-local SSTs is stronger than local-SSTs. The precipitation fields were doubly binned with respect to SST and boundary-layer mass and/or moisture convergence. The analysis discerned the rate of change of precipitation with local SST as a sum of partial derivative of precipitation with local SST plus partial derivative of precipitation with boundary layer moisture convergence multiplied by the rate of change of boundary-layer moisture convergence with SST (see Eqn. 3 of Section 4.5). This analysis is mathematically rigorous as well as provides a quantitative measure of the influence of local SST on the local precipitation. The results were recast to examine the dependence of local rainfall on local SSTs; it was discernible only in the tropics. Our methodology can be used for computing relationship between any forcing function and its effect(s) on a chosen field.

Sud, Y. C.↗
NASA NTRS2005

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Gottschalck, Jon↗
NASA NTRS2008

Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements

First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.

Smith, Eric A.↗
NASA NTRS2017

Land Surface Precipitation and Hydrology in MERRA-2

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

MERRA-↗
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.↗
NASA NTRS2019

Assessment of Precipitation Anomalies in California Using TRMM and MERRA Data

After more than a decade of moderate seasonal deviations from the expected climate, it is easy to forget that California is actually prone to instabilities in precipitation patterns that occur on various scales. Using modern satellite and reanalysis data we reassess certain aspects of the precipitation climate in California from the past three decades. California has a well-pronounced rain season that peaks in December-February. However, the 95% confidence interval around the climatological precipitation during these months imply that deviations on the order of 60% of the expected amounts are very likely during the most important period of the rain season. While these positive and negative anomalies alternate almost every year and tend to cancel each other, severe multi-year declines of precipitation in California seem to appear on decadal scales. The 1986-1994 decline of precipitation was similar to the current one that started in 2011, and is apparent in the reanalysis data. In terms of accumulated deficits of precipitation, that episode was no less severe than the current one. While El Niño (the warm phase of the El Niño Southern Oscillation, ENSO) is frequently cited as the natural forcing expected to bring a relief, our assessment is that ENSO has been driving at best only 6% of precipitation variability in California in the past three decades. It means El Niño needs to be stronger and longer, in order to have a higher likelihood of a positive impact, and the current one does not match these criteria. Using fractional risk analysis of precipitation populations during normal and dry periods, we show that the likelihood of losing the most intensive precipitation events drastically increases during the multi-year drying events. Since storms delivering up to 50% of precipitation in California are driven by atmospheric rivers making landfall, thus the importance of their suppression and blockage by persistent ridges of atmospheric pressure in the northeast Pacific.

Savtchenko, Andrey K.↗
NASA NTRSDate not supplied

Global Precipitation Means and Variations with the New Version of GPCP

Knowledge of global precipitation means, patterns and variations is essential for understanding the global water cycle. The observation-based global analysis of the Global Precipitation Climatology Project (GPCP) has been a key input to many such studies, including those related to means of the global (and regional) water and energy cycles. A new version (Version 3.1) of the GPCP monthly analysis is now available (1983-2019), with finer spatial resolution (0.5º latitude/longitude), updated satellite algorithms, latest gauge analysis over land from the Global Precipitation Climatology Center (GPCC), and with ocean climatologies adjusted using information from the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission and CloudSat. The presentation will give key findings from the new analysis, compare with the previous version, link to studies of the water cycle and compare to CMIP6 climate model results. The GPCP Monthly V3.1 analysis uses a Tropical Composite Climatology (TCC) using 22 years (1998-2019) of TRMM and GPM-based surface precipitation estimates from passive microwave, radar and combined passive microwave and radar observations to adjust the long-term mean values in the tropics over ocean. At higher latitudes over ocean climatological values of merged CloudSat and GPM combined passive microwave and radar surface precipitation estimates are used. The result of the new algorithms and procedures is an ocean mean value 60º N to 60º S of 3.2 mm/d, an increase of 7% from the older V2.3. Over land the gauge analysis (from GPCC in Germany), combined with satellite estimates results in a small decrease (~ 0.5%) from the previous version, giving a total global precipitation mean of 2.81 mm/d for V3.1, an increase of 4.5%. Variations from inter-annual to trend scales over most of the ocean are driven by the Colorado State University (CSU) Goddard Profiling (GPROF) algorithm applied to SSMI/SSMIS satellite data. The new GPCP version retains a near zero trend of global precipitation, with significant positive trends in the deep tropics along the Pacific ITCZ and elsewhere, countered by middle latitude decreases, very similar to the previous version of the GPCP Monthly analysis. The pattern of trends is similar to that of AMIP climate model results, driven by observed SSTs for the period in question, but very different from results for “free-running” CMIP historical ensembles, likely due in part to the relatively short comparison period and effects of inter-decadal variations in the GPCP and AMIP results that are not in the “history” models. Interannual variations are also nearly the same in the new version, but with finer detail, although ENSO variations over the ocean have slightly larger amplitude than before, an effect likely related to the change in ocean satellite algorithm used in Version 3. For precipitation intensity (percentiles) at the monthly scale, especially in the tropics, GPCP shows a positive trend for the upper one third of the percentiles (Pct ≥ 70th) and a much weaker positive trend for the lowest percentiles (Pct ≤ 10th), while negative trends appear for the middle one-half percentiles (20th-65th). AMIP results agree with those from the GPCP in terms of the sign of the changes/trends for high and intermediate percentiles. The CMIP historical results also agree in the sign of the trends, but the trends are weaker. Comparisons with other types of CMIP historical simulations including the GHG-only, aerosol-only, and nature-only runs suggest that the observed changes/trends in precipitation amount and intensity during the GPCP period are dominated by a combination of the effects of the Pacific Decadal Oscillation (PDO) and anthropogenic GHG-related surface warming.

Robert Adler↗
NASA NTRS2021

Improving Cross-track Scanning Radiometers’ Precipitation Retrieval over Ocean by Morphing

Previous studies showed that conical scanning radiometers greatly outperform cross-track scanning radiometers for precipitation retrieval over ocean. This study demonstrates a novel approach to improve precipitation rates at the cross-track scanning radiometers’ observation time by propagating the conical scanning radiometers’ retrievals to the cross-track scanning radiometers’ observation time. The improved precipitation rate is a weighted average of original cross-track radiometers’ retrievals and retrievals propagated from a conical scanning radiometer. The cross-track scanning radiometers include the Advanced Technology Microwave Sounder (ATMS) on board the SNPP satellite and four Microwave Humidity Sounders (MHSs). The conical scanning radiometers include the Advanced Microwave Scanning Radiometer 2 (AMSR2) and three Special Sensor Microwave Imager/Sounders (SSMISs), while the precipitation retrievals from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) are taken as the reference. Results show that the morphed precipitation rates agree much better with the reference. The degree of improvement depends on several factors, including the propagated precipitation source, the time interval between the cross-track scanning radiometer and the conical scanning radiometer, the precipitation type (convective versus stratiform), the precipitation events’ size, and the geolocation. The study has potential to greatly improve high-impact weather systems monitoring (e.g., hurricanes) and multisatellite precipitation products. It may also enhance the usefulness of future satellite missions with cross-track scanning radiometers on board.

Yalei You↗
NASA NTRS2023

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↗
DOE OSTI2022

Microstructural Characterization of A709 Commercial Heats with Precipitation Treatment

This report discusses work conducted at Idaho National Laboratory in fiscal year 2022 associated with the precipitates in Alloy 709 (A709). The purpose of this work is to support the development of the A709 Code Cases to qualify A709 in Section III, Division 5 of the American Society of Mechanical Engineers Boiler and Pressure Vessel Code. This would permit the use of A709 for elevated-temperature nuclear construction. This work encompassed two broad goals. The first goal was to understand the microstructure of the second commercial heat of plate A709 purchased through the Advanced Reactors Technologies Program in both the solution-annealed and precipitation-treated conditions. Transmission electron microscopy was utilized to characterize these microstructures. Direct comparisons were then made between the solution-annealed and precipitation-treated conditions as well as between the first and second commercial heats of plate A709. The second goal was to understand the impact of variations in the time and temperature of the precipitation treatment on the properties of A709. The precipitation treatment temperature was varied from 750°C to 800°C for times ranging from 3 hours to 30 hours. The hardness of each precipitation treatment variation was measured. All of the precipitation treatment variations investigated besides a specimen from the second commercial heat of plate A709 precipitation treated at 800? for 9 hours met the room-temperature hardness requirement specified in ASTM A213 and SA-213 for UNS S31025. The hardness measured for the specimen from the second commercial heat of plate A709 that was precipitation treated at 800? for 9 hours is considered an outlier. The next step is to look at the extremes of the precipitation treatment variations investigated and conduct elevated-temperature mechanical testing. The purpose of this testing would be to assess if these time and temperature variations have any impact on the mechanical performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Impacts of precipitation variability on plant species and community water stress in a temperate deciduous forest in the central US

Variations in precipitation regimes can shift ecosystem structure and function by altering frequency, severity and timing of plant water stress. There is a need for predictively understanding impacts of precipitation regimes on plant water stress in relation to species water use strategies. Here we first formulated two complementary, physiologically-linked measures of precipitation variability (PV) - Precipitation Variability Index (PVI) and Average Recurrence Interval of Effective Precipitation (ARIEP). We then used nine-year continuous measurements of Predawn Leaf Water Potential Integral (PLWPI) in a central US forest to relate PVI and ARIEP to actual plant water availability and comparative water stress responses of six species with different capacities to regulate their internal water status. We found that PVI and ARIEP explained nearly all inter-annual variations in PLWPI for all species as well as for the community scaled from species measurements. The six species investigated showed differential sensitivities to variations in precipitation regimes. Their sensitivities were reflected more in the responses to PVI and ARIEP than to the mean precipitation rate. Further, they exhibited tradeoffs between responses to low and high PV. Finally, PVI and ARIEP were closely correlated with temporal integrals of positive temperature anomalies and vapor pressure deficit. We suggest that the comparative responses of plant species to PV are part of species-specific water use strategies in a plant community facing the uncertainty of fluctuating precipitation regimes. In conclusion, PVI and ARIEP should be adopted as key indices to quantify physiological drought and the ecological impacts of precipitation regimes in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Parametric study and speciation analysis of rare earth precipitation using oxalic acid in a chloride solution system

Oxalic acid precipitation is a common step in the purification of rare earth elements (REE) from a concentrated pregnant leach solution (PLS). However, the presence of contaminants such as Al, Fe, and Ca in given amounts decreases the REE precipitation efficiency and product purity while also increasing the amount of oxalic acid needed to maximize recovery. As such, a statistically designed test program was performed to identify the optimal conditions necessary for a relatively low REE content PLS containing elevated concentrations of contaminant ions. The performance objective was maximization of REE precipitation efficiency while minimizing the oxalic acid dosage. A central composite design was utilized to quantify performance impacts and identify the ultimate set of parameter values for oxalic acid dosage, Fe(III) contamination concentration, solution pH, and reaction temperature. The resultant model suggested that oxalic acid dosage and reaction pH are the most significant factors for the REE precipitation efficiency, followed by the interaction of oxalic dosage and Fe concentration. Test results indicate that increasing the oxalic acid concentration from 0 g/L to 80 g/L improved the REE precipitation efficiency from approximately 4.2% to 95.0%. Furthermore, raising the solution pH from 0.5 to 2.5 considerably enhanced the precipitation efficiency from 0.0% to 98.9%. A solution temperature elevation decreased REE recovery, which indicated an exothermic reaction between REEs and oxalate anions. Finally, a high level of Fe contamination adversely impacted REE precipitation efficiency. Here, to further the understanding of the REE-oxalate system, a fundamental solution chemistry study was performed using the equilibrium constants of the reactions. The study resulted in the development of oxalate speciation diagrams and provided an analysis of the REE precipitation characteristics at various oxalate anion concentrations and Fe(III) contamination levels using MINTEQ software. The dominant Fe(III) species in the solution system were found to be Fe-(C 2 O 4 ) 3 3- , Fe-(C 2 O 4 ) 2- , and Fe-(C 2 O 4 ) + , which consume the majority of the oxalate anions. The simulated model was found to be in agreement with the experimental findings and helped to explain the adverse impact of increased iron concentrations on REE precipitation efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Changing Characteristics of Tropical Extreme Precipitation-Cloud Regimes in Warmer Climates

In this paper, we have investigated the changing characteristics of climatic scale (monthly) tropical extreme precipitation in warming climates using the Energy Exascale Earth System Model (E3SM). Results are from Atmospheric Model Intercomparison Project (AMIP)-type simulations driven by a) control experiment with present-day sea surface temperature (SST) and CO 2 concentration, b) P4K, same as in a) but with uniform increase by 4K in SST globally, and c) same as in a), but with imposed SST and CO 2 concentration from outputs of coupled E3SM forced by 4xCO 2 concentration. We find that as the surface warms under P4K and 4xCO 2 , both convective and stratiform rain increase. Importantly, there is increasing fractional contribution of stratiform rain as a function of precipitation intensity, with the most extreme but rare events occurring preferentially over land more than ocean, more so under 4xCO 2 than P4K. Extreme precipitation is facilitated by increased precipitation efficiency, reflecting accelerated rates of recycling of precipitation-cloud water (both liquid and ice phases) in regions with colder anvil cloud tops. Changes in vertical profiles of clouds, condensation heating and vertical motions indicate increasing precipitation-cloud-circulation organization from control, P4K to 4xCO 2 . Results suggest that large-scale ocean warming, i.e., P4K, is the primary cause contributing to organization structure resembling the well-known Mesoscale Convective System (MCS) for increased extreme precipitation on shorter (hourly to daily) time scales. Additional 4xCO 2 atmospheric radiative heating, and dynamically consistent anomalous SST further amplifies the MCS organization under P4K. Analyses of the surface moist static energy distribution show that increase in surface moisture (temperature) under P4K and 4xCO 2 is the key driver leading to enhanced convective instability over tropical ocean (land). However, the fast and large increase in land surface temperature and lack of available local moisture result in strong reduction in land surface relative humidity, reflecting severe drying and enhanced convective inhibition (CIN). It is argued that very extreme and rare “record-breaking” precipitation events found over land under P4K, more so under 4xCO 2 , are likely due to the delayed onset of deep convection, i.e., the longer the suppression of deep convection by CIN, the more severe the extreme precipitation when eventually occur, due to the release of large amount of stored surplus convective available potential energy in the lower troposphere during prolonged CIN.

climate-scale extreme tropical precipitation↗
DOE OSTI2025

Stimulating β -Series Precipitation in Mg–Nd Alloys Via Microalloying: A Comparison of Electron Microscopy and Small-Angle Scattering Techniques

The Mg–Nd alloy system is of particular interest in the development of high-strength, lightweight structural alloys due to the formation of strengthening metastable Mg–Nd β-series precipitates during heat treatment. The strengthening is primarily provided by a combination of the β''' and β 1 precipitation. It is therefore important to understand how the precipitation behavior can be enhanced by other common alloying elements. In this work, the effects of 0.2 wt pct Zn and Ca on β-series precipitation were studied. Small-angle/ultra-small-angle X-ray scattering (SAXS/USAXS) techniques in combination with scanning transmission electron microscopy (STEM) were used to study the evolution of precipitation microstructure. Here, it is found that the Zn additions refine the precipitates, leading to an increase in hardness with aging at 200 °C. On the other hand, the Ca additions result in an acceleration in the formation of larger β 1 precipitates and chains which provides less strengthening. The β 1 chains are surrounded by precipitate-free zones (PFZs) that further contribute to the decreases in hardness observed in the over-aged condition. This paper demonstrated that SAXS/USAXS provides a powerful tool for an in situ study of the early stages of precipitation in the Mg–Nd-based alloys.

36 MATERIALS SCIENCE↗