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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Abstract Prior research confirmed the substantial bias from using precipitation‐based intensity‐duration‐frequency curves (PREC‐IDF) in design flood estimates and proposed next‐generation IDF curves (NG‐IDF) that represent both rainfall and snow processes in runoff generation. This study improves the NG‐IDF technology for a snow‐dominated test basin in the Sierra Nevada. A well‐validated physics‐based hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM), is used to continuously simulate snowmelt and streamflow that are used as benchmark data sets to systematically assess the NG‐IDF technology. We find that, for the studied small snow‐dominated basin, the use of standard rainfall hyetographs in the NG‐IDF technology leads to substantial underestimation of design floods. Thus, we propose probabilistic hyetographs that can represent unique patterns of events with different underlying mechanisms. For the test basin where flooding events are generated entirely by snowmelt, we develop a hyetograph that characterizes snowmelt temporal patterns, which greatly improves the performance of NG‐IDF technology in design flood estimates. In contrast to the standard rainfall hyetographs characterized by a symmetrically peaked, bell‐shaped curve, the snowmelt hyetograph displays a more rapid rise (i.e., greater intensity) and a distinct diurnal pattern influenced by solar energy input. The results also show that the uncertainty of hyetography plays an important role in design flood estimation and can have important implications for future flood projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

How Flood Hazards in a Warming Climate Could Be Amplified by Changes in Spatiotemporal Patterns and Mechanisms of Water Available for Runoff

Prior research on climate change impacts on flooding has primarily focused on changes in extreme rainfall magnitudes, often neglecting snow processes and spatiotemporal storm patterns, such as hyetograph shapes and areal reduction factors (ARFs). This study examines projected changes in extreme water available for runoff (W) events in two snow-dominated basins in the western United States: the Yakima River Basin (YRB) in Washington State and the Walker River Basin (WRB) spanning the California-Nevada border. We analyze changes in W magnitudes, mechanisms, hyetograph shapes, and ARFs, and study their compounded impacts on flood hazard. Our findings suggest increased extreme W magnitudes across a large portion of the basins, with steeper or flatter hyetographs, and higher ARF values under the future climate. These changes are driven by a shift from seasonal snowmelt to more rain-on-snow events at higher elevations and by increased rainfall at lower elevations. We then use a single event-based rainfall-runoff model to estimate flood hazard changes based on extreme W magnitudes, hyetograph shapes, ARFs, and their compounded impacts. Our analysis reveals that focusing solely on the magnitude of changes in extreme W can significantly underestimate future flood hazards and uncertainties. Ignoring future changes in spatiotemporal patterns can underestimate future flood hazards by 63% and underestimate the uncertainty in future flood events by 18% in the WRB. These results underscore the necessity of incorporating spatiotemporal dynamics into future flood hazard assessments to provide a more accurate evaluation of potential impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Anthropogenic influences on major tropical cyclone events

There is no consensus on whether climate change has yet affected the statistics of tropical cyclones, owing to their large natural variability and the limited period of consistent observations. In addition, projections of future tropical cyclone activity are uncertain, because they often rely on coarse-resolution climate models that parameterize convection and hence have difficulty in directly representing tropical cyclones. Here we used convection-permitting regional climate model simulations to investigate whether and how recent destructive tropical cyclones would change if these events had occurred in pre-industrial and in future climates. We found that, relative to pre-industrial conditions, climate change so far has enhanced the average and extreme rainfall of hurricanes Katrina, Irma and Maria, but did not change tropical cyclone wind-speed intensity. In addition, future anthropogenic warming would robustly increase the wind speed and rainfall of 11 of 13 intense tropical cyclones (of 15 events sampled globally). Additional regional climate model simulations suggest that convective parameterization introduces minimal uncertainty into the sign of projected changes in tropical cyclone intensity and rainfall, which allows us to have confidence in projections from global models with parameterized convection and resolution fine enough to include tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multiscale drivers of extreme southern California flooding: ENSO, MJO, North Pacific jet, and atmospheric rivers

Extreme rainfall and flooding, driven by a powerful atmospheric river (AR) and a persistent Madden-Julian Oscillation (MJO), hit Southern California in February 2024 during the 2023–2024 El Niño, affecting over 10 million people. ARs are key contributors to extreme rainfall and flooding along the U.S. West Coast. Although the AR-MJO link has been documented, its spatio-temporal variability remains a major forecasting and risk-management challenge. Combining precipitation, stream gauge and demographic data, we quantify the physical drivers and population exposure to this extreme event. Leveraging a Lagrangian MJO precipitation tracking algorithm, we unravel the multiscale interactions responsible for the AR’s development. El Niño favored a large, long-lived MJO that interacted with the North Pacific Jet (NPJ) over more than three weeks. The MJO convective outflow modulated the NPJ by inducing negative potential vorticity advection along the tropopause. The ensuing NPJ extension and acceleration induced explosive cyclogenesis, whose AR-driven moisture transport resulted in extreme rainfall.

Atmospheric dynamics↗
DOE OSTI2015

Redesigning rain gauges network in Johor using geostatistics and simulated annealing

Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stomatal behaviour moderates the water cost of CO 2 acquisition for 21 boreal and temperate species under experimental climate change

Abstract The linkage of stomatal behaviour with photosynthesis is critical to understanding water and carbon cycles under global change. The relationship of stomatal conductance (g s ) and CO 2 assimilation (A net ) across a range of environmental contexts, as represented in the model parameter (g 1 ), has served as a proxy of the marginal water cost of carbon acquisition. We useg 1 to assess species differences in stomatal behaviour to a decade of open‐air experimental climate change manipulations, asking whether generalisable patterns exist across species and climate contexts.A net ‐g s measurements (17 727) for 21 boreal and temperate tree species under ambient and +3.3°C warming, and ambient and ~40% summer rainfall reduction, provided >2700 estimates ofg 1 . Warming and/or reduced rainfall treatments both loweredg 1 because those treatments resulted in lower soil moisture and because stomatal behaviour changed more in warming when soil moisture was low. Species tended to respond similarly, although, in species from warmer and drier habitats, g 1 tended to be slightly higher and to be the least sensitive to the decrease in soil water. Overall, both warming and rainfall reduction consistently made stomatal behaviour more conservative in terms of water loss per unit carbon gain across 21 species and a decade of experimental observation.

Plant Sciences↗
DOE OSTI2016

The Interhemispheric Pattern and Long-Term Variations in the Tropical Climate over the 20th and 21st Centuries

Several lines of evidence - paleoclimate observations, model simulations, and theory - suggest that thermal forcing originating from the extratropics have a profound effect on tropical rainfall. Cold thermal forcing located in the Northern extratropics cools air and surface temperatures over the entire hemisphere, generating an interhemispheric temperature asymmetry that shifts the latitudinal position of the Intertropical Convergence Zone southwards and weaken rainfall over Northern Hemisphere summer monsoon regions. This change is associated with a northward anomalous cross-equatorial atmospheric energy transport induced by differences in the energy flux entering each hemisphere. I summarize how this 'interhemispheric pattern' could be usefully applied to understanding multidecadal and longer-timescale forced changes in tropical rainfall over the 20th and 21st centuries, focusing on three specific causes: anthropogenic aerosols, the late 1960s climate shift, and hemispheric asymmetric feedbacks to greenhouse warming.

Chiang, John C. H.↗
DOE OSTI2025

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Characteristics Associated with the Madden-Julian Oscillation at Manus Island

Ground-based high temporal and vertical resolution datasets from 2002 to 2008 of observations at the Atmospheric Radiation Measurement (ARM) Tropical Western Pacific (TWP) site on Manus Island, Papua New Guinea are used to examine the evolution of clouds and rainfall associated with the MJO life cycle. A composite MJO event is developed based on the NOAA MJO Index 4 using 13 events. The analysis shows that the cloud evolution during the composited MJO life cycle depicts a two-phase structure consisting of a development phase and a mature phase. During the development phase, congestus is the most important cloud type; during the mature phase, deep convection is the dominant cloud type. Consistent with this two-phase structure, the heavy rainfall frequency also shows a two-peak structure during the MJO life cycle. Light rainfall does not show a clear relation to the MJO life cycle, but shows variability on shorter time scales. From the development phase to the mature phase, the MJO structure shifts from the Type I to Type II structure, showing a different phase relationship between convection and dynamic fields (or wave motion) in the development and mature phases. During the shift, mid-level clouds play an important role in moving moisture to the mid-troposphere and preparing the atmosphere for the following deep convection. The discharge-recharge theory explains some of observed features of the MJO evolution at the ARM TWP Manus Island site.

Mid-level Clouds, Madden-Julian, Oscillation Life ↗
DOE OSTI2020

Forecasting Remote Atmospheric Responses to Decadal Kuroshio Stability Transitions

Based on observational estimates and global ocean eddy-resolving coupled retrospective initialized predictions, we show that Kuroshio Extension variability affects rainfall variability along the west coast of North America. We show that the teleconnection between the current undulations and downstream rainfall can lead to improved subseasonal to seasonal predictions of precipitation over California, and we demonstrate that capturing these teleconnections requires coupled systems with sufficient ocean resolution (i.e., eddy-resolving), especially over time scales longer than one season. The improved forecast skill is diagnosed in terms of 35 years of retrospective initialized ensemble forecasts with an ocean eddy-resolving and an ocean eddy-parameterized coupled model. Not only does the ocean eddy-resolving model show sensitivity to Kuroshio Extension variability in terms of western North America precipitation, but the ocean eddy-resolving forecasts also show improved forecast skill compared to the ocean eddy-parameterized model. Additionally, the ocean eddy-parameterized coupled model shows no sensitivity to Kuroshio Extension variability. We also find near-decadal variability associated with a progression of a lower-tropospheric height dipole around the North Pacific and how these height anomalies lead to wind-driven Rossby waves that affect the eddy activity in the Kuroshio Extension with a time lag on the order of four years. This decadal-scale variability (~10 years) opens the possibility of multiyear predictability of western North American rainfall.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Globally Coherent Pattern of Autumn Monsoon Precipitation

Over most tropical land areas, the annual peak in precipitation occurs during summer, associated with the local monsoon circulation. However, in some coastal regions in the tropics the bulk of annual precipitation occurs in autumn, after the low-level summer monsoon westerlies have abated. Examples include the Nordeste region of Brazil, southeastern India and Sri Lanka, and coastal Tanzania. Unlike equatorial regions, they receive little rainfall during local spring. Such regions are present along the eastern coasts of nearly all continents, suggesting that they comprise a coherent yet previously unrecognized global phenomenon. In this study, we identify eight tropical locations that experience an “autumn monsoon” and show that this unusual seasonal cycle is generated by similar mechanisms in all of these. When these regions receive their peak rainfall, they lie poleward of the ITCZ in easterly low-level winds. The spatial structure of precipitation in these regions can be explained by their placement to the east of mountain ranges that organize moist convection on their windward sides. However, orographic forcing alone cannot explain their unique seasonal cycle: despite similarities in wind direction, surface humidity, and sea surface temperatures (SSTs) between autumn and spring, these regions receive significantly more rainfall in autumn than in spring. Here, we show that this is due to differences in the large-scale atmospheric stability between the equinoctial seasons, which can be captured by a relative SST metric and is influenced by SSTs in the remote eastern upwelling zones of the Pacific and Atlantic Oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗
DOE OSTI2021

Scale-Dependent Value of QPF for Real-Time Streamflow Forecasting

Incorporating rainfall forecasts into a real-time streamflow forecasting system extends the forecast lead time. Since quantitative precipitation forecasts (QPFs) are subject to substantial uncertainties, questions arise on the trade-off between the time horizon of the QPF and the accuracy of the streamflow forecasts. This study explores the problem systematically, exploring the uncertainties associated with QPFs and their hydrologic predictability. The focus is on scale dependence of the trade-off between the QPF time horizon, basin-scale, space-time scale of the QPF, and streamflow forecasting accuracy. To address this question, the study first performs a comprehensive independent evaluation of the QPFs at 140 U.S. Geological Survey (USGS) monitored basins with a wide range of spatial scales (~10 – 40,000 km 2 ) over the state of Iowa in the Midwestern United States. The study uses High-Resolution Rapid Refresh (HRRR) and Global Forecasting System (GFS) QPFs for short and medium-range forecasts, respectively. Using Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimate (QPE) as a reference, the results show that the rainfall-to-rainfall QPF errors are scale-dependent. The results from the hydrologic forecasting experiment show that both QPFs illustrate clear value for real-time streamflow forecasting at longer lead times in the short- to medium-range relative to the no-rain streamflow forecast. The value of QPFs for streamflow forecasting is particularly apparent for basin sizes below 1,000 km 2 . The space-time scale, or reference time t r ) (ratio of forecast lead time to basin travel time) ~ 1 depicts the largest streamflow forecasting skill with a systematic decrease in forecasting accuracy for t r > 1.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data and code for: "Soil respiration response to simulated precipitation change depends on ecosystem type and study duration"

Data, code, and figures from our meta-analysis of the effect of precipitation change on soil respiration, with an emphasis on ecosystem variability and the effect of study duration. We combined the results of 81 separate studies to determine the effect of altered rainfall on the amount of carbon that leaves soil in the form of carbon dioxide, a major component of global carbon cycling. In addition we looked at how long the changes lasted, and how different soil properties and the intensity of precipitation changes affected the study results. We found that more precipitation resulted in greater amounts of carbon dioxide leaving the soil, and less precipitation resulted in less. However, the changes weakened over time in ecosystems that typically receive plenty of rainfall (e.g., forests), in contrast to ecosystems that typically receive little rainfall (e.g., deserts) where changes strengthened over time. Changes in the amount of carbon dioxide that left the soil were also affected by the amount of carbon in the soil, which impacts how much water soil can hold.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

PA-BCI Meteorological dataset 1985-2018

This data package contains a QA/QC-ed meteorological time series dataset from 1985 to 2018, including relative humidity, temperature, solar radiation, rainfall, wind speed, and barometric pressure at Barro Colorado Island (PA-BCI) in Panama. The data were collected at the elevations of 42 m and 48 m at the BCI Lutz station, except for rainfall that was collected at the BCI Clearing station at the elevation of 1 m. Individual time series datasets were collected using electro-mechanical (electronic sensors, data loggers, chart recorders, etc.). The rainfall dataset was collected using the tipping bucket method, and the data could have been underestimated by 13-17% (likely the large values). The data is included as a single CSV file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Probabilistic Hazard Assessment for Tornadoes, Straight-line Wind, and Extreme Precipitation at the Savannah River Site

Recent data sets for three meteorological phenomena with the potential to inflict damage on SRS facilities - tornadoes, straight winds, and heavy precipitation - are analyzed using appropriate statistical techniques to estimate occurrence probabilities for these events in the future. Summaries of the results for DOE-mandated return periods and comparisons to similar calculations performed in 1998 by Weber, et al., are given. Using tornado statistics for the states of Georgia and South Carolina, we calculated the probability per year of any location within a 2⁰ square area surrounding SRS being struck by a tornado (the ‘strike’ probability) and the probability that any point will experience winds above set thresholds. The strike probability was calculated to be 1.15E-3 (1 chance in 870) per year and wind speeds for DOE mandated return periods of 50,000 years, 125,000 years, and 1E+7 years (USDOE, 2012) were estimated to be 136 mph, 151 mph and 221 mph, respectively. In 1998 the strike probability for SRS was estimated to be 3.53 E-4 and the return period wind speeds were 148 mph every 50,000 years and 180 mph every 125,000 years. A 1E+7 year tornado wind speed was not calculated in 1998; however a 3E+6 year wind speed was 260 mph. The lower wind speeds resulting from this most recent analysis are largely due to new data since 1998, and to a lesser degree differences in the models used. By contrast, default tornado wind speeds taken from ANSI/ANS-2.3-2011 are somewhat higher: 161 mph for return periods of 50,000 years, 173 mph every 125,000 years, and 230 mph every 1E+7 years (ANS, 2011). Although the ANS model and the SRS models are very similar, the region defined in ANS 2.3 that encompasses the SRS also includes areas of the Great Plains and lower Midwest, regions with much higher occurrence frequencies of strong tornadoes. The SRS straight wind values associated with various return periods were calculated by fitting existing wind data to a Gumbel distribution, and extrapolating the values for any return period from the tail of that function. For the DOE mandated return periods, we expect straight winds of 123 mph every 2500 years, and 132mph every 6250 years at any point within the SRS. These values are similar to those from the W98 report (which also used the Gumbel distribution for wind speeds) which gave wind speeds of 115mph and 122 mph for return periods of 2500 years and 6250 years, respectively. For extreme precipitation accumulation periods, we compared the fits of three different theoretical extreme-value distributions, and in the end decided to maintain the use of the Gumbel distribution for each period. The DOE mandated 6-hr accumulated rainfall for return periods of 2500 years and 6250 years was estimated as 7.8 inches and 8.4 inches, respectively. For the 24-hr rainfall return periods of 10,000 years and 25,000 years, total rainfall estimates were 10.4 inches and 11.1 inches, respectively. These values are substantially lower than comparable values provided in the W98 report. This is largely a consequence of the W98 use of a different extreme value distribution with its corresponding higher extreme probabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Unveiling Microbial Carbon Cycling Processes in Key U.S. Soils using ''Omics''

Soils process and store large amounts of C; however, considerable uncertainty still exists about the details of that influence microbial partitioning of C into soil C pools, and what are the main influential forces that control the fraction of the C input that is stabilized. The soil microbial community is genotypically and phenotypically diverse. Despite our ability to predict the kinds of regional environmental changes that will accompany global climate change, it is not clear how the microbial community will respond to climate-induced modification of precipitation and inter-precipitation intervals, and if this response will affect the fate of C deposited into soil by the local plant community. Part of this uncertainty lies with our ignorance of how the microbial community adapts genotypically and physiologically to changes in soil moisture brought about by shifts in precipitation. Our overarching goal is to harness the power of multiple meta-omics tools to gain greater understanding of the functioning of whole-soil microbial communities and their role in C cycling. We will do this by meeting the following three objectives: 1. Further develop and optimize a combination of meta-omics approaches to study how environmental factors affect microbially-mediated C cycling processes. 2. Determine the impacts of long-term changes in precipitation timing on microbial C cycling using an existing long-term field manipulation of a tallgrass prairie soil. 3. Conduct laboratory experiments that vary moisture and C inputs to confirm field observations of the linkages between microbial communities and C cycling processes. We took advantage of our state-of-the-art expertise in community “omics” to better understand the functioning soil C cycling within the Great Prairie ecosystem, including our ongoing Konza Prairie soil metagenome flagship project at JGI and the unique rainfall manipulation plots (RaMPs) established at this site more than a decade ago. We employed a systems biology approach, considering the complex soil microbial community as a functioning system and using state-of-the-art metatranscriptomic, metaproteomic, and metabolomic approaches. These omics tools were refined, applied to field experiments, and confirmed with controlled laboratory studies. Our experiments were designed to specifically identify microbial community members and processes that are instrumental players in processing of C in the prairie soils and how these processes are impacted by wetting and drying events. This project addresses a key ecosystem in the United States that current climate models predict will be subjected to dramatic changes in rainfall patterns as a result of global warming. Currently Mollisols, such as those of the tallgrass prairie, are thought to sequester more C than is released into the atmosphere, but it is not known what changes in rainfall patterns will have on future C fluxes. Through an analysis of the molecular response of the soil microbial community to shifts in precipitation cycles that are accompanied by phenologically driven changes in quality of plant C rhizodeposits, we gained deeper insight into how the metabolism of microbes has adapted to different precipitation regimes and the impact of this adaption on the fate of C deposited into soil. In doing so, we addressed key questions about the microbial cycling of C in soils that have been identified by the DOE.

54 ENVIRONMENTAL SCIENCES↗