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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Data from: "Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range"

This data package contains data that were used for analysis in “Warming and the dependence of limber pine (Pinus flexilis) establishment on summer soil moisture within and above its current elevation range”, by Moyes et al. 2013. All data collection and field research were completed on Niwot Ridge, Colorado, USA.This data package contains nine comma-separated-values (.csv) files, one text (.txt) file, and two zipped seedling folders that were used for leaf area analysis. One zipped folder contains 468 .jpg photographs of seedlings, and the second contains 468 corresponding Image J-processed .jpg images that include silhouette leaf area values. .csv and .txt files can be opened using any compatible simple text-editor software such as TextEdit (Mac) and Notepad (Windows); .csv’s can also be opened using R and Microsoft Excel. Image files can be opened using Preview (Mac) and Photos (Windows). In addition, there are a total of 31 Microsoft Excel files: three .xlsx files, and 28 raw Li-Cor output .xls files. This data user’s guide is available in .pdf format, and can be opened using Adobe Acrobat Reader, or any other compatible file viewing software. Geospatial data showing field site locations are also included in the archive for use and reference. There are two geospatial formats in this archive: ESRI shapefiles (.shp) and keyhole markup-language (.kml) files. Both file types contain bounding box information, with the former being polygons, and the latter containing corner coordinates for each site. ESRI shapefiles can be opened using any geospatial software compatible with the file type (such as ESRI’s ArcGIS suite and QGIS), and .kml files are compatible with Google Earth and Google Maps.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Continued changes in climate are projected to alter the geographic distributions of plant species, in part by affecting where individuals can establish from seed. We tested the hypothesis that warming promotes uphill redistribution of subalpine tree populations by reducing cold limitation at high elevation and enhancing drought stress at low elevation. We seeded limber pine (Pinus flexilis) into plots with combinations of infrared heating and water addition treatments, at sites positioned in lower subalpine forest, the treeline ecotone, and alpine tundra. In 2010, first-year seedlings were assessed for physiological performance and survival over the snow-free growing season. Seedlings emerged in midsummer, about 5–8 weeks after snowmelt. Low temperature was not observed to limit seedling photosynthesis or respiration between emergence and October, and thus experimental warming did not appear to reduce cold limitation at high elevation. Instead, gas exchange and water potential from all sites indicated a prevailing effect of summer moisture stress on photosynthesis and carbon balance. Infrared heaters raised soil growing degree days (base 5 °C, p < 0.001) and August–September mean soil temperature (p < 0.001). Despite marked differences in vegetation cover and meteorological conditions across sites, volumetric soil moisture content (θ) at 5–10 cm below 0.16 and 0.08 m^3 m^(−3) consistently corresponded with moderate and severe indications of drought stress in midday stem water potential, stomatal conductance, photosynthesis, and respiration. Seedling survival was greater in watered plots than in heated plots (p = 0.01), and negatively related to soil growing degree days and duration of exposure to θ < 0.08 m^3 m^(−3) in a stepwise linear regression model (p < 0.0001). We concluded that seasonal moisture stress and high soil surface temperature imposed a strong limitation to limber pine seedling establishment across a broad elevation gradient, including at treeline, and that these limitations are likely to be enhanced by further climate warming.--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Maintenance log:Amended file name error in Data User's Guide May 19 2022

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

The Impacts of Recent Drought on Fire, Forest Loss, and Regional Smoke Emissions in Lowland Bolivia

In the southern Amazon relationships have been established among drought, human activities that cause forest loss, fire, and smoke emissions. We explore the impacts of recent drought on fire, forest loss, and atmospheric visibility in lowland Bolivia. To assess human influence on fire, we consider climate, fire, and vegetation dynamics in an area largely excluded from human activities since 1979, Noel Kempff Mercado National Park (NK) in northeastern Bolivia. We use data from five sources: the Moderate Resolution Imaging Spectroradiometer Collection 6 active fire product (2001-2015) (MODIS C6), Global Fire Weather Database (GFWED) data (1982-2015), MODIS land cover data (2001-2010), MODIS forest loss data (2000-2012), and the regional extinction coefficient for the southwestern Amazon (i.e., B(sub ext)), which is derived from horizontal visibility data from surface stations at the World Meteorological Organization (WMO) level (1973-2015). The B(sub ext) is affected by smoke and acts as a proxy for visibility and regional fire emissions. In lowland Bolivia from 2001 to 2015, interannual Drought Code (DC) variability was linked to fire activity, while from 1982 to 2015, interannual DC variability was linked to B(sub ext). From 2001 to 2015, the B(sub ext) and MODIS C6 active fire data for lowland Bolivia captured fire seasonality, and covaried between low- and high-fire years. Consistent with previous studies, our results suggest B(sub ext)t can be used as a longer-term proxy of regional fire emissions in southwestern Amazonia. Overall, our study found drought conditions were the dominant control on interannual fire variability in lowland Bolivia, and fires within NK were limited to the Cerrado and seasonally inundated wetland biomes. Our results suggest lowland Bolivian tropical forests were susceptible to human activities that may have amplified fire during drought. Human activities and drought need to be considered in future projections of southern Amazonian fire, in regard to carbon emissions and global climate.

Forest Loss↗
DOE OSTI2024

The Changing Influence of Precipitation on Soil Moisture Drought With Warming in the Mediterranean and Western North America

Abstract Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below‐normal precipitation and terminated by average or above‐normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming‐driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts.

Environmental Sciences & Ecology↗
NASA NTRS2012

Evaluation ofthe Middle East and North Africa Land Data Assimilation System

The Middle East and North Africa (MENA) region is dominated by dry, warm deserts, areas of dense population, and inefficient use of fresh water resources. Due to the scarcity, high intensity, and short duration of rainfall in the MENA, the region is prone to hydro climatic extremes that are realized by devastating floods and times of drought. However, given its widespread water stress and the considerable demand for water, the MENA remains relatively poorly monitored. This is due in part to the shortage of meteorological observations and the lack of data sharing between nations. As a result, the accurate monitoring of the dynamics of the water cycle in the MENA is difficult. The Land Data Assimilation System for the MENA region (MENA LDAS) has been developed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. As an extension of the Global Land Data Assimilation System (GLDAS), the MENA LDAS was designed to aid in the identification and evaluation of regional hydrological anomalies by synergistically combining the physically-based Catchment Land Surface Model (CLSM) with observations from several independent data products including soil-water storage variations from the Gravity Recovery and Climate Experiment (GRACE) and irrigation intensity derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this fashion, we estimate the mean and seasonal cycle of the water budget components across the MENA.

Bolten, John D.↗
NASA NTRS2014

In-Orbit Performance of the MWRI Scanning Mechanisms

Scanning Equipment supporting the Millimeter Wave Radiometer Instrument (MWRI) are flying in a sunsynchronized orbit of 850-km altitude with an inclination of 98.8 deg on the FY-3 meteorological satellite (FY = Feng Yun, Wind and Cloud). MWRI is a linearly polarized, ten-channel passive Radiometer; it measures precipitation and water clouds, sea ice, snow/water equivalent, drought and flood index, land temperature and soil moisture. Following the FY3-A, the FY3-B Satellite was launched in autumn 2010. Since that time, the Scanning Equipment was continuously operated. During the last three and a half years in orbit, the Scanning Mechanism has executed about 65 million revolutions, while the Scan Compensation Mechanism (SCM) - used for momentum compensation - has already successfully executed more than one billion revolutions. During the commissioning phase of the instrument and during the first operation phase, random torque spikes, which manifested themselves as a motor current increase, were observed in the Scan Drive Mechanism, whereas the Scan Compensation drive operated nominally from the beginning. The result of the root cause investigations performed in order to isolate the issue, and the consequences for the follow-on MWRI equipment which was successfully launched by end of September 2013 (now flying on the FY 3-C Spacecraft), are discussed.

Schmid, Manfred↗
NASA NTRS1979

The LACIE crop years: An assessment of the crop conditions experienced in the three years of LACIE

Meteorological data and LANDSAT spectral data from growing regions in the U.S. Great Plains, the U.S.S.R., and Canada were used to assess growing conditions and to document where anomalies such as drought, floods, and freezes were impacting the crop yield and appearance of spring and winter wheat. In the United States, the weekly rainfall and temperature data were used to estimate soil moisture, which was then related to crop needs by a crop moisture index. The transformation of LANDSAT digital data into a green index number provided a procedure whereby data from a LACIE segment could be classified as drought affected or not. The growing seasons encountered in each LACIE country during the three phases are described.

Hill, J. D.↗
NASA NTRS2012

Understanding Changes in Water Availability in the Rio Grande/Rio Bravo del Norte Basin Under the Influence of Large-Scale Circulation Indices Using the Noah Land Surface Model

Water availability plays an important role in the socio-economic development of a region. It is however, subject to the influence of large-scale circulation indices, resulting in periodic excesses and deficits. An assessment of the degree of correlation between climate indices and water availability, and the quantification of changes with respect to major climate events is important for long-term water resources planning and management, especially in transboundary basins as it can help in conflict avoidance. In this study we first establish the correlation of the Pacific Decadal Oscillation (PDO) and El Nino-Southern Oscillation (ENSO) with gauged precipitation in the Rio Grande basin, and quantify the changes in water availability using runoff generated from the Noah land surface model. Both spatial and temporal variations are noted, with winter and spring being most influenced by conditions in the Pacific Ocean. Negative correlation is observed at the headwaters and positive correlation across the rest of the basin. The influence of individual ENSO events, classified using four different criteria, is also examined. El Ninos (La Ninas) generally cause an increase (decrease) in runoff, but the pattern is not consistent; percentage change in water availability varies across events. Further, positive PDO enhances the effect of El Nino and dampens that of La Nina, but during neutral/transitioning PDO, La Nina dominates meteorological conditions. Long El Ninos have more influence on water availability than short duration high intensity events. We also note that the percentage increase during El Ninos significantly offsets the drought-causing effect of La Ninas.

Khedun, C. Prakash↗
NASA NTRS2021

Tonlé Sap Food Security & Agriculture III: Evaluating Changes in Ecosystem Vitality and Freshwater Health in the Tonlé Sap Basin using Remotely Sensed Data

Tonlé Sap Lake, located in Cambodia, Southeast Asia, is one of the most productive inland fisheries in the world. With the unique reverse flow hydrology of the Tonlé Sap River, this freshwater system contains rich biodiversity and provides critical freshwater resources for the local community. Overfishing, stronger seasonality, drought, dam construction, forest fires, and untreated industrial domestic sewage threaten the ecosystem vitality and economic success of Tonlé Sap. In collaboration with Conservation International and the Cambodian Ministry of Water Resources and Meteorology’s Tonlé Sap Authority, we calibrated and finalized remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI). We used NASA Earth observation data from Moderate Resolution Imaging Spectroradiometer (MODIS), and the Gravity Recovery and Climate Experiment (GRACE). These datasets were used in RS proxies and a Soil and Water Assessment Tool (SWAT) model that previous teams developed for sub-indicators of FHI. They included landcover, bank modification, and water quality metrics. It was determined that the ground water storage in Tonlé Sap Lake exhibited a slight declining trend over from April 1st, 2002 to February 3rd, 2017. To calculate chlorophyll-a concentration in the Tonlé Sap Lake, we used Copernicus Global Land Service mission data which provided a Trophic State Index of the lake. Between January 1st, 2000 and December 31st, 2020, the lake and surrounding region within the study area boundary displayed a slight decrease in vegetation density and consistently high chlorophyll-a concentrations. The SWAT model calculated nitrogen and phosphorus content measured in outlet points of the lake. We demonstrated that remotely sensed data is valuable for providing additional information for the FHI, but is not fully capable of replacing its in situ counterpart. We also concluded the water quantity is on a slowly declining trend within the basin.

Joey Lindsay↗
DOE OSTI2021

Microbial community response to a decade of simulated global changes depends on the plant community

Global changes such as increased drought and atmospheric nitrogen deposition perturb both the microbial and plant communities that mediate terrestrial ecosystem functioning. However, few studies consider how microbial responses to global changes may be influenced by interactions with plant communities. To begin to address the role of microbial–plant interactions, we tested the hypothesis that the response of microbial communities to global change depends on the plant community. We characterized bacterial and fungal communities from 395 plant litter samples taken from the Loma Ridge Global Change Experiment, a decade-long global change experiment in Southern California that manipulates rainfall and nitrogen levels across two adjacent ecosystems, a grassland and a coastal sage scrubland. The differences in bacterial and fungal composition between ecosystems paralleled distinctions in plant community composition. In addition to the direct main effects, the global change treatments altered microbial composition in an ecosystem-dependent manner, in support of our hypothesis. The interaction between the drought treatment and ecosystem explained nearly 5% of the variation in bacterial community composition, similar to the variation explained by the ecosystem-independent effects of drought. Unexpectedly, we found that the main effect of drought was approximately four times as strong on bacterial composition as that of nitrogen addition, which did not alter fungal or plant composition. Overall, the findings underscore the importance of considering plant–microbe interactions when considering the transferability of the results of global change experiments across ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variability in Wind Energy Generation across the Contiguous United States

ERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Additionally, gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

17 WIND ENERGY↗
NASA NTRS2021

Tonlé Sap Food Security and Agriculture II: Evaluating Changes in Ecosystem Vitality and Freshwater Healthin the Tonlé Sap Basin using Remotely Sensed Data

The Tonlé Sap Lake and river basin in central Cambodia provide critical ecosystem services to the region, including fisheries, agricultural irrigation, hydropower, and biodiverse habitats. Deforestation, increased pumping for farming, and effects of climate change such as droughts and forest fires threaten the health of the lake and food security in the region. This project built upon the previous term through a partnership with Conservation International (CI), the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority to assess ecosystem vitality and implement CI’s Freshwater Health Index (FHI) tool, in an effort to prioritize resource expenditure and highlight areas of concern. Due to the COVID-19 pandemic and related travel restrictions, partners had not been able to readily collect in situ data for the past year, which make up the majority of FHI inputs. To help fill this data gap, we developed a methodology for using Gravity Recovery and Climate Experiment (GRACE) satellite data to calculate groundwater storage depletion, and a Python Application Programming Interface for processing and formatting remotely-sensed data for the Soil and Water Assessment Tool (SWAT) model. We then used SWAT to model nutrient flows and of phosphorous, nitrogen and suspended sediments amounts in the basin from October 2000 to December 2020. These outputs served as inputs for the FHI and provided policy makers with robust monitoring information to aid decision-making in the area and safeguard the lake’s vital fisheries and biodiversity.

Justine Spore↗
NASA NTRSDate not supplied

Updates of MERRA-2 Data and Services at NASA GES DISC

Over40 years of NASA climate reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) are available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition to being used in traditional weather and climate research, MERRA-2 is also widely used in application studies of, e.g., wind and solar energy, air quality and health, food and drought, and heat waves. Two new MERRA-2 datasets were recently added at the GES DISC: (1) climate statistics derived fromMERRA-2 daily data to assist in the analysis of extreme temperature and precipitation events and of large-scale meteorological patterns from 1980 to the present and (2) gridded satellite and conventional observations processed in the MERRA-2 system, along with key statistics derived from the data assimilation, to help better understand how the quality of observations directly affect there analysis data. The GES DISC focuses its efforts on continually improving existing data services and to develop new data tools to satisfy various user communities. The newly added features include the following: Time series service: This is a new service for MERRA-2 data, which enables the easy and fast access of long-term hourly or daily time series at a location for popular parameters. The data is saved in a single le in Ascii format with a user- friendly structure. New analytic functions in the subsetter interface: Options for downloading daily minimum and maximum values have been added into the subsetter interface, in addition to the existing daily mean option, for all MERRA-2 and MERRA sub-daily products. Data format conversion to GeoTIFF has been implemented. New variables in Giovanni: Most monthly variables have been integrated into Giovanni, GESDISC’s online visualization and analysis tool. Due to the large data volume, hourly variables were selected based on user requests. More online information: New MERRA-2 documentation has been added: Data How-To, Data in Action, and FAQ. This presentation overviews two new MERRA-2 datasets and illustrates the new features of data services through a number of case studies. MERRA-2 data and services can be found at: https://disc.gsfc.gov/datasets?

Data management↗
NASA NTRS2003

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Welker, Jean E.↗
NASA NTRS2020

Supporting Information for ”The 2019-2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes

The model configuration employs the modified International Geosphere Biosphere Programme (IGBP) MODIS 20 category landcover data, soil parameters derived from the International Soil Reference and Information Centre, and the Shuttle Radar Topography Mission based elevation, slope, and aspect data. Statistical downscaling approaches are used to transform the coarse resolution MERRA2 meteorological inputs to 1km. The input meteorological fields of air temperature, humidity, surface pressure, wind, downward shortwave radiation, and downward longwave radiation are downscaled to 1km by adjusting for terrain differences in elevation, slope, and aspect. The high resolution monthly precipitation climatology from WorldClim is used to spatially disaggregate input MERRA2 precipitation to 1km. The initial conditions for the model simulations are generated from a long spinup of NoahMP starting from year 2000. All model integrations and evaluations are conducted using the NASA Land Information System and the Land surface Verification Toolkit.

Sujay V Kumar↗
NASA NTRSDate not supplied

Characterizing Wildfires in Western US.: A Cloud-based Case Study for Interdisciplinary Research using NASA Resources

This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).

Xiaohua Pan↗