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Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"
This data package contains the associated data and scripts for Nagamoto, E., Ombadi, M., Ciulla, F. et al. Widespread drought-driven declines in streamflows and water quality in the Upper Colorado River Basin during 1998-2022. Commun Earth Environ 7, 734 (2026). https://doi.org/10.1038/s43247-026-03890-5. This purpose of this study was to investigate the impact of the 21st century drought on water quantity and quality at catchments throughout the Upper Colorado River Basin (UCRB). We used stream flow, water temperature, specific conductance, air temperature, precipitation, and catchment attribute data for over 200 sites in the UCRB, collected from the National Water Information System using Basin3D (Varadharajan, 2023), GAGESII (Falcone, 2010), and the Google Earth Engine. We identified years of severe drought between 1998 and 2022 using the Standardized Precipitation Evaporation Index (SPEI), then calculated the relative change percentage of the stream flow, water temperature, and specific conductance from drought versus non-drought years. We used the attribute information from GAGESII to investigate what physical traits of catchments are associated streamflow vulnerability (greater relative change) or resilience to drought. We used land cover data from the National Land Cover Database (USGS, 2024) to assess any changes to physical attributes that may not be represented in the static attributes information in GAGESII. To increase data availability, we modeled stream temperature using methods from Willard, 2023. While the study period is water years 1998 to 2022, the raw water quantity and quality data extends to 1950 and the meteorological data extends to 1980. The data and code can be downloaded via the UCRB_drought.zip. Within the zip, the files are organized as follows: - INPUTS: Contains all input data used in UCRB_Drought_Workflow.ipynb - OUTPUTS: Contains all intermediate data created from UCRB_Drought_Workflow.ipynb as well as final products including the calculated Standardized Evapotranspiration Index (SPEI) - climatic_variables: The code used to collect meteorologic data from Google Earth Engine - feature_importance: The code used for the catchment attributes analysis - preprocessing: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - pyeto: Code used in UCRB_Drought_Workflow_Preprocessing.ipynb - calculations: Code used in UCRB_Drought_Workflow_Impacts.ipynb - plotting: Code used in UCRB_Drought_Workflow_Impacts.ipynb - README.md - UCRB_Drought_Workflow_Preprocessing.ipynb: The code used to prep raw data for the analysis - UCRB_Drought_Workflow_Impact.ipynb: The code which uses the prepped raw data for analysis, and plots all figures - requirements_ucrb-drought_v2.yml: The requirements file to create a virtual environment and Jupyter Lab kernel to run the code The INPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_RAW" folder contains raw data for streamflow, water temperature, and specific conductance in a ".h5" file. The "NLCD_RAW" folder contains ".csv" files with annual land cover percentages for counties within the UCRB. The "MET_RAW" folder contains a ".csv" file with monthly meteorological data (air temperature and precipitation) for the sites in the UCRB which was obtained from code in the climatic_variables folder. The "GAGESII" folder contains ".csv" files with physical catchment attribute variables for catchments across the country. The "WT_LSTM_data" folder contains ".csv" files with calculated WT (Willard, 2023) and the associated RMSEs. The "Upper_Colorado_River_Basin_Boundary" folder contains geographic data including a shapefile for plotting in the UCRB_Drought_Workflow.ipynb. The "RESERVOIRS_RAW" folder contains ".csv" files for each reservoir in the UCRB with daily reservoir storage. There are also two files in the INPUTS folder that have combined reservoir storage data and reservoir metadata. The OUTPUTS folder is organized into the following major directories and sub-directories. The "RDC_WT_SC_data" folder contains a folder "Water_year" with the associated cleaned data, metadata, and data availability information in ".csv" files, a folder "Median_Relchange" with the relative change comparing drought to non-drought years in ".csv" files, and a folder "Peak95_Min5_Relchange" that has ".csv" files for the relative change in peak (95th %) and minimum (5th %) variables. The "NLCD_data" folder contains the difference in land cover from the beginning to end of the study period and the percentage of the county that is within UCRB bounds can be found in Nagamoto et al (2025)). The "MET_data" folder contains separated monthly air temperature and precipitation data and the calculated PET in ".csv" files. The "SPEI_data" folder contains ".csv" files with calculated SPEI values (one restricted to the study period and the other with information from the entire MET data period). The "Paper_Tables" folder contains two ".csv" files containing site information and data availability and information about the GAGESII trait aggregated categories. The base directory includes the file “flmd.csv” for a list and description of all files and the file “dd.csv” for data dictionaries. Scripts for preprocessing, analysis, and figure generation are located in the associated GitHub repository found at [https://github.com/iNAIADS/drought-impacts/tree/develop/UCRB-drought]. UPDATE 1: Title and code file updated to match submitted manuscript 10-15-2025. UPDATE 2: Code and data files updated to match revised manuscript 3-4-2026. UPDATE 3: Code and data files updated to match revised manuscript 6-7-2026. ** NOTE: DD and FLMD have not been updated yet. UPDATE 4: Added associated Manuscript information and DD and FLMD have been updated. To cite this code, please use the following BibTeX: @misc{nagamoto2025drought, author = {Emily Nagamoto and Fabio Ciulla and Mohammad Ombadi and Jared Willard and Rosemary Carroll and Charuleka Varadharajan}, title = {Dataset: "Widespread Drought-driven Declines in Streamflows and Water quality in the Upper Colorado River Basin (1998-2022)"}, year = {2025}, doi = {10.15485/2551894}, publisher = {ESS-DIVE Repository}, url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2551894} }
Short-term time variability of Cygnus X-1. III
Data from a SAS 3 observation of Cygnus X-1 have been analyzed, assuming a simple shot-noise model for the time variability. The results confirm the suggestion of Sutherland, Weisskopf, and Kahn that the shot parameters are constant when the source is in its low state. The first significant measurement of the time sense of the shot-noise pulses was performed, with the result that the average pulse shape is time-symmetric, not asymmetric as has been previously assumed.
Characterizing the 2019-2021 Drought in La Plata River Basin With GLDAS and SMAP
Study region The La Plata River Basin (LPRB) is an area of interest, as there was a significant drought event from 2019 to 2021. With the LPRB being the second largest river basin in South America, this drought affected all aspects of life for over 100 million people who inhabit this area. Study focus In this study, we utilized satellite and model datasets to examine spatial and temporal variability of hydrological anomalies throughout the basin before and during the drought event. These variable anomalies, such as precipitation and groundwater, are derived from the Global Land Data Assimilation System (GLDAS). Additionally, the Soil Moisture Active Passive (SMAP) observations were used in the spatial and temporal analysis of the drought. The water loss was calculated using the Mann-Kendall test to assess the changes in anomalies for the terrestrial water storage throughout the basin and subbasins. New hydrological insights for the region The main insight from this study is the agreement of the GLDAS anomalies with the SMAP data throughout the drought. The variable anomalies all decreased and showed alignment with the downscaled 1 km SMAP which shows alignment with the trends from in-situ observations. It was also found that the Upper Parana subbasin lost the most water over the drought period. These products improve understanding of the spatial variability within the entire basin and facilitate understanding of droughts and resources to assist in the future management of water resources.
Measured acoustic properties of variable and low density bulk absorbers
Experimental data were taken to determine the acoustic absorbing properties of uniform low density and layered variable density samples using a bulk absober with a perforated plate facing to hold the material in place. In the layered variable density case, the bulk absorber was packed such that the lowest density layer began at the surface of the sample and progressed to higher density layers deeper inside. The samples were placed in a rectangular duct and measurements were taken using the two microphone method. The data were used to calculate specific acoustic impedances and normal incidence absorption coefficients. Results showed that for uniform density samples the absorption coefficient at low frequencies decreased with increasing density and resonances occurred in the absorption coefficient curve at lower densities. These results were confirmed by a model for uniform density bulk absorbers. Results from layered variable density samples showed that low frequency absorption was the highest when the lowest density possible was packed in the first layer near the exposed surface. The layers of increasing density within the sample had the effect of damping the resonances.
Mapping tall shrub biomass in Alaska at landscape scale using structure-from-motion photogrammetry and lidar
Warming in arctic and boreal regions is increasing shrub cover and biomass. In southcentral Alaska, willow (Salix spp.) and alder (Alnus spp.) shrubs grow taller than many tree species and account for a substantial proportion of aboveground biomass, yet they are not individually measured as part of the operational Forest Inventory and Analysis (FIA) Program. The goal of this research was to test methods for landscape-scale mapping of tall shrub biomass in upper montane and subalpine environments using FIA-type plot measurements (n = 51) and predictor variables from imagery-based structure-from-motion (SfM) and airborne lidar. Specifically, we compared biomass models constructed from imagery acquired by unmanned aerial vehicle (UAV; ~1.7 cm pixels), imagery from the NASA Goddard's Lidar, Hyperspectral, and Thermal Airborne Imager (G-LiHT; ~3.1 cm pixels), and concomitant G-LiHT small-footprint lidar. Tall shrub biomass was most accurately predicted at 5 m resolution (R^2 = 0.81, RMSE = 1.09 kg/sq. m) using G-LiHT SfM color and structure variables. Lidar-only models had lower precision (R^2 = 0.74, RMSE = 1.26 kg/sq. m), possibly due to reduced model information content from variable multicollinearity or lower data density. Separate models for upper montane zones with trees and shrubs and subalpine zones with only shrubs were always chosen over single models based on minimization of Akaike's Information Criterion, indicating the need for variable sets robust to overhanging tree canopy. Decreasing point density from UAV (5000–8000 pts./sq. m) to the G-LiHT SfM point cloud (500–2000 pts./sq. m) had little impact on model fit, suggesting that high-resolution airborne imagery can extend SfM approaches well beyond line-of-sight restrictions for UAV platforms. Overall, our results confirmed that SfM from high-resolution imagery is a viable approach to estimate shrub biomass in the boreal region, especially when an existing lidar terrain model and local field calibration data are available to quantify uncertainty in the SfM point cloud and landscape-scale estimates of shrub biomass.
Reanalyses and Essential Climate Variables
Reanalyses are a potentially powerful climate data collection driven by observations but also subjected to model bias. Additionally, reanalyses can produce and use essential climate variables in a consistent method. For example, snow cover and soil moisture (among other variables) will eventually be assimilated into the reanalyses, but also provide crucial validation data. Sea surface temperature can be prescribed or assimilated in a coupled reanalysis. The strength of reanalysis lies in the ancillary data that is produced from the modeling components but not routinely observed thereby providing more complete Earth system information. The weakness in this concept is that the model derived data can be affected by model bias and may also change relative to the available observing system. Here, we will review the status of existing reanalyses and the ECVs being considered for the workshop. Purpose of Michael Bosilovich's contribution to the workshop: Michael Bosilovich will represent US reanalysis community in this international discussion of Essential Climate Variables (ECVs) and the relative nature of reanalyses to ECVs.
Vector wind profile gust model
Work towards establishing a vector wind profile gust model for the Space Transportation System flight operations and trade studies is reported. To date, all the statistical and computational techniques required were established and partially implemented. An analysis of wind profile gust at Cape Kennedy within the theoretical framework is presented. The variability of theoretical and observed gust magnitude with filter type, altitude, and season is described. Various examples are presented which illustrate agreement between theoretical and observed gust percentiles. The preliminary analysis of the gust data indicates a strong variability with altitude, season, and wavelength regime. An extension of the analyses to include conditional distributions of gust magnitude given gust length, distributions of gust modulus, and phase differences between gust components has begun.
Satellite Observed Variability in Antarctic and Arctic Surface Temperatures and Their Correlation to Open Water Areas
Recent studies using meterological station data have indicated that global surface air temperature has been increasing at a rate of 0.05 K/decade. Using the same set of data but for stations in the Antarctic and Arctic regions (>50 N) only, the increases in temperature were 0.08, and 0.22 K/decade, when record lengths of 100 and 50 years, respectively, were used. To gain insights into the increasing rate of warming, satellite infrared and passive microwave observations over the Arctic region during the last 20 years were processed and analyzed. The results show that during this period, the ice extent in the Antarctic has been increasing at the rate of 1.2% per decade while the surface temperature has been decreasing at about 0.08 K per decade. Conversely, in the Northern Hemisphere, the ice extent has been decreasing at a rate of 2.8% per decade, while the surface temperatures have been increasing at the rate of 0.38 K per decade. In the Antarctic, it is surprising that there is a short term trend of cooling during a global period of warming. Very large anomalies in open water areas in the Arctic were observed especially in the western region, that includes the Beaufort Sea, where the observed open water area was about 1x10(exp 6) sq km, about twice the average for the region, during the summer of 1998. In the eastern region, that includes the Laptev Sea, the area of open water was also abnormally large in the summer of 1995. Note that globally, the warmest and second warmest years in this century, were 1998 and 1995, respectively. The data, however, show large spatial variability with the open water area distribution showing a cyclic periodicity of about ten years, which is akin to the North Atlantic and Arctic Oscillations. This was observed in both western and eastern regions but with the phase of one lagging the other by about two years. This makes it difficult to interpret what the trends really mean. But although the record length of satellite data is still relatively short and the climate trend difficult to establish, the immediate impact of a continued warming trend may be very profound.
Data and scripts associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration”
This data package is associated with “Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration” published in EGU Biogeosciences (Stegen et al., 2026; https://doi.org/10.5194/bg-23-3981-2026). It contains cotton strip decomposition rates (Kcd and Kdd) collected across the Yakima River Basin (YRB), Washington, USA. These data were collected to support a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. Associated data used in analysis, metadata, and field protocols can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1969566, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1987520. This data package is associated with the repository found at https://github.com/river-corridors-sfa/rcsfa-ST-2B-SSS-cotton-strip. A preliminary version of this data package was published in December 2025 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include additional metadata (this readme, data dictionary, and file level metadata). The data did not change. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This data package consists of (1) readme; (2) data dictionary (dd); (3) file level metadata (flmd); and (4) four folders: (1) R-scripts; (2) figures; (3) outputs from the scripts; and (4) published data. The published data folder contains a readme directing the user to download data in order to run the R-scripts. All files are .csv, .pdf, .R, .Rmd, and .txt. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.
HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP
Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.
Two-Dimensional Model Simulations of Interannual Variability in the Tropical Stratosphere
Meteorological data from the United Kingdom Meteorological Office (UKMO) and constituent data from the Upper Atmospheric Research Satellite (UARS) are used to construct yearly zonal mean dynamical fields for the 1990s for use in the GSFC 2-D chemistry and transport model. This allows for interannual dynamical variability to be included in the model constituent simulations. In this study, we focus on the tropical stratosphere. We find that the phase of quasi-biennial oscillation (QBO) signals in equatorial CH4, and profile and total column 03 data is resolved quite well using this empirically- based 2-D model transport framework. However. the QBO amplitudes in the model constituents are systematically underestimated relative to the observations at most levels. This deficiency is probably due in part to the limited vertical resolutions of the 2-D model and the UKMO and UARS input data sets. We find that using different heating rate calculations in the model affects the interannual and QBO amplitudes in the constituent fields, but has little impact on the phase. Sensitivity tests reveal that the QBO in transport dominates the ozone interannual variability in the lower stratosphere. with the effect of the temperature QBO being dominant in the tipper stratosphere via the strong temperature dependence of the ozone loss reaction rates. We also find that the QBO in odd nitrogen radicals, which is caused by the QBO modulated transport of NOy, plays a significant but not dominant role in determining the ozone QBO variability in the middle stratosphere. The model mean age of air is in good overall agreement with that determined from tropical lower,middle stratospheric OMS balloon observations of SF6 and CO2. The interannual variability of tile equatorial mean age in the model increases with altitude and maximizes near 40 km, with a range, of 4-5 years over the 1993-2000 time period.
Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars
Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.
Application of spectral analysis techniques in the intercomparison of aerosol data: Part III. Using combined PCA to compare spatiotemporal variability of MODIS, MISR, and OMI aerosol optical depth
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Diurnal variability of regional cloud radiative parameters from geostationary satellite data
In the discussed study, Geostationary Operational Environmental Satellite visible and infrared brightness measurements are used to infer regional cloud cover and several associated radiative parameters on an hourly basis. Several techniques are utilized to derive the parameters of interest. These parameters include the areal cloud fraction, cloud-atmosphere albedo, surface-atmosphere albedo, and equivalent blackbody surface and cloud-top temperatures. Attention is given to clear radiance temperature determinations, surface temperature modeling, the infrared threshold method, narrowband-broadband correlations, and albedo determination. Monthly mean values were computed for each parameter as a function of local time. Cloud amounts and temperatures are considered along with longwave emission and shortwave albedo, and composite results.
Kelvin wave variability in the upper stratosphere observed in SBUV ozone data
The Solar Backscatter UV ozone data collected for the eight years between 1979 and 1986 are used to analyze the signatures of equatorially trapped Kelvin waves in the upper stratosphere. The data reveal a strong semiannual modulation of Kelvin wave activity, confirming the results of previous rocketsonde observations. A comparison of the eight-year-average ensemble spectra to the semiannual oscillation in the stratospheric zonal winds revealed a seasonal asymmetry in the strength of Kelvin waves, which mimics the asymmetry observed in the zonal winds. No consistent relationship was observed with the quasi-biennial oscillation in the lower stratosphere, while correlations with the upper stratospheric winds are weak or nonexistent.
Interannual Variability of Snow and Ice and Impact on the Carbon Cycle
The goal of this research is to assess the impact of the interannual variability in snow/ice using global satellite data sets acquired in the last two decades. This variability will be used as input to simulate the CO2 interannual variability at high latitudes using a biospheric model. The progress in the past few years is summarized as follows: 1) Albedo decrease related to spring snow retreat; 2) Observed effects of interannual summertime sea ice variations on the polar reflectance; 3) The Northern Annular Mode response to Arctic sea ice loss and the sensitivity of troposphere-stratosphere interaction; 4) The effect of Arctic warming and sea ice loss on the growing season in northern terrestrial ecosystem.