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DOE OSTI2026

Warming and snow loss increase reliance on old groundwater in a Colorado River headwater

Atmospheric warming is reducing snowpack, with uncertain effects on mountainous streamflow, a crucial water resource. Despite limited historical observations of groundwater–streamflow interactions above 2,500 m, new measurements in the Upper Colorado River headwaters indicate declining groundwater storage that is dated decades to millennia old. Here we use integrated hydrologic modelling spanning water years 2015–2021 to determine whether the loss of old-age groundwater buffers streamflow during low-snow years and whether that loss is exacerbated with warming. Results show that old-groundwater contributions to streams remain relatively steady through time, unlike the more variable contributions from young groundwater. Numerical experiments of increased surface air temperatures (+2.5 °C and +4 °C) increase rain–snow fractions and evapotranspiration and decrease runoff ratio by 2–3% per degree Celsius increase. As streamflow declines with warming, the age of groundwater supporting it gets older, in part owing to intermediate-aged (1–3 year) groundwater declining twice as fast. Simulations show that water table depths at higher elevations (>3,700 m) decline disproportionately and fail to recover even during wet years. These findings suggest altered groundwater–streamflow interactions with warming and snow loss, with implications for water resources.

Siirila-Woodburn, Erica R. [Lawrence Berkeley Nati↗

NASA NTRSDate not supplied

Implementation of A New Microwave Scattering Database and A Forward Model for Active Microwave Sensors in CRTM

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. CRTM is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk scattering lookup tables in order to perform all-sky RT calculations. However, the current CRTM lookup tables for microwave frequencies were generated based on the Mie theory by assuming spherical frozen particles. The scattering lookup tables generated using the DDA technique has shown to largely improve the RT scattering calculations in the MW region. This presentation targets (i) the implementation and validation of a DDA database that was originally developed for the ARTS RT model into CRTM, and (ii) developing the CRTM active sensor module that takes advantage of the backscattering coefficients computed using the DDA method. The DDA database only provides single scattering properties of different habits, while CRTM requires bulk scattering properties. The CRTM cloud coefficients were previously generated based on the effective radius for representing the size of the particles. However, effective radius is neither measurable nor provided by the NWP models, thus need to be estimated from other geophysical variables such as water content. Therefore, in addition to calculating the CRTM bulk scattering properties from the DDA single scattering database, the CRTM was also largely modified to use cloud water content (kg.m-3), instead of effective radius, for performing the interpolation over size/mass of the particles. CRTM already requires water content as input, thus no extra variables are required for performing scattering calculations using the new ARTS DDA database. The CRTM scattering modules search for effective radius in cloud coefficient files and will use the cloud water content if the effective radius dimension is not found in the cloud coefficient files. Figure 1 shows the CRTM simulated brightness temperatures computed using different cloud coefficients versus ATMS observed values over Hurricane Irma on September 7, 2017 at 18:00 UTC. We used all the cloud water content values included in ERA5 with default CRTM/DDA habits for water, rain, snow, ice, hail, and graupel. ERA5 does not provide separate water content values for ice, hail, and graupel, thus the ice water content values were divided between ice, hail, and graupel clouds similar to what was explained in the previous section. In channels with a frequency lower than 90 GHz, emission from water and rain clouds can compensate for cloud scattering so that cloud contaminated Tbs are larger than corresponding clear sky Tbs. The DDA simulations for channels 1-7 largely perform better than the Mie simulations. The DDA simulations show a mix of small negative and positive simulated minus observed values, while the Mie results show large negative biases. The weighting functions for some of the ATMS temperature sounding channels (channels 9-15) peak mostly above the clouds, therefore the measured Tbs become less sensitive to clouds so that the results of both Mie and DDA become very similar. The Mie lookup tables generate excessive scattering for channel 16, but not enough scattering for the water vapor channels. In the specific case of Hurricane Maria, the DDA lookup tables do not generate enough scattering for channel 16, but the DDA results are much more consistent with observations for water vapor channels than for channel 16. It should be noted that the results may vary if we use other habits to represent snow, hail, and graupel in the DDA simulations. Although these results clearly show the advantage of the DDA database over the Mie dataset, different error sources such as error in the observations, displacement of clouds in the ERA5 reanalysis, and also lack of convective clouds or in general errors in the input atmospheric and cloud profiles contribute to the differences between the simulated and observed values. Aside from the improvements in the simulations, a major advantage of the new dataset is a large number of habits that can be used to tune the data assimilation systems to perform well in different weather conditions.

Isaac Moradi↗

NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗

NASA NTRS1993

Aircraft empennage structural detail design

The purpose of this project is to provide an empennage structural assembly that will withstand the operational loads defined in FAR Part 23, as well as those specified in the statement of work, i.e. snow, rain, humidity, tiedown forces, etc. The goal is to provide a simple yet durable lightweight structure that will transfer the aerodynamic forces produced by the tail surfaces through the most efficient load path to the airframe. The structure should be simple and cost-effective to manufacture and repair. All structures meet or exceed loading and fatigue criteria. The structure provides for necessary stiffness and ease of maintenance.

Lesnewski, David↗

DOE OSTI2025

Temporal Study 2022-2024: Sample-Based Surface Water Dissolved Inorganic Carbon, Dissolved Organic Carbon, Total Nitrogen, Stable Isotopes, and Total Suspended Solids from across Multiple Watersheds in the Yakima River Basin, Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides geochemistry data generated from samples collected at bi-weekly or monthly intervals at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sensor data from 2022-2024 will be published separately. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) dissolved inorganic carbon (DIC) and averages; (6) dissolved organic carbon (DOC; reported as non-purgeable organic carbon; NPOC) and averages; (7) total dissolved nitrogen (TN) and averages; (8) total suspended solids (TSS); (9) stable isotopes; (10) surface water sampling protocol; (11) sensor protocol; (12) methods codes; and (13) international generic sample number (IGSN) mapping file. All files are .csv or .pdf. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. For data and scripts associated with "Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest" (Butler et al., 2026), go to https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3025481

18-O↗

DOE OSTI2021

Quality Data Essential for Modeling Water Cycles Effectively

The experimental and observational data is the backbone of effective modeling of all aspects of water cycles. As the computer technology used for these data gathering efforts has improved dramatically in the recent decades, the environmental conditions these instruments are subjected to remain pretty much the same. These measuring instruments are exposed to the sun light, wind, rain, snow and ice; and they are immersed in dirt, water and mud. All of these are damaging to the electronics components used for data gathering, storage, and transmission, which creates many different kinds of data quality issues that affect the quality and reliability of modeling and prediction efforts.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Seventh Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems 26-28 October 1983, Tullahoma, Tennessee

A summary of reports and recommendations resulting from the Workshop on Meteorological and Environmental Inputs to Aviation Systems is presented. The Workshops have been held to characterize the interaction between aircraft and airport operators with the atmosphere, identify necessary meteorological enhancements, and establish criteria for meteorological data needed by the aviation community. The topics covered included winds and wind shear, turbulence, fog, visibility and ceiling, lightning and atmospheric electricity, icing, frost and snow, rain, ozone and acid rain. The recommendations issued included a denser meteorological network with more automated stations, the development of radar systems for icing forecasts and wind shear alerts, the accumulation of a greater data base on convective cells and lightning strikes, and further study of the impact of rain on aircraft performance.

Camp, D. W.↗

NASA NTRS1987

The terminal area simulation system. Volume 1: Theoretical formulation

A three-dimensional numerical cloud model was developed for the general purpose of studying convective phenomena. The model utilizes a time splitting integration procedure in the numerical solution of the compressible nonhydrostatic primitive equations. Turbulence closure is achieved by a conventional first-order diagnostic approximation. Open lateral boundaries are incorporated which minimize wave reflection and which do not induce domain-wide mass trends. Microphysical processes are governed by prognostic equations for potential temperature water vapor, cloud droplets, ice crystals, rain, snow, and hail. Microphysical interactions are computed by numerous Orville-type parameterizations. A diagnostic surface boundary layer is parameterized assuming Monin-Obukhov similarity theory. The governing equation set is approximated on a staggered three-dimensional grid with quadratic-conservative central space differencing. Time differencing is approximated by the second-order Adams-Bashforth method. The vertical grid spacing may be either linear or stretched. The model domain may translate along with a convective cell, even at variable speeds.

Proctor, F. H.↗

NASA NTRS1991

Thunderstorm detection and warning system atmospheric potential monitor

An new type of electric field instrumentation was developed for lighting prediction at KSC. Currently, it is being installed at several government laboratories and is being made available to the public. It has important advantages over the previous method for measuring electric fields with motor driven field mills: (1) it has no moving parts and requires little maintenance compared to rotating machinery; (2) it is unaffected by rain, snow, sand, or insects, all of which can influence field mills; and (3) the lightweight sensor can be mounted easily on a tall mast. By mounting the instrumentation on a tall mast the instrumentation is placed above much of the blanket of point discharge ions that are emitted from objects on the ground during thunderstorms. This space charge limits the ability of any ground based electric field sensor to accurately measure cloud electric fields which produce lightning. The elevated mounting was demonstrated to significantly improve monitoring of thunderstorm electric fields. This instrumentation measures the atmospheric potential relative to earth at a corona needle sensor on top of a mast which normally is mounted on a tower or roof. The needle is kept in corona at all times by a low power high voltage power supply. This produces a small cloud of ions around the needle allowing a current to flow. Measurement of the current provides the atmospheric potential. The potential divided by the height of the needle above the ground is proportional to the average electric field between the needle and earth. The potential on top of a tall pole or above a rooftop is more representative of the intensity of cloud electrification than electric field measurements made at ground level. Photographs that depict the computer terminal, video display of a two sensor system, and the individual components installed on a tower are presented.

Source record↗

NASA NTRS2005

Real-time Enhanced Vision System

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

Hines, Glenn D.↗

NASA NTRS2004

A Hybrid Synthetic Vision System for the Tele-operation of Unmanned Vehicles

A system called SmartCam3D (SC3D) has been developed to provide enhanced situational awareness for operators of a remotely piloted vehicle. SC3D is a Hybrid Synthetic Vision System (HSVS) that combines live sensor data with information from a Synthetic Vision System (SVS). By combining the dual information sources, the operators are afforded the advantages of each approach. The live sensor system provides real-time information for the region of interest. The SVS provides information rich visuals that will function under all weather and visibility conditions. Additionally, the combination of technologies allows the system to circumvent some of the limitations from each approach. Video sensor systems are not very useful when visibility conditions are hampered by rain, snow, sand, fog, and smoke, while a SVS can suffer from data freshness problems. Typically, an aircraft or satellite flying overhead collects the data used to create the SVS visuals. The SVS data could have been collected weeks, months, or even years ago. To that extent, the information from an SVS visual could be outdated and possibly inaccurate. SC3D was used in the remote cockpit during flight tests of the X-38 132 and 131R vehicles at the NASA Dryden Flight Research Center. SC3D was also used during the operation of military Unmanned Aerial Vehicles. This presentation will provide an overview of the system, the evolution of the system, the results of flight tests, and future plans. Furthermore, the safety benefits of the SC3D over traditional and pure synthetic vision systems will be discussed.

Delgado, Frank↗

NASA NTRS2007

Aircraft Weather Mitigation for the Next Generation Air Transportation System

Atmospheric effects on aviation are described by Mahapatra (1999) as including (1) atmospheric phenomena involving air motion - wind shear and turbulence; (2) hydrometeorological phenomena - rain, snow and hail; (3) aircraft icing; (4) low visibility; and (5) atmospheric electrical phenomena. Aircraft Weather Mitigation includes aircraft systems (e.g. airframe, propulsion, avionics, controls) that can be enacted (by a pilot, automation or hybrid systems) to suppress and/or prepare for the effects of encountered or unavoidable weather or to facilitate a crew operational decision-making process relative to weather. Aircraft weather mitigation can be thought of as a continuum (Figure 1) with the need to avoid all adverse weather at one extreme and the ability to safely operate in all weather conditions at the other extreme. Realistic aircraft capabilities fall somewhere between these two extremes. The capabilities of small general aviation aircraft would be expected to fall closer to the "Avoid All Adverse Weather" point, and the capabilities of large commercial jet transports would fall closer to the "Operate in All Weather Conditions" point. The ability to safely operate in adverse weather conditions is dependent upon the pilot s capabilities (training, total experience and recent experience), the airspace in which the operation is taking place (terrain, navigational aids, traffic separation), the capabilities of the airport (approach guidance, runway and taxiway lighting, availability of air traffic control), as well as the capabilities of the airplane. The level of mitigation may vary depending upon the type of adverse weather. For example, a small general aviation airplane may be equipped to operate "in the clouds" without outside visual references, but not be equipped to prevent airframe ice that could be accreted in those clouds.

Stough, H. Paul, III↗

NASA NTRS2005

Constraining Hydrological and Cryospheric Mass Flux in Southeastern Alaska using Space-Based Gravity Measurements

Watersheds draining into the Gulf of Alaska (GoA) experience large seasonal and inter-annual variations of water in the form of rain, snow, and ice, but accurate constraints on these variations have been difficult to obtain. Over larger geographic regions, water variations can be inferred directly from the Gravity Recovery and Climate Experiment (GRACE) data. However, because GoA variations occur over such a small region, the inferred average value of water flux increases as the applied smoothing of the GRACE data decreases. We use this observed scaling together with scaling results obtained from forward models to infer a seasonal amplitude of 115 plus or minus 20 cubic kilometers of water and an average contribution to sea level rise over the two years of data of 0.31 plus or minus 0.09 millimeters per year. These results suggest that accelerated melting that began in the late 1990s, as inferred from altimetry, continues unabated.

Tamisiea, M. E.↗

NASA NTRS2010

4-D Cloud Water Content Fields Derived from Operational Satellite Data

In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.

Smith, William L., Jr.↗

NASA NTRS2011

Precipitation Estimates for Hydroelectricity

Hydroelectric plants require precise and timely estimates of rain, snow and other hydrometeors for operations. However, it is far from being a trivial task to measure and predict precipitation. This paper presents the linkages between precipitation science and hydroelectricity, and in doing so it provides insight into current research directions that are relevant for this renewable energy. Methods described include radars, disdrometers, satellites and numerical models. Two recent advances that have the potential of being highly beneficial for hydropower operations are featured: the Global Precipitation Measuring (GPM) mission, which represents an important leap forward in precipitation observations from space, and high performance computing (HPC) and grid technology, that allows building ensembles of numerical weather and climate models.

Tapiador, Francisco J.↗

NASA NTRS2013

Aerogel-Based Multilayer Insulation with Micrometeoroid Protection

Ultra-low-density, highly hydrophobic, fiber-reinforced aerogel material integrated with MLI (aluminized Mylar reflectors and B4A Dacron separators) offers a highly effective insulation package by providing unsurpassed thermal performance and significant robustness, delivering substantial MMOD protection via the addition of a novel, durable, external aerogel layer. The hydrophobic nature of the aerogel is an important property for maintaining thermal performance if the material is exposed to the environment (i.e. rain, snow, etc.) during ground installations. The hybrid aerogel/MLI/MMOD solution affords an attractive alternative because it will perform thermally in the same range as MLI at all vacuum levels (including high vacuum), and offers significant protection from micrometeoroid damage. During this effort, the required low-density and resilient aerogel materials have been developed that are needed to optimize the thermal performance for space (high vacuum) cryotank applications. The proposed insulation/MMOD package is composed of two sections: a stack of interleaved aerogel layers and MLI intended for cryotank thermal insulation, and a 1.5- to 1-in. (.2.5- to 3.8- cm) thick aerogel layer (on top of the insulation portion) for MMOD protection. Learning that low-density aerogel cannot withstand the hypervelocity impact test conditions, the innovators decided during the course of the program to fabricate a high-density and strong material based on a cross-linked aerogel (X-aerogel; developed elsewhere by the innovators) for MMOD protection. This system has shown a very high compressive strength that is capable of withstanding high-impact tests if a proper configuration of the MMOD aerogel layer is used. It was learned that by stacking two X-aerogel layers [1.5-in. (.3.8-cm) thick] separated by an air gap, the system would be able to hold the threat at a speed of 5 km/s and gpass h the test. The first aerogel panel stopped the projectile from damaging the second aerogel panel. The impacted X-aerogel (the back specimen from the successful test) was further tested in comparison to another similar sample (not impacted) at Kennedy Space Center for thermal conductivity evaluation at cryogenic conditions. The specimens were tested under high vacuum and cryogenic temperatures, using Cryostat 500. The results show that the specimen did not lose a significant amount of thermal performance due to the impact test, especially at high vacuum.

Begag, Redouane↗

NASA NTRS2019

A Landslide Climate Indicator from Machine Learning

In order to create a Landslide Hazard Index, we accessed rain, snow, and a dozen other variables from the National Climate Assessment Land Data Assimilation System. These predictors were converted to probabilities of landslide occurrence with XGBoost, a major machine-learning tool. The model was fitted with thousands of historical landslides from the Pacific Northwest Landslide Inventory (PNLI).

Stanley, T. A.↗

NASA NTRSDate not supplied

An Update on the Hydrological Land Surface Data and Services at NASA GES DISC

"The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth Observing System data centers that document, process, archive and distribute data from Earth science missions and related projects. The GES DISC hosts many hydrological land surface data products including North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and assimilated-Gravity Recovery and Climate Experiment (GRACE). The Land Surface Model (LSM) products contain model output, including heat fluxes, rain, snow, soil temperature, soil moisture and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at the GES DISC ranges from hourly to monthly and the spatial resolution 0.1 degree to 1.0 degree. The variability of Earth’s water and energy cycles can be characterized with these spatially and temporally consistent, and quality controlled hydrological land surface data. These data could support ongoing modeling activities, and help improve our understanding of land-surface-atmosphere interactions and their impact on climate. Over the years, new data is added, and older data is reprocessed and updated. This presentation provides a summary table of the hydrological data and discusses recent updates to the data and data services at the GES DISC. New data products include (1) GRACE Global Version 3.0 drought indicators and (2) FLDAS monthly global and Central Asia daily data. Reprocessed and updated products include (1) NLDAS Version 2.0 and (2) GRACE United States Version 4.0 drought indicators. Lastly, this presentation will discuss the opportunities for accessing some of our hydrology data from the cloud. As the hydrology land surface data is moved to the cloud, users can expect faster service for longer time series, notably the hydrology data rods time series service."

Ashley Heath↗