159 research outputs found
Data for figures in Kemp, E M, J W Wegiel, S V Kumar, J V Geiger, D M Mocko, J P Jacob, and C D Peters-Lidard, 2021: A NASA-Air Force precipitation analysis for near-real-time operations. Submitted to _J Hydrometeor_
No full text<p>Tar files containing gridded metrics, domain-wide metric means and confidence intervals, and rain-gauge reports used to generate figures in Kemp et al (2021).<br>
<br>
Citation:<br>
</p>
<p>Kemp, E M, J W Wegiel, S V Kumar, J V Geiger, D M Mocko, J P Jacob, and C D Peters-Lidard, 2021: A NASA-Air Force precipitation analysis for near-real-time operations. Submitted to _J Hydrometeor_.</p>
Data and code for: Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent
No full textCode and data to reproduce figures in manuscript entitled "Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent" published in Hydrology and Earth System Sciences (https://hess.copernicus.org/preprints/hess-2022-136/).
The contents include three folders, "Codes", "Data", and "Figures". In "Codes" folder, R scripts are listed in the order needed to reproduce the figures. All code is written in R version 4.2.0. Data sets needed to reproduce figures are provided in "Data" folder (Rdata format). The pdf files in "Figures" folder are outputs generated from the corresponding R scripts. Note that final figures in the article were produced by combining multiple figures using a vector graphics software (Inkscape) or PowerPoint. Please contact Eunsang Cho ([email protected]) with any questions.
Preferred citation: Cho, E., Vuyovich, C. M., Kumar, S. V., Wrzesien, M. L., Kim, R. S., and Jacobs, J. M. (2022). Precipitation Biases and Snow Physics Limitations Drive the Uncertainties in Macroscale Modeled Snow Water Equivalent, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-2022-136.
Corresponding author: Eunsang Cho ([email protected]; [email protected])This work has been supported by the NASA Terrestrial Hydrology Program (NNH16ZDA001N
Quantifying and Reducing Uncertainty from Multiple Sources in Forecasting Monthly to Seasonal Land-Surface Attributes.
No full textLand surface Verification Toolkit (LVT)
No full textLVT is a framework developed to provide an automated, consolidated environment for systematic land surface model evaluation Includes support for a range of in-situ, remote-sensing and other model and reanalysis products. Supports the analysis of outputs from various LIS subsystems, including LIS-DA, LIS-OPT, LIS-UE. Note: The Land Information System Verification Toolkit (LVT) is a NASA software tool designed to enable the evaluation, analysis and comparison of outputs generated by the Land Information System (LIS). The LVT software is released under the terms and conditions of the NASA Open Source Agreement (NOSA) Version 1.1 or later. Land Information System Verification Toolkit (LVT) NOSA
SMAP soil moisture assimilated Noah-MP model output
No full textThe Noah-MP land surface model was run on an equidistant cylindrical grid at a spatial resolution of 0.05 degree x 0.05 degree from 2015 to 2020. Open loop and data assimilation (with and without CDF-matching) runs were executed based on the methodology described in Ahmad et al. (2021) using MERRA2 and IMERG precipitation boundary conditions. The NetCDF files archived here were reprocessed to include the model output states discussed in the paper only. These include: 1) surface soil moisture, 2) rootzone soil moisture, 3) evapotranspiration, and 4) gross primary production.
References:
Ahmad, J. A., Forman, B. A., and Kumar, S. V. (2021), SMAP retrieval assimilation improves soil moisture estimation across irrigated areas in South Asia, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2021-460.The data archived here includes the NASA Noah-MP (version 4.0.1) land surface model output used in the investigation of the impact of passive microwave-based soil moisture retrieval assimilation on soil moisture estimation in South Asia (Ahmad et al., 2021). SMAP soil moisture retrievals are assimilated into the Noah-MP land surface model to improve the estimation of soil moisture and other related states. The open loop (OL) represents Noah-MP’s modeling capabilities using MERRA2 and IMERG precipitation. Two different types of data assimilation runs were executed using the MERRA2 and IMERG precipitation boundary conditions, i.e., with CDF-matching (DA-CDF) and without CDF matching (DA-NoCDF). The key findings in this paper include: 1) assimilation results without any CDF-matching yielded the lowest error in estimated soil moisture, 2) the best goodness-of-fit statistics were achieved for the IMERG-forced DA-NoCDF soil moisture experiment, 3) biases associated with unmodeled hydrologic processes such as irrigation were corrected via assimilation, and 4) the highest influence of assimilation was observed across croplands.NASA Understanding Changes in High Mountain Asia (Contract# 80NSSC2OK1531)https://doi.org/10.5194/hess-2021-46
Vitri - A Generic Framework for Engineering Decision Support Systems on Heterogeneous Computer Networks
No full textVitri is an object-oriented framework implemented in Java for high-performance distributed computing. Using Vitri, applications can engage in cooperativeproblem solving by dividing their tasks among heterogeneous clusters of workstations and PCs. Vitri's features include basic support fordistributed computing and communication, as well as visual tools for evaluating run-time performance, and modules for heuristic optimization. It balances loads dynamically using a client-side task pool, allows theaddition or removal of servers during a run, and provides fault tolerance transparently for servers and networks. Among its more powerful featuresare modules for heuristic optimization and decision support tools such asmodeling to generate alternatives (MGA). Vitri also provides an asynchronous global-parallel genetic algorithm that is particularly suited for coarse-grained tasks executing on processors with large variations in processor speeds. By using dataflow techniques, in which computations areexplicitly based on the availability and forwarding of data, the usual end-of-generation synchronization points are removed from the algorithm. The tools in Vitri are applied to a number of different applicationsfrom the civil engineering domain. The results indicate the adaptability of Vitri to various problems and its utility as a tool for managing engineering decision support systems
Surface albedo decreases from anthropogenic impacts over High Mountain Asia with implications of positive radiative forcing feedbacks
No full textHuman and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the radiative forcing by changing the surface albedo. Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in High Mountain Asia (HMA), home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges-Brahmaputra) which causes the highest surface albedo decreases (£1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of human management and human-induced greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.This research was supported by the grant from the National Aeronautics and Space Administration High Mountain Asia program (19-HMA19-0012). Computing was supported by the resources at the NASA Center for Climate Simulation.https://www.researchsquare.com/article/rs-1413058/v
Diverging Trends in Rain-On-Snow Over High Mountain Asia
No full textRain-on-snow (ROS) over snow-dominated regions such as High Mountain Asia (HMA) modulates snowmelt and runoff and is key contributor in influencing water availability and hazards (e.g., floods and landslides). We studied the trends in ROS in HMA over the past two decades from 2001 to 2018 using the land surface model Noah-MP driven by an ensemble precipitation data set. Our results show that changes in precipitation phase and rainfall are altering ROS. Because of the strong physical heterogeneity and atmospheric dynamics of HMA, ROS characteristics and trends are region-dependent and ROS occurs predominantly over the Indus, Ganges-Brahmaputra, and northwestern basins. In the Indus, ROS representing ∼5% of the annual precipitation and ∼20% of the annual snowmelt, has an increasing trend. This is contrary to the Ganges-Brahmaputra characterized by decreasing ROS trends, where it represents ∼11% of the annual precipitation and ∼60% of the annual snowmelt. In the northwestern basins, ROS has bidirectional trends due to elevation patterns and trends in rainfall, and it constitutes ∼5 to ∼10% of the annual precipitation. Increasing trends in ROS over Indus contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation. Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges-Brahmaputra will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt. These results provide new insights on ROS-driven changes in the hydrological cycle over HMA.This research was supported by funding support from the National Aeronaut-ics and Space Administration High Mountain Asia program (19-HMA19-0012). Computing was supported by the resources at the NASA Center for Climate Simulation.https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022EF00300
Vitri- A Generic Framework for Engineering Decision Support Systems on Heterogeneous Computer Networks
No full textVitri is an object-oriented framework implemented in Java for high-performance distributed computing. Using Vitri, applications can engage in cooperative problem solving by dividing their tasks among heterogeneous clusters of workstations and PCs. Vitri’s features include basic support for distributed computing and communication, as well as visual tools for evaluating run-time performance, and modules for heuristic optimization. It balances loads dynamically using a client-side task pool, allows the addition or removal of servers during a run, and provides fault tolerance transparently for servers and networks. Among its more powerful features are modules for heuristic optimization and decision support tools such as modeling to generate alternatives (MGA). Vitri also provides an asynchronous global-parallel genetic algorithm that is particularly suited for coarse-grained tasks executing on processors with large variations in processor speeds. By using dataflow techniques, in which computations are explicitly based on the availability and forwarding of data, the usual end-of-generation synchronization points are removed from the algorithm. The tools in Vitri are applied to a number of different applications from the civil engineering domain. The results indicate the adaptability of Vitri to various problems and its utility as a tool for managing engineering decision support systems
Global patterns of rain-on-snow and its impacts on runoff from past to future projections
No full textGlobal warming has induced rain-on-snow (ROS) in cold regions leading to significant consequences on ecosystems and socioeconomic development. However, a global analysis of ROS under historical conditions and future projections following different emissions scenarios, essential for management strategies, is currently lacking. Here, we examine ROS changes and their impacts on the water available for runoff, analyzing historical conditions since 1950 and projecting future trends under SSP245 and SSP585 until 2100. By the end of the century, ROS will predominantly occur in high-latitude and altitude regions such as High Mountain Asia, the Alps, Northern Eurasia, and America with rates up to three times higher than those of the historical conditions. Nonetheless, the increasing rainfall will reduce by more than half the contribution of ROS to the water available for runoff despite its rise. Although regions like the Western United States have historically experienced significant ROS, warming will diminish ROS impacts as they become twice lower due to decreasing snowpack and intensified rainfall.computing was supported by the resources at the NASA Center for
Climate Simulation.https://www.nature.com/articles/s41467-025-59855-
- …
