"B. Pérez Galdós", ed. D. M. Rogers (Book Review)

Rodgers, Eamonn

doi:10.3828/bhs.53.2.161

Cited by 2 publications

(2 citation statements)

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“…datasets 18, 26, 39-44), surface-groundwater interactions (e.g. datasets [63][64][65][66][67][68], nitrogen cycling and export to the river (e.g. datasets 15, 20, 21, 27, 31-32, 52, 56), the impact of weathering and other processes on river water composition (e.g.…”

Section: Scientific Impact Of Er Datasetsmentioning

confidence: 99%

The Colorado East River Community Observatory Data Collection

Varadharajan

Kakalia

Alper

et al. 2021

Preprint

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The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow-dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behavior. The ER has both long-term and spatiallyextensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross-disciplinary process-based investigations and modeling of watershed behavior. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value-added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within five years of collection, these datasets have revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over seventy ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.

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Section: Scientific Impact Of Er Datasetsmentioning

confidence: 99%

The Colorado East River Community Observatory Data Collection

Varadharajan

Kakalia

Alper

et al. 2021

Preprint

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“…The retrieval performance can be estimated from the covariance matrix which is the Hessian of (1) (Rodgers 1976)…”

Section: Linear Error Analysismentioning

confidence: 99%

Comparison of simulated radiances, Jacobians and linear error analysis for the Microwave Humidity Sounder and the Advanced Microwave Sounding Unit‐B

Kleespies

Watts

2006

Quart J Royal Meteoro Soc

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SUMMARYThe Microwave Humidity Sounder (MHS) has scan characteristics similar to those of the Advanced Microwave Sounding Unit-B (AMSU-B). However, its radiometric characteristics are somewhat different, for two channels in particular. Both of these channels have more attenuation with the MHS than the AMSU-B. Linear error analysis suggests that the improved noise characteristics of the MHS will let it have slightly lower errors than the AMSU-B.

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"B. Pérez Galdós", ed. D. M. Rogers (Book Review)

Cited by 2 publications

References 0 publications

The Colorado East River Community Observatory Data Collection

The Colorado East River Community Observatory Data Collection

Comparison of simulated radiances, Jacobians and linear error analysis for the Microwave Humidity Sounder and the Advanced Microwave Sounding Unit‐B

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