FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4220988511> ?p ?o ?g. }

• W4220988511 abstract "Abstract Accurate estimation of the spatio‐temporal distribution of snow water equivalent is essential given its global importance for understanding climate dynamics and climate change, and as a source of fresh water. Here, we explore the potential of using the Long Short‐Term Memory (LSTM) network for continental and regional scale modeling of daily snow accumulation and melt dynamics at 4‐km pixel resolution across the conterminous US (CONUS). To reduce training costs (data are available for ∼0.31 million snowy pixels), we combine spatial sampling with stagewise model development, whereby the network is first pretrained across the entire CONUS and then subjected to regional fine‐tuning. Accordingly, model evaluation is focused on out‐of‐sample predictive performance across space (analogous to the prediction in ungauged basins problem). We find that, given identical inputs (precipitation, temperature, and elevation), a single CONUS‐wide LSTM provides significantly better spatio‐temporal generalization than a regionally calibrated version of the physical‐conceptual temperature‐index‐based SNOW17 model. Adding more meteorological information (dew point temperature, vapor pressure deficit, longwave radiation, and shortwave radiation) further improves model performance, while rendering redundant the local information provided by elevation. Overall, the LSTM exhibits better transferability than SNOW17 to locations that were not included in the training data set, reinforcing the advantages of structure learning over parameter learning. Our results suggest that an LSTM‐based approach could be used to develop continental/global‐scale systems for modeling snow dynamics." @default.
• W4220988511 created "2022-04-03" @default.
• W4220988511 creator A5003155510 @default.
• W4220988511 creator A5010241378 @default.
• W4220988511 creator A5044623451 @default.
• W4220988511 creator A5082540817 @default.
• W4220988511 date "2022-03-01" @default.
• W4220988511 modified "2023-10-18" @default.
• W4220988511 title "Exploring the Potential of Long Short‐Term Memory Networks for Improving Understanding of Continental‐ and Regional‐Scale Snowpack Dynamics" @default.
• W4220988511 cites W105912250 @default.
• W4220988511 cites W132837105 @default.
• W4220988511 cites W1481171371 @default.
• W4220988511 cites W1484996118 @default.
• W4220988511 cites W1508156815 @default.
• W4220988511 cites W1537396274 @default.
• W4220988511 cites W1539229456 @default.
• W4220988511 cites W1560807794 @default.
• W4220988511 cites W1788360020 @default.
• W4220988511 cites W1806891645 @default.
• W4220988511 cites W1838747416 @default.
• W4220988511 cites W1851420719 @default.
• W4220988511 cites W1972423686 @default.
• W4220988511 cites W1987951529 @default.
• W4220988511 cites W1988503945 @default.
• W4220988511 cites W1988753456 @default.
• W4220988511 cites W1994616231 @default.
• W4220988511 cites W2025910073 @default.
• W4220988511 cites W2027999255 @default.
• W4220988511 cites W2033904036 @default.
• W4220988511 cites W2048069199 @default.
• W4220988511 cites W2051833014 @default.
• W4220988511 cites W2053082698 @default.
• W4220988511 cites W2064675550 @default.
• W4220988511 cites W2079797871 @default.
• W4220988511 cites W2084170744 @default.
• W4220988511 cites W2084241734 @default.
• W4220988511 cites W2086038705 @default.
• W4220988511 cites W2103497845 @default.
• W4220988511 cites W2111645678 @default.
• W4220988511 cites W2116876650 @default.
• W4220988511 cites W2117396433 @default.
• W4220988511 cites W2118092919 @default.
• W4220988511 cites W2121345872 @default.
• W4220988511 cites W2122389133 @default.
• W4220988511 cites W2127062432 @default.
• W4220988511 cites W2133837084 @default.
• W4220988511 cites W2137597204 @default.
• W4220988511 cites W2138763184 @default.
• W4220988511 cites W2145563193 @default.
• W4220988511 cites W2147800946 @default.
• W4220988511 cites W2150013545 @default.
• W4220988511 cites W2160241847 @default.
• W4220988511 cites W2160741281 @default.
• W4220988511 cites W2165201237 @default.
• W4220988511 cites W2166533771 @default.
• W4220988511 cites W2171761316 @default.
• W4220988511 cites W2177229967 @default.
• W4220988511 cites W2180106900 @default.
• W4220988511 cites W2339994680 @default.
• W4220988511 cites W2344937825 @default.
• W4220988511 cites W2393014624 @default.
• W4220988511 cites W2401580071 @default.
• W4220988511 cites W2507570964 @default.
• W4220988511 cites W2593494947 @default.
• W4220988511 cites W2618013857 @default.
• W4220988511 cites W2621194191 @default.
• W4220988511 cites W2756918570 @default.
• W4220988511 cites W2762486656 @default.
• W4220988511 cites W2774855798 @default.
• W4220988511 cites W2800819102 @default.
• W4220988511 cites W2810735212 @default.
• W4220988511 cites W2885109349 @default.
• W4220988511 cites W2895988889 @default.
• W4220988511 cites W2896198709 @default.
• W4220988511 cites W2898661956 @default.
• W4220988511 cites W2898962279 @default.
• W4220988511 cites W2904678447 @default.
• W4220988511 cites W2913323966 @default.
• W4220988511 cites W2939407418 @default.
• W4220988511 cites W2969309273 @default.
• W4220988511 cites W2969834763 @default.
• W4220988511 cites W2969964489 @default.
• W4220988511 cites W2989857225 @default.
• W4220988511 cites W2991471696 @default.
• W4220988511 cites W2994898777 @default.
• W4220988511 cites W2995149074 @default.
• W4220988511 cites W2995501491 @default.
• W4220988511 cites W2997258543 @default.
• W4220988511 cites W2998736501 @default.
• W4220988511 cites W3008633406 @default.
• W4220988511 cites W3009131884 @default.
• W4220988511 cites W3013563811 @default.
• W4220988511 cites W3016401366 @default.
• W4220988511 cites W3017283281 @default.
• W4220988511 cites W3034385753 @default.
• W4220988511 cites W3048430933 @default.
• W4220988511 cites W3083897301 @default.
• W4220988511 cites W3088538572 @default.
• W4220988511 cites W3092026988 @default.
• W4220988511 cites W3094112595 @default.

• next