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Scott Curtis   Dr.  University Educator/Researcher 
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Scott Curtis published an article in April 2019.
Top co-authors
Munshi Rahman

3 shared publications

Department of Geography and Anthropology, UW-Eau Claire, Phillips Science Hall 257, 101 Roosevelt Ave., Eau Claire, WI 54702, USA

Jun Matsumoto

1 shared publications

Mohin Patel

1 shared publications

Department of Meteorology and Climate Science, San Jose State University, One Washington Square, San Jose, CA 95192, USA

Ronald H. Isaac

1 shared publications

Publication Record
Distribution of Articles published per year 
(1995 - 2019)
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Publications See all
Article 0 Reads 0 Citations Means and Long-Term Trends of Global Coastal Zone Precipitation Scott Curtis Published: 01 April 2019
Scientific Reports, doi: 10.1038/s41598-019-41878-8
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Precipitation in the coastal zone is important to the socio-economic and ecological well-being of the world. Meteorologically, precipitation is generated by unique mechanisms at the land-sea interface, which is why coastal zone precipitation is not well resolved by global climate models. Yet, to date, much more effort has been placed in analyzing global precipitation over the oceans and land. In this study, global coastal zone precipitation is quantified by selecting Global Precipitation Climatology Centre V2018 0.5° grid cells in 50 km zones from the shoreline into the interior. The transition from maritime to continental precipitation regimes is revealed in the long-term (1931–2010) average, as there is a pronounced coast-to-interior decline in rainfall from approximately 911.5 mm yr−1 within 50 km of the coast to 727.2 mm yr−1 from 100 to 150 km away from the coast. Globally, coastal zone precipitation peaks in boreal summer, extending into fall for precipitation at the coastline. Dividing the long-term record into early and late 40-year periods reveals an increasing trend in precipitation in the coastal zone, with the interior increasing faster than at the coastline. Averaging over 30-year climate normals from 1931–60 to 1981–2010 further confirms this result. A seasonal analysis reveals that the upward trends, and discrepancy between the coast and inland are maximized in the austral summer season. Interestingly, from May to September there is a declining trend in rainfall at the coastline, whereas the interior only shows minimal declines in August and September. Potential forcing mechanisms that could favor a wetter interior coastal zone include changes in the sea breeze circulation, urban heat island effect, or precipitation content associated with synoptic systems or monsoonal circulations.
Article 0 Reads 1 Citation Weather on the Go: An Assessment of Smartphone Mobile Weather Application Use among College Students Minh D. Phan, Burrell E. Montz, Scott Curtis, Thomas M. Rick... Published: 01 November 2018
Bulletin of the American Meteorological Society, doi: 10.1175/bams-d-18-0020.1
DOI See at publisher website
Article 0 Reads 0 Citations Getting More out of Storm Surge Forecasts: Emergency Support Personnel Needs in North Carolina Robert Munroe, Burrell Montz, Scott Curtis Published: 01 October 2018
Weather, Climate, and Society, doi: 10.1175/wcas-d-17-0074.1
DOI See at publisher website
Article 1 Read 1 Citation A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin Scott Curtis, Thomas Crawford, Munshi Rahman, Bimal Paul, M.... Published: 29 September 2018
Water, doi: 10.3390/w10101359
DOI See at publisher website ABS Show/hide abstract
Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.
CONFERENCE-ARTICLE 20 Reads 0 Citations Monsoon Dynamics in the Ganges-Brahmaputra-Meghna Basin Scott Curtis, Thomas Crawford, Munshi Khaledur Rahman, Bimal... Published: 08 November 2017
Proceedings of First International Electronic Conference on the Hydrological Cycle, doi: 10.3390/CHyCle-2017-04865
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A recently funded US National Science Foundation project seeks to investigate monsoon variability within the Ganges-Brahmaputra-Meghna (GBM) river basin as a potential predictor for annual shoreline erosion rates in the lower coastal delta region. Many previous studies have examined the interannual variability of South Asian precipitation either within political boundaries or across large spans of latitudes and longitudes, but few have taken a more hydrologic approach by analyzing the atmospheric-oceanic forcings that lead to precipitation falling only within the GBM basin.  The temporal climate patterns would likely be different from previous studies and are hypothesized to have a more direct effect on outlet discharge and erosion rates. In the present study, mean monsoon precipitation (June-July-August-September) for the 2309 0.25° grid boxes of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) was extracted using geospatial methods. A Principal Component (PC) analysis was performed over the period 1983 to 2015. The first PC explains 88.7% of the variance and resembles climatology with the center of action over Bangladesh.  The eigenvector shows a downward trend consistent with studies reporting a recent decline in monsoon rainfall. The second PC explains 2.9% of the variance and concentrates rainfall in the western portion of the basin. The 2nd component has greater temporal variability than the 1st component and an apparent decadal cycle. An analysis of global precipitation indicates that the rainfall patterns obtained within the GBM are localized. Surface and upper-air atmospheric height fields suggest the 2nd PC pattern is forced by a Rossby wave train stemming from the North Atlantic.

Article 0 Reads 1 Citation The Madden-Julian Oscillation: A Tool for Regional Seasonal Precipitation Outlooks? Scott Curtis Published: 20 September 2017
Atmosphere, doi: 10.3390/atmos8090180
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The Madden-Julian Oscillation (MJO) is an important intraseasonal climate signal which circles the global tropics, but also impacts extratropical weather regimes. Few studies have investigated whether the MJO is a source of regional seasonal climate predictability. The present objective is to determine the extent to which the season and phase (geographic location) of MJO contribute to the frequency of global rainfall anomalies in ensuing seasons. Indices of June-July-August and December-January-February MJO activity for each phase and the El Niño/Southern Oscillation (ENSO) were correlated to three-month averages of rainfall up to a six-month lead time. Field significance was calculated and patterns of the relationships were described. In general, MJO shows some skill in regional seasonal precipitation prediction, but to a lesser extent than ENSO. However, the presence of MJO in the western Indian Ocean and near the date line did reveal a persistent and significant relationship with regional seasonal rainfall, especially over Northern Hemisphere land areas.