Simulating block-scale flood inundation and streamflow using the WRF-Hydro model in the New York City metropolitan area.

This study assesses the performance of the Weather Research and Forecasting-Hydrological modeling system (WRF-Hydro) in the simulation of street-scale flood inundation. The case study is the Hackensack River Watershed in New Jersey, US, which is part of the operational Stevens Flood Advisory System (SFAS), a one-way coupled hydrodynamic-hydrologic system that currently uses the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) to simulate streamflow. The performance of the 50-m gridded WRF-Hydro model was assessed for potential integration into the operational SFAS system.

A systematic review of natural language processing applications for hydrometeorological hazards assessment.

Natural language processing (NLP) is a promising tool for collecting data that are usually hard to obtain during extreme weather, like community response and infrastructure performance. Patterns and trends in abundant data sources such as weather reports, news articles, and social media may provide insights into potential impacts and early warnings of impending disasters. This paper reviews the peer-reviewed studies (journals and conference proceedings) that used NLP to assess extreme weather events, focusing on heavy rainfall events.

On the crucial role of atmospheric rivers in the two major Weddell Polynya events in 1973 and 2017 in Antarctica.

This study reports the occurrence of intense atmospheric rivers (ARs) during the two large Weddell Polynya events in November 1973 and September 2017 and investigates their role in the opening events via their enhancement of sea ice melt. Few days before the polynya openings, persistent ARs maintained a sustained positive total energy flux at the surface, resulting in sea ice thinning and a decline in sea ice concentration in the Maud Rise region. The ARs were associated with anomalously high amounts of total precipitable water and cloud liquid water content exceeding 3 SDs above the climatological mean.

Analysis of bloom conditions in fall 2013 in the Strait of Hormuz using satellite observations and model simulations.

In this study an algal bloom event in fall 2013 in the Strait of Hormuz was thoroughly investigated using satellite remote sensing and hydrodynamic modeling. The motivation of this study is to deduce ambient conditions prior to and during the bloom outbreak and understand its trigger. Bloom tracking was achieved by sequential MODIS imagery and numerical simulations.

Analysis of the spatio-temporal variability of seawater quality in the southeastern Arabian Gulf.

In this study, seawater quality measurements, including salinity, sea surface temperature (SST), chlorophyll-a (Chl-a), Secchi disk depth (SDD), pH, and dissolved oxygen (DO), were made from June 2013 to November 2014 at 52 stations in the southeastern Arabian Gulf. Significant variability was noticed for all collected parameters. Salinity showed a decreasing trend, and Chl-a, DO, pH, and SDD demonstrated increasing trends from shallow onshore stations to deep offshore ones, which could be attributed to variations of ocean circulation and meteorological conditions from onshore to offshore waters, and the likely effects of desalination plants along the coast.

Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters--a case study in the Arabian Gulf.

Remote sensing provides an effective tool for timely oil pollution response. In this paper, the spectral signature in the optical and infrared domains of oil slicks observed in shallow coastal waters of the Arabian Gulf was investigated with MODIS, MERIS, and Landsat data. Images of the Floating Algae Index (FAI) and estimates of sea currents from hydrodynamic models supported the multi-sensor oil tracking technique.