When El Niño Rages: How Satellite Data Can Help Water-Stressed Islands

Abstract

There are more than 2,000 islands across Hawaii and the U.S.-Affiliated Pacific Islands (USAPI), where freshwater resources are heavily dependent upon rainfall. Many of the islands experience dramatic variations in precipitation during the different phases of the El Niño–Southern Oscillation (ENSO). Traditionally, forecasters in the region relied on ENSO climatologies based on spatially limited in situ data to inform their seasonal precipitation outlooks. To address this gap, a unique NOAA/NASA collaborative project updated the ENSO-based rainfall climatology for the Exclusive Economic Zones (EEZs) encompassing Hawaii and the USAPI using NOAA’s PERSIANN Climate Data Record (CDR). The PERSIANN-CDR provides a 30-yr record of global daily precipitation at 0.25° resolution (∼750 km2 near the equator). This project took place over a 10- week NASA DEVELOP National Program term and resulted in a 478-page climatic reference atlas. This atlas is based on a 30-yr period from 1 January 1985 through 31 December 2014 and complements station data by offering an enhanced spatial representation of rainfall averages. Regional and EEZ-specific maps throughout the atlas illustrate the percent departure from average for each season based on the Oceanic Niño Index (ONI) for different ENSO phases. To facilitate intercomparisons across locations, this percentage-based climatology was provided to regional climatologists, forecasters, and outreach experts within the region. Anomalous wet and dry maps for each ENSO phase are used by the regional constituents to better understand precipitation patterns across their regions and to produce more accurate forecasts to inform adaptation, conservation, and mitigation options for drought and f looding events.

Event‐Based Evaluation of the GPM Multisatellite Merged Precipitation Product From 2014 to 2018 Over China: Methods and Results

“…By detecting the properties of precipitating clouds, satellites estimate snapshots of the precipitation rate from infrared (IR) sensors, relatively direct passive microwave (PMW) sensors, or Precipitation Radar (PR) (Kummerow et al., 2015; Sun et al., 2018; Yang et al., 2013). By further combining these multiple satellite sources, quasi‐global gridded products have been developed (e.g., Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), Climate Prediction Center (CPC) Morphing (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Integrated MultisatellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG)), which have been used in a wide range of applications (Brunetti et al., 2018; Luchetti et al., 2016; McCabe et al., 2017; Schlosser & Houser, 2007; Y. P. Zhou et al., 2019).…”

Global Precipitation Trends across Spatial Scales Using Satellite Observations

“…Furthermore, to achieve any semblance of understanding of global historical precipitation trends, spatial aggregation of precipitation is necessary (Fischer et al 2013). In fact, the conversation of global hydrometeorological response to climate change often has taken shape around political concerns or national security foci such as food (Rosenzweig and Parry 1994), water resources, or hazard mitigation (e.g., flood and drought), and are typically spatially confined by | have shown the usefulness of PERSIANN-CDR for climate studies (Miao et al 2015;Luchetti et al 2016;Ashouri et al 2016).…”

The Impact of El Niño and La Nina on Fluctuation of Rice Production in Banten Province

“…Penentuan tahun kejadian iklim ekstrem dalam penelitian ini berdasarkan pada nilai Oceanic Niño Index (ONI) yang merupakan standar indeks yang digunakan oleh NOAA untuk mengidentifikasi kejadian El Niño dan La Nina (Jong et al, 2016;Luchetti et al, 2016;Nabilah et al, 2017). Penelitian lainnya dalam menentukan tahun El Niño dan La Nina menggunakan nilai tekanan udara di Tahiti dan Darwin (SOI) (Santoso, 2016;Taufik et al, 2017;Varotsos et al, 2016).…”