No abstract

As the limitation of rainfall collection by ground measurement has been widely recognized, satellite-based rainfall estimate is a promising high-resolution alternative in both time and space. This study is aimed at exploring the capacity of the satellite-based rainfall product Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), including 3B42V7 research data and its real-time 3B42RT data, by comparing them against data from 29 ground observation stations over the lower part of the Red–Thai Binh River Basin from March 2000 to December 2016. Various statistical metrics were applied to evaluate the TMPA products. The results showed that both 3B42V7 and 3B42RT had weak relationships with daily observations, but 3B42V7 data had strong agreement on the monthly scale compared to 3B42RT. Seasonal analysis showed that 3B42V7 and 3B42RT underestimated rainfall during the dry season and overestimated rainfall during the wet season, with high bias observed for 3B42RT. In addition, detection metrics demonstrated that TMPA products could detect rainfall events in the wet season much better than in the dry season. When rainfall intensity was analyzed, both 3B42V7 and 3B42RT overestimated the no rainfall event during the dry season but underestimated these events during the wet season. Finally, based on the moderate correlation between climatology–topography characteristics and correction factors of linear-scaling (LS) approach, a set of multiple linear models was developed to reduce the error between TMPA products and the observations. The results showed that climatology–topography-based linear-scaling approach (CTLS) significantly reduced the percentage bias (PBIAS) score and moderately improved the Nash–Sutcliffe efficiency (NSE) score. The finding of this paper gives an overview of the capacity of TMPA products in the lower part of the Red–Thai Binh River Basin regarding water resource applications and provides a simple bias correction that can be used to improve the correctness of TMPA products.

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.

Typhoons are known for causing heavy precipitation, very strong winds, and storm surges. With climate change, the occurrence, strength, and duration of typhoons are changing. Daily, weekly, and monthly precipitation from in situ stations from the NOAA Global Historical Climatological Network (GHCN) were compared in the Western North Pacific from 2000 to 2018 against two widely used datasets: NASA’s TRMM TMPA and PERSIANN-CDR. Additionally, precipitation levels during twenty-five typhoons were compared using precipitation estimates. There have been reductions in the average number of typhoons per year from 1959 to present and by month during the months of August, September, and October. Satellite-derived precipitation estimates from PERSIANN and TRMM TMPA explained approximately 50% of the variation in weekly cumulative precipitation and approximately 72% of the variation in monthly cumulative precipitation during the study period (March 2000–December 2018) when using all available stations. When analysis was completed using only stations close to the best track for the entire duration of a typhoon, 62% of the variation was explained, which is comparable to the weekly and monthly cumulative comparisons. However, most of the stations available and with sufficient data were not located in the tracks of the typhoons. It is of utmost importance to better understand typhoon events by utilizing precipitation data from satellite remote sensing in the Western North Pacific.