Evaluation and Uncertainty Estimation of the Latest Radar and Satellite Snowfall Products Using SNOTEL Measurements over Mountainous Regions in Western United States

Wen, Yixin; Behrangi, Ali; Lambrigtsen, Bjorn; Kirstetter, Pierre‐Emmanuel

doi:10.3390/rs8110904

Cited by 34 publications

(27 citation statements)

References 36 publications

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“…Most of the IMERG assessment studies were conducted in Asia. It should be noted that several other IMERG assessment studies were conducted in Western countries, for example, [17,18], but they did not perform the daily scale assessment and were therefore excluded from this comparison. To date, the IMERG's daily precipitation was found to have a very good correlation with ground-based precipitation in China [16,38,46].…”

Section: Discussionmentioning

confidence: 99%

“…There have been fewer accuracy assessment studies of the IMERG than those for TMPA products as the IMERG product has been released recently. Some initial assessments of the IMERG have been conducted in China [16], the Netherlands [17], Western United States [18] and the upper Blue Nile basin [19]. Most of the studies found that the product is suitable to be used in hydro-climatic applications in their regions.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of GPM and TRMM Precipitation Products over Singapore

2017

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The evaluation of satellite precipitation products (SPPs) at regional and local scales is essential in improving satellite-based algorithms and sensors, as well as in providing valuable guidance when choosing alternative precipitation data for the local community. The Tropical Rainfall Measuring Mission (TRMM) has made significant contributions to the development of various SPPs since its launch in 1997. The Global Precipitation Measurement (GPM) mission launched in 2014 and is expected to continue the success of TRMM. During the transition from the TRMM era to the GPM era, it is necessary to assess GPM products and make comparisons with TRMM products in different regions to achieve a global view of the performance of GPM products. To this end, this study aims to assess the capability of the latest Integrated Multi-satellite Retrievals for GPM (IMERG) and two TRMM Multisatellite Precipitation Analysis (TMPA) products (TMPA 3B42 and TMPA 3B42RT) in estimating precipitation over Singapore that represents a typical tropical region. The evaluation was conducted at daily, monthly, seasonal and annual scales from 1 April 2014 to 31 January 2016. The capability of SPPs in detecting rainy/non-rainy days and different precipitation classes was also evaluated. The findings showed that: (1) all SPPs correlated well with measurements from gauges at the monthly scale, but moderately at the daily scale; (2) SPPs performed better in the northeast monsoon season (1 December-15 March) than in the inter-monsoon 1 ((3) IMERG had better performance in the characterization of spatial precipitation variability and precipitation detection capability compared to the TMPA products; (4) for the daily precipitation estimates, IMERG had the lowest systematic bias, followed by 3B42 and 3B42RT; and (5) most of the SPPs overestimated moderate precipitation events (1-20 mm/day), while underestimating light (0.1-1 mm/day) and heavy (>20 mm/day) precipitation events. Overall, IMERG is superior but with only slight improvement compared to the TMPA products over Singapore. This study is one of the earliest assessments of IMERG and a comparison of it with TMPA products in Singapore. Our findings were compared with existing studies conducted in other regions, and some limitations of the IMERG and TMPA products in this tropical region were identified and discussed. This study provides an added value to the understanding of the global performance of the IMERG product.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of GPM and TRMM Precipitation Products over Singapore

2017

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“…In mountainous regions, precipitation is extremely variable and there are changes in rainfall distribution over short distances. Additionally, higher altitudes mean that a large proportion of precipitation is in the solid phase, which is a challenge not only for satellites but also for rain gauges and weather radars [52]. A way to evaluate the performance of IMERG-F is by comparing it with the uncalibrated version of the product.…”

Section: Alps and Adriatic Seamentioning

confidence: 99%

Assessment of IMERG Precipitation Estimates over Europe

et al. 2019

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This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data.

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“…While there have been several studies focused on evaluation of precipitation products in the mountains, the general consensus from the literature is that larger underestimations are incurred with increasing altitude for complex terrain in both warm and cold climates (Henn et al, 2018;Hong et al, 2007Hong et al, , 2004Wen et al, 2016). Global precipitation products have also been shown to disagree the most during winter in both event magnitude and the number of precipitation events (Behrangi, Andreadis, et al, 2014;Tian & Peters-Lidard, 2010;Maggioni et al, 2017), and at high elevation (Henn et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Using the Airborne Snow Observatory to Assess Remotely Sensed Snowfall Products in the California Sierra Nevada

Behrangi

Bormann

Painter

2018

Water Resources Research

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The Airborne Snow Observatory (ASO) performed two acquisitions over two mountainous basins in California on 29 January and 3 March 2017, encompassing two atmospheric river events that brought heavy snowfall to the area. These surveys produced high‐resolution (50 m) maps of snow depth and snow water equivalent (SWE) that were used to estimate monthly areal snowfall accumulation. Comparison of ASO snow accumulation with point measurements showed that the ASO estimates ranged from −10 to +16% relative bias across three sites, which is likely inflated by the disagreement in areal representation of the quantities from the actual errors in these products. The aggregated SWE accumulations from ASO are then used to evaluate a suite of in situ based and remote sensing precipitation products. During the study period, Parameter‐Elevation Regressions on Independent Slopes Model (PRISM) and Mountain Mapper estimates had relative bias <10% compared with ASO‐based estimates of snow accumulation, but satellite and radar products largely underestimate snowfall accumulation compared to ASO (up to 50%). Despite their underestimation, satellite and radar products show correlation coefficients >0.8 with ASO snow accumulation over the selected grids at the monthly scale. Finally, we leveraged the fine‐scale sampling of the spatially complete ASO products to show that by moving from 100 m to 2 km spatial scales, the perceived bias errors SWE at point locations increased by an order of magnitude, displaying a nonlinear relationship. The study demonstrates that ASO acquisitions in cold months can bring a new and effective approach to spatial evaluation of precipitation products.

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Evaluation and Uncertainty Estimation of the Latest Radar and Satellite Snowfall Products Using SNOTEL Measurements over Mountainous Regions in Western United States

Cited by 34 publications

References 36 publications

Assessment of GPM and TRMM Precipitation Products over Singapore

Assessment of GPM and TRMM Precipitation Products over Singapore

Assessment of IMERG Precipitation Estimates over Europe

Using the Airborne Snow Observatory to Assess Remotely Sensed Snowfall Products in the California Sierra Nevada

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