Validation of ocean surface winds from the OCEANSAT-2 scatterometer using triple collocation

Chakraborty, Abhisek; Kumar, Raj; Stoffelen, Ad

doi:10.1080/2150704x.2012.693967

Cited by 39 publications

(22 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Triple collocation is an alternative method for assessing the quality of a product without assuming a reference and the random errors are computed against an unknown truth [30][31][32][33][34][35][36]. This technique has been widely used in precipitation studies, although some studies showed that TCA is highly sensitive to its input configurations, including scale differences, time span under observation, and measurement triplets [37][38][39].…”

Section: Performance Analysismentioning

confidence: 99%

Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans

Khan¹,

Maggioni²

2019

Remote Sensing

View full text Add to dashboard Cite

The performance of Level-3 gridded Global Precipitation Mission (GPM)-based precipitation products (IMERG, Integrated Multi-satellite Retrievals for GPM) is assessed against two references over oceans: the OceanRAIN dataset, derived from oceanic shipboard disdrometers, and a satellite-based radar product (the Level-3 Dual-frequency Precipitation Radar, 3DPRD). Daily IMERG products (early, late, final) and microwave-only (MW) and Infrared-only (IR) precipitation components are evaluated at four different spatial resolutions (0.5 • , 1 • , 2 • , and 3 • ) during a 3-year study period (March 2014-February 2017). Their performance is assessed based on both categorical and continuous performance metrics, including correlation coefficient, probability of detection, success ratio, bias, and root mean square error (RMSE). A triple collocation analysis (TCA) is also presented to further investigate the performance of these satellite-based products. Overall, the IMERG products show an underestimation with respect to OceanRAIN. Rain events in OceanRAIN are correctly detected by all IMERG products~80% of the times. IR estimates show relatively large errors and low correlations with OceanRAIN compared to the other products. On the other hand, the MW component performs better than other products in terms of both categorical and continuous statistics. TCA reveals that 3DPRD performs consistently better than OceanRAIN in terms of RMSE and coefficient of determination at all spatial resolutions. This work is part of a larger effort to validate GPM products over nontraditional regions such as oceans.

show abstract

Section: Performance Analysismentioning

confidence: 99%

Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans

Khan¹,

Maggioni²

2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Because the production of wind retrievals from QuikSCAT ended on 19 November 2009, ocean wind-vector products now rely on the more recent microwave scatterometers, including Satellite for the Ocean-2 (OceanSat-2) Scanning Scatterometer (OSCAT), Ku band (Chakraborty et al 2013), ASCAT-A and -B C-band (Figa-Saldaña et al 2002), and the WindSat polarimetric radiometer (Gaiser et al 2004). In addition, the International Space Station (ISS) Rapid Scatterometer instrument, which is essentially a replica of the QuikSCAT instrument, is currently flying aboard the ISS to measure the earth's ocean surface wind speed and direction.…”

Section: Future Workmentioning

confidence: 99%

The Impact of Hurricane Force Wind Fields on the North Pacific Ocean Environment

Yildiz

Robinson

2015

Weather and Forecasting

View full text Add to dashboard Cite

This study analyzes QuikSCAT surface wind data over the North Pacific Ocean to document the distribution of captured fetches in extratropical cyclones that produced hurricane force (HF) wind fields from January 2003 through May 2008. A case study is presented to introduce the datasets, which include surface wind analyses from the Global Forecast System (GFS) Global Data Assimilation System (GDAS), and wave hindcasts from the third-generation wave model (WAVEWATCH III; hereafter, WW3), in addition to the QuikSCAT surface wind data. The analysis shows significant interannual variability in the location of the captured fetches as documented by QuikSCAT, including a shift in the distribution of captured fetches associated with ENSO. GDAS surface winds over the ocean are consistently underanalyzed when compared to QuikSCAT surface winds, despite the fact that satellite observations of ocean surface winds are assimilated. When the WW3 hindcasts associated with HF cyclones are compared with buoy observations over the eastern and central North Pacific Ocean, the wave model significantly underestimates the large-swell events.

show abstract

“…Comprehensive use of wind information from four scatterometers, including ASCAT-A/B, OSCAT, and HY2-SCAT, will shorten observation intervals and fi ll data gaps (Zhang et al, 2006a ). Validation studies of scatterometer winds using in situ measurements or NWP model outputs have been conducted, such as a comparison of Oceansat-2 scatterometer wind products with buoy observations (Sudha et al, 2013) and their validation with winds from ECMWF, using triple collocation (Chakraborty et al, 2013). Advanced Scatterometer (ASCAT) and SeaWinds winds were assessed by similar methods (Vogelzang et al, 2011), and the fi rst 6 months of HY2-SCAT winds were compared with in situ data .…”

Section: Introductionmentioning

confidence: 99%

Assessment of wind products obtained from multiple microwave scatterometers over the China Seas

Wang

Zhao

2015

Chin. J. Ocean. Limnol.

View full text Add to dashboard Cite

Sea surface winds (SSWs) are vital to many meteorological and oceanographic applications, especially for regional study of short-range forecasting and Numerical Weather Prediction (NWP) assimilation. Spaceborne scatterometers can provide global ocean surface vector wind products at high spatial resolution. However, given the limited spatial coverage and revisit time for an individual sensor, it is valuable to study improvements of multiple microwave scatterometer observations, including the advanced scatterometer onboard parallel satellites MetOp-A (ASCAT-A) and MetOp-B (ASCAT-B) and microwave scatterometers aboard Oceansat-2 (OSCAT) and HY-2A (HY2-SCAT). These four scatterometer-derived wind products over the China Seas (0°-40°N, 105°-135°E) were evaluated in terms of spatial coverage, revisit time, bias of wind speed and direction, after comparison with ERA-Interim forecast winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) and spectral analysis of wind components along the satellite track. The results show that spatial coverage of wind data observed by combination of the four sensors over the China Seas is about 92.8% for a 12-h interval at 12:00 and 90.7% at 24:00, respectively. The analysis of revisit time shows that two periods, from 5:30-8:30 UTC and 17:00-21:00 UTC each day, had no observations in the study area. Wind data observed by the four sensors along satellite orbits in one month were compared with ERA-Interim data, indicating that bias of both wind speed and direction varies with wind speed, especially for speeds less than 7 m/s. The bias depends on characteristics of each satellite sensor and its retrieval algorithm for wind vector data. All these results will be important as guidance in choosing the most suitable wind product for applications and for constructing blended SSW products.

show abstract

Validation of ocean surface winds from the OCEANSAT-2 scatterometer using triple collocation

Cited by 39 publications

References 14 publications

Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans

Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans

The Impact of Hurricane Force Wind Fields on the North Pacific Ocean Environment

Assessment of wind products obtained from multiple microwave scatterometers over the China Seas

Contact Info

Product

Resources

About