Bin Yong

Hydrologic evaluation of Multisatellite Precipitation Analysis standard precipitation products in basins beyond its inclined latitude band: A case study in Laohahe basin, China

[1] Two standard Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products, 3B42RT and 3B42V6, were quantitatively evaluated in the Laohahe basin, China, located within the TMPA product latitude band (50°NS) but beyond the inclined TRMM satellite latitude band (36°NS). In general, direct comparison of TMPA rainfall estimates to collocated rain gauges from 2000 to 2005 show that the spatial and temporal rainfall characteristics over the region are well captured by the 3B42V6 estimates. Except for a few months with underestimation, the 3B42RT estimates show unrealistic overestimation nearly year round, which needs to be resolved in future upgrades to the real-time estimation algorithm. Both model-parameter error analysis and hydrologic application suggest that the three-layer Variable Infiltration Capacity (VIC-3L) model cannot tolerate the nonphysical overestimation behavior of 3B42RT through the hydrologic integration processes, and as such the 3B42RT data have almost no hydrologic utility, even at the monthly scale. In contrast, the 3B42V6 data can produce much better hydrologic predictions with reduced error propagation from input to streamflow at both the daily and monthly scales. This study also found the error structures of both RT and V6 have a significant geo-topography-dependent distribution pattern, closely associated with latitude and elevation bands, suggesting current limitations with TRMM-era algorithms at high latitudes and high elevations in general. Looking into the future Global Precipitation Measurement (GPM) era, the Geostationary Infrared (GEO-IR) estimates still have a long-term role in filling the inevitable gaps in microwave coverage, as well as in enabling sub-hourly estimates at typical 4-km grid scales. Thus, this study affirms the call for a real-time systematic bias removal in future upgrades to the IR-based RT algorithm using a simple scaling factor. This correction is based on MW-based monthly rainfall climatologies applied to the combined monthly satellite-gauge research products.

Global View Of Real-Time Trmm Multisatellite Precipitation Analysis: Implications For Its Successor Global Precipitation Measurement Mission

AbstractAccurate estimation of high-resolution precipitation on the global scale is extremely challenging. The operational Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has created over 16 years of high-resolution quantitative precipitation estimation (QPE), and has built the foundation for improved measurements in the upcoming Global Precipitation Measurement (GPM) mission. TMPA is intended to produce the “best effort” estimates of quasi-global precipitation from almost all available satelliteborne precipitation-related sensors by consistently calibrating them with the high-quality measurements from the core instrument platform aboard TRMM. Recently, the TMPA system has been upgraded to version 7 to take advantage of newer and better sources of satellite inputs than version 6, and has attracted a large user base. A key product from TMPA is the near-real-time product (TMPA-RT), as its timeliness is particularly appealing for time-sensitive applications such as flo...

Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA 3B42V7?

AbstractThe goal of this study is to quantitatively intercompare the standard products of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, the Global Precipitation Measurement (GPM) mission Integrated Multisatellite Retrievals for GPM (IMERG), with a dense gauge network over the midlatitude Ganjiang River basin in southeast China. In general, direct comparisons of the TMPA 3B42V7, 3B42RT, and GPM Day-1 IMERG estimates with gauge observations over an extended period of the rainy season (from May through September 2014) at 0.25° and daily resolutions show that all three products demonstrate similarly acceptable (~0.63) and high (0.87) correlation at grid and basin scales, respectively, although 3B42RT shows much higher overestimation. Both of the post-real-time corrections effectively reduce the bias of Day-1 IMERG and 3B42V7 to single digits of underestimation from 20+% overestimation of 3B42RT. The Taylor diagram shows that Day-1 IMERG and 3B42...

Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins

An innovative flood-prediction framework is developed using Tropical Rainfall Measuring Mission precipitation forcing and a proxy for river discharge from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) onboard the National Aeronautics and Space Administrations Aqua satellite. The AMSR-E-detected water surface signal was correlated with in situ measurements of streamflow in the Okavango Basin in Southern Africa as indicated by a Pearson correlation coefficient of 0.90. A distributed hydrologic model, with structural data sets derived from remote-sensing data, was calibrated to yield simulations matching the flood frequencies from the AMSR-E-detected water surface signal. Model performance during a validation period yielded a Nash-Sutcliffe efficiency of 0.84. We concluded that remote-sensing data from microwave sensors could be used to supplement stream gauges in large sparsely gauged or ungauged basins to calibrate hydrologic models. Given the global availability of all required data sets, this approach can be potentially expanded to improve flood monitoring and prediction in sparsely gauged basins throughout the world.

Similarity and Error Intercomparison of the GPM and Its Predecessor-TRMM Multisatellite Precipitation Analysis Using the Best Available Hourly Gauge Network over the Tibetan Plateau

The performance of Day-1 Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) and its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 Version 7 (3B42V7), was cross-evaluated using data from the best-available hourly gauge network over the Tibetan Plateau (TP). Analyses of three-hourly rainfall estimates in the warm season of 2014 reveal that IMERG shows appreciably better correlations and lower errors than 3B42V7, though with very similar spatial patterns for all assessment indicators. IMERG also appears to detect light rainfall better than 3B42V7. However, IMERG shows slightly lower POD than 3B42V7 for elevations above 4200 m. Both IMERG and 3B42V7 successfully capture the northward dynamic life cycle of the Indian monsoon reasonably well over the TP. In particular, the relatively light rain from early and end Indian monsoon moisture surge events often fails to be captured by the sparsely-distributed gauges. In spite of limited snowfall field observations, IMERG shows the potential of detecting solid precipitation, which cannot be retrieved from the 3B42V7 products.

Hyperspectral Band Selection Using Improved Firefly Algorithm

An improved firefly algorithm (FA)-based band selection method is proposed for hyperspectral dimensionality reduction (DR). In this letter, DR is formulated as an optimization problem that searches a small number of bands from a hyperspectral data set, and a feature subset search algorithm using the FA is developed. To avoid employing an actual classifier within the band searching process to greatly reduce computational cost, criterion functions that can gauge class separability are preferred; specifically, the minimum estimated abundance covariance and Jeffreys-Matusita distances are employed. The proposed band selection technique is compared with an FA-based method that actually employs a classifier, the well-known sequential forward selection, and particle swarm optimization algorithms. Experimental results show that the proposed algorithm outperforms others, providing an effective option for DR.

Error analysis of multi-satellite precipitation estimates with an independent raingauge observation network over a medium-sized humid basin

ABSTRACT This study focuses on quantifying the error characteristics of four widely utilized satellite precipitation products (i.e. TMPA 3B42RTV7, TMPA 3B42V7, CMORPH and PERSIANN-CDR) for a five-year period (2005–2009) using an independent raingauge network over the upper-middle Huai River basin in central-eastern China. Assessment results show that CMORPH generally exhibits the best performance with slight underestimation, while 3B42RTV7 has the worst performance with large positive biases. Additionally, 3B42V7 and PERSIANN-CDR tend to have an approximate accuracy. The monthly gauge adjustment applied to 3B42V7 and PERSIANN-CDR significantly reduces their systematic bias and in particular it makes these two research products maintain a stable skill level during winter. As for the heavy rainfall events (>50 mm/d) in summer, 3B42V7 and CMORPH exhibit a relatively better degree of agreement to the gauge observations. Overall, our study suggests that the satellite-based precipitation estimates all have their own pros and cons at different spatiotemporal scales. We expect the results reported here will provide a better understanding of current mainstream satellite precipitation products over similar medium-sized humid basins. Editor Z.W. Kundzewicz; Associate editor N. Verhoest

Analyzing projected changes and trends of temperature and precipitation in the southern USA from 16 downscaled global climate models

This study aims to examine how future climate, temperature and precipitation specifically, are expected to change under the A2, A1B, and B1 emission scenarios over the six states that make up the Southern Climate Impacts Planning Program (SCIPP): Oklahoma, Texas, Arkansas, Louisiana, Tennessee, and Mississippi. SCIPP is a member of the National Oceanic and Atmospheric Administration-funded Regional Integrated Sciences and Assessments network, a program which aims to better connect climate-related scientific research with in-the-field decision-making processes. The results of the study found that the average temperature over the study area is anticipated to increase by 1.7°C to 2.4°C in the twenty-first century based on the different emission scenarios with a rate of change that is more pronounced during the second half of the century. Summer and fall seasons are projected to have more significant temperature increases, while the northwestern portions of the region are projected to experience more significant increases than the Gulf coast region. Precipitation projections, conversely, do not exhibit a discernible upward or downward trend. Late twenty-first century exhibits slightly more precipitation than the early century, based on the A1B and B1 scenario, and fall and winter are projected to become wetter than the late twentieth century as a whole. Climate changes on the city level show that greater warming will happened in inland cities such as Oklahoma City and El Paso, and heavier precipitation in Nashville. These changes have profound implications for local water resources management as well as broader regional decision making. These results represent an initial phase of a broader study that is being undertaken to assist SCIPP regional and local water planning efforts in an effort to more closely link climate modeling to longer-term water resources management and to continue assessing climate change impacts on regional hazards management in the South.

Incorporating NASA Spaceborne Radar Data into NOAA National Mosaic QPE System for Improved Precipitation Measurement: A Physically Based VPR Identification and Enhancement Method

AbstractThis study proposes an approach that identifies and corrects for the vertical profile of reflectivity (VPR) by using Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements in the region of Arizona and southern California, where the ground-based Next Generation Weather Radar (NEXRAD) finds difficulties in making reliable estimations of surface precipitation amounts because of complex terrain and limited radar coverage. A VPR identification and enhancement (VPR-IE) method based on the modeling of the vertical variations of the equivalent reflectivity factor using a physically based parameterization is employed to obtain a representative VPR at S band from the TRMM PR measurement at Ku band. Then the representative VPR is convolved with ground radar beam sampling properties to compute apparent VPRs for enhancing NEXRAD quantitative precipitation estimation (QPE). The VPR-IE methodology is evaluated with several stratiform precipitation events during the cold season and is co...

An Improved Top-Hat Filter with Sloped Brim for Extracting Ground Points from Airborne Lidar Point Clouds

Airborne light detection and ranging (lidar) has become a powerful support for acquiring geospatial data in numerous geospatial applications and analyses. However, the process of extracting ground points accurately and effectively from raw point clouds remains a big challenge. This study presents an improved top-hat filter with a sloped brim to enhance the robustness of ground point extraction for complex objects and terrains. The top-hat transformation is executed and the elevation change intensity of the transitions between the obtained top-hats and outer brims is inspected to suppress the omission error caused by protruding terrain features. Finally, the nonground objects of complex structures, such as multilayer buildings, are identified by the brim filter that is extended outward. The performance of the proposed filter in various environments is evaluated using diverse datasets with difficult cases. The comparison of the proposed filter with the commercial software Terrasolid TerraScan and other popular filtering algorithms demonstrates the applicability and effectiveness of this filter. Experimental results show that the proposed filter has great promise in terms of its application in various types of landscapes. Abrupt terrain features with dramatic elevation changes are well preserved, and diverse objects with complicated shapes are effectively removed. This filter has minimal omission and commission error oscillation for different test areas and thus demonstrates a stable and reliable performance in diverse landscapes. In addition, the proposed algorithm has high computational efficiency because of its simple and efficient data structure and implementation.