Comparison of GPM IMERG and TRMM 3B43 Products over Cyprus

Retalis, Adrianos; Katsanos, Dimitrios; Tymvios, Filippos; Michaelides, Silas

doi:10.3390/rs12193212

Cited by 27 publications

(12 citation statements)

References 50 publications

(52 reference statements)

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“…The authors underscore the importance of IMERG algorithm refinement in order to improve the accuracy of IMERG products over the country, where plenty of rainfall data are urgently needed for hydrological utilities, as indicated in the present study. For a more comprehensive survey of the literature on IMERG and TMPA comparisons, the reader is referred to Retalis et al [66].…”

Section: Discussionmentioning

confidence: 99%

“…Due to the limited amount of in-situ data, the effect of elevation on the estimation of rainfall from satellite-derived products cannot be done in a satisfactory way in the present study. This is a very challenging viewpoint that has been pursued in other studies with more ground-based data [58,66]. This challenging viewpoint will be part of future work to investigate this aspect as well but following a substantial upgrade of the rain gauge network over the area.…”

Section: Discussionmentioning

confidence: 99%

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Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai

et al. 2021

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The replenishment of aquifers depends mainly on precipitation rates, which is of vital importance for determining water budgets in arid and semi-arid regions. El-Qaa Plain in the Sinai Peninsula is a region that experiences constant population growth. This study compares the performance of two sets of satellite-based data of precipitation and in situ rainfall measurements. The dates selected refer to rainfall events between 2015 and 2018. For this purpose, 0.1° and 0.25° spatial resolution TMPA (Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis) and IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement) data were retrieved and analyzed, employing appropriate statistical metrics. The best-performing data set was determined as the data source capable to most accurately bridge gaps in the limited rain gauge records, embracing both frequent light-intensity rain events and more rare heavy-intensity events. With light-intensity events, the corresponding satellite-based data sets differ the least and correlate more, while the greatest differences and weakest correlations are noted for the heavy-intensity events. The satellite-based records best match those of the rain gauges during light-intensity events, when compared to the heaviest ones. IMERG data exhibit a superior performance than TMPA in all rainfall intensities.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai

et al. 2021

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“…In this study, the GPM_3IMERGDL v06 (D: daily, L: late run) products were employed, as they are widely used for research purposes and have enhanced accuracy. In fact, IMERG for GPM (IMERG) is the level 3 GPM algorithm, which integrates precipitation estimates from all constellation microwave (MW) sensors, IR-based sensors onboard geosynchronous satellites, and a monthly precipitation gauge product [14]. The spatial resolution of IMERG is 0.1 • × 0.1 • .…”

Section: Datamentioning

confidence: 99%

Linking Soil Erosion Modeling to Landscape Patterns and Geomorphometry: An Application in Crete, Greece

2021

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Soil erosion is a severe and continuous environmental problem caused mainly by natural factors, which can be enhanced by anthropogenic activities. The morphological relief with relatively steep slopes, the dense drainage network, and the Mediterranean climate are some of the factors that render the Paleochora region (South Chania, Crete, Greece) particularly prone to soil erosion in cases of intense rainfall events. In this study, we aimed to assess the correlation between soil erosion rates estimated from the Revised Universal Soil Loss Equation (RUSLE) and the landscape patterns and to detect the most erosion-prone sub-basins based on an analysis of morphometric parameters, using geographic information system (GIS) and remote sensing technologies. The assessment of soil erosion rates was conducted using the RUSLE model. The landscape metrics analysis was carried out to correlate soil erosion and landscape patterns. The morphometric analysis helped us to prioritize erosion-prone areas at the sub-basin level. The estimated soil erosion rates were mapped, showing the spatial distribution of the soil loss for the study area in 2020. For instance, the landscape patterns seemed to highly impact the soil erosion rates. The morphometric parameter analysis is considered as a useful tool for delineating areas that are highly vulnerable to soil erosion. The integration of three approaches showed that there is are robust relationships between soil erosion modeling, landscape patterns, and morphometry.

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“…53,54 The GPM mission was launched in February 2014 as a successor for the Tropical Rainfall Measuring Mission. 55 Total precipitation estimate was downloaded in NETCDF format for this study. 53 The spacecraft used to collect GPM data has additional channels on both the dual-frequency precipitation radar and GPM microwave imager with capabilities to sense light rain and falling snow, with advanced observations of precipitation in the midlatitudes.…”

Section: Satellite Datamentioning

confidence: 99%

Model inter-comparison for short-range forecasts over the southern African domain

Mulovhedzi¹,

Rambuwani²,

Bopape³

et al. 2021

S. Afr. J. Sci.

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Numerical weather prediction (NWP) models have been increasing in skill and their capability to simulate weather systems and provide valuable information at convective scales has improved in recent years. Much effort has been put into developing NWP models across the globe. Representation of physical processes is one of the critical issues in NWP, and it differs from one model to another. We investigated the performance of three regional NWP models used by the South African Weather Service over southern Africa, to identify the model that produces the best deterministic forecasts for the study domain. The three models – Unified Model (UM), Consortium for Small-scale Modelling (COSMO) and Weather Research and Forecasting (WRF) – were run at a horizontal grid spacing of about 4.4 km. Model forecasts for precipitation, 2-m temperature, and wind speed were verified against different observations. Snow was evaluated against reported snow records. Both the temporal and spatial verification of the model forecasts showed that the three models are comparable, with slight variations. Temperature and wind speed forecasts were similar for the three different models. Accumulated precipitation was mostly similar, except where WRF captured small rainfall amounts from a coastal low, while it over-estimated rainfall over the ocean. The UM showed a bubble-like shape towards the tropics, while COSMO cut-off part of the rainfall band that extended from the tropics to the sub-tropics. The COSMO and WRF models simulated a larger spatial coverage of precipitation than UM and snow-report records.

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Comparison of GPM IMERG and TRMM 3B43 Products over Cyprus

Cited by 27 publications

References 50 publications

Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai

Comparative Analysis of TMPA and IMERG Precipitation Datasets in the Arid Environment of El-Qaa Plain, Sinai

Linking Soil Erosion Modeling to Landscape Patterns and Geomorphometry: An Application in Crete, Greece

Model inter-comparison for short-range forecasts over the southern African domain

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