Nowadays, spaceborne Synthetic Aperture Radar (SAR) has become a powerful tool for providing significant wave height (SWH). Traditionally, validation of SAR derived SWH has been carried out against buoy measurements or model outputs, which only yield...
Triple collocation analysis is an established technique for calculating the relative linear intercalibration coefficients and observation error variances for physical quantities measured simultaneously in space and time by three different observation...
The accuracy of wind speed measurements is important in many applications. In the present work, error standard deviations of wind speed measured by satellites and National Data Buoy Center (NDBC) buoys were estimated using triple collocation. The sat...
This study uses a triple-sensor collocation approach to evaluate the performance of small-holder irrigation schemes in the Zamra catchment of Northern Ethiopia. Crop water productivity (CWP), as an integrator of biomass production and water use, was...
The validation of precipitation estimates is necessary for the selection of the most appropriate dataset, as well as for having confidence in its selection. Traditional validation against gauges or radars is much less effective when the quality of th...
The error characterization of satellite observations is crucial for blending observations from multiple platforms into a unique dataset and for assimilating them into numerical weather prediction models. In the last years, the triple collocation (TC)...
The Yangtze River Basin (YRB) is highly vulnerable to both floods and droughts, with precipitation playing a key role in driving these hydrological extremes. Understanding and reducing uncertainty in precipitation estimates is therefore crucial for e...
Existing validation of mean wind speed estimates via reflectometry from global navigation systems of satellites (GNSS-R)—has been largely limited in spatial coverage to equatorial buoys or tropical cyclone events near continental United States....
Triple/N-way collocation is a statistical analysis tool used to estimate the individual error variances of simultaneous observations of a physical quantity by three or more distinct systems. The tool is widely used to validate remote sensing data pro...
Sea surface temperature (SST) is vital for climate monitoring and extreme weather forecasting. Existing global SST datasets are typically provided at daily to seasonal resolutions, while hourly data remain limited to regional scales. Polar-orbiting s...
Evaluating the reliability of satellite-based and reanalysis soil moisture products is very important in soil moisture research. The traditional methods of evaluating soil moisture products rely on the verification of satellite inversion data and gro...
Sea Surface Temperature (SST) is an essential climate variable (ECV) for monitoring the state and detecting changes in the climate. The concept of ECVs, developed by the Global Climate Observing System (GCOS) program of the World Meteorological Organ...
High-spatiotemporal resolution soil moisture (SM) plays an essential role in optimized irrigation, agricultural droughts, and hydrometeorological model simulations. However, producing high-spatiotemporal seamless soil moisture products is challenging...
Satellite remote sensing-based soil moisture (SM) retrieval quantifies the spatial and temporal distributions of SM to support Earth system modeling. However, existing SM products, including satellite remote sensing, model-simulated, and land data as...
Validating remotely sensed sea surface temperature (SST) is a fundamental step in establishing reliable biological/physical models that can be used in different marine applications. Mapping SST using accurate models would assess in understanding crit...
Accurate estimation of evapotranspiration (ET) is critical for understanding land-atmospheric interactions. Despite the advancement in ET measurement, a single ET estimate still suffers from inherent uncertainties. Data fusion provides a viable optio...
Triple collocation (TC) shows potential in estimating the errors of various geographical data in the absence of the truth. In this study, the TC techniques are first applied to evaluate the performances of multiple column-averaged dry air CO2 mole fr...
Accurate daily gridded precipitation estimates are needed to characterize spatial rainfall variability and support retrospective hydrological analysis in Southeast Asia, where complex rainfall regimes and sparse rain gauge coverage remain major chall...
Accurate and reliable estimation of actual evapotranspiration (AET) is essential for various hydrological studies, including drought prediction, water resource management, and the analysis of atmospheric–terrestrial carbon exchanges. Gridded AE...
Integrated Water Vapor (IWV) is a key indicator of atmospheric moisture, and its accurate quantification requires precise characterization of the errors inherent to each observing system, a task complicated by the absence of a true, error-free atmosp...
Currently, satellite-based soil moisture (SM) products and land surface model assimilation techniques are widely utilized. However, the presence of systematic errors in the observation process, algorithmic discrepancies between products, and variatio...
Snow depth is a crucial variable when assessing the hydrological cycle and total water supply. Therefore, thorough and large-scale assessments of the widely used gridded snow depth products are highly important. In previous studies, triple collocatio...
Satellite retrieval and land surface models have become the mainstream methods for monitoring soil moisture (SM) over large regions; however, the uncertainty and coarse spatial resolution of these products limit their applications at the regional and...
Global land cover (GLC) data are an indispensable resource for understanding the relationship between human activities and the natural environment. Estimating their classification accuracy is significant for studying environmental change and sustaina...
Reliable assessment of satellite-based precipitation estimation (SPE) and production of more accurate precipitation data by data fusion is typically challenging in sparsely gauged and ungauged areas. Triple collocation (TC) is a novel assessment appr...
Obtaining accurate near-real-time precipitation data and merging multiple precipitation estimates require sufficient in-situ rain gauge networks. The triple collocation (TC) approach is a novel error assessment method that does not require rain gauge...
Land surface models (LSMs) simulate water and energy cycles at the atmosphere–soil interface, however, the physical processes in the subsurface are typically oversimplified and lateral water movement is neglected. Here, a cross-evaluation of land sur...
Remote sensing (RS) soil moisture (SM) products have been widely used in various environmental studies. Understanding the error structure of data is necessary to properly apply RS SM products in trend and variation analysis and data fusion. However,...
The model error is a direct reflection of the accuracy of the model simulation. However, it is challenging to estimate the model error due to the presence of numerous uncertainties inherent to the atmospheric and soil data, as well as the structure a...
Improvements in soil moisture observations and modeling play a vital role in drought, water resources, flooding, and landslide management and forecasting. However, the lack of multisensor products that integrate different spatial scales (i.e., from 1...
Accurate and up-to-date data on built-up areas are crucial for urban planning, disaster management, and sustainable development, yet Romania still lacks a unified, official database. In this study we integrated the three widely used global data sourc...
This study develops a triple-collocation (TC) based, multi-source shallow-soil moisture product for Oklahoma. The method uses a least squared weights (LSW) optimization to find the set of parameters that result in the lowest root mean squared error (...
Quantifying uncertainties of precipitation estimation, especially in extreme events, could benefit early warning of water-related hazards like flash floods and landslides. Rain gauges, weather radars, and satellites are three mainstream data sources...
Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validatio...
In this paper, the advantages of shaping a non-conventional triple collocation-based calibration of a wave propagation model is pointed out. Illustrated through a case study in the Bagnoli-Coroglio Bay (central Tyrrhenian Sea, Italy), a multi-compari...
The Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in “low-resolution” (LR) and synthetic aperture radar...
Soil moisture (SM) measurements from ground stations are often after quality control (QC) in the operational system, but the QC flags may not be reliable in some cases when precipitation events or manual watering happen. This study applies the triple...
Reliable soil moisture information is essential for agricultural drought warning, but tropical smallholder regions often lack ground networks for validating satellite products. This study evaluates the Cyclone Global Navigation Satellite System (CYGN...
With the increasing utilization of satellite-based soil moisture products, a primary challenge is knowing their accuracy and robustness. This study presents a comprehensive assessment over China of three widely used global satellite soil moisture pro...
HY–4A is China’s first ocean salinity remote-sensing satellite, launched into orbit in November 2024 and currently in operational service. The LASMR (L-Band Aperture Synthesis Microwave Radiometer) is the L-band synthetic aperture radiome...
Shortfalls in regular evapotranspiration (ET) monitoring and evaluation pose a huge challenge to agricultural water resource distribution in arid Central Asia (CA). In this study, a first detailed regional assessment of GLEAM, ERA5, MERRA2, CLSM and...
The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with t...
It is crucial to monitor the dynamics of soil moisture over the Tibetan Plateau, while considering its important role in understanding the land-atmosphere interactions and their influences on climate systems (e.g., Eastern Asian Summer Monsoon). Howe...
Precipitation plays a key control in the water, energy, and carbon cycles, and it is also an important driving force for land surface modeling. This study provides an optimal least squares merging approach to merge precipitation data sets from multip...
Most existing precipitation data fusion methods rely on reliable precipitation values, such as those observed from ground-based rain gauges, to correct the satellite precipitation estimates (SPEs) that often involve systematic biases. However, such r...
Soil moisture is an important factor in land-atmosphere interactions and other land processes. Improved estimates from climate models have, in the last two decades, become an important alternate source of information. In this study, we extend the eva...
The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions. Cosmic Ray Neutron Probes (CRNP) could be an option to fill the scale g...
Gridded runoff product at the sub-basin level is pivotal for effective hydrologic modeling and applications. Although reanalyses can overcome the lack of traditional stream gauge networks to provide reliable geospatial runoff data, the inherent uncer...
Soil moisture products acquired from passive satellite missions have been widely applied in environmental processes. A primary challenge for the use of soil moisture products from passive sensors is their reliability. It is crucial to evaluate the re...
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 ship...
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