Error Estimates for Near-Real-Time Satellite Soil Moisture as Derived From the Land Parameter Retrieval Model

2011 ◽  
Vol 8 (4) ◽  
pp. 779-783 ◽  
Author(s):  
R. M. Parinussa ◽  
A. G. C. A. Meesters ◽  
Y. Y. Liu ◽  
W. Dorigo ◽  
W. Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Error Estimates ◽  
Retrieval Model ◽  
Parameter Retrieval

An Improved Soil Moisture Retrieval Algorithm Based on the Land Parameter Retrieval Model for Water–Land Mixed Pixels Using AMSR-E Data

2019 ◽  
Vol 57 (10) ◽  
pp. 7643-7657 ◽  
Author(s):  
Peilin Song ◽  
Jingfeng Huang ◽  
Lamin R. Mansaray ◽  
Huayang Wen ◽  
Hongyan Wu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Retrieval Algorithm ◽  
Retrieval Model ◽  
Mixed Pixels ◽  
Parameter Retrieval

SMOS soil moisture retrievals using the land parameter retrieval model: Evaluation over the Murrumbidgee Catchment, southeast Australia

2015 ◽  
Vol 163 ◽  
pp. 70-79 ◽  
Author(s):  
R. van der Schalie ◽  
R.M. Parinussa ◽  
L.J. Renzullo ◽  
A.I.J.M. van Dijk ◽  
C.-H. Su ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Model Evaluation ◽  
Retrieval Model ◽  
Southeast Australia ◽  
Parameter Retrieval

Global SMOS Soil Moisture Retrievals from The Land Parameter Retrieval Model

2016 ◽  
Vol 45 ◽  
pp. 125-134 ◽  
Author(s):  
R.van der Schalie ◽  
Y.H. Kerr ◽  
J.P. Wigneron ◽  
N.J. Rodríguez-Fernández ◽  
A. Al-Yaari ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Retrieval Model ◽  
Parameter Retrieval

scholarly journals NOAA Satellite Soil Moisture Operational Product System (SMOPS) Version 3.0 Generates Higher Accuracy Blended Satellite Soil Moisture

2020 ◽  
Vol 12 (17) ◽  
pp. 2861
Author(s):  
Jifu Yin ◽  
Xiwu Zhan ◽  
Jicheng Liu
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Land Surface ◽  
Vital Role ◽  
Product System ◽  
Global Soil ◽  
One Stop ◽  
Satellite Sensors ◽  
Blended Data

Soil moisture plays a vital role for the understanding of hydrological, meteorological, and climatological land surface processes. To meet the need of real time global soil moisture datasets, a Soil Moisture Operational Product System (SMOPS) has been developed at National Oceanic and Atmospheric Administration to produce a one-stop shop for soil moisture observations from all available satellite sensors. What makes the SMOPS unique is its near real time global blended soil moisture product. Since the first version SMOPS publicly released in 2010, the SMOPS has been updated twice based on the users’ feedbacks through improving retrieval algorithms and including observations from new satellite sensors. The version 3.0 SMOPS has been operationally released since 2017. Significant differences in climatological averages lead to remarkable distinctions in data quality between the newest and the older versions of SMOPS blended soil moisture products. This study reveals that the SMOPS version 3.0 has overwhelming advantages of reduced data uncertainties and increased correlations with respect to the quality controlled in situ measurements. The new version SMOPS also presents more robust agreements with the European Space Agency’s Climate Change Initiative (ESA_CCI) soil moisture datasets. With the higher accuracy, the blended data product from the new version SMOPS is expected to benefit the hydrological, meteorological, and climatological researches, as well as numerical weather, climate, and water prediction operations.

Near real time de-noising of satellite-based soil moisture retrievals: An intercomparison among three different techniques

2017 ◽  
Vol 198 ◽  
pp. 17-29 ◽  
Author(s):  
Christian Massari ◽  
Chun-Hsu Su ◽  
Luca Brocca ◽  
Yan-Fang Sang ◽  
Luca Ciabatta ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Real Time

scholarly journals Rancang Bangun Sistem Monitoring Lahan Pertanian Berbasis Mikrokontroler Arduino dan Mobile Web

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Emilyana Varida ◽  
Arif Supriyanto ◽  
Wiwik Kusrini ◽  
Fathurahmani Fathur
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Mobile Web ◽  
Moisture Sensor ◽  
Soil Moisture Sensor

Saat ini para petani sayuran dalam menanam jenis sayuran masih menggunakan cara tradisional dan belum memperhatikan kondisi tanah yang sesuai untuk jenis sayuran yang akan mereka tanam, hal ini menyebabkan pertumbuhan sayuran menjadi kurang maksimal. Oleh karena itu diperlukan sebuah sistem yang mampu memberikan informasi kadar tanah dan memberikan rekomendasi jenis sayuran yang cocok untuk ditanami. Sistem yang akan dibangun berbasis mikrokontorler arduino, sensor soil moisture, sensor pH, dan modul ESP8266 yang digunakan untuk mengirimkan data hasil dari pembacaan sensor ke perangkat mobile secara real-time  untuk diproses dan menghasilkan rekomendasi jenis sayuran yang cocok berdasarkan data hasil dari pembacaan sensor. Berdasarkan hasil pengujian, sistem ini telah mampu menampilkan kondisi kelembaban tanah, kadar pH dengan baik dan mampu merekomendasi jenis sayuran sesuai dengan kondisi hasil pembacaan sensor, sehingga harapannya dapat membantu para petani sayuran dalam menentukan jenis sayuran yang akan mereka tanam dan mampu meminimalisir resiko gagal panen. Kata Kunci: Arduino, soil moisture, pH, mobile web

scholarly journals Tropical Cyclone Gale Wind Radii Estimates, Forecasts, and Error Forecasts for the Western North Pacific

2018 ◽  
Vol 33 (4) ◽  
pp. 1081-1092 ◽  
Author(s):  
Charles R. Sampson ◽  
James S. Goerss ◽  
John A. Knaff ◽  
Brian R. Strahl ◽  
Edward M. Fukada ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Real Time ◽  
Error Estimates ◽  
Forecast Error ◽  
Operational Reliability ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Initial Size ◽  
Time Estimates ◽  
Joint Typhoon Warning Center

Abstract In 2016, the Joint Typhoon Warning Center extended forecasts of gale-force and other wind radii to 5 days. That effort and a thrust to perform postseason analysis of gale-force wind radii for the “best tracks” (the quality controlled and documented tropical cyclone track and intensity estimates released after the season) have prompted requirements for new guidance to address the challenges of both. At the same time, operational tools to estimate and predict wind radii continue to evolve, now forming a quality suite of gale-force wind radii analysis and forecasting tools. This work provides an update to real-time estimates of gale-force wind radii (a mean/consensus of gale-force individual wind radii estimates) that includes objective scatterometer-derived estimates. The work also addresses operational gale-force wind radii forecasting in that it provides an update to a gale-force wind radii forecast consensus, which now includes gale-force wind radii forecast error estimates to accompany the gale-force wind radii forecasts. The gale-force wind radii forecast error estimates are computed using predictors readily available in real time (e.g., consensus spread, initial size, and forecast intensity) so that operational reliability and timeliness can be ensured. These updates were all implemented in operations at the Joint Typhoon Warning Center by January 2018, and more updates should be expected in the coming years as new and improved guidance becomes available.

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