Daniel Fiifi T. Hagan

The Evaluation of Single-Sensor Surface Soil Moisture Anomalies over the Mainland of the People’s Republic of China

In recent years, different space agencies have launched satellite missions that carry passive microwave instruments on-board that can measure surface soil moisture. Three currently operational missions are the Soil Moisture and Ocean Salinity (SMOS) mission developed by the European Space Agency (ESA), the Advanced Microwave Scanning Radiometer 2 (AMSR2) developed by the Japan Aerospace Exploration Agency (JAXA), and the Microwave Radiation Imager (MWRI) from China’s National Satellite Meteorological Centre (NSMC). In this study, the quality of surface soil moisture anomalies derived from these passive microwave instruments was sequentially assessed over the mainland of the People’s Republic of China. First, the impact of a recent update in the Land Parameter Retrieval Model (LPRM) was assessed for MWRI observations. Then, the soil moisture measurements retrieved from the X-band observations of MWRI were compared with those of AMSR2, followed by an internal comparison of the multiple frequencies of AMSR2. Finally, SMOS retrievals from two different algorithms were also included in the comparison. For each sequential step, processing and verification chains were specifically designed to isolate the impact of algorithm (version), observation frequency or instrument characteristics. Two verification techniques are used: the statistical Triple Collocation technique is used as the primary verification tool, while the precipitation-based Rvalue technique is used to confirm key results. Our results indicate a consistently better performance throughout the entire study area after the implementation of an update of the LPRM. We also find that passive microwave observations in the AMSR2 C-band frequency (6.9 GHz) have an advantage over the AMSR2 X-band frequency (10.7 GHz) over moderate to densely vegetated regions. This finding is in line with theoretical expectations as emitted soil radiation will become masked under a dense canopy with stricter thresholds for higher passive microwave frequencies. Both AMSR2 and MWRI make X-band observations; a direct comparison between them reveals a consistently higher quality obtained by AMSR2, specifically over semi-arid climate regimes. Unfortunately, Radio Frequency Interference hampers the usefulness of soil moisture products for the SMOS L-band mission, leading to a significantly reduced revisit time over the densely populated eastern part of the country. Nevertheless, our analysis demonstrates that soil moisture products from a number of multi-frequency microwave sensors are credible alternatives for this dedicated L-band mission over the mainland of the People’s Republic of China.

Evaluation of soil moisture derived from FY3B microwave brightness temperature over the Tibetan Plateau

ABSTRACT In recent years, remote sensing has become one newest technology for deriving soil moisture at large scales. Using a radiative transfer algorithm, we have derived soil moisture over the Tibetan Plateau from the brightness temperature of the microwave radiometer imager (MWRI) onboard China’s Fengyun 3B (FY3B) satellite. The derived FY3B soil moisture data are evaluated with in situ observations, the ERA-Interim reanalysis and the retrievals from microwave imager (TMI) onboard the Tropical Rainforest Measuring Mission (TRMM). The FY3B and the TMI data are found to have both overestimated the soil moisture magnitudes against in situ observations. The FY3B data significantly outperform the TMI retrievals and particularly the ERA-Interim data with respect to their temporal dynamics, which is more important in soil moisture applications. This finding suggests the promising potential for using FY3B microwave brightness temperature to derive soil moisture over the Tibetan Plateau.

Robust drying and wetting trends found in regions over China based on Köppen climate classifications

Controversial results in the drying and wetting trends were found with different indices and potential evapotranspiration calculations in previous studies. Here we make an attempt to find robust conclusions of drying and wetting trends over regions by coherent results of various independent indices by using China (1961–2012) as a study area. Precipitation, statistical, and physical drought indices, including the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI) and self-calibrating PDSI (sc_PDSI), with both the Penman-Monteith (PM) and Thornthwaite (TH) approaches in PDSI calculation are considered. In consequence, four PDSI variants of PDSI_pm, sc_PDSI_pm, PDSI_th, and sc_PDSI_th are involved. To illustrate regional characteristics, six climatic regions based on the Koppen climate classification are defined. At the national scale, precipitation and SPEI indicate wetting trends but all PDSI variants have drying trends. On the other hand, these six indices exhibit coherent results in five of these six regions. Increases in wetness occur in arid region and the Qinghai-Tibet Plateau. Drying trends were found in semiarid and cold and temperate semihumid regions. Only the humid region in southeastern China is seen to have increasing precipitation and SPEI and decreasing PDSI variants. From the perspective of climatic regions, the drying trends mainly occur in the transition regions between the humid and arid regions in China. The spatial pattern of changes in droughts could be categorized by climatic zones, and the changes at regional scale are robust based on these six indices.

Improved surface soil moisture anomalies from Fengyun-3B over the Jiangxi province of the People’s Republic of China

ABSTRACT This study develops a data-driven modification scheme for a commonly used soil moisture retrieval algorithm by introducing a vegetation density-related single scattering albedo based on in situ and Fengyun-3B passive microwave observations. The Jiangxi province in China’s mainland is one of the most challenging regions for soil moisture retrievals due to its complex topography, open water, and vegetation conditions. However, it has a very dense in situ soil moisture observation network which makes it a suitable test-bed to examine the performance of the modification scheme. The development of this new scheme consists of two steps. In a first step, the model is initialized using the most recently developed algorithm configuration. In the second step, these initial outcomes are used as input to determine the vegetation density related single scattering albedo which is solely based on observational data and used as the final algorithm configuration over our study area. We start by comparing the two most recent algorithm configurations against the in situ soil moisture network and demonstrate an overall improvement in terms of correlations coefficient for the most recent version. Then, the observational data- driven modification scheme was proposed and evaluated against the in situ soil moisture network with further improvements after its implementation. We furthermore applied the vegetation density-based scattering albedo in soil moisture retrievals over all grid cells in Jiangxi, and found that soil moisture data with the newly developed configuration significantly improved (up to 30%) compared to the preceding algorithm configurations. The two existing algorithm configurations were also evaluated over all grid cells and all results indicate consistent improvements between the successive algorithm versions.

Spatio-temporal analysis of precipitable water vapour over northwest china utilizing MERSI/FY-3A products

ABSTRACT Northwest China is considered as the arid and semi-arid temperate continental climate, where the precipitation is closely related to precipitable water vapour (PWV) content. In this paper, the Medium-Resolution Spectral Imager (MERSI) water vapour products were first used to study the spatial and temporal characteristics of water vapour over Northwest China, which were developed by the National Satellite Meteorological Center of China from the Chinese second-generation polar orbit Meteorological Satellite Fengyun 3A (FY-3A). In order to utilize the MERSI water vapour products, the MERSI 5 min water vapour product is compared respectively with global positioning system (GPS), Aerosol Robotic Network (AERONET) and Radiosonde water vapour data in situ datasets. The results show that the water vapour values of the MERSI product are a slightly lower than referenced data, and the accuracy of MERSI product compared with GPS water vapour is the most agreeable, with a mean absolute percentage error (MAPE) of 22.83%. The PWV content displays a typical spatial distribution pattern in Northwest China that it is the highest in the southeast, the second for the northwest and the lowest in the south-centre. The water vapour content over each province in a descending order is Shaanxi, Ningxia, west of Inner Mongolia, Xinjiang, Gansu and Qinghai. The seasonal variation of water vapour content over Northwest China appears to be lowest in winter, followed by spring, then for autumn, and highest in summer. The PWV content of each province in Northwest China shows the periodic inner-annual variation, that is, the PWV content is lowest in January, and gradually increases with time till it peaks in July, and then decreases monthly afterwards, which agrees with the quadratic polynomial model by months. The standard deviation of the water vapour content in summer is 0.533–1.027 mm, while that in winter is 0.262–0.527 mm.

Changes of Soil Moisture from Multiple Sources during 1988–2010 in the Yellow River Basin, China

Soil moisture is a key variable in terrestrial water cycle, playing a key role in the exchange of water and energy in the landatmosphere interface.The spatiotemporal variations of soil moisture frommultiple sources during 1988–2010 are evaluated against in situ observations in the Yellow River basin, China, including the Essential Climate Variable satellite’s passive microwave product (SMECV), ERA-Interim reanalysis (SMERA), theNational Centers for Environmental Prediction/Department of Energy’s Reanalysis2 (SMNCEP), and the Variable Infiltration Capacity model products (SMVIC). The seasonal soil moisture dynamics of SMECV and SMVIC appear to be consistent with SMin situ, with significant soil drying in spring and wetting in summer. SMERA and SMNCEP, however, fail to capture the soil drying before rainy seasons. Remarkably, SMECV shows large agreement with SMin situ in terms of the interannual variations and the long-term drying trends. SMVIC captures the interannual variations but fails to have the longterm trends in SMin situ. As for SMERA and SMNCEP, they fail to capture both the interannual variations and the long-term soil drying trends in SMin situ.