Guojie Wang

Global surface soil moisture from the Microwave Radiation Imager onboard the Fengyun-3B satellite

Soil moisture retrievals from China’s recently launched meteorological Fengyun-3B satellite are presented. An established retrieval algorithm – the Land Parameter Retrieval Model (LPRM) – was applied to observations of the Microwave Radiation Imager (MWRI) onboard this satellite. The newly developed soil moisture retrievals from this satellite mission may be incorporated in an existing global microwave-based soil moisture database. To reach consistency with an existing data set of multi-satellite soil moisture retrievals, an intercalibration step was applied to correct brightness temperatures for sensor differences between MWRI and the radiometer of the Tropical Rainfall Measuring Mission’s (TRMM’s) Microwave Imager (TMI), resulting from their individual calibration procedures. The newly derived soil moisture and vegetation optical depth product showed a high degree of consistency with parallel retrievals from both TMI and WindSat, the two satellites that are observing during the same time period and are already part of the LPRM database. High correlation (R > 0.60 at night-time) between the LPRM and official MWRI soil moisture products was shown over the validation networks experiencing semiarid climate conditions. The skills drop below 0.50 over forested regions, with the performance of the LPRM product slightly better than the official MWRI product. To demonstrate the promising use of the MWRI soil moisture in drought monitoring, a case study for a recent and unusually dry East Asian summer Monsoon was conducted. The MWRI soil moisture products are able to effectively delineate the regions that are experiencing a considerable drought, highly in agreement with spatial patterns of precipitation and temperature anomalies. The results in this study give confidence in the soil moisture retrievals from the MWRI onboard Fengyun-3B. The integration of the newly derived products into the existing database will allow a better understanding the diurnal, seasonal and interannual variations, and long-term (35 year) changes of soil moisture at the global scale, consequently enhancing hydrological, meteorological, and climate studies.

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.

Assessment of Multi-Source Evapotranspiration Products over China Using Eddy Covariance Observations

As an essential variable in linking water, carbon, and energy cycles, evapotranspiration (ET) is difficult to measure. Remote sensing, reanalysis, and land surface model-based ET products offer comprehensive alternatives at different spatio-temporal intervals, but their performance varies. In this study, we selected four popular ET global products: The Global Land Evaporation Amsterdam Model version 3.0a (GLEAM3.0a), the Modern Era Retrospective-Analysis for Research and Applications-Land (MERRA-Land) project, the Global Land Data Assimilation System version 2.0 with the Noah model (GLDAS2.0-Noah) and the EartH2Observe ensemble (EartH2Observe-En). Then, we comprehensively evaluated the performance of these products over China using a stratification method, six validation criteria, and high-quality eddy covariance (EC) measurements at 12 sites. The aim of this research was to provide important quantitative information to improve and apply the ET models and to inform choices about the appropriate ET product for specific applications. Results showed that, within one stratification, the performance of each ET product based on a certain criterion differed among classifications of this stratification. Furthermore, the optimal ET (OET) among these products was identified by comparing the magnitudes of each criterion. Results suggested that, given a criterion (a stratification classification), the OETs varied among stratification classifications (the selected six criteria). In short, no product consistently performed best, according to the selected validation criterion. Thus, multi-source ET datasets should be employed in future studies to enhance confidence in ET-related conclusions.

Drought losses in China might double between the 1.5 °C and 2.0 °C warming

Significance We project drought losses in China under global warming of 1.5 °C and 2.0 °C. To assess future drought losses, we project the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration patterns. With increasing drought intensity and areal coverage across China, drought losses will increase considerably. The estimated losses in a sustainable development pathway at 1.5 °C warming will be 10 times higher than in the reference period 1986–2005 and three times higher than in 2006–2015. Yet, climate change mitigation, limiting the temperature increase to 1.5 °C, can considerably reduce the annual drought losses in China, compared with 2.0 °C warming. We project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and “intensity-loss rate” function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020–2039 and 2040–2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986–2005 and nearly threefold relative to the interval 2006–2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.

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.

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.