Liling Liu

Scatterometers are highlighted in polar applications, such as sea ice extent retrieval. There are currently three types of spaceborne scatterometer in operation, among which the rotating pencil beam scatterometer and the rotating fan beam scatterometer have similar rotating observation geometry, but different beam sampling. However, it is difficult to objectively evaluate the performance of the two rotating beam scatterometers using the obtained data. This is because there are significant differences in their system parameters, which in turn affects the objectivity of the evaluation. Considering the high flexibility of the rotating fan beam scatterometer, this study proposes a dual-mode sea ice extent retrieval method for the rotating fan beam scatterometer. The dual modes refer to the rotating fan beam mode (or full incidence mode) and the equivalent rotating pencil beam mode (or single incidence mode). The two modes share the same system and spatiotemporal synchronous backscatter measurements provide the possibility of objectively comparing the rotating pencil beam and rotating fan beam scatterometers. The comparison, validation, and evaluation of the dual-mode sea ice extent of China France Oceanography Satellite Scatterometer (CSCAT) were performed. The results indicate that the sea ice extent retrieval of the equivalent rotating pencil beam mode of the rotating fan beam scatterometer is realizable, and compared to the existing rotating pencil beam scatterometers (such as the OceanSat Scatterometer on ScatSat-1, OSCAT, on ScatSat-1, and the Hai Yang 2B Scatterometer, HSCAT-B), the derived sea ice extent is closer to that of Advanced Microwave Scanning Radiometer 2 (AMSR2). For the two modes of CSCAT, when compared to AMSR2, the sea ice extent of the CSCAT full incidence mode has smaller values of root mean squared error (RMSE), error-of-ice (EI), and ice edge location distance (LD) than those of the CSCAT single incidence mode. These suggest that the rotating fan beam scatterometer shows better observation abilities for sea ice extent than the rotating pencil beam scatterometers.

Polar sea ice extent exhibits a highly dynamic nature. This paper investigates the sea ice extent retrieval on a fine (6.25 km) grid based on the 12.5 km sampling data from the China France Ocean Satellite Scatterometer (CSCAT), which is generated by an adapted Bayesian sea ice detection algorithm. The CSCAT 12.5 km sampling data are analyzed, a corresponding sea ice GMF model is established, and the important calculation procedures and parameter settings of the adapted Bayesian algorithm for CSCAT 12.5 km sampling data are elaborated on. The evolution of the sea ice edge and extent based on CSCAT 12.5 km sampling data from 2020 to 2022 is introduced and quantitatively compared with sea ice extent products of Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Advanced Scatterometer onboard MetOp-C (ASCAT-C). The results suggest the sea ice extent of CSCAT 12.5 km sampling data has good consistency with AMSR2 at 15% sea ice concentration. The sea ice edge accuracy between them is about 7 km and 10 km for the Arctic and Antarctic regions, and their sea ice extent difference is 0.25 million km² in 2020 and 0.5 million km² in 2021 and 2022. Compared to ASCAT-C 12.5 km sampling data, the sea ice edge Euclidean distance (ED) of CSCAT 12.5 km data is 14 km (2020 and 2021) and 12.5 km (2022) for the Arctic region and 14 km for the Antarctic region. The sea ice extent difference between them is small except for January to May 2020 and 2021 for the Arctic region. There are significant deviations in the sea ice extents of CSCAT 12.5 km and 25 km sampling data, and their sea ice extent difference is 0.3–1.0 million km².

Scatterometers are dedicated to monitoring sea surface wind vectors, but they also provide valuable data for polar applications. As a new type of scatterometer, the rotating fan beam scatterometer delivers a higher diversity of incidence angles and more azimuth sampling. The paper takes the first rotating fan beam scatterometer, the China France Oceanography Satellite scatterometer (CSCAT), as an example to explore the effectiveness of this new type of scatterometer in polar sea ice detection. In this paper, a Bayesian method with consideration of geometric characteristics of CSCAT is developed for sea ice detection. The implementation of this method includes the definition of CSCAT backscatter space, an estimation of the sea ice Physical Model Function (GMF), a calculation of the sea ice backscatter distance to the sea ice GMF, a probability distribution function (PDF) estimation of the square distance to the GMF (sea ice GMF and wind GMF), and a calculation of the sea ice Bayesian posterior probability. This algorithm was used to generate a daily CSCAT polar sea ice mask during the CSCAT mission period (2019–2022) (by setting a 55% threshold on the Bayesian posterior probability). The sea ice masks were validated against passive microwaves by quantitatively comparing the sea ice edges and extents. The validation suggests that the CSCAT sea ice edge and extent show good agreement with the sea ice concentration distribution (i.e., sea ice concentration ≥ 15%) of the Advanced Microwave Scanning Radiometer 2 (AMSR2). The average Euclidean distance of the sea ice edges was basically less than 12.5 km, and the deviation of the sea ice extents was less than 0.3 × 10⁶ km².

Objective: To study the growth, accumulation and soil nutrient content of each overseeded species under different interharvesting intensity treatments of Eucalyptus, and to explore the best re-cultivation method suitable for mixed overseeded species after Eucalyptus interharvesting. Methods: In Guangxi state-owned Qipo forest, Eucalyptus tailorii with different planting densities (DH32-29) were mixed with Castanopsis hystrix, Mytilaria laosensis and Michelia macclurei, and four different treatments (CK, LT, MT and HT) were established for re-cultivation of Eucalyptus near-mature forests with different logging intensities, and the differences in growth conditions and soil physicochemical properties of each species were analyzed. Results: (1) As the proportion of Eucalyptus allocation decreased, the growth of Eucalyptus diameter at breast height, tree height and individual wood volume could be promoted; the growth of the three parameters of HT and MT Eucalyptus were significantly different from LT and CK. (2) The average wood volume per plant of the set species in the CK and LT treatments was Mytilaria laosensis > Michelia macclurei > Castanopsis hystrix, while in the MT and HT treatments it was Mytilaria laosensis > Castanopsis hystrix > Michelia macclurei. (3) The differences in soil aeration, total saturated water holding capacity, capillary water holding capacity, and field water holding capacity in soil layers of different depth varied. In the same soil layer, soil aeration, total porosity and capillary porosity were HT > CK > LT > MT; saturated water holding capacity and capillary water holding capacity were HT > CK > LT > MT, while field water holding capacity was CK > HT > LT > MT. (4) Organic matter, pH, total nitrogen, total phosphorus, total potassium, fast-acting nitrogen, fast-acting phosphorus, and fast-acting potassium changed with varying soil depth in each treatment.

Polar sea ice is an important and sensitive indicator of climate change. The scatterometer onboard the China-France Oceanography Satellite (CFOSAT) is a Ku-band rotating fan-beam scatterometer with dual polarization capability and dedicated to the measurement of sea surface wind vectors. Because of the wide swath, it is also a good candidate for sea ice detection in the polar regions. The paper explorers a Bayesian sea ice detection method for the CFOSAT scatterometer. The performance of the approach is analyzed and validated against coincident sea ice concentration product of Special Sensor Microwave/Imager (SSMI). The results shows that the sea ice detection approach is feasible and effective. The resulting agreement between the sea ice maps of the CFOSAT scatterometer and sea ice concentration of SSMI is high.

Dual-frequency polarized scatterometer (DFPSCAT) is a pencil-beam rotating scatterometer which is designed for snow water equivalent (SWE) measurement, and Doppler beam sharpening (DBS) technique is proposed for DFPSCAT to achieve the azimuth resolution. However, the DBS technique is inapplicable for the forward-looking and afterward-looking regions. Based on an approximate aperiodic model of scatterometer echo signal, an improved adaptive regularization deconvolution algorithm with gradient histogram preservation (GHP) constraint is implemented to settle the problem. To investigate its performance of resolution enhancement and resulted accuracy, both a synthetic backscattering coefficient (σ ⁰ ) field reconstruction and SWE σ ⁰ reconstruction are carried out. The results show that the proposed method can recover the truth signal and achieve azimuth resolution of 2 km with the designed scatterometer system, which is required by the SWE retrieval. Moreover, the relative errors of reconstructed σ ⁰ are less than 0.5 dB that satisfy the accuracy requirement for SWE retrieval, and comparisons with observed results show that the error reduction is more than 0.03 dB. Meanwhile, a comparison between the proposed algorithm and some existing resolution enhancement methods is analyzed, which concludes that the proposed method can obtain a comparable resolution enhancement as L1 method and has less noise. The technique is also verified with advanced scatterometer (ASCAT) scatterometer data.