Observations of Microwave Ultra-Fast Absorption Phenomena Above Solar Active Region

While we process observational data of the Flares 22, two rare phenomena of microwave ultra fast absorption (MUFA) are found for the first time. They occurred at 3 67 GHz and 4 00 GHz in the atmospheric layers above both active regions of NOAA/USAF 4808 and 5060 in the interval 05 h50 m17 s～05 h50 m25 s UT on May 19, 1987 and 07 h38 m50 s～07 h38 m58 s UT on June 29, 1988, respectively. These absorption phenomena were observed with Phoenix Ⅱ Micowave Spectrometer at three frequencies (1 42, 2 84 and 3 67 GHz) and (1 42, 2 84 and 4 00 GHz) at Yunnan observatory. Spike emissions appeared at both 2 84 GHz and 1 42 GHz. The notable observational characteristics of both absorption phenomena are given. A possible absorption mechanism of MUFA is discussed.

Spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River during the period 2002–2011 based on the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) data

Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.

The local contribution to the microwave background radiation

The observed microwave background radiation （MBR） is commonly in- terpreted as the relic of an early hot universe, and its observed features （spectrum and anisotropy） are explained in terms of properties of the early universe. Here we describe a complementary, even possibly alternative, interpretation of MBR, first proposed in the early 20th century, and adapt it to modern observations. For example, the stellar Hipparcos data show that the energy density of starlight from the Milky Way, if suit- ably thermalized, yields a temperature of ~2.81 K. This and other arguments given here strongly suggest that the origin of MBR may lie, at least in a very large part, in re-radiation of thermalized galactic starlight. The strengths and weaknesses of this alternative radical explanation are discussed.

Comparison of TMI and AMSR-E sea surface temperatures with Argo near-surface temperatures over the global oceans

Satellite-derived sea surface temperatures（SSTs） from the tropical rainfall measuring mission（TRMM）microwave imager（TMI） and the advanced microwave scanning radiometer for the earth observing system（AMSR-E） were compared with non-pumped near-surface temperatures（NSTs） obtained from Argo profiling floats over the global oceans. Factors that might cause temperature differences were examined, including wind speed, columnar water vapor, liquid cloud water, and geographic location. The results show that both TMI and AMSR-E SSTs are highly correlated with the Argo NSTs; however, at low wind speeds, they are on average warmer than the Argo NSTs. The TMI performs slightly better than the AMSR-E at low wind speeds, whereas the TMI SST retrievals might be poorly calibrated at high wind speeds. The temperature differences indicate a warm bias of the TMI/AMSR-E when columnar water vapor is low, which can indicate that neither TMI nor AMSR-E SSTs are well calibrated at high latitudes. The SST in the Kuroshio Extension region has higher variability than in the Kuroshio region. The variability of the temperature difference between the satellite-retrieved SSTs and the Argo NSTs is lower in the Kuroshio Extension during spring. At low wind speeds, neither TMI nor AMSR-E SSTs are well calibrated, although the TMI performs better than the AMSR-E.

Microwave diagnostics of magnetic field strengths in solar flaring loops

We have performed microwave diagnostics of the magnetic field strengths in solar flaring loops based on the theory of gyrosynchrotron emission.From Nobeyama Radioheliograph observations of three flare events at 17 and 34 GHz,we obtained the degree of circular polarization and the spectral index of microwave flux density,which were then used to map the magnetic field strengths in post-flare loops.Our results show that the magnetic field strength typically decreases from ~800 G near the loop footpoints to~100 G at a height of 10-25 Mm.Comparison of our results with magnetic field modeling using a flux rope insertion method is also discussed.Our study demonstrates the potential of microwave imaging observations,even at only two frequencies,in diagnosing the coronal magnetic field of flaring regions.

Identifying AMSR-E radio-frequency interference over winter land

Satellite microwave emission mixed with signals from active sensors is referred to as radio- frequency interference （RFI）. RFI affects greatly the quality of data and retrieval products from space-bome microwave radiometry. An accurate RFI detection will not only enhance geophysical retrievals over land but also provide evidence of the much-needed protection of the microwave frequency band for satellite remote sensing technologies. It is difficult to detect RFI from space-borne microwave radiometer data over winter land, because RFI signals are usually mixed with snow in mid-high latitudes. A modified principal component analysis （PCA） method is proposed in this paper for detecting microwave low frequency RFI signals. Only three original variables, one RFI index （sensitive to RFI signal） and two scattering indices （sensitive to snow scattering）, are included in the vector for principal component analysis in this modified method instead of the nine or seven RFI index original variables used in a normal PCA algorithm. The principal component with higher correlation and contribution to the original RFI index is the RFI-related principal component. In the absence of a reliable validation data set of the ＂true＂ RFI, the consistency in the identified RFI distribution obtained from this method compared to other independent methods, such as the spectral difference method, the normalized PCA method, and the double PCA method, give confidence to the RFI signals＇ identification over land. The simple and reliable modified PCA method could successfully detect RFI not only in summer but also in winter AMSR-E data.