Anthropogenic Space Weather

Anthropogenic effects on the space environment started in the late 19th century and reached their peak in the 1960s when high-altitude nuclear explosions were carried out by the USA and the Soviet Union. These explosions created artificial radiation belts near Earth that resulted in major damages to several satellites. Another, unexpected impact of the high-altitude nuclear tests was the electromagnetic pulse (EMP) that can have devastating effects over a large geographic area (as large as the continental United States). Other anthropogenic impacts on the space environment include chemical release ex- periments, high-frequency wave heating of the ionosphere and the interaction of VLF waves with the radiation belts. This paper reviews the fundamental physical process behind these phenomena and discusses the observations of their impacts.Comment: 71 pages, 35 figure

Validation of soil moisture and ocean salinity (SMOS). Soil moisture over watershed networks in the U.S.

International audienceEstimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods over the past two decades. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must be conducted to insure product quality that will, in turn, support the widespread utilization of the data. This is especially important since SMOS utilizes a new sensor technology and is the first passive L-band system in routine operation. In this paper, we contribute to the validation of SMOS using a set of four in situ soil moisture networks located in the U.S. These ground-based observations are combined with retrievals based on another satellite sensor, the Advanced Microwave Scanning Radiometer (AMSR-E). The watershed sites are highly reliable and address scaling with replicate sampling. Results of the validation analysis indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with the in situ data and AMSR-E retrievals. The overall root-mean-square error of the SMOS soil moisture estimates is 0.043 m3/m3 for the watershed networks (ascending). There are bias issues at some sites that need to be addressed, as well as some outlier responses. Additional statistical metrics were also considered. Analyses indicated that active or recent rainfall can contribute to interpretation problems when assessing algorithm performance, which is related to the contributing depth of the satellite sensor. Using a precipitation flag can improve the performance. An investigation of the vegetation optical depth (tau) retrievals provided by the SMOS algorithm indicated that, for the watershed sites, these are not a reliable source of information about the vegetation canopy. The SMOS algorithms will continue to be refined as feedback from validation is evaluated, and it is expected that the SMOS estimates will improve

Performance of SMOS Soil Moisture Products over Core Validation Sites

International audienceThe European Space Agency (ESA) launched the SMOS (Soil Moisture Ocean Salinity) mission in 2009; currently, multiple global soil moisture (SM) products are based on the measurements of its L-band (1.4 GHz) radiometer. We compared four SMOS products with each other: Level 2, Level 3, IC (INRA-CESBIO), and Near Real Time products. The comparisons focused on core validation sites (CVS), whose spatial representativeness errors allow the estimation of the SM product performance for bias-insensitive metrics (unbiased root mean square error (ubRMSE) and correlation (R), and anomaly R) with negligible uncertainty and for bias-sensitive metrics (mean difference (MD) and root mean square difference or RMSD) with acceptable uncertainty. When the products were compared with CVS independently, the results showed that the ubRMSE, R, and anomaly R of the IC product were better than those of the other products, while the MD was larger. However, the differences between the performances were smaller when the products were assessed using only the data points when each product had a valid retrieval. This indicates that the algorithms have similar performance and that data screening and quality flagging of the retrievals markedly affects the performance. The NASA Soil Moisture Active Passive (SMAP) mission produces a similar SM product as SMOS using an L-band radiometer. The closeness of the ubRMSE, R, and anomaly R performance of the IC product and the SMAP product (0.039 m 3 /m 3 vs. 0.041 m 3 /m 3 , 0.80 vs. 0.81, and 0.75 vs. 0.75) demonstrate that the SMOS and SMAP radiometers can achieve similar SM sensitivity

An assessment of the differences between spatial resolution and grid size for the SMAP enhanced soil moisture product over homogeneous sites

Satellite-based passive microwave remote sensing typically involves a scanning antenna that makes measurements at irregularly spaced locations. These locations can change on a day to day basis. Soil moisture products derived from satellite-based passive microwave remote sensing are usually resampled to a fixed Earth grid that facilitates their use in applications. In many cases the grid size is finer than the actual spatial resolution of the observation, and often this difference is not well understood by the user. Here, this issue was examined for the Soil Moisture Active Passive (SMAP) enhanced version of the passive-based soil moisture product, which has a grid size of 9-km and a nominal spatial resolution of 33-km. In situ observations from core validation sites were used to compute comparison metrics. For sites that satisfied the established reliability and scaling criteria, the impact of validating the 9-km grid product with in situ data collected over a 9-km versus a 33-km domain was very small for the sites studied (0.039 m3/m3 unbiased root mean square difference for the 9-km case versus 0.037 m3/m3 for the 33-km case). This result does not mean that the resolution of the product is 9-km but that for the conditions studied here the soil moisture estimated from in situ observations over 9-km is a close approximation of the soil moisture estimated from in situ observations over the 33-km resolution. The implication is that using the enhanced SMAP product at its grid resolution of 9-km should not introduce large errors in most applications