The first simultaneous electric field observations performed in the ionosphere and atmosphere over an active nighttime thunderstorm are reported here. In the stratosphere, typical storm‐related dc electric fields were detected from a horizontal distance of ∼100 km, and transient electric fields due to lightning were measured at several different altitudes. In the ionosphere and mesosphere, lightning‐induced transient electric fields in the range of tens of millivolts per meter were detected with rise times at least as fast as 0.2 ms and typical duration of 10–20 ms. The transients had significant components parallel to the magnetic field at 150 km altitude. This implies that either considerable Joule heating occurs or a collective instability is present because of the high drift velocities induced by the transient electric fields. Copious numbers of whistlers were genrated by the storm and were detected above but not below the base of the ionosphere. We present here the outline of a new model for direct whistler wave generation over an active thunderstorm based on these observations. The intensity of the observed two‐hop whistlers implies that they were amplified along their propagation path and suggests that particles were precipitated in both hemispheres.

This paper describes measurements of the dielectric constant of seawater at a frequency of 1.413 GHz, the center of the protected band (i.e., passive use only) used in the measurement of sea surface salinity from space. The objective of the measurements is to accurately determine the complex dielectric constant of seawater as a function of salinity and temperature. A resonant cylindrical microwave cavity in transmission mode has been employed to make the measurements. The measurements are made using standard seawater at salinities of 30, 33, 35, and 38 practical salinity units over a range of temperatures from 0°C to 35°C in 5°C intervals. Repeated measurements have been made at each temperature and salinity. Mean values and standard deviations are then computed. The total error budget indicates that the real and imaginary parts of the dielectric constant have a combined standard uncertainty of about 0.3 over the range of salinities and temperatures considered. The measurements are compared with the dielectric constants obtained from the model functions of Klein and Swift and those of Meissner and Wentz. The biggest differences occur at low and high temperatures.

A solution has been obtained for s, ,ring from thin dielectric disks by approximating the currents induced inside the disk with the currents which would exist inside a dielectric slab of the same thickness, orientation and dielectric properties. This approximation reduces to an electrostatic approximation when the disk thickness, T, is small compared to the wavelength of the incident radiation and the approximation yields a conventional physical optics solution when the dimension, A. characteristic of the geometrical cross section of the disk (e.g. the diameter of a circular disk) is large compared to wavelength. When the ratio A/T is sut'ficiently large t hc disk will always be in one or the other of these reg;mes (Tc cX or k A > > 1). Consequently, when A/T is large this solution provides a conventional approximation for the scattered fields which can be applied at all fre-, quencies. As a check on this conclusion, a comparison has bfxn made between the theoretical and measured radar cross section of thin dielectric disks. Agreement was found for thin disks with both large and small values of kA. PXECI-,DZ' T+<: PACE ELANIC NOT m i T . S D

Abstract-This paper gives an overview of the algorithm for retrieving sea surface salinity from the AQUARIUS L-band radiometer and its physical background.Keywords-Aquarius, Sea surface salinity, L-band radiometers, sea surface roughness. I. BACKGROUNDThe Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to an accuracy of 0.2 psu [1]. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. II. OVERVIEW OF THE AQUARIUS LEVEL 2 PROCESSINGThis section gives an overview over the Aquarius salinity retrieval algorithm.The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface and sea surface salinity (SSS). As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at Lband is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models (e.g. NCEP) and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section III.The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step. III. MODEL FOR THE EMISSION OF WIND ROUGHENED OCEAN SURFACE AT L-BANDOne of the major error sources in the Aquarius salinity retrieval is the change in the ocean surface emissivity due to roughening by wind. A model for the wind induced emissivity has been developed post-launch based on actual Aquarius observations. As a first step, Aquarius brightness surface brightness temperatures were collocated with surface wind speed and wind direction measurements from NCEP, SSMIS F17 and WindSat, from https://ntrs.nasa.gov/search.jsp?R=20120009347 2018-05-09T20:08:50+00:00Z A. Wind Speed Dependence

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