Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, the simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and –35°C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient. The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to –1.8 W m^−2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed

Observation of Ultra-high-energy Cosmic Rays with the ANITA Balloon-borne Radio Interferometer

We report the observation of sixteen cosmic ray events of mean energy of 1.5 x 10^{19} eV, via radio pulses originating from the interaction of the cosmic ray air shower with the Antarctic geomagnetic field, a process known as geosynchrotron emission. We present the first ultra-wideband, far-field measurements of the radio spectral density of geosynchrotron emission in the range from 300-1000 MHz. The emission is 100% linearly polarized in the plane perpendicular to the projected geomagnetic field. Fourteen of our observed events are seen to have a phase-inversion due to reflection of the radio beam off the ice surface, and two additional events are seen directly from above the horizon.Comment: 5 pages, 5 figures, new figure adde

The microwave emissivity variability of snow covered first-year sea ice from late winter to early summer: a model study

Satellite observations of microwave brightness temperatures between 19 GHz and 85 GHz are the main data sources for operational sea-ice monitoring and retrieval of ice concentrations. However, microwave brightness temperatures depend on the emissivity of snow and ice, which is subject to pronounced seasonal variations and shows significant hemispheric contrasts. These mainly arise from differences in the rate and strength of snow metamorphism and melt. We here use the thermodynamic snow model SNTHERM forced by European Re-Analysis (ERA) interim data and the Microwave Emission Model of Layered Snowpacks (MEMLS), to calculate the sea-ice surface emissivity and to identify the contribution of regional patterns in atmospheric conditions to its variability in the Arctic and Antarctic. The computed emissivities reveal a pronounced seasonal cycle with large regional variability. The emissivity variability increases from winter to early summer and is more pronounced in the Antarctic. In the pre-melt period (January–May, July–November) the standard deviations in surface microwave emissivity due to diurnal, regional and inter-annual variability of atmospheric forcing reach up to Δε = 0.034, 0.043, and 0.097 for 19 GHz, 37 GHz and 85 GHz channels, respectively. Between 2000 and 2009, small but significant positive emissivity trends were observed in the Weddell Sea during November and December as well as in Fram Strait during February, potentially related to earlier melt onset in these regions. The obtained results contribute to a better understanding of the uncertainty and variability of sea-ice concentration and snow-depth retrievals in regions of high sea-ice concentrations

Convective and stratiform rain: Multichannel microwave sensing over oceans

Measurements made by the Special Sensor Microwave/Imager (SSM/I) radiometer over the oceans, at 19, 37, and 85 GHz in dual polarization, are used to develop a model to classify rain into light-stratiform, moderately convective, and heavy convective types in the mesoscale convective systems (MCS). It is observed that the bulk of the 19- and 37-GHz data are linearly correlated with respect to one another, and generally increase together in brightness as the mean rain rate in the field of view (FOV) of the radiometer increases. However, a significant fraction of the data from these channels departs from this linear relationship, reflecting the nonuniform rain that is convective vs. the relatively light stratiform rain. It is inferred from the SSM/I data, in a MCS, when the slope dT sub 3/dT sub 19 is greater than unity there are optically thin clouds which produce light uniform rain. On the other hand, when dT sub 3/dT sub 19 is close to unity, the rain cells have an open structure and correspond to the convective type of rain. The openings between the cells are apparently a result of the downdrafts and/or entrainment. Relatively low values of 85-GHz brightness temperatures that are present when dT sub 37/dT sub 19 is close to unity support these views and, in addition, leads us to conclude that when the convection is heavy this brightness temperature decreases due to scattering by hydrometeors. On the basis of this explanation of the SSM/I data, an empirical rain retrieval algorithm is developed. Radar backscatter observations over the Atlantic Ocean next to Florida are used to demonstrate the applicability of this method. Three monthly mean maps of rainfall over the oceans from 50 degrees N to 50 degrees S, are presented to illustrate the ability of this method to sense seasonal and interannual variations of rain

In Search for Extraterrestrial High Energy Neutrinos

In this paper we review the search for astrophysical neutrinos. We begin by summarizing the various theoretical predictions which correlate the expected neutrino flux with data from other messengers, specifically gammas and ultra-high energy cosmic rays. We then review the status and results of neutrino telescopes in operation and decommissioned, the methods used for data analysis and background discrimination. Particular attention is devoted to the challenge enforced by the highly uncertain atmospheric muon and neutrino backgrounds in relation to searches of diffuse neutrino fluxes. Next, we examine the impact of existing limits on neutrino fluxes on studies of the chemical composition of cosmic rays. After that, we show that not only do neutrinos have the potential to discover astrophysical sources, but the huge statistics of atmospheric muons can be a powerful tool as well. We end by discussing the prospects for indirect detection of dark matter with neutrino telescopes.Comment: Solicited Review Article submitted to Annual Review of Nuclear and Particle Science; 50 pages and 15 figures; the review is limited to 150 references, so many of them have been grouped. See http://www.icecube.wisc.edu/~tmontaruli/review for errata and other feature

Potential of millimeter- and submillimeter-wave satellite observations for hydrometeor studies

The distribution of hydrometeors is highly variable in space and time, since it is the result of a complex chain of processes with scales from microphysical (1e-6 m) to synoptical (1e3 m). It is a challenging task to observe these highly variable atmospheric constituents on a global scale with a temporal and spatial resolution sufficient for numerical weather prediction (NWP) and hydrological purposes. This study investigates the potential of the millimeter- and submillimeter-wavelength range on space-borne sensors for hydrometeor and surface precipitation rate observations. The approach is based on simulations with cloud resolving models (CRMs) coupled to a radiative transfer (RT) model. The simulations are performed for mid-latitude cases covering a broad band of precipitation events such as heavy convective and light stratiform winter precipitation. Realistic atmospheric conditions were simulated with two mesoscale CRMs: the Meso-scale NonHydrostatic model (Meso-NH) on a 10 km and the COSMO-DE (COnsortium for Small-scale MOdeling-DEutschland) on a 2.8 km horizontal resolution. When calculating brightness temperatures for satellite observations with the one-dimensional radiative transfer model MWMOD (MicroWave MODel), the detailed cloud microphysics and the three-dimensional fields of temperature, humidity, and pressure of the CRMs are considered in the calculation of the interaction parameters. The model framework has been evaluated by comparing the simulated brightness temperature fields to observations of the Special Sensor Microwave Imager (SSM/I) as well as to those of the Advanced Microwave Sounding Unit-B (AMSU-B). The results show a good agreement as long as the CRMs capture the atmospheric situation correctly. Consequently, by coupling the radiative transfer model for microwave radiation to CRMs it is possible to evaluate these models through comparison to microwave satellite observations. Brightness temperatures for frequencies between 50 and 428 GHz at nine observation angles have been simulated for five mid-latitude cases at two time steps. In combination with the vertically integrated hydrometeor contents, these brightness temperature simulations have been used to set up a database. On the basis of this database simple retrieval algorithms have been developed to estimate the potential of the millimeter- and submillimeter-wavelength region for precipitation and hydrometeor observations. The results show, that especially for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 20% in stratiform precipitation cases over land and ocean surfaces. The performance for rain water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain water path are larger especially over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain water path. Algorithms with a reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval. These are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size

Performance assessment of time–frequency RFI mitigation techniques in microwave radiometry

©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio–frequency interference (RFI) signals are a well-known threat for microwave radiometry (MWR) applications. In order to alleviate this problem, different approaches for RFI detection and mitigation are currently under development. Since RFI signals are man made, they tend to have their power more concentrated in the time–frequency (TF) space as compared to naturally emitted noise. The aim of this paper is to perform an assessment of different TF RFI mitigation techniques in terms of probability of detection, resolution loss (RL), and mitigation performance. In this assessment, six different kinds of RFI signals have been considered: a glitch, a burst of pulses, a wide-band chirp, a narrow-band chirp, a continuous wave, and a wide-band modulation. The results show that the best performance occurs when the transform basis has a similar shape as compared to the RFI signal. For the best case performance, the maximum residual RFI temperature is 14.8 K, and the worst RL is 8.4%. Moreover, the multiresolution Fourier transform technique appears as a good tradeoff solution among all other techniques since it can mitigate all RFI signals under evaluation with a maximum residual RFI temperature of 21 K, and a worst RL of 26.3%. Although the obtained results are still far from an acceptable bias Misplaced < 1 K for MWR applications, there is still work to do in a combined test using the information gathered simultaneously by all mitigation techniques, which could improve the overall performance of RFI mitigation.Peer ReviewedPostprint (author's final draft

Insights on past and future sea-ice evolution from combining observations and models

We discuss the current understanding of past and future sea-ice evolution as inferred from combining model simulations and observations. In such combined analysis, the models allow us to enhance our understanding behind the observed evolution of sea ice, while the observations allow us to assess how realistically the models represent the processes that govern sea-ice evolution in the real world. Combined, observations and models thus provide robust insights into the functioning of sea ice in the Earth's climate system, and can inform policy decisions related to the future evolution of the ice cover. We find that models and observations agree well on the sensitivity of Arctic sea ice to global warming and on the main drivers for the observed retreat. In contrast, a robust reduction of the uncertainty range of future sea-ice evolution remains difficult, in particular since the observational record is often too short to robustly examine the impact of internal variability on model biases. Process-based model evaluation and model evaluation based on seasonal-prediction systems provide promising ways to overcome these limitations