Changes in global net radiative imbalance 1985-2012

Combining satellite data, atmospheric reanalyses and climate model simulations, variability in the net downward radiative flux imbalance at the top of Earth's atmosphere (N) is reconstructed and linked to recent climate change. Over the 1985-1999 period mean N (0.34 ± 0.67 Wm–2) is lower than for the 2000-2012 period (0.62 ± 0.43 Wm–2, uncertainties at 90% confidence level) despite the slower rate of surface temperature rise since 2000. While the precise magnitude of N remains uncertain, the reconstruction captures interannual variability which is dominated by the eruption of Mt. Pinatubo in 1991 and the El Niño Southern Oscillation. Monthly deseasonalized interannual variability in N generated by an ensemble of 9 climate model simulations using prescribed sea surface temperature and radiative forcings and from the satellite-based reconstruction is significantly correlated (r ∼ 0.6) over the 1985-2012 period.

Immunolocalization of estrogen and progesterone receptors in neuroendocrine tumors of lung, skin, gastrointestinal and female genital tracts

Expression of estrogen (ER) and progesterone (PR) receptors has traditionally been associated with hormone-responsive organs, such as breast, ovary, and endometrium, and carcinomas arising therefrom. More recently, examples of ''unexpected'' ER or PR expression have been reported, particularly in tumors of endocrine tissues, such as thyroid and pancreatic islet cells. We tested the hypothesis that neuroendocrine tumors of various primary and metastatic sites might also express ER or PR or both by performing a retrospective immunohistochemical study in a series of 59 formalin- or mechacarn-fixed neuroendocrine carcinomas of various sites, including lung, skin, gastrointestinal and female genital tracts, and including carcinoid and atypical carcinoid tumors, small cell carcinomas, and Merkel cell carcinomas. We employed the anti-ER monoclonal antibody 1D5 and the anti-PR monoclonal antibody PgR1A6 using standard immunohistochemical techniques after microwave-based heat-induced epitope retrieval. Two of 28 carcinoid tumors demonstrated ER positivity; six of 30 cases were positive for progesterone receptor only. In addition, PR expression was found in one of two cases of atypical carcinoid, in five of 25 cases of small cell carcinoma, and in one of two cases of Merkel cell carcinoma. None of the atypical carcinoids, small cell carcinomas, or Merkel cell carcinomas were ER positive. In most cases, the fraction of tumor cell nuclei that were positive was <50%. These studies add the spectrum of neuroendocrine tumors that can express these hormone receptors. Similar to the pattern previously described in the subsets of meningiomas and islet cell tumors, PR but not ER is detectable in most cases. These results underscore the caution that should be exercised in determining tissue origin of metastatic carcinomas based only on detection of hormone receptors by immunohistochemistry.

The evolution of massive clumps in star forming regions

In this thesis two related arguments are investigated: - The first stages of the process of massive star formation, investigating the physical conditions and -properties of massive clumps in different evolutionary stages, and their CO depletion; - The influence that high-mass stars have on the nearby material and on the activity of star formation. I characterise the gas and dust temperature, mass and density of a sample of massive clumps, and analyse the variation of these properties from quiescent clumps, without any sign of active star formation, to clumps likely hosting a zero-age main sequence star. I briefly discuss CO depletion and recent observations of several molecular species, tracers of Hot Cores and/or shocked gas, of a subsample of these clumps. The issue of CO depletion is addressed in more detail in a larger sample consisting of the brightest sources in the ATLASGAL survey: using a radiative tranfer code I investigate how the depletion changes from dark clouds to more evolved objects, and compare its evolution to what happens in the low-mass regime. Finally, I derive the physical properties of the molecular gas in the photon-dominated region adjacent to the HII region G353.2+0.9 in the vicinity of Pismis 24, a young, massive cluster, containing some of the most massive and hottest stars known in our Galaxy. I derive the IMF of the cluster and study the star formation activity in its surroundings. Much of the data analysis is done with a Bayesian approach. Therefore, a separate chapter is dedicated to the concepts of Bayesian statistics.

Evaluation of simulated sea-ice concentrations from sea-ice/ocean models using satellite data and polynya classification methods

Sea-ice concentrations in the Laptev Sea simulated by the coupled North Atlantic-Arctic Ocean-Sea-Ice Model and Finite Element Sea-Ice Ocean Model are evaluated using sea-ice concentrations from Advanced Microwave Scanning Radiometer-Earth Observing System satellite data and a polynya classification method for winter 2007/08. While developed to simulate largescale sea-ice conditions, both models are analysed here in terms of polynya simulation. The main modification of both models in this study is the implementation of a landfast-ice mask. Simulated sea-ice fields from different model runs are compared with emphasis placed on the impact of this prescribed landfast-ice mask. We demonstrate that sea-ice models are not able to simulate flaw polynyas realistically when used without fast-ice description. Our investigations indicate that without landfast ice and with coarse horizontal resolution the models overestimate the fraction of open water in the polynya. This is not because a realistic polynya appears but due to a larger-scale reduction of ice concentrations and smoothed ice-concentration fields. After implementation of a landfast-ice mask, the polynya location is realistically simulated but the total open-water area is still overestimated in most cases. The study shows that the fast-ice parameterization is essential for model improvements. However, further improvements are necessary in order to progress from the simulation of large-scale features in the Arctic towards a more detailed simulation of smaller-scaled features (here polynyas) in an Arctic shelf sea.

Impact of a Fram Strait cyclone on ice edge, drift, divergence, and concentration: Possibilities and limits of an observational analysis

This study aims at the determination of a Fram Strait cyclone track and of the cyclone’s impact on ice edge, drift, divergence, and concentration. A 24 h period on 13–14 March 2002 framed by two RADARSAT images is analyzed. Data are included from autonomous ice buoys, a research vessel, Special Sensor Microwave Imager (SSM/I) and QuikSCAT satellite, and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) model. During this 24 h period the cyclone moved northward along the western ice edge in the Fram Strait, crossed the northern ice edge, made a left-turn loop with 150 km diameter over the sea ice, and returned to the northern ice edge. The ECMWF analysis places the cyclone track 100 km too far west over the sea ice, a deviation which is too large for representative sea ice simulations. On the east side of the northward moving cyclone, the ice edge was pushed northward by 55 km because of strong winds. On the rear side, the ice edge advanced toward the open water but by a smaller distance because of weaker winds there. The ice drift pattern as calculated from the ice buoys and the two RADARSAT images is cyclonically curved around the center of the cyclone loop. Ice drift divergence shows a spatial pattern with divergence in the loop center and a zone of convergence around. Ice concentration changes as retrieved from SSM/I data follow the divergence pattern such that sea ice concentration increased in areas of divergence and decreased in areas of convergence.

Design methodologies of microwawe integrated circuits for satellite telecommunications

The running innovation processes of the microwave transistor technologies, used in the implementation of microwave circuits, have to be supported by the study and development of proper design methodologies which, depending on the applications, will fully exploit the technology potentialities. After the choice of the technology to be used in the particular application, the circuit designer has few degrees of freedom when carrying out his design; in the most cases, due to the technological constrains, all the foundries develop and provide customized processes optimized for a specific performance such as power, low-noise, linearity, broadband etc. For these reasons circuit design is always a “compromise”, an investigation for the best solution to reach a trade off between the desired performances. This approach becomes crucial in the design of microwave systems to be used in satellite applications; the tight space constraints impose to reach the best performances under proper electrical and thermal de-rated conditions, respect to the maximum ratings provided by the used technology, in order to ensure adequate levels of reliability. In particular this work is about one of the most critical components in the front-end of a satellite antenna, the High Power Amplifier (HPA). The HPA is the main power dissipation source and so the element which mostly engrave on space, weight and cost of telecommunication apparatus; it is clear from the above reasons that design strategies addressing optimization of power density, efficiency and reliability are of major concern. Many transactions and publications demonstrate different methods for the design of power amplifiers, highlighting the availability to obtain very good levels of output power, efficiency and gain. Starting from existing knowledge, the target of the research activities summarized in this dissertation was to develop a design methodology capable optimize power amplifier performances complying all the constraints imposed by the space applications, tacking into account the thermal behaviour in the same manner of the power and the efficiency. After a reminder of the existing theories about the power amplifier design, in the first section of this work, the effectiveness of the methodology based on the accurate control of the dynamic Load Line and her shaping will be described, explaining all steps in the design of two different kinds of high power amplifiers. Considering the trade-off between the main performances and reliability issues as the target of the design activity, we will demonstrate that the expected results could be obtained working on the characteristics of the Load Line at the intrinsic terminals of the selected active device. The methodology proposed in this first part is based on the assumption that designer has the availability of an accurate electrical model of the device; the variety of publications about this argument demonstrates that it is so difficult to carry out a CAD model capable to taking into account all the non-ideal phenomena which occur when the amplifier operates at such high frequency and power levels. For that, especially for the emerging technology of Gallium Nitride (GaN), in the second section a new approach for power amplifier design will be described, basing on the experimental characterization of the intrinsic Load Line by means of a low frequency high power measurements bench. Thanks to the possibility to develop my Ph.D. in an academic spin-off, MEC – Microwave Electronics for Communications, the results of this activity has been applied to important research programs requested by space agencies, with the aim support the technological transfer from universities to industrial world and to promote a science-based entrepreneurship. For these reasons the proposed design methodology will be explained basing on many experimental results.

The quasi 16-day wave in mesospheric water vapor during boreal winter 2011/2012

This study investigates the characteristics of the quasi 16-day wave in the mesosphere during boreal winter 2011/2012 using observations of water vapor from ground-based microwave radiometers and satellite data. The ground-based microwave radiometers are located in Seoul (South Korea, 37° N), Bern (Switzerland, 47° N) and Sodankylä (Finland, 67° N). The quasi 16-day wave is observed in the mesosphere at all three locations, while the dominant period increases with latitude from 15 days at Seoul to 20 days at Sodankylä. The observed evolution of the quasi 16-day wave confirms that the wave activity is strongly decreased during a sudden stratospheric warming that occurred in mid-January 2012. Using satellite data from the Microwave Limb Sounder on the Aura satellite, we examine the zonal characteristics of the quasi 16-day wave and conclude that the observed waves above the mid-latitudinal stations Seoul and Bern are eastward-propagating s=−1 planetary waves with periods of 15 to 16 days, while the observed oscillation above the polar station Sodankylä is a standing oscillation with a period of approximately 20 days. The strongest relative wave amplitudes in water vapor during the investigated time period are approximately 15%. The wave activity varies strongly along a latitude circle. The activity of the quasi 16-day wave in mesospheric water vapor during boreal winter 2011/2012 is strongest over Northern Europe, the North Atlantic ocean and North-West Canada. The region of highest wave activity seems to be related to the position of the polar vortex. We conclude that the classic approach to characterize planetary waves zonally averaged along a latitude circle is not sufficient to explain the local observations because of the strong longitudinal dependence of the wave activity.

The quasi 16-day wave in mesospheric water vapor during boreal winter 2011/2012

This study investigates the characteristics of the quasi 16-day wave in the mesosphere during boreal winter 2011/2012 using observations of water vapor from ground-based microwave radiometers and satellite data. The ground-based microwave radiometers are located in Seoul (South Korea, 37° N), Bern (Switzerland, 47° N) and Sodankylä (Finland, 67° N). The quasi 16-day wave is observed in the mesosphere at all three locations, while the dominant period increases with latitude from 15 days at Seoul to 20 days at Sodankylä. The observed evolution of the quasi 16-day wave confirms that the wave activity is strongly decreased during a sudden stratospheric warming that occurred in mid-January 2012. Using satellite data from the Microwave Limb Sounder on the Aura satellite, we examine the zonal characteristics of the quasi 16-day wave and conclude that the observed waves above the midlatitudinal stations Seoul and Bern are eastward-propagating s = −1 planetary waves with periods of 15 to 16 days, while the observed oscillation above the polar station Sodankylä is a standing wave with a period of approximately 20 days. The strongest relative wave amplitudes in water vapor during the investigated time period are approximately 15%. The wave activity varies strongly along a latitude circle. The activity of the quasi 16-day wave in mesospheric water vapor during boreal winter 2011/2012 is strongest over northern Europe, the North Atlantic Ocean and northwestern Canada. The region of highest wave activity seems to be related to the position of the polar vortex. We conclude that the classic approach to characterize planetary waves zonally averaged along a latitude circle is not sufficient to explain the local observations because of the strong longitudinal dependence of the wave activity.

Precipitation and latent heating distributions from satellite passive microwave radiometry. Part I: improved method and uncertainties

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

Global oceanic precipitation: A joint view by TOPEX and the TOPEX microwave radiometer

The TOPEX/POSEIDON mission offers the first opportunity to observe rain cells over the ocean by a dual-frequency radar altimeter (TOPEX) and simultaneously observe their natural radiative properties by a three-frequency radiometer (TOPEX microwave radiometer (TMR)). This work is a feasibility study aimed at understanding the capability and potential of the active/passive TOPEX/TMR system for oceanic rainfall detection. On the basis of past experiences in rain flagging, a joint TOPEX/TMR rain probability index is proposed. This index integrates several advantages of the two sensors and provides a more reliable rain estimate than the radiometer alone. One year's TOPEX/TMR TMR data are used to test the performance of the index. The resulting rain frequency statistics show quantitative agreement with those obtained from the Comprehensive Ocean-Atmosphere Data Set (COADS) in the Intertropical Convergence Zone (ITCZ), while qualitative agreement is found for other regions of the world ocean. A recent finding that the latitudinal frequency of precipitation over the Southern Ocean increases steadily toward the Antarctic continent is confirmed by our result. Annual and seasonal precipitation maps are derived from the index. Notable features revealed include an overall similarity in rainfall pattern from the Pacific, the Atlantic, and the Indian Oceans and a general phase reversal between the two hemispheres, as well as a number of regional anomalies in terms of rain intensity. Comparisons with simultaneous Global Precipitation Climatology Project (GPCP) multisatellite precipitation rate and COADS rain climatology suggest that systematic differences also exist. One example is that the maximum rainfall in the ITCZ of the Indian Ocean appears to be more intensive and concentrated in our result compared to that of the GPCP. Another example is that the annual precipitation produced by TOPEX/TMR is constantly higher than those from GPCP and COADS in the extratropical regions of the northern hemisphere, especially in the northwest Pacific Ocean. Analyses of the seasonal variations of prominent rainy and dry zones in the tropics and subtropics show various behaviors such as systematic migration, expansion and contraction, merging and breakup, and pure intensity variations, The seasonality of regional features is largely influenced by local atmospheric events such as monsoon, storm, or snow activities. The results of this study suggest that TOPEX and its follow-on may serve as a complementary sensor to the special sensor microwave/imager in observing global oceanic precipitation.

Microwave Resonant and Zero-Field Absorption Study of Doped Magnetite Prepared by a Co-Precipitation Method

Fe3O4 and ZnxFe3-xO4 pure and doped magnetite magnetic nanoparticles (NPs) were prepared in aqueous solution (Series A) or in a water-ethyl alcohol mixture (Series B) by the co-precipitation method. Only one ferromagnetic resonance line was observed in all cases under consideration indicating that the materials are magnetically uniform. The shortfall in the resonance fields from 3.27 kOe (for the frequency of 9.5 GHz) expected for spheres can be understood taking into account the dipolar forces, magnetoelasticity, or magnetocrystalline anisotropy. All samples show non-zero low field absorption. For Series A samples the grain size decreases with an increase of the Zn content. In this case zero field absorption does not correlate with the changes of the grain size. For Series B samples the grain size and zero field absorption behavior correlate with each other. The highest zero-field absorption corresponded to 0.2 zinc concentration in both A and B series. High zero-field absorption of Fe3O4 ferrite magnetic NPs can be interesting for biomedical applications.

A stochastic model of temporal variations in monthly temperature, precipitation, snowfall, and resulting snowpack

We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

How robust are observed and simulated precipitation responses to tropical ocean warming?

Robust responses and links between the tropical energy and water cycles are investigated using multiple datasets and climate models over the period 1979-2006. Atmospheric moisture and net radiative cooling provide powerful constraints upon future changes in precipitation. While moisture amount is robustly linked with surface temperature, the response of atmospheric net radiative cooling, derived from satellite data, is less coherent. Precipitation trends and relationships with surface temperature are highly sensitive to the data product and the time-period considered. Data from the Special Sensor Microwave Imager (SSM/I) produces the strongest trends in precipitation and response to warming of all the datasets considered. The tendency for moist regions to become wetter while dry regions become drier in response to warming is captured by both observations and models. Citation: John, V. O., R. P. Allan, and B. J. Soden (2009), How robust are observed and simulated precipitation responses to tropical ocean warming?

Monitoring changes in precipitation and radiative energy using satellite data and climate models

Current changes in the tropical hydrological cycle, including water vapour and precipitation, are presented over the period 1979-2008 based on a diverse suite of observational datasets and atmosphere-only climate models. Models capture the observed variability in tropical moisture while reanalyses cannot. Observed variability in precipitation is highly dependent upon the satellite instruments employed and only cursory agreement with model simulations, primarily relating to the interannual variability associated with the El Niño Southern Oscillation. All datasets display a positive relationship between precipitation and surface temperature but with a large spread. The tendency for wet, ascending regions to become wetter at the expense of dry, descending regimes is in general reproduced. Finally, the frequency of extreme precipitation is shown to rise with warming in the observations and for the model ensemble mean but with large spread in the model simulations. The influence of the Earth’s radiative energy balance in relation to changes in the tropical water cycle are discussed

Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations

A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate.