Eastern Pacific Emitted Aerosol Cloud Experiment

Aerosol–cloud–radiation interactions are widely held to be the largest single source of uncertainty in climate model projections of future radiative forcing due to increasing anthropogenic emissions. The underlying causes of this uncertainty among modeled predictions of climate are the gaps in our fundamental understanding of cloud processes. There has been significant progress with both observations and models in addressing these important questions but quantifying them correctly is nontrivial, thus limiting our ability to represent them in global climate models. The Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE) 2011 was a targeted aircraft campaign with embedded modeling studies, using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft and the research vessel Point Sur in July and August 2011 off the central coast of California, with a full payload of instruments to measure particle and cloud number, mass, composition, and water uptake distributions. EPEACE used three emitted particle sources to separate particle-induced feedbacks from dynamical variability, namely 1) shipboard smoke-generated particles with 0.05–1-μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke), 2) combustion particles from container ships with 0.05–0.2-μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components), and 3) aircraft-based milled salt particles with 3–5-μm diameters (which showed enhanced drizzle rates in some clouds). The aircraft observations were consistent with past large-eddy simulations of deeper clouds in ship tracks and aerosol– cloud parcel modeling of cloud drop number and composition, providing quantitative constraints on aerosol effects on warm-cloud microphysics

High-Spatial-Resolution Position-Sensitive Plastic Scintillation Optical Fiber Bundle Detector

We fabricated a 5 m long position-sensitive plastic scintillation optical fiber (PSOF) bundle detector composed of a sensing probe, two photomultiplier tubes (PMTs), two fast amplifiers, and a digitizer. Seven PSOFs in a bundle were used as sensing probes to estimate the gamma-ray source position, and 60Co, an uncollimated solid-disc-type radioactive isotope, was used as a gamma-ray emitter. To improve on the spatial resolution of previous studies, the transit time spread (TTS) was reduced by using a high-timing-response PMT and a bundle type of multi-cladded PSOFs. Noise was filtered out of the data. In addition, the accuracy of the data was improved through cubic spline interpolation. We determined the measurement time and measured the full width at half maximum (FWHM) considering the spatial resolution. We obtained the best spatial resolution—compared to the results of earlier studies—using our proposed bundle detector. Moreover, the sensitivity of the PSOF bundle detector was evaluated at several positions in the sensing probe. Based on the results of this study, a position-sensitive PSOF bundle detector could be used to measure gamma-ray source positions accurately over a wide contaminated area and in a shorter period of time

Interpretations of systematic errors in the NCEP Climate Forecast System at lead times of 2, 4, 8, ..., 256 days

The climatology of mean bias errors (relative to 1-day forecasts) was examined in a 20-year hindcast set from version 1 of the Climate Forecast System (CFS), for forecast lead times of 2, 4, 8, 16, ... 256 days, verifying in different seasons. Results mostly confirm the simple expectation that atmospheric model biases should be evident at short lead (2–4 days), while soil moisture errors develop over days-weeks and ocean errors emerge over months. A further simplification is also evident: surface temperature bias patterns have nearly fixed geographical structure, growing with different time scales over land and ocean. The geographical pattern has mostly warm and dry biases over land and cool bias over the oceans, with two main exceptions: (1) deficient stratocumulus clouds cause warm biases in eastern subtropical oceans, and (2) high latitude land is too cold in boreal winter. Further study of the east Pacific cold tongue-Intertropical Convergence Zone (ITCZ) complex shows a possible interaction between a rapidly-expressed atmospheric model bias (poleward shift of deep convection beginning at day 2) and slow ocean dynamics (erroneously cold upwelling along the equator in leads > 1 month). Further study of the high latitude land cold bias shows that it is a thermal wind balance aspect of the deep polar vortex, not just a near-surface temperature error under the wintertime inversion, suggesting that its development time scale of weeks to months may involve long timescale processes in the atmosphere, not necessarily in the land model. Winter zonal wind errors are small in magnitude, but a refractive index map shows that this can cause modest errors in Rossby wave ducting. Finally, as a counterpoint to our initial expectations about error growth, a case of non-monotonic error growth is shown: velocity potential bias grows with lead on a time scale of weeks, then decays over months. It is hypothesized that compensations between land and ocean errors may cause this behavior

Estimating Convection’s Moisture Sensitivity: An Observation–Model Synthesis Using AMIE-DYNAMO Field Data

Abstract We seek to use ARM MJO Investigation Experiment (AMIE)-DYNAMO field campaign observations to significantly constrain height-resolved estimates of the parameterization-relevant, causal sensitivity of convective heating Q to water vapor q. In field data, Q profiles are detected via Doppler radar wind divergence D while balloon soundings give q. Univariate regressions of D on q summarize the information from a 10-layer time–pressure series from Gan Island (0°, 90°E) as a 10 × 10 matrix. Despite the right shape and units, this is not the desired causal quantity because observations reflect confounding effects of additional q-correlated casual mechanisms. We seek to use this matrix to adjudicate among candidate estimates of the desired causal quantity: Kuang’s matrix of the linear responses of a cyclic convection-permitting model (CCPM) at equilibrium. Transforming to more observation-comparable forms by accounting for observed autocorrelations, the comparisons are still poor, because (we hypothesize) larger-scale vertical velocity, forbidden by CCPM methodology, is another confounding cause that must be permitted to covary with q. By embedding and modified candidates in an idealized GCM, and treating its outputs as virtual field campaign data, we find that observations favor a factor of 2 (rather than 0 or 1) to small-domain ’s free-tropospheric causal q sensitivity of about 25% rain-rate increment over 3 subsequent hours per +1 g kg−1 q impulse in a 100-hPa layer. Doubling this sensitivity lies partway toward Kuang’s for a long domain that organizes convection into squall lines, a weak but sign-consistent hint of a detectable parameterization-relevant (causal) role for convective organization in nature. Caveats and implications for field campaign proposers are discussed

Tangent linear superparameterization of convection in a 10 layer global atmosphere with calibrated climatology

This paper describes a new intermediate global atmosphere model in which synoptic and planetary dynamics including the advection of water vapor are explicit in 10 layers, the time‐mean flow is centered near a realistic state through the use of carefully calibrated time‐independent 3‐D forcings, and temporal anomalies of convective tendencies of heat and moisture in each column are represented as a linear matrix acting on the anomalous temperature and moisture profiles. Currently, this matrix is Kuang's [] linear response function (LRF) of a cyclic convection‐permitting model (CCPM) in equilibrium with specified atmospheric cooling (i.e., without radiation or WISHE interactions, so it conserves column moist static energy exactly). The goal of this effort is to cleanly test the role of convection's free‐tropospheric moisture sensitivity in tropical waves, without incurring large changes of mean climate that confuse the interpretation of experiments with entrainment parameters in the convection schemes of full‐physics GCMs. When the sensitivity to free‐tropospheric moisture is multiplied by a factor ranging from 0 to 2, the model's variability ranges from: (1) moderately strong convectively coupled Kelvin waves with speeds near 20 m s−1; to (0) similar but much weaker waves; to (2) similar but stronger and slightly faster waves as the water vapor field plays an increasingly important role. Longitudinal structure in the model's time‐mean tropical flow is not fully realistic, and does change significantly with matrix‐coupled variability, but further work on editing the anomaly physics matrix and calibrating the mean state could improve this class of models. Key Points A new intermediate global atmosphere model with tangent linear superparameterization of convection coupled to realistic 3‐D flow is described Increasing the free‐tropospheric moisture sensitivity in the matrix‐coupled model increases the amplitude of wave variability Despite strict linearity of the matrix, rectified time‐mean effects emerge in the GCM due to the coupling to nonlinear atmospheric dynamic

Monte Carlo simulations for gamma-ray spectroscopy using bismuth nanoparticle-containing plastic scintillators with spectral subtraction

In this study, we used the Monte Carlo N-Particle program to simulate the gamma-ray spectra obtained from plastic scintillators holes filled with bismuth nanoparticles. We confirmed that the incorporation of bismuth nanoparticles into a plastic scintillator enhances its performance for gamma-ray spectroscopy using the subtraction method. The subtracted energy spectra obtained from the bismuth-nanoparticle-incorporated and the original plastic scintillator exhibit a distinct energy peak that does not appear in the corresponding original spectra. We varied the diameter and depth of the bismuth-filled holes to determine the optimal hole design for gamma-ray spectroscopy using the subtraction method. We evaluated the energy resolutions of the energy peaks in the gamma-ray spectra to estimate the effects of the bismuth nanoparticles and determine their optimum volume in the plastic scintillator. In addition, we calculated the peak-to-total ratio of the energy spectrum to evaluate the energy measuring limit of the bismuth nanoparticle-containing plastic scintillator using the subtraction method

Feasibility study on fiber-optic inorganic scintillator array sensor system for multi-dimensional scanning of radioactive waste

We developed a miniaturized multi-dimensional radiation sensor system consisting of an inorganic scintillator array and plastic optical fibers. This system can be applied to remotely obtain the radioactivity distribution and identify the radionuclides in radioactive waste by utilizing a scanning method. Variation in scintillation light was measured in two-dimensional regions of interest and then converted into radioactivity distribution images. Outliers present in the images were removed by using a digital filter to make the hot spot location more accurate and cubic interpolation was applied to make the images smoother and clearer. Next, gamma-ray spectroscopy was performed to identify the radionuclides, and three-dimensional volume scanning was also performed to effectively find the hot spot using the proposed array sensor

Gamma-ray Spectroscopy Using Inorganic Scintillator Coated with Reduced Graphene Oxide in Fiber-Optic Radiation Sensor

In this study, we developed a remote gamma-ray spectroscopy system based on a fiber-optic radiation sensor (FORS) that is composed of an inorganic scintillator coated with reduced graphene oxide (RGO) and a plastic optical fiber (POF). As a preliminary experiment, we measured the transmitted light intensities using RGO membranes of different thicknesses with different wavelengths of emitted light. To evaluate the FORS performance, we determined the optimal thickness of the RGO membrane and measured the amounts of scintillating light and gamma energy spectra using radioactive isotopes such as 60Co and 137Cs. The amounts of scintillating light from the RGO-coated inorganic scintillators increased, and the energy resolutions of the gamma-ray spectra were enhanced. In addition, the gamma-ray energy spectra were measured using different types of RGO-coated inorganic scintillators depending on the lengths of the POFs for remote gamma-ray spectroscopy. It was expected that inorganic scintillators coated with RGO in FORS can deliver improved performance, such as increments of scintillating light and energy resolution in gamma-ray spectroscopy, and they can be used to identify nuclides remotely in various nuclear facilities

Interpretations of systematic errors in the NCEP Climate Forecast System at lead times of 2, 4, 8, ..., 256 days

The climatology of mean bias errors (relative to 1-day forecasts) was examined in a 20-year hindcast set from version 1 of the Climate Forecast System (CFS), for forecast lead times of 2, 4, 8, 16, ... 256 days, verifying in different seasons. Results mostly confirm the simple expectation that atmospheric model biases should be evident at short lead (2–4 days), while soil moisture errors develop over days-weeks and ocean errors emerge over months. A further simplification is also evident: surface temperature bias patterns have nearly fixed geographical structure, growing with different time scales over land and ocean. The geographical pattern has mostly warm and dry biases over land and cool bias over the oceans, with two main exceptions: (1) deficient stratocumulus clouds cause warm biases in eastern subtropical oceans, and (2) high latitude land is too cold in boreal winter. Further study of the east Pacific cold tongue-Intertropical Convergence Zone (ITCZ) complex shows a possible interaction between a rapidly-expressed atmospheric model bias (poleward shift of deep convection beginning at day 2) and slow ocean dynamics (erroneously cold upwelling along the equator in leads > 1 month). Further study of the high latitude land cold bias shows that it is a thermal wind balance aspect of the deep polar vortex, not just a near-surface temperature error under the wintertime inversion, suggesting that its development time scale of weeks to months may involve long timescale processes in the atmosphere, not necessarily in the land model. Winter zonal wind errors are small in magnitude, but a refractive index map shows that this can cause modest errors in Rossby wave ducting. Finally, as a counterpoint to our initial expectations about error growth, a case of non-monotonic error growth is shown: velocity potential bias grows with lead on a time scale of weeks, then decays over months. It is hypothesized that compensations between land and ocean errors may cause this behavior

Eastern Pacific Emitted Aerosol Cloud Experiment (E-PEACE)

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