Description: In this work, we will identify the existence of “rough dependence on initial conditions” in atmospheric phenomena, a concept which is a problem for weather analysis and forecasting. Typically, two initially similar atmospheric states will diverge slowly over time such that forecasting the weather using the Navier-Stokes equations is useless after some characteristic time scale. With rough dependence, two initial states diverge very quickly, implying forecasting may be impossible. Using previous research in atmospheric science, rough dependence is characterized by using quantities that can be calculated using atmospheric data and quantities. Rough dependence will be tested for and identified in atmospheric phenomena at different time scales using case studies. Data were provided for this project by archives outside the University of Missouri (MU) and by using the MU RADAR at the South Farm experiment station.

Description: The microwave humidity and temperature sounder (MWHTS) on the Fengyun (FY)-3C satellite measures the outgoing radiance from the Earth’s surface and atmospheric constituents. MWHTS, which makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of the strong water vapor absorption line around 183 GHz, can provide fine vertical distribution structures of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by physical retrieval methods, the bias between the observed and simulated radiance calculated by the radiative transfer model from the background or first guess profiles must be corrected. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion; one is the linear regression correction (LRC), and the other is the neural network correction (NNC), representing the linear and nonlinear relationships between MWHTS measurements and air mass, respectively. The correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180° W–180° E, 60° S–60° N). The corrected results are evaluated by the probability density function of the differences between corrected observations and simulated values and the root mean square errors (RMSE) with respect to simulated observations. The numerical results show that the NNC method has better performance, especially in MWHTS Channels 1 and 7–9, whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS brightness temperatures to estimate the atmospheric temperature and humidity profiles. The retrieval results also show that NNC has better performance. An indication of the stability and robustness of the NNC method is given, which suggests that the NNC method has promising application perspectives in the physical retrieval.

Description: Atmospheric monitoring produces huge amounts of data. Univariate and bivariate statistics are widely used to investigate variations in the parameters. To summarize information graphs are usually used in the form of histograms or tendency profiles (e.g., variable concentration vs. time), as well as bidimensional plots where two-variable correlations are considered. However, when dealing with big data sets at least two problems arise: a great quantity of numbers (statistics) and graphs are produced, and only two-variable interactions are often considered. The aim of this article is to show how the use of multivariate statistics helps in handling atmospheric data sets. Multivariate modeling considers all the variables simultaneously and returns the main results as bidimensional graphs that are easy-to-read. Principal Component Analysis (PCA; the most known multivariate method) and multiway-PCA (Tucker3) are compared from methodological and interpretative points of view. The article demonstrates the ability to emphasize different information depending on the data handling performed. The results and benefits achieved using a more complex model that allows for the simultaneous consideration of the entire variability of the system are compared with the results provided by the simpler but better-known model. Atmospheric monitoring (SO2, NOx, NO2, NO, and O3) data from the Lake Como Area (Italy) since 1992 to 2007 were chosen for consideration for the case study.

Description: In this study, long-term (10 years) radiosonde-based cloud data are compared with the ground-based active remote sensing product under six prevailing large-scale synoptic patterns, i.e., cyclonic center (CC), weak pressure pattern (WP), the southeast bottom of cyclonic center (CB), cold front (CF), anticyclone edge (AE) and anticyclone center (AC) over the Southern Great Plains (SGP) site. The synoptic patterns are generated by applying the self-organizing map weather classification method to the daily National Centers for Environmental Protection mean sea level pressure records from the North American Regional Reanalysis. It reveals that the large-scale synoptic circulations can strongly influence the regional cloud formation, and thereby have impact on the consistency of cloud retrievals from the radiosonde and ground-based cloud product. The total cloud cover at the SGP site is characterized by the least in AC and the most in CF. The minimum and maximum differences between the two cloud methods are 10.3% for CC and 13.3% for WP. Compared to the synoptic patterns characterized by scattered cloudy and clear skies (AE and AC), the agreement of collocated cloud boundaries between the two cloud approaches tends to be better under the synoptic patterns dominated by overcast and cloudy skies (CC, WP and CB). The rainy and windy weather conditions in CF synoptic pattern influence the consistency of the two cloud retrieval methods associated with the limited capabilities inherent to the instruments. The cloud thickness distribution from the two cloud datasets compares favorably with each other in all synoptic patterns, with relative discrepancy of ≤0.3 km.

Description: In this work, the seasonal variations and sources of trace metal elements in atmospheric fine aerosols (PM2.5) were investigated for a year-long field campaign from July 2012 to June 2013, conducted in suburban Nanjing, eastern China, at a site adjacent to an industry zone. The PM2.5 samples collected across four seasons were analyzed for 17 metal elements, namely, Sodium (Na), Magnesium (Mg), Aluminum (Al), Vanadium (V), Chromium (Cr), Manganese (Mn), Nickel (Ni), Copper (Cu), Zinc (Zn), Arsenic (As), Selenium (Se), Strontium (Sr), Cadmium (Cd), Barium (Ba), Lead (Pb), Molybdenum (Mo), and Antimony (Sb) using an inductively coupled plasma mass spectrometry (ICP-MS). We found that the total concentration of all 17 metal elements was 1.23 μg/m3, on average accounting for 1.0% of the total PM2.5 mass. For our data, mass concentrations of Al, Cd, Ba were highest in summer, Mg, Cu, Zn, Se, Pb peaked in autumn, Cr, Mn, Ni, As, Sr, Sb increased significantly in winter, while the concentrations of Na, V, Mo were at their highest levels in spring. Air mass back trajectory analysis suggested that air parcels that arrived at the site originated from four dominant regions (Japan, yellow sea and bohai; Southeast of China, the Pacific Ocean; Southwest of Jiangsu and Anhui province; Northern Asia inland and Mongolia region), in particular, the one from Northern Asia inland and Mongolia contained the highest concentrations of As, Sb, Sr, and was predominant in winter. Positive matrix factorization (PMF) analyses revealed that the industrial emission is the largest contributor (34%) of the observed metal elements, followed by traffic (25%), soil dust (19%), coal combustion (10%), incineration of electronic waste (9%), and a minor unknown source (3%). In addition, we have also investigated the morphology and composition of particles by using the scanning electron microscopy (SEM)/energy-dispersive spectrometry (EDS) techniques, and identified particles from coal burning sources, etc., similar to the PMF results.

Description: The paper describes the net momentum transported by the transient electromagnetic radiation field of a long transient dipole in free space. In the dipole a current is initiated at one end and propagates towards the other end where it is absorbed. The results show that the net momentum transported by the radiation is directed along the axis of the dipole where the currents are propagating. In general, the net momentum P transported by the electromagnetic radiation of the dipole is less than the quantity U / c , where U is the total energy radiated by the dipole and c is the speed of light in free space. In the case of a Hertzian dipole, the net momentum transported by the radiation field is zero because of the spatial symmetry of the radiation field. As the effective wavelength of the current decreases with respect to the length of the dipole (or the duration of the current decreases with respect to the travel time of the current along the dipole), the net momentum transported by the radiation field becomes closer and closer to U / c , and for effective wavelengths which are much shorter than the length of the dipole, P ≈ U / c . The results show that when the condition P ≈ U / c is satisfied, the radiated fields satisfy the condition Δ t Δ U ≥ h / 4 π where Δ t is the duration of the radiation, Δ U is the uncertainty in the dissipated energy and h is the Plank constant.

Description: Multiple data sets were combined to investigate five dust storm events over East Asia in spring 2010 and their impacts on chlorophyll in the East China Sea (ECS) and the North Pacific Subtropical Gyre (NPSG). Satellite-observed column aerosol images were able to show the spatial distribution of the transport of dust from the source regions to the two seas for some of the dust storm events. The CALIPSO satellite showed the vertical structure of dust aerosol for a greater number of dust storm events, including some weak events. This was confirmed by simulations of dust deposition and backward trajectories traced to dust source regions. The simulated dust deposition flux for five dust storms ranged from 13.0 to 145.6 mg·m−2·d−1 in the ECS and from 0.6 to 5.5 mg·m−2·d−1 in the NPSG, suggesting that the highest deposition was about one order of magnitude higher than the lowest. The estimated nutrients from dust showed that dust containing iron had the greatest effect on phytoplankton growth in both seas; the iron deposited by one dust storm event accounted for at least 5% of growth and satisfied the increase in demand required for chlorophyll a concentration.

Description: Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March–May season using the Mann–Kendall ( M K ) trend test and simple linear regression ( S L R ) over the period 2000–2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days ( S L R = 0.181; M K = 0.350) and wet days ( S L R = 0.092; M K = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: S L R = 0.020; M K = 0.279 and wet days: S L R = 0.146; M K = 0.376) was slightly greater than during the seventh dekad (light rain days: S L R = 0.014; M K = 0.018 and wet days: S L R = 0.061; M K = 0.315) dekad. Seventy-four percent accounted for 2–4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third ( M K = 0.363) and seventh ( M K = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43–0.72).

Description: The radiative perturbation associated to stratospheric aerosols from major explosive volcanic eruptions may induce significant changes in stratospheric dynamics. The aerosol heating rates warm up the lower stratosphere and cause a westerly wind anomaly, with additional tropical upwelling. Large scale transport of stratospheric trace species may be perturbed as a consequence of this intensified Brewer–Dobson circulation. The radiatively forced changes of the stratospheric circulation during the first two years after the eruption of Mt. Pinatubo (June 1991) may help explain the observed trend decline of long-lived greenhouse gases at surface stations (approximately −8 and −0.4 ppbv/year for CH4 and N2O, respectively). This decline is partly driven by the increased mid- to high-latitude downward flux at the tropopause and also by an increased isolation of the tropical pipe in the vertical layer near the tropopause, with reduced horizontal eddy mixing. Results from a climate-chemistry coupled model are shown for both long-lived trace species and the stratospheric age-of-air. The latter results to be younger by approximately 0.5 year at 30 hPa for 3–4 years after the June 1991 Pinatubo eruption, as a result of the volcanic aerosols radiative perturbation and is consistent with independent estimates based on long time series of in situ profile measurements of SF6 and CO2. Younger age of air is also calculated after Agung, El Chichón and Ruiz eruptions, as well as negative anomalies of the N2O growth rate at the extratropical tropopause layer. This type of analysis is made comparing the results of two ensembles of model simulations (1960–2005), one including stratospheric volcanic aerosols and their radiative interactions and a reference case where the volcanic aerosols do not interact with solar and planetary radiation.

Description: This study used mesocosms to examine the effects of alternate drying and rewetting on CO2 and CH4 emissions from high-altitude peatlands on the Tibetan Plateau. The drying and rewetting experiment conducted in this study included three phases: a 10-day predrying phase, a 32-day drying phase, and an 18-day rewetting phase. During the experiment, the water table varied between 0 and 50 cm with respect to the reference peat column where the water table stayed constant at 0 cm. The study found that drying and rewetting had no significant effect on CO2 emissions from the peatland, while CH4 emissions decreased. The cumulative CH4 emissions in the control group was 2.1 times higher than in the drying and rewetting treatment over the study period. Moreover, CO2 and CH4 emissions were positively correlated with soil temperature, and the drying process increased the goodness of fit of the regression models predicting the relationships between CO2 and CH4 emissions and temperature. These results indicate that small-scale water table variation has a limited effect on CO2 emissions, but might reduce CH4 emissions in high-altitude peatlands on the Tibetan Plateau.