Testing random effects in linear mixed‐effects models with serially correlated errors

In linear mixed-effects models, random effects are used to capture the heterogeneityand variability between individuals due to unmeasured covariates or unknown bio-logical differences. Testing for the need of random effects is a nonstandard problembecause it requires testing on the boundary of parameter space where the asymptoticchi-squared distribution of the classical tests such as likelihood ratio and score testsis incorrect. In the literature several tests have been proposed to overcome this diffi-culty, however all of these tests rely on the restrictive assumption of i.i.d. measurementerrors. The presence of correlated errors, which often happens in practice, makes test-ing random effects much more difficult. In this paper, we propose a permutation testfor random effects in the presence of serially correlated errors. The proposed test notonly avoids issues with the boundary of parameter space, but also can be used fortesting multiple random effects and any subset of them. Our permutation procedureincludes the permutation procedure in Drikvandi, Verbeke, Khodadadi, and PartoviNia (2013) as a special case when errors are i.i.d., though the test statistics are dif-ferent. We use simulations and a real data analysis to evaluate the performance of theproposed permutation test. We have found that random slopes for linear and quadratictime effects may not be significant when measurement errors are serially correlated

Effects of glycerol and sire breed on growth and carcass traits of finishing wether lambs

Objectives: To evaluate crude glycerin as an energy source for finishing lambs and to determine the effect of sire breed on finishing lamb growth performance and carcass characteristics. In light of previous research, the hypothesis for this experiment was that glycerol would have an energy value similar to that of corn when fed in high concentrate diets to finishing lambs

Measuring the Effects of Surface Features on the Atmospheric Boundary Layer with Instrumented Aircraft

The influence of mesoscale features (e.g., irrigation projects, desert regions, patches of forest, cities, etc.) on the atmosphere is difficult to determine unless the sensors are very numerous or highly mobile. An instrumented aircraft system permits such measurements and was used to determine the influence of lakes and reservoirs, irrigation, a group of forested hills, a small city, and an area of (dry land) nonirrigated agricultural land on the vertical and horizontal characteristics of the lowest layer of the atmosphere. Studies were conducted over portions of southern Alberta, and southern Idaho. Strong sensible heat advection was found to cause high evaporation from a small lake with the formation of a cool air layer which extended well beyond the lee side of the lake. The flux of water vapor over irrigated land was essentially double that over surrounding nonirrigated areas. A small city produced a heat island which delayed development of a temperature inversion for up to 9 h

Fingerprint of Climate Change on Southern Ocean Carbon Storage

The Southern Ocean plays a critical role in the uptake, transport, and storage of carbon by the global oceans. It is the ocean's largest sink of CO2, yet it is also among the regions with the lowest storage of anthropogenic carbon. This behavior results from a unique combination of high winds driving the upwelling of deep waters and the subduction and northward transport of surface carbon. Here we isolate the direct effect of increasing anthropogenic CO2 in the atmosphere from the indirect effect of climate variability and climate change on the reorganization of carbon in the Southern Ocean interior using a combination of modeling and observations. We show that the effect of climate variability and climate change on the storage of carbon in the Southern Ocean is nearly as large as the effect of anthropogenic CO2 during the period 1998–2018 compared with the climatology around the year 1995. We identify a distinct climate fingerprint in dissolved inorganic carbon (DIC), with elevated DIC concentration in the ocean at 300–600 m that reinforces the anthropogenic CO2 signal, and reduced DIC concentration in the ocean around 2,000 m that offsets the anthropogenic CO2 signal. The fingerprint is strongest at lower latitudes (30°–55°S). This fingerprint could serve to monitor the highly uncertain evolution of carbon within this critical ocean basin, and better identify its drivers.publishedVersio

Gathering the evidence and identifying opportunities for future research in climate, heat and health in South Africa : the role of the South African Medical Research Council

Abstract: Background. A changing climate is likely to have widespread and varying impacts on ecosystems and human health. South Africa (SA) is particularly vulnerable to the impacts of climate change, given the projected increases in temperature, and changes in the amount and patterns of rainfall. Moreover, SA’s vulnerability is exacerbated by extreme inequality and poverty. To prepare for the impacts of climate change and to ensure timeous adaptation, a perspective is given on essential heat and health research in the country. Objectives. To gather studies conducted by the South African Medical Research Council (SAMRC)’s Environment and Health Research Unit (EHRU) to illustrate the range of possible research key areas in the climate, heat and health domain and to present future research priorities. Methods. Studies conducted by the SAMRC’s EHRU were gathered and used to illustrate the range of possible research key areas in the climate, heat and health domain. Using national and international published and grey literature, and tapping into institutional research experiences, an overview of research findings to date and future research priorities were developed. Results. Heat and health-related research has focussed on key settings, for example, schools, homes and outdoor work places, and vulnerable groups such as infants and children, the elderly and people with pre-existing diseases. The need to address basic needs and services provision was emphasised as an important priority. Conclusions. High and low temperatures in SA are already associated with mortality annually; these impacts are likely to increase with a changing climate. Critical cross-sectoral research will aid in understanding and preparing for temperature extremes in SA

Modeling and Observations of the Effects of the Alfvén Velocity Profile on the Ionospheric Alfvén Resonator

We have modeled the individual harmonic frequencies of the Ionospheric Alfvén Resonator (IAR) at Eskdalemuir by solving a one-dimensional wave equation and using non-uniform modeled Alfvén velocity profiles. By comparing the results of the modeling alongside harmonics obtained from the Eskdalemuir, UK, data set from 2013 to 2021, the effects of the non-uniformity of the Alfvén velocity profile on the IAR are considered. We calculated the offset between the fundamental frequency and the harmonic frequency separation and found that this is not constant. From this parameter, we infer that the lower boundary condition of the electric field of the IAR is closest to a node, which agrees with previous studies. We compare the results of the non-uniform model with previous uniform models and evaluate their interpretations and the implications for the lower boundary condition

Climatology of the harmonic frequency separation of ionospheric Alfvén Resonances at Eskdalemuir Observatory, UK

We extracted the harmonic frequency separation (Δf) of Ionospheric Alfvén Resonances (IAR) observed in the Eskdalemuir induction coil magnetometer data for the 9 year data set of 2013–2021. To obtain Δf values, we used a machine learning technique that identifies the harmonics and from this we calculated the average separation. To investigate the climatology of the IAR, we have modeled the Δf of the IAR for the data set using a time of flight calculation with model Alfvén velocity profiles. When analyzing Δf from the model and data, we found that in general they follow the same trends. The modeled Δf and Δf from the data both show an inverse correlation with foF2, which confirms that the frequencies of the IAR are controlled by electron density. It follows that Δf is greater around midnight and during the winter months, due to the decrease in plasma mass density. Variability is also reflected when comparing yearly trends in Δf with the sunspot number; higher frequencies are observed and modeled at low sunspot number. It is difficult to examine trends with instantaneous geomagnetic activity as IAR are not visible in spectrograms when geomagnetic activity is high. We find cases where the difference in measured and modeled Δf is significant, suggesting that the model does not capture short term variations in plasma mass density that influence the IAR during these days. We plan to undertake further modeling of Δf on shorter timescales