Large Negative Bias Research Articles

Ultrathin α-Bi2O3 Thin-Film Transistor for Cost-Effective Oxide-TFT Inverters.

Electronics is advancing toward greater diversity and sustainability by prioritizing energy efficiency and cost-effectiveness. Metal oxide thin-film transistor (TFT) represents a technology at the forefront of advancing next-generation sustainable electronics, and exploring oxide channel compositions is a crucial step in opening opportunities for developing next-generation device applications. This study presents the first development of n-channel α-Bi2O3-TFTs using a 4 nm ultrathin channel prepared by a cost-effective vacuum-free and solvent-free liquid metal printing method in ambient air. Even the pristine device exhibited a clear TFT action but required a large negative gate bias to turn off due mainly to excess carriers from oxygen vacancy in the α-Bi2O3 channel. Oxygen-containing post-annealing reduced both channel carrier and subgap defect densities, enabling the development of depletion and enhancement-type α-Bi2O3-TFTs with the saturation mobility of 2-4 cm2 V-1 s-1. Two types of oxide-TFT-based inverter circuits, zero-VGS-NMOS and CMOS inverters, were fabricated by using α-Bi2O3-TFTs, operating in a high voltage gain of over 130. This work demonstrates the potential of oxide semiconductor materials toward the development of next-generation sustainable electronics.

Negative global metacognitive biases are associated with depressive and posttraumatic stress disorder symptoms and improve with targeted or game-based cognitive training.

Metacognition is disrupted in several clinical populations. One aspect of metacognition, global metacognitive bias (difference between objective and self-reported abilities), has shown to be particularly relevant to clinical functioning. However, previous studies of global metacognitive biases in populations with elevated depressive/posttraumatic stress disorder (PTSD) symptoms have not measured objective and self-reported abilities relative to normative samples, limiting the quantification of biases. Additionally, few studies have examined whether cognitive interventions can improve metacognitive biases or how this relates to depressive/PTSD symptom severity. A total of 84 participants with mild traumatic brain injury (77% veterans) performed PTSD and depression assessments along with self-reported and objective measures of global cognition. Age-adjusted norm-based z scores were used for self-reported and objective cognition, and bias was calculated by subtracting objective minus self-report scores. Participants then received 13 weeks of targeted cognitive training or entertainment games training (both providing performance feedback). Participants were assessed at baseline, immediately posttraining, and 3 months posttraining. We found large negative metacognitive biases in those with clinically significant severity of depressive symptoms (z score difference = -1.77), PTSD symptoms (-1.47), and depressive + PTSD symptoms (-2.29). Metacognitive biases improved after both targeted and entertainment training and was associated with reductions in depressive/PTSD symptom severity (r = -.41/-.42, respectively), led by the entertainment training group (r = -.54/-.46, respectively). These findings show that clinically significant severity of depressive/PTSD symptoms is associated with substantial negative global metacognitive biases and preliminarily suggests that cognitive training may improve these biases and depressive/PTSD symptom severity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part I: Evaluation of Wind Speeds and Gusts

Abstract Strong wind events cause significant societal damage ranging from loss of property and disruption of commerce to loss of life. Over portions of the United States, the strongest winds occur in the cold season and may be driven by interactions with the terrain (downslope winds, gap flow, and mountain wave activity). In the first part of this two-part series, we evaluate the High-Resolution Rapid Refresh (HRRR) model wind speed and gust forecasts for the 2016–22 winter months over Wyoming and Colorado, an area prone to downslope windstorms and gap flows due to its complex topography. The HRRR model exhibits a positive bias for low wind speeds/gusts and a large negative bias for strong wind speeds/gusts. In general, the model misses many strong wind events, but when it does predict strong winds, there is a high false alarm probability. An analysis of proxies for surface winds is conducted. Specifically, 700- and 850-mb (1 mb = 1 hPa) geopotential height gradients are found to be good proxies for strong wind speeds and gusts at two wind-prone locations in Wyoming. Given the good agreement between low-level height gradients and surface wind speeds yet a strong negative bias for strong wind speeds and gusts, there is a potential shortcoming in the boundary layer physics in the HRRR model with regard to predicting strong winds over complex terrain, which is the focus of the second part of this two-part study. Last, the sites with the largest strong wind speed bias are found to mostly sit on the leeward side of high mountains, suggesting that the HRRR model performs poorly in the prediction of downslope windstorms. Significance Statement We investigate the performance of the High-Resolution Rapid Refresh (HRRR) model with respect to strong wintertime wind speeds and gusts over the complex terrain of Wyoming and Colorado. We show that the overall performance of the HRRR model is low with regard to strong wind speed and wind gust forecasts across the investigated winter seasons, with a large negative bias in predicted strong wind speeds and gusts and a small positive bias for weak wind speeds and gusts. The largest biases are found to be on the leeward side of high mountains, indicating poor prediction of downslope winds. This study also utilizes National Weather Service forecasting metrics to understand their performance with respect to strong wind forecasts, and we find that they provide skill in forecasting these events.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part II: Sensitivity of Surface Wind Speeds to Model Resolution and Physics

Abstract Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in the first part of this two-part series, it was shown that the High-Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In this part of the study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) Model simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor–Yamada–Nakanishi–Niino scheme to the Mellor–Yamada–Janjić PBL and SL schemes results in nearly no change in the r2 values, but there is a decrease in the magnitude of the strong wind speed bias (from −12.52 to −10.16 m s−1). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service. Significance Statement Motivated by prior studies showing low skill in the prediction of strong winds using state-of-the-art weather forecast models, in this study, we aim to investigate two questions: 1) does increasing the horizontal resolution improve the prediction of strong wind events over the complex terrain of Wyoming and Colorado, and 2) are the biases in High-Resolution Rapid Refresh (HRRR) forecasted winds related to the selected planetary boundary layer, surface layer, and/or land surface model parameterizations? We find that increasing the horizontal resolution provides a slight improvement in the prediction of strong winds. Further, considerable improvement in the prediction of strong winds is found for varying boundary layer, surface layer, and land surface parameterizations.

Comparison of direct and indirect measures of transport efficiency in single particle inductively coupled plasma mass spectrometry

Accurate calibration of the fraction of introduced sample that is transported to the plasma, termed “transport efficiency” (TE), is required for particle sizing and number concentration determination by single particle inductively coupled plasma mass spectrometry (spICP-MS). In this study, we systematically compare three methods for the measurement of TE: the particle frequency (TEF), particle size (TES), and dynamic mass flow (DMF) methods. The TEF and TES methods provide a direct measure of TE but require a single nanoparticle (NP) reference material accurately value-assigned for particle size and number concentration of which few are available. The DMF method provides an indirect measure of TE and only requires measurement of the mass difference between the amount of sample solution introduced to the instrument and the amount of effluent exiting the spray chamber. Because the DMF method relies solely on mass measurements, it can provide an SI traceable measure of TE. However, the DMF method assumes that the mass difference represents the fraction of sample transported to the plasma. The veracity of the three approaches to account for TE is assessed using three different spray chamber types, i.e., Scott-type double pass, conical impact bead, and baffled cyclonic spray chambers operated at cooled (2 °C to 10 °C) and ambient temperature (19 °C to 21 °C) conditions equipped with different nebulizers on different ICP-MS platforms. When operating the spray chamber at ambient temperature, the DMF method yielded systematically higher measures of TE than the TEF and TES methods regardless of nebulizer type, spray chamber type, or ICP-MS platform. While better agreement between the three measures of TE was achieved when operating the spray chambers at 2 °C, DMF repeatability was poor. The deviation of particle number concentration, expressed as the median percent difference from the known value for various in-house value-assigned AuNP suspensions, ranged from – 18% to +8% (TEF) and from – 1% to – 70% (DMF) whereas the deviation for particle size ranged from – 3% to +1% (TES) and from – 4% to +44% (DMF) across all conditions. The large negative bias for counting and positive bias for sizing by the DMF method indicates an overestimation of TE which was traced to low recovery of the mass of effluent exiting the spray chamber. We found that the indirect measure of TE (DMF method) yielded acceptable results (within ±10% of known values for particle size and ± 20% of known values for number concentration) under select conditions (cyclonic spray chamber at 2 °C and Meinhard nebulizer), but the biases inherent to the DMF method are not fully understood for all studied conditions. Only the direct measures of TE (TEF and TES) yielded acceptable results across all use conditions.

Long-term validation and error analysis of DB and MAIAC aerosol products over bright surface of China

Two distinct algorithms, namely Deep Blue (DB) and Multiangle Implementation of Atmospheric Correction (MAIAC), based on the Moderate Resolution Imaging Spectroradiometer (MODIS), can provide aerosol optical depth (AOD) products over bright surfaces. Recently, the newest MAIAC Collection 6.1 (C6.1) product was available, which corrected many known deficiencies of C6. Due to the significant impact of high-reflectivity surfaces on the accuracy of aerosol retrieval, long-term validation and comprehensive assessment of AOD over bright surfaces are required at a regional scale. Firstly, this study conducted a systematic evaluation of three products against ground-based Sunphotometer data obtained from 21 sites of the China Aerosol Remote Sensing Network (CARSNET) and 2 sites of the Aerosol Robotic Network (AERONET) from the year 2002 to 2014. The validation results showed a significant underestimation in DB and MAIAC AOD retrievals as indicated by the large percent of retrievals below the expected error (EE) envelope, and significant negative biases. In comparison, both versions of MAIAC products performed better than DB product, which was also revealed by the site scale validation. Besides, the performance of the C6.1 MAIAC was slightly improved over the study region compared to the C6 MAIAC. Finally, this study made an in-depth investigation of the underestimation of AOD products affected by various factors, i.e., aerosol loading, land type, NDVI, surface albedo, and scattering angle. The results indicated that the large negative bias of AOD retrievals for the three products tended to occur in the case of large aerosol loadings and high bright surfaces, which could be attributed to the inaccurate assumption of aerosol models and the insensitivity of top of atmosphere (TOA) reflectance to AOD variations caused by the high reflectivity of the underlying surface. The findings of this study are expected to provide some reference for the improvement of aerosol retrieval algorithms over bright surfaces.

Design and Performance of a Low-Cost, Portable Platelet Counter for Point-of-Care and at-Home Use

Background Patients with recurrent or chronic moderate-to-severe thrombocytopenia can experience a marked reduction in quality of life due to the need for regular blood draws, frequent contact with the health care system, and potential for bleeding complications requiring emergency department visits and/or hospital admissions. To improve quality of life while maintaining effective platelet monitoring, we introduce a portable, point-of-care platelet counter that can be used in any health care setting or at home. Methods Obtaining a platelet count requires three components: a counter, staining modality, and erythrocyte lysing agent. The counting device described here is the Athelas One, a small cylindrical device containing a miniaturized microscope embedded with a control board. A strip containing a stained microfluidic channel approximately 10µm tall and thus suitable for a monolayer of blood cells houses the sample. An ammonium oxalate solution is used to lyse the erythrocytes in the capillary sample. Images of the blood sample are acquired and then analyzed using a convolutional neural network to yield platelet counts. To use the device, a patient pricks his or her finger and collects 20µL of blood in a K2EDTA-coated minivette. The blood is mixed with the lysing agent and inserted into the strip, which in turn is inserted into the device. A platelet count is obtained within 5 minutes. In this observational study, we enrolled 233 adults at least 21 years of age with normal platelet counts at a single teaching hospital. Non-hematological illness was allowed. Each patient's platelet count was obtained using both capillary samples processed on Athelas One and paired anticoagulated venous samples processed on a standard hematology analyzer, the Sysmex XS-1000i (SX). Platelet counts from Athelas One and SX were compared using a Passing-Bablok regression model with a Pearson correlation coefficient. Bland-Altman analysis was also performed. Confidence intervals (CI) were calculated using a Student's t-distribution. Least squares regression modeled the relationship between time necessary to collect capillary samples and bias between Athelas One and SX. Analyses were conducted in R. Results A strong linear relationship was observed between Athelas One and SX: Passing-Bablok regression revealed a slope of 0.98 and a y-intercept estimate of -16.45 (Figure), and the Pearson correlation-coefficient was 0.70. Bland-Altman statistics revealed an average percent difference of -8.66% (95% CI: -6.55% to -10.77%), reflecting a bias of Athelas One to undercount as compared with SX. In an effort to explain the predilection for undercounting, device performance was analyzed as a function of sample collection time. Least squares regression revealed a slope of -1.08 (95% CI: -1.55 to -0.61) and a y-intercept estimate of 8.16 (95% CI: -12.15 to 28.47). The Pearson correlation-coefficient was 0.54. Conclusion Athelas One compared favorably with SX. The bias for undercounting may be a consequence of a pseudothrombocytopenia phenomenon due to platelet activation and clot formation prior to sample collection, which sequesters platelets out of solution. This hypothesis is supported by the fact that longer time needed to collect the capillary sample correlated with larger negative bias between Athelas One and SX. To improve agreement, a number of methods in the counting procedure, namely sample collection, could be altered. A potential solution involves wiping the finger with an anticoagulant prior to sample collection to discourage clot formation. This proof-of-concept analysis demonstrates the plausibility of point-of-care platelet monitoring. Future work will focus on validating Athelas One in thrombocytopenic and thrombocytotic samples.

Tuning In-Plane Magnetic Anisotropy and Interfacial Exchange Coupling in Epitaxial La2/3Sr1/3CoO3/La2/3Sr1/3MnO3 Heterostructures.

Controlling the in-plane magnetocrystalline anisotropy and interfacial exchange coupling between ferromagnetic (FM) layers plays a key role in next-generation spintronic and magnetic memory devices. In this work, we explored the effect of tuning the magnetocrystalline anisotropy of La2/3Sr1/3CoO3 (LSCO) and La2/3Sr1/3MnO3 (LSMO) layers and the corresponding effect on interfacial exchange coupling by adjusting the thickness of the LSCO layer (tLSCO). The epitaxial LSCO/LSMO bilayers were grown on (110)o-oriented NdGaO3 (NGO) substrates with a fixed LSMO (top layer) thickness of 6 nm and LSCO (bottom layer) thicknesses varying from 1 to 10 nm. Despite the small difference (∼0.2%) in lattice mismatch between the two in-plane directions, [001]o and [11̅0]o, a pronounced in-plane magnetic anisotropy was observed. Soft X-ray magnetic circular dichroism hysteresis loops revealed that for tLSCO ≤ 4 nm, the easy axes for both LSCO and LSMO layers were along the [001]o direction, and the LSCO layer was characterized by magnetically active Co2+ ions that strongly coupled to the LSMO layer. No exchange bias effect was observed in the hysteresis loops. In contrast, along the [11̅0]o direction, the LSCO and LSMO layers displayed a small difference in their coercivity values, and a small exchange bias shift was observed. As tLSCO increased above 4 nm, the easy axis for the LSCO layer remained along the [100]o direction, but it gradually rotated to the [11̅0]o direction for the LSMO layer, resulting in a large negative exchange bias shift. Therefore, we provide a way to control the magnetocrystalline anisotropy and exchange bias by tuning the interfacial exchange coupling between the two FM layers.

A-214 Modified CDC Beta-Quantification Reference Method for HDL-C and LDL-C Determinations Using Isotope-Dilution Mass Spectrometry—Pilot Report

Abstract Background It is known that there is average positive 1.6% bias of total cholesterol by modified Abell-Levy-Brodie-Kendall (AK) colorimetric method, which have been the traceable reference measurement procedure (RMP) used by most of clinical guidelines, comparing to those by isotope-dilution mass spectrometry (ID-MS), the most accurate RMP. The CDC beta-quantification (BQ) reference method is currently the only RMP registered JCTLM database for high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) using the AK colorimetric assay after ultracentrifugation. We compared the modified BQ method using ID-MS assay after ultracentrifugation with the original CDC BQ reference method of HDL-C or LDL-C. Methods For this study, 18 commutable serum pools according to the CLSI 37A and 6 external quality assessment survey materials operated by Cholesterol Reference Method Laboratory Network (CRMLN) were used. We used the same ultracentrifugation procedure as in the original CDC BQ reference method, and the bottom fraction cholesterol (BFC) and HDL-C from supernatant after apo B-containing lipoprotein precipitation using heparin/manganese were measured for each sample using both AK and ID-MS methods, then LDL-C was calculated as the difference between BFC and HDL-C. The comparability analysis between methods at multiple medical decision levels (MDL), and Passing-Bablok regression analysis for each analyte were performed. Results Each Passing-Bablok regression equation of modified CDC BQ reference method vs. original CDC BQ reference method for three fractions, BFC, HDL-C, and LDL-C, were as follows; BFC was y (IDMS) = 0.996x (AK) - 0.342 (R = 0.999), for HDL-C was y (IDMS) = 1.007x (AK)-1.037 (R = 0.995), and for LDL-C was y (IDMS) = 0.990x (AK) + 0.860 (R = 0.999). Both cholesterol results by two methods showed excellent correlation and agreement of the three fractions showing regression R larger than 0.995 and slope or intercept containing 1 and 0 in their 95% confidence interval. The mean differences of IDMS against AK method were −0.56% for BFC, −0.51 mg/dL for HDL-C, and −0.35% for LDL-C, respectively. When the regression prediction at MDLs, 40/50/60 mg/dL for HDL-C and 100/130/160 mg/dL for LDL-C were estimated, all the differences were confirmed to be within allowable level claimed by CRMLN member laboratory accreditation criteria, ±1mg/dL for HDL-C and ±2.0% for LDL-C, showing equivalent results against CDC BQ reference method, but average negative bias of −0.72%, −1.59%, and −0.28% for BFC, HDL-C, and LDL-C, respectively are still present. These results of the modified BQ method using ID-MS assay may be promising, because the tedious and less accurate AK-assay can be switched to the ID-MS assay, not sacrificing trueness LDL-C or changing clinical guidelines, but quite large negative bias of HDL-C for some samples should require further investigation. Conclusion We got comparable HDL-C and LDL-C results using modified BQ method using ID-MS assay with those by original CDC BQ reference method using AK colorimetric assay. The quite large negative bias of HDL-C for some samples require large-scale additional further multi-center study among CRMLN network laboratories to evaluate the results observed in our study.

First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements

Abstract. The Geostationary Environmental Monitoring Spectrometer (GEMS) is a UV-visible (UV-Vis) spectrometer on board the GEO-KOMPSAT-2B (Geostationary Korea Multi-Purpose Satellite 2B) satellite launched into a geostationary orbit in February 2020. To evaluate the GEMS NO2 total column data, a comparison was carried out using the NO2 vertical column density (VCD) that measured direct sunlight using the Pandora spectrometer system at four sites in Seosan, South Korea, from November 2020 to January 2021. Correlation coefficients between GEMS and Pandora NO2 data at four sites ranged from 0.35 to 0.48, with root mean square errors (RMSEs) from 4.7×1015 to 5.5×1015 molec. cm−2 for a cloud fraction (CF) <0.7. Higher correlation coefficients of 0.62–0.78 with lower RMSEs from 3.3×1015 to 5.0×1015 molec. cm−2 were found with CF <0.3, indicating the higher sensitivity of GEMS to atmospheric NO2 in less cloudy conditions. Overall, the GEMS NO2 total column data tended to be lower than the Pandora data, owing to differences in the representative spatial coverage, with a large negative bias under high CF conditions. With a correction for horizontal representativeness in the Pandora measurement coverage, correlation coefficients ranging from 0.69 to 0.81, with RMSEs from 3.2×1015 to 4.9×1015 molec. cm−2, were achieved for CF <0.3, showing a better correlation with the correction than without the correction.

Agreement of Temperatures Measured Using a Non-Contact Infrared Thermometer With a Rectal Digital Thermometer in Horses.

Evaluating the body temperature of horses is an essential tool for monitoring horse health and biosecurity in groups of horses. Temperatures of horses and foals are determined most often using rectal thermometry. Rectal thermometry has limitations that include safety considerations for horses and humans. Thus, we investigated the agreement between a noncontact infrared thermometer (NCIT) and a rectal digital thermometer in 142 horses and 34 foals. For each horse and foal, measurements using the NCIT were collected from the forehead (n=2) or neck (n=1) and with a rectal digital thermometer (n=1). Although the NCIT demonstrated good reliability (i.e. repeatability of measurements), a large negative bias (nearly 2°F (-16.7°C) in adult horses and >3°F (-16.1°C) in foals) was observed between readings from the NCIT and the rectal thermometer in healthy horses. Although horses with febrile illness were not included in the study, our results indicate that the large and inconsistent bias observed with the NCIT indicates that these devices will not be a suitable substitute for rectal thermometry for obtaining valid estimates of core body temperature in horses.

Estimates of large whale abundance in Greenlandic waters from a ship-based survey in 2005

A ship-based line transect survey of large whales in East and West Greenland was conducted in September 2005. The survey platform primarily targeted capelin, Mallotus villosus, using acoustic methods and systematically covered the east and west coasts of Greenland from the coast to the shelf break (approximately 200m). The surveyed area comprised 81,000km2 in East Greenland and 225,000km2 in West Greenland. A total of 194 sightings of 13 cetacean species were obtained and standard line transect methods were used to derive abundance estimates of the four most commonly encountered large cetaceans. Fin whales, Balaenoptera physalus, were most abundant in East Greenland (3,214, 95% CI=980-10,547) with lower abundances estimated for West Greenland (1,980, 95% CI=913-4,296). Sei whales, B. borealis, were frequently encountered in the same areas as fin whales, but the estimated abundance in East Greenland (763, 95% CI=236- 2,465) was lower than in West Greenland (1,599, 95% CI=690-3,705). Humpback whales, Megaptera novaeangliae, were found both in offshore and coastal areas of West Greenland (1,306, 95% CI=570-2,989) and in low numbers in East Greenland (347, 95% CI=48-2,515). Finally, common minke whale, B. acutorostrata, abundance was estimated at 1,848 (95% CI=197-17,348) for East Greenland and 4,479 (95% CI=1,760-11,394) for West Greenland. Inclusion of sightings of unidentified large baleen whales in West Greenland distributed in proportion to species and strata increased abundance estimates for fin, sei, and humpback whales to 2,824 (95% CI=1,346-5,925), 2,009 (95% CI=948-4,260), and 1,514 (95% CI=560-4,089), respectively. Despite good conditions and considerable effort, few cetaceans were observed in the northernmost strata in West Greenland. This suggests that the southbound fall migration of large whales from North West Greenland had already started by the time the survey was initiated. The abundance estimates presented in this study are negatively biased. No corrections were applied for whales missed by observers or for whales submerged during the passage of the survey platform, which should cause a particularly large negative bias, for the estimates of common minke whale abundance.

Estimates of large whale abundance in West Greenland waters from an aerial survey in 2005

An aerial line transect and cue counting survey of large whales in West Greenland was conducted in August and September 2005. The survey covered the area between Cape Farewell and Disko Island on the West Greenland coast out to the 200m depth contour. The surveyed area covered 163,574km2 and a total of 246 sightings of 9 cetacean species were obtained. Abundance estimates were developed for humpback whales, Megaptera novaeangliae (21 sightings), fin whales, Balaenoptera physalus (78 sightings) and common minke whales, B. acutorostrata (42 sightings). The mean group size of humpback whales was 3.30 but groups as large as 95 animals were seen off effort. The mean group size of fin whales was 2.96 with groups as large as 50 seen. Common minke whale group size was 1.1 with only one sighting of a group of two whales. Humpback whales were found both in offshore and coastal areas of West Greenland with the exception of Store Hellefiske Bank and the Cape Farewell offshore area. The line transect abundance estimate of humpback whales was 1,218 (CV=0.56), uncorrected for submerged whales (availability bias) and whales that were available to be seen but were missed by the observers (perception bias). Fin whales were observed in all areas of the survey and the uncorrected line transect estimate was 1,660 (CV=0.38). When corrected for perception bias the estimates increases to 3,234 fin whales (CV=0.44). Common minke whales were found in almost equal densities in all strata except for the Cape Farewell offshore area, where none were seen. The cue-counting abundance estimate of common minke whales was 4,856 (CV=0.49) for West Greenland using a cue rate of 46.3 cues per hour (CV=0.11). If the estimate is corrected for perception bias the common minke whale abundance is estimated to be 10,792 whales (CV=0.59). Low coverage was attained in the northern area of West Greenland and this should cause an especially large negative bias for the estimates of fin whale and humpback whale abundance because this area is believed to have particularly large densities of these whales.

A Study on The Effects of Long-Term Tidal Constituents on Surge Forecasting Along The Coasts of Korean Peninsula

In this study we investigated the characteristics of long-term tidal constituents based on 30 tidal gauge data along the coasts of Korea and its the effects on total water level (TWL) forecasts. The results show that the solar annual (a) and semiannual (sa) tides were dominant among long-term tidal constituents, and they are relatively large in western coast of Korea peninsula. To investigate the effect of long-term tidal constituents on TWL forecasts, we produced predicted tides in 2021 with and without long-term tidal constituents. The TWL forecasts with and without long-term tidal constituents are then calculated by adding surge forecasts into predicted tides. Comparing with the TWL without long-term tidal constituents, the results with long-term tidal constituents reveals small bias in summer and relatively large negative bias in winter. It is concluded that the large error found in winter generally caused by double-counting of meteorological factors in predicted tides and surge forecasts. The predicted surge for 2021 based on the harmonic analysis shows seasonality, and it reduces the large negative bias shown in winter when it subtracted from the TWL forecasts with long-term tidal constituents.

First validation of GEDI canopy heights in African savannas

Savannas have complex, discontinuous woody vegetation structures that vary greatly in vertical and spatial arrangement and change due to climatic, ecological and management impacts. While airborne laser scanning (ALS) data have provided detailed information on vertical vegetation structure and is widely used in ecological studies, it is lacking in availability and repeat frequency. Although the Global Ecosystem Dynamics Investigation (GEDI) waveform Light Detection and Ranging (LiDAR) sensor and algorithms were optimized for measuring dense forests, it was anticipated that GEDI metrics could provide useful characterization of lower stature, sparse savannas structures. This study provided the first baseline validation of Version 2 GEDI (L2A) relative height 98 (RH98) by comparing the on-orbit GEDI-RH98orb to the simulated GEDI-RH98sim derived from ALS data across diverse savanna vegetation. It furthermore determined the influence of various factors on error, e.g. algorithm setting group (SGs), beam type, day vs. night, beam sensitivity, and vegetation phenology. After applying quality flags, 22,813 GEDI footprints were analyzed across 11 sites. SGs 4–6 that are aimed at dense forests had much larger errors than SGs 1–3. The phenological conditions at the time of GEDI data acquisition had a very large influence on the error of RH98orb. During leaf-on conditions for savanna vegetation with RH98sim < 15 m, RH98orb was very accurate with R2 = 0.61, mean bias = −0.55 m, %bias = −11.1%, RMSE = 1.64 m and %RMSE = 29.8%. In leaf-off conditions where RH98sim < 15 m, RH98orb was less accurate with R2 = 0.43, mean bias = −1.47 m, %bias = −26.5%, RMSE = 2.03 m and %RMSE = 40.9%. During leaf-off conditions, the GEDI LiDAR signal at the start of the waveform may be weaker as it interacts with denuded branches and may be truncated as noise, leading to a large negative height bias. Therefore, assessments of deciduous vegetation structures should be conducted during leaf-on periods. In leaf-on conditions, GEDI's RH98orb was very accurate between canopy heights of 3 and 7 m, with a mean bias of −0.79 m (−10%). The bias of RH98orb was not influenced by canopy cover. Due to the GEDI LiDAR pulse width of 15.6 ns, the GEDI-RH98 data product cannot reliably estimate canopy heights of shrubs below 2.34 m and will require more complex deconvolution of the waveform. GEDI's RH98 accurately estimates the canopy height of trees between 3 and 15 m allowing assessment of canopy heights over vast savanna areas.

Dynamical Effects of Excess Carriers on SOI FeFET Memory Device Operations

We study the carrier dynamics of memory program (PGM) and readout operations for an n-type silicon-on-insulator (SOI) ferroelectric field-effect transistor (FeFET) through TCAD simulations. We found that gate-induced drain leakages (GIDL) during the PGM operation with large negative gate biases can result in excess hole concentrations as high as 7.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 10^{{20}}$ </tex-math></inline-formula> cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-{3}}$ </tex-math></inline-formula> in the potential well formed in the SOI channel. The hole accumulation causes a large electric field across the ferroelectric (FE) layer and results in a polarization boost at a low PGM voltage. For a nano-scale SOI channel, the retention time of the excess holes can exceed microseconds according to our simulations. The outflow of the excess holes leads to a transient effect in the drain current during the readout operation, and we observed additional retention effects for the FeFET memory window due to the hole dynamic effects on the electrostatics and the FE polarizations. While the excess holes result in a ~100 ps delay in the readout phase before a large read margin can be detected, they have boosted the PGM speed and polarization window. The boosted polarization can be retained for milliseconds, and potentially beyond, resulting in an appreciable ON/OFF ratio during readout. Therefore, such effects can be utilized for low-power memory applications through proper SOI FeFET designs with the awareness of excess carrier dynamics.

Uncertainty-bounded estimates of ash cloud properties using the ORAC algorithm: application to the 2019 Raikoke eruption

Abstract. Uncertainty-bounded satellite retrievals of volcanic ash cloud properties such as ash cloud-top height, effective radius, optical depth and mass loading are needed for the robust quantitative assessment required to warn aviation of potential hazards. Moreover, there is an imperative to improve quantitative ash cloud estimation due to the planned move towards quantitative ash concentration forecasts by the Volcanic Ash Advisory Centers. Here we apply the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm to Advanced Himawari Imager (AHI) measurements of the ash clouds produced by the June 2019 Raikoke (Russia) eruption. The ORAC algorithm uses an optimal estimation technique to consolidate a priori information, satellite measurements and associated uncertainties into uncertainty-bounded estimates of the desired state variables. Using ORAC, we demonstrate several improvements in thermal infrared volcanic ash retrievals applied to broadband imagers. These include an improved treatment of measurement noise, accounting for multi-layer cloud scenarios, distinguishing between heights in the troposphere and stratosphere, and the retrieval of a wider range of effective radii sizes than existing techniques by exploiting information from the 10.4 µm channel. Our results indicate that 0.73 ± 0.40 Tg of very fine ash (radius ≤ 15 µm) was injected into the atmosphere during the main eruptive period from 21 June 18:00 UTC to 22 June 10:00 UTC. The total mass of very fine ash decreased from 0.73 to 0.10 Tg over ∼ 48 h, with an e-folding time of 20 h. We estimate a distal fine ash mass fraction of 0.73 % ± 0.62 % based on the total mass of very fine ash retrieved and the ORAC-derived height–time series. Several distinct ash layers were revealed by the ORAC height retrievals. Generally, ash in the troposphere was composed of larger particles than ash present in the stratosphere. We also find that median ash cloud concentrations fall below peak ash concentration safety limits (&lt; 4 mg m−3) 11–16 h after the eruption begins, if typical ash cloud geometric thicknesses are assumed. The ORAC height retrievals for the near-source plume showed good agreement with GOES-17 side-view height data (R=0.84; bias = −0.75 km); however, a larger negative bias was found when comparing ORAC height retrievals for distal ash clouds against Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) measurements (R=0.67; bias = −2.67 km). The dataset generated here provides uncertainties at the pixel level for all retrieved variables and could potentially be used for dispersion model validation or be implemented in data assimilation schemes. Future work should focus on improving ash detection, improving height estimation in the stratosphere and exploring the added benefit of visible channels for retrieving effective radius and optical depth in opaque regions of nascent ash plumes.

A Bootstrap Variance Procedure for the Generalised Regression Estimator

SummaryThe generalised regression estimator (GREG) uses auxiliary data that are available from the finite population to improve the efficiency of the estimator of a total (mean). Estimators of the variance of GREG that have been proposed in the sampling literature include those based on Taylor linearisation and the jackknife techniques. Approximations based on Taylor expansions are reasonable for large samples. However, when the sample size is small, the Taylor‐based variance estimator has a large negative bias. The jackknife variance estimators overestimate the variance of GREG for small sample sizes. We offset these setbacks using a bootstrap procedure for estimating the variance of the GREG. The method uses a bootstrap population constructed with the model underlying the GREG estimator. Repeated samples are selected in the bootstrap population according to the design used to select the initial sample, and the variability associated with these bootstrap samples is used to compute the proposed bootstrap variance estimator. Simulations show that the new bootstrap estimator has a small bias for samples that have few observations.

Evaluation of Urban Canopy Models against Near-Surface Measurements in Houston during a Strong Frontal Passage

Urban canopy models (UCMs) in mesoscale numerical weather prediction models need evaluation to understand biases in urban environments under a range of conditions. The authors evaluate a new drag formula in the Weather Research and Forecasting (WRF) model’s multilayer UCM, the Building Effect Parameterization combined with the Building Energy Model (BEP+BEM), against both in-situ measurements in the urban environment as well as simulations with a simple bulk scheme and BEP+BEM using the old drag formula. The new drag formula varies with building packing density, while the old drag formula is constant. The case study is a strong cold frontal passage that occurred in Houston during the winter of 2017, causing high winds. It is found that both BEP+BEM simulations have lower peak wind speeds, consistent with near-surface measurements, while the bulk simulation has winds that are too strong. The constant-drag BEP+BEM simulation has a near-zero wind speed bias, while the new-drag simulation has a negative bias. Although the focus is on the impact of drag on the urban wind speeds, both BEP+BEM simulations have larger negative biases in the near-surface temperature than the bulk-scheme simulation. Reasons for the different performances are discussed.

Evaluation of simulations of near-surface variables using the regional climate model CCLM for the MOSAiC winter period

The ship-based experiment MOSAiC 2019/2020 was carried out during a full year in the Arctic and yielded an excellent data set to test the parameterizations of ocean/sea-ice/atmosphere interaction processes in regional climate models (RCMs). In the present paper, near-surface data during MOSAiC are used for the verification of the RCM COnsortium for Small-scale MOdel–Climate Limited area Mode (COSMO-CLM or CCLM). CCLM is used in a forecast mode (nested in ERA5) for the whole Arctic with 15 km resolution and is run with different configurations of sea ice data. These include the standard sea ice concentration taken from passive microwave data with around 6 km resolution, sea ice concentration from Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data and MODIS sea ice lead fraction data for the winter period. CCLM simulations show a good agreement with the measurements. Relatively large negative biases for temperature occur for November and December, which are likely associated with a too large ice thickness used by CCLM. The consideration of sea ice leads in the sub-grid parameterization in CCLM yields improved results for the near-surface temperature. ERA5 data show a large warm bias of about 2.5°C and an underestimation of the temperature variability.