Low-level Inversion Research Articles

Assessment of AIRS Version 7 Temperature Profiles and Low-Level Inversions with GRUAN Radiosonde Observations in the Arctic

The extensive global climate observing system (GCOS) reference upper-air network (GRUAN) datasets provide a chance to validate newly released Atmospheric Infrared Sounder (AIRS) version 7 (v7) products over the Arctic. This manuscript reports on the analysis performed to evaluate errors from AIRS version 6 (v6) and v7 temperature profiles and to characterize the derived low-level temperature inversion (LLI) representativeness in the Arctic region. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to reduce the vertical resolution of the radiosonde profiles for comparison. Due to improved retrieval algorithms, v7 produces smaller biases in the troposphere and suppresses the cold bias in v6. Nevertheless, the profile-averaged root mean square error (RMSE) increased by over 30% in v7, particularly in the winter half-year when v7 showed a larger RMSE below 800 hPa. The AIRS temperature retrieval accuracy is primarily sensitive to surface type and cloud fraction. Compared to v6, v7 has less bias over frozen land and sea ice in different cloud fraction conditions. However, the RMSEs of v7 are more sensitive to the effective cloud fraction (ECF) and are highly influenced by a more significant contribution from nonfrozen land samples. Compared to the kernel-averaged radiosonde profiles, more than 80% of the temperature profiles from v6 and v7 accurately detect LLIs. The discreteness of the AIRS’s predefined pressure level results is consistent with the radiosondes only 65% of the time for LLI depth calculation. In contrast, the AIRS can obtain LLI intensity with a relatively high correlation (>0.9). With the AIRS temperature retrieval in the boundary layer further improved, it has the potential to be used as an independent LLI detector in the Arctic region.

Importance of the choice of heat flux parameterization in regional air–sea coupled simulations: Case studies of marine heatwaves induced by atmospheric heatwaves in 1994 and 2018

This study investigated the marine heat wave events (MHWs) that occurred near the Korean Peninsula during the summer of 1994 and 2018, using a regional air–sea coupled model. We analyzed the fifth-generation reanalysis data, ERA5, published by the European Centre for Medium-Range Weather Forecasts for both events. We found that the North Pacific High and Tibetan High were stronger than usual and were associated with warm and moist air intrusion from the subtropical regions. Air-sea interactions play an important role in the development of MHWs. Warm and moist air combined with low-level inversion and a subsequent sinking motion induced the downward latent heat flux (LHF) toward the relatively colder sea surface, resulting in increased sea surface temperatures (SSTs). To quantify the contribution of the downward LHF and evaluate the importance of the relevant physical parameters of the MHWs, we set up two coupled model experiments, namely, CPL_down and CPL_nodown. Results show that the CPL_down experiment captured the downward LHF well in both events. The model also successfully captured the observed inversion near the surface. The cold SST bias tended to be reduced as the low-level clouds decreased in the area where the downward LHF occurred. In our simulation, permitting downward LHF improved the MHW reproducibility. Therefore, we suggest that the increased downward LHF is favorable for simulating MHWs, and surface physical parameterization must be carefully performed.

Aerosol-boundary layer dynamics and its effect on aerosol radiative forcing and atmospheric heating rate in the Indian Ocean sector of Southern Ocean

The study examines the thermodynamic structure of the marine atmospheric boundary layer (MABL) and its effect on the aerosol dynamics in the Indian Ocean sector of Southern Ocean (ISSO) between 30°S-67°S and 57°E-77°E. It includes observations of aerosols and meteorology collected during the Xth Southern Ocean Expedition conducted in December 2017. The results revealed the effect of frontal-region-specific air-sea coupling on the thermodynamic structure of MABL and its role in regulating aerosols in ISSO. The MABL over the subtropical front was unstable and formed a well-evolved mixed layer (≈2400 m) capped by low-level inversions (≈660 m). Convective activities in the Sub-Antarctic Frontal region were associated with the Agulhas Retroflection Current, which supported the formation of a well-developed mixed layer (≈1860 m). The mean estimates of aerosol optical depth (AOD) and black carbon (BC) mass concentrations were 0.095 ± 0.006 and 50 ± 14 ng m−3, respectively, and the resultant clear sky direct shortwave radiative forcing (DARF) and atmospheric heating rate (HR) were 1.32 ± 0.11 W m−2 and 0.022 ± 0.002 K day−1, respectively. In the polar front (PF) region, frequent mid-latitude cyclones led to highly stabilized MABL, supported low-level multi-layered clouds (>3-layers) and multiple high-level inversions (strength > 0.5 K m−1 > 3000 m). The clouds were mixed-phased with temperatures less than −12 °C at 3000 m altitude. Interestingly, there was higher loading of dust and BC aerosols (276 ± 24 ng m−3), maximum AOD (0.109 ± 0.009), clear sky DARF (1.73 ± 0.02 W m−2), and HR (0.029 ± 0.005 K day−1). This showed an accumulation of long-range advected anthropogenic aerosols within baroclinic-boundaries formed over the PF region. Specifically, in the region south of PF, weak convection caused weakly-unstable MABL with a single low-level inversion followed by no clouds/single-layer clouds. Predominant clean maritime air holding a small fraction of dust and BC accounted for lower estimates of AOD (0.071 ± 0.004), BC concentrations (90 ± 55 ng m−3) and associated clear sky DARF and HR were 1.16 ± 0.06 W m−2 and 0.019 ± 0.001 K day−1, respectively.

Impact of the selected boundary layer schemes and enhanced horizontal resolution on the Weather Research and Forecasting model performance on James Ross Island, Antarctic Peninsula

The output of the various Weather Research and Forecasting (WRF) model configurations was compared with ground-based observations in the northern part of James Ross Island, Antarctic Peninsula. In this region, a network of automatic weather stations deployed at ice-free sites (as well as small glaciers) is operated by the Czech Antarctic Research Programme. Data from these stations provide a unique opportunity to evaluate the WRF model in a complex terrain of James Ross Island. The model was forced by the ERA5 reanalysis data and the University of Bremen sea ice data. The model configurations include a novel Three-Dimensional Scale-Adaptive Turbulent Kinetic Energy (3D TKE) planetary boundary layer scheme and a more traditional Quasi-Normal Scale Elimination (QNSE) scheme. Impact of model horizontal resolution was evaluated by running simulations in both 700 m and 300 m. The validation period, 25 May 2019 to 12 June 2019, was selected to cover different stratification regimes of air temperature and a significant snowfall event. Air temperature was simulated well except for strong low-level inversions. These inversions occurred in 44% of all cases and contributed to a higher mean bias (2.0–2.9°C) at low-elevation sites than at high altitude sites (0.2–0.6°C). The selection of the 3D TKE scheme led to improvement at low-elevation sites; at high altitude sites, the differences between model configurations were rather small. The best performance in wind speed simulation was achieved with the combination of the 3D TKE scheme and 300 m model resolution. The most important improvement was decrease of bias at a coastal Mendel Station from 3.5 m·s‑1 with the QNSE scheme on the 700 m grid to 1.2 m·s‑1 with the 3D TKE scheme on the 300 m grid. The WRF model was also proven to simulate a large snowfall event with a good correspondence with the observed snow height.

A Model-Based Climatology of Low-Level Jets in the Weddell Sea Region of the Antarctic

Low-level jets (LLJs) are climatological features in polar regions. It is well known that katabatic winds over the slopes of the Antarctic ice sheet are associated with strong LLJs. Barrier winds occurring, e.g., along the Antarctic Peninsula may also show LLJ structures. A few observational studies show that LLJs occur over sea ice regions. We present a model-based climatology of the wind field, of low-level inversions and of LLJs in the Weddell Sea region of the Antarctic for the period 2002–2016. The sensitivity of the LLJ detection on the selection of the wind speed maximum is investigated. The common criterion of an anomaly of at least 2 m/s is extended to a relative criterion of wind speed decrease above and below the LLJ. The frequencies of LLJs are sensitive to the choice of the relative criterion, i.e., if the value for the relative decrease exceeds 15%. The LLJs are evaluated with respect to the frequency distributions of height, speed, directional shear and stability for different regions. LLJs are most frequent in the katabatic wind regime over the ice sheet and in barrier wind regions. During winter, katabatic LLJs occur with frequencies of more than 70% in many areas. Katabatic LLJs show a narrow range of heights (mostly below 200 m) and speeds (typically 10–20 m/s), while LLJs over the sea ice cover a broad range of speeds and heights. LLJs are associated with surface inversions or low-level lifted inversions. LLJs in the katabatic wind and barrier wind regions can last several days during winter. The duration of LLJs is sensitive to the LLJ definition criteria. We propose to use only the absolute criterion for model studies.

Characteristics of low-level temperature inversions over the Arctic Ocean during the CHINARE 2018 campaign in summer

Across the Arctic Ocean, the semi-permanent sea-ice layer insulates the atmosphere from the Arctic Ocean, thereby influencing the lower boundary conditions of the atmosphere in this region. The presence of a temperature inversion predominantly characterizes the Arctic lower troposphere throughout the year. The 9th Chinese National Arctic Research Expedition took place in the Pacific Sectors of the Arctic Ocean from July to September 2018, gathering high-resolution radiosonde data to provide a detailed structure of the low-level temperature inversion (LLI) over the summer months. Statistical analyses showed that LLIs occurred most frequently below 500m and were generally weaker and shallower than those occurring during the winter months. Low-level inversions are influenced by both local meteorology and large scale synoptic conditions. The continual presence of low-level clouds or fog tends to lift the inversion layer at the local scale, transferring it from a surface-based inversion (SBI) to an elevated inversion (EI). By contrast, SBIs were found to dominate over regions of melting sea-ice. Regimes, where the cloud top penetrated the inversion base were more frequently observed than cloud capped by inversion regimes. Inversions tended to be deeper, stronger, and with a lower base during cloud top penetrating inversion base regimes. At the synoptical scale, the intense poleward intrusions of warm air brought moist air to the top of low-level inversions, creating a robust thermal stratification between layers and promoting extensive and frequency occurrences of low cloud/fog. Moreover, the polar high contributed to establishing a multilayer inversion structure at relatively high altitudes by subsidence. These findings contribute to an improving understanding of low-level vertical temperature structures and their influence on a rapidly warming Arctic.

Climatology of low-level temperature inversions over China based on high-resolution radiosonde measurements

Low-level temperature inversions play crucial roles in inhibiting vertical exchange of energy and mass, and may lead to air pollutants accumulation. The climatological study of them provides a fundamental overview of the static stability of atmosphere and is indispensable for air pollution controls. Based on high-vertical-resolution radiosondes at 00 and 12 UTC during 2011–2018, this work comprehensively examined the spatial and temporal variability of three characteristics (occurrences, strengths, and depths) of low-level inversions in China. Results revealed that inversions are prevalent (more than 80% of the observation records) over Eastern China. The northern part of Eastern China is dominated by the thick strong surface-based inversions with median thickness and strength of 200 m and 3 K, while the southern part by thin weak elevated ones of 80 m and 0.8 K. Tibetan Plateau experiences rare inversions (less than 50% of the time) which tend to be strong thick surface-based inversions with median depth and intensity of 170 m and 4 K. Inversion depths and strengths are positively correlated. The three properties of inversions present remarkable seasonal variations. Generally, inversions are strongest, thickest, and most frequent in winter and least so in summer, with median intensity and depth ranging from 0.3 K and 80 m to 5 K and 220 m. This paper also analyzed the monthly variations of inversions of four representative stations (Harbin, Urumqi, Beijing, and Chongqing) in details. These four cities are known for frequent severe air pollution events. The quantitative investigations of inversions may play a significant role in atmospheric environmental management.

Air-Traffic Restrictions at the Madeira International Airport Due to Adverse Winds: Links to Synoptic-Scale Patterns and Orographic Effects

The Madeira International Airport (MIA) lies on the island’s south-eastern coast and it is known to be exposed to wind hazards. A link between these adverse winds at MIA and the synoptic-scale circulation is established using a weather type (WT) classification. From April to September (summer period), five WTs prevail, cumulatively representing nearly 70% of days. These WTs reflect the presence of well-established Azores high, with some variations on location and strength. Although with a low frequency of occurrence (<5%), this anticyclone occasionally strengthens and extends towards Iberia, inducing anomalously strong NNE/NE up to 3–5 km over Madeira. The most severe and longer-lasting wind conditions at the MIA, with a higher frequency of gusts above 35 kt, are driven by this synoptic-scale pattern and are more common in summer. An episode of adverse winds at the MIA is analysed, illustrating the occurrence of upstream stagnation, flow splitting, and lee wake formation. The upstream conditions include a low-level inversion, strong NNE/NE winds near and above the inversion and a Froude number less than 1. The AROME (Application of Research to Operations at Mesoscale) model predicted the occurrence of downslope winds, in association with a large-amplitude mountain wave. At this time, the strongest wind gusts were registered and one aircraft executed a missed approach. The wind regime in different places of the island suggests that these conditions are relatively frequent, mostly in summer. Finally, objective verification of AROME wind forecast, for a three-year period and from June to August, is discussed.

Evaluating Himawari-8 Cloud Products Using Shipborne and CALIPSO Observations: Cloud-Top Height and Cloud-Top Temperature

AbstractCloud-top height (CTH) and cloud-top temperature (CTT) retrieved from the Himawari-8 observations are evaluated using the active shipborne radar–lidar observations derived from the 31-day Clouds, Aerosols, Precipitation Radiation and Atmospheric Composition over the Southern Ocean (CAPRICORN) experiment in 2016 and 1-yr observations from the spaceborne Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) cloud product over a large sector of the Southern Ocean. The results show that the Himawari-8 CTH (CTT) retrievals agree reasonably well with both the shipborne estimates, with a correlation coefficient of 0.837 (0.820), a mean bias error of 0.226 km (−2.526°C), and an RMSE of 1.684 km (10.069°C). In the comparison with CALIOP, the corresponding quantities are found to be 0.786 (0.480), −0.570 km (1.343°C), and 2.297 km (25.176°C). The Himawari-8 CTH (CTT) generally falls between the physical CTHs observed by CALIOP and the shipborne radar–lidar estimates. However, major systematic biases are also identified. These errors include (i) a low (warm) bias in CTH (CTT) for warm liquid cloud type, (ii) a cold bias in CTT for supercooled liquid water cloud type, (iii) a lack of CTH at ~3 km that does not have a corresponding gap in CTT, (iv) a tendency of misclassifying some low-/mid-top clouds as cirrus and overlap cloud types, and (v) a saturation of CTH (CTT) around 10 km (−40°C), particularly for cirrus and overlap cloud types. Various challenges that underpin these biases are also explored, including the potential of parallax bias, low-level inversion, and cloud heterogeneity.

Inversion Climatology in High-Production Agricultural Regions of Missouri and Implications for Pesticide Applications

ABSTRACTMost pesticides applied in the United States have labels that include language prohibiting application during temperature inversions. This restriction, which is well known and is followed by aerial pesticide applicators, has more recently become a focus for ground pesticide applicators. This is partially due to the recent introduction of genetically engineered soybean and cotton with tolerance to dicamba herbicide. Dicamba has been utilized for more than 50 years to control weeds in grain crops, such as corn. In 2017, dicamba was approved for use in dicamba-tolerant soybean and cotton. In 2017 and 2018, dicamba movement onto nontarget plants was substantial. As based on patterns of injury to nontolerant crops and time of applications, some of which occurred during the evening, inversions were likely contributors to off-target movement. Historically, most research on surface temperature inversions and pesticides focused on aerial applications. Research presented here focused on development of inversion profiles at atmospheric heights relevant to ground applications, which typically occur 46–107 cm above ground level (AGL). During the 2015–17 soybean growing seasons, data were collected at three heights AGL (46, 168, and 305 cm) in three soybean-producing regions of Missouri to characterize inversions. Over 600 inversions were characterized; all were nocturnal in nature. Inversions typically lasted overnight at two locations; duration varied at the third. The largest temperature difference recorded was 6°C. This research has resulted in real-time inversion monitoring that is available online to applicators (http://agebb.missouri.edu/weather/realTime/maps/index.php#temp_inversion), and the data generated can be utilized to improve accuracy of low-level inversion forecasting models.

Applying Anomaly-based Weather Analysis to the Prediction of Low Visibility Associated with the Coastal Fog at Ningbo-Zhoushan Port in East China

Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 January 2016 over Ningbo-Zhoushan Port, Zhejiang Province, East China, was first examined. Some basic features from the anomalous weather analysis for this case were identified: (1) the process of low visibility mainly caused by coastal fog was a direct response to anomalous temperature inversion in the lower troposphere, with a warm center around the 925 hPa level, which was formed by a positive geopotential height (GPH) anomaly in the upper troposphere and a negative GPH anomaly near the surface; (2) the positive humidity anomaly was conducive to the formation of coastal fog and rain; (3) regional coastal fog formed at the moment when the southwesterly wind anomalies transferred to northeasterly wind anomalies. Other cases confirmed that the low visibility associated with coastal fog depends upon low-level inversion, a positive humidity anomaly, and a change of wind anomalies from southwesterly to northeasterly, rain and stratus cloud amount. The correlation coefficients of six-hourly inversion, 850–925-hPa-averaged temperature, GPH and humidity anomalies against visibility are −0.31, 0.40 and −0.48, respectively, reaching the 99% confidence level in the first half-years of 2015 and 2016. By applying the anomaly-based weather analysis method to medium-range model output products, such as ensemble prediction systems, the anomalous temperature-pressure pattern and humidity—wind pattern can be used to predict the process of low visibility associated with coastal fog at several days in advance.

Loss to Aviation Economy Due to Winter Fog in New Delhi during the Winter of 2011–2016

Stable and clear atmospheric conditions, lower surface temperatures, an ample moisture supply, and a strong low-level inversion persisting for most of the night usually facilitates the formation of dense fog during winter in Delhi. This severely hinders the flight operations at India’s busiest airport, the Indira Gandhi International (IGI) Airport, where more than 900 flight operations occur per day and an interruption can cause significant financial losses to the aviation industry. It is important to undertake a quantitative study of the estimated losses. This study, undertaken for the first time in India, aimed to evaluate the impact of dense fog at IGI Airport on economic losses which occurred during the winter season between 2011 and 2016. The breakdown of charges for different segments of flight operations for the domestic and international sectors was obtained from India’s Ministry of Civil Aviation and the Center for Asia Pacific Aviation (CAPA) India. A total of 653 h of dense fog between 2011 and 2016 at IGI Airport caused economic losses of approximately 3.9 million USD (248 million Indian rupees) to the airlines. The analysis further found that from 2014–2015 onwards, there has been a reduction in the number of flight delays, diversions, and cancellations by approximately 88%, 55%, and 36%, respectively, due to the strict implementation of guidelines to facilitate the Category (CAT)-III landing for aircraft during dense fog.

Research and Analysis of a Persistent Heavy Pollution Event in Ningbo, China

From 7 to 12 January 2015, there was a rare persistent severe pollution event in Ningbo. Based on the data from routine weather observation, automatic weather station in Zhejiang Province and urban pollutant monitoring in Ningbo City, by using the particle backward trajectory analysis of NOAA HYSPLIT4 model, the diagnosis and analysis of the pollution development and dissipation process were carried out. The results show that: 1) Pollutants carried by cold air are main reason for pollution in the first stage of the pollution process. The transition from near-surface northwest wind to north-northeast wind is the key to air improvement; 2) Favorable atmospheric circulation is the important reason for the long-term persistence of pollution. The long-term control of high-pressure center and low-level inversion between the two cold air effects make the boundary layer particularly stable, while the low horizontal wind speed is beneficial to polluting particles. With the continuous accumulation, the contaminated particles can not effectively diffuse either vertically or horizontally; 3) In the late period of January 11, the supplement of weak cold air in the East Road made the air quality index (AQI) climb to about 300 again. The two advection conveyances of cold air to pollutant particles and the long-term stable maintenance of weather conditions conducive to the accumulation of pollutant particles are two important reasons for this rare and sustained heavy pollution event.

The Thermodynamic Structure of Arctic Coastal Fog Occurring During the Melt Season over East Greenland

An automated method to classify Arctic fog into distinct thermodynamic profiles using historic in-situ surface and upper-air observations is presented. This classification is applied to low-resolution Integrated Global Radiosonde Archive (IGRA) soundings and high-resolution Arctic Summer Cloud Ocean Study (ASCOS) soundings in low- and high-Arctic coastal and pack-ice environments. Results allow investigation of fog macrophysical properties and processes in coastal East Greenland during melt seasons 1980–2012. Integrated with fog observations from three synoptic weather stations, 422 IGRA soundings are classified into six fog thermodynamic types based on surface saturation ratio, type of temperature inversion, fog-top height relative to inversion-base height and stability using the virtual potential temperature gradient. Between 65–80% of fog observations occur with a low-level inversion, and statically neutral or unstable surface layers occur frequently. Thermodynamic classification is sensitive to the assigned dew-point depression threshold, but categorization is robust. Despite differences in the vertical resolution of radiosonde observations, IGRA and ASCOS soundings yield the same six fog classes, with fog-class distribution varying with latitude and environmental conditions. High-Arctic fog frequently resides within an elevated inversion layer, whereas low-Arctic fog is more often restricted to the mixed layer. Using supplementary time-lapse images, ASCOS microwave radiometer retrievals and airmass back-trajectories, we hypothesize that the thermodynamic classes represent different stages of advection fog formation, development, and dissipation, including stratus-base lowering and fog lifting. This automated extraction of thermodynamic boundary-layer and inversion structure can be applied to radiosonde observations worldwide to better evaluate fog conditions that affect transportation and lead to improvements in numerical models.

Quantifying the relationship between PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; concentration, visibility and planetary boundary layer height for long-lasting haze and fog–haze mixed events in Beijing

Abstract. Air quality and visibility are strongly influenced by aerosol loading, which is driven by meteorological conditions. The quantification of their relationships is critical to understanding the physical and chemical processes and forecasting of the polluted events. We investigated and quantified the relationship between PM2.5 (particulate matter with aerodynamic diameter is 2.5 µm and less) mass concentration, visibility and planetary boundary layer (PBL) height in this study based on the data obtained from four long-lasting haze events and seven fog–haze mixed events from January 2014 to March 2015 in Beijing. The statistical results show that there was a negative exponential function between the visibility and the PM2.5 mass concentration for both haze and fog–haze mixed events (with the same R2 of 0.80). However, the fog–haze events caused a more obvious decrease of visibility than that for haze events due to the formation of fog droplets that could induce higher light extinction. The PM2.5 concentration had an inversely linear correlation with PBL height for haze events and a negative exponential correlation for fog–haze mixed events, indicating that the PM2.5 concentration is more sensitive to PBL height in fog–haze mixed events. The visibility had positively linear correlation with the PBL height with an R2 of 0.35 in haze events and positive exponential correlation with an R2 of 0.56 in fog–haze mixed events. We also investigated the physical mechanism responsible for these relationships between visibility, PM2.5 concentration and PBL height through typical haze and fog–haze mixed event and found that a double inversion layer formed in both typical events and played critical roles in maintaining and enhancing the long-lasting polluted events. The variations of the double inversion layers were closely associated with the processes of long-wave radiation cooling in the nighttime and short-wave solar radiation reduction in the daytime. The upper-level stable inversion layer was formed by the persistent warm and humid southwestern airflow, while the low-level inversion layer was initially produced by the surface long-wave radiation cooling in the nighttime and maintained by the reduction of surface solar radiation in the daytime. The obvious descending process of the upper-level inversion layer induced by the radiation process could be responsible for the enhancement of the low-level inversion layer and the lowering PBL height, as well as high aerosol loading for these polluted events. The reduction of surface solar radiation in the daytime could be around 35 % for the haze event and 94 % for the fog–haze mixed event. Therefore, the formation and subsequent descending processes of the upper-level inversion layer should be an important factor in maintaining and strengthening the long-lasting severe polluted events, which has not been revealed in previous publications. The interactions and feedbacks between PM2.5 concentration and PBL height linked by radiation process caused a more significant and long-lasting deterioration of air quality and visibility in fog–haze mixed events. The interactions and feedbacks of all processes were particularly strong when the PM2.5 mass concentration was larger than 150–200 µg m−3.

Assessment of the Uncertainties in Arctic Low-Level Temperature Inversion Characteristics in Radio Occultation Observations

The variation of low-level inversion characteristics is one of the important factors for Arctic amplification. Radiosonde (RS) observations are one of the reliable tools to study Arctic inversions. However, they provide limited information on the spatial distribution of temperature inversions. The radio occultation (RO) technique can provide accurate, all-weather, high vertical resolution atmospheric parameter profiles over both land and ocean. In this paper, the RO technique is investigated to estimate the inversions, and their uncertainties are assessed via comparing with the RS inversions. Results show that the inversions (base, depth, and strength) from RS and RO observations are lower, deeper, and stronger in winter than in autumn, spring, and summer. Moreover, comparisons of spatiotemporally synchronized RO and RS inversions (i.e., Scheme I) during 2007–2013 reveal that the former are higher, deeper, and weaker than the latter. Further comparisons of RS and $5 {^{\circ }} \times 5 {^{\circ }}$ gridded RO inversions (i.e., Scheme II) show smaller overall standard deviations than Scheme I, indicating that the gridded RO observations can better describe the large-scale spatial structure of temperature inversions. Furthermore, corrections of the observed remarkable systematic differences between RO and RS inversions in both the schemes are also made. The results show that the RO inversions can be well calibrated, and that greater improvements in RO inversions calibration are achieved in Scheme II than in Scheme I. Therefore, the RO technique could be a potential tool to study the Arctic low-level temperature inversions as well as improve our understanding of Arctic climate change.

Numerical simulations of atmospheric dispersion of iodine-131 by different models.

Nowadays, several dispersion models are available to simulate the transport processes of air pollutants and toxic substances including radionuclides in the atmosphere. Reliability of atmospheric transport models has been demonstrated in several recent cases from local to global scale; however, very few actual emission data are available to evaluate model results in real-life cases. In this study, the atmospheric dispersion of 131I emitted to the atmosphere during an industrial process was simulated with different models, namely the WRF-Chem Eulerian online coupled model and the HYSPLIT and the RAPTOR Lagrangian models. Although only limited data of 131I detections has been available, the accuracy of modeled plume direction could be evaluated in complex late autumn weather situations. For the studied cases, the general reliability of models has been demonstrated. However, serious uncertainties arise related to low level inversions, above all in case of an emission event on 4 November 2011, when an important wind shear caused a significant difference between simulated and real transport directions. Results underline the importance of prudent interpretation of dispersion model results and the identification of weather conditions with a potential to cause large model errors.

An investigation on the dynamic and scale interactive processes for estimating the predictability of cloudburst over elevated orography

The cloudburst is defined as a heavy downpour at a very high rainfall rate over small spatio-temporal scale. The Indian states of Uttarakhand (30°15′N; 79°15′E) and Himachal Pradesh (32°29′N; 75°10′E) are prone to cloudburst due to its geographical setup. The large-scale monsoon flow along with elevated orography makes cloudburst phenomena frequent a well as severe over the regions. However, cloudburst and the heavy rainfall events occasionally, become difficult to distinguish. The present study attempts to identify the processes associated with cloudburst over elevated orography and compare it with one of the most debated event of 2013 which was reported as heavy rainfall but, not a cloudburst by Indian Meteorological Department (IMD). The temporal variations of rainfall and cloud-top pressure (CTP) are considered to identify the genesis of the event. The vertical developments of the system along with large-scale circulation pattern are estimated in the present study. The result of the study reveals that the mid-tropospheric dry entrainment, low-level temperature inversion and cloud height clearly distinguish the “cloudburst” and “heavy rainfall” events and confirms that the system of 2013 was indeed a heavy rainfall event and not a cloudburst.

Improving simulations of precipitation phase and snowpack at a site subject to cold air intrusions: Snoqualmie Pass, WA

Low-level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet, these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. Correlations of phase between surface-based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to -6% of accumulated snow water equivalent) by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast

Analysis of a 7-year low-level temperature inversion data set measured at the 280 m high Hamburg weather mast