Strength Of Temperature Inversion Research Articles

Changing PM2.5 and related meteorology over India from 1950–2014: a new perspective from a chemistry-climate model ensemble

Surface PM2.5 concentrations in India have increased dramatically as emissions have risen in recent years. The role of meteorological factors in this increase is unclear, mainly due to a lack of long-term observations over the region. A 12-member ensemble of historical (1950–2014) simulations from the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6) offers an unprecedented opportunity to examine simulated PM2.5 and meteorology for 20th century climates that can arise due to ‘climate noise’ under the same historical greenhouse gas and air pollutant emission trajectories. CESM2-WACCM6 includes interactive aerosol and gas-phase chemistry in the atmosphere coupled to ocean-sea ice-land models, and each ensemble member differs only in its initial conditions of the climate state. We systematically examine, decade-by-decade, the changes in PM2.5 and associated meteorology, including wind speed, surface temperature inversions, boundary layer height, precipitation, and relative humidity in four cities in India: Chennai, Kolkata, Mumbai, and New Delhi. Forced changes clearly emerge in meteorological variables from 1950 to 2014, including increases in both relative humidity and temperature inversion strength, and decreases in boundary layer height and average surface wind speed. The timing of these changes varies by city: boundary layer heights decrease most over New Delhi in the premonsoon season (ensemble average decrease of 400 m), but over Mumbai in the postmonsoon season (ensemble average decrease of 100 m). PM2.5 concentrations increase across India regardless of climate variability, with an almost threefold increase from 1950 to 2014 over New Delhi. Analysis of dimensionless variables shows that PM2.5 exhibits larger ensemble mean trends and smaller variability than the trends in the meteorological variables, enabling us to infer that the increase in PM2.5 is predominantly controlled by increases in anthropogenic emissions rather than climate variability. Overall, our simulations corroborate the dominant role of air pollutant emissions on poor air quality in India.

Spatio-temporally differentiated impacts of temperature inversion on surface PM2.5 in eastern China

Temperature inversion (TI) is one of the meteorological conditions that significantly affect regional air quality. Knowledge gap regarding the impacts of TI on surface PM2.5 in different topographies still existed. In the present study, the occurrence frequency, temperature lapse rate (TLR), depth, and the diurnal variations of TI, surface-based TI (SBTI), elevated TI (ElTI), and multiple layers of TIs (MultiTI) and their impacts on near-surface PM2.5 concentrations over eastern China that covers a range of topographies and climates, are systematically investigated based on global reanalysis ERA5 and the nationwide monitoring PM2.5 dataset from 2014 to 2020. TIs occurred mostly in the early morning. Different types of TIs present distinctive seasonal and spatial patterns. The majority of SBTIs and ElTIs occurred during nighttime in northern China and daytime in southern China, respectively, as the result of their formation mechanisms. SBTIs usually had larger TLR while ElTIs had deeper depth. SBTIs showed strong enhancement effects on PM2.5 concentration over the study domain while ElTIs showed more obvious impacts on northern nocturnal PM2.5. The peak time of PM2.5 was found around 18:00–22:00 LST, and TLR and depth of TIs are thought to be more relevant to PM2.5 peak concentration due to their coincident peak times. The strength of TIs is therefore more crucial in regulating PM2.5 than its occurrence frequency. Based on statistical analysis, our study provided a large picture of the generic spatiotemporal patterns of TIs and illustrated the impacts of different TIs on surface PM2.5 pollution on a diurnal basis. For a deeper understanding of the formation of PM2.5 pollution, more attention needs to be paid to the nocturnal PM2.5 not only at surface level but also at higher levels in the presence of TIs.

Varied midlatitude shortwave cloud radiative responses to Southern Hemisphere circulation shifts

AbstractChanges in midlatitude clouds as a result of shifts in general circulation patterns are widely thought to be a potential source of radiative feedbacks onto the climate system. Previous work has suggested that two general circulation shifts anticipated to occur in a warming climate, poleward shifts in the midlatitude jet streams and a poleward expansion of the Hadley circulation, are associated with differing effects on midlatitude clouds. This study examines two dynamical cloud‐controlling factors, mid‐tropospheric vertical velocity, and the estimated inversion strength (EIS) of the marine boundary layer temperature inversion, to explain why poleward shifts in the Southern Hemisphere midlatitude jet and Hadley cell edge have varying shortwave cloud‐radiative responses at midlatitudes. Changes in vertical velocity and EIS occur further equatorward for poleward shifts in the Hadley cell edge than they do for poleward shifts of the midlatitude jet. Because the sensitivity of shortwave cloud radiative effects (SWCRE) to variations in vertical velocity and EIS is a function of latitude, the SWCRE anomalies associated with jet and Hadley cell shifts differ. The dynamical changes associated with a poleward jet shift occur further poleward in a regime where the sensitivities of SWCRE to changes in vertical velocity and EIS balance, leading to a near‐net zero change in SWCRE in midlatitudes with a poleward jet shift. Conversely, the dynamical changes associated with Hadley cell expansion occur further equatorward at a latitude where the sensitivity of SWCRE is more strongly associated with changes in mid‐tropospheric vertical velocity, leading to a net shortwave cloud radiative warming effect in midlatitudes.

Surface-based nocturnal air temperature inversions in southern Poland and their influence on PM10 and PM2.5 concentrations in Upper Silesia

The frequency, strength and seasonal variations of surface-based temperature inversions (SBTIs) in Upper Silesia (Southern Poland) were examined using data from January 2001 to September 2020. Based on the air temperatures recorded at the meteorological station of the Institute of Earth Sciences in Sosnowiec (263 m a.s.l.) at heights of 2 m and 88 m above the ground, the vertical temperature gradient of the 100-m layer (γSos100 m) was determined. A lapse rate of γSos100 m > 0.5 K was defined as a temperature inversion. The measurements for 00 UTC (midnight) and 12 UTC (midday) were compared with data from the upper air station in Wrocław (116 m a.s.l.) located in the Lower Silesia Lowland, approximately 170 km NW of Sosnowiec. Based on soundings from Wrocław, in addition to the temperature gradient in the lower 100-m layer of air (γWrc100), three other characteristics of SBTIs were calculated: inversion depth (ID) or thickness in metres, inversion strength (ΔTi) in K and vertical temperature gradients across the whole SBTI layer γi in K 100 m−1. On an annual basis, the frequency of nighttime SBTIs (γ > 0.5 K 100 m−1) ranged from 47% in Sosnowiec to almost 59% in Wrocław. At both stations, the fewest SBTIs occurred in winter (23–38%) and the most in summer (64–75%). Moreover, they were more frequent in spring (52–61%) than in autumn (49–59%). The SBTI frequency was very low during the midday hours, amounting to 0.6–0.7% days a year, and it increased to 1–2% only in winter. Annually, the depth of 81% of inversions ranged between 50 and 300 m, varying seasonally from almost 67% in winter to 87% in summer. The presented research shows that SBTIs in winter were among the main factors contributing to a high concentration of particulate matter pollutants in the ground-level atmosphere. During nights with temperature inversions, the annual mean PM10 concentration reached 125% of the mean value, ranging from 114% in summer to 189% in winter.

Characteristics of temperature inversion from radiosonde measurements in the Western Ghats region

The characteristics of temperature inversion (TI) are believed to be dependent on topographical features and synoptic regime. Western Ghats (WGs) mountains located in the west coast of India have a complex topography, and the TI features for this region remain unknown due to the complexity and non-availability of observational datasets. This study investigates TI characteristics in the troposphere using high-resolution radiosonde data (2012–2015). The radiosonde measurements are collected at Mahabaleshwar (17.92°N, 73.6°E, ~1.4 km above mean sea level, AMSL), a high-altitude site in the WGs. The characteristics of TI in terms of height, depth, and strength (i.e., temperature difference between base and top of the inversion layer) are studied. The results showed that TI occurs in all seasons, however, their frequency differs. Winter (Dec.-Feb.) shows the maximum number of inversions followed by pre-monsoon (Mar.-May), post-monsoon (Oct.-Nov.), and monsoon (Jun.-Sep.). In winter, the depth of inversion is higher; however, the inversion strength is weaker as compared to other seasons. The TI strength is always below 5 K. Apart from surface-based inversions, elevated and upper-tropospheric inversions are also observed. Vertical and horizontal wind shear profiles along with ERA-5 data were analyzed to examine the plausible mechanism for TI to occur.

Near-surface Temperature Inversion over the East China Sea

Temperature inversion structure affects the boundary layer activity and convective activity. The frequency, strength, and formation mechanism of near-surface temperature inversion are studied using sounding data at three stations over the East China Sea from 2000 to 2015. The results show that the frequency and strength of the inversion are larger in summer (over Cheju station) than in winter (over ROIG station). The inversion is mainly classified as advection inversion over Cheju station, while mainly classified as radiation inversion over ROIG station. Low cloud amount in winter is larger than that in summer over the East China Sea, which is opposite to the inversion frequency. The reason is that the frequent and strong inversions hinder the height of convection in summer, it is difficult for moist air to reach the lifting condensation level and form clouds.

Study on conceptual model of regional pollution meteorological conditions in Guanzhong Urban Agglomeration

This paper defined regional pollution day and regional heavy pollution day, calculated the atmospheric stability by Pasqual classification and the height of mixed layer by national standard method, established a conceptual model of meteorological conditions in Guanzhong Urban Agglomeration. The results show that：(1) The more possibility of the regional pollution and regional heavy pollution is, the lower the mixing layer height is. (2)The frequency of stability increased with degree of pollution, the frequency of regional heavy pollution stability reached nearly 60% as regional heavy pollution. (3)In heavily polluted area, the frequency of ground temperature inversion is nearly 90%, the average cumulative temperature inversion thickness is 260m at assurance rate of 80%, and the maximum temperature inversion strength is 10.8℃/100m. (4) Regional pollution is easy to occur when the frequency of quiet wind is higher than 50%. At the same time, it is easy to form wind convergence area in the hinterland of Guanzhong Area, which causes the accumulation of pollutants.

Observed Upper Ocean Seasonal and Intraseasonal Variability in the Andaman Sea

AbstractThe observed seasonal and intraseasonal evolution of near‐surface meteorological and oceanographic variables in the Andaman Sea for the period March 2014 to December 2017 are examined using moored buoy observations at 10.5°N, 94°E. The amplitude of temperature inversions is very weak (0.2 to 0.4 °C), and they appeared primarily during winter (November–January) and latter part of summer (May–August). The net surface heat flux plays a primary role, and vertical processes term contributes secondarily to determine the seasonal mixed layer (ML) heat storage variability. Consistent with the seasonal variations of formation and strength of temperature inversion, vertical processes term shows a positive tendency during winter. The sea surface salinity shows large amplitude intraseasonal variability during fall and winter, and it is attributed to the variability of horizontal circulation in the presence of large lateral sea surface salinity gradients at the mooring location. The sea surface temperature shows the presence of strong intraseasonal variability between 20 and 80 days, though its amplitude of oscillation is distinctly higher during May–October than November–April. Band‐pass filtered (20–80 days) time series of different components of the ML heat budget shows that the net surface heat flux primarily determines the intraseasonal ML heat storage variability. Our analysis further shows that during May–October, both net shortwave radiation and latent heat flux together determine the modulation of the intraseasonal net surface heat flux. In contrast, latent heat flux acts as the sole factor to determine the modulation of the intraseasonal net surface heat flux during November–April.

Projected change in characteristics of near surface temperature inversions for southeast Australia

Air pollution has significant impacts on human health. Temperature inversions, especially near surface temperature inversions, can amplify air pollution by preventing convective movements and trapping pollutants close to the ground, thus decreasing air quality and increasing health issues. This effect of temperature inversions implies that trends in their frequency, strength and duration can have important implications for air quality. In this study, we evaluate the ability of three reanalysis-driven high-resolution regional climate model (RCM) simulations to represent near surface inversions at 9 sounding sites in southeast Australia. Then we use outputs of 12 historical and future RCM simulations (each with three time periods: 1990–2009, 2020–2039, and 2060–2079) from the NSW/ACT (New South Wales/Australian Capital Territory) Regional Climate Modelling (NARCliM) project to investigate changes in near surface temperature inversions. The results show that there is a substantial increase in the strength of near surface temperature inversions over southeast Australia which suggests that future inversions may intensify poor air quality events. Near surface inversions and their future changes have clear seasonal and diurnal variations. The largest differences between simulations are associated with the driving GCMs, suggesting that the large-scale circulation plays a dominant role in near surface inversion strengths.

Suppression of Arctic Air Formation with Climate Warming: Investigation with a Two-Dimensional Cloud-Resolving Model

AbstractArctic climate change in winter is tightly linked to changes in the strength of surface temperature inversions, which occur frequently in the present climate as Arctic air masses form during polar night. Recent work proposed that, in a warmer climate, increasing low-cloud optical thickness of maritime air advected over high-latitude landmasses during polar night could suppress the formation of Arctic air masses, amplifying winter warming over continents and sea ice. But this mechanism was based on single-column simulations that could not assess the role of fractional cloud cover change. This paper presents two-dimensional cloud-resolving model simulations that support the single-column model results: low-cloud optical thickness and duration increase strongly with initial air temperature, slowing the surface cooling rate as the climate is warmed. The cloud-resolving model cools less at the surface than the single-column model, and the sensitivity of its cooling to warmer initial temperatures is also higher, because it produces cloudier atmospheres with stronger lower-tropospheric mixing and distributes cloud-top cooling over a deeper atmospheric layer with larger heat capacity. Resolving larger-scale cloud turbulence has the greatest impact on the microphysics schemes that best represent general observed features of mixed-phase clouds, increasing their sensitivity to climate warming. These findings support the hypothesis that increasing insulation of the high-latitude land surface by low clouds in a warmer world could act as a strong positive feedback in future climate change and suggest studying Arctic air formation in a three-dimensional climate model.

First assimilation of temperature lidar data into an NWP model: impact on the simulation of the temperature field, inversion strength and PBL depth

The impact of assimilating lower‐tropospheric lidar temperature profiles into a numerical weather prediction (NWP) model was investigated. The profiles were measured with the Temperature Rotational Raman Lidar (TRRL) of the University of Hohenheim on 24 April 2013. The day showed the development of a typical daytime planetary boundary layer (PBL) with no optically thick clouds. The Weather Research and Forecasting (WRF) model was operated with 57 vertical levels covering Central Europe with 3 km horizontal resolution. Three different experiments were carried out with a rapid update cycle with hourly three‐dimensional variational data assimilation. The impact run (ALL_DA) was performed with the assimilation of conventional data and the additional assimilation of TRRL profiles between 0900 and 1800 UTC in a height range from about 500 to 3000 m above ground level with a vertical resolution of about 100 m. In CONV_DA and NO_DA, only conventional data and no data were assimilated, respectively. To consider the representativeness of the TRRL profiles, an observation error of 0.7 K was used for all heights. The assimilation was performed using the radiosonde operator. The TRRL data assimilation corrected the temperature profiles towards the lidar data. In the mean, the boundary‐layer height was improved by 60 m in ALL_DA compared to the TRRL data and the temperature gradient in the entrainment layer by 0.19 K (100 m)−1. While ALL_DA showed a root mean square error (RMSE) of 0.6 K compared to the TRRL data, the RMSE of CONV_DA was twice as large. Compared to data from radiosondes launched at the TRRL site, ALL_DA showed a significantly smaller RMSE than CONV_DA in two out of the four times radiosonde data were available. We conclude that the assimilation of TRRL data has great potential to close the critical gap of missing temperature observations in the lower troposphere.

Analysis of Urban Effects in Oklahoma City using a Dense Surface Observing Network

AbstractMany studies have investigated urban heat island (UHI) intensity for cities around the world, which is normally quantified as the temperature difference between urban location(s) and rural location(s). A few open questions still remain regarding the UHI, such as the spatial distribution of UHI intensity, temporal (including diurnal and seasonal) variation of UHI intensity, and the UHI formation mechanism. A dense network of atmospheric monitoring sites, known as the Oklahoma City (OKC) Micronet (OKCNET), was deployed in 2008 across the OKC metropolitan area. This study analyzes data from OKCNET in 2009 and 2010 to investigate OKC UHI at a subcity spatial scale for the first time. The UHI intensity exhibited large spatial variations over OKC. During both daytime and nighttime, the strongest UHI intensity is mostly confined around the central business district where land surface roughness is the highest in the OKC metropolitan area. These results do not support the roughness warming theory to explain the air temperature UHI in OKC. The UHI intensity of OKC increased prominently around the early evening transition (EET) and stayed at a fairly constant level throughout the night. The physical processes during the EET play a critical role in determining the nocturnal UHI intensity. The near-surface rural temperature inversion strength was a good indicator for nocturnal UHI intensity. As a consequence of the relatively weak near-surface rural inversion, the strongest nocturnal UHI in OKC was less likely to occur in summer. Other meteorological factors (e.g., wind speed and cloud) can affect the stability/depth of the nighttime boundary layer and can thus modulate nocturnal UHI intensity.

DETECTION AND MODELING OF TEMPERATURE INVERSION IN THE ATMOSPHERE USING MODIS IMAGES (CASE STUDY: KERMANSHAH)

Abstract. Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface. The common approach in determination of these parameters is the use of Radiosonde where these measurements are too sparse. The main objective of this study is detection and modeling the temperature inversion using MODIS thermal infrared data. There are more than 180 days per year in which the temperature inversion conditions are present in Kermanshah city. Kermanshah weather station was selected as the study area. 90 inversion days was selected from 2007 to 2008 where the sky was clear and the Radiosonde data were available. Brightness temperature for all thermal infrared bands of MODIS was calculated for these days. Brightness temperature difference between any of the thermal infrared bands of MODIS and band 31 was found to be sensitive to strength and depth of temperature inversion. Then correlation coefficients between these pairs and the inversion depth and strength both calculated from Radiosonde were evaluated. The results showed poor linear correlation. This was found to be due to the change of the atmospheric water vapor content and the relatively weak temperature inversion strength and depth occurring in Kermanshah. The polynomial mathematical models and Artificial intelligence algorithms were deployed for detection and modeling the temperature inversion. A model with the lowest terms and highest possible accuracy was obtained. The Model was tested using 20 independent test data. Results indicate that the inversion strength can be estimated with RMSE of 0.84° C and R2 of 0.90. Also inversion depth can be estimated with RMSE of 54.56 m and R2 of 0.86.

Characterization of the Marine Boundary Layer and the Trade-Wind Inversion over the Sub-tropical North Atlantic

The stability of the lower troposphere along the east side of the sub-tropical North Atlantic is analyzed and characterized using upper air meteorological long-term records at the Canary Islands (Tenerife), Madeira (Madeira) and Azores (Terceira) archipelagos. The most remarkable characteristic is the strong stratification observed in the lower troposphere, with a strengthening of stability centred at levels near 900 and 800 hPa in a significant percentage of soundings (ranging from 17 % in Azores to 33 % in Guimar, Canary Islands). We show that this double structure is associated with the top of the marine boundary layer (MBL) and the trade-wind inversion (TWI) respectively. The top of the MBL coincides with the base of the first temperature inversion (\(\approx \)900 hPa) where a sharp change in water vapour mixing ratio is observed. A second temperature inversion is found near 800 hPa, which is characterized by a large directional wind shear just above the inversion layer, tied to the TWI. We find that seasonal and latitudinal variations of the height and strength of both temperature inversions are driven by large-scale subsiding air from the upper troposphere associated with the descent branch of the Hadley cell. Increased general subsidence in summertime enhances stability in the lower troposphere, more markedly in the southern stations, where the inversion-layer heights are found at lower levels enhancing the main features of these two temperature inversions. A simple conceptual model that explains the lower tropospheric inversion enhancement by subsidence is proposed.

Variation and co-variation of PM10, particle number concentration, NOx and NO2 in the urban air – Relationships with wind speed, vertical temperature gradient and weather type

Atmospheric ultrafine particles (UFP; diameter < 0.1 μm) represent a growing global health concern in urban environments and has a strong link to traffic related emissions. UFP is usually the dominating fraction of atmospheric particle number concentrations (PNC) despite being a minor part of total particle mass. The aim of this study was to empirically investigate the relationship between PNC and other air pollutants (NOX, NO2 and PM10) in the urban environment and their dependence on meteorology and weather type, using the Lamb Weather Type (LWT) classification scheme. The study was carried out in Gothenburg, Sweden, at an urban background site during April 2007–May 2008. It was found that daily average [PNC] correlated very well with [NOx] (R2 = 0.73) during inversion days, to a lesser extent with [NO2] (R2 = 0.58) and poorly with [PM10] (R2 = 0.07). Both PNC and NOx had similar response patterns to wind speed and to the strength of temperature inversions. PNC displayed two regimes, one strongly correlated to NOx and a second poorly correlated to NOx which was characterised by high wind speed. For concentration averages based on LWTs, the PNC-[NOx] relationship remained strong (R2 = 0.70) where the windy LWT W deviated noticeably. Exclusion of observations with wind speed >5 ms−1 or ΔT < 0 °C from LWTs produced more uniform and stronger relationships (R2 = 0.90; R2 = 0.93). Low wind speeds and positive vertical temperature gradients were most common during LWTs A, NW, N and NE. These weather types were also associated with the highest daily means of NOx (∼30 ppb) and PNC (∼10 000 # cm−3). A conclusion from this study is that NOx (but not PM10) is a good proxy for PNC especially during calm and stable conditions and that LWTs A, NW, N and NE are high risk weather types for elevated NOx and PNC.

Antarctic Low-Tropospheric Humidity Inversions: 10-Yr Climatology

Abstract Humidity inversions are nearly permanently present in the coastal Antarctic atmosphere. This is shown based on an investigation of statistical characteristics of humidity inversions at 11 Antarctic coastal stations using radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2000 to 2009. The humidity inversion occurrence was highest in winter and spring, and high atmospheric pressure and cloud-free conditions generally increased the occurrence. A typical humidity inversion was less than 200 m deep and 0.2 g kg−1 strong, and a typical humidity profile contained several separate inversion layers. The inversion base height had notable seasonal variations, but generally the humidity inversions were located at higher altitudes than temperature inversions. Roughly half of the humidity inversions were associated with temperature inversions, especially near the surface, and humidity and temperature inversion strengths as well as depths correlated at several stations. On the other hand, approximately 60% of the humidity inversions were accompanied by horizontal advection of water vapor increasing with height, which is also a probable factor supporting humidity inversions. The spatial variability of humidity inversions was linked to the topography and the water vapor content of the air. Compared to previous results for the Arctic, the most striking differences in humidity inversions in the Antarctic were a much higher frequency of occurrence in summer, at least under clear skies, and a reverse seasonal cycle of the inversion height. The results can be used as a baseline for validation of weather prediction and climate models and for studies addressing changes in atmospheric moisture budget in the Antarctic.

Surface Energy Balance Framework for Arctic Amplification of Climate Change

Abstract Using 22 Canadian radiosonde stations from 1971 to 2010, the annually averaged surface air temperature trend amplification ranged from 1.4 to 5.2 relative to the global average warming of 0.17°C decade−1. The amplification factors exhibit a strong latitudinal dependence varying from 2.6 to 5.2 as the latitude increases from 50° to 80°N. The warming trend has a strong seasonal dependence with the greatest warming taking place from September to April. The monthly variations in the warming trend are shown to be related to the surface-based temperature inversion strength and the mean monthly surface air temperatures. The surface energy balance (SEB) equation is used to relate the response of the surface temperature to changes in the surface energy fluxes. Based on the SEB analysis, there are four contributing factors to Arctic amplification: 1) a larger change in net downward radiation at the Arctic surface compared to the global average; 2) a larger snow and soil conductive heat flux change than the global average; 3) weaker sensible and latent heat flux responses that result in a larger surface temperature response in the Arctic; and 4) a colder skin temperature compared to the global average, which forces a larger surface warming to achieve the same increase in upward longwave radiation. The observed relationships between the Canadian station warming trends and both the surface-based inversion strength and the surface air temperature are shown to be consistent with the SEB analysis. Measurements of conductive flux were not available at these stations.

Modelling the vertical structure of the atmospheric boundary layer over Arctic fjords in Svalbard

AbstractThe vertical structure of the atmospheric boundary layer (ABL), simulated with the mesoscale model Weather Research and Forecasting (WRF) as well as with its polar optimized version Polar WRF, was compared to tethered balloon soundings and mast observations taken in March and April 2009 from two Arctic fjords in Svalbard. From twelve short (48 h) simulations, the Quasi‐Normal Scale Elimination scheme for the ABL and the NOAH land surface scheme for the surface were found to perform best and were selected for one long (16 day) simulation. The differences in performance of the standard WRF and Polar WRF were marginal. A warm bias, especially near the surface, was found in the modelled temperature profiles related to underestimated temperature inversion strength and depth. The modelled humidity inversions were generally deeper but weaker than the observed, and often occurred independently of temperature inversions. The largest errors in temperature and humidity occurred under high pressure conditions. Multiple temperature and humidity inversions were usually not captured by WRF. Compared to the compact sea ice east of Svalbard, the modelled temperature and humidity inversions were weaker and less frequent over the fjords. The biases in modelled wind speed profiles were closely related to low‐level jets (LLJs); the modelled LLJs were stronger and deeper, and typically located at higher altitudes than the observed LLJs. Errors in the near‐surface variables were notably reduced by applying post‐processing equations based on other modelled variables. Copyright © 2012 Royal Meteorological Society

Vineyard frost protection with upward-blowing wind machines

Upward-blowing wind machines have been commercialized for use in frost protection but little quantitative information exists regarding how their operation alters site temperatures. In particular, their performance relative to conventional wind machines has been debated. To address this need, experiments were conducted on 12 spring frost nights in 2010 and 2011 in a commercial winegrape vineyard where either two upward-blowing wind machines or a single conventional wind machine were operated. Comprehensive measurements of air temperature changes caused by wind machine operation were evaluated on multiple transects at heights of 1.1, 4, 7 and 10m. All 12 frost nights were characterized by low wind and clear sky conditions, with temperature inversion strengths commonly associated with beneficial wind machine use occurring on 9 of the 12 nights. The operation of the conventional wind machine produced consistently larger and more statistically significant increases in temperature, particularly at the 1.1m vine level, as compared to the operation of the upward-blowing wind machines which produced very minor increases in temperature at the 1.1m level under strong inversion conditions and either no change or decreases in temperature under weaker inversion conditions. Based on the summary relationships between temperature changes as a function of inversion strength, under conditions of an inversion gradient of 0.2°Cm−1 the conventional wind machine would be expected to raise target area temperatures by 1.6°C at the vine level, while the upward-blowing wind machines would have no net effect under the same inversion conditions. Smoke tracking of the air flow from the upward-blowing wind machines indicated that the air jet reached 25m height, and then tended to slowly settle back towards the ground. These results indicate relatively poor performance of this type of low-powered (6.3kW) upward-blowing wind machine compared to a conventional wind machine under the conditions of this study.

Arctic Inversion Strength in Climate Models

Recent work indicates that climate models have a positive bias in the strength of the wintertime low-level temperature inversion over the high-latitude Northern Hemisphere. It has been argued this bias leads to underestimates of the Arctic’s surface temperature response to anthropogenic forcing. Here the bias in inversion strength is revisited. The spatial distribution of low-level stability is found to be bimodal in climate models and observational reanalysis products, with low-level inversions represented by a stable primary mode over the interior Arctic Ocean and adjacent continents, and a secondary unstable mode over the Atlantic Ocean. Averaging over these differing conditions is detrimental to understanding the origins of the inversion strength bias. While nearly all of the 21 models examined overestimate the area-average inversion strength, conditionally sampling the two modes shows about half the models are biased because of the relative partitioning of the modes and half because of biases within the stable mode.