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Definition of the tropopause has remained a focus of atmospheric science since its discovery near the beginning of the twentieth century. Few universal definitions (those that can be reliably applied globally and to both common observations and numerical model output) exist and many definitions with unique limitations have been developed over the years. The most commonly used universal definition of the tropopause is the temperature lapse-rate definition established by the World Meteorological Organization (WMO) in 1957 (the LRT). Despite its widespread use, there are recurrent situations where the LRT definition fails to reliably identify the tropopause. Motivated by increased availability of coincident observations of stability and composition, this study seeks to reexamine the relationship between stability and composition change in the tropopause transition layer and identify areas for improvement in a stability-based definition of the tropopause. In particular, long-term (40+ years) balloon observations of temperature, ozone, and water vapor from six locations across the globe are used to identify covariability between several metrics of atmospheric stability and composition. We found that the vertical gradient of potential temperature is a superior stability metric to identify the greatest composition change in the tropopause transition layer, which we use to propose a new universally applicable potential temperature gradient tropopause (PTGT) definition. Application of the new definition to both observations and reanalysis output reveals that the PTGT largely agrees with the LRT, but more reliably identifies tropopause-level composition change when the two definitions differ greatly. Significance Statement: In this study we provide a review of existing tropopause definitions (and their limitations) and investigate potential improvement in the definition of the tropopause using balloon-based observations of stability and atmospheric composition. This work is motivated by the need for correct identification of the tropopause to accurately assess upper-troposphere–lower-stratosphere processes, which in turn has far-reaching implications for our understanding of Earth's radiation budget and climate. The result of this research is the creation of a new, universally applicable stability-based definition of the tropopause: the potential temperature gradient tropopause (PTGT). [ABSTRACT FROM AUTHOR]

Thermal infrared spectra taken by the Emirates Mars Infrared Spectrometer (EMIRS) on‐board the Emirates Mars Mission (EMM) spacecraft are well suited for the retrieval of surface temperatures, the atmospheric temperature profile from the surface to ∼40 km, and the column abundance of dust aerosols, water ice clouds, and water vapor. A constrained linear inversion retrieval routine that includes multiple scattering has been developed and optimized for this purpose. Here, we present a brief overview of the retrieval algorithm and first atmospheric science results from observations taken by EMIRS over the first Earth year of EMM Science Phase operations. These retrievals show extensive water ice clouds, typical for the aphelion season of these observations, and the expected north polar summer maximum and subsequent equatorward transport of water vapor is well documented. An unusually strong and early regional dust storm and its associated thermal response were also observed. Plain Language Summary: Data returned from the Emirates Mars Infrared Spectrometer (EMIRS) have been used to characterize the atmosphere of Mars. These data allow estimates of atmospheric temperature as a function of height, the amount of dust and water ice clouds in the atmosphere, and the abundance of water vapor. In this work we describe the process for estimating these quantities and we give a brief overview of our first results. The results show that Mars was relatively cool, relatively cloudy, but with little dust. This was expected given the season on Mars that was observed. More surprising was the observation of a dust storm that occurred earlier in the Martian year than usual. Key Points: Thermal infrared spectra of Mars taken by the Emirates Mars Infrared Spectrometer have been used to characterize the atmospheric stateThese aphelion season observations show the expected relatively cool atmosphere with prominent water ice clouds and generally little dustThe initiation and evolution of a regional dust storm that occurred unusually early in the season was observed [ABSTRACT FROM AUTHOR]

The article presents the discussion on wind changes allowing more frequent QBO disruptions in the future, leading to less predictability in atmospheric weather and climate systems. Topics include quasi-biennial oscillation (QBO) in the tropical stratosphere being the dominant form of interannual variability in the zonal-mean zonal wind; and equatorial waves dissipated in the middle of a descending WQBO concurrent with the development of very localized easterly winds.

Understanding how increases in water temperature may affect winter dormancy period duration and overwinter survival are important for the effective conservation and management of estuarine species in the face of a warming climate. In this study, we determined the length of the overwintering period and the probability of overwinter survival of blue crab (Callinectes sapidus), an ecologically and economically important estuarine crustacean. Overwintering period length and probability of overwinter survival were determined using projected water temperatures up to the year 2100, derived from a harmonic model that utilized air temperatures from multi-model ensemble of regional-scale climate projections. Our estimates of warming water temperatures by 2100 in Chesapeake Bay indicate that winters will be up to 50% shorter and overwinter survival will increase by at least 20% compared to current conditions. The warmer conditions will lead to faster and prolonged seasonal growth, which, when combined with lower winter mortality, will lead to increased population productivity. The level of expression of this increased productivity will depend on the response of other elements of the Chesapeake Bay food web, as well as possible changes to fishery management policies over the same time period. [ABSTRACT FROM AUTHOR]

Climatological changes in the environments of key meteorological parameters that affect Significant Tornado Days (SigTorDs) have been determined for two active tornado regions defined as Box a and Box ß, centered, respectively, over Oklahoma and Alabama and their respective environs. The North American Regional Reanalysis data was selected for 1980-2013, providing two successive 17-year periods corresponding to the last 34 years of previous research findings that focused on the aforementioned regions. This data record also corresponds to an increasing surface air temperature trend for the continental United States. Period I (1980-1996) and Period II (1997-2013) defined the years of changing environments for the two regions studied. Environmental parameters investigated and compared to SigTorDs were surface-based convective available potential energy (CAPE), storm relative helicity (0-3 km), bulk wind difference (1,000 mb to 500 mb), and lifted condensation level (LCL). Environments have changed to fewer SigTorDs (130 to 74) in Box a from Period I to Period II, dominated by decreasing frequency of storm relative helicity and slightly increasing CAPE. Box ß is characterized by more SigTorDs (94 to 119) in Period II with an environment dominated by increasing frequency of storm relative helicity and minimal change in CAPE. These results support the importance of the changes in storm relative helicity (as opposed to CAPE) in explaining the eastward shift in U.S. tornado activity. [ABSTRACT FROM AUTHOR]

Abstract—: The results of numerical experiments on the sensitivity of the INMCM48 Earth System model (Institute of Numerical Mathematics, Russian Academy of Science (INM RAS)) to the various parameterizations of convection induced by the formation of a new ice are presented and analyzed. It is shown that the response in temperature and salinity is observed not only directly under the ice, but in ocean subpolar regions as well, which is especially pronounced in the North Atlantic. An effective parameterization is proposed which significantly reduces the estimation error of the surface salinity in the AO with no formation of the trends of the near-bottom salinity fields, in contrast with the well-known parameterization (Nguyen, Menemenlis and Kwok, 2009). [ABSTRACT FROM AUTHOR]

Predicting future climatic events is one of the key issues in many fields, whether in scientific or industrial areas. An artificial neural network (ANN) model, based on a backpropagation type, was developed in this study to predict the minimum air temperature of the following day from meteorological data using air temperature, relative humidity, radiation, precipitation, and wind direction and speed to detect the occurrence of radiative frost events. The configuration of the next day ANN prediction system allows operating with low-power computing machines; it is able to generate early warnings that can lead to the development of effective strategies to reduce crop damage, lower quality, and losses in agricultural production. This paper presents a procedural approach to an ANN, which was trained, validated, and tested in 10 meteorological stations in central Chile for approximately 8 yr (2010-2017). The overall mean results were classified by a confusion matrix and showed good performance in predicting minimum temperature with a mean square error (MSE) of 2.99 °C for the network, 1.71 °C for training, 1.77 °C for validation, and 1.74 °C for the testing processes. Frost detection results had an appropriate 98% overall mean accuracy (ACC), 86% sensitivity (TPR), and 2% error rate (ER). Differences and errors in frost detection can be attributed to several factors that are mainly associated with the accuracy of the sensors meteorological stations, local climatic and geographic conditions, and the number of parameters that enter in the ANN training processes. [ABSTRACT FROM AUTHOR]

The Pasquill system was designed to describe dispersion conditions and was never intended to be a “stand-alone” measure of stability, but it has nevertheless been used to characterize stability in a wide range of applications unrelated to atmospheric dispersion. In this study we evaluate whether the method's underlying assumptions are sufficiently robust for characterizing stability, and whether the method provides acceptable characterizations when used as a stability classification tool outside the context of atmospheric dispersion. Observed temperature lapse rates at six locations across Eurasia largely fail to support the Pasquill method's “exclusivity” assumptions prohibiting the identification of stable classes during daytime, unstable classes at night, and all non-neutral classes during day/night transition and overcast periods. While observed nighttime stability is mostly stable or neutral and thus largely consistent with the Pasquill method, daytime lapse rates frequently indicate stable conditions. Moreover, the majority of lapse rates during day/night transition periods are non-neutral. Substantial seasonal variability is observed in diurnal stability variations and is unaccounted for in the Pasquill system. When compared with observed stability based on lapse rates, the Pasquill classification scheme exhibits a strong neutral bias at most sites. The method performs particularly poorly during daytime, correctly identifying instability in only 1%–29% of cases at the sites analyzed. Nighttime stability is correctly identified more frequently, but the strength of nocturnal stability is overestimated at all sites analyzed. [ABSTRACT FROM AUTHOR]

A set of homogenized monthly mean surface air temperature (SAT) series at 32 stations in China back to the 19th century had previously been developed based on the RHtest method by Cao et al., but some inhomogeneities remained in the dataset. The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series. The new data show significant warming trends during 1924-2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)−1, with a regional mean trend of 1.65°C (100 yr)−1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)−1. It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at http://www.dx.doi.org/10.11922/sciencedb.516. [ABSTRACT FROM AUTHOR]

Atmospheric concentration of beryllium-7 (7Be) at ground level was measured from September 2012 to October 2013 in San Carlos de Bariloche, Argentina, using a HPV-5300AFC brushless, automatic flow control outdoor high volume air sampler for continuous use, and 8”×10” 0.8 microns fiberglass filters. The activity of 7Be was determined on a high-purity germanium (HPGe) detector (relative efficiency 12.3%) by standard gamma spectrometry. The average value found was 4.1 ± 0.1 mBq/m3. Seasonal changes in the atmospheric concentration of 7Be were compared with other environmental variables (temperature, humidity, precipitations, and air kerma rate), and correlation, both positive and negative, was observed as expected. Measurements were carried out following the Radiological Environmental Monitoring Programme at Bariloche Atomic Centre. The aim of the study was to determine atmospheric concentration of 7Be at ground level and to correlate its seasonal changes with environmental variables. Air samplers and environmental dosemeter locations were far away from buildings and any other thing that could influence or alter the measurements. Pearson's correlation coefficient was calculated to evaluate the relation between atmospheric 7Be concentration and environmental variables of interest. These changes in 7Be concentration can be attributed to the variations and dynamic of air exchange between the stratosphere and the troposphere and to the variations of the tropopause height. To fully understand and correctly interpret the meaning of these seasonal variations in the concentrations of atmospheric 7Be, active atmospheric processes must be taken into account. According to the measurements carried out, contribution of 7Be concentration to the natural background radiation dose is negligible. [ABSTRACT FROM AUTHOR]

Elevated atmospheric temperature and CO 2 concentration ([CO 2 ]) can strongly affect yield, CH 4 and N 2 O emissions in rice paddies. However, understanding of their response to combined temperature and [CO 2 ] increases under field conditions is still limited. To study this issue further, an open-top chamber (OTC) platform was set up to simulate two levels of atmospheric temperature (ambient and 2 °C elevated) and two levels of [CO 2 ] (ambient and 60 ppm elevated) during two rotations of double rice, including twelve independent OTCs and three un-chambered open field sites as trial plots. The experimental site is located in Hubei Province, Central China, which has a subtropical monsoon climate. In all four rice seasons, elevated CO 2 induced an increment in grain yield by 11.4–19.7%, while also enhancing CH 4 and N 2 O emissions by 19.8–52.6% and 102.4–140.0%, respectively, compared with ambient temperature and [CO 2 ]. Elevated temperature enhanced CH 4 emissions by 4.4–36.0%, and decreased N 2 O emissions by 1.5–10.5% in three rice seasons. Elevated temperature had different effects on grain yield, with a reduction of 1.0–3.2% in early rice and an increase of 6.3–9.2% in late rice. When elevated temperature and [CO 2 ] were combined, there was a positive interaction that further enhanced CH 4 emissions and yield of late rice, and an offsetting effect on N 2 O emissions and yield of early rice. Over the 2-year experiment, warming and CO 2 enrichment caused an increase of 9.3–44.2% in greenhouse gas intensity, suggesting that more greenhouse gas emissions will be emitted to produce a unit mass of rice under projected global warming. These findings provide initial data for the estimation of CH 4 and N 2 O emissions under elevated temperature and [CO 2 ] in double rice cropping system, and stress the need for effective management practices that promote rice yield while reducing greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

The Generalized Equilibrium Feedback Analysis (GEFA) is used to distinguish the influence of the Oyashio Extension (OE) and the Kuroshio Extension (KE) variability on the atmosphere from 1979 to 2014 from that of the main SST variability modes, using seasonal mean anomalies. Remote SST anomalies are associated with each single oceanic regressor, but the multivariate approach efficiently confines their SST footprints. In autumn [October–December (OND)], the OE meridional shifts are followed by a North Pacific Oscillation (NPO)-like signal. The OE influence is not investigated in winter [December–February (DJF)] because of multicollinearity, but a robust response with a strong signal over the Bering Sea is found in late winter/early spring [February–April (FMA)], a northeastward strengthening of the Aleutian low following a northward OE shift. A robust response to the KE variability is found in autumn, but not in winter and late winter when the KE SST footprint becomes increasingly small and noisy as regressors are added in GEFA. In autumn, a positive PDO is followed by a northward strengthening of the Aleutian low and a southward shift of the storm track in the central Pacific, reflecting the surface heat flux footprint in the central Pacific. In winter, the PDO shifts the maximum baroclinicity and storm track southward, the response strongly tilts westward with height in the North Pacific, and there is a negative NAO-like teleconnection. In late winter, the North Pacific NPO-like response to the PDO interferes negatively with the response to the OE and is only detected when the OE is represented in GEFA. A different PDO influence on the atmospheric circulation is found from 1958 to 1977. [ABSTRACT FROM AUTHOR]

A new version of the Community Land Model (CLM) was introduced to the Saudi King Abdulaziz University Atmospheric Global Climate Model (Saudi-KAU AGCM) for better land surface component representation, and so to enhance climate simulation. CLM replaced the original land surface model (LSM) in Saudi-KAU AGCM, with the aim of simulating more accurate land surface fluxes globally, but especially over the Arabian Peninsula. To evaluate the performance of Saudi-KAU AGCM, simulations were completed with CLM and LSM for the period 1981–2010. In comparison with LSM, CLM generates surface air temperature values that are closer to National Centre for Environmental Prediction (NCEP) observations. The global annual averages of land surface air temperature are 9.51, 9.52, and 9.57 °C for NCEP, CLM, and LSM respectively, although the same atmospheric radiative and surface forcing from Saudi-KAU AGCM are provided to both LSM and CLM at every time step. The better temperature simulations when using CLM can be attributed to the more comprehensive plant functional type and hierarchical tile approach to the land cover type in CLM, along with better parameterization of upward land surface fluxes compared to LSM. At global scale, CLM exhibits smaller annual and seasonal mean biases of temperature with respect to NCEP data. Moreover, at regional scale, CLM demonstrates reasonable seasonal and annual mean temperature over the Arabian Peninsula as compared to the Climatic Research Unit (CRU) data. Finally, CLM generated better matches to single point-wise observations of surface air temperature and surface fluxes for some case studies. [ABSTRACT FROM AUTHOR]

Climate change has greatly affected agriculture. Agriculture is facing increasing risks as its sensitivity and vulnerability to climate change. Scientific assessment of climate change-induced agricultural risks could help to actively deal with climate change and ensure food security. However, quantitative assessment of risk is a difficult issue. Here, based on the IPCC assessment reports, a quantitative method for risk assessment of agriculture due to climate change is proposed. Risk is described as the product of the degree of loss and its probability of occurrence. The degree of loss can be expressed by the yield change amplitude. The probability of occurrence can be calculated by the new concept of climate change effect-accumulated frequency (CCEAF). Specific steps of this assessment method are suggested. This method is determined feasible and practical by using the spring wheat in Wuchuan County of Inner Mongolia as a test example. The results show that the fluctuation of spring wheat yield increased with the warming and drying climatic trend in Wuchuan County. The maximum yield decrease and its probability were 3.5 and 64.6%, respectively, for the temperature maximum increase 88.3%, and its risk was 2.2%. The maximum yield decrease and its probability were 14.1 and 56.1%, respectively, for the precipitation maximum decrease 35.2%, and its risk was 7.9%. For the comprehensive impacts of temperature and precipitation, the maximum yield decrease and its probability were 17.6 and 53.4%, respectively, and its risk increased to 9.4%. If we do not adopt appropriate adaptation strategies, the degree of loss from the negative impacts of multiclimatic factors and its probability of occurrence will both increase accordingly, and the risk will also grow obviously. [ABSTRACT FROM AUTHOR]

Variations in the atmospheric carbon dioxide concentration and the average global near-surface air temperature are compared over the last 50-year period. It turns out that, within the interannual time scales, the carbon dioxide concentration variations generally lagged behind the corresponding temperature variations. However, within time scales of more than 40 years in the 1980s-1990s, when the growth of CO and temperature accelerated, carbon dioxide was in the lead. This fact indicates that atmospheric pollution actually could have begun to affect the climate at that time. [ABSTRACT FROM AUTHOR]

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations. [ABSTRACT FROM AUTHOR]

This article reports on the near-surface atmospheric response at the High Arctic site of Svalbard, latitude 78° N, as a result of abrupt changes in solar insolation during the 20 March 2015 equinox total solar eclipse and notifies the atmospheric science community of the availability of a rare dataset. Svalbard was central in the path of totality, and had completely clear skies. Measurements of shaded air temperature and atmospheric pressure show only weak, if any, responses to the reduced insolation. A minimum in the air temperature at 1.5m above the ground occurred starting 2min following the end of totality, though this drop was only slightly beyond the observed variability for the midday period. Eclipse-produced variations in surface pressure, if present, were less than 0.3 hPa. [ABSTRACT FROM AUTHOR]

Near-surface air temperature (NSAT) anomalies during the 20 March 2015 solar eclipse are investigated at 266UK sites, using operational data. The high density of observing sites, together with the wide range of ambient meteorological conditions, provided an unprecedented opportunity for analysis of the spatial variability of NSAT anomalies under relatively uniform eclipse conditions. Anomalies ranged from -0.03°C to -4.23°C (median -1.02°C). The maximum (negative) anomaly lagged the maximum obscuration by 15 min on average. Cloud cover impacted strongly on NSAT anomalies, with larger anomalies in clearsky situations (p<0.0001). Weaker, but statistically significant, correlations were found with wind speed (larger anomalies inweaker winds), proximity to coast (larger anomalies at inland sites), topography (larger anomalies in topographical low points) and land cover (larger anomalies over vegetated surfaces). In this mid-morning eclipse, the topographical influences on NSAT anomalies were apparently dominated by variations in residual nocturnal inversion strength, as suggested by significant correlations between postsunrise temperature and NSAT anomaly at clear-sky sites (larger negative anomalies with lower postsunrise temperatures). The largest NSAT anomaly occurred at a coastal site where flow transitioned from onshore to offshore during the eclipse, in a situation with large coastal temperature gradients associated with antecedent nocturnal cooling. [ABSTRACT FROM AUTHOR]

The effect of cloud-radiation interactions on cloud properties is examined in the context of a limited-domain cloud-resolving model. The atmospheric cloud radiative effect (ACRE) influences the areal extent of tropical high clouds in two distinct ways. The first is through direct radiative destabilization of the elevated cloud layers, mostly as a result of longwave radiation heating the cloud bottom and cooling the cloud top. The second effect is radiative stabilization, whereby cloud radiative heating of the atmospheric column stabilizes the atmosphere to deep convection. In limited area domain simulations, the stabilizing (or indirect) effect is the dominant role of the cloud radiative heating, thus reducing the cloud cover in simulations where ACRE is included compared to those where it is removed. Direct cloud radiative heating increases high cloud fraction, decreases mean cloud optical depth, and increases cloud top temperature. The indirect cloud radiative heating decreases high cloud fraction, but also decreases mean cloud optical depth and increases cloud top temperature. The combination of these effects increases the top-of-atmosphere cloud radiative effect. In mock-Walker circulation experiments, the decrease in high cloud amount owing to radiative stabilization tends to cancel out the increase in high cloud amount owing to the destabilization within the cloud layer. The changes in cloud optical depth and cloud top pressure, however, are similar to those produced in the limited area domain simulations. [ABSTRACT FROM AUTHOR]

The Met Office reports that September 2021 was the second warmest on record across the UK, with a mean temperature of 14.7 °C. European average wind speed is weakening The I Financial Times i has reported that average surface wind speeds across many parts of Europe are declining. Storm wind speeds in the outer cloud-ring, that can reach 640kmh SP -1 sp , have increased by 4 to 8 percent over a decade as the storm increases its vorticity. [Extracted from the article]

Idealized explicit convection simulations of the Met Office Unified Model exhibit spontaneous self-aggregation in radiative-convective equilibrium, as seen in other models in previous studies. This self-aggregation is linked to feedbacks between radiation, surface fluxes, and convection, and the organization is intimately related to the evolution of the column water vapor field. Analysis of the budget of the spatial variance of column-integrated frozen moist static energy (MSE), following Wing and Emanuel (2014), reveals that the direct radiative feedback (including significant cloud longwave effects) is dominant in both the initial development of self-aggregation and the maintenance of an aggregated state. A low-level circulation at intermediate stages of aggregation does appear to transport MSE from drier to moister regions, but this circulation is mostly balanced by other advective effects of opposite sign and is forced by horizontal anomalies of convective heating (not radiation). Sensitivity studies with either fixed prescribed radiative cooling, fixed prescribed surface fluxes, or both do not show full self-aggregation from homogeneous initial conditions, though fixed surface fluxes do not disaggregate an initialized aggregated state. A sensitivity study in which rain evaporation is turned off shows more rapid self-aggregation, while a run with this change plus fixed radiative cooling still shows strong self-aggregation, supporting a 'moisture-memory' effect found in Muller and Bony (2015). Interestingly, self-aggregation occurs even in simulations with sea surface temperatures (SSTs) of 295 and 290 K, with direct radiative feedbacks dominating the budget of MSE variance, in contrast to results in some previous studies. [ABSTRACT FROM AUTHOR]

A 32-year global ensemble reforecast dataset has recently been developed at Météo-France that is approximatively consistent with the operational global ensemble forecast system PEARP. Unlike ECMWF or NCEP, Météo-France does not possess a reanalysis of its own operational forecast system. Therefore, the initial atmospheric state and boundary conditions of the reforecasts are from the ECMWF ERA-Interim reanalysis. This article presents a study of the sensitivity of the reforecasts to the method of land-surface initialization. To this end, two sets of short-range hindcasts using different land-surface initialization approaches are compared. The first set is initialized from interpolated ERAInterim land-surface fields based on a transfer function. The second set is initialized from offline simulations of the Météo-France land-surface model (SURFEX) driven by the 3-hourly near-surface atmospheric fields of the ERA-Interim reanalysis. Each set is run from 1800 UTC initial conditions and up to +108 h. Because better results overall are found using offline SURFEX simulations, this latter approach was chosen to perform an ensemble reforecast dataset. Then, this ensemble reforecast database will be used to build a climatology of the operational ensemble prediction system of Météo-France, which will, in turn, help to better estimate systematic forecast errors and, more importantly, improve the forecasting of rare extreme weather events. [ABSTRACT FROM AUTHOR]

With extreme winds, rapidly changing weather, and myriad weather conditions during any given month, Mount Washington, New Hampshire (1,917 m MSL), is an ideal location to observe and learn about atmospheric sciences. During the summer of 2013, Mount Washington Observatory (MWO) welcomed a select group of interns to experience life at the "Home of the World's Worst Weather" and develop scientific and meteorological skills. The goals of the internship program are to learn how to observe and forecast mountain weather; develop data analysis and critical thinking skills through individual research projects; and live, work, and collaborate effectively with others at a remote mountain-top observatory. Interns are typically undergraduate students or recent graduates of atmospheric science programs and are selected from a highly competitive field of applicants. The summer 2013 interns worked on a variety of research projects, ranging from developing a forecast tool for the gustiness of wind at the summit to understanding the evolution of atmospheric and environmental conditions that lead to avalanches in nearby Tuckerman Ravine. To accomplish their research projects, the interns learned how hourly weather observations are made, used data analysis software, and practiced critical thinking about their methods and results. Weekly meetings with the interns and the MWO director of research allowed for the sharing of research progress, peer feedback, and practice presenting scientific results. The internships ended with presentations of their scientific research to MWO observers, staff, and observatory members. Post-internship survey responses revealed the program was highly effective at meeting its goals and provided constructive suggestions for future internship programs. [ABSTRACT FROM AUTHOR]

We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day-1. This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10-20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system. [ABSTRACT FROM AUTHOR]

The latter was a particularly notable achievement for Fred himself, who was one of the chief advocates to make the case to ESA for a reflight of the previously developed Mars Express spacecraft to send into orbit around Venus. Fred proposed an instrument that would use the same pressure modulator concept for the Venus atmosphere as used by Houghton and Taylor for Earth. Fredric (Fred) W Taylor was a distinguished atmospheric physicist with particular expertise in atmospheric radiative transfer. [Extracted from the article]

Boretti (Theor Appl Clim 114:567-573, ) presents an analysis of observed temperature trends in the Northern Territory, Australia, and claims that this analysis is inconsistent with trends reported by the Australian Bureau of Meteorology and thus that the Bureau of Meteorology results are flawed. This paper presents evidence that the results presented by Boretti () are at least partly attributable to his failure to account for inhomogeneities in the underlying station data and to the use of time periods for trends which are different to those in the Bureau of Meteorology analyses with which he is comparing them. The evidence, as presented in this paper, therefore fails to support his conclusions of inconsistencies between the Bureau of Meteorology analyses and the station data. [ABSTRACT FROM AUTHOR]

A near-surface specific humidity (Qa) and air temperature (Ta) climatology on daily and 0.25° grids was constructed by the objectively analyzed air-sea fluxes (OAFlux) project by objectively merging two recent satellite-derived high-resolution analyses, the OAFlux existing 1° analysis, and atmospheric reanalyses. The two satellite products include the multi-instrument microwave regression (MIMR) Qa and Ta analysis and the Goddard Satellite-Based Surface Turbulent Fluxes, version 3 (GSSTF3), Qa analysis. This study assesses the degree of improvement made by OAFlux using buoy time series measurements at 137 locations and a global empirical orthogonal function (EOF) analysis. There are a total of 130 855 collocated daily values for Qa and 283 012 collocated daily values for Ta in the buoy evaluation. It is found that OAFlux Qa has a mean difference close to 0 and a root-mean-square (RMS) difference of 0.73 g kg−1, and Ta has a mean difference of −0.03°C and an RMS difference of 0.45°C. OAFlux shows no major systematic bias with respect to buoy measurements over all buoy locations except for the vicinity of the Gulf Stream boundary current, where the RMS difference exceeds 1.8°C in Ta and 1.2 g kg−1 in Qa. The buoy evaluation indicates that OAFlux represents an improvement over MIMR and GSSTF3. The global EOF-based intercomparison analysis indicates that OAFlux has a similar spatial-temporal variability pattern with that of three atmospheric reanalyses including MERRA, NCEP-1, and ERA-Interim, but that it differs from GSSTF3 and the Climate Forecast System Reanalysis (CFSR). [ABSTRACT FROM AUTHOR]

The COSMO model uses operationally two sub-grid schemes for the evaluation of stratus clouds. A semi-empirical scheme based on relative humidity is used in the radiation module while a statistical scheme is used in the turbulence module. The objective is to investigate the possibility of the implementation of the statistical scheme also in the radiation module. The relative impact is presented in reference to a spring test case with synoptic conditions that favor stratiform clouds. The domain considered is the wider Balkan region around the Hellenic geographical area and is characterized by comparable sea and land partitions. This particular domain choice gives rise to a strong coexistence of continental as well as marine clouds which is one of the most challenging features regarding the operational use of numerical weather prediction models by the Hellenic Meteorological Service. The results are evaluated through direct comparisons with satellite data as well as the observed 2-m temperatures for an approximate total of fifty Greek synoptic meteorological stations. The implementation of the statistical scheme led to an underestimation of low cloud-cover by the model in contrast to the implementation of the default relative-humidity scheme, while regarding medium cloud-cover the situation was reversed. Also, the daily 2-meter minimum and maximum temperatures were slightly better simulated, but not conclusively, when the statistical scheme was implemented in the radiation module. Although the statistical scheme cannot in its present form replace operationally the relative-humidity scheme in the radiation module, it is an important asset to COSMO model invoking valuable insight to the physics of the model and can be used as a basis to support the ongoing research in this crucial area of atmospheric sciences. [ABSTRACT FROM AUTHOR]

A recent re-evaluation of urban heat island (UHI) studies has suggested that the urban effect may be expressed more meaningfully as a difference between Local Climate Zones (LCZ), defined as areas with characteristic dimensions of between one and several kilometers that have distinct effects on climate at both micro-and local-scales (city streets to neighborhoods), rather than adopting the traditional method of comparing urban and rural air temperatures. This paper reports on a UHI study in Dublin (Ireland) which maps the urban area into LCZ and uses these as a basis for carrying out a UHI study. The LCZ map for Dublin is derived using a widely available land use/cover map as a basis. A small network of in-situ stations is deployed into different LCZ across Dublin and additional mobile temperature traverses carried out to examine the thermal characteristics of LCZ following mixed weather during a 1 week period in August 2010. The results show LCZ with high impervious/building coverage were on average >4 °C warmer at night than LCZ with high pervious/vegetated coverage during conditions conducive to strong UHI development. The distinction in mean LCZ nocturnal temperature allows for the generation of a heat map across the entire urban area. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is an important indicator of atmospheric evaporation demand and has been widely used to characterize hydrological change. However, sparse observations of pan evaporation (EP) prohibit the accurate characterization of the spatial and temporal patterns of PET over large spatial scales. In this study, we have estimated PET of China using the Penman-Monteith (PM) method driven by gridded reanalysis datasets to analyze the spatial and decadal variations of PET in China during 1982-2010. The results show that the estimated PET has decreased on average by 3.3 mm per year (p < 0.05) over China during 1982-1993, while PET began to increase since 1994 by 3.4 mm per year (p < 0.05). The spatial pattern of the linear trend in PET of China illustrates that a widely significant increasing trend in PET appears during 1982-2010 in Northwest China, Central China, Northeast China and South China while there are no obvious variations of PET in other regions. Our findings illustrate that incident solar radiation (Rs) is the largest contributor to the variation of PET in China, followed by vapor pressure deficit (VPD), air temperature (Tair) and wind speed (WS). However, WS is the primary factor controlling inter-annual variation of PET over Northwest China. [ABSTRACT FROM AUTHOR]

The effects of land cover on urban-rural and intra-urban temperature differences have been extensively documented. However, few studies have quantitatively related air temperature to land cover composition at a local scale which may be useful to guide landscape planning and design. In this study, the quantitative relationships between air temperature and land cover composition at a neighborhood scale in Beijing were investigated through a field measurement campaign and statistical analysis. The results showed that the air temperature had a significant positive correlation with the coverage of man-made surfaces, but the degree of correlation varied among different times and seasons. The different land cover types had different effects on air temperature, and also had very different spatial extent dependence: with increasing buffer zone size (from 20 to 300 m in radius), the correlation coefficient of different land cover types varied differently, and their relative impacts also varied among different times and seasons. At noon in summer, ∼37% of the variations in temperature were explained by the percentage tree cover, while ∼87% of the variations in temperature were explained by the percentage of building area and the percentage tree cover on summer night. The results emphasize the key role of tree cover in attenuating urban air temperature during daytime and nighttime in summer, further highlighting that increasing vegetation cover could be one effective way to ameliorate the urban thermal environment. [ABSTRACT FROM AUTHOR]

Regularities in variations in the intensity of hydroxyl radiation (the (6–2) λ834.4-nm band) and the Atmospheric system of molecular oxygen (the A(0–1) λ864.5-nm band) of the mesopause, hydroxyl temperature, and its night variability during sudden winter warmings of the stratosphere have been obtained based on long-term observations in Zvenigorod. [ABSTRACT FROM AUTHOR]

Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) refractivity profiles in altostratus and nimbostratus clouds from 2007 to 2010 are first identified based on collocated CloudSat data. Vertical temperature profiles in these clouds are then retrieved from cloudy refractivity profiles. Contributions of cloud liquid water content and ice water content are also included in the retrieval algorithm. The temperature profiles and their lapse rates are compared with those from a standard GPS RO wet retrieval without including cloud effects. On average, the temperatures from cloudy retrieval are about 0.5-1.0 K warmer than the GPS RO wet retrieval, except for the altitudes near the nimbostratus base. The differences of temperature between the two methods are largest in summer and smallest in winter. The lapse rate in altostratus clouds is around 6.5°-7.5°C km−1 and does not vary greatly with height. On the contrary, the lapse rate increases significantly with height in nimbostratus clouds, from about 2.5°-3.5°C km−1 near the cloud base to about 5.0°-6.0°C km−1 at cloud center and 6.5°-7.5°C km−1 below the cloud top. Seasonal variability of lapse rate derived from the cloudy retrieval is larger than that derived from the wet retrieval. The lapse rate within clouds is smaller in summer and larger in winter. The mean lapse rate decreases with temperature in all seasons. [ABSTRACT FROM AUTHOR]

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961–2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of −6°C and −4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961–2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991–2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions. [ABSTRACT FROM AUTHOR]

The article presents a time series of major climate indicators in 2013, many of which are said to be essential climate variables (ECM). Topics discussed include atmospheric surface, atmospheric upper air, and atmospheric composition. Also mentioned are ocean surface, ocean subsurface and terrestrial climate indicators.

In atmospheric science we are confronted with inverse problems arising in applications associated with retrievals of geophysical parameters. A nonlinear mapping from geophysical quantities (e.g., atmospheric properties) to spectral measurements can be represented by a forward model. An inversion often suffers from the lack of stability and its stabilization introduced by proper approaches, however, can be treated with sufficient generality. In principle, regularization can enforce uniqueness of the solution when additional information is incorporated into the inversion process. In this paper, we analyze different forms of the regularization matrix L in the framework of Tikhonov regularization: the identity matrix L 0 , discrete approximations of the first and second order derivative operators L 1 and L 2 , respectively, and the Cholesky factor of the a priori profile covariance matrix L C . Each form of L has its intrinsic pro/cons and thus may lead to different performance of inverse algorithms. An extensive comparison of different matrices is conducted with two applications using synthetic data from airborne and satellite sensors: retrieving atmospheric temperature profiles from microwave spectral measurements, and deriving aerosol properties from near infrared spectral measurements. The regularized solution obtained with L 0 possesses a reasonable magnitude, but its smoothness is not always assured. The retrieval using L 1 and L 2 produces a solution in favor of the smoothness, and the impact of the a priori knowledge is less critical on the retrieval using L 1 . The retrieval performance of L C is affected by the accuracy of the a priori knowledge. [ABSTRACT FROM AUTHOR]

The extended range temperature prediction is of great importance for public health, energy and agriculture. The two machine learning methods, namely, the neural networks and natural gradient boosting (NGBoost), are applied to improve the prediction skills of the 2-m maximum air temperature with lead times of 1–35 days over East Asia based on the Environmental Modeling Center, Global Ensemble Forecast System (EMC-GEFS), under the Subseasonal Experiment (SubX) of the National Centers for Environmental Prediction (NCEP). The ensemble model output statistics (EMOS) method is conducted as the benchmark for comparison. The results show that all the post-processing methods can efficiently reduce the prediction biases and uncertainties, especially in the lead week 1–2. The two machine learning methods outperform EMOS by approximately 0.2 in terms of the continuous ranked probability score (CRPS) overall. The neural networks and NGBoost behave as the best models in more than 90% of the study area over the validation period. In our study, CRPS, which is not a common loss function in machine learning, is introduced to make probabilistic forecasting possible for traditional neural networks. Moreover, we extend the NGBoost model to atmospheric sciences of probabilistic temperature forecasting which obtains satisfying performances. [ABSTRACT FROM AUTHOR]

More than 1.35 billion people in India rely on the Indian summer monsoon for water to drink, to irrigate crops and to raise livestock. Although the rainy season happens annually between June and September, the time of monsoon season's onset and withdrawal varies within a month from year to year. Such variability strongly affects agricultural production. In particular, for planning the agriculture cycle, farmers need to know one month in advance when the monsoon arrives. However, official monsoon forecast is delivered two weeks before monsoon onset and for Kerala only - a state in South India. Other states receive the information in the frame of operational weather forecast 2 - 5 days in advance. There is no forecast of withdrawal date at all due to lack of methodology. The worst situation is in central India, which suffering from severe drought before the monsoon starts. A new approach of forecasting monsoon for central India [1] promises considerable progress by showing that an accurate forecast of onset and withdrawal is possible to deliver more than one month in advance.The new approach relies upon the recently discovered feature of monsoon: at the onset of monsoon, some atmospheric variables (in particular, in near-surface air temperature, relative humidity) pass a critical threshold. There is a similar feature at monsoon withdrawal. The critical conditions appear first in the area of the Eastern Ghats (EG), and then it propagates towards to North Pakistan (NP), the areas are defined as Tipping Elements of the Indian Summer Monsoon. The forecast for monsoon is performed for central India (EG) using data from NP area. The forecast relies on analysis of near-surface air temperature, and relative humidity from both the ERA-40 and NCEP/NCAR re-analyzes. The results from the Tipping element approach confirm that the methodology allows forecasting the monsoon retrospectively (over the period 1951-2015) [1], as well as for the future. Thus, successful predictions for upcoming monsoon for 2016, 2017 and 2018 [2] have validated the accuracy of the methodology and proved that such early prediction of monsoon timings is possible.The new methodology offers three key advances of monsoon forecasting: (i) predicting monsoon timing in central India where prediction has never been made, (ii) predicting the date of the upcoming monsoon onset for 40 days in advance, that is unprecedently early; (iii) forecasting withdrawal date for 70 days in advance, that is a new kind of extraordinary early forecast and the only one available in India. Altogether, it is a significant achievement in the atmospheric sciences with great practical importance for the population of India.The new methodology opens new possibilities for regional monsoon forecasting and can be extended for other parts in India and around the globe.The author would like to acknowledge the support of the EPICC project (18_II_149_Global_A_Risikovorhersage) funded by the IKI of the BMU.[1] Stolbova, V., E. Surovyatkina, B. Bookhagen, and J. Kurths (2016): Tipping elements of the Indian monsoon: Prediction of onset and withdrawal. GRL 43, 1–9 [doi:10.1002/2016GL068392][2] https://www.pik-potsdam.de/services/infodesk/forecasting-indian-monsoon [ABSTRACT FROM AUTHOR]

2016 was another very warm year globally. Global temperatures in 2015 and 2016 were clearly the warmest two years on record. The record heat arose from the combined effect of the long-term temperature rise, attributed largely to greenhouse gases, and a temporary boost from the strong 2015/2016 El Niño event. Record low sea-ice extent was observed in a number of months in the Arctic, and December also saw record low extent for the Antarctic. Winter 2015/2016 was the second wettest winter on record for the UK. European-average temperatures in 2016 were nominally the third highest on record, slightly cooler than 2014 and 2015. [ABSTRACT FROM AUTHOR]