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The AMANOM session will focus on observations related to contrails, fog, clouds, precipitation, and short range forecasting of weather conditions associated with aviation operations. Abstracts for all areas of aviation meteorology, including Polar regions, high altitude conditions, as well as airport environments, can be submitted to this session. Work on aviation meteorology parameters such as visibility, icing, gusts and turbulence, as well as fog and precipitation, will be considered for this session. Topics related to In-situ observations obtained from aircraft, Unmanned Aerial Vehicles (UAVs), and supersites, remote sensing retrievals of meteorological parameters from satellites, radars, lidars, and MicroWave Radiometers (MWRs), as well as other emerging technological platforms, and predictions of meteorological parameters from the numerical weather prediction models will be considered highly related to the goals of this session.

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Convener: Ismail Gultepe | Co-conveners: Wayne Feltz, Stan Benjamin, Andrew Heymsfield
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| Attendance Mon, 04 May, 08:30–10:15 (CEST)

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Chat time: Monday, 4 May 2020, 08:30–10:15

D3375 |
EGU2020-12169
| Highlight
Paul Williams

The climate is changing, not just where we live at ground level, but also where we fly in the upper troposphere and lower stratosphere. Climate change has important consequences for aviation, because the atmosphere’s meteorological characteristics strongly influence flight routes, journey times, and turbulence. This presentation will review the possible impacts of climate change on aviation, which have only recently begun to emerge (as opposed to the impacts of aviation on climate change, which have long been recognised).

Turbulence currently injures hundreds of air passengers each year worldwide, costing airlines hundreds of millions of dollars and occasionally causing structural damage to planes. To investigate the influence of climate change on turbulence, we diagnose an ensemble of 21 clear-air turbulence measures from climate model simulations. We find that turbulence strengthens significantly under climate change, all around the world, in all seasons, and at a wide range of aircraft cruising altitudes. For example, within the transatlantic flight corridor in winter at around 39,000 feet, the occurrence of light turbulence increases by an ensemble-mean value of 59% (with an intra-ensemble range of 43–68%), light-to-moderate by 75% (39–96%), moderate by 94% (37–118%), moderate-to-severe by 127% (30–170%), and severe by 149% (36–188%). These findings underline the urgent need to improve the skill of operational clear-air turbulence forecasts, to avoid increases in on-board discomfort and injuries in the coming decades.

To investigate the influence of climate change on flight routes and journey times, we feed atmospheric wind fields generated from climate model simulations into a routing algorithm of the type used operationally by flight planners. We focus on transatlantic flights between London and New York, and how they change when the atmospheric carbon dioxide (CO2) concentration is doubled. We find that a strengthening of the prevailing jet-stream winds causes eastbound flights to significantly shorten and westbound flights to significantly lengthen in all seasons. For example, eastbound and westbound crossings in winter become approximately twice as likely to take under 5 hours 20 minutes and over 7 hours, respectively. Even assuming no future growth in aviation, the extrapolation of our results to all transatlantic traffic suggests that aircraft will collectively be airborne for an extra 2,000 hours each year, burning an extra 7.2 million gallons of jet fuel at a cost of US$ 22 million, and emitting an extra 70 million kg CO2.

The above findings provide further evidence of the two-way interaction between aviation and climate change, which is an emerging research area that deserves further study.

How to cite: Williams, P.: Aviation meteorology in a changing climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12169, https://doi.org/10.5194/egusphere-egu2020-12169, 2020.

D3376 |
EGU2020-878
Inna Khomenko and Oleksii Hustenko

Fog that limit visibility and low-level stratiform clouds represent a significant hazard to aviation especially during takeoff and landing, and also low-level flying of aircrafts, because accidents often occur in reduced visibility conditions and low clouds. Therefore, forecasting fog and low ceilings is one of the most important, but at the same time the most difficult issue, because both phenomena strongly depend on local conditions and unsteady in both time and space. So weather observations can be used for statistical dependencies of fog/ low-level stratiform cloud characteristics on numerical model outputs.

To study fog and low-level stratiform clouds event characteristics occurring at the airport of Odessa, Ukraine, half hourly observations in the period of 2010-2018 are used. Applying a statistical approach annual, seasonal and diurnal distribution of fog and low stratus and their frequency distribution associated with various meteorological parameters are obtained.

The monthly distributions of low-level stratiform clouds reveal maximum occurrence frequencies in November and January, and fog most frequently occurs in December. No significant diurnal cycle of stratiform cloud occurrence is discovered, as opposed to fog for which the highest frequency is observed in the hours before sunrise, while when the day sets in, frequencies are declining and increasing at night.

Fog and low-level stratiform clouds have the same distribution in duration and the mean event duration is 4.5 h while 55% of the events lasted 2 h or less. The most long-lived fog and stratiform clouds can last about 4 days during the December-January period.

Occurrence of fog and stratiform clouds as function of temperature and relative humidity reveals a close statistical relationship, especially for fog events. More than 33% of all fogs are observed at temperatures of 0°C to 6°C and 96-100% relative humidity, the most frequencies of low-level clouds (13%) occur in the same temperature interval, but at lower values of relative humidity (91-95%).

Regarding fog density 75% of the events have minimum visibility lower than 400 m, which indicates the severity of the problem, because, despite the season and type of fog, they are usually quite intense and dense.

In all seasons of the year, the highest frequency of low-level stratiform clouds is in interval of 3...4 m/s, excluding summer, when most often such cloud is registered at higher speeds. The wind directions associated with low-level stratiform clouds are, as a rule, northern and eastern ones, which meant that forming stratiform clouds is also related to cyclonic activity.

Fogs, on the contrary, most often in all seasons, except winter, are formed at calm, meaning that radiation fogs are the most common type in the Odessa airport. In winter fogs are most commonly associated with northern and easterly winds; in all other seasons the southern wind is the most frequent.

On this basis, a relationship between the weather conditions near the surface and occurrence of fog and low-level stratiform clouds can be found.

How to cite: Khomenko, I. and Hustenko, O.: Evaluation of local weather observations as predictors of fog and low-level stratiform clouds at the airport of Odessa, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-878, https://doi.org/10.5194/egusphere-egu2020-878, 2020.

D3377 |
EGU2020-4677
Michael Weston and Marouane Temimi

The detection of fog and low cloud (FLC) from satellite data remains challenging despite advances in methodologies and technology. Current methods make use of one or a combination of channel differencing from satellite instruments, surface observations, model data or artificial intelligence. An alternative to the brightness temperature difference method was developed for the GOES-R advanced baseline imager (ABI) which makes use of a channel ratio instead of a channel difference. We apply this method, the so called pseudo emissivity of the 3.9 µm channel, to SEVIRI MSG8 data over the United Arab Emirates, a desert region of the Arabian Peninsula. Low cloud is removed using temperature difference between ERA5 land surface temperature and 10.8 µm channel brightness temperature. Visual inspection of the final fog only mask shows that this method works well over this region. Verification at three sites where METAR data is available returned POD (FAR) of 0.77 (0.27), 0.50 (0.65) and 0.83 (0.26) respectively. Application of this method can be further developed to represent seasonal fog distribution and frequency across the United Arab Emirates.

How to cite: Weston, M. and Temimi, M.: Application of nighttime fog detection method using MSG8 SEVIRI in an arid environment , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4677, https://doi.org/10.5194/egusphere-egu2020-4677, 2020.

D3378 |
EGU2020-2526
Wanchun Zhang

The outgoing longwave radiation (OLR) is a crucial parameter for studying many areas in the atmospheric science, including the investigations of the cloud/water vapor/radiative interaction processes, climate variability, and for climate change monitoring and numerical model evaluation and diagnostics, etc. The OLR has continued being observed or estimated from Fengyun meteorological satellites, including solar orbit satellites (such as FY3D/MERSI) and geostationary satellites (such as FY4A/AGRI).

The advantage of solar orbiting satellites is global coverage. Thus it is difficult to reflect the diurnal variation of OLR for twice observations a day. While geostationary satellites are observed 24 times a day, which can accurately describe the diurnal variation of OLR. But its coverage is limited. Therefore, the development of OLR fusion products combined with solar orbit satellite and geostationary satellite, can improve product accuracy without losing coverage advantage. In this study, we use OLR from FY4A and FY3D to build a fusion OLR product to correct the diurnal variation of OLR, and get good results.

How to cite: Zhang, W.: Outgoing Longwave Radiation and Its Diurnal Variation from Combined FY3D and FY4A, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2526, https://doi.org/10.5194/egusphere-egu2020-2526, 2020.

D3379 |
EGU2020-2899
Peter Bräuer, Hanna Weikert, and Matthias Tesche

Effects of aviation on the Earth’s radiation budget and climate related to CO2 emissions and from the formation of linear contrails and contrail cirrus have been the focus of detailed studies. Aviation effects on existing cirrus clouds are much less investigated. Contrail formation in existing cirrus clouds has the potential to increase the cloud optical thickness (COT) of optically thin cirrus, which might result in a net cooling effect.

Spaceborne remote sensing generally provides the means for studying the impact of aviation on climate. However, only active instruments such as lidar or radar can be used to study the effect of contrails that form within existing cirrus clouds. For such an investigation, the location of an aircraft at a given time needs to be matched with information on cloud coverage, cloud type, cloud layer height, and COT as can be retrieved from spaceborne CALIPSO lidar data.

We have developed an algorithm to find intersections of aircraft flight tracks with satellite tracks. Besides the spatial coordinates, the time difference between the passing of the aircraft and the satellite at the intersection is monitored and relevant aircraft data and satellite recordings are retrieved at the intersection. The algorithm is highly adjustable so that it can be adapted for other applications such as investigation of ship tracks or cloud tracking. The new algorithm has been used to identify aircraft flying through cirrus clouds in remote regions of the Earth to study the effects of individual aircraft on existing cirrus.

How to cite: Bräuer, P., Weikert, H., and Tesche, M.: Investigating contrails within cirrus clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2899, https://doi.org/10.5194/egusphere-egu2020-2899, 2020.

D3380 |
EGU2020-3193
Jing Sun

Two tests of aircraft icing observations were conducted on March 2018 in Xin Jiang in northwest of China. The icing conditions are studied using observations of satellite, radar, soundings and simulations using the WRF mesoscale model coupled with CAMS cloud scheme. The large-scale weather systems of the two icing cases are the vortex and the shallow trough on 500hPa separately, accompanied by the cold front on the surface. The icing time is in the early stage of vortex system and the middle stage of shallow trough system. The icing clouds are both low and middle clouds. The cloud top height is 4km and the cloud top temperature is -15~-25℃. The cloud bottom height is 1.5km and the cloud thickness is 1-3km. The optical thickness is larger than 12 and the radar reflectivity is less than 10dBZ. There is an inversion layer of the shallow trough. The microphysical structures of CPEFS model simulations show that the icing cloud is composed of large number of supercooled water and few ice particles. The CIP initial icing potential results can basically reflect the icing height and time of the two cases.

How to cite: Sun, J.: Two Cases Studies of Cloud Structures of Aircraft Icing Tests in the Northwest of China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3193, https://doi.org/10.5194/egusphere-egu2020-3193, 2020.

D3381 |
EGU2020-4889
Mariëlle Mulder, Delia Arnold, Christian Maurer, and Marcus Hirtl

An operational framework is developed to provide timely and frequent source term updates for volcanic emissions (ash and SO2). The procedure includes running the Lagrangian particle dispersion model FLEXPART with an initial (a priori) source term, and combining the output with observations (from satellite, ground-based, etc. sources) to obtain an a posteriori source term. This work was part of the EUNADICS-AV (eunadics-av.eu), which is a continuation of the work developed in the VAST project (vast.nilu.no). The aim is to ensuring that at certain time intervals when new observational and meteorological data is available during an event, an updated source term is provided to analysis and forecasting groups. The system is tested with the Grimsvötn eruption of 2011. Based on a source term sensitivity test, one can find the optimum between a sufficiently detailed source term and computational resources. Because satellite and radar data from different sources is available at different times, the source term is generated with the data that is available the earliest after the eruption started and data that is available later is used for evaluation.

How to cite: Mulder, M., Arnold, D., Maurer, C., and Hirtl, M.: Operational evaluation of volcanic source terms (volcanic ash and SO2) from inverse modelling for aviation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4889, https://doi.org/10.5194/egusphere-egu2020-4889, 2020.

D3382 |
EGU2020-19130
Natalie Harvey, Helen Dacre, and Helen Webster

In the event of a volcanic eruption airlines need to make fast decisions about which routes are safe to operate and to ensure airborne aircraft land safely.  Currently these high-impact decisions are based on qualitative forecasts produced without any indication of uncertainty. Two of the largest sources of uncertainty in forecasting ash cloud location and concentration are the emissions of ash from the volcano and the meteorological situation. This study extends the UK Met Office Inversion Technique for Emission Modelling (InTEM) system to use an ensemble of meteorological conditions to investigate the dependence of emission estimates on wind field and wet deposition uncertainty. In the case of the 2011 Grimsvotn eruption, preliminary work shows that the impact of the variability of the ensemble wind fields is greater than that of the variability in the wet deposition. The next steps in this research are to quantify the improvement in the forecasts of ash location due to this ensemble approach and to develop an operational methodology that can be applied in a real-time emergency response situation.

How to cite: Harvey, N., Dacre, H., and Webster, H.: The impact of ensemble meteorology on volcano emission estimates and ash dispersion forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19130, https://doi.org/10.5194/egusphere-egu2020-19130, 2020.

D3383 |
EGU2020-5154
Andre Lanyon, Jessica Standen, and Piers Buchanan

Terminal Aerodrome Forecasts (TAFs) are a widely accepted international form of aviation forecast used for flight planning procedures at all major airports. TAF production in the UK is currently a time-consuming, manual process carried out by Operational Meteorologists. It has long been speculated that providing a numerical weather prediction (NWP) model-derived first guess solution could bring large improvements in the efficiency of TAF production. Research into first guess TAFs has a long history but making progress has been challenging. However, significant progress has been made at the Met Office in recent months. A practical approach has been adopted that draws on experience of manually producing TAFs. Although NWP model data is utilised as much as possible, steps have been taken to ensure the first guess TAFs are kept as simple and readable as possible whilst retaining information important to the customer. By taking this approach, it is hoped that the first guess TAFs will require minimal intervention from Operational Meteorologists in the majority of weather situations. Development of first guess TAFs is still in the preliminary stages and not all weather parameters are currently included. However, they are produced in such a way that they can be verified using standard Met Office methods, allowing objective comparison with operationally issued TAFs. Verification scores analysed over a 3 year period are encouraging and suggest that forecast performance of first guess TAFs is generally similar to that of operationally issued TAFs. Occasionally, some large differences become apparent when comparing forecasts of rare events such as mist, fog and very low cloud bases, and this is likely to be an area of future research. With further development, it is speculated that the use of first guess TAFs could significantly reduce TAF production time, allowing Operational Meteorologists to make better use of their expertise, perhaps by adding value to model output or by providing valuable consultation services to aviation customers.

How to cite: Lanyon, A., Standen, J., and Buchanan, P.: A New Process for Producing First Guess TAFs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5154, https://doi.org/10.5194/egusphere-egu2020-5154, 2020.

D3384 |
EGU2020-6937
Adrien Warnan
In the framework of a single european sky and to improve Air Traffic Flow and Capacity
Management, involved actors need to share a common situational awareness of the airspace
conditions. These include the meteorological conditions with a focus on weather phenomena with a
strong impact on air traffic and network operations such as convection.
Within this framework, Météo-France is working to provide a new product of convection forecasts
based on ensemble prediction system (EPS) and global model, and is developing a similarity-based
method (Rottner et al., 2019) at Centre National de la Recherche Météorologique (CNRM).
The method aims to detect areas where meteorological conditions are homogeneous which are
called called objects. The latter are defined by a reference histogram representing the
meteorological phenomena to be detected and so are physically consistent. The similarity-based
method can be applied to each member of a EPS. The results can be summarized by a map that
contains the information predicted by all members of the ensemble. Thus, it provides spatialization
for local weather events. This method is currently tested to detect rainfall objects, however we can
apply this method to detect other event type, like convection. To discriminate the convection
characteristic within these rainfall objects, we use a diagnostic of cloud top pressure extracted from
global model outputs. Furthermore, to improve the convection forecast accuracy, the similarity-
based method can also be applied to several models to create a composite of convection forecast.
Météo-France will soon deliver a convection potential product to aeronautical users.

How to cite: Warnan, A.: Object-based aviaton convection forecasts from global ensemble model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6937, https://doi.org/10.5194/egusphere-egu2020-6937, 2020.

D3385 |
EGU2020-10962
Austin Cross, Stephanie Avey, and Dan Veitor

The Helicopter Emergency Medical Services (HEMS) tool is designed to be an intuitive web-based platform that presents weather conditions for short-distance and low-altitude flights to non-weather experts quickly and effectively.  Having timely and accurate weather information is crucial for the flight planning needs of the HEMS community.  

The Aviation Weather Center (AWC) has been working closely with FAA partners from the Aviation Weather Research Program (AWRP) and the Aviation Weather Demonstration and Evaluation (AWDE) Services group to enhance the ceiling and visibility capabilities within the tool, as well as the usability of the tool to meet user needs. An updated gridded ceiling and visibility analysis, as well as forecast ceiling and visibility, are two recent improvements based on user evaluation results that are set for operational implementation in early spring 2020. Evaluations have shown that users span well beyond helicopter pilots, and therefore the tool must evolve to accomodate all low level flight users, including unmanned aerial systems (UAS)/urban air mobility (UAM) users.

To meet this evolution, AWC will be incorporating the HEMS tool capabilities into the same framework as the one-stop-shop tool for general aviation users, the Graphical Forecasts for Aviation (GFA). The Low Altitude GFA (GFA-LA) will continue to meet the needs of the HEMS community, and will provide better consistency with other products across aviationweather.gov providing a common user experience for all aviation users. Research into automated quality control of surface observations is expected to allow addition of non-regulated station information to be added, and work on on-the-fly visualizations is expected to allow three dimensional data interrogation. Recent updates to the HEMS tool, as well as future plans to evolve HEMS into GFA-LA will be presented.

How to cite: Cross, A., Avey, S., and Veitor, D.: Evolving the Helicopter Emergency Medical Services (HEMS) Tool, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10962, https://doi.org/10.5194/egusphere-egu2020-10962, 2020.

D3386 |
EGU2020-18368
Nikolaos Papagiannopoulos, Vassilis Amiridis, Aldo Amodeo, Sara Barsotti, Giuseppe D'Amico, Anna Gialitaki, Anna Kampouri, Giuseppe Leto, Michelle Maree Parks, Simona Scollo, Stavros Solomos, and Lucia Mona

Volcanic eruptions have the capacity to significantly impact human life, consequently, tools for mitigating them are of high importance. The early detection of a potentially hazardous volcanic eruption and the issuance of early warnings concerning volcanic hazards (e.g. ash dispersal), are key elements in the initiation of operational response procedures. Historically, lidars have not typically played a key operational role during volcanic eruptions, with other remote sensing instruments such as radars, infrared and ultraviolet cameras being preferred. Recently, a tailored product of the European Aerosol Research Lidar Network (EARLINET) for the early warning of the presence of volcanic ash and desert dust plumes at cruising altitudes has been developed. Here, we extend the applicability of this methodology to lidars and ceilometers near active volcanoes in Iceland and Mt. Etna in Italy. The tailored methodology and selected case studies will be presented, demonstrating its potential for real-time application during volcanic eruptions.

Acknowledgements: This work has been conducted within the framework of the E-shape (Grant Agreement n. 820852) and EUNADICS-AV (Grant agreement no. 723986) H2020 projects. Furthermore, the authors acknowledge the ACTRIS-2 and ACTRIS Preparatory Phase projects that have received funding from the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 654109) and from European Union’s Horizon 2020 Coordination and Support Action (grant agreement No. 739530), respectively.

How to cite: Papagiannopoulos, N., Amiridis, V., Amodeo, A., Barsotti, S., D'Amico, G., Gialitaki, A., Kampouri, A., Leto, G., Parks, M. M., Scollo, S., Solomos, S., and Mona, L.: EARLINET/ACTRIS Early Warning System for atmospheric aerosol aviation hazards, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18368, https://doi.org/10.5194/egusphere-egu2020-18368, 2020.

D3387 |
EGU2020-21913
Piers Buchanan, Jacob Cheung, Katie Bennett, Graeme Anderson, Claire Bartholomew, Debi Turp, Mark Canning, Teil Howard, Andre Lanyon, Edward Steele, Brian Pettegrew, and Matt Strahan

Global aviation industry needs are evolving, with increased volumes of traffic, increased capacity demands and the need to limit the environmental impacts of travel. Therefore, the provision of accurate/detailed meteorological information is becoming even more essential for the safe and efficient management of airline and airport operations.  Underpinning much of this is the World Area Forecast System (WAFS), provided by the London and Washington centres, whose capabilities are currently undergoing significant upgrades that promises improved prediction of en-route hazards. These upgrades, focused on atmospheric turbulence, cumulonimbus cloud, and in-flight icing will see the transition of services to a fully probabilistic offering, as well as the provision of a new high-resolution (0.25 degree) deterministic severity-based forecasts of turbulence and icing (replacing the previously used ‘potential’ metric). With the delivery of the deterministic products due by 2020, and the probabilistic products due by 2024, we will report on these key developments – providing both an overview of the new operational diagnostics and their validation, presenting preliminary results from initial trials involving the ensemble data – enabling users to avoid en-route hazards more safely and efficiently in the future.

How to cite: Buchanan, P., Cheung, J., Bennett, K., Anderson, G., Bartholomew, C., Turp, D., Canning, M., Howard, T., Lanyon, A., Steele, E., Pettegrew, B., and Strahan, M.: Scientific Enhancements to the World Area Forecast System (WAFS)., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21913, https://doi.org/10.5194/egusphere-egu2020-21913, 2020.

D3388 |
EGU2020-22575
Stan Benjamin, Eric James, Joseph Olson, Curtis Alexander, and Terra Ladwig

An accurate short-range cloud and precipitation forecast is a fundamental component of rapidly updating data assimilation/short-range model forecast systems such as the NOAA 3-km High-Resolution Rapid Refresh or the 13-km Rapid Refresh (RAP). To reduce cloud and precipitation spin-up problems, a cloud/hydrometeor non-variational assimilation technique for stratiform clouds was developed within the Gridpoint Statistical Interpolation (GSI) data assimilation system. The goal of this technique was retention into the subsequent model forecast, as appropriate, of observed stratiform cloud and observed clear 3-d volumes.

New observation impact studies show that the ceiling forecasts are particularly improved by use of this cloud/hydrometeor assimilation in the HRRR/RAP model in both summer and winter season.   Daytime 2m temperature and dewpoint forecasts are also improved in the summer period, important for convective storms.

Improved design of the MYNN boundary-layer turbulence scheme is also shown to benefit HRRR/RAP ceiling prediction and is now also being tested in the FV3 3km stand-along regional model and in the NOAA FV3 Global Forecast System.   Improved boundary-layer prediction, also through other parameterization additions for gravity-wave drag and land/lake modeling, is demonstrated and isolated to these modifications.

How to cite: Benjamin, S., James, E., Olson, J., Alexander, C., and Ladwig, T.: A new look at assimilation and boundary-layer modeling effects to improve NOAA ceiling/visibility/convection HRRR forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22575, https://doi.org/10.5194/egusphere-egu2020-22575, 2020.