The fine-scale predictability of severe storms could reduce their impact over the highly urbanized Milan metropolitan area.

The area is located on four river catchments (Lambro, Seveso, Groane and Olona rivers), all characterized by a short concentration time. In particular, among the four rivers, the flash floods of Seveso, after very localized and short thunderstorms, are the most dangerous for the Milan metropolitan area, also due to their frequency. In 2014, considering only the Milan municipality, Seveso floods produced damages for several million euros.

It is well known that atmospheric water vapor content in pre-convective environments and in their surroundings is a key parameter for the development of thunderstorms. In an unstable atmosphere, a high water vapor content can release a high energy, through latent heat of condensation, that helps the convective clouds generation. However, due to its strong spatial and temporal variation, as well as to the technological limitations in its estimate, water vapor trend and pattern in convective environments is still unclear.
Lombardy-based Advanced Meteorological Predictions and Observations (LAMPO) is a pilot project, funded by the Cariplo Foundation and led by the Geomatics and Earth Observation Laboratory (GEOlab) of Politecnico di Milano in cooperation with ARPA Lombardia and the Politecnico spin-off GReD (Geomatics and Research Development), which aims at improving the nowcasting of severe storms over the Milan metropolitan area.
The LAMPO system will exploit the continuous water vapor monitoring performed by a dense network of Global Navigation Satellite System (GNSS) low-cost receivers deployed in the Seveso area. The integration of GNSS water vapor measurements with the existent meteorological observations will allow to formulate an early warning system, based on a neural network approach, intended for a direct use of the final decision-maker.

The project started last May 2018 with a study on the climatology of the Lombardy. Meteorological data from 2001 to 2017 provided by ARPA Lombardia ground weather stations have been already analyzed, by developing monthly and seasonal climatology of pressure, temperature, relative humidity, and wind speed. GNSS water vapor delays have been estimated, in the same regions and time span, from the data collected by existent permanent geodetic networks. Those data will be used as well to do monthly and seasonal climatology of water vapor.
At the same time, a detailed analysis of the extreme events, still in progress, will allow for the evaluation of the anomalies of the above variables with respect to the reference climatology. The analysis will exploit also the convective cell database, kindly provided by the Federal Office and of Meteorology and Climatology MeteoSwiss.
The anomalies will be the main input of the neural network at the base of the nowcasting algorithm.
The state of-the-art of the project and the first results of the above analysis will be presented together with a description of the LAMPO GNSS low-cost network design.

Area D - Board 385

Ground-based GNSS data contribute to Atmospheric Science by providing atmospheric water vapour, one of the Essential Climate Variables of the Global Climate Observing System (GCOS).
Water vapor is under-sampled in the current meteorological and climate observing systems, therefore obtaining and exploiting more high-quality humidity observations is essential to weather forecasting and climate monitoring. The production, exploitation and evaluation of operational GNSS Meteorology for weather forecasting is well established in Europe thanks to about two decades of outstanding cooperation between the atmospheric and geodetic communities. In contrast, the use of ground-based GNSS long-term data for climate research is still an emerging field. It is now possible because of the availability of long-term homogeneously reprocessed time series on global and regional scale. These long-term time series of homogeneously reprocessed troposphere parameters will provide a ground-based GNSS climate data record with high potential for climate monitoring. Unfortunately, these time series still suffer from site-related inhomogeneities (for example instrumental changes, changes in the station environment) which might affect the analysis of the long-term variability. Therefore, to get realistic and reliable water vapour trend estimates such change points in the time series need to be detected and corrected for. This presentation deals with the creation of long and consistent time series of ground-based GNSS tropospheric parameters, their conversion into Integrated Water Vapour and their exploitation for climate research.

Area D - Board 386

The Global Navigation Satellite System (GNSS) has been widely used in research and applications for navigation, positioning and atmospheric science, engineering because of its high precision, high temporal resolution, all-weather capabilities and low cost. Thus, many Continuously Operating Reference Stations (CORS) networks have been established around the world.

GNSS signals passing through atmospheric layers are delayed due to the effects of the ionosphere and the troposphere. Therefore, Tropospheric Zenith Delay (ZTD) is considered one of the main error source in GNSS. It can also be considered as a meteorological variable that contains temporal and spatial fluctuations due to the fact that water vapor is estimated from GNSS derived ZTD and is influenced by ZTD errors directly.

Empirical Orthogonal Function (EOF) analysis is a statistical method which is used for decomposing a multi-variate data set into its principal components or EOF modes. For better understanding of EOF analysis, temporal and spatial data matrix is reconstructed with significant EOF modes. Thereafter, statistical significance of the EOF which depends widely on the degree of separation between eigenvalues is determined using “rule of thumb”. In addition, the differences between original matrix and reconstructed matrix are taken as the residual errors. Root Mean Square Residual Error (RMSE) of each matrix are also calculated. The RMSE is a good indicator of the reconstructed matrix and the separation of the significant EOF modes and noise.

In this study, the determination of the separation capabilities of the noise and the principal components of ZTD and the precision of ZTD time series using EOF analysis is investigated. Time series of hourly derived ZTD at 8 CORS stations for 32 days in a test area limited to 30°–34° northern latitudes and 39°–42° eastern longitudes were chosen.

The eigenvalues, eigenvectors, EOF modes and statistical significance of the EOF modes of the observation matrix and RMSE of each reconstructed matrix were calculated. The RMSE value corresponding to the lowest significant EOF value was taken as the precision of ZTD for the evaluation time. In addition, the total variances of significant modes was used in the determination of the optimal level of the EOF modes.

Daily, 10-day, 20-day and 30-day time series were evaluated. As a result, RMSE of ZTD were found to be ± 1,7 mm - ± 3,6 mm. The results were consistent with ± 2,0 mm - ± 4,0 mm, the precision of ZTD obtained from various studies.

Area D - Board 387

Supersaturation (relative humidity) in upper level cirrus clouds are critical to microphysical ice processes (e.g. sublimation/deposition, growth of specific habits, co-existence of supercooled droplets) that can advance our understanding of ice cloud formation and evolution and their impact in the water vapor budget in the upper troposphere. A multi-frequency differential absorption radar (DAR) system, with several tones within the 183.3 GHz water vapour absorption line, is proposed for profiling water vapour within ice clouds. Recent advances in high radar frequency amplifiers have paved the way towards the possible exploitation of these high frequencies from space.
The feasibility of water vapour sounding is assessed by applying a DAR simulator to A-Train observations in combination with collocated European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis.
Observations from the CloudSat W-band radar and from the CALIPSO radar are converted first into ice microphysical properties and then coupled with ECMWF temperature and relative humidity profiles in order to compute scattering properties at any frequency within the 183.3 GHz band. Self-similar Rayleigh-Gans approximation is used to model the ice crystal scattering properties. Then radar reflectivities are computed using the profiles of scattering properties and noise levels which are deemed realistic for a space-borne instrument. Sets of multi-frequency synthetic observation of attenuated reflectivities are finally used to retrieve profile of water vapour density by fitting the line shape at different levels. Water vapour densities can be derived at 500 m vertical resolution and for different integration lengths. 10 days of A-Train observations are used to test the measurement technique performance for different combination of tones when sampling ice clouds globally. Results show that in regions where W-band reflectivities exceed -10dBZ retrievals of relative humidity when employing 6-7 tones can reach accuracies better than 5%. The work will also discuss how to select radar tones that maximize the water vapour signal and minimize errors associated to the spectral variability of the target scattering properties. The 183-GHz radar is a very compact system and it can be deployed as a companion sensor on board a larger payload satellite or as part of a constellation of SmallSats.

Area D - Board 388

Global distributions of atmospheric water vapor content retrieved from several decades of satellite radiothermal observations are available to the researchers nowadays. These regular sequential observations bare essential information on atmospheric mesoscale and synoptic-scale dynamics independent of estimates from numerical circulation models.
The approach of satellite radiothermovision [1] extends the classical inverse problem of retrieving atmospheric geophysical parameters from remote data with a simple description of atmospheric advection thus allowing to link individual phases of fragmentary observable processes. As a result, the two new kinds of products are generated: 1) the global total precipitable water (TPW) fields over the ocean on the 0.25° grid (or even finer) with no gaps interpolated to an arbitrary time; 2) the corresponding (vector) velocity fields, which describe TPW redistribution with time. The accuracy of the resulting dynamical description had been shown to be very satisfactory for numerous research applications [2]. Unlike the known approach [3], satellite radiothermovision does not exploit estimates from numerical circulation models to construct advection field as a weighted sum of wind fields on several horizons. The developed processing algorithm is fully closed in respect to the TPW retrievals from satellite radiothermal observations.
The long-term series of the pairs of TPW and advection fields were calculated for 15-year continuous satellite observations on the 0.25° grid with 6-hour time sampling and are freely accessible on the geoportal of satellite radiothermovision (http://fire.fryazino.net/tpw/). Combining the TPW and advection fields allows a detailed study of atmospheric dynamics in both kinematic (velocities) and energetic (latent heat fluxes) terms. This opportunity has been recently used for a statistical analysis of global atmospheric circulation patterns [4]. Among other results for the first time the meridional latent heat fluxes over oceans as functions of time (6-hour time step) and latitude were calculated within the 70N – 70S belt directly from observational data. This significantly extends the previously known estimates based on synthetic approach [5] (artificial neural networks trained on reanalysis data) by longer time interval, finer time sampling and wider spatial coverage. On the whole the analysis results are in good (or principal) agreement with the theoretical concepts. Also a new indication of so-called tropical belt widening [6] is possibly found.
The present study is mainly focused on a structural element of atmospheric circulation called atmospheric rivers [7]. One key issue is whether the observational data can prove a previously stated concept (based on modeling) [8] that atmospheric rivers (AR) almost totally determine the meridional transport of latent heat in midlatitudes. Some special features of satellite radiothermovision for the study of AR were discussed in [9]. Most important are overcoming of fragmentation problem (AR are only partly observable within satellite swaths) and opportunity to directly calculate latent heat fluxes inside and outside of AR. This allows performing full-coverage multiyear data analysis over all basins of the World Ocean aimed at automated detection of all AR and calculation of their parametric representation (locations, spatial extents, time of existence, frequency of formation, water vapor transport etc). Based on the preliminary results of the study a new climatologic database of AR is designed and developed and is being populated with the parametric descriptions of AR observed since January 2003 (which is currently the beginning of the series of data products generated for the geoportal of satellite radiothermovision). The principal results of the study as well as the data accessibility and formats are to be discussed.

References
1. Ermakov, D.M. & Sharkov, E.A. (2013) Evolution of hurricane Alberto (2000) in the field of water vapor over North Atlantic retrieved from satellite data. In Proc. ‘ESA Living Planet Symposium 2013’, 9–13 September 2013, ESA SP-722, 312.
2. Ermakov, D.M., Sharkov, E.A. & Chernushich, A.P. (2015) Satellite radiothermovision of atmospheric mesoscale processes: case study of tropical cyclones. ISPRS Archives. XL(7/W3), 179 – 186.
3. Wimmers, A.J. & Velden, C.S. (2011) Seamless advective blending of total precipitable water retrievals from polar orbiting satellites. J. Appl. Meteor. Climatol. 50(5), 1024–1036.
4. Ermakov, D.M. (2018) Global circulation of the latent heat in the Earth’s atmosphere according to satellite radiothermovision. Izvestija, Atmos. Ocean. Phys. 54(9) (in print).
5. Liu, W.T. & Tang W. (2005) Estimating moisture transport over oceans using space-based observations. J. Geophys Res. 110(D10101), doi:10.1029/2004JD005300.
6. Lu, J., Deser, C. & Reichler T. (2009) Cause of the widening of the tropical belt since 1958. Geophys. Res. Lett. 36(L03803), doi:10.1029/2008GL036076.
7. Ralph, F.M. & Dettinger, M.D. (2011) Storms, floods, and the science of atmospheric rivers. Eos. 92(32), 265–272.
8. Zhu, Y. & Newell, R.E. (1998) A proposed algorithm for moisture fluxes from atmospheric rivers. Mon. Wea. Rev. 126(3), 725–735.
9. Ermakov D.M. (2017) Investigation of the features of long-term global atmospheric circulation via satellite radiothermovision. In Proc. Spring (PIERS) 2017, 22-25 May 2017, 413 – 418. doi: 10.1109/PIERS.2017.8261775.

Area D - Board 389

The knowledge of the water vapor distribution in the Earth’s atmosphere is of great importance for weather prediction. Meteorological models, including the so called limited area models, can assimilate humidity measurements, increasing the reliability of the simulated atmospheric dynamics. Existing atmospheric remote sensing instruments are still insufficient to cover global scales with systematic WV measurements in the lowest part of the troposphere (5-6 km): this would indeed help to improve both climate modeling and numerical weather prediction capabilities at short time scale. In order to solve this problem, a new approach (the Normalized Differential Spectral Attenuation-NDSA) capable of estimating the integrated water vapor (IWV) through attenuation measurements in the Ku/K band along microwave is assessed. Nevertheless, the developed technique needs to be demonstrated with real measurements before moving toward space applications. A recent project (SWAMM-Sounding Water Vapor by Attenuation Microwave Measurements) had as main goal to develop low-cost instrumentation to perform the first NDSA measurements. The instrument was designed to operate with the transmitter located on the ground and the receiver placed on a moving platform (e.g. airborne, stratospheric balloon, HAPS), even though, as a preliminary test, the instrumentation was tested in a ground- to-ground link configuration. An instrument prototype, which includes a synthesized microwave transmitter and a Software Defined Radio (SDR) microwave receiver has been designed, assembled and tested in laboratory. Laboratory tests confirm that the transmitter generates two tones, respectively at 18.8 GHz and 19.2 GHz, with very high stability in both amplitude and frequency, and the receiver measures the amplitude (and its fluctuations) of the received signals with enough accuracy (< 0.1 dB) over a wide dynamic range. The differential attenuation is ±0.02dB then far below the theoretical value of the minimum sensitivity required to measure IWV. The instrument was then tested on a ground-to-ground link during an experimental campaign, which was carried out in the period June-October 2018. In order to obtain a transect in the troposphere of tens of km, (thus providing a value of differential attenuation high enough to be measurable by the instrument), the transmitter was installed at sea level and the receiver on the top of a mountain (around 2165m a.s.l.). In detail, the receiver and the transmitter were installed at the CNR laboratories, respectively in Bologna (central Italy) and Cimone mount in the Apennines; as a result, the length of the transect is 62 km. Data are acquired continuously for four months well covering different atmospheric conditions occurred in the summer/autumn seasons. Differential attenuation exhibits temporal variations, at both weekly and monthly scales, which can be correlated to the IWV. As first validation we compared the IWV calculated by NDSA measurements with the same quantity calculated, under the assumption of plane parallel atmosphere conditions, by using different hygrometers placed along the transect and daily radiosoundings of a nearby WMO station. The comparisons show that data are generally in good agreement as both absolute values and temporal variations. However, further investigations are necessary to better interpret the results also in terms of a few discrepancies found. Finally, Sentinel- 3 OLCI L2- IWV product will be used as additional term of comparison for the retrieved IWV over the same transect. A detailed analysis will be presented at the conference.

Area D - Board 390

The Microwave Radiometer (MWR) flown onboard each of the satellites ERS-1, ERS-2, and Envisat provides a nearly uninterrupted time series of microwave observations over a period of almost 21 years spanning from 1991 to 2012. This dataset is complementary to other microwave datasets, such as from e.g. the Special Sensor Microwave Imager (SSM/I). Despite its nadir-only coverage, it provides an opportunity to independently provide estimates on total column water vapor (TCWV) and cloud liquid water path (LWP) above the global ice-free oceans.

Here we report on our efforts towards a fully inter-calibrated and validated physical retrieval of TCWV and LWP from MWR observations, leading to the generation of the publicly and freely accessible EMiR (ERS/Envisat Microwave Recalibration) data record, meanwhile available in Version 1.1. We will address issues related to satellite inter-calibration, homogeneity of the derived time series of brightness temperatures, and observation-simulation biases. We will provide results of fully physical optimal estimation retrievals of TCWV and compare those to independent TCWV observations, both ground and satellite based. An outlook on future envisaged activities will be given and the importance of the results in light of the anew availability of MWR observations through the Sentinel-3 series of satellites since February 2016 will be discussed.

We finally analyze the impact of the EMiR TCWV on wet tropospheric correction (WTC) of ocean altimetry observations and subsequently identify a number of improvements to be applied in the context of a future reprocessing with the aim to further increase accuracy and coverage and enhance user-friendliness.

Area D - Board 391

Water vapour is the single most important natural greenhouse gas in the atmosphere, thereby constraining the Earth’s energy balance, and is also a key component of the water cycle. Due to its importance, the WMO’s Global Climate Observing System (GCOS) program has highlighted water vapour as an Essential Climate Variable (ECV) in the GCOS 2016 Implementation Plan. There is consequently the need to consolidate our knowledge of natural variability and past changes in water vapour and to establish climate data records of both total column and vertically resolved water vapour for use in climate research. These climate data records need to be homogeneous in space and time, which bears great challenges due to changing instrument characteristics and performances. Well-characterized uncertainties will be a key attribute of the envisaged climate data records in order to reduce the uncertainty in estimates of climate change and global radiative forcing. The Climate Change Initiative (CCI) is a program of the European Space Agency (ESA), established to tackle the challenges encountered in merging climate data records of ECVs and has the goal to provide climate modelers and researchers with long-term satellite records from current and past European (and other space agencies’) missions. In this contribution, we will introduce the ESA CCI Water Vapour project and present first results related to both stratospheric and tropospheric water vapour. In particular, we will focus on the use of chemistry-climate models to help assess sampling uncertainties in observational datasets, which can introduce biases in climatologies on both temporal and spatial scales. We also will discuss the use of such models as transfer functions between different observational time series, which help assess observational biases over a longer time span that just during the years of measurement overlap. We will show that this procedure allows for a more informed bias-correction, but also helps assessing drifts in instruments.

Area D - Board 392

THE VALIDATION OF FY-3D MWRI TOTAL PRECIPITABLE WATER PRODUCTS

Qiong Wu, Fangli Dou, Songyan Gu

National Satellite Meteorological Center, CMA
Email: wuqiong@cma.gov.cn

FY-3D is the second generation polar meteorological satellite which is developed by china independently and launched in November 15, 2017. MWRI (Microwave Radiance Imager) is an important microwave load which can monitor air, ocean and land. For MWRI there are 10 channels corresponding to 5 frequencies (10.65, 18.7, 23.6, 36.5 and 89GHz) and 2 polarizations (V-pol and h-pol). This channel set is more than sufficient to separate the atmosphere signals (vapor, cloud and rain). As a product of MWRI，TPW (Total Precipitable water) can be used in numerical weather prediction(NWP) and climate research. But, the result of application relied on the accuracy of TPW. FY-3D TPW products have three categories. They are separately orbit product, daily product and month product.
The FY-3D TPW retrieval algorithm is a regression algorithm that express TPW in terms of brightness temperature (TB). The TPW can be obtained from the following expressions:
TPW = α_0 + ∑α_1（In290-T_Bi ）（i=1,2,3...）
where T_Bi refers to the brightness temperature for the ith channel. The channels which have been chosen in retrieval are separately 18.7V, 18.7H, 23.6V, 23.6H, 36.5V and 36.5H. The terms α_0 and α_1 are regression coefficients that are determined from a 4-monthes satellite observation brightness temperature and radiosonde TPW.
By using 3-monthes satellite observation data, the quality of TPW products is validated through the comparison between TPW products and 42 NCDC (National Climate Data Center) IGRA (Integrated Global Radiosonde Archive) stations data. As a result, the RMSE (Root Mean Square Error) of orbit product is 2.7mm and the average relative error is 12%. What’s more, the RMSE of day product is 1mm when compare with AMSR2 daily product from RSS (remote sensing system). The accuracy of month product is stable and less than 1mm.

Area D - Board 393

Utraviolet/visible (UV/vis), near infrared (NIR) and IR measurements from satellites allow the retrieval of information on atmospheric water vapour on global scale since the late 1970s (IR), over land and ocean (IR, UV/vis) and with high spatial resolution over land (NIR). All related retrievals are applied under predominantly clear-sky conditions. Though a careful validation of instantaneous water vapour products revealed high quality, gridded and temporally averaged products reveal systematic differences among another as it was shown for example by the GEWEX water vapor assessment. These differences can partly be explained with the clear-sky bias: conditions are typically more humid in clouds than in surrounding clear-sky areas, thus leading to a systematic difference between purely clear-sky and clear-sky and cloudy observations. This systematic difference is in the order of 10% and was estimated using data from a single microwave sensor. In order to provide a reliable uncertainty estimate for gridded and temporally averaged clear-sky products the contribution of this source of uncertainty to the total uncertainty needs to be characterized. This is the final goal of this effort. In addition, a bias between all-sky and cloudy-sky observations is potentially present.
We present results from the analysis of the clear-sky bias as a function of local overpass time and cloud information. This analysis relies on water vapour and cloud information from the latest reanalysis of the European Centre for Medium-Ranged Weather Forecasts, ERA5. ERA5 is used as it provides the relevant parameters at required spatial and temporal resolutions. In addition, the clear-sky bias will be assessed using collocated Global Navigation Satellite System (GNSS) and Medium Resolution Imaging Spectrometer (MERIS) data, i.e., at MERIS specific overpass. This way the ERA5 based results will be evaluated at the time of the MERIS overpass, and the diurnal cycle of clouds and its impact on the clear-sky bias will be described. First results from the analysis of a potential cloudy-sky bias will be presented as well.

Area D - Board 394

The Ocean and Land Colour Instruments (OLCI) flying on-board the Sentinel3-A and Sentinel 3-B platforms have two dedicated near infrared bands (Oa19 and Oa20 at 0.9µm and 0.94µm resp.) for the retrieval of total columnar water vapor under clear sky conditions, providing high spatial resolution and accuracy over land surfaces on a global scale. OLCIs operational L2 product, based on the OLCI precursor MERIS, uses band 19 only. We will present the results of an ongoing validation based on comparisons with ground based GNSS (Ware et al 2000) measurements, water vapor from AERONET (Pérez-Ramírez et al 2014, Holben et al 1998) and water vapor from ground based microwave radiometer at the Atmospheric Radiation Measurement (ARM) Climate Research Facility of the US Department of Energy ARM (Turner et al. 2003, Turner et al. 2007). We concentrate on the non-time-critical reduced-resolution data (RR NT). Up to now, several 10000 co-locations of OLCI-A with AERONET and GNSS stations have been identified for the time period from 2016-04. For a matchup, the temporal distance between the satellite overpass and the ground acquisition had to be less than 30 minutes. Only OLCI measurements are used for the validation which are cloud-free (according to the standard cloud flags: cloud, cloud margin and cloud ambiguous) in an area of about 20x20 km².
To account for the enhanced ability of OLCI (compared to MERIS) we developed a new water vapor retrieval, being applicable for MERIS, OLCI and furthermore MODIS. In this way it is suited to fill the observational gap between MERIS and the OLCI series. We will present first validations for the new retrieval.

Area D - Board 395

An in-depth understanding and advanced prediction of the Earth’s temperature and water vapour fields is fundamental for a sustainable development of the Earth system. However, our understanding of the water and energy cycles still shows critical gaps on all temporal and spatial scales. This is mainly due to a lack of accurate high vertical resolution measurements of water vapour and temperature profiles - hereafter called thermodynamic (TD) profiles - with high temporal-spatial resolution, especially in the lower troposphere [1]. These observational gaps can be addressed with a new active remote sensing system in space based on the lidar technique. Combining vibrational and rotational Raman backscatter signals, simultaneous measurements of water vapour and temperature profiles and a variety of derived variables are possible with unprecedented vertical and horizontal resolution, especially from the surface to the lower troposphere. This is the key concept of the Atmospheric Thermodynamics LidAr in Space – ATLAS, which was recently submitted (March 2018) to the European Space Agency in response to the Call for Earth Explorer-10 Mission Ideas in the Frame of the ESA Earth Observation Envelope Programme. The instrument is based on the experience and know-how gained with the development and operation of several existing ground-based instruments and airborne instruments.
In addition to the temperature and water vapour mixing ratio profile, among the independently measured further products: the particle backscatter and extinction coefficient profiles in the UV, allowing the determination of the optical properties of aerosol layers and the geometric and optical properties of clouds, thus complementing similar measurements performed with EarthCARE; the profile of relative humidity, the real daytime PBL depth over land and the oceans directly obtained from the temperature profile, as well as atmospheric stability parameters like buoyancy, convective available potential energy (CAPE) and convective inhibition (CIN).
Recent advances in solid-state laser, large-aperture telescope, and detector technologies allow achieving a new performance level from space with this technique. With a laser power of up to 250 W in the ultraviolet (UV) and a telescope with a 4 m primary mirror, the above specified observational requirements will be reached, thus realizing a breakthrough in earth system sciences. Different candidates for the laser transmitter of ATLAS are available, one of them being a frequency-tripled, diode-laser pumped Nd:YAG laser and the other one a frequency-doubled alexandrite laser. The use of a new generation of pump chambers and diode lasers results in a wall-plug efficiency of > 5 %. The receiver will consist of a large-aperture telescope with a diameter of 4 m. Such a telescope would be larger than the ones of previous lidar missions, but stability and optical quality demands are significantly relaxed (no astronomic quality needed) and the receiver technology is comparatively simple and very rugged.
An assessment of the specifications of the different lidar sub-systems has been performed with the analytical simulation model for space-borne Raman lidar systems developed at Università della Basilicata. The expected performance was simulated under a variety of environmental and climate scenarios using different atmospheric reference models, which cover various climatic regions and seasons as well as a variety of solar illumination conditions. In our present simulations the payload is hosted on a frozen dusk/dawn low-Earth sun-synchronous orbit at an altitude of 450 km (inclination ~97 degrees). The horizontal spatial coverage domain will be global, i.e. from tropical to sub-polar regions. With daily overpasses at 6/18 h local time, it is possible to capture the TD states before and after the daytime development of the PBL, which are very important for data assimilation in weather forecast models. Vertical profiles of the water-vapour mixing ratio and of temperature uncertainty have been estimated for the tropical and mid-latitude summer atmospheric reference models. For the tropical atmosphere values of the water-vapour mixing ratio uncertainty are in the range 2-20 % and 3-30 % up to 5.5 km for a horizontal resolution of 50 and 20 km, respectively, while for the mid-latitude summer atmosphere values are in the range 2-20 % and 3-30 % up to 4 km for a horizontal resolution of 50 and 20 km, respectively. For both the tropical and mid-latitude summer atmosphere values of the temperature uncertainty are in the range 0.4-1 K and 0.7-1.2 K up to 18 km for a horizontal resolution of 50 and 20 km, respectively. More results from the simulations and more aspects of the proposed mission will be illustrated at the conference.

Area D - Board 396

Lee waves are internal gravity waves which are produced when a stably stratified flow is forced over an obstacle. They are nowadays a well-recognized cause of hazard to aviation, especially under dry condition, when they are not clearly visible. They may also impact the global circulation and the climatological momentum balance, because of their interaction with high mountains, causing non-linear perturbations which may, in turn, interact with the larger-scale flow.
The AIRWAVE (v1 and v2) datasets contain 20-years of day-night Total Column of Water Vapour (TCWV) over water surfaces at the ATSR native 1x1 km2 spatial resolution grid, allowing the investigation of small scale features as the lee waves. We focused our analysis on the Mediterranean region, which is the largest semi-enclosed basin on the Earth. The peculiarities of this area, characterized by complex orography and rough coastlines, may indeed lead to the development of such phenomena. For this purpose, the Mediterranean area was divided in three regions. To identify the regions characterized by lee waves we considered the AIRWAVEv2 TCWV products within an “optimized” latitude/longitude grid. For each grid point, the standard deviation was then computed and used as a proxy for the detection. The classification has been based on the number of grid points having a TCWV standard deviation exceeding a defined threshold. The atmospheric conditions which lead to the lee waves development were identified using the ECMWF wind fields at the finest resolution 0.125°x0.125° (10 metre U wind component, 10 metre V wind component every 6 hours).
During the work it was clear that day time ATSR overpasses may sometimes be affected by wrong cloud mask classification. To overcome this problem, a cloud masking classification based only on ATSR infra-red channels was applied, and new TCWV values have been obtained from the re-analysis of these data.
Here we show some examples of lee waves detections, comparing the AIRWAVEv2 TCWV fields with measurements from other sensors, e.g. from Synthetic Aperture Radar (SAR) observations, and with atmospheric model output from Weather Research and Forecasting (WRF) model.
The application of the AIRWAVE algorithm to the current sensors, e.g. to Sentinel 3 SLSTR, would enable the extension of this study to a longer time period.

Area D - Board 397

Water vapour in the upper troposphere and lower stratosphere (UTLS) is a key component of the Earth climate, not only through its radiative impact in the shortwave and in the longwave, but also because it is a central element of stratospheric chemistry, affecting in particular stratospheric ozone. Although UTLS water vapour is characterized by significant spatial and temporal variations, the latter remain poorly understood, and consequently inadequately simulated in numerical weather prediction (NWP) and climate models. This caveat largely stems from a lack of accurate observations in this remote region of the atmosphere, where satellite observations are limited, either because of coarse spatial resolution, or due to insufficient sensitivity to small variations of water vapour.

An original retrieval method was recently developed (Feng & Huang, 2018) to overcome this issue. It shows how infrared sounders can benefit from the presence of optically thick clouds near the tropopause to retrieve above-cloud water vapour. Practically, such clouds mask the strong emission signal originating from the moist lower atmosphere, thus constituting an ideal and better-constrained blackbody-like background to retrieve UTLS water vapour. The original work was applied to data from the Atmospheric InfraRed Sounder (AIRS), but also pointed out that extending current mid-infrared observations to the far-infrared would be very valuable. In the present work, the method is thus extended to the far-infrared range, not yet covered by any spaceborne instrument. As a consequence, the ESA’s 9th Earth Explorer candidate FORUM, which proposes to measure the far-infrared Earth spectrum from 100 to 1600 cm-1, is considered. The nominal instrument characteristics of FORUM are assumed, but alternative configurations are also explored. The potential of the method is investigated in terms of information content of far-infrared radiances. This underlines the strong sensitivity of the Earth far-infrared signature to UTLS water vapour. This also highlights the potential of assimilating cloudy radiances in NWP models, while generally only clear sky scenes are assimilated.

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Atmospheric water plays a key role for the Earth's energy budget and temperature distribution via radiative effects (clouds and vapour) and latent heat transport and the distribution and transport of water vapour is closely linked to atmospheric dynamics on all scales. In this context, global monitoring of the water vapour distribution is essential for numerical weather prediction, climate modeling and the understanding of climate feedbacks.
In the visible spectral range, total column water vapour (TCWV) was first retrieved using Differential Optical Absorption Spectroscopy (DOAS) in the „red“ spectral range (620-670nm) as implemented in the GOME Data Processor GDP because of the relatively strong water vapour absorption in that spectral range. However, this method has some limitations: several post-corrections e.g. due to non-linear effects (for strong water vapour absorptions) have to be applied and the low ocean surface albedo leads to low sensitivity for near-surface layers. In addition some of the new satellite sensors do not cover the red spectral range, e.g. TROPOMI on board ESA's Sentinel 5 Precursor.
Here, we apply a new approach using the spectral absorption structures of H₂O in the „blue“ spectral range (430-450nm). It has the advantage that nonlinear effects are negligible. Also, this spectral window shows a higher sensitivity for near-surface layers over ocean and in general a smoother spatial distribution of the surface albedo compared to the red spectral range.
We use this new algorithm for retrieving TCWV from TROPOMI spectra and compare the results with a variety of different reference data sets.

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The Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) algorithm [Casadio et al. (2016)] exploits the dual view of the Thermal Infrared channels of the ATSR instruments and a sea surface emissivity dataset to compute the Total Column of Water Vapour (TCWV) over water in clear sky conditions. 20-years of day-night TCWV dataset have been produced applying AIRWAVE to the measurements of the Along Track Scanning Radiometer (ATSR) missions.
AIRWAVE has been developed for observations over water surfaces but the algorithm can also be applied to land surfaces. The main difficulty in exploiting land measurements is linked to the knowledge of the surface emissivity in the ATSR infrared channels. While sea emissivity is generally close to one and is almost constant all over the globe, land emissivity has strong variations depending on e.g. surface type and vegetation cover. Furthermore, the angular emissivity variations can also be relevant.
For the extension of the AIRWAVE algorithm to land surfaces, one strategy is the use of tabulated emissivity datasets. The limitations of these datasets is that they report data relative to only daytime (ATSR measures both day and night) and the data are averaged over long time spans (tenth of days). Another strategy is the use of retrieved emissivities from instruments covering the same spectral region of the TIR channels of ATSR and measuring almost at the same time.
Recently Masiello et al. (2013-2015) have developed a retrieval scheme to obtain the Land Emissivity from SEVIRI observations. SEVIRI measures on board the geostationary satellite Meteosat and two of its channels superimpose to the TIR channels of ATSR. Therefore, SEVIRI and AATSR/ENVISAT represent a perfect match to test the possibility of a joint analysis to get both land emissivities and TCWV.
In this work we will show the results of the application of the AIRWAVE algorithm to measurements over land. We will critically compare the results obtained using emissivity databases and the SEVIRI retrieved emissivities, assessing their performance through the comparison of the obtained results with correlative data contained into the ESA DUE GlobVapour project (http://www.globvapour.info/).

Casadio S., et al. (2016) Remote sensing of Environment, doi:10.1016/j.rse.2015.10.037
Masiello G., et al. (2013), Atmos. Meas. Tech., doi:10.5194/amt-6-3613-2013
Masiello G., et al. (2015). Atmos. Meas. Tech., doi:10.5194/amt-8-2981-2015.

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