PRL-3 overexpression in epithelial cells is induced by surrounding stromal fibroblasts

We isolate and culture carcinoma-associated fibroblasts (CAFs) from primary tumour (CAFpt), CAFs from corresponding synchronous liver metastasis (CAFlm) as well as normal colonic fibroblasts (NCF) from the same patient. From these cultures, conditioned media (CM) was obtained. Culture of a wide panel of colorectal and pancreatic cell lines in CM from CAFlm resulted in overexpression of mRNA PRL-3 and higher overexpression in CAFs than in non-activated fibroblasts. Moreover PRL-3 mRNA expression correlates with expression of α-SMA and deposition of collagen fibrils in the stroma. We demonstrate that products secreted by CAFs trigger PRL-3 overexpression in cancer cells. Identification of these factors may contribute to new stroma-targeted therapies for desmoplastic tumours

Level of hamstrings damage depending on force-generating capacity and creatine kinase activity

The aim of the present study was to categorize the eccentric exercise-induced hamstrings damage by using easy measurable markers such as force-generating capacity and serum creatine kinase activityPeer ReviewedPostprint (published version

The ROHP-PAZ Polarimetric Radio Occultation research dataset and its applications

Trabajo presentado al 7th International Workshop on Occultations for Probing Atmosphere and Climate y al 9th Workshop of the International Radio Occultation Working Group (OPAC-IROWG), celebrados del 8 al 14 de septiembre de 2022 en Leibnitz, Austria.After more than 4 years on orbit, the Radio Occultations and Heavy Precipitation aboard PAZ satellite (ROHP-PAZ) experiment has already demonstrated the ability of polarimetric radio occultations (PRO) to detect precipitation. In fact, PRO have shown potential not only in rain detection, but also in precipitation characterization and in sensing the associated vertical cloud structures. PAZ PRO Δϕ observable profiles were made available in 2020 trough the ICE servers (https://paz.ice.csic.es), (https://genesis.jpl.nasa.gov). and more recently through the JPL A new re-processing of the PRO observations is being carried out with the aim to make it public during the second half of 2022. In addition to a better treatment of the rainy observations, the new re-processed profiles will come with an extensive collocation dataset that will allow the users to address scientific studies much more easily. These will take into account the limb-sounding geometry of the observations, performing the collocations directly into the RO rays obtained through a ray-tracer. These collocations include observations like the 30-minute geostationary 10.8 µm brightness temperature, GPM IMERG surface precipitation, microwave brightness temperatures from the numerous overpasses by the satellites in the GPM constellation, radar reflectivities from the GPM core satellite and the NEXRAD ground based weather radars, among others. Furthermore, the collocation algorithms are designed so that more external observations can be easily included. In addition to the exact collocations as described above, external databases are also checked so that coincidences with Tropical Cyclones, Mesoscale Convective Systems and other relevant precipitating systems are identified nearby PAZ observations. In this presentation, we will show a brief overview of the re-processing of the ROHP-PAZ data, with emphasis in the differences between the Δϕ profiles obtained from UCAR’s CDAAC excess phases and from those obtained from JPL excess phases. After that, examples of the coincident datasets will be presented. Results will include statistics gathered from the differentiation of different precipitation regimes (e.g. stratiform vs convective), identification and validation of cloud top height determination, and comparison with other relevant parameters obtained from the collocated observations.The ROHP-PAZ project is part of the Grant RTI2018-099008-B-C22 funded by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” of the “European Union”. Part of the investigations are done under the EUMETSAT ROM SAF CDOP4. This work was partially supported by the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. Part of this research has received funding from the postdoctoral fellowships program Beatriu de Pinós, funded by the Secretary of Universities and Research (Government of Catalonia) and by the Horizon 2020 program of research and innovation of the European Union under the Marie Sklodowska-Curie grant agreement No 801370.Peer reviewe

A Multi-center exercise on the sensitivity of PAZ GNSS Polarimetric RO for NWP modelling

Trabajo presentado al 7th International Workshop on Occultations for Probing Atmosphere and Climate y al 9th Workshop of the International Radio Occultation Working Group (OPAC-IROWG), celebrados del 8 al 14 de septiembre de 2022 en Leibnitz, Austria.A better understanding of the thermodynamics of heavy precipitation events is necessary towards improving weather and climate models and quantifying the impact of climate variability on precipitation. However, there are limited observations available to assess the model structure within heavy precipitation conditions. Recently, it has also been shown that the Radio Occultations Through Heavy Precipitation (ROHP) GNSS polarimetric radio occultation (GNSS PRO) observations are highly sensitive to hydrometeors above the freezing layer, which expands the potential uses of the GNSS PRO dataset for weather-related science and applications. An exercise is presented to analyze the sensitivity of PRO observations for NWP modeling applications. The ROHP experiment now provides over four years of coincident thermodynamic and precipitation information with high vertical resolution within regions with thick clouds. Murphy et al. (2019) simulated GNSS airborne polarimetric RO (GNSS PRO) events along an atmospheric river. These were modeled by the community WRF mesoscale model using two different microphysical parameterization schemes. The GNSS PRO observables simulated with the two schemes differed significantly, more than the actual GNSS PRO precision. The new exercise presented here reproduces this methodology for spaceborne data, using different global and regional NWP models, and it analyzes the results and divergences with the help of actual GNSS PRO data acquired aboard the PAZ satellite. The objectives of the activity are: (1) To compare simulated GNSS PRO observables, generated with models from different centers and different microphysics schemes, against actual PAZ GNSS PRO observables. Can the models reproduce the main features of the actual data? (2) To assess whether different models/schemes result in different GNSS PRO observables, and whether these differences are larger than the measurement uncertainty. This effort provides insight on future methods to assimilate the PRO profile alongside other conventional (non-polarimetric) RO data. (3) To examine the utility of PAZ GNSS PRO observations for model validation and diagnosis. The exercise includes comparisons with ECWMF reanalysis ERA-5 model, the operational NWP at the Japan Meteorological Agency, and a near-real-time implementation of the WRF regional model over the northeastern Pacific produced at the Center for Western Weather and Water Extremes (CW3E) called West WRF, among others.The ROHP-PAZ project is part of the Grant RTI2018-099008-B-C22 funded by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” of the “European Union”. Part of the investigations are done under the EUMETSAT ROM SAF CDOP4. This work was partially supported by the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. Part of this research has received funding from the postdoctoral fellowships program Beatriu de Pinós, funded by the Secretary of Universities and Research (Government of Catalonia) and by the Horizon 2020 program of research and innovation of the European Union under the Marie Sklodowska-Curie grant agreement No 801370.Peer reviewe

Precipitation measurements with polarimetric radio occultations

[eng] In 2009, the Spanish Ministry of Science and Innovation approved a proposal to modify the Global Positioning System (GPS) receiver and to allocate a Polarimetric (Pol) Radio Occultation (RO) antenna in the Spanish PAZ satellite. PAZ became an opportunity to test the new Pol-RO concept, which aims to capture ROs using a two orthogonal linear polarization antenna. The experiment has been named Radio Occultations and Heavy Precipitation with PAZ (ROHP-PAZ). The objective is to measure the phase difference between the horizontal and the vertical components of the incoming electromagnetic field that is induced when heavy precipitation flattened raindrops are present in the ray-path. This effect, widely studied in weather radar community, will be measured from space using GNSS signals for the first time with PAZ, which is planned to be launched in 2017. The main objective of this new concept is to enhance the RO capabilities by providing vertical precipitation information along with the current standard RO thermodynamic products (i.e. temperature, pressure and moisture). Until now, no other observing system has been able to provide simultaneous thermodynamic and precipitation information under extreme conditions. The high vertical resolution, global coverage and all-weather capability properties of the RO observations combined with vertical indication of precipitation intensity can be of great value for heavy rain characterization, and therefore for climate and weather forecast and research. The theoretical background for the technique, its feasibility and applications have been assessed in this dissertation. The theoretical basis has been developed combining electromagnetic propagation theory and cloud and precipitation microphysics. Forward scattering simulations at L-band have been obtained in order to relate the microphysics parameters with the expected Pol-RO observables. The feasibility has been addressed using coincident (in space and time) RO profiles and space-based precipitation observations. Such simultaneous observations allow for the characterization of actual RO measurements according to the coincident precipitation information. Finally, the applications have been investigated through realistic end-to-end simulations of the Pol-RO observations, which provide the anticipated Pol-RO products for different precipitation situations, regions, and seasons. Before the launch of the satellite, a field campaign has been conducted with the aim of starting the characterization of the polarimetric measurements. The engineering model of the PAZ antenna was placed at the top of a mountain peak in order to capture, for the first time, linear polarimetric GNSS signals at low grazing angle. This campaign has been useful to start identifying the hardware internal effects and unexpected precipitation features that will be affecting the Pol-RO observations. These effects have been incorporated to the simulations, hence providing valuable feedback to obtain more realistic Pol-RO products. Besides feedback, the data from the field campaign have shown the first observational evidence that precipitation and other hydrometeors induce a noticeable effect on the GNSS polarimetric signals. All these exercises yielded several relevant results. The noise level analysis from actual RO observations sensing precipitation scenarios has allowed to set a detectability threshold for the technique, indicating that a high percentage of moderate to heavy precipitation events will be detected with PAZ. Nevertheless, the integrated nature of the Pol-RO observable does not allow to distinguish between the contributions from the rain's intensity and extension, leaving an ambiguity in the provided product. In an attempt to solve such ambiguity, a tomographic approach has been proposed, which has yielded promising theoretical results. Moreover, it has been shown how the Pol-RO observables can be linked to physical precipitation parameters, such as the along-ray averaged rain rate, in a probabilistic way. The end-to-end simulation has also revealed that the ionosphere will induce a non-negligible depolarization, that will require calibration. Finally, the collocated data has shown the potential applications for Pol-ROs products.[cat] Obtenir mesures simultànies de l’estat termodinàmic de l’atmosfera i de precipitació ha esdevingut un repte per la comunitat científica. Les missions espacials dedicades a obtenir perfils termodinàmics de l’atmosfera tenen problemes amb la presència de núvols gruixuts, ja que el medi esdevé opac a la radiació infraroja (que és la banda de l’espectre electromagnètic en la qual operen). Alternativament, es poden utilitzar radiosondes. Les radiosondes obtenen perfils termodinàmics de l’atmosfera amb molt alta resolució vertical, però tenen l’inconvenient que el seu llençament necessita certa infraestructura, i per tant les zones més remotes en queden al marge. Això inclou pràcticament la totalitat dels mars i oceans, i moltes zones sub-desenvolupades. Per tant, moltes de les zones amb precipitació extrema no poden ser caracteritzades amb aquesta tècnica. A més a més, la resolució temporal acostuma a ser molt baixa, ja que no se’n poden llençar moltes al dia degut a l’elevat cost econòmic que suposaria. Per altra banda, els radars que mesuren les estructures en tres dimensions de la precipitació no tenen la capacitat d’obtenir perfils de temperatura o pressió. Les estacions meteorològiques, que poden ser molt nombroses en segons quins territoris, estan limitades a mesures en superfície, i altra vegada, mars, oceans i regions sub-desenvolupades en queden al marge. Amb tot, les Radio Ocultacions Polarimètriques emergeixen com una tècnica a tenir en compte a l’hora de caracteritzar precipitació extrema. La seva cobertura global, alta resolució vertical i la capacitat de penetrar en núvols i precipitació la fa una tècnica molt atractiva en aquest sentit. Cada cop més estudis científics coincideixen en apuntar un augment en la frequència d’aquests fenòmens extrems, i una caracterització acurada és necessària per millorar els models de predicció

The polarimetric radio occultations and heavy precipitation aboard PAZ experiment (ROHP-PAZ): findings and challenges after +4 years on orbit

Trabajo presentado al Special COSMIC Seminar, celebrado online en octubre de 2022.Peer reviewe

On the global relationship between polarimetric radio occultation differential phase shift and ice water content

The Radio Occultations and Heavy Precipitation (ROHP) experiment aboard the Spanish PAZ satellite was deployed in 2018 with the objective of demonstrating the ability of the polarimetric radio occultation measurement (PRO) concept in detecting rain (liquid-phase precipitation). Analysis of these data has also demonstrated the ability of PRO to detect horizontally oriented frozen-phase precipitation. To verify these observations, a global climatological comparison is performed using the CloudSat (94 GHz) radar as a reference for different heights and taking into account the radio occultation (limb-based) viewing geometry. A robust relationship (e.g., high correlation coefficient) is found between the polarimetric radio occultation observable differential phase shift (ΔΦ) and the integrated ice water content (IWC) along the rays, globally, and for heights above freezing level. PAZ observations capture the major precipitation features and the signatures of the Intertropical Convergence Zone. The correlation coefficients maximize for tropical oceans, for a range of heights between 5 and 12 km. The ratios between ΔΦ and along-ray integrated IWC mean that climatologies are found to be within the range 0.03–0.09 mm kg−1 m2, although uncertainty due to the IWC retrieval algorithm must be noted. Further evaluation of the ratios with single-particle forward-scattering simulations indicate that the scattering by frozen hydrometeors with a combination of effective densities, axis ratios, and tilt angle distribution yield results that agree well with the observations. Overall, the global climatological results obtained in this study show the presence of horizontally oriented particles across the whole globe and for a wide range of height layers.This research has been supported by the Agència de Gestió d'Ajuts Universitaris i de Recerca (grant no. 2019 BP 00110), the H2020 Marie Skłodowska-Curie Actions (grant no. 801370), and the Agencia Estatal de Investigación (grant nos. RTI2018-099008-B-C22, PID2021-126436OB, and MCIN/AEI/10.13039/501100011033). This work has also been partially supported by the program Unidad de Excelencia María de Maeztu (grant no. CEX2020-001058-M).We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer reviewe

Variational retrievals of high winds using uncalibrated CyGNSS observables

This study presents a new retrieval approach for obtaining wind speeds from CyGNSS level-1 observables. Unlike other existing approaches, (1) this one is a variational technique that is based on a physical forward model, (2) it uses uncalibrated bin raw counts observables, (3) the geophysical information content comes from only one pixel of the broader delay-Doppler map, finest achievable resolution in level-1 products over the sea, and (4) calibrates them against track-wise polynomial adjustments to a background numerical weather prediction model. Through comparisons with the background model, other spaceborne sensors (SMAP, SMOS, ASCAT-A/B), and CyGNSS wind retrievals by other organizations, the study shows that this approach has skills to infer wind speeds, including hurricane force winds. For example, the Pearson’s correlation coefficient between these CyGNSS retrievals and ERA5 is 0.884, 0.832 with NOAA CyGNSS results, and 0.831 with respect to SMAP co-located measurements. Furthermore, the variational retrieval algorithm is a simplified version of the more general equations that are used in data assimilation, and the calibration scheme could also be integrated in the assimilation process. Therefore, this approach is also a good tool for analyzing the potential performance of ingesting uncalibrated level-1 single-pixel observables into NWP.This research was funded by the Spanish Ministry of Science, Innovation and Universities grant number RTI2018-099008-B-C22/AEI/10.13039/501100011033/FEDER, EU, with computing facilities covered by grant EQC2019-005664-P. Yang NAN appreciated the financial support from China Scholarship Council (CSC) by a State Scholarship Fund (No.201906270212). This investigation is done in the frame of the NASA CyGNSS Extended Science Team and it represents a contribution to CSIC Thematic Interdisciplinary Platform PTI TELEDETECT. Part of this study is a contribution to ESA C.N.4000132954/20/I-NB

What does artificial intelligence tell us about the geophysical information content in GNSS polarimetric RO?

Trabajo presentado al 7th International Workshop on Occultations for Probing Atmosphere and Climate y al 9th Workshop of the International Radio Occultation Working Group (OPAC-IROWG), celebrados del 8 al 14 de septiembre de 2022 en Leibnitz, Austria.Machine learning algorithms build a model based on sample data, capable to make predictions without being explicitly programmed to do so. In the field of GNSS polarimetric RO (GNSS PRO), these algorithms can be used to find patterns and relationships between different variables, even before any physical model is foreseen. In this study, we present a set of investigations done with PAZ GNSS PRO observables (the vertical profile of polarimetric phase shift, DeltaPhi(h)) and their thermodynamic profiles (T(h), p(h), q(h)), sometimes complemented with ancillary (non-RO) information such as the average rain rate or infrared brightness temperatures. Both forward and backward relationships are studied: Can the thermodynamic profiles predict the polarimetric phase shift vertical profile? Are the polarimetric observables sufficient for predicting the rain rate? When is it necessary to complement with ancillary data? Which ancillary data provides useful information? In which range of altitudes these relationships and patterns are stronger? The answer to these questions might help (1) understanding the GNSS PRO observables; (2) designing optimal forward/backward models; and (3) assessing uses and applications of the GNSS PRO. Different classifiers and regressors are tested, playing with different subsets of variables. For example, it is found that presence of rain (> 1 mm) can be classified with 92% sensitivity and 85% total accuracy, or that vertical profiles of T,p,q can predict the vertical profiles of GNSS PRO polarimetric phase shift between 6 and 14 km altitude with accuracies between 85% and 90%.The ROHP-PAZ project is part of the Grant RTI2018-099008-B-C22 funded by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” of the “European Union”. Part of the investigations are done under the EUMETSAT ROM SAF CDOP4. This work was partially supported by the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. Part of this research has received funding from the postdoctoral fellowships program Beatriu de Pinós, funded by the Secretary of Universities and Research (Government of Catalonia) and by the Horizon 2020 program of research and innovation of the European Union under the Marie Sklodowska-Curie grant agreement No 801370.Peer reviewe

The Potential for Discriminating Microphysical Processes in Numerical Weather Forecasts Using Airborne Polarimetric Radio Occultations

Accurate representation of cloud microphysical processes in numerical weather and climate models has proven challenging, in part because of the highly specialized instrumentation required for diagnosing errors in simulated distributions of hydrometeors. Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) is a promising new technique that is sensitive to hydrometeors and has the potential to help address these challenges by providing microphysical observations that are relevant to larger spatial scales, especially if this type of observing system can be implemented on aircraft that can target heavy precipitation events. Two numerical experiments were run using a mesoscale model configured with two different microphysical parameterization schemes for a very intense atmospheric river (AR) event that was sampled by aircraft deploying dropsondes just before it made landfall in California, during the CalWater 2015 field campaign. The numerical experiments were used to simulate profiles of airborne polarimetric differential phase delay observations. The differential phase delay due to liquid water hydrometeors below the freezing level differed significantly in the two experiments, as well as the height of the maximum differential phase delay due to all hydrometeors combined. These results suggest that PRO observations from aircraft have the potential to contribute to validating and improving the representation of microphysical processes in numerical weather forecasts once these observations become available