Integrated Water Vapor Research Articles

Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe

Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe

A Performance Baseline for the Representation of Clouds and Humidity in Cloud‐Resolving ICON‐LEM Simulations in the Arctic

AbstractIn the context of Arctic amplification many of the feedback mechanisms, decreasing or enhancing the warming, involve clouds and water vapor. Currently, there is a gap in understanding the role of clouds which leads to uncertainties in climate simulations. Modeling frameworks such as the ICOsahedral Non‐hydrostatic model (ICON) are used to understand the Arctic atmospheric processes as well as predict future changes. In this study, we challenge ICON in the large‐eddy setup (ICON‐LEM) by performing cloud‐resolving simulations over parts of Svalbard, including Ny‐Ålesund. We ran daily simulations over 5 months and analyzed the column above Ny‐Ålesund. The local supersite's observations enabled us to create a baseline for the model performance focusing on the representation of liquid water and water vapor. We narrow in on possibilities to improve the cloud microphysical representation based on statistical evaluations, not just single cases. We found an astonishing agreement between most of the analyzed variables. For instance, the model integrated water vapor showed only a low bias of 0.21 kg m−2. The number of cloudy days is slightly higher in the model (+4%). Further, we found that the model produces an unrealistically high number of pure ice clouds. Small to medium precipitation events are similar in amount and time but the number of strong precipitation events is underestimated. Further results are discussed and show that ICON‐LEM is a useful tool to study the Arctic. With this thorough analysis, we highlight the value of local cloud‐resolving simulations to understand changes in the Arctic atmosphere.

Fog in Sofia 2010–2019: Objective Circulation Classification and Fog Indices

Low visibility caused by fog events can lead to disruption of every type of public transportation, and even loss of life. The focus of this study is the synoptic conditions associated with fog formation. The data used in this study was collected over the course of ten years (2010–2019) in Sofia, Bulgaria. The forecast skills of the Fog Stability Index (FSI) and the local Sofia Stability Index (SSI), as well as the relation between the Integrated Water Vapor (IWV) and fog from the Global Navigation Satellite System (GNSS), were tested. Both fog indices are used for fog nowcasting as their lead times are short and unclear. The Jenkinson–Collison Type method was used for extracting the predominant synoptic-scale pressure systems which provide suitable weather conditions for fog formation. Surface observations from two synoptic stations were used to calculate and evaluate the performance of the two fog indices and of the ground-based GNSS receiver for the IWV. The forecast skills provided by Probability of Detection (POD) and False Alarm Ratio (FAR), for both fog and no-fog periods, were obtained by discriminant analysis. Additionally, several weather parameters, such as surface wind speed, relative humidity and IWV, were added in order to improve the results of the local index (SSI). This led to a 77.9% hit rate. The cyclonic system influence and zonal flows from the west and the southwest are both responsible for a number of fog cases that are comparable to those associated with the anticyclonic system. The IWV was not found to improve the forecast skill of the fog indices. However, it was found that its values had a larger spread during no-fog periods in comparison to fog periods.

An innovative approach to predict atmospheric rivers: Exploring convolutional autoencoder

Atmospheric rivers (ARs) are filamentary regions of high moisture content in mid-latitude regions through which most of the poleward moisture is being transported. These ARs carry a huge amount of water in the form of vapor and thus landfalling of these ARs may bring either a beneficial supply of water or may create hazardous flood situations and thus cause damage to life and property. These regions have been statistically characterized as intense integrated water vapor transport (IVT) regions in the troposphere based on various thresholds of magnitude, direction, and geometry. To enhance the knowledge of data-driven methods for modelling nonlinear atmospheric dynamics associated with ARs, a first ever study with data-driven methodology incorporating a Deep Learning architecture, Autoencoder has been proposed. While training the proposed model, the Adam optimizer was used to reduce the mean squared error loss and was optimized using the Rectified Linear Unit (ReLU) and Sigmoid activation functions. The prediction results of the availability of ARs at next frames by the Autoencoder were assessed by popularly used performance evaluation metrics structural similarity index metrics (SSMI), mean squared error (MSE), root mean squared error (RMSE), and peak signal to noise ratio (PSNR). We have got comparatively higher scores (average) of SSIM (0.739) and PSNR (64.422) and lower scores (average) of RMSE (0.155) and MSE (0.0247) for AR prediction from our model which signifies the accuracy of the proposed Autoencoder in capturing AR dynamics. The findings of the study could be useful in giving important insights to incorporate Deep Learning models for forecasting ARs at significant lead time and consequently reducing the risk and increasing the resilience of AR flood prone regions.

Synoptic Drivers of Atmospheric River Induced Precipitation Near Dronning Maud Land, Antarctica

AbstractAtmospheric rivers (ARs) that reach the Antarctic Ice Sheet (AIS) transport anomalous moisture from lower latitudes and can impact the AIS via extreme precipitation and increased downward longwave radiation. ARs contribute significantly to the interannual variability of precipitation over the AIS and thus are likely to play a key role in understanding future changes in the surface mass balance of the AIS. Dronning Maud Land (DML) is one of four maxima in AR frequency over coastal East Antarctica, with AR precipitation explaining 77% of the interannual variability in precipitation for this region. We employ a 16‐node self‐organizing map (SOM) trained with MERRA‐2 sea‐level pressure anomalies to identify synoptic‐scale environments associated with landfalling ARs in and around DML. Node composites of atmospheric variables reveal common drivers of precipitation associated with ARs reaching DML including anomalous high‐low surface pressure couplets, anomalously high integrated water vapor, and coastal barrier jets. Using a quasi‐geostrophic framework, we find that upward vertical motion associated with the occlusion process of attendant cyclones dominates atmospheric lift in AR environments. We further identify mechanisms that explain the variability in AR precipitation intensity across nodes, such as the lift associated with the occlusion process of attendant cyclones and the spatial coincidence of ascent induced by the occlusion process and frontogenesis. The latter suggests that ARs making landfall during the mature phase of cyclogenesis result in higher precipitation intensity compared to landfalling ARs that occur during the occluded phase.

Large-scale background and role of quasi-biweekly moisture transport in the extreme Yangtze River rainfall in summer 2020

A severe flooding hit southern China along the Yangtze River in summer 2020. The floods were induced by extreme rains, and the associated dynamic and thermodynamic conditions are investigated using daily gridded rainfall data of China and NCEP-NCAR reanalysis. It is found that the June–July rainfall over the Yangtze River Basin (YRB) experienced pronounced subseasonal variation in 2020, dominated by a quasi-biweekly oscillation (QBWO) mode. The southwestward-moving anomalous QBWO circulation was essentially the fluctuation of cold air mass related to the tropospheric polar vortex or trough-ridge activities over the mid-high latitude Eurasian in boreal summer. The southwestward-transport of cold air mass from mid-high latitudes and the northeastward-transport of warm and moist air by the strong anomalous anticyclone over the western North Pacific provided important large-scale circulation support for the extreme rainfall in the YRB. The analysis of streamfunction of water vapor flux demonstrates that a large amount of water vapor eastward zonal transport from the Bay of Bengal and Indo-China and northward transport from the South China Sea provided the background moisture supply for the rainfall. The quasi-biweekly anomalies of potential and divergent component of vertically integrated water vapor flux played an important role in maintaining the subseasonal variability of rainfall in June–July of 2020. The diagnosis of moisture tendency budget shows that the enhanced moisture closely related to the quasi-biweekly fluctuated rainfall was primarily attributed to the moisture convergence. Further analysis of time-scale decomposition in the moisture convergence indicates that the convergence of background mean specific humidity by the QBWO flow and convergence of QBWO specific humidity by the mean flow played dominant roles in contributing to the positive moisture tendency. In combination with adiabatic ascent over the YRB induced by the warm temperature advection, the boundary layer moisture convergence strengthened the upward transport of water vapor to moisten the middle troposphere, favoring the persistence of rainfall during June–July. The vertical moisture transport associated with boundary layer convergence was of critical importance in causing low-level tropospheric moistening. By comparison, the horizontal moisture advection played a secondary important role in the quasi-biweekly oscillation of rainfall in June–July 2020.

Characterisations of Europe's integrated water vapour and assessments of atmospheric reanalyses using more than 2 decades of ground-based GPS

Abstract. The ground-based Global Positioning System (GPS) has been used extensively to retrieve integrated water vapour (IWV) and has been adopted as a unique tool for the assessments of atmospheric reanalyses. In this study, we investigated the multi-temporal-scale variabilities and trends of IWV over Europe by using IWV time series from 108 GPS stations for more than 2 decades (1994–2018). We then adopted the GPS IWV as a reference to assess six commonly used atmospheric reanalyses, namely the Climate Forecast System Reanalysis (CFSR); ERA5; ERA-Interim; the Japanese 55-year Reanalysis (JRA-55); the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2); and NCEP-DOE AMIP-II Reanalysis (NCEP-2). The GPS results show that the peaks of the diurnal harmonics are within 15:00–21:00 in local solar time at 90 % of the stations. The diurnal amplitudes are 0–1.2 kg m−2 (0 %–8 % of the daily mean IWV), and they are found to be related to seasons and locations with different mechanisms, such as solar heating, land–sea breeze, and orographic circulation. However, mismatches in the diurnal cycle of ERA5 IWV between 09:00 and 10:00 UTC as well as between 21:00 and 22:00 UTC were found and evaluated for the first time, and they can be attributed to the edge effect in each ERA5 assimilation cycle. The average ERA5 IWV shifts are −0.08 and 0.19 kg m−2 at the two epochs, and they were found to be more significant in summer and in the Alps and in Eastern and central Europe in some cases. Nevertheless, ERA5 outperforms the other reanalyses in reproducing diurnal IWV anomalies at all the 1-, 3-, and 6-hourly temporal resolutions. ERA5 is also superior to the others in modelling the annual cycle and linear trend of IWV. For instance, the IWV trend differences between ERA5 and GPS are quite small, with a mean value and a standard deviation of 0.01 % per decade and 0.97 % per decade, respectively. However, due to significant discrepancies with respect to GPS, CFSR and NCEP-2 are not recommended for the analysis of IWV trends over southern Europe and the whole of Europe, respectively.

Towards Space Deployment of the NDSA Concept for Tropospheric Water Vapour Measurements

A novel measurement concept specifically tuned to monitoring tropospheric water vapour’s vertical distribution has been demonstrated on a theoretical basis and is currently under development for space deployment. The NDSA (Normalised Differential Spectral Attenuation) technique derives the integrated water vapour (IWV) along the radio link between a transmitter and a receiver carried by two LEO satellites, using the linear correlation between the IWV and a parameter called spectral sensitivity. This is the normalised incremental ratio of the spectral attenuation at two frequencies in the Ku and K bands, with the slope of the water vapour absorption line at 22.235 GHz. Vertical profiles of WV can be retrieved by inverting a set of IWV measurements acquired in limb geometry at different tangent altitudes. This paper provides a comprehensive insight into the NDSA approach for sounding lower tropospheric WV, from the theoretical investigations in previous ESA studies, to the first experimental developments and testing, and to the latest advancements achieved with the SATCROSS project of the Italian Space Agency. The focus is on the new results from SATCROSS activities; primarily, on the upgrading of the instrument prototype, with improved performance in terms of its power stability and the time resolution of the measurements. Special emphasis is also placed on discussing tomographic inversion methods capable of retrieving tropospheric WV content from IWV measurements, i.e., the least squares and the external reconstruction approaches, showing results with different spatial features when applied to a given atmospheric scenario. The ultimate goal of deploying the NDSA measurement technique from space is thoroughly examined and conclusions are drawn after presenting the results of an Observing System Simulation Experiment conducted to assess the impact of NDSA data assimilation on environmental model simulations.

Observation of an Extremely Dry Atmospheric Air Column above Bern

The water vapour column density or vertically integrated water vapour (IWV) ranges from about 8 mm in winter to about 25 mm in summer in Bern, Switzerland. However, there can be day episodes when IWV drops to 2 mm or even less so that the atmosphere is extremely dry. We selected an event in February 2021 when the tropospheric water radiometer TROWARA measured a mean IWV value of about 1.5 ± 0.2 mm for a time interval of about one day in Bern. The ECMWF reanalysis ERA5 indicated a slightly higher IWV value of about 2.2 ± 0.4 mm where the uncertainty is the standard deviation of IWV during the time of IWV depression. The ERA5 profiles of relative humidity and specific humidity during this episode are reduced by 50% and more compared to the monthly mean profiles. On a global map, it can be seen that Bern is within a mesoscale dry region on that day with descending wind. Back trajectory analysis gives the result that the dry air masses in Bern came from the North and the trajectories are descending in altitude so that dry air from the mid troposphere came into the lower troposphere. These descending air masses from the North explain the minimum of IWV observed in Bern on 13–14 February 2021. The surface climate in Switzerland was dominated by a cold wave at that time. At the same time, severe cold waves occurred in Greece and Northern America.

Boundary-dependent urban impacts on timing, pattern, and magnitude of heavy rainfall in Istanbul

An emphasis on whether the modeled response of rainfall to urban signature is consistent across different boundary forcings is lacking. Here, using the Weather Research and Forecasting (WRF) model, we compare urban impacts in the boundary-dependent simulations of a record-breaking rainfall event in Istanbul, designing urban and nourban land cover scenarios. The data used for the boundaries are ECMWF Reanalysis v5 (ERA5) and NCEP Final Analysis (FNL), and we perform simulations with variable boundary and parameterization configurations and use their ensemble mean in our analysis. Our results highlight that some aspects of the urban impact on rainfall produced by different boundary conditions resemble each other. First, hourly rainfall intensifies over and upwind part of the urban domain independent of the employed boundary forcing. Especially within the urban borders, the boost in rainfall amounts during the investigation period totals 6% and 21% for the simulations forced with ERA5 and FNL, respectively. In addition, our simulations exhibit urban signals not only in the rainfall amounts but also in their timing and concentration. This signal in timing is evident by the urban rainfall system that moves slightly ahead of its nourban counterpart at each analyzed hour. We, in particular, observe a spatially less concentrated rainfall pattern as the system positions over the urban area and point out a potential urbanization-topography interaction. We further support these findings with cross-section and integrated water vapor transport analyses. By contrast, the main dissimilarities between the simulations forced with different boundary data include rainfall changes downwind of the city center. This behavior is commensurate with the increase in the temperature and sensible-heat flux values that are not similar in strength in the simulations forced with ERA5 and FNL. These findings suggest that different boundary data can promote similar urban impacts only to some extent, underlining the importance of considering their regional performance before using them in modeling studies.

An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020

Abstract. We developed a high-quality global integrated water vapour (IWV) dataset from 12 552 ground-based global positioning system (GPS) stations in 2020. It consists of 5 min GPS IWV estimates with a total number of 1 093 591 492 data points. The completeness rates of the IWV estimates are higher than 95 % at 7253 (58 %) stations. The dataset is an enhanced version of the existing operational GPS IWV dataset provided by the Nevada Geodetic Laboratory (NGL). The enhancement is reached by employing accurate meteorological information from the fifth generation of European ReAnalysis (ERA5) for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. A dedicated data screening algorithm is also implemented. The GPS IWV dataset has a good agreement with in situ radiosonde observations at 182 collocated stations worldwide. The IWV biases are within ±3.0 kg m−2 with a mean absolute bias (MAB) value of 0.69 kg m−2. The standard deviations (SD) of IWV differences are no larger than 3.4 kg m−2. In addition, the enhanced IWV product shows substantial improvements compared to NGL's operational version, and it is thus recommended for high-accuracy applications, such as research of extreme weather events and diurnal variations of IWV and intercomparisons with other IWV retrieval techniques. Taking the radiosonde-derived IWV as reference, the MAB and SD of IWV differences are reduced by 19.5 % and 6.2 % on average, respectively. The number of unrealistic negative GPS IWV estimates is also substantially reduced by 92.4 % owing to the accurate zenith hydrostatic delay (ZHD) derived by ERA5. The dataset is available at https://doi.org/10.5281/zenodo.6973528 (Yuan et al., 2022).

The Structure of extreme precipitation and flood events over India in association with integrated water vapor transport from 1980 to 2015

The Structure of extreme precipitation and flood events over India in association with integrated water vapor transport from 1980 to 2015

The Hydrometeorology of Extreme Floods in the Lower Mississippi River

Abstract The Lower Mississippi River has experienced a cluster of extreme floods during the past two decades. The Bonnet Carré spillway, which is located on the Mississippi River immediately upstream of New Orleans, has been operated 15 times since its completion in 1931, with 7 occurrences after 2008. In this study, we examine rainfall and atmospheric water balance components associated with Lower Mississippi River flooding in 2008, 2011, and 2015–19. We focus on multiple time scales—1, 3, 7, and 14 days—reflecting contributions from individual storm systems and the aggregate contributions from a sequence of storm systems. Atmospheric water balance variables—integrated water vapor flux (IVT) and precipitable water—are central to our assessment of the storm environment for Lower Mississippi flood events. We find anomalously large IVT corridors accompany the critical periods of heavy rainfall and are organized in southwest–northeast orientation over the Mississippi domain. Atmospheric rivers play an important role as agents of extremes in water vapor flux and rainfall. We conduct climatological analyses of IVT and precipitable water extremes across the four time scales using 40 years of North American Regional Reanalysis (NARR) fields from 1979 to 2018. We find significant increasing trends in both variables at all time scales. Increases in IVT especially cover large regions of the Mississippi domain. The findings point to increased vulnerability faced by the Mississippi flood control system in the current and future climate.

On the Impact of GPS Multipath Correction Maps and Post-Fit Residuals on Slant Wet Delays for Tracking Severe Weather Events

Climate change has increased the frequency and intensity of weather events with heavy precipitation, making communities worldwide more vulnerable to flash flooding. As a result, accurate fore- and nowcasting of impending excessive rainfall is crucial for warning and mitigating these hydro-meteorological hazards. The measurement of integrated water vapour along slant paths is made possible by ground-based global positioning system (GPS) receiver networks, delivering three-dimensional (3D) water vapour distributions at low cost and in real-time. As a result, these data are an invaluable supplementary source of knowledge for monitoring storm events and determining their paths. However, it is generally known that multipath effects at GPS stations have an influence on incoming signals, particularly at low elevations. Although estimates of zenith total delay and horizontal linear gradients make up the majority of the GPS products for meteorology to date, these products are not sufficient for understanding the full 3D distribution of water vapour above a station. Direct utilization of slant delays can address this lack of azimuthal information, although, at low elevations it is more prone to multipath (MP) errors. This study uses the convective storm event that happened on 27 July 2017 over Bulgaria, Greece, and Turkey, which caused flash floods and severe damage, to examine the effects of multipath-corrected slant wet delay (SWD) estimations on monitoring severe weather events. First, we reconstructed the one-way SWD by adding GPS post-fit phase residuals, describing the anisotropic component of the SWD. Because MP errors in the GPS phase observables can considerably impact SWD from individual satellites, we used an averaging technique to build station-specific MP correction maps by stacking the post-fit phase residuals acquired from a precise point positioning (PPP) processing strategy. The stacking was created by spatially organizing the residuals into congruent cells with an optimal resolution in terms of the elevation and azimuth at the local horizon.This enables approximately equal numbers of post-fit residuals to be distributed across each congruent cell. Finally, using these MP correction maps, the one-way SWD was improved for use in the weather event analysis. We found that the anisotropic component of the one-way SWD accounts for up to 20% of the overall SWD estimates. For a station that is strongly influenced by site-specific multipath error, the anisotropic component of SWD can reach up to 4.3 mm in equivalent precipitable water vapour. The result also showed that the spatio-temporal changes in the SWD as measured by GPS closely reflected the moisture field estimated from a numerical weather prediction model (ERA5 reanalysis) associated with this weather event.

A physical analysis of summertime North American heatwaves

This study examines the dominant heatwave variability over North America (NA), extracted from an empirical orthogonal function (EOF) analysis of summertime monthly warm extreme index anomalies over 1959–2021. The principal mode features a dipole structure with a large area of anomaly over northwestern NA and an anomaly of opposite sign over the southern U.S. The corresponding principal component is associated with a large-scale atmospheric wave train extending from the North Pacific to North America (NP-NA) and a northeastward injection of moisture from the subtropical western Pacific towards western NA, which are key factors in supporting the NA heatwave variability. The NP-NA wave train can be systematically reinforced and supported by synoptic-scale eddies, and may also be forced by an anomalous convection over the tropical-subtropical western Pacific. Surface radiation heating directly contributes to surface temperature anomalies and is dominated by anomalous downwelling shortwave and longwave radiations. In association with a positive phase of the heatwave variability, the NP-NA wave train brings an anticyclonic anomaly over northern NA, leading to anomalous descent, reduced total cloud cover and below-normal precipitation and surface relative humidity over northern NA. Over northwestern NA, the anomalous subsidence causes air to warm through compression. Reduced cloud cover results in increased downward shortwave radiation that is a key contributor to surface radiation heating. In addition, increase in vertically integrated water vapour through the moisture injection from the North Pacific collocates with tropospheric warming. The atmosphere has more water vapor holding capability and acts as a greenhouse gas to absorb longwave radiation, leading to increased downward longwave radiation that is the second major contributor to surface radiation heating. Processes with circulation and surface radiation anomalies of opposite signs will likewise lead to the negative heatwave variability.

A Back Propagation Neural Network-Based Calibration Approach for Sentinel-3 OLCI Near-Infrared Water Vapor Product

A back propagation neural network (BPNN)-based calibration method is developed to enhance the all-weather quality of official integrated water vapor (IWV) products from near-infrared (NIR) observations of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B satellites. The model utilizes multiple variables that link with the derivation of satellite NIR IWV products, including official OLCI NIR IWV, latitude, land quality and science flag, month, and solar zenith angle. The in situ IWV observations, collected from 100 Global Positioning System (GPS) stations, are employed as the desired IWV estimates. The model is evaluated using one-year water vapor data at additional 114 GPS stations and 97 radiosonde stations from June 1, 2019 to May 31, 2020 in China and its surrounding regions. The results show that the BPNN-based calibration model reduces the root-mean-square error (RMSE) of official OLCI NIR all-weather IWV products by 24.52% from 3.10 to 2.34 mm for Sentinel-3A and by 25.00% from 3.44 to 2.58 mm for Sentinel-3B, when compared with in situ GPS-observed reference IWV. When compared with in situ radiosonde-observed IWV, the RMSE reduces 21.01% from 4.57 to 3.61 mm and 20.81% from 5.19 to 4.11 mm for Sentinel-3A and Sentinel-3B, respectively.

An Indoor Microwave Radiometer for Measurement of Tropospheric Water

This paper presents the first detailed description of the innovative measurement set up of an indoor tropospheric microwave radiometer (TROWARA) that avoids water films on radome. We discuss the performance of a commercial outdoor microwave radiometer (HATPRO) for measuring tropospheric water parameters in Bern, Switzerland. The HATPRO is less than 20 meters from the TROWARA and has different instrument characteristics. Brightness temperatures measured by HATPRO are analyzed by comparing them with coincident measurements from TROWARA and radiative transfer simulations based on the ECMWF operational analysis data (denoted as RTSE). To find the source of brightness temperature bias, a gradient boosting decision tree is used to analyze the sensitivity of eight feature factors to bias. Data processing routines of the two radiometers use different algorithms to retrieve integrated water vapour (IWV) and integrated cloud liquid water (ILW), whereas the same physical algorithms based on the radiative transfer equation are applied to obtain the opacity and rain rate. Using 62 days of data with varied weather conditions, it was found that TROWARA brightness temperatures are in good agreement with RTSE. HATPRO brightness temperatures are significantly overestimated by about 5 K at 22 GHz, compared to TROWARA and RTSE. HATPRO brightness temperatures at 31 GHz agree well with TROWARA and RTSE (within about +/-1 K). The overestimated brightness temperatures in the K-band and the HATPRO retrieval algorithm lead to an overestimation of IWV and ILW by HATPRO. The opacities at 31 GHz match very well for TROWARA and HATPRO during no rain with a verified R2 of 0.96. However, liquid water floating or remaining water films on the radome of the outdoor HATPRO radiometer induce an overestimation of the rain rate. The physical reason for the overestimated 22 GHz brightness temperatures of the HATPRO is mainly the result of the combined effect of instrument calibration, the surrounding environment of the instrument, and the sun elevation angle. This can be a problem with the Generation 2 HATPRO radiometer and this problem was resolved in the Generation 5 HATPRO radiometer.

ВЗРЫВНЫЕ ЦИКЛОНЫ НАД СЕВЕРНОЙ ЧАСТЬЮ ТИХОГО ОКЕАНА: СТРУКТУРА И ПАРАМЕТРЫ АТМОСФЕРЫ ПО ПАССИВНЫМ И АКТИВНЫМ МИКРОВОЛНОВЫМ ИЗМЕРЕНИЯМ ИЗ КОСМОСА

The data of microwave satellite sensing of two bomb cyclones over the Pacific Ocean are considered. The distinctive features of the cyclones are dramatic pressure drops in the center (≥1 hPa/hour during a day), intense precipitation, and strong winds. The fields of cloud liquid water content, atmospheric integrated water vapor, and surface wind speed were retrieved, and their evolution was studied based on brightness temperatures measured by the AMSR2, GMI, and MTVZA-GY radiometers in the frequency range of 6-190 GHz in the cyclones observed on December 29, 2020-January 2, 2021 and January 25-28, 2022. The results obtained by microwave radiometers and scatterometers were interpreted using visible and infrared images, surface analysis maps, radiosonde data, etc. A correlation between the cloud top temperature and brightness temperature in the 176-190 GHz water vapor resonance region was found.

Precipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study "Convective Phenomena over Europe and the Mediterranean" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results.

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Abstract. Tropospheric water vapor is one of the most important trace gases of the Earth's climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)2. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021).