12 research outputs found

    Challenges in Diurnal Humidity Analysis from Cellular Microwave Links (CML) over Germany

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    Near-surface humidity is a crucial variable in many atmospheric processes, mostly related to the development of clouds and rain. The humidity at the height of a few tens of meters above ground level is highly influenced by surface characteristics. Measuring the near-surface humidity at high resolution, where most of the humidity’s sinks and sources are found, is a challenging task using classical tools. A novel approach for measuring the humidity is based on commercial microwave links (CML), which provide a large part of the cellular networks backhaul. This study focuses on employing humidity measurements with high spatio–temporal resolution in Germany. One major goal is to assess the errors and the environmental influence by comparing the CML-derived humidity to in-situ humidity measurements at weather stations and reanalysis (COSMO-Rea6) products. The method of retrieving humidity from the CML has been improved as compared to previous studies due to the use of new data at high temporal resolution. The results show a similar correlation on average and generally good agreement between both the CML retrievals and the reanalysis, and 32 weather stations near Siegen, West Germany (CML—0.84, Rea6—0.85). Higher correlations are observed for CML-derived humidity during the daytime (0.85), especially between 9–17 LT (0.87) and a maximum at 12 LT (0.90). During the night, the correlations are lower on average (0.81), with a minimum at 3 LT (0.74). These results are discussed with attention to the diurnal boundary layer (BL) height variation which has a strong effect on the BL humidity temporal profile. Further metrics including root mean square errors, mean values and standard deviations, were also calculated

    Weather regimes and analogues downscaling of seasonal precipitation for the 21st century: A case study over Israel

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    Global climate models provide only partial information on local-scale phenomenon, such as precipitation, primarily due to their coarse resolution. In this study, statistical downscaling algorithms, based on both weather regimes and past analogues, are operated for 18 Israeli rain gauges with an altitude ranging between −200 and ~1,000 m above sea level (ASL). To project seasonal precipitation over Israel and its hydrologic basins, the algorithms are applied to six Coupled Model Inter-comparison Project Phase 5 (CMIP5) models for the end of the 21st century, according to the RCP4.5 and RCP8.5 scenarios. The downscaled models can capture quite well the seasonal precipitation distribution, though with underestimation in winter and overestimation in spring. All models display a significant reduction of seasonal precipitation for the 21st century according to both scenarios. The winter reductions for the end of the century and the RCP8.5 scenario are found to be ~22 and ~37% according to the weather regimes and the analogues downscaling methods, respectively. Spring reductions are found to be ~10–20% larger than winter reductions. It is shown that the projected reduction results from a decrease in the frequency of the rain-bearing systems, as well as a decrease in the average daily precipitation intensity. The areas with the largest reductions in seasonal precipitation are found over the central mountains, the Mediterranean coastal area, and the Sea of Galilee hydrologic basins, which are the main fresh-water aquifers and reservoirs of Israel. The statistical downscaling methods applied in this study can be easily transferred to other regions where long-term data sets of observed precipitation are available. This study and others may serve as a basis for priority and policy setting toward better climate adaptation with associated uncertainties related to the methods used and nonstationary of the climate system

    On the Potential of Improving WRF Model Forecasts by Assimilation of High-Resolution GPS-Derived Water-Vapor Maps Augmented with METEOSAT-11 Data

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    Improving the accuracy of numerical weather predictions remains a challenging task. The absence of sufficiently detailed temporal and spatial real-time in-situ measurements poses a critical gap regarding the proper representation of atmospheric moisture fields, such as water vapor distribution, which are highly imperative for improving weather predictions accuracy. The estimated amount of the total vertically integrated water vapor (IWV), which can be derived from the attenuation of global positioning systems (GPS) signals, can support various atmospheric models at global, regional, and local scales. Currently, several existing atmospheric numerical models can estimate the IWV amount. However, they do not provide accurate results compared with in-situ measurements such as radiosondes. Here, we present a new strategy for assimilating 2D IWV regional maps estimations, derived from combined GPS and METEOSAT satellite imagery data, to improve Weather Research and Forecast (WRF) model predictions accuracy in Israel and surrounding areas. As opposed to previous studies, which used point measurements of IWV in the assimilation procedure, in the current study, we assimilate quasi-continuous 2D GPS IWV maps, combined with METEOSAT-11 data. Using the suggested methodology, our results indicate an improvement of more than 30% in the root mean square error (RMSE) of WRF forecasts after assimilation relative standalone WRF, when both are compared to the radiosonde measured data near the Mediterranean coast. Moreover, significant improvements along the Jordan Rift Valley and Dead Sea Valley areas are obtained when compared to 2D IWV regional maps estimations. Improvements in these areas suggest the impact of the assimilated high resolution IWV maps, with initialization times which coincide with the Mediterranean Sea Breeze propagation from the coastline to highland stations, as the distance to the Mediterranean Sea shore, along with other features, dictates its arrival times

    Challenges in Diurnal Humidity Analysis from Cellular Microwave Links (CML) over Germany

    No full text
    Near-surface humidity is a crucial variable in many atmospheric processes, mostly related to the development of clouds and rain. The humidity at the height of a few tens of meters above ground level is highly influenced by surface characteristics. Measuring the near-surface humidity at high resolution, where most of the humidity’s sinks and sources are found, is a challenging task using classical tools. A novel approach for measuring the humidity is based on commercial microwave links (CML), which provide a large part of the cellular networks backhaul. This study focuses on employing humidity measurements with high spatio–temporal resolution in Germany. One major goal is to assess the errors and the environmental influence by comparing the CML-derived humidity to in-situ humidity measurements at weather stations and reanalysis (COSMO-Rea6) products. The method of retrieving humidity from the CML has been improved as compared to previous studies due to the use of new data at high temporal resolution. The results show a similar correlation on average and generally good agreement between both the CML retrievals and the reanalysis, and 32 weather stations near Siegen, West Germany (CML—0.84, Rea6—0.85). Higher correlations are observed for CML-derived humidity during the daytime (0.85), especially between 9–17 LT (0.87) and a maximum at 12 LT (0.90). During the night, the correlations are lower on average (0.81), with a minimum at 3 LT (0.74). These results are discussed with attention to the diurnal boundary layer (BL) height variation which has a strong effect on the BL humidity temporal profile. Further metrics including root mean square errors, mean values and standard deviations, were also calculated

    Is it foehn or sea breeze? Eulerian and Lagrangian analysis of the flow in the Jordan Valley

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    For more than one century, the penetration of the Mediterranean Sea Breeze into the Jordan Valley has been studied. At times, the associated downslope westerlies in the Dead Sea area exhibit foehn characteristics, leading to a warming and drying upon arrival and therefore contradicting the typical characteristics of a sea breeze. In this paper, a particular summer day (16 August 2014) is analyzed using a kilometre-scale model simulation. For the first time, the Mediterranean Sea Breeze penetration is investigated with Lagrangian backward trajectories and its characterization is extended to the entire Jordan Valley. Along the western slopes of the valley, two well-distinguishable layers are detected in the afternoon: a moist and cold sea breeze layer, and a dry and warm foehn layer above. While the air parcels of both layers cover similar pathways in the hours before reaching the Jordan Valley, they originate from strikingly different altitudes. For this reason, significant differences in their temperature evolution and humidity content are detected. In the evening, the Mediterranean Sea Breeze layer is eroded, enabling the foehn layer to reach the surface. The arrival of foehn retards the afternoon cooling and leads to a decrease in relative humidity. This unique imprint of foehn breakthrough is confirmed by in situ measurements. Therefore, the two-layered flow pattern is found to be a key element in understanding the mesoscale wind system and the surface signals in the Dead Sea area. The foehn layer is spatially confined to the Dead Sea area since the locally elevated upstream Judean Mountains cause a major disturbance of the westerly flow. This work extends the knowledge on summer mesoscale flows in the Jordan Valley and on different types of foehn-breeze interactions

    Fog Measurements with IR Whole Sky Imager and Doppler Lidar, Combined with In Situ Instruments

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    This study describes comprehensive measurements performed for four consecutive nights during a regional-scale radiation fog event in Israel’s central and southern areas in January 2021. Our data included both in situ measurements of droplets size distribution, visibility range, and meteorological parameters and remote sensing with a thermal IR Whole Sky Imager and a Doppler Lidar. This work is the first extensive field campaign aimed to characterize fog properties in Israel and is a pioneer endeavor that encompasses simultaneous remote sensing measurements and analysis of a fog event with a thermal IR Whole Sky Imager. Radiation fog, as monitored by the sensor’s field of view, reveals three distinctive properties that make it possible to identify it. First, it exhibits an azimuthal symmetrical shape during the buildup phase. Second, the zenith brightness temperature is very close to the ground-level air temperature. Lastly, the rate of increase in cloud cover up to a completely overcast sky is very fast. Additionally, we validated the use of a Doppler Lidar as a tool for monitoring fog by proving that the measured backscatter-attenuation vertical profile agrees with the calculation of the Lidar equation fed with data measured by in situ instruments. It is shown that fog can be monitored by those two, off-the-shelf-stand-off-sensing technologies that were not originally designed for fog purposes. It enables the monitoring of fog properties such as type, evolution with time and vertical depth, and opens the path for future works of studying the different types of fog events

    Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model

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    Heavy precipitation events (HPEs) can lead to natural hazards (e.g. floods and debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological, and societal effects of HPEs. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with these events. Information from rain gauges is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterised by the highest rain intensities; however, for short durations, the highest rain intensities were found for the inland desert. During the rainy season, the rain field's centre of mass progresses from the sea inland. Rainfall during HPEs is highly localised in both space (less than a 10 km decorrelation distance) and time (less than 5 min). WRF model simulations were accurate in generating the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors

    Profiling the Planetary Boundary Layer Wind with a StreamLine XR Doppler LiDAR: Comparison to In-Situ Observations and WRF Model Simulations

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    Halo-Photonics StreamLine XR Doppler LiDAR measurements are performed using several scan configurations (Velocity Azimuth Display-VAD and Doppler Beam Swing-DBS) and elevation angles of 60° and 80°. The measurements are compared to wind observations conducted by various in situ instruments (tethered balloon, meteorological mast, and radiosondes). Good agreement is obtained, with R2 over 0.90 for wind speed and a standard error ≤ 18.6° for wind direction. The best performance was attained for lower elevation scans (60°), which is consistent with the higher spatial horizontal homogeneity exhibited by lower angle scans. VAD and DBS scans performed almost equally well with slight advantage for VAD in higher altitudes and for DBS for lower altitudes. The boundary layer structure along a diurnal cycle is analyzed by utilizing retrieved backscatter data and wind measurements in conjunction with Weather Research and Forecast (WRF) simulations. The presence of multiple inversions which allow the coexistence of different layers within the studied profile is also verified using data acquired by several radiosondes. Synergic use of LiDAR data with WRF simulations for low SNR regions is demonstrated

    Reduced Rainfall in Future Heavy Precipitation Events Related to Contracted Rain Area Despite Increased Rain Rate

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    Heavy precipitation events (HPEs) can lead to deadly and costly natural disasters and are critical to the hydrological budget in regions where rainfall variability is high and water resources depend on individual storms. Thus, reliable projections of such events in the future are needed. To provide high-resolution projections under the RCP8.5 scenario for HPEs at the end of the 21st century, and to understand the changes in sub-hourly to daily rainfall patterns, weather research and forecasting (WRF) model simulations of 41 historic HPEs in the eastern Mediterranean are compared with "pseudo global warming" simulations of the same events. This paper presents the changes in rainfall patterns in future storms, decomposed into storms' mean conditional rain rate, duration, and area. A major decrease in rainfall accumulation (-30% averaged across events) is found throughout future HPEs. This decrease results from a substantial reduction of the rain area of storms (-40%) and occurs despite an increase in the mean conditional rain intensity (+15%). The duration of the HPEs decreases (-9%) in future simulations. Regionally maximal 10-min rain rates increase (+22%), whereas over most of the region, long-duration rain rates decrease. The consistency of results across events, driven by varying synoptic conditions, suggests that these changes have low sensitivity to the specific synoptic evolution during the events. Future HPEs in the eastern Mediterranean will therefore likely be drier and more spatiotemporally concentrated, with substantial implications on hydrological outcomes of storms.Plain Language Summary Heavy precipitation events are large storms that can recharge freshwater reservoirs, but can also lead to hazardous outcomes such as flash floods. Therefore, understanding the impacts of climate change on such storms is critical. Here, a weather model similar to those used in weather forecasts is used to simulate heavy precipitation events in the eastern Mediterranean. A large collection of storms is simulated in pairs: (a) historic storms, selected for their high impact, and (b) the same storms placed in a global warming scenario projected for the end of the 21st century. Using these simulations we ask how present-day storms would look like were they to occur at the warmer end of the 21st century. The future storms are found to produce much less rainfall compared to their historic counterparts. This decrease in rainfall is attributed mainly to the reduction in the area covered by storms' rainfall, and happens despite increasing rainfall intensities. These results suggest that the region will be drier in the future with larger dry areas during storms; however, over short durations, it would rain more intensely over contracted areas-increasing local hazards associated with heavy precipitation events
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