Gridded rainfall maps retrieved from commercial microwave link (CML) data from Sri Lanka

Gridded dataset of rainfall intensities (mm/h) covering Sri Lanka over the period 12 September 2019 through 31 December 2019. Commercial microwave link (CML) data were used to estimate path-average rainfall between telephone towers. These were interpolated to 15-min rainfall maps on a 0.02 degree grid (approximately 4 km)

Gridded rainfall maps retrieved from commercial microwave link (CML) data from Sri Lanka

Gridded dataset of rainfall intensities (mm/h) covering Sri Lanka over the period 12 September 2019 through 31 December 2019. Commercial microwave link (CML) data were used to estimate path-average rainfall between telephone towers. These were interpolated to 15-min rainfall maps on a 0.02 degree grid (approximately 4 km)

Commercial microwave link data for rainfall monitoring

Dataset of commercial microwave link (CML) data, which can be used to estimate path-average rainfall between telephone towers. Contains microwave frequency, end date & time of reading, minimum & maximum received power, path length, coordinates, and link identifier. For a network of on average ~2500 links covering the Netherlands having a temporal resolution of 15 min. The dataset, which consists of two files, can be used with the open-source R package RAINLINK (https://github.com/overeem11/RAINLINK) to estimate path-averaged rainfall and to make rainfall maps. Data have been used in the mentioned papers under "link to publication", but these use either a subset of the dataset or also other data. A manuscript which will describe the exact characteristics of this dataset is in preparation

Forecasted freezing level height from the numerical weather prediction model HARMONIE-AROME

Dataset of forecasted freezing level height from the numerical weather prediction model HARMONIE-AROME cycle 38, as of 3 April 2018 cycle 40. HARMONIE-AROME is a non-hydrostatic regional numerical weather prediction model used operationally at the Royal Netherlands Meteorological Institute (KNMI) and various other European weather centers. At KNMI, the HARMONIE-AROME model operates at 2.5 times 2.5 km horizontal resolution and 65 vertical levels, and 48-hour long forecasts are initiated every three hours. A subset of the full output was archived on model-levels for a 300 times 300 cell domain covering part of the full 800 times 800 cell simulation domain. For each cell and simulation output time-step, the freezing level height was determined by scanning from the top of the atmosphere downwards to the first level for which the temperature reached 273.15K. The subset covers the Netherlands and surroundings, coinciding with the coverage of the two KNMI ground-based weather radars. This dataset has been employed for a study on rainfall-induced attenuation correction for two dual-pol C-band radars in the Netherlands, for which a paper is in preparation. For this, HARMONIE data which would have been available in real-time for coupling with real-time 5-min radar data were obtained, resulting in the selection of the forecasts with +2, +3, +4 or +5 h lead time, being available every 3 h (32 files per day). The HARMONIE data allow for distinguishing between rain and other types of precipitation. This dataset may also be useful for other (radar) applications

F4. Country-Wide Rainfall Maps from a Commercial Cellular Telephone Network

Accurate rainfall observations with high spatial and temporal resolutions are needed for many applications, for instance, as input for hydrological models. Weather radars often provide data with sufficient spatial and temporal resolution, but usually need adjustment. In general, only few rain gauge measurements are available to adjust the radar data in real-time, for example, each hour. Physically based methods, such as a Vertical Profile of Reflectivity (VPR) correction, can be valuable and hold a promise. However, they are not always performed in real-time yet and can be difficult to implement. The estimation of rainfall using microwave links from commercial cellular telephone networks is a new and potentially valuable source of information. Such networks cover large parts of the land surface of the earth and have a high density. The data produced by the microwave links in such networks is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the pathintegrated attenuation. A recent study of us shows that urban rainfall can be estimated from commercial microwave link data for the Rotterdam region, a densely-populated delta city in the Netherlands. A data set from a commercial microwave link network over the Netherlands is analyzed, containing approximately 1500 links covering the land surface of the Netherlands (35500 km2). This data set consists of several days with extreme rainfall in June, July and August 2011. A methodology is presented to derive rainfall intensities and daily rainfall depths from the microwave link data, which have a temporal resolution of 15 min. The magnitude and dynamics of these rainfall intensities is compared with those obtained from weather radar. Rainfall maps are derived from the microwave link data and are verified against rainfall maps based on gaugeadjusted weather radar data. Although much more work needs to be done, the first results look promising. Since cellular telephone networks are used worldwide, data from such networks could also become a valuable source of rainfall information in countries which do not have continuously operating weather radars, and no or few rain gauges. Apart from rainfall maps which are solely based on microwave link data, a preliminary analysis will be presented to assess whether commercial microwave link data can be used to adjust radar rainfall accumulations

Full-year evaluation of nonmeteorological Echo removal with dual-polarization fuzzy logic for two C-band radars in a temperate climate

The Royal Netherlands Meteorological Institute (KNMI) operates two dual-polarization C-band weather radars in simultaneous transmission and reception (STAR; i.e., horizontally and vertically polarized pulses are transmitted simultaneously) mode, providing 2D radar rainfall products. Despite the application of Doppler and speckle filtering, remaining nonmeteorological echoes (especially sea clutter) mainly due to anomalous propagation still pose a problem. This calls for additional filtering algorithms, which can be realized by means of polarimetry. Here we explore the effectiveness of the open-source wradlib fuzzy echo classification and clutter identification based on polarimetric moments. Based on our study, this has recently been extended with the depolarization ratio and clutter phase alignment as new decision variables. Optimal values for weights of the different membership functions and threshold are determined employing a 4-h calibration dataset from one radar. The method is applied to a full year of volumetric data from the two radars in the Dutch temperate climate. The verification focuses on the presence of remaining nonmeteorological echoes by mapping the number of exceedances of radar reflectivity factors for given thresholds. Moreover, accumulated rainfall maps are obtained to detect unrealistically large rainfall depths. The results are compared to those for which no further filtering has been applied. Verification against rain gauge data reveals that only a little precipitation is removed. Because the fuzzy logic algorithm removes many nonmeteorological echoes, the practice to composite data from both radars in logarithmic space to hide these echoes is abandoned and replaced by linearly averaging reflectivities.</p

Rainfall Monitoring Using Microwave Links from Cellular Communication Networks : The Dutch Experience

Microwave links from commercial cellular communication networks have been used for rainfall monitoring in The Netherlands since 2003. Here we report on the start of our work on this topic using a dedicated microwave link in 1999, our first trails with commercial microwave links (CMLs) from Vodafone in 2003, our first published results in 2007, our work on sources of error and uncertainties in rainfall retrievals using microwave links of different lengths and frequencies, and finally the fruitful collaboration with T-Mobile NL, which lead to areal rainfall estimation for the Rotterdam metropolitan area in 2009 and 2010 and country-wide rainfall mapping for the entire land surface area of The Netherlands since 2012. Our current work on this topic follows three lines of research: (1) further refinement of our rainfall retrieval and mapping algorithm; (2) further quantification of sources of error and uncertainties using a dedicated experimental setup of multiple microwave links and a line configuration of disdrometers for ground validation; (3) promotion of the international replication of this method for rainfall monitoring through collaboration with partners in Europe and beyond.</p

Opportunistic remote sensing of rainfall using microwave links from cellular communication networks

Microwave backhaul links from cellular communication networks provide a valuable “opportunistic” source of high‐resolution space–time rainfall information, complementing traditional in situ measurement devices (rain gauges, disdrometers) and remote sensors (weather radars, satellites). Over the past decade, a growing community of researchers has, in close collaboration with cellular communication companies, developed retrieval algorithms to convert the raw microwave link signals, stored operationally by their network management systems, to hydrometeorologically useful rainfall estimates. Operational meteorological and hydrological services as well as private consulting firms are showing an increased interest in using this complementary source of rainfall information to improve the products and services they provide to end users from different sectors, from water management and weather prediction to agriculture and traffic control. The greatest potential of these opportunistic environmental sensors lies in those geographical areas over the land surface of the Earth where the densities of traditional rainfall measurement devices are low: mountainous and urban areas and the developing world. This article provides a nonexpert summary of the history, theory, challenges, and opportunities toward continental‐scale rainfall monitoring using microwave links from cellular communication networks