H. Leijnse

Country-wide rainfall maps from cellular communication networks

Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent.

Continental-scale radar monitoring of the aerial movements of animals

Billions of organisms travel through the air, influencing population dynamics, community interactions, ecosystem services and our lives in many different ways. Yet monitoring these movements are technically very challenging. During the last few decades, radars have increasingly been used to study the aerial movements of birds, bats and insects, yet research efforts have often been local and uncoordinated between research groups. However, a network of operational weather radars is continuously recording atmospheric conditions all over Europe and these hold enormous potential for coordinated, continental-scale studies of the aerial movements of animals.The European Network for the Radar surveillance of Animal Movement (ENRAM) is a new e-COST research network aiming exactly at exploring this potential. The main objective of ENRAM is to merge expertise to utilize weather radars to monitor the aerial movement of animals across Europe for a broad range of stakeholders at an unprecedented scale and enable researchers to study the causes and consequences of movement. In this paper we describe the aims of ENRAM in more detail and the challenges researchers will address, provide an overview of aero-ecological studies using radar, and present some of the opportunities that a large sensor network can provide for movement ecology research.

Precipitation Measurement at CESAR, the Netherlands

Abstract The Cabauw Experimental Site for Atmospheric Research (CESAR) observatory hosts a unique collection of instruments related to precipitation measurement. The data collected by these instruments are stored in a database that is freely accessible through a Web interface. The instruments present at the CESAR site include three disdrometers (two on the ground and one at 200 m above ground level), a dense network of rain gauges, three profiling radars (1.3, 3.3, and 35 GHz), and an X-band Doppler polarimetric scanning radar. In addition to these instruments, operational weather radar data from the nearby (∼25 km) De Bilt C-band Doppler radar are also available. The richness of the datasets available is illustrated for a rainfall event, where the synergy of the different instruments provides insight into precipitation at multiple spatial and temporal scales. These datasets, which are freely available to the scientific community, can contribute greatly to our understanding of precipitation-related atmosp...

First-Year Evaluation of GPM Rainfall over the Netherlands: IMERG Day 1 Final Run (V03D)

AbstractThe Global Precipitation Measurement (GPM) mission is the successor to the Tropical Rainfall Measuring Mission (TRMM), which orbited Earth for ~17 years. With Core Observatory launched on 27 February 2014, GPM offers global precipitation estimates between 60°N and 60°S at 0.1° × 0.1° resolution every 30 min. Unlike during the TRMM era, the Netherlands is now within the coverage provided by GPM. Here the first year of GPM rainfall retrievals from the 30-min gridded Integrated Multisatellite Retrievals for GPM (IMERG) product Day 1 Final Run (V03D) is assessed. This product is compared against gauge-adjusted radar rainfall maps over the land surface of the Netherlands at 30-min, 24-h, monthly, and yearly scales. These radar rainfall maps are considered to be ground truth. The evaluation of the first year of IMERG operations is done through time series, scatterplots, empirical exceedance probabilities, and various statistical indicators. In general, there is a tendency for IMERG to slightly underesti...

Errors and uncertainties in microwave link rainfall estimation explored using drop size measurements and high-resolution radar data

Microwave links can be used for the estimation of path-averaged rainfall by using either the path-integrated attenuation or the difference in attenuation of two signals with different frequencies and/or polarizations. Link signals have been simulated using measured time series of raindrop size distributions (DSDs) over a period of nearly 2 yr, in combination with wind velocity data and Taylor’s hypothesis. For this purpose, Taylor’s hypothesis has been tested using more than 1.5 yr of high-resolution radar data. In terms of correlation between spatial and temporal profiles of rainfall intensities, the validity of Taylor’s hypothesis quickly decreases with distance. However, in terms of error statistics, the hypothesis is seen to hold up to distances of at least 10 km. Errors and uncertainties (mean bias error and root-mean-square error, respectively) in microwave link rainfall estimates due to spatial DSD variation are at a minimum at frequencies (and frequency combinations) where the power-law relation for the conversion to rainfall intensity is close to linear. Errors generally increase with link length, whereas uncertainties decrease because of the decrease of scatter about the retrieval relations because of averaging of spatially variable DSDs for longer links. The exponent of power-law rainfall retrieval relations can explain a large part of the variation in both bias and uncertainty, which means that the order of magnitude of these error statistics can be predicted from the value of this exponent, regardless of the link length.

Birds flee en mass from New Year’s Eve fireworks

Anthropogenic disturbances of wildlife, such as noise, human presence, hunting activity, and motor vehicles, are becoming an increasing concern in conservation biology. Fireworks are an important part of celebrations worldwide, and although humans often find fireworks spectacular, fireworks are probably perceived quite differently by wild animals. Behavioral responses to fireworks are difficult to study at night, and little is known about the negative effects fireworks may have on wildlife. Every year, thousands of tons of fireworks are lit by civilians on New Year’s Eve in the Netherlands. Using an operational weather radar, we quantified the reaction of birds to fireworks in 3 consecutive years. Thousands of birds took flight shortly after midnight, with high aerial movements lasting at least 45 min and peak densities measured at 500 m altitude. The highest densities were observed over grasslands and wetlands, including nature conservation sites, where thousands of waterfowl rest and feed. The Netherlands is the most important winter staging area for several species of waterfowl in Europe. We estimate that hundreds of thousands of birds in the Netherlands take flight due to fireworks. The spatial and temporal extent of disturbance is substantial, and potential consequences are discussed. Weather radar provides a unique opportunity to study the reaction of birds to fireworks, which has otherwise remained elusive.

Two and a half years of country‐wide rainfall maps using radio links from commercial cellular telecommunication networks

Although rainfall estimation employing microwave links from cellular telecommunication networks is recognized as a new promising measurement technique, its potential for long-term large-scale operational rainfall monitoring remains to be demonstrated. This study contributes to this endeavor by deriving a continuous series of rainfall maps from a large 2.5 year microwave link data set of, on average, 3383 links (2044 link paths) covering Netherlands (∼3.5 × 104 km2), a midlatitude country (∼5°E, ∼52°N) with a temperate climate. Maps are extensively verified against an independent gauge-adjusted radar rainfall data set for different temporal (15 min, 1 h, 1 day, 1 month) and spatial (0.9, 74 km2) scales. The usefulness of different steps in the rainfall retrieval algorithm, i.e., a wet-dry classification method and a filter to remove outliers, is systematically assessed. A novel dew filter is developed to correct for dew-induced wet antenna attenuation, which, although a relative underestimation of 6% to 9% is found, generally yields good results. The microwave link rainfall estimation technique performs well for the summer months (June, July, August), even outperforming interpolation of automatic rain gauge data (with a density of ∼1 gauge per 1000 km2), but large deviations are found for the winter months (December, January, February). These deviations are generally expected to be related to frozen or melting precipitation. Hence, our results show the potential of commercial microwave links for long-term large-scale operational rainfall monitoring.

From Agricultural Benefits to Aviation Safety: Realizing the Potential of Continent-Wide Radar Networks

Abstract Migratory animals provide a multitude of services and disservices—with benefits or costs in the order of billions of dollars annually. Monitoring, quantifying, and forecasting migrations across continents could assist diverse stakeholders in utilizing migrant services, reducing disservices, or mitigating human–wildlife conflicts. Radars are powerful tools for such monitoring as they can assess directional intensities, such as migration traffic rates, and biomass transported. Currently, however, most radar applications are local or small scale and therefore substantially limited in their ability to address large-scale phenomena. As weather radars are organized into continent-wide networks and also detect “biological targets,” they could routinely monitor aerial migrations over the relevant spatial scales and over the timescales required for detecting responses to environmental perturbations. To tap these unexploited resources, a concerted effort is needed among diverse fields of expertise and among stakeholders to recognize the value of the existing infrastructure and data beyond weather forecasting.

Sensitivity of power functions to aggregation: Bias and uncertainty in radar rainfall retrieval

Rainfall retrieval using weather radar relies on power functions between radar reflectivity Z and rain rate R. The nonlinear nature of these relations complicates the comparison of rainfall estimates employing reflectivities measured at different scales. Transforming Z into R using relations that have been derived for other scales results in a bias and added uncertainty. We investigate the sensitivity of Z-R relations to spatial and temporal aggregation using high-resolution reflectivity fields for five rainfall events. Existing Z-R relations were employed to investigate the behavior of aggregated Z-R relations with scale, the aggregation bias, and the variability of the estimated rain rate. The prefactor and the exponent of aggregated Z-R relations systematically diverge with scale, showing a break that is event-dependent in the temporal domain and nearly constant in space. The systematic error associated with the aggregation bias at a given scale can become of the same order as the corresponding random error associated with intermittent sampling. The bias can be constrained by including information about the variability of Z within a certain scale of aggregation, and is largely captured by simple functions of the coefficient of variation of Z. Several descriptors of spatial and temporal variability of the reflectivity field are presented, to establish the links between variability descriptors and resulting aggregation bias. Prefactors in Z-R relations can be related to multifractal properties of the rainfall field. We find evidence of scaling breaks in the structural analysis of spatial rainfall with aggregation.

Crowdsourcing Urban Air Temperatures through Smartphone Battery Temperatures in São Paulo, Brazil

AbstractCrowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where routine weather observations are scarce. Previous studies showed that smartphone battery temperature readings can be used to estimate the daily and citywide air temperature via a direct heat transfer model. This work extends model estimates by studying smaller temporal and spatial scales. The study finds the number of battery readings influences the accuracy of temperature retrievals. Optimal results are achieved for 700 or more retrievals. An extensive dataset of over 10 million battery temperature readings for estimating hourly and daily air temperatures is available for Sao Paulo, Brazil. The air temperature estimates are validated with measurements from a WMO station, an Urban Flux Network site, and data from seven citizen weather stations. Daily temperature estimates are good (coefficient of determination ρ2 of 86%), and the study shows they improve by opt...