Five years of commercial microwave link network derived rainfall research in Sweden

2020 ◽  
Author(s):  
Remco (C.Z.) van de Beek ◽  
Jafet Andersson ◽  
Jonas Olsson ◽  
Jonas Hansryd
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Rain Rate ◽  
Ground Level ◽  
Rain Gauge ◽  
Professional Services ◽  
High Temporal Resolution ◽  
Rain Gauges ◽  
Microwave Link ◽  
Rain Rates

<p>Accurate rainfall measurements are very important in hydrology, meteorology, agriculture and other fields. Traditionally rain gauges combined with radar have been used to measure rain rates. However, these instruments are not always available. Also combining point measurements at the ground with measured reflectivities of volumes in the air to an accurate rain rate map at ground level poses challenges. Commercial microwave link networks can help in these areas as these can provide measurements at a high temporal resolution and tend to be available wherever people live, with highest network densities where most people are. They also measure precipitation along a path near ground level and offer a way to close the gap between rain gauge measurements and radar.</p><p>In this study we highlight the work SMHI has performed on deriving rain rates from commercial microwave links since 2015. This started with a pilot study in Gothenburg. The signal strengths of 364 microwave links were sampled every ten seconds and were used to create rainfall maps at a one-minute temporal resolution and 500m spatial resolution. These rain maps were then applied in a hydrological experiment and compared to rain gauge and radar measurements. The results were very promising, not only due to the high temporal and spatial resolution, but also with the accuracy of the actual measurements. The correlation was found to be equal to those of the rain gauges, while links were found to overestimate rainfall volumes on average. A demo site was created showing the one-minute rain rate maps and can be found at: https://www.smhi.se/en/services/professional-services/microweather/. Since then the methodology has been further improved and also applied within Stockholm in a new hydrological experiment. Currently new regions are being considered, as well as novel ways to merge data sources to create high quality precipitation maps. This contribution summarizes the progress to date.</p>

scholarly journals High Temporal Resolution Path-Average Rain Gauge with 50-GHz Band Microwave

2005 ◽  
Vol 22 (2) ◽  
pp. 165-179 ◽  
Author(s):  
Haruya Minda ◽  
Kenji Nakamura
Keyword(s):  
Temporal Resolution ◽  
Rain Gauge ◽  
High Temporal Resolution ◽  
Spatial Average ◽  
Rain Gauges ◽  
Average Rainfall ◽  
Rain Events ◽  
Microwave Link ◽  
Rain Radar ◽  
Average Rain

Abstract Rain radar measures instantaneous spatial-average rainfall, while conventional rain gauges directly measure point rainfall with low temporal resolution. Thus differences in the resolution of the sensors create difficulties for rain radar validation, especially for spaceborne rain radar. Accordingly, rainfall measurement by microwave link has been proposed for several decades, as it estimates instantaneous path-average rainfall. Thus it is expected that the microwave link rain gauge will overcome, at least partly, the problems in the rain radar validation, toward which a 50-GHz band microwave link [the path-averaged rain gauge (PRG)] was developed that has been in operation since September 2000. In this paper, the authors show the potential of the PRG system by a simple model and rainfall comparison with a disdrometer and a tipping-bucket rain gauge. Differences observed by the instruments were within 15% (within 10% in half of the cases) during actual rain events in 2003. This confirmed that the PRG system displayed good performance as a rain gauge. Finally, the possibility of the PRG system being applied for spaceborne rain radar validation is considered.

scholarly journals Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information

2019 ◽  
Vol 20 (5) ◽  
pp. 1015-1026 ◽  
Author(s):  
Nobuyuki Utsumi ◽  
Hyungjun Kim ◽  
F. Joseph Turk ◽  
Ziad. S. Haddad
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Rain Gauges ◽  
Gauge Data ◽  
Surface Rain Rate ◽  
Trmm Precipitation ◽  
Time Lagged ◽  
Rain Rates

Abstract Quantifying time-averaged rain rate, or rain accumulation, on subhourly time scales is essential for various application studies requiring rain estimates. This study proposes a novel idea to estimate subhourly time-averaged surface rain rate based on the instantaneous vertical rain profile observed from low-Earth-orbiting satellites. Instantaneous rain estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) are compared with 1-min surface rain gauges in North America and Kwajalein atoll for the warm seasons of 2005–14. Time-lagged correlation analysis between PR rain rates at various height levels and surface rain gauge data shows that the peak of the correlations tends to be delayed for PR rain at higher levels up to around 6-km altitude. PR estimates for low to middle height levels have better correlations with time-delayed surface gauge data than the PR’s estimated surface rain rate product. This implies that rain estimates for lower to middle heights may have skill to estimate the eventual surface rain rate that occurs 1–30 min later. Therefore, in this study, the vertical profiles of TRMM PR instantaneous rain estimates are averaged between the surface and various heights above the surface to represent time-averaged surface rain rate. It was shown that vertically averaged PR estimates up to middle heights (~4.5 km) exhibit better skill, compared to the PR estimated instantaneous surface rain product, to represent subhourly (~30 min) time-averaged surface rain rate. These findings highlight the merit of additional consideration of vertical rain profiles, not only instantaneous surface rain rate, to improve subhourly surface estimates of satellite-based rain products.

scholarly journals A Variational Approach to Retrieve Rain Rate by Combining Information from Rain Gauges, Radars, and Microwave Links

2013 ◽  
Vol 14 (6) ◽  
pp. 1897-1909 ◽  
Author(s):  
Blandine Bianchi ◽  
Peter Jan van Leeuwen ◽  
Robin J. Hogan ◽  
Alexis Berne
Keyword(s):  
Variational Approach ◽  
Rain Rate ◽  
Rain Gauge ◽  
Sources Of Information ◽  
Rain Gauges ◽  
Strongly Nonlinear ◽  
Using Data ◽  
The Cost ◽  
Microwave Link ◽  
Link Information

Abstract Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

scholarly journals Using High-Speed Photography to Study Undercatch in Tipping-Bucket Rain Gauges*

2014 ◽  
Vol 31 (6) ◽  
pp. 1330-1336 ◽  
Author(s):  
Claude Duchon ◽  
Christopher Fiebrich ◽  
David Grimsley
Keyword(s):  
High Speed ◽  
Rain Rate ◽  
Slow Motion ◽  
Rain Gauge ◽  
The Other ◽  
High Speed Photography ◽  
High Speed Camera ◽  
Rain Gauges ◽  
Linear Correction ◽  
Rain Rates

Abstract To better understand the undercatch process associated with tipping-bucket rain gauges, a high-speed camera normally used in determining the structure of lightning was employed. The photo rate was set at 500 frames per second to observe the tipping of the bucket in a commonly used tipping-bucket rain gauge. The photos showed detail never seen before as the bucket tipped from one side to the other. Two fixed rain rates of 19.9 mm h−1 (0.78 in. h−1) and 175.2 mm h−1 (6.90 in. h−1), the minimum and maximum available, respectively, were used. The data from four tips at each rain rate were examined. The results show that the time from the beginning of a tip to the time the bucket assembly is horizontal—defined as the period during which undercatch occurs—was an average of 0.450 s for the eight cases. The average time for a complete tip was 0.524 s; thus, the vast majority of the time of a tip, 86%, is spent in undercatch mode. Because there was no apparent dependence of these times on rain rate, it should be possible to apply an accurate linear correction for undercatch as a function of rain rate given the time that undercatch occurs during a tip. Over all eight tips, the undercatch was found to be 0.98% for the 19.9 mm h−1 rate and 8.78% for the 175.2 mm h−1 rate. The procedure used to estimate the undercatch is described. Slow motion videos of the tipping of a bucket are available online.

scholarly journals High temporal resolution rainfall rate estimation from rain gauge measurements

2017 ◽  
Vol 19 (6) ◽  
pp. 930-941 ◽  
Author(s):  
Yang Song ◽  
Dawei Han ◽  
Miguel A. Rico-Ramirez
Keyword(s):  
Temporal Resolution ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Rain Gauge ◽  
Rainfall Rate ◽  
High Temporal Resolution ◽  
Feed Forward Neural Network ◽  
Rate Estimation ◽  
Rain Gauges ◽  
Nonlinear Relationships

Abstract Rainfall rates derived from tipping bucket rain gauges generally ignore the detailed variation at a finer temporal scale that particularly occurs in light rainfall events. This study extends the exploration of using artificial neural networks (ANNs), in comparison with the conventional linear interpolation method (LIM) and the cubic spline algorithm (CSA) for rainfall rate estimation at fine temporal resolution using rain gauge data based on a case study at Chilbolton and Sparsholt observatories, UK. A supervised feed-forward neural network integrated with the backpropagation algorithm is used to identify the complex nonlinear relationships between input and target variables. The results indicate that the ANN considerably outperforms the CSA and LIM with higher Nash–Sutcliffe efficiency, lower root mean square error and lower rainfall amount differences when compared to the disdrometer observations when the model is trained within a broad span of input values. Consistent stability in accurately estimating rainfall rate in different sites shows the intrinsic advantage of ANNs in learning and self-adaptive abilities in modelling complex nonlinear relationships between the inputs and target variables.

scholarly journals Polarimetric Estimates of a 1-Month Accumulation of Light Rain with a 3-cm Wavelength Radar

2011 ◽  
Vol 12 (5) ◽  
pp. 1024-1039 ◽  
Author(s):  
L. Borowska ◽  
D. Zrnić ◽  
A. Ryzhkov ◽  
P. Zhang ◽  
C. Simmer
Keyword(s):  
Rain Rate ◽  
Rain Gauge ◽  
Light Rain ◽  
Differential Phase ◽  
Rain Gauges ◽  
Bright Band ◽  
X Band ◽  
Wet Snow ◽  
Composite Estimator ◽  
Rain Rates

Abstract The authors evaluate rainfall estimates from the new polarimetric X-band radar at Bonn, Germany, for a period between mid-November and the end of December 2009 by comparison with rain gauges. The emphasis is on slightly more than 1-month accumulations over areas minimally affected by beam blockage. The rain regime was characterized by reflectivities mainly below 45 dBZ, maximum observed rain rates of 47 mm h−1, a mean rain rate of 0.1 mm h−1, and brightband altitudes between 0.6 and 2.4 km above the ground. Both the reflectivity factor and the specific differential phase are used to obtain the rain rates. The accuracy of rain total estimates is evaluated from the statistics of the differences between radar and rain gauge measurements. Polarimetry provides improvement in the statistics of reflectivity-based measurements by reducing the bias and RMS errors from −25% to 7% and from 33% to 17%, respectively. Essential to this improvement is separation of the data into those attributed to pure rain, those from the bright band, and those due to nonmeteorological scatterers. A type-specific (rain or wet snow) relation is applied to obtain the rain rate by matching on the average the contribution by wet snow to the radar-measured rainfall below the bright band. The measurement of rain using specific differential phase is the most robust and can be applied to the very low rain rates and still produce credible accumulation estimates characterized with a standard deviation of 11% but a bias of −25%. A composite estimator is also tested and discussed.

scholarly journals Assessing Satellite-Based Rainfall Estimates in Semiarid Watersheds Using the USDA-ARS Walnut Gulch Gauge Network and TRMM PR

2012 ◽  
Vol 13 (5) ◽  
pp. 1579-1588 ◽  
Author(s):  
Eyal Amitai ◽  
Carl L. Unkrich ◽  
David C. Goodrich ◽  
Emad Habib ◽  
Bryson Thill
Keyword(s):  
Rain Rate ◽  
Correlation Coefficients ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Field Of View ◽  
High Temporal Resolution ◽  
Coverage Area ◽  
Rain Gauges ◽  
Walnut Gulch ◽  
Rain Gauge Network

Abstract The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in situ measurements and satellite-based instantaneous rain rate estimates like those from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). The WGEW network is the densest rain gauge network in the PR coverage area for watersheds greater than 10 km2. It consists of 88 weighing rain gauges within a 149-km2 area. On average, approximately 10 gauges can be found in each PR field of view (~5-km diameter). All gauges are very well synchronized with 1-min reporting intervals. This allows generating very-high-temporal-resolution rain rate fields and obtaining accurate estimates of the area-average rain rate for the entire watershed and for a single PR field of view. In this study, instantaneous rain rate fields from the PR and the spatially interpolated gauge measurements (on a 100 m × 100 m grid, updated every 1 min) are compared for all TRMM overpasses in which the PR recorded rain within the WGEW boundaries (25 overpasses during 1999–2010). The results indicate very good agreement between the fields with low bias values (<10%) and high correlation coefficients, especially for the near-nadir cases (>0.9). The correlation is high at overpass time but the peak occurs several minutes after the overpass, which can be explained by the fact that it takes several minutes for the raindrops to reach the gauge from the time they are observed by the PR. The correlation improves with the new version of the TRMM algorithm (V7). The study includes assessment of the accuracy of the reference products.

scholarly journals Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Radar Reflectivity ◽  
Time Shift ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Reflectivity Data ◽  
Rain Rates ◽  
Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

Large-scale Arctic sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission

2021 ◽  
Author(s):  
Stephen Howell ◽  
Mike Brady ◽  
Alexander Komarov
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
High Temporal Resolution ◽  
Sar Images ◽  
Sea Ice Extent ◽  
Arctic Sea

<p>As the Arctic’s sea ice extent continues to decline, remote sensing observations are becoming even more vital for the monitoring and understanding of this process.  Recently, the sea ice community has entered a new era of synthetic aperture radar (SAR) satellites operating at C-band with the launch of Sentinel-1A in 2014, Sentinel-1B in 2016 and the RADARSAT Constellation Mission (RCM) in 2019. These missions represent a collection of 5 spaceborne SAR sensors that together can routinely cover Arctic sea ice with a high spatial resolution (20-90 m) but also with a high temporal resolution (1-7 days) typically associated with passive microwave sensors. Here, we used ~28,000 SAR image pairs from Sentinel-1AB together with ~15,000 SAR images pairs from RCM to generate high spatiotemporal large-scale sea ice motion products across the pan-Arctic domain for 2020. The combined Sentinel-1AB and RCM sea ice motion product provides almost complete 7-day coverage over the entire pan-Arctic domain that also includes the pole-hole. Compared to the National Snow and Ice Data Center (NSIDC) Polar Pathfinder and Ocean and Sea Ice-Satellite Application Facility (OSI-SAF) sea ice motion products, ice speed was found to be faster with the Senintel-1AB and RCM product which is attributed to the higher spatial resolution of SAR imagery. More sea ice motion vectors were detected from the Sentinel-1AB and RCM product in during the summer months and within the narrow channels and inlets compared to the NSIDC Polar Pathfinder and OSI-SAF sea ice motion products. Overall, our results demonstrate that sea ice geophysical variables across the pan-Arctic domain can now be retrieved from multi-sensor SAR images at both high spatial and temporal resolution.</p>

scholarly journals Automated rain rate estimates using the Ka-band ARM zenith radar (KAZR)

2015 ◽  
Vol 8 (9) ◽  
pp. 3685-3699 ◽  
Author(s):  
A. Chandra ◽  
C. Zhang ◽  
P. Kollias ◽  
S. Matrosov ◽  
W. Szyrmer
Keyword(s):  
Rain Rate ◽  
Tropical Indian Ocean ◽  
Rain Gauge ◽  
Signal Attenuation ◽  
Ka Band ◽  
Automated Algorithm ◽  
Atmospheric Radiation Measurement ◽  
Microphysical Processes ◽  
The Tropics ◽  
Rain Rates

Abstract. The use of millimeter wavelength radars for probing precipitation has recently gained interest. However, estimation of precipitation variables is not straightforward due to strong signal attenuation, radar receiver saturation, antenna wet radome effects and natural microphysical variability. Here, an automated algorithm is developed for routinely retrieving rain rates from the profiling Ka-band (35-GHz) ARM (Atmospheric Radiation Measurement) zenith radars (KAZR). A 1-dimensional, simple, steady state microphysical model is used to estimate impacts of microphysical processes and attenuation on the profiles of radar observables at 35-GHz and thus provide criteria for identifying situations when attenuation or microphysical processes dominate KAZR observations. KAZR observations are also screened for signal saturation and wet radome effects. The algorithm is implemented in two steps: high rain rates are retrieved by using the amount of attenuation in rain layers, while low rain rates are retrieved from the reflectivity–rain rate (Ze–R) relation. Observations collected by the KAZR, rain gauge, disdrometer and scanning precipitating radars during the DYNAMO/AMIE field campaign at the Gan Island of the tropical Indian Ocean are used to validate the proposed approach. The differences in the rain accumulation from the proposed algorithm are quantified. The results indicate that the proposed algorithm has a potential for deriving continuous rain rate statistics in the tropics.

Sign in / Sign up

Export Citation Format

Share Document