Rainfall Nowcasting Using Commercial Microwave Links. Issue 19 (28th September 2020)

• Record Type: Journal Article
• Authors: Imhoff, R. O.; Overeem, A.; Brauer, C. C.; Leijnse, H.; Weerts, A. H.; Uijlenhoet, R.
• Is Part Of: Geophysical research letters. Volume 47:Issue 19(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-28
• Subjects: commerical microwave links -- nowcasting -- opportunistic sensing -- radar -- rainfall; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2020GL089365
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Accurate and timely precipitation forecasts are crucial for early warning. Rainfall nowcasting, the process of statistically extrapolating recent rainfall observations, is increasingly used for short‐term forecasting. Nowcasts are generally constructed with high‐resolution radar observations. As a proof of concept, we construct nowcasts with country‐wide rainfall maps estimated from signal level data of commercial microwave links (CMLs) for 12 summer days in the Netherlands. CML nowcasts compare well to radar rainfall nowcasts. Provided well‐calibrated CML rainfall estimates are employed, CML nowcasts can outperform unadjusted real‐time radar nowcasts for high rainfall rates, which are underestimated as compared to a reference. Care should be taken with the sensitivity of the advection field derivation to areas with low CML coverage and the inherent measurement scale of CML data, which can be larger than the application scale. We see potential for rainfall nowcasting with CML data, for example, in regions where weather radars are absent. Plain Language Summary: Capturing the amount, timing and location of rainfall are of key importance for water management and the agricultural sector. Nowcasting of rainfall, a computational approach where the most recent rainfall observations are spatially extrapolated, is increasingly used for short‐term rainfall forecasts. The required rainfall observations normally originate from weather radars, but it has previously been demonstrated that rainfall can also be estimated from rain‐induced signal attenuation from the commercial microwave links (CMLs) in cellular telecommunication networks, which are used worldwide. In this study, we use such estimates to construct rainfall nowcasts for 12 summer events in the Netherlands, which we compare to nowcasts using operational radars. The results demonstrate that there is potential for using rainfall estimates from CML data to nowcast rainfall up to a few hours ahead, for example, in (low‐ and middle‐income) regions where high‐resolution rainfall observations or weather radars are absent. Key Points: Probabilistic rainfall nowcasts are constructed with rainfall estimates from commercial microwave links The nowcasts are compared to radar rainfall nowcasts for 12 summer days Nowcast skill depends on link network density and is generally comparable to that of radar rainfall nowcasts