Challenges in Observation-Based Mapping of Daily Precipitation across the Conterminous United States

There is a great need for gridded daily precipitation datasets to support a wide variety of disciplines in science and industry. Production of such datasets faces many challenges, from station data ingest to gridded dataset distribution. The quality of the dataset is directly related to its information content, and each step in the production process provides an opportunity to maximize that content. The first opportunity is maximizing station density from a variety of sources, and assuring high quality through intensive screening, including manual review. To accommodate varying data latency times, the PRISM Climate Group releases eight versions of a day’s precipitation grid, from 24 hours after day’s end to six months elapsed time. The second opportunity is to distribute the station data to a grid using methods that add information and minimize the smoothing effect of interpolation. We use two competing methods, one that utilizes the information in long-term precipitation climatologies, and the other using weather radar return patterns. Finally, maintaining consistency among different time scales (monthly vs. daily) affords the opportunity to exploit information available at each scale. Maintaining temporal consistency over longer time scales is at cross purposes with maximizing information content. We therefore produce two datasets, one that maximizes data sources, and a second that includes only networks with long-term stations and no radar (a short-term data source). Further work is underway to improve station metadata, refine interpolation methods by producing climatologies targeted to specific storm conditions, and employ higher-resolution radar products.

A Satellite-USV System for Persistent Observation of Mesoscale Oceanographic Phenomena

Traditional tools and methodologies for mesoscale observation of oceanographic phenomena are limited by under-sampling and data latency. In this article we evaluate three different scenario variants of an architecture for how heterogeneous sensor nodes can be integrated with satellite remote sensing. Independent space and marine sensing platforms are interconnected either directly or by means of a ground-based mission control center responsible for data processing, relay, and coordination of the assets. A wave-propelled unmanned surface vehicle (USV) persistently collects in situ data of the targeted phenomenon. In two variants of the architecture, a dedicated small satellite acts as a sensor node, a data processing facility and a communication node. We have used a System-of-Systems (SoS) modeling approach coupled with operational simulations in different locations on Earth, in order to support the proposed methodology and investigate quantitatively the reduction the data latency to end-users. Through a combination of field experiments and simulations we estimate how the different scenarios perform with respect to providing remote sensing data that are used to create a measurement and navigation plan for the autonomous vessel.

Advancements and Characteristics of Gauge Ingest and Quality Control within the Multi-Radar Multi-Sensor System

This study describes recent advancements in the Multi-Radar Multi-Sensor (MRMS) automated gauge ingest and quality control (QC) processes. A data latency analysis for the combined multiple gauge collection platforms provided guidance for a multiple-pass generation and delivery of gauge-based precipitation products. Various advancements to the gauge QC logic were evaluated over a 21-month period, resulting in an average of 86% of hourly gauge observations per hour being classified as useful. The fully-automated QC logic was compared to manual human QC for a limited domain, which showed a > 95% agreement in their QC reasoning categories. This study also includes an extensive evaluation of various characteristics related to the gauge observations ingested into the MRMS system. Duplicate observations between gauge collection platforms highlighted differences in site coordinates; moreover, errors in Automated Surface Observing System (ASOS) station site coordinates resulted in > 79% of sites being located in a different MRMS 1-km grid cell. The ASOS coordinate analysis combined with examinations of other limitations regarding gauge observations highlight the need for robust and accurate metadata to further enhance the quality control of gauge data.

Design and Testing of AUV Docking Modules for a Renewably Powered Offshore AUV Servicing Platform

Autonomous Underwater Vehicle (AUV) missions are limited in range and duration by the vehicle’s battery capacity, and sensor payloads are limited by the processing power onboard which is also restricted by the vehicle’s battery capacity. Furthermore, the power consumption of a vehicle’s acoustic system limits the possibility of substantial data transmission, requiring the AUV be retrieved to download most data. The Platform for Expanding AUV exploRation to Longer ranges (PEARL), described in this paper, aims to extend the range and endurance of AUVs while reducing data latency and operating costs. PEARL is an integrated autonomous floating servicing station that utilizes renewable energy to simultaneously provide AUV battery recharging and data uplink via new generation high-bandwidth low-Earth orbit satellite constellations. This paper details the design and testing of two potential AUV docking modules of the PEARL system. The modules are uniquely located near the ocean surface, an energetic environment that presents a particular set of challenges for AUV docking. The results will be used to inform the design of a prototype system to be tested in an ocean setting.

Global Forecast Impact of Low Data Latency Infrared and Microwave Sounders Observations from Polar Orbiting Satellites

The Direct Broadcast Network (DBNet) provides near-real-time delivery of low-earth-orbiting (LEO) meteorological satellites to operational numerical weather prediction (NWP) systems that need short data cut-off times to allow for the assimilation of the most recent satellite measurements. The NWP model requires timely delivery of observations including atmospheric temperature, humidity, and surface wind vectors. The World Meteorological Organization (WMO) Space Program (WSP) recommends the data latency of no more than 20 min for the satellite measurements. Currently, not all DBNet stations are delivering satellite data within the 20-min time frame. In this study, the forecast impact of the observations of LEO satellite sounders with data latency of 20 min or less was evaluated using the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). Reducing the data latency up to 5 min increases the number of LEO infrared (IR) and microwave (MW) sounder observations delivered to the NCEP GFS data assimilation system by more than 20%. Overall, this study demonstrates a positive impact on the global weather forecasts when the IR and MW sounder data are delivered by 20 min anywhere in the world. Additional forecast benefits are not obvious for shorter data latency. Results from this study support the WSP recommendation of 20–minute data latency.

Commercial Microwave Links as a tool for operational rainfall monitoring in Northern Italy

There is a growing interest in emerging opportunistic sensors for precipitation estimates, motivated by the need to describe with detail precipitation structures. In this work a preliminary assessment of the accuracy of Commercial Microwave Links (CMLs) retrieved rainfall rates in northern Italy is presented. The CML product, obtained by the publicly available RAINLINK package, is evaluated at different scales (single link, 5 km x 5 km grid, river basin) against the precipitation products operationally used at Arpae-SIMC, the Regional Weather Service of Emilia-Romagna, in northern Italy. The results of the 15 min single-link validation with close-by raingauges show high variability, with influence of the area physiography and precipitation patterns and the impact of some known issues (e.g. melting layer). However, hourly cumulated spatially interpolated CML rainfall maps, validated with respect to the established regional gauge-based reference, show performances (R2 of 0.47 and CV of 0.77) which are very similar, when not even better, to satellite- and adjusted radar-based precipitation gridded products. This is especially true when basin-scale total precipitation amounts are considered (R2 of 0.85 and CV of 0.63). Taking into account also delays in the availability of the data (latency of 0.33 hours for CML against 1 hour for the adjusted radar and 24 h for the quality controlled raingauges), CMLs appear as a valuable data source in particular from a local operational framework perspective. A diffuse underestimation is evident at both grid box (Mean Error of −0.26) and basin scale (Multiplicative Bias of 0.7), while the number of false alarms is generally low and gets even lower as coverage increases. Finally, results show complementary strengths for CMLs and radars, encouraging a joint exploitation.