Intercomparison of snowfall measurements using disdrometers in two mountainous environments: Weissfluhjoch (Switzerland) and Formigal-Sarrios (Spain)

Comunicación presentada en: TECO-2016 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Madrid, del 27 al 30 de septiembre de 2016.One of the objectives of the WMO/CIMO Solid Precipitation Intercomparison Experiment (SPICE) is to assess the performance of emerging technologies such as disdrometers for the measurement of solid precipitation. Numerous studies have assessed the performance of disdrometers for liquid precipitation, but the experience of using such instruments for solid precipitation is still limited. Among others, the Spanish site at Formigal and the Swiss site at Weissfluhjoch were built with very similar design (especially the reference measurement setting in a Double Fence Intercomparison Reference (DFIR)). Moreover, the environment of both sites (siting) is similar. This work evaluates the potential use of disdrometers for solid precipitation measurement in a mountainous environment. At each site two LPM Thies disdrometers, one shielded in a DFIR and the other one outside (with or without a Thies wind shield), are intercompared under different weather conditions (wind speed and direction, temperature and snowfall intensity) against the SPICE reference measurement using a weighing gauge (OTT Pluvio2 in a DFIR). This study will present preliminary results from both sites and will give first conclusion on the impact of various external parameters (such as wind and temperature) on the disdrometer snow accumulation measurement in and outside the DFIR, and with and without a Thies shield. Moreover, new lines of research are recommended in order to better understand the instrument and the raw data output

Surface salinity of the North Atlantic : can we reconstruct its fluctuations over the last one hundred years ?

Surface samples have been collected in the North Atlantic in the past one hundred years for determining the ocean salinity and its temperature. A large share of the data we have used were collected by merchant vessels of weather ships of European countries and to a large extent are listed in reports, in particular in the "Bulletin Hydrographique". We investigate whether these data are relevant for determining low frequency fluctuations of the sea surface salinity. We find many crossing in the 1920s for which salinity is anomalously high compared with the climatology or with other crossings collected on the same ship line. These anomalies are indicative of a contamination of the sample. By examining hydrographic data, reports and recent experience in collectionand storage in sea water, we can attribute these large errors to unclean buckets where salt crystals dissolve into the sample and to breathing of the samples during the storage. Each of these stages contributes in estimating a too large salinity and adds to the scatter of the measurements. (D'après résumé d'auteur

Measuring solid precipitation using heated tipping bucket gauges: an overview of performance and recommendations from WMO‐SPICE

Comunicación presentada en: TECO-2016 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Madrid, del 27 al 30 de septiembre de 2016

Errors and adjustments for WMO-SPICE tipping-bucket precipitation gauges

Presentación realizada en: 19th Symposium on Meteorological Observation and Instrumentation celebrado del 7 al 11 de enero de 2018 en Austin, Texas

The WMO SPICE snow-on-ground intercomparison: an overview of sensor assessment and recommendations on best practices

Comunicación presentada en: TECO-2016 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Madrid, del 27 al 30 de septiembre de 2016.One of the objectives of the WMO Solid Precipitation Intercomparison Experiment (SPICE) was to assess the performance and capabilities of automated sensors for measuring snow on the ground (SoG), including sensors that measure snow depth and snow water equivalent (SWE). The intercomparison focused on five snow depth sensors (models SHM30, SL300, SR50A, FLS-CH 10 and USH-8) and two SWE sensors (models CS725 and SSG1000) over two winter seasons (2013/2014 and 2014/2015). A brief discussion of the measurement reference(s) and an example of the intercomparisons are included. Generally, each of the sensors under test operated according to the manufacturer’s specifications and compared well with the site references, exhibiting high correlations with both the manual and automated reference measurements. The use of natural and artificial surface targets under snow depth sensors were examined in the context of providing a stable and representative surface for snow depth measurements. An assessment of sensor derived measurement quality and sensor return signal strength, where available as an output option, were analysed to help explain measurement outliers and sources of uncertainty with the goal of improving data quality and maximizing the sensor capabilities. Finally, where possible, relationships are established between the gauge measurement of solid precipitation and the measurement of snow on the ground. This paper will provide a brief summary of these results with more detail included in the WMO SPICE Final Report

Errors, biases, and corrections for weighing gauge precipitation measurements from WMO-SPICE

Presentación realizada en: American Meteorological Society Annual Meeting (2017) celebrado en Seattle (Washington) del 22 al 26 de enero de 2017

Errors, Biases, and Corrections for Weighing Gauge Precipitation Measurements from the WMO Solid Precipitation Intercomparison Experiment

Comunicación presentada en: TECO-2016 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) celebrada en Madrid, del 27 al 30 de septiembre de 2016.Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant biases and errors. Solid precipitation is particularly difficult to measure accurately, and biases between winter-time precipitation measurements from different measurement networks or different regions can exceed 100%. Using precipitation gauge results from the WMO Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, and wind are quantified. The methods used to calculate gauge catch efficiency and correct known biases are described briefly. Transfer functions describing catch efficiency as a function of air temperature and wind speed are also presented. In addition, the biases and errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites are discussed

Assimilation of temperature profiles in a general circulation model of the Tropical Atlantic

Thirty-six hundred temperature profiles collected during 1984 were assimilated into a multilayer primitive equation model of the Tropical ocean. The method consists in a monthly correction of the simulated temperature field. Each month, an observed field is computed from the temperature profiles with a successive correction analysis starting from the simulated field. The difference between the observed field and simulation is computed, the model is restarted from the previous month, progressively introducing the difference as a Newton forcing in the heat equation. The sensitivity to the initial state is greatly reduced near the equator after six months, but persists for a longer time at higher latitudes. The assimilated temperature structure is closer to the observations than was the unassimilated simulation. The thermocline has strengthened, and low-frequency variability near the equator is close to the observed one, resulting in a more realistic zonal slope of the thermocline. The current structure, although it still differs noticeably from the observations, is more realistic, with stronger near-surface countercurrents and a faster equatorial undercurrent. (Résumé d'auteur