Abstract. Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant inaccuracies. Solid precipitation is particularly difficult to measure accurately, and wintertime precipitation measurement biases between different observing networks or different regions can exceed 100 %. Using precipitation gauge results from the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, crystal habit, and wind were quantified. The methods used to calculate gauge catch efficiency and correct known biases are described. Adjustments, in the form of "transfer functions" that describe catch efficiency as a function of air temperature and wind speed, were derived using measurements from eight separate WMO-SPICE sites for both unshielded and single-Alter-shielded precipitationweighing gauges. For the unshielded gauges, the average undercatch for all eight sites was 0.50 mm h −1 (34 %), and for the single-Alter-shielded gauges it was 0.35 mm h −1 (24 %). After adjustment, the mean bias for both the unshielded and single-Alter measurements was within 0.03 mm h −1 (2 %) of zero. The use of multiple sites to derive such adjustments makes these results unique and more broadly applicable to other sites with various climatic conditions. In addition, errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites were estimated.

Abstract. Precipitation measurements exhibit large coldseason biases due to under-catch in windy conditions. These uncertainties affect water balance calculations, snowpack monitoring and calibration of remote sensing algorithms and land surface models. More accurate data would improve the ability to predict future changes in water resources and mountain hazards in snow-dominated regions.In 2010, a comprehensive test site for precipitation measurements was established on a mountain plateau in southern Norway. Automatic precipitation gauge data are compared with data from a precipitation gauge in a Double Fence Intercomparison Reference (DFIR) wind shield construction which serves as the reference. A large number of other sensors are provided supporting data for relevant meteorological parameters.In this paper, data from three winters are used to study and determine the wind-induced under-catch of solid precipitation. Qualitative analyses and Bayesian statistics are used to evaluate and objectively choose the model that best describes the data. A continuous adjustment function and its uncertainty are derived for measurements of all types of winter precipitation (from rain to dry snow). A regression analysis does not reveal any significant misspecifications for the adjustment function, but shows that the chosen model does not describe the regression noise optimally. The adjustment function is operationally usable because it is based only on data available at standard automatic weather stations.The results show a non-linear relationship between undercatch and wind speed during winter precipitation events and there is a clear temperature dependency, mainly reflecting the precipitation type. The results allow, for the first time, derivation of an adjustment function based on measurements above 7 m s −1 . This extended validity of the adjustment function shows a stabilization of the wind-induced precipitation loss for higher wind speeds.

Abstract. This paper presents extensive bias determination analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloonborne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45-60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (∼35-55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45-55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.

Abstract. Hydrologic measurements are important for both the short- and long-term management of water resources. Of the terms in the hydrologic budget, precipitation is typically the most important input; however, measurements of precipitation are subject to large errors and biases. For example, an all-weather unshielded weighing precipitation gauge can collect less than 50 % of the actual amount of solid precipitation when wind speeds exceed 5 m s−1. Using results from two different precipitation test beds, such errors have been assessed for unshielded weighing gauges and for weighing gauges employing four of the most common windshields currently in use. Functions to correct wind-induced undercatch were developed and tested. In addition, corrections for the single-Alter weighing gauge were developed using the combined results of two separate sites in Norway and the USA. In general, the results indicate that the functions effectively correct the undercatch bias that affects such precipitation measurements. In addition, a single function developed for the single-Alter gauges effectively decreased the bias at both sites, with the bias at the US site improving from −12 to 0 %, and the bias at the Norwegian site improving from −27 to −4 %. These correction functions require only wind speed and air temperature as inputs, and were developed for use in national and local precipitation networks, hydrological monitoring, roadway and airport safety work, and climate change research. The techniques used to develop and test these transfer functions at more than one site can also be used for other more comprehensive studies, such as the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE).

Published by Copernicus Publications on behalf of the European Geosciences Union. Abstract. The Atmospheric Chemistry Experiment (ACE) satellite was launched on 12 August 2003. Its two instruments measure vertical profiles of over 30 atmospheric trace gases by analyzing solar occultation spectra in the ultraviolet/visible and infrared wavelength regions. The reservoir gases HNO 3 , ClONO 2 , and N 2 O 5 are three of the key species provided by the primary instrument, the ACE Fourier Transform Spectrometer (ACE-FTS). This paper describes the ACE-FTS version 2.2 data products, including the N 2 O 5 update, for the three species and presents validation comparisons with available observations. We have compared volume mixing ratio (VMR) profiles of HNO 3 , ClONO 2 , and N 2 O 5 with measurements by other satellite instruments (SMR, MLS, MIPAS), aircraft measurements (ASUR), and single balloon-flights (SPIRALE, FIRS-2). Partial columns of HNO 3 and ClONO 2 were also compared with measurements by ground-based Fourier Transform Infrared (FTIR) spectrometers. Overall the quality of the ACE-FTS v2.2 HNO 3 VMR profiles is good from 18 to 35 km. For the statistical satellite comparisons, the mean absolute differences are generally within ±1 ppbv (±20%) from 18 to 35 km. For MI-PAS and MLS comparisons only, mean relative differences lie within ±10% between 10 and 36 km. ACE-FTS HNO 3 partial columns (∼15-30 km) show a slight negative bias of −1.3% relative to the ground-based FTIRs at latitudes ranging from 77.8 • S-76.5 • N. Good agreement between ACE-FTS ClONO 2 and MIPAS, using the Institut für Meteorologie und Klimaforschung and Instituto de Astrofísica de Andalucía (IMK-IAA) data processor is seen. Mean absolute differences are typically within ±0.01 ppbv between 16 and 27 km and less than +0.09 ppbv between 27 and 34 km. The ClONO 2 partial column comparisons show varying degrees of agreement, depending on the location and the quality of the FTIR measurements. Good agreement was found for the comparisons with the midlatitude Jungfraujoch partial columns for which the mean relative difference is 4.7%. ACE-FTS N 2 O 5 has a low bias relative to MIPAS IMK-IAA, reaching −0.25 ppbv at the altitude of the N 2 O 5 maximum (around 30 km). Mean absolute differences at lower altitudes (16-27 km) are typically −0.05 ppbv for MIPAS nighttime and ±0.02 ppbv for MIPAS daytime measurements.