Significant sources of bias in temperature measurements by rotational Raman lidar, and mitigation in the French mobile system WALI

2021 ◽  
Author(s):  
Julien Totems ◽  
Patrick Chazette ◽  
Alexandre Baron
Keyword(s):  
Measurement Errors ◽  
Weather Prediction ◽  
Absolute Accuracy ◽  
Raman Lidar ◽  
Mobile System ◽  
Optical Elements ◽  
Interference Filters ◽  
Common Path ◽  
Weather Model ◽  
The World

<p>Lidars using rotational Raman backscattering to monitor the temperature profile in the low troposphere offer enticing perspectives for applications in weather prediction, as well as studies of aerosol and water vapor interactions, when deriving simultaneously relative humidity and aerosol optical properties. We describe the technical choices made during the design and calibration of the new temperature Raman channels for the mobile Weather and Aerosol Lidar (WALI), going over the sources of bias and uncertainty stemming from the different optical elements of the instrument. The impacts of interference filters and non-common-path differences between Raman channels, and their mitigation, are particularly investigated; without countermeasures, we find the theoretical magnitude of the highlighted biases can be much larger than the targeted absolute accuracy of 1°C defined by the World Meteorological Organization (WMO). Effective measurement errors are quantified using numerical end-to-end simulations and numerous radiosoundings launched close to the lidar location. Our aim is to fully discuss design choices and sources of bias which have been little reported in the literature. An application of the WALI measurements during heat wave conditions in the summer of 2020 will also be presented, and compared to ERA5 weather model reanalyses.</p>

scholarly journals Mitigation of bias sources for atmospheric temperature and humidity in the mobile Weather & Aerosol Raman Lidar (WALI)

2021 ◽  
Author(s):  
Julien Totems ◽  
Patrick Chazette ◽  
Alexandre Baron
Keyword(s):  
Water Vapor ◽  
Measurement Errors ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Temperature Profiles ◽  
Raman Lidar ◽  
Optical Elements ◽  
Interference Filters ◽  
Common Path ◽  
First Time

Abstract. Lidars using vibrational and rotational Raman scattering to continuously monitor both the water vapor and temperature profiles in the low and middle troposphere offer enticing perspectives for applications in weather prediction and studies of aerosol/cloud/water vapor interactions by deriving simultaneously relative humidity and atmospheric optical properties. Several heavy systems exist in European laboratories but only recently have they been downsized and ruggedized for deployment in the field. In this paper, we describe in detail the technical choices made during the design and calibration of the new Raman channels for the mobile Weather and Aerosol Lidar (WALI), going over the important sources of bias and uncertainty on the water vapor & temperature profiles stemming from the different optical elements of the instrument. For the first time, the impacts of interference filters and non-common-path differences between Raman channels, and their mitigation, are particularly investigated, using horizontal shots in a homogenous atmosphere. For temperature, the magnitude of the highlighted biases can be much larger than the targeted absolute accuracy of 1 °C defined by the WMO. Measurement errors are quantified using simulations and a number of radiosoundings launched close to the laboratory.

scholarly journals Mitigation of bias sources for atmospheric temperature and humidity in the mobile Raman Weather and Aerosol Lidar (WALI)

2021 ◽  
Vol 14 (12) ◽  
pp. 7525-7544
Author(s):  
Julien Totems ◽  
Patrick Chazette ◽  
Alexandre Baron
Keyword(s):  
Water Vapor ◽  
Measurement Errors ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Temperature Profiles ◽  
Optical Elements ◽  
Common Path ◽  
Calibration Uncertainty ◽  
Mean Differences ◽  
First Time

Abstract. Lidars using vibrational and rotational Raman scattering to continuously monitor both the water vapor and temperature profiles in the low and middle troposphere offer enticing perspectives for applications in weather prediction and studies of aerosol–cloud–water vapor interactions by simultaneously deriving relative humidity and atmospheric optical properties. Several heavy systems exist in European laboratories, but only recently have they been downsized and ruggedized for deployment in the field. In this paper, we describe in detail the technical choices made during the design and calibration of the new Raman channels for the mobile Weather and Aerosol Lidar (WALI), going over the important sources of bias and uncertainty on the water vapor and temperature profiles stemming from the different optical elements of the instrument. For the first time, the impacts of interference filters and non-common-path differences between Raman channels, and their mitigation, in particular are investigated, using horizontal shots in a homogeneous atmosphere. For temperature, the magnitude of the highlighted biases can be much larger than the targeted absolute accuracy of 1 ∘C defined by the WMO (up to 6 ∘C bias below 300 m range). Measurement errors are quantified using simulations and a number of radiosoundings launched close to the laboratory. After de-biasing, the remaining mean differences are below 0.1 g kg−1 on water vapor and 1 ∘C on temperature, and rms differences are consistent with the expected error from lidar noise, calibration uncertainty, and horizontal inhomogeneities of the atmosphere between the lidar and radiosondes.

scholarly journals On-sky correction of non-common path aberration with the pyramid wavefront sensor

2020 ◽  
Vol 636 ◽  
pp. A88 ◽  
Author(s):  
S. Esposito ◽  
A. Puglisi ◽  
E. Pinna ◽  
G. Agapito ◽  
F. Quirós-Pacheco ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Critical Issue ◽  
Wavefront Sensor ◽  
Interaction Matrix ◽  
Scientific Instrument ◽  
Wavefront Sensors ◽  
Successful Operation ◽  
Optical Elements ◽  
Common Path ◽  
External Conditions

The paper deals with with the on-sky performance of the pyramid wavefront sensor-based Adaptive Optics (AO) systems. These wavefront sensors are of great importance, being used in all first light AO systems of the ELTs (E-ELT, GMT, and TMT), currently in design phase. In particular, non-common path aberrations (NCPAs) are a critical issue encountered when using an AO system to produce corrected images in an associated astronomical instrument. The AO wavefront sensor (WFS) and the supported scientific instrument typically use a series of different optical elements, thus experiencing different aberrations. The usual way to correct for such NCPAs is to introduce a static offset in the WFS signals. In this way, when the AO loop is closed the sensor offsets are zeroed and the deformable mirror converges to the shape required to null the NCPA. The method assumes that the WFS operation is linear and completely described by some pre-calibrated interaction matrix. This is not the case for some frequently used wavefront sensors like the Pyramid sensor or a quad-cell Shack-Hartmann sensor. Here we present a method to work in closed-loop with a pyramid wavefront sensor, or more generally a non-linear WFS, introducing a wavefront offset that remains stable when AO correction quality changes due to variations in external conditions like star brightness, seeing, and wind speed. The paper details the methods with analytical and numerical considerations. Then we present results of tests executed at the LBT telescope, in daytime and on sky, using the FLAO system and LUCI2 facility instrument. The on-sky results clearly show the successful operation of the method that completely nulls NCPA, recovering diffraction-limited images with about 70% Strehl ratio in H band in variable seeing conditions. The proposed method is suitable for application to the above-mentioned ELT AO systems.

scholarly journals High Clouds over Oceans in the ECMWF 15- and 45-Yr Reanalyses

2005 ◽  
Vol 18 (14) ◽  
pp. 2647-2661 ◽  
Author(s):  
Frédéric Chevallier ◽  
Graeme Kelly ◽  
Adrian J. Simmons ◽  
Sakari Uppala ◽  
Angeles Hernandez
Keyword(s):  
Cloud Cover ◽  
Weather Prediction ◽  
Systematic Errors ◽  
Interannual Variations ◽  
The World ◽  
Before And After ◽  
Infrared Radiances ◽  
High Clouds ◽  
Seasonal And Interannual Variations ◽  
Ecmwf Reanalysis

Abstract The reanalysis programs of numerical weather prediction (NWP) centers provide global, comprehensive descriptions of the atmosphere and of the earth’s surface over long periods of time. The high realism of their representation of key NWP parameters, like temperature and winds, implies some realism for less emblematic parameters, such as cloud cover, but the degree of this realism needs to be documented. This study aims to evaluate the high clouds over open oceans in the ECMWF 15- and 45-yr reanalyses. The assessment is based on a new 23-yr climatology of monthly frequencies of high-cloud occurrence retrieved from the infrared radiances measured by operational polar satellites. It is complemented by data from the International Satellite Cloud Climatology Project. It is shown that the 45-yr ECMWF reanalysis dramatically improves on the previous 15-yr reanalysis for the realism of seasonal and interannual variations in high clouds, despite remaining systematic errors. More than 60% of the observed anomalies during the January 1979–February 2002 period over large oceanic basins are captured by the latest reanalysis. However the realism of the analyses in the areas and in the years with sparse observations appears to be poor. Consequently, the interannual variations may not be reliable before January 1979 in most parts of the world. Possible improvements of the handling of assimilated satellite observations before and after this date are suggested.

Evaluation of the economic impacts of length and diameter measurement error on mechanical harvesters and processors operating in pine stands

2006 ◽  
Vol 36 (7) ◽  
pp. 1661-1673 ◽  
Author(s):  
Hamish D Marshall ◽  
Glen E Murphy ◽  
Kevin Boston
Keyword(s):  
Measurement Error ◽  
Simulation Model ◽  
Measurement Errors ◽  
Economic Impacts ◽  
Error Rates ◽  
Potential Value ◽  
Value Recovery ◽  
The World ◽  
Length Measurements ◽  
Value Loss

Value recovery studies from around the world have shown that on average mechanical log-making systems lose 18% of the potential value compared to 11% for motor manual systems. One of the potential reasons for their poor value recovery performance is the level of accuracy of their stem diameter and length measurements. Numerous studies have looked at the level of error in both the diameter and length measurements made by mechanical harvesters and processors; however, few have looked at the economic impacts of these errors. The paper investigates the economic impacts in terms of value loss of six different harvesting operations in three different pine species. The accuracy and precision of the measurements recorded in this study were similar to those of other studies from around the world. A simulation model was developed to estimate the value loss caused by these errors. The results of the simulation model showed that the operations were losing between 3% and 23% of the potential value because of measurement errors. Further analysis showed that the industry should concentrate on increasing the precision of the length and diameter measurements to optimize gains from reducing the measurement error rates.

scholarly journals Preliminary results of the Analysis of Precipitation Processes in the Eastern Ebro Subbasin (WISE-PreP) Field Campaign within HILIAISE

2021 ◽  
Author(s):  
Joan Bech ◽  
Mireia Udina ◽  
Bernat Codina ◽  
Sergi Gonzalez ◽  
Albert Garcia ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Weather Prediction ◽  
Surface Characteristics ◽  
Ensemble Prediction ◽  
Field Campaign ◽  
Preliminary Results ◽  
The World ◽  
Precipitation Processes ◽  
Semi Arid

<p>Understanding future changes of the terrestrial water cycle and their interaction with human activity, with emphasis on agricultural areas, was selected as one of the World Climate Research Programme (WCRP) Grand Challenges, entitled “Water for the Food Baskets of the World”. Within this framework, the scientific objectives of the “Human Imprint on Land surface Interactions with the Atmosphere over the Iberian Semi-arid Environment” (HILIAISE) are the characterization of evapotranspiration and other key processes of water cycle in semi-arid environments. For this purpose, an international field campaign, scheduled for 2021, has been planned focused on a region with highly contrast surface characteristics (irrigated vs non-irrigated areas), particularly during summer.</p><p>An overview and preliminary results of a specific project (WISE-PreP) within HILIAISE is given here. WISE-PreP was designed to study precipitation processes aiming to characterize possible differences in precipitation induced by surface characteristics. For this purpose, planned instrumentation for the campaign includes the deployment of three sites equipped each with a vertical radar Doppler Micro Rain Radar (MRR) and a laser disdrometer (PARSIVEL), covering both irrigated and non-irrigated sites, with three disdrometers (model PARSIVEL-2) and three MRRs (one model MRR-2 and two MRR-PROs). Time series of vertical precipitation profiles will be recorded to study microphysical processes trough the evolution of raindrop size distributions and related variables including precipitation intensity or convective vs stratiform rainfall regimes. Additional observations include raingauge data, C-band Doppler weather radar observations, and satellite products, as well as high resolution deterministic numerical weather prediction model data plus Ensemble Prediction Systems (EPS) model output. Funding for this research was provided by “Analysis of Precipitation Processes in the Eastern Ebro Subbasin” (WISE-PreP, RTI2018-098693-B-C32) and the Water Research Institute (IdRA) of the University of Barcelona.</p>

scholarly journals Coupling a weather model directly to GNSS orbit determination

2021 ◽  
Author(s):  
Angel Navarro Trastoy ◽  
Sebastian Strasser ◽  
Lauri Tuppi ◽  
Maksym Vasiuta ◽  
Markku Poutanen ◽  
...  
Keyword(s):  
Orbit Determination ◽  
Prediction Models ◽  
Weather Prediction ◽  
Direct Coupling ◽  
Atmospheric Effects ◽  
Satellite Orbits ◽  
Small Data ◽  
Neutral Atmosphere ◽  
Data Set ◽  
Weather Model

Abstract. Neutral atmosphere bends and delays propagation of microwave signals in satellite-based navigation. Weather prediction models can be used to estimate these effects by providing 3-dimensional refraction fields to estimate signal delay in the zenith direction and determine a low-dimensional mapping of this delay to desired azimuth and elevation angles. In this study, a global numerical weather prediction model (OpenIFS licensed for Academic use by ECMWF) is used to generate the refraction fields. The ray-traced slant delays are supplied as such – in contrast to mapping – for an orbit solver (GROOPS software toolkit of TUG) which applies the raw observation method. Here we show that such a close coupling is possible without need for major additional modifications in the solver codes. The main finding here is that the adopted approach provides a very good a priori model for the atmospheric effects on navigation signals, as measured with the midnight discontinuity of GNSS satellite orbits. Our interpretation is that removal of the intermediate mapping step allows to take advantage of the local refraction field asymmetries in the GNSS signal processing. Moreover, the direct coupling helps in identifying deficiencies in the slant delay computation because the modelling errors are not convoluted in the precision-reducing mapping. These conclusions appear robust, despite the relatively small data set of raw code and phase observations covering the core network of 66 ground-based stations of the International GNSS Service over one-month periods in December 2016 and June 2017. More generally, the new configuration enhances our control of geodetic and meteorological aspects of the orbit problem. This is pleasant because we can, for instance, regulate at will the weather model output frequency and increase coverage of spatio-temporal aspects of weather variations. The direct coupling of a weather model in precise GNSS orbit determination presented in this paper provides a unique framework for benefiting even more widely than previously the apparent synergies in space geodesy and meteorology.

scholarly journals Comparison between Geostatistical Interpolation and Numerical Weather Model Predictions for Meteorological Conditions Mapping

2020 ◽  
Vol 5 (2) ◽  
pp. 15 ◽  
Author(s):  
Javier López Gómez ◽  
Francisco Troncoso Pastoriza ◽  
Enrique Granada Álvarez ◽  
Pablo Eguía Oller
Keyword(s):  
Local Level ◽  
Weather Prediction ◽  
Ground Truth ◽  
Weather Conditions ◽  
Meteorological Conditions ◽  
Accurate Information ◽  
Numerical Weather ◽  
Weather Model ◽  
Geostatistical Interpolation ◽  
Solid Foundation

Mapping of meteorological conditions surrounding road infrastructures is a critical tool to identify high-risk spots related to harsh weather. However, local or regional data are not always available, and researchers and authorities must rely on coarser observations or predictions. Thus, choosing a suitable method for downscaling global data to local levels becomes essential to obtain accurate information. This work presents a deep analysis of the performance of two of these methods, commonly used in meteorology science: Universal Kriging geostatistical interpolation and Weather Research and Forecasting numerical weather prediction outputs. Estimations from both techniques are compared on 11 locations in central continental Portugal during January 2019, using measured data from a weather station network as the ground truth. Results show the different performance characteristics of both algorithms based on the nature of the specific variable interpolated, highlighting potential correlations to obtain the most accurate data for each case. Hence, this work provides a solid foundation for the selection of the most appropriate tool for mapping of weather conditions at the local level over linear transport infrastructures.

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