scholarly journals Evaluation of a Prototype Broadband Water-Vapour Profiling Differential Absorption Lidar at Cardington, UK

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1521
Author(s):  
Catherine Gaffard ◽  
Zhihong Li ◽  
Dawn Harrison ◽  
Raisa Lehtinen ◽  
Reijo Roininen
Keyword(s):  
Water Vapour ◽  
Weather Prediction ◽  
Cloud Base ◽  
Maximum Height ◽  
Differential Absorption ◽  
Differential Absorption Lidar ◽  
Average Maximum ◽  
Resolution Model ◽  
Variable Bias ◽  
Nwp Model

For a one-month period in summer 2020, a prototype Vaisala broadband differential absorption lidar (BB-DIAL) was deployed at a Met Office research site. It was compared with in-situ observations of humidity (93 radiosonde ascents and 27 of uncrewed aerial vehicle flights) and the Met Office 1.5 km resolution numerical weather prediction (NWP) model: UK Variable resolution model (UKV). The BB-DIAL was able to collect data up to the cloud base, in all-weather situations including rain, when it was possible to reach 3 km. The average maximum height was 1300 m, with 75% of the data reaching 1000 m and 35% extending to 1500 m. Compared with radiosondes, the standard deviation for the water vapour is between 5% and 10%. The comparison with the UKV is very encouraging, with a correlation of 0.90. The error against the radiosonde is smaller than against the UKV, which is encouraging for assimilation the BB-DIAL data in UKV. Some data quality issues, such as an increase in error and variable bias in the region of overlap between the far field and close field, spurious oscillations and an unrealistic dry layer above fog are identified. Despite these issues, the overall results from this assessment are promising in terms of potential benefit, instrument reliability and capturing significant humidity changes in the boundary layer.

scholarly journals Numerical Guidance Methods for Decision Support in Aviation Meteorological Forecasting

2005 ◽  
Vol 20 (1) ◽  
pp. 82-100 ◽  
Author(s):  
A. J. M. Jacobs ◽  
N. Maat
Keyword(s):  
Weather Prediction ◽  
Forecast Accuracy ◽  
Transformation Method ◽  
Skill Score ◽  
Cloud Base ◽  
Model Data ◽  
Operational Environment ◽  
Automatic Production ◽  
Statistical Measures ◽  
Nwp Model

Abstract Numerical guidance methods for decision making support of aviation meteorological forecasters are presented. The methods have been developed to enhance the usefulness of numerical weather prediction (NWP) model data and local and upstream observations in the production of terminal aerodrome forecasts (TAFs) and trend-type forecasts (TRENDs) for airports. In this paper two newly developed methods are described and it is shown how they are used to derive numerical guidance products for aviation. The first is a combination of statistical and physical postprocessing of NWP model data and in situ observations. This method is used to derive forecasts for all aviation-related meteorological parameters at the airport. The second is a high-resolution wind transformation method, a technique used to derive local wind at airports from grid-box-averaged NWP model winds. For operational use of the numerical guidance products encoding software is provided for automatic production of an alphanumeric TAF and TREND code. A graphical user interface with an integrated code editor enables the forecaster to modify the suggested automatic codes. For aviation, the most important parameters in the numerical guidance are visibility and cloud-base height. Both have been subjected to a statistical verification analysis, together with their automatically produced codes. The results in terms of skill score are compared to the skill of the forecasters’ TAF and TREND code. The statistical measures suggest that the guidance has the best skill at lead times of +4 h and more. For the short term, mainly trend-type forecasts, the persistence forecast based on recent observations is difficult to beat. Verification has also shown that the wind transformation method, which has been applied to generate 10-m winds at Amsterdam Airport Schiphol, reduces the mean error in the (grid box averaged) NWP model wind significantly. Among the potential benefits of these numerical guidance methods is increasing forecast accuracy. As a result, the related numerical guidance products and encoding software have been integrated in the operational environment for the production of TAFs and TRENDs.

First model evaluations of height-resolved diurnal water vapour cycles using lidar observations in an Arctic environment

2021 ◽  
Author(s):  
Shannon Hicks-Jalali ◽  
Zen Mariani ◽  
Barbara Casati ◽  
Sylvie Leroyer ◽  
Francois Lemay ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Water Vapour ◽  
Diurnal Cycle ◽  
Weather Prediction ◽  
Vertical Motion ◽  
The Arctic ◽  
Diurnal Cycles ◽  
Surface Station ◽  
Nwp Model ◽  
Total Column

<p>Atmospheric water vapour is a critical component of both meteorological and climatological processes. It is the dominant gas in the greenhouse effect and its diurnal cycle is an essential component of the hydrological cycle. Diurnal water vapour cycles are complex and are a product of several mechanisms, including (but not necessarily limited to): evapotranspiration, advection, large-scale vertical motion, and precipitation. They are dependent on local geography, as well as latitude. Numerical Weather Prediction (NWP) models rely on high-quality water vapour input to provide accurate forecasts, which is particularly difficult in the Arctic due to its extreme weather and harsh environment. Diurnal water vapour cycle observations are also excellent tools for evaluating NWPs due to their complex nature and dependence on multiple processes. Integrated water vapour (IWV), or total column, diurnal water vapour cycles, usually calculated with Global Navigation Satellite Systems (GNSS) instruments, have been the focus of most previous diurnal WV studies; however, height-resolved diurnal cycles provide a more complete picture of the diurnal mechanisms and include vertical motion, which cannot be discerned via IWV measurements. Differential Absorption Lidars (DIALs) are well suited to providing height-resolved diurnal cycles in the boundary layer due to their high vertical and temporal resolution.</p><p>We use the novel Vaisala pre-production DIAL, installed in Iqaluit, Nunavut (63.75 N, 68.55 W), to calculate seasonal height-resolved diurnal WV cycles from 100 m to 1500 m altitude. We also calculate the surface and total column WV diurnal cycles using co-located surface station and GNSS measurements. We find that the first 250 m of the DIAL diurnal cycle magnitudes agree well with the surface station measurements. The phases of the cycle do shift with altitude, and the amplitudes generally increase with altitude. In the summer, all instruments observe a strong 24 hr cycle. As the amount of solar radiation decreases over the year, the 24 hr cycle weakens and the 12 hr cycle begins to dominate in all instruments. While we find a strong correlation between the 24 hr cycle and the solar cycle, we do not observe any correlation between the 12 hr cycle and the solar cycle. Finally, we also compare the DIAL observations to the Environment and Climate Change Canada (ECCC) NWP model. We evaluate both the assimilation of the humidity input and initial water vapour fields, as well as the diurnal cycle over the 24 hour forecast. Future work will include case study comparisons with the Canadian NWP model to assess the model’s ability to resolve rapid changes in diurnal water vapour.</p>

Atmospheric Motion Vectors from Model Simulations. Part II: Interpretation as Spatial and Vertical Averages of Wind and Role of Clouds

2014 ◽  
Vol 53 (1) ◽  
pp. 65-82 ◽  
Author(s):  
Angeles Hernandez-Carrascal ◽  
Niels Bormann
Keyword(s):  
Weather Prediction ◽  
Cloud Layer ◽  
Cloud Base ◽  
Random Errors ◽  
Motion Vectors ◽  
Single Level ◽  
Model Cloud ◽  
Atmospheric Motion ◽  
Nwp Model ◽  
Atmospheric Motion Vectors

AbstractThis is the second part of a two-part paper whose main objective is to improve the characterization of atmospheric motion vectors (AMVs) and their errors to guide developments in the use of AMVs in numerical weather prediction (NWP). AMVs tend to exhibit considerable systematic and random errors. These errors can arise in the AMV derivation or the interpretation of AMVs as single-level point estimates of wind. An important difficulty in the study of AMV errors is the scarcity of collocated observations of clouds and wind. The study uses instead a simulation framework: geostationary imagery for Meteorological Satellite-8 (Meteosat-8) is generated from a high-resolution simulation with the Weather Research and Forecasting regional model, and AMVs are derived from sequences of these simulated images. The NWP model provides the “truth” with a sophisticated description of the atmosphere. This second part focuses on alternative interpretations of AMVs. The key results are 1) that interpreting the AMVs as vertical and horizontal averages of wind can give some benefits over the traditional single-level interpretation (improvements in RMSVD of 5% for high-level AMVs and 20% for low-level AMVs) and 2) that there is evidence that AMVs are more representative of either a wind average over the model cloud layer or wind at a representative level within the cloud layer than of wind at the model cloud top or cloud base.

scholarly journals Evaluation of Arctic Water Vapor Profile Observations from a Differential Absorption Lidar

2021 ◽  
Vol 13 (4) ◽  
pp. 551
Author(s):  
Zen Mariani ◽  
Shannon Hicks-Jalali ◽  
Kevin Strawbridge ◽  
Jack Gwozdecky ◽  
Robert W. Crawford ◽  
...  
Keyword(s):  
Water Vapor ◽  
Weather Prediction ◽  
Ground Level ◽  
Model Verification ◽  
The Arctic ◽  
High Temporal Resolution ◽  
Differential Absorption ◽  
Differential Absorption Lidar ◽  
Arctic Water ◽  
Average Bias

The continuous measuring of the vertical profile of water vapor in the boundary layer using a commercially available differential absorption lidar (DIAL) has only recently been made possible. Since September 2018, a new pre-production version of the Vaisala DIAL system has operated at the Iqaluit supersite (63.74°N, 68.51°W), commissioned by Environment and Climate Change Canada (ECCC) as part of the Canadian Arctic Weather Science project. This study presents its evaluation during the extremely dry conditions experienced in the Arctic by comparing it with coincident radiosonde and Raman lidar observations. Comparisons over a one year period were strongly correlated (r > 0.8 at almost all heights) and exhibited an average bias of +0.13 ± 0.01 g/kg (DIAL-sonde) and +0.18 ± 0.02 g/kg (DIAL-Raman). Larger differences exhibiting distinct artifacts were found between 250 and 400 m above ground level (AGL). The DIAL’s observations were also used to conduct a verification case study of operational numerical weather prediction (NWP) models during the World Meteorological Organization’s Year of Polar Prediction. Comparisons to ECCC’s global environmental multiscale model (GEM-2.5 km and GEM-10 km) indicate good agreement with an average bias < 0.16 g/kg for the higher-resolution (GEM-2.5 km) models. All models performed significantly better during the winter than the summer, likely due to the winter’s lower water vapor concentrations and decreased variability. This study provides evidence in favor of using high temporal resolution lidar water vapor profile measurements to complement radiosonde observations and for NWP model verification and process studies.

scholarly journals Data Mining Numerical Model Output for Single-Station Cloud-Ceiling Forecast Algorithms

2007 ◽  
Vol 22 (5) ◽  
pp. 1123-1131 ◽  
Author(s):  
Richard L. Bankert ◽  
Michael Hadjimichael
Keyword(s):  
Data Mining ◽  
Weather Prediction ◽  
Ground Truth ◽  
Cloud Base ◽  
Model Output ◽  
Model Data ◽  
Single Station ◽  
Low Cloud ◽  
Nwp Model ◽  
Model Output Statistics

Abstract Accurate cloud-ceiling-height forecasts derived from numerical weather prediction (NWP) model data are useful for aviation and other interests where low cloud ceilings have an impact on operations. A demonstration of the usefulness of data-mining methods in developing cloud-ceiling forecast algorithms from NWP model output is provided here. Rapid Update Cycle (RUC) 1-h forecast data were made available for nearly every hour in 2004. Various model variables were extracted from these data and stored in a database of hourly records for routine aviation weather report (METAR) station KJFK at John F. Kennedy International Airport along with other single-station locations. Using KJFK cloud-ceiling observations as ground truth, algorithms were derived for 1-, 3-, 6-, and 12-h forecasts through a data-mining process. Performance of these cloud-ceiling forecast algorithms, as evaluated through cross-validation testing, is compared with persistence and Global Forecast System (GFS) model output statistics (MOS) performance (6 and 12 h only) over the entire year. The 1-h algorithms were also compared with the RUC model cloud-ceiling (or cloud base) height translation algorithms. The cloud-ceiling algorithms developed through data mining outperformed these RUC model translation algorithms, showed slightly better skill and accuracy than persistence at 3 h, and outperformed persistence at 6 and 12 h. Comparisons to GFS MOS (which uses observations in addition to model data for algorithm derivation) at 6 h demonstrated similar performance between the two methods with the cloud-ceiling algorithm derived through data mining demonstrating more skill at 12 h.

scholarly journals Evaluation of ECMWF water vapour fields by airborne differential absorption lidar measurements: a case study between Brazil and Europe

2007 ◽  
Vol 7 (19) ◽  
pp. 5033-5042 ◽  
Author(s):  
H. Flentje ◽  
A. Dörnbrack ◽  
A. Fix ◽  
G. Ehret ◽  
E. Hólm
Keyword(s):  
Water Vapour ◽  
Hadley Circulation ◽  
Convective Transport ◽  
Differential Absorption ◽  
Short Term ◽  
Differential Absorption Lidar ◽  
Air Mass ◽  
Back Trajectories ◽  
Air Masses ◽  
Upper Troposphere

Abstract. Three extended airborne Differential Absorption Lidar (DIAL) sections of tropospheric water vapour across the tropical and sub-tropical Atlantic in March 2004 are compared to short-term forecasts of the European Centre for Medium Range Weather Forecasts (ECMWF). The humidity fields between 28° S and 36° N exhibit large inter air-mass gradients and reflect typical transport patterns of low- and mid-latitudes like convection (e.g. Hadley circulation), subsidence and baroclinic development with stratospheric intrusion. These processes re-distribute water vapour vertically such that locations with extraordinary dry/moist air-masses are observed in the lower/upper troposphere, respectively. The mixing ratios range over 3 orders of magnitude. Back-trajectories are used to trace and characterize the observed air-masses. Overall, the observed water vapour distributions are largely reproduced by the short-term forecasts at 0.25° resolution (T799/L91), the correlation ranges from 0.69 to 0.92. Locally, large differences occur due to comparably small spatial shifts in presence of strong gradients. Systematic deviations are found associated with specific atmospheric domains. The planetary boundary layer in the forecast is too moist and to shallow. Convective transport of humidity to the middle and upper troposphere tends to be overestimated. Potential impacts arising from data assimilation and model physics are considered. The matching of air-mass boundaries (transport) is discussed with repect to scales and the representativity of the 2-D sections for the 3-D humidity field. The normalized bias of the model with respect to the observations is 6%, 11% and 0% (moist model biases) for the three along-flight sections, whereby however the lowest levels are excluded.

scholarly journals Study of the Vertical Structure of the Coastal Boundary Layer Integrating Surface Measurements and Ground-Based Remote Sensing

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6516
Author(s):  
Teresa Lo Feudo ◽  
Claudia Roberta Calidonna ◽  
Elenio Avolio ◽  
Anna Maria Sempreviva
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Vertical Structure ◽  
Weather Prediction ◽  
Internal Boundary Layer ◽  
Internal Boundary ◽  
Maximum Height ◽  
Coastal Boundary Layer ◽  
Wind Profiles ◽  
Nwp Model

The understanding of the atmospheric processes in coastal areas requires the availability of quality datasets describing the vertical and horizontal spatial structure of the Atmospheric Boundary Layer (ABL) on either side of the coastline. High-resolution Numerical Weather Prediction (NWP) models can provide this information and the main ingredients for good simulations are: an accurate description of the coastline and a correct subgrid process parametrization permitting coastline discontinuities to be caught. To provide an as comprehensive as possible dataset on Mediterranean coastal area, an intensive experimental campaign was realized at a near-shore Italian site, using optical and acoustic ground-based remote sensing and surface instruments, under different weather characteristic and stability conditions; the campaign is also fully simulated by a NWP model. Integrating information from instruments responding to different atmospheric properties allowed for an explanation of the development of various patterns in the vertical structure of the atmosphere. Wind LiDAR measurements provided information of the internal boundary layer from the value of maximum height reached by the wind profile; a height between 80 and 130 m is often detected as an interface between two different layers. The NWP model was able to simulate the vertical wind profiles and the eight of the ABL.

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