Profiling water vapor mixing ratios in Finland by means of a Raman lidar, a satellite and a model

Abstract. We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitée Adaptation dynamique Développement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are  < 2.8, 7.4 and 3.9 %, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50 % up to 8 km altitude in most cases. A 4-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15±0.40 g kg−1); during summer it is wet (5.54±1.02 g kg−1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer.

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Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0094.1 ◽

2015 ◽

Vol 16 (4) ◽

pp. 1843-1856 ◽

Cited By ~ 26

Author(s):

Silvio Davolio ◽

Francesco Silvestro ◽

Piero Malguzzi

Keyword(s):

High Resolution ◽

Weather Prediction ◽

Flood Forecasting ◽

Horizontal Resolution ◽

Precipitation Forecast ◽

Limited Area ◽

Flood Prediction ◽

Meteorological Model ◽

The Impact ◽

Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

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Understanding Satellite-Observed Mountain-Wave Signatures Using High-Resolution Numerical Model Data

Weather and Forecasting ◽

10.1175/2008waf2222127.1 ◽

2009 ◽

Vol 24 (1) ◽

pp. 76-86 ◽

Cited By ~ 23

Author(s):

W. F. Feltz ◽

K. M. Bedka ◽

J. A. Otkin ◽

T. Greenwald ◽

S. A. Ackerman

Keyword(s):

Water Vapor ◽

High Resolution ◽

Weighting Function ◽

Model Simulation ◽

Wave Train ◽

Radiative Transfer Model ◽

Transfer Model ◽

Model Data ◽

Mountain Wave ◽

Mountain Waves

Abstract Prior work has shown that pilot reports of severe turbulence over Colorado often occur when complex interference or crossing wave patterns are present in satellite water vapor imagery downstream of the Rocky Mountains. To improve the understanding of these patterns, a high-resolution (1-km) Weather Research and Forecasting (WRF) model simulation was performed for an intense mountain-wave event that occurred on 6 March 2004. Synthetic satellite imagery was subsequently generated by passing the model-simulated data through a forward radiative transfer model. Comparison with concurrent Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor imagery demonstrates that the synthetic satellite data realistically captured many of the observed mesoscale features, including a mountain-wave train extending far downstream of the Colorado Front Range, the deformation of this wave train by an approaching cold front, and the substantially warmer brightness temperatures in the lee of the major mountain ranges composing the Colorado Rockies. Inspection of the model data revealed that the mountain waves redistributed the water vapor within the lower and middle troposphere, with the maximum column-integrated water vapor content occurring one-quarter wavelength downstream of the maximum ascent within each mountain wave. Due to this phase shift, the strongest vertical motions occur halfway between the locally warm and cool brightness temperature couplets in the water vapor imagery. Interference patterns seen in the water vapor imagery appear to be associated with mesoscale variability in the ambient wind field at or near mountaintop due to flow interaction with the complex topography. It is also demonstrated that the synergistic use of multiple water vapor channels provides a more thorough depiction of the vertical extent of the mountain waves since the weighting function for each channel peaks at a different height in the atmosphere.

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First-Year Operation of a New Water Vapor Raman Lidar at the JPL Table Mountain Facility, California

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2007jtecha978.1 ◽

2008 ◽

Vol 25 (8) ◽

pp. 1454-1462 ◽

Cited By ~ 26

Author(s):

Thierry Leblanc ◽

I. Stuart McDermid ◽

Robin A. Aspey

Keyword(s):

Water Vapor ◽

Current System ◽

First Year ◽

Raman Lidar ◽

Upper Troposphere ◽

Mixing Ratios ◽

Table Mountain ◽

Lidar Measurements ◽

Better Than ◽

Good Agreement

Abstract A new water vapor Raman lidar was recently built at the Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL) in California and more than a year of routine 2-h-long nighttime measurements 4–5 times per week have been completed. The lidar was designed to reach accuracies better than 5% anywhere up to 12-km altitude, and with the capability to measure water vapor mixing ratios as low as 1 to 10 ppmv near the tropopause and in the lower stratosphere. The current system is not yet fully optimized but has already shown promising results as water vapor profiles have been retrieved up to 18-km altitude. Comparisons with Vaisala RS92K radiosondes exhibit very good agreement up to at least 10 km. They also revealed a wet bias in the lidar profiles (or a dry bias in the radiosonde profiles), increasing with altitude and becoming significant near 10 km and large when approaching the tropopause. This bias cannot be explained solely by well-known too-dry measurements of the RS92K in the upper troposphere and therefore must partly originate in the lidar measurements. Excess signal due to residual fluorescence in the lidar receiver components is among the most likely candidates and is subject to ongoing investigation.

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An online trajectory module (version 1.0) for the non-hydrostatic numerical weather prediction model COSMO

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-1223-2013 ◽

2013 ◽

Vol 6 (1) ◽

pp. 1223-1257

Author(s):

A. K. Miltenberger ◽

S. Pfahl ◽

H. Wernli

Keyword(s):

High Resolution ◽

Wind Field ◽

Model Simulation ◽

Weather Prediction ◽

Limited Area ◽

Model Output ◽

Wind Fields ◽

Time Step ◽

Flow Distortion ◽

Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the non-hydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are fairly small for high-resolution simulations. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO module an Alpine North Föhn event in summer 1987 has been simulated with horizontal resolutions of 2.2 km, 7 km, and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

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The Sydney Australia Wildfires of January 1994 - Meteorological Conditions and High Resolution Numerical Modeling Experiments

International Journal of Wildland Fire ◽

10.1071/wf9960145 ◽

1996 ◽

Vol 6 (3) ◽

pp. 145 ◽

Cited By ~ 8

Author(s):

MS Speer ◽

LM Leslie ◽

JR Colquhoun ◽

E Mitchell

Keyword(s):

High Resolution ◽

Weather Prediction ◽

Weather Conditions ◽

Detailed Examination ◽

Meteorological Conditions ◽

Limited Area ◽

Research Activity ◽

Southeastern Australia ◽

South Wales ◽

Resolution Model

Southeastern Australia is particularly vulnerable to wildfires during the spring and summer months, and the threat of devastation is present most years. In January 1994, the most populous city in Australia, Sydney, was ringed by wildfires, some of which penetrated well into suburban areas and there were many other serious fires in coastal areas of New South Wales (NSW). In recent years much research activity in Australia has focussed on the development of high resolution limited area models, for eventual operational prediction of meteorological conditions associated with high levels of wildfire risk. In this study, the period January 7-8, 1994 was chosen for detailed examination, as it was the most critical period during late December 1993/early January 1994 for the greater Sydney area. Routine forecast guidance from the Australian Bureau of Meteorology's operational numerical weather prediction (NWP) models was very useful in that both the medium and short range models predicted synoptic patterns suggesting extreme fire weather conditions up to several days in advance. However, vital information of a detailed nature was lacking. A new high resolution model was run at the operational resolution of 150 km and the much higher resolutions of 25 km and 5 km. The new model showed statistically significant greater skill in predicting details of wind, relative humidity and temperature patterns both near the surface and above the boundary layer. It also produced skilful predictions of the Forest Fire Danger Index.

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The ALADIN System and its canonical model configurations AROME CY41T1 and ALARO CY40T1

Geoscientific Model Development ◽

10.5194/gmd-11-257-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 257-281 ◽

Cited By ~ 63

Author(s):

Piet Termonia ◽

Claude Fischer ◽

Eric Bazile ◽

François Bouyssel ◽

Radmila Brožková ◽

...

Keyword(s):

High Resolution ◽

Data Assimilation ◽

Numerical Weather Prediction ◽

Weather Forecasting ◽

Weather Prediction ◽

Forecast Model ◽

Canonical Model ◽

Limited Area ◽

Climate Simulations ◽

Process Studies

Abstract. The ALADIN System is a numerical weather prediction (NWP) system developed by the international ALADIN consortium for operational weather forecasting and research purposes. It is based on a code that is shared with the global model IFS of the ECMWF and the ARPEGE model of Météo-France. Today, this system can be used to provide a multitude of high-resolution limited-area model (LAM) configurations. A few configurations are thoroughly validated and prepared to be used for the operational weather forecasting in the 16 partner institutes of this consortium. These configurations are called the ALADIN canonical model configurations (CMCs). There are currently three CMCs: the ALADIN baseline CMC, the AROME CMC and the ALARO CMC. Other configurations are possible for research, such as process studies and climate simulations. The purpose of this paper is (i) to define the ALADIN System in relation to the global counterparts IFS and ARPEGE, (ii) to explain the notion of the CMCs, (iii) to document their most recent versions, and (iv) to illustrate the process of the validation and the porting of these configurations to the operational forecast suites of the partner institutes of the ALADIN consortium. This paper is restricted to the forecast model only; data assimilation techniques and postprocessing techniques are part of the ALADIN System but they are not discussed here.

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Carbon monoxide mixing ratios over Oklahoma between 2002 and 2009 retrieved from Atmospheric Emitted Radiance Interferometer spectra

Atmospheric Measurement Techniques ◽

10.5194/amt-3-1319-2010 ◽

2010 ◽

Vol 3 (5) ◽

pp. 1319-1331 ◽

Cited By ~ 11

Author(s):

L. Yurganov ◽

W. McMillan ◽

C. Wilson ◽

M. Fischer ◽

S. Biraud ◽

...

Keyword(s):

Water Vapor ◽

Great Plains ◽

Microwave Radiometer ◽

Precipitable Water ◽

Retrieval Algorithm ◽

Southern Great Plains ◽

Diurnal Cycles ◽

Mixing Ratios ◽

Clear Sky ◽

The Tropics

Abstract. CO mixing ratios for the lowermost 2-km atmospheric layer were retrieved from downwelling infrared (IR) radiance spectra of the clear sky measured between 2002 and 2009 by a zenith-viewing Atmospheric Emitted Radiance Interferometer (AERI) deployed at the Southern Great Plains (SGP) observatory of the Atmospheric Radiation Measurements (ARM) Program near Lamont, Oklahoma. A version of a published earlier retrieval algorithm was improved and validated. Archived temperature and water vapor profiles retrieved from the same AERI spectra through automated ARM processing were used as input data for the CO retrievals. We found the archived water vapor profiles required additional constraint using SGP Microwave Radiometer retrievals of total precipitable water vapor. A correction for scattered solar light was developed as well. The retrieved CO was validated using simultaneous independently measured CO profiles from an aircraft. These tropospheric CO profiles were measured from the surface to altitudes of 4572 m a.s.l. once or twice a week between March 2006 and December 2008. The aircraft measurements were supplemented with ground-based CO measurements using a non-dispersive infrared gas correlation instrument at the SGP and retrievals from the Atmospheric IR Sounder (AIRS) above 5 km to create full tropospheric CO profiles. Comparison of the profiles convolved with averaging kernels to the AERI CO retrievals found a squared correlation coefficient of 0.57, a standard deviation of ±11.7 ppbv, a bias of -16 ppbv, and a slope of 0.92. Averaged seasonal and diurnal cycles measured by the AERI are compared with those measured continuously in situ at the SGP in the boundary layer. Monthly mean CO values measured by the AERI between 2002 and 2009 are compared with those measured by the AIRS over North America, the Northern Hemisphere mid-latitudes, and over the tropics.

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An online trajectory module (version 1.0) for the nonhydrostatic numerical weather prediction model COSMO

Geoscientific Model Development ◽

10.5194/gmd-6-1989-2013 ◽

2013 ◽

Vol 6 (6) ◽

pp. 1989-2004 ◽

Cited By ~ 23

Author(s):

A. K. Miltenberger ◽

S. Pfahl ◽

H. Wernli

Keyword(s):

High Resolution ◽

Wind Field ◽

Weather Prediction ◽

Limited Area ◽

Model Output ◽

Wind Fields ◽

Time Step ◽

Flow Distortion ◽

Computational Costs ◽

Cosmo Model

Abstract. A module to calculate online trajectories has been implemented into the nonhydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated resolved wind field at every model time step (typically less than a minute) to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO-model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO-model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain), the additional computational costs are found to be fairly small for the high-resolution simulations described in this paper. The computational costs may, however, vary strongly depending on the number of trajectories and trace variables. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO-model module, an Alpine north foehn event in summer 1987 has been simulated with horizontal resolutions of 2.2, 7 and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and 150–750 m, respectively, after 24 h. This first application illustrates the potential for Lagrangian studies of mesoscale flows in high-resolution convection-resolving simulations using online trajectories.

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An Integrated Assessment of Measured and Modeled Integrated Water Vapor in Switzerland for the Period 2001–03

Journal of Applied Meteorology ◽

10.1175/jam2255.1 ◽

2005 ◽

Vol 44 (7) ◽

pp. 1033-1044 ◽

Cited By ~ 22

Author(s):

G. Guerova ◽

E. Brockmann ◽

F. Schubiger ◽

J. Morland ◽

C. Mätzler

Keyword(s):

Water Vapor ◽

Standard Deviation ◽

Diurnal Cycle ◽

Integrated Assessment ◽

Mesoscale Model ◽

Microwave Radiometer ◽

Measurement Techniques ◽

Bimodal Distribution ◽

Limited Area ◽

Dry Bias

Abstract In this paper an integrated assessment of the vertically integrated water vapor (IWV) measured by radiosonde, microwave radiometer (MWR), and GPS and modeled by the limited-area mesoscale model of MeteoSwiss is presented. The different IWV measurement techniques are evaluated through intercomparisons of GPS to radiosonde in Payerne, Switzerland, and to the MWR operated at the Institute of Applied Physics at the University of Bern in Switzerland. The validation of the IWV field of the nonhydrostatic mesoscale Alpine Model (aLMo) of MeteoSwiss is performed against 14 GPS sites from the Automated GPS Network of Switzerland (AGNES) in the period of 2001–03. The model forecast and the nudging analysis are evaluated, with special attention paid to the diurnal cycle. The results from the GPS–radiosonde intercomparison are in agreement, but with a bimodal distribution of the day-to-night basis. At 0000 UTC, the bias is negative (−0.4 kg m−2); at 1200 UTC, it is positive (0.9 kg m−2) and the variability increases. The intercomparison of GPS to MWR shows better agreement (0.4 kg m−2), with a small increase of the daytime bias with 0.3 kg m−2. The intercomparison of MWR to the radiosonde gives a bimodal distribution of the bias, with an increase in the standard deviation at the daytime measurement. The relative bias is negative (−3%) at 0000 UTC and is positive (3%) at 1200 UTC. Based on this cross correlation, it can be concluded that the bimodal distribution is a result of radiosonde humidity measurements. Possible reasons are the solar-heating correction or sensor errors. The monthly bias and standard deviation of aLMo exhibit a strong seasonal dependence with a pronounced dry bias during the warm months of May–October 2002. The diurnal IWV cycle in 2001 shows good model performance between 0000 and 0900 UTC but IWV underestimation by up to 1.5 kg m−2 for the rest of the day. In 2002 the diurnal cycle shows a systematic dry bias in both the analysis and forecast that is more pronounced in the analysis. This substantial underestimation of IWV was found to correlate with overestimation of aLMo precipitation, especially light precipitation up to 0.1 mm (6 h)−1 in 2002. There is strong evidence that this underestimation can be related to the dry radiosonde bias in midday summer observations. The aLMo dry bias is about 1.0–1.5 kg m−2 greater in the nudging analysis as compared with the forecast initialized at 0000 UTC.

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