Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data

Lamquin, Nicolas; Gierens, Klaus; Stubenrauch, C.; Chatterjee, R.

doi:10.5194/acp-9-1779-2009

Cited by 29 publications

(45 citation statements)

References 38 publications

(45 reference statements)

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“…An exception is the report by Lamquin et al (2009) focusing on humidity in the upper troposphere. Results of an analysis on systematic variations of 98 % quantiles of wind speed are given in Fig.…”

Section: Spin-up Effects Threshold and Diurnal Cyclementioning

confidence: 99%

An approach to build an event set of European windstorms based on ECMWF EPS

Osinski¹,

Lorenz²,

Kruschke

et al. 2016

Nat. Hazards Earth Syst. Sci.

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Abstract. The properties of European windstorms under present climate conditions are estimated on the basis of surface wind forecasts from the European Centre for MediumRange Weather Forecast (ECMWF) Ensemble Prediction System (EPS). While the EPS is designed to provide forecast information of the range of possible weather developments starting from the observed state of weather, we use its archive in a climatological context. It provides a large number of modifications of observed storm events and includes storms that did not occur in reality. Thus it is possible to create a large sample of storm events, which entirely originate from a physically consistent model, whose ensemble spread represents feasible alternative storm realizations of the covered period. This paper shows that the huge amount of identifiable events in the EPS is applicable to reduce uncertainties in a wide range of fields of research focusing on winter storms. Windstorms are identified and tracked in this study over their lifetime using an algorithm based on the local exceedance of the 98th percentile of instantaneous 10 m wind speed, which is associated with a storm severity measure. After removing inhomogeneities in the data set arising from major modifications of the operational system, the distributions of storm severity, storm size, and storm duration are computed. The overall principal properties of the homogenized EPS storm data set are in good agreement with storms from the ERAInterim data set, making it suitable for climatological investigations of these extreme events. A demonstrated benefit in the climatological context by the EPS is presented. It gives clear evidence of a linear increase of maximum storm intensity and wind field size with storm duration. This relation is not recognizable from a sparse ERA-Interim sample for long-lasting events, as the number of events in the reanalysis is not sufficient to represent these characteristics.

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Section: Spin-up Effects Threshold and Diurnal Cyclementioning

confidence: 99%

An approach to build an event set of European windstorms based on ECMWF EPS

Osinski¹,

Lorenz²,

Kruschke

et al. 2016

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…The introduction of ice supersaturation delayed the formation of ice clouds, and the upper-tropospheric humidity increased in the forecast model (Tompkins et al, 2007). However, the degree of ice supersaturation was limited in the four-dimensional variational assimilation (4DVAR) scheme, leading to a spin-up of humidity from the analysis into the forecast (Lamquin et al, 2009).…”

Section: Changes To the Ifs Over Timementioning

confidence: 99%

Comparison of Fast In situ Stratospheric Hygrometer (FISH) measurements of water vapor in the upper troposphere and lower stratosphere (UTLS) with ECMWF (re)analysis data

Kunz

Spelten²,

Konopka³

et al. 2014

Atmos. Chem. Phys.

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Abstract. An evaluation of water vapor in the upper troposphere and lower stratosphere (UTLS) of the ERA-Interim, the global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), is presented. Water vapor measurements are derived from the Fast In situ Stratospheric Hygrometer (FISH) during a large set of airborne measurement campaigns from 2001 to 2011 in the tropics, midlatitudes and polar regions, covering isentropic layers from 300 to 400 K (5-18 km).The comparison shows around 87 % of the reanalysis data are within a factor of 2 of the FISH water vapor measurements and around 30 % have a nearly perfect agreement with an over-and underestimation lower than 10 %. Nevertheless, strong over-and underestimations can occur both in the UT and LS, in particularly in the extratropical LS and in the tropical UT, where severe over-and underestimations up to 10 times can occur.The analysis data from the evolving ECMWF operational system is also evaluated, and the FISH measurements are divided into time periods representing different cycles of the Integrated Forecast System (IFS). The agreement with FISH improves over the time, in particular when comparing water vapor fields for time periods before 2004 and after 2010. It appears that influences of tropical tropospheric and extratropical UTLS processes, e.g., convective and quasiisentropic exchange processes, are particularly challenging for the simulation of the UTLS water vapor distribution. Both the reanalysis and operational analysis data show the tendency of an overestimation of low water vapor mixing ratio ( 10 ppmv) in the LS and underestimation of high water vapor mixing ratio ( 300 ppmv) in the UT.

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“…However, supersaturated regions are shallow and narrow and, hence, may not be resolved by the discrete humidity field on a finite grid. Moreover, subgrid scale variability could cause local supersaturation in a grid cell that is subsaturated on average (Lamquin et al, 2009). Hence, the critical value RHi c is usually taken different and below 100 % in NWP models.…”

Section: Numerical Weather Prediction Inputmentioning

confidence: 99%

“…Since a few years, the ECMWF model allows for supersaturation in clear air which has been demonstrated useful for this purpose (Tompkins et al, 2007;Rädel and Shine, 2007;Haywood et al, 2009;Lamquin et al, 2009Lamquin et al, , 2012. The model assumes that ice forms in a fraction of a grid cell when the supersaturation reaches the limit for homogeneous ice nucleation (Koop et al, 2000), typically of the order 150 %.…”

Section: Numerical Weather Prediction Inputmentioning

confidence: 99%

A contrail cirrus prediction model

2012

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Abstract.A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP). This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrailcirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.

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Evaluation of upper tropospheric humidity forecasts from ECMWF using AIRS and CALIPSO data

Cited by 29 publications

References 38 publications

An approach to build an event set of European windstorms based on ECMWF EPS

An approach to build an event set of European windstorms based on ECMWF EPS

Comparison of Fast In situ Stratospheric Hygrometer (FISH) measurements of water vapor in the upper troposphere and lower stratosphere (UTLS) with ECMWF (re)analysis data

A contrail cirrus prediction model

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