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Canada Archives Canada Published Heritage Direction Du Branch Patrimoine De I'edition A Procedure to Convert Total Column Ozone Data to Numerical Weather Prediction Model Initializing Fields, and its Validation via Simulations of the 24-25 January 2000 East Coast Snowstorm By Dorothy A. Durnford Department of Atmospheric and Oceanic Sciences McGill University Montreal Submitted August 2007 A thesis submitted to McGill University in partial fulfilment of the requirements of the degree of Doctor of Philosophy. © Dorothy Alexandra Durnford 2007 Library and Bibliotheque et 1*1 Archives Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-50811-4 Our file Notre reference ISBN: 978-0-494-50811-4 NOTICE: AVIS: The author has granted a non­ L'auteur a accorde une licence non exclusive exclusive license allowing Library permettant a la Bibliotheque et Archives and Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Plntemet, prefer, telecommunication or on the Internet, distribuer et vendre des theses partout dans loan, distribute and sell theses le monde, a des fins commerciales ou autres, worldwide, for commercial or non­ sur support microforme, papier, electronique commercial purposes, in microform, et/ou autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in et des droits moraux qui protege cette these. this thesis. Neither the thesis Ni la these ni des extraits substantiels de nor substantial extracts from it celle-ci ne doivent etre imprimes ou autrement may be printed or otherwise reproduits sans son autorisation. reproduced without the author's permission. In compliance with the Canadian Conformement a la loi canadienne Privacy Act some supporting sur la protection de la vie privee, forms may have been removed quelques formulaires secondaires from this thesis. ont ete enleves de cette these. While these forms may be included Bien que ces formulaires in the document page count, aient inclus dans la pagination, their removal does not represent il n'y aura aucun contenu manquant. any loss of content from the thesis. Canada This page is left intentionally blank. Preliminaries Abstract Satellites provide uniform data coverage globally. Thus, their data have the potential to reduce analysis errors in data sparse areas significantly, thereby improving numerical weather prediction (NWP) model forecasts. We describe a previously-used methodology to generate NWP model initial conditions (ICs) from satellite total column ozone data based on three principal steps: 1) convert a chemical total column ozone field to a dynamical mean potential vorticity (MPV) field via linear regression, 2) convert the 2D MPV field to a 3D potential vorticity (PV) field via vertical mapping onto average PV profiles, 3) invert the 3D PV field to obtain model-initializing height, temperature and wind fields in the mid and upper troposphere. Our contribution to the discipline has been to increase significantly the overall accuracy of the process through a substantial reworking of the details of this previous version. For instance, in recognition of the fact that total column ozone ridges tend to be less reliable than troughs, the MPV field that is converted to a 3D PV field in the second step is a synthesis of ozone-derived MPV troughs and analysis MPV ridges. We also adjust the vertical mapping procedure of the second step so that the MPV field converts to a more realistic 3D PV field; unrealistic PV features appearing strongly at upper levels and decaying with decreasing altitude are no longer generated. As a result of these and other novel procedures, the previously-described conversion procedure produces a more realistic set of model upper-level initializing fields. Using the 24-25 January 2000 east coast snowstorm as an example, we use the developed methodology to initialize the Mesoscale Compressible Community model (MC2). We find that ozone-influenced upper-level initializing fields improve the quantitative precipitation forecast for two of three (re)analyses. Furthermore, our best forecast of all utilizes ozone-influenced upper-level initializing fields. Finally, this novel procedure gives a quantitative precipitation forecast that is superior to an ozone-influenced four dimensional variational assimilation forecast of the same case. The methodology presented, which generates NWP model ICs from total column ozone data, may be useful for the forecasting of weather systems originating in data sparse areas. i Preliminaries Resume Les donnees meteorologiques acquises par satellite ont une resolution globale uniforme. Elles peuvent ainsi etre utilisees pour ameliorer les predictions par modele numerique (MN), en particulier, dans les regions ayant peu de stations d'observations meteorologiques. Nous decrirons une methodologie qui a deja ete presentee, qui produit des conditions initiales (CI) utilisables par les modeles numeriques. Cette methodologie utilise des donnees obtenues par satellite qui mesurent la quantite totale d'ozone dans une colonne verticale atmospherique. Ces CI sont obtenues en trois etapes. Premierement, un champ de la quantite d'ozone totale (un champ chimique) est converti en un champ dynamique de tourbillon potentiel moyen (TPM) par regression lineaire. Deuxiemement, le champ en deux dimensions de TPM est converti en un champ de trois dimensions de tourbillon potentiel (TP) par regression verticale basee sur les profils moyens de TP. Troisiemement, le dernier champ de TP est inverse afin d'obtenir les CI du MN, qui consistent de champs d'altitude, de temperature et de vent a la mi-troposphere et aux niveaux superieurs tropospheriques. Nous avons augmente la precision du processus d'une maniere significative en raffinant substantiellement les details de cette version anterieure, ce qui constitue notre contribution scientifique. Par exemple, comme les cretes d'ozone totale sont souvent moins fiables que les creux, le champ de TPM que nous convertissons en un champ de TP de trois dimensions pendant la deuxieme etape est une synthese des creux de TPM provenant d'ozone totale avec des cretes de TPM analysees. De plus, la regression verticale de la deuxieme etape est reglee afin de ne plus convertir des anomalies du champ de TMP en des anomalies de TP non realistes qui sont exagerees aux niveaux superieurs et qui diminuent avec 1'altitude. La methodologie de conversion mentionnee auparavant produit des CI de MN de niveaux superieurs qui sont plus realistes avec l'addition de ces processus et d'autres processus originaux. En utilisant la tempete du 24-25 Janvier 2000, qui est associee a d'importantes accumulations de neige sur la cote est americaine, nous initialisons le Mesoscale Compressible Community Model (MC2) avec les CI produits par la methodologie developpee. Nous trouvons que les CI influencees par l'ozone sur les niveaux eleves ameliorent la prevision de precipitation quantitative pour deux des trois (re)analyses. De plus, la meilleure prevision utilise les CI influencees par l'ozone sur les niveaux eleves. Finalement, cette methodologie originale produit une prevision de precipitation quantitative qui est superieure a une prevision influencee par l'ozone de la meme tempete qui utilisait l'assimilation variationnelle en quatre dimensions. La methodologie presentee, qui produit des CI de MN en utilisant les donnees de la quantite d'ozone totale, pourrait etre utile pour les previsions associees aux systemes meteorologiques qui proviennent des regions caracterisees par un manque de donnees. ii Preliminaries Statement of Originality To our knowledge, the following aspects of this thesis are original: 1. Previously, ozone-derived fields, which are valid near local noon, were interpolated to the chosen universal time after both the performance of the total column ozone/Mean Potential Vorticity (MPV) regression and the conversion of the two-dimensional (2D) MPV field to a three-dimensional (3D) Potential Vorticity (PV) field (see Davis et al. 1999). This system is undesirable for two reasons: 1) the regression's ozone and MPV fields are valid at different times, and are, therefore, spatially misaligned, which reduces the accuracy of the regression, and 2) since pressure level winds are used as the advecting agent in the temporal interpolation of the 3D PV field, and since winds at different levels vary in strength and direction, the vertical alignment of PV features created by the vertical mapping of the MPV field onto carefully constructed average PV profiles is distorted by the temporal interpolation. The presented methodology addresses both of these issues by temporally interpolating the total column ozone field itself. The regression's fields are then spatially aligned, which increases its accuracy. Furthermore, the integrity of the 3D PV field's vertical alignments is preserved as pressure level winds no longer operate on this field. This advantageous temporal interpolation of the total column ozone field is made possible by our use of analysis dynamic tropopause winds as the advecting agent, which is appropriate owing to the fact that the majority of the ozone molecules contributing to the total column ozone field reside just above the tropopause (Salby and Callaghan 1993). No mention
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