Verification against observations EXP: RCR71 RCR71T

Size: px
Start display at page:

Download "Verification against observations EXP: RCR71 RCR71T"

Transcription

1 Testof enhancedsoiltypedetermination in Kai Sattler Danish Meteorological Institute H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

2 a medium soil type with medium soil water capabilities. see experiment showed an improvement of Tm by to Introduction&Motivation HIRLAM climate generation includes processing of type (Bringfelt et al. 99), and the data base it refers soil One reason for this is that the three classes are good repe- of the soil characteristics. sand () and clay sentatives represent two extremes, whereas loam () represents () medium. is taken from the FAO-UNESCO soil database (FAO- to 987). This soil data classifies soil types into UNESCO, categories: the limitations of the implemented soil type remapping However, became clear some years ago during spring time sand. loam. loam & clay 6. peat 7. the western part of Denmark, when HIRLAM's m temperature in forecasts where found to grow too much during clay. sand & loam. ice 8. rock 9. compared to the observed values. daytime significant contribution to this effect was found to come A. sand & clay. missing data the lack of soil water content, which in turn was found from be connected to the definition of the soil type in the low to ISBA surface scheme in HIRLAM, however, does make use of these categories. Instead the ISBA not sub-surface tile of the HIRLAM grid, e.g. soil vegetation initialization during a cold start depends strongly moisture code for the climate files (steered by script preparation includes a remapping of the FAO soil types Preps_ISBA) the underlying soil type. on large part of western Denmark (Jutland) was hereby A classes, which are a sub-set of the ISBA soil types to 996, table A.). three soili types are: (Bringfelt to be classified by soil type sand. Even though this found type occurs at coastal locations, it cannot be seen as a soil sand. loam. soil type over the area. FAO soil type data base major not supply these details. does clay. make up the sub-surface soil type soili used in y (Bringfelt 996, table A.). representation HIRLAM snow surface (SN) is hereby not used in recent HIRLAM of experiment was then performed, where the soil type An set to loam instead of sand, in order to make HIRLAM was versions. though the remapping of the soil types and reduction Even only three categories is a significant simplification, the to has worked reasonably well. proceduce locally in Jutland. A quick fix was then applied in degrees DMI-HIRLAM. operational H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

3 Refiningsoil typedetermination F A O s o il ty p e,7,6 8 9 T ile n o v e g e ta tio n the issue of soil type definition for HIRLAM ISBA Recently was taken up again, when extreme surface tem- scheme were observed at the coast of Greenland. Even peratures these problems had other causes and were not though v e g i = 8 ( d e s e r t) v e g i = ( ic e ) they revealed a code bug concerning the no vegetation related, sub-surface tile. As a consequence, the potential T ile lo w b e g e ta tio n v e g i = ( c r o p ) of soil type definitions in the other two subsurface insufficiencies tiles low vegetation and forest were discussed. v e g i = ( s h o r t g r a s s ) v e g i = 7 ( ta ll g r a s s ) v e g i = 9 ( tu n d r a ) v e g i = ( ir r ig a te d c r o p ) discussions took up the idea to refine the soil type se by utilizing the sub-surface type vegi in addi- determination to the FAO soil type not only under sub-surface tile no tion but also under low vegetation and forest (As vegetation, v e g i = ( s e m i- d e s e r t) v e g i = ( b o g /m a r s h ) v e g i = 6 ( e v e r g r e e n s h r u b ) A. in Bringfelt (996) shows, vegi has been utilized Table tile, but not in tiles and ). in v e g i = 7 ( d e c id u o u s s h r u b ) T ile fo re s t combination of using vegi and FAO soil type has potential to refine the ISBA soil type determination, the v e g i = ( e v e r g r e e n n e e d le tr e e ) v e g i = ( d e c id u o u s n e e d le tr e e ) v e g i = ( d e c id u o u s b r o a d le a f tr e e ) the vegetation type may give an indication on the because soil type. This way the crude information on soil underlying v e g i = 6 ( e v e r g r e e n b r o a d le a f tr e e ) v e g i = 8 ( m ix e d w o o d la n d ) in the FAO data can be enhanced by making use of type about the vegetation. information v e g i = 9 ( fo r e s t/fie ld s ) new mapping of FAO soil type and vegi into ISBA subsurface soil type is formulated in the list to the right, difference between the current and the new ISBA type determination in HIRLAM can be seen from the soil each of the three sub-surface tiles no vegetation (), low for () and forest (): vegetation pictures below. H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

4 current new H ir la m A ll S ta ff M e e tin g 8 th A la d in W o r k s h o p 7 - A p r il 8, B r u s s e ls

5 scores Overall impact of the refinement of ISBA soil type deter- Impact onsurfaceparameters Verification against observations EXP: RCR7 RCR7T Time: 7-78 Domain: EWG Forecast from soili was tested in two experiments. first mination made use of the soil types as in the current experiment system, and the second one used the newly HIRLAM soil types as described above. defined Both experiments were run over the following three periods:. 7 to to 7-- Mean and RMS error (hpa) Mean sea level pressure Mean and RMS error (K) -metre temperature. 7-6 to 7-7 first period is to represent winter conditions, and the period includes shifting weather condition, which second sunny high pressure situations over Europe. include period contains a summer period with many thunder- third storms. experiments are based on HIRLAM trunk version as of Both [67], still including the fix of changeset [69]. changeset experiments were configured to run on the RCR-7. and using DVAR analysis. Else default specifications domain, were used. standard verification was applied to the experiment HIRLAM runs. Overall impact of the soili refinement on surface MSLP, Tm, RHm and Wm is shown in the parameters figures (EWGLAM station list). following Mean and RMS error (m/s) metre wind speed Mean and RMS error (%) - -metre relative humidity H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

6 Verification against observations EXP: RCR7 RCR7T Time: 7-7 Domain: EWG Forecast from Verification against observations EXP: RCR7 RCR7T Time: Domain: EWG Forecast from Impact onsurfaceparameters Mean and RMS error (hpa) Mean sea level pressure Mean and RMS error (K) -metre temperature Mean and RMS error (hpa) Mean sea level pressure Mean and RMS error (K) -metre temperature Mean and RMS error (m/s) metre wind speed Mean and RMS error (%) - -metre relative humidity Mean and RMS error (m/s) metre wind speed Mean and RMS error (%) - -metre relative humidity the figures above show the impact of the refined determination As of soili on surface parameters is very small. these tendencies seem to be rather counter-productive, RHm, however. re is no visible impact on m wind definitions have slight tendency to higher m humidity, new in accordance to this, a slight tendency to lower m and For mean sea level pressure, a very small improvement speed. of the negative bias in the April period is visible (upper temerature. When considering the model bias for Tm and left figure of the left panel on this sheet). H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

7 series Time look at the time evolvement of the verification scores A Impact onsurfaceparameters the slight impact almost at all times. Respective confirms are shown for the m dew point to the right and figures below (bias and rms). further dew point parameter experiences the biggest influ- but it a very small one. ence, th still th is a short period around the 7 and 8 of is exception An 7, where the refined soili settings have a February postitive impact on the RMS of the dew point (see visible lower figure to the right. period between 6 th and th of February was characterized by a warming over 9 European continent, especially the eastern and some the the northern parts. following two maps of metre of illustrate this: temperature m te m p e ra tu re a n d m e a n s e a le v e l p re s s u r e a t 6 th a n d 9 th F e b r u a r y 7 H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

8 Impact onsurfaceparameters H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

9 distribution Spatial verification scores of the surface parameters MSLP, the curent soili settings in HIRLAM used on the left hand side of each panel respec- shown tively RCR7T. Impact onsurfaceparameters figures show that small local differences occur, usually with improvements in one region and deterioration at RHm and Wm compare very similarly between the Tm, experiments, when regarding the stationwise scores two another location at the same time. the two HIRLAM experiments. following figures from the distributions of bias (panels to the left) and rms show is interesting to notice, still, that differences also occur It the open sea. This may indicate that the differences over (panels to the right) valid for 8h forecast length. scores shown are: experiments surface parameter scores induced by the change in soili of over land tiles have propagated through the model fields RCR7. domain within the time period of the forecast range. the effect of changing soili does not remain a local So but it spreads over the model domain within the usual one, range. It can also be expected that the effect has forecast impact on the daily cycle in an operational setup of (small) the refined soili settings used on the right hand side of each panel respec- shown tively HIRLAM. Each row in a panel refers to one of the three periods. H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

10 Impact onsurfaceparameters(meansealevel pressure) H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

11 Impactonsurfaceparameters(mtemperature) H ir la m A ll S ta ff M e e tin g 8 th A la d in W o r k s h o p 7 - A p r il 8, B r u s s e ls

12 Impactonsurfaceparameters(mdewpointtemperature) H ir la m A ll S ta ff M e e tin g 8 th A la d in W o r k s h o p 7 - A p r il 8, B r u s s e ls

13 Impact onsurfaceparameters(mwindspeed) H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

14 SummaryandConclusions work tries to investigate the effect of changing the This soil type fields (soili) in HIRLAM on the verification ISBA show that refining the soili determination in Results has a small effect on the vefification scores. HIRLAM of surface parameters mean sea level pressure, m scores m humidity and m wind speed. temperature, effect consists mainly in the tendency towards slightly This humidity and slightly decreased temperature increased new soili fields are based on a refined determination the soil type. This refinement takes both the FAO soil of to the surface. close cases where the temperature bias of HIRLAM is nega- In or where humidity bias is positive, the refinement of tive, has a rather negative influence. soili as well as the sub-surface type vegi into account when type one of the three ISBA soil types for a certain land defining the same way, in case of positive temperature bias, or In humidity bias in HIRLAM, the soili refinement has negative of the HIRLAM grid. This methodology has been in use tile the sub-grid surface tile (no vegetation land) since the for slight positive effect. a spring case also indicates a slight improvement of scheme was introduced into HIRLAM, but it was never ISBA for the sub-grid surface tiles (low vegetation land) applied sea level pressure bias. mean differences in scores occur, as well as there are Local and (forest). differences in bias scores, so the effect of the soili local changes from region to region. An improvement refinement refined methodology was compared to the current in HIRLAM by running HIRLAM experiments for procedure verification scores for surface parameters due to soili of can therefore hardly be stated in general. refinement periods of several weeks duration each. periods three winter season, spring and summer conditions. represent single case within the first comparison period indicates, A an improved rms in dew point during some days however, comparison comprises standard verification scores for surface parameters mentioned above. the of the winter period. H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

15 References B., Gustafsson N., Vilmusenaho P., Jarvenoja Bringfelt S. 99: Updating the HIRLAM physiography and climate data base. HIRLAM Tech. Rep., 9. Bringfelt B. 996: Tests of a new Land Surface Treatment in HIRLAM. HIRLAM Tech. Rep.,. 987: Soils of the World. Food and Agriculture Organization and United Nations Educational, FAO-UNESCO and Cultural Organization. Technical Report, Elsevier Science Publishing Co. Inc., New York. Scientific H i r l a m A l l S t a f f M e e t i n g 8 t h A l a d i n W o r k s h o p 7 - A p r i l 8, B r u s s e l s

Simo Järvenoja s inheritance

Simo Järvenoja s inheritance Long-term verification of HIRLAM at FMI Simo Järvenoja s inheritance Kalle Eerola Finnish Meteorological Institute Contents Introduction Simo Järvenoja s inheritance, part 1 Simo Järvenoja s inheritance,

More information

2 1-D Experiments, near surface output

2 1-D Experiments, near surface output Tuning CBR A.B.C. Tijm 1 Introduction The pre 6.2 reference Hirlam versions have a positive bias in the wind direction under stable conditions (night and winter conditions), accompanied by too strong near

More information

Application and verification of ECMWF products 2017

Application and verification of ECMWF products 2017 Application and verification of ECMWF products 2017 Finnish Meteorological Institute compiled by Weather and Safety Centre with help of several experts 1. Summary of major highlights FMI s forecasts are

More information

Assimilation of Globsnow data into HIRLAM. Mostamandy Suleiman Sodankyla August 2011

Assimilation of Globsnow data into HIRLAM. Mostamandy Suleiman Sodankyla August 2011 Assimilation of Globsnow data into HIRLAM Mostamandy Suleiman Sodankyla August 2011 Motivation Small number of observations (especially in eastern Europe and Russia) 00 cm of snow problem Non-uniform in

More information

Validation of HARMONIE 36h1.3

Validation of HARMONIE 36h1.3 Validation of HARMONIE 36h1.3 Xiaohua Yang, Ulf Andrae, Trygve Aspelien, Ole Vignes, Lisa Bengtsson, Sami Niemela, Bjarne S. Andersen, Wim de Rooy, Shiyu Zhuang, Magnus Lindskog, Niels W. Nielsen Introduction

More information

Assimilating AMSU-A over Sea Ice in HIRLAM 3D-Var

Assimilating AMSU-A over Sea Ice in HIRLAM 3D-Var Abstract Assimilating AMSU-A over Sea Ice in HIRLAM 3D-Var Vibeke W. Thyness 1, Leif Toudal Pedersen 2, Harald Schyberg 1, Frank T. Tveter 1 1 Norwegian Meteorological Institute (met.no) Box 43 Blindern,

More information

Road Weather Modelling System: Verification for Road Weather Season

Road Weather Modelling System: Verification for Road Weather Season Road Weather Modelling System: Verification for 2009-2010 Road Weather Season Claus Petersen, Alexander Mahura, Bent Sass Copenhagen 2010 www.dmi.dk/dmi/tr10-12.pdf page 1 of 20 Colophon Serial title:

More information

but 2012 was dry Most farmers pulled in a crop

but 2012 was dry Most farmers pulled in a crop After a winter that wasn t, conditions late in the year pointed to a return to normal snow and cold conditions Most farmers pulled in a crop but 2012 was dry b y M i k e Wr o b l e w s k i, w e a t h e

More information

Application and verification of ECMWF products 2012

Application and verification of ECMWF products 2012 Application and verification of ECMWF products 2012 Met Eireann, Glasnevin Hill, Dublin 9, Ireland. J.Hamilton 1. Summary of major highlights The verification of ECMWF products has continued as in previous

More information

Technical Report Road Weather Modelling System: Verification for Road Weather Season. Claus Petersen, Alexander Mahura, Bent Sass

Technical Report Road Weather Modelling System: Verification for Road Weather Season. Claus Petersen, Alexander Mahura, Bent Sass Technical Report 09-10 Road Weather Modelling System: Verification for 2008-2009 Road Weather Season Claus Petersen, Alexander Mahura, Bent Sass www.dmi.dk/dmi/tr09-10 Copenhagen 2009 page 1 of 20 Colophon

More information

Road Weather Modelling System: Verification for Road Weather Season

Road Weather Modelling System: Verification for Road Weather Season Road Weather Modelling System: Verification for 2010-2011 Road Weather Season Claus Petersen, Alexander Mahura, Bent Sass Copenhagen 2011 www.dmi.dk/dmi/tr11-19.pdf page 1 of 28 Colophon Serial title:

More information

CLIMATE. UNIT TWO March 2019

CLIMATE. UNIT TWO March 2019 CLIMATE UNIT TWO March 2019 OUTCOME 9.2.1Demonstrate an understanding of the basic features of Canada s landscape and climate. identify and locate major climatic regions of Canada explain the characteristics

More information

Studies on adaptation capacity of Carpathian ecosystems/landscape to climate change

Studies on adaptation capacity of Carpathian ecosystems/landscape to climate change ` Studies on adaptation capacity of Carpathian ecosystems/landscape to climate change Science for the Carpathians CARPATHIAN CONVENTION COP5 Lillafüred, 10.10.2017-12.10.2017 Marcel Mîndrescu, Anita Bokwa

More information

Application and verification of ECMWF products 2016

Application and verification of ECMWF products 2016 Application and verification of ECMWF products 2016 RHMS of Serbia 1 Summary of major highlights ECMWF forecast products became the backbone in operational work during last several years. Starting from

More information

2013 ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Cat Response

2013 ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Cat Response 2013 ATLANTIC HURRICANE SEASON OUTLOOK June 2013 - RMS Cat Response Season Outlook At the start of the 2013 Atlantic hurricane season, which officially runs from June 1 to November 30, seasonal forecasts

More information

The ECMWF Extended range forecasts

The ECMWF Extended range forecasts The ECMWF Extended range forecasts Laura.Ferranti@ecmwf.int ECMWF, Reading, U.K. Slide 1 TC January 2014 Slide 1 The operational forecasting system l High resolution forecast: twice per day 16 km 91-level,

More information

Our climate system is based on the location of hot and cold air mass regions and the atmospheric circulation created by trade winds and westerlies.

Our climate system is based on the location of hot and cold air mass regions and the atmospheric circulation created by trade winds and westerlies. CLIMATE REGIONS Have you ever wondered why one area of the world is a desert, another a grassland, and another a rainforest? Or have you wondered why are there different types of forests and deserts with

More information

Validation of 2-meters temperature forecast at cold observed conditions by different NWP models

Validation of 2-meters temperature forecast at cold observed conditions by different NWP models Validation of 2-meters temperature forecast at cold observed conditions by different NWP models Evgeny Atlaskin Finnish Meteorological Institute / Russian State Hydrometeorological University OUTLINE Background

More information

Operational MRCC Tools Useful and Usable by the National Weather Service

Operational MRCC Tools Useful and Usable by the National Weather Service Operational MRCC Tools Useful and Usable by the National Weather Service Vegetation Impact Program (VIP): Frost / Freeze Project Beth Hall Accumulated Winter Season Severity Index (AWSSI) Steve Hilberg

More information

1 What Is Climate? TAKE A LOOK 2. Explain Why do areas near the equator tend to have high temperatures?

1 What Is Climate? TAKE A LOOK 2. Explain Why do areas near the equator tend to have high temperatures? CHAPTER 17 1 What Is Climate? SECTION Climate BEFORE YOU READ After you read this section, you should be able to answer these questions: What is climate? What factors affect climate? How do climates differ

More information

Road Weather Modelling System: Verification for Road Weather Season

Road Weather Modelling System: Verification for Road Weather Season Road Weather Modelling System: Verification for 2007-2008 Road Weather Season Claus Petersen, Alexander Mahura, Bent Sass, Torben Pedersen Copenhagen 2008 www.dmi.dk/dmi/tr08-09 page 1 of 14 Colophon Serial

More information

Use and impact of ATOVS in the DMI-HIRLAM regional weather model

Use and impact of ATOVS in the DMI-HIRLAM regional weather model Use and impact of ATOVS in the DMI-HIRLAM regional weather model J. Grove-Rasmussen B. Amstrup and K.S. Mogensen E-mail: jgr@dmi.dk, bja@dmi.dk and ksm@dmi.dk Danish Meteorological Institute Lyngbyvej,

More information

JMA s Seasonal Prediction of South Asian Climate for Summer 2018

JMA s Seasonal Prediction of South Asian Climate for Summer 2018 JMA s Seasonal Prediction of South Asian Climate for Summer 2018 Atsushi Minami Tokyo Climate Center (TCC) Japan Meteorological Agency (JMA) Contents Outline of JMA s Seasonal Ensemble Prediction System

More information

TC/PR/RB Lecture 3 - Simulation of Random Model Errors

TC/PR/RB Lecture 3 - Simulation of Random Model Errors TC/PR/RB Lecture 3 - Simulation of Random Model Errors Roberto Buizza (buizza@ecmwf.int) European Centre for Medium-Range Weather Forecasts http://www.ecmwf.int Roberto Buizza (buizza@ecmwf.int) 1 ECMWF

More information

Plan for operational nowcasting system implementation in Pulkovo airport (St. Petersburg, Russia)

Plan for operational nowcasting system implementation in Pulkovo airport (St. Petersburg, Russia) Plan for operational nowcasting system implementation in Pulkovo airport (St. Petersburg, Russia) Pulkovo airport (St. Petersburg, Russia) is one of the biggest airports in the Russian Federation (150

More information

Bugs in JRA-55 snow depth analysis

Bugs in JRA-55 snow depth analysis 14 December 2015 Climate Prediction Division, Japan Meteorological Agency Bugs in JRA-55 snow depth analysis Bugs were recently found in the snow depth analysis (i.e., the snow depth data generation process)

More information

S e a s o n a l F o r e c a s t i n g f o r t h e E u r o p e a n e n e r g y s e c t o r

S e a s o n a l F o r e c a s t i n g f o r t h e E u r o p e a n e n e r g y s e c t o r S e a s o n a l F o r e c a s t i n g f o r t h e E u r o p e a n e n e r g y s e c t o r C3S European Climatic Energy Mixes (ECEM) Webinar 18 th Oct 2017 Philip Bett, Met Office Hadley Centre S e a s

More information

Atmospheric patterns for heavy rain events in the Balearic Islands

Atmospheric patterns for heavy rain events in the Balearic Islands Adv. Geosci., 12, 27 32, 2007 Author(s) 2007. This work is licensed under a Creative Commons License. Advances in Geosciences Atmospheric patterns for heavy rain events in the Balearic Islands A. Lana,

More information

Weather and Climate 1. Elements of the weather

Weather and Climate 1. Elements of the weather Weather and Climate 1 affect = to have an effect on, influence, change altitude = the height of a place above the sea axis = the line around which an object rotates certain = special consist of = to be

More information

Mesoscale meteorological models. Claire L. Vincent, Caroline Draxl and Joakim R. Nielsen

Mesoscale meteorological models. Claire L. Vincent, Caroline Draxl and Joakim R. Nielsen Mesoscale meteorological models Claire L. Vincent, Caroline Draxl and Joakim R. Nielsen Outline Mesoscale and synoptic scale meteorology Meteorological models Dynamics Parametrizations and interactions

More information

Application and verification of ECMWF products 2016

Application and verification of ECMWF products 2016 Application and verification of ECMWF products 2016 Icelandic Meteorological Office (www.vedur.is) Bolli Pálmason and Guðrún Nína Petersen 1. Summary of major highlights Medium range weather forecasts

More information

Application and verification of ECMWF products 2009

Application and verification of ECMWF products 2009 Application and verification of ECMWF products 2009 Danish Meteorological Institute Author: Søren E. Olufsen, Deputy Director of Forecasting Services Department and Erik Hansen, forecaster M.Sc. 1. Summary

More information

2007: The Netherlands in a drought again (2 May 2007)

2007: The Netherlands in a drought again (2 May 2007) 2007: The Netherlands in a drought again (2 May 2007) Henny A.J. van Lanen, Wageningen University, the Netherlands (henny.vanlanen@wur.nl) Like in June and July 2006, the Netherlands is again facing a

More information

P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES. Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski #

P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES. Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski # P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski # *Cooperative Institute for Meteorological Satellite Studies, University of

More information

El Niño / Southern Oscillation

El Niño / Southern Oscillation El Niño / Southern Oscillation Student Packet 2 Use contents of this packet as you feel appropriate. You are free to copy and use any of the material in this lesson plan. Packet Contents Introduction on

More information

Regional Climate Simulations with WRF Model

Regional Climate Simulations with WRF Model WDS'3 Proceedings of Contributed Papers, Part III, 8 84, 23. ISBN 978-8-737852-8 MATFYZPRESS Regional Climate Simulations with WRF Model J. Karlický Charles University in Prague, Faculty of Mathematics

More information

Claus Petersen* and Bent H. Sass* Danish Meteorological Institute Copenhagen, Denmark

Claus Petersen* and Bent H. Sass* Danish Meteorological Institute Copenhagen, Denmark 6.8 Improving of road weather forecasting by using high resolution satellite data Claus Petersen* and Bent H. Sass* Danish Meteorological Institute Copenhagen, Denmark. INTRODUCTION Observations of high

More information

Polar Portal Season Report 2016

Polar Portal Season Report 2016 Polar Portal Season Report 2016 Less ice both on land and at sea This year s report is the fourth since the Polar Portal was launched, and as an introduction, we have chosen to take a look at the trends

More information

MESOSCALE MODELLING OVER AREAS CONTAINING HEAT ISLANDS. Marke Hongisto Finnish Meteorological Institute, P.O.Box 503, Helsinki

MESOSCALE MODELLING OVER AREAS CONTAINING HEAT ISLANDS. Marke Hongisto Finnish Meteorological Institute, P.O.Box 503, Helsinki MESOSCALE MODELLING OVER AREAS CONTAINING HEAT ISLANDS Marke Hongisto Finnish Meteorological Institute, P.O.Box 503, 00101 Helsinki INTRODUCTION Urban heat islands have been suspected as being partially

More information

Annex I to Target Area Assessments

Annex I to Target Area Assessments Baltic Challenges and Chances for local and regional development generated by Climate Change Annex I to Target Area Assessments Climate Change Support Material (Climate Change Scenarios) SWEDEN September

More information

EWGLAM/SRNWP National presentation from DMI

EWGLAM/SRNWP National presentation from DMI EWGLAM/SRNWP 2013 National presentation from DMI Development of operational Harmonie at DMI Since Jan 2013 DMI updated HARMONIE-Denmark suite to CY37h1 with a 3h-RUC cycling and 57h forecast, 8 times a

More information

HIGH SPATIAL AND TEMPORAL RESOLUTION ATMOSPHERIC MOTION VECTORS GENERATION, ERROR CHARACTERIZATION AND ASSIMILATION

HIGH SPATIAL AND TEMPORAL RESOLUTION ATMOSPHERIC MOTION VECTORS GENERATION, ERROR CHARACTERIZATION AND ASSIMILATION HIGH SPATIAL AND TEMPORAL RESOLUTION ATMOSPHERIC MOTION VECTORS GENERATION, ERROR CHARACTERIZATION AND ASSIMILATION John Le Marshall Director, JCSDA 2004-2007 CAWCR 2007-2010 John Le Marshall 1,2, Rolf

More information

The benefits and developments in ensemble wind forecasting

The benefits and developments in ensemble wind forecasting The benefits and developments in ensemble wind forecasting Erik Andersson Slide 1 ECMWF European Centre for Medium-Range Weather Forecasts Slide 1 ECMWF s global forecasting system High resolution forecast

More information

Ganbat.B, Agro meteorology Section

Ganbat.B, Agro meteorology Section NATIONAL AGENCY FOR METEOROLOGY, HYDROLOGY AND ENVIRONMENT MONITORING OF MONGOLIA Ganbat.B, Agro meteorology Section OF INSTITUTE OF METEOROLOGY AND HYDROLOGY 2009 YEAR Location Climate Northern Asia,

More information

Technical Report DMI SYNOP AWS Summit. Data status March Ellen Vaarby Laursen. SYNOP weather station Summit.

Technical Report DMI SYNOP AWS Summit. Data status March Ellen Vaarby Laursen. SYNOP weather station Summit. 10-09 DMI SYNOP AWS 04416 Summit. Data status March 2010. Ellen Vaarby Laursen SYNOP weather station 04416 Summit Picture Taken: 2007:06:20 16:16:11 Picture Taken: 2009:07:09 08:22:51 Copenhagen 2010 www.dmi.dk/dmi/tr

More information

Application and verification of ECMWF products 2012

Application and verification of ECMWF products 2012 Application and verification of ECMWF products 2012 Instituto Português do Mar e da Atmosfera, I.P. (IPMA) 1. Summary of major highlights ECMWF products are used as the main source of data for operational

More information

Representing inland water bodies and coastal areas in global numerical weather prediction

Representing inland water bodies and coastal areas in global numerical weather prediction Representing inland water bodies and coastal areas in global numerical weather prediction Gianpaolo Balsamo, Anton Beljaars, Souhail Boussetta, Emanuel Dutra Outline: Introduction lake and land contrasts

More information

New soil physical properties implemented in the Unified Model

New soil physical properties implemented in the Unified Model New soil physical properties implemented in the Unified Model Imtiaz Dharssi 1, Pier Luigi Vidale 3, Anne Verhoef 3, Bruce Macpherson 1, Clive Jones 1 and Martin Best 2 1 Met Office (Exeter, UK) 2 Met

More information

WHAT CAN MAPS TELL US ABOUT THE GEOGRAPHY OF ANCIENT GREECE? MAP TYPE 1: CLIMATE MAPS

WHAT CAN MAPS TELL US ABOUT THE GEOGRAPHY OF ANCIENT GREECE? MAP TYPE 1: CLIMATE MAPS WHAT CAN MAPS TELL US ABOUT THE GEOGRAPHY OF ANCIENT GREECE? MAP TYPE 1: CLIMATE MAPS MAP TYPE 2: PHYSICAL AND/OR TOPOGRAPHICAL MAPS MAP TYPE 3: POLITICAL MAPS TYPE 4: RESOURCE & TRADE MAPS Descriptions

More information

Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia.

Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia. Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia. 1 Hiromitsu Kanno, 2 Hiroyuki Shimono, 3 Takeshi Sakurai, and 4 Taro Yamauchi 1 National Agricultural

More information

DMI Report Weather observations from Tórshavn, The Faroe Islands Observation data with description

DMI Report Weather observations from Tórshavn, The Faroe Islands Observation data with description DMI Report 17-09 Weather observations from Tórshavn, The Faroe Islands 1953-2016 - Observation data with description John Cappelen Copenhagen 2017 http://www.dmi.dk/laer-om/generelt/dmi-publikationer/

More information

A) usually less B) dark colored and rough D) light colored with a smooth surface A) transparency of the atmosphere D) rough, black surface

A) usually less B) dark colored and rough D) light colored with a smooth surface A) transparency of the atmosphere D) rough, black surface 1. Base your answer to the following question on the diagram below which shows two identical houses, A and B, in a city in North Carolina. One house was built on the east side of a factory, and the other

More information

25.1 Air Masses. Section 25.1 Objectives

25.1 Air Masses. Section 25.1 Objectives Section 25.1 Objectives Explain how an air mass forms. List the four main types of air masses. Describe how air masses affect the weather of North America. Air Masses 25.1 Air Masses Differences in air

More information

Meteorological information

Meteorological information Meteorological Meteorological information information for for locust locust monitoring monitoring & & control control locusts locusts & & systems systems meteorological meteorological data data solutions

More information

Global Atmospheric Circulation

Global Atmospheric Circulation Global Atmospheric Circulation Polar Climatology & Climate Variability Lecture 11 Nov. 22, 2010 Global Atmospheric Circulation Global Atmospheric Circulation Global Atmospheric Circulation The Polar Vortex

More information

COntinuous Mesoscale Ensemble Prediction DMI. Henrik Feddersen, Xiaohua Yang, Kai Sattler, Bent Hansen Sass

COntinuous Mesoscale Ensemble Prediction DMI. Henrik Feddersen, Xiaohua Yang, Kai Sattler, Bent Hansen Sass COntinuous Mesoscale Ensemble Prediction System @ DMI Henrik Feddersen, Xiaohua Yang, Kai Sattler, Bent Hansen Sass Why short-range ensemble forecasting? Quantify uncertainty Precipitation Cloud cover

More information

Assessment of the Noah LSM with Multi-parameterization Options (Noah-MP) within WRF

Assessment of the Noah LSM with Multi-parameterization Options (Noah-MP) within WRF Assessment of the Noah LSM with Multi-parameterization Options (Noah-MP) within WRF Michelle Harrold, Jamie Wolff, and Mei Xu National Center for Atmospheric Research Research Applications Laboratory and

More information

PRMS WHITE PAPER 2014 NORTH ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Event Response

PRMS WHITE PAPER 2014 NORTH ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Event Response PRMS WHITE PAPER 2014 NORTH ATLANTIC HURRICANE SEASON OUTLOOK June 2014 - RMS Event Response 2014 SEASON OUTLOOK The 2013 North Atlantic hurricane season saw the fewest hurricanes in the Atlantic Basin

More information

Meteo-France operational land surface analysis for NWP: current status and perspectives

Meteo-France operational land surface analysis for NWP: current status and perspectives Meteo-France operational land surface analysis for NWP: current status and perspectives Camille Birman, Jean-François Mahfouf, Yann Seity, Eric Bazile, Françoise Taillefer, Zied Sassi, Nadia Fourrié, Vincent

More information

Chapter outline. Reference 12/13/2016

Chapter outline. Reference 12/13/2016 Chapter 2. observation CC EST 5103 Climate Change Science Rezaul Karim Environmental Science & Technology Jessore University of science & Technology Chapter outline Temperature in the instrumental record

More information

4th Grade Social Studies First Nine Weeks

4th Grade Social Studies First Nine Weeks 4th Grade Social Studies First Nine Weeks Multiple Choice Identify the choice that best completes the statement or answers the question. 1 Name the mountains that are located in the eastern United States.

More information

Contributions to The State of Climate 2004 Recent Greenland climate variability and consequences to ice sheet mass balance

Contributions to The State of Climate 2004 Recent Greenland climate variability and consequences to ice sheet mass balance Contributions to The State of Climate 2004 Recent Greenland climate variability and consequences to ice sheet mass balance Jason E. Box AMS Committee on Polar Meteorology Byrd Polar Research Center, The

More information

Attribution of Estonian phyto-, ornitho- and ichtyophenological trends with parameters of changing climate

Attribution of Estonian phyto-, ornitho- and ichtyophenological trends with parameters of changing climate Attribution of Estonian phyto-, ornitho- and ichtyophenological trends with parameters of changing climate Rein Ahas*, Anto Aasa, Institute of Geography, University of Tartu, Vanemuise st 46, Tartu, 51014,

More information

Scatterometer winds in rapidly developing storms (SCARASTO) First experiments on data assimilation of scatterometer winds

Scatterometer winds in rapidly developing storms (SCARASTO) First experiments on data assimilation of scatterometer winds Scatterometer winds in rapidly developing storms (SCARASTO) First experiments on data assimilation of scatterometer winds Teresa Valkonen, EUMETSAT fellow Norwegian Meteorological Institute MET Norway,Oslo

More information

NIDIS Intermountain West Regional Drought Early Warning System February 7, 2017

NIDIS Intermountain West Regional Drought Early Warning System February 7, 2017 NIDIS Drought and Water Assessment NIDIS Intermountain West Regional Drought Early Warning System February 7, 2017 Precipitation The images above use daily precipitation statistics from NWS COOP, CoCoRaHS,

More information

Colorado CoCoRaHS. Colorado CoCoRaHS. Because Every Drop Counts! November 2014 Volume 2, Issue 11

Colorado CoCoRaHS. Colorado CoCoRaHS. Because Every Drop Counts! November 2014 Volume 2, Issue 11 U.S. PRECIPITATION (% OF AVERAGE) LOOKING BACK AT OCTOBER 2014 October was a fairly dry month for much of the nation with the exception of the Pacific Northwest, portions of New England and the Tennessee

More information

Numerical Weather Prediction at high latitudes. Nils Gustafsson, SMHI

Numerical Weather Prediction at high latitudes. Nils Gustafsson, SMHI Numerical Weather Prediction at high latitudes Nils Gustafsson, SMHI High latitude NWP - outline of talk The HIRLAM-A program The reference HIRLAM forecasting system Verification scores The Nordic temperature

More information

Ashraf S. Zakey The Egyptian Meteorological Autority

Ashraf S. Zakey The Egyptian Meteorological Autority Ashraf S. Zakey The Egyptian Meteorological Autority A new inter-regional climate outlook forum for the Mediterranean Region. Development and dissemination of a consensus-based seasonal climate outlook.

More information

The weather in Iceland 2012

The weather in Iceland 2012 The Icelandic Meteorological Office Climate summary 2012 published 9.1.2013 The weather in Iceland 2012 Climate summary Sunset in Reykjavík 24th April 2012 at 21:42. View towards west from the balcony

More information

Application and verification of ECMWF products at the Finnish Meteorological Institute

Application and verification of ECMWF products at the Finnish Meteorological Institute Application and verification of ECMWF products 2010 2011 at the Finnish Meteorological Institute by Juhana Hyrkkènen, Ari-Juhani Punkka, Henri Nyman and Janne Kauhanen 1. Summary of major highlights ECMWF

More information

2018 mid-winter ag weather update

2018 mid-winter ag weather update E-book Bryce Anderson s 2018 mid-winter ag weather update Table of contents Contributing weather patterns... 3 About the author An updated mid-winter forecast... 4 Early expectations for the growing season...

More information

Weather observations from Tórshavn, The Faroe Islands

Weather observations from Tórshavn, The Faroe Islands Weather observations from Tórshavn, The Faroe Islands 1953-2014 - Observation data with description John Cappelen Copenhagen 2015 http://www.dmi.dk/fileadmin/rapporter/tr/tr15-09 page 1 of 14 Colophon

More information

Verification of the Seasonal Forecast for the 2005/06 Winter

Verification of the Seasonal Forecast for the 2005/06 Winter Verification of the Seasonal Forecast for the 2005/06 Winter Shingo Yamada Tokyo Climate Center Japan Meteorological Agency 2006/11/02 7 th Joint Meeting on EAWM Contents 1. Verification of the Seasonal

More information

J8.4 TRENDS OF U.S. SNOWFALL AND SNOW COVER IN A WARMING WORLD,

J8.4 TRENDS OF U.S. SNOWFALL AND SNOW COVER IN A WARMING WORLD, J8.4 TRENDS OF U.S. SNOWFALL AND SNOW COVER IN A WARMING WORLD, 1948-2008 Richard R. Heim Jr. * NOAA National Climatic Data Center, Asheville, North Carolina 1. Introduction The Intergovernmental Panel

More information

WG5: Common Plot Reports

WG5: Common Plot Reports WG5: Common Plot Reports Dimitra Boucouvala & WG5 COSMO GM Parallel session, 7-10 Sept 2015, Wroclaw THE COSMO MODELS COSMO-RU7(RHM) COSMO-EU (DWD) COSMO-7 (MCH) COSMO-PL(IMGW) COSMO-ME (IT) COSMO-I7 (IT)

More information

CANARI summer problem. Antonio Stanešić and Stjepan Ivatek-Šahdan

CANARI summer problem. Antonio Stanešić and Stjepan Ivatek-Šahdan CANARI summer problem Antonio Stanešić and Stjepan Ivatek-Šahdan Introduction Description of problem Tests Results Summary & Questions Model setup ALADIN HR domain 8 km horizontal resolution 37 levels,

More information

Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system

Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system 2nd Workshop on Parameterization of Lakes in Numerical Weather Prediction and Climate Modelling Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system R. Salgado(1),

More information

Evaluation of a New Land Surface Model for JMA-GSM

Evaluation of a New Land Surface Model for JMA-GSM Evaluation of a New Land Surface Model for JMA-GSM using CEOP EOP-3 reference site dataset Masayuki Hirai Takuya Sakashita Takayuki Matsumura (Numerical Prediction Division, Japan Meteorological Agency)

More information

Climate Variables for Energy: WP2

Climate Variables for Energy: WP2 Climate Variables for Energy: WP2 Phil Jones CRU, UEA, Norwich, UK Within ECEM, WP2 provides climate data for numerous variables to feed into WP3, where ESCIIs will be used to produce energy-relevant series

More information

Application and verification of ECMWF products 2016

Application and verification of ECMWF products 2016 Application and verification of ECMWF products 2016 Met Eireann, Glasnevin Hill, Dublin 9, Ireland. J.Hamilton 1. Summary of major highlights The verification of ECMWF products has continued as in previous

More information

Application and verification of ECMWF products 2015

Application and verification of ECMWF products 2015 Application and verification of ECMWF products 2015 Hungarian Meteorological Service 1. Summary of major highlights The objective verification of ECMWF forecasts have been continued on all the time ranges

More information

Assimilation of satellite derived soil moisture for weather forecasting

Assimilation of satellite derived soil moisture for weather forecasting Assimilation of satellite derived soil moisture for weather forecasting www.cawcr.gov.au Imtiaz Dharssi and Peter Steinle February 2011 SMOS/SMAP workshop, Monash University Summary In preparation of the

More information

ONE-YEAR EXPERIMENT IN NUMERICAL PREDICTION OF MONTHLY MEAN TEMPERATURE IN THE ATMOSPHERE-OCEAN-CONTINENT SYSTEM

ONE-YEAR EXPERIMENT IN NUMERICAL PREDICTION OF MONTHLY MEAN TEMPERATURE IN THE ATMOSPHERE-OCEAN-CONTINENT SYSTEM 71 4 MONTHLY WEATHER REVIEW Vol. 96, No. 10 ONE-YEAR EXPERIMENT IN NUMERICAL PREDICTION OF MONTHLY MEAN TEMPERATURE IN THE ATMOSPHERE-OCEAN-CONTINENT SYSTEM JULIAN ADEM and WARREN J. JACOB Extended Forecast

More information

World Geography Chapter 3

World Geography Chapter 3 World Geography Chapter 3 Section 1 A. Introduction a. Weather b. Climate c. Both weather and climate are influenced by i. direct sunlight. ii. iii. iv. the features of the earth s surface. B. The Greenhouse

More information

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 23 April 2012

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 23 April 2012 ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 23 April 2012 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index

More information

By: J Malherbe, R Kuschke

By: J Malherbe, R Kuschke 2015-10-27 By: J Malherbe, R Kuschke Contents Summary...2 Overview of expected conditions over South Africa during the next few days...3 Significant weather events (27 October 2 November)...3 Conditions

More information

Seasonal Climate Watch January to May 2016

Seasonal Climate Watch January to May 2016 Seasonal Climate Watch January to May 2016 Date: Dec 17, 2015 1. Advisory Most models are showing the continuation of a strong El-Niño episode towards the latesummer season with the expectation to start

More information

Winter Storm of 15 December 2005 By Richard H. Grumm National Weather Service Office State College, PA 16803

Winter Storm of 15 December 2005 By Richard H. Grumm National Weather Service Office State College, PA 16803 Winter Storm of 15 December 2005 By Richard H. Grumm National Weather Service Office State College, PA 16803 1. INTRODUCTION A complex winter storm brought snow, sleet, and freezing rain to central Pennsylvania.

More information

On the Prediction of Road Conditions by a Combined Road Layer-Atmospheric

On the Prediction of Road Conditions by a Combined Road Layer-Atmospheric TRANSPORTATION RESEARCH RECORD 1387 231 On the Prediction of Road Conditions by a Combined Road Layer-Atmospheric Model in Winter HENRIK VOLDBORG An effective forecasting system for slippery road warnings

More information

1 What Is Climate? TAKE A LOOK 2. Explain Why do areas near the equator tend to have high temperatures?

1 What Is Climate? TAKE A LOOK 2. Explain Why do areas near the equator tend to have high temperatures? CHAPTER 17 1 What Is Climate? SECTION Climate BEFORE YOU READ After you read this section, you should be able to answer these questions: What is climate? What factors affect climate? How do climates differ

More information

Application and verification of the ECMWF products Report 2007

Application and verification of the ECMWF products Report 2007 Application and verification of the ECMWF products Report 2007 National Meteorological Administration Romania 1. Summary of major highlights The medium range forecast activity within the National Meteorological

More information

New applications using real-time observations and ECMWF model data

New applications using real-time observations and ECMWF model data New applications using real-time observations and ECMWF model data 12 th Workshop on Meteorological Operational Systems Wim van den Berg [senior meteorological researcher, project coordinator] Overview

More information

Land Surface: Snow Emanuel Dutra

Land Surface: Snow Emanuel Dutra Land Surface: Snow Emanuel Dutra emanuel.dutra@ecmwf.int Slide 1 Parameterizations training course 2015, Land-surface: Snow ECMWF Outline Snow in the climate system, an overview: Observations; Modeling;

More information

Deke Arndt, Chief, Climate Monitoring Branch, NOAA s National Climatic Data Center

Deke Arndt, Chief, Climate Monitoring Branch, NOAA s National Climatic Data Center Thomas R. Karl, L.H.D., Director, NOAA s National Climatic Data Center, and Chair of the Subcommittee on Global Change Research Peter Thorne, PhD, Senior Scientist, Cooperative Institute for Climate and

More information

Weather and climate. reflect. what do you think? look out!

Weather and climate. reflect. what do you think? look out! reflect You re going on vacation in a week and you have to start thinking about what clothes you re going to pack for your trip. You ve read the weather reports for your vacation spot, but you know that

More information

Soil Moisture Prediction and Assimilation

Soil Moisture Prediction and Assimilation Soil Moisture Prediction and Assimilation Analysis and Prediction in Agricultural Landscapes Saskatoon, June 19-20, 2007 STEPHANE BELAIR Meteorological Research Division Prediction and Assimilation Atmospheric

More information

1. Oceans. Example 2. oxygen.

1. Oceans. Example 2. oxygen. 1. Oceans a) Basic facts: There are five oceans on earth, making up about 72% of the planet s surface and holding 97% of the hydrosphere. Oceans supply the planet with most of its oxygen, play a vital

More information

LECTURE #14: Extreme Heat & Desertification

LECTURE #14: Extreme Heat & Desertification GEOL 0820 Ramsey Natural Disasters Spring, 2018 LECTURE #14: Extreme Heat & Desertification Date: 27 February 2018 (lecturer: Dr. Shawn Wright) I. Start of Part 2 of the Course weather-related disasters

More information

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 15 July 2013

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 15 July 2013 ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 15 July 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index

More information

Name Period 4 th Six Weeks Notes 2013 Weather

Name Period 4 th Six Weeks Notes 2013 Weather Name Period 4 th Six Weeks Notes 2013 Weather Radiation Convection Currents Winds Jet Streams Energy from the Sun reaches Earth as electromagnetic waves This energy fuels all life on Earth including the

More information