Verification and Case Studies for Urban Effects in HIRLAM Numerical Weather Forecasting A. Baklanov, A. Mahura, C. Petersen, N.W. Nielsen, B. Amstrup Danish Meteorological Institute, DMI, Copenhagen, Denmark 3-4 May 2007, COST-728 Workshop on “Model Urbanization Strategy” UKMO, Exeter, United Kingdom

Goal and Specific Objectives GOAL:  Evaluate effects of urbanization of numerical weather prediction (NWP) model on simulating meteorological fields for specific cases and overall model performance over the urbanized areas SPECIFIC OBJECTIVES:  Perform short- and long-term simulations of meteorological fields using DMI-HIRLAM-U01/I01 models in two modes: control vs. urbanized runs  Evaluate effects of urbanization on temporal-spatial structure and variability of meteorological fields  Estimate on a diurnal cycle the differences between control and urbanized runs for meteorological variables such as surface pressure, temperature, wind, and relative humidity

HIRLAM Domains, Land-Use Classification, & Urban Features  Domain - DMI-HIRLAM-U01 (1.4 km)  Focus - Island of Zeeland (I01)  Land surface scheme - Interaction Soil-Biosphere-Atmosphere (ISBA)  Tiles - 5 (low vegetation, forest, ice, water, bare soil) + urban (fraction >0.1+)

HIRLAM Numerical Weather Prediction Modelling  Model DMI-HIgh Resolution Limited Area Model (HIRLAM)  Boundary conditions DMI-HIRLAM-T15 -> -S05 -> U01/I01  Runs control vs urbanized (i.e. modif ISBA scheme) for U01/I01 domain  Modification/ Urbanization SIMPLE: roughness and anthropogenic heat flux for urban grid cells BEP: Building effect parameterization module  Output 3D meteorological fields (40 levels) for 2 types of runs

Module 1 (DMI etc): Analytical urban parameterisations (SIMPLE) (i) Displacement height, (ii) Effective roughness and flux aggregation, (iii) Effects of stratification on the roughness (Zilitinkevich et al, 2004), (iv) Different roughness for momentum, heat, and moisture; (v) Calculation of anthropogenic and storage urban heat fluxes; (vi) Prognostic MH parameterisations for SBL; (vii) Parameterisations of wind profile in canopy layer (Coceal and Belcher, 2004; Zilitinkevich and Baklanov, 2004). 1st NWP layer

HIRLAM Approaches + Evaluation of Modelling Results 1. Long-term simulations 2. Short-term simulations - specific meteorological situations 3. NWP Control vs. urbanized runs 1. Diurnal cycle 2. Difference fields for control vs. urbanized runs 3. Temperature at 2m, wind at 10m, rel humidity, surf. pressure 4. Focus: impact of urbanized areas on meteorological fields

Typical Wind Conditions : SIMPLE URBAN 06 UTC Difference (control vs. urbanized run) field for wind at 10 m Difference (control vs. urbanized run) field for temperature at 2 m UTC 18 UTC

Low Wind Conditions : SIMPLE URBAN 03 UTC Difference (control vs. urbanized run) field for wind at 10 m Difference (control vs. urbanized run) field for temperature at 2 m UTC 21 UTC

Low Wind Conditions : BEP URBAN Difference plots between outputs of DMI-HIRLAM vs. DMI-HIRLAM+BEP for (a) wind velocity at 10 m and (b) air temperature at 2 m for 20 UTC forecast on 12 April 2005 (a) (b)

HIRLAM NWP Model Performance: Overall all stations

HIRLAM NWP Model Performance: Over Urban Areas Wind velocity at 10 m (w10s, in m/s; top panel) & Air temperature at 2 m (T2m, in deg. C; lower panel) based on the DMI-HIRLAM-U01 control (NOA) vs urbanized runs (A20, ZO2) vs. observational data (obs) Værløse urban station (55.8ºN, 12.3ºE) located in metropolitan Copenhagen

Conclusions  Long-term runs with the DMI-HIRLAM-U01/I01 high resolution urbanized model showed a slight improvement for the overall NWP model performance, & this improvement is more considerable over the urbanized areas Differences between NWP control vs. urbanized runs: For typical wind conditions:  wind at 10 m (m/s) <0.5 (max up to 1.5, at midday)  temperature at 2 m (ºC) <0.25 (max up to 0.5, at nighttime)  relative humidity (%) > 3 (max up to 5, at midday) For low wind conditions:  wind at 10 m (m/s) >1 (max up to 3 at nighttime)  temperature at 2 m (ºC) >0.5 (max up to 1.5, at nighttime)  relative humidity > 4 (max up to 7, at midday)

Plans  Long-term simulations by DMI-HIRLAM high resolution model urbanized version (on-going runs): HIRLAM+BEP - building effect parameterization module, HIRLAM+SM2_U - soil model for sub-meso scales urbanized version,  At first, at least, for 1-2 months;  Second, for a longer period (year) in order to evaluate month-to-month variability.

Thank you  Computing DMI facilities of NEC SX6 Advice of DMI EDB Computer Support Department  Financial Support DMI-ENVIRO-HIRLAM project activities