1. Dragos Isvoranu Viorel Badescu University Politehnica of Bucharest
Comparison between measurements and numerical assessment of global solar irradiation in Romania
Dragos Isvoranu
Viorel Badescu
University Politehnica of Bucharest

2. Purpose Motivation Quality and performance of global solar
irradiance forecasting.
Purpose
Motivation
Variability of solar power production at different
spatial and temporal scales:
intermittent weather patterns
day/night cycles
humidity and aerosol load
cloud structure
Adapting the load schedule of grid operators
optimization of energy transport in low voltage grid
balancing energy; avoid outages and congestions
spot market sell ; penalties for wrong load schedules
maintenance planning
protection from extreme events

3. Historical perspective
contrary to wind forecasting, solar radiation forecasting is relatively new
2008, Germany
2011, Canada
significant reduction in RMSE with increasing the geographic area
under consideration in both cases
2011, Spain, point forecast, RMSE between 10-50% depending on
cloudiness.
Solar radiation forecasting
Forecasting horizon for PV: from 24 h up to 72 h.
In this range: numerical weather prediction based on equations of
fluid dynamics and thermodynamics to estimate the state of the
atmosphere at some time in the future.
NWP: Initialization: sample the state of the atmosphere at a given time
( ground station, satellite, radar)
Time stepping: tens of minutes for global climate models to a few seconds
or minutes for regional models.
extrapolation methods (mainly for nowcasting) (global models)
statistical methods (up to 24 h horizon) (global models)
for regional models additional physics details

4. WRF presentation NWP is stronly dependent on space scale
Meteorology scales:
global planetary (synoptic)
regional (mesoscale) (5- hundreds of km)
microscale (below 1 km)
Synoptic models: GFS, ECMWF, GME, UKMO
Mesoscale models: HRM, Hirlam, Lokal Model, WRF-(NMM, ARW),
Unified Model, MM5
Selection of the numerical model:
popularity
cost
performance
accessibility to meteo and satellite data
European mesoscale codes: HRM, Hirlam, Lokal Model
semi-Lagrangian, semi-implicit formulation
North-American codes: WRF (ARW,NMM), MM5
Eulerian formulation
Many pros and cons for each type of formulation
Though, a major failure for London Met Office for cloud propagation
from Eyjafjallajökul eruption in April 2010

5. WRF presentation 2 dynamical nuclei: ARW (NCAR) and NMM (NCEP)
multigrid
multi-level
non-hidrostatic
LES turbulence model
space scales from tens of meters hundreds of km and even synoptic
one and bi-directional coupling with various physics modules
nested and moving grids
ARW : Arakawa-C type of grid
NMM : Arakawa-E type of grid
great flexibility and versatility by adding up new tailored modules
less numerical dissipation due to high order numerical algorithms
full parallelization
recent simulations showed similar accuracy compared to Unified Model
from UK Meteorological Office and GME from Deutsche Wetterdienst

6. WRF presentation

7. WRF presentation

8. Radiation model
radiation schemes: atmospheric heating and ground heat budget.
LW radiation: infrared radiation absorbed and emitted by gases and
surfaces.
Upward LW flux depends on the surface emissivity (land-use type, and ground (skin) temperature.)
SW radiation includes visible and surrounding wavelengths that make up
the solar spectrum. Hence, the only source is the Sun, but processes
include absorption, reflection, and scattering in the atmosphere and at
surfaces
Upward SW flux is the reflection due to surface albedo.
Within the atmosphere, radiation responds to model-predicted cloud and
water vapor distributions, as well as specified carbon dioxide, ozone.
All the radiation schemes in WRF currently are column (one-dimensional)
schemes(each column is treated independently),
Radiative fluxes are similar to those in infinite horizontally uniform planes
WRF options:
GFDL ; Lacis and Hansen (1974)
MM5 (Dudhia); Dudhia (1989)
Goddard Shortwave; Chou and Suarez (1994)
CAM Shortwave; NCAR Community Atmosphere Model (CAM 3.0)

9. Radiation model  MM5 (Dudhia);
Simple downward integration of solar flux,.
Accounting for clear-air scattering, water vapor absorption (Lacis
and Hansen, 1974), and cloud albedo and absorption.
It uses look-up tables for clouds from Stephens (1978).
In WRF V3, the scheme has an option to account for terrain
slope and shadowing effects on the surface solar flux.
cloud absorption
and scattering
absorption and scattering
transmisivity
Evaluation of downward component of shortwave flux:
effects of solar zenith angle downward component and the path length;
clouds  albedo and absorption; bilinearly interpolated from tabulated
functions. The total effect above height z  percentage of Sd
clear air: scattering taken uniform and proportional to the atmosphere's
mass path length, again allowing for the zenith angle
 water-vapour absorption as a function of water vapor path
(zenith angle)

10. ANM Timisoara station supplied with Kipp & Zonen CM6B radiometers.
Results
Station name
Station
code
Geogra-phical code
Lat. (deg N)
Long. (deg E)
Alt.
(m asl)
Timisoara
15247
546115
45.77
21.26 86

11. WRF set-up
single-moment microphysics scheme following Hong et al. (2004)
the YSU planetary boundary layer scheme (Hong et al., 2006)
Kain–Fritsch cumulus scheme (Kain and Fritsch, 1993)
MM5 similarity based on Monin-Obukhov with Carslon-Boland
viscous sub-layer for surface layer (Paulson, 1970, Dyer and Hicks,
1970 and Webb, 1970),
Unified Noah land-surface model,
RRTM scheme for long-wave radiation (Mlawer et al., 1997)
Dudhia scheme for shortwave radiation (Dudhia, 1989)
The synoptic meteorological data (GFS model) started on 06/13/2010-
00:00:00 and expanded up to 06/20/ :00:00 covering 180 hours
of forecast of the 0 cycle initialization.
Simulation domain centered on the geographical coordinates of radiometer
station and expands 1700 km in E-W direction and 850 km in N-S direction.
Grid spacing is 18.5 km. No nested grids.
The measured data consist of only 110 recordings covering the same forecast
horizon

12. red dots: simulation;
black line: measurements;
n: point-cloudiness ranging between 0 and 1.

15. n=0
n=0-0.3 n= n=
n=1.0
all data
rMBE
(%)
18.23
14.22
11.68
75.69
281.91
32.50
rRMSE
21.62
17.64
26.55
105
412.84
53.63

16. Thank you for your patience
Conclusions
GHI forecast fits well within experimental data for situations ranging
from clear sky to moderate cloudiness (n<= 0.7)
The statistics (MBE, RMSE) show 5%-10% larger values than
results of Lara-Fanego (2011) who used a different micro-physics
and grid step.
Thank you for your patience