Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) is a program of the World Meteorological Organization (WMO) with the mission to enhance the ability of countries to deliver timely and quality sand and dust storm forecasts, observations, information and knowledge to end users. The Regional Center for Northern Africa, Middle East and Europe (NAMEE), hosted by the Spanish State Meteorological Agency (AEMET) and the Barcelona Supercomputing Center (BSC-CNS), supports a network of research and operational partners implementing the objectives of the SDS-WAS program in the region.
A system to routinely exchange forecast model products has been established as the basis for a model comparison that includes common near real-time (NRT) evaluation and generation of multi-model products.
In particular, a system to evaluate the performance of the different models has been set. The system yields, on a monthly, seasonal and annual basis, evaluation scores computed from the comparison of the simulated dust optical depth (DOD) and the direct-sun AOD observations from the AErosol RObotic NETwork (AERONET).
The geographical domain for the evaluation covers the main source areas for North Africa, Europe and Middle East, as well as the main transport routes and deposition zones.
Models
At present, 7 modelling systems: BSC-DREAM8b (Pérez et al., 2006; Basart et al., 2012), MACC-ECMWF (Morcrette et al, 2009; Benedetti et al, 2009), DREAM8-MACC (Nickovic et al., 2001), NMMB/BSC-Dust (Pérez et al., 2011), UM MetOffice (Woodward, 2001, 2011), NCEP/NGAC (Lu et al., 2010) and NASA/GEOS-5 (Colarco et al., 2010) daily provide dust forecast products (surface concentration and dust optical depth at 550 nm) for the reference area with a 3-hourly basis until a lead time of 72 hours.
Model
|
Institution
|
Run time (UTC)
|
Contact
|
BSC-DREAM8b
|
BSC-CNS
|
12
|
J. M. Baldasano
|
CHIMERE
|
LMD
|
00
|
L. Menut
|
LMDzT-INCA
|
LSCE
|
00
|
M. Schulz
|
MACC-ECMWF
|
ECMWF
|
00
|
J.-J. Morcrette A. Benedetti
|
DREAM8-NMME-MACC
|
SEEVCCC
|
12
|
G. Pejanovic
|
NMMB/BSC-Dust
|
BSC-CNS
|
12
|
J. M. Baldasano
|
UM
|
U.K. MetOffice
|
00
|
D. Walters
|
NGAC
|
NCEP
|
00
|
S. Lu
|
GEOS-5
|
NASA
|
00
|
A. da Silva
|
The evaluation system is applied to instantaneous forecast values of DOD ranging from the initial day (D) at 15:00 UTC to the following day (D+1) at 12:00 UTC. It means that the lead times of forecasts to be evaluated range from 15 to 36 hours for model runs starting at 00 UTC, but from 3 to 24 hours for model runs starting at 12 UTC.
Furthermore, a median multi-model is generated from the values of the different forecasts. In order to produce it, the model outputs are previously bi-linearly interpolated to a common grid mesh of 0.5º x 0.5º. Median values ranging from the initial day at 15:00 UTC to the following day at 12:00 UTC are also evaluated.
The evaluation system is built to easily incorporate new dust forecast models or multi-model products.
The forecasts of dust optical depth (DOD) are compared with the total AOD provided by the AERONET network for 42 selected dust-prone stations located around the Mediterran Basin, Iberian Peninsula, northern Africa and Middle East (see the figure below). They are described in detail in Appendix A.
Version 2-Level 1.5 of AERONET products are used for the present NRT evaluation. Level 1.5 AERONET data is automatically cloud screened but may not have final calibration applied. Thus, these data are not quality assured.
Since AERONET sun photometers do not yield AOD at 550 nm (AOD550), this variable is calculated from AOD at 440, 675 and 870 nm (AOD440, AOD675, AOD870) and the Ångström exponent 440-870 (AE440_870) using the Ångström law.
To minimize the sources of error, it is intended to restrict the comparison to situations in which mineral dust is the dominant aerosol type. Threshold discrimination is made by discarding observations with an Ångström exponent 440-870 higher than 0.6 (Pérez et al., 2006b).
Rather than time-interpolated, AERONET observations are assigned to the nearest multiple-of-3 hour. In case more than one observation is assigned to the same hour, only the closest-in-time is considered.
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