1. DATABASE OF MINERAL CONTENT IN ARID SOILS
GMINER30
Belgrade University, Serbia
Contact: Ana Vukovic

2. Why database of mineral content in arid soils is important?
behavior of aerosol dust in its interactions with the environment on global and local scales
is to a large extent determined by mineral composition of dust particle
it is necessary to provide gridded global data set of significant minerals that have impact
on environment in order to be able to use it as input for atmospheric-dust transport models
that can improve understanding of the transport, interaction and impact processes
after extensive study introduction into models of mineral transport and processes which
censers them can improve forecast qualities and climate simulation results
Claquin et al. (1999) – pioneer work:
- silicates (quartz, feldspars, illite, kaolinite, and smectite), carbonates (calcite),
sulfates (gypsum) and iron oxides (hematite)
- global dataset masked with mask for arid regions, available on 0.25X0.25 resolution
GMINER30 database:
+ additional content in several more soil types
- added phosphorus
- global dataset on 1km resolution without mask

3. Why modeling of mineral transport is important?
Introduction of mineral dust transport and its interaction in numerical models:
can improve skill of forecast and climate simulations
can help to understand processes of mineral impact, considering the problem of data
insufficiency, and to point out important parameters and areas that should be monitored
Implementation in atmospheric models is important, in modeling sense, because of:
nucleation process (Klein at al. 2010)
→ to improve modeling of cloud formation
it directly affect atmospheric radiation
and thereby atmospheric dynamics by
modifying the incoming solar radiation
and the outgoing infrared radiation…..
Aqua MODIS, Dec 30th 2010
Dust storm, El Paso, Mexico

4. Benefit of mineral transport modeling for other science disciplines
dust has a great influence on environment and health, which depends on its
mineral composition
output of models can serve scientists of other disciplines to understand processes
from their field of research, such is ocean productivity (sea blooming) and
human health issues
Bloom of Trichodesmium Canary Islands
August 2004 (Ramos et al., 2008)

5. + Steps that lead to GMINER30 USGS land cover + FAO soil texture
which soil types are dust productive/arid/erodible +
mineral composition of selected soil types in silt and clay population
global mineral database of dust productive soils GMINER30

6. Land cover types distribution in arid regions
Mask of arid regions based on USGS land cover categories
● areas that are mostly bare and dry

7. Frequency of FAO soil types in arid regions
Added soil types
(light blue)
Yermosols (Y)
Podzoluvisols (D)
Haplic Yermosols (Yh)
Fluvisols (J)
Need to include
(dark blue)
Luvic Kastanozems
Halpic Kastanozems
Solonchaks
…..
orange + blue soil types cover
more than 95% area in arid regions
Claquin et al, 1999
Nickovic et al, 2011
no data on mineral
composition

8. Mineral database http://www.seevccc.rs/GMINER30/
Mineral fractions are separated for silt and clay size populations
silt
clay
silt & clay
feldspar
illite
calcite
gypsium
kaolinite
hematite
smectite
quartz
+ phosphorus
data are organized in 27 tiles for each mineral
30-second resolution (~1km)
4800x6000 points in each tile

9. CLAY POPULATION
SILT POPULATION
CALCITE
QUARTZ
HEMATITE

10. ILLITE
KAOLINITE
SMECTITE
FELDSPARS
PHOSPHORUS
QYPSUM

11. Model: DREAM-IRON (first results)
Iron is transported with dust particles
in dust model DREAM is added information about iron content of transported dust
T=total Fe and S=soluble Fe
Total Fe (T) = Soluble (S) + Non-soluble (N)
during transport through atmosphere (N)  (S)
Dust concentration (C):
Total iron concentration (T):
Soluble iron concentration (S):

12. Clay content masked with LC Silt content masked with LC
Iron in clay
minerals: illite, kaolinite, smectite, hematite
Iron in silt
minerals: feldspars, hematite
OPTIANAL:
Dust source mask in this case study are USGS arid regions (LC mask)
Clay content masked with LC
Silt content masked with LC
DREAM-IRON knows where and how much Fe is available for uptake

13. Case study: Canary Islands (July-August 2004)
Bloom of Trichodesmium Canary Islands
August 2004 (Ramos et al., 2008)
model domain
CANARY
ISLANDS
when soluble iron is deposited to the ocean after ~10days (more or less)
bloom of the sea can be expected
at the end of the July 2004 large dust episode happened over west Africa and
dust was transported over the Atlantic Ocean
in August 2004 was recorded sea bloom near Canary Islands

14. Model results for June 24th 2004 12UTC
Surface dust concentration
Image: 2004/ /25 14 :20 UTC Saharan dust off West Africa Satellite: Aqua MODIS
Dust Load

15. surface total iron (TS)
surface soluble iron (SS)
soluble iron load (TL)

16. Future plans
include 4 more soil types (dark blue) with its mineral content in GMINER30:
mineral composition needed!
replace 4km FAO database with new 1km HWSD (Harmonized World Soil Database)
first update of the model: improved iron dynamics
test model for more marine response to Fe cases
necessary collaboration with soil scientists, ocean scientists,…..
implementation of deposited soluble iron in ocean models in order to transport soluble Fe
by ocean dynamics and to estimate marine biology response
(coupling DREAM Fe and ocean models)
include in models impact of minerals on cloud formation and radiation
………… etc.