1. Calculation SW fluxes by SAIL and MGO parametrization
Calculation of incoming shortwave fluxes for the Atlantic Ocean using
SAIL and MGO parametrizations and CLAAS-2 cloud satellite data.
Sinitsyn A.V. Gulev S.K P.P. Shirshov Institute of Oceanology, RAS
Outline:
Calculation SW fluxes by SAIL and MGO parametrization
Compare results of calculation with SARAH
Way to improve results
In 2009, we create new parameterization called SAIL, which was based on onboard measurement of incoming SW fluxes and different metrological parameters such as cloud type and number.
This measurement was made in different parts of Atlantic Ocean.
The main goal of this parameterization was create climatology of SW fluxes for Atlantic Ocean base on VOS data.
However, Technology does not stand still and now we get several data sets of clouds base on satellite measurement.
Of course, this data sets does not have long period as VOS data. However, they have high time and spatial resolution
In this work, we try to use satellite data sets of cloud to calculate incoming SW fluxes for Atlantic Ocean.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

2. SAIL parameterization 2009
Okta,CL 1 2 3 4 5 6 7 8 ai
0.81
0.80
0.78
0.76
0.74
0.71
0.67
0.60
0.31 bi
0.15
0.13
0.17
0.14
0.12
Separate equations for different cloud types №
Category
Atm. transmission 1
Ns(7/0_2_X)
T=0,14 x sinh +0,11 2
Sc(Cu) (4_0_0)
T=0,33 x sinh +0,17 3
AsAc(0_7_X)
T=0,34 x sinh +0,19 4
Sc(no_Cu) (5_0_0_Sun1/0)
T=0,31 x sinh +0,22 5
Sc(no_Cu) (5_0_0_Sun_П)
T=0,25 x sinh +0,11
Slide 2
Parameterization SAIL is Empirical okta model where incoming SW fluxes depend on clouds cover number in octas. Coefficient of atmosphere transmission is nonlinear sun altitude, this allows us to better calculate fluxes for Sun close to horizon.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

3. MGO-parameterization (Malevsky-Malevich 1992)
Clear sky radiation
transmission factors c and d depend on the
atmospheric temperature and humidity
Parameterizations MGO is classical two-step parameterization, when you on first step calculate possible SW fluxes (cloudless sky), taking into account only water vapor in atmosphere. In the next step, we account cloudiness – total or total and low Cloud mode.
Important point. Since SAIL and MGO parameterizations were developed for hourly value of SW fluxes, but in satellite data we have often daily and month value for SW fluxes, clouds cover and other parameters, which we can use in parameterization. And so we will use virtual clock rotation – when we for calculation of daily SW fluxes will fix cloud cover and calculate sun altitude for each hour and coordinate and then average this sum.
And result of this averaging we compare with satellite data of SW fluxes.
For total cloud cover only in Decimal
For both total and low cloud cover in Decimal
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

4. Surface incoming shortwave radiation
Data set
Time
Area
Temporal resolution
Spatial resolution
Data source
Surface incoming shortwave radiation
SARAH ed. 1.0 –
70°S-70°N, 70°W-70°E
Daily
0.05°x0.05°
MVIRI/SEVIRI on METEOSAT
NCEP CFSR 
SLP –
Global
0.5°x0.5
Near surface specific humidity
HOAPS 3.2 –
Monthly
NSH on SSM/I
Fractional cloud cover
CLAAS-2 –
90°S-90°N, 90°W-90°E
SEVIRI on METEOSAT
Operational Products of SIS
 15x15 km2
On this slide, you can see satellite data, which we use like incoming and referents data set for our calculation of SW fluxes by SAIL and MGO.
This data was taken in CM SAF.
SIS and operation product of SIS we use like reference data.
SLP data and Near surface specific humidity we us for calculating relative humidity near surface for calculating possible SW fluxes in first step of MGO.
Fractional cloud cover we use like incoming data set for SAIL and MGO on second step
The work performed was done by using data from EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF)
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

5. Bais SARAH and Parameterizaition for Jan. 2004 – Dec. 2008
On next 2 slides I’ll show comparison result of calculation for SW fluxes by SAIL and two version on MGO parameterization with SARAH data set for period Jan 2004 to Dec 2008.
The Bias SARAH and SAIL lies between -10 до 10 Wt/m2 and less in comparison MGO parametrization.
MGO1 underestimate SW fluxes more than 10 Wt/m2 for all area of Atlantic Ocean.
The main error for MGO2 is overestimate SW fluxes for south part of Atlantic about 30 Wt/m2
And underestimate SW fluxes more than for tropic and north part of Atlantic about 20 Wt/m2
The maximum bias we can see in central part of Atlantic. In this area MGO parameterization underestimate SW fluxes about 40 Wt/m2. And this area is area of Highest resolution and accuracy for MSG satellite.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

6. RMSD SARAH and Parameterization for Jan. 2004 – Dec. 2008
Further, we will consider RMSD for our calculation. RMSD characterizes the accuracy of calculation SW fluxes by parametrization.
For SAIL the error of calculation less then 40 Wt/m2. And for SAIL we can note area where error less than for Atlantic as a whole.
About Wt/m2. This area are central and south part, the eastern part from the islands of Cape Verde to the Bay of Biscay.
These are the areas in which measurements were carried out the largest number of times during the work in the Atlantic Ocean.
For MGO1 error in little bigger- about 50 Wt/m2. And we can see area where this error more bigger - about 60 Wt/m2 this is north tropic for MGO1 and south part of Atlantic for MGO2
The central part have high level of error about Wt/m2 too.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

7. Jan – Dec 2013
After good agreement result SAIL and SARAH for we decide to calculate SW fluxes by our parameterization for whole period using data about cloud cover and where we can compare calculation and SARAH.
On next two slides, you can see comparison for Jan 2004 to Dec 2013, because this work was made in the beginning of this year and we have not yet SARAH v.2 till 2015.
On this slide, you can see average SW fluxes for this period. At first look this picture very similar.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

8. Jan – Dec 2013
Better, we look to Bias and RMSD.
SAIL underestimate SW fluxes for central-south part of Atlantic about 15 Wt/m2. And good agreement for north part about +/- 15 Wt/m2. Maximum bias belong area with average cloud cover about 5-7 octa. In this case, we have high variability of cloud type for accounting in integral parameterization.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

9. Jan – Dec 2013
A proof of this we can see in RMSD picture. Minimum of error about Wt/m2 we can see of in area with 4-5 octa. In this case, directional fluxes prevail over scattered fluxes especially for tropic and equator. Area with overcast does not show any different compare to SARAH
We mask continental data consciously because SAIL parameterization was made for sail application. And our experience say us that cloud properties above ocean and continental are different. And we have high errors in this case.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

10. Jan – Dec 2015
And the last stage of comparison SW fluxes from CM-SAF and SAIL calculation. As I note above we start to calculate this task in the beginning this year. And so we have SARAH data only till Dec And two last year 2014 and 2015 we compare with Operational product of SIS.
On this slide, you can see Bias and RMSD between operational data and SAIL calculation.
We have increasing of bias to Wtm-2 for whole area and strong increasing to board of area about 40 Wtm-2. From our point of view, this is due to accuracy of satellite measurements. The error to the edge of the area of view increases.
RMSD looks like above picture RMSD for SAIL. Minimum in center of Atlantic – 15Wtm-2, In last area about 55Wtm-2.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

11. The main question of this work is SAIL suitable for calculating SW fluxes in Atlantic?
If we look Validation report for SARAH with BSRN station we can see RMSD about 25 and optimum 15 Wtm-2.
In our work we come close to this value this is regain with cloudiness up to 4 okta.
And the region with overcast on South Atlantic have value too.
For other part RMSD does not exceed 50 Wtm-2
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

12. From our point of view is better to consider RMSD relation to ave SW fluxes.
And now we can see that SAIL good calculated SW fluxes for cloudiness up to 5 okta.
And for South Atlantic the result is not good because 25 Wt-m of RMSD is too much for aver fluxes about 150 Wt-m2.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

13. Conclusion…
Parametrization SAIL suitable for calculating SW fluxes in Atlantic Ocean for cloudiness up 5 Octa.
Taking in to account separately cloud layer in frame the same model can reduce error of SW fluxes calculation about 5-10 Wtm-2.
…and plans for the future.
The future way of improvement SAIL parameterization is to try take into account separately direct and scattered fluxes. And we are going make such experiment on sea platform in Black Sea near Crimea coast.
The future way of improvement SAIL parameterization is to try take into account separately direct and scattered fluxes. And we are going make such experiment on sea platform in Black Sea near Crimea coast.
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland

14. Acknowledgments:
The work performed was done (i.a.) by using data from EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF).
This work was supported by the RSF (Grant No , Agreement No and ).
EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2017 | 4–8 September 2017 | Dublin, Ireland