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Challenge ID |
C-C= ORE_OFF1.17 |
Title |
|
Challenge originator: |
&nb= sp; |
<= p style=3D"margin-top:0pt; margin-bottom:0pt; text-align:center; font-size:= 10pt">General Descrip= tion | <= p style=3D"margin-top:0pt; margin-bottom:0pt; font-size:10pt"> |
What data/products do you use? |
Off= shore convective downbursts that are beyond the footprints of land-based ra= dar systems are currently not directly identified via products; however, th= e existence of convective downbursts may be indirectly inferred by using ge= ostationary and polar-orbiting satellite observations, as well as surface-b= ased observations. Most convective downbursts offshore are not qualified an= d quantified properly, because, typically, the events are not directly obse= rved. |
When do you use this kind of dataset? |
Obs=
ervations of convective downbursts are mostly used by the O&G industry =
in affected areas during operations. The onset of thee events can be sudden=
and interrupt all kinds of operations on deck, helicopter activity etc as =
they pose a large threat to personnel onboard rigs and vessels. Historical =
data are important to assess risk of operations in these areas, frequency o=
f occurrence, strength of gusts etc, but are mostly used as input to improv=
e operational forecasting. Also, many other data sources do not catch the e=
xtremes in the area without these data added to the time series for the poi=
nt of interest, since data often are averaged and conditions often are most=
ly benign. |
What are your actual limitations and do y= ou have a work around? |
In =
the absence of surface-based radar data, in order to qualify and quantify c=
onvective downbursts at sea requires (a) vertical wind profile data, (b) sa=
tellite imagery and (c) surface wind data, which must be analyzed together.=
Typically, the spatial and temporal resolution of a and c are inadequate f=
or the identification of historical convective downbursts. |
Needs and expectations on EO data<= /p> |
EO =
is used for this today, to spot convective cells and try to assess they mov=
ement. However, it is hard to assess the wind speed of each individual cell=
based on satellite data. Also, the direction of movement for each individu=
al cell is often hard to predict. This leads to unnecessary downtime becaus=
e of warnings. |
<= p style=3D"margin-top:0pt; margin-bottom:0pt; text-align:center; font-size:= 10pt">Challenge class= ification | <= p style=3D"margin-top:0pt; margin-bottom:0pt; font-size:10pt"> |
Pre license |
1= span> |
Exp. |
3= span> |
Dev. |
1= span> |
Prod. |
3= span> |
Decom. |
2= span> |
Geographic context/ restrictions= p> |
App=
lies to all six Areas of interest. |
Topographic classification / Offshore cla= ssification |
Oce= an |
Activity impacted/concerned | &nb= sp; |
Technology Urgency |
Sho= rt term (2-5 years) |
<= p style=3D"margin-top:0pt; margin-bottom:0pt; text-align:center; font-size:= 10pt">Information req= uirements | <= p style=3D"margin-top:0pt; margin-bottom:0pt; font-size:10pt"> |
Update frequency |
The= parameter is not directly available in observations. |
Temporal resolution |
The= parameter is not directly available in observations. |
Spatial resolution |
The= parameter is not directly available in observations. |
Data quality |
The= selected sources in this document are selected because they are known to h= ave sufficient quality (after some work arounds and adaptations). In genera= l separate indepth verification studies has to be made for each source plan= ned to be used for analysis, and the analysis has to be repeated for each g= eographical area (since sources might be of sufficient quality in one area = but not another). |
Data Coverage and extent |
Reg= ional |
Example format |
The= parameter is not directly available in observations. |
Timeliness |
Rea= l- time or near-real time |
Existing standards |
NA<= /span> |
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