Common use of Ocean Clause in Contracts

Ocean. For CMEMS applications, there are two different data gaps:  Observations needed do not exist. This kind of gap can be roughly identified by comparing the requirements and spatiotemporal distribution of the observations.  Observations exist but: o do not fit with CMEMS purposes. As CMEMS is an operational program, most of the applications have a strict requirement for timeliness. For example, near real time forecast and validation need observations in near real time; interim reanalysis needs observations in interim scale, i.e., 1-12 months before present time. Observations for CMEMS use will also need to reach certain quality standards. This can be especially true for calibrating satellite retrieval algorithms in TACs which may need observations with very high quality. o Data are not freely available. This can be caused by different reasons, e.g. data policy, research publication, economic benefit, technological confidentiality and even political issues. Besides the data gaps, lack of in situ observations can be caused by technological gaps and sustainability gaps. The former relates to the technology capacity in providing operational and cost- effective monitoring for a given parameter, while the latter is determined by economic, policy, organizational and infrastructure-related issues in support for maintaining the monitoring activities. In the following subsections, we will analyse the data -, technology - and sustainability gaps in Arctic Ocean in situ observations for CMEMS. 4.3.1 Data gaps and adequacy analysis 3.1. All 106 PSMSL tide gauges above 68o ▇. ▇▇▇▇▇ dots mark the 69 gauges with at least 5 years of data and trends within ~2 cm/year, while red dots mark rejected gauges (Source: ▇▇▇▇▇▇▇▇ et al., 2015). 3.1). However only a part of the Norwegian data is included in CMEMS and only monthly data are used by ARC MFC. For SL TAC, monthly mean sea level data from 10 GLOSS stations SST: in SST TAC, in situ SST is mainly used for calibrating and validating the satellite products. Currently only SST from about 132 surface drifters and 80 Argo profilers are used. There will be more high- quality data added from EUMETSAT/Copernicus Trusted projects. There are no significant data gaps identified for this purpose. However, many other in-situ SST datasets have been identified from the Ferrybox and moorings. For ARC MFC, regional error statistics of forecast and reanalysis are becoming important. Hence more SST data are need for validation. For data assimilation, satellite products play a major role. IST: accurate IST can be measured by using near surface radiometers. They are needed for calibrating and validating satellite IST products. IST in situ data are sparse but there are more data existing in non- EU countries. These data can be collected and used by ▇▇▇▇▇▇▇▇▇▇. T/S profiles: there is a good coverage of T/S profiles in ice-free waters. The data have been well collected and quality controlled and openly accessible from WOD, UDASH, iAOS, SeaDataNet, ICES and EMODnet. The estimated amount of non-Russian profiles is >20000 per year, i.e., 54 profiles per day. More than 90% of these data are open and free. This meets ARC MFC requirements of 50 profiles per day. However, data availability is not even: few data are accessible from the Russian Arctic, and few data exist in ice-covered waters. Under-▇▇▇ ▇/S profiles are mainly observed with ITP profilers which is currently providing about 400 profiles per year (down to 500-800 m depth), as collected in CMEMS INSTAC. More ITP profiler data are needed. Regular monitoring cruise data in Greenlandic and Icelandic waters are restricted for access. In addition, there exist major data gaps for CMEMS NRT/Interim applications due to delayed accessibility of the data: the delivery time of CTD data in many cases is simply too long (1-2 years). The delayed data delivery prevents data usage for NRT and interim assimilation. One of the priorities for T/S observations is to release ship CTD data in near real time to meet the requirement for NRT and interim assimilation. Snow and Ice over sea: the snow depth and sea ice thickness (SIT) and ice temperature can be measured by using Ice Mass Balance (IMB) buoys. An IMB array has been operated in central Artic with interruptions since 2012. However, there are only 3 stations in operation. The data gap in Copernicus can be partly filled by improved data collection but the gap is still large and caused by no data. It is also noted that, when validating satellite products, point observations still have their weaknesses in the representativeness. Waves: currently there are about 30-40 wave buoys operating in the north of 60 N. Most of the data are found in Norwegian waters, measured at oil platforms. These data have restricted access. On the other hand, due to existence of ice, requirements on in situ wave data are higher in the Arctic than other seas for validation of satellite wave products and forecasting the wave conditions. Significant gaps in in situ wave observations exist due to both lack of data and lack of data sharing by the private sector.

Ocean. For CMEMS applications, there are two different data gaps:  • Observations needed do not exist. This kind of gap can be roughly identified by comparing the requirements and spatiotemporal distribution of the observations.  • Observations exist but: o do not fit with CMEMS purposes. As CMEMS is an operational program, most of the applications have a strict requirement for timeliness. For example, near real time forecast and validation need observations in near real time; interim reanalysis needs observations in interim scale, i.e., 1-12 months before present time. Observations for CMEMS use will also need to reach certain quality standards. This can be especially true for calibrating satellite retrieval algorithms in TACs which may need observations with very high quality. o Data are not freely available. This can be caused by different reasons, e.g. data policy, research publication, economic benefit, technological confidentiality and even political issues. Besides the data gaps, lack of in situ observations can be caused by technological gaps and sustainability gaps. The former relates to the technology capacity in providing operational and cost- effective monitoring for a given parameter, while the latter is determined by economic, policy, organizational and infrastructure-related issues in support for maintaining the monitoring activities. In the following subsections, we will analyse the data -, technology - and sustainability gaps in Arctic Ocean in situ observations for CMEMS. 4.3.1 Data gaps and adequacy analysis 3.14.3.1. All 106 PSMSL tide gauges above 68o ▇. ▇▇▇▇▇ dots mark the 69 gauges with at least 5 years of data and trends within ~2 cm/year, while red dots mark rejected gauges (Source: ▇▇▇▇▇▇▇▇ et al., 2015). 3.1). However only a part of the Norwegian data is included in CMEMS and only monthly data are used by ARC MFC. For SL TAC, monthly mean sea level data from 10 GLOSS stations SST: in SST TAC, in situ SST is mainly used for calibrating and validating the satellite products. Currently only SST from about 132 surface drifters and 80 Argo profilers are used. There will be more high- quality data added from EUMETSAT/Copernicus Trusted projects. There are no significant data gaps identified for this purpose. However, many other in-situ SST datasets have been identified from the Ferrybox and moorings. For ARC MFC, regional error statistics of forecast and reanalysis are becoming important. Hence more SST data are need for validation. For data assimilation, satellite products play a major role. IST: accurate IST can be measured by using near surface radiometers. They are needed for calibrating and validating satellite IST products. IST in situ data are sparse but there are more data existing in non- EU countries. These data can be collected and used by ▇▇▇▇▇▇▇▇▇▇. T/S profiles: there is a good coverage of T/S profiles in ice-free waters. The data have been well collected and quality controlled and openly accessible from WOD, UDASH, iAOS, SeaDataNet, ICES and EMODnet. The estimated amount of non-Russian profiles is >20000 per year, i.e., 54 profiles per day. More than 90% of these data are open and free. This meets ARC MFC requirements of 50 profiles per day. However, data availability is not even: few data are accessible from the Russian Arctic, and few data exist in ice-covered waters. Under-▇▇▇ ▇/S profiles are mainly observed with ITP profilers which is currently providing about 400 profiles per year (down to 500-800 m depth), as collected in CMEMS INSTAC. More ITP profiler data are needed. Regular monitoring cruise data in Greenlandic and Icelandic waters are restricted for access. In addition, there exist major data gaps for CMEMS NRT/Interim applications due to delayed accessibility of the data: the delivery time of CTD data in many cases is simply too long (1-2 years). The delayed data delivery prevents data usage for NRT and interim assimilation. One of the priorities for T/S observations is to release ship CTD data in near real time to meet the requirement for NRT and interim assimilation. Snow and Ice over sea: the snow depth and sea ice thickness (SIT) and ice temperature can be measured by using Ice Mass Balance (IMB) buoys. An IMB array has been operated in central Artic with interruptions since 2012. However, there are only 3 stations in operation. The data gap in Copernicus can be partly filled by improved data collection but the gap is still large and caused by no data. It is also noted that, when validating satellite products, point observations still have their weaknesses in the representativeness. Waves: currently there are about 30-40 wave buoys operating in the north of 60 N. Most of the data are found in Norwegian waters, measured at oil platforms. These data have restricted access. On the other hand, due to existence of ice, requirements on in situ wave data are higher in the Arctic than other seas for validation of satellite wave products and forecasting the wave conditions. Significant gaps in in situ wave observations exist due to both lack of data and lack of data sharing by the private sector.