Detailed Report. If the initial feasibility study concludes that the aim is achievable and has a realistic prospect of success, and provided the Commissioner agrees, the Project will move on to the second phase. This will be a more detailed phase examining the current information rights activity within schools (which may necessitate some additional research), the shortfalls, what opportunities to improve the situation exist, recommendations for implementation and expected outcomes if such opportunities are taken. This phase is about the practical application of the aim of embedding information rights into the education systems and about what action the Commissioner can realistically take to improve the current landscape. Specific recommendations are required. This phase should include an overview of how the UK compares to initiatives in other countries, such as Ireland, Poland and France, and an evaluation of their success. Reports for both phases must be written in a manner consistent with the Commissioner’s role as a respected regulator adopting an impartial, considered and evidence based approach, using plain English and in accordance with the Commissioner’s own style guide for written communications (copies available on request). The final text of the detailed second phase report must be agreed with the Commissioner and he reserves the right to exercise editorial control and make decisions as to format and publication. During the progress of the Project the Contractor will provide fortnightly update reports to the Commissioner in a format agreed between the parties at the start of the Project or as advised to the Contractor from time to time.
Detailed Report. The original title of this deliverable – “Energy sector visual prototype” – was amended to “PRIMAVERA Data Viewer”, with approval from the project’s Technical Officer at the EC, to better reflect the results that we wanted to achieve in this task. Namely, the PRIMAVERA Data Viewer goes beyond presenting the data only relevant for the energy sector. Instead, the indices it presents can be useful to other sectors too, for example health and transport. The prototype Data Viewer is ready and accessible online. It is linked to the PRIMAVERA User Interface Platform, providing additional information relevant for users and promoting the exploration and interaction of users with some of the PRIMAVERA results. It will be updated in the coming months as new project data becomes available. Due to the delay of the delivery of the forcing data from the CMIP6 initiative, that we needed for conducting future model runs, the project was extended for nine months. Accordingly, D11.4 as well as some of the other project deliverables, was postponed to the project month 51 (from the original 36).
3.1 The Data Viewer initial prototype An initial prototype was developed using the available data produced in the project and the knowledge on climate indices and indicators relevant for different users. The data viewer is seamlessly integrated in the UIP as a new section in the main header/menu.
Fig. 1 First prototype of the Data Viewer
Detailed Report. Climate forecast systems predict the future evolution of climate, taking into account internal and external sources of variability, over timescales that range from a month to a few decades. Predictions are started from an accurate estimate of the contemporaneous state of the climate system, based on observations, and are run for a number of years into the future - typically up to a decade. Predictions are performed using ensembles of simulations, to account for a variety of sources of uncertainties in the inputs and to allow quantification of their effect on the outputs. The predictions require sets of hindcasts (forecasts for the past performed with the same forecast system) to describe the climatology of the model - and thus identify systematic errors (i.e. biases) and estimate their magnitude - as well as the performance of the forecast system, from a variety of perspectives. Climate forecasting is quickly becoming an operational activity around the world; at present, roles and responsibilities for coordination of operational activities reside with the WMO Lead Centres for long-range forecasts. In 2017, WMO designated a Lead Centre for Annual to Decadal Climate Prediction (LC-ADCP, xxx.xxxxx-xxxx.xxx) based at the Met Office in the UK; four Global Producing Centres for decadal predictions (GPC-ADCP) were also designated: Barcelona Supercomputing Center (BSC), Deutscher Wetterdienst (DWD), the Canadian Centre for Climate Modelling and Analysis (CCCMA), and the UK’s Met Office Xxxxxx Centre, (MOHC). Standards and protocols regarding the provision of decadal prediction by GPCs-ADCP and LC-ADCP have also been developed and included in the 2017 Edition of WMO’s Manual on the Global Data Processing and Forecasting System. These define a clear process for the contributing centres seeking WMO accreditation as GPC-ADCP, requiring commitment to the WMO-specified products and fixed production cycles, as well as to prediction verification. In 2010 an informal exchange of near real-time decadal forecasts started as a research collaboration among several institutions around the world. In the first few years 8-10 centres participated, all participants provided surface air temperature, while few (only three centres in the first two years) also provided precipitation and mean sea level pressure. In 2013 data describing the Atlantic Meridional Overturning Circulation (AMOC) also became part of the exchange. The exchange was set on a more robust footing, with the designat...
Detailed Report. The original plan for the coupled stream 2 simulations, as stated in WP6 description, was to produce a smaller number of high-resolution simulations, as compared to stream 1, but with improved model components derived from WP2 and WP3 and guided with input from user requirements (WP11). In discussions ahead of and during a project EMB meeting held at Schiphol on November 12, 2018, it was argued that the initial plan, as stated in the project description, might not be the best path forward, and had a number of difficulties:
1. Much of the new physics had not been tested at high resolutions
2. Not many models could use each model development, therefore leading to a small sample in each case
3. Biases could very well become worse in long simulations Furthermore, it was argued in discussions about the design for Stream 2 that in order to adequately quantify the impact of increasing resolution, a larger ensemble size was required (stream 1 required only 1 ensemble member per configuration). Thus, given the considerable time that would be required to run the simulations as initially planned, the uncertainty as to whether it would be really useful and the need for larger ensemble, it was agreed that a large part of the effort for stream 2 would go into producing additional members and follow the same protocol as stream 1, but with a reduced output, as guided with the data request from stream 1 simulation. As a reminder, Figure 1 (below) presents the HighResMIP (stream 1) protocol, for coupled simulations. The HighResMIP protocol divides the simulations in 4 distinct experiments:
Detailed Report. A monthly detailed report from which the summary information will be generated that includes the following information for each key Component (as mutually agreed to by the Parties): OJO Component part; inventory on hand and on order by OJO Component part; and minimum order quantities and lead times for each key OJO Component part.
Detailed Report. In order to clarify the contribution that different models (and resolutions) play in the uncertainty of future projections, HighResMIP proposed a future simulation with given SST and sea-ice forcing that are reasonable for this period under a specific forcing scenario (SSP5-RCP8.5). Future atmosphere-only simulations for the period 2015– 2050 have thus been carried out in the past months (these are Tier 3 experiments of the HighResMIP project) by different groups. Although the future period suggested by the HighResMIP protocol covers the entire present century, the PRIMAVERA simulations had to be restricted to the mid-century (2050), mostly for computational and storage space reasons. The future SST and sea-ice forcing datasets have to be produced for the future period. The method broadly follows the methodology of Xxxxxx et al. (2008), enabling a smooth, continuous transition from the present day into the future. The rate of future warming is derived from an ensemble mean of CMIP5 RCP8.5 simulations, while the interannual variability is derived from the historic 1950–2014 period. Here is a description of how these datasets have been constructed. Note that for CMIP6, the future is 2015 onwards. We had planned to use observed HadISST2 data up to 2017, but for reasons beyond our control this is no longer possible, so the first real future year is 2016. We first describe the observed dataset then the models that have been used to infer the SST and SIC climate change signal. Observations: The HadISST2.2 SST and sea-ice concentration (Xxxxxxx et al. 2017) is used for the 1950-2014 HighResMIP highresSST-present experiment. This is a daily, ¼˚ dataset. We have used the variability derived from this dataset, together with the future change from a set of CMIP5 coupled model simulations (of the historic period and the RCP8.5 future period), to construct the future SSTs and SICs to 2050. Details about the extraction of daily variability and the treatment of the links between SST and SIC can be found here: (xxxxx://xxxx.xxxxxx.xxx/document/d/1nIGeDaU40jO5ZLKVDDs0bdEIxjdno7J4nRV 4 7hnvw/edit). These include the models that Xxxxxxxxx et al. (2012) suggested to have represented the Arctic sea-ice variability in the most realistic way, together with three additional models which have Arctic sea-ice decline at a similar rate to these others. All the data was also available on the CEDA platform (as part of the CMIP5 archive). The full SST datasets for the CMIP5 models, comb...
Detailed Report. INTEGRITY OVERSIGHT MONITORING SERVICES – FINDINGS AND/OR OBSERVATIONS - 11 - III............................................... DETAILED REPORT: PROCESS AND/OR BEST PRACTICE RECOMMENDATIONS - 13 - I. EXECUTIVE SUMMARY • Brief statement regarding the federal and state requirements requiring integrity oversight monitoring services.
Detailed Report. This report will provide a line by line breakdown of all the orders that had direct debit collections matching your search criteria. Below is a description on some of the important columns.
i. Main Headings – Scrolling from left to right, the report is broken down into 3 main sections:
a. Order Details
Detailed Report. In-depth analyses are carried out on a series of global climate model simulations, mainly conducted within PRIMAVERA, to assess the impact of increased resolution, stochastic physics and explicit deep convection on the phase and amplitude of the diurnal cycle in precipitation. All datasets used for this report are listed in Table 1. Depending on the dataset, calculations are either performed using hourly data as e.g, for 4km ECMWF simulations or using 3 hourly data. TRMM 3B42 (Xxxxxxx et al., 2007) 3 hourly observational data is used as reference except if stated otherwise. For all analyses, except those presented in Section 3.1.3 using data from the Met Office and ECMWF IFS, the input data has been interpolated to a common 1x1 degree grid. The phase and amplitude of the first harmonic of the diurnal cycle of precipitation is calculated by applying a Fast-Fourier-Transformation (fft) on the long-term average sub-daily precipitation amounts. Next, the phase is further transformed from UTC into local time (LT), by using the following equation: LT = UTC + (longitude of location)/15 Besides analysing the diurnal cycle using a fft approach, the daily precipitation cycle is assessed separately for several regions: Southern Europe (35N-45N, 10W-40E), the tropics (20S-20N) and the Amazon (15S-0S, 80W-50W). Analyses are mainly carried out for the boreal summer season June-July-August (JJA). Due to a bug in the cmorization tool, time bounds have been set incorrectly for the PRIMAVERA EC-Earth data used in this study, which is related to the report at xxxxx://xxxxxx.xxx/EC-Earth/ece2cmor3/issues/354. Thus, 3-hourly data from EC-Earth simulations at 0,3,6,9,12,15,18,21 UTC represent the start of the averaging period. Here, we associated the precipitation during e.g. 0 and 3UTC to 1.5UTC and so on.
3.1 Phase and amplitude of the diurnal cycle of precipitations
Detailed Report. List of all businesses receiving grant funds including business location, business type, and grant amount. COUNTY will be responsible for funding grants based upon the detailed report provided.
