United Kingdom's main stock market index, the GB100, fell to 8997 points on July 15, 2025, losing 0.01% from the previous session. Over the past month, the index has climbed 1.37% and is up 10.19% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on July of 2025.

The Office of Policy and Management (OPM) prepares the Public Investment Community (PIC) index not later than July 15 annually, pursuant to §7-545 of the Connecticut General Statutes (CGS). The PIC index measures the relative wealth and need of Connecticut’s towns by ranking them in descending order by their cumulative point allocations for: (1) per capita income; (2) adjusted equalized net grand list per capita; (3) equalized mill rate; (4) per capita aid to children receiving Temporary Family Assistance program benefits; and (5) unemployment rate. Pursuant to CGS §7-545 the PIC index includes each town that has a cumulative point ranking in the top quartile of the PIC Index (i.e. the 42 towns with the highest number of points). When a town’s ranking falls below the top quartile in a given fiscal year, the town's designation as a Public Investment Community continues for that year and the following four fiscal years. As a result, the PIC index includes certain towns carried over from previous fiscal years. The PIC index determines eligibility for several financial assistance programs that various agencies administer, including: -Urban Action Bond Assistance -Small Town Economic Assistance Program -Community Economic Development Program -Residential Mortgage Guarantee Program -Education Cost Sharing -Malpractice Insurance Purchase Program -Connecticut Manufacturing Innovation Fund -Enterprise Corridor Zone Designation Most of the towns included on the PIC index are eligible to elect for assistance under the Small Town Economic Assistance Program (STEAP) in lieu of Urban Action Bond assistance, pursuant to CGS §4-66g(b). An eligible town’s legislative body (or its board of selectmen if the town’s legislative body is the town meeting) must vote to choose STEAP assistance and the town must notify OPM following the vote. STEAP election is valid for four years and the statute allows extensions for additional four-year periods. STEAP election is not available for Ansonia, Bridgeport, Bristol, Danbury, East Hartford, Enfield, Groton, Hartford, Killingly, Manchester, Meriden, Middletown, New Britain, New Haven, New London, Norwalk, Norwich, Stamford, Torrington, Vernon, Waterbury, West Hartford, West Haven, and Windham. Pursuant to CGS §7-545, the following municipalities are also Public Investment Communities: Groton Montville Preston Scotland Thomaston Thompson Voluntown Wethersfield

Indonesia's main stock market index, the JCI, rose to 7138 points on July 15, 2025, gaining 0.58% from the previous session. Over the past month, the index has climbed 0.29%, though it remains 1.19% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Indonesia. Indonesia Stock Market (JCI) - values, historical data, forecasts and news - updated on July of 2025.

Detailed price prediction analysis for Colony Avalanche Index on Jul 15, 2025, including bearish case ($95.653), base case ($105.311), and bullish case ($115.031) scenarios with Buy trading signal based on technical analysis and market sentiment indicators.

The Minerals Management Service (MMS) of the U. S. Department of the Interior funded the Deepwater Physical Oceanography Reanalysis and Synthesis of Historical Data Study in the Gulf of Mexico. MMS awarded the contract to the Texas A&M Research Foundation in July 1998. The basic study area is bounded by the shelf edge and the 25DGN latitude, which is the southern boundary; it extends from sea surface to sea floor. MMS has four objectives for the study. First is to create an inventory of physical oceanographic data and compile it into a single database on a CD-ROM. Second is to conduct analyses and interpretations of the physical oceanographic data to identify physical processes and phenomena. Third is to produce a climatology of the processes from available data and analyses and to prioritize the processes in terms of importance to improved understanding, simulation, and prediction of deepwater circulation. Fourth is to provide criteria and constraints useful in design of future field observations and numerical modeling efforts. Study results will provide MMS with information needed to direct its resources more efficiently and effectively in the review and assessment of potential environmental impacts of offshore oil and gas operations in the deepwater Gulf of Mexico.

Interactive historical chart showing the daily level of the CBOE VIX Volatility Index back to 1990. The VIX index measures the expectation of stock market volatility over the next 30 days implied by S&P 500 index options.

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CPI: Semimonthly: FB: Food: SC: SD: Soft Drinks data was reported at 158.616 16Jul2018-31Jul2018=100 in 15 Apr 2025. This records an increase from the previous number of 157.975 16Jul2018-31Jul2018=100 for 31 Mar 2025. CPI: Semimonthly: FB: Food: SC: SD: Soft Drinks data is updated daily, averaging 63.936 16Jul2018-31Jul2018=100 from Jan 1995 (Median) to 15 Apr 2025, with 727 observations. The data reached an all-time high of 158.616 16Jul2018-31Jul2018=100 in 15 Apr 2025 and a record low of 11.829 16Jul2018-31Jul2018=100 in 15 Jan 1995. CPI: Semimonthly: FB: Food: SC: SD: Soft Drinks data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.I002: Consumer Price Index: Second Half July 2018=100. [COVID-19-IMPACT]

CPI: Semimonthly: FB: Food: Other Food: Condim: Others data was reported at 145.056 16Jul2018-31Jul2018=100 in 15 Apr 2025. This records an increase from the previous number of 143.375 16Jul2018-31Jul2018=100 for 31 Mar 2025. CPI: Semimonthly: FB: Food: Other Food: Condim: Others data is updated daily, averaging 67.529 16Jul2018-31Jul2018=100 from Jan 1995 (Median) to 15 Apr 2025, with 727 observations. The data reached an all-time high of 145.056 16Jul2018-31Jul2018=100 in 15 Apr 2025 and a record low of 14.435 16Jul2018-31Jul2018=100 in 15 Jan 1995. CPI: Semimonthly: FB: Food: Other Food: Condim: Others data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.I002: Consumer Price Index: Second Half July 2018=100. [COVID-19-IMPACT]

Year type designates grouping labels assigned for analysis of covariance models.

The Minerals Management Service (MMS) of the U. S. Department of the Interior funded the Deepwater Physical Oceanography Reanalysis and Synthesis of Historical Data Study in the Gulf of Mexico. MMS awarded the contract to the Texas A&M Research Foundation in July 1998. The basic study area is bounded by the shelf edge and the 25DGN latitude, which is the southern boundary; it extends from sea surface to sea floor. MMS has four objectives for the study. First is to create an inventory of physical oceanographic data and compile it into a single database on a CD-ROM. Second is to conduct analyses and interpretations of the physical oceanographic data to identify physical processes and phenomena. Third is to produce a climatology of the processes from available data and analyses and to prioritize the processes in terms of importance to improved understanding, simulation, and prediction of deepwater circulation. Fourth is to provide criteria and constraints useful in design of future field observations and numerical modeling efforts. Study results will provide MMS with information needed to direct its resources more efficiently and effectively in the review and assessment of potential environmental impacts of offshore oil and gas operations in the deepwater Gulf of Mexico.

United States - ICE BofA 15+ Year US Corporate Index Effective Yield was 5.86% in July of 2025, according to the United States Federal Reserve. Historically, United States - ICE BofA 15+ Year US Corporate Index Effective Yield reached a record high of 9.35 in October of 2008 and a record low of 2.83 in August of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - ICE BofA 15+ Year US Corporate Index Effective Yield - last updated from the United States Federal Reserve on July of 2025.

Portugal's main stock market index, the PSI 20, closed flat at 7707 points on July 15, 2025. Over the past month, the index has climbed 2.14% and is up 13.75% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Portugal. Portugal Stock Market (PSI20) - values, historical data, forecasts and news - updated on July of 2025.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Various climate variables summary for all 15 subregions based on Bureau of Meteorology Australian Water Availability Project (BAWAP) climate grids. Including

1. Time series mean annual BAWAP rainfall from 1900 - 2012.

2. Long term average BAWAP rainfall and Penman Potentail Evapotranspiration (PET) from Jan 1981 - Dec 2012 for each month

3. Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P (precipitation); (ii) Penman ETp; (iii) Tavg (average temperature); (iv) Tmax (maximum temperature); (v) Tmin (minimum temperature); (vi) VPD (Vapour Pressure Deficit); (vii) Rn (net radiation); and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend.

4. Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009).

As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).

There are 4 csv files here:

BAWAP_P_annual_BA_SYB_GLO.csv

Desc: Time series mean annual BAWAP rainfall from 1900 - 2012.

Source data: annual BILO rainfall

P_PET_monthly_BA_SYB_GLO.csv

long term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month

Climatology_Trend_BA_SYB_GLO.csv

Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend

Risbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv

Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).

Dataset History

Dataset was created from various BAWAP source data, including Monthly BAWAP rainfall, Tmax, Tmin, VPD, etc, and other source data including monthly Penman PET, Correlation coefficient data. Data were extracted from national datasets for the GLO subregion.

BAWAP_P_annual_BA_SYB_GLO.csv

Desc: Time series mean annual BAWAP rainfall from 1900 - 2012.

Source data: annual BILO rainfall

P_PET_monthly_BA_SYB_GLO.csv

long term average BAWAP rainfall and Penman PET from 198101 - 201212 for each month

Climatology_Trend_BA_SYB_GLO.csv

Values calculated over the years 1981 - 2012 (inclusive), for 17 time periods (i.e., annual, 4 seasons and 12 months) for the following 8 meteorological variables: (i) BAWAP_P; (ii) Penman ETp; (iii) Tavg; (iv) Tmax; (v) Tmin; (vi) VPD; (vii) Rn; and (viii) Wind speed. For each of the 17 time periods for each of the 8 meteorological variables have calculated the: (a) average; (b) maximum; (c) minimum; (d) average plus standard deviation (stddev); (e) average minus stddev; (f) stddev; and (g) trend

Risbey_Remote_Rainfall_Drivers_Corr_Coeffs_BA_NSB_GLO.csv

Correlation coefficients (-1 to 1) between rainfall and 4 remote rainfall drivers between 1957-2006 for the four seasons. The data and methodology are described in Risbey et al. (2009). As described in the Risbey et al. (2009) paper, the rainfall was from 0.05 degree gridded data described in Jeffrey et al. (2001 - known as the SILO datasets); sea surface temperature was from the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST) on a 1 degree grid. BLK=Blocking; DMI=Dipole Mode Index; SAM=Southern Annular Mode; SOI=Southern Oscillation Index; DJF=December, January, February; MAM=March, April, May; JJA=June, July, August; SON=September, October, November. The analysis is a summary of Fig. 15 of Risbey et al. (2009).

Dataset Citation

Bioregional Assessment Programme (2014) GLO climate data stats summary. Bioregional Assessment Derived Dataset. Viewed 18 July 2018, http://data.bioregionalassessments.gov.au/dataset/afed85e0-7819-493d-a847-ec00a318e657.

Dataset Ancestors

• Derived From Natural Resource Management (NRM) Regions 2010

• Derived From Bioregional Assessment areas v03

• Derived From BILO Gridded Climate Data: Daily Climate Data for each year from 1900 to 2012

• Derived From Bioregional Assessment areas v01

• Derived From Bioregional Assessment areas v02

• Derived From GEODATA TOPO 250K Series 3

• Derived From NSW Catchment Management Authority Boundaries 20130917

• Derived From Geological Provinces - Full Extent

• Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)

Mexico Consumer Price Index (CPI): Semimonthly: FH: FA: Appliances: Electronic: Audio Players data was reported at 102.222 16Jul2018-31Jul2018=100 in 15 Apr 2025. This records a decrease from the previous number of 105.241 16Jul2018-31Jul2018=100 for 31 Mar 2025. Mexico Consumer Price Index (CPI): Semimonthly: FH: FA: Appliances: Electronic: Audio Players data is updated daily, averaging 100.512 16Jul2018-31Jul2018=100 from Jun 2002 (Median) to 15 Apr 2025, with 548 observations. The data reached an all-time high of 111.547 16Jul2018-31Jul2018=100 in 31 Jan 2023 and a record low of 91.027 16Jul2018-31Jul2018=100 in 15 Jul 2019. Mexico Consumer Price Index (CPI): Semimonthly: FH: FA: Appliances: Electronic: Audio Players data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.I002: Consumer Price Index: Second Half July 2018=100. [COVID-19-IMPACT]

Domains sorted by creation date for July 15, 1985, in our daily-updated WHOIS database. Ideal for trend analysis, market research, and more.

Domains sorted by creation date for July 15, 2010, in our daily-updated WHOIS database. Ideal for trend analysis, market research, and more.

This dataset contains community leaf area index (LAI) in the Jena-Ecotron Experiment in 2012. This experiment was conducted in the Montpellier European Ecotron (CNRS, France), an advanced controlled environment facility for ecosystem research, and aimed at understanding the impact of plant species richness (4 vs. 16 species) for ecosystem carbon and water fluxes. The soil monoliths used in this experiment contained plant communities originating from the long- term Jena Experiment (50°57.1' N, 11°37.5' E, 130 m above sea level; mean annual temperature 9.3°C, mean annual precipitation 587 mm) established in May 2002. Twelve plots were selected for the Jena-Ecotron study according to the following criteria: (1) the four functional groups grasses, legumes, small and tall herbs were present, (2) realized species numbers were close to sown species richness, and (3) plots were equally distributed across the experimental field site to account for different soil textures. Large monoliths (2 m² surface area, diameter of 1.6 m, 2 m depth with a weight of 7 to 8 tons) including intact soil and vegetation were excavated in December 2011 and placed in lysimeters. In March 2012, before the start of the vegetation growth, the lysimeters were transported and installed in the Macrocosms platform of the Montpellier European Ecotron. Community leaf area index (LAI) was measured with a portable LAI-2000 plant canopy analyzer (LI-COR, Lincoln, USA) on 15th July 2012. LAI was measured under diffuse light (evening) by taking one reference measurement above the canopy and five measurements near ground level within the center of each lysimeter. The zenith angle was restricted to 0-43° in order to minimize the edge effect (Hyer & Goetz, 2004) inherent to a canopy with a surface of 2m². In lysimeters with a high proportion of one rosulate species (Plantago media) with leaves laying very close to the ground, the values measured with the LAI-2000 were replaced with the average value of two leaf area measurements using a LI-3100 leaf area meter (LI-COR, Lincoln, USA) from two rectangles of 0.2 × 0.5 m per plot.

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Domains sorted by creation date for July 15, 2002, in our daily-updated WHOIS database. Ideal for trend analysis, market research, and more.