The inflation rate for the Retail Price Index (RPI) in the United Kingdom was 3.4 percent in February 2025, down from 3.6 percent in the previous month. From 2021 onwards, prices in the UK rose rapidly, with the RPI inflation rate peaking at 14.2 percent in October 2022. Although inflation fell in subsequent months, it wasn't until July 2023 that inflation fell below double digits, and as of late 2024, the RPI rate was still above three percent. The CPI and CPIH While the retail price index is still a popular method of calculating inflation, the consumer price index (CPI) is the current main measurement of inflation in the UK. There is also an additional price index, which includes some extra housing costs, known as the Consumer Price Index including homer occupiers' costs (CPIH) index, which is seen by the UK's Office of National Statistics as the official inflation rate. As of December 2024, the CPI inflation rate stood at 2.5 percent, while the CPIH rate was 3.5 percent. Core inflation down in 2024 Another way of measuring inflation is to strip out the volatility of energy and food prices and look at the underlying core inflation rate. As of December 2024, this was 3.2 percent, slightly higher than the overall CPI rate, but more aligned with the overall figure than it was in 2022 and 2023. When inflation peaked at 11.2 percent in October 2022, for example, core inflation stood at just 6.5 percent. After energy prices in 2023 fell relative to 2022, the overall inflation rate in the UK declined quite rapidly, with core inflation overtaking the overall rate in July 2023. During the most recent period of high inflation, core inflation peaked at 7.1 percent in May 2023, and while taking longer to fall than the overall figure, has generally been declining since then.

Inflation is an important measure of any country’s economy, and the Retail Price Index (RPI) is one of the most widely used indicators in the United Kingdom, with the rate expected to be 2.9 percent in 2024, compared with 9.7 percent in 2023. This followed 2022, when inflation reached a rate of 11.6 percent, by far the highest annual rate during this provided time period. CPI vs RPI Although the Retail Price Index is a commonly utilized inflation indicator, the UK also uses a newer method of calculating inflation, the Consumer Price Index. The CPI, along with the CPIH (Consumer Price Index including owner occupiers' housing costs) are usually preferred by the UK government, but the RPI is still used in certain instances. Increases in rail fares for example, are calculated using the RPI, while increases in pension payments are calculated using CPI, when this is used as the uprating factor. The use of one inflation measure over the other can therefore have a significant impact on people’s lives in the UK. High inflation gradually subsiding in 2024 Like the Retail Price Index, the Consumer Price Index inflation rate also reached a recent peak in October 2022. In that month, prices were rising by 11.1 percent and did not fall below double figures until April 2023. This fall was largely due to slower price increases in key sectors such as energy, which drove a significant amount of the 2022 wave of inflation. Inflation nevertheless remains elevated, fueled not only by high food inflation, but also by underlying core inflation. As of January 2024, the overall CPI inflation rate had fallen to four percent, and is expected to fall further throughout the year.

This set of daily plasmagrams/echograms comes from the IMAGE Radio Plasma Imager that studies the Earth's magnetophere in the 3 kHz to 3 MHz frequency range. RPI plasmagrams are visualized by plotting images in which received signal strength (color scale) is a function of echo delay (range in vertical scale) and radio-sounder frequency (horizontal scale) of the sounder pulses. Echoes that can be used to derive remote, long-range, magnetospheric electron-density profiles, appear as discrete traces on plasmagrams. These plasmagram traces are intermixed with vertical signatures with greater intensity at shorter ranges, corresponding to locally excited plasma resonances, and other vertical signatures that cover the entire listening period, i.e., the entire virtual-range scale, corresponding to various natural and/or man-made emissions propagating in space and/or local interference.

Collection of RPI Plasmagram images at University of Massachusetts Lowell, covering complete mission period from 2000-04-21 to 2005-12-18. Access to images is arranged via a webpage containing a query form with the time period of interest and options for search of expert-annotated plasmagrams. The query returns a list of qualifying plasmagrams with URLs pointing to images. RPI plasmagrams are visualized by plotting images in which received signal strength (color scale) is a function of echo delay (range in vertical scale) and radio-sounder frequency (horizontal scale) of the sounder pulses. Echoes that can be used to derive remote, long-range, magnetospheric electron-density profiles, appear as discrete traces on plasmagrams. These plasmagram traces are intermixed with vertical signatures with greater intensity at shorter ranges, corresponding to locally excited plasma resonances, and other vertical signatures that cover the entire listening period, i.e., the entire virtual-range scale, corresponding to various natural and/or man-made emissions propagating in space and/or local interference.

The Retail Price Index (RPI) is one of the main measures of inflation used to calculate the change in the price of goods and services within the British economy. In the fourth quarter of 2024 the index value was 391.2, indicating that the price for a fixed basket of goods had increased by more than 391 percent since 1987. The RPI inflation rate for December 2024 was 3.5 percent, down from 3.6 percent in the previous month. Inflation and UK living standards For UK consumers, high inflation is one of the main drivers of the ongoing cost of living crisis. With wages struggling to keep up with the pace of inflation for a long period between 2021 and 2023, UK households saw their living standards fall significantly. In 2022/23, real household disposable income in the UK is estimated to have fallen by 2.1 percent, which was the biggest fall in living standards since 1956. While there have been some signals that the crisis eased somewhat in 2024, such as falling energy and food inflation, an increasing share of UK households have reported increasing living costs since Summer 2024. Additional inflation indicators Aside from the Retail Price Index, the UK also produces other inflation indices such as the Consumer Price Index (CPI) and the Consumer Price Index including owner occupiers' housing costs (CPIH). While these particular indices measure consumer price increases slightly differently, they both provide an overall picture of rising prices. More specific inflation rates, such as by sector, are also produced, while other indices omit certain items, such as core inflation, which excludes food and energy inflation, to provide a more stable measure of inflation.

France RPI: Hypermarkets and Supermarkets (HS) data was reported at 125.610 1998=100 in Dec 2015. This records an increase from the previous number of 125.560 1998=100 for Nov 2015. France RPI: Hypermarkets and Supermarkets (HS) data is updated monthly, averaging 121.550 1998=100 from Jan 2005 (Median) to Dec 2015, with 132 observations. The data reached an all-time high of 127.470 1998=100 in Aug 2013 and a record low of 112.840 1998=100 in Apr 2005. France RPI: Hypermarkets and Supermarkets (HS) data remains active status in CEIC and is reported by French National Institute for Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.I014: Retail Price Index: 1998=100. Retail Price Index refers to price indexes of frequently purchased goods in large and predominantly food stores are developed from the data collected during the whole month for the calculation of the national Consumer Price Index (CPI). Large and Predominantly Food Stores is defined as supermarkets and hypermarkets. Hypermarkets are defined as predominantly food retail outlets with a surface higher than 2500 sqm. Supermarkets are retail outlets with more than 65% of his turnover in food products with a surface between 400sqm and 2500 sqm (but not the hard-discount outlets).

RPI passive wave measurement capturing voltage spectral density of the radio emissions in space as a function of frequency, typically between 3 and 1009 kHz. This operating frequency range was selected by the RPI team to provide optimal temporal resolution of the wave observations. Commonly used in the analysis of noise generators, spectral density is a frequency-dependent characteristic that describes how much power is generated by the emission source in a 1 Hz bandwidth. The original description of emissions was done in terms of thermal noise measurements, though the same approach also applies to non-thermal emissions such as AKR. CDF_DS_PT5M stores calibrated data from all three RPI antennas X, Y, and Z individually and a combined X+Y antenna channel. The data are presented as the Voltage Spectral Density (VSD), which is the root of power spectral density, measured in [V/root-Hz] units. Note that conversion of antenna voltage to electric field strength depends on the effective length of the receive antenna, and such conversion is not performed here. (See spase://SMWG/Instrument/IMAGE/RPI for a time history of the lengths of the three mutually orthogonal RPI dipole antennas.) RPI is capable of detecting input radio emissions above its noise floor of 5 nV/root-Hz, which is determined by the internal white noise of the RPI antenna pre-amplifiers. The VSD in RPI spectrogram data is presented in dB relative to 1 V/root-Hz (logarithmic scale), units of dB(V/root-Hz). The RPI instrument noise floor is 5 nV/root-Hz = -166 dB(V/root-Hz) at the receiver input. Software suggested by the science team for CDF file visualization: (1) Plotting tool at the CDAWeb portal, (2) For analysis beyond static image inspection, including color scale optimization, zooming, text export, alternative data representations in physical units, detailed frequency and time information, overlaid model fpe and fce graphs, and EPS quality figures, use BinBrowser software at UML, http://ulcar.uml.edu/rpi.html

This dataset includes paleomagnetic and rock magnetic analyses from four sediment cores collected on continental slope of Storfjorden (EG-02, EG-03, SV-04) and Kveithola (GeoB17603-3) trough‐mouth fans and two cores collected at the crest of the Bellsund (GS191-01PC) and Isfjorden (GS191-02PC) sediment drifts (NW Barents Sea). The dataset gave the opportunity to reconstruct variation of past geomagnetic field at high latitude for the last 22 kya and define the path of the virtual geomagnetic pole (VGP). Data are presented as two metadata table: one with definitions of the column heads and one with the core details; six tables with the data on the measured rock magnetic and paleomagnetic parameters and 3 tables with the results of data analyses and elaboration. List of tables is as follows: 1) Metadata: definition of columns heads; 2) Metadata: core details; 3) GS191-01PC: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GS191-01PC; 4) GS191-02PC: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GS191-02PC; 5) EG03: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core EG03; 6) EG02: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core EG02; 7) SV04: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core SV04; 8) GeoB17603-3: down-core variation of rock magnetic and paleomagnetic parameters [k (10E-05 SI); ARM (A/m); MDF (mT); NRM (A/m); MAD (°); Incl PCA (°); Decl PCA (°)] for Core GeoB17603-3; 9) Cores Correlation: GS191-01PC depth (cm) and ARM (A/m) down-core variations for core GS191-01PC (master core); GS191-02PC depth (cm), GS191-02PC depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core GS191-02PC and correlation tie points; GeoB17603-3 depth (cm), GeoB17603-3 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core GeoB17603-3 and correlation tie points; EG02 depth (cm), EG02 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core for core EG02 and correlation tie points; EG03 depth (cm), EG03 depth transferred to GS191-01PC depth (cm), ARM (A/m) down-core and correlation tie points; SV04 depth (cm), SV04 transferred to GS191-01PC (cm), ARM (A/m) down-core for core SV04 and correlation tie points; 10) Age model: age model for Core GS191-01PC; GS191-02PC; EG02; EG03; SV04 and correlation tie points; 11) NBS stack: paleomagnetic inclination, declination and RPI variations for NBS22.2k stack. In order to define high-resolution correlation between the cores the along-core variation of rock magnetic and paleomagnetic parameters (Sagnotti et al., 2011; Caricchi et al., 2018; Caricchi et al., 2019) have been integrated with the distribution of characteristic lithofacies (Lucchi et al., 2013), and the available age constraints (Sagnotti et al., 2011; Caricchi et al., 2018, Caricchi et al., 2019; Caricchi et al., 2020). Core to core correlation has been reconstructed by means of the StratFit software (Sagnotti and Caricchi, 2018), which is based on the Excel forecast function and linear regression between subsequent couples of selected tie-points. The data are presented as one Excel sheet with eleven tables and in tab-delimited ASCII format in the zip folder: 2022-028_Caricchi-et-al_data-txt.zip.

This dataset contains the known hydrocarbon reservoirs within the study area of the Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB) as part of Phase 1, Natural Reservoirs Quality Analysis. The final values for Reservoir Productivity Index (RPI) and uncertainty (in terms of coefficient of variation, CV) are included. RPI is in units of liters per MegaPascal-second (L/MPa-s), quantified using permeability, thickness of formation, and depth. A higher RPI is more optimal. Coefficient of Variation (CV) is the ratio of the standard deviation to the mean RPI for each reservoir. A lower CV is more optimal. Details on these metrics can be found in the Reservoirs_Methodology_Memo.pdf uploaded in the associated "Natural Reservoir Analysis" dataset linked below.

The files included in this submission contain all data pertinent to the methods and results of this task's output, which is a cohesive multi-state map of all known potential geothermal reservoirs in our region, ranked by their potential favorability. Favorability is quantified using a new metric, Reservoir Productivity Index, as explained in the Reservoirs Methodology Memo (included in zip file). Shapefile and images of the Reservoir Productivity and Reservoir Uncertainty are included as well (hover over file display names to see actual file names in bottom-left corner of screen). This shapefile contains the data associated with the GPFA-AB Phase 1 Task 2, Natural Reservoirs Quality Analysis, in a format that can be uploaded into any GIS software. The final values for Reservoir Productivity Index (RPI) and uncertainty (in terms of coefficient of variation, CV) are held in columns "RPI" and "RPI CV". RPI is in units of liters per MegaPascal-second (L/MPa-s), quantified using permeability, thickness of formation, and depth. A higher RPI is more optimal.Coefficient of Variation (CV) is the ratio of the standard deviation to the mean RPI for each reservoir. A lower CV is more optimal. Details on these metrics can be found in the Reservoirs_Methodology_Memo.pdf. *Newer version exists - see link below

Means (±standard deviation), p-values and effect size for the differences in anthropometry, motor performance and physical activity between Peru (Barranco) and Brazil (Cariri) for boys and girls.

Integrated Ocean Drilling Program (IODP) Site U1308 (central North Atlantic) records paleomagnetic directional and relative paleointensity (RPI) variations for the last 1.5 Myr, in 110 m of the sediment sequence at a mean sedimentation rate of 7.3 cm/kyr. A detailed benthic oxygen isotope record was combined with RPI to produce an integrated, high-resolution magneto-isotopic stratigraphy for Site U1308. Apart from the well-known polarity reversals in this interval, the Punaruu excursion is recorded at 1092 ka and the Cobb Mountain Subchron in the 1182-1208 ka interval. The paleointensity proxies are determined as slopes of NRM versus ARM and NRM versus ARMAQ (ARM acquisition) with linear correlation coefficients to monitor the quality of the linear fit. The RPI record for Site U1308 is compared with the three other paleointensity records (one from the Western Equatorial Pacific and two from the North Atlantic) that cover the same time interval and have accompanying oxygen isotope records. The Match protocol of Lisiecki and Lisiecki (2002) is used to optimize the correlation of paleointensity records. Beginning with the original (published) age models for each record, the Match routine is used to optimize the RPI correlations to Site U1308, with checks to ensure compatibility with oxygen isotope records. Squared wavelet coherence (WTC) indicates significant improvement in RPI (and oxygen isotope) correlations after matching each RPI record to Site U1308, particularly for periods > 10 kyr. The level of coherence for the Atlantic RPI records and the lower resolution Pacific record implies synchronous global variability (at scales > 10 kyr) that can be attributed to the axial dipole geomagnetic field.

The Regional Price Index contrasts the cost of a common basket of goods and services at a number of regional locations to the Perth metropolitan area. The RPIs were commissioned to assist with the calculation of the Western Australian State Government’s regional district allowance, and it has been used to assist in policy decision-making. Show full description

UPDATE: AN ERROR WAS FOUND IN THE TRAINING DATA PREPARATION. AN UPDATED VERSION HAS BEEN CREATED. THIS VERSION SIGNIFICANTLY UNDERESTIMATES VALUES, BUT REPRESENTS TRENDS DECENTLY, PLEASE SEE THE UPDATED VERSION OF THIS REPOSITORY FOR BETTER PREDICTIONS.

Repository includes maps describing the depth (cm) to the top of any water or root soil restrictive layer (resdept) as defined by United States soil survey program.

These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.

The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds.

Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal.

File Name Details:

ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for the training sample (file ending _CV_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are >3000).

Elements are separated by underscore (_) in the following sequence:

property_r_depth_cm_geometry_model_additional_elements.extension

Example: resdept_r_cm_2D_QRF.tif

Indicates depth to top of restriction (resdept; in cm) using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions.

The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below).

_95PI_h: Indicates the layer is the upper 95% prediction interval value.

_95PI_l: Indicates the layer is the lower 95% prediction interval value.

_95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI.

References

Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma

In February 2025, the Consumer Price Index including owner occupiers' housing costs (CPIH) inflation rate of the United Kingdom was 3.7 percent, unchanged from the previous month. The inflation rate fell noticeably after the COVID-19 pandemic, but rose sharply between Spring 2021 and Autumn 2022. After peaking at 9.6 percent in October 2022, CPIH inflation declined throughout 2023 and into 2024, falling to 2.6 percent by September of that year, before increasing again in recent months. Cost of living problems persist into 2025 Although it is likely that the worst of the recent inflation surge may have passed, the issues caused by it look set to linger into 2025 and beyond. While the share of households experiencing living cost rises has fallen from 91 percent in August 2022, to 45 percent in July 2024, this share rose towards the end of the year, with more than half of households reporting rising costs in December. Even with lower inflation, overall consumer prices have already increased by around 20 percent in the last three years, rising to almost 30 percent for food prices, which lower income households typically spend more of their income on. The significant increase in people relying on food banks across the UK, is evidence of the magnitude of this problem, with approximately 3.12 million people using food banks in 2023/24. Other measure of inflation While the CPIH inflation rate displayed here is the preferred index of the UK's Office of National Statistics, the Consumer Price Index (CPI) is often more prominently featured in the media in general. An older index, the Retail Price Index (RPI) is also still used by the government to calculate certain taxes, and rail fare rises. Other metrics include the core inflation rate, which measures prices increases without the volatility of food and energy costs, while price increases in goods and services can also be tracked separately. The inflation rate of individual sectors can also be measured, and as of December 2024, prices were rising fastest in the communications sector, at 6.1 percent, with costs falling in the transport and furniture sectors.

The National Renewable Energy Laboratory, Southern Methodist University Geothermal Laboratory, Eastman Chemical, Turbine Air Systems, and the Electric Power Research Institute are evaluating the feasibility of using geothermal heat to improve the efficiency of natural gas power plants. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of the Sabine Uplift. The study is focused on determining the potential for a geothermal reservoir within a 10 km radius of the site as defined by data from existing geological studies and cross-sections within the depths of 2,100 to 3,400 meters. Wells within a 20 km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, and oil and gas field porosity and permeability. The geothermal reservoir model is based on the multiple formation top data sources, published literature data, and well log interpretations within the 10 km radius. Area thickness estimates, reservoir extent bounding parameters, potential flow rates, and temperatures are combined to calculate a reservoir productivity index and develop a reservoir production model. Historical fluid volumes production data are used as an independent check for the reservoir productivity index and production model results. The reservoir parameters calculated here are being used for the surface engineering model to determine the economic viability of using geothermal fluids for a deep direct use application at this site. The data files are submitted as separate workbooks in 'content model' format, including: Well Fluid Production, Heat Flow, and Geologic Reservoir.

Definition of Hydrographic Unit based on the Sander: Environmental variable for calculating the RPI (River Fish Index) and relating to a territorial area that has been demarcated according to faunistic criteria. The perimeter concerns 17 municipalities, i.e. 24 680 ha.

The Environmental Department releases river water quality monitoring data, including River Pollution Index (RPI) and monitored values of major pollutants. Due to the need for monthly on-site sampling, laboratory testing and data quality control procedures, monitoring data is usually provided every other month.

The average inflation rate in the United Kingdom was forecast to continuously decrease between 2024 and 2029 by in total 0.6 percentage points. The inflation is estimated to amount to two percent in 2029. Following the definitions provided by the International Monetary Fund, this indicator measures inflation based upon the year on year change in the average consumer price index. The latter expresses a country's average level of prices based on a typical basket of consumer goods and services. Depicted here is the year-on-year change in said index measure, expressed in percent.Find more statistics on other topics about the United Kingdom with key insights such as the total population, the national debt, and the share in the global GDP adjusted for purchasing power parity.