The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal accumulated amounts for various stations around the world. These charts are created for different scales of time (30, 90, 365 days). Each station has a graphic that contains two charts. The first chart in the graphic is a time series in the format of a line graph, representing accumulated precipitation for each day in the time series compared to the accumulated normal amount of precipitation. The second chart is a bar graph displaying actual daily precipitation. The total accumulation and surplus or deficit amounts are displayed as text on the charts representing the entire time scale, in both inches and millimeters. The graphics are updated daily and the graphics reflect the updated observations and accumulated precipitation amounts including the latest daily data available. The available graphics are rotated, meaning that only the most recently created graphics are available. Previously made graphics are not archived.

This dataset provides a gridded analysis of daily surface air temperature over global land areas, including daily maximum (Tmax), minimum (Tmin) temperatures. Spanning from 1979 to the present, the data is presented on 0.5-degree latitude/longitude grids, aligning with the resolution of CPC's gauge-based global daily precipitation analysis. The construction of this dataset considers orographic effects. Its primary purpose is to support climate monitoring and forecast verification activities. Input data originates from the CPC archive of GTS (Global Telecommunication System) daily reports, incorporating Tmax and Tmin data from approximately 6,000 to 7,000 global stations. Refer this for technical documentation.

Fork this notebook to get started on accessing data in the BigQuery dataset by writing SQL queries using the BQhelper module.

Context

The CPC is the result of a partnership between the EPO and the USPTO in their joint effort to develop a common, internationally compatible classification system for technical documents, in particular patent publications, which will be used by both offices in the patent granting process.

Content

Cooperative Patent Classification Data contains the scheme and definitions of the Cooperative Patent Classification system for classifying patent documents.

Acknowledgments

“Cooperative Patent Classification” by the EPO and USPTO, for public use. Modifications have been made to parse the XML description sections to extract references to other classification symbols.

Data Origin: https://bigquery.cloud.google.com/dataset/patents-public-data:cpc

Banner photo by Helloquence on Unsplash

This dataset contains National Centers for Environmental Prediction/Climate Prediction Center (NCEP/CPC) Hourly Precipitation data in QC format for the GCIP LSA-NW EAOP-99 domain and time period. This dataset was formed by extracting incremental precipitation values that fell on the hour. All raw precipitation data, including data that do not fall on the hour, can be found in the GCIP/EOP Surface: Precipitation NCEP/CPC Gage Only Hourly Dataset.

A station observation-based global land monthly mean surface air temperature dataset at 0.5 0.5 latitude-longitude resolution for the period from 1948 to the present . It uses a combination of two large individual data sets of station observations collected from the Global Historical Climatology Network version 2 and the Climate Anomaly Monitoring System (GHCN + CAMS), so it can be regularly updated in near real time with plenty of stations and (2) some unique interpolation methods, such as the anomaly interpolation approach with spatially-temporally varying temperature lapse rates derived from the observation-based Reanalysis for topographic adjustment.

This dataset contains the bias-corrected CPC MORPHing technique (CMORPH) global precipitation analyses, version 1, and is obtained from the NOAA Climate Data Record [https://www.ncei.noaa.gov/products/climate-data-records/precipitation-cmorph]. The following description is from the NOAA Climate Data Record CMORPH dataset page: This data set is for the bias-corrected, reprocessed CPC Morphing technique (CMORPH) high-resolution global satellite precipitation estimates. The CMORPH satellite precipitation estimates are created in two steps. First, the purely satellite-based global fields of precipitation are constructed through integrating Level 2 retrievals of instantaneous precipitation rates from all available passive microwave measurements aboard low earth orbiting platforms. Bias in these integrated satellite precipitation estimates is then removed through comparison against CPC daily gauge analysis over land and adjustment against the Global Precipitation Climatology Project (GPCP) merged analysis of pentad precipitation over ocean. The bias corrected CMORPH satellite precipitation estimates are created on an 8 km by 8 km grid over the global domain from 60 degrees S to 60 degrees N and in a 30-minute interval from January 1, 1998. Due to the delay of some input data sets, this formal version (Version 1) bias corrected CMORPH is produced manually once a month at a latency of 3-4 months. For the CDR production, the bias corrected CMORPH generated at its native resolution of 8 km by 8 km / 30-minute is upscaled to form THREE sets of data files of different time/space resolution for improved user experience: a) the full-resolution CMORPH data; Output variable: precipitation rate in mm/hour; spatial resolution: 8 km by 8km (at equator); spatial coverage: global (60S-60N); temporal resolution: 30min; data period: January 1, 1998 to the present b) Hourly CMORPH; Output variable: precipitation rate in mm/hour; spatial resolution: 0.25 degrees latitude/longitude;...

The monthly data set consists of a file containing 1/2 degree monthly averaged soil moisture water height equivalents for the globe from 1948 onwards. Values are model-calculated and not measured directly. Soil moisture is estimated by a one-layer hydrological model (Huang et al., 1996; van den Dool et al, 2003). The model takes observed precipitation and temperature and calculates soil moisture, evaporation and runoff.

The Climate Prediction Center releases a US Hazards Outlook daily, Monday through Friday. The product highlights regions of anticipated hazardous weather during the next 3-7 and 8-14 days and examples include heavy snow, high winds, flooding, extreme heat and cold and severe thunderstorms. The product highlights regions of anticipated hazardous weather during the next 3-7 and 8-14 days. Three separate files are available for download for each time period. A soils shapefile (and KMZ) contain severe drought and enhanced wildfire risk hazards. A temperature file contains temperature, wind, and wave hazards, and a precipitation file contains rain, snow, and severe weather hazards. The contents of these file are mashed up to create one composite graphic per time period as well as being displayed on an interactive Google Map

The GPM Ground Validation NOAA CPC Morphing Technique (CMORPH) IFloodS dataset consists of global precipitation analyses data produced by the NOAA Climate Prediction Center (CPC). The Iowa Flood Studies (IFloodS) campaign was a ground measurement campaign that took place in eastern Iowa from May 1 to June 15, 2013. The goals of the campaign were to collect detailed measurements of precipitation at the Earth's surface using ground instruments and advanced weather radars and, simultaneously, collect data from satellites passing overhead. The CPC morphing technique uses precipitation estimates from low orbiter satellite microwave observations to produce global precipitation analyses at a high temporal and spatial resolution. Data has been selected for the Iowa Flood Studies (IFloodS) field campaign which took place from April 1, 2013 to June 30, 2013. The dataset includes both the near real-time raw data and bias corrected data from NOAA in binary and netCDF format.

Precipitation from five kinds of satellite estimates and the NCEP/NCAR reanalysis model output are combined for global coverage monthly precipitation values. The standard products merge only the 5 kinds of satellite estimates (GPI, OPI, SSM/I scattering, SSM/I emission and MSU). The enhanced products merge the satellite estimates with the blended NCEP/NCAR Reanalysis precipitation. Both products are available as monthly totals, pentads and long term monthly means on a global 2.5 degree latitude-longitude grid. All data is in the netCDF format.

Monthly U.S. reported precipitation amounts in hundredths of inches (ex 100 is 1.00 inches) generated from the GTS metar(hourly) and synoptic(6-hourly)observations for selected cities based on the Weekly Weather and Crop Bulletin station list

CPC Unified Gauge-Based Analysis of Daily Precipitation over CONUS at PSD: Gridded Monthly Values. Monthly Values after 2006 are from the real time files (RT)

Observational reports of daily snow fall (1200 UTC to 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network and NWS Cooperative Observer Network (COOP). Reports from approximately 2,000 stations across the US including Alaska and Hawaii are sent on a daily basis to the Climate Prediction Center (CPC).CPC processes these reports once per day. All reports for the same day are put into an ASCII text file whose name includes the date of observation. These data are used by CPC in its role of supporting the Joint Agricultural Weather Facility (JAWF).

Monthly global soil moisture, runoff, and evaporation data sets produced by the Leaky Bucket model at 0.5? ? 0.5? resolution for the period from 1948 to the present. The land model is a one?layer ?bucket? water balance model, while the driving input fields are Climate Prediction Center monthly global precipitation over land, which uses over 17,000 gauges worldwide, and monthly global temperature from GHCN-CAMS (Fan and Van den Dool 2008). The output consists of global monthly soil moisture, evaporation, and runoff, starting from January 1948. A distinguishing feature of this data set is that all fields are updated monthly, which greatly enhances utility for near real time purposes. Data validation shows that the land model does well; both the simulated annual cycle and interannual variability of soil moisture are reasonably good against the limited observations in different regions. Refer to these papers: Fan, Y. and H. van den Dool (2004), Climate Prediction Center global monthly soil moisture data set at 0.5? resolution for 1948 to present, J. Geophys. Res., 109, D10102, doi:10.1029/2003JD004345. Fan, Y. and H. van den Dool (2008), A global monthly land surface air temperature analysis for 1948?present, J. Geophys. Res., 113, D01103, doi:10.1029/2007JD008470.

description: This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two components, the land analysis (PREC/L) and oceanic analysis (PREC/O). The land analysis is defined by interpolation of gauge observations from the Global Historical Climatology Network (GHCN) version 2, and the Climate Prediction Center Climate Anomaly Monitoring System (CAMS) dataset through the Optimal Interpolation (OI) algorithm. The oceanic analysis is defined by Empirical Orthogonal Function (EOF) reconstruction of historical gauge observation from islands and atolls and land. The output resolutions are 0.5deg, 1.0deg, and 2.5deg latitude/longitude for the PREC/L, and 2.5deg latitude/longitude for PREC/O. The analysis covers time period from 1948 to current and is updated on real time basis. The data set is available at format of ASCII and binary.; abstract: This global monthly precipitation analysis is called the Climate Prediction Center (CPC) Precipitation Reconstruction (PREC). This analysis consists of two components, the land analysis (PREC/L) and oceanic analysis (PREC/O). The land analysis is defined by interpolation of gauge observations from the Global Historical Climatology Network (GHCN) version 2, and the Climate Prediction Center Climate Anomaly Monitoring System (CAMS) dataset through the Optimal Interpolation (OI) algorithm. The oceanic analysis is defined by Empirical Orthogonal Function (EOF) reconstruction of historical gauge observation from islands and atolls and land. The output resolutions are 0.5deg, 1.0deg, and 2.5deg latitude/longitude for the PREC/L, and 2.5deg latitude/longitude for PREC/O. The analysis covers time period from 1948 to current and is updated on real time basis. The data set is available at format of ASCII and binary.

The Climate Prediction Center (CPC) issues a probabilistic one-month precipitation outlook for the United States twice a month. CPC issues an initial monthly outlook with a lead time of 0.5 months on the third Thursday of every month. CPC issues an updated version of the monthly outlook with a lead time of 0.0 months on the last day of each month. For example, in mid-January, CPC will issue a One-Month Probabilistic Precipitation Outlook for February. An updated version of this outlook (valid for February) would then be issued at the end of January. New outlooks, valid for March, would then be released in mid-February and the end of February, respectively. CPC expresses the outlooks in a 3-category probabilistic format as the chance the total precipitation for the period will be above, below, or near median. CPC bases its definition of above median, near median, and below median by fitting a Gamma distribution to a thirty year climatology and dividing this distribution into equally likely thirds. Note that the base period for the thirty year climatology (currently beginning in 1981 and ending in 2010) is updated once per decade. CPC indicates the probability of the most likely category with shaded contours and labels the centers of maximum probability with the letters "A" (for Above Median), "B" (for Below Median), or "N" (for Near Median). For areas where a favored category cannot be determined, CPC indicates those areas with an "EC" meaning "Equal Chances". CPC also accompanies the outlook maps with a technical discussion of the meteorological and climatological basis for the outlooks. CPC may include analysis of statistical and numerical models, meteorological and sea-surface temperature patterns, trends and past analogs, and confidence factors in this technical discussion.

Observational reports of daily precipitation (1200 UTC to 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network; NWS Cooperative Observer Network (COOP); the Hydrometeorological Automated Data System (HADS) network; the SNOTEL (SNOwpack TELemetry) network; and the Integrated Flood Observing and Warning System (IFLOWS) network. Reports from approximately 9,000 stations across the US including Alaska, Hawaii, and Puerto Rico are sent on a daily basis to the Climate Prediction Center (CPC). During the winter season when the type of precipitation is frozen, the amount reported is the liquid equivalent. CPC processes these reports once per day. All reports for the same day are put into an ASCII text file whose name includes the date of observation. These data are used by CPC in its role of supporting the Joint Agricultural Weather Facility (JAWF).

Daily U.S. minimum and maximum temperatures in whole degrees Fahrenheit and reported and estimated precipitation amounts in hundredths of inches(ex 100 is 1.00 inches) generated from the Global Telecommunications System (GTS) metar(hourly) and synoptic(6-hourly) observations.

The Climate Prediction Center (CPC) issues a series of thirteen probabilistic three-month precipitation outlooks for the United States. CPC issues the thirteen outlooks each month with lead times from 0.5 months to 12.5 months. For example, in mid-January, CPC will issue Three-Month Precipitation Outlooks for February through April, March through May, April through June, and so on into February through April of the following year. A new set of outlooks would then be released in mid-February for March through May, April through June, and so on into March through May of the following year. CPC expresses the outlooks in a 3-category probabilistic format as the chance the total precipitation for the period will be above, below, or near median. CPC bases its definition of above median, near median, and below median by fitting a Gamma distribution to a thirty year climatology and dividing this distribution into equally likely thirds. Note that the base period for the thirty year climatology (currently beginning in 1981 and ending in 2010) is updated once per decade. CPC indicates the probability of the most likely category with shaded contours and labels the centers of maximum probability with the letters "A" (for Above Median), "B" (for Below Median), or "N" (for Near Median). For areas where a favored category cannot be determined, CPC indicates those areas with an "EC" meaning "Equal Chances". CPC also accompanies the outlook maps with a technical discussion of the meteorological and climatological basis for the outlooks. CPC may include analysis of statistical and numerical models, meteorological and sea-surface temperature patterns, trends and past analogs, and confidence factors in this technical discussion.

The monthly data set consists of two files containing global monthly averaged precipitation rate values at a 2.5x2.5 resolution starting in 1979. Values are obtained from 5 kinds of satellite estimates (GPI,OPI,SSM/I scattering, SSM/I emission and MSU). The enhanced file also includes blended NCEP/NCAR Reanalysis Precipitation values. The other just includes the satellite estimates. Pentad data is also available.