Natl. The microwave-based algorithms derive the precipitation signal from both scattering and emission but only the scattering signal is useful over land because of strong variations in surface emissivity that distort the emission. Complex algorithms are required to translate indirect and infrequent satellite measurements into high-resolution gridded precipitation estimates at regular time intervals. For this reason, many data sets combine observations from multiple satellite platforms that carry passive microwave and/or infrared instruments. Behrangi, A., M. Lebsock, S. Wong, and B. Lambrigtsen (2012), On the quantification of oceanic rainfall using spaceborne sensors, J. Geophys. Climate. Select the desired Date from the date range (data are available after two business days) Select the desired Observation (temperature, precipitation, snowfall, snow depth) Select the Units (Fahrenheit or Celsius) Select Options, if desired and available (not available for all data) Click Update Map; 2) Choose WHERE you want it for. Monthly and Daily rainfall data are available from Climate Data Online. Any queries (other than missing content) should be directed to the corresponding author for the article. Proc. Readings are transferred via telemetry to internal and external systems in or close to real time. Verification, impacts and post-processing, Climate information for international development, Science for Impacts, Resilience and Adaptation (SIRA), Atmospheric processes and parametrizations, Regional model evaluation and development, Environmental Hazard and Resilience Services, National Meteorological Library & Archive. Retrieved from https://climatedataguide.ucar.edu/climate-data/gpcp-daily-global-precipitation-climatology-project. Attribution statement: © Environment Agency copyright and/or database right 2016. J. Hydrometeor, 10, 149–166. Often, the default interpolation in an analysis software package is bilinear interpolation (e.g., Matlab), which is not conservative. Despite many advances in observing systems and algorithms over the years, validating global precipitation observations, for example through the energy budget approach, has proven challenging. Sun, Q., C. Miao, Q. Duan, H. Ashouri, S. Sorooshian, and K. Hsu, 2018: A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons. US Dept of Commerce and Chemical Oceanography, Physical National River and Lake Observations and Forecasts, Daily National Multisensor Precipitation Reports, National Oceanic and Atmospheric Administration. Rain rates, and especially the distribution of rain rates at a particular location, depend strongly on spatial resolution of the dataset. This data may be transferred to these systems or users at different intervals varying for example from once per day during normal conditions to several times per day during a flood event. Find historical weather by searching for a city, zip code, or airport code. Right: Rain frequency with logarithmically-spaced rain rate bins. Tree ring data, temperature and NAO reconstructions, IPCC AR4 data . If you do not receive an email within 10 minutes, your email address may not be registered, Then choose a weather parameter (Precipitation, Max Temp, Min Temp, Snow Depth) to view observations for that date. Processes, Information J. Satellites can only indirectly measure quantities related to rain rate at the surface: microwave and infrared satellites measure brightness temperature, which is then converted to rain rate indirectly, while radars measure energy reflected by cloud and rain drops throughout the depth of the column. The Southwest, West Coast and High Plains have distinct seasonal maxima, while the eastern US and inter-mountain West have a more even seasonal distribution of precipitation. Then, these indirect measurements (along with direct gauge measurements over land) are used as an input to a complex algorithm that produces estimates of surface rain rate on a regular grid in time and space. Precipitation (rain, snow, hail, ...) is one of the key components of the hydrological cycle. Select a location using the Text or Map search. For Example: 10/02/14 Precipitation fell … The spatial gridding results in a smoother dataset. Objects, Solid Surface Bolvin et al (2009) contains further validation with high-latitude gauges. Even with the near-global coverage of satellites, most satellites fly over a region only twice per day, potentially missing precipitation events. Files can be downloaded in rank or year order. Download time-series of monthly, seasonal and annual values. One could compare climatologies over the same time period, or compare variations in time by examining model integrations forced with prescribed SSTs (AMIP experiments) and historical forcing (see, eg, Pendergrass 2013 for composites over warm and cold ENSO phases in CMIP5 AMIP experiments). Data shown is raw data collected from the gauges and is subject to quality control procedures. J. Res., 117, D20105. Behrangi, A., Y. Tian, B. H. Lambrigtsen, and G. L. Stephens (2014), What does CloudSat reveal about global land precipitation detection by other spaceborne sensors?, Water Resour. Proc. Physics, Comets and Clim. A list of combined satellite-gauge precipitation datasets was compiled by the International Precipitation Working Group, and can be found here: http://www.isac.cnr.it/~ipwg/data/datasets1.html TRMM 3B42 is another dataset which combines satellite and rain gauge measurements, which higher resolution in time and space, but without global coverage. Behrangi, A. et al (2014): An Update on Oceanic Precipitation Rate and Its Zonal Distribution in Light of Advanced Observations from Space. Climate, 27, 8357–8371. Here, the 13 monthly precipitation data sets and the 11 daily precipitation data sets are analyzed to examine the relative uncertainty of individual data based on the developed generalized three‐cornered hat (TCH) method. It relies on the GPCP monthly product for the total monthly rainfall, and uses primarily geostationary infrared satellite imagery to determine daily rainfall rates. and Paleomagnetism, History of Geophysics, Biological However, the errors in monthly mean values from the GPCP monthly product are also relevant for this dataset. CPC .50x.50 Global Daily Unified Gauge-Based Analysis of Precipitation, Temporal Coverage: Daily 1979/01/01 to present; Long Term Means of daily, monthly for years 1981 to 2010. Bolvin, D. T., Adler, R. F., Huffman, G. J., Nelkin, E. J., & Poutiainen, J. P. (2009). Physically Consistent Responses of the Global Atmospheric Hydrological Cycle in Models and Observations. The uniform spatial grid of this dataset lends itself to comparison with climate models (though, see comments about regridding above). Further, regional variations in topography can affect precipitation amounts significantly. You’ve accepted all cookies. Huffman G.J. and Bolvin, D.T. ***Data shown is for a 24 hour period ending at 7am on the date selected. Data comes from a network of over 1000 gauges across England. Multiple time spans, ranging from 1 to 72 hours, are available. and you may need to create a new Wiley Online Library account. Further anomalies are listed in the documentation, Huffman and Bolvin (2012): Before 2001 the treatment of the gaps in TOVS data were treated differently than after, and in April/May 2005 there is a change from TOVS to AIRS infrared estimates as TOVS left service. Download Daily_Rainfall_Archive , Format: N/A, Dataset: Realtime Rainfall Data: N/A: 09 July 2019 Not available: Additional information View additional metadata. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors.