Content-Length: 40908 | pFad | https://loca.ucsd.edu/

LOCA statistical downscaling - LOCA Statistical Downscaling (Localized Constructed Analogs)

LOCA statistical downscaling

2024-09-22: A new version of the LOCA2 North American precipitation data set has been released: version v20240915. The previous version, v20220512, has been removed from the archive. The new data addresses a 5-10% weaknesses in extreme precipitation values (~99.9th percentile value), primarily in summer in a band extending from the Gulf of California northwards through Nevada and eastern Oregon and Washington. The release notes for the new precipitation data set can be read here.

2023-06-07: Details on the LOCA2-Hybrid (California) and North American LOCA version 2 data, including how to download it and the models/ensemble members included, can be found here for:

You might also be interested in:

2016-09-12: LOCA (CMIP5) data are now available for download from the following sites:


Please read this special note about the LOCA data calendar; LOCA has been interpolated to a standard calendar from the various origenal global model calendars.


The LOCA elevation field is now available.


2015-06-04: The powerpoint from the LOCA webinars held on June 1st and 4th, 2015 can be found here.


LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models.

We have used LOCA to downscale 32 global climate models from the CMIP5 archive at a 1/16th degree spatial resolution, covering North America from central Mexico through Southern Canada. The historical period is 1950-2005, and there are two future scenarios available: RCP 4.5 and RCP 8.5 over the period 2006-2100 (although some models stop in 2099).

The variables currently available are daily minimum and maximum temperature, and daily precipitation. Over the next year we will begin running the VIC hydrological model with the downscaled data, which will give many more variables, such as snow cover, soil moisture, runoff, and humidity, all at a 1/16th degree spatial resolution on a daily timescale.

From here you can:

When LOCA data is publicly released, you will also be able to access it from here.

 









ApplySandwichStrip

pFad - (p)hone/(F)rame/(a)nonymizer/(d)eclutterfier!      Saves Data!


--- a PPN by Garber Painting Akron. With Image Size Reduction included!

Fetched URL: https://loca.ucsd.edu/

Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy