KrigR—a tool for downloading and statistically downscaling climate reanalysis data
نویسندگان
چکیده
Abstract Advances in climate science have rendered obsolete the gridded observation data widely used downstream applications. Novel reanalysis products outperform legacy accuracy, temporal resolution, and provision of uncertainty metrics. Consequently, there is an urgent need to develop a workflow through which integrate these improved into biological analyses. The ERA5 product family (ERA5 ERA5-Land) are latest most advanced global created by European Center for Medium-range Weather Forecasting. These offer up 83 essential variables at hourly intervals time-period 1981 today with preliminary back-extensions being available 1950–1981. Spatial resolutions range from 30 × km (ERA5) 11 (ERA5-Land) can be statistically downscaled study-requirements finer spatial resolutions. Kriging one such method interpolate has advantages that leverage additional covariate information obtain associated downscaling. KrigR R-package enables users (a) download ERA5(-Land) user-specified region, time-period, (b) aggregate desired metrics, (c) acquire topographical co-variates, (d) downscale resolution using co-variate via kriging. execute all tasks single function call, thus enabling user any (ERA5)/50 high R-command. Additionally, contains functionality computation bioclimatic metrics offered ERA5(-Land). This provides easy-to-implement implementation state-of-the-art while avoiding issues storage limitations providing according user-needs rather than sets. toolbox wide tailored unprecedented combinations use world-leading R-interface beyond.
منابع مشابه
A tool for downscaling weather data from large-grid reanalysis products to finer spatial scales for distributed hydrological applications
متن کامل
Convolutional Neural Networks for Climate Downscaling
A key challenge in climate modeling is the assessment of the impact of global climate variables on regional weather measurements such as temperature and precipitation. This assessment is usually done by downscaling the output of (coarse resolution) global climate models to regional (high resolution) predictions. There are two independent downscaling pathways: dynamic and statistical. Dynamic do...
متن کاملCan climate trends be calculated from reanalysis data?
[1] Several global quantities are computed from the ERA40 reanalysis for the period 1958–2001 and explored for trends. These are discussed in the context of changes to the global observing system. Temperature, integrated water vapor (IWV), and kinetic energy are considered. The ERA40 global mean temperature in the lower troposphere has a trend of +0.11 K per decade over the period of 1979–2001,...
متن کاملSatellite-driven downscaling of global reanalysis precipitation products
Introduction Conclusions References
متن کاملThe Need for a Dynamical Climate Reanalysis
T he Earth’s climate is dominated by diverse and changeable natural processes over a wide range of time and space scales (e.g., Folland et al. 2001). This includes changes related to transient synoptic weather systems and to phenomena on much longer time scales, such as the quasibiennial oscillation (QBO) and El Niño–Southern Oscillation (ENSO) with time scales up to several years. Especially i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Environmental Research Letters
سال: 2022
ISSN: ['1748-9326']
DOI: https://doi.org/10.1088/1748-9326/ac48b3