Dataset Information

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

ABSTRACT: The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to 'smart' interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

SUBMITTER: Funk C

PROVIDER: S-EPMC4672685 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

Funk Chris C Peterson Pete P Landsfeld Martin M Pedreros Diego D Verdin James J Shukla Shraddhanand S Husak Gregory G Rowland James J Harrison Laura L Hoell Andrew A Michaelsen Joel J

Scientific data 20151208

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to 'smart' interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimat ...[more]

PMID: 26646728

Similar Datasets

Project description:Ongoing global warming increases the frequency and severity of tropical typhoons and prolonged drought, leading to forest degradation. Simultaneous and/or successive masting events and climatic extremes may thus occur frequently in the near future. If these climatic extremes occur immediately after mass seed reproduction, their effects on individual trees are expected to be very severe because mass reproduction decreases carbohydrate reserves. While the effects of either a single climate extreme or masting alone on tree resilience/growth have received past research attention, understanding the cumulative effects of such multiple events remains challenging and is crucial for predicting future forest changes. Here, we report tree hazards compound by two successive climate extremes, a tropical typhoon and prolonged drought, after mass reproduction in an endemic tree species (Distylium lepidotum Nakai) on oceanic islands. Across individual trees, the starch stored within the sapwood of branchlets significantly decreased with reproductive efforts (fruit mass/shoot mass ratio). Typhoon damage significantly decreased not only the total leaf area of apical shoots but also the maximum photosynthetic rates. During the 5-month period after the typhoon, the mortality of large branchlets (8-10-mm diameter) increased with decreasing stored starch when the typhoon hit. During the prolonged summer drought in the next year, the recovery of total leaf area, stored starch, and hydraulic conductivity was negatively correlated with the stored starch at the typhoon. These data indicate that the level of stored starch within branchlets is the driving factor determining tree regrowth or dieback, and the restoration of carbohydrates after mass reproduction is synergistically delayed by such climate extremes. Stored carbohydrates are the major cumulative factor affecting individual tree resilience, resulting in their historical effects. Because of highly variable carbohydrate levels among individual trees, the resultant impacts of such successive events on forest dieback will be fundamentally different among trees.

Dataset Information

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

Publications

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets