The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.
Chris Funk,Pete Peterson,Martin Landsfeld,Diego Pedreros,James P. Verdin,Shraddhanand Shukla,Gregory Husak,James Rowland,Laura Harrison,Andrew Hoell,Joel Michaelsen +10 more
TLDR
The Variable Infiltration Capacity model, a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights, is presented and it is shown that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.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.read more
Citations
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Emergence of behavioural avoidance strategies of malaria vectors in areas of high LLIN coverage in Tanzania.
Katharina Kreppel,Katharina Kreppel,Mafalda Viana,Bradley J. Main,Paul C. D. Johnson,Nicodem J. Govella,Yoosook Lee,Deodatus F. Maliti,Felician C. Meza,Gregory C. Lanzaro,Heather M. Ferguson +10 more
TL;DR: A longitudinal investigation of malaria vector host choice over 3 years and resting behaviour over 4 years following a mass long-lasting insecticidal nets distribution in Tanzania detected clear evidence of intra-specific shifts in mosquito behaviour that could be obscured in shorter-term or temporally-coarse surveys.
Proceedings ArticleDOI
A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast
TL;DR: A system that incorporates satellite-derived precipitation and soil properties datasets, seasonal climate forecasting data from physical models and other sources to produce a pre-season prediction of soybean/maize yield-with no need of NDVI data is described.
Journal ArticleDOI
Evaluation of GPM-IMERG and TRMM-3B42 precipitation products over Pakistan
Muhammad Arshad,Muhammad Arshad,Xieyao Ma,Jun Yin,Waheed Ullah,Gohar Ali,Gohar Ali,Safi Ullah,Mengyang Liu,Muhammad Shahzaman,Irfan Ullah +10 more
TL;DR: In this article, the performance of remotely-sensed precipitation with rain gauge as reference is evaluated, taking the rain gauge data as a reference for the period of 2004 to 2018 over Pakistan.
Journal ArticleDOI
Inter-comparison of remotely sensed precipitation datasets over Kenya during 1998-2016
TL;DR: In this article, four Satellite derived Precipitation Estimates (SPE): TMPA V7 3B42, PERSIANN-CDR, CHIRPS, and ARC2, are assessed over four homogeneous zones in Kenya with gauge-based data during 1998 -2016.
Proceedings ArticleDOI
DeepDownscale: A Deep Learning Strategy for High-Resolution Weather Forecast
TL;DR: In this paper, a deep neural network is used to learn a high-resolution representation from low-resolution predictions using weather forecast as a practical use case, and the results show significant improvement when compared with standard practices and the strategy is still lightweight enough to run on modest computer systems.
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