# Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate
## 3 Satellite Measurement of Precipitation
### Scientific and Technological Challenges  
#### 3.2.1 Observational Grand Challenges  
A better translation from radiometric observations from space to physical properties is a prerequisite for a complete quantification of the hydrologic cycle components and their interactions [163]. Such \"translation grammar\" varies considerably from case to case, depending on the frequency of observations, timeliness, latency, spatial resolution, and uncertainty, which can hardly be addressed by a single mission; rather, they require several missions and/or constellations of sensors conceived for different applications. Thus, a complete understanding of precipitation structure, its changes, and links to the other water cycle components is still burdened by relevant science challenges.  
The first challenge concerns the design of the future satellite precipitation observing system as an essential component of a consistent climate observing system conceived for addressing sea level rise, droughts, floods, extreme events, food security, and freshwater availability in a changing climate. Whetherhead et al. [164] propose to give priority to the Grand Challenges of the World Climate Research Program (WCRP) (Figure 7): (1) melting ice and global consequences; (2) clouds, circulation and climate sensitivity; (3) carbon feedback in the climate system; (4) understanding and predicting weather and climate extremes; (5) water for the food baskets of the world; (6) regional sea-level change and coastal impacts; and (7) near-term climate prediction. Monitoring the Earth through satellite missions that are not part of an integrated global system is no longer possible, since interconnected climate processes require observations designed to contribute to a data system that enables better-quality projections of future scenarios. Precipitation is relevant to most of the seven challenges, and its global observation requires a coordinated worldwide effort. In particular, precipitation observations should help model development focused around processes that most affect storm tracks, tropical rain belts, and climate sensitivity [165]. Such an approach will help reducing model biases and uncertainties, while at the same time advancing the utility of global modeling. Answers to questions such as the future of the permafrost layers, or the dynamics of the terrestrial and ocean carbon sinks, depend on the magnitude of warming and the distribution of precipitation. Validation has become an integral part of model development due to the availability of global gridded products that support the evaluation of the next generation of climate models ([166]).  
A study by Waliser et al. [167] on the water cycle description in the climate models of the IPCC Fourth Assessment Report (AR4) demonstrated good agreement in 20 th century climate representations of quantities that have a relatively robust global observational basis, and that are physically unambiguous; rainfall and precipitable water are among such quantities. A poorer agreement was found for quantities that have a weak or incomplete global observation basis, such as snowfall and cloud liquid water. Awareness of the limitations of the precipitation datasets avoids jumping to wrong conclusions when assessing the various models, as argued by Tapiador et al. [96] in the case of IPCC AR5, which still acknowledged large observational uncertainties in precipitation observations for model validation.  
Figure 7: WCRP Grand Challenges ([[https://www.wcrp-climate.org/grand-challenges/grand-challenges-overview](https://www.wcrp-climate.org/grand-challenges/grand-challenges-overview)]([https://www.wcrp-climate.org/grand-challenges/grand-challenges-overview](https://www.wcrp-climate.org/grand-challenges/grand-challenges-overview)), last accessed 27 September 2019).