Hexbyte Glen Cove Chang’E-5 lander makes first onsite detection of water on moon

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Context images and water content at the Chang’E-5 landing site. Credit: LIN Honglei

A joint research team led by Profs. Lin Yangting and Lin Honglei from the Institute of Geology and Geophysics of the Chinese Academy of Sciences (IGGCAS) observed water signals in reflectance spectral data from the lunar surface acquired by the Chang’E-5 lander, providing the first evidence of in-situ detection of water on the Moon.

The study was published in Science Advances on Jan. 7.

Researchers from the National Space Science Center of CAS, the University of Hawaiʻi at Mānoa, the Shanghai Institute of Technical Physics of CAS and Nanjing University were also involved in the study.

Many orbital observations and sample measurements completed over the past decade have presented evidence for the presence of (as hydroxyl and/or H2O) on the moon. However, no in-situ measurements have ever been conducted on the .

The Chang’E-5 spacecraft landed on one of the youngest mare basalts, located at a mid-high latitude on the Moon, and returned 1,731 g of samples. Before sampling and returning the lunar soil to Earth, however, the lunar mineralogical spectrometer (LMS) onboard the lander performed spectral reflectance measurements of the regolith and of a rock, thereby providing the unprecedented opportunity to detect lunar surface water.

Water (OH/H2O) can be detected using spectral features at ~3 μm. However, above 2 μm, thermal emission from the hot lunar surface will significantly modify and mask spectral features.

Therefore, the researchers used a thermal correction model to correct the LMS spectra. Following this correction, the undoubted spectral absorptions at 2.85 μm were observed at the Chang’E-5 landing site.

The quantitative spectral analysis indicates that the lunar soil at the landing site contains less than 120 ppm of water, which is mostly attributed to solar wind implantation. This is consistent with the preliminary analysis of the returned Chang’E-5 samples.

In contrast, a light and vesicular rock that was also analyzed exhibited much stronger absorption at 2.85 μm, corresponding to an estimated ~180 ppm of water, thus suggesting an additional water source from the lunar interior.

The results of compositional and orbital remote sensing analyses show that the rock may have been excavated from an older basaltic unit and ejected to the landing site of Chang’E-5. Therefore, the lower water content of the soil, as compared to the higher water content of the rock fragment, suggests that degassing of the mantle reservoir beneath the Chang’E-5 landing site took place.

This discovery is consistent with the prolonged in the Procellarum KREEP (potassium, , phosphorus) Terrain region, and also provides vital geological context for the analysis of the returned Chang’E-5 samples.

More information:
Honglei Lin et al, In situ detection of water on the Moon by the Chang’E-5 lander, Science Advances (2022). DOI: 10.1126/sciadv.abl9174

Chang’E-5 lander makes first onsite detection of water on moon (2022, January 10)
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from https://phys.org/news/2022-01-change-lander-onsite-moon.html

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Hexbyte Glen Cove Climate cycles create California precipitation uncertainty

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Credit: CC0 Public Domain

Over the past 40 years, winters in California have become drier. This is a problem for the region’s agricultural operations, as farmers rely on winter precipitation to irrigate their crops. Determining if California will continue getting drier, or if the trend will reverse, has implications for its millions of residents.

But so far, that account for changes in and other human activities have had trouble reproducing California’s observed drying trends. When climate models project the future or simulate the past, they can’t agree on long-term precipitation trends. Researchers at Pacific Northwest National Laboratory (PNNL) want to know why because these mixed results aren’t very useful for future water resource planning.

“When we see these large uncertainties in model simulations and projections, we have to ask whether or not the models are up for the task,” said Ruby Leung, a Battelle Fellow and at PNNL. “One challenge with modeling California is that long-term heavily affect its precipitation.”

These cycles range from years long, like El Niño and La Niña, to decades long, like the Interdecadal Pacific Oscillation (IPO). They represent natural variability associated with sea surface temperature patterns in the Pacific Ocean and affect winter precipitation in California.

But how much of a role do they play in spawning uncertainty in California’s precipitation projections? A big one, it turns out. Results from Leung and a PNNL team show that natural cycles are responsible for >70 percent of the uncertainty in model simulations of precipitation trends over the past 40 years. By isolating the effects of the natural cycles, scientists can focus on improving models to reduce the remaining uncertainty related to how greenhouse gases and other human activities affect climate.

The impact of ensembles

With more computing power, researchers can now run large sets of simulations called large ensemble simulations. To produce them, researchers run climate models from 40–100 times with minor differences in their starting conditions. Because everything except for the starting conditions remains the same, these ensembles provide a unique representation of natural variability. Modeling centers around the world also run simulations that contribute toward multi-model ensembles. These represent the total uncertainty due to both natural variability and model uncertainty.

Leung and her team analyzed three ensemble simulations generated by three different climate models and two multi-model ensembles of two recent climate model generations. They wanted to determine the sources of uncertainty in the projections of California precipitation. What they found surprised them.

The team found that natural climate cycles were responsible for roughly 70 percent of the total uncertainty in of California precipitation trends in the past 40 years. That leaves 30 percent of the uncertainty for how models represent on climate.

“We know that natural cycles have major impacts on California’s climate, but we didn’t think that they would dominate the total uncertainty in climate simulations to this extent,” said Leung. “This result shows the importance of large ensemble simulations for isolating human influence on climate, which may be small compared to natural cycles in some regions.”

Natural cycles versus human impacts

Of the natural cycles that influence California’s climate, the IPO is one of the most important. Its decades-long phases help determine if California is in a wetting or drying trend. The team’s results point to its substantial role in California’s drying over the past 40 years.

Currently, climate models have limited skill in predicting the transition between the IPO phases—especially decades from now. Therefore, future projections of California precipitation have large uncertainty due to IPO cycles.

So where does that leave human-induced changes, like warming and increasing greenhouse gases? They still play a substantial role in shaping the future climate and weather. As greenhouse gases continue to accumulate in the atmosphere and the ocean’s large heat capacity catches up with increasing temperatures, warming and its effects will become more pronounced.

“Natural variability, such as the IPO, is like background noise,” said Leung. “Although that noise is substantial, the climate response to rising concentrations of greenhouse gases is a signal that grows over time. Focusing our efforts on reducing model disagreement for this signal is impactful, particularly when looking to the far future.”

Understanding the extent to which natural and external factors affect California precipitation helps researchers better contextualize their projections. This knowledge helps modelers explain why their models might be missing the mark in simulating past observed trends. Scientists can then communicate more nuanced results to people planning California’s water future.

More information:
Lu Dong et al, Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation, Nature Communications (2021). DOI: 10.1038/s41467-021-26797-5

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