A simple framework to quantitatively describe monthly precipitation and temperature climatology

Berghuijs, Wouter; Woods, Ross

doi:10.1002/joc.4544

Cited by 39 publications

(54 citation statements)

References 78 publications

(151 reference statements)

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“…The occurrence of snow was estimated for daily time steps using a temperature threshold of 0 • C. The seasonality and timing of precipitation are combined into a single metric, which relies on sine curves representing the annual cycle of precipitation and temperature. Note that sine curves do not necessarily provide a good fit to the annual precipitation cycle, for instance, in areas experiencing a strong annual cycle and multiple consecutive months with low precipitation, such as California (see Berghuijs and Woods, 2015 for a solution to this issue), yet they enable a first-order characterization of the dominant climatological features of diverse locations, which is useful for studies such as this one. These three seasonal indices provide a good overview of the mean and seasonal climatic conditions but do not explicitly consider dry periods and intense precipitation events, which occur at different timescales and are key drivers of droughts and floods.…”

Section: Methodsmentioning

confidence: 99%

The CAMELS data set: catchment attributes and meteorology for large-sample studies

Addor

Newman

Mizukami

et al. 2017

Hydrol. Earth Syst. Sci.

517

566

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Abstract. We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six main classes of attributes at the catchment scale: topography, climate, streamflow, land cover, soil, and geology. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of the attributes we extracted, makes this new data set well suited for large-sample studies and comparative hydrology. In comparison to the similar Model Parameter Estimation Experiment (MOPEX) data set, this data set relies on more recent data, it covers a wider range of attributes, and its catchments are more evenly distributed across the CONUS. This study also involves assessments of the limitations of the source data sets used to compute catchment attributes, as well as detailed descriptions of how the attributes were computed. The hydrometeorological time series provided by Newman et al. (2015b, https://doi.org/10.5065/D6MW2F4D) together with the catchment attributes introduced in this paper (https://doi.org/10.5065/D6G73C3Q) constitute the freely available CAMELS data set, which stands for Catchment Attributes and MEteorology for Large-sample Studies.

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Section: Methodsmentioning

confidence: 99%

The CAMELS data set: catchment attributes and meteorology for large-sample studies

Addor

Newman

Mizukami

et al. 2017

Hydrol. Earth Syst. Sci.

517

566

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“…It has been shown that the vast majority of monthly precipitation climates around the world can be adequately described by a sinusoidal function with a 1 year period [25]. That is,…”

Section: Precipitationmentioning

confidence: 99%

Origin of the RNA world: The fate of nucleobases in warm little ponds

Pearce

Pudritz

Semenov

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

176

222

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Prior to the origin of simple cellular life, the building blocks of RNA (nucleotides) had to form and polymerize in favourable environments on the early Earth. At this time, meteorites and interplanetary dust particles delivered organics such as nucleobases (the characteristic molecules of nucleotides) to warm little ponds whose wet-dry cycles promoted rapid polymerization. We build a comprehensive numerical model for the evolution of nucleobases in warm little ponds leading to the emergence of the first nucleotides and RNA. We couple Earth's early evolution with complex prebiotic chemistry in these environments. We find that RNA polymers must have emerged very quickly after the deposition of meteorites (< a few years). Their constituent nucleobases were primarily meteoritic in origin and not from interplanetary dust particles. Ponds appeared as continents rose out of the early global ocean but this increasing availability of "targets" for meteorites was offset by declining meteorite bombardment rates. Moreover, the rapid losses of nucleobases to pond seepage during wet periods, and to UV photodissociation during dry periods means that the synthesis of nucleotides and their polymerization into RNA occurred in just one to a few wet-dry cycles. Under these conditions, RNA polymers likely appeared prior to 4.17 billion years ago.Significance: There are currently two competing hypotheses for the site at which an RNA world emerged: hydrothermal vents in the deep ocean and warm little ponds. Because the former lacks wet and dry cycles, which are well known to promote polymerization (in this case, of nucleotides into RNA), we construct a comprehensive model for the origin of RNA in the latter sites. Our model advances the story and timeline of the RNA world by constraining the source of biomolecules, the environmental conditions, the timescales of reaction, and the emergence of first RNA polymers.Keywords: life origins | astrobiology | planetary science | meteoritics | RNA worldOne of the most fundamental questions in science is how life first emerged on the Earth. Given its ubiquity in living cells and its ability to both store genetic information and catalyze its own replication, RNA probably formed the basis of first life [1]. RNA molecules are made up of sequences of 4 different nucleotides, the latter of which can be formed through reaction of a nucleobase with a ribose and a reduced phosphorous (P) source [2,3]. The evidence suggests that first life appeared earlier than 3.7 Gyr ago (Ga) [4,5] and thus the RNA world would have developed on a violent early Earth undergoing meteoritic bombardment at a rate of ∼1-1000 ×10 12 kg/yr [6], which is approximately 8-11 orders of magnitude greater than today [7]. At this time, the atmosphere was dominated by volcanic gases, and dry land was scarce as continents were rising out of the global ocean. [8,9], the answer to these questions are largely unknown.As to the sources of nucleobases, the early Earth's atmosphere was likely dominated by CO 2 , N 2 , SO 2 , and H 2 O [10...

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“…We used a global dataset of monthly precipitation oxygen and hydrogen isotope measurements from 650 and 610 precipitation monitoring stations, respectively. These previously compiled (Jasechko et al, 2016) data were collected from the Canadian Network for Isotopes in Precipitation (Birks and Edwards, 2009;Birks and Gibson, 2013), the US Network for Isotopes in Precipitation (Delavau et al, 2015;Welker, 2000Welker, , 2012, and the Global Network for Isotopes in Precipitation (Aggarwal et al, 2011;Halder et al, 2015). Following Jasechko et al 2016, we characterize seasonal cycles only at monitoring stations that report precipitation isotope compositions for at least eight unique months.…”

Section: Datamentioning

confidence: 99%

Global sinusoidal seasonality in precipitation isotopes

Allen

Jasechko

Berghuijs

et al. 2019

Hydrol. Earth Syst. Sci.

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Abstract. Quantifying seasonal variations in precipitation δ2H and δ18O is important for many stable isotope applications, including inferring plant water sources and streamflow ages. Our objective is to develop a data product that concisely quantifies the seasonality of stable isotope ratios in precipitation. We fit sine curves defined by amplitude, phase, and offset parameters to quantify annual precipitation isotope cycles at 653 meteorological stations on all seven continents. At most of these stations, including in tropical and subtropical regions, sine curves can represent the seasonal cycles in precipitation isotopes. Additionally, the amplitude, phase, and offset parameters of these sine curves correlate with site climatic and geographic characteristics. Multiple linear regression models based on these site characteristics capture most of the global variation in precipitation isotope amplitudes and offsets; while phase values were not well predicted by regression models globally, they were captured by zonal (0–30∘ and 30–90∘) regressions, which were then used to produce global maps. These global maps of sinusoidal seasonality in precipitation isotopes based on regression models were adjusted for the residual spatial variations that were not captured by the regression models. The resulting mean prediction errors were 0.49 ‰ for δ18O amplitude, 0.73 ‰ for δ18O offset (and 4.0 ‰ and 7.4 ‰ for δ2H amplitude and offset), 8 d for phase values at latitudes outside of 30∘, and 20 d for phase values at latitudes inside of 30∘. We make the gridded global maps of precipitation δ2H and δ18O seasonality publicly available. We also make tabulated site data and fitted sine curve parameters available to support the development of regionally calibrated models, which will often be more accurate than our global model for regionally specific studies.

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A simple framework to quantitatively describe monthly precipitation and temperature climatology

Cited by 39 publications

References 78 publications

The CAMELS data set: catchment attributes and meteorology for large-sample studies

The CAMELS data set: catchment attributes and meteorology for large-sample studies

Origin of the RNA world: The fate of nucleobases in warm little ponds

Global sinusoidal seasonality in precipitation isotopes

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