Precipitable Water Research Articles

Growth conditions of tree species relative to climate change and sea level rise in low-lying Mid Atlantic coastal forests

IntroductionCoastal forests occupy low-lying elevations, typically adjacent to tidal salt marshes. Exposed to increased flooding with sea level rise, coastal forests have retreated as salt marshes advance upslope. Coastal forests likely currently experience periodic tidal flooding, but whether they temporarily accommodate or quickly succumb to rising sea level under changing climatic conditions remains a complex question. Disentangling how tidal flooding and climate affect tree growth is important for gauging which coastal forests are most at risk of loss with increasing sea levels.MethodsHere, dendrochronology was used to study tree growth relative to climate variables and tidal flooding. Specifically, gradients in environmental conditions were compared to species-specific (Pinus taeda, Pinus rigida, Ilex opaca) growth in coastal forests of two estuaries (Delaware and Barnegat Bays). Gradient boosted linear regression, a machine learning approach, was used to investigate tree growth responses across gradients in temperature, precipitation, and tidal water levels. Whether tree ring widths increased or decreased with changes in each parameter was compared to predictions for seasonal climate and mean high water level to identify potential vulnerabilities.ResultsThese comparisons suggested that climate change as well as increased flood frequency will have mixed, and often non-linear, effects on coastal forests. Variation in responses was observed across sites and within species, supporting that site-specific conditions have a strong influence on coastal forest response to environmental change.DiscussionSite- and species-specific factors will be important considerations for managing coastal forests given increasing tidal flood frequencies and climatic changes.

CONCERTO at APEX On-sky performance in continuum

Context. CarbON CII line in post-rEionisation and ReionisaTiOn epoch (CONCERTO) instrument is a low-resolution mapping spectrometer based on lumped element kinetic inductance detector (LEKIDs) technology, operating at 130-310 GHz. It was installed on the 12-metre APEX telescope in Chile in April 2021 and was in operation until May 2023. CONCERTO’s main goals were the observation of [CII]-emission line fluctuations at high redshift and of the Sunyaev–Zel’dovich (SZ) signal from galaxy clusters. Aims. We present the data processing algorithms and the performance of CONCERTO in continuum by analysing the data from the commissioning and scientific observations. Methods. We developed a standard data processing pipeline to proceed from the raw data to continuum maps. Using a large dataset of calibrators (Uranus, Mars, and quasars) acquired in 2021 and 2022 at the APEX telescope across a wide range of atmospheric conditions, we measured the CONCERTO continuum performance and tested its stability against observing conditions. Further, using observations on the COSMOS field and observations targeting a distant sub-millimetre galaxy in the UDS field, we assessed the robustness of the CONCERTO performance on faint sources and compared our measurements with expectations. Results. The beam pattern is characterised by an effective full width at half maximum (FWHM) of 31.9 ± 0.6″ and 34.4 ± 1.0″ for high-frequency (HF) and low-frequency (LF) bands, respectively. The main beam is slightly elongated with a mean eccentricity of 0.46. Two error beams of ~65″ and ~130″ are characterised, allowing us to estimate a main beam efficiency of ~0.52. The field of view is accurately reconstructed and presents coherent distortions between the HF and LF arrays. LEKID parameters were robustly determined for 80% of the read tones. Cross-talks between LEKIDs are the first cause of flagging, followed by an excess of eccentricity for ~10% of the LEKIDs, all located in a given region of the field of view. Of the 44 scans of Uranus selected for the absolute photometric calibration, 72.5% and 78.2% of the LEKIDs were selected as valid detectors with a probability >70%. By comparing the Uranus measurements with a model, we obtain calibration factors of 19.5±0.6 Hz Jy−1 and 25.6±0.9 Hz Jy−1 for HF and LF, respectively. The point-source continuum measurement uncertainties are 3.0% and 3.4% for the HF and LF bands, ignoring the uncertainty in the model (which is <2%). This demonstrates the accuracy of the methods we deployed to process the data. Finally, the RMS of CONCERTO maps is verified to evolve as proportional to the inverse square root of the integration time. The measured noise-equivalent flux densities (NEFDs) for HF and LF are 115±2 mJy beam−1 s1/2 and 95±1 mJy beam−1 s1/2, respectively, obtained using CONCERTO data on the COSMOS field for a mean precipitable water vapour (pwv) and elevation of 0.81 mm and 55.7 deg. Conclusions. CONCERTO has unique capabilities in fast dual-band spectral mapping at ~30 arcsec resolution and with a ~18.5 arcmin instantaneous field of view. CONCERTO’s performance in continuum is perfectly in line with expectations.

Environmental sensitivity of the Caribbean economic growth rate

Abstract. The year-over-year changes in economic growth across the Caribbean Antilles islands demonstrate sensitivity to climatic conditions. Daily wind and rainfall exceedances from passing storms are negatively related to the gross domestic product (GDP). Field regression of the GDP time series from 1971 to 2022 for Puerto Rico and the neighboring Antilles islands reveals links with eastern Pacific sea temperature. A zonal overturning atmospheric circulation over the equatorial Atlantic emerges in composite analysis. Alternating at an approximate 7-year interval, it modulates weather events and economic prosperity in the Caribbean. A multivariate algorithm is developed to predict changes in the annual GDP growth rate. The most influential predictor is precipitable water in the equatorial Atlantic 1 year earlier. Reduced moisture overlain by westerly winds in a global bottleneck at 5° S–5° N, 20–40° W tends to suppress Caribbean storms, leading to economic prosperity in the following year. Statistical methods and risk-reduction strategies are outlined.

GNSS Real-Time ZTD/PWV Retrieval Based on PPP with Broadcast Ephemerides

GNSS precise point positioning (PPP) plays an important role in retrieving atmospheric water vapor values and performing numerical weather prediction. However, traditional PPP relies on real-time orbits and clocks, which require continuous internet or satellite communication. Improved broadcast ephemerides of GNSSs offer new opportunities for PPP with broadcast ephemerides (BE-PPP) instead of using precise ephemeride products. Therefore, we investigated the feasibility of utilizing BE-PPP for retrieving zenith tropospheric delay (ZTD) and precipitable water vapor (PWV) data. We processed the GPS/Galileo observations from 80 IGS stations during a 30-day experiment to retrieve ZTD values using both real-time PPP (RT-PPP) and BE-PPP solutions. Then, we processed observations from 20 EUREF Permanent GNSS Network (EPN) stations to retrieve PWV data. The IGS final tropospheric products were used to validate the ZTD, and radiosonde (RDS) and ERA5 data were used to validate the PWV. The results show that the real-time ZTD from BE-PPP agrees well with that from RT-PPP: the standard deviation (STD) of the ZTD is 1.07 cm when using BE-PPP and 0.6 cm when using RT-PPP. Furthermore, the STD of the PWV is 1.69 mm when using BE-PPP, and 0.96 mm when using RT-PPP, compared to the ERA5-PWV. Compared to the RDS-PWV, the STD is 3.09 mm when using BE-PPP and 1.39 mm when using RT-PPP. In conclusion, the real-time ZTD/PWV products obtained using the BE-PPP solution are consistent with those of RT-PPP and meet the requirements of NWP, so this method can be used as an effective complement to RT-PPP to expand its application potential.

A lightweight ZWD model with high spatiotemporal resolution established based on ERA5 and GNSS observation

The use of a high-precision a priori zenith wet delay can effectively improve the convergence time and increase the accuracy of precise point positioning (PPP). Considering the limitations of empirical and blind ZWD models, a new lightweight ZWD model was developed based on GNSS observations and ERA5 precipitable water vapor (PWV) and temperature information that can provide reliable ZWD with 0.25° spatial resolution and hourly temporal resolution without relying on massive meteorological parameters. The correlation between the ERA5 PWV/temperature and the GNSS-derived ZWD was first analyzed in 2020 in this study. Subsequently, a functional mapping model based on machine learning was established, considering the effects of spatial and temporal factors, such as time, topography, geographical location. The validation results showed the proposed model's RMSE/STD/Bias were 1.70/1.70/0cm compared with GNSS ZWD, respectively. Furthermore, an independent GNSS and radiosonde ZWD in 2021, was introduced to validate the generalization ability of the proposed model, and the RMSE/STD/Bias values were 1.63/1.49/0.2cm and 2.77/2.63/0.23cm, respectively. The ZWD model developed in this study effectively reduces the dependence on meteorological data from numerical weather models, which is beneficial for broadcasting ZWD data and enhances precise regional positioning and navigation.

Tracing the physical signatures among the calculated global clear-sky spectral shortwave radiative flux distribution

This study utilized the high-spectral resolution radiative transfer model (MODerate resolution atmospheric TRANsmission, MODTRAN6.0.2.5) to compute global clear-sky shortwave (SW) radiative flux and compared it with NASA’s Clouds and the Earth’s Radiant Energy System (CERES) Synoptic Radiative Fluxes and Clouds (SYN1deg) product. The comparison revealed that the global distributions of clear-sky downwelling SW fluxes at the surface from the M6.0 calculations and SYN1 results are similar, with annual means of 246.51 Wm-2 and 242.42 Wm-2, respectively. Analysis further showed that most of the M6.0 calculations are slightly higher from low to mid-latitudes, particularly in the Northern Hemisphere (NH), but lower in higher latitudes compared to SYN1 results. However, these differences mostly fall within the CERES estimated uncertainty (6 Wm-2) of monthly mean clear-sky downwelling SW flux at the surface. The sensitivity of clear-sky SW/μ0 fluxes to changes in Precipitable Water Vapor (PWV), represented by the clear-sky water vapor radiative kernel, is about -0.7 Wm-2/(kgm-2) over oceans for both M6.0 and CERES SYN1 products, except for SYN1 results over the Southern Hemisphere (SH) ocean. Additionally, the zonal means of land coverage and SW/VIS/NIR albedos from M6.0 calculations indicate that VIS albedos are highest in polar regions (>60°), followed by SW and NIR albedos, while NIR albedos become highest from low to mid-latitudes (<60°). Generally, SW/VIS/NIR albedos and their differences increase monotonically with increased land coverage from 60°S to 60°N. The consistent clear-sky water vapor radiative kernels derived from both products exceeded our expectations, suggesting their potential use to trace physical signatures in climate model calculations. It is recommended that these model-derived radiative kernels should be validated by the long-term global and regional surface observations in order to enhance confidence to implement these radiative kernels in climate models.

Assessing a machine learning-based downscaling framework for obtaining 1km daily precipitation from GPM data

Hydro-meteorological monitoring through satellites in arid and semi-arid regions is constrained by the coarse spatial resolution of precipitation data, which impedes detailed analyses. The objective of this study is to evaluate various machine learning techniques for developing a downscaling framework that generates high spatio-temporal resolution precipitation products. Focusing on the Hai River Basin, we evaluated three machine learning approaches—Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Back Propagation (BP) neural networks. These methods integrate environmental variables including land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Precipitable Water Vapor (PWV), and albedo, to downscale the 0.1° spatial resolution Global Precipitation Measurement (GPM) product to a 1 km resolution. We further refined the results with residual correction and calibration using terrestrial rain gauge data. Subsequently, utilizing the 1 km annual precipitation, we employed the moving average window method to derive monthly and daily precipitation. The results demonstrated that the XGBoost method, calibrated with Geographical Difference Analysis (GDA) and Kriging spatial interpolation, proved to be the most accurate, achieving a Mean Absolute Error (MAE) of 58.40 mm for the annual product, representing a 14 % improvement over the original data. The monthly and daily products achieved MAE values of 11.61 mm and 1.79 mm, respectively, thus enhancing spatial resolution while maintaining accuracy comparable to the original product. In the Hai River Basin, key factors including longitude, latitude, DEM, LST_night, and PWV demonstrated greater importance and stability than other factors, thereby enhancing the model's precipitation prediction capabilities. This study provides a comprehensive assessment of the annual, monthly, and daily high-temporal and high-spatial resolution downscaling processes of precipitation, serving as an important reference for hydrology and related fields.

Enhancing Extreme Precipitation Forecasts through Machine Learning Quality Control of Precipitable Water Data from Satellite FengYun-2E: A Comparative Study of Minimum Covariance Determinant and Isolation Forest Methods

Enhancing Extreme Precipitation Forecasts through Machine Learning Quality Control of Precipitable Water Data from Satellite FengYun-2E: A Comparative Study of Minimum Covariance Determinant and Isolation Forest Methods

Precipitable water vapor retrieval for rainfall forecasting using BDS-3 PPP-B2b signal in the coastal region of China

Abstract Currently, rainfall cannot be accurately forecast because of poor network communication at the ocean. The advantage of the BeiDou Global Navigation Satellite System (BDS-3) precise point positioning (PPP-B2b) signal, which does not rely on network communication to receive data, is that it can provide precipitable water vapor (PWV) retrieval application services for the open seas in eastern China, where the communication system presents difficulties. In this study, data from stations in the coastal region of China were used to establish a rainfall forecasting method for monitoring extreme weather on the sea. First, the service performance of PPP-B2b was explored. Then, based on 17 Chinese coastal stations, the PWV accuracy was evaluated. Finally, based on an analysis of the relationship between PWV and actual rainfall, a threshold rainfall forecasting method based on a sliding window was constructed. The experimental results show that the PWV accuracy varies slightly depending on the geographic location, in which the mean absolute error in the North Sea region is the smallest (2.1 mm), that of the South China Sea region is the largest (2.60 mm), and that of the East China Sea region is in the middle (2.48 mm). The optimal predictors of the constructed 12 h sliding-window threshold rainfall prediction method are a PWV maximum of 49 mm, PWV increase of 5 mm, and PWV increase rate of 1.2 mm h−1. The prediction results can reach a critical success index value of more than 45%, indicating high prediction accuracy and applicability to the coastal region of China during the same period.

Ripples of Negligence: Unravelling Iraq’s Descent from Water Abundance to Scarcity

ABSTRACT This study critically assesses security dynamics in developing nations, centering on water scarcity in Iraq. It challenges the reductionist perspective that equates security solely with the absence of military threats, positing instead that the governing body itself can constitute an existential threat to the state. Many developing countries, typified by a myopic conception of security, have engendered internal insecurity. Iraq exemplifies this paradigm, where successive ruling elites, marked by military adventurism and administrative incompetence, directly precipitate water scarcity. The nation’s ominous trajectory results from governmental prioritization of external threats over essential societal well-being. This article elucidates the intricate interplay between governance priorities and societal vulnerabilities, advocating for a more comprehensive understanding of security that transcends conventional militaristic frameworks. The analysis underscores the urgent need for recalibrating security paradigms in developing countries to address internal threats emanating from governmental neglect and skewed priorities.

Evolution of Dew and Rain Water Resources in Gujarat (India) between 2005 and 2021

The present study, carried out in Gujarat (India) between 2005 and 2021, aims to prepare dew and rain maps of Gujarat over a long period (17 years, from 2005 to 2021) in order to evaluate the evolution of the potential for dew and rain in the state. The ratio of dew to precipitation is also determined, which is an important metric that quantifies the contribution of dew to the overall water resources. Global warming leads, in general, to a reduction in precipitation and non-rainfall water contributions such as dew. The study shows, however, a rare increase in the rainfall and dew condensation, with the latter related to an increase in relative humidity and a decrease in wind amplitudes. Rain primarily occurs during the monsoon months, while dew forms during the dry season. Although dew alone cannot resolve water scarcity, it nonetheless may provide an exigent and unignorable contribution to the water balance in time to come. According to the site, the dew–rain ratios, which are also, in general, well correlated with dew yields, can represent between 4.6% (Ahmedabad) and 37.2% (Jamnagar). The positive trend, observed since 2015–2017, is expected to continue into the future.

Different supplemental irrigation methods result in discrepant water use efficiency and yield by changing steps of water use process in dryland wheat

Supplemental irrigation (SI) at critical growth stages is a practical way to mitigate water shortage of winter wheat in dryland. However, the yield performance after SI is unstable in different precipitation years. To obtain a better understanding about the applicability of SI in dryland, the utilization efficiency of precipitation and irrigation water (IUE) was divided into 5 sequential ratios: water storage ratio, water consumption ratio, water transpired ratio, transpiration efficiency and harvest index. In this study, those ratios were investigated under four SI methods: no irrigation (W0), SI once at jointing (Wj), SI once at booting (Wb) and SI twice at jointing and booting (Wj+b) throughout four years. Our results showed that water storage ratio was increased under all SI treatments, but water transpired ratio was only significantly increased under Wj and Wj+b, due to their greater development of plant population compared to W0. Thus, wheat yield was greatly improved by 7–12 % under Wj and Wj+b than that under W0 in dry and normal years. However, IUE was significantly decreased under Wj+b. Compared with W0, Wj+b had higher evaporation during the fallow period and lower water consumption ratio. Furthermore, 100–300 cm subsoil water utilization was decreased under Wj+b from jointing to harvest time due to the low root length density (RDL) in subsoil. Under Wj, evaporation, subsoil water utilization and RDL were not negatively affected and water use efficiency was increased compared to W0. Thus, SI once at jointing stage is a more suitable practice in dryland wheat farmland when considering the dual goal of effectively using water while increasing yields under worse precipitation year.

The Evaluation of Rainfall Forecasting in a Global Navigation Satellite System-Assisted Numerical Weather Prediction Model

Accurate water vapor information is crucial for improving the quality of numerical weather forecasting. Previous studies have incorporated tropospheric water vapor data obtained from a global navigation satellite system (GNSS) into numerical weather models to enhance the accuracy and reliability of rainfall forecasts. However, research on evaluating forecast accuracy for different rainfall levels and the development of corresponding forecasting platforms is lacking. This study develops and establishes a rainfall forecasting platform supported by the GNSS-assisted weather research and forecasting (WRF) model, quantitatively assessing the effect of GNSS precipitable water vapor (PWV) on the accuracy of WRF model forecasts for light rain (LR), moderate rain (MR), heavy rain (HR), and torrential rain (TR). Three schemes are designed and tested using data from seven ground meteorological stations in Xi’an City, China, in 2021. The results show that assimilating GNSS PWV significantly improves the forecast accuracy of the WRF model for different rainfall levels, with the root mean square error (RMSE) improvement rates of 8%, 15%, 19%, and 25% for LR, MR, HR, and TR, respectively. Additionally, the RMSE of rainfall forecasts demonstrates a decreasing trend with increasing magnitudes of assimilated PWV, particularly effective in the range of [50, 55) mm where the lowest RMSE is 3.58 mm. Moreover, GNSS-assisted numerical weather model shows improvements in statistical forecasting indexes such as probability of detection (POD), false alarm rate (FAR), threat score (TS), and equitable threat score (ETS) across all rainfall intensities, with notable improvements in the forecasts of HR and TR. These results confirm the high precision, visualization capabilities, and robustness of the developed rainfall forecasting platform.

Rising damp in heritage sites under urban expansion: A comprehensive case study of the Jinsha Earthen Site

Rising damp poses a significant threat to cultural heritage, yet its dynamics within actual heritage sites remain inadequately understood, particularly regarding its evolution and the impact of urbanization. The Jinsha Site, an earthen site from the Shang periods, is primarily composed of silt, with a layer of sand beneath and pebbles at the bottom, making it susceptible to rising damp. This study investigates the Jinsha Site as a case, monitoring soil water content and electrical conductivity, tracking changes in groundwater, precipitation, and river water levels, and investigating the relationship between urbanization and rising damp. The study aims to understand the process, causes, and influencing factors of rising damp and evaluate previous preservation strategies. The findings indicate that groundwater level in the sand layer trigger dampness, whereas the pebble layer exhibits dryness. Urban construction from 2006 to 2013 and 2014–2017 caused fluctuating groundwater levels, leading to repeated transitions between dryness and dampness at the site. Rainfall and river levels have negligible effect; even rainfall exceeding 100 mm (frequency <0.0056) only raises groundwater levels by approximately 1 m and increases water content by less than 2 % for a brief duration, typically less than half a month. The 2022 groundwater pumping strategy effectively maintained levels beneath the pebble layer (506 m), decreasing moisture by 12.71 % and conductivity by 0.27 dS/m. This study reflects on previous protection effortsand offers evidence-based strategies for heritage conservation amidst urban expansion.

Dynamics of soil water potential as a function of stand types in a temperate forest: Emphasis on flash droughts

In the context of a changing climate and the increasing occurrences of extreme events, including droughts, field evidence, and models suggest that cases of forest decline and migration of tree species to more suitable climates will augment in the 21st century. In northeastern North America, an expansion of American beech at the expense of maples has been observed since the 1970s and has been associated to several causes. Through an analysis of time series leveraging thousands of data collected in a temperate forest in southern Quebec, Canada, dynamics of soil water potential were analyzed in interaction with soil temperature, meteorological variables and forest types, including hardwoods (mostly maple) with a large presence of beech trees (hardwood-beech stands), hardwoods (maple and birch) and mixedwoods (maple and fir). During flash drought events with a net precipitation deficit and water stress, the presence of beech led to a decrease in soil temperature and favored the maintenance of low soil water potential and faster restoration of water reserves compared to mixedwoods. Using machine learning-based approaches, distinct critical soil temperature thresholds in regard to water potential were identified for the various forest types, and the temporality in soil water regime changes was more favorable under hardwood-beech stands. The presence of beech appears to render greater resilience in regard to water stress in this forest. A greater capacity of beech to preserve and restore soil water not only offers an additional explanation for its establishment in hardwoods in the last decades, but greater water conservation in the presence of beech, assuming it remains in the landscape, could also help local plant species adapt to climate change and to the predicted increased water deficits, as well as species migrating northward to find more suitable environmental envelopes.

Changing dynamics of Western European summertime cut‐off lows: A case study of the July 2021 flood event

AbstractIn July 2021, a cut‐off low‐pressure system brought extreme precipitation to Western Europe. Record daily rainfall totals led to flooding that caused loss of life and substantial damage to infrastructure. Climate change can amplify rainfall extremes via thermodynamic processes, but the role of dynamical changes is uncertain. We assess how the dynamics involved in this particular event are changing using flow analogues. Using past and present periods in reanalyses and large ensemble climate model data of the present‐day climate and 2°C warmer climate, we find that the best flow analogues become more similar to the cut‐off low‐pressure system observed over Western Europe in 2021. This may imply that extreme rain events will occur more frequently in the future. Moreover, the magnitude of the analogue lows has deepened, and the associated air masses contain more precipitable water. Simulations of future climate show similar events of the future could lead to intense rainfall further east than in the current climate, due to a shift of the pattern. Such unprecedented events can have large consequences for society, we need to mitigate and adapt to reduce future impacts.

Paleoclimate, paleoenvironment, and human impact over the last 400 years based on lipid biomarkers from Lake Höglwörth, Germany

Lipid biomarkers are valuable proxies for reconstructing paleoclimate and paleoenvironmental changes as well as human impact. However, little attention has been paid on evaluating how the combination of biomarkers can be used to reconstruct various aspects of local paleoenvironmental conditions. This study presents a suite of lipid biomarker records from a sediment core from Lake Höglwörth, southern Germany, covering the past 400 years. Compound-specific hydrogen isotopic compositions (δD) of terrestrial n-alkanes (n-C29-alkane) and n-alkanoic acids (n-C30-acid) indicate minor changes in isotopic composition of precipitation. The δD of n-C22-acid is interpreted to record the isotopic composition of the lake water and evaporative enrichment, which drops after 1700 CE, coinciding with the construction of a mill and the related rerouting of a creek into Lake Höglwörth. The δD of n-C25-alkane is also enriched but decoupled from the reconstructed isotopic composition of precipitation and lake water. Therefore, we suggest that δD of n-C25-alkane reflects the leaf water isotopic composition of Sphagnum, which is present in the catchment and undergoes transpirative enrichment. Both short-chain compounds have become more enriched over the last century, maybe related to increasing temperature associated with anthropogenic climate warming. The faecal biomarkers record the changes in human population, partly related to the history of the local Monastery, the World Wars I and II as well as the intensive farming after the mid-20th century. Polycyclic aromatic hydrocarbons (PAHs) reveal a significant change in combustion activities associated with human activities such as the industrial revolution, biomass burning, and environmental cleanup as well as the implementation of emission standards. Our study demonstrates that the combination of plant wax compounds, faecal biomarkers, and PAHs from lacustrine sediment serves as a valuable tool to reconstruct and distinguish various aspects of paleoclimate and paleoenvironmental changes including human impacts.

Interspecific, conspecific, and ontogenetic responses of tree rings to climate: A case study utilizing Carya glabra, Carya ovata, Carya tomentosa, and Quercus montana from an Oak-Hickory Forest in Southeastern Ohio

Climate change in eastern North America is likely to impact the abundance and distribution of the region’s tree species. However, determining the degree to which species will be impacted by altered climates is challenging. Dendrochronology research aimed at understanding relationships between climate and annual ring-width is one way of understanding how climate change may impact forest communities. Oak (Quercus spp.) and hickory (Carya spp.) are two foundational groups of trees likely to undergo changes in abundance and distribution due to climate change. The goal of this study was to compare the radial growth climate sensitivity of three common and co-occurring hickory species (Carya glabra, Carya ovata, and Carya tomentosa) to ecologically similar Quercus montana in southeast Ohio. Also, this study compared conspecific radial-growth climate responses between canopy and subcanopy trees to assess the impacts of climate and drought on subcanopy forest layers. All four species in the forest canopy demonstrated significant positive relationships to growing season precipitation, significant negative relationships with growing season temperature, and significant positive relationships with growing season site water balance. Subcanopy chronologies for all four species demonstrated weaker growth responses to climate, with only Carya glabra demonstrating significant growth relationships with May precipitation and site water balance. Additionally, the increased drought resistance of subcanopy trees provided some evidence of the forest overstory buffering the impacts of climate variability on understory trees. Overall, ontogenetic differences in tree sensitivity to climate variability and drought show that climate change likely has the potential to influence the forest understory, but the degree to which systems are impacted may be highly species-specific.

Optimizing Ridge–Furrow Rainwater-Harvesting Strategies for Potato Cultivation in the Drylands of Northwestern China: A Regional Approach

The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China’s arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific.

Performance of Ground-Based Global Navigation Satellite System Precipitable Water Vapor Retrieval in Beijing with the BeiDou B2b Service

Performance of Ground-Based Global Navigation Satellite System Precipitable Water Vapor Retrieval in Beijing with the BeiDou B2b Service