Degree-day Model Research Articles

A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks

Our understanding of the impact of climate change on water availability and natural hazards in high-mountain regions is limited due to the spatial and temporal scarcity of ground observations of precipitation and snow. Freely available, satellite-based information about the snowpack is currently mainly limited to indirect measurements of snow-covered area or very coarse-scale snow water equivalent (SWE), but only for flat areas in lowlands without vegetation cover. Novel space-based laser altimeters, such as ICESat-2, have the potential to provide high-resolution snow depth data in worldwide mountain regions where no ground observations exist. However, these space-based laser altimeters come with spatial gaps between ground tracks, obtained without repetition at a give location. To overcome these drawbacks, here, we present a combined probabilistic data assimilation and deep learning approach to reconstruct spatio-temporal SWE from observations of snow depth along ground tracks, imitating ICESat-2 tracks in view of a potential future global application.Our approach is based on assimilating SWE and snow cover information in a degree-day model with an iterative ensemble smoother (IES) which allows temporally reconstructing SWE along hypothetical ground tracks separated by 3 km. As input, the degree-day model uses daily precipitation and downscaled air temperature from the ERA5 reanalysis. A feedforward neural network (FNN) is then used for spatial propagation of the daily mean and standard deviation of the updated SWE ensemble members obtained from the IES. The combined IES-FNN approach provides uncertainty-aware spatio-temporally continuous estimates of SWE.We tested our approach in the alpine Dischma valley (Switzerland) using high-resolution snow depth maps obtained from photogrammetric techniques mounted on airplanes and unmanned aerial system observations. Our results show that the IES-FNN model provides reliable estimates at a resolution of approximately 100 m. Even assimilating only one SWE observation during the year (combined with satellite-based melt-out date estimates) produces satisfying results when evaluating the IES-FNN SWE reconstructions on independent dates and smaller (<4 km2) areas: mean absolute error of 86 mm (78 mm) at Schürlialp (Latschüelfurgga) for average SWE of 180 mm (254 mm), and average spatial linear correlation with the reference SWE of 0.51 (0.48). However, the assimilated SWE observation must not be too early in the accumulation season or too late in the melt season when the snowpack is starting or ending to accumulate or melt, respectively. Smaller distances between ground tracks (1500 m and 500 m) show improved performance of the IES-FNN approach in space, with no significant improvement in terms of temporal reconstruction.Applying the IES-FNN approach to e.g., real ICESat-2 data, remains challenging due to the higher uncertainties associated with these data. However, the approach we propose remains potentially very helpful in addressing the problem of scarcity of ground observations of precipitation and snow in high-mountain regions.

Modelling permafrost deformation with InSAR technology considering soil moisture variation and spatial-temporal heterogeneity of the freeze‒thaw process

ABSTRACT Monitoring and modelling surface deformation are crucial components of understanding the freeze‒thaw process and preventing disasters in permafrost regions. However, previous methods had limitations that inhibited the interpretation of freeze‒thaw deformation, such as a lack of physical meaning, an inability to reflect the physical freeze–thaw process and consideration of only a single external factor’s impact on permafrost deformation. This study proposes an improved degree-day model (IDM) for quantitatively isolating surface deformation using interferometric synthetic aperture radar (InSAR) technology over permafrost. We considered the effect of soil moisture variation on permafrost deformation and incorporated interannual variation in the freeze‒thaw process due to climate change. By applying small baseline subset (SBAS) technology to Sentinel-1 InSAR measurements over the Wudaoliang permafrost region on the Qinghai‒Tibet Plateau from 2018 to 2019, we estimated long-term and seasonal permafrost deformation. The reliability of InSAR results was validated using in situ measurements, with root mean square errors (RMSEs) less than 10 mm. The results showed that the average linear deformation rates in 2018 and 2019 were −3.8 mm a−1 and −11.0 mm a−1, respectively, and the maximum seasonal deformations were 15.7 mm and 13.2 mm, respectively. Compared with the original degree-day model (ODM), the method used in this study produced smaller residual deformations of 6.9 mm and 6.4 mm, highlighting its ability to improve a quantitative description of permafrost deformation.

Degree-day models for predicting adult Delia platura (Diptera: Anthomyiidae) spring flight and first emergence in New York State.

The seedcorn maggot, Delia platura (Meigen), is a pest affecting many crops, including corn. The early spring emergence of adults and belowground seed damage by maggots leave no room for rescue treatments during the short growing season in New York State. Degree-day (DD) models play a crucial role in predicting insect emergence and adult peak activity and are essential for effective pest management. The current D. platura DD model was launched on the Network for Environment and Weather Applications (NEWA) in 2022, using existing scientific literature from other North American regions. The NEWA model predicted adult D. platura first emergence at an average of 471 (39°F) DD in 2022. To gain an accurate and precise understanding of D. platura adult spring emergence and activity, we used interpolated temperature data to calculate the DD for each specific location where adults were captured in the field. DD calculations were performed using the average method, setting a biofix on January 1st and a base temperature of 39°F. In 2023, overwintering adults emerged at an average of 68 DD, and in 2022, adult activity was registered at an average of 282 DD. Accurately predicting the emergence of D. platura could contribute to informing integrated pest management strategies that incorporate timing and cultural practices over chemical solutions to protect crops and the environment.

Proposing the application of the Degree-Day Model in predicting phenological events in fireflies (Coleoptera: Lampyridae)

Proposing the application of the Degree-Day Model in predicting phenological events in fireflies (Coleoptera: Lampyridae)

Historical reconstruction of glacier mass balance and its contribution to water resources in the Sawir Mountains from 2000 to 2020

Glacial changes are crucial to regional water resources and ecosystems in the Sawir Mountains. However, glacial changes, including the mass balance and glacial meltwater of the Sawir Mountains, have sparsely been reported. Three model calibration strategies were constructed including a regression model based on albedo and in-situ mass balance of Muz Taw Glacier (A-Ms), regression model based on albedo and geodetic mass balance of valley, cirque, and hanging glaciers (A-Mr), and degree-day model (DDM) to obtain a reliable glacier mass balance in the Sawir Mountains and provide the latest understanding in the contribution of glacial meltwater runoff to regional water resources. The results indicated that the glacial albedo reduction was significant from 2000 to 2020 for the entire Sawir Mountains, with a rate of 0.015 (10a)−1, and the spatial pattern was higher in the east compared to the west. Second, the three strategies all indicated that the glacier mass balance has been continuously negative during the past 20 periods, and the average annual glacier mass balance was −1.01 m w.e. Third, the average annual glacial meltwater runoff in the Sawir Mountains from 2000 to 2020 was 22 × 106 m3, and its contribution to streamflow was 25.81 % from 2000 to 2018. The glacier contribution rates in the Ulkun- Ulastu, Lhaster, and Kendall River basins were 31.37 %, 22.51 %, and 19.27 %, respectively.

On the Challenges of Simulating Streamflow in Glacierized Catchments of the Himalayas Using Satellite and Reanalysis Forcing Data

Abstract Hydrologic assessment of climate change impacts on complex terrains and data-sparse regions like High Mountain Asia is a major challenge. Combining hydrological models with satellite and reanalysis data for evaluating changes in hydrological variables is often the only available approach. However, uncertainties associated with the forcing dataset, coupled with model parameter uncertainties, can have significant impacts on hydrologic simulations. This work aims to understand and quantify how the uncertainty in precipitation and its interaction with the model uncertainty affect streamflow estimation in glacierized catchments. Simulations for four precipitation datasets [Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), Climate Hazards Group Infrared Precipitation with Station (CHIRPS), ERA5-Land, and Asian Precipitation–Highly Resolved Observational Data Integration Toward Evaluation (APHRODITE)] and two glacio-hydrological models [Glacio-Hydrological Degree-Day Model (GDM) and Hydrological Model for Distributed Systems (HYMOD_DS)] are evaluated for the Marsyangdi and Budhigandaki River basins in Nepal. Temperature sensitivity of streamflow simulations is also investigated. Relative to APHRODITE, which compared well with ground stations, ERA5-Land overestimates the catchment average precipitation for both basins by more than 70%; IMERG and CHIRPS overestimate by ∼20%. Precipitation uncertainty propagation to streamflow exhibits strong dependencies to model structure and streamflow components (snowmelt, ice melt, and rainfall-runoff), but overall uncertainty dampens through precipitation-to-streamflow transformation. Temperature exerts a significant additional source of uncertainty in hydrologic simulations of such environments. GDM was found to be more sensitive to temperature variations, with &gt;50% increase in total flow for 20% increase in actual temperature, emphasizing that models that rely on lapse rates for the spatial distribution of temperature have much higher sensitivity. Results from this study provide critical insight into the challenges of utilizing satellite and reanalysis products for simulating streamflow in glacierized catchments. Significance Statement This work investigates the uncertainty of streamflow simulations due to climate forcing and model parameter/structure uncertainty and quantifies the relative importance of each source of uncertainty and its impact on simulating different streamflow components in glacierized catchments of High Mountain Asia. Results highlight that in high mountain regions, temperature uncertainty exerts a major control on hydrologic simulations and models that do not adequately represent the spatial variability of temperature are more sensitive to bias in the forcing data. These findings provide guidance on important aspects to be considered when modeling glacio-hydrological response of catchments in such areas and are thus expected to impact both research and operation practice related to hydrologic modeling of glacierized catchments.

Was there a low-altitude Younger Dryas Stadial glacier in south-east Wales? Re-interpretation of landforms and palaeo-climatic inferences

A glacial origin for cirque-like hollows cut into the western escarpment of the Usk valley near Abergavenny, South Wales has become widely accepted. Associated supposed extensive moraine ‘festoons’ have been depicted merging and contemporaneous with Last Glacial Maximum (LGM) deposits formed by ice occupying the adjacent Usk valley. We re-interpret these festoons as the product mainly of rock slope failures (RSFs) emanating from the hollows. A cirque glacier origin is preferred to account for a compact double-ridge feature in one of the hollows. The equilibrium-line altitude (ELA) of the reconstructed glacier (357 m) is >60 m lower than all similarly small, presumed Younger Dryas Stadial (YDS; c., 12.9–11.7 ka) glaciers elsewhere in South Wales. To test whether this glacier nevertheless might date from the YDS, we apply three approaches to reconstruct annual palaeo-precipitation amounts at the ELA, two based on relationships between accumulation and ablation for modern glaciers and the third on a simple degree-day model (DDM) using likely climatic characteristics for this event. The DDM can be tailored to represent the recognised large-amplitude YDS annual temperature range rather than the much smaller one experienced by modern glaciers, making it our preferred approach. Although conditions along the Usk valley escarpment during the LGM would have been well suited to cirque glacier formation, the DDM approach, using the large-amplitude annual temperature ranges, suggests that a YDS age might also be possible. The results have implications for re-assessing the likely ages of some former small glaciers in South Wales.

Extension of a Monolayer Energy-Budget Degree-Day Model to a Multilayer One

This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model.

Insecticide efficacy and emergence timing of the Douglas-fir twig weevil.

The Douglas-fir twig weevil (Cylindrocopturus furnissi Buchanan) (Coleoptera: Curculionidae) has recently emerged as a significant pest of Christmas trees grown in the Pacific Northwest United States. The larvae girdle and disfigure twigs, which adversely affects tree marketability. Trees produced for export are also routinely destroyed for phytosanitary reasons when C. furnissi is discovered at border crossings. Due to historically being a sporadic and benign pest on planted and natural Douglas-fir (Psuedotsuga menziesii), there is a lack of chemical management options. In laboratory experiments, we assessed the knockdown effects (ability to kill or incapacitate) of 4 insecticides commonly used on Christmas trees: one assay tested knockdown after direct contact for 24 h, and the other assay tested knockdown after being allowed to feed on treated twigs with 2 days, 7 days, and 14 days residuals. Concurrently, we monitored temperature and adult C. furnissi emergence at a noble fir bough farm for 2 years to estimate the ideal degree-day window for applying insecticides. Bifenthrin and esfenvalerate knocked down all weevils on contact within just 4 h, whereas chlorpyrifos and acephate failed to achieve 100% knockdown within 24 h. Only acephate failed to knock down more weevils than the control (water) after feeding on treated twigs, regardless of the insecticide residue age. Degree-day modeling revealed a variable emergence window between the 2 years but 50% of adult emergence occurred between approximately 1,000-1,100 degree days (1st January, 50 °F (10 °C), single sine). Future work should assess the resulting management recommendation: apply bifenthrin or esfenvalerate once annually just after 1,000 growing degree days for 2 or more years prior to harvest.

The Effects of Temperature on the Development and Survival of Bathycoelia distincta (Hemiptera: Pentatomidae), a Significant Pest of Macadamia in South Africa.

Temperature is the most influential condition affecting insect development and population dynamics. Understanding its impact and other important factors, such as diet, could provide fine-scale predictions of species abundance and distribution in space and time. The two-spotted stink bug, Bathycoelia distincta Distant (Hemiptera: Pentatomidae), is a significant pest of macadamia in South Africa for which limited information on developmental biology exists. Here, for the first time, variations in key developmental parameters of the B. distincta biology were studied systematically. The developmental duration, survival rate, development rate, lower developmental threshold (Tmin), optimum developmental threshold (Topt), upper developmental threshold (Tmax), and thermal constant were quantified for each developmental stage of B. distincta. In addition, the effect of diet (macadamia nut and sweetcorn) on the developmental duration and survival rate were quantified. This study was conducted at five constant temperatures (18, 21, 22, 25, and 29 °C) with relative humidity (RH) variations. The developmental duration from egg to adult decreased significantly with increased temperature: 21 °C (±60 days) to 29 °C (±32 days). The survival rate was significantly different for instar 2 between temperatures. Nymphs (instars 2 and 4) developed faster on the sweetcorn diet than on a macadamia diet, but the total developmental time did not differ significantly between the diets. Development from egg to adult required 783 degree days (DD), with a Tmin of 13.5 °C, Topt of 29.5 °C, and Tmax of 38 °C. Ongoing global warming will increase the population growth of B. distincta through increased development rate, resulting in more damage to macadamia nuts. Understanding the developmental biology and thresholds for the DD model of B. distincta is fundamental for predicting its phenology and outbreaks in macadamia orchards.

Phenology model development for Neodryinus typhlocybae: Evaluation of phenological synchrony with its host, Metcalfa pruinosa

The invasive species Metcalfa pruinosa has inflicted significant economic losses in various European and Asian regions. To combat this pest, the parasitoid wasp Neodryinus typhlocybae has been effectively introduced in Europe. Despite its success, research on the field occurrence patterns of N. typhlocybae, particularly its phenology, remains scarce. This study aims to develop a degree-day model for predicting the adult emergence of N. typhlocybae from overwintering cocoons and to assess the phenological synchrony between N. typhlocybae adults and the nymphal stages of M. pruinosa in Korea. In this study, we estimated the thermal parameters of N. typhlocybae under field temperatures and six constant temperatures (13.92, 17.71, 18.53, 20.53, 22.78, and 24.03 °C) conditions. The lower developmental temperature was estimated using the values of the coefficient of variation for the cumulative degree days of emerged individual adults. The estimated lower developmental threshold temperature was 12.3 °C. With this developmental threshold, a degree-day model was developed, and this model well-predicted emergence in field conditions. By simulating this developed model with the actual occurrence of the nymphal stages of its host, M. pruinosa, adult wasp emergence was estimated to be 1.5 weeks later than the first instar nymph of the host but faster than other nymphal stages of M. pruinosa. Thus, the findings in this study would be helpful in determining the possibility of establishing N. typhlocybae and improving the management efficiency of M. pruinosa.

Seedcorn maggot response to planting date, cover crops, and tillage in organic cropping systems.

Seedcorn maggot, Delia platura (Meigen) (Diptera: Anthomyiidae), is an economically important early-season pest of corn and soybean in the United States. Adult seedcorn maggot is attracted to decomposing plant residues for oviposition, creating potential management issues where growers typically use tillage to incorporate fertility amendments and to create a seedbed. The use of growing degree-day models to time planting dates is an important tool for effectively managing this pest, but their use has not been examined in organic crop production. Here, we report the results of experiments to determine the effects of cover crops, tillage, and relative planting date on seedcorn maggot in corn and soybean in 2 experiments: The first during the transition to organic from conventional management and the second during the 3 yr following organic certification in central Pennsylvania, United States. Overall, delaying the planting date by 1-2 wk reduced fly emergence in corn, but not in soybean in both experiments. Seedcorn maggot emergence was also consistently greater in corn than in soybean, with 6 times more flies in corn than in soy. About 15 times more seedcorn maggot flies emerged from corn in treatments in which cover crops were managed with tillage compared to treatments in which cover crops were terminated with a roller-crimper followed by no-till planting of corn. Fly emergence was negatively related to the proportion of legumes in the cover crop mixture preceding corn. These results can help inform soil, cover crop, and crop decisions for organic growers in the Mid-Atlantic United States.

Hydrological response to climate change in a glacierized catchment in eastern Tien Shan, Central Asia

Study regionThe headwaters of Urumqi River basin located in eastern Tien Shan Study focusGlacier shrinkage in recent decades has caused the volume and timing of glacier-fed streamflow to change, which in turn has significantly impacted the water supply and ecological system in the vast arid land in Central Asia and drawn wide public attention. Based on a glacio-hydrologic degree-day model, the runoff mechanisms and processes of the glacier-fed catchment are revealed. New hydrological insights for the regionThe study found that about 51 % glacier coverage of the Urumqi Glacier No.1 catchment (UG1C) generates approximately 76 % glacier runoff, indicating that glacier melt comprises a significant water resource in the region. The different ways that the glacier melts in response to temperature versus precipitation on a daily scale by changing glacier mass balance can effectively stabilize streamflow, showing a strong capacity of the glacier to naturally adjust streamflow beneficially to water utilization by those downstream. Based on the sensitivity of modelled runoff to glacier change by comparing simulations using constant glacier cover that accommodated dynamic changes in glacier area, we found that the maximum volume of ice melt runoff during the past four decades appeared during the period 1996–2019, most likely around 2010.

Water temperature, mixing, and ice phenology in the arctic–alpine Lake Darfáljávri (Lake Tarfala), northern Sweden

ABSTRACT In the rapidly warming circumpolar Arctic, recent research of lakes has focused on their climatology and ecology but is challenged by sparsity of wintertime data. At the c. 48-m-deep and c. 0.5-km2 large proglacial Darfáljávri (Lake Tarfala), located in an arctic–alpine environment in the Scandinavian Mountains, year-round water temperatures were previously reported for 2016 to 2019. Here, this record is continued for 2019–2020 and 2021–2022, complemented by time-lapse imagery records of the state of the lake surface, as well as degree-day modeling of ice phenology (timing of ice-on and ice-off). Darfáljávri is cryostratified during winter, with interannual variations in the thermocline’s thickness and temperature range. The ice season lasts from October to July. Modeled ice-on dates match observed ones reasonably well; however, observed ice-off dates occur much later than modeled ones, likely because of cold impact from Darfáljávri’s glacial environment as inferred from a comparison with a close tundra lake. Though new insights into the complex lake mixing and ice phenology are provided, it remains to attribute the characteristics of Darfáljávri’s winter stratification to additional potential drivers, such as lake ice thickness, atmospheric heat fluxes, and the water balance of the lake.

Phenological Mapping of Invasive Insects: Decision Support for Surveillance and Management.

Readily accessible and easily understood forecasts of the phenology of invasive insects have the potential to support and improve strategic and tactical decisions for insect surveillance and management. However, most phenological modeling tools developed to date are site-based, meaning that they use data from a weather station to produce forecasts for that single site. Spatial forecasts of phenology, or phenological maps, are more useful for decision-making at area-wide scales, such as counties, states, or entire nations. In this review, we provide a brief history on the development of phenological mapping technologies with a focus on degree-day models and their use as decision support tools for invasive insect species. We compare three different types of phenological maps and provide examples using outputs of web-based platforms that are presently available for real-time mapping of invasive insects for the contiguous United States. Next, we summarize sources of climate data available for real-time mapping, applications of phenological maps, strategies for balancing model complexity and simplicity, data sources and methods for validating spatial phenology models, and potential sources of model error and uncertainty. Lastly, we make suggestions for future research that may improve the quality and utility of phenological maps for invasive insects.

Evaluating insecticide application timings against billbugs (Sphenophorus spp.) using a degree‐day model and calendar‐based approach in the Intermountain West

AbstractRecommendations for timing insecticides against billbugs have historically been based on adult activity and a corresponding degree‐day (DD) model that is optimized for the eastern United States. A DD model was recently developed for billbugs in Utah and Idaho that refines predictions of adult activity based on the phenology of species that inhabit the Intermountain West (IMW) region. However, timings still follow eastern US recommendations and have not been verified with field applications in the IMW. We evaluated the synthetic insecticides Merit 75 WP and Acelepryn 1.67 SC and the bioinsecticides Grandevo and Venerate for controlling larvae when using the eastern recommended treatment thresholds of 30% and 50% adult activity (adults collected in pitfall traps) based on the Utah–Idaho model for two years. Applications of insecticides at these adult emergence thresholds provided &gt;75% control of billbug larvae preventively and curatively in Utah, confirming these are appropriate action thresholds to use in the Utah–Idaho model to time insecticides. Insecticides applied at various calendar dates around these recommended timings, but typical for a professional applicator in Utah based on site history and weather, were assigned model‐calculated DD for testing in the Utah–Idaho model. Instances where a professional applicator treated within model‐predicted timings resulted in larval reductions, further validating that the model parameters are good recommendations for the region and should be adopted. Additionally, several calendar‐based applications made earlier or later than optimal timings based on model predictions were effective, suggesting that applicators have flexibility for timing applications when targeting larvae.

Development of a degree-day model to predict the growth of Anopheles stephensi (Diptera: Culicidae): implication for vector control management.

Anopheles stephensi is an efficient vector of malaria parasites in Iran. Despite its importance in malaria transmission, there is a scarcity of accurate predictive models of its rates of development at different temperatures. A laboratory colony of An. stephensi, collected from Bandar Abbas County, southern Iran, was established, and all its developmental stages were maintained in temperature-controlled incubators so that the water temperature set at 5, 8, 10, 12.5, 14, 28, 38, 39.5, 42, and 45(±0.2) °C for different treatments until subsequent adult emergence. The Lower and Upper Developmental Temperatures (LDT and UDT) and the growth degree-day (GDD) were calculated for each development stage. A 12-mo population dynamics survey of the larvae and adults of An. stephensi was performed in 3 malaria-endemic villages (Geno, Hormoodar, and Sarkhoon) of Bandar Abbas County, and the obtained data were matched with the constructed GDD model. Based on the field meteorological and dynamics data, the model was verified in the field and used to determine the appropriate date to start spraying. The LDT was determined to be 8.19, 9.74, 8.42, 5.6, 13.57, and 10.03 °C for egg hatching, first, second, and third ecdysis, pupation, and eclosion events, respectively. The UDT was 38 °C for all developmental stages. The thermal requirement for the development of all immature stages of An stephensi was determined to be 187.7 (±56.3) GDD above the LDT. Therefore, the appropriate date to start residual spraying is when the region's GDD reaches 187.7 (±56.3). Given the climatic conditions in Bandar Abbas County, it is expected that the first activity peak of adult An. stephensi would be in March. Field observations showed that An. stephensi activity starts in February and peaks in March. The GDD model can provide a good estimate for peak An. stephensi activity and indicate the optimal deployment time of residual spraying operations against the multiplication and development of malaria parasites inside the vector.

Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022

Abstract. Surface melting is one of the primary drivers of ice shelf collapse in Antarctica and is expected to increase in the future as the global climate continues to warm because there is a statistically significant positive relationship between air temperature and melting. Enhanced surface melt will impact the mass balance of the Antarctic Ice Sheet (AIS) and, through dynamic feedbacks, induce changes in global mean sea level (GMSL). However, the current understanding of surface melt in Antarctica remains limited in terms of the uncertainties in quantifying surface melt and understanding the driving processes of surface melt in past, present and future contexts. Here, we construct a novel grid-cell-level spatially distributed positive degree-day (PDD) model, forced with 2 m air temperature reanalysis data and spatially parameterized by minimizing the error with respect to satellite estimates and surface energy balance (SEB) model outputs on each computing cell over the period 1979 to 2022. We evaluate the PDD model by performing a goodness-of-fit test and cross-validation. We assess the accuracy of our parameterization method, based on the performance of the PDD model when considering all computing cells as a whole, independently of the time window chosen for parameterization. We conduct a sensitivity experiment by adding ±10 % to the training data (satellite estimates and SEB model outputs) used for PDD parameterization and a sensitivity experiment by adding constant temperature perturbations (+1, +2, +3, +4 and +5 ∘C) to the 2 m air temperature field to force the PDD model. We find that the PDD melt extent and amounts change analogously to the variations in the training data with steady statistically significant correlations and that the PDD melt amounts increase nonlinearly with the temperature perturbations, demonstrating the consistency of our parameterization and the applicability of the PDD model to warmer climate scenarios. Within the limitations discussed, we suggest that an appropriately parameterized PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.

Assessment of Variability in Hydrological Droughts Using the Improved Innovative Trend Analysis Method

The use of hydro-climatological time series to identify patterns is essential for comprehending climate change and extreme events such as drought. Hence, in this study, hydrological drought variability based on the standard drought index (SDI) using DrinC was investigated at ten (10) hydrological stations in the Upper Indus River Basin (UIRB) of Pakistan on a monthly timescale for a period of 1961–2018. Moreover, the applicability of the improved innovative trend analysis by Sen Slope method (referred hereafter as the IITA) method was evaluated in comparison with innovative trend analysis (ITA) and Mann–Kendall (MK). The findings demonstrated a significant decreasing trend in the hydrological drought from October to March; on the other hand, from April through September, a significant increasing trend was observed. In addition to that, the consistency of the outcomes across the three trend analysis methods was also observed in most of the cases, with some discrepancies in trend direction, such as at Kharmong station. Conclusively, consistency of results in all three trend analysis methods showed that the IITA method is reliable and effective due to its capability to investigate the trends in low, median, and high values of hydrometeorological timeseries with graphical representation. A degree-day or energy-based model can be used to extend the temporal range and link the effects of hydrological droughts to temperature, precipitation, and snow cover on a sub-basin scale.

Ovicidal potential of plant extract mixtures against the Asian spongy moth (Lymantria dispar asiatica)

The Asian spongy moth (ASM, Lymantria dispar asiatica) is a destructive pest of forests, agricultural fields, and urban areas. Plant extract mixtures were evaluated as alternative tools for integrated pest management targeting the overwintering eggs of ASM. When formulated with an adjuvant able to penetrate the hairy egg mass, plant extract mixtures inhibited egg hatching. The extract mixture (cinnamon extract 5% + citronella oil 10% + citrus oil 30% + derris extract 10% + neem extract 20% + penetrating surfactant 25%) with the highest ovicidal activity (97.6% mortality) is a potential botanical insecticide for use against ASM eggs. Susceptibility to mortality from plant extract mixtures increased with egg maturation. Optimal timing for control of overwintering ASM eggs corresponded to the period in spring when larvae inside eggs were fully differentiated. These results will help improve control efficacy with a day-degree model that predicts egg hatch as well as future development nano-formulations.