Annual Weather Research Articles

Production and outmigration of young-of-year northern pike Esox lucius from natural and modified waterways connected to Lower Green Bay, Wisconsin.

Production and outmigration of young-of-year (YOY) northern pike from natal sites in Lower Green Bay, WI, USA, were documented over three consecutive years (2013-2015). We tested the hypothesis that spawning success and outmigration characteristics of YOY northern pike would vary among natural and anthropogenically modified habitats. Sixteen focal study locations were surveyed, including a restored natural wetland, agricultural drainage ditches, a flooded forested wetland and several unimpounded tributaries. We collected 1469 YOY northern pike with most individuals (N= 1163) originating from a flooded forested wetland on the east shore. Most sites produced YOY in all years (range N= 2-1145 individuals among study years). Outmigration ranged between 1 and 40 days during 2013-2015. Greater production and extended outmigration times occurred at most sites in 2014 (range 17-40 days) when the region experienced a late spring with heavy precipitation. In contrast, the lowest production and shortest outmigration period occurred at most sites in 2015 (range 14-23 days) when environmental conditions reflected regional averages. Outmigration began nearly 3 weeks earlier in 2015 (5/8) than in other study years (8 June 2013 and 25 May 2014). Total length (TL) of outmigrating northern pike ranged between 17 and 138 mm. Total length of YOY was significantly different among sites in 2013 and 2014, with the smallest fish (17 mm TL) outmigrating from agricultural ditches in both years. There were no significant variations in size among sites in 2015 (range 21-95 mm TL). Our results indicate significant variation in YOY northern pike outmigration characteristics within Lower Green Bay that may reflect the interplay between adult spawning site selection and annual weather patterns. Our findings highlight the importance of quantifying overlooked habitats in regions of mixed development.

Effect of Aging on Solar Reflectance of White Cool Roof Coatings: Natural Weathering and the Influence on Building Energy Needs for Different Climate Conditions in Brazil

The use of cool materials on the building envelope is one of the most cost-effective ways to increase indoor thermal comfort conditions in hot climates and decrease the cooling energy needs. Despite the benefit of reducing cooling loads, researches have demonstrated that aging of roof coatings changes the initial solar reflectance (SR), which influences the long term building thermal and energy performance. Thus, this work presents preliminary natural weathering tests performed on samples of nine white coatings exposed to natural weathering for one year in the city of Sao Carlos, Brazil. Solar reflectances were measured with a spectrophotometer before and after exposure, every 3 months, for identifying the effect of aging along the time. The findings showed changes of 13% to 23% on SR after one year of natural weathering, with higher decrease on SR for rougher surfaces. The cleaning process restored from 90% to 100% of the original SR, which means maintenance can be an effective solution to restore the initial SR. Simulations indicated that roofs with higher solar reflectance increase indoor thermal comfort conditions and decrease the cooling energy need for buildings in hot climates, but the aging of white coatings increased the cooling energy needs along the time

Maintenance Optimization of Wind Turbines Using Weather-Dependent Equivalent Age Model

Aging models are important input into wind farm maintenance and financial viability models. Aging of wind turbines depends on many factors, including both ambient and usage conditions. This paper presents a virtual age based maintenance model for wind turbines considering the effect of wind speed and ambient air temperature on turbine aging. Two maintenance thresholds (i.e., corrective threshold and preventive threshold) and three repair actions (i.e., unscheduled corrective, scheduled corrective and preventive actions) are integrated into the maintenance model. The objective is to determine the optimal thresholds values that minimize the expected total maintenance costs. A discreet time simulation model is developed to produce 20 years of weather and usage scenarios for a single onshore wind turbine. The optimization model is formulated as a mixed-integer nonlinear problem and solved using the Nelder–Mead method. A numerical example is presented to highlight the benefits of the proposed approach. Compared with traditional age-based maintenance, the proposed approach can achieve improvement in both availability and costs. The results show up to 50% reduction in maintenance cost as well as the significance of the effects of wind speed and ambient air temperature in maintenance planning.

A Cross-Country Model for End-Use Specific Aggregated Household Load Profiles

End-use specific residential electricity load profiles are of interest for energy system modelling that requires future load curves or demand-side management. We present a model that is applicable across countries to predict consumption on a regional and national scale, using openly available data. The model uses neural networks (NNs) to correlate measured consumption from one country (United Kingdom) with weather data and daily profiles of a mix of human activity and device specific power profiles. We then use region-specific weather data and time-use surveys as input for the trained NNs to predict unscaled electric load profiles. The total power profile consists of the end-use household load profiles scaled with real consumption. We compare the model’s results with measured and independently simulated profiles of various European countries. The NNs achieve a mean absolute error compared with the average load of 6.5 to 33% for the test set. For Germany, the standard deviation between the simulation, the standard load profile H0, and measurements from the University of Applied Sciences Berlin is 26.5%. Our approach reduces the amount of input data required compared with existing models for modelling region-specific electricity load profiles considering end-uses and seasonality based on weather parameters. Hourly load profiles for 29 European countries based on four historical weather years are distributed under an open license.

La actividad frutícola en los Valles Templados de Jujuy, Argentina: caracterización del sector

En la provincia de Jujuy, extremo noroccidental de Argentina, se distinguen cuatro regiones ambientales: valles templados, valles cálidos, quebrada y puna. El valle templado es un valle húmedo de clima templado en invierno, se estiman de 350 a 550 horas frío. Cuenta con 30000 ha bajo riego. La actividad principal es la tabacalera, además se desarrolla la horticultura y la fruticultura. La producción frutícola es una alternativa viable económica y agroclimáticamente, con antecedentes de más de 50 años, cuando se introdujeron almendros, higueras, chirimoyos y durazneros, entre otros. La producción que continúa en crecimiento y con incorporación de tecnología es la de duraznos. Los cultivares que se cultivan en la zona tienen características de primicia y de extraprimicia (cosechas de septiembre a diciembre). La condición agroecológica de los valles templados es adecuada para una producción muy temprana, no equiparable a ninguna otra zona del país, con lo cual obtiene grandes ventajas competitivas en los mercados nacionales. Al Mercado Central de Buenos Aires ingresan anualmente, desde Jujuy, 1.300 toneladas de duraznos, esta fruta marca la tendencia de la temporada y la convierte en la principal zona de primicia de duraznos de Argentina. Desde las instituciones del medio (INTA-FCA-UNJU) se trabaja mancomunadamente con el sector frutícola y se han podido realizar importantes avances en la tecnología de producción: densidades de plantación, índices de cosecha, carta de colores para la cosecha, información de mercados, estudios de mercado y análisis de oportunidades comerciales, manejo del cultivo y mejoramiento genético.

Refugees' Encounters With Nordic Rural Areas-Darkness, Wind and "Hygge"!

The paper investigates how refugees settled in rural Norway and Denmark experience and interact with their new rural places of residence. Theoretically, the paper finds inspiration in “phenomenology of practices” (Simonsen, Prog. Hum. Geogr., 2012, 37, 10–26), which emphasizes the bodily and sensory experiences of daily life that spur feelings of, for example, “orientation” or “disorientation”. The empirical material is based on fieldwork and qualitative interviews with refugees and local volunteers in 2016/2017/2019 in small towns in the rural north of Norway and rural Denmark. There are several differences between the Norwegian and Danish rural areas, in relation to distances, climate and population density. Nonetheless, the ways in which the rural areas are experienced from within, by refugees settled there, show surprisingly many similarities. Many of the informants, in both the Norwegian and Danish cases, initially expressed frustration at being placed in rural areas without having any say in the matter. Those who were former city-dwellers especially experienced moments of disorientation, as their encounters with Nordic rural life were experienced as the opposite of their urban backgrounds. Limiting structural conditions very much shape the everyday lives of refugees in the first years, when they do not have a car or the financial capacity to find their own house. They feel stressed, with busy everyday lives made up of long commuting hours on public transport. In these first years of uncertainty, the dark and harsh weather very much adds to the feeling of stress and insecurity. What seem to add “orientation” are social relations with other refugees and local volunteers organizing activities.

The aeolian component inferred from lake sediments in China

Lake sediments preserve different components transported by wind, runoff, and glaciers; therefore, it is important to distinguish the aeolian components in lake sediments. In this study, we used the sediment grain-size characteristics, the end-member modelling algorithm (EMMA), and the thickness of coarse-grained layers in varves to identify aeolian sediments in the KS-2010 core from Kusai Lake. The results indicate that the sand component in the lake sediments can be considered to be related to aeolian processes. Then, we used the sand contents of the surface sediments from 67 lakes to infer the distribution of aeolian activity in China, and the results correlate well with the spatial distribution of the annual maximum wind speed, mean annual blowing sand weather, and mean annual sandstorm. Therefore, the sand component in lake sediments is transported by aeolian processes and can be used as an indicator of wind activity.

An assessment of long-term changes in mortalities due to extreme weather events in India: A study of 50 years’ data, 1970–2019

In the Indian subcontinent, the annual average extreme weather events (EWEs) are reported to be increasing during the last few decades. The impact of increased EWEs on mortality has become a key issue in terms of minimizing it, even with the increasing population. In the present study, based on 50 years’ data (1970–2019) of India Meteorological Department, mortality rates of different EWEs viz., floods, tropical cyclones, heat waves, cold waves, lightning, etc. were analysed, both at the national and state level. The analysis was done based on different periods, i.e. annual, decadal and twenty-year slice periods. Various statistical analyses were carried out. Out of these EWEs, floods accounted for maximum mortality of 46.1%, followed by tropical cyclones with 28.6% mortality. Over the decades, despite a significant rise in EWEs (except for tropical cyclones), there has been a decrease in the mortality rate (mortalities per year per million population). The number of mortalities per event had a significant negative trend for heatwaves and floods, during the last 50 years. The total EWEs had a mortality rate of 3.86 during 1980–1999 and it reduced to 2.14 during 2000–2019. The mortality rate of tropical cyclones reduced by 94% in the past 20 years, whereas for heatwaves and lightning it increased by 62.2% and 52.8%, respectively. However, the change in mortality rate was not found to be statistically significant due to high year to year variability in mortality associated with floods, lightning, and tropical cyclones in the last two decades as compared to earlier decades. In India, among the major states, Odisha, Andhra Pradesh, Assam, Bihar, Kerala, and Maharashtra were found to be having maximum mortality rates due to EWEs in the last two decades and thus there is a need to consider these states with priority for developing disaster management action plans.

Irrigation decision method for winter wheat growth period in a supplementary irrigation area based on a support vector machine algorithm

In supplementary irrigation areas, it is very important to formulate an irrigation plan based on the previous precipitation. However, because of the difficulty of accurately predicting the weather, most studies on irrigation decision making have recommended irrigation schemes under different historical weather years. In this study, a water-saving irrigation system for winter wheat based on the DSSAT model and a genetic algorithm was optimized for different historical years (1970–2017). Accordingly, a decision-making method for determining whether to irrigate in the growth stage of winter wheat was developed using a support vector machine algorithm based on the amount of precipitation in the early stage of winter wheat and the amount of irrigation. The results indicated that the decision-making accuracy in the wintering period, regreening period, and jointing period were 89.4%, 95.7%, and 93.6%, respectively. Thus, the proposed method can effectively determine the irrigation schemes corresponding to different growth stages of winter wheat and facilitate optimal decision making for water-saving irrigation in the winter wheat season in supplementary irrigation areas.

A systematic evaluation of wind's capacity credit in the Western United States

AbstractThe degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.

UK annual weather summary: 2020

UK annual weather summary: 2020

Robust design of a future 100% renewable european energy supply system with hydrogen infrastructure

Variable renewable energy sources (VRES) will be the cornerstones of future energy supply systems. Nevertheless, their inherent intermittency remains an obstacle to their widespread deployment. Renewably-produced or ‘green’ hydrogen has been suggested as an energy carrier that could account for this in a sustainable manner. In this study, a fully VRES-based European energy system in the year 2050 is designed using an iterative minimal cost-optimization approach that ensures robust supply security across 38 weather-year scenarios (1980–2017). The impact of different power generation locations is factored in by defining exclusive VRES groups within each optimization region. From this, it can be seen that higher numbers of groups in each region offer cheaper electricity generation locations to the optimizer and thus decrease the system's total annual costs. Furthermore, the robust system design and impact of inter-annual variability is identified by iteratively combining the installed capacities of different system designs derived through the application of the 38 historical weather years. The system design outlined here has significantly lower capacities in comparison to the maximum regional capacities obtained in the first round of optimization.

Quantifying 450 years of limestone weathering induced by salt crystallization on fortifications in Malta and Gozo

Structure from Motion (SfM) photogrammetry, on-site hardness and water absorption tests, and petrographical and porosimetric analyses on targeted samples were carried out on representative areas within six different locations of Maltese fortifications affected by salt weathering. The objective was to quantify the limestone loss over the last half-millennium and to attempt to identify the controlling factors of durability. The results highlight the existence of a two-rate weathering regime within the Miocene Globigerina Limestone which is the main building stone of the Maltese Islands. With a median stone recession of 1.4 mm/century, the subtype locally called Franka has resisted atmospheric aggression on average 36 times better than the Soll subtype (median stone recession of 50 mm/century). The Oligo-Miocene Coralline Limestone has also resisted well, with a stone recession of on average 1.3 mm/century. Two main controls of the varying durability of these limestones have been identified. First, the water uptake capacity of the least durable, already weathered limestone (Soll) is two to three times higher than that of the weathered but more resistant Franka and Coralline Limestone (6.3 g.m−2.s−1 against 2.5 g.m−2.s−1). Second, there is a marked difference in cohesiveness between these limestones. Whereas the weathered, susceptible Soll facies is poorly-cemented or microcracked, the exposed durable Franka displays an abundant micritic and microsparitic matrix. The statistical relationship between durability and surface hardness is not straightforward, and other controls such as the clay content of limestones should be explored. Investigating a larger number of sites would allow the refining of the limestone durability scale inferred from the present study.

Using recurrent neural networks for localized weather prediction with combined use of public airport data and on-site measurements

Weather data is a crucial input for myriad applications in the built environment, including building energy modeling and daylight analysis. Building science practitioners and researchers have been able to select from a variety of weather files, such as Weather Year for Energy Calculation 2 (WYEC2) and the Typical Meteorological Year (TMY). However, commonly used weather files are typically synthesized to represent trends over a relatively longer periods of time, and are often unable to accurately depict climatic conditions that result from local contexts, such as the heat island effect, wind flow, even local temperature and relative humidity. This results in discrepancies in building performance simulations.This study proposes a methodology using recurrent neural networks to generate synthetic localized weather data that are significantly more accurate and representative of local conditions than standard weather files. The predictions were validated against actual on-site measurements, and achieved a low mean square error of 2.96 and over 185% improvement in validation accuracy. Overall, the performance of selected models has shown over 100% improvements in test accuracy compared with standard weather files and weather station data at the nearest airport. The proposed methodology can be used to morph generic weather files to accurately represent localized conditions, or generate localized data for a longer time span with only a subset of data available/collected. This is useful for downstream built environment applications, especially building energy modeling, since representative weather data capturing trends of temperature and other variables will result in enhanced accuracies of the building energy models. The method can also be used in urban analysis pipelines to enhance resilience against climate change.

Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use

Buildings are subject to significant stresses due to climate change and design strategies for climate resilient buildings are rife with uncertainties which could make interpreting energy use distributions difficult and questionable. This study intends to enhance a robust and credible estimate of the uncertainties and interpretations of building energy performance under climate change. A four-step climate uncertainty propagation approach which propagates downscaled future weather file uncertainties into building energy use is examined. The four-step approach integrates dynamic building simulation, fitting a distribution to average annual weather variables, regression model (between average annual weather variables and energy use) and random sampling. The impact of fitting different distributions to the weather variable (such as Normal, Beta, Weibull, etc.) and regression models (Multiple Linear and Principal Component Regression) of the uncertainty propagation method on cooling and heating energy use distribution for a sample reference office building is evaluated. Results show selecting a full principal component regression model following a best-fit distribution for each principal component of the weather variables can reduce the variation of the output energy distribution compared to simulated data. The results offer a way of understanding compound building energy use distributions and parsing the uncertain nature of climate projections.

100% Sustainable Electricity in the Faroe Islands: Expansion Planning Through Economic Optimization

SEV, the Faroese Power Company, has a vision to reach a 100% renewable power system by 2030. SEV is committed to achieve this, starting from a 41% share of renewables in 2019. A detailed expansion plan for the generation, storage and transmission is needed to reach this goal. This is the focus of this study. Practical constrains e.g. resource potential and available space must be considered. Balmorel, an optimisation tool, has been used to optimise investments and dispatch. A method to translate optimal results to a realistic RoadMap was developed and applied. The impact of different technologies and costs has been investigated through multiple scenarios. In ratios of average consumption in 2030, installed power will be 224% wind, 105% solar with 8–9 days of pumped hydro storage according to the proposed RoadMap. The plan is economically favorable up to 87% of renewables, but in order to reach a 100% renewable production in an average weather year, the renewable generation capacity has to be increased by 80%. The study also shows that if biofules or tidal technologies become viable, these will be game changers needing a significantly lower total sum of installed renewable power.

ПРИМЕНЕНИЕ МИКРОЭЛЕМЕНТОВ ПРИ ВЫРАЩИВАНИИ КАРТОФЕЛЯ -ПРЕДПОСЫЛКИ ИСПОЛЬЗОВАНИЯ ДРОНОВ

The use of trace elements in the form of a chelated fertilizer can increase the yield and shelf life of potato tubers. When processing plantings with a tractor unit after closing the tops, severe damage to the plants by the tractor wheels is likely to be caused. In this case, it is advisable to use drones. The aim of the study was to make a comparative assessment of the eff ect of innovative preparations: sulfur-containing and containing trace elements in chelated form: Fe, Zn, Mn, Cu, Mo, Co, B, and the Aquarin-12 preparation on the yield and shelf life parameters of potato tubers of the Udacha and Kolobok varieties, as well as to perform preliminary calculations of the spray (capture) width when spraying potato plantings with a drone. The studies were conducted in 2018-2019 on sod-podzolic sandy loam soil. The experiment was carried out according to the requirements of the fi eld experiment and potato research methodology. The experiment was laid out according to the scheme, by the method of systematic placement of plots in four-fold repetition with a planting density of 44.4 thousand bushes/ha and the inter-row width of 75 cm. The use of the tested preparations allowed increasing the yield by 3.4…8.7 t/ha (12…37%) and reducing the total storage losses by 1.6…2.3%, especially in a good weather year. According to the calculations performed, it turned out that at the height of the drone fl ight of 9 m, the value of the spraying width or the sprayer’s operating width was 10.4 m. When conducting fi eld tests on potato plantings in a fi eld of 120x20 meters with a plant height of up to 1.0 m, the drone performed that task in 15 minutes (including refueling). A signifi cant increase in yield and a reduction in total losses during storage confi rm the feasibility of using preparations with trace elements in a chelated form when growing potatoes.

Economic Analysis of Power Grid Interconnections Among Europe, North-East Asia, and North America With 100% Renewable Energy Generation

In this paper, we investigate whether the interconnection of power grids with 100% renewable energy generation can bring greater economic benefits now that the technology exists for high power, long distance Ultra High Voltage Direct Current transmission. Based on multi-year historical weather data and demand series, this study compares eight interconnection schemes for three regional grids in Europe, North-East Asia, and North America where there is around 8-hour time difference between any of the two regions. Sensitivity analyses are presented with respect to infrastructure capital cost and different weather year which show that interconnection yields a reduction of approximately 18% in the total annual system cost. The results in this paper also indicate that the regional levelized cost of electricity (LCOE) drops by 31%, 10%, and 10% for Europe, North-East Asia and North America, respectively. It is concluded that there is a strong incentive through both annual cost saving and regional LCOE drop in favour of full long-distance interconnections between the three regions in the context of the international drive towards a net-zero strategy.

Little Drought on the Prairie

Little Drought on the Prairie Barbara Mayes Boustead (bio) For seven years there had been too little rain. The prairies were dust. Day after day, summer after summer, the scorching winds blew the dust and the sun was brassy in a yellow sky. Crop after crop failed. Again and again the barren land had to be mortgaged, for taxes and food and next year's seed. The agony of hope ended when there was no harvest and no more credit, no money to pay interest and taxes; the banker took the land. Then the bank failed. —Rose Wilder Lane, On the Way Home1 author laura Ingalls Wilder (1867–1957), born in Wisconsin, lived in Kansas, Missouri, Minnesota, Iowa, and South Dakota (Dakota Territory) in the course of her childhood, settling in Missouri for most of her adult life. In this essay, I approach the topic of drought in the life and literature of Laura Ingalls Wilder through the lens of my experience as a meteorologist, with thirteen years of experience forecasting weather in the central Plains of the United States, and as a climatologist, in addition to experience as a Laura Ingalls Wilder scholar and researcher. As readers of the Little House book series know, Wilder's historical fiction explores the homestead settlement era of the late 1800s through Wilder's eyes, chronicling the Ingalls family's migratory life in the central United States during her childhood. Wilder documented many weather and climate events in her books, often with stunning accuracy (Boustead et al.). Through the course of her series, Wilder documents a range of weather- and climate-related events: blizzards and tragically difficult winter conditions (On the Banks of Plum Creek, The Long Winter, These Happy Golden Years), extreme cold (Farmer Boy, These Happy Golden Years), tornadoes (These Happy Golden Years), hail storms (The First Four Years), grass fires (Little House on the Prairie, On the Banks of Plum Creek, The First Four Years), a locust infestation (On the Banks of Plum Creek), and floods (On the Banks of Plum Creek, The Long Winter). This essay focuses on her depiction of drought in On the Banks of Plum Creek (1937) and The First Four Years (1971), as well as references to drought in her travel journal, published as On the Way Home (1962). The meteorology community has defined drought rather loosely, compared to other meteorological events, as a period of abnormally dry weather, of short or long duration, that causes a hydrological imbalance ("Drought") that has an impact (Wilhite and Glantz 9). A drought can last for a month or for decades, over small swaths of land or large. In our modern era, meteorologists and climatologists track drought by analyzing precipitation—and sometimes temperature—observations, satellite vegetative health, and objective and subjective impact reports. In the era of homesteading in the central United States, when homesteaders had comparatively brief lived experiences or observations in their new home areas and were unlikely to deeply [End Page 14] consider the input of the Indigenous peoples of the Great Plains, any relative dryness could have been labelled a drought, even if it would not qualify as such by today's standards. Droughts drove the migration of the Ingalls and Wilder families at least three times. The first of these migrations was from Walnut Grove, Minnesota (near the titular Plum Creek), to Burr Oak, Iowa, in 1876. Although Burr Oak was left out of the "Little House" narrative, the Ingalls family spent a year there after failing to thrive on their Plum Creek farm. The Ingalls family arrived at their Walnut Grove farm in 1874, the same year that witnessed the first season of Rocky Mountain locust infestation to reach Minnesota in the 1870s. The locusts had followed unusually warm and dry weather from the central Plains, especially Kansas and Nebraska, then migrated into Missouri, Iowa, and Minnesota. Waves of the airborne locusts dropped into these areas, stripping vegetation and consuming cloth, leather, and other soft materials. They also laid eggs, ensuring a new wave of locusts would spread onward. While other pioneers described a hot summer followed by a dry fall as "grasshopper weather" (Lockwood), Wilder attaches the label "grasshopper weather...

‘Unscrambling’ the drivers of egg production in Agassiz’s desert tortoise: climate and individual attributes predict reproductive output

The ‘bet hedging’ life history strategy of long-lived iteroparous species reduces short-term reproductive output to minimize the risk of reproductive failure over a lifetime. For desert-dwelling ectotherms living in variable and unpredictable environments, reproductive output is further influenced by precipitation and temperature via effects on food availability and limits on activity. We assembled multiple (n = 12) data sets on egg production for the threatened Agassiz’s desert tortoiseGopherus agassiziiacross its range and used these data to build a range-wide predictive model of annual reproductive output as a function of annual weather variation and individual-level attributes (body size and prior-year reproductive status). Climate variables were more robust predictors of reproductive output than individual-level attributes, with overall reproductive output positively related to prior-year precipitation and an earlier start to the spring activity season, and negatively related to spring temperature extremes (monthly temperature range in March-April). Reproductive output was highest for individuals with larger body sizes that reproduced in the previous year. Expected annual reproductive output from 1990-2018 varied from 2-5 to 6-12 eggs female-1yr-1, with a weak decline in expected reproductive output over this time (p = 0.02). Climate-driven environmental variation in expected reproductive output was highly correlated across all 5 Recovery Units for this species (Pearson’s r > 0.9). Overall, our model suggests that climate change could strongly impact the reproductive output of Agassiz’s desert tortoise, and could have a negative population-level effect if precipitation is significantly reduced across the species’ range as predicted under some climate models.