Daily Totals Research Articles

REGIONÁLNE KLIMATICKÉ SCENÁRE FREKVENCIE VÝSKYTU DNÍ SO ZRÁŽKAMI NA SLOVENSKU

We present scenarios of how frequency of days with precipitation may change over the territory of Slovakia by 2050 and 2080 in the article. Climatic scenarios were created from three regional climate models EURO-CORDEX for the pessimistic emission scenario RCP8.5. We analysed the occurrence of the number of precipitation days for class intervals: 5 – 9.9 mm, 10 – 19.9 mm, 20 – 29.9 mm, 30 – 39.9 mm, as well as for open intervals ≥ 5 mm, ≥ 10 mm, ≥ 20 mm, ≥ 30 mm, and ≥ 40 mm. To correct systematic errors in climate models, we used data (daily precipitation totals) from the national network of rain gauges. The RCM models were corrected in two steps: first in terms of excessive occurrence of so-called “drizzle days”, and then in terms of systematic underestimation of daily sums across the entire distribution function (bias correction). The occurrence of days with daily rainfall exceeding 40 mm for the horizons of 2050 and 2080 is presented in the form of maps. As our analyses revealed, the annual frequency of days with daily rainfall exceeding 40 mm is expected to increase by approximately 20% by the middle of the 21st century and by up to 60% by the end of the century compared to the present. The paper also includes tables with relative changes and absolute frequencies of wet days for 75 selected locations in Slovakia.

Trends in extreme rainfall over the past 55 years suggest springtime subhourly rainfall extremes have intensified in Mahantango Creek, Pennsylvania.

Extreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968-2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek.

Spatiotemporal variability of flash floods and their human impacts in the Czech Republic during the 2001–2023 period

Abstract. Flash floods, characterized by their sudden onset, extreme discharge, short duration, material damage, and human loss, represent a significant natural hazard. Not well covered by standard hydrological observations, flash flood data can primarily be derived from various types of documentary evidence. This evidence served as the main data source for creating a flash flood database for the Czech Republic from 2001 to 2023. This database enabled detailed analysis of different aspects of flash floods. The annual series of 233 flash flood events, 160 flash flood days, and 424 affected municipalities showed significant inter-annual variability but no linear trends. The triggering rainfall that generates flash floods was analyzed with respect to 1–3-hourly and daily precipitation totals and circulation types from the objective classification. While flash floods can occur anywhere, they were more frequently recorded at the foots of mountain slopes, often coinciding with “critical points” where built-up areas meet concentrated surface runoff pathways. The division of material damage caused by flash floods into eight categories indicated that the highest proportion of damage was to streets and communications (24.3 %), to houses (21.7 %), and to their cellars and basements (18.3 %). There were also 36 recorded fatalities. The understanding of flash floods in the Czech Republic aligns generally well with studies of flash floods in other European regions.

Climatology of Orographic Precipitation Gradients Over High Mountain Asia Derived From Dynamical Downscaling

AbstractWithin High Mountain Asia (HMA), the annual melting of glaciers and snowpack provides vital freshwater to populations living downstream. Precipitation over HMA can directly affect the freshwater availability in this region by altering the mass balance of glaciers and snowpack. However, available reanalyses and downscaling simulations lack the resolution required to understand important glacier‐scale variations in precipitation. This study aimed to determine the current characteristics of orographic precipitation gradients (OPG) by curve‐fitting daily precipitation as a function of elevation from a 15‐year, 4‐km grid spaced Weather Research and Forecasting (WRF) model simulation focused on the Himalayan, Karakoram, and Hindu‐Kush mountain ranges. To facilitate precipitation curve‐fitting, the WRF model grid points were separated into regions of similar orientation, referred to as facets. Akaike Information Criterion‐corrected values and an F‐test p‐value identified the need for a curvature term to account for a varying OPG with elevation. Regions with similar seasonal variability were found using ‐means clustering of the monthly mean OPG coefficients. The central Himalayan slope's intra‐seasonal variability of OPG depended on synoptic scale conditions, in which cyclonically‐forced heavy‐precipitation events produced strong sublinear increases in precipitation with elevation. Initial testing of precipitation estimates using monthly coefficients showed promising results in downscaling daily WRF precipitation; the daily mean absolute error at each grid point had a lower magnitude than the daily mean precipitation total, on average. Results provide a physically‐based context for machine learning algorithms being developed to predict OPG and downscale precipitation output from global climate models over HMA.

Variability of Dry Days and Sequences of Dry Days in the Polish Carpathians in the Period 1986–2020

This study provides a climatological analysis of annual and long-term variability of dry days and sequences of dry days in the Polish Carpathians between 1986 and 2020. The input data for the research was compiled from the daily precipitation totals from 17 meteorological stations and the T. Niedźwiedź catalogue of circulation types over southern Poland. The frequency of sequences of dry days of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. The number of dry days and the averages of both the number and of the duration of sequences of dry days were analysed for the study period. This yielded an average annual number of dry days ranging from 142 to 195 (39–53% of days in a year), depending on the altitude above sea level and longitude. A general pattern emerged in which the number of dry days increased from west to east. At most stations, there were no statistically significant trends with respect to the dry day characteristics analysed. This is an obvious result of high year-to-year variability, which means that only large changes can achieve statistical significance. Dry days have been evidenced to relate to circulation types. The vast majority of dry days are related to anticyclonic systems, particularly the anticyclonic wedge (Ka) and western anticyclonic (Wa) situations. On the other hand, no clear-cut relationship was established between an increase in air temperature and the occurrence of dry days.

Water Budget Input Linked to Atmospheric Rivers in British Columbia's Nechako River Basin

ABSTRACTThis study explores the contribution of atmospheric rivers (ARs) to the water budget input of the Nechako River Basin (NRB) in British Columbia (BC), western Canada. The study quantifies the fraction of precipitation, rainfall, snowfall, and snow water equivalent (SWE) associated with ARs at multiple scales and tests for trends using the Mann–Kendall (MK) test. AR‐related totals for 1950–2021 were created by linking AR events to water budget input variables of the ERA5‐Land reanalysis product on a daily scale. Associations with different phases of the El Niño‐Southern Oscillation (ENSO) climate pattern and AR‐related contributions to the NRB are also investigated. Results indicate an increasing fractional contribution of rain in ARs landfalling in the NRB in the last two decades (2000–2019). Moreover, 21% of the total annual precipitation in the NRB is associated with ARs, with decreasing contributions from west to east. October has higher AR‐related total precipitation than other months, while March, May and June are the least affected. ARs contribute disproportionately more to mid‐ and high‐intensity daily precipitation totals, and provide up to 45% and 24% of the seasonal rainfall and snowfall, respectively. AR‐related SWE is relatively higher in autumn due to the increased frequency and intensity of ARs, resulting in a greater fractional contribution of ARs to the snowpack compared to winter. ARs influence snowpack accumulation during fall (18%) and winter (13%) but also increase the risk of natural hazards. The MK test for AR‐related water budget variables on the annual scale identified no significant trends. However, AR‐related snowfall shows decreasing trends in the NRB, more specifically in the Upper Nechako, Lower Nechako and Stellako sub‐basins during the summer. Over the study period, ARs consistently contribute up to one‐fifth of the annual input to the NRB's water budget. This study provides the first quantitative assessment and trend analyses of AR contributions to the water budget input of a reservoir‐regulated watershed in north‐central BC, yielding valuable information for hydropower production, ecological flows, irrigation, domestic and industrial water use.

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

Rapid Estimation of Soil Erosion Rate from Exhumed Roots (Xiaolong Mts, China)

Soil erosion is a challenge worldwide, including in China. The dendrogeomorphic method was applied, for the first time, at Xiaolong Mts in Gansu Province to obtain a quantitative estimate of the soil erosion rate. The dataset built in this pilot study allowed the identification of exhumation texture in exposed roots between 1967 and 2002. The calculated mean erosion rate estimates (Era) ranged from 2.6 to 16.5 mm yr−1 and showed an increase with the slope steepness (s). The best fitting linear model (Era = 0.043(±0.017) × s + 3.09(±1.04); R² = 0.20; R²adj = 0.16; F = 6.18; p = 0.02) could be used in future research to determine and to map soil denudation in this part of the Xiaolong Mts. Notable associations were found between erosive rainfalls and root exhumation events. Daily (Rx1day) and 5-day (Rx5day) precipitation totals of 56 and 73 mm, respectively, seem to be critical thresholds which if exceeded will always induce root exhumation in the same year or in the consecutive season in the forest of the Xiaolong Mts in the studied period.

Dry and Wet Spells in Poland in the Period 1966–2023

The aim of this study is to present the spatial and temporal variability of the frequency of dry and wet days and dry and wet spells against the background of changes in precipitation and atmospheric circulation. The study is based on daily precipitation totals from 46 meteorological stations in Poland from 1966 to 2023. Additionally, seven circulation indices were used, namely GBI, NAO, AO, EA, EA/WR, SCAND, and AMO. Dry days are defined as days without precipitation. Wet days are days with at least 1 mm of precipitation. It was shown that dry spells are much more common than wet spells, are longer, and cover larger areas. Long-term changes in the annual characteristics of dry and wet days and spells are not statistically significant. Only the length of the most extended dry spell in the year increases. However, there are significant changes in their annual cycles. Spring is drier; in summer, precipitation decreases in the south and increases in the north; November and December, symbols of gloomy rainy weather, are increasingly drier; and rainy weather has shifted to January and February. The impact of circulation varies according to the season, with the NAO, AO, SCAND, and GBI indices having the greatest influence.

Price And Replenishment of Vegetables Based on NARX Neural Network

The research on the replenishment and pricing of vegetable commodities is helpful for supermarket to make more scientific purchase and sale decisions. Based on this, this paper mainly uses NARX neural network to study the replenishment and pricing of vegetable commodities. Firstly, it preprocesses the missing and abnormal values of the data, constructs a correlation analysis model to study the relationship between the sales of various categories of vegetables, then establishes a NARX neural network model to solve the daily replenishment total, and finally constructs a single objective programming model to get the pricing strategy, which provides a theoretical basis for supermarket to make scientific pricing and replenishment decisions.

Rainstorm variability is mainly influenced by the southwest monsoon in the Hanjiang River basin of China during 1985–2020

AbstractThe extreme precipitation in China is greatly influenced by the East Asian summer monsoon, which can be divided into two components: the southeast monsoon (SEM) and the southwest monsoon (SWM). The Hanjiang River basin (HJB), a representative monsoon‐influenced basin in China, is alternately influenced by the southwest monsoon and southeast monsoon throughout the year. However, the specific relationship between rainstorms and monsoons, and the relative contribution of different monsoons, remains unclear in the HJB. Using multiple datasets, this study analysed the variability of various rainstorm types in the HJB during 1985–2020, investigated their relationships with different monsoon indicators and assessed the contribution of monsoons on the rainstorm variance. The results reveal a nonsignificant increasing trend in rainstorms within the basin, the severe convective rainstorm days accounted for a high proportion of the total rainstorm days, and the spatiotemporal characteristics of different rainstorm types are different. The rainstorm indicators are significantly correlated with the monsoon within the HJB and are positively correlated with the SWM, particularly its intensity. The SEM exhibits a weak correlation with rainstorms and has limited explanation for the variance in rainstorms. The intensity of SWM within the HJB shows a significant positive correlation with all rainstorm indicators. It is also detected as the most important indicator for explaining the interannual variation in rainstorms, explaining 41.97% and 39.45% of the variance in daily rainstorm frequency and totals, which comprises more than half of the total explanatory portion. The explanation of circulation factors for the variance in daily rainstorms is higher than that for severe convective rainstorms. In addition to monsoons, the Pacific Decadal Oscillation and the Southern Oscillation Index also have a great contribution to the rainstorm variability in the HJB.

The Variability of Maximum Daily Precipitation and the Underlying Circulation Conditions in Kraków, Southern Poland

This article studies the intra-annual and long-term variability in the maximum daily precipitation totals and their association with atmospheric circulation in Kraków. It investigates daily precipitation maxima by year and by month. The research is based on daily precipitation totals in the years 1863–2021 and draws on the calendar of atmospheric circulation types by Niedźwiedź. It examines the frequency of precipitation maxima in individual months and their variation from one year to another. No statistically significant trend of change in precipitation over the study period has been found. All annual maximum daily precipitation totals in Kraków fall into the category of heavy precipitation (>10 mm), and almost 99% qualify as very heavy (>20 mm). In the summer months, these are about 3–4 times higher than in winter. The share of the daily precipitation maximum in the monthly total exceeds 30% in all months. The maximum daily precipitation occurring on 5 August 2021 was the highest in the period that extends from the start of instrumental measurements. The study period saw 12 cases of maximum precipitation that belong to ‘flood-inducing’ categories (over 70 mm/day). Such cases of the very heaviest precipitation occurred in cyclonic situations: Cc, Bc, Nc, NEc, Ec and SEc. Most spring and summer maxima were seen on days with a cyclonic circulation. The instances of high daily precipitation in the Kraków area led to the flooding of residential and historic buildings, as well as of municipal infrastructure.

IMERG Precipitation Improves the SMAP Level-4 Soil Moisture Product

Abstract The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface and root-zone soil moisture from April 2015 to the present with a mean latency of 2.5 days from the time of observation. The L4_SM algorithm assimilates SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observation-based precipitation. This paper describes and evaluates the use of satellite- and gauge-based precipitation from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products in the L4_SM algorithm beginning with L4_SM Version 6. Specifically, IMERG is used in two ways: (i) The L4_SM precipitation reference climatology is primarily based on IMERG-Final (Version 06B) data, replacing the Global Precipitation Climatology Project Version 2.2 data used in previous L4_SM versions, and (ii) the precipitation forcing outside of North America and the high latitudes is corrected to match the daily totals from IMERG, replacing the gauge-only, daily product or uncorrected weather analysis precipitation used there in earlier L4_SM versions. The use of IMERG precipitation improves the anomaly time series correlation coefficient of L4_SM surface soil moisture (versus independent satellite estimates) by 0.03 in the global average and by up to ∼0.3 in parts of South America, Africa, Australia, and East Asia, where the quality of the gauge-only precipitation product used in earlier L4_SM versions is poor. The improvements also reduce the time series standard deviation of the Tb observation-minus-forecast residuals from 5.5 K in L4_SM Version 5 to 5.1 K in Version 6. Significance Statement Soil moisture links the land surface water, energy, and carbon cycles. NASA Soil Moisture Active Passive (SMAP) satellite observations and observation-based precipitation data are merged into a numerical model of land surface water and energy balance processes to generate the global, 9-km resolution, 3-hourly Level-4 Soil Moisture (L4_SM) data product. The product is available with ∼2.5-day latency to support Earth science research and applications, such as flood prediction and drought monitoring. We show that a recent L4_SM algorithm update using satellite- and gauge-based precipitation inputs from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products improves the temporal variations in the estimated soil moisture, particularly in otherwise poorly instrumented regions in South America, Africa, Australia, and East Asia.

Geriatric Pain Protocol: Impact of Multimodal Pain Care for Elderly Orthopaedic Trauma Patients.

Hip fractures are costly, and associated complications are the leading cause of injury-related deaths in persons 65 years or older. Pain medications in this population can be more potent, have a longer duration of action, and have serious side effects (Chau et al., 2008). Hip fractures are projected to reach 6.26 million worldwide by 2050 (Gullberg et al., 1997; Kannus et al., 1996). Morrison et al. (2003) report that uncontrolled pain leads to increased hospital length of stay (LOS), delayed physical therapy, and long-term functional impairment. The Geriatric Pain Protocol (GPP) is Cedars-Sinai's multimodal pain management solution, addressing the needs of older adult inpatients who have suffered fractures. Can the implementation of GPP reduce the morphine milligram equivalents (MMEs) used, LOS, and postoperative outcomes compared with non-GPP patients? Study participants included hip fracture patients admitted between February 1, 2019, and March 5, 2021; data were collected prospectively from electronic medical records. Inclusion criteria were patients 65 years or older with a hip fracture sustained from a ground-level fall and surgical candidate. Participants were divided into two categories: Geriatric Fracture Program (GFP) and non-GFP, with physician participation in the GFP being the differentiating factor. End points included postoperative pain, postoperative opioid utilization, LOS, complications, and 30-day readmission rates. The Mann-Whitney U test and Fisher's exact test were used for data analysis. Spearman's rank-based correlation coefficient was used to assess associations. The GPP decreased MME daily totals on Days 1 and 2 and improved pain management compared with non-GPP patients. The MMEs were lower in the GPP group than in the non-GPP group for both Postoperative Day 1 (POD1) (p = .007) and POD2 (p = .043); Numerical Rating Scale (NRS) Pain on POD1 was lower in the GPP group (vs. non-GPP, p = .013). There were no group differences in NRS POD2 Pain or complications (all ps > .1). The study sample (N = 453) had no significant difference between sex and LOS (all ps > .3). Although not statistically significant, the 30-day readmission rate trended lower in patients treated in accordance with the GPP. Use of the multimodal GPP reduced pain levels and MME totals for older adult hip fracture inpatients. More data are needed to evaluate the efficiency of the proposed protocol. Future studies should explore the possibilities of using the GPP across the geriatric orthopaedic patient care continuum.

A gauge-based sub-daily extreme rainfall climatology for western Europe

We present here the first climatology of extreme sub-daily rainfall for a large part of western Europe, developed using a newly developed set of sub-daily rainfall indices, derived from a recently created global sub-daily rainfall (GSDR) dataset. The indices describe sub-daily (3-hourly) rainfall extremes in terms of their intensity, frequency and timing. Analysis of the frequency index (number of 3hr periods with >20 mm rain (R3hr20mm)) and a suite of intensity indices including the annual maxima (Rx3hr) and values of the 99.9th percentile at each gauge (R99.9p3hr) indicate a peak in the frequency and intensity of short-duration rainfall extremes in summer across most of western Europe, while areas around the north-west Mediterranean experience the highest intensities and frequencies of 3-hr rainfall in autumn. The index of contribution from 3-h annual maxima to the daily total (Rx3hrP) indicates that these events are often produced by very short-duration or very peaked storms, with a tendency towards a late afternoon or evening peak in the time of occurrence. There are also clear differences in the spatiotemporal occurrence of the sub-daily extremes when compared to extreme daily rainfall indices, which could have repercussions for flood management. Additional analysis of the sub-daily rainfall indices within the context of Köppen-Geiger climate zones indicates Mediterranean-type climate zones experience more intense and more frequent sub-daily extremes, while the intensity of rainfall within cooler climate zones is lower and the most intense events are restricted to summer. The climate zones are found to be a relatively good indicator of the extreme rainfall characteristics that can be expected in a region. Being able to compare sub-daily rainfall characteristics across a wide region in this manner greatly enhances our ability to investigate future variability and change in sub-daily extremes and will aid in high-resolution climate model validation.

Sap flow responses in pioneer and late-successional tree species in secondary tropical montane forests of Eastern Himalaya, India.

The interactive role of life-history traits and environmental forcing on plant-water relations is crucial for understanding species response to climate change but remains poorly understood in secondary tropical montane forests (TMFs). Comparing contrasting life-history traits (pioneer vs late-successional species) in a biodiverse Eastern Himalayan secondary TMF, we investigated sap flow responses in co-occurring pioneer species, Symplocos racemosa (n=5) and Eurya acuminata (n=5), and late-successional species, Castanopsis hystrix (n=3), using modified Granier's Thermal Dissipation probes. The fast-growing pioneers S. racemosa and E. acuminata) had 2.1- and 1.6-times higher sap flux density than the late-successional C. hystrix, respectively, and exhibited characteristics of long-lived pioneer species. Significant radial and azimuthal variability in sap flow (V) between species was observed and attributed to life history traits and the canopy's access to sunlight. Nocturnal V (1800-0500hr) was 13.8 % of daily V and is attributed to stem recharge for evening V (1800-2300hr) and to endogenous stomatal controls for pre-dawn V (0000-0500hr). Both the shallow-rooted pioneer species exhibited midday depression in V attributed to photosensitivity and diel moisture stress response. In contrast, deep-rooted C. hystrix transpired unaffected across the dry season likely accessing groundwater. Thus, the secondary broadleaved TMFs, with the dominance of shallow-rooted pioneers, are more prone to the negative impacts of drier and warmer winters than primary forests, which are dominated by deep-rooted species. The study provides an empirical understanding of life-history traits and microclimate modulating plant-water use in widely distributed secondary TMFs in Eastern Himalaya and highlights their vulnerability against warmer winters and reduced snowfall due to climate change.

Bartlett–Lewis Model Calibrated with Satellite-Derived Precipitation Data to Estimate Daily Peak 15 Min Rainfall Intensity

Temporal variability of rainfall is extreme in the rangelands of northern Australia and occurs at annual, decadal, and even longer timescales. To maintain long-term productivity of the rangelands of northern Australia under highly variable rainfall conditions, suitable land management practices are assessed using rangeland biophysical models, e.g., GRASP (GRASs Production). The daily maxima of the 15 min rainfall intensity (I15) are used to predict runoff and moisture retention in the model. The performance of rangeland biophysical models heavily relies on the I15 estimates. As the number of pluviograph stations is very limited in northern Australian rangelands, an empirical I15 model (Fraser) was developed using readily available daily climate variables, i.e., daily rainfall total, daily diurnal temperature range, and daily minimum temperature. The aim of this study is to estimate I15 from daily rainfall totals using a well-established disaggregation scheme coupled with the Bartlett–Lewis rectangular pulse (BLRP) model. In the absence of pluviograph data, the BLRP models (RBL-E and RBL-G) were calibrated with the precipitation statistics estimated using the Integrated Multi-satellitE Retrievals for GPM (global precipitation measurement) (IMERG; 30 min, 0.1° resolution) precipitation product. The Fraser, RBL-E, and RBL-G models were assessed using 1 min pluviograph data at a single test site in Darwin. The results indicated that all three models tended to underestimate the observed I15, while a serious underestimation was observed for RBL-E and RBL-G. The underestimation by the Fraser, RBL-E, and RBL-G models consisted of 23%, 38%, and 50% on average, respectively. Furthermore, the Fraser model represented 29% of the variation in observed I15, whereas RBL-E and RBL-G represented only 7% and 11% of the variation, respectively. A comparison of RBL-E and RBL-G suggested that the difference in the spatial scales of IMERG and pluviograph data needs to be addressed to improve the performance of RBL-E and RBL-G. Overall, the findings of this study demonstrate that the BLRP model calibrated with IMERG statistics has the potential for estimating I15 for the GRASP biophysical model once the scale difference between IMERG and point rainfall data is addressed.

The effect of day-only versus day-plus-night cooling of dairy cows

The aim of this study was to assess effects on milk yield (MY), rumen temperature, and panting score when lactating dairy cows were cooled during the day only or during the day and night. The study was conducted over 106 d during using 120 multiparous Holstein-Friesian cows assigned to 2 treatments (60 cows/treatment; 2 pens/treatment): (1) day cooling (DC): overhead sprinklers (large droplet) and fans while in the dairy holding yard only, shade and fans at the feedpad, and a shaded loafing area; and (2) enhanced day+night cooling (EDN): overhead sprinklers (large droplet) and fans in dairy holding yard, ducted air blowing onto cows during milking, plus thorough wetting (shower array) on exit from dairy; shade and fans at feedpad (turned off at night); and shaded loafing area + ducted fan-forced air blowing onto cows at night. The ducted air at night was manually activated at 2030 h when the maximum daily temperature-humidity index exceeded 75 and remained on until 0430 h the next day. The cows were fed a total mixed ration ad libitum, and feed intake was determined on a pen basis. Rumen temperature and cow activity were obtained from each cow at 10-min intervals via rumen boluses. Panting scores were obtained by direct observation 4 times a day at approximately 0430, 0930, 1530, and 2030 h. Cows were milked twice daily: 0500 to 0600 h and 1600 to 1700 h. Individual MY were obtained at each milking and combined to give individual daily totals. The EDN cows had greater daily MY (+2.05 kg/cow per day) over the duration of the study compared with DC cows. Rumen temperature during the third heat wave was lower for EDN (39.51 ± 0.01°C) than for DC (39.66 ± 0.01°C) cows. During the most severe heat wave (heat wave 3), MY for the 2 groups was similar, but over the 6 d following the heat wave, EDN cows had greater daily MY (+3.61 kg/cow per day). Rumen temperature was lower for EDN (39.58 ± 0.01°C) than for DC (40.10 ± 0.01°C) cows.

Evaluation of IMERG for GPM satellite-based precipitation products for extreme precipitation indices over Turkiye

As hydrological disasters become more common, the need for monitoring extreme precipitation events is growing globally. Remote sensing technologies developed in recent years help to meet this demand with satellite-based precipitation products, particularly for ungauged basins. However, due to limitations and uncertainties, these products must be validated before being used in hydrometeorological/climatological applications. Validation studies also help improve retrieval algorithms by identifying errors and biases in the data that can be corrected or adjusted. One of NASA's Global Precipitation Measurement products, called Integrated Multi-satellitE Retrievals for GPM (IMERG), has been extensively validated for its ability to detect extreme precipitation events in drastically different climate regions across the world. However, such studies remain limited for Turkiye. In this study, we examined the ability of IMERG Early (E), Late (L), and Final (F) products to detect extreme precipitation in Turkiye using rain gauge data over an eleven-year period (2010−2020). We used extreme precipitation indices recommended by the Expert Team on Climate Change Detection Indices (ETCCDI) to evaluate the ability of IMERG products to detect extreme precipitation. For the stations selected across Turkiye, the Pearson correlation coefficients (R) between daily ground-based precipitation measurements and the three IMERG precipitation products (IMERG-E, IMERG-L, and IMERG-F) were found to be 0.54, 0.55, and 0.64, respectively. IMERG products performed better in detecting the precipitation extreme based on the 85% percentile compared to the 95% and 99% percentiles. IMERG underestimates consecutive dry days by about 25% while overestimating consecutive wet days at the same rate. The performance of IMERG Early, Late, and Final products is inversely proportional to the daily precipitation totals. The annual intensity of precipitation outperformed in the Final run compared to other products across the country. Light and moderate rainfall was detected well, while the detection capability of IMERG decreased for heavy and heavy torrential precipitation. Geographically, the Aegean, Mediterranean, and Southeastern Anatolia regions generally performed better, while Eastern Anatolia and interior parts of the Black Sea region exhibited poorer performance. The low performance in Eastern Anatolia may be attributed to the region's mountainous terrain, while the low performance in the Black Sea region may be due to orographic forcing and land-sea interaction. Overall, the findings of this study showed that the detection capability of IMERG products performed better with increasing latency.

Evaluation of Selected Amateur Rain Gauges with Hellmann Rain Gauge Measurements

The paper compares precipitation measurements from the Stratus manual rain gauge from the CoCoRaHS network and two Davis Vantage Vue and Davis Vantage Pro 2A rain gauges with the Hellmann rain gauge. Comparative measurements were made on a specially prepared experimental plot. The statistical calculations took into account 15 full months in the period from 1 October 2019, to 31 December 2020. In order to estimate the differences in measurements between amateur rain gauges and the Hellmann rain gauge, two statistics were calculated: the mean square error (MSE) and the mean absolute error (MAE). In order to present formal and more detailed differences in measurements between amateur rain gauges and the Hellmann rain gauge, analyses were performed using a linear regression model. The general form of the tested models was presented. The procedure for estimating the parameters of the models and the method of comparing the fit of the models to the data were described, and the rain gauge whose measurements were most closely related to the measurements of the Hellmann rain gauge was indicated. The study showed that the higher price of amateur rain gauges does not mean higher quality. The study showed that the Stratus rain gauge was the best at recording daily precipitation totals. The Davis Vantage Pro 2A rain gauge recorded daily precipitation sums with less accuracy. The Davis Vantage Vue rain gauge, despite being located on the roof, recorded similar rainfall totals as the Hellmann rain gauge. It was found that, despite the different construction and measurement methods, the precipitation measurement data from the Stratus rain gauge and the Davis Vantage Vue rain gauge are suitable both for climate monitoring and for use, after applying quality control, in NMHS networks.