Extreme Heat Waves Research Articles

Integration of resilient cooling technologies in building stock: Impact on thermal comfort, final energy consumption, and GHG emissions

Buildings in the EU contribute significantly to energy consumption and greenhouse gas emissions, with HVAC systems being major contributors. This paper assesses the impact of the resilience of various cooling strategies on thermal comfort, energy consumption, and GHG emissions in the residential building stock in Belgium. This study uses an innovative approach for sizing and designing cooling systems, considering the impact of climate change on future weather conditions and extreme heatwaves. The findings reveal alarming temperature increases, with potential rises of up to 4.1 °C from the 2010s to the 2090s, particularly in the high-emission SSP5-8.5 scenario. The study investigates three cooling strategies: scenario 1 (mechanical ventilation), scenario 2 (mechanical ventilation and natural ventilation), and scenario 3 (mechanical ventilation, natural ventilation, and split system). In scenario 1, there is a notable increase in Indoor Overheating Degree (IOhD), reaching up to 586% in the 2090s for semi-detached buildings, while scenario 2 consistently reduces IOhD, reaching only 0.2 °C by the 2090s. Scenario 3 achieves near-zero IOhD by the 2050s and 2090s. Notably, the “Heatwave [2081–2100]" exhibits unprecedented daytime temperatures, peaking at 46.0 °C. During the 2054 heatwave, insulated buildings maintained the Indoor Operative Temperature (IOpT) below 40 °C, whereas non-insulated buildings reached 44.3 °C, indicating challenges in meeting thermal comfort standards. Furthermore, cooling energy consumption increased by 106%–141% in the 2050s and surge by 174%–280% in the 2090s compared to the 2010s, along with significant GHG emissions growth in the future scenarios, particularly in SSP5-8.5.

Resonant Forcing by Solar Declination of Rossby Waves at the Tropopause and Implications in Extreme Events, Precipitation, and Heat Waves—Part 1: Theory

The purpose of this first article is to provide a physical basis for atmospheric Rossby waves at the tropopause to clarify their properties and improve our knowledge of their role in the genesis of extreme precipitation and heat waves. By analogy with the oceanic Rossby waves, the role played by the pycnocline in ocean Rossby waves is replaced here by the interface between the polar jet and the ascending air column at the meeting of the polar and Ferrel cell circulation or between the subtropical jet and the descending air column at the meeting of the Ferrel and Hadley cell circulation. In both cases, the Rossby waves are suitable for being resonantly forced in harmonic modes by tuning their natural period to the forcing period. Here, the forcing period is one year as a result of the variation in insolation due to solar declination. A search for cause-and-effect relationships is performed from the joint representation of the amplitude and phase of (1) the velocity of the cold or warm modulated airflows at 250 mb resulting from Rossby waves, (2) the geopotential height at 500 mb, and (3) the precipitation rate or ground air temperature. This is for the dominant harmonic mode whose period can be 1/16, 1/32, or 1/64 year, which reflects the intra-seasonal variations in the rising and falling air columns at the meeting of the polar, Ferrel, and Hadley cell circulation. Harmonics determine the duration of blocking. Two case studies referring to extreme cold and heat waves are presented. Dual cyclone–anticyclone systems seem to favor extreme events. They are formed by two joint vortices of opposite signs reversing over a period, concomitantly with the involved modulated airflows at the tropopause. A second article will be oriented toward (1) the examination of different case studies in order to ascertain the common characteristics of Rossby wave patterns leading to extreme events and (2) a map of the globe revealing future trends in the occurrence of extreme events.

Physical mechanism of the rapid increase in intense and long-lived extreme heatwaves in the Northern Hemisphere since 1980

Physical mechanism of the rapid increase in intense and long-lived extreme heatwaves in the Northern Hemisphere since 1980

Amplification of the discrepancy between simplified and physics-based wet-bulb globe temperatures in a warmer climate

The Simplified Wet Bulb Globe Temperature (sWBGT) is widely used in heat stress assessments for climate-change studies, but its limitations have not been thoroughly explored. Building on recent critiques of sWBGT's use for current climate on global scale, this study examines sWBGT's biases using dynamically-downscaled sub-daily climate projections under multiple future emission scenarios. The analysis is aimed at understanding caveats in the application of sWBGT and the uncertainties in existing climate change analysis dependent on sWBGT. Results indicate sWBGT's biases are heavily influenced by local near-surface air temperature, with overestimation of heat stress in East Asia regions, particularly hot and humid areas, due to static assumptions of radiation and wind speed. This overestimation is amplified in warmer climates, leading to exaggerated projected heat stress increases in future. In contrast, underestimations are found for heat stress levels attributed to low wind speeds and strong radiations, such as over the Tibetan Plateau and certain extreme events. Additionally, sWBGT underestimates variability in extreme heatwave events compared to WBGT in both current and future climates, irrespective of overestimation in absolute heatwave intensities. This study emphasizes the limitations of sWBGT, especially in future warmer climates. Importance of sub-daily data for capturing daily maximum heat stress level and reflecting diurnal variations in different components is also discussed. In conclusion, we recommend using Liljegren's model (i.e., physics-based calculation) with high-resolution sub-daily climate data for more accurate outdoor heat stress assessments in climate change studies.

Atmosphere teleconnections from abatement of China aerosol emissions exacerbate Northeast Pacific warm blob events

During 2010 to 2020, Northeast Pacific (NEP) sea surface temperature (SST) experienced the warmest decade ever recorded, manifested in several extreme marine heatwaves, referred to as "warm blob" events, which severely affect marine ecosystems and extreme weather along the west coast of North America. While year-to-year internal climate variability has been suggested as a cause of individual events, the causes of the continuous dramatic NEP SST warming remain elusive. Here, we show that other than the greenhouse gas (GHG) forcing, rapid aerosol abatement in China over the period likely plays an important role. Anomalous tropospheric warming induced by declining aerosols in China generated atmospheric teleconnections from East Asia to the NEP, featuring an intensified and southward-shifted Aleutian Low. The associated atmospheric circulation anomaly weakens the climatological westerlies in the NEP and warms the SST there by suppressing the evaporative cooling. The aerosol-induced mean warming of the NEP SST, along with internal climate variability and the GHG-induced warming, made the warm blob events more frequent and intense during 2010 to 2020. As anthropogenic aerosol emissions continue to decrease, there is likely to be an increase in NEP warm blob events, disproportionately large beyond the direct radiative effects.

Prolonged exposure to elevated temperature leads to severe thermal stress in the broad-nosed pipefish, Syngnathus typhle

ABSTRACT Changes in water temperature may have profound effects on physiology, metabolism, and fish behaviour. However, much of the existing research is based on relatively short-term experiments. In the context of climate change, where water temperatures are increasing seasonally, and the frequency and duration of extreme heatwave events are rising, incorporating longer exposure periods will provide a better understanding of the potential effects of warming on marine species. Here, we tested the effects of prolonged exposure to elevated temperature on broad-nosed pipefish, Syngnathus typhle. Fish were exposed to ambient (20ºC) and high (24ºC) temperatures for a four-month period, during which activity levels, growth and survival were monitored. Fish under high temperature were less active when compared to fish under ambient temperature, grew less, and survival was dramatically decreased. These findings have significant implications for the long-term sustainability of broad-nosed pipefish populations, as the species may struggle to adapt to future ocean conditions.

How virtuous are the bias corrected CMIP6 models in the simulation of heatwave over different meteorological subdivisions of India?

With rising global temperatures, extreme weather events have become more frequent, intense and of longer duration. CMIP6 GCMs provide improved climate simulations that need robust evaluation for historical period for reliable future projections. The present study assesses the ability of bias corrected CMIP6 14 Global Climate Models (GCMs) in simulating heat wave over India for March–June during the historical period (1951–2014). Heat waves were identified using IITM criteria. Model biases were removed using variance scaling bias correction method that showed higher correlation (0.93) and lower root mean square error (2.15) and improvement in approximating the inter-annual variability as well as spatial patterns as observed maximum temperature after bias correction. Evaluation of model performance for 95th and 99th percentile maximum temperature and heatwaves showed that most of the models simulate these extremes similar to observation. Northwestern, Central and South-central regions recorded highest number of heatwaves with a frequency of 50 heatwave days/decade, which were captured by the most of the GCMs varying in decadal frequency over the region. Among the GCM, although all models were found competent, ACCESS-ESM1–5, MPI-ESM1–2HR and MRI-ESM2–0 models were found to be the best performing models for extreme indices and heat wave simulation over India. The study will aid to the current understanding of CMIP6-GCMs performances over the different meteorological subdivisions of India and pave way for future projection of heat waves as well as reduction in uncertainty among the models.

Traces of Local Adaptive Acclimatization Response in the Tracheid Anatomical Traits between Dry and Wet Mesic Norway Spruce (Picea abies) Forests in Moravia, Czech Republic?

Norway spruce (Picea abies) forests in temperate zones are already reacting to short-term extreme summer heatwaves, threatening the vitality of trees and forest productivity, and can even lead to local and regional dieback events. Examining quantitative wood anatomy can provide helpful information in terms of understanding the physiology mechanisms and related responses of conifer trees to local environmental interactions in relation to tracheid adaptive capacity. This study analysed the tracheid functional anatomical traits (FATs) plasticity of six young Norway spruce trees growing in two mesic research plots with high annual precipitation (~43%) and air temperature differences during 2010–2017. The research plots are located in the sub-mountainous (Rájec Němčice) and mountainous (Bílý Kříž) belts of the Moravia region, Czech Republic. Vapour pressure deficit and cell wall reinforcement index (CWRI) were shown to be the most representative environmental parameters as proxies of dry conditions. Tracheid FATs indicated latewood phenological plasticity sensitivity, with more pronounced variability in the warmer and drier plots. Latewood tracheids of Norway spruce trees grown in the RAJ formed significantly thicker cell walls than BK during the studied period. The observed differences between the two research plots indicate additional support for tracheid cells’ hydraulic safety against cavitation and potential traces of adaptive acclimatization response.

Boost to early spring compound heatwaves over South Asia from anomalous Tibetan Plateau atmospheric heat source

In the early spring of 2022, South Asia (SA) experienced an unprecedented and prolonged episode of compound extreme heatwaves (EHWs), which pose significant risks to both human society and ecosystems. This exceptional event broke historical records for both frequency and intensity anomalies since 1981 and could be attributed to a barotropic atmospheric regime characterized by an anomalous anticyclone. This study ascribed this record-breaking event to an exceptionally warm Tibetan Plateau (TP) atmospheric apparent heat source (TPAHS). Both the observations and the numerical experiments conducted with a linear baroclinic model revealed that the unusual TPAHS acted as an “air pump”, driving the vigorous lower-level convergence and ascending motion around the TP. Abnormal TPAHS led to an increase in air temperature, subsequently elevating the height of the tropopause. This, in turn, induced a cooler upper-level and warmer lower-level thermal structure over the TP, resulting in a negative potential vorticity (PV) source near 200 hPa. As the TPAHS continued to intensify, the anomalous anticyclone strengthened and extended westward, facilitating the advection of negative PV anomalies from the TP to upstream regions. This resulted in negative PV anomalies and increased geopotential height over the SA. Furthermore, the triggered zonal circulation significantly enhanced descending motion and reduced relative vorticity, thereby strengthening the barotropic atmospheric regime over the SA. Consequently, clear skies prevailed, amplifying the solar shortwave radiation reaching the ground. This increase in surface thermal radiation warmed the near-surface air temperatures, ultimately resulting in compound EHWs on an interannual timescale.

A Simple Artificial Neural Model to Predict Dambovita River Temperature Affected by Urban Heat Islands in Bucharest City

Water bodies can offer local microclimates that have the potential to attenuate the effects of urban heat islands by reducing local temperature. This capability is shaded when the river is channelized. In such cases, the river temperature rises during hot periods, leading to negative impacts on the water quality. The main aim of this paper is to develop a local simple model to predict the temperature of the Dâmbovița River at its exit from Bucharest City, the capital of Romania. The location is chosen based on the historical critical impacts, in terms of extreme heatwaves that took place during hot summers, as well as future possible risks due to climate change. The water temperature prediction model is based on an artificial neural network that uses the Levenberg–Marquardt algorithm, due to its stability and rapid convergence capabilities. The model forecasts, with an accuracy of ±1 °C, the water temperature in an ungauged, downstream location, as a function of measured air and upstream water temperatures. The proposed model represents a first attempt to provide water managers in Bucharest City with a useful tool that will allow them to take timely measures to counteract the unwanted effects that can be generated by high water temperatures.

Global oceans suffer extreme heatwaves intensifying since the early 21st century: A new comprehensive index

As a result of global warming, major ocean basins have witnessed an increase in the number of extreme warm events and a decrease in the number of extreme cold events, increasing the number of marine heatwave (MHW) events. Previous quantification of MHW events has been limited to simple single metrics, which can only recognize some characteristics from a particular aspect. Here, we propose a new marine Heat Wave Comprehensive Index (HWCI) by fusing multiple metrics to characterize the scalable cumulative intensity of MHWs, which exhibits excellent identification reliability and superiority to effectively monitor the evolutionary patterns of various levels of MHW events. We find that five levels of global MHW events have presented an obvious spatial expansion and temporal enhancement pattern since the early 21st century, with the obvious spatial contraction (32.98 %) of weak events followed by the expansion (19.82 %) of extreme events at the highest growth rate of 0.07, primarily in the mid–low-latitude oceans and the Arctic. The results demonstrate that extreme MHW events dominate global MHW evolution patterns and that the expansion and intensification of such episodes have major implications for the event distribution and level structure. The new indicator is promising for directly measuring and identifying MHWs, and contributes to a more comprehensive understanding of the evolution of MHWs in the context of global climate change.

Record-breaking Barents Sea ice loss favors to the unprecedented summertime extreme heatwave in 2021 over western North America by enhancing Rossby wave ridge

Record-breaking Barents Sea ice loss favors to the unprecedented summertime extreme heatwave in 2021 over western North America by enhancing Rossby wave ridge

Increasing duration of heatwaves poses a threat to oyster sustainability in the Gulf of Mexico

The future of the wild oyster fishery in the northern Gulf of Mexico is largely uncertain due to changing environmental conditions and declining abundance of harvestable oysters. Specifically, rising temperatures can directly impact the physiological thresholds of the eastern oyster (Crassostrea virginica) at all life history stages and alter the narrow ecological niche this oyster occupies. The impact of rising temperatures is likely most pronounced during atmospheric heatwaves, defined as three or more days above the 90th percentile of daily maximum air temperatures, which have been shown to be increasing in frequency. Increasing exposure to high temperature extremes may contribute to and exacerbate an already declining oyster fishery. Critical to fishery health is recruitment i.e., the addition of new harvestable biomass, which is a dynamic process strongly driven by temperature. Here, we examine the relationship between heatwave characteristics and the prediction of poor oyster recruitment, measured as the abundance of post-larval oysters (e.g. spat) below the site-specific median density observed in historically productive oyster fisheries over 46-years (1976 – 2020) in Mobile Bay, Alabama and 21-years (1993 – 2014) in Apalachicola Bay, Florida. We acquired daily maximum air temperature measurements measured over 50 years (1970 – 2020) at weather monitoring stations adjacent to the bays to identify site specific annual heatwave events (maximum yearly air temperature, yearly and consecutive heatwave days, and number of annual heatwaves). Then, years with extreme heatwaves that exceeded the 75th percentile for the 50-year measurements were compared to years with non-extreme heatwave events. Years with extreme total heatwave days and extreme consecutive heatwave days were correlated with low post-larval oyster density. Across both bay systems, if consecutive heatwave days exceeded 11 days, then poor recruitment of oysters occurred 83 % of the time. Extreme heatwave duration as an indicator for poor recruitment has the potential to be a powerful tool for fishery managers to forecast recruitment and inform sustainable oyster harvest based on year-to-year variability in heatwave duration and long-term warming trends. Our findings illustrate how extreme temperatures can exacerbate multiple physiological and ecological stressors resulting in the loss of a keystone species for healthy and resilient coastal ecosystems.

Exposure of future nuclear energy infrastructure to climate change hazards: A review assessment

This review discusses climate hazards and specific risks associated with existing and new nuclear power plants under global warming level futures, with an emphasis on water-based risks for plants that rely on traditional water-cooling processes. Projected hazards, including extreme heatwaves, sea-level rise, and altered precipitation patterns pose significant challenges to the safe and efficient operation of nuclear plants. Additional risks include reduced water-cooling system efficiency, clogging due to biological contamination of water streams, water access issues in reactors during droughts, disruptions from extreme storms, and coastal sea level rise. These findings emphasise the importance of formulating appropriate adaptation strategies that incorporate enhanced safety measures in the planning and design of new nuclear facilities. Incorporating these specific risks into mitigation scenarios and decision-making processes for nuclear energy expansion or modernisation is crucial to improve the resilience of such infrastructure in the face of a changing climate.

Spatial-temporal dynamics of population exposure to compound extreme heat-precipitation events under multiple scenarios for Pearl River Basin, China

Extreme heat-precipitation events, such as heatwaves and extreme precipitation, can have substantial impacts on the population, particularly in urbanized watersheds. However, few studies have investigated individual and compound extreme heat-precipitation events, causing much valuable information loss for watershed climate risk management. This study focuses on the Pearl River Basin (PRB), a highly urbanized area in southern China, and aims to predict changes in population exposure to extreme heat-precipitation events. To achieve this, a ranked ensemble global climate model (GCM) was used to generate projections for individual extreme precipitation, heatwaves, and sequential and coincident heat waves and precipitation extremes (SHWPs and CHWPs) under three future scenarios (SSP-RCPs). The main findings of the study are as follows: Precipitation extremes represent increasing extreme days and intensity under all three scenarios across the PRB. Towards the end of the 21st century, the SSP5-8.5 scenario predicts that heat waves will last ten times longer than historical records. Comparing two types of compound extreme events, we conclude that the 21st century will see a near-term high risk for SHWPs and a long-term high risk for CHWPs in the PRB. Furthermore, in both individual and compound heat-precipitation events, five hotspot cities in the PRB (i.e., Guangzhou, Dongguan, Foshan, Shenzhen, and Huizhou) will face higher population exposure to extreme heat-precipitation events. These cities share common characteristics: key to economic development, coastal, and densely populated. This study can provide insight into extreme climate risk management in other tropical and subtropical basins.

Anthropogenic forcing has increased the risk of longer-traveling and slower-moving large contiguous heatwaves.

Heatwaves are consecutive hot days with devastating impacts on human health and the environment. These events may evolve across both space and time, characterizing a spatiotemporally contiguous propagation pattern that has not been fully understood. Here, we track the spatiotemporally contiguous heatwaves in both reanalysis datasets and model simulations and examine their moving patterns (i.e., moving distance, speed, and direction) in different continents and periods. Substantial changes in contiguous heatwaves have been identified from 1979 to 2020, with longer persistence, longer traveling distance, and slower propagation. These changes have been amplified since 1997, probably due to the weakening of eddy kinetic energy, zonal wind, and anthropogenic forcing. The results suggest that longer-lived, longer-traveling, and slower-moving contiguous heatwaves will cause more devastating impacts on human health and the environment in the future if greenhouse gas emissions keep rising and no effective measures are taken immediately. Our findings provide important implications for the adaption and mitigation of globally connected extreme heatwaves.

L-arginine alleviates heat stress-induced mammary gland injury through modulating CASTOR1-mTORC1 axis mediated mitochondrial homeostasis

As global warming intensifies, extreme heat is becoming increasingly frequent. These extreme heatwaves have decreased the milk production of dairy animals such as cows and goats and have caused significant damage to the entire dairy industry. It is known that heat stress (HS) can induce the apoptosis and autophagy of mammary epithelial cells (MECs), leading to a decrease in lactating MECs. L-arginine can effectively attenuate HS-induced decreases in milk yield, but the exact mechanisms are not fully understood. In this study, we found that HS upregulated the arginine sensor CASTOR1 in mouse MECs. Arginine activated mTORC1 activity through CASTOR1 and promoted mitochondrial biogenesis through the mTORC1/PGC-1α/NRF1 pathway. Moreover, arginine inhibited mitophagy through the CASTOR1/PINK1/Parkin pathway. Mitochondrial homeostasis ensures ATP synthesis and a stable cellular redox state for MECs under HS, further alleviating HS-induced damage and improving the lactation performance of MECs. In conclusion, these findings reveal the molecular mechanisms by which L-arginine relieves HS-induced mammary gland injury, and suggest that the intake of arginine-based feeds or feed additives is a promising method to increase the milk yield of dairy animals in extreme heat conditions.

Heatwave-like events affect drone production and brood-care behaviour in bumblebees.

Climate change is currently considered one of the major threats to biodiversity and is associated with an increase in the frequency and intensity of extreme weather events, such as heatwaves. Heatwaves create acutely stressful conditions that may lead to disruption in the performance and survival of ecologically and economically important organisms, such as insect pollinators. In this study, we investigated the impact of simulated heatwaves on the performance of queenless microcolonies of Bombus terrestris audax under laboratory conditions. Our results indicate that heatwaves can have significant impacts on bumblebee performance. However, contrary to our expectations, exposure to heatwaves did not affect survival. Exposure to a mild 5-day heatwave (30-32 °C) resulted in increased offspring production compared to those exposed to an extreme heatwave (34-36 °C) and to the control group (24 °C). We also found that brood-care behaviours were impacted by the magnitude of the heatwave. Wing fanning occurred occasionally at temperatures of 30-32 °C, whereas at 34-36 °C the proportion of workers engaged in this thermoregulatory behaviour increased significantly. Our results provide insights into the effects of heatwaves on bumblebee colony performance and underscore the use of microcolonies as a valuable tool for studying the effects of extreme weather events. Future research, especially field-based studies replicating natural foraging conditions, is crucial to complement laboratory-based studies to comprehend how heatwaves compromise the performance of pollinators. Such studies may potentially help to identify those species more resilient to climate change, as well as those that are most vulnerable.

Temperature forecasts for the continental United States: a deep learning approach using multidimensional features

Accurate weather forecasts are critical for saving lives, emergency services, and future developments. Climate models such as numerical weather prediction models have made significant advancements in weather forecasts, but these models are computationally expensive and can be subject to inaccurate representations of complex natural interconnections. Alternatively, data-driven machine learning methods have provided new dimensions in assisting weather forecasts. In this study, we used convolutional neural networks (CNN) to assess how geopotential height at different levels of the troposphere may affect the predictability of extreme surface temperature (t2m) via two cases. Specifically, we analyzed temperature forecasts over the continental United States at lead times from 1 day to 30 days by incorporating z100, z200, z500, z700, and z925 hPa levels as inputs to the CNN. In the first case, we applied the framework to predict summer temperatures of 2012, which contributed to one of the extreme heatwave events in the U.S. history. The results show that z500 leads to t2m forecasts with relatively less root mean squared errors (RMSE) than other geopotential heights at most of the lead time under consideration, while the inclusion of more atmospheric pressure levels improves t2m forecasts to a limited extent. At the same lead time, we also predicted the z500 patterns with different levels of geopotential height and temperature as the inputs. We found that the combination of z500, t2m, and t850 (temperature at 850 hPa) is associated with less RMSE for the z500 forecasts compared to other inputs. In contrast to the 2012 summer, our second case examined the wintertime temperature of 2014 when the upper Midwest and Great Lakes regions experienced the coldest winter on record. We found that z200 contributes to better t2m predictions for up to 7-days lead times whereas z925 gives better results for z500 forecasts during this cold event. Collectively, the results suggest that for long-range temperature forecasts based on the CNN, including various levels of geopotential heights could be beneficial.

Summer heatwaves trends and hotspots in the Barcelona Metropolitan Region (1914–2020)

Daily maximum, TX, and minimum, TN, temperatures recorded at Fabra Observatory, for the period 1914–2020 (from June to September), have permitted to identify the daytime and night time heatwaves, HWs, at the Barcelona Metropolitan Region, BMR, along 107 years. Four heatwaves indices have been computed both for maximum and minimum temperatures: the number of events per season, HWN; their maximum duration, HWD; their frequency of occurrence, HWF; and the amplitude of the hottest day event, HWA. Trends in these indices have been obtained and their statistical significance quantified by means of the Mann-Kendall test. For the whole period (1914–2020), positive significant trends have been detected for the four indices, with a marked positive trend since year 2000 for TX, and since 1985 for TN. Nevertheless, when 31-year moving windows have been analysed, both positive and negative significant trends are obtained, being remarkable the change in trend signs around 1960s. The convenience of using the four HW indices is evaluated applying a Principal Component Analysis, PCA, obtaining two principal components. Additionally, the spatial distributions of the MODIS land surface temperatures, LST, corresponding to some extreme heatwaves, permits the detection of two hotspots in the BMR, one for TX and the other for TN. It is also worth mentioning that correlations between the Western Mediterranean Oscillation index, WeMOi, and HW episodes are detected, being notable that, at the beginning of these episodes, WEMOi values are usually lower. These correlations could improve the HWs forecasting.