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The high latitude Southern Hemisphere (SH) is an important region for Earth's climate. Ocean heat content, cryosphere interactions, Antarctic bottom water development and the cloud‐albedo feedbacks need to be understood to form a complete picture of the climate system. However, the high latitude SH is one of the most under‐observed regions due to its remoteness. The advent of satellites and reanalyses have improved our monitoring of this region. Some previous studies observed an increase in precipitation over the SH high latitudes, however we argue that some of the trends in commonly used data sets may be artifacts. We use regression analysis of trends in precipitation and the Southern Annular Mode to contrast these relationships in satellite and reanalysis products, and to evaluate precipitation over the SH. We suggest that sensor changes and the lack of in situ data available for calibration may be responsible for unusual precipitation patterns especially around 65°S. Plain Language Summary: Many important processes in the Earth's climate occur at high latitudes in the Southern Hemisphere. However, due to its remoteness and inhospitable conditions, scientists have trouble obtaining data for this region. Satellites have helped to provide information about this area but are not well constrained due to a lack of in situ data. Sensor changes and the launch of new satellites means that the data can vary in quality and reliability over time. By comparing precipitation trends over the Southern Hemisphere with known climate patterns, we suggest that an observed increase in precipitation over the Southern Hemisphere high latitudes may be due to variations in the satellite technology rather than a physical increase in precipitation. This is important for understanding the impacts of climate change on Earth's water cycle and heat storage. Key Points: High latitude precipitation trends are likely artifactsSensor changes may be responsible for spurious trends in the Southern OceanSatellite products do not agree on the zonal mean precipitation pattern in the Southern Hemisphere [ABSTRACT FROM AUTHOR]

Estimates of observed long-term changes in daily precipitation globally have been limited due to availability of high-quality observations. In this study, a new gridded dataset of daily precipitation, called Rainfall Estimates on a Gridded Network (REGEN) V1–2019, was used to perform an assessment of the climatic changes in precipitation at each global land location (except Antarctica). This study investigates changes in the number of wet days (≥1 mm) and the entire distribution of daily wet- and all-day records, in addition to trends in annual and seasonal totals from daily records, between 1950 and 2016. The main finding of this study is that precipitation has intensified across a majority of land areas globally throughout the wet-day distribution. This means that when it rains, light, moderate, or heavy wet-day precipitation has become more intense across most of the globe. Widespread increases in the frequency of wet days are observed across Asia and the United States, and widespread increases in the precipitation intensity are observed across Europe and Australia. Based on a comparison of spatial pattern of changes in frequency, intensity, and the distribution of daily totals, we propose that changes in light and moderate precipitation are characterized by changes in precipitation frequency, whereas changes in extreme precipitation are primarily characterized by intensity changes. Based on the uncertainty estimates from REGEN, this study highlights all results in the context of grids with high-quality observations. [ABSTRACT FROM AUTHOR]

Robust conclusions regarding changes in the temperature distribution rely on the accuracy and reliability of the input datasets used. Differences between methodologies and datasets in previous studies add uncertainty when comparing and quantifying findings. Here, the authors investigate the sensitivity of assessing global and regional temperature variability and extremes over 1980-2014 in gridded datasets of daily temperature anomalies. A gridded in situ-based dataset, Hadley Centre Global Historical Climatology Network-Daily (HadGHCND), is compared against several commonly used reanalysis products by assessing both the entire distribution and the tails of the distribution. Empirical probability distribution functions show sensitivity to the input dataset when estimating aspects such as standard deviation and skewness, with the mean showing robust results for most regions, irrespective of dataset choice. Standard deviation is especially sensitive, with larger disagreements between datasets for some regions more than others, such as Africa and the Mediterranean region, andwith larger differences inminimumtemperatures compared withmaximumtemperatures. Estimates of extreme parameters also show sensitivity to dataset choice, particularly in the lower tails and for daily minimum temperature anomalies. Comparing changes in the means and the extremes of the temperature distributions, the cold extremes in the lower tails have been warming at a faster rate than the mean of the entire distribution for much of the Northern Hemisphere extratropics, with warm extremes warming at a faster rate than the mean in some subtropical regions. These documented sensitivities call for caution when assessing changes in temperature variability and extremes, as dataset choice can have substantial effects on results. [ABSTRACT FROM AUTHOR]

ABSTRACT Some of the major drivers of extreme temperatures in Australia are related to large-scale variations in the climate. While many of the relationships between climate variability and heatwaves have been described, the preceding climate conditions and the circulation patterns responsible for interannual heatwave variations are still poorly understood. We have used rotated principal component analysis ( PCA) to describe the variance of frequency, duration, magnitude and timing of Australian summer heatwaves. This provides a simple means of investigating both the spatial patterns of circulation and the preceding climate mode conditions of summer heatwaves. We find that spatial patterns of heatwave variability associated with El Niño-Southern Oscillation ( ENSO) were focused in the north and northeast of Australia for heatwave occurrence. Patterns of heatwave amplitude in southeastern Australia were also weakly related to ENSO. The PCA did not find any direct, concurrent Indian Ocean Dipole ( IOD) or Southern Annular Mode ( SAM) signal. However, lead correlations indicate that winter IOD conditions can have a weak indirect effect on heatwave occurrence in northeast Australia and similarly, winter SAM conditions can affect heatwave timing in central eastern Australia. Regressions reveal that ENSO related heatwave duration and frequency in the northeast are related to the movement of the Walker circulation, while southeastern heatwave amplitude is associated with a north-south movement of the Tasman high pressure system. These results may lead to improvements in understanding the predictability and general preparedness for heatwaves in the summer season. [ABSTRACT FROM AUTHOR]

The skill of eight climate models in simulating the variability and trends in the observed areal extent of daily temperature and precipitation extremes is evaluated across five large-scale regions, using the climate extremes index (CEI) framework. Focusing on Europe, North America, Asia, Australia, and the Northern Hemisphere, results show that overall the models are generally able to simulate the decadal variability and trends of the observed temperature and precipitation components over the period 1951-2005. Climate models are able to reproduce observed increasing trends in the area experiencing warm maximum and minimum temperature extremes, as well as, to a lesser extent, increasing trends in the areas experiencing an extreme contribution of heavy precipitation to total annual precipitation for the Northern Hemisphere regions. Using simulations performed under different radiative forcing scenarios, the causes of simulated and observed trends are investigated. A clear anthropogenic signal is found in the trends in the maximum and minimum temperature components for all regions. In North America, a strong anthropogenically forced trend in the maximum temperature component is simulated despite no significant trend in the gridded observations, although a trend is detected in a reanalysis product. A distinct anthropogenic influence is also found for trends in the area affected by a much-above-average contribution of heavy precipitation to annual precipitation totals for Europe in a majority of models and to varying degrees in other Northern Hemisphere regions. However, observed trends in the area experiencing extreme total annual precipitation and extreme number of wet and dry days are not reproduced by climate models under any forcing scenario. [ABSTRACT FROM AUTHOR]

This study examines trends in the area affected by temperature and precipitation extremes across five large-scale regions using the climate extremes index (CEI) framework. Analyzing changes in temperature and precipitation extremes in terms of areal fraction provides information from a different perspective and can be useful for climate monitoring. Trends in five temperature and precipitation components are analyzed, calculated using a new method based on standard extreme indices. These indices, derived from daily meteorological station data, are obtained from two global land-based gridded extreme indices datasets. The four continental-scale regions of Europe, North America, Asia, and Australia are analyzed over the period from 1951 to 2010, where sufficient data coverage is available. These components are also computed for the entire Northern Hemisphere, providing the first CEI results at the hemispheric scale. Results show statistically significant increases in the percentage area experiencing much-above-average warm days and nights and much-below-average cool days and nights for all regions, with the exception of North America for maximum temperature extremes. Increases in the area affected by precipitation extremes are also found for the Northern Hemisphere regions, particularly Europe and North America. [ABSTRACT FROM AUTHOR]

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an empirical orthogonal teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. The authors illustrate that, as with mean rainfall, the El Niño-Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean dipole and southern annular mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter-than-average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with midlatitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anticyclone. Tropical cyclone activity is observed to have significant relationships with some warm-season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year. [ABSTRACT FROM AUTHOR]