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In this paper we introduce an objective definition for the onset and the retreat of the northern Australian rainy season that overlaps significantly with the Australian monsoon season. We define onset and retreat dates of the northern Australian rainy season as being the first and the last day of the year when the daily rain rate exceeds and falls below the climatological annual mean rain rate, respectively. However, our definition of onset/demise is not as restrictive as the traditional monsoon season that seeks the arrival of the westerlies and the equatorward retreat of the trough at its onset and demise, respectively. As defined in this paper, the length of the rainy season is longer than the monsoon season and includes the pre- and post-monsoon rainfall. It is noted that an early or later onset date of the northern Australian rainy season is associated with a longer or shorter, wetter or drier, and colder or warmer season, respectively. Similar relationship is also observed with demise date variations, which are, however, weaker than the onset date variations. Furthermore, we find that the relationship of the northern Australian seasonal rainfall variations with ENSO variability becomes stronger when we account for variations in the length of the rainy season compared to the fixed (December-- February) monsoon season length. We also find a significant linear trend over the time period of the analysis from 1901 to 2015 toward an increasing length of the northern Australian rainy season that influences the corresponding rising trend of seasonal rainfall anomalies. [ABSTRACT FROM AUTHOR]

The Global Energy and Water Cycle Exchanges (GEWEX) project was created more than 30 years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth's energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described. [ABSTRACT FROM AUTHOR]

The unique characteristics of land–air coupling and troposphere–stratosphere interaction over the Tibetan Plateau (TP), the highest landform in the world, play a vital role in weather and climate on regional and global scales. Although a great deal of research has been carried out, large gaps remain in our understanding of TP land–air coupling and its climate effects, due to a lack of observations and the issue of model biases. To address these obstacles, a 10-yr national research program entitled "Changes in the Land–Air Coupled System over the Tibetan Plateau and its Impacts on Global Climate (LASTPIC)" was launched by the National Natural Science Foundation of China in January 2014. What LASTPIC does revolves around three aspects: TP land–air coupled processes; TP's influence on global climate; and reanalysis and model. This paper mainly focuses on the data collection, scientific understanding, and model development of LASTPIC in terms of TP land–atmosphere–ocean coupling and its global climate impacts since program's inception. [ABSTRACT FROM AUTHOR]

The western North Pacific anomalous anticyclone (WNPAC) significantly affects East Asian climate. Previous studies have elucidated interannual variability of the WNPAC associated with El Niño, but decadal variability of the WNPAC remains unknown. The present paper investigates the dominant modes of decadal variability of the WNPAC by using observational data. The first decadal mode, characterized by an anomalous anticyclone centered over the western North Pacific, is associated with the Pacific decadal oscillation (PDO). The relationship between the first mode and the PDO shifted from in phase to out of phase around 1966. From 1900 to 1966 when the PDO and the first mode are in phase, the anticyclone is maintained by the effects of both the strengthened Aleutian low through meridional atmospheric forcing and Indian Ocean warming through enhanced zonal Walker circulation. From 1967 to 2012, the anticyclone is induced by cold SST anomalies over the central equatorial Pacific when the PDO and the first mode are out of phase. The second decadal mode is characterized by an anomalous anticyclone extending from southeastern China to the Philippine Sea and is associated with the Maritime Continent (MC). This anticyclone resides in the sinking branch of the local Hadley circulation, triggered by enhanced convection associated with the MC warming from 1900 to 2012. The finding of the decadal WNPAC in this paper may provide a new way to explain East Asian climate on a decadal time scale. [ABSTRACT FROM AUTHOR]

Under the new background of climate change, it is very important to identify the characteristics of drought in North China. Based on the daily meteorological drought comprehensive index from 494 national meteorological stations in North China during 1961–2019, the drought processes and their intensity are identified by applying the "extreme" intensity–duration (EID) theory. Then, the stage variation characteristics of the drought trend, the average drought intensity, and the drought frequency are analyzed. The results show that among the five drought intensity indices the process maximum intensity demonstrates the greatest correlation coefficient with the disaster rate of drought in North China. Therefore, the process maximum intensity of drought is selected as the annual drought intensity to analyze the drought characteristics in North China. According to the climate warming trends, the study period is divided into three stages, that is, 1951–84 (stage I), 1985–97 (stage II), and 1998–2019 (stage III). The comprehensive results show that the drought intensity in North China has significant stage characteristics. In stage I, the drought shows an increasing trend in most parts of North China, but its average intensity is relatively weaker, with a lower severe drought frequency. The drought also shows an increasing trend in most parts in stage II, with a more significant increase rate than that in stage I, and the average drought intensity is the strongest and the severe drought frequency is the highest. In stage III, the drought shows a decreasing trend in some areas, and the average intensity is the weakest, with a lower severe drought frequency. Significance Statement: In this paper, we develop a drought intensity formula, the maximum intensity of drought, based on the "extreme" intensity–duration theory. The maximum intensity of drought was then calculated and selected as an annual drought intensity to analyze the drought characteristics in North China. We found that the annual drought intensity better captured the extremity and the patterns of drought process than that obtained with single indices and comprehensive indices. The results show a decreasing trend of drought in North China after 1998. [ABSTRACT FROM AUTHOR]

This paper shows that joint temperature-precipitation information over a global domain provides a more accurate estimate of aerosol forced responses in climate models than does any other combination of temperature, precipitation, or sea level pressure. This fact is demonstrated using a new quantity called potential detectability, which measures the extent to which a forced response can be detected in a model. In particular, this measure can be evaluated independently of observations and therefore permits efficient exploration of a large number of variable combinations before performing optimal fingerprinting on observations. This paper also shows that the response to anthropogenic aerosol forcing can be separated from that of other forcings using only spatial structure alone, leaving the time variation of the response to be inferred from data, thereby demonstrating that temporal information is not necessary for detection. The spatial structure of the forced response is derived by maximizing the signal-to-noise ratio. For single variables, the north-south hemispheric gradient and equator-to-pole latitudinal gradient are important spatial structures for detecting anthropogenic aerosols in some models but not all. Sea level pressure is not an independent detection variable because it is derived partly from surface temperature. In no case does sea level pressure significantly enhance potential detectability beyond that already possible using surface temperature. Including seasonal or land-sea contrast information does not significantly enhance detectability of anthropogenic aerosol responses relative to annual means over global domains. [ABSTRACT FROM AUTHOR]

Identifying and separating the signal of urbanization effects in current temperature data series is essential for accurately detecting, attributing, and projecting mean and extreme temperature change on varied spatial scales. This paper proposes a new method based on machine learning to classify the observational stations into rural stations and urban stations. Based on the classification of rural and urban stations, the global and regional land annual mean and extreme temperature indices series over 1951–2018 for all stations and rural stations were calculated, and the urbanization effects and the urbanization contribution of global land annual mean and extreme temperature indices series are quantitatively evaluated using the difference series between all stations and the rural stations. The results showed that the global land annual mean time series for mean temperature and most extreme temperature indices experienced statistically significant urbanization effects. The urbanization effects in the mean and extreme temperature indices series generally occurred after the mid-1980s, and there were significant differences of the magnitudes of urbanization effects among different regions. The urbanization effect on the trends of annual mean and extreme temperature indices series in East Asia is generally the strongest, which is consistent with the rapidly urbanization process in the region over the past decades, but it is generally small in Europe during the recent decades. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Ensembles of climate model simulations are commonly used to separate externally forced climate change from internal variability. However, much of the information gained from running large ensembles is lost in traditional methods of data reduction such as linear trend analysis or large-scale spatial averaging. This paper demonstrates how a pattern recognition method (signal-to-noise-maximizing pattern filtering) extracts patterns of externally forced climate change from large ensembles and identifies the forced climate response with up to 10 times fewer ensemble members than simple ensemble averaging. It is particularly effective at filtering out spatially coherent modes of internal variability (e.g., El Niño, North Atlantic Oscillation), which would otherwise alias into estimates of regional responses to forcing. This method is used to identify forced climate responses within the 40-member Community Earth System Model (CESM) large ensemble, including an El Niño--like response to volcanic eruptions and forced trends in the North Atlantic Oscillation. The ensemble-based estimate of the forced response is used to test statistical methods for isolating the forced response from a single realization (i.e., individual ensemble members). Low-frequency pattern filtering is found to skillfully identify the forced response within individual ensemble members and is applied to the HadCRUT4 reconstruction of observed temperatures, whereby it identifies slow components of observed temperature changes that are consistent with the expected effects of anthropogenic greenhouse gas and aerosol forcing. [ABSTRACT FROM AUTHOR]

The variations of large-scale climatic controls and surface responses through the annual cycle during strong positive (El Niño) and negative (La Niña) phase ENSO events are analyzed to assess the within-year and among-year variations of climate anomalies. Data from the NCEP–NCAR reanalysis project are presented as small-multiple maps to illustrate the spatial and temporal variability in North American climate associated with extreme phases of ENSO. Temperature, mean sea level pressure, 500-mb geopotential heights, and 850-mb specific humidity have composite-anomaly patterns that exhibit the greatest degree of spatial and temporal coherence. In general, the composite-anomaly patterns for El Niño and La Niña events are of opposite sign, with stronger, more spatially coherent anomalies occurring during El Niño events than during La Niña events. However, the strength and coherency of the precipitation anomaly patterns are reduced in the interior intermountain west during both positive and negative phase of ENSO. The variations in precipitation anomalies are compared to the 500-mb omega and 850-mb specific humidity composite-anomaly patterns, which provide information on the controls of precipitation by large-scale vertical motions and moisture availability thus providing information on the specific mechanisms associated with precipitation variability during ENSO events. [ABSTRACT FROM AUTHOR]

Long and homogeneous series are a necessary requirement for reliable climate analysis. Relocation of measuring equipment from one station to another, such as from the city center to a rural area or a nearby airport, is one of the causes of discontinuities in these long series that may affect trend estimates. In this paper, an updated procedure for the composition of long series, by combining data from nearby stations, is introduced. It couples an evolution of the blending procedure already implemented within the European Climate Assessment and Dataset (ECA&D, which combines data from stations no more than 12.5 km apart from each other) with a duplicate removal, alongside the quantile matching homogenization procedure. The ECA&D contains approximately 3000 homogenized series for each temperature variable prior to the blending procedure, and approximately 820 of these are longer than 60 years; the process of blending increases the number of long series to more than 900. Three case studies illustrate the effects of the homogenization on single blended series, showing the effectiveness of separate adjustments on extreme and mean values (Geneva, Switzerland), on cases in which blending is complex (Rheinstetten, Germany), and on series that are completed by adding relevant portions of Global Telecommunications System synoptic data (Siauliai, Lithuania). A trend assessment on the whole European continent reveals the removal of negative and very large trends, demonstrating a stronger spatial consistency. The new blended and homogenized dataset will allow a more reliable use of temperature series for indices calculation and for the calculation of gridded datasets and it will be available online for users (https://www.ecad.eu). [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

This paper explores the effects from averaging weather station data onto a grid on the first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over the entire globe. The Global Historical Climatology Network-Daily (GHCND) and the Met Office Hadley Centre GHCND (HadGHCND) datasets from 1950 to 2010 are examined. The GHCND station data exhibit large spatial patterns for each moment and statistically significant moment trends from 1950 to 2010, indicating that SAT probability density functions are non-Gaussian and have undergone characteristic changes in shape due to decadal variability and/or climate change. Comparisons with station data show that gridded averages always underestimate observed variability, particularly in the extremes, and have altered moment trends that are in some cases opposite in sign over large geographic areas. A statistical closure approach based on the quasi-normal approximation is taken to explore SAT's higher-order moments and point correlation structure. This study focuses specifically on relating variability calculated from station data to that from gridded data through the moment equations for weighted sums of random variables. The higher-order and nonlinear spatial correlations up to the fourth order demonstrate that higher-order moments at grid scale can be determined approximately by functions of station pair correlations that tend to follow the usual Kolmogorov scaling relation. These results can aid in the development of constraints to reduce uncertainties in climate models and have implications for studies of atmospheric variability, extremes, and climate change using gridded observations. [ABSTRACT FROM AUTHOR]

This paper scrutinizes the zonal oscillation of the western North Pacific subtropical high (WNPSH) via diagnosing its two extreme phases, which are defined by the top 10% strongest (positive phase) and the weakest (negative phase) WNPSH index (WNPSHI) days during summers in 1979–2016. Key findings include the following: a tripole pattern consisting of intensified (weakened) precipitation over the Maritime Continent and the East Asian summer monsoon regions, and suppressed (strengthened) precipitation over the western North Pacific summer monsoon region during positive (negative) WNPSH phases; a westward movement of WNPSH-induced precipitation anomalies that subsequently affects eastern China, Japan, and the Korean Peninsula at different time lags; an OLR–vorticity pattern explained by atmospheric responses to thermal sources is suggested to drive the oscillation; and the competitive interaction of local air–sea feedbacks, especially during the positive phase. In addition, moderate-to-strong positive correlations between the WNPSHI and the Niño-3.4 index are found on 1–2-, 2–3-, and 3–6-yr time scales; both exhibit decadal shifts to a higher-frequency mode, suggesting the intensification of both the zonal WNPSH oscillation and the ENSO under the changing climate and their close interdecadal association. A nonlinear quasi-biennial WNPSH–ENSO relationship is identified: the positive (negative) WNPSH phase sometimes occurs during 1) a decaying El Niño (La Niña) in the preceding summer/autumn, and/or 2) a developing La Niña (El Niño) in the current summer/autumn. A full ENSO transition from moderate-to-strong El Niño to La Niña is often seen during the positive phase, offering potential in predicting ENSO events and extreme WNPSH phases and thereby the summer monsoon rainfall in East Asia. [ABSTRACT FROM AUTHOR]

Extreme precipitation can have significant adverse impacts on infrastructure and property, human health, and local economies. This paper examines recent changes in extreme precipitation in the northeast United States. Daily station data from 58 stations missing less than 5% of days for the years 1979–2014 from the U.S. Historical Climatology Network were used to analyze extreme precipitation, defined as the top 1% of days with precipitation. A statistically significant (95% confidence level) increasing trend of the threshold for the top 1% of extreme precipitation events was found (0.3 mm yr−1). This increasing trend was due to both an increase in the frequency of extreme events and the magnitude of extreme events. Rainfall events ≥ 150 mm (24-h accumulation) increased in frequency from 6 events between 1979 and 1996 to 25 events between 1997 and 2014, a 317% increase. The annual daily maximum precipitation, or the highest recorded precipitation amount in a given year, increased by an average of 1.6 mm yr−1, a total increase of 58.0 mm. Decreasing trends in extreme precipitation were observed east of Lake Erie during the warm season. Increasing trends in extreme precipitation were most robust during the fall months of September, October, and November, and particularly at locations further inland. The analysis showed that increases in events that were tropical in nature, or associated with tropical moisture, led to the observed increase in extreme precipitation during the fall months. [ABSTRACT FROM AUTHOR]

A recent paper suggested that the global climate models used to project future climate changes may significantly overestimate the stability of the Atlantic meridional overturning circulation under anthropogenic global warming. It further asserted that "flux adjusting" the models (adding offsets to heat and freshwater fluxes to reproduce the observed density field) may reduce model stability. However, temperature, salinity, and density fields in climate models likely deviate from observations because of biases in model physics as well as inaccuracies in fluxes. In such cases it is unclear whether adjusting the fluxes to produce a more realistic density field will result in a model with more realistic stability properties, as flux correction may be compensating for other inaccuracies in model formulation. We investigate this question using a simplified dynamical box model, in which we can flux correct one version of the model to match density gradients within another version of the model. We show that flux adjustment can realistically compensate for biases in stability associated with some processes, such as uncertainty in the value of the vertical diffusivity, but not other processes, such as inaccurate simulation of the relationship between density structure and overturning or the isopycnal tracer diffusivity coefficient. An ability to compensate for biases when the overturning shuts off does not imply an ability to compensate for biases in when it reestablishes itself, and vice versa. [ABSTRACT FROM AUTHOR]

The uncertainty arising from internal climate variability in climate change projections of the Hadley circulation (HC) is presently unknown. In this paper it is quantified by analyzing a 40-member ensemble of integrations of the Community Climate System Model, version 3 (CCSM3), under the Special Report on Emissions Scenarios (SRES) A1B scenario over the period 2000-60. An additional set of 100-yr-long time-slice integrations with the atmospheric component of the same model [Community Atmosphere Model, version 3.0 (CAM3)] is also analyzed. Focusing on simple metrics of the HC-its strength, width, and height-three key results emerge from the analysis of the CCSM3 ensemble. First, the projected weakening of the HC is almost entirely confined to the Northern Hemisphere, and is stronger in winter than in summer. Second, the projected widening of the HC occurs only in the winter season but in both hemispheres. Third, the projected rise of the tropical tropopause occurs in both hemispheres and in all seasons and is, by far, the most robust of the three metrics. This paper shows further that uncertainty in future trends of the HC width is largely controlled by extratropical variability, while those of HC strength and height are associated primarily with tropical dynamics. Comparison of the CCSM3 and CAM3 integrations reveals that ocean-atmosphere coupling is the dominant source of uncertainty in future trends of HC strength and height and of the tropical mean meridional circulation in general. Finally, uncertainty in future trends of the hydrological cycle is largely captured by the uncertainty in future trends of the mean meridional circulation. [ABSTRACT FROM AUTHOR]

This paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multimodel ensemble. The method regresses each model's estimate of internal variability from the preindustrial control simulation on the variability derived from a model's ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multimodel consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics, and polar regions, and extremely likely decreases in midlatitudes. Applying the method to sea ice volume and area shows that their respective internal variability likely or extremely likely decreases proportionally to their mean state, except for Arctic sea ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice, the method confirms that internal variability can explain most of the models' deviation from observed trends but often not the models' deviation from the observed mean states. The new method benefits from a large number of models and long preindustrial control simulations, but it requires only a small number of ensemble simulations. The method allows for consistent consideration of internal variability in multimodel studies and thus fosters understanding of the role of internal variability in a changing climate. [ABSTRACT FROM AUTHOR]

Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state's agriculture is located) experience the most significant (P < 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year. Significance Statement: Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures. [ABSTRACT FROM AUTHOR]

Zonal and meridional surface temperature gradients are considered to be determinants of large-scale atmospheric circulation patterns. However, there has been limited investigation of these gradients as diagnostic aids. Here, the twentieth-century variability in the Northern Hemisphere equator-to-pole temperature gradient (EPG) and the ocean-land temperature contrast (OLC) is explored. A secular trend in decreasing EPG and OLC is noted. Decadal and interannual (ENSO-related) variations in the joint distribution of EPG and OLC are identified, hinting at multistable climate states that may be indigenous to the climate or due to changing boundary forcings. The NH circulation patterns for cases in the tails of the joint distribution of EPG and OLC are also seen to be different. Given this context, this paper extends past efforts to develop insights into jet stream dynamics using the Lorenz-1984 model, which is forced directly and only by EPG and OLC. The joint probability distribution of jet stream and eddy energy, conditional on EPG and OLC scenarios, is investigated. The scenarios correspond to (i) warmer versus colder climate conditions and (ii) polarized ENSO phases. The latter scenario involves the use of a heuristic ENSO model to drive the Lorenz-1984 model via a modulation of the EPG or the OLC. As with GCMs, the low-order model reveals that the response to El Niño forcing is not similar to an anthropogenic warming signature. The potential uses of EPG and OLC as macro-level indicators of climate change and variability and for comparing results across GCMs and observations are indicated. [ABSTRACT FROM AUTHOR]

A full understanding of the causes of the severe drought seen in the Sahel in the latter part of the twentieth-century remains elusive some 25 yr after the height of the event. Previous studies have suggested that this drying trend may be explained by either decadal modes of natural variability or by human-driven emissions (primarily aerosols), but these studies lacked a sufficiently large number of models to attribute one cause over the other. In this paper, signatures of both aerosol and greenhouse gas changes on Sahel rainfall are illustrated. These idealized responses are used to interpret the results of historical Sahel rainfall changes from two very large ensembles of fully coupled climate models, which both sample uncertainties arising from internal variability and model formulation. The sizes of these ensembles enable the relative role of human-driven changes and natural variability on historic Sahel rainfall to be assessed. The paper demonstrates that historic aerosol changes are likely to explain most of the underlying 1940-80 drying signal and a notable proportion of the more pronounced 1950-80 drying. [ABSTRACT FROM AUTHOR]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

Reconstructions of historical climate changes indicate that surface air temperatures decreased over the preindustrial last millennium. Conflicting explanations have been proposed for the cause of the transition from the Medieval Climate Anomaly (MCA) in the early part of the last millennium to the Little Ice Age (LIA) near its end. The possible causes include volcanic emissions, total solar irradiance (TSI) variations, greenhouse gas concentration fluctuations, and orbital forcing variations. In the present paper, it is demonstrated that all of these climate forcings contribute significantly to simulated surface air temperature (SAT) and sea ice concentration changes over this period. On the other hand, simulated ocean heat content appears to respond significantly only to volcanic and TSI variations. In model simulations at T85 spectral resolution, TSI reductions and volcanic emissions together generate significant increases in sea ice extent in the Barents Sea, which is found to be responsible for most of the temperature reductions over northwestern Europe. TSI appears less important to Arctic sea ice and SAT changes in simulations at T42 spectral resolution, which are weaker than at T85 resolution. Such resolution dependence is attributed to differences in background conditions in the responses to these external climate forcings. Nonlinearities in the forcing responses and sensitivities to background conditions challenge the assumption that sensitivity tests for given forcings can be run independently. Additionally, it is demonstrated that an ensemble of model simulations is required to isolate forcing responses even over a period as long as the last millennium. [ABSTRACT FROM AUTHOR]

Large-scale synoptic circulations have a profound effect on western U.S. summer weather and climate. Heat waves, water availability, the distribution of monsoonal moisture, fire-weather conditions, and other phenomena are impacted by the position and amplitude of large-scale synoptic circulations. Furthermore, regional weather is modulated by the interactions of the large-scale flow with terrain and land-water contrasts. It is therefore crucial to understand projected changes in large-scale circulations and their variability under anthropogenic global warming. Although recent research has examined changes in the jet stream, storm tracks, and synoptic disturbances over the Northern Hemisphere under global warming, most papers have focused on the cold season. In contrast, this work analyzes the projected trends in the spatial distribution and amplitude of large-scale synoptic disturbances over the western United States and eastern Pacific during July and August. It is shown that CMIP5 models project weaker mean midtropospheric gradients in geopotential height as well as attenuated temporal variability in geopotential height, temperature, vorticity, vertical motion, and sea level pressure over this region. Most models suggest reduced frequency of troughs and increased frequency of ridges over the western United States. These changes in the variability of synoptic disturbances have substantial implications for future regional weather and climate. [ABSTRACT FROM AUTHOR]

This paper addresses the effect of interannual variability in jet stream orientation on weather systems over the North Atlantic basin (NAB). The observational analysis relies on 65 yr of NCEP-NCAR reanalysis (1948-2012). The total daily kinetic energy of the geostrophic wind (GTKE) is taken as a measure of storm activity over the North Atlantic. The NAB is partitioned into four rectangular regions, and the winter average of GTKE is calculated for each quadrant. The spatial GTKE average over all four quadrants shows striking year-to-year variability and is strongly correlated with the North Atlantic Oscillation (NAO). The GTKE strength in the northeast quadrant is closely related to the diffluence angle of the jet stream in the northwest quadrant. To gain insight into the relationship between the diffluence angle and its downstream impact, a quasigeostrophic baroclinic model is used. The results show that an initially zonal jet persists at its initial latitude over 30 days or longer, while a tilted jet propagates meridionally according to the Rossby wave group velocity, unless kept stationary by external forcing. A Gulf Stream-like narrow sea surface temperature (SST) front provides the requisite forcing for an analytical steady-state solution to this problem. This SST front influences the atmospheric jet in the northwest quadrant: it both strengthens the jet and tilts it northward at higher levels, while its effect is opposite at lower levels. Reanalysis data confirm these effects, which are consistent with thermal wind balance. The results suggest that the interannual variability found in the GTKE may be caused by intrinsic variability of the thermal Gulf Stream front. [ABSTRACT FROM AUTHOR]

Changes in internal variability of seasonal and annual mean 2-m temperature in response to anthropogenic forcing are quantified for a global domain using climate models driven by a twenty-first-century high-emissions scenario. While changes in variance have been quantified previously in a univariate sense, the field significance of such changes has remained unclear. This paper proposes a new field significance test for changes in variance that accounts for spatial and temporal relationships within the domain. The test proposed here uses an optimization technique based on discriminant analysis, yielding results that are invariant to linear transformations of the data and therefore independent of normalization procedures. Multiple significance tests are employed because spatial fields can differ in many ways in a multivariate space. All climate models investigated here predict significant changes in internal variability of temperature in response to anthropogenic forcing. The models consistently predict decreases to temperature variance in regions of seasonal sea ice formation and across the Southern Ocean by the end of the twenty-first century. While more than half the models also predict significant changes in variance over ENSO regions and the North Atlantic Ocean, the direction of this change is model dependent. Seasonal mean changes are remarkably similar to annual mean changes, but there are model-dependent exceptions. Some models predict future variability that is more than double their preindustrial control variability, raising questions about the adequacy of doubling uncertainty estimates to test robustness in detection and attribution studies. [ABSTRACT FROM AUTHOR]

Few if any high-resolution (annually resolved) paleoclimate records are available for the Hawaiian Islands prior to ~1850 CE, after which some instrumental records start to become available. This paper shows how atmospheric teleconnection patterns between North America and the northeastern North Pacific (NNP) allow for reconstruction of Hawaiian Islands rainfall using remote proxy information from North America. Based on a newly available precipitation dataset for the state of Hawaii and observed and reconstructed December-February (DJF) sea level pressures (SLPs) in the North Pacific Ocean, the authors make use of a strong relationship between winter SLP variability in the northeast Pacific and corresponding DJF Hawaii rainfall variations to reconstruct and evaluate that season's rainfall over the period 1500-2012 CE. A general drying trend, though with substantial decadal and longer-term variability, is evident, particularly during the last ~160 years. Hawaiian Islands rainfall exhibits strong modulation by El Niño-Southern Oscillation (ENSO), as well as in relation to Pacific decadal oscillation (PDO)-like variability. For significant periods of time, the reconstructed large-scale changes in the North Pacific SLP field described here and by construction the long-term decline in Hawaiian winter rainfall are broadly consistent with long-term changes in tropical Pacific sea surface temperature (SST) based on ENSO reconstructions documented in several other studies, particularly over the last two centuries. Also noted are some rather large multidecadal fluctuations in rainfall (and hence in NNP SLP) in the eighteenth century of undetermined provenance. [ABSTRACT FROM AUTHOR]

Because they are rare, extreme weather events have critical impacts on societies and ecosystems and attract public and scientific attention. The most unusual events are regularly documented as part of routine climate monitoring by meteorological services. A growing number of attribution studies also aim at quantifying how their probability has evolved under human-induced climate change. However, it is often recognized that (i) the selection of studied events is geographically uneven, and (ii) the definition of a given event, in particular, its spatiotemporal scale, is subjective, which may impact attribution statements. Here we present an original method that objectively selects, defines, and compares extreme events that have occurred worldwide in the recent years. Building on previous work, the event definition consists of automatically selecting the spatiotemporal scale that maximizes the event rarity, accounting for the nonstationary context of climate change. We then explore all years, seasons, and regions and search for the most extreme events. We demonstrate how our searching procedure can be both useful for climate monitoring over a given territory, and resolve the geographical selection bias of attribution studies. Ultimately, we provide a selection of the most exceptional hot and cold events in the recent past, among which are iconic heatwaves such as those seen in 2021 in Canada and in 2003 in Europe. [ABSTRACT FROM AUTHOR]

This paper studies operators inspired by the fluctuation-dissipation theorem that consider the seasonality (nonstationarity) of the climate system under conditions of limited sample size relevant to application of the method to observational records. The approach is used to predict the steady-state response of an atmospheric general circulation model to localized temperature perturbations. A seasonal operator nominally requires a much larger data sample than a stationary operator; the authors study some strategies to overcome this. First, two methods for approximating the seasonality of the system are examined. Second, an alternative 'transpose approach' to the standard dimension reduction is considered that is more efficient and accurate for small sample sizes and additionally enables the use of a kernel, which provides a convenient way to incorporate prior physical understanding into the operator. All operators show considerable skill in predicting seasonal responses for a variety of variables (temperature, winds, rainfall, and cloud cover) and better skill in predicting the annual-mean ones. A comparison of these predictions to ones done on the same system with temporally fixed boundary conditions shows unexpectedly that skill is, if anything, improved by the presence of a seasonal cycle. The authors suggest that the extra complexity due to a seasonal system is outweighed by the added information due to the seasonal forcing and the effect of seasonality in smoothing out prediction errors. [ABSTRACT FROM AUTHOR]

Measurements of air temperature and precipitation at 35 stations in Hubei Province, China, during 1962-2011 are used to investigate the regional climate change. There is an increasing trend for observed air temperature (0.23°C decade−1), which is slightly higher than that from multiple model simulations/predictions [phase 5 of CMIP (CMIP5) datasets] (0.16°C decade−1). The observed precipitation increases at the rate of 11.4 mm decade−1, while the CMIP5 results indicate a much lower decreasing trend (0.8 mm decade−1) in this region. To examine the ecological responses to the climate changes in Hubei Province, annual gross primary productivity (GPP) and net primary productivity (NPP) products during 2000-10 and leaf area index (LAI) products during 1981-2011 are also analyzed. It is discovered that GPP, NPP, and LAI increase at the rate of 1.8 TgC yr−1 yr−1, 1.1 TgC yr−1 yr−1, and 0.14 m2 m−2 decade−1, respectively. A linear model is further used to conduct the correlation analyses between climatic parameters (i.e., air temperature and precipitation) and ecological indicators (i.e., GPP, NPP, and LAI). The results indicate that the air temperature has a significant positive correlation with LAI ( R2 = 0.311) and GPP ( R2 = 0.189); precipitation is positively correlated with NPP ( R2 = 0.209). Thus, it is concluded that the air temperature exerts a stronger effect on the ecosystem than precipitation in Hubei Province over the past decades. [ABSTRACT FROM AUTHOR]

This paper examines the physical processes controlling how synoptic midlatitude temperature variability near the surface changes with climate. Because synoptic temperature variability is primarily generated by advection, it can be related to mean potential temperature gradients and mixing lengths near the surface. Scaling arguments show that the reduction of meridional potential temperature gradients that accompanies polar amplification of global warming leads to a reduction of the synoptic temperature variance near the surface. This is confirmed in simulations of a wide range of climates with an idealized GCM. In comprehensive climate simulations (CMIP5), Arctic amplification of global warming similarly entails a large-scale reduction of the near-surface temperature variance in Northern Hemisphere midlatitudes, especially in winter. The probability density functions of synoptic near-surface temperature variations in midlatitudes are statistically indistinguishable from Gaussian, both in reanalysis data and in a range of climates simulated with idealized and comprehensive GCMs. This indicates that changes in mean values and variances suffice to account for changes even in extreme synoptic temperature variations. Taken together, the results indicate that Arctic amplification of global warming leads to even less frequent cold outbreaks in Northern Hemisphere winter than a shift toward a warmer mean climate implies by itself. [ABSTRACT FROM AUTHOR]

One of the potential impacts of global warming is likely to be experienced through changes in flood frequency and magnitude, which poses a potential threat to the downstream reservoir flood control system. In this paper, the downscaling results of the multimodel dataset from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) were coupled with the Variable Infiltration Capacity (VIC) model to evaluate the impact of climate change on the Feilaixia reservoir flood control in the Beijiang River basin for the first time. Four emissions scenarios [A1B and representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5] were chosen. Results indicate that annual distribution and interannual variability of temperature and precipitation are well simulated by the downscaling results of the CMIP3 and CMIP5 multimodel dataset. The VIC model, which performs reasonably well in simulating runoff processes with high model efficiency and low relative error, is suitable for the study area. Overall, annual maximum 1-day precipitation in 2020-50 would increase under all the scenarios (relative to the baseline period 1970-2000). However, the spatial distribution patterns of changes in projected extreme precipitation are uneven under different scenarios. Extreme precipitation is most closely associated with extreme floods in the study area. There is a gradual increase in extreme floods in 2020-50 under any of the different emission scenarios. The increases in 500-yr return period daily discharge of the Feilaixia reservoir have been found to be from 4.35% to 9.18% in 2020-50. The reservoir would be likely to undergo more flooding in 2020-50. [ABSTRACT FROM AUTHOR]

Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China. [ABSTRACT FROM AUTHOR]

The change in predictability of monthly mean temperature in a future climate is quantified based on the Community Climate System Model, version 4. According to this model, the North Atlantic overtakes the El Niño-Southern Oscillation (ENSO) as the dominant area of seasonal predictability by 2095. This change arises partly because ENSO becomes less variable and partly because the ENSO teleconnection pattern expands into the Atlantic. Over land, the largest change in temperature predictability occurs in the tropics and is predominantly due to a decrease in ENSO variability. The southern peninsula of Africa and northeast South America are predicted to experience significant drying in a future climate, which decreases the effective heat capacity and memory, and hence increases variance independently of ENSO changes. Extratropical land areas experience enhanced precipitation in a future climate, which decreases temperature variance by the same mechanism. Finally, the model predicts that surface temperatures near the poles will become more predictable and less variable in a future climate, primarily because melting sea ice exposes the underlying sea surface temperature, which is more predictable owing to its longer time scale. Some of these results, especially the change in ENSO variance, are known to be model dependent. This paper also advances the use of information theory to quantify predictability, including 1) deriving a quantitative relation between predictability of the first and second kinds; 2) showing how differences in predictability can be decomposed in two dramatically different ways, facilitating physical interpretation; and 3) proposing a sample estimate of mutual information whose significance can be tested using standard techniques. [ABSTRACT FROM AUTHOR]

The impacts of absorbing aerosols on global climate are not completely understood. This paper presents the results of idealized experiments conducted with the Community Atmosphere Model, version 4 (CAM4), coupled to a slab ocean model (CAM4-SOM) to simulate the climate response to increases in tropospheric black carbon aerosols (BC) by direct and semidirect effects. CAM4-SOM was forced with 0, 1×, 2×, 5×, and 10× an estimate of the present day concentration of BC while maintaining the estimated present day global spatial and vertical distribution. The top-of-atmosphere (TOA) radiative forcing of BC in these experiments is positive (warming) and increases linearly as the BC burden increases. The total semidirect effect for the 1 × BC experiment is positive but becomes increasingly negative for higher BC concentrations. The global-average surface temperature response is found to be a linear function of the TOA radiative forcing. The climate sensitivity to BC from these experiments is estimated to be 0.42 K W−1 m2 when the semidirect effects are accounted for and 0.22 K W−1 m2 with only the direct effects considered. Global-average precipitation decreases linearly as BC increases, with a precipitation sensitivity to atmospheric absorption of 0.4% W−1 m2. The hemispheric asymmetry of BC also causes an increase in southward cross-equatorial heat transport and a resulting northward shift of the intertropical convergence zone in the simulations at a rate of 4° PW−1. Global-average mid- and high-level clouds decrease, whereas the low-level clouds increase linearly with BC. The increase in marine stratocumulus cloud fraction over the southern tropical Atlantic is caused by increased BC-induced diabatic heating of the free troposphere. [ABSTRACT FROM AUTHOR]

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data-model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño-Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data-model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches. [ABSTRACT FROM AUTHOR]

As an additional classification to Köppen's climate classification for polar (E) climates, the Polar Marine (EM) climate was presented nearly five decades ago and is revisited in this paper. The EM climate was traced to the North Atlantic, North Pacific, and Southern Ocean and recognized as wet, cloudy, and windy, especially during winter. These areas by definition are encompassed by monthly mean air temperatures of −6.7°C (20°F) and 10°C (50°F) in the coldest and warmest months of the annual cycle, respectively. Here three global reanalyses [ECMWF Interim Re-Analysis (ERA-Interim), Climate Forecast System Reanalysis (CFSR), and Japan Meteorological Agency (JMA) 25-yr reanalysis (JRA-25)] are used to produce a modern depiction of EM climate. General agreement is found between original and new EM boundaries, for which the poleward boundary can be approximated by the winter sea ice maximum and the equatorward boundary by the warmest month SSTs. Variability of these parameters is shown to largely dictate the EM area. A downward trend in global EM areal extent for 1979-2010 (−42.4 × 109 m2 yr−1) is dominated by the negative Northern Hemisphere (NH) EM trend (−45.7 × 109 m2 yr−1), whereas the Southern Hemisphere (SH) EM areal trend is insignificant. This observed reduction in NH EM areal extent of roughly 20% over the past three decades, largely from losses at the equatorward boundaries of these biologically rich EM zones, may not be fully compensated by poleward shifts in the EM environment due to projected warming and sea ice decline in the twenty-first century. [ABSTRACT FROM AUTHOR]

Recently Diem questioned the western ridge movement of the North Atlantic subtropical high (NASH) reported in a 2011 paper of Li et al. This reply shows more analysis that further strengthens the conclusions originally put forth by Li et al. Diem''s analysis of the trend in the western ridge of the NASH was based on the data over a 30-yr period (1978-2007), whereas the main conclusions in Li et al. were drawn according to the data over a 60-yr period (1948-2007). Over the last 60 years, the NASH has shown a significant trend of westward movement, the meridional movement of the western ridge of the NASH has enhanced in the recent three decades, and the potential impact of global warming cannot be ruled out in an attempt to explain these changes of the NASH. [ABSTRACT FROM AUTHOR]

Recent heightened concern regarding possible consequences of anthropogenically induced global warming has spurred analyses of data aimed at detection of climate change and more thorough characterization of the natural climate variability. However, there is greater concern regarding the extent and especially quality of the historical climate data. In this paper, rainfall records of 233 gauge stations over Ethiopia for the 1978-2007 period are employed in an analysis that involves homogenization, reconstruction, and gridding onto a regular 0.5° × 0.5° resolution grid. Inhomogeneity is detected and adjusted based on quantile matching. The regularized expectation-maximization and multichannel singular spectrum analysis algorithms are then utilized for imputation of missing values, and the latter has been determined to have a marginal advantage. Ordinary kriging is used to create a gridded monthly rainfall dataset. The spatial and temporal coherence of this dataset are assessed using harmonic analysis, self-organizing maps, and intercomparison with global datasets. The self-organizing map delineates Ethiopia into nine homogeneous rainfall regimes, which is consistent with seasonal and interannual rainfall variations. The harmonic analysis of the dataset reveals that the annual mode accounts for 55%-85% of the seasonal rainfall variability over western Ethiopia while the semiannual mode accounts for up to 40% over southern Ethiopia. The dataset is also intercompared with Global Precipitation Climatology Project (GPCP), Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), Climatic Research Unit time series version 3 (CRUTS3.0), Tropical Rainfall Measuring Mission (TRMM), and interim ECMWF Re-Analysis (ERA-Interim) rainfall. The correlation of the dataset with global datasets ranges from 0.52 to 0.95 over sparse to dense rain gauge regions. The GPCP rainfall has a small bias and good correlation with the new dataset whereas TRMM and ERA-Interim have relatively large dry and wet biases, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of different ocean initialization strategies on the forecast skill of decadal prediction experiments performed with the ECHAM5/Max Planck Institute Ocean Model (MPI-OM) coupled model. The ocean initializations assimilate three-dimensional temperature and salinity anomalies from two different ocean state estimates, the ocean reanalysis of the German contribution to Estimating the Circulation and Climate of the Ocean (GECCO) and an ensemble of MPI-OM ocean experiments forced with the NCEP-NCAR atmospheric reanalysis. The results show that North Atlantic and Mediterranean sea surface temperature (SST) variations can be skillfully predicted up to a decade ahead and with greater skill than by both uninitialized simulations and persistence forecasts. The regional distribution of SST predictive skill is similar in both initialization approaches; however, higher skill is found for the NCEP hindcasts than for the GECCO hindcasts when a combination of predictive skill measures is used. Skillful predictions of surface air temperature are obtained over northwestern Europe, northern Africa, and central-eastern Asia. The North Atlantic subpolar gyre region stands out as the region with the highest predictive skill beyond the warming trend, in both SST and upper-ocean heat-content predictions. Here the NCEP hindcasts deliver the best results due to a more accurate initialization of the observed variability. The dominant mechanism for North Atlantic climate predictability is of dynamical origin and can be attributed to the initialization of the Atlantic meridional overturning circulation, thus explaining the reoccurrence of high predictive skill within the second pentad of the hindcasts experiments. The results herein demonstrate that ocean experiments forced with the observed history of the atmospheric state constitute a simple but successful alternative strategy for the initialization of skillful climate predictions over the next decade. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal method for estimating time-dependent climate change signals from general circulation models. The basic idea is to identify vectors that maximize the mean-square detection statistic derived from optimal fingerprinting techniques. The method also provides an objective and systematic procedure for identifying the limit to which a signal can be restricted in space and time without losing detectability. As an illustration, the method is applied to the Coupled Model Intercomparison Project, phase 3 multimodel dataset to determine the continental seasonal-mean anomaly in surface air temperature and precipitation that is most detectable, on average, in these models. Anomalies in seasonal-mean surface air temperature are detectable in all seasons by almost all models on all continents but Europe; seasonal-mean anomalies over Europe are undetectable for some models, though this does not preclude other expressions of the signal, such as those that include longer time averages or time-lag information, from being detectable. Detectability in seasonal-mean temperature is found not only for multidecadal warming trends but also for cooling after major volcanic eruptions. In contrast, seasonal-mean precipitation anomalies are detectable in only a few models for averages over 5 yr or more, suggesting that the signal should include more spatiotemporal detail to be detectable across more models. Nevertheless, of the precipitation anomalies that are detectable, the signal appears to be of two characters: a systematic trend and enhanced frequency of extreme values. These results derived from twentieth-century simulations appear to be consistent with previous studies based on twenty-first-century simulations with larger signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

Previous studies have indicated a widespread decline in snowpack over Utah accompanied by a decline in the snow-precipitation ratio while anecdotal evidence claims have been put forward that measured changes in Utah's snowpack are spurious and do not reflect actual change. Using two distinct lines of investigation, this paper further analyzes the winter precipitation regime in the state of Utah. First, by means of observation-based, gridded daily temperature, precipitation, and remotely sensed data, as well as utilizing a climatological rain-snow threshold (RST) temperature method, the precipitation regime of Utah was scrutinized. Second, a comprehensive synoptic analysis was conducted as an alternate means that is independent from surface observations. It was found that the proportion of winter (January-March) precipitation falling as snow has decreased by 9% during the last half century, a combined result from a significant increase in rainfall and a minor decrease in snowfall. Meanwhile, observed snow depth across Utah has decreased and is accompanied by consistent decreases in snow cover and surface albedo. Weather systems with the potential to produce precipitation in Utah have decreased in number with those producing snowfall decreasing at a considerably greater rate. Further circulation analysis showed that an anomalous anticyclone has developed over western North America, which acts to reduce the frequency of cyclone waves impacting Utah. Combined with the increased precipitation, this feature suggests that the average precipitation per event has intensified with more of it falling as rain than as snow. Trends in the hydroclimate such as these have implications for present and future regional water policy in the state of Utah. [ABSTRACT FROM AUTHOR]

A reanalysis of the Atlantic basin tropical storm and hurricane database ('best track') for the period from 1921 to 1930 has been completed. This reassessment of the main archive for tropical cyclones of the North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico was necessary to correct systematic biases and random errors in the data as well as to search for previously unrecognized systems. The methodology for the reanalysis process for revising the track and intensity of tropical cyclone data has been detailed in a previous paper on the reanalysis. The 1921-30 dataset now includes several new tropical cyclones, excludes one system previously considered a tropical storm, makes generally large alterations in the intensity estimates of most tropical cyclones (both toward stronger and weaker intensities), and typically adjusts existing tracks with minor corrections. Average uncertainty in intensity and track values is estimated for both open-ocean conditions as well as landfalling systems. Highlights are given for changes to the more significant hurricanes to impact the United States, Central America, and the Caribbean for this decade. [ABSTRACT FROM AUTHOR]

Variations of land surface parameters over the Tibetan Plateau have great importance on local energy and water cycles, the Asian monsoon, and climate change studies. In this paper, the NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset is used to retrieve the land surface temperature (LST), the normalized difference vegetation index (NDVI), and albedo, from 1982 to 2000. Simultaneously, meteorological parameters and land surface heat fluxes are acquired from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset and the Global Land Data Assimilation System (GLDAS), respectively. Results show that from 1982 to 2000 both the LST and the surface air temperature increased on the Tibetan Plateau (TP). The rate of increase of the LST was 0.26±0.16 K decade−1 and that of the surface air temperature was 0.29 ± 0.16 K decade−1, which exceeded the increase in the Northern Hemisphere (0.054 K decade−1). The plateau-wide annual mean precipitation increased at 2.54 mm decade−1, which indicates that the TP is becoming wetter. The 10-m wind speed decreased at about 0.05±0.03 m s−1 decade−1 from 1982 to 2000, which manifests a steady decline of the Asian monsoon wind. Due to the diminishing ground-air temperature gradient and subdued surface wind speed, the sensible heat flux showed a decline of 3.37 ± 2.19 W m−2 decade−1. The seasonal cycle of land surface parameters could clearly be linked to the patterns of the Asian monsoon. The spatial patterns of sensible heat flux, latent heat flux, and their variance could also be recognized. [ABSTRACT FROM AUTHOR]

This paper examines characteristic changes in North Pacific sea surface temperature (SST) variability during the boreal winter (December--February) for two subperiods (1956--88 and 1977--2009) during which the 1976/77 and the 1988/89 climate transitions occurred. It is found that the Pacific decadal oscillation (PDO)-like SST variability plays a dominant role in the 1976/77 climate transition, while both the North Pacific Gyre Oscillation (NPGO)-like and PDO-like SST variability contribute to the 1988/89 climate transition. Furthermore, the leading mode changes from PDO-like SST variability during the period 1956--88 to NPGO-like SST variability during the period 1977--2009, indicative of an enhancement of NPGO-like SST variability since 1988. Changes in sea level pressure across the 1976/77 climate transition project strongly onto the Aleutian low pressure system. But sea level pressure changes across the 1988/89 climate transition project primarily onto the North Pacific Oscillation, which is associated with remote changes in the Arctic Oscillation over the polar region as well. This contributes to enhancing the NPGO-like SST variability after 1988. The authors also analyze the output from an ensemble of Tropical Ocean and Global Atmosphere (TOGA) experiments in which the observed SSTs are inserted only at grid points in the tropics between 20°°S and 20°°N. The results indicate that the changes in the North Pacific atmosphere in the 1976/77 climate transition are mostly due to the tropics, whereas those in the 1988/89 climate transition are not. [ABSTRACT FROM AUTHOR]

Monthly climatologies (1971-2000 monthly averages) for stations in the western United States, obtained from the NOAA/National Climatic Data Center (NCDC), are used to illustrate the spatial variations in the annual cycle of climate. Animated map sequences of temperature and precipitation, their average, intermonthly changes, and the local timing of annual maxima or minima provide a comprehensive spatiotemporal baseline of regional climate. The animated maps illustrate three scales of variation: 1) broadscale patterns related to the annual cycle of insolation and hemispheric-scale atmospheric circulation features; 2) mesoscale patterns related to location on the continent and the influence of specific regional circulation features like those associated with the North American monsoon; and 3) smaller-scale spatial variations, related to the mediation by local physiography of the influence of large-scale circulation. Although most western U.S. stations have temperature maxima in July, a delay occurs at stations along the West Coast and interior Washington, northern Idaho, and Montana. A seesaw pattern of precipitation maxima is evident between coastal areas (winter dominated) and the interior (summer dominated). Cluster analyses of the ratio of monthly-to-annual precipitation values for each station identify regions with similar annual cycles of precipitation. Regions of high spatial heterogeneity in the timing of when precipitation occurs include the northern Rocky Mountains, Utah, Arizona, and northwestern Montana. The superimposition of these three scales of spatial variability leads to steep gradients and, in some regions, considerable spatial heterogeneity in annual precipitation. The regional patterns of precipitation heterogeneity highlight vulnerability to drought, especially in regions of the interior west that do not have a dominant precipitation month or season. [ABSTRACT FROM AUTHOR]

The idea of using large-scale information to predict local climate variability is widely exploited in climate change impact studies as an alternative to computationally expensive high-resolution models. This approach implies the hypothesis that the statistical relationship between large-scale climate states and local variables defined for the present-day climate remains valid in the altered climate. In this paper, the concept of weather regimes is used to deduce a relationship between large-scale circulation and European winter temperature. The change in temperature with increased greenhouse gases is, however, not homogeneous among the individual regimes. As a result, the impact of the weather regimes on local temperature changes varies in the future, limiting its usefulness for refining temperature changes to the small scale. [ABSTRACT FROM AUTHOR]

Snow avalanches are natural hazards strongly controlled by the mountain winter climate, but their recent response to climate change has thus far been poorly documented. In this paper, hierarchical modeling is used to obtain robust indexes of the annual fluctuations of runout altitudes. The proposed model includes a possible level shift, and distinguishes common large-scale signals in both mean- and high-magnitude events from the interannual variability. Application to the data available in France over the last 61 winters shows that the mean runout altitude is not different now than it was 60 yr ago, but that snow avalanches have been retreating since 1977. This trend is of particular note for high-magnitude events, which have seen their probability rates halved, a crucial result in terms of hazard assessment. Avalanche control measures, observation errors, and model limitations are insufficient explanations for these trends. On the other hand, strong similarities in the pattern of behavior of the proposed runout indexes and several climate datasets are shown, as well as a consistent evolution of the preferred flow regime. The proposed runout indexes may therefore be usable as indicators of climate change at high altitudes. [ABSTRACT FROM AUTHOR]

Agricultural stakeholders can effectively manage the risks and opportunities arising from climate change and variability by enhancing climate services in agriculture. Key to understanding and addressing the climate challenge is the provision and the use of climate information to aid decision-makers and policy-makers. Climate services are now integral to the United Nations Framework Convention on Climate Change, the Intergovernmental Panel on Climate Change's Assessment Reports, governments' national adaptation plans, funding bodies, and a growing number of sectors and industries worldwide. The article provides our personal perspective, experience, and views on the important and timely issue of managing better the risks and opportunities to the agriculture sector and community that are arising from changes in climate. We describe a framework to help drive action to tackle the climate challenge comprising enhanced knowledge and information products, efficient information delivery and use, and assured policy and institutional support, in an iterative loop. [ABSTRACT FROM AUTHOR]

The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean's role in Earth's climate system. Individual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements. [ABSTRACT FROM AUTHOR]