Showing papers in "Journal of Climate in 2021"

Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1

Abstract: The NOAA/NESDIS/NCEI Daily Optimum Interpolation Sea Surface Temperature (SST), version 2.0, dataset (DOISST v2.0) is a blend of in situ ship and buoy SSTs with satellite SSTs derived from the Advanced Very High Resolution Radiometer (AVHRR). DOISST v2.0 exhibited a cold bias in the Indian, South Pacific, and South Atlantic Oceans that is due to a lack of ingested drifting-buoy SSTs in the system, which resulted from a gradual data format change from the traditional alphanumeric codes (TAC) to the binary universal form for the representation of meteorological data (BUFR). The cold bias against Argo was about −0.14°C on global average and −0.28°C in the Indian Ocean from January 2016 to August 2019. We explored the reasons for these cold biases through six progressive experiments. These experiments showed that the cold biases can be effectively reduced by adjusting ship SSTs with available buoy SSTs, using the latest available ICOADS R3.0.2 derived from merging BUFR and TAC, as well as by including Argo observations above 5-m depth. The impact of using the satellite MetOp-B instead of NOAA-19 was notable for high-latitude oceans but small on global average, since their biases are adjusted using in situ SSTs. In addition, the warm SSTs in the Arctic were improved by applying a freezing point instead of regressed ice-SST proxy. This paper describes an upgraded version, DOISST v2.1, which addresses biases in v2.0. Overall, by updating v2.0 to v2.1, the biases are reduced to −0.07° and −0.14°C in the global ocean and Indian Ocean, respectively, when compared with independent Argo observations and are reduced to −0.04° and −0.08°C in the global ocean and Indian Ocean, respectively, when compared with dependent Argo observations. The difference against the Group for High Resolution SST (GHRSST) Multiproduct Ensemble (GMPE) product is reduced from −0.09° to −0.01°C in the global oceans and from −0.20° to −0.04°C in the Indian Ocean.

Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models

Abstract: Author(s): Li, C; Zwiers, F; Zhang, X; Li, G; Sun, Y; Wehner, M | Abstract: This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius-Clapeyron rate of;7% 8C21. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.

?A Global, Continental, and Regional Analysis of Changes in Extreme Precipitation

Abstract: This paper provides an updated analysis of observed changes in extreme precipitation using high-quality station data up to 2018. We examine changes in extreme precipitation represented by annual maxima of 1-day (Rx1day) and 5-day (Rx5day) precipitation accumulations at different spatial scales and attempt to address whether the signal in extreme precipitation has strengthened with several years of additional observations. Extreme precipitation has increased at about two-thirds of stations and the percentage of stations with significantly increasing trends is significantly larger than that can be expected by chance for the globe, continents including Asia, Europe, and North America, and regions including central North America, eastern North America, northern Central America, northern Europe, the Russian Far East, eastern central Asia, and East Asia. The percentage of stations with significantly decreasing trends is not different from that expected by chance. Fitting extreme precipitation to generalized extreme value distributions with global mean surface temperature (GMST) as a covariate reaffirms the statistically significant connections between extreme precipitation and temperature. The global median sensitivity, percentage change in extreme precipitation per 1 K increase in GMST is 6.6% (5.1% to 8.2%; 5%–95% confidence interval) for Rx1day and is slightly smaller at 5.7% (5.0% to 8.0%) for Rx5day. The comparison of results based on observations ending in 2018 with those from data ending in 2000–09 shows a consistent median rate of increase, but a larger percentage of stations with statistically significant increasing trends, indicating an increase in the detectability of extreme precipitation intensification, likely due to the use of longer records.

Response of Global Tropical Cyclone Activity to Increasing CO2: Results from Downscaling CMIP6 Models

Abstract: Global models comprising the sixth-generation Coupled Climate Model Intercomparison Project (CMIP6) are downscaled using a very high-resolution but simplified coupled atmosphere–ocean tropical cyclonemodel, as ameans of estimating the response of global tropical cyclone activity to increasing greenhouse gases. As with a previous downscaling of CMIP5models, the results show an increase in both the frequency and severity of tropical cyclones, robust across themodels downscaled, in response to increasing greenhouse gases. The increase is strongly weighted to theNorthernHemisphere, and especially noteworthy is a large increase in the higher latitudes of the North Atlantic. Changes are insignificant in the South Pacific across metrics. Although the largest increases in track density are far from land, substantial increases in global landfalling power dissipation are indicated. The incidence of rapid intensification increases rapidly with warming, as predicted by existing theory. Measures of robustness across downscaled climate models are presented, and comparisons to tropical cyclones explicitly simulated in climate models are discussed.

An Evaluation of the Performance of the Twentieth Century Reanalysis Version 3

Abstract: The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a “best estimate” of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

Impact of the Indian Ocean Dipole on Evolution of the Subsequent ENSO: Relative Roles of Dynamic and Thermodynamic Processes

Abstract: The complex interaction between the Indian Ocean dipole (IOD) and El Niño–Southern Oscillation (ENSO) is further investigated in this study, with a focus on the impacts of the IOD on ENSO in the subsequent year [ENSO(+1)]. The interaction between the IOD and the concurrent ENSO [ENSO(0)] can be summarized as follows: ENSO(0) can trigger and enhance the IOD, while the IOD can enhance ENSO(0) and accelerate its demise. Regarding the impacts of IOD(0) on the subsequent ENSO(+1), it is revealed that the IOD can lead to anomalous SST cooling patterns over the equatorial Pacific after the winter following the IOD, indicating the formation of a La Niña–like pattern in the subsequent year. While the SST cooling tendency associated with a positive IOD is attributable primarily to net heat flux (thermodynamic processes) from autumn to the ensuing spring, after the ensuing spring the dominant contribution comes from oceanic processes (dynamic processes) instead. From autumn to the ensuing spring, the downward shortwave flux response contributes the most to SST cooling over the central and eastern Pacific, due to the cloud–radiation–SST feedback. From the ensuing winter to the ensuing summer, changes in latent heat flux (LHF) are important for SST cooling, indicating that the release of LHF from the ocean into the atmosphere increases due to strong evaporation and leads to SST cooling through the wind–evaporation–SST feedback. The wind stress response and thermocline shoaling verify that local Bjerknes feedback is crucial for the initiation of La Niña in the later stage.

IMDAA: High-Resolution Satellite-Era Reanalysis for the Indian Monsoon Region

Abstract: A high resolution regional reanalysis of the Indian Monsoon Data Assimilation and Analysis (IMDAA) project is made available to researchers for deeper understanding of the Indian monsoon and its variability. This 12 km resolution reanalysis covering the satellite-era from 1979 to 2018 using 4D-Var data assimilation method and the UK Met Unified Model is presently the highest resolution atmospheric reanalysis carried out for the Indian monsoon region. Conventional and satellite observations from different sources are used, including Indian surface and upper air observations, of which some were not used in any previous reanalyses. Various aspects of this reanalysis, like quality control and bias correction of observations, data assimilation system, land surface analysis, and verification of reanalysis products, are presented in this paper. Representation of important weather phenomena of each season over India in the IMDAA reanalysis verifies reasonably well against India Meteorological Department (IMD) observations and compares closely with ERA5. Salient features of the Indian summer monsoon are found to be well represented in the IMDAA reanalysis. Characteristics of major semi-permanent summer monsoon features (e.g., Low-level Jet and Tropical Easterly Jet) in IMDAA reanalysis are consistent with ERA5. The IMDAA reanalysis has captured the mean, inter-annual, and intra-seasonal variability of summer monsoon rainfall fairly well. IMDAA produces a slightly cooler winter and a hotter summer than the observations; the reverse for ERA5. IMDAA captured the fine-scale features associated with a notable heavy rainfall episode over complex terrain. In this study, the fine grid spacing nature of IMDAA is compromised due to the lack of comparable resolution observations for verification.

Attribution of Extreme Precipitation with Updated Observations and CMIP6 Simulations

Abstract: While the IPCC Fifth Assessment Working Group I report assessed observed changes in extreme precipitation on the basis of both absolute and percentile-based extreme indices, human influence on extreme precipitation has rarely been evaluated on the basis of percentile-based extreme indices. Here we conduct a formal detection and attribution analysis on changes in four percentile-based precipitation extreme indices. The indices include annual precipitation totals from days with precipitation exceeding the 99th and 95th percentiles of wet-day precipitation in 1961–90 (R99p and R95p) and their contributions to annual total precipitation (R99pTOT and R95pTOT). We compare these indices from a set of newly compiled observations during 1951–2014 with simulations from models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). We show that most land areas with observations experienced increases in these extreme indices with global warming during the historical period 1951–2014. The new CMIP6 models are able to reproduce these overall increases, although with considerable over- or underestimations in some regions. An optimal fingerprinting analysis reveals detectable anthropogenic signals in the observations of these indices averaged over the globe and over most continents. Furthermore, signals of greenhouse gases can be separately detected, taking other forcing into account, over the globe and over Asia in these indices except for R95p. In contrast, signals of anthropogenic aerosols and natural forcings cannot be detected in any of these indices at either global or continental scales.

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the United States

Abstract: A process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the United States. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation features at 12-, 25-, and 50-km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency, and intensity are found to be consistently underestimated in the central United States, particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while the MCS precipitation area is too large and its intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during the daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

Impact of Developing ENSO on Tibetan Plateau Summer Rainfall

Abstract: The year-to-year variations of Tibetan Plateau (TP) summer rainfall have tremendous climate impacts on the adjoining and even global climate, attracting extensive research attention in recent decades to understand the underlying mechanism. In this study, we investigate an open question of how El Niño–Southern Oscillation (ENSO) influences the TP precipitation. We show that the developing ENSO has significant impacts on the summer rainfall over the southwestern TP (SWTP), which is the second EOF mode of the interannual variability of summer rainfall over the TP. The moisture budget indicates that both the suppressed vertical motion and the deficit of moisture contribute to the reduction of SWTP rainfall during El Niño’s developing summer, with the former contribution 4 times larger than the latter. Moist static energy analyses indicate that the anomalous advection of climatological moist enthalpy by anomalous zonal wind is responsible for the anomalous descending motions over the SWTP. The El Niño–related southward displacements of the South Asian high and the upper-level cyclonic anomalies over the west of TP stimulated by the suppressed Indian summer monsoon precipitation are two key processes dominating the anomalous zonal moist enthalpy advection over SWTP. Meanwhile, the India–Burma monsoon trough is strengthened during El Niño developing summer, which prevents the advection of water vapor into the SWTP, and thus contributes to the deficit of summer SWTP rainfall. Our results help to understand the complicated ENSO-related air–sea interaction responsible for the variability of TP precipitation and have implications for seasonal prediction of the TP climate.

Are 100 Ensemble Members Enough to Capture the Remote Atmospheric Response to +2°C Arctic Sea Ice Loss?

Abstract: Author(s): Peings, Y; Labe, ZM; Magnusdottir, G | Abstract: This study presents results from the Polar Amplification Multimodel Intercomparison Project (PAMIP) single-year time-slice experiments that aim to isolate the atmospheric response to Arctic sea ice loss at global warming levels of 128C. Using two general circulation models (GCMs), the ensemble size is increased up to 300 ensemble members, beyond the recommended 100 members. After partitioning the response in groups of 100 ensemble members, the reproducibility of the results is evaluated, with a focus on the response of the midlatitude jet streams in the North Atlantic and North Pacific. Both atmosphere-only and coupled ocean–atmosphere PAMIP experiments are analyzed. Substantial differences in the midlatitude response are found among the different experiment subsets, suggesting that 100-member ensembles are still significantly influenced by internal variability, which can mislead conclusions. Despite an overall stronger response, the coupled ocean–atmosphere runs exhibit greater spread due to additional ENSO-related internal variability when the ocean is interactive. The lack of consistency in the response is true for anomalies that are statistically significant according to Student’s t and false discovery rate tests. This is problematic for the multimodel assessment of the response, as some of the spread may be attributed to different model sensitivities whereas it is due to internal variability. We propose a method to overcome this consistency issue that allows for more robust conclusions when only 100 ensemble members are used.

Observed Statistical Connections Overestimate the Causal Effects of Arctic Sea Ice Changes on Midlatitude Winter Climate

Abstract: Disentangling the contribution of changing Arctic sea ice to midlatitude winter climate variability remains challenging because of the large internal climate variability in midlatitudes, difficulties separating cause from effect, methodological differences, and uncertainty around whether models adequately simulate connections between Arctic sea ice and midlatitude climate. We use regression analysis to quantify the links between Arctic sea ice and midlatitude winter climate in observations and large initial-condition ensembles of multiple climate models, in both coupled configurations and so-called Atmospheric Model Intercomparison Project (AMIP) configurations, where observed sea ice and/or sea surface temperatures are prescribed. The coupled models capture the observed links in interannual variability between winter Barents–Kara sea ice and Eurasian surface temperature, and between winter Chukchi–Bering sea ice and North American surface temperature. The coupled models also capture the delayed connection between reduced November–December Barents–Kara sea ice, a weakened winter stratospheric polar vortex, and a shift toward the negative phase of the North Atlantic Oscillation in late winter, although this downward impact is weaker than observed. The strength and sign of the connections both vary considerably between individual 35-yr-long ensemble members, highlighting the need for large ensembles to separate robust connections from internal variability. All the aforementioned links are either absent or are substantially weaker in the AMIP experiments prescribed with only observed sea ice variability. We conclude that the causal effects of sea ice variability on midlatitude winter climate are much weaker than suggested by statistical associations, evident in observations and coupled models, because the statistics are inflated by the effects of atmospheric circulation variability on sea ice.

Arctic Warming Revealed by Multiple CMIP6 Models: Evaluation of Historical Simulations and Quantification of Future Projection Uncertainties

Abstract: The Arctic has experienced a warming rate higher than the global mean in the past decades, but previous studies show that there are large uncertainties associated with future Arctic temperature projections. In this study, near-surface mean temperatures in the Arctic are analyzed from 22 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Compared with the ERA5 reanalysis, most CMIP6 models underestimate the observed mean temperature in the Arctic during 1979–2014. The largest cold biases are found over the Greenland Sea the Barents Sea, and the Kara Sea. Under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, the multimodel ensemble mean of 22 CMIP6 models exhibits significant Arctic warming in the future and the warming rate is more than twice that of the global/Northern Hemisphere mean. Model spread is the largest contributor to the overall uncertainty in projections, which accounts for 55.4% of the total uncertainty at the start of projections in 2015 and remains at 32.9% at the end of projections in 2095. Internal variability uncertainty accounts for 39.3% of the total uncertainty at the start of projections but decreases to 6.5% at the end of the twenty-first century, while scenario uncertainty rapidly increases from 5.3% to 60.7% over the period from 2015 to 2095. It is found that the largest model uncertainties are consistent cold bias in the oceanic regions in the models, which is connected with excessive sea ice area caused by the weak Atlantic poleward heat transport. These results suggest that large intermodel spread and uncertainties exist in the CMIP6 models’ simulation and projection of the Arctic near-surface temperature and that there are different responses over the ocean and land in the Arctic to greenhouse gas forcing. Future research needs to pay more attention to the different characteristics and mechanisms of Arctic Ocean and land warming to reduce the spread. (Less)

Midlatitude Winter Extreme Temperature Events and Connections with Anomalies in the Arctic and Tropics

Abstract: For the last few decades the Northern Hemisphere midlatitudes have seen an increasing number of temperature extreme events It has been suggested that some of these extremes are related to planetary wave activity In this study we identify wave propagation regions at 300 hPa using the ERA-Interim dataset from 1980 to 2017 and link them to temperature extremes in densely populated regions of the Northern Hemisphere Most studies have used background flow fields at monthly or seasonal scale to investigate wave propagation For a phenomenon that is influenced by threshold incidents and nonlinear processes, this can distort the net Rossby wave signal A novel aspect of our investigation lies in the use of daily data to study wave propagation allowing it to be diagnosed for limited but important periods across a wider range of latitudes, including the polar region We show that winter temperature extremes in the midlatitudes can be associated with circulation anomalies in both the Arctic and the tropics, while the relative importance of these areas differs according to the specific midlatitude region In particular, wave trains connecting the tropical Pacific and Atlantic may be associated with temperature anomalies in North America and Siberia Arctic seas are markedly important for Eurasian regions Analysis of synoptic temperature extremes suggests that preexisting local temperature anomalies play a key role in the development of those extremes, as well as amplification of large-scale wave trains We also demonstrate that warm Arctic regions can create cold outbreaks in both Siberia and North America

Changes in Observed Daily Precipitation over Global Land Areas since 1950

Abstract: This study was funded by Australian Research Council (ARC) Grant DP160103439. MGD received funding from ARC Grant DE150100456, and the Spanish Ministry for the Economy, Industry and Competitiveness Grant RYC-2017-22964. LVA was also funded by ARC Grant CE110001028. We are also grateful to the National Centers for Environmental Information (NCEI) and the Global Precipitation Climatology Centre (GPCC) for support during the production of REGEN.

Origins of the Excessive Westward Extension of ENSO SST Simulated in CMIP5 and CMIP6 Models

Abstract: An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSOSST variability among themodels. TheENSOSSTbias lowers themodels’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension ofENSOSST in 25CMIP5 and 25CMIP6models. Based on the intermodel spread ofENSOSST variability simulated in the 50models, we reveal that this ENSO SST bias among themodels largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue fromCMIP5 to CMIP6, the excessive westward extension bias ofENSOSST inCMIP6models is also reduced relative to those inCMIP5models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.

Urbanization Effects on Estimates of Global Trends in Mean and Extreme Air Temperature

Abstract: 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.

Observed Linkage between Tibetan Plateau Soil Moisture and South Asian Summer Precipitation and the Possible Mechanism

Abstract: Understanding the Tibetan Plateau (TP) thermal processes is of utmost significance in changing climate. This study investigates the effect of soil moisture in changing the TP thermal profile and consequently summer precipitation in South Asia (SA). Soil moisture from Special Sensor Microwave Imager (SSM/I) developed from the F-08, F-11, and F-13 fundamental climate data record and atmospheric reanalysis from ERA-Interim, MERRA-2, and NCEP/CFSR during 1988–2008 are used. A generalized linear method that assesses the reciprocal forcing between two connected fields, named the coupled manifold technique (CMT), is applied to TP soil moisture and SA summer precipitation. It is revealed that interannual variations of SA precipitation are significantly (confidence level = 99%) impacted by TP soil moisture and the explained ratio of variance in SA is 0.3–0.4. Composite analysis indicates that SA summer precipitation has positive anomalies in response to dry TP soil moisture in the previous spring and vice versa. For understanding the possible mechanism, thermal processes, relative humidity, wind components, and moisture flux anomalies were calculated for dry and wet TP soil moisture and summer precipitation. The results suggested that TP soil moisture is likely to regulate near-surface energy balance and diabatic heating profile over TP. As a result, the surrounding lower-level westerlies (easterlies) (at 850 hPa) converge (diverge), associated with divergence (convergence) at the upper troposphere (200 hPa). The westerlies (easterlies) are usually moisture-rich (moisture-deficient) and thus cause more (less) precipitation in western (eastern) SA. It is thus suggested that the spring soil moisture may affect the thermal profile of TP, affecting the summer precipitation in SA as a consequence.

Anthropogenic Greenhouse Gas and Aerosol Contributions to Extreme Temperature Changes during 1951–2015

Abstract: This study conducted a detection and attribution analysis of the observed global and regional changes in extreme temperatures during 1951–2015. HadEX3 observations were compared with multimodel simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) using an optimal fingerprinting technique. Annual maximum daily maximum and minimum temperatures (TXx and TNx; warm extremes) and annual minimum daily maximum and minimum temperatures (TXn and TNn; cold extremes) over land were analyzed considering global, continental, and subcontinental scales. Response patterns (fingerprints) of extreme temperatures to anthropogenic (ANT), greenhouse gases (GHG), aerosols (AA), and natural (NAT) forcings were obtained from CMIP6 forced simulations. The internal variability ranges were estimated from preindustrial control simulations. A two-signal detection analysis where the observations are regressed onto ANT and NAT fingerprints simultaneously reveals that ANT signals are robustly detected in separation from NAT over global and all continental domains (North and South America, Europe, Asia, and Oceania) for most of the extreme indices. ANT signals are also detected over many subcontinental regions, particularly for warm extremes (more than 60% of 33 subregions). A three-signal detection analysis that considers GHG, AA, and NAT fingerprints simultaneously demonstrates that GHG signals are detected in isolation from other external forcings over global, continental, and several subcontinental domains especially for warm extremes, explaining most of the observed warming. Moreover, AA influences are detected for warm extremes over Europe and Asia, indicating significant offsetting cooling contributions. Overall, human influences are detected more frequently, compared to previous studies, particularly for cold extremes, due to the extended period and the improved spatial coverage of observations.

Impact of winds and Southern Ocean SSTs on Antarctic sea ice trends and variability

Abstract: Antarctic sea ice extent (SIE) has slightly increased over the satellite observational period (1979 to the present) despite global warming. Several mechanisms have been invoked to explain this trend, such as changes in winds, precipitation, or ocean stratification, yet there is no widespread consensus. Additionally, fully coupled Earth system models run under historic and anthropogenic forcing generally fail to simulate positive SIE trends over this time period. In this work, we quantify the role of winds and Southern Ocean SSTs on sea ice trends and variability with an Earth system model run under historic and anthropogenic forcing that nudges winds over the polar regions and Southern Ocean SSTs north of the sea ice to observations from 1979 to 2018. Simulations with nudged winds alone capture the observed interannual variability in SIE and the observed long-term trends from the early 1990s onward, yet for the longer 1979–2018 period they simulate a negative SIE trend, in part due to faster-than-observed warming at the global and hemispheric scale in the model. Simulations with both nudged winds and SSTs show no significant SIE trends over 1979–2018, in agreement with observations. At the regional scale, simulated sea ice shows higher skill compared to the pan-Antarctic scale both in capturing trends and interannual variability in all nudged simulations. We additionally find negligible impact of the initial conditions in 1979 on long-term trends.

Improvement of ERA5 over ERA-Interim in Simulating Surface Incident Solar Radiation throughout China

Abstract: Surface incident solar radiation (Rs) is important for providing essential information on climate change. Existing studies have shown that the Rs values from current reanalyses are significantly overestimated throughout China. The European Centre for Medium-Range Weather Forecasts (ECMWF) recently released the fifth generation of atmospheric reanalysis (i.e., ERA5) with a much higher spatiotemporal resolution and a major upgrade compared to its predecessor, ERA-Interim. This study is to verify whether ERA5 can improve the Rs simulation using sunshine duration–derived Rs values at ~2200 stations over China from 1979 to 2014 as reference data. Compared with the observed multiyear national mean, the Rs overestimation is reduced from 15.88 W m−2 in ERA-Interim to 10.07 W m−2 in ERA5. From 1979 to 1993, ERA-Interim (−1.99 W m−2 decade−1; p < 0.05) and ERA5 (−2.42 W m−2 decade−1; p < 0.05) estimates of Rs in China continued to decrease and the decline of the latter is closer to the observed. After 1993, they both show a strong brightening (i.e., 2.26 W m−2 decade−1 in ERA-Interim and 1.49 W m−2 decade−1 in ERA5) but observations show a nonsignificant increase by 0.30 W m−2 decade−1. Due to the improvement of total cloud cover (TCC) simulation by ERA5, its Rs trend bias induced by the TCC trend bias is smaller than that in ERA-Interim. In addition, the reason why the simulation trend in ERA5 remains biased might be that ERA5 still ignores aerosol changes on interannual or decadal time scales. Therefore, subsequent reanalysis products still need to improve their simulation of clouds, water vapor, and aerosol, especially in aerosol direct and indirect effects on Rs.

Extreme Temperatures in the Antarctic

Abstract: We present the first Antarctic-wide analysis of extreme near-surface air temperatures based on data collected up to the end of 2019 as part of the synoptic meteorological observing programs. We consider temperatures at 17 stations on the Antarctic continent and nearby sub-Antarctic islands. We examine the frequency distributions of temperatures and the highest and lowest individual temperatures observed. The variability and trends in the number of extreme temperatures were examined via the mean daily temperatures computed from the 0000, 0600, 1200, and 1800 UTC observations, with the thresholds for extreme warm and cold days taken as the 5th and 95th percentiles. The five stations examined from the Antarctic Peninsula region all experienced a statistically significant increase (p < 0.01) in the number of extreme high temperatures in the late-twentieth-century part of their records, although the number of extremes decreased in subsequent years. For the period after 1979 we investigate the synoptic background to the extreme events using ECMWF interim reanalysis (ERA-Interim) fields. The majority of record high temperatures were recorded after the passage of air masses over high orography, with the air being warmed by the foehn effect. At some stations in coastal East Antarctica the highest temperatures were recorded after air with a high potential temperature descended from the Antarctic plateau, resulting in an air mass 5°–7°C warmer than the maritime air. Record low temperatures at the Antarctic Peninsula stations were observed during winters with positive sea ice anomalies over the Bellingshausen and Weddell Seas.

Compatible Fossil Fuel CO2 Emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway Experiments of the Twenty-First Century

Abstract: We present the compatible CO2 emissions from fossil fuel (FF) burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth system models (ESMs) participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (394 ± 59 GtC vs 400 ± 20 GtC, respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the integrated assessment models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4, and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land-use and land-cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

Global Near-Surface Wind Speed Changes over the Last Decades Revealed by Reanalyses and CMIP6 Model Simulations

Abstract: Near-surface (10 m) wind speed (NWS) plays a crucial role in many areas, including hydrological cycles, wind energy production, and air pollution, but what drives its multidecadal changes is still unclear. Using reanalysis datasets and model simulations from phase 6 of the Coupled Model Intercomparison Projection (CMIP6), this study investigates recent trends in the annual mean NWS. The results show that the Northern Hemisphere (NH) terrestrial NWS experienced significant (p < 0.1) decreasing trends during 1980–2010, when the Southern Hemisphere (SH) ocean NWS was characterized by significant (p < 0.1) upward trends. However, during 2010–19, global NWS trends shifted in their sign: NWS trends over the NH land became positive, and trends over the SH tended to be negative. We propose that the strengthening of SH NWS during 1980–2010 was associated with an intensified Hadley cell over the SH, while the declining of NH land NWS could have been caused by changes in atmospheric circulation, alteration of vegetation and/or land use, and the accelerating Arctic warming. The CMIP6 model simulations further demonstrate that the greenhouse gas (GHG) warming plays an important role in triggering the NWS trends over the two hemispheres during 1980–2010 through modulating meridional atmospheric circulation. This study also points at the importance of anthropogenic GHG forcing and the natural Pacific decadal oscillation to the long-term trends and multidecadal variability in global NWS, respectively.

Evaluating the Diurnal and Semidiurnal Cycle of Precipitation in CMIP6 Models Using Satellite- and Ground-Based Observations

Abstract: The diurnal and semi-diurnal cycle of precipitation simulated from CMIP6 models during 1996-2005 are evaluated globally between 60°S and 60°N, as well as at ten selected locations representing three categories of diurnal cycle of precipitation: (1) afternoon precipitation over land, (2) early morning precipitation over ocean, and (3) nocturnal precipitation over land. Three satellite-based and two ground-based rainfall products are used to evaluate the climate models. Globally, the ensemble mean of CMIP6 models shows a diurnal phase of 3 to 4 hours earlier over land and 1 to 2 hours earlier over ocean, when compared with the latest satellite products. These biases are in line with what were found in previous versions of climate models but reduced compared to the CMIP5 ensemble mean. Analysis at the selected locations complimented with in-situ measurements further reinforces these results. Several CMIP6 models have shown a significant improvement in the diurnal cycle of precipitation compared to their CMIP5 counterparts, notably on delaying afternoon precipitation over land. This can be attributed to the use of more sophisticated convective parameterizations. Most models are still unable to capture the nocturnal peak associated with elevated convection and propagating mesoscale convective systems, with a few exceptions that allow convection to be initiated above the boundary layer to capture nocturnal elevated convection. We also quantify an encouraging consistency between the satellite- and ground-based precipitation measurements despite differing spatiotemporal resolutions and sampling periods, which provides confidence in using them to evaluate the diurnal and semi-diurnal cycle of precipitation in climate models.

Decomposing the Drivers of Polar Amplification with a Single Column Model.

Abstract: The precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods based on top-of-atmosphere energy budgets have assumed all forcings and feedbacks lead to vertically-uniform temperature changes, with any departures from this collected into the lapse-rate feedback. We propose an alternative attribution method using a single column model that accounts for the forcing-dependence of high latitude lapse-rate changes. We test this method in an idealized General Circulation Model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they lead to bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea-ice retreat), changes in energy transport are primarily responsible for the polar amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport. This physically-based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.

Separating the Indian and Pacific Ocean Impacts on the Euro-Atlantic Response to ENSO and Its Transition from Early to Late Winter

Abstract: The present study focuses on the mechanism that controls the transition of the Euro-Atlantic circulation responses to El Niño–Southern Oscillation (ENSO) from early (December) to late winter (February) for the period 1981–2015. A positive phase of ENSO induces a precipitation dipole with increased precipitation in the western and reduced precipitation in the eastern tropical Indian Ocean; this occurs mainly during early winter (December) and less so in late winter (February). It is shown that these interbasin atmospheric teleconnections dominate the response in the Euro-Atlantic sector in early winter by modifying the subtropical South Asian jet (SAJET) and forcing a wavenumber-3 response that projects spatially onto the positive North Atlantic Oscillation (NAO) pattern. On the contrary, during late winter, the response in the Euro-Atlantic sector is dominated by the well-known ENSO wave train from the tropical Pacific region, involving extratropical anomalies that project spatially on the positive phase of the Pacific–North American (PNA) pattern and the negative phase of the NAO pattern. Numerical experiments with an atmospheric model (an AGCM) forced by an Indian Ocean heating dipole anomaly support the hypothesis that the Indian Ocean modulates the SAJET and enforces the Rossby wave propagation to the Euro-Atlantic region in early winter. These phenomena are also investigated using the ECMWF SEAS5 reforecast dataset. In SEAS5, the ENSO interbasin tropical teleconnections and the response of the Euro-Atlantic circulation anomalies and their change from early to late winter are realistically predicted, although the strength of the early winter signal originated from the Indian Ocean is underestimated.

Seasonal prediction and predictability of regional Antarctic sea ice

Abstract: Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_ LO, and SPEAR_MEDdynamicalmodels, differ in their coupledmodel components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability.We find that each system is capable of skillfully predicting regionalAntarctic sea ice extent (SIE)with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/ Bellingshausen, Indian, and west Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upperocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently developedSPEARsystems aremore skillful thanFLORfor summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal time scales.

Impact of stochastic physics and model resolution on the simulation of Tropical Cyclones in climate GCMs

Abstract: The role of model resolution in simulating geophysical vortices with the characteristics of realistic Tropical Cyclones (TCs) is well established The push for increasing resolution continues, with General Circulation Models (GCMs) starting to use sub-10km grid spacing In the same context it has been suggested that the use of Stochastic Physics (SP) may act as a surrogate for high resolution, providing some of the benefits at a fraction of the cost Either technique can reduce model uncertainty, and enhance reliability, by providing a more dynamic environment for initial synoptic disturbances to be spawned and to grow into TCs We present results from a systematic comparison of the role of model resolution and SP in the simulation of TCs, using EC-Earth simulations from project Climate-SPHINX, in large ensemble mode, spanning five different resolutions All tropical cyclonic systems, including TCs, were tracked explicitly As in previous studies, the number of simulated TCs increases with the use of higher resolution, but SP further enhances TC frequencies by � 30%, in a strikingly similar way The use of SP is beneficial for removing systematic climate biases, albeit not consistently so for interannual variability; conversely, the use of SP improves the simulation of the seasonal cycle of TC frequency An investigation of the mechanisms behind this response indicates that SP generates both higher TC (and TC seed) genesis rates, and more suitable environmental conditions, enabling a more efficient transition of TC seeds into TCs These results were confirmed by the use of equivalent simulations with the HadGEM3-GC31 GCM

Summer Extreme Cyclone Impacts on Arctic Sea Ice

Abstract: In this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate that sea ice loss in the vicinity of the cyclone trajectories during each year was associated with different dominant processes: thermodynamic processes (melting) in the Pacific sector of theArctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of theArctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016. Central to a characterization of extreme cyclone impacts onArctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warmingArctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure, and designation of protected and ecologically sensitive marine zones.