Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air ...temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively.
Abstract
According to the characteristics of forced and unforced components to climate change, sophisticated statistical models were used to fit and separate multiple scale variations in the global ...mean surface temperature (GMST) series. These include a combined model of the multiple linear regression and autoregressive integrated moving average models to separate the contribution of both the anthropogenic forcing (including anthropogenic factors (GHGs, aerosol, land use, Ozone, etc) and the natural forcing (volcanic eruption and solar activities)) from internal variability in the GMST change series since the last part of the 19th century (which explains about 91.6% of the total variances). The multiple scale changes (inter-annual variation, inter-decadal variation, and multi-decadal variation) are then assessed for their periodic features in the remaining residuals of the combined model (internal variability explains the rest 8.4% of the total variances) using the ensemble empirical mode decomposition method. Finally, the individual contributions of the anthropogenic factors are attributed using a partial least squares regression model.
Radiosonde humidity records represent the only in situ observations of tropospheric water vapor content with multidecadal length and quasi-global coverage. However, their use has been hampered by ...ubiquitous and large discontinuities resulting from changes to instrumentation and observing practices. Here a new approach is developed to homogenize historical records of tropospheric (up to 100 hPa) dewpoint depression (DPD), the archived radiosonde humidity parameter. Two statistical tests are used to detect changepoints, which are most apparent in histograms and occurrence frequencies of the daily DPD: a variant of the Kolmogorov–Smirnov (K–S) test for changes in distributions and the penalized maximalFtest (PMFred) for mean shifts in the occurrence frequency for different bins of DPD. These tests capture most of the apparent discontinuities in the daily DPD data, with an average of 8.6 changepoints (∼1 changepoint per 5 yr) in each of the analyzed radiosonde records, which begin as early as the 1950s and ended in March 2009. Before applying breakpoint adjustments, artificial sampling effects are first adjusted by estimating missing DPD reports for cold (T< −30°C) and dry (DPD artificially set to 30°C) conditions using empirical relationships at each station between the anomalies of air temperature and vapor pressure derived from recent observations when DPD reports are available under these conditions. Next, the sampling-adjusted DPD is detrended separately for each of the 4–10 quantile categories and then adjusted using a quantile-matching algorithm so that the earlier segments have histograms comparable to that of the latest segment. Neither the changepoint detection nor the adjustment uses a reference series given the stability of the DPD series.
Using this new approach, a homogenized global, twice-daily DPD dataset (available online at www.cgd.ucar.edu/cas/catalog/) is created for climate and other applications based on the Integrated Global Radiosonde Archive (IGRA) and two other data sources. The adjusted-daily DPD has much smaller and spatially more coherent trends during 1973–2008 than the raw data. It implies only small changes in relative humidity in the lower and middle troposphere. When combined with homogenized radiosonde temperature, other atmospheric humidity variables can be calculated, and these exhibit spatially more coherent trends than without the DPD homogenization. The DPD adjustment yields a different pattern of change in humidity parameters compared to the apparent trends from the raw data. The adjusted estimates show an increase in tropospheric water vapor globally.
Celotno besedilo
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The El Niño-Southern Oscillation (ENSO) exerts significant influences on extreme significant wave height (SWH) but climate model capabilities in reproducing the observed ENSO impact on SWH have not ...been evaluated. This study assesses the performances of the Coupled Model Intercomparison Project phase 5 (CMIP5) models in term of extreme SWH responses to ENSO over the Indo-Pacific Ocean focusing on December-February (DJF). 18 CMIP5 models are evaluated using their historical simulations for 1950–2005 in view of the ERA-20C reanalysis. A non-stationary generalized extreme value (GEV) analysis is employed to fit DJF maxima of 6-hourly SWHs and obtain the extreme SWH response patterns to ENSO by incorporating Niño3.4 index as a covariate. Results show that CMIP5 models can on average capture the major observed mean and extreme SWH responses to ENSO, including the increased SWH over the northeastern North Pacific (NENP) and the decreased SWH over the Maritime Continent (MC) during El Niño. The inter-model relations between ENSO characteristics and SWH responses are further examined for the two hotspot regions (NENP and MC). It is found that ENSO intensity is a dominant factor determining simulated SWH over the NENP such that models with stronger ENSO simulate stronger SWH responses. In contrast, for the MC, the sea level pressure teleconnection pattern significantly affects the inter-model spread in SWH responses, also explaining the systematic underestimation of SWH responses over the region. Implication is that ENSO intensity and atmospheric teleconnection patterns need to be considered for better simulations and reliable predictions of extreme SWH variability.
An objective cyclone tracking algorithm is applied to twentieth century reanalysis (20CR) 6-hourly mean sea level pressure fields for the period 1871–2010 to infer historical trends and variability ...in extra-tropical cyclone activity. The tracking algorithm is applied both to the ensemble-mean analyses and to each of the 56 ensemble members individually. The ensemble-mean analyses are found to be unsuitable for accurately determining cyclone statistics. However, pooled cyclone statistics obtained by averaging statistics from individual members generally agree well with statistics from the NCEP-NCAR reanalyses for 1951–2010, although 20CR shows somewhat weaker cyclone activity over land and stronger activity over oceans. Both reanalyses show similar cyclone trend patterns in the northern hemisphere (NH) over 1951–2010. Homogenized pooled cyclone statistics are analyzed for trends and variability. Conclusions account for identified inhomogeneities, which occurred before 1949 in the NH and between 1951 and 1985 in the southern hemisphere (SH). Cyclone activity is estimated to have increased slightly over the period 1871–2010 in the NH. More substantial increases are seen in the SH. Notable regional and seasonal variations in trends are evident, as is profound decadal or longer scale variability. For example, the NH increases occur mainly in the mid-latitude Pacific and high-latitude Atlantic regions. For the North Atlantic-European region and southeast Australia, the 20CR cyclone trends are in agreement with trends in geostrophic wind extremes derived from in-situ surface pressure observations. European trends are also consistent with trends in the mean duration of wet spells derived from rain gauge data in Europe.
This study characterizes historical changes in surface wind speed and ocean surface waves in the Beaufort–Chukchi–Bering Seas using Environment Canada’s Beaufort Wind and Wave Reanalysis for the ...period 1970–2013. The results show that both the significant wave height (Hs
) and mean wave period (Tm
) have increased significantly over the Bering Sea in July and August and over the Canadian Beaufort Sea westward to the northern Bering Sea in September, and that the 1992–2013 trends in September meanHs
agree well with satellite-based trend estimates for 1993–2010. Most outstandingly, the regional meanTm
has increased at a rate of 3%–4% y−1of the corresponding 1970–99 climatology; it has more than tripled since 1970. Also, the regional meanHs
has increased at a rate of 0.3% to 0.8% yr−1. The trends of lengthening wave period and increasing wave height imply a trend of increasing wave energy flux, providing a mechanism to break up sea ice and accelerate ice retreat. The results also show that changes in the local wind speeds alone cannot explain the significant changes in waves. The wind speeds show significant increases over the Bering Sea to the north of Alaska in July and over the central part of the domain in August and September, with decreases in the region off the Canadian coasts in August. In the region west of the Canadian coast, the climatological mean wind direction has rotated clockwise in July and August, with the climatological anticyclonic center being displaced northeastward in August.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 China Meteorological Administration global Land Surface Air Temperature ...(CMA-LSAT) is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal
t
test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900–2014, 1979–2014 and 1998–2014. The best estimates of warming trends and there 95% confidence ranges for 1900–2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900–2014 and 1979–2014. For an even shorter and more recent period (1998–2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes.
This study first homogenizes time series of daily maximum and minimum temperatures recorded at 825 stations in China over the period from 1951 to 2010, using both metadata and the penalized maximum t ...test with the first‐order autocorrelation being accounted for to detect change points and using the quantile‐matching algorithm to adjust the data time series to diminish discontinuities. Station relocation was found to be the main cause for discontinuities, followed by station automation. The effects of discontinuities on estimation of long‐term trends in the annual mean and extreme indices of temperature are illustrated. The data homogenization is shown to have improved the spatial consistency of estimated trends. Using the homogenized daily minimum and daily maximum temperature data, this study also analyzes trends in extreme temperature indices. The results show that the vast majority (85%–90%) of the 825 sites have experienced significantly more warm nights and less cold nights since 1951. There have also been more warm days and less cold days since 1951, although these trends are less extensive. About 62% of the 825 sites were found to have experienced significantly more warm days and about 50% significantly less cold days. None of the 825 sites were found to have significantly more cold nights/days or less warm nights/days. These indicate that the warming is stronger in nighttime than in daytime and stronger in winter than in summer. Thus, the diurnal temperature range was found to have significantly decreased at 49% of the 825 sites, with significant increases being identified only at 3% of these sites.
Key Points
Homogenized time series of daily temperatures in China.
Illustrated the effects of nonclimatic changes trends.
Analyzed trends in extreme temperature indices.
Trends in soil temperature are important, but rarely reported, indicators of climate change. On the basis of the soil temperature data from 30 climate stations across Canada during 1958–2008, trends ...in soil temperatures at 5, 10, 20, 50, 100, and 150 cm depths were analyzed, together with atmospheric variables, such as air temperature, precipitation, and depth of snow on the ground, observed at the same locations. There was a significant positive trend with soil temperatures in spring and summer means, but not for the winter and annual means. A positive trend with time in soil temperature was detected at about two‐thirds of the stations at all depths below 5 cm. A warming trend of 0.26–0.30°C/decade was consistently detected in spring (March–April–May) at all depths between 1958 and 2008. The warming trend in soil temperatures was associated with trends in air temperatures and snow cover depth over the same period. A significant decreasing trend in snow cover depth in winter and spring was associated with increasing air temperatures. The combined effects of the higher air temperature and reduced snow depth probably resulted in an enhanced increasing trend in spring soil temperatures, but no significant trends in winter soil temperatures. The thermal insulation by snow cover appeared to play an important role in the response of soil temperatures to climate change and must be accounted for in projecting future soil‐related impacts of climate change.
IMILAST Neu, Urs; Akperov, Mirseid G.; Bellenbaum, Nina ...
Bulletin of the American Meteorological Society,
04/2013, Letnik:
94, Številka:
4
Journal Article
Recenzirano
Odprti dostop
The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen ...international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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