scholarly journals Erroneous Arctic Temperature Trends in the ERA-40 Reanalysis: A Closer Look

2011 ◽  
Vol 24 (10) ◽  
pp. 2620-2627 ◽  
Author(s):  
James A. Screen ◽  
Ian Simmonds
Keyword(s):  
Lower Troposphere ◽  
The Arctic ◽  
Extreme Caution ◽  
Scientific Debate ◽  
Weather Forecasts ◽  
Temperature Trends ◽  
Air Temperatures ◽  
Arctic Temperature ◽  
Arctic Climate Change

Abstract Atmospheric reanalyses can be useful tools for examining climate variability and change; however, they must be used cautiously because of time-varying biases that can induce artificial trends. This study explicitly documents a discontinuity in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) that leads to significantly exaggerated warming in the Arctic mid- to lower troposphere, and demonstrates that the continuing use of ERA-40 to study Arctic temperature trends is problematic. The discontinuity occurs in 1997 in response to refined processing of satellite radiances prior to their assimilation into the reanalysis model. It is clearly apparent in comparisons of ERA-40 output against satellite-derived air temperatures, in situ observations, and alternative reanalyses. Decadal or multidecadal Arctic temperature trends calculated over periods that include 1997 are highly inaccurate, particularly below 600 hPa. It is shown that ERA-40 is poorly suited to studying Arctic temperature trends and their vertical profile, and conclusions based upon them must be viewed with extreme caution. Consequently, its future use for this purpose is discouraged. In the context of the wider scientific debate on the suitability of reanalyses for trend analyses, the results show that a series of alternative reanalyses are in broad-scale agreement with observations. Thus, the authors encourage their discerning use instead of ERA-40 for examining Arctic climate change while also reaffirming the importance of verifying reanalyses with observations whenever possible.

Assessment of Temperature and Specific Humidity Inversions and Their Relationships in Three Global Reanalysis Products over the Arctic Ocean

2021 ◽  
Vol 60 (4) ◽  
pp. 493-511
Author(s):  
Liang Chang ◽  
Shiqiang Wen ◽  
Guoping Gao ◽  
Zhen Han ◽  
Guiping Feng ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Specific Humidity ◽  
The Arctic ◽  
Weather Forecasts ◽  
The Arctic Ocean ◽  
Temperature Inversions ◽  
Global Reanalysis ◽  
Less Common Multiple ◽  
Better Than

AbstractCharacteristics of temperature inversions (TIs) and specific humidity inversions (SHIs) and their relationships in three of the latest global reanalyses—the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-I), the Japanese 55-year Reanalysis (JRA-55), and the ERA5—are assessed against in situ radiosonde (RS) measurements from two expeditions over the Arctic Ocean. All reanalyses tend to detect many fewer TI and SHI occurrences, together with much less common multiple TIs and SHIs per profile than are seen in the RS data in summer 2008, winter 2015, and spring 2015. The reanalyses generally depict well the relationships among TI characteristics seen in RS data, except for the TIs below 400 m in summer, as well as above 1000 m in summer and winter. The depth is simulated worst by the reanalyses among the SHI characteristics, which may result from its sensitivity to the uncertainties in specific humidity in the reanalyses. The strongest TI per profile in RS data exhibits more robust dependency on surface conditions than the strongest SHI per profile, and the former is better presented by the reanalyses than the latter. Furthermore, all reanalyses have difficulties simulating the relationships between TIs and SHIs, together with the correlations between the simultaneous inversions. The accuracy and vertical resolution in the reanalyses are both important to properly capture occurrence and characteristics of the Arctic inversions. In general, ERA5 performs better than ERA-I and JRA-55 in depicting the relationships among the TIs. However, the representation of SHIs is more challenging than TIs in all reanalyses over the Arctic Ocean.

scholarly journals Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements

2021 ◽  
Author(s):  
Pia Nielsen-Englyst ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Rasmus T. Tonboe ◽  
Gorm Dybkjær ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Arctic Region ◽  
Satellite Observations ◽  
The Arctic ◽  
Clear Sky ◽  
Ice Surface ◽  
Air Temperatures ◽  
In Situ Observations ◽  
The Arctic Region

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of ice covered areas in the Arctic is heavily under-sampled when it comes to in situ measurements, resulting in large uncertainties in existing weather- and reanalysis products. This paper presents a method for estimating daily mean clear sky 2 meter air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model, which has been tuned against in situ observations to estimate daily mean T2m based on clear sky satellite ice surface skin temperatures. The daily satellite derived T2m product includes estimated uncertainties and covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009, provided on a 0.25 degree regular latitude-longitude grid. Comparisons with independent in situ measured T2m show average biases of 0.30 °C and 0.35 °C and average root mean square errors of 3.47 °C and 3.20 °C for land ice and sea ice, respectively. The associated uncertainties are verified to be very realistic for both land ice and sea ice, using in situ observations. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic, is independent of numerical weather prediction model input and it therefore provides an important supplement to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m derived from satellite and ERA-Interim/ERA5 estimates shows that the T2m derived from satellite observations validate similar or better than ERA-Interim/ERA5 in the Arctic.

scholarly journals In-situ sounding of radiation flux profiles through the Arctic lower troposphere

2018 ◽  
Author(s):  
Ralf Becker ◽  
Marion Maturilli ◽  
Rolf Philipona ◽  
Klaus Behrens
Keyword(s):  
Surface Composition ◽  
Lower Troposphere ◽  
Time Frame ◽  
The Arctic ◽  
Heating Rates ◽  
Heterogeneous Terrain ◽  
Near Surface ◽  
Clear Sky ◽  
Radiation Fluxes

Abstract. In-situ profiles of all four net radiation components were obtained at Ny Ålesund/Svalbard (78.9° N, 11.9° E) in the time frame May 04–21, 2015. Measurements could be performed using adapted high quality instrumentation classified as secondary standard carried by a tethered balloon system. Balloon lifted measurements of albedo under clear sky conditions demonstrate the altitude dependence of this parameter over heterogeneous terrain. Depending on the surface composition within the sensor's footprint, the albedo over predominantly snow covered surfaces was found to decrease to 53.4 % and 35.8 % compared to 73.1 % and 78.8 % measured with near surface references, respectively. Albedo profiles show an all-sky maximum at 150 m above surface level, and an averaged vertical change rate of −2.1 %/100 m (clear sky) and −3.4 %/100 m (overcast) above. Profiling of arctic low-level clouds reveals distinct vertical gradients in all radiation fluxes but longwave upward. Observed radiative cooling at cloud top with heating rates of −53 to −84 K/d in subsequent observations tend to be lower than suggested by 1-D simulations.

Vertical distribution of aerosol particles over the Russian Arctic derived from in-situ aircraft measurements: the September 2020 campaign

2021 ◽  
Author(s):  
Mikhail Yu. Arshinov ◽  
Boris Belan ◽  
Denis Davydov ◽  
Artem Kozlov ◽  
Alexandr Fofonov
Keyword(s):  
Vertical Distribution ◽  
Lower Troposphere ◽  
In Situ Measurements ◽  
The Arctic ◽  
Future Climate Change ◽  
Russian Arctic ◽  
Size Distributions ◽  
Cloudy Weather ◽  
Wide Range

<p>The Arctic is warming much faster than other regions of the globe. In 2020, temperature anomalies in the Russian Arctic reached unprecedented high levels. The atmospheric composition in this key region still remains insufficiently studied that makes difficult predicting future climate change.</p><p>In September 2020, an extensive aircraft campaign was conducted to document the tropospheric composition over the Russian Arctic. The Optik Tu-134 research aircraft was equipped with instruments to carry out in-situ measurements of trace gases and aerosols, as well as with a lidar for profiling of aerosol backscatter. The aircraft flew over a vast area from Arkhangelsk to Anadyr. Six measurement flights with changing altitudes from 0.2 to 9.0 m were conducted over the waters of the Barents, Kara, Laptev, East Siberian, Chukchi, and Bering Seas. The weather was unusually warm for this period of the year, surface air temperatures were above 0°C through the campaign.</p><p>Here, we present the results of in-situ measurements of the vertical distribution of aerosol number concentrations in a wide range of sizes. A modified diffusional particle sizer (DPS) consisted of the Novosibirsk-type eight-stage screen diffusion battery connected to the TSI condensation particle counter Model 3756 was used to determine the number size distribution of particles between 0.003 mm and 0.2 mm (20 size bins). Distribution of particles in the size range from 0.25 µm to 32 µm (31 size bins) was measured by means of the Grimm aerosol spectrometer Model 1.109.</p><p>The flights over Barents and Kara Seas were predominantly performed under clear sky or partly cloudy weather conditions. Number size distributions were wide representing particles of almost all aerosol fractions. When flying in the upper troposphere with a constant altitude over these seas, some cases of enhanced concentrations of nucleation and Aitken mode particles comparable to ones in the lower troposphere were recorded, suggesting in situ new particle formation was likely to be taking place via gas-to-particle conversion aloft.</p><p>East of the Kara Sea, flights were conducted under mostly cloudy conditions resulting in a lower median aerosol number concentration and narrower size distributions.</p><p>This work was supported by the Russian Foundation for Basic Research (Grant No. 19-05-50024).</p>

scholarly journals The emergence of surface-based Arctic amplification

2009 ◽  
Vol 3 (1) ◽  
pp. 11-19 ◽  
Author(s):  
M. C. Serreze ◽  
A. P. Barrett ◽  
J. C. Stroeve ◽  
D. N. Kindig ◽  
M. M. Holland
Keyword(s):  
Sea Ice ◽  
21St Century ◽  
Lower Troposphere ◽  
Cold Season ◽  
The Arctic ◽  
Arctic Amplification ◽  
Sea Ice Extent ◽  
Air Temperatures ◽  
The Arctic Ocean ◽  
Heat Transfers

Abstract. Rises in surface and lower troposphere air temperatures through the 21st century are projected to be especially pronounced over the Arctic Ocean during the cold season. This Arctic amplification is largely driven by loss of the sea ice cover, allowing for strong heat transfers from the ocean to the atmosphere. Consistent with observed reductions in sea ice extent, fields from both the NCEP/NCAR and JRA-25 reanalyses point to emergence of surface-based Arctic amplification in the last decade.

scholarly journals The Intraseasonal and Interannual Variability of Arctic Temperature and Specific Humidity Inversions

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 214 ◽  
Author(s):  
Lejiang Yu ◽  
Qinghua Yang ◽  
Mingyu Zhou ◽  
Xubin Zeng ◽  
Donald H. Lenschow ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Lower Troposphere ◽  
Specific Humidity ◽  
The Arctic ◽  
Self Organizing Map ◽  
Eastern Hemisphere ◽  
Temperature And Humidity ◽  
Arctic Temperature

Temperature and humidity inversions are common in the Arctic’s lower troposphere, and are a crucial component of the Arctic’s climate system. In this study, we quantify the intraseasonal oscillation of Arctic temperature and specific humidity inversions and investigate its interannual variability using data from the Surface Heat Balance of the Arctic (SHEBA) experiment from October 1997 to September 1998 and the European Centre for Medium-Range Forecasts (ECMWF) Reanalysis (ERA)-interim for the 1979–2017 period. In January 1998, there were two noticeable elevated inversions and one surface inversion. The transitions between elevated and surface-based inversions were associated with the intraseasonal variability of the temperature and humidity differences between 850 and 950 hPa. The self-organizing map (SOM) technique is utilized to obtain the main modes of surface and elevated temperature and humidity inversions on intraseasonal time scales. Low (high) pressure and more (less) cloud cover are related to elevated (surface) temperature and humidity inversions. The frequency of strong (weak) elevated inversions over the eastern hemisphere has decreased (increased) in the past three decades. The wintertime Arctic Oscillation (AO) and Arctic Dipole (AD) during their positive phases have a significant effect on the occurrence of surface and elevated inversions for two Nodes only.

scholarly journals In situ sounding of radiative flux profiles through the Arctic lower troposphere

2020 ◽  
Vol 1 (2) ◽  
pp. 155-177
Author(s):  
Ralf Becker ◽  
Marion Maturilli ◽  
Rolf Philipona ◽  
Klaus Behrens
Keyword(s):  
Lower Troposphere ◽  
Radiative Flux ◽  
The Arctic

scholarly journals Evaluation of 2-m Air Temperature and Surface Temperature from ERA5 and ERA-I Using Buoy Observations in the Arctic during 2010–2020

2021 ◽  
Vol 13 (14) ◽  
pp. 2813
Author(s):  
Yining Yu ◽  
Wanxin Xiao ◽  
Zhilun Zhang ◽  
Xiao Cheng ◽  
Fengming Hui ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Weather Forecasts ◽  
Ice Concentration ◽  
Medium Range ◽  
In Situ Observations ◽  
Two Temperature

In data-sparse regions such as the Arctic, atmospheric reanalysis is one of the key tools for understanding rapid climate change at the regional and global scales. The utility of reanalysis datasets based on data assimilation is affected by their accuracy and biases. Therefore, it is important to evaluate their performance. Here, we conduct inter-comparisons of two temperature variables, namely, the 2-m air temperature (Ta) and the surface temperature (Ts), from the widely used ERA-I and ERA5 reanalysis datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) against in situ observations from three international buoy programs (i.e., the International Arctic Buoy Programme (IABP), the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC), and the Cold Regions Research and Engineering Laboratory (CRREL)) during 2010–2020 in the Arctic. Overall, the results show that both the ERA-I and ERA5 were well correlated with the buoy observations, with the highest correlation coefficient reaching 0.98. There were generally warm Ta biases for both ERA-I (2.27 ± 3.33 °C) and ERA5 (2.34 ± 3.22 °C) when compared with more than 3000 matching pairs of daily buoy observations. The warm Ta biases of both reanalysis datasets exhibited seasonal variations, reaching the maximum of 3.73 ± 2.84 °C in April and the minimum of 1.36 ± 2.51 °C in September. For Ts, both ERA-I and ERA5 exhibited good consistencies with the buoy observations, but have higher amplitude biases compared with those for Ta, with generally negative biases of −4.79 ± 4.86 °C for ERA-I and −4.11 ± 3.92 °C for ERA5. For both reanalysis datasets, the largest bias of Ts (−11.18 ± 3.08 °C) occurred in December, while the biases were rather small (less than −3 °C) in the warmer months (April to October). The cold Ts biases for ERA-I and ERA5 were probably overestimated due to the location of the surface temperature sensors on the buoys, which may have been affected by snow cover. Both the Ta and Ts biases varied for different buoy programs and different sea ice concentration conditions, yet they exhibited similar trends.

scholarly journals Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements

2019 ◽  
Author(s):  
Pia Nielsen-Englyst ◽  
Jacob L. Høyer ◽  
Kristine S. Madsen ◽  
Rasmus T. Tonboe ◽  
Gorm Dybkjær
Keyword(s):  
Surface Temperature ◽  
Arctic Region ◽  
Satellite Observations ◽  
The Arctic ◽  
Ice Surface ◽  
Air Temperatures ◽  
In Situ Observations ◽  
The Arctic Region ◽  
Snow And Ice

Abstract. The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic, ice covered areas is heavily under-sampled when it comes to in situ measurements, and large uncertainties exist in weather- and reanalysis products. This paper presents a method for estimating daily mean 2 meter air temperatures (T2m) in the Arctic from satellite observations of skin temperature, using the Arctic and Antarctic ice Surface Temperatures from thermal Infrared (AASTI) satellite dataset, providing spatially detailed observations of the Arctic. The method is based on a linear regression model which has been developed using in situ observations and daily mean satellite ice surface skin temperatures combined with a seasonal variation to estimate daily T2m. The satellite derived T2m product including estimated uncertainties covers clear sky snow and ice surfaces in the Arctic region during the period 2000–2009. Comparison with independent in situ measured T2m gives average correlations of 95.5 % and 96.5 % and average root mean square errors of 3.47 °C and 3.19 °C for land ice and sea ice, respectively. The reconstruction provides a much better spatial coverage than the sparse in situ observations of T2m in the Arctic, is independent of numerical weather prediction model input and it therefore provides an important alternative to simulated air temperatures to be used for assimilation or global surface temperature reconstructions. A comparison between in situ T2m versus T2m from satellite and ERA-Interim shows that the T2m derived from satellite observations validate similar or better than ERA-Interim estimates in the Arctic.

scholarly journals The Influence of Changes in Cloud Cover on Recent Surface Temperature Trends in the Arctic

2008 ◽  
Vol 21 (4) ◽  
pp. 705-715 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key ◽  
Xuanji Wang
Keyword(s):  
Surface Temperature ◽  
Cloud Cover ◽  
Temperature Trend ◽  
The Arctic ◽  
Surface Warming ◽  
Weather Forecasts ◽  
Temperature Trends ◽  
Four Seasons ◽  
Sky Conditions ◽  
Arctic Surface

Abstract A method is presented to assess the influence of changes in Arctic cloud cover on the surface temperature trend, allowing for a more robust diagnosis of causes for surface warming or cooling. Seasonal trends in satellite-derived Arctic surface temperature under clear-, cloudy-, and all-sky conditions are examined for the period 1982–2004. The satellite-derived trends are in good agreement with trends in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product and surface-based weather station measurements in the Arctic. Surface temperature trends under clear and cloudy conditions have patterns similar to the all-sky trends, though the magnitude of the trends under cloudy conditions is smaller than those under clear-sky conditions, illustrating the negative feedback of clouds on the surface temperature trends. The all-sky surface temperature trend is divided into two parts: the first part is a linear combination of the surface temperature trends under clear and cloudy conditions; the second part is caused by changes in cloud cover as a function of the clear–cloudy surface temperature difference. The relative importance of these two components is different in the four seasons, with the first part more important in spring, summer, and autumn, but with both parts being equally important in winter. The contribution of biases in satellite retrievals is also evaluated.

Sign in / Sign up

Export Citation Format

Share Document