scholarly journals Striking Seasonality in the Secular Warming of the Northern Continents: Structure and Mechanisms

2017 ◽  
Vol 30 (16) ◽  
pp. 6521-6541 ◽  
Author(s):  
Sumant Nigam ◽  
Natalie P. Thomas ◽  
Alfredo Ruiz-Barradas ◽  
Scott J. Weaver
Keyword(s):  
Twentieth Century ◽  
Land Surface ◽  
Climate Models ◽  
Linear Trend ◽  
Surface Air Temperature ◽  
Cost Effective ◽  
Secular Change ◽  
Radiative Energy ◽  
Intergovernmental Panel ◽  
Climate Simulations

The linear trend in twentieth-century surface air temperature (SAT)—a key secular warming signal—exhibits striking seasonal variations over Northern Hemisphere continents; SAT trends are pronounced in winter and spring but notably weaker in summer and fall. The SAT trends in historical twentieth-century climate simulations informing the Intergovernmental Panel for Climate Change’s Fifth Assessment show varied (and often unrealistic) strength and structure, and markedly weaker seasonal variation. The large intra-ensemble spread of winter SAT trends in some historical simulations was surprising, especially in the context of century-long linear trends, with implications for the detection of the secular warming signal. The striking seasonality of observed secular warming over northern continents warrants an explanation and the representation of related processes in climate models. Here, the seasonality of SAT trends over North America is shown to result from land surface–hydroclimate interactions and, to an extent, also from the secular change in low-level atmospheric circulation and related thermal advection. It is argued that the winter dormancy and summer vigor of the hydrologic cycle over middle- to high-latitude continents permit different responses to the additional incident radiative energy from increasing greenhouse gas concentrations. The seasonal cycle of climate, despite its monotony, provides an expanded phase space for the exposition of the dynamical and thermodynamical processes generating secular warming, and an exceptional cost-effective opportunity for benchmarking climate projection models.

Twentieth-Century Surface Air Temperature over China and the Globe Simulated by Coupled Climate Models

2006 ◽  
Vol 19 (22) ◽  
pp. 5843-5858 ◽  
Author(s):  
Tianjun Zhou ◽  
Rucong Yu
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
Air Temperature ◽  
Climate Models ◽  
Eastern China ◽  
Surface Air Temperature ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Coupled Climate Models ◽  
Anthropogenic Forcings

Abstract This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations.

scholarly journals Performance of Land Surface Schemes in the WRF Model for Climate Simulations over the MENA-CORDEX Domain

2020 ◽  
Vol 4 (4) ◽  
pp. 647-665
Author(s):  
Katiana Constantinidou ◽  
Panos Hadjinicolaou ◽  
George Zittis ◽  
Jos Lelieveld
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Linear Trend ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Mena Region ◽  
Surface Climate ◽  
Climate Simulations ◽  
Realistic Representation

AbstractLand–atmosphere interactions need to be optimally represented in climate models for the realistic representation of past and future climate. In this work, six different versions of land surface schemes (LSS) are used to simulate the climate over the Middle East–North Africa (MENA) region for the period 2000–2010 with a horizontal resolution of 0.44°, using the Weather Research and Forecasting (WRF) model. The monthly time series output is evaluated against observations for several surface climate variables using statistical metrics (climatology, 5th and 95th percentiles, standard deviation, linear trend) and Taylor diagrams. The resulting biases are presented for the whole MENA domain as well as 7 sub-domains. A ranking procedure objectively retrieves a performance spectrum among the schemes. The LSS that is closest to observations and is, therefore, considered as the best performing is Noah, followed by its augmented version (NoahMP). For these simulations at the relatively coarse horizontal resolution of 50 km, the more elaborate LSSs are not performing very well. These results are useful for the choice of LSS in climate change modelling of the MENA-CORDEX as a whole, as well as its sub-regions.

scholarly journals Twentieth-Century Climate Change over Africa: Seasonal Hydroclimate Trends and Sahara Desert Expansion

2018 ◽  
Vol 31 (9) ◽  
pp. 3349-3370 ◽  
Author(s):  
Natalie Thomas ◽  
Sumant Nigam
Keyword(s):  
Twentieth Century ◽  
Source Region ◽  
Surface Air Temperature ◽  
Rain Gauge ◽  
Mitigation Strategies ◽  
Annual Rainfall ◽  
Sahara Desert ◽  
Seasonal Temperature ◽  
African Continent ◽  
Climate Simulations

Twentieth-century trends in seasonal temperature and precipitation over the African continent are analyzed from observational datasets and historical climate simulations. Given the agricultural economy of the continent, a seasonal perspective is adopted as it is more pertinent than an annual-average one, which can mask offsetting but agriculturally sensitive seasonal hydroclimate variations. Examination of linear trends in seasonal surface air temperature (SAT) shows that heat stress has increased in several regions, including Sudan and northern Africa where the largest SAT trends occur in the warm season. Broadly speaking, the northern continent has warmed more than the southern one in all seasons. Precipitation trends are varied but notable declining trends are found in the countries along the Gulf of Guinea, especially in the source region of the Niger River in West Africa, and in the Congo River basin. Rainfall over the African Great Lakes—one of the largest freshwater repositories—has, however, increased. It is shown that the Sahara Desert has expanded significantly over the twentieth century, by 11%–18% depending on the season, and by 10% when defined using annual rainfall. The expansion rate is sensitively dependent on the analysis period in view of the multidecadal periods of desert expansion (including from the drying of the Sahel in the 1950s–80s) and contraction in the 1902–2013 record, and the stability of the rain gauge network. The desert expanded southward in summer, reflecting retreat of the northern edge of the Sahel rainfall belt, and to the north in winter, indicating potential impact of the widening of the tropics. Specific mechanisms for the expansion are investigated. Finally, this observational analysis is used to evaluate the state-of-the-art climate simulations from a comparison of the twentieth-century hydroclimate trends. The evaluation shows that modeling regional hydroclimate change over the African continent remains challenging, warranting caution in the development of adaptation and mitigation strategies.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

scholarly journals The Pliocene Model Intercomparison Project Phase 2: large-scale climate features and climate sensitivity

2020 ◽  
Vol 16 (6) ◽  
pp. 2095-2123 ◽  
Author(s):  
Alan M. Haywood ◽  
Julia C. Tindall ◽  
Harry J. Dowsett ◽  
Aisling M. Dolan ◽  
Kevin M. Foley ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Large Scale ◽  
Climate Models ◽  
Temperature Response ◽  
Surface Air Temperature ◽  
System Response ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Intergovernmental Panel ◽  
Intercomparison Project

Abstract. The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

scholarly journals Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Zhenchun Hao ◽  
Qin Ju ◽  
Weijuan Jiang ◽  
Changjun Zhu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Surface Air Temperature ◽  
Global Climate Models ◽  
The Tibetan Plateau ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Ipcc Ar4

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least.

scholarly journals Intrinsic versus Forced Variation in Coupled Climate Model Simulations over the Arctic during the Twentieth Century*

2007 ◽  
Vol 20 (6) ◽  
pp. 1093-1107 ◽  
Author(s):  
Muyin Wang ◽  
James E. Overland ◽  
Vladimir Kattsov ◽  
John E. Walsh ◽  
Xiangdong Zhang ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Land Surface ◽  
General Circulation ◽  
Climate Model ◽  
General Circulation Models ◽  
Performance Criteria ◽  
The Arctic ◽  
Temperature Record ◽  
Coupled Models ◽  
Intergovernmental Panel

Abstract There were two major multiyear, Arctic-wide (60°–90°N) warm anomalies (>0.7°C) in land surface air temperature (LSAT) during the twentieth century, between 1920 and 1950 and again at the end of the century after 1979. Reproducing this decadal and longer variability in coupled general circulation models (GCMs) is a critical test for understanding processes in the Arctic climate system and increasing the confidence in the Intergovernmental Panel on Climate Change (IPCC) model projections. This study evaluated 63 realizations generated by 20 coupled GCMs made available for the IPCC Fourth Assessment for their twentieth-century climate in coupled models (20C3M) and corresponding control runs (PIcntrl). Warm anomalies in the Arctic during the last two decades are reproduced by all ensemble members, with considerable variability in amplitude among models. In contrast, only eight models generated warm anomaly amplitude of at least two-thirds of the observed midcentury warm event in at least one realization, but not its timing. The durations of the midcentury warm events in all the models are decadal, while that of the observed was interdecadal. The variance of the control runs in nine models was comparable with the variance in the observations. The random timing of midcentury warm anomalies in 20C3M simulations and the similar variance of the control runs in about half of the models suggest that the observed midcentury warm period is consistent with intrinsic climate variability. Five models were considered to compare somewhat favorably to Arctic observations in both matching the variance of the observed temperature record in their control runs and representing the decadal mean temperature anomaly amplitude in their 20C3M simulations. Seven additional models could be given further consideration. Results support selecting a subset of GCMs when making predictions for future climate by using performance criteria based on comparison with retrospective data.

scholarly journals Failure analysis of parameter-induced simulation crashes in climate models

2013 ◽  
Vol 6 (4) ◽  
pp. 1157-1171 ◽  
Author(s):  
D. D. Lucas ◽  
R. Klein ◽  
J. Tannahill ◽  
D. Ivanova ◽  
S. Brandon ◽  
...  
Keyword(s):  
Climate Models ◽  
Ocean Model ◽  
Support Vector ◽  
Parameter Uncertainties ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Climate Simulations ◽  
Class Climate ◽  
Predicted Model ◽  
Parameter Values

Abstract. Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Differing Responses of the Diurnal Cycle of Land Surface and Air Temperatures to Deforestation

2019 ◽  
Vol 32 (20) ◽  
pp. 7067-7079 ◽  
Author(s):  
Liang Chen ◽  
Paul A. Dirmeyer
Keyword(s):  
Land Cover ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Daily Maximum ◽  
Near Surface ◽  
Diurnal Cycles ◽  
Air Temperatures ◽  
Temperature Responses

ABSTRACT Recent studies have shown the impacts of historical land-use land-cover changes (i.e., deforestation) on hot temperature extremes; contradictory temperature responses have been found between studies using observations and climate models. However, different characterizations of surface temperature are sometimes used in the assessments: land surface skin temperature Ts is more commonly used in observation-based studies while near-surface air temperature T2m is more often used in model-based studies. The inconsistent use of temperature variables is not inconsequential, and the relationship between deforestation and various temperature changes can be entangled, which complicates comparisons between observations and model simulations. In this study, the responses in the diurnal cycle of summertime Ts and T2m to deforestation are investigated using the Community Earth System Model. For the daily maximum, opposite responses are found in Ts and T2m. Due to decreased surface roughness after deforestation, the heat at the land surface cannot be efficiently dissipated into the air, leading to a warmer surface but cooler air. For the daily minimum, strong warming is found in T2m, which exceeds daytime cooling and leads to overall warming in daily mean temperatures. After comparing several climate models, we find that the models agree in daytime land surface (Ts) warming, but different turbulent transfer characteristics produce discrepancies in T2m. Our work highlights the need to investigate the diurnal cycles of temperature responses carefully in land-cover change studies. Furthermore, consistent consideration of temperature variables should be applied in future comparisons involving observations and climate models.

scholarly journals Different response of surface temperature and air temperature to deforestation in climate models

2018 ◽  
Author(s):  
Johannes Winckler ◽  
Christian H. Reick ◽  
Sebastiaan Luyssaert ◽  
Alessandro Cescatti ◽  
Paul C. Stoy ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Model Comparison ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Atmospheric Layer ◽  
Nonlocal Effects ◽  
Local Effects ◽  
Near Surface

Abstract. Deforestation affects temperatures at the land surface and higher up in the atmosphere. Satellite-based observations typically register deforestation-induced changes in surface temperature, in-situ observations register changes in near-surface air temperature, and climate models simulate changes in both temperatures and the temperature of the lowest atmospheric layer. Yet a focused analysis of how these variables respond differently to deforestation is missing. Here, this is investigated by analyzing the biogeophysical temperature effects of large-scale deforestation in the climate model MPI-ESM, separately for local effects (which are only apparent at the location of deforestation) and nonlocal effects (which are also apparent elsewhere). While the nonlocal effects affect the temperature of the surface and lowest atmospheric layer equally, the local effects mainly affect the temperature of the surface. In agreement with observation-based studies, the local effects on surface and near-surface air temperature respond differently in the MPI-ESM, both concerning the magnitude of local temperature changes and the latitude at which the local deforestation effects turn from a cooling to a warming (at 45–55° N for surface temperature and around 35° N for near-surface air temperature). An inter-model comparison shows that in the northern mid latitudes, both for summer and winter, near-surface air temperature is affected by the 5local effects only about half as much compared to surface temperature. Thus, studies about the biogeophysical effects of deforestation must carefully choose which temperature they consider.

Sign in / Sign up

Export Citation Format

Share Document