Can climate models capture the high amplitudes circumglobal waves and their surface imprints?  

2021 ◽  
Author(s):  
Fei Luo ◽  
Kai Kornhuber ◽  
Frank Selten ◽  
Dim Coumou
Keyword(s):  
Soil Moisture ◽  
Climate Models ◽  
Phase Locking ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
Circulation Types ◽  
Temperature And Precipitation ◽  
Wave Patterns ◽  
Precipitation Anomalies ◽  
June July

<p>Pronounced circumglobal waves can trigger and maintain persistent summer weather conditions by remaining in their preferred phase-locked positions for several weeks in a row. This phenomenon, especially important for wave numbers 5 and 7, has been observed in recent years, but it is unclear whether climate models can reproduce circulation types and their surface imprints.</p><p>Here we assess three climate models (EC-Earth3, CESM1.2, and MIROC5)  for their representation of amplified circumglobal waves and associated surface imprints in summer (June, July and August) over 1979-2016. ERA5 reanalysis data is used as reference to assess the models’ performance. We run a series of modeling experiments to understand the source of biases in the climate models: free interactive atmosphere and soil moisture runs (AISI), atmospheric nudged runs (AFSI), soil moisture prescribed runs (AISF), and both atmosphere and soil moisture nudged experiments (AFSF).</p><p>We show that all models reasonably well reproduce the climatological wave spectra. Further, both wave 5 and wave 7 are found to exhibit phase-locking behaviors across all models, resulting in similar wave patterns across the hemisphere as compared to reanalysis. The surface imprints are observed in the models as well, but depending on the model, the results vary in strength. We also found the biases in surface temperature and precipitation anomalies mainly come from the atmospheric circulation in the models as these biases reduced considerably from AISI runs to AFSI and AFSF runs where upper atmosphere levels were nudged. Nudging soil moisture also minimizes some biases in the models but not as obvious as nudging the atmosphere. </p><div> <div> <div> </div> </div> </div>

New method to detect and quantify weather persistence associated with hydro-climatic extremes

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Jascha Lehmann ◽  
Bijan Fallah ◽  
Fred Hattermann
Keyword(s):  
Climate Models ◽  
Heat Waves ◽  
Weather Conditions ◽  
Reanalysis Data ◽  
New Method ◽  
Climate Projections ◽  
Weather Extremes ◽  
Weather Patterns ◽  
Temperature And Precipitation ◽  
Height Fields

<p>Changes in weather persistence are of particular concern in the context of climate change as periods of longer persistence can reinforce weather extremes. In our study we apply structural image recognition methods to global ERA5 reanalysis data to identify when, where and how long isolines of atmospheric geopotential height fields run in similar tracks. We identify regions and episodes around the world in which, retrospectively, unusually long-lasting weather patterns repeatedly occurred. Concerning the temperature and precipitation meteorological fields, we derive a connection between the occurrence of weather persistence and hydro-climatic extreme events.</p><p>Based on our new method we find that weather persistence has been particularly increasing in Northern Hemisphere mid-latitudes in summer confirming earlier studies. Here, highly populated regions like Central Europe have experienced long-term increases in persistent weather conditions of up to 4-5% between 1981 and 2019 amplifying the risk of prolonged heat waves and droughts. Further, we show that climate models tend to have difficulties in capturing the dynamics of weather persistence and thus may severely underestimate the frequency and magnitude of future extremes events in their climate projections.</p>

scholarly journals Arctic hydroclimate variability during the last 2000 years – current understanding and research challenges

2017 ◽  
Author(s):  
Hans W. Linderholm ◽  
Marie Nicolle ◽  
Pierre Francus ◽  
Konrad Gajewski ◽  
Samuli Helama ◽  
...  
Keyword(s):  
North America ◽  
Climate Models ◽  
Reanalysis Data ◽  
Current Understanding ◽  
Ice Age ◽  
The Arctic ◽  
Oceanic Circulation ◽  
Natural Ecosystems ◽  
Temperature And Precipitation ◽  
Hydroclimate Variability

Abstract. Along with Arctic amplification, changes in Arctic hydroclimate have become increasingly apparent. Reanalysis data show increasing trends in Arctic temperature and precipitation over the 20th century, but changes are not homogenous across seasons or space. The observed hydroclimate changes are expected to continue, and possibly accelerate, in the coming century, not only affecting pan-Arctic natural ecosystems and human activities, but also lower latitudes through changes in atmospheric and oceanic circulation. However, a lack of spatiotemporal observational data makes reliable quantification of Arctic hydroclimate change difficult, especially in a long-term context. To understand hydroclimate variability and the mechanisms driving observed changes, beyond the instrumental record, climate proxies are needed. Here we bring together the current understanding of Arctic hydroclimate during the past 2000 years, as inferred from natural archives and proxies and palaeoclimate model simulations. Inadequate proxy data coverage is apparent, with distinct data gaps in most of Eurasia and parts of North America, which makes robust assessments for the whole Arctic currently impossible. Hydroclimate proxies and climate models indicate that the Medieval Climate Anomaly (MCA) was anomalously wet, while conditions were in general drier during the Little Ice Age (LIA), relative to the last 2000 years. However, it is clear that there are large regional differences, which are especially evident during the LIA. Due to the spatiotemporal differences in Arctic hydroclimate, we recommend detailed regional studies, e.g. including field reconstructions, to disentangle spatial patterns and potential forcing factors. At present, it is only possible to carry out regional syntheses for a few areas of the Arctic, e.g. Fennoscandia, Greenland and western North America. To fully assess pan-Arctic hydroclimate variability for the last two millennia additional proxy records are required.

scholarly journals Snowfall in the Himalayas: an uncertain future from a little-known past

2015 ◽  
Vol 9 (3) ◽  
pp. 1147-1167 ◽  
Author(s):  
E. Viste ◽  
A. Sorteberg
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Reanalysis Data ◽  
Indus Basin ◽  
Data Sets ◽  
Anthropogenic Forcing ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Uncertain Future ◽  
Relative Change

Abstract. Snow and ice provide large amounts of meltwater to the Indus, Ganges and Brahmaputra rivers. This study combines present-day observations and reanalysis data with climate model projections to estimate the amount of snow falling over the basins today and in the last decades of the 21st century. Estimates of present-day snowfall based on a combination of temperature and precipitation from reanalysis data and observations vary by factors of 2–4. The spread is large, not just between the reanalysis and the observations but also between the different observational data sets. With the strongest anthropogenic forcing scenario (RCP8.5), the climate models project reductions in annual snowfall by 30–50% in the Indus Basin, 50–60% in the Ganges Basin and 50–70% in the Brahmaputra Basin by 2071–2100. The reduction is due to increasing temperatures, as the mean of the models show constant or increasing precipitation throughout the year in most of the region. With the strongest anthropogenic forcing scenario, the mean elevation where rain changes to snow – the rain/snow line – creeps upward by 400–900 m, in most of the region by 700–900 meters. The largest relative change in snowfall is seen in the upper westernmost sub-basins of the Brahmaputra. With the strongest forcing scenario, most of this region will have temperatures above freezing, especially in the summer. The projected reduction in annual snowfall is 65–75%. In the upper Indus, the effect of a warmer climate on snowfall is less extreme, as most of the terrain is high enough to have temperatures sufficiently far below freezing today. A 20–40% reduction in annual snowfall is projected.

scholarly journals North Atlantic midwinter storm track suppression and the European weather response in ERA5 reanalysis

2021 ◽  
Author(s):  
Estefania Montoya Duque ◽  
Frank Lunkeit ◽  
Richard Blender
Keyword(s):  
North Atlantic ◽  
Large Scale ◽  
Storm Track ◽  
Reanalysis Data ◽  
Band Pass Filter ◽  
Pass Filter ◽  
The North ◽  
Temperature And Precipitation ◽  
Precipitation Increase ◽  
Precipitation Anomalies

AbstractIn this study, we analyse the influence of North Atlantic midwinter storm track suppressions on European synoptic temperature and precipitation anomalies to determine the large-scale conditions relevant for the so-called Christmas thaw. We diagnose this relation in daily ERA5 reanalysis data in the spatial resolution of 0.25∘ between 1979 and 2018. To access synoptic time scales, a 3–10-day band-pass filter is applied. An index for the suppression is defined by the upper tropospheric Eddy Kinetic Energy (EKE) anomalies in the North Atlantic. We define the strong jet stream years as the year exceeding the 75% of the winter seasonal values at 250 hPa. In winters with strong jet activity, the storm track suppression is found, in agreement with the barotropic governor mechanism. Composites of European surface temperature and precipitation for low index values reveal weakly warmer conditions during winter (DJF) in Central Europe and the British Isles and a distinct cooling in Northern Europe. In the 1-month interval during December 15 to January 15, the warming is more pronounced. The clearest signal is the precipitation increase with a magnitude of 1 mm/day in the Mediterranean region.

scholarly journals Snowfall in the Himalayas: an uncertain future from a little-known past

2015 ◽  
Vol 9 (1) ◽  
pp. 441-493 ◽  
Author(s):  
E. Viste ◽  
A. Sorteberg
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Reanalysis Data ◽  
Indus Basin ◽  
Data Sets ◽  
Anthropogenic Forcing ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Uncertain Future ◽  
Relative Change

Abstract. Snow and ice provide large amounts of meltwater to the Indus, Ganges and Brahmaputra rivers. This study combines present-day observations and reanalysis data with climate model projections to estimate the amount of snow falling over the basins today and in the last decades of the 21st century. Estimates of present-day snowfall based on a combination of temperature and precipitation from reanalysis data and observations, vary by factors of 2–4. The spread is large, not just between the reanalysis and the observations, but also between the different observational data sets. With the strongest anthropogenic forcing scenario (RCP 8.5), the climate models project reductions in annual snowfall by 30–50% in the Indus Basin, 50–60% in the Ganges Basin and 50–70% in the Brahmaputra Basin, by 2071–2100. The reduction is due to increasing temperatures, as the mean of the models show constant or increasing precipitation throughout the year in most of the region. With the strongest anthropogenic forcing scenario, the mean elevation where rain changes to snow – the rain/snow line – creeps upward by 400–900 m, in most of the region by 700–900 m. The largest relative change in snowfall is seen in the upper, westernmost sub-basins of the Brahmaputra. With the strongest forcing scenario, most of this region will have temperatures above freezing, especially in the summer. The projected reduction in annual snowfall is 65–75%. In the upper Indus, the effect of a warmer climate on snowfall is less extreme, as most of the terrain is high enough to have temperatures sufficiently far below freezing today. A 20–40% reduction in annual snowfall is projected.

scholarly journals DAPS 2nd Workshop Presentation: Assessing the impact of 1815 Tambora volcanic eruption on surface temperature and precipitation variabilities in Indonesia using MPI-ESM simulation outputs

2019 ◽  
Author(s):  
Hana Camelia ◽  
Sandy Hardian Susanto Herho ◽  
Muhammad Ridho Syahputra ◽  
Rusmawan Suwarman
Keyword(s):  
Surface Temperature ◽  
Reanalysis Data ◽  
Precipitation Anomaly ◽  
Observation Data ◽  
Max Planck ◽  
Temperature And Precipitation ◽  
Workshop Presentation ◽  
June July ◽  
Precipitation Changes ◽  
The Impact

The impact of the eruption of Mount Tambora in 1815 on meteorological parameters in Indonesia is not widely known because of the absence of weather observation data at that time. In this study we examine the impact of the eruption in Indonesia by using one of the Max-Planck Institute Earth System Model (MPI-ESM) simulation output scenarios which previously selected by comparing it to the proxy data δ^18 O of the Porites sp. coral. This study examines the impacts of temperature and precipitation variability in the period of June-July-August (JJA) and December-February-January (DJF). The δ^18 O data is compared with the reanalysis data to see whether the δ^18 O data is capable of recording temperature and precipitation changes or not. The model data is then compared with the δ^18 O data to see the consistency between them. Consistency analysis is performed to select the most representative model scenario. In addition, a comparison of the Niño 3.4 index from proxy reconstruction data with the Niño 3.4 index which was derived from the model to analyze the effect of ENSO on the occurrence and after Tambora eruption. The model simulations show well consistency over surface temperature during JJA, but has not been able to accurately describe the precipitation anomaly after the eruption. Based on the simulation results, the eruption of Mount Tambora in 1815 caused a decrease in temperature of 0.4-1°C in Indonesia in 1816-1817 and the temperature returned to normal in the years after.

scholarly journals The Representation of the Southern Annular Mode Signal in the Brazilian Earth System Model

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1045
Author(s):  
Luciana F. Prado ◽  
Ilana Wainer ◽  
Ronald B. de Souza
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Coupled Modeling ◽  
Annular Mode ◽  
Temperature And Precipitation

The Southern Annular Mode (SAM, also known as the Antarctic Oscillation—AAO) explains most of the climate variability in the Southern Hemisphere. A ring pattern in mean sea level pressure (MSLP) or 500 hPa geopotential height around Antarctica characterizes SAM. Differences of MSLP values between SH mid and high latitudes define positive and negative SAM phases with impacts on mean atmospheric circulation. Thus, investigating how different models represent SAM is of paramount importance, as it can improve their ability to describe or even predict most of the SH climate variability. Here we examine how the Brazilian Earth System Model (BESM) represents SAM’s signal compared with observations, reanalysis, and other climate models contributing to the Coupled Modeling Intercomparison Project version 5 (CMIP5). We also evaluate how SAM relates to the South American surface temperature and precipitation and discuss the models’ limitations and biases compared with reanalysis data.

scholarly journals Interannual Coupling between Summertime Surface Temperature and Precipitation over Land: Processes and Implications for Climate Change*

2015 ◽  
Vol 28 (3) ◽  
pp. 1308-1328 ◽  
Author(s):  
Alexis Berg ◽  
Benjamin R. Lintner ◽  
Kirsten Findell ◽  
Sonia I. Seneviratne ◽  
Bart van den Hurk ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Time Scales ◽  
Land Surface ◽  
Climate Models ◽  
Negative Temperature ◽  
Seasonal Temperature ◽  
Near Surface ◽  
Temperature And Precipitation

Abstract Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture–atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature–precipitation correlations using simulations from the Global Land–Atmosphere Coupling Experiment–phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950–2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture–atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature–precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature–precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture–atmosphere interactions.

scholarly journals High-Resolution Future Projections of Temperature and Precipitation in the Canary Islands

2015 ◽  
Vol 28 (19) ◽  
pp. 7846-7856 ◽  
Author(s):  
Francisco J. Expósito ◽  
Albano González ◽  
Juan C. Pérez ◽  
Juan P. Díaz ◽  
David Taima
Keyword(s):  
Soil Moisture ◽  
Canary Islands ◽  
Climate Models ◽  
Global Climate ◽  
Statistical Significance ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Reanalysis Dataset ◽  
Temperature And Precipitation

Abstract The complex orography of the Canary Islands favors the creation of microclimates, which cannot be studied using global climate models or regional models with moderate resolution. In this work, WRF is used to perform a dynamic climate regionalization in the archipelago, using the pseudo–global warming technique to compute the initial and boundary conditions from a reanalysis dataset and from results of 14 global climate models. The simulations were performed for three decades, one at present (1995–2004) and two in the future (2045–54 and 2090–99), and for two different greenhouse gas scenarios (RCP4.5 and RCP8.5), defined in phase 5 of the Coupled Model Intercomparison Project. The obtained results, at a 5-km horizontal resolution, show a clear dependence of temperature increase with height and a positive change in diurnal temperature range, which is mainly due to a reduction in soil moisture and a slight decrease in cloud cover. This negative change in soil moisture is mainly a consequence of a decrease in precipitation, although the evaluation of simulated reduction in precipitation does not show statistical significance in most of the Canary Islands for the analyzed periods and scenarios.

scholarly journals Responses of Hydrological Processes under Different Shared Socioeconomic Pathway Scenarios in the Huaihe River Basin, China

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1053
Author(s):  
Yuan Yao ◽  
Wei Qu ◽  
Jingxuan Lu ◽  
Hui Cheng ◽  
Zhiguo Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Climate Models ◽  
Global Climate Models ◽  
Hydrological Response ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Infiltration Capacity ◽  
Change Analysis ◽  
Average Annual Runoff

The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides more scenarios and reliable climate change results for improving the accuracy of future hydrological parameter change analysis. This study uses five CMIP6 global climate models (GCMs) to drive the variable infiltration capacity (VIC) model, and then simulates the hydrological response of the upper and middle Huaihe River Basin (UMHRB) under future shared socioeconomic pathway scenarios (SSPs). The results show that the five-GCM ensemble improves the simulation accuracy compared to a single model. The climate over the UMHRB likely becomes warmer. The general trend of future precipitation is projected to increase, and the increased rates are higher in spring and winter than in summer and autumn. Changes in annual evapotranspiration are basically consistent with precipitation, but seasonal evapotranspiration shows different changes (0–18%). The average annual runoff will increase in a wavelike manner, and the change patterns of runoff follow that of seasonal precipitation. Changes in soil moisture are not obvious, and the annual soil moisture increases slightly. In the intrayear process, soil moisture decreases slightly in autumn. The research results will enhance a more realistic understanding of the future hydrological response of the UMHRB and assist decision-makers in developing watershed flood risk-management measures and water and soil conservation plans.

Sign in / Sign up

Export Citation Format

Share Document