scholarly journals Projected Drought Conditions over Southern Slope of the Central Himalaya Using CMIP6 Models

2021 ◽  
Author(s):  
Shankar Sharma ◽  
Kalpana Hamal ◽  
Nitesh Khadka ◽  
Munawar Ali ◽  
Madan Subedi ◽  
...  
Keyword(s):  
Coupled Model ◽  
Southern Slope ◽  
Drought Frequency ◽  
Drought Intensity ◽  
Central Himalayas ◽  
Drought Conditions ◽  
The Future ◽  
Drought Mitigation ◽  
Intercomparison Project

AbstractNepal is located on the southern slope of the Central Himalayas and has experienced frequent droughts in the past. In this study, we used an ensemble of 13 biased corrected models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to assess the future drought conditions over Nepal under three shared socioeconomic pathways (SSP126, SSP245, and SSP585) using the Standardized Precipitation Evapotranspiration Index (SPEI) at annual timescale. The monthly correlation between observed and CMIP6-simulated historical SPEI is 0.23 (p < 0.01), which indicates the CMIP6 model ensemble can simulate the drought characteristics over Nepal. In the future period (2020–2100), the duration and severity of droughts are projected to increase with higher emission scenarios, especially for SSP585. Our results indicate enhanced drought intensity under SSP126, whereas, under SSP245, the drought frequency will be slightly higher. The drought frequency is projected to increase in the early future (2020–2060), decreasing in the late future (2061–2100) under all SSP scenarios. The results further indicate more prolonged and severe droughts in the early future under SSP585 as compared to SSP126 and SSP245. The findings of the present study can help drought mitigation as well as long-term adaptation strategies over Nepal.

scholarly journals Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

2012 ◽  
Vol 16 (7) ◽  
pp. 2005-2020 ◽  
Author(s):  
S. L. Sun ◽  
H. S. Chen ◽  
W. M. Ju ◽  
J. Song ◽  
J. J. Li ◽  
...  
Keyword(s):  
Poyang Lake ◽  
Water Cycle ◽  
Coupled Model ◽  
Soil Water Storage ◽  
Future Climate Change ◽  
Lake Basin ◽  
Poyang Lake Basin ◽  
The Future ◽  
Intercomparison Project ◽  
Meteorological Observations

Abstract. To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan) within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m3 s−1 yr−1 and 1.29 m3 s−1 yr−1 at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m3 s−1 yr−1), Gaosha (1.12 m3 s−1 yr−1), and Xiashan (1.34 m3 s−1 yr−1), while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m3 s−1 yr−1). In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds. For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3) under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1) for the period of 2061–2100. When the future changes in the soil water storage changes are assumed ignorable, the streamflow shows an uptrend with the projected increases in both precipitation and evapotranspiration (except for the SRESB1 scenario in Xiashan watershed) relative to the observed mean during 1961–2000. Furthermore, the largest increase in the streamflow is found at Meigang (+4.31%) and Xiashan (+3.84%) under the SRESA1B scenario, while the increases will occur at Saitang (+6.87%) and Gaosha (+5.15%) under the SRESB1 scenario.

Anthropogenic and Natural Contributions to the Lengthening of the Summer Season in the Northern Hemisphere

2018 ◽  
Vol 31 (17) ◽  
pp. 6803-6819 ◽  
Author(s):  
Bo-Joung Park ◽  
Yeon-Hee Kim ◽  
Seung-Ki Min ◽  
Eun-Pa Lim
Keyword(s):  
Northern Hemisphere ◽  
Coupled Model ◽  
Atlantic Multidecadal Oscillation ◽  
Summer Season ◽  
Season Length ◽  
The Past ◽  
External Forcings ◽  
Regional Trends ◽  
Intercomparison Project

Observed long-term variations in summer season timing and length in the Northern Hemisphere (NH) continents and their subregions were analyzed using temperature-based indices. The climatological mean showed coastal–inland contrast; summer starts and ends earlier inland than in coastal areas because of differences in heat capacity. Observations for the past 60 years (1953–2012) show lengthening of the summer season with earlier summer onset and delayed summer withdrawal across the NH. The summer onset advance contributed more to the observed increase in summer season length in many regions than the delay of summer withdrawal. To understand anthropogenic and natural contributions to the observed change, summer season trends from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel simulations forced with the observed external forcings [anthropogenic plus natural forcing (ALL), natural forcing only (NAT), and greenhouse gas forcing only (GHG)] were analyzed. ALL and GHG simulations were found to reproduce the overall observed global and regional lengthening trends, but NAT had negligible trends, which implies that increased greenhouse gases were the main cause of the observed changes. However, ALL runs tend to underestimate the observed trend of summer onset and overestimate that of withdrawal, the causes of which remain to be determined. Possible contributions of multidecadal variabilities, such as Pacific decadal oscillation and Atlantic multidecadal oscillation, to the observed regional trends in summer season length were also assessed. The results suggest that multidecadal variability can explain a moderate portion (about ±10%) of the observed trends in summer season length, mainly over the high latitudes.

scholarly journals Long-term Surface Temperature (LoST) database as a complement for GCM preindustrial simulations

2019 ◽  
Vol 15 (3) ◽  
pp. 1099-1111 ◽  
Author(s):  
Francisco José Cuesta-Valero ◽  
Almudena García-García ◽  
Hugo Beltrami ◽  
Eduardo Zorita ◽  
Fernando Jaume-Santero
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Ground Surface ◽  
Coupled Model ◽  
Circulation Model ◽  
Research Unit ◽  
Large Spread ◽  
Intercomparison Project ◽  
Past Millennium

Abstract. Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.

The Double-ITCZ Bias in CMIP6 Models

2020 ◽  
Author(s):  
Baijun Tian
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Tropical Precipitation ◽  
Double Itcz ◽  
Intercomparison Project ◽  
Fully Coupled

&lt;p&gt;The double-Intertropical Convergence Zone (ITCZ) bias is one of the most outstanding problems in climate models. This study seeks to examine the double-ITCZ bias in the latest state-of-the-art fully coupled global climate models that participated in Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) in comparison to their previous generations (CMIP3 and CMIP5 models). To that end, we have analyzed the long-term annual mean tropical precipitation distributions and several precipitation bias indices that quantify the double-ITCZ biases in 75 climate models including 24 CMIP3 models, 25 CMIP3 models, and 26 CMIP6 models. We find that the double-ITCZ bias and its big inter-model spread persist in CMIP6 models but the double-ITCZ bias is slightly reduced from CMIP3 or CMIP5 models to CMIP6 models.&lt;/p&gt;

Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans

2014 ◽  
Vol 27 (2) ◽  
pp. 925-940 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy C. Clement ◽  
Joel R. Norris ◽  
Brian J. Soden
Keyword(s):  
Coupled Model ◽  
Cloud Amount ◽  
Western Indian Ocean ◽  
Model Intercomparison ◽  
Central Pacific ◽  
Radiative Impact ◽  
Southern Central ◽  
Intercomparison Project ◽  
Very High

AbstractConstraining intermodel spread in cloud feedback with observations is problematic because available cloud datasets are affected by spurious behavior in long-term variability. This problem is addressed by examining cloud amount in three independent ship-based [Extended Edited Cloud Reports Archive (EECRA)] and satellite-based [International Satellite Cloud Climatology Project (ISCCP) and Advanced Very High Resolution Radiometer Pathfinder Atmosphere–Extended (PATMOS-X)] observational datasets, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The three observational datasets show consistent cloud variability in the overlapping years of coverage (1984–2007). The long-term cloud amount change from 1954 to 2005 in ship-based observations shares many of the same features with the multimodel mean cloud amount change of 42 CMIP5 historical simulations, although the magnitude of the multimodel mean is smaller. The radiative impact of cloud changes is estimated by computing an observationally derived estimate of cloud amount feedback. The observational estimates of cloud amount feedback are statistically significant over four regions: the northeast Pacific subtropical stratocumulus region and equatorial western Pacific, where cloud amount feedback is found to be positive, and the southern central Pacific and western Indian Ocean, where cloud amount feedback is found to be negative. Multimodel mean cloud amount feedback is consistent in sign but smaller in magnitude than in observations over these four regions because models simulate weaker cloud changes. Individual models, however, can simulate cloud amount feedback of the same magnitude if not larger than observed. Focusing on the regions where models and observations agree can lead to improved understanding of the mechanisms of cloud amount changes and associated radiative impact.

scholarly journals The GRISLI-LSCE contribution to the Ice Sheet Model Intercomparison Project for phase 6 of the Coupled Model Intercomparison Project (ISMIP6) – Part 1: Projections of the Greenland ice sheet evolution by the end of the 21st century

2021 ◽  
Vol 15 (2) ◽  
pp. 1015-1030 ◽  
Author(s):  
Aurélien Quiquet ◽  
Christophe Dumas
Keyword(s):  
Mass Loss ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheet ◽  
Coupled Model ◽  
Greenland Ice Sheet ◽  
Model Intercomparison ◽  
The Future ◽  
Intercomparison Project ◽  
Global Sea Level

Abstract. Polar amplification will result in amplified temperature changes in the Arctic with respect to the rest of the globe, making the Greenland ice sheet particularly vulnerable to global warming. While the ice sheet has been showing an increased mass loss in the past decades, its contribution to global sea level rise in the future is of primary importance since it is at present the largest single-source contribution after the thermosteric contribution. The question of the fate of the Greenland and Antarctic ice sheets for the next century has recently gathered various ice sheet models in a common framework within the Ice Sheet Model Intercomparison Project for the Coupled Model Intercomparison Project – phase 6 (ISMIP6). While in a companion paper we present the GRISLI-LSCE (Grenoble Ice Sheet and Land Ice model of the Laboratoire des Sciences du Climat et de l'Environnement) contribution to ISMIP6-Antarctica, we present here the GRISLI-LSCE contribution to ISMIP6-Greenland. We show an important spread in the simulated Greenland ice loss in the future depending on the climate forcing used. The contribution of the ice sheet to global sea level rise in 2100 can thus be from as low as 20 mm sea level equivalent (SLE) to as high as 160 mm SLE. Amongst the models tested in ISMIP6, the Coupled Model Intercomparison Project – phase 6 (CMIP6) models produce larger ice sheet retreat than their CMIP5 counterparts. Low-emission scenarios in the future drastically reduce the ice mass loss. The oceanic forcing contributes to about 10 mm SLE in 2100 in our simulations. In addition, the dynamical contribution to ice thickness change is small compared to the impact of surface mass balance. This suggests that mass loss is mostly driven by atmospheric warming and associated ablation at the ice sheet margin. With additional sensitivity experiments we also show that the spread in mass loss is only weakly affected by the choice of the ice sheet model mechanical parameters.

Internal variability of surface solar radiation and associated PV production

2020 ◽  
Author(s):  
Doris Folini
Keyword(s):  
Solar Radiation ◽  
Coupled Model ◽  
Internal Variability ◽  
Industrial Control ◽  
Surface Solar Radiation ◽  
Decadal Scale ◽  
Intercomparison Project ◽  
Analytical Relations ◽  
Average Uncertainty

&lt;p&gt;Results on the statistical properties of internal variability of annual mean surface solar radiation (SSR) and associated decadal scale trends are presented, following in part Folini et al. 2017 (doi:10.1002/2016JD025869). Estimates are based on 43 pre-industrial control (piControl) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Trends are shown to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long term mean SSR. Providing one map for absolute and one map for relative trends is sufficient, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. Comparison with present-day observations and inter-model spread suggest an average uncertainty of these estimates of about 30%. &amp;#160;Intermodel spread suggests that regional uncertainties can be up to about three times larger or smaller. Using the model by Crook et al. 2011 (doi:10.1039/C1EE01495A) to translate SSR into PV production, associated internal variability of photo voltaic (PV) energy production is inferred. Results suggest that it is plausible for PV production to change by several per cent over a decade just because of internal variability.&lt;/p&gt;

scholarly journals Global peatlands under future climate – seamless model projections from the Last Glacial Maximum

2021 ◽  
Author(s):  
Jurek Müller ◽  
Fortunat Joos
Keyword(s):  
Last Glacial Maximum ◽  
Climate Model ◽  
Coupled Model ◽  
Glacial Maximum ◽  
Dynamic Global Vegetation Model ◽  
Last Glacial ◽  
The Future ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. Peatlands are diverse wetland ecosystems distributed mostly over the northern latitudes and tropics. Globally they store a large portion of the global soil organic carbon and provide important ecosystem services. The future of these systems under continued anthropogenic warming and direct human disturbance has potentially large impacts on atmospheric CO2 and climate. We performed global long term projections of peatland area and carbon over the next 5000 years using a dynamic global vegetation model forced with climate anomalies from ten models of the Coupled Model Intercomparison Project (CMIP6) and three scenarios. These projections are continued from a transient simulation from the Last Glacial Maximum to the present to account for the full transient history. Our results suggest short to long term net losses of global peatland area and carbon, with higher losses under higher emission scenarios. Large parts of today's active northern peatlands are at risk. Conditions for peatlands in the tropics and, in case of mitigation, eastern Asia and western north America improve. Factorial simulations reveal committed historical changes and future rising temperature as the main driver of future peatland loss and increasing precipitations as driver for regional peatland expansion. Additional simulations forced with two CMIP6 scenarios extended transiently beyond 2100, show qualitatively similar results to the standard scenarios, but highlight the importance of extended future scenarios for long term carbon cycle projections. The spread between simulations forced with different climate model anomalies suggests a large uncertainty in projected peatland variables due to uncertain climate forcing. Our study highlights the importance of quantifying the future peatland feedback to the climate system and its inclusion into future earth system model projections.

Long-term Surface Temperature (LoST) Database as a Complement for Transient and Control Preindustrial Simulations

2021 ◽  
Author(s):  
Francisco José Cuesta-Valero ◽  
Almudena García-García ◽  
Hugo Beltrami ◽  
Eduardo Zorita ◽  
Fernando Jaume Santero
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Climate Modeling ◽  
Ground Surface ◽  
Coupled Model ◽  
Circulation Model ◽  
Temperature Profiles ◽  
Intercomparison Project ◽  
Past Millennium

&lt;div&gt;Estimates of climate sensitivity from Atmosphere-Ocean Coupled General Circulation Model (GCM) simulations present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. However, it is difficult to provide a reference to assess the climatology of preindustrial control simulations as there are no long-term preindustrial observations.&lt;br&gt;In the ground, recent changes in ground surface temperature are observed at shallow depths as perturbations to the quasi-steady state geothermal regime. However, if undisturbed by recent surface temperature changes, the deep ground temperatures vary linearly as a function of depth, and the extrapolation of this linear behavior to the surface can be interpreted as the past long-term surface temperature climatology.&lt;/div&gt;&lt;div&gt;We assemble a new gridded database of past long-term ground surface temperatures (LoST database) obtained from 514 borehole temperature profiles measured across North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial control simulations and past millennium simulations. All temperature profiles are truncated at 300 m depth, allowing to estimate the ground surface climatology for the period 1300-1700 of the common era. We compare the LoST database with observations from the CRU database, as well as with five past millennium simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5) archives. Our results suggest that LoST temperatures could be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.&lt;/div&gt;

scholarly journals Evaluation of 22 Precipitation and 23 Soil Moisture Products over a Semiarid Area in Southeastern Arizona*

2015 ◽  
Vol 17 (1) ◽  
pp. 211-230 ◽  
Author(s):  
Susan Stillman ◽  
Xubin Zeng ◽  
Michael G. Bosilovich
Keyword(s):  
Soil Moisture ◽  
Coupled Model ◽  
Cold Season ◽  
Annual Precipitation ◽  
Product Categories ◽  
Scale Mismatch ◽  
Intercomparison Project ◽  
Land Data Assimilation ◽  
Mean Square Difference

Abstract Precipitation and soil moisture are rigorously measured or estimated from a variety of sources. Here, 22 precipitation and 23 soil moisture products are evaluated against long-term daily observed precipitation (Pobs) and July–September daily observationally constrained soil moisture (SM) datasets over a densely monitored 150 km2 watershed in southeastern Arizona, United States. Gauge–radar precipitation products perform best, followed by reanalysis and satellite products, and the median correlations of annual precipitation from these three categories with Pobs are 0.83, 0.68, and 0.46, respectively. Precipitation results from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are the worst, including an overestimate of cold season precipitation and a lack of significant correlation of annual precipitation with Pobs from all (except one) models. Satellite soil moisture products perform best, followed by land data assimilation systems and reanalyses, and the CMIP5 results are the worst. For instance, the median unbiased root-mean-square difference (RMSD) values of July–September soil moisture compared with SM are 0.0070, 0.011, 0.014, and 0.029 m3 m−3 for these four product categories, respectively. All 17 (except 3) precipitation [17 (except 2) soil moisture] products with at least 20 years of data agree with Pobs (SM) without significant trends. The uncertainties associated with the scale mismatch between Pobs and coarser-resolution products are addressed using two 4-km gauge–radar precipitation products, and their impact on the results presented in this study is overall small. These results identify strengths and weaknesses of each product for future improvement; they also emphasize the importance of using multiple gauge–radar and satellite products along with their uncertainties in evaluating reanalyses and models.

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